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Cui Z, Xu H, Wu F, Chen J, Zhu L, Shen Z, Yi X, Yang J, Jia C, Zhang L, Zhou P, Li MJ, Zhu L, Duan S, Yao Z, Yu Y, Liu Q, Zhou J. Maternal circadian rhythm disruption affects neonatal inflammation via metabolic reprograming of myeloid cells. Nat Metab 2024:10.1038/s42255-024-01021-y. [PMID: 38561509 DOI: 10.1038/s42255-024-01021-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/21/2023] [Accepted: 03/05/2024] [Indexed: 04/04/2024]
Abstract
Disruption of circadian rhythm during pregnancy produces adverse health outcomes in offspring; however, the role of maternal circadian rhythms in the immune system of infants and their susceptibility to inflammation remains poorly understood. Here we show that disruption of circadian rhythms in pregnant mice profoundly aggravates the severity of neonatal inflammatory disorders in both male and female offspring, such as necrotizing enterocolitis and sepsis. The diminished maternal production of docosahexaenoic acid (DHA) and the impaired immunosuppressive function of neonatal myeloid-derived suppressor cells (MDSCs) contribute to this phenomenon. Mechanistically, DHA enhances the immunosuppressive function of MDSCs via PPARγ-mediated mitochondrial oxidative phosphorylation. Transfer of MDSCs or perinatal supplementation of DHA relieves neonatal inflammation induced by maternal rhythm disruption. These observations collectively demonstrate a previously unrecognized role of maternal circadian rhythms in the control of neonatal inflammation via metabolic reprograming of myeloid cells.
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Affiliation(s)
- Zhaohai Cui
- Tianjin Institute of Immunology, Key Laboratory of Immune Microenvironment and Disease (Ministry of Education), The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, International Joint Laboratory of Ocular Diseases, Ministry of Education, State Key Laboratory of Experimental Hematology, Department of Immunology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China
- Institute of Pediatric Health and Disease, Guangdong Provincial Key Laboratory of Major Obstetric Diseases, Guangdong Provincial Clinical Research Center for Obstetrics and Gynecology, Guangzhou, China
| | - Haixu Xu
- Tianjin Institute of Immunology, Key Laboratory of Immune Microenvironment and Disease (Ministry of Education), The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, International Joint Laboratory of Ocular Diseases, Ministry of Education, State Key Laboratory of Experimental Hematology, Department of Immunology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China
| | - Fan Wu
- Institute of Pediatric Health and Disease, Guangdong Provincial Key Laboratory of Major Obstetric Diseases, Guangdong Provincial Clinical Research Center for Obstetrics and Gynecology, Guangzhou, China
- Department of Neonatology, Guangzhou Key Laboratory of Neonatal Intestinal Diseases, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | - Jiale Chen
- Tianjin Institute of Immunology, Key Laboratory of Immune Microenvironment and Disease (Ministry of Education), The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, International Joint Laboratory of Ocular Diseases, Ministry of Education, State Key Laboratory of Experimental Hematology, Department of Immunology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China
| | - Lin Zhu
- Tianjin Institute of Immunology, Key Laboratory of Immune Microenvironment and Disease (Ministry of Education), The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, International Joint Laboratory of Ocular Diseases, Ministry of Education, State Key Laboratory of Experimental Hematology, Department of Immunology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China
| | - Zhuxia Shen
- Department of Cardiology, Jing'an District Central Hospital of Shanghai, Fudan University, Shanghai, China
| | - Xianfu Yi
- Department of Bioinformatics, Tianjin, China
| | - Jinhao Yang
- Tianjin Institute of Immunology, Key Laboratory of Immune Microenvironment and Disease (Ministry of Education), The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, International Joint Laboratory of Ocular Diseases, Ministry of Education, State Key Laboratory of Experimental Hematology, Department of Immunology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China
| | - Chunhong Jia
- Institute of Pediatric Health and Disease, Guangdong Provincial Key Laboratory of Major Obstetric Diseases, Guangdong Provincial Clinical Research Center for Obstetrics and Gynecology, Guangzhou, China
- Department of Neonatology, Guangzhou Key Laboratory of Neonatal Intestinal Diseases, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | - Lijuan Zhang
- Tianjin Institute of Immunology, Key Laboratory of Immune Microenvironment and Disease (Ministry of Education), The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, International Joint Laboratory of Ocular Diseases, Ministry of Education, State Key Laboratory of Experimental Hematology, Department of Immunology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China
| | - Pan Zhou
- Tianjin Institute of Immunology, Key Laboratory of Immune Microenvironment and Disease (Ministry of Education), The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, International Joint Laboratory of Ocular Diseases, Ministry of Education, State Key Laboratory of Experimental Hematology, Department of Immunology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China
| | | | - Lu Zhu
- Department of Pharmacology, Tianjin Key Laboratory of Inflammatory Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China
| | - Shengzhong Duan
- Stomatology Hospital, School of Stomatology, Zhejiang University School of Medicine, Zhejiang, China
| | - Zhi Yao
- Tianjin Institute of Immunology, Key Laboratory of Immune Microenvironment and Disease (Ministry of Education), The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, International Joint Laboratory of Ocular Diseases, Ministry of Education, State Key Laboratory of Experimental Hematology, Department of Immunology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China
| | - Ying Yu
- Tianjin Institute of Immunology, Key Laboratory of Immune Microenvironment and Disease (Ministry of Education), The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, International Joint Laboratory of Ocular Diseases, Ministry of Education, State Key Laboratory of Experimental Hematology, Department of Immunology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China.
- Department of Pharmacology, Tianjin Key Laboratory of Inflammatory Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China.
| | - Qiang Liu
- Tianjin Institute of Immunology, Key Laboratory of Immune Microenvironment and Disease (Ministry of Education), The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, International Joint Laboratory of Ocular Diseases, Ministry of Education, State Key Laboratory of Experimental Hematology, Department of Immunology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China.
- Department of Neurology, Tianjin Neurological Institute, Tianjin Medical University General Hospital, Tianjin, China.
| | - Jie Zhou
- Tianjin Institute of Immunology, Key Laboratory of Immune Microenvironment and Disease (Ministry of Education), The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, International Joint Laboratory of Ocular Diseases, Ministry of Education, State Key Laboratory of Experimental Hematology, Department of Immunology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China.
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Liao Z, Teng J, Li T, Liu H, Li T, Zhang C, Xing R, Teng S, Yang Y, Zhao J, Xiao W, Zhang G, Li MJ, Yao W, Yang J. Evaluation of the efficacy and safety of immunotherapy in sarcoma: a two-center study. Front Immunol 2024; 15:1292325. [PMID: 38585276 PMCID: PMC10995229 DOI: 10.3389/fimmu.2024.1292325] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2023] [Accepted: 02/21/2024] [Indexed: 04/09/2024] Open
Abstract
Background Sarcoma is a highly heterogeneous malignancy with a poor prognosis. Although chemotherapy and targeted therapy have improved the prognosis to some extent, the efficacy remains unsatisfactory in some patients. The efficacy and safety of immunotherapy in sarcoma need further evaluation. Methods We conducted a two-center study of sarcoma patients receiving PD-1 immunotherapy at Tianjin Medical University Cancer Institute and Hospital and Henan Provincial Cancer Hospital. The treatment regimens included PD-1 inhibitor monotherapy and combination therapy based on PD-1 inhibitors. The observed primary endpoints were median progression-free survival (mPFS) and median overall survival (mOS). Survival curves were compared using the Kaplan-Meier method. Results A total of 43 patients were included from the two centers. The median follow-up time for all patients was 13 months (range, 1-48 months). In the group of 37 patients with advanced or unresectable sarcoma, the mPFS was 6 months (95%CI: 5-12 months), and the mOS was 16 months (95%CI: 10-28 months). The ORR was 10.8% (4/37), and the DCR was 18.9% (7/37). Subgroup analysis showed no significant differences in mPFS (p=0.11) and mOS (p=0.88) between patients with PD-L1 negative/positive expression. There were also no significant differences in mPFS (p=0.13) or mOS (p=0.72) between PD-1 inhibitor monotherapy and combination therapy. Additionally, there were no significant differences in mPFS (p=0.52) or mOS (p=0.49) between osteogenic sarcoma and soft tissue sarcoma. Furthermore, the results showed no significant differences in mPFS (p=0.66) or mOS (p=0.96) between PD-1 inhibitors combined with targeted therapy and PD-1 inhibitors combined with AI chemotherapy. Among the 6 patients receiving adjuvant therapy after surgery, the mPFS was 15 months (95%CI: 6-NA months), and the mOS was not reached. In terms of safety, most adverse events were mild (grade 1-2) and manageable. The most severe grade 4 adverse events were bone marrow suppression, which occurred in 4 patients but resolved after treatment. There was also one case of a grade 4 adverse event related to hypertension. Conclusion Immunotherapy is an effective treatment modality for sarcoma with manageable safety. Further inclusion of more patients or prospective clinical trials is needed to validate these findings.
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Affiliation(s)
- Zhichao Liao
- Department of Bone and Soft Tissue Tumor, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China
- National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin’s Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China
| | - Jianjin Teng
- Department of Bioinformatics, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China
| | - Tao Li
- Department of Bone and Soft-Tissue Tumor, Institute of Cancer and Basic Medicine, Chinese Academy of Sciences, Cancer Hospital of the University of Chinese Academy of Sciences, Zhejiang Cancer Hospital, Hangzhou, China
| | - Haotian Liu
- Department of Bone and Soft Tissue Tumor, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China
- National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin’s Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China
| | - Ting Li
- Department of Bone and Soft Tissue Tumor, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China
- National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin’s Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China
| | - Chao Zhang
- Department of Bone and Soft Tissue Tumor, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China
- National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin’s Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China
| | - Ruwei Xing
- Department of Bone and Soft Tissue Tumor, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China
- National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin’s Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China
| | - Sheng Teng
- Department of Bone and Soft Tissue Tumor, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China
- National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin’s Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China
| | - Yun Yang
- Department of Bone and Soft Tissue Tumor, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China
- National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin’s Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China
| | - Jun Zhao
- Department of Bone and Soft Tissue Tumor, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China
- National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin’s Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China
| | - Wanyi Xiao
- Department of Bone and Soft Tissue Tumor, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China
- National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin’s Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China
| | - Gengpu Zhang
- Department of Bone and Soft Tissue Tumor, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China
- National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin’s Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China
| | - Mulin Jun Li
- Department of Bioinformatics, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China
| | - Weitao Yao
- Department of Bone and Soft Tissue Cancer, The Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, China
| | - Jilong Yang
- Department of Bone and Soft Tissue Tumor, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China
- National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin’s Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China
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Zhou Z, Du J, Wang J, Liu L, Gordon MG, Ye CJ, Powell JE, Li MJ, Rao S. SingleQ: a comprehensive database of single-cell expression quantitative trait loci (sc-eQTLs) cross human tissues. Database (Oxford) 2024; 2024:baae010. [PMID: 38459946 PMCID: PMC10924434 DOI: 10.1093/database/baae010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2023] [Revised: 01/09/2024] [Accepted: 02/11/2024] [Indexed: 03/11/2024]
Abstract
Mapping of expression quantitative trait loci (eQTLs) and other molecular QTLs can help characterize the modes of action of disease-associated genetic variants. However, current eQTL databases present data from bulk RNA-seq approaches, which cannot shed light on the cell type- and environment-specific regulation of disease-associated genetic variants. Here, we introduce our Single-cell eQTL Interactive Database which collects single-cell eQTL (sc-eQTL) datasets and provides online visualization of sc-eQTLs across different cell types in a user-friendly manner. Although sc-eQTL mapping is still in its early stage, our database curates the most comprehensive summary statistics of sc-eQTLs published to date. sc-eQTL studies have revolutionized our understanding of gene regulation in specific cellular contexts, and we anticipate that our database will further accelerate the research of functional genomics. Database URL: http://www.sqraolab.com/scqtl.
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Affiliation(s)
- Zhiwei Zhou
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, 288 Nanjing Road, Tianjin 300020, China
- Tianjin Institutes of Health Science, 28 Tuanbo Avenue, Tianjin 301600, China
| | - Jingyi Du
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, 288 Nanjing Road, Tianjin 300020, China
- Tianjin Institutes of Health Science, 28 Tuanbo Avenue, Tianjin 301600, China
| | - Jianhua Wang
- Department of Pharmacology, Tianjin Key Laboratory of Inflammation Biology, School of Basic Medical Sciences, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, 22 Qixiangtai Road, Tianjin 300070, China
| | - Liangyi Liu
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, 288 Nanjing Road, Tianjin 300020, China
| | - M Gracie Gordon
- Biological and Medical Informatics Graduate Program, University of California, 500 Parnassus Avenue, San Francisco, CA 94143, USA
- Division of Rheumatology, Department of Medicine, University of California, 500 Parnassus Avenue, San Francisco, CA 94143, USA
- Institute for Human Genetics, University of California, 500 Parnassus Avenue, San Francisco, CA 94143, USA
- Department of Bioengineering and Therapeutic Sciences, University of California, 500 Parnassus Avenue, San Francisco, CA 94143, USA
| | - Chun Jimmie Ye
- Division of Rheumatology, Department of Medicine, University of California, 500 Parnassus Avenue, San Francisco, CA 94143, USA
- Institute for Human Genetics, University of California, 500 Parnassus Avenue, San Francisco, CA 94143, USA
- Rosalind Russell/Ephraim P. Engleman Rheumatology Research Center, University of California, 500 Parnassus Avenue, San Francisco, CA 94143, USA
- Department of Epidemiology and Biostatistics, University of California, 500 Parnassus Avenue, San Francisco, CA 94143, USA
- Parker Institute for Cancer Immunotherapy, University of California, 500 Parnassus Avenue, San Francisco, CA 94143, USA
- Chan Zuckerberg Biohub, 499 Illinois Street, San Francisco, CA 94158, USA
- Bakar Computational Health Sciences Institute, University of California, 500 Parnassus Avenue, San Francisco, CA 94143, USA
| | - Joseph E Powell
- Garvan-Weizmann Centre for Cellular Genomics, Garvan Institute of Medical Research, 384 Victoria Street, Sydney, NSW 2010, Australia
- UNSW Cellular Genomics Futures Institute, University of New South Wales, UNSW Sydney, Sydney, NSW 2052, Australia
| | - Mulin Jun Li
- Department of Pharmacology, Tianjin Key Laboratory of Inflammation Biology, School of Basic Medical Sciences, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, 22 Qixiangtai Road, Tianjin 300070, China
| | - Shuquan Rao
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, 288 Nanjing Road, Tianjin 300020, China
- Tianjin Institutes of Health Science, 28 Tuanbo Avenue, Tianjin 301600, China
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Jain S, Bakolitsa C, Brenner SE, Radivojac P, Moult J, Repo S, Hoskins RA, Andreoletti G, Barsky D, Chellapan A, Chu H, Dabbiru N, Kollipara NK, Ly M, Neumann AJ, Pal LR, Odell E, Pandey G, Peters-Petrulewicz RC, Srinivasan R, Yee SF, Yeleswarapu SJ, Zuhl M, Adebali O, Patra A, Beer MA, Hosur R, Peng J, Bernard BM, Berry M, Dong S, Boyle AP, Adhikari A, Chen J, Hu Z, Wang R, Wang Y, Miller M, Wang Y, Bromberg Y, Turina P, Capriotti E, Han JJ, Ozturk K, Carter H, Babbi G, Bovo S, Di Lena P, Martelli PL, Savojardo C, Casadio R, Cline MS, De Baets G, Bonache S, Díez O, Gutiérrez-Enríquez S, Fernández A, Montalban G, Ootes L, Özkan S, Padilla N, Riera C, De la Cruz X, Diekhans M, Huwe PJ, Wei Q, Xu Q, Dunbrack RL, Gotea V, Elnitski L, Margolin G, Fariselli P, Kulakovskiy IV, Makeev VJ, Penzar DD, Vorontsov IE, Favorov AV, Forman JR, Hasenahuer M, Fornasari MS, Parisi G, Avsec Z, Çelik MH, Nguyen TYD, Gagneur J, Shi FY, Edwards MD, Guo Y, Tian K, Zeng H, Gifford DK, Göke J, Zaucha J, Gough J, Ritchie GRS, Frankish A, Mudge JM, Harrow J, Young EL, Yu Y, Huff CD, Murakami K, Nagai Y, Imanishi T, Mungall CJ, Jacobsen JOB, Kim D, Jeong CS, Jones DT, Li MJ, Guthrie VB, Bhattacharya R, Chen YC, Douville C, Fan J, Kim D, Masica D, Niknafs N, Sengupta S, Tokheim C, Turner TN, Yeo HTG, Karchin R, Shin S, Welch R, Keles S, Li Y, Kellis M, Corbi-Verge C, Strokach AV, Kim PM, Klein TE, Mohan R, Sinnott-Armstrong NA, Wainberg M, Kundaje A, Gonzaludo N, Mak ACY, Chhibber A, Lam HYK, Dahary D, Fishilevich S, Lancet D, Lee I, Bachman B, Katsonis P, Lua RC, Wilson SJ, Lichtarge O, Bhat RR, Sundaram L, Viswanath V, Bellazzi R, Nicora G, Rizzo E, Limongelli I, Mezlini AM, Chang R, Kim S, Lai C, O’Connor R, Topper S, van den Akker J, Zhou AY, Zimmer AD, Mishne G, Bergquist TR, Breese MR, Guerrero RF, Jiang Y, Kiga N, Li B, Mort M, Pagel KA, Pejaver V, Stamboulian MH, Thusberg J, Mooney SD, Teerakulkittipong N, Cao C, Kundu K, Yin Y, Yu CH, Kleyman M, Lin CF, Stackpole M, Mount SM, Eraslan G, Mueller NS, Naito T, Rao AR, Azaria JR, Brodie A, Ofran Y, Garg A, Pal D, Hawkins-Hooker A, Kenlay H, Reid J, Mucaki EJ, Rogan PK, Schwarz JM, Searls DB, Lee GR, Seok C, Krämer A, Shah S, Huang CV, Kirsch JF, Shatsky M, Cao Y, Chen H, Karimi M, Moronfoye O, Sun Y, Shen Y, Shigeta R, Ford CT, Nodzak C, Uppal A, Shi X, Joseph T, Kotte S, Rana S, Rao A, Saipradeep VG, Sivadasan N, Sunderam U, Stanke M, Su A, Adzhubey I, Jordan DM, Sunyaev S, Rousseau F, Schymkowitz J, Van Durme J, Tavtigian SV, Carraro M, Giollo M, Tosatto SCE, Adato O, Carmel L, Cohen NE, Fenesh T, Holtzer T, Juven-Gershon T, Unger R, Niroula A, Olatubosun A, Väliaho J, Yang Y, Vihinen M, Wahl ME, Chang B, Chong KC, Hu I, Sun R, Wu WKK, Xia X, Zee BC, Wang MH, Wang M, Wu C, Lu Y, Chen K, Yang Y, Yates CM, Kreimer A, Yan Z, Yosef N, Zhao H, Wei Z, Yao Z, Zhou F, Folkman L, Zhou Y, Daneshjou R, Altman RB, Inoue F, Ahituv N, Arkin AP, Lovisa F, Bonvini P, Bowdin S, Gianni S, Mantuano E, Minicozzi V, Novak L, Pasquo A, Pastore A, Petrosino M, Puglisi R, Toto A, Veneziano L, Chiaraluce R, Ball MP, Bobe JR, Church GM, Consalvi V, Cooper DN, Buckley BA, Sheridan MB, Cutting GR, Scaini MC, Cygan KJ, Fredericks AM, Glidden DT, Neil C, Rhine CL, Fairbrother WG, Alontaga AY, Fenton AW, Matreyek KA, Starita LM, Fowler DM, Löscher BS, Franke A, Adamson SI, Graveley BR, Gray JW, Malloy MJ, Kane JP, Kousi M, Katsanis N, Schubach M, Kircher M, Mak ACY, Tang PLF, Kwok PY, Lathrop RH, Clark WT, Yu GK, LeBowitz JH, Benedicenti F, Bettella E, Bigoni S, Cesca F, Mammi I, Marino-Buslje C, Milani D, Peron A, Polli R, Sartori S, Stanzial F, Toldo I, Turolla L, Aspromonte MC, Bellini M, Leonardi E, Liu X, Marshall C, McCombie WR, Elefanti L, Menin C, Meyn MS, Murgia A, Nadeau KCY, Neuhausen SL, Nussbaum RL, Pirooznia M, Potash JB, Dimster-Denk DF, Rine JD, Sanford JR, Snyder M, Cote AG, Sun S, Verby MW, Weile J, Roth FP, Tewhey R, Sabeti PC, Campagna J, Refaat MM, Wojciak J, Grubb S, Schmitt N, Shendure J, Spurdle AB, Stavropoulos DJ, Walton NA, Zandi PP, Ziv E, Burke W, Chen F, Carr LR, Martinez S, Paik J, Harris-Wai J, Yarborough M, Fullerton SM, Koenig BA, McInnes G, Shigaki D, Chandonia JM, Furutsuki M, Kasak L, Yu C, Chen R, Friedberg I, Getz GA, Cong Q, Kinch LN, Zhang J, Grishin NV, Voskanian A, Kann MG, Tran E, Ioannidis NM, Hunter JM, Udani R, Cai B, Morgan AA, Sokolov A, Stuart JM, Minervini G, Monzon AM, Batzoglou S, Butte AJ, Greenblatt MS, Hart RK, Hernandez R, Hubbard TJP, Kahn S, O’Donnell-Luria A, Ng PC, Shon J, Veltman J, Zook JM. CAGI, the Critical Assessment of Genome Interpretation, establishes progress and prospects for computational genetic variant interpretation methods. Genome Biol 2024; 25:53. [PMID: 38389099 PMCID: PMC10882881 DOI: 10.1186/s13059-023-03113-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2023] [Accepted: 11/17/2023] [Indexed: 02/24/2024] Open
Abstract
BACKGROUND The Critical Assessment of Genome Interpretation (CAGI) aims to advance the state-of-the-art for computational prediction of genetic variant impact, particularly where relevant to disease. The five complete editions of the CAGI community experiment comprised 50 challenges, in which participants made blind predictions of phenotypes from genetic data, and these were evaluated by independent assessors. RESULTS Performance was particularly strong for clinical pathogenic variants, including some difficult-to-diagnose cases, and extends to interpretation of cancer-related variants. Missense variant interpretation methods were able to estimate biochemical effects with increasing accuracy. Assessment of methods for regulatory variants and complex trait disease risk was less definitive and indicates performance potentially suitable for auxiliary use in the clinic. CONCLUSIONS Results show that while current methods are imperfect, they have major utility for research and clinical applications. Emerging methods and increasingly large, robust datasets for training and assessment promise further progress ahead.
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Meng X, Wang Q, Chen S, Zhang S, Yu J, Li H, Chen X, Wang Z, Yu W, Zheng Z, Zhou H, Luo J, Wang Z, Chen H, Wu N, Hu D, Chen S, Wei Y, Cui H, Song H, Chen H, Wang Y, Zhong J, Chen Z, Zhang H, Yang T, Li M, Liu Y, Dong X, Du M, Wang X, Yao X, Lin H, Li MJ, Yan H. An interpretable model predicts visual outcomes of no light perception eyes after open globe injury. Br J Ophthalmol 2024; 108:285-293. [PMID: 36596662 DOI: 10.1136/bjo-2022-322753] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2022] [Accepted: 12/17/2022] [Indexed: 01/05/2023]
Abstract
BACKGROUND The visual outcome of open globe injury (OGI)-no light perception (NLP) eyes is unpredictable traditionally. This study aimed to develop a model to predict the visual outcomes of vitrectomy surgery in OGI-NLP eyes using a machine learning algorithm and to provide an interpretable system for the prediction results. METHODS Clinical data of 459 OGI-NLP eyes were retrospectively collected from 19 medical centres across China to establish a training data set for developing a model, called 'VisionGo', which can predict the visual outcome of the patients involved and compare with the Ocular Trauma Score (OTS). Another 72 cases were retrospectively collected and used for human-machine comparison, and an additional 27 cases were prospectively collected for real-world validation of the model. The SHapley Additive exPlanations method was applied to analyse feature contribution to the model. An online platform was built for real-world application. RESULTS The area under the receiver operating characteristic curve (AUC) of VisionGo was 0.75 and 0.90 in previtrectomy and intravitrectomy application scenarios, which was much higher than the OTS (AUC=0.49). VisionGo showed better performance than ophthalmologists in both previtrectomy and intravitrectomy application scenarios (AUC=0.73 vs 0.57 and 0.87 vs 0.64). In real-world validation, VisionGo achieved an AUC of 0.60 and 0.91 in previtrectomy and intravitrectomy application scenarios. Feature contribution analysis indicated that wound length-related indicators, vitreous status and retina-related indicators contributed highly to visual outcomes. CONCLUSIONS VisionGo has achieved an accurate and reliable prediction in visual outcome after vitrectomy for OGI-NLP eyes.
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Affiliation(s)
- Xiangda Meng
- Department of Ophthalmology, Tianjin Medical University General Hospital, Tianjin, China
| | - Qihua Wang
- Department of Ophthalmology, Tianjin Medical University General Hospital, Tianjin, China
- Department of Ophthalmology, Beijing Tsinghua Changgung Hospital, School of Clinical Medicine, Tsinghua University, Beijing, China
| | - Song Chen
- Department of Ophthalmology, Tianjin Medical University General Hospital, Tianjin, China
| | - Shijie Zhang
- Department of Pharmacology, Tianjin Key Laboratory of Inflammation Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China
| | - Jinguo Yu
- Department of Ophthalmology, Tianjin Medical University General Hospital, Tianjin, China
| | - Haibo Li
- Department of Ocular Trauma, Xiamen University Xiamen Eye Center, Xiamen, Fujian, China
| | - Xinkang Chen
- Department of Pharmacology, Tianjin Key Laboratory of Inflammation Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China
| | - Zhaoyang Wang
- Department of Ophthalmology, Shanghai Tenth People's Hospital, School of Medicine, Tongji University, Shanghai, China
| | - Wenzhen Yu
- Department of Ophthalmology, Peking University People's Hospital, Beijing, China
| | - Zhi Zheng
- Department of Ophthalmology, Shanghai General Hospital, Shanghai Jiao Tong University, Shanghai, China
| | - Heding Zhou
- Department of Ophthalmology, Ningbo Eye Hospital, Ningbo, Zhejiang, China
| | - Jing Luo
- Department of Ophthalmology, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Zhiliang Wang
- Department of Ophthalmology, Fudan University Huashan Hospital, Shanghai, China
| | - Haoyu Chen
- Department of Ocular Trauma, Joint Shantou International Eye Center of Shantou University and The Chinese University of Hong Kong, Shantou, Guangdong, China
| | - Nan Wu
- Department of Ophthalmology, Southwest Hospital, Third Military Medical University (Army Medical University), Chongqing, China
| | - Dan Hu
- Department of Ophthalmology, Eye Institute of Chinese PLA, Xijing Hospital, Fourth Military Medical University, Xi'an, Shaanxi, China
| | - Suihua Chen
- Department of Ophthalmology, General Hospital of Eastern Theater Command, Nanjing, Jiangsu, China
| | - Yong Wei
- National Clinical Research Center for Ocular Diseases, Eye Hospital, Wenzhou Medical University, Wenzhou, Zhejiang, China
| | - Haibin Cui
- Department of Ocular Trauma, Heilongjiang Province Ophthalmology Hospital, Harbin, Heilongjiang, China
| | - Huping Song
- Department of Ophthalmology, Xi'an People's Hospital (Xi'an No.4 Hospital), Xi'an, Shaanxi, China
| | - Huijin Chen
- Department of Ophthalmology, Beijing Key Laboratory of Restoration of Damaged Ocular Nerve, Peking University Third Hospital, Beijing, China
| | - Yun Wang
- Department of Ophthalmology, Xining First People's Hospital, Xining, Qinghai, China
| | - Jie Zhong
- Department of Ophthalmology, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, Sichuan, China
| | - Zhen Chen
- Eye Center, Renmin Hospital of Wuhan University, Wuhan, Hubei, China
| | - Haokun Zhang
- Department of Ophthalmology, Tianjin Medical University General Hospital, Tianjin, China
| | - Tiantian Yang
- Department of Ophthalmology, Tianjin Medical University General Hospital, Tianjin, China
| | - Mengxuan Li
- Department of Ophthalmology, Tianjin Medical University General Hospital, Tianjin, China
| | - Yuanyuan Liu
- Department of Ophthalmology, Tianjin Medical University General Hospital, Tianjin, China
| | - Xue Dong
- Department of Ophthalmology, Tianjin Medical University General Hospital, Tianjin, China
- Laboratory of Molecular Ophthalmology and Tianjin Key Laboratory of Ocular Trauma, Tianjin Medical University, Tianjin, China
| | - Mei Du
- Department of Pharmacology, Tianjin Key Laboratory of Inflammation Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China
- Laboratory of Molecular Ophthalmology and Tianjin Key Laboratory of Ocular Trauma, Tianjin Medical University, Tianjin, China
| | - Xiaohong Wang
- Department of Pharmacology, Tianjin Key Laboratory of Inflammation Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China
- Laboratory of Molecular Ophthalmology and Tianjin Key Laboratory of Ocular Trauma, Tianjin Medical University, Tianjin, China
| | - Xuyang Yao
- Tianjin Medical University Eye Hospital, Eye Institute & School of Optometry and Ophthalmology, Tianjin, China
| | - Haotian Lin
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Vision Science, Guangdong Provincial Clinical Research Center for Ocular Diseases, Guangzhou, Guangdong, China
- Hainan Eye Hospital and Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Haikou, Hainan, China
- Center for Precision Medicine and Department of Genetics and Biomedical Informatics, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, Guangdong, China
| | - Mulin Jun Li
- Department of Pharmacology, Tianjin Key Laboratory of Inflammation Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China
- Department of Bioinformatics, The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China
| | - Hua Yan
- Department of Ophthalmology, Tianjin Medical University General Hospital, Tianjin, China
- Laboratory of Molecular Ophthalmology and Tianjin Key Laboratory of Ocular Trauma, Tianjin Medical University, Tianjin, China
- School of Medicine, Nankai University, Tianjin, China
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Huang MT, Qu Z, Liang PF, Liu WD, He ZY, Cui X, Guo L, Chen J, Li MJ, Huang XY, Zhang PH. [Clinical effect of modified vertical rectus abdominis myocutaneous flap in repairing skin and soft tissue defects after abdominoperineal resection for rectal cancer]. Zhonghua Shao Shang Yu Chuang Mian Xiu Fu Za Zhi 2024; 40:57-63. [PMID: 38296237 DOI: 10.3760/cma.j.cn501225-20231030-00156] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 02/15/2024]
Abstract
Objective: To investigate the clinical effect of the modified vertical rectus abdominis myocutaneous flap in repairing the skin and soft tissue defect after abdominoperineal resection for rectal cancer. Methods: This study was a retrospective observational study. From June 2019 to July 2022, five male patients with low rectal cancer who were conformed to the inclusion criteria were admitted to the Department of Basic Surgery of Xiangya Hospital of Central South University, with ages ranging from 65 to 70 years and the sizes of the perianal skin ulcers ranging from 5 cm×4 cm to 11 cm×9 cm, and all of them underwent abdominoperineal resection. The secondary skin and soft tissue defects in the perineum with an area of 8 cm×6 cm-14 cm×12 cm (with the depth of pelvic floor dead space being 10-15 cm) were repaired intraoperatively with transplantation of modified vertical rectus abdominis myocutaneous flaps with the skin area being 9 cm×7 cm-16 cm×12 cm, the volume of the muscle being 18 cm×10 cm×5 cm-20 cm×12 cm×5 cm, and the vessel pedicle being 18-20 cm in length. During the operation, most of the anterior sheath of the rectus abdominis muscle was retained, the flap was transferred to the recipient area through the abdominal cavity, the remaining anterior sheaths of the rectus abdominis muscle on both sides of the donor area were repeatedly folded and sutured, the free edge of the transverse fascia of the abdomen was sutured with the anterior sheath of the rectus abdominis muscle, and the donor area skin was directly sutured. After the operation, the survival of the transplanted myocutaneous flap was observed. The occurrence of complications in the perineal recipient area was recorded within 2 weeks after the operation. The recovery of the perineal recipient area and the abdominal donor area was observed during follow-up, and the occurrence of complications in the donor area of the abdomen as well as the recurrence of tumors and metastasis were recorded. Results: All transplanted myocutaneous flaps in 5 patients survived after surgery. One patient had dehiscence of the incision in the perineal recipient area 2 days after surgery, which healed after 7 d with intermittent dressing changes and routine vacuum sealing drainage treatment. In the other 4 patients, no complications such as incisional rupture, incisional infection, or fat liquefaction occurred in the perineal recipient area within 2 weeks after surgery. Follow-up for 6-12 months after discharge showed that the skin of the perineal recipient area had good color, texture, and elasticity, and was not bloated in appearance; linear scars were left in the perineal recipient area and the abdominal donor area without obvious scar hyperplasia or hyperpigmentation; no complications such as incisional rupture, incisional infection, intestinal adhesion, intestinal obstruction, or weakening of the abdominal wall strength occurred in the abdominal donor area, and the abdominal appearance was good with no localized bulge or formation of abdominal hernia; there was no local recurrence of tumor or metastasis in any patient. Conclusions: The surgical approach of using the modified vertical rectus abdominis myocutaneous flap to repair the skin and soft tissue defects after abdominoperineal resection for rectal cancer is relatively simple in operation, can achieve good postoperative appearances of the donor and recipient areas with few complications, and is worthy of clinical promotion.
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Affiliation(s)
- M T Huang
- Department of Burns and Plastic Surgery, Xiangya Hospital, Central South University, Changsha 410008, China
| | - Z Qu
- Department of Basic Surgery, Xiangya Hospital, Central South University, Changsha 410008, China
| | - P F Liang
- Department of Burns and Plastic Surgery, Xiangya Hospital, Central South University, Changsha 410008, China
| | - W D Liu
- Department of Basic Surgery, Xiangya Hospital, Central South University, Changsha 410008, China
| | - Z Y He
- Department of Burns and Plastic Surgery, Xiangya Hospital, Central South University, Changsha 410008, China
| | - X Cui
- Department of Burns and Plastic Surgery, Xiangya Hospital, Central South University, Changsha 410008, China
| | - L Guo
- Department of Burns and Plastic Surgery, Xiangya Hospital, Central South University, Changsha 410008, China
| | - J Chen
- Department of Basic Surgery, Xiangya Hospital, Central South University, Changsha 410008, China
| | - M J Li
- Department of Medical Beauty Center, Hunan Provincial Institute of Occupational Disease Control, Changsha 410012, China
| | - X Y Huang
- Department of Burns and Plastic Surgery, Xiangya Hospital, Central South University, Changsha 410008, China
| | - P H Zhang
- Department of Burns and Plastic Surgery, Xiangya Hospital, Central South University, Changsha 410008, China
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7
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Li N, Fu QQ, Luo Y, Li MJ, Chen HL, Liao JM. [Application effects of rehabilitation care decision-making scheme based on case management model in severe burn patients]. Zhonghua Shao Shang Yu Chuang Mian Xiu Fu Za Zhi 2024; 40:78-86. [PMID: 38296240 DOI: 10.3760/cma.j.cn501225-20230905-00078] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 02/07/2024]
Abstract
Objective: To explore the application effects of application of rehabilitation care decision-making scheme based on case management model in severe burn patients. Methods: The study was a non-randomized historical control study. Thirty patients who met the inclusion criteria and received routine rehabilitation nursing in the First Affiliated Hospital of Army Medical University (the Third Military Medical University, hereinafter referred to as the hospital) from April 2021 to March 2022 were included in routine rehabilitation nursing group (26 males and 4 females, aged 48.50 (31.75, 56.25) years), and 30 patients who met the inclusion criteria and received case management rehabilitation nursing in the hospital from April 2022 to March 2023 were included in case management rehabilitation nursing group (22 males and 8 females, aged 46.00 (36.75, 55.25) years). The length of intensive care unit (ICU) stay, total hospitalization day, and total hospitalization cost of the patients in two groups were recorded. At admission, convalescence, discharge, and 6 months after injury, the patients' life quality was evaluated by the concise burn specific health scale, the sleep quality was evaluated by the Pittsburgh sleep quality index, and the functional independence was evaluated by the functional independence rating scale. At convalescence, discharge, and 6 months after injury, the patients' scar status was evaluated by the Vancouver scar scale. At 6 months after injury, a third-party satisfaction questionnaire was used to investigate the efficacy satisfaction of patients. Results: The length of ICU stay and total hospitalization day of patients in case management rehabilitation nursing group were both significantly shorter than those in routine rehabilitation nursing group (with Z values of -1.97 and -1.99, respectively, P<0.05), and the total hospitalization cost was less than that in routine rehabilitation nursing group (Z=-1.99, P<0.05). At discharge and 6 months after injury, the life quality scores of patients in case management rehabilitation nursing group were significantly higher than those in routine rehabilitation nursing group (with t values of -3.19 and -4.43, respectively, P<0.05), while the sleep quality scores were significantly lower than those in routine rehabilitation nursing group (with Z values of -2.18 and -3.33, respectively, P<0.05). There were no statistically significant differences in cognitive function scores of functional independence of patients between the 2 groups at admission, convalescence, discharge, and 6 months after injury (P>0.05). The exercise function scores and total scores of functional independence of patients in case management rehabilitation nursing group at convalescence, discharge, and 6 months after injury were significantly higher than those in routine rehabilitation nursing group (with Z values of -4.37, -2.73, -4.10, -4.37, -2.64, and -4.06, respectively, P<0.05). The scar pigmentation scores of patients in case management rehabilitation nursing group at 6 months after injury were significantly lower than those in routine rehabilitation nursing group (Z=-2.05, P<0.05), and the scar vascularity scores of patients in case management rehabilitation nursing group at discharge and 6 months after injury in case management rehabilitation nursing group were significantly lower than those in routine rehabilitation nursing group (with Z values of -3.16 and -2.07, respectively, P<0.05). The scar pliability scores (with Z values of -3.16, -2.45, and -4.38, respectively, P<0.05), thickness scores (with Z values of -2.56, -2.35, and -4.70, respectively, P<0.05), and total scores (with Z values of -3.77, -3.04, and -3.13, respectively, P<0.05) of patients in case management rehabilitation nursing group at convalescence, discharge, and 6 months after injury were significantly lower than those in routine rehabilitation nursing group. At 6 months after injury, the efficacy satisfaction scores of patients in case management rehabilitation nursing group were 4.00 (3.00, 4.25), which were significantly higher than 3.00 (2.00, 4.00) in routine rehabilitation nursing group (Z=-2.72, P<0.05). Conclusions: The implementation of rehabilitation care decision-making scheme based on case management model can optimize the cost efficiency, improve the effectiveness of clinical treatment, and enhance the life quality and satisfaction of the curative effect of severe burn patients.
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Affiliation(s)
- N Li
- Institute of Burn Research, State Key Laboratory of Trauma and Chemical Poisoning, the First Affiliated Hospital of Army Medical University (the Third Military Medical University), Chongqing 400038, China
| | - Q Q Fu
- Institute of Burn Research, State Key Laboratory of Trauma and Chemical Poisoning, the First Affiliated Hospital of Army Medical University (the Third Military Medical University), Chongqing 400038, China
| | - Y Luo
- Institute of Burn Research, State Key Laboratory of Trauma and Chemical Poisoning, the First Affiliated Hospital of Army Medical University (the Third Military Medical University), Chongqing 400038, China
| | - M J Li
- Institute of Burn Research, State Key Laboratory of Trauma and Chemical Poisoning, the First Affiliated Hospital of Army Medical University (the Third Military Medical University), Chongqing 400038, China
| | - H L Chen
- Institute of Burn Research, State Key Laboratory of Trauma and Chemical Poisoning, the First Affiliated Hospital of Army Medical University (the Third Military Medical University), Chongqing 400038, China
| | - J M Liao
- Nursing Department, the First Affiliated Hospital of Army Medical University (the Third Military Medical University), Chongqing 400038, China
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8
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Huang X, Huang J, Li X, Fan J, Zhou D, Qu HQ, Glessner JT, Ji D, Jia Q, Ding Z, Wang N, Wei W, Lyu X, Li MJ, Liu Z, Liu W, Wei Y, Hakonarson H, Xia Q, Li J. Target genes regulated by CLEC16A intronic region associated with common variable immunodeficiency. J Allergy Clin Immunol 2024:S0091-6749(24)00030-7. [PMID: 38191060 DOI: 10.1016/j.jaci.2023.12.023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2022] [Revised: 12/25/2023] [Accepted: 12/29/2023] [Indexed: 01/10/2024]
Abstract
BACKGROUND CLEC16A intron 19 has been identified as a candidate locus for common variable immunodeficiency (CVID). OBJECTIVES This study sought to elucidate the molecular mechanism by which variants at the CLEC16A intronic locus may contribute to the pathogenesis of CVID. METHODS The investigators performed fine-mapping of the CLEC16A locus in a CVID cohort, then deleted the candidate functional SNP in T-cell lines by the CRISPR-Cas9 technique and conducted RNA-sequencing to identify target gene(s). The interactions between the CLEC16A locus and its target genes were identified using circular chromosome conformation capture. The transcription factor complexes mediating the chromatin interactions were determined by proteomic approach. The molecular pathways regulated by the CLEC16A locus were examined by RNA-sequencing and reverse phase protein array. RESULTS This study showed that the CLEC16A locus is an enhancer regulating expression of multiple target genes including a distant gene ATF7IP2 through chromatin interactions. Distinct transcription factor complexes mediate the chromatin interactions in an allele-specific manner. Disruption of the CLEC16A locus affects the AKT signaling pathway, as well as the molecular response of CD4+ T cells to immune stimulation. CONCLUSIONS Through multiomics and targeted experimental approaches, this study elucidated the underlying target genes and signaling pathways involved in the genetic association of CLEC16A with CVID, and highlighted plausible molecular targets for developing novel therapeutics.
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Affiliation(s)
- Xubo Huang
- Affiliated Cancer Hospital and Institute of Guangzhou Medical University, Guangzhou, China
| | - Jinxia Huang
- Affiliated Cancer Hospital and Institute of Guangzhou Medical University, Guangzhou, China
| | - Xiumei Li
- Department of Cell Biology, The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, Key Laboratory of Immune Microenvironment and Disease (Ministry of Education), Tianjin Key Laboratory of Medical Epigenetics, Tianjin Institute of Immunology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China
| | - Jingxian Fan
- Department of Cell Biology, The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, Key Laboratory of Immune Microenvironment and Disease (Ministry of Education), Tianjin Key Laboratory of Medical Epigenetics, Tianjin Institute of Immunology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China; Department of Bioinformatics, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China
| | - Desheng Zhou
- Affiliated Cancer Hospital and Institute of Guangzhou Medical University, Guangzhou, China
| | - Hui-Qi Qu
- Center for Applied Genomics, The Children's Hospital of Philadelphia, Philadelphia, Pa
| | - Joseph T Glessner
- Center for Applied Genomics, The Children's Hospital of Philadelphia, Philadelphia, Pa; Division of Human Genetics, The Children's Hospital of Philadelphia, Philadelphia, Pa; Department of Pediatrics, The Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pa
| | - Dandan Ji
- Department of Cell Biology, The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, Key Laboratory of Immune Microenvironment and Disease (Ministry of Education), Tianjin Key Laboratory of Medical Epigenetics, Tianjin Institute of Immunology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China
| | - Qi Jia
- International School of Information Science Engineering, Dalian University of Technology, Dalian, China
| | - Zhiyong Ding
- Mills Institute for Personalized Cancer Care, Fynn Biotechnologies Ltd, Jinan, China
| | - Nan Wang
- Mills Institute for Personalized Cancer Care, Fynn Biotechnologies Ltd, Jinan, China
| | - Wei Wei
- Department of Rheumatology and Immunology, Tianjin Medical University General Hospital, Tianjin, China
| | - Xing Lyu
- Department of Rheumatology and Immunology, Tianjin Medical University General Hospital, Tianjin, China
| | - Mulin Jun Li
- Department of Bioinformatics, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China
| | - Zhe Liu
- Department of Immunology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China
| | - Wei Liu
- Tianjin Children's Hospital (Tianjin University Children's Hospital), Tianjin, China; Tianjin Key Laboratory of Birth Defects for Prevention and Treatment, Tianjin, China
| | - Yongjie Wei
- Affiliated Cancer Hospital and Institute of Guangzhou Medical University, Guangzhou, China
| | - Hakon Hakonarson
- Center for Applied Genomics, The Children's Hospital of Philadelphia, Philadelphia, Pa; Division of Human Genetics, The Children's Hospital of Philadelphia, Philadelphia, Pa; Department of Pediatrics, The Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pa
| | - Qianghua Xia
- Department of Cell Biology, The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, Key Laboratory of Immune Microenvironment and Disease (Ministry of Education), Tianjin Key Laboratory of Medical Epigenetics, Tianjin Institute of Immunology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China; Department of Bioinformatics, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China.
| | - Jin Li
- Department of Cell Biology, The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, Key Laboratory of Immune Microenvironment and Disease (Ministry of Education), Tianjin Key Laboratory of Medical Epigenetics, Tianjin Institute of Immunology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China; Department of Rheumatology and Immunology, Tianjin Medical University General Hospital, Tianjin, China.
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9
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Chang Y, Zhou Y, Zhou J, Li W, Cao J, Jing Y, Zhang S, Shen Y, Lin Q, Fan X, Yang H, Dong X, Zhang S, Yi X, Shuai L, Shi L, Liu Z, Yang J, Ma X, Hao J, Chen K, Li MJ, Wang F, Huang D. Unraveling the causal genes and transcriptomic determinants of human telomere length. Nat Commun 2023; 14:8517. [PMID: 38129441 PMCID: PMC10739845 DOI: 10.1038/s41467-023-44355-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2023] [Accepted: 12/11/2023] [Indexed: 12/23/2023] Open
Abstract
Telomere length (TL) shortening is a pivotal indicator of biological aging and is associated with many human diseases. The genetic determinates of human TL have been widely investigated, however, most existing studies were conducted based on adult tissues which are heavily influenced by lifetime exposure. Based on the analyses of terminal restriction fragment (TRF) length of telomere, individual genotypes, and gene expressions on 166 healthy placental tissues, we systematically interrogate TL-modulated genes and their potential functions. We discover that the TL in the placenta is comparatively longer than in other adult tissues, but exhibiting an intra-tissue homogeneity. Trans-ancestral TL genome-wide association studies (GWASs) on 644,553 individuals identify 20 newly discovered genetic associations and provide increased polygenic determination of human TL. Next, we integrate the powerful TL GWAS with placental expression quantitative trait locus (eQTL) mapping to prioritize 23 likely causal genes, among which 4 are functionally validated, including MMUT, RRM1, KIAA1429, and YWHAZ. Finally, modeling transcriptomic signatures and TRF-based TL improve the prediction performance of human TL. This study deepens our understanding of causal genes and transcriptomic determinants of human TL, promoting the mechanistic research on fine-grained TL regulation.
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Affiliation(s)
- Ying Chang
- Tianjin Key Lab of Human Development and Reproductive Regulation, Tianjin Central Hospital of Obstetrics and Gynecology, Nankai University, Tianjin, China
| | - Yao Zhou
- Department of Bioinformatics, The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, Key Laboratory of Immune Microenvironment and Disease (Ministry of Education), School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China
| | - Junrui Zhou
- Department of Genetics and Tianjin Key Laboratory of Cellular and Molecular Immunology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China
- Department of Clinical Laboratory, Shanghai Children's Hospital, Shanghai Jiaotong University, Shanghai, China
| | - Wen Li
- Tianjin Key Lab of Human Development and Reproductive Regulation, Tianjin Central Hospital of Obstetrics and Gynecology, Nankai University, Tianjin, China
| | - Jiasong Cao
- Tianjin Key Lab of Human Development and Reproductive Regulation, Tianjin Central Hospital of Obstetrics and Gynecology, Nankai University, Tianjin, China
| | - Yaqing Jing
- Department of Genetics and Tianjin Key Laboratory of Cellular and Molecular Immunology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China
| | - Shan Zhang
- Department of Genetics and Tianjin Key Laboratory of Cellular and Molecular Immunology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China
| | - Yongmei Shen
- Tianjin Key Lab of Human Development and Reproductive Regulation, Tianjin Central Hospital of Obstetrics and Gynecology, Nankai University, Tianjin, China
| | - Qimei Lin
- Tianjin Key Lab of Human Development and Reproductive Regulation, Tianjin Central Hospital of Obstetrics and Gynecology, Nankai University, Tianjin, China
| | - Xutong Fan
- Department of Bioinformatics, The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, Key Laboratory of Immune Microenvironment and Disease (Ministry of Education), School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China
| | - Hongxi Yang
- Department of Bioinformatics, The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, Key Laboratory of Immune Microenvironment and Disease (Ministry of Education), School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China
- Department of Pharmacology, Tianjin Key Laboratory of Inflammation Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China
| | - Xiaobao Dong
- Department of Genetics and Tianjin Key Laboratory of Cellular and Molecular Immunology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China
| | - Shijie Zhang
- Department of Pharmacology, Tianjin Key Laboratory of Inflammation Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China
| | - Xianfu Yi
- Department of Bioinformatics, The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, Key Laboratory of Immune Microenvironment and Disease (Ministry of Education), School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China
| | - Ling Shuai
- State Key Laboratory of Medicinal Chemical Biology, College of Pharmacy, Tianjin Central Hospital of Gynecology Obstetrics/Tianjin Key Laboratory of Human Development and Reproductive Regulation, Nankai University, Tianjin, China
| | - Lei Shi
- Key Laboratory of Immune Microenvironment and Disease (Ministry of Education), School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China
| | - Zhe Liu
- Key Laboratory of Immune Microenvironment and Disease (Ministry of Education), School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China
| | - Jie Yang
- Key Laboratory of Immune Microenvironment and Disease (Ministry of Education), School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China
| | - Xin Ma
- Wuxi School of Medicine, Jiangnan University, Wuxi, China
| | - Jihui Hao
- Department of Pancreatic Cancer, Key Laboratory of Cancer Prevention and Therapy, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China
| | - Kexin Chen
- Department of Epidemiology and Biostatistics, Tianjin Key Laboratory of Molecular Cancer Epidemiology, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin, China
| | - Mulin Jun Li
- Department of Bioinformatics, The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, Key Laboratory of Immune Microenvironment and Disease (Ministry of Education), School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China.
- Department of Epidemiology and Biostatistics, Tianjin Key Laboratory of Molecular Cancer Epidemiology, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin, China.
| | - Feng Wang
- Department of Genetics and Tianjin Key Laboratory of Cellular and Molecular Immunology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China.
- Tianjin Medical University School of Stomatology, Tianjin Medical University, Tianjin, China.
- Department of Geriatrics, Tianjin Medical University General Hospital; Tianjin Geriatrics Institute, Tianjin, China.
| | - Dandan Huang
- Department of Pharmacology, Tianjin Key Laboratory of Inflammation Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China.
- Wuxi School of Medicine, Jiangnan University, Wuxi, China.
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10
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Xu H, Yi X, Cui Z, Li H, Zhu L, Zhang L, Chen J, Fan X, Zhou P, Li MJ, Yu Y, Liu Q, Huang D, Yao Z, Zhou J. Maternal antibiotic exposure enhances ILC2 activation in neonates via downregulation of IFN1 signaling. Nat Commun 2023; 14:8332. [PMID: 38097561 PMCID: PMC10721923 DOI: 10.1038/s41467-023-43903-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2023] [Accepted: 11/23/2023] [Indexed: 12/17/2023] Open
Abstract
Microbiota have an important function in shaping and priming neonatal immunity, although the cellular and molecular mechanisms underlying these effects remain obscure. Here we report that prenatal antibiotic exposure causes significant elevation of group 2 innate lymphoid cells (ILC2s) in neonatal lungs, in both cell numbers and functionality. Downregulation of type 1 interferon signaling in ILC2s due to diminished production of microbiota-derived butyrate represents the underlying mechanism. Mice lacking butyrate receptor GPR41 (Gpr41-/-) or type 1 interferon receptor IFNAR1 (Ifnar1-/-) recapitulate the phenotype of neonatal ILC2s upon maternal antibiotic exposure. Furthermore, prenatal antibiotic exposure induces epigenetic changes in ILC2s and has a long-lasting deteriorative effect on allergic airway inflammation in adult offspring. Prenatal supplementation of butyrate ameliorates airway inflammation in adult mice born to antibiotic-exposed dams. These observations demonstrate an essential role for the microbiota in the control of type 2 innate immunity at the neonatal stage, which suggests a therapeutic window for treating asthma in early life.
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Affiliation(s)
- Haixu Xu
- Department of Immunology, Tianjin Institute of Immunology, Key Laboratory of Immune Microenvironment and Disease of the Ministry of Education, State Key Laboratory of Experimental Hematology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, 300070, China
| | - Xianfu Yi
- Department of Bioinformatics, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, 300070, China
| | - Zhaohai Cui
- Department of Immunology, Tianjin Institute of Immunology, Key Laboratory of Immune Microenvironment and Disease of the Ministry of Education, State Key Laboratory of Experimental Hematology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, 300070, China
| | - Hui Li
- Department of Immunology, Tianjin Institute of Immunology, Key Laboratory of Immune Microenvironment and Disease of the Ministry of Education, State Key Laboratory of Experimental Hematology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, 300070, China
| | - Lin Zhu
- Department of Immunology, Tianjin Institute of Immunology, Key Laboratory of Immune Microenvironment and Disease of the Ministry of Education, State Key Laboratory of Experimental Hematology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, 300070, China
| | - Lijuan Zhang
- Department of Immunology, Tianjin Institute of Immunology, Key Laboratory of Immune Microenvironment and Disease of the Ministry of Education, State Key Laboratory of Experimental Hematology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, 300070, China
| | - JiaLe Chen
- Department of Immunology, Tianjin Institute of Immunology, Key Laboratory of Immune Microenvironment and Disease of the Ministry of Education, State Key Laboratory of Experimental Hematology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, 300070, China
| | - Xutong Fan
- Department of Bioinformatics, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, 300070, China
| | - Pan Zhou
- Department of Immunology, Tianjin Institute of Immunology, Key Laboratory of Immune Microenvironment and Disease of the Ministry of Education, State Key Laboratory of Experimental Hematology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, 300070, China
| | - Mulin Jun Li
- Department of Bioinformatics, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, 300070, China
| | - Ying Yu
- Department of Pharmacology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, 300070, China
| | - Qiang Liu
- Department of Neurology, Institute of Neuroimmunology, Tianjin Medical University General Hospital, Tianjin, 300052, China
| | - Dandan Huang
- Department of Pharmacology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, 300070, China.
| | - Zhi Yao
- Department of Immunology, Tianjin Institute of Immunology, Key Laboratory of Immune Microenvironment and Disease of the Ministry of Education, State Key Laboratory of Experimental Hematology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, 300070, China.
| | - Jie Zhou
- Department of Immunology, Tianjin Institute of Immunology, Key Laboratory of Immune Microenvironment and Disease of the Ministry of Education, State Key Laboratory of Experimental Hematology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, 300070, China.
- Department of Neonatology, Guangzhou Key Laboratory of Neonatal Intestinal Diseases, the Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510150, China.
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11
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Zhang B, Li Y, Zhang J, Wang Y, Liang C, Lu T, Zhang C, Liu L, Qin Y, He J, Zhao X, Yu J, Hao J, Yang J, Li MJ, Yao Z, Ma S, Cheng H, Cheng T, Shi L. ADAR1 links R-loop homeostasis to ATR activation in replication stress response. Nucleic Acids Res 2023; 51:11668-11687. [PMID: 37831098 PMCID: PMC10681745 DOI: 10.1093/nar/gkad839] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2023] [Revised: 09/12/2023] [Accepted: 09/21/2023] [Indexed: 10/14/2023] Open
Abstract
Unscheduled R-loops are a major source of replication stress and DNA damage. R-loop-induced replication defects are sensed and suppressed by ATR kinase, whereas it is not known whether R-loop itself is actively involved in ATR activation and, if so, how this is achieved. Here, we report that the nuclear form of RNA-editing enzyme ADAR1 promotes ATR activation and resolves genome-wide R-loops, a process that requires its double-stranded RNA-binding domains. Mechanistically, ADAR1 interacts with TOPBP1 and facilitates its loading on perturbed replication forks by enhancing the association of TOPBP1 with RAD9 of the 9-1-1 complex. When replication is inhibited, DNA-RNA hybrid competes with TOPBP1 for ADAR1 binding to promote the translocation of ADAR1 from damaged fork to accumulate at R-loop region. There, ADAR1 recruits RNA helicases DHX9 and DDX21 to unwind R-loops, simultaneously allowing TOPBP1 to stimulate ATR more efficiently. Collectively, we propose that the tempo-spatially regulated assembly of ADAR1-nucleated protein complexes link R-loop clearance and ATR activation, while R-loops crosstalk with blocked replication forks by transposing ADAR1 to finetune ATR activity and safeguard the genome.
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Affiliation(s)
- Biao Zhang
- State Key Laboratory of Experimental Hematology, Haihe Laboratory of Cell Ecosystem, Key Laboratory of Breast Cancer Prevention and Therapy (Ministry of Education), Key Laboratory of Immune Microenvironment and Disease (Ministry of Education), The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin 300070, China
- Tianjin Institutes of Health Science, National Clinical Research Center for Blood Diseases, Institute of Hematology and Blood Diseases Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Tianjin 300020, China
| | - Yi Li
- State Key Laboratory of Experimental Hematology, Haihe Laboratory of Cell Ecosystem, Key Laboratory of Breast Cancer Prevention and Therapy (Ministry of Education), Key Laboratory of Immune Microenvironment and Disease (Ministry of Education), The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin 300070, China
| | - Jieyou Zhang
- State Key Laboratory of Experimental Hematology, Haihe Laboratory of Cell Ecosystem, Key Laboratory of Breast Cancer Prevention and Therapy (Ministry of Education), Key Laboratory of Immune Microenvironment and Disease (Ministry of Education), The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin 300070, China
| | - Yuejiao Wang
- State Key Laboratory of Experimental Hematology, Haihe Laboratory of Cell Ecosystem, Key Laboratory of Breast Cancer Prevention and Therapy (Ministry of Education), Key Laboratory of Immune Microenvironment and Disease (Ministry of Education), The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin 300070, China
| | - Can Liang
- State Key Laboratory of Experimental Hematology, Haihe Laboratory of Cell Ecosystem, Key Laboratory of Breast Cancer Prevention and Therapy (Ministry of Education), Key Laboratory of Immune Microenvironment and Disease (Ministry of Education), The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin 300070, China
| | - Ting Lu
- State Key Laboratory of Experimental Hematology, Haihe Laboratory of Cell Ecosystem, Key Laboratory of Breast Cancer Prevention and Therapy (Ministry of Education), Key Laboratory of Immune Microenvironment and Disease (Ministry of Education), The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin 300070, China
- Tianjin Institutes of Health Science, National Clinical Research Center for Blood Diseases, Institute of Hematology and Blood Diseases Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Tianjin 300020, China
| | - Chunyong Zhang
- State Key Laboratory of Experimental Hematology, Haihe Laboratory of Cell Ecosystem, Key Laboratory of Breast Cancer Prevention and Therapy (Ministry of Education), Key Laboratory of Immune Microenvironment and Disease (Ministry of Education), The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin 300070, China
| | - Ling Liu
- State Key Laboratory of Experimental Hematology, Haihe Laboratory of Cell Ecosystem, Key Laboratory of Breast Cancer Prevention and Therapy (Ministry of Education), Key Laboratory of Immune Microenvironment and Disease (Ministry of Education), The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin 300070, China
| | - Yan Qin
- State Key Laboratory of Experimental Hematology, Haihe Laboratory of Cell Ecosystem, Key Laboratory of Breast Cancer Prevention and Therapy (Ministry of Education), Key Laboratory of Immune Microenvironment and Disease (Ministry of Education), The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin 300070, China
| | - Jiahuan He
- Tianjin Institutes of Health Science, National Clinical Research Center for Blood Diseases, Institute of Hematology and Blood Diseases Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Tianjin 300020, China
- State Key Laboratory of Medical Molecular Biology, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences & School of Basic Medicine, Peking Union Medical College, 100006, Beijing, China
| | - Xiangnan Zhao
- State Key Laboratory of Experimental Hematology, Haihe Laboratory of Cell Ecosystem, Key Laboratory of Breast Cancer Prevention and Therapy (Ministry of Education), Key Laboratory of Immune Microenvironment and Disease (Ministry of Education), The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin 300070, China
- Tianjin Institutes of Health Science, National Clinical Research Center for Blood Diseases, Institute of Hematology and Blood Diseases Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Tianjin 300020, China
| | - Jia Yu
- Tianjin Institutes of Health Science, National Clinical Research Center for Blood Diseases, Institute of Hematology and Blood Diseases Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Tianjin 300020, China
- State Key Laboratory of Medical Molecular Biology, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences & School of Basic Medicine, Peking Union Medical College, 100006, Beijing, China
| | - Jihui Hao
- State Key Laboratory of Experimental Hematology, Haihe Laboratory of Cell Ecosystem, Key Laboratory of Breast Cancer Prevention and Therapy (Ministry of Education), Key Laboratory of Immune Microenvironment and Disease (Ministry of Education), The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin 300070, China
| | - Jie Yang
- State Key Laboratory of Experimental Hematology, Haihe Laboratory of Cell Ecosystem, Key Laboratory of Breast Cancer Prevention and Therapy (Ministry of Education), Key Laboratory of Immune Microenvironment and Disease (Ministry of Education), The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin 300070, China
| | - Mulin Jun Li
- State Key Laboratory of Experimental Hematology, Haihe Laboratory of Cell Ecosystem, Key Laboratory of Breast Cancer Prevention and Therapy (Ministry of Education), Key Laboratory of Immune Microenvironment and Disease (Ministry of Education), The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin 300070, China
| | - Zhi Yao
- State Key Laboratory of Experimental Hematology, Haihe Laboratory of Cell Ecosystem, Key Laboratory of Breast Cancer Prevention and Therapy (Ministry of Education), Key Laboratory of Immune Microenvironment and Disease (Ministry of Education), The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin 300070, China
| | - Shuai Ma
- State Key Laboratory of Experimental Hematology, Haihe Laboratory of Cell Ecosystem, Key Laboratory of Breast Cancer Prevention and Therapy (Ministry of Education), Key Laboratory of Immune Microenvironment and Disease (Ministry of Education), The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin 300070, China
| | - Hui Cheng
- State Key Laboratory of Experimental Hematology, Haihe Laboratory of Cell Ecosystem, Key Laboratory of Breast Cancer Prevention and Therapy (Ministry of Education), Key Laboratory of Immune Microenvironment and Disease (Ministry of Education), The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin 300070, China
- Tianjin Institutes of Health Science, National Clinical Research Center for Blood Diseases, Institute of Hematology and Blood Diseases Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Tianjin 300020, China
| | - Tao Cheng
- State Key Laboratory of Experimental Hematology, Haihe Laboratory of Cell Ecosystem, Key Laboratory of Breast Cancer Prevention and Therapy (Ministry of Education), Key Laboratory of Immune Microenvironment and Disease (Ministry of Education), The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin 300070, China
- Tianjin Institutes of Health Science, National Clinical Research Center for Blood Diseases, Institute of Hematology and Blood Diseases Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Tianjin 300020, China
| | - Lei Shi
- State Key Laboratory of Experimental Hematology, Haihe Laboratory of Cell Ecosystem, Key Laboratory of Breast Cancer Prevention and Therapy (Ministry of Education), Key Laboratory of Immune Microenvironment and Disease (Ministry of Education), The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin 300070, China
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12
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Wang Z, Luo M, Liang Q, Zhao K, Hu Y, Wang W, Feng X, Hu B, Teng J, You T, Li R, Bao Z, Pan W, Yang T, Zhang C, Li T, Dong X, Yi X, Liu B, Zhao L, Li M, Chen K, Song W, Yang J, Li MJ. Landscape of enhancer disruption and functional screen in melanoma cells. Genome Biol 2023; 24:248. [PMID: 37904237 PMCID: PMC10614365 DOI: 10.1186/s13059-023-03087-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2022] [Accepted: 10/12/2023] [Indexed: 11/01/2023] Open
Abstract
BACKGROUND The high mutation rate throughout the entire melanoma genome presents a major challenge in stratifying true driver events from the background mutations. Numerous recurrent non-coding alterations, such as those in enhancers, can shape tumor evolution, thereby emphasizing the importance in systematically deciphering enhancer disruptions in melanoma. RESULTS Here, we leveraged 297 melanoma whole-genome sequencing samples to prioritize highly recurrent regions. By performing a genome-scale CRISPR interference (CRISPRi) screen on highly recurrent region-associated enhancers in melanoma cells, we identified 66 significant hits which could have tumor-suppressive roles. These functional enhancers show unique mutational patterns independent of classical significantly mutated genes in melanoma. Target gene analysis for the essential enhancers reveal many known and hidden mechanisms underlying melanoma growth. Utilizing extensive functional validation experiments, we demonstrate that a super enhancer element could modulate melanoma cell proliferation by targeting MEF2A, and another distal enhancer is able to sustain PTEN tumor-suppressive potential via long-range interactions. CONCLUSIONS Our study establishes a catalogue of crucial enhancers and their target genes in melanoma growth and progression, and illuminates the identification of novel mechanisms of dysregulation for melanoma driver genes and new therapeutic targeting strategies.
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Affiliation(s)
- Zhao Wang
- Oujiang Laboratory (Zhejiang Lab for Regenerative Medicine, Vision and Brain Health), Institute of Aging, Key Laboratory of Alzheimer's Disease of Zhejiang Province, The Second Affiliated Hospital, Wenzhou Medical University, Wenzhou, China.
- Department of Epidemiology and Biostatistics, Tianjin Key Laboratory of Molecular Cancer Epidemiology, The Province and Ministry Co-Sponsored Collaborative Innovation Center for Medical Epigenetics, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin, China.
| | - Menghan Luo
- Department of Epidemiology and Biostatistics, Tianjin Key Laboratory of Molecular Cancer Epidemiology, The Province and Ministry Co-Sponsored Collaborative Innovation Center for Medical Epigenetics, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin, China
- Department of Bioinformatics, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China
| | - Qian Liang
- Oujiang Laboratory (Zhejiang Lab for Regenerative Medicine, Vision and Brain Health), Institute of Aging, Key Laboratory of Alzheimer's Disease of Zhejiang Province, The Second Affiliated Hospital, Wenzhou Medical University, Wenzhou, China
- Department of Epidemiology and Biostatistics, Tianjin Key Laboratory of Molecular Cancer Epidemiology, The Province and Ministry Co-Sponsored Collaborative Innovation Center for Medical Epigenetics, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin, China
- Scientific Research Center, Wenzhou Medical University, Wenzhou, China
| | - Ke Zhao
- Department of Bioinformatics, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China
| | - Yuelin Hu
- Oujiang Laboratory (Zhejiang Lab for Regenerative Medicine, Vision and Brain Health), Institute of Aging, Key Laboratory of Alzheimer's Disease of Zhejiang Province, The Second Affiliated Hospital, Wenzhou Medical University, Wenzhou, China
| | - Wei Wang
- Department of Epidemiology and Biostatistics, Tianjin Key Laboratory of Molecular Cancer Epidemiology, The Province and Ministry Co-Sponsored Collaborative Innovation Center for Medical Epigenetics, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin, China
| | - Xiangling Feng
- Department of Bioinformatics, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China
| | - Bolang Hu
- Oujiang Laboratory (Zhejiang Lab for Regenerative Medicine, Vision and Brain Health), Institute of Aging, Key Laboratory of Alzheimer's Disease of Zhejiang Province, The Second Affiliated Hospital, Wenzhou Medical University, Wenzhou, China
| | - Jianjin Teng
- Department of Bioinformatics, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China
| | - Tianyi You
- Department of Bioinformatics, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China
| | - Ran Li
- Oujiang Laboratory (Zhejiang Lab for Regenerative Medicine, Vision and Brain Health), Institute of Aging, Key Laboratory of Alzheimer's Disease of Zhejiang Province, The Second Affiliated Hospital, Wenzhou Medical University, Wenzhou, China
| | - Zhengkai Bao
- Oujiang Laboratory (Zhejiang Lab for Regenerative Medicine, Vision and Brain Health), Institute of Aging, Key Laboratory of Alzheimer's Disease of Zhejiang Province, The Second Affiliated Hospital, Wenzhou Medical University, Wenzhou, China
| | - Wenhao Pan
- Oujiang Laboratory (Zhejiang Lab for Regenerative Medicine, Vision and Brain Health), Institute of Aging, Key Laboratory of Alzheimer's Disease of Zhejiang Province, The Second Affiliated Hospital, Wenzhou Medical University, Wenzhou, China
| | - Tielong Yang
- Department of Bone and Soft Tissue Tumor, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin, China
| | - Chao Zhang
- Department of Bone and Soft Tissue Tumor, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin, China
| | - Ting Li
- Department of Bone and Soft Tissue Tumor, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin, China
| | - Xiaobao Dong
- Department of Bioinformatics, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China
| | - Xianfu Yi
- Department of Bioinformatics, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China
| | - Ben Liu
- Department of Epidemiology and Biostatistics, Tianjin Key Laboratory of Molecular Cancer Epidemiology, The Province and Ministry Co-Sponsored Collaborative Innovation Center for Medical Epigenetics, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin, China
| | - Li Zhao
- Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China
| | - Miaoxin Li
- Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou, China
| | - Kexin Chen
- Department of Epidemiology and Biostatistics, Tianjin Key Laboratory of Molecular Cancer Epidemiology, The Province and Ministry Co-Sponsored Collaborative Innovation Center for Medical Epigenetics, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin, China
| | - Weihong Song
- Oujiang Laboratory (Zhejiang Lab for Regenerative Medicine, Vision and Brain Health), Institute of Aging, Key Laboratory of Alzheimer's Disease of Zhejiang Province, The Second Affiliated Hospital, Wenzhou Medical University, Wenzhou, China.
| | - Jilong Yang
- Department of Bone and Soft Tissue Tumor, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin, China.
| | - Mulin Jun Li
- Department of Epidemiology and Biostatistics, Tianjin Key Laboratory of Molecular Cancer Epidemiology, The Province and Ministry Co-Sponsored Collaborative Innovation Center for Medical Epigenetics, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin, China.
- Department of Bioinformatics, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China.
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13
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Li R, Huang D, Zhao Y, Yuan Y, Sun X, Dai Z, Huo D, Liu X, Helin K, Li MJ, Wu X. PR-DUB safeguards Polycomb repression through H2AK119ub1 restriction. Cell Prolif 2023; 56:e13457. [PMID: 36959757 PMCID: PMC10542648 DOI: 10.1111/cpr.13457] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2023] [Revised: 03/01/2023] [Accepted: 03/11/2023] [Indexed: 03/25/2023] Open
Abstract
Polycomb group (PcG) proteins are critical chromatin regulators for cell fate control. The mono-ubiquitylation on histone H2AK119 (H2AK119ub1) is one of the well-recognized mechanisms for Polycomb repressive complex 1 (PRC1)-mediated transcription repression. Unexpectedly, the specific H2AK119 deubiquitylation complex composed by additional sex comb-like proteins and BAP1 has also been genetically characterized as Polycomb repressive deubiquitnase (PR-DUB) for unclear reasons. However, it remains a mystery whether and how PR-DUB deficiency affects chromatin states and cell fates through impaired PcG silencing. Here through a careful epigenomic analysis, we demonstrate that a bulk of H2AK119ub1 is diffusely distributed away from promoter regions and their enrichment is positively correlated with PRC1 occupancy. Upon deletion of Asxl2 in mouse embryonic stem cells (ESCs), a pervasive gain of H2AK119ub1 is coincident with increased PRC1 sampling at chromatin. Accordingly, PRC1 is significantly lost from a subset of highly occupied promoters, leading to impaired silencing of associated genes before and after lineage differentiation of Asxl2-null ESCs. Therefore, our study highlights the importance of genome-wide H2AK119ub1 restriction by PR-DUB in safeguarding robust PRC1 deposition and its roles in developmental regulation.
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Affiliation(s)
- Rui Li
- State Key Laboratory of Experimental Hematology, The Province and Ministry Co‐sponsored Collaborative Innovation Center for Medical Epigenetics, Key Laboratory of Immune Microenvironment and Disease (Ministry of Education), Department of Cell Biology, School of Basic Medical SciencesTianjin Medical UniversityTianjin300070China
| | - Dandan Huang
- Wuxi School of MedicineJiangnan UniversityWuxi214000China
| | - Yingying Zhao
- State Key Laboratory of Experimental Hematology, The Province and Ministry Co‐sponsored Collaborative Innovation Center for Medical Epigenetics, Key Laboratory of Immune Microenvironment and Disease (Ministry of Education), Department of Cell Biology, School of Basic Medical SciencesTianjin Medical UniversityTianjin300070China
| | - Ye Yuan
- State Key Laboratory of Experimental Hematology, The Province and Ministry Co‐sponsored Collaborative Innovation Center for Medical Epigenetics, Key Laboratory of Immune Microenvironment and Disease (Ministry of Education), Department of Cell Biology, School of Basic Medical SciencesTianjin Medical UniversityTianjin300070China
| | - Xiaoyu Sun
- State Key Laboratory of Experimental Hematology, The Province and Ministry Co‐sponsored Collaborative Innovation Center for Medical Epigenetics, Key Laboratory of Immune Microenvironment and Disease (Ministry of Education), Department of Cell Biology, School of Basic Medical SciencesTianjin Medical UniversityTianjin300070China
| | - Zhongye Dai
- State Key Laboratory of Experimental Hematology, The Province and Ministry Co‐sponsored Collaborative Innovation Center for Medical Epigenetics, Key Laboratory of Immune Microenvironment and Disease (Ministry of Education), Department of Cell Biology, School of Basic Medical SciencesTianjin Medical UniversityTianjin300070China
| | - Dawei Huo
- State Key Laboratory of Experimental Hematology, The Province and Ministry Co‐sponsored Collaborative Innovation Center for Medical Epigenetics, Key Laboratory of Immune Microenvironment and Disease (Ministry of Education), Department of Cell Biology, School of Basic Medical SciencesTianjin Medical UniversityTianjin300070China
| | - Xiaozhi Liu
- Pediatric Center, Tianjin Key Laboratory of Epigenetics for Organ Development of Premature InfantsThe Fifth Central Hospital of TianjinTianjin300450China
| | - Kristian Helin
- Biotech Research and Innovation CentreUniversity of CopenhagenCopenhagenDenmark
- The Institute of Cancer Research (ICR)LondonUK
| | - Mulin Jun Li
- Department of Bioinformatics, School of Basic Medical SciencesTianjin Medical UniversityTianjin300070China
- Department of Epidemiology and Biostatistics, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and HospitalTianjin Medical UniversityTianjin300070China
| | - Xudong Wu
- State Key Laboratory of Experimental Hematology, The Province and Ministry Co‐sponsored Collaborative Innovation Center for Medical Epigenetics, Key Laboratory of Immune Microenvironment and Disease (Ministry of Education), Department of Cell Biology, School of Basic Medical SciencesTianjin Medical UniversityTianjin300070China
- Department of OrthopedicsTianjin Medical University General HospitalTianjin300052China
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14
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Li MJ, Chen HL, Ju YY, Zeng LJ, Li N. [A cross-sectional survey and influencing factors analysis of knowledge, attitude, and behavior of enteral nutrition implemented by nurses in burn intensive care unit]. Zhonghua Shao Shang Yu Chuang Mian Xiu Fu Za Zhi 2023; 39:874-881. [PMID: 37805804 DOI: 10.3760/cma.j.cn501225-20220522-00198] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 10/09/2023]
Abstract
Objective: To investigate the status of knowledge, attitude, and behavior of enteral nutrition implemented by nurses in burn intensive care unit (BICU) and analyze its influencing factors. Methods: A multi-center cross-sectional survey research method was used. On May 8th, 2022, 107 BICU nurses who met the inclusion criteria were selected from the burn departments of the First Affiliated Hospital of Army Medical University (the Third Military Medical University), Guangdong Provincial People's Hospital, the First Affiliated Hospital of Guangxi Medical University, the Affiliated Hospital of Qinghai University, the Second Affiliated Hospital of Air Force Medical University, the Affiliated Hospital of Nantong University, Guiyang Steel Factory Staff Hospital, and the Second Affiliated Hospital of Kunming Medical University. The self-made nurses' enteral nutrition nursing knowledge-attitude-behavior questionnaire for severely burned patients was used to investigate the nurses' gender, age, working years, professional title, position, highest educational background, and whether they received systematic training in knowledge of enteral nutrition, the scores of each factor, and the total scores of knowledge, attitude, and behavior dimensions of enteral nutrition in nurses. The nurses were classified according to the general data, and the total scores of their knowledge, attitude, and behavior of enteral nutrition were calculated. Data were statistically analyzed with independent sample t test, one-way analysis of variance, Mann-Whitney U test, and Kruskal-Wallis H test. According to the results of univariate analysis and combined with clinical experience and significance, the generalized linear model analysis was carried out to screen the independent influencing factors of the total scores of knowledge, attitude, and behavior of enteral nutrition in BICU nurses. Results: A total of 107 nurses were surveyed, and 107 valid questionnaires were collected, with an effective recovery rate of 100%. In the BICU nurses' enteral nutrition knowledge-attitude-behavior questionnaire, the total scores of knowledge, attitude, and behavior were 44±13, 87±15, and 70±19, respectively. Most of the BICU nurses in this survey were female, aged 22-48 (31±6) years, and the number of nurses worked for 1-5, 6-10, and ≥11 years was evenly distributed. The majority of the professional titles of nurses were nurses, positions were responsible nurses, and the highest educational background was undergraduate. Forty-four nurses received systematic training in knowledge of enteral nutrition. There were statistically significant differences in the total scores of knowledge of enteral nutrition among BICU nurses with different ages, working years, professional titles, positions, highest educational background, and whether they received systematic training in knowledge of enteral nutrition (with H values of 27.36, 15.27, and 10.19, respectively, Z values of -3.33, -2.59, and -6.46, respectively, P<0.05). There were no statistically significant differences in the total scores of attitude and behavior of enteral nutrition among BICU nurses with different gender, ages, working years, professional titles, positions, highest educational background, and whether they received systematic training in knowledge of enteral nutrition (P>0.05). Age (26-30, 31-35, and ≥36 years old), highest educational background (undergraduate), and the systematic training received in enteral nutrition knowledge were the independent influencing factors for the total score of knowledge of enteral nutrition in BICU nurses (with 95% confidence intervals of 0.12-0.36, 0-0.30, 0.03-0.31, 0.01-0.32, and 0.19-0.40, respectively, standardized regression coefficients of 0.24, 0.15, 0.17, 0.17, and 0.29, respectively, P<0.05). There were no independent influencing factors for the total scores of enteral nutrition attitude and behavior of BICU nurses in different characteristics (P>0.05). Conclusions: The BICU nurses have low cognitive level in the implementation of enteral nutrition, their concept needs to be updated in time, and their behavior needs to be further standardized. Age (26-30, 31-35, and ≥36 years old), highest educational background (undergraduate), and the systematic training received in enteral nutrition knowledge were the independent influencing factors for the knowledge of enteral nutrition in BICU nurses.
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Affiliation(s)
- M J Li
- Institute of Burn Research, State Key Laboratory of Trauma and Chemical Poisoning, the First Affiliated Hospital of Army Medical University (the Third Military Medical University), Chongqing 400038, China
| | - H L Chen
- Institute of Burn Research, State Key Laboratory of Trauma and Chemical Poisoning, the First Affiliated Hospital of Army Medical University (the Third Military Medical University), Chongqing 400038, China
| | - Y Y Ju
- Institute of Burn Research, State Key Laboratory of Trauma and Chemical Poisoning, the First Affiliated Hospital of Army Medical University (the Third Military Medical University), Chongqing 400038, China
| | - L J Zeng
- Institute of Burn Research, State Key Laboratory of Trauma and Chemical Poisoning, the First Affiliated Hospital of Army Medical University (the Third Military Medical University), Chongqing 400038, China
| | - N Li
- Institute of Burn Research, State Key Laboratory of Trauma and Chemical Poisoning, the First Affiliated Hospital of Army Medical University (the Third Military Medical University), Chongqing 400038, China
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15
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Li MJ, Li J, Niu DS. [The cell nuclear damage probably induces chronic refractory diseases]. Zhonghua Lao Dong Wei Sheng Zhi Ye Bing Za Zhi 2023; 41:636-640. [PMID: 37667165 DOI: 10.3760/cma.j.cn121094-20230302-00059] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 09/06/2023]
Abstract
The cell nuclear damage is mainly caused by the radiation and various carcinogenic compounds, the essence of the damage is molecular adhesion fracture and chemical modification. After nuclear damage, the cells whose nuclei may be abnormal in morphology, structure and function, then become a kind of morbid cells or defective cells. The cell nuclear damage can affect gene expression and regulation, leading to dysfunctions or abnormalities of transcription and protein synthesis, which results in aging and induces various chronic refractory diseases, such as hypertension, atherosclerosis, diabetes, Alzheimer's disease, autoimmune diseases, and so on. The cell nuclear damage can also affect the state of cell differentiation and lead to restart of genes related to division and proliferation, thus inducing cancer. The cancer cells are derived from the cells with nuclear abnormalities, and the biological behavior or characteristics of cancer cells (shedding and metastasis, immune tolerance, uncontrolled, loss of contact inhibition, etc.) are derived from cells with nuclear abnormalities. This article reviewed the chronic refractory diseases caused by nuclear damage and their mechanisms, which provided a new idea for occupational health and toxicology research, as well as a new method and strategy for occupational disease prevention and treatment.
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Affiliation(s)
- M J Li
- Department of Medical Examination, the Beijing Institute of Occupational Disease Prevention and Treatment Beijing Prevention and Treatment Hospital of Occupational Disease for Chemical Industry, Beijing 100093, China
| | - J Li
- Department of Medical Examination, the Beijing Institute of Occupational Disease Prevention and Treatment Beijing Prevention and Treatment Hospital of Occupational Disease for Chemical Industry, Beijing 100093, China
| | - D S Niu
- Department of Medical Examination, the Beijing Institute of Occupational Disease Prevention and Treatment Beijing Prevention and Treatment Hospital of Occupational Disease for Chemical Industry, Beijing 100093, China
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16
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Xu H, Yi X, Fan X, Wu C, Wang W, Chu X, Zhang S, Dong X, Wang Z, Wang J, Zhou Y, Zhao K, Yao H, Zheng N, Wang J, Chen Y, Plewczynski D, Sham PC, Chen K, Huang D, Li MJ. Inferring CTCF-binding patterns and anchored loops across human tissues and cell types. Patterns (N Y) 2023; 4:100798. [PMID: 37602215 PMCID: PMC10436006 DOI: 10.1016/j.patter.2023.100798] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/12/2022] [Revised: 01/25/2023] [Accepted: 06/20/2023] [Indexed: 08/22/2023]
Abstract
CCCTC-binding factor (CTCF) is a transcription regulator with a complex role in gene regulation. The recognition and effects of CTCF on DNA sequences, chromosome barriers, and enhancer blocking are not well understood. Existing computational tools struggle to assess the regulatory potential of CTCF-binding sites and their impact on chromatin loop formation. Here we have developed a deep-learning model, DeepAnchor, to accurately characterize CTCF binding using high-resolution genomic/epigenomic features. This has revealed distinct chromatin and sequence patterns for CTCF-mediated insulation and looping. An optimized implementation of a previous loop model based on DeepAnchor score excels in predicting CTCF-anchored loops. We have established a compendium of CTCF-anchored loops across 52 human tissue/cell types, and this suggests that genomic disruption of these loops could be a general mechanism of disease pathogenesis. These computational models and resources can help investigate how CTCF-mediated cis-regulatory elements shape context-specific gene regulation in cell development and disease progression.
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Affiliation(s)
- Hang Xu
- Department of Epidemiology and Biostatistics, Key Laboratory of Prevention and Control of Human Major Diseases (Ministry of Education), National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin 300070, China
- Singapore Immunology Network (SIgN), Agency for Science, Technology and Research (A∗STAR), Singapore 138648, Singapore
| | - Xianfu Yi
- Department of Bioinformatics, The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, School of Basic Medical Sciences, Tianjin Medical University, Tianjin 300070, China
| | - Xutong Fan
- Department of Bioinformatics, The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, School of Basic Medical Sciences, Tianjin Medical University, Tianjin 300070, China
| | - Chengyue Wu
- Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin 300070, China
| | - Wei Wang
- Department of Epidemiology and Biostatistics, Key Laboratory of Prevention and Control of Human Major Diseases (Ministry of Education), National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin 300070, China
| | - Xinlei Chu
- Department of Epidemiology and Biostatistics, Key Laboratory of Prevention and Control of Human Major Diseases (Ministry of Education), National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin 300070, China
| | - Shijie Zhang
- Department of Pharmacology, Tianjin Key Laboratory of Inflammation Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin 300070, China
| | - Xiaobao Dong
- Department of Genetics, School of Basic Medical Sciences, Tianjin Medical University, Tianjin 300070, China
| | - Zhao Wang
- Department of Pharmacology, Tianjin Key Laboratory of Inflammation Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin 300070, China
| | - Jianhua Wang
- Department of Bioinformatics, The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, School of Basic Medical Sciences, Tianjin Medical University, Tianjin 300070, China
| | - Yao Zhou
- Department of Bioinformatics, The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, School of Basic Medical Sciences, Tianjin Medical University, Tianjin 300070, China
| | - Ke Zhao
- Department of Pharmacology, Tianjin Key Laboratory of Inflammation Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin 300070, China
| | - Hongcheng Yao
- Centre for PanorOmic Sciences-Genomics and Bioinformatics Cores, The University of Hong Kong, Hong Kong 999077, China
| | - Nan Zheng
- Department of Network Security and Informatization, Tianjin Medical University, Tianjin 300070, China
| | - Junwen Wang
- Department of Health Sciences Research and Center for Individualized Medicine, Mayo Clinic, Scottsdale, AZ 85259, USA
| | - Yupeng Chen
- Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin 300070, China
| | - Dariusz Plewczynski
- Faculty of Mathematics and Information Science, Warsaw University of Technology, Warsaw, Poland
| | - Pak Chung Sham
- Centre for PanorOmic Sciences-Genomics and Bioinformatics Cores, The University of Hong Kong, Hong Kong 999077, China
| | - Kexin Chen
- Department of Epidemiology and Biostatistics, Key Laboratory of Prevention and Control of Human Major Diseases (Ministry of Education), National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin 300070, China
| | - Dandan Huang
- Wuxi School of Medicine, Jiangnan University, Wuxi 214122, China
| | - Mulin Jun Li
- Department of Epidemiology and Biostatistics, Key Laboratory of Prevention and Control of Human Major Diseases (Ministry of Education), National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin 300070, China
- Department of Bioinformatics, The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, School of Basic Medical Sciences, Tianjin Medical University, Tianjin 300070, China
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17
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Liu N, Zhang L, Tian T, Cheng J, Zhang B, Qiu S, Geng Z, Cui G, Zhang Q, Liao W, Yu Y, Zhang H, Gao B, Xu X, Han T, Yao Z, Qin W, Liu F, Liang M, Xu Q, Fu J, Xu J, Zhu W, Zhang P, Li W, Shi D, Wang C, Lui S, Yan Z, Chen F, Li J, Zhang J, Wang D, Shen W, Miao Y, Xian J, Gao JH, Zhang X, Li MJ, Xu K, Zuo XN, Wang M, Ye Z, Yu C. Cross-ancestry genome-wide association meta-analyses of hippocampal and subfield volumes. Nat Genet 2023:10.1038/s41588-023-01425-8. [PMID: 37337106 DOI: 10.1038/s41588-023-01425-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2022] [Accepted: 05/11/2023] [Indexed: 06/21/2023]
Abstract
The hippocampus is critical for memory and cognition and neuropsychiatric disorders, and its subfields differ in architecture and function. Genome-wide association studies on hippocampal and subfield volumes are mainly conducted in European populations; however, other ancestral populations are under-represented. Here we conduct cross-ancestry genome-wide association meta-analyses in 65,791 individuals for hippocampal volume and 38,977 for subfield volumes, including 7,009 individuals of East Asian ancestry. We identify 339 variant-trait associations at P < 1.13 × 10-9 for 44 hippocampal traits, including 23 new associations. Common genetic variants have similar effects on hippocampal traits across ancestries, although ancestry-specific associations exist. Cross-ancestry analysis improves the fine-mapping precision and the prediction performance of polygenic scores in under-represented populations. These genetic variants are enriched for Wnt signaling and neuron differentiation and affect cognition, emotion and neuropsychiatric disorders. These findings may provide insight into the genetic architectures of hippocampal and subfield volumes.
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Affiliation(s)
- Nana Liu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Longjiang Zhang
- Department of Radiology, Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China
| | - Tian Tian
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Jingliang Cheng
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Bing Zhang
- Department of Radiology, Drum Tower Hospital, Medical School of Nanjing University, Nanjing, China
| | - Shijun Qiu
- Department of Medical Imaging, The First Affiliated Hospital of Guangzhou University of Traditional Chinese Medicine, Guangzhou, China
| | - Zuojun Geng
- Department of Medical Imaging, The Second Hospital of Hebei Medical University, Shijiazhuang, China
| | - Guangbin Cui
- Functional and Molecular Imaging Key Lab of Shaanxi Province & Department of Radiology, Tangdu Hospital, Air Force Medical University, Xi'an, China
| | - Quan Zhang
- Department of Radiology, Characteristic Medical Center of Chinese People's Armed Police Force, Tianjin, China
| | - Weihua Liao
- Department of Radiology, Xiangya Hospital, Central South University, Changsha, China
- Molecular Imaging Research Center of Central South University, Changsha, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China
| | - Yongqiang Yu
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Hui Zhang
- Department of Radiology, The First Hospital of Shanxi Medical University, Taiyuan, China
| | - Bo Gao
- Department of Radiology, The Affiliated Hospital of Guizhou Medical University, Guiyang, China
- Department of Radiology, Yantai Yuhuangding Hospital, Yantai, China
| | - Xiaojun Xu
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University, School of Medicine, Hangzhou, China
| | - Tong Han
- Department of Radiology, Tianjin Huanhu Hospital, Tianjin, China
| | - Zhenwei Yao
- Department of Radiology, Huashan Hospital, Fudan University, Shanghai, China
| | - Wen Qin
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Feng Liu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Meng Liang
- School of Medical Imaging and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University, Tianjin, China
| | - Qiang Xu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Jilian Fu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Jiayuan Xu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Wenzhen Zhu
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Peng Zhang
- Department of Radiology, Tianjin Medical University Cancer Institute & Hospital, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Tianjin Medical University, Ministry of Education, Key Laboratory of Cancer Prevention and Therapy, Tianjin, China
| | - Wei Li
- Department of Radiology, Tianjin Medical University Cancer Institute & Hospital, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Tianjin Medical University, Ministry of Education, Key Laboratory of Cancer Prevention and Therapy, Tianjin, China
| | - Dapeng Shi
- Department of Radiology, Henan Provincial People's Hospital & Zhengzhou University People's Hospital, Zhengzhou, China
| | - Caihong Wang
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Su Lui
- Department of Radiology, Huaxi MR Research Center (HMRRC), Functional and Molecular lmaging key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, China
| | - Zhihan Yan
- Department of Radiology, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Wenzhou, China
| | - Feng Chen
- Department of Radiology, Hainan General Hospital (Hainan Affiliated Hospital of Hainan Medical University), Haikou, China
| | - Jiance Li
- Department of Radiology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Jing Zhang
- Department of Magnetic Resonance, Lanzhou University Second Hospital, Lanzhou, China
- Gansu Province Clinical Research Center for Functional and Molecular Imaging, Lanzhou, China
| | - Dawei Wang
- Department of Radiology, Qilu Hospital of Shandong University, Jinan, China
| | - Wen Shen
- Department of Radiology, Tianjin First Center Hospital, Tianjin, China
| | - Yanwei Miao
- Department of Radiology, The First Affiliated Hospital of Dalian Medical University, Dalian, China
| | - Junfang Xian
- Department of Radiology, Beijing Tongren Hospital, Capital Medical University, Beijing, China
| | - Jia-Hong Gao
- Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China
| | - Xiaochu Zhang
- Division of Life Science and Medicine, University of Science & Technology of China, Hefei, China
| | - Mulin Jun Li
- Department of Bioinformatics, The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China
| | - Kai Xu
- Department of Radiology, The Affiliated Hospital of Xuzhou Medical University, Xuzhou, China
| | - Xi-Nian Zuo
- Developmental Population Neuroscience Research Center at IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
- Institute of Psychology, Chinese Academy of Sciences, Beijing, China
| | - Meiyun Wang
- Department of Radiology, Henan Provincial People's Hospital & Zhengzhou University People's Hospital, Zhengzhou, China.
| | - Zhaoxiang Ye
- Department of Radiology, Tianjin Medical University Cancer Institute & Hospital, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Tianjin Medical University, Ministry of Education, Key Laboratory of Cancer Prevention and Therapy, Tianjin, China.
| | - Chunshui Yu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China.
- CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, China.
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18
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Li N, Chen HL, Li MJ, Huang YQ, Li HS, Wang LH. [Prospective study on application of mind mapping combined with scenario simulation training on the ability training of junior nurses in hospital transfer of patients with critical burns and trauma]. Zhonghua Shao Shang Yu Chuang Mian Xiu Fu Za Zhi 2023; 39:465-471. [PMID: 37805756 DOI: 10.3760/cma.j.cn501225-20220524-00200] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 10/09/2023]
Abstract
Objective: To explore the application effects of mind mapping combined with scenario simulation training on the ability training of junior nurses in hospital transfer of patients with critical burns and trauma. Methods: A prospective randomized controlled study was conducted. From December 2019 to December 2020, 55 female junior nurses from the Institute of Burn Research of the First Affiliated Hospital of Army Medical University (the Third Military Medical University) who met the inclusion criteria were enrolled in this study and divided into routine group (27 nurses, aged (24.0±0.9) years) and combined group (28 nurses, aged (24.2±0.8) years), according to the random number table. The nurses in routine group were trained with hospital transfer of patients with critical burns and trauma by theory combined with operational skill, and the nurses in combined group were trained with hospital transfer of patients with critical burns and trauma by mind mapping combined with scenario simulation training. Before and after the training, the self-made theoretical examination papers and skill assessment items were used for the examination and assessment to nurses, and their scores were calculated and compared. The self-made emergency ability scoring system was used to evaluate the emergency disposal ability of nurses from five dimensions, including team cooperation ability, emergency response ability, operative technique ability, specialized business ability, and nurse-patient communication ability, and their scores were calculated and compared. The non-standard implementation rates of transfer nursing measures, such as incomplete preparation of goods, poor communication effect of patients, inadequate pipeline nursing, unclear handover, and inadequate final treatment, were calculated and compared in the process of transporting highly simulated human (hereinafter referred to as simulated human) by nurses before and after training; and the rate of disease change and successful rate of transport of simulated human were calculated and compared after training. After assessment, self-made satisfaction questionnaire was used to compare nurses' satisfaction with the training mode, content, and effects. Data were statistically analyzed with independent sample t test, Pearson chi-square test, or Yates corrected chi-square test. Results: Fifty-five enrolled nurses were fully involved in the training, examination, assessment, and questionnaire filling. Before training, there were no statistically significant differences in theoretical examination and skill assessment scores between the 2 groups (P>0.05); After training, the theoretical examination and skill assessment scores of nurses in combined group were significantly higher than those in routine group (with t values of -3.89 and -4.24, respectively, P<0.05). Before training, there were no statistically significant differences in the scores of each item of emergency disposal ability between the 2 groups (P>0.05); after training, the scores in terms of team cooperation ability, emergency response ability, operative technique ability, specialized business ability, and nurse-patient communication ability of nurses in combined group were significantly higher than those in routine group (with t values of -6.49, -6.44, -2.21, -2.85, and -2.34, respectively, P<0.05). Before training, there were no statistically significant differences in the non-standard implementation rates of transfer nursing measures of nurses between the 2 groups (P>0.05); after training, the non-standard rates of incomplete preparation of goods, unclear handover, and inadequate final treatment of nurses in combined group were significantly lower than those in routine group (with t values of 3.87, 5.89, and 5.28, respectively, P<0.05). After training, the rate of disease change of simulated human of nurses in combined group was 7.14% (2/28), which was significantly lower than 33.33% (9/27) in routine group (χ2=5.89, P<0.05); the successful rate of transport was 96.43% (27/28), which was significantly higher than 74.07% (20/27) in routine group (χ2=3.87, P<0.05). After assessment, the total score of training satisfaction and scores of satisfaction with training mode and training effect of nurses in combined group were significantly higher than those in routine group (with t values of 5.22, 4.67, and 10.71, respectively, P<0.05). There was no statistically significant difference in the satisfaction score on training content between the two groups (P>0.05). Conclusions: Evidence-based mind mapping combined with scenario simulation training significantly improves the nursing skills and emergency handling capabilities of junior nurses in transferring patients with critical burns and trauma.
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Affiliation(s)
- N Li
- State Key Laboratory of Trauma, Burns and Combined Injury, Institute of Burn Research, the First Affiliated Hospital of Army Medical University (the Third Military Medical University), Chongqing 400038, China
| | - H L Chen
- State Key Laboratory of Trauma, Burns and Combined Injury, Institute of Burn Research, the First Affiliated Hospital of Army Medical University (the Third Military Medical University), Chongqing 400038, China
| | - M J Li
- State Key Laboratory of Trauma, Burns and Combined Injury, Institute of Burn Research, the First Affiliated Hospital of Army Medical University (the Third Military Medical University), Chongqing 400038, China
| | - Y Q Huang
- State Key Laboratory of Trauma, Burns and Combined Injury, Institute of Burn Research, the First Affiliated Hospital of Army Medical University (the Third Military Medical University), Chongqing 400038, China
| | - H S Li
- State Key Laboratory of Trauma, Burns and Combined Injury, Institute of Burn Research, the First Affiliated Hospital of Army Medical University (the Third Military Medical University), Chongqing 400038, China
| | - L H Wang
- Hospital Office, the First Affiliated Hospital of Army Medical University (the Third Military Medical University), Chongqing 400038, China
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Lei X, Tian X, Wang H, Xu X, Li G, Liu W, Wang D, Xiao Z, Zhang M, Li MJ, Zhang Z, Ma Z, Liu Z. Noncoding SNP at rs1663689 represses ADGRG6 via interchromosomal interaction and reduces lung cancer progression. EMBO Rep 2023:e56212. [PMID: 37154297 DOI: 10.15252/embr.202256212] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2022] [Revised: 04/05/2023] [Accepted: 04/18/2023] [Indexed: 05/10/2023] Open
Abstract
A previous genome-wide association study (GWAS) revealed an association of the noncoding SNP rs1663689 with susceptibility to lung cancer in the Chinese population. However, the underlying mechanism is unknown. In this study, using allele-specific 4C-seq in heterozygous lung cancer cells combined with epigenetic information from CRISPR/Cas9-edited cell lines, we show that the rs1663689 C/C variant represses the expression of ADGRG6, a gene located on a separate chromosome, through an interchromosomal interaction of the rs1663689 bearing region with the ADGRG6 promoter. This reduces downstream cAMP-PKA signaling and subsequently tumor growth both in vitro and in xenograft models. Using patient-derived organoids, we show that rs1663689 T/T-but not C/C-bearing lung tumors are sensitive to the PKA inhibitor H89, potentially informing therapeutic strategies. Our study identifies a genetic variant-mediated interchromosomal interaction underlying ADGRG6 regulation and suggests that targeting the cAMP-PKA signaling pathway may be beneficial in lung cancer patients bearing the homozygous risk genotype at rs1663689.
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Affiliation(s)
- Xinyue Lei
- Department of Lung Cancer Center, Tianjin Medical University Cancer Institute and Hospital, Haihe Laboratory of Cell Ecosystem, State Key Laboratory of Experimental Hematology, Department of Urology, The Second Hospital of Tianjin Medical University, Key Laboratory of Immune Microenvironment and Disease of the Ministry of Education, Department of Immunology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China
| | - Xiaoling Tian
- Department of Lung Cancer Center, Tianjin Medical University Cancer Institute and Hospital, Haihe Laboratory of Cell Ecosystem, State Key Laboratory of Experimental Hematology, Department of Urology, The Second Hospital of Tianjin Medical University, Key Laboratory of Immune Microenvironment and Disease of the Ministry of Education, Department of Immunology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China
| | - Hao Wang
- Department of Lung Cancer Center, Tianjin Medical University Cancer Institute and Hospital, Haihe Laboratory of Cell Ecosystem, State Key Laboratory of Experimental Hematology, Department of Urology, The Second Hospital of Tianjin Medical University, Key Laboratory of Immune Microenvironment and Disease of the Ministry of Education, Department of Immunology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China
| | - Xinran Xu
- Department of Pharmacology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China
| | - Guoli Li
- Department of Lung Cancer Center, Tianjin Medical University Cancer Institute and Hospital, Haihe Laboratory of Cell Ecosystem, State Key Laboratory of Experimental Hematology, Department of Urology, The Second Hospital of Tianjin Medical University, Key Laboratory of Immune Microenvironment and Disease of the Ministry of Education, Department of Immunology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China
| | - Wenxu Liu
- Department of Lung Cancer Center, Tianjin Medical University Cancer Institute and Hospital, Haihe Laboratory of Cell Ecosystem, State Key Laboratory of Experimental Hematology, Department of Urology, The Second Hospital of Tianjin Medical University, Key Laboratory of Immune Microenvironment and Disease of the Ministry of Education, Department of Immunology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China
| | - Dan Wang
- Department of Lung Cancer Center, Tianjin Medical University Cancer Institute and Hospital, Haihe Laboratory of Cell Ecosystem, State Key Laboratory of Experimental Hematology, Department of Urology, The Second Hospital of Tianjin Medical University, Key Laboratory of Immune Microenvironment and Disease of the Ministry of Education, Department of Immunology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China
| | - Zengtuan Xiao
- Department of Lung Cancer Center, Tianjin Medical University Cancer Institute and Hospital, Haihe Laboratory of Cell Ecosystem, State Key Laboratory of Experimental Hematology, Department of Urology, The Second Hospital of Tianjin Medical University, Key Laboratory of Immune Microenvironment and Disease of the Ministry of Education, Department of Immunology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China
| | - Mengzhe Zhang
- Department of Lung Cancer Center, Tianjin Medical University Cancer Institute and Hospital, Haihe Laboratory of Cell Ecosystem, State Key Laboratory of Experimental Hematology, Department of Urology, The Second Hospital of Tianjin Medical University, Key Laboratory of Immune Microenvironment and Disease of the Ministry of Education, Department of Immunology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China
| | - Mulin Jun Li
- Department of Pharmacology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China
| | - Zhenfa Zhang
- Department of Lung Cancer Center, Tianjin Medical University Cancer Institute and Hospital, Haihe Laboratory of Cell Ecosystem, State Key Laboratory of Experimental Hematology, Department of Urology, The Second Hospital of Tianjin Medical University, Key Laboratory of Immune Microenvironment and Disease of the Ministry of Education, Department of Immunology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China
| | - Zhenyi Ma
- Key Laboratory of Aging and Cancer Biology of Zhejiang Province, Department of Cell Biology, School of Basic Medical Sciences, Hangzhou Normal University, Hangzhou, China
| | - Zhe Liu
- Department of Lung Cancer Center, Tianjin Medical University Cancer Institute and Hospital, Haihe Laboratory of Cell Ecosystem, State Key Laboratory of Experimental Hematology, Department of Urology, The Second Hospital of Tianjin Medical University, Key Laboratory of Immune Microenvironment and Disease of the Ministry of Education, Department of Immunology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China
- Department of Pharmacology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China
- Key Laboratory of Aging and Cancer Biology of Zhejiang Province, Department of Cell Biology, School of Basic Medical Sciences, Hangzhou Normal University, Hangzhou, China
- Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing, China
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20
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Zhang L, Yuan Y, Peng W, Tang B, Li MJ, Gui H, Wang Q, Li M. GBC: a parallel toolkit based on highly addressable byte-encoding blocks for extremely large-scale genotypes of species. Genome Biol 2023; 24:76. [PMID: 37069653 PMCID: PMC10108510 DOI: 10.1186/s13059-023-02906-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2022] [Accepted: 03/22/2023] [Indexed: 04/19/2023] Open
Abstract
Whole -genome sequencing projects of millions of subjects contain enormous genotypes, entailing a huge memory burden and time for computation. Here, we present GBC, a toolkit for rapidly compressing large-scale genotypes into highly addressable byte-encoding blocks under an optimized parallel framework. We demonstrate that GBC is up to 1000 times faster than state-of-the-art methods to access and manage compressed large-scale genotypes while maintaining a competitive compression ratio. We also showed that conventional analysis would be substantially sped up if built on GBC to access genotypes of a large population. GBC's data structure and algorithms are valuable for accelerating large-scale genomic research.
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Affiliation(s)
- Liubin Zhang
- Program in Bioinformatics, Zhongshan School of Medicine and The Fifth Affiliated Hospital, Sun Yat-Sen University, Guangzhou, 510080, China
- Center for Precision Medicine, Sun Yat-Sen University, Guangzhou, China
- Center for Disease Genome Research, Sun Yat-Sen University, Guangzhou, China
| | - Yangyang Yuan
- Program in Bioinformatics, Zhongshan School of Medicine and The Fifth Affiliated Hospital, Sun Yat-Sen University, Guangzhou, 510080, China
- Center for Precision Medicine, Sun Yat-Sen University, Guangzhou, China
- Center for Disease Genome Research, Sun Yat-Sen University, Guangzhou, China
- School of Medical Technology and Information Engineering, Zhejiang Chinese Medical University, Hangzhou, China
| | - Wenjie Peng
- Program in Bioinformatics, Zhongshan School of Medicine and The Fifth Affiliated Hospital, Sun Yat-Sen University, Guangzhou, 510080, China
- Center for Precision Medicine, Sun Yat-Sen University, Guangzhou, China
- Center for Disease Genome Research, Sun Yat-Sen University, Guangzhou, China
| | - Bin Tang
- Program in Bioinformatics, Zhongshan School of Medicine and The Fifth Affiliated Hospital, Sun Yat-Sen University, Guangzhou, 510080, China
- Center for Precision Medicine, Sun Yat-Sen University, Guangzhou, China
- Center for Disease Genome Research, Sun Yat-Sen University, Guangzhou, China
| | - Mulin Jun Li
- The Province and Ministry Co-Sponsored Collaborative Innovation Center for Medical Epigenetics, Tianjin Medical University, Tianjin, China
| | - Hongsheng Gui
- Behavioral Health Services, Henry Ford Health, Detroit, MI, USA
- Center for Health Policy & Health Services Research, Henry Ford Health, Detroit, MI, USA
| | - Qiang Wang
- Mental Health Center, West China Hospital, Sichuan University, Chengdu, China
| | - Miaoxin Li
- Program in Bioinformatics, Zhongshan School of Medicine and The Fifth Affiliated Hospital, Sun Yat-Sen University, Guangzhou, 510080, China.
- Center for Precision Medicine, Sun Yat-Sen University, Guangzhou, China.
- Center for Disease Genome Research, Sun Yat-Sen University, Guangzhou, China.
- Key Laboratory of Tropical Disease Control (SYSU), Ministry of Education, Guangzhou, 510080, China.
- Guangdong Provincial Key Laboratory of Biomedical Imaging and Guangdong Provincial Engineering Research Center of Molecular Imaging, The Fifth Affiliated Hospital, Sun Yat-sen University, Zhuhai, China.
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21
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Yao X, Yang H, Han H, Kou X, Jiang Y, Luo M, Zhou Y, Wang J, Fan X, Wang X, Li MJ, Yan H. Genome-wide analysis of genetic pleiotropy and causal genes across three age-related ocular disorders. Hum Genet 2023; 142:507-522. [PMID: 36917350 DOI: 10.1007/s00439-023-02542-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2022] [Accepted: 03/04/2023] [Indexed: 03/16/2023]
Abstract
Age-related macular degeneration (AMD), cataract, and glaucoma are leading causes of blindness worldwide. Previous genome-wide association studies (GWASs) have revealed a variety of susceptible loci associated with age-related ocular disorders, yet the genetic pleiotropy and causal genes across these diseases remain poorly understood. By leveraging large-scale genetic and observational data from ocular disease GWASs and UK Biobank (UKBB), we found significant pairwise genetic correlations and consistent epidemiological associations among these ocular disorders. Cross-disease meta-analysis uncovered seven pleiotropic loci, three of which were replicated in an additional cohort. Integration of variants in pleiotropic loci and multiple single-cell omics data identified that Müller cells and astrocytes were likely trait-related cell types underlying ocular comorbidity. In addition, we comprehensively integrated eye-specific gene expression quantitative loci (eQTLs), epigenomic profiling, and 3D genome data to prioritize causal pleiotropic genes. We found that pleiotropic genes were essential in nerve development and eye pigmentation, and targetable by aflibercept and pilocarpine for the treatment of AMD and glaucoma. These findings will not only facilitate the mechanistic research of ocular comorbidities but also benefit the therapeutic optimization of age-related ocular diseases.
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Affiliation(s)
- Xueming Yao
- Department of Ophthalmology, Tianjin Medical University General Hospital, Tianjin, 300052, China
| | - Hongxi Yang
- Department of Pharmacology, Tianjin Key Laboratory of Inflammation Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, 300070, China
| | - Han Han
- Department of Ophthalmology, Tianjin Medical University General Hospital, Tianjin, 300052, China
| | - Xuejing Kou
- Department of Ophthalmology, Tianjin Medical University General Hospital, Tianjin, 300052, China
| | - Yuhan Jiang
- Department of Bioinformatics, The Province and Ministry Co-Sponsored Collaborative Innovation Center for Medical Epigenetics, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, 300070, China
| | - Menghan Luo
- Department of Bioinformatics, The Province and Ministry Co-Sponsored Collaborative Innovation Center for Medical Epigenetics, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, 300070, China
| | - Yao Zhou
- Department of Bioinformatics, The Province and Ministry Co-Sponsored Collaborative Innovation Center for Medical Epigenetics, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, 300070, China
| | - Jianhua Wang
- Department of Bioinformatics, The Province and Ministry Co-Sponsored Collaborative Innovation Center for Medical Epigenetics, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, 300070, China
| | - Xutong Fan
- Department of Bioinformatics, The Province and Ministry Co-Sponsored Collaborative Innovation Center for Medical Epigenetics, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, 300070, China
| | - Xiaohong Wang
- Department of Pharmacology, Tianjin Key Laboratory of Inflammation Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, 300070, China.
| | - Mulin Jun Li
- Department of Pharmacology, Tianjin Key Laboratory of Inflammation Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, 300070, China. .,Department of Bioinformatics, The Province and Ministry Co-Sponsored Collaborative Innovation Center for Medical Epigenetics, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, 300070, China.
| | - Hua Yan
- Department of Ophthalmology, Tianjin Medical University General Hospital, Tianjin, 300052, China. .,Laboratory of Molecular Ophthalmology, Tianjin Medical University, Tianjin, 300070, China. .,School of Medicine, Nankai University, Tianjin, 300071, China.
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22
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Han L, Zhang C, Wang D, Zhang J, Tang Q, Li MJ, Sack MN, Wang L, Zhu L. Retrograde regulation of mitochondrial fission and epithelial to mesenchymal transition in hepatocellular carcinoma by GCN5L1. Oncogene 2023; 42:1024-1037. [PMID: 36759571 DOI: 10.1038/s41388-023-02621-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2022] [Revised: 01/29/2023] [Accepted: 01/31/2023] [Indexed: 02/11/2023]
Abstract
Metabolic reprogram is crucial to support cancer cell growth and movement as well as determine cell fate. Mitochondrial protein acetylation regulates mitochondrial metabolism, which is relevant to cancer cell migration and invasion. The functional role of mitochondrial protein acetylation on cancer cell migration remains unclear. General control of amino acid synthesis 5 like-1(GCN5L1), as the regulator of mitochondrial protein acetylation, functions on metabolic reprogramming in mouse livers. In this study, we find that GCN5L1 expression is significantly decreased in metastatic HCC tissues. Loss of GCN5L1 promotes reactive oxygen species (ROS) generation through enhanced fatty acid oxidation (FAO), followed by activation of cellular ERK and DRP1 to promote mitochondrial fission and epithelia to mesenchymal transition (EMT) to boost cell migration. Moreover, palmitate and carnitine-stimulated FAO promotes mitochondrial fission and EMT gene expression to activate HCC cell migration. On the other hand, increased cellular acetyl-CoA level, the product of FAO, enhances HCC cell migration. Taken together, our finding uncovers the metastasis suppressor role as well as the underlying mechanism of GCN5L1 in HCC and also provides evidence of FAO retrograde control of HCC metastasis.
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Affiliation(s)
- Linmeng Han
- Department of Pharmacology, Tianjin Key Laboratory of Inflammatory Biology, The province and ministry co-sponsored collaborative innovation center for medical epigenetics, NHC Key Laboratory of Hormones and Development, Chu Hsien-I Memorial Hospital and Tianjin Institute of Endocrinology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China
| | - Chunyu Zhang
- Department of Pharmacology, Tianjin Key Laboratory of Inflammatory Biology, The province and ministry co-sponsored collaborative innovation center for medical epigenetics, NHC Key Laboratory of Hormones and Development, Chu Hsien-I Memorial Hospital and Tianjin Institute of Endocrinology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China
| | - Danni Wang
- Department of Pharmacology, Tianjin Key Laboratory of Inflammatory Biology, The province and ministry co-sponsored collaborative innovation center for medical epigenetics, NHC Key Laboratory of Hormones and Development, Chu Hsien-I Memorial Hospital and Tianjin Institute of Endocrinology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China
| | - Jiaqi Zhang
- Department of Physiology and Pathophysiology, Tianjin Key Laboratory of Cell Homeostasis and Major Diseases, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China
| | - Qiqi Tang
- Department of Pharmacology, Tianjin Key Laboratory of Inflammatory Biology, The province and ministry co-sponsored collaborative innovation center for medical epigenetics, NHC Key Laboratory of Hormones and Development, Chu Hsien-I Memorial Hospital and Tianjin Institute of Endocrinology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China
| | - Mulin Jun Li
- Department of Bioinformatics, Tianjin Key Laboratory of Inflammation Biology, School of Basic Medical Sciences, Tianjin, China
| | - Michael N Sack
- Laboratory of Mitochondrial Biology and Metabolism, NHLBI, National Institutes of Health, Bethesda, MD, USA
| | - Lingdi Wang
- Department of Physiology and Pathophysiology, Tianjin Key Laboratory of Cell Homeostasis and Major Diseases, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China.
| | - Lu Zhu
- Department of Pharmacology, Tianjin Key Laboratory of Inflammatory Biology, The province and ministry co-sponsored collaborative innovation center for medical epigenetics, NHC Key Laboratory of Hormones and Development, Chu Hsien-I Memorial Hospital and Tianjin Institute of Endocrinology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China.
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23
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Qian Y, Wang J, Wang B, Wang W, Li P, Zhao Z, Jiang Y, Ren H, Huang D, Yang Y, Zhao Z, Zhang L, Shi J, Li MJ, Lu W. Systematic fine-mapping and functional studies of prostate cancer risk variants. iScience 2023; 26:106497. [PMID: 37096036 PMCID: PMC10121464 DOI: 10.1016/j.isci.2023.106497] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2022] [Revised: 02/18/2023] [Accepted: 03/22/2023] [Indexed: 03/29/2023] Open
Abstract
To date, genome-wide association studies (GWAS) have revealed over 200 genetic risk loci associated with prostate cancer; yet, true disease-causing variants remain elusive. Identification of causal variants and their targets from association signals is complicated by high linkage disequilibrium and limited availability of functional genomics data for specific tissue/cell types. Here, we integrated statistical fine-mapping and functional annotation from prostate-specific epigenomic profiles, 3D genome features, and quantitative trait loci data to distinguish causal variants from associations and identify target genes. Our fine-mapping analysis yielded 3,395 likely causal variants, and multiscale functional annotation linked them to 487 target genes. We prioritized rs10486567 as a genome-wide top-ranked SNP and predicted HOTTIP as its target. Deletion of the rs10486567-associated enhancer in prostate cancer cells decreased their capacity for invasive migration. HOTTIP overexpression in enhancer-KO cell lines rescued defective invasive migration. Furthermore, we found that rs10486567 regulates HOTTIP through allele-specific long-range chromatin interaction.
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Affiliation(s)
- Yuyang Qian
- State Key Laboratory of Medicinal Chemical Biology and College of Life Sciences, Nankai University, 94 Weijin Road, Tianjin 300071, China
| | - Jianhua Wang
- Department of Pharmacology, Tianjin Key Laboratory of Inflammation Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China
| | - Bo Wang
- State Key Laboratory of Medicinal Chemical Biology and College of Life Sciences, Nankai University, 94 Weijin Road, Tianjin 300071, China
| | - Wenbin Wang
- State Key Laboratory of Medicinal Chemical Biology and College of Life Sciences, Nankai University, 94 Weijin Road, Tianjin 300071, China
| | - Peng Li
- State Key Laboratory of Medicinal Chemical Biology and College of Life Sciences, Nankai University, 94 Weijin Road, Tianjin 300071, China
| | - Zhenhao Zhao
- State Key Laboratory of Medicinal Chemical Biology and College of Life Sciences, Nankai University, 94 Weijin Road, Tianjin 300071, China
| | - Yuan Jiang
- State Key Laboratory of Medicinal Chemical Biology and College of Life Sciences, Nankai University, 94 Weijin Road, Tianjin 300071, China
| | - He Ren
- Center for GI Cancer Diagnosis and Treatment, Tumor Immunology and Cytotherapy, Medical Research Center, The Affiliated Hospital of Qingdao University, No. 1677 Wutaishan Road, Huangdao District, Qingdao 266000, China
| | - Dandan Huang
- Department of Pharmacology, Tianjin Key Laboratory of Inflammation Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China
| | - Yang Yang
- State Key Laboratory of Medicinal Chemical Biology and College of Life Sciences, Nankai University, 94 Weijin Road, Tianjin 300071, China
| | - Zhongfang Zhao
- State Key Laboratory of Medicinal Chemical Biology and College of Life Sciences, Nankai University, 94 Weijin Road, Tianjin 300071, China
| | - Lei Zhang
- State Key Laboratory of Medicinal Chemical Biology and College of Life Sciences, Nankai University, 94 Weijin Road, Tianjin 300071, China
| | - Jiandang Shi
- State Key Laboratory of Medicinal Chemical Biology and College of Life Sciences, Nankai University, 94 Weijin Road, Tianjin 300071, China
- Corresponding author
| | - Mulin Jun Li
- Department of Pharmacology, Tianjin Key Laboratory of Inflammation Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China
- Corresponding author
| | - Wange Lu
- State Key Laboratory of Medicinal Chemical Biology and College of Life Sciences, Nankai University, 94 Weijin Road, Tianjin 300071, China
- Corresponding author
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24
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Yuan J, Tong Y, Liu X, Li MJ, Zhang Q, Yang Y. eaQTLdb: An atlas of enhancer activity quantitative trait loci across cancer types. Int J Cancer 2023; 153:111-119. [PMID: 36840614 DOI: 10.1002/ijc.34481] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2022] [Revised: 12/28/2022] [Accepted: 02/14/2023] [Indexed: 02/26/2023]
Abstract
Enhancers are key regulatory elements that exert crucial roles in diverse biological processes, including tumorigenesis and cancer development. Active enhancers could produce transcripts termed enhancer RNAs (eRNAs), which could be used as an index of enhancer activity. Here, we present a versatile data portal, enhancer activity quantitative trait loci database (eaQTLdb; http://www.bioailab.com:3838/eaQTLdb), for exploring the effects of genetic variants on enhancer activity and prioritizing candidate variants across different cancer types. By leveraging the accumulated multiomics data, we systematically identified genetic variants which influence enhancer activity in different cancer types, termed as eaQTLs. We have linked the eaQTLs to hallmarks of cancer and patients' overall survival to illustrate their potential biological roles in cancer development and progression. Notably, eaQTLs associated with the infiltration abundance of 24 different immune cell types were identified and incorporated into eaQTLdb. In addition, we applied colocalization analyses to examine 59 complex diseases and traits to identify eaQTLs colocalized with diseases/traits GWAS signals. Overall, eaQTLdb, incorporating a rich resource for exploration of eaQTLs in different cancer types, will not only benefit users in prioritizing candidate genetic variants and enhancers, but also help researchers decipher the roles of eaQTLs in the dysregulated pathways of cancer and tumor immune microenvironment, opening new diagnostic and therapeutic avenues in precise medicine.
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Affiliation(s)
- Jiapei Yuan
- Department of Geriatrics, Tianjin Medical University General Hospital, The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, Center for Reproductive Medicine of Tianjin Medical University Second Hospital, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China.,State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, China
| | - Yang Tong
- Department of Geriatrics, Tianjin Medical University General Hospital, The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, Center for Reproductive Medicine of Tianjin Medical University Second Hospital, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China
| | - Xiaochuan Liu
- Department of Geriatrics, Tianjin Medical University General Hospital, The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, Center for Reproductive Medicine of Tianjin Medical University Second Hospital, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China
| | - Mulin Jun Li
- Department of Bioinformatics, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China
| | - Qiang Zhang
- Department of Geriatrics, Tianjin Geriatrics Institute, Tianjin Medical University General Hospital, Tianjin, China
| | - Yang Yang
- Department of Geriatrics, Tianjin Medical University General Hospital, The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, Center for Reproductive Medicine of Tianjin Medical University Second Hospital, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China.,Department of Bioinformatics, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China
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25
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Liu W, Yu X, Yuan Y, Feng Y, Wu C, Huang C, Xie P, Li S, Li X, Wang Z, Qi L, Chen Y, Shi L, Li MJ, Huang Z, Tang B, Chang A, Hao J. CD73, a Promising Therapeutic Target of Diclofenac, Promotes Metastasis of Pancreatic Cancer through a Nucleotidase Independent Mechanism. Adv Sci (Weinh) 2023; 10:e2206335. [PMID: 36563135 PMCID: PMC9951332 DOI: 10.1002/advs.202206335] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/30/2022] [Revised: 12/04/2022] [Indexed: 06/17/2023]
Abstract
CD73, a cell surface-bound nucleotidase, facilitates extracellular adenosine formation by hydrolyzing 5'-AMP to adenosine. Several studies have shown that CD73 plays an essential role in immune escape, cell proliferation and tumor angiogenesis, making it an attractive target for cancer therapies. However, there are limited clinical benefits associated with the mainstream enzymatic inhibitors of CD73, suggesting that the mechanism underlying the role of CD73 in tumor progression is more complex than anticipated, and further investigation is necessary. In this study, CD73 is found to overexpress in the cytoplasm of pancreatic ductal adenocarcinoma (PDAC) cells and promotes metastasis in a nucleotidase-independent manner, which cannot be restrained by the CD73 monoclonal antibodies or small-molecule enzymatic inhibitors. Furthermore, CD73 promotes the metastasis of PDAC by binding to the E3 ligase TRIM21, competing with the Snail for its binding site. Additionally, a CD73 transcriptional inhibitor, diclofenac, a non-steroidal anti-inflammatory drug, is more effective than the CD73 blocking antibody for the treatment of PDAC metastasis. Diclofenac also enhances the therapeutic efficacy of gemcitabine in the spontaneous KPC (LSL-KrasG12D/+ , LSL-Trp53R172H/+ , and Pdx-1-Cre) pancreatic cancer model. Therefore, diclofenac may be an effective anti-CD73 therapy, when used alone or in combination with gemcitabine-based chemotherapy regimen, for metastatic PDAC.
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Affiliation(s)
- Weishuai Liu
- Key Laboratory of Cancer Prevention and TherapyNational Clinical Research Center for CancerTianjin's Clinical Research Center for CancerTianjin Medical University Cancer Institute and HospitalTianjin300060China
| | - Xiaozhou Yu
- Key Laboratory of Cancer Prevention and TherapyNational Clinical Research Center for CancerTianjin's Clinical Research Center for CancerTianjin Medical University Cancer Institute and HospitalTianjin300060China
| | - Yudong Yuan
- Key Laboratory of Cancer Prevention and TherapyNational Clinical Research Center for CancerTianjin's Clinical Research Center for CancerTianjin Medical University Cancer Institute and HospitalTianjin300060China
| | - Yixing Feng
- Key Laboratory of Cancer Prevention and TherapyNational Clinical Research Center for CancerTianjin's Clinical Research Center for CancerTianjin Medical University Cancer Institute and HospitalTianjin300060China
| | - Chao Wu
- Key Laboratory of Cancer Prevention and TherapyNational Clinical Research Center for CancerTianjin's Clinical Research Center for CancerTianjin Medical University Cancer Institute and HospitalTianjin300060China
| | - Chongbiao Huang
- Key Laboratory of Cancer Prevention and TherapyNational Clinical Research Center for CancerTianjin's Clinical Research Center for CancerTianjin Medical University Cancer Institute and HospitalTianjin300060China
| | - Peng Xie
- Key Laboratory of Cancer Prevention and TherapyNational Clinical Research Center for CancerTianjin's Clinical Research Center for CancerTianjin Medical University Cancer Institute and HospitalTianjin300060China
| | - Shengnan Li
- Key Laboratory of Cancer Prevention and TherapyNational Clinical Research Center for CancerTianjin's Clinical Research Center for CancerTianjin Medical University Cancer Institute and HospitalTianjin300060China
| | - Xiaofeng Li
- Key Laboratory of Cancer Prevention and TherapyNational Clinical Research Center for CancerTianjin's Clinical Research Center for CancerTianjin Medical University Cancer Institute and HospitalTianjin300060China
| | - Ziyang Wang
- Key Laboratory of Cancer Prevention and TherapyNational Clinical Research Center for CancerTianjin's Clinical Research Center for CancerTianjin Medical University Cancer Institute and HospitalTianjin300060China
| | - Lisha Qi
- Key Laboratory of Cancer Prevention and TherapyNational Clinical Research Center for CancerTianjin's Clinical Research Center for CancerTianjin Medical University Cancer Institute and HospitalTianjin300060China
| | - Yanan Chen
- School of MedicineNankai UniversityTianjin300071China
| | - Lei Shi
- Tianjin Medical UniversityTianjin300070China
| | | | - Zhiyong Huang
- Tianjin Institute of Industrial Biotechnology Chinese Academy of SciencesTianjin300308China
| | - Bo Tang
- Key Laboratory of Cancer Prevention and TherapyNational Clinical Research Center for CancerTianjin's Clinical Research Center for CancerTianjin Medical University Cancer Institute and HospitalTianjin300060China
| | - Antao Chang
- Key Laboratory of Cancer Prevention and TherapyNational Clinical Research Center for CancerTianjin's Clinical Research Center for CancerTianjin Medical University Cancer Institute and HospitalTianjin300060China
| | - Jihui Hao
- Key Laboratory of Cancer Prevention and TherapyNational Clinical Research Center for CancerTianjin's Clinical Research Center for CancerTianjin Medical University Cancer Institute and HospitalTianjin300060China
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26
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Li MJ, Shao DT, Zhou JC, Gu JH, Fan ZY, Qin JJ, Li XQ, Hao CQ, Wei WW. [Correlation analysis of age and microbial characteristics in saliva and feces of high-risk population of upper gastrointestinal cancer]. Zhonghua Yu Fang Yi Xue Za Zhi 2022; 56:1759-1766. [PMID: 36536563 DOI: 10.3760/cma.j.cn112150-20220715-00720] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/17/2023]
Abstract
Objective: To explore the correlation between age and diversity and microbial composition in saliva and feces microbiota in high-risk population of upper gastrointestinal cancer. Methods: Based on the national project on early diagnosis and early treatment of upper gastrointestinal cancer, 38 participants were enrolled in Linzhou in Henan province in August 2019. The participant information was collected by questionnaire. Saliva and feces specimens were collected from each participant for 16S rRNA sequencing and bioinformatics analysis. Spearman rank correlation was used to analyze the correlation between age and α diversity (Observed ASVs and Shannon index) and relative abundance of microbiota (phyla, genera, and species) in saliva and feces. Results: The median age (age range) of 38 participants was 54 (43-60) years old, and there were 16 males (42.1%). The Observed ASVs of saliva was negatively correlated with age (rs=-0.35, P<0.05), but the observed ASVs of feces was not correlated with age. In saliva, the relative abundance of Treponema (rs=‒0.44, P<0.05), Alloprevotella (rs=‒0.42, P<0.05), and Porphyromonas (rs=‒0.41,P<0.05) were significantly negatively correlated with age. At the species level, the relative abundance of Porphyromonas endodontalis, Alloprevotella tannerae, Haemophilus influenza, Moraxella bovoculi, Prevotella sp.oral clone ID019, and Prevotella sp.oral clone ASCG10 in saliva were significantly negatively correlated with age, and the rs values were -0.50, -0.40, -0.38, -0.35, -0.33 and -0.33 (P<0.05), respectively. In feces, the relative abundance of Enterobacteria (rs=-0.35, P<0.05), Escherichia (rs=-0.33, P<0.05), and Bifidobacteria (rs=0.33, P<0.05) were correlated with age. At the species level, the relative abundance of Romboutsia sedimentorum, Citrobacter murliniae, and bacteroides uniformis in feces were correlated with age, and the rs values were -0.42, -0.37 and 0.36 (P<0.05), respectively. Conclusion: Age of the high-risk population of upper gastrointestinal cancer is correlated with the relative abundance of microbiota in saliva and feces.
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Affiliation(s)
- M J Li
- National Central Cancer Registry, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - D T Shao
- Division of Birth Cohort Study, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou 510623, China
| | - J C Zhou
- Department of Epidemiology and Biostatistics, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an 710061, China
| | - J H Gu
- National Central Cancer Registry, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - Z Y Fan
- National Central Cancer Registry, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - J J Qin
- Promegene Institute, Shenzhen 518038, China
| | - X Q Li
- National Central Cancer Registry, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - C Q Hao
- Department of Endoscopy, Cancer Institute/Hospital of Linzhou, Linzhou 456550, China
| | - W W Wei
- National Central Cancer Registry, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
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27
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Wang C, Zhou J, Wang L, Xing T, Dai H, Zhou Y, Qi L, Zhao Y, Huang C, Li D, Li H, Li MJ, Liu B, Zheng H, Chen K, Li L. ABO
blood groups and expression of blood group antigens of epithelial ovarian cancer in Chinese women. Cancer Med 2022; 12:7498-7507. [PMID: 36415180 PMCID: PMC10067109 DOI: 10.1002/cam4.5476] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2022] [Revised: 10/07/2022] [Accepted: 11/13/2022] [Indexed: 11/24/2022] Open
Abstract
BACKGROUND ABO blood groups has been associated with risk of several cancers; however, the results for an association with ovarian cancer are inconsistent and little is known about the expression of histo-blood group (ABH) antigens and ABO gene in ovarian tumor tissues. METHODS To assess the impact of genotype-derived ABO blood types on the risk of EOC, we conducted a case-control study in 1,870 EOC and 4,829 controls. Expression of A and B antigen in 70 pairs of ovarian tumor tissues and adjacent normal tissues were detected by immunohistochemistry. Gene expression and DNA methylation profiling was conducted in ovarian tumor tissues. RESULTS We identified that blood group A was associated with increased risk for EOC compared to blood group O (OR = 1.18, 95% CI = 1.03-1.36, p = 0.019). Increased frequency of aberrant expression of histo-blood group antigens was observed in patients with blood group A (76.5%) compared to patients with blood group O (21.1%) and B (5.0%) by immunohistochemistry (p < 0.001). ABO gene expression was down-regulated in ovarian tumor tissues compared with paired adjacent normal tissues (p = 0.027). In addition, ABO gene expression was positively correlated with NFYB (r = 0.38, p < 0.001) and inversely correlated with DNA methylation level of four CpG sites on ABO gene (cg11879188, r = - 0.3, p = 0.002; cg22535403, r = - 0.30, p = 0.002; cg13506600, r = - 0.22, p = 0.025; cg07241568, r = - 0.21, p = 0.049) in ovarian tumor tissues. CONCLUSION We identified blood group A was associated with increased EOC risk in Chinese women and provided the clues of the possible molecular mechanisms of blood group A related to ovarian cancer risk.
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Affiliation(s)
- Chao Wang
- Department of Epidemiology and Biostatistics Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy of Tianjin, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Molecular Cancer Epidemiology of Tianjin Tianjin China
| | - Jingjing Zhou
- Department of Epidemiology and Biostatistics Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy of Tianjin, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Molecular Cancer Epidemiology of Tianjin Tianjin China
| | - Lili Wang
- Department of Epidemiology and Biostatistics Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy of Tianjin, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Molecular Cancer Epidemiology of Tianjin Tianjin China
| | - Tongyu Xing
- Department of Epidemiology and Biostatistics Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy of Tianjin, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Molecular Cancer Epidemiology of Tianjin Tianjin China
| | - Hongji Dai
- Department of Epidemiology and Biostatistics Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy of Tianjin, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Molecular Cancer Epidemiology of Tianjin Tianjin China
| | - Yao Zhou
- Department of Pharmacology, the Province and Ministry Co‐sponsored Collaborative Innovation Center for Medical Epigenetics, School of Basic Medical Sciences Tianjin Medical University Tianjin China
| | - Lisha Qi
- Department of Pathology Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy of Tianjin, Tianjin's Clinical Research Center for Cancer Tianjin China
| | - Yanrui Zhao
- Department of Epidemiology and Biostatistics Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy of Tianjin, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Molecular Cancer Epidemiology of Tianjin Tianjin China
| | - Caiyun Huang
- Department of Epidemiology and Biostatistics Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy of Tianjin, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Molecular Cancer Epidemiology of Tianjin Tianjin China
| | - Ding Li
- Department of Clinical Laboratory Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin's Clinical Research Center for Cancer Tianjin P. R. China
| | - Haixin Li
- Cancer Biobank Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy of Tianjin, Tianjin's Clinical Research Center for Cancer Tianjin China
| | - Mulin Jun Li
- Department of Pharmacology, the Province and Ministry Co‐sponsored Collaborative Innovation Center for Medical Epigenetics, School of Basic Medical Sciences Tianjin Medical University Tianjin China
| | - Ben Liu
- Department of Epidemiology and Biostatistics Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy of Tianjin, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Molecular Cancer Epidemiology of Tianjin Tianjin China
| | - Hong Zheng
- Department of Epidemiology and Biostatistics Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy of Tianjin, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Molecular Cancer Epidemiology of Tianjin Tianjin China
| | - Kexin Chen
- Department of Epidemiology and Biostatistics Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy of Tianjin, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Molecular Cancer Epidemiology of Tianjin Tianjin China
| | - Lian Li
- Department of Epidemiology and Biostatistics Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy of Tianjin, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Molecular Cancer Epidemiology of Tianjin Tianjin China
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Xu J, Xia X, Li Q, Dou Y, Suo X, Sun Z, Liu N, Han Y, Sun X, He Y, Qin W, Zhang S, Banaschewski T, Flor H, Grigis A, Gowland P, Heinz A, Brühl R, Martinot JL, Artiges E, Nees F, Paus T, Poustka L, Hohmann S, Walter H, Sham PC, Schumann G, Wu X, Li MJ, Yu C. A causal association of ANKRD37 with human hippocampal volume. Mol Psychiatry 2022; 27:4432-4445. [PMID: 36195640 DOI: 10.1038/s41380-022-01800-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/24/2021] [Revised: 09/01/2022] [Accepted: 09/12/2022] [Indexed: 12/14/2022]
Abstract
Human hippocampal volume has been separately associated with single nucleotide polymorphisms (SNPs), DNA methylation and gene expression, but their causal relationships remain largely unknown. Here, we aimed at identifying the causal relationships of SNPs, DNA methylation, and gene expression that are associated with hippocampal volume by integrating cross-omics analyses with genome editing, overexpression and causality inference. Based on structural neuroimaging data and blood-derived genome, transcriptome and methylome data, we prioritized a possibly causal association across multiple molecular phenotypes: rs1053218 mutation leads to cg26741686 hypermethylation, thus leads to overactivation of the associated ANKRD37 gene expression in blood, a gene involving hypoxia, which may result in the reduction of human hippocampal volume. The possibly causal relationships from rs1053218 to cg26741686 methylation to ANKRD37 expression obtained from peripheral blood were replicated in human hippocampal tissue. To confirm causality, we performed CRISPR-based genome and epigenome-editing of rs1053218 homologous alleles and cg26741686 methylation in mouse neural stem cell differentiation models, and overexpressed ANKRD37 in mouse hippocampus. These in-vitro and in-vivo experiments confirmed that rs1053218 mutation caused cg26741686 hypermethylation and ANKRD37 overexpression, and cg26741686 hypermethylation favored ANKRD37 overexpression, and ANKRD37 overexpression reduced hippocampal volume. The pairwise relationships of rs1053218 with hippocampal volume, rs1053218 with cg26741686 methylation, cg26741686 methylation with ANKRD37 expression, and ANKRD37 expression with hippocampal volume could be replicated in an independent healthy young (n = 443) dataset and observed in elderly people (n = 194), and were more significant in patients with late-onset Alzheimer's disease (n = 76). This study revealed a novel causal molecular association mechanism of ANKRD37 with human hippocampal volume, which may facilitate the design of prevention and treatment strategies for hippocampal impairment.
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Affiliation(s)
- Jiayuan Xu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, 300052, PR China
| | - Xianyou Xia
- Department of Cell Biology, The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, Tianjin Medical University, Tianjin, 300070, PR China
| | - Qiaojun Li
- College of Information Engineering, Tianjin University of Commerce, Tianjin, 300052, PR China
| | - Yan Dou
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, 300052, PR China
| | - Xinjun Suo
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, 300052, PR China
| | - Zuhao Sun
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, 300052, PR China
| | - Nana Liu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, 300052, PR China
| | - Yating Han
- Department of Cell Biology, The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, Tianjin Medical University, Tianjin, 300070, PR China
| | - Xiaodi Sun
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, 300052, PR China
| | - Yukun He
- Department of Pharmacology, The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, Tianjin Key Laboratory of Inflammatory Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, 300070, PR China
| | - Wen Qin
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, 300052, PR China
| | - Shijie Zhang
- Department of Pharmacology, The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, Tianjin Key Laboratory of Inflammatory Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, 300070, PR China
| | - Tobias Banaschewski
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, 68159, Mannheim, Germany
| | - Herta Flor
- Department of Cognitive and Clinical Neuroscience, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, Mannheim, Germany
- Department of Psychology, School of Social Sciences, University of Mannheim, 68131, Mannheim, Germany
| | - Antoine Grigis
- NeuroSpin, CEA, Université Paris-Saclay, F-91191, Gif-sur-Yvette, France
| | - Penny Gowland
- Sir Peter Mansfield Imaging Centre School of Physics and Astronomy, University of Nottingham, University Park, Nottingham, UK
| | - Andreas Heinz
- Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Department of Psychiatry and Psychotherapy, Campus Charité Mitte, Charitéplatz 1, Berlin, Germany
| | - Rüdiger Brühl
- Physikalisch-Technische Bundesanstalt (PTB), Abbestr. 2 - 12, Berlin, Germany
| | - Jean-Luc Martinot
- Université Paris-Saclay, Institut National de la Santé et de la Recherche Médicale, INSERM U1299 "Developmental trajectories & psychiatry"; Ecole Normale supérieure Paris-Saclay, CNRS, Centre Borelli, Gif-sur-Yvette, France
| | - Eric Artiges
- Université Paris-Saclay, Institut National de la Santé et de la Recherche Médicale, INSERM U1299 "Developmental trajectories & psychiatry"; Ecole Normale supérieure Paris-Saclay, CNRS, Centre Borelli; Gif-sur-Yvette; and Etablissement Public de Santé (EPS) Barthélemy Durand, 91700, Sainte-Geneviève-des-Bois, France
| | - Frauke Nees
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, 68159, Mannheim, Germany
- Department of Cognitive and Clinical Neuroscience, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, Mannheim, Germany
- Institute of Medical Psychology and Medical Sociology, University Medical Center Schleswig-Holstein, Kiel University, Kiel, Germany
| | - Tomáš Paus
- Bloorview Research Institute, Holland Bloorview Kids Rehabilitation Hospital and Departments of Psychology and Psychiatry, University of Toronto, Toronto, ON, M6A 2E1, Canada
| | - Luise Poustka
- Department of Child and Adolescent Psychiatry and Psychotherapy, University Medical Centre Göttingen, von-Siebold-Str. 5, 37075, Göttingen, Germany
| | - Sarah Hohmann
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, 68159, Mannheim, Germany
| | - Henrik Walter
- Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Department of Psychiatry and Psychotherapy, Campus Charité Mitte, Charitéplatz 1, Berlin, Germany
| | - Pak Chung Sham
- Centre for PanorOmic Sciences-Genomics and Bioinformatics Cores, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, 999077, P.R. China
| | - Gunter Schumann
- Centre for Population Neuroscience and Stratified Medicine (PONS), Institute for Science and Technology of Brain-inspired Intelligence 20 (ISTBI), Fudan University, Shanghai, P.R. China
- PONS Centre, Department of Psychiatry and Psychotherapy, CCM, Charite Universitaetsmedizin Berlin, Berlin, Germany
| | - Xudong Wu
- Department of Cell Biology, The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, Tianjin Medical University, Tianjin, 300070, PR China.
- Department of Neurosurgery, Tianjin Medical University General Hospital, Tianjin, 300052, PR China.
| | - Mulin Jun Li
- Department of Pharmacology, The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, Tianjin Key Laboratory of Inflammatory Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, 300070, PR China.
- Department of Bioinformatics, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, 300070, China.
| | - Chunshui Yu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, 300052, PR China.
- CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, 200031, PR China.
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Fu QQ, Li MJ, Huang L, Tan JL, Zhou YQ, Li N. [Clinical application effect of sequential nursing on the management of new skin on face and neck after deep burns]. Zhonghua Shao Shang Yu Chuang Mian Xiu Fu Za Zhi 2022; 38:952-958. [PMID: 36299207 DOI: 10.3760/cma.j.cn501120-20210323-00101] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 06/16/2023]
Abstract
Objective: To explore the clinical application effect of sequential nursing on the management of new skin on face and neck after deep burns. Methods: The retrospective case-control research approach was used. From January to December 2019, 109 patients who met the inclusion criteria were admitted to the First Affiliated Hospital of Army Medical University (the Third Military Medical University) within 1 week after deep burn wound healing on the face and neck. Fifty-five patients who were admitted to the hospital from January to June and received comprehensive treatment and conventional nursing were included in conventional nursing group (27 males and 28 females, aged 21-65 (40±17) years), and fifty-four patients who were admitted to the hospital from July to December and received comprehensive treatment and sequential nursing were included in sequential nursing group (29 males and 25 females, aged 18-57 (37±11) years). The scores of pigmentation, vascularity, pliability, and thickness in Vancouver scar scale (VSS), the total score of VSS, the score of itch's impact on sleep in the four-item itch questionnaire (FIIQ), and the total score of FIIQ of patients were counted in the two groups before the first treatment (hereinafter referred to as treatment) and 3 months, 6 months, and 1 year after treatment. The treatment effective rate and the score of patients' satisfaction with the treatment effect in one year after treatment and the occurrence of adverse reaction during the treatment were counted. Data were statistically analyzed with independent sample t test, Mann-Whitney U test, and chi-square test. Results: The scores of pigmentation, vascularity, pliability, and thickness in VSS and the total VSS score of patients between the two groups before treatment were close (P>0.05). The pliability score in VSS and total VSS score after 3 months of treatment, the score of vascularity in VSS and total VSS score after 6 months of treatment, and the scores of pigmentation, vascularity, pliability, and thickness in VSS and total VSS score of patients after 1 year of treatment in sequential nursing group were significantly lower than those in conventional nursing group (with Z values of -2.51, -3.37, -2.05, -3.28, -3.12, -5.86, -4.63, -5.56, -6.76, respectively, P<0.05 or P<0.01). The score of itch's impact on sleep in FIIQ after 3 months of treatment of patients in sequential nursing group was significantly lower than that in conventional nursing group (Z=-4.17, P<0.01), and the total scores of FIIQ after 3 months, 6 months, and 1 year of treatment of patients in sequential nursing group were significantly lower than those in conventional nursing group (with Z values of -6.56, -5.53, -5.84, respectively, P<0.01). After 1 year of treatment, the treatment effective rate of patients in sequential nursing group was 96.3% (52/54), which was significantly higher than 81.8% (45/55) in conventional nursing group (χ2=5.83, P<0.05), and the score of patients' satisfaction with the treatment effect in sequential nursing group was significantly higher than that in conventional nursing group (Z=-4.49, P<0.01). During the treatment period, there was no adverse reaction in patients in sequential nursing group, but there were 3 patients with pruritus and peripheral erythema on the wound in conventional nursing group, which were improved after dressing changes. Conclusions: Sequential nursing can effectively improve the prevention and management of new skin scars in patients after deep burns on the face and neck, improve the itching, the efficiency of treatment, and the satisfaction of patients with the treatment effect.
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Affiliation(s)
- Q Q Fu
- State Key Laboratory of Trauma, Burns and Combined Injury, Institute of Burn Research, the First Affiliated Hospital of Army Medical University (the Third Military Medical University), Chongqing 400038, China
| | - M J Li
- State Key Laboratory of Trauma, Burns and Combined Injury, Institute of Burn Research, the First Affiliated Hospital of Army Medical University (the Third Military Medical University), Chongqing 400038, China
| | - L Huang
- State Key Laboratory of Trauma, Burns and Combined Injury, Institute of Burn Research, the First Affiliated Hospital of Army Medical University (the Third Military Medical University), Chongqing 400038, China
| | - J L Tan
- State Key Laboratory of Trauma, Burns and Combined Injury, Institute of Burn Research, the First Affiliated Hospital of Army Medical University (the Third Military Medical University), Chongqing 400038, China
| | - Y Q Zhou
- State Key Laboratory of Trauma, Burns and Combined Injury, Institute of Burn Research, the First Affiliated Hospital of Army Medical University (the Third Military Medical University), Chongqing 400038, China
| | - N Li
- State Key Laboratory of Trauma, Burns and Combined Injury, Institute of Burn Research, the First Affiliated Hospital of Army Medical University (the Third Military Medical University), Chongqing 400038, China
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Wang J, Liu J, Luo M, Cui H, Zhang W, Zhao K, Dai H, Song F, Chen K, Yu Y, Zhou D, Li MJ, Yang H. Rational drug repositioning for coronavirus-associated diseases using directional mapping and side-effect inference. iScience 2022; 25:105348. [PMID: 36267550 PMCID: PMC9556799 DOI: 10.1016/j.isci.2022.105348] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2022] [Revised: 09/02/2022] [Accepted: 10/11/2022] [Indexed: 02/08/2023] Open
Abstract
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the pathogen of coronavirus disease 2019 (COVID-19), has infected hundreds of millions of people and caused millions of deaths. Looking for valid druggable targets with minimal side effects for the treatment of COVID-19 remains critical. After discovering host genes from multiscale omics data, we developed an end-to-end network method to investigate drug-host gene(s)-coronavirus (CoV) paths and the mechanism of action between the drug and the host factor in a directional network. We also inspected the potential side effect of the candidate drug on several common comorbidities. We established a catalog of host genes associated with three CoVs. Rule-based prioritization yielded 29 Food and Drug Administration (FDA)-approved drugs via accounting for the effects of drugs on CoVs, comorbidities, and drug-target confidence information. Seven drugs are currently undergoing clinical trials as COVID-19 treatment. This catalog of druggable host genes associated with CoVs and the prioritized repurposed drugs will provide a new sight in therapeutics discovery for severe COVID-19 patients.
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Affiliation(s)
- Jianhua Wang
- Department of Epidemiology and Biostatistics, The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, Tianjin Key Laboratory of Molecular Cancer Epidemiology, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin, China,Department of Bioinformatics, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China,Department of Pharmacology, Tianjin Key Laboratory of Inflammation Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China
| | - Jiaojiao Liu
- Department of Pathogen Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China
| | - Menghan Luo
- Department of Bioinformatics, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China,Department of Pharmacology, Tianjin Key Laboratory of Inflammation Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China
| | - Hui Cui
- School of Life Science and Technology, ShanghaiTech University, Shanghai, China
| | - Wenwen Zhang
- Department of Bioinformatics, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China,Department of Pharmacology, Tianjin Key Laboratory of Inflammation Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China
| | - Ke Zhao
- Department of Bioinformatics, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China,Department of Pharmacology, Tianjin Key Laboratory of Inflammation Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China
| | - Hongji Dai
- Department of Epidemiology and Biostatistics, The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, Tianjin Key Laboratory of Molecular Cancer Epidemiology, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin, China
| | - Fangfang Song
- Department of Epidemiology and Biostatistics, The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, Tianjin Key Laboratory of Molecular Cancer Epidemiology, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin, China
| | - Kexin Chen
- Department of Epidemiology and Biostatistics, The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, Tianjin Key Laboratory of Molecular Cancer Epidemiology, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin, China
| | - Ying Yu
- Department of Pharmacology, Tianjin Key Laboratory of Inflammation Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China
| | - Dongming Zhou
- Department of Pathogen Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China,Corresponding author
| | - Mulin Jun Li
- Department of Epidemiology and Biostatistics, The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, Tianjin Key Laboratory of Molecular Cancer Epidemiology, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin, China,Department of Bioinformatics, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China,Department of Pharmacology, Tianjin Key Laboratory of Inflammation Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China,Corresponding author
| | - Hongxi Yang
- Department of Bioinformatics, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China,Department of Pharmacology, Tianjin Key Laboratory of Inflammation Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China,Corresponding author
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Han BH, Wu ZW, Li MJ, Jin F, Gao Z, Pan LL, Ma JC, Jin H, Zhao YL, Li Q. [Safety of an inactivated 2019-nCoV vaccine (Vero) in adults aged 60 years and older]. Zhonghua Yu Fang Yi Xue Za Zhi 2022; 56:1295-1301. [PMID: 36207894 DOI: 10.3760/cma.j.cn112150-20220119-00069] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/16/2023]
Abstract
Objective: To analyze the safety of an inactivated 2019-nCoV vaccine (Vero cell) in adults aged 60 years and older. Methods: A randomized, double-blind, placebo-controlled clinical study was conducted in May 2020 The eligible residents aged 60 and above were recruited in Renqiu city, Hebei Province. A total of 422 subjects (phase Ⅰ/Ⅱ:72/350) were enrolled. Two doses of the trial vaccine or placebo were randomly administered according to a 0 and 28-day immunization schedule. Subjects were randomly divided into two groups in Phase Ⅰ. Within each group, participants received vaccine or placebo in a ratio of 2∶1. Subjects were randomly divided into four groups in phase Ⅱ to receive low-dose, medium-dose, high-dose vaccine and placebo, respectively, in a ratio of 2∶2∶2∶1. A combination of regular follow-up and active reporting was used to observe adverse reactions within 28 days after vaccination, and compare the incidence rate of adverse reactions in the trial and control groups. Results: 422 subjects were (66.45±4.70) years old, and 48.82% were male (206/422). There were 100, 124, 124 and 74 patients enrolled into the low-dose, medium-dose, high-dose vaccine groups and the placebo group, respectively. One person without the vaccination was removed, and 421 participants who received at least one dose of vaccine were included in the safety analysis. Within 28 days after the first or second dose, a total of 20.67% (87/421) subjects had adverse reactions (both solicitation and non-solicitation). About 76 patients suffered grade 1 adverse reactions [18.05% (76/421)] and 22 patients suffered grade 2 adverse reactions [5.23% (22/421)]. No grade 3 or above adverse reactions occurred. A total of 19.71% (83/421) subjects had solicited adverse reactions. The most common grade 1 adverse reaction was injection site pain, followed by fever and fatigue. The most common grade 2 adverse reactions were fever and fatigue, followed by muscle pain and injection site redness. A total of 2.61% (11/421) subjects had unsolicited adverse reactions. A total of 1.66% (7/421) subjects had serious adverse events after vaccination, and no serious vaccine-related adverse events were reported. Conclusions: The inactivated SARS-CoV-2 vaccine is safe for people aged 60 years and above.
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Affiliation(s)
- B H Han
- Institute for Vaccine Clinical Research, Hebei Province Center for Disease Control and Prevention, Shijiazhuang 050021, China
| | - Z W Wu
- Institute for Vaccine Clinical Research, Hebei Province Center for Disease Control and Prevention, Shijiazhuang 050021, China
| | - M J Li
- Institute for Vaccine Clinical Research, Hebei Province Center for Disease Control and Prevention, Shijiazhuang 050021, China
| | - F Jin
- Institute for Vaccine Clinical Research, Hebei Province Center for Disease Control and Prevention, Shijiazhuang 050021, China
| | - Z Gao
- Institute for Vaccine Clinical Research, Hebei Province Center for Disease Control and Prevention, Shijiazhuang 050021, China
| | - L L Pan
- Institute for Vaccine Clinical Research, Hebei Province Center for Disease Control and Prevention, Shijiazhuang 050021, China
| | - J C Ma
- Institute for Vaccine Clinical Research, Hebei Province Center for Disease Control and Prevention, Shijiazhuang 050021, China
| | - H Jin
- Renqiu City Center for Disease Control and Prevention,Renqiu 062550, China
| | - Y L Zhao
- Institute for Vaccine Clinical Research, Hebei Province Center for Disease Control and Prevention, Shijiazhuang 050021, China
| | - Qi Li
- Hebei Province Center for Disease Control and Prevention, Shijiazhuang 050021, China
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Yi X, Luo M, Feng X, Zhou Y, Wang J, Li MJ. 3DCoop: An approach for computational inference of cell-type-specific transcriptional regulators cooperation in 3D chromatin. STAR Protoc 2022; 3:101382. [PMID: 35600920 PMCID: PMC9114683 DOI: 10.1016/j.xpro.2022.101382] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022] Open
Abstract
Precise identification of context-specific transcriptional regulators (TRs) cooperation facilitates the understanding of complex gene regulation. However, previous methods are highly reliant on the availability of ChIPped TRs. Here, we provide a protocol for running 3DCoop, a pipeline for computational inference of cell type-specific TR cooperation in 3D chromatin by integrating TR motifs, open chromatin profiles, gene expression, and chromatin loops. 3DCoop provides a feasible solution to study the potential interplay among TRs across multiple human or mouse tissue/cell types. For complete details on the use and execution of this protocol, please refer to Yi et al. (2021). Inference of transcriptional regulator (TR) cooperation in 3D chromatin Integration of TR motifs, open chromatin, gene expression, and chromatin loops Identification of context-specific TR cooperation not relying on ChIPped factors 3DCoop facilitates TR cooperation study across multiple human/mouse cell types
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Affiliation(s)
- Xianfu Yi
- Department of Bioinformatics, School of Basic Medical Sciences, Tianjin Medical University, Tianjin 300070, China
- School of Biomedical Engineering and Technology, Tianjin Medical University, Tianjin 300070, China
- Corresponding author
| | - Menghan Luo
- Department of Bioinformatics, School of Basic Medical Sciences, Tianjin Medical University, Tianjin 300070, China
| | - Xiangling Feng
- Department of Bioinformatics, School of Basic Medical Sciences, Tianjin Medical University, Tianjin 300070, China
| | - Yao Zhou
- Department of Bioinformatics, School of Basic Medical Sciences, Tianjin Medical University, Tianjin 300070, China
| | - Jianhua Wang
- Department of Bioinformatics, School of Basic Medical Sciences, Tianjin Medical University, Tianjin 300070, China
| | - Mulin Jun Li
- Department of Bioinformatics, School of Basic Medical Sciences, Tianjin Medical University, Tianjin 300070, China
- Department of Epidemiology and Biostatistics, Tianjin Key Laboratory of Molecular Cancer Epidemiology, The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin 300070, China
- Corresponding author
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Li X, Jiang L, Xue C, Li MJ, Li M. A conditional gene-based association framework integrating isoform-level eQTL data reveals new susceptibility genes for schizophrenia. eLife 2022; 11:70779. [PMID: 35412455 PMCID: PMC9005191 DOI: 10.7554/elife.70779] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2021] [Accepted: 11/11/2021] [Indexed: 11/13/2022] Open
Abstract
Linkage disequilibrium and disease-associated variants in the non-coding regions make it difficult to distinguish the truly associated genes from the redundantly associated genes for complex diseases. In this study, we proposed a new conditional gene-based framework called eDESE that leveraged an improved effective chi-squared statistic to control the type I error rates and remove the redundant associations. eDESE initially performed the association analysis by mapping variants to genes according to their physical distance. We further demonstrated that the isoform-level eQTLs could be more powerful than the gene-level eQTLs in the association analysis using a simulation study. Then the eQTL-guided strategies, that is, mapping variants to genes according to their gene/isoform-level variant-gene cis-eQTLs associations, were also integrated with eDESE. We then applied eDESE to predict the potential susceptibility genes of schizophrenia and found that the potential susceptibility genes were enriched with many neuronal or synaptic signaling-related terms in the Gene Ontology knowledgebase and antipsychotics-gene interaction terms in the drug-gene interaction database (DGIdb). More importantly, seven potential susceptibility genes identified by eDESE were the target genes of multiple antipsychotics in DrugBank. Comparing the potential susceptibility genes identified by eDESE and other benchmark approaches (i.e., MAGMA and S-PrediXcan) implied that strategy based on the isoform-level eQTLs could be an important supplement for the other two strategies (physical distance and gene-level eQTLs). We have implemented eDESE in our integrative platform KGGSEE (http://pmglab.top/kggsee/#/) and hope that eDESE can facilitate the prediction of candidate susceptibility genes and isoforms for complex diseases in a multi-tissue context.
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Affiliation(s)
- Xiangyi Li
- Program in Bioinformatics, Zhongshan School of Medicine and The Fifth Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.,Key Laboratory of Tropical Disease Control (Sun Yat-sen University), Ministry of Education, Guangzhou, China.,Center for Precision Medicine, Sun Yat-sen University, Guangzhou, China
| | - Lin Jiang
- Research Center of Medical Sciences, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Chao Xue
- Program in Bioinformatics, Zhongshan School of Medicine and The Fifth Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.,Key Laboratory of Tropical Disease Control (Sun Yat-sen University), Ministry of Education, Guangzhou, China.,Center for Precision Medicine, Sun Yat-sen University, Guangzhou, China
| | - Mulin Jun Li
- The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, Tianjin Medical University, Tianjin, China
| | - Miaoxin Li
- Program in Bioinformatics, Zhongshan School of Medicine and The Fifth Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.,Key Laboratory of Tropical Disease Control (Sun Yat-sen University), Ministry of Education, Guangzhou, China.,Center for Precision Medicine, Sun Yat-sen University, Guangzhou, China.,Guangdong Provincial Key Laboratory of Biomedical Imaging and Guangdong Provincial Engineering Research Center of Molecular Imaging, The Fifth Affiliated Hospital, Sun Yat-sen University, Zhuhai, China
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Xu J, Liu X, Li Q, Goldblatt R, Qin W, Liu F, Chu C, Luo Q, Ing A, Guo L, Liu N, Liu H, Huang C, Cheng J, Wang M, Geng Z, Zhu W, Zhang B, Liao W, Qiu S, Zhang H, Xu X, Yu Y, Gao B, Han T, Cui G, Chen F, Xian J, Li J, Zhang J, Zuo XN, Wang D, Shen W, Miao Y, Yuan F, Lui S, Zhang X, Xu K, Zhang L, Ye Z, Banaschewski T, Barker GJ, Bokde ALW, Flor H, Grigis A, Garavan H, Gowland P, Heinz A, Brühl R, Martinot JL, Artiges E, Nees F, Orfanos DP, Lemaitre H, Paus T, Poustka L, Robinson L, Hohmann S, Fröhner JH, Smolka MN, Walter H, Whelan R, Winterer J, Patrick K, Calhoun V, Li MJ, Liang M, Gong P, Barker ED, Clinton N, Marquand A, Yu L, Yu C, Schumann G. Global urbanicity is associated with brain and behaviour in young people. Nat Hum Behav 2022; 6:279-293. [PMID: 34711977 DOI: 10.1038/s41562-021-01204-7] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2021] [Accepted: 08/26/2021] [Indexed: 02/05/2023]
Abstract
Urbanicity is a growing environmental challenge for mental health. Here, we investigate correlations of urbanicity with brain structure and function, neuropsychology and mental illness symptoms in young people from China and Europe (total n = 3,867). We developed a remote-sensing satellite measure (UrbanSat) to quantify population density at any point on Earth. UrbanSat estimates of urbanicity were correlated with brain volume, cortical surface area and brain network connectivity in the medial prefrontal cortex and cerebellum. UrbanSat was also associated with perspective-taking and depression symptoms, and this was mediated by neural variables. Urbanicity effects were greatest when urban exposure occurred in childhood for the cerebellum, and from childhood to adolescence for the prefrontal cortex. As UrbanSat can be generalized to different geographies, it may enable assessments of correlations of urbanicity with mental illness and resilience globally.
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Affiliation(s)
- Jiayuan Xu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, P. R. China
- Centre for Population Neuroscience and Precision Medicine (PONS), Institute of Psychiatry, Psychology and Neuroscience, SGDP Centre, King's College London, London, UK
| | - Xiaoxuan Liu
- Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System Science, Tsinghua University, Beijing, P. R. China
| | - Qiaojun Li
- College of Information Engineering, Tianjin University of Commerce, Tianjin, P. R. China
| | | | - Wen Qin
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, P. R. China
| | - Feng Liu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, P. R. China
| | - Congying Chu
- Centre for Population Neuroscience and Precision Medicine (PONS), Institute of Psychiatry, Psychology and Neuroscience, SGDP Centre, King's College London, London, UK
| | - Qiang Luo
- Institute of Science and Technology for Brain-Inspired Intelligence, Ministry of Education-Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Fudan University, Shanghai, China
- State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Institutes of Brain Science and Human Phenome Institute, Fudan University, Shanghai, China
| | - Alex Ing
- Centre for Population Neuroscience and Precision Medicine (PONS), Institute of Psychiatry, Psychology and Neuroscience, SGDP Centre, King's College London, London, UK
| | - Lining Guo
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, P. R. China
| | - Nana Liu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, P. R. China
| | - Huaigui Liu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, P. R. China
| | - Conghong Huang
- Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System Science, Tsinghua University, Beijing, P. R. China
| | - Jingliang Cheng
- Department of Magnetic Resonance Imaging, First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Meiyun Wang
- Department of Radiology, Zhengzhou University People's Hospital and Henan Provincial People's Hospital, Zhengzhou, China
| | - Zuojun Geng
- Department of Medical Imaging, Second Hospital of Hebei Medical University, Shijiazhuang, China
| | - Wenzhen Zhu
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Bing Zhang
- Department of Radiology, Drum Tower Hospital, Medical School of Nanjing University, Nanjing, China
| | - Weihua Liao
- Department of Radiology, Xiangya Hospital, Central South University, Changsha, China
| | - Shijun Qiu
- Department of Medical Imaging, First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Hui Zhang
- Department of Radiology, The First Hospital of Shanxi Medical University, Taiyuan, China
| | - Xiaojun Xu
- Department of Radiology, Second Affiliated Hospital of Zhejiang University, School of Medicine, Hangzhou, China
| | - Yongqiang Yu
- Department of Radiology, First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Bo Gao
- Department of Radiology, Affliated Hospital of Guizhou Medical University, Guiyang, Guizhou, China
| | - Tong Han
- Department of Radiology, Tianjin Huanhu Hospital, Tianjin, China
| | - Guangbin Cui
- Functional and Molecular Imaging Key Lab of Shaanxi Province and Department of Radiology, Tangdu Hospital, Military Medical University of PLA Airforce (Fourth Military Medical University), Xi'an, China
| | - Feng Chen
- Department of Radiology, Hainan General Hospital, Haikou, China
| | - Junfang Xian
- Department of Radiology, Beijing Tongren Hospital, Capital Medical University, Beijing, China
| | - Jiance Li
- Department of Radiology, First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Jing Zhang
- Department of Magnetic Resonance, Lanzhou University Second Hospital, Lanzhou, China
| | - Xi-Nian Zuo
- State Key Laboratory of Cognitive Neuroscience and IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Dawei Wang
- Department of Radiology, Qilu Hospital of Shandong University, Jinan, China
| | - Wen Shen
- Department of Radiology, Tianjin First Center Hospital, Tianjin, China
| | - Yanwei Miao
- Department of Radiology, First Affiliated Hospital of Dalian Medical University, Dalian, China
| | - Fei Yuan
- Department of Radiology, Pingjin Hospital, Logistics University of Chinese People's Armed Police Forces, Tianjin, China
| | - Su Lui
- Department of Radiology, Center for Medical Imaging, West China Hospital of Sichuan University, Chengdu, China
| | - Xiaochu Zhang
- Department of Radiology, First Affiliated Hospital of USTC, Hefei National Laboratory for Physical Sciences at the Microscale and School of Life Science, Division of Life Science and Medicine, University of Science and Technology of China, Hefei, China
| | - Kai Xu
- Department of Radiology, Affiliated Hospital of Xuzhou Medical University, Xuzhou, China
| | - Longjiang Zhang
- Department of Medical Imaging, Jinling Hospital, Medical School of Nanjing University, Nanjing, China
| | - Zhaoxiang Ye
- Department of Radiology, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China
| | - Tobias Banaschewski
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Gareth J Barker
- Department of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Arun L W Bokde
- Discipline of Psychiatry, School of Medicine and Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
| | - Herta Flor
- Department of Cognitive and Clinical Neuroscience, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
- Department of Psychology, School of Social Sciences, University of Mannheim, Mannheim, Germany
| | - Antoine Grigis
- NeuroSpin, CEA, Université Paris-Saclay, Gif-sur-Yvette, France
| | - Hugh Garavan
- Department of Psychiatry and Psychology, University of Vermont, Burlington, VT, USA
| | - Penny Gowland
- Sir Peter Mansfield Imaging Centre School of Physics and Astronomy, University of Nottingham, Nottingham, UK
| | - Andreas Heinz
- Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Department of Psychiatry and Psychotherapy, Berlin, Germany
| | - Rüdiger Brühl
- Physikalisch-Technische Bundesanstalt (PTB), Berlin, Germany
| | - Jean-Luc Martinot
- Ecole Normale Supérieure Paris-Saclay, Université Paris-Saclay, CNRS, Centre Borelli, INSERM U1299 "Trajectoires Développementales & Psychiatrie", Gif-sur-Yvette, France
| | - Eric Artiges
- Institut National de la Santé et de la Recherche Médicale, INSERM Unit 1000 Neuroimaging and Psychiatry, University Paris Sud, University Paris Descartes - Sorbonne Paris Cité; Psychiatry Department 91G16, Orsay Hospital, Orsay, France
| | - Frauke Nees
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
- Department of Cognitive and Clinical Neuroscience, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | | | - Herve Lemaitre
- Institute National de la Santé et de la Recherche Médicale, UMR 992 INSERM, CEA, Faculté de médecine, Université Paris-Sud, Université Paris-Saclay NeuroSpin, Gif-sur-Yvette, France
| | - Tomáš Paus
- Departments of Psychiatry and Neuroscience, Faculty of Medicine and Centre Hospitalier Universitaire Sainte-Justine, University of Montreal, Montreal, Quebec, Canada
- Departments of Psychology and Psychiatry, University of Toronto, Toronto, Ontario, Canada
| | - Luise Poustka
- Department of Child and Adolescent Psychiatry and Psychotherapy, University Medical Centre Göttingen, Göttingen, Germany
| | - Lauren Robinson
- Department of Psychology, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Sarah Hohmann
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Juliane H Fröhner
- Department of Psychiatry and Neuroimaging Center, Technische Universität Dresden, Dresden, Germany
| | - Michael N Smolka
- Department of Psychiatry and Neuroimaging Center, Technische Universität Dresden, Dresden, Germany
| | - Henrik Walter
- Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Department of Psychiatry and Psychotherapy, Berlin, Germany
| | - Robert Whelan
- School of Psychology and Global Brain Health Institute, Trinity College Dublin, Dublin, Ireland
| | - Jeanne Winterer
- Department of Psychiatry and Psychotherapy CCM, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
- Department of Education and Psychology, Freie Universität Berlin, Berlin, Germany
| | - Kevin Patrick
- Center for Wireless and Population Health Systems, Department of Family and Preventive Medicine and Calit2's Qualcomm Institute, University of California San Diego, La Jolla, CA, USA
| | - Vince Calhoun
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, GA, USA
| | - Mulin Jun Li
- Collaborative Innovation Center of Tianjin for Medical Epigenetics, Tianjin Key Laboratory of Medical Epigenetics, Department of Pharmacology, Tianjin Medical University, Tianjin, P. R. China
| | - Meng Liang
- School of Medical Imaging and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University, Tianjin, P. R. China
| | - Peng Gong
- Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System Science, Tsinghua University, Beijing, P. R. China
- Department of Geography and Department of Earth Sciences, University of Hong Kong, Hong Kong, China
| | - Edward D Barker
- Department of Psychology, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | | | - Andre Marquand
- Predictive Clinical Neuroscience Group at the Donders Institute, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Le Yu
- Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System Science, Tsinghua University, Beijing, P. R. China
| | - Chunshui Yu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, P. R. China.
- CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, P. R. China.
| | - Gunter Schumann
- Centre for Population Neuroscience and Stratified Medicine (PONS), Institute for Science and Technology of Brain-Inspired Intelligence (ISTBI), Fudan University, Shanghai, P. R. China.
- Centre for Population Neuroscience and Stratified Medicine (PONS), Charite Mental Health, Dept. of Psychiatry and Psychotherapy, CCM, Charite Universitätsmedizin Berlin, Berlin, Germany.
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Li N, Chen HL, Li MJ, Luo GX, Yuan ZQ. [Application effects of bundle nursing of citric acid extracorporeal anticoagulation on continuous renal replacement therapy of severe burn patients]. Zhonghua Shao Shang Yu Chuang Mian Xiu Fu Za Zhi 2022; 38:29-37. [PMID: 34954935 DOI: 10.3760/cma.j.cn501120-20201201-00511] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
Objective: To explore the application effects of bundle nursing of citric acid extracorporeal anticoagulation on continuous renal replacement therapy (CRRT) of severe burn patients. Methods: A non-randomized controlled study was conducted. Forty-six patients who met the inclusion criteria and received regular nursing of citric acid extracorporeal anticoagulation during CRRT in the First Affiliated Hospital of Army Medical University (the Third Military Medical University) from January to December 2017 were included in regular nursing group (30 males and 16 females, aged 42.0 (38.7,47.0) years, with 201 times of CRRT performed), and 48 patients who met the inclusion criteria and received bundle nursing of citric acid extracorporeal anticoagulation during CRRT in the same hospital from January to December 2018 were included in bundle nursing group (32 males and 16 females, aged 41.0 (36.0,46.0) years, with 164 times of CRRT performed). The clinical data of all the patients in the two groups were recorded, including the length of intensive care unit (ICU) stay, total cost of treatment in ICU, cost of CRRT, unplanned ending of treatment, ending of treatment due to operation (with the rates of unplanned ending of treatment and ending of treatment due to operation calculated), times of disposable hemodialysis filter and supporting pipeline filter (hereinafter referred to as filter) with use time>24 h, times of CRRT, and lifetime of filter. For the patients in both groups who continuously received CRRT for 3 days or more from the first treatment, the prothrombin time (PT), activated partial thromboplastin time (APTT), international normalized ratio (INR), total calcium, ionic calcium (with the difference of total calcium or ionic calcium between before and after treatment calculated), creatinine, urea, β2 microglobulin, cystatin C, platelet count, mean arterial pressure, pH value, oxygenation index, bicarbonate radical, and lactic acid levels before the first treatment (hereinafter referred to as before treatment) and 3 days after the first treatment (hereinafter referred to as after 3 days of treatment). The treatment-related complications of all patients in the two groups were recorded during hospitalization. Data were statistically analyzed with independent sample t test, Mann-Whitney U test, and chi-square test. Results: Compared with those in regular nursing group, the length of ICU stay was significantly shortened (Z=-4.71, P<0.01), the total cost of treatment in ICU was significantly reduced (t=-1.39, P<0.01), the cost of CRRT had no significant change (P>0.05), the rates of unplanned ending of treatment and ending of treatment due to operation were both significantly decreased (with χ2 values of 12.20 and 17.83, respectively, P<0.01), the times of filter service time>24 h was increased significantly (Z=-5.93, P<0.01), the times of CRRT were significantly reduced (Z=-4.75, P<0.01), and the filter service life was significantly prolonged (Z=-9.24, P<0.01) among patients in bundle nursing group. Thirty-one patients in bundle nursing group and 28 patients in regular nursing group continuously received CRRT for 3 days or more from the first treatment. Before treatment, PT, APTT, and INR of patients in bundle nursing group were 24.10 (16.08, 39.20) s, 38.81 (32.32, 45.50) s, and 1.17 (1.12, 1.19), respectively, similar to 31.75 (22.99, 40.96) s, 41.82 (35.05, 48.06) s, and 1.15 (1.11, 1.19) of patients in regular nursing group (P>0.05); the levels of total calcium and ionic calcium of patients in the two groups were similar (P>0.05). After 3 days of treatment, PT, APTT, and INR of patients in bundle nursing group and regular nursing group were 29.06 (20.11, 39.46) s, 35.25 (30.06, 40.28) s, 1.13 (1.09, 1.17) and 36.51 (26.64, 42.92) s, 39.89 (34.81, 46.62) s, 1.14 (1.10, 1.18), respectively, similar to those before treatment (P>0.05); the level of ionic calcium of patients in regular nursing group was significantly higher than that before treatment (Z=-2.08, P<0.05); the levels of total calcium and ionic calcium of patients in bundle nursing group were both significantly higher than those before treatment (with Z values of -3.55 and -3.69, respectively, P<0.01); compared with those in regular nursing group, APTT of patients was significantly shorter (Z=-2.29, P<0.05), while the total calcium level of patients was significantly higher in bundle nursing group (Z=-2.26, P<0.05). The difference of total calcium between before and after treatment of patients in bundle nursing group was significantly higher than that in regular nursing group (Z=-3.15, P<0.01). The differences of ionic calcium between before and after treatment of patients in the two groups were similar (P>0.05). Before treatment, the level of β2 microglobulin of patients in bundle nursing group was significantly higher than that in regular nursing group (Z=-2.84, P<0.01), the platelet count of patients in bundle nursing group was significantly lower than that in regular nursing group (Z=-2.44, P<0.05), while the levels of creatinine, urea, cystatin C, mean arterial pressure, pH value, oxygenation index, bicarbonate radical, and lactic acid of patients in the two groups were similar (P>0.05). After 3 days of treatment, the levels of creatinine, urea, β2 microglobulin, cystatin C, pH value, bicarbonate radical, and lactic acid of patients were all significantly lower than those before treatment (with Z values of -2.10, -2.90, -3.11, -2.02, -2.34, -2.63, and -2.84, respectively, P<0.05 or P<0.01), while the levels of platelet count, oxygenation index, and mean arterial pressure of patients were all significantly higher than those before treatment in bundle nursing group (with Z values of -6.65 and -2.40, respectively, t=-9.97, P<0.05 or P<0.01); the levels of creatinine, urea, β2 microglobulin, cystatin C, platelet count, pH value, bicarbonate radical, and lactic acid of patients were all significantly lower than those before treatment (with Z values of -5.32, -2.31, -2.41, -2.21, -3.68, -2.93, -2.20, and -2.31, respectively, P<0.05 or P<0.01), while the oxygenation index and mean arterial pressure of patients were both significantly higher than those before treatment in regular nursing group (Z=-5.59, t=-7.74, P<0.01). After 3 days of treatment, compared with those in regular nursing group, the levels of creatinine, cystatin C, platelet count, oxygenation index, bicarbonate radical, and mean arterial pressure of patients were all significantly higher (with Z values of -2.93, -1.99, -6.39, -2.09, and -2.52, respectively, t=-3.28, P<0.05 or P<0.01), while the levels of urea, β2 microglobulin, pH value, and lactic acid of patients were all significantly lower (with Z values of -3.87, -2.58, -4.24, and -2.75, respectively, P<0.05 or P<0.01) in bundle nursing group. During hospitalization, there were no treatment-related bleeding events or hypernatremia related to citric acid treatment of patients in the two groups. The ratio of total calcium to ionic calcium in one patient in bundle nursing group was >2.5, but there was no manifestation of citric acid accumulation poisoning; 1 patient had hypoionic calcemia, and 1 patient had severe metabolic alkalosis. Five patients had hypoionic calcemia and 2 patients had severe metabolic alkalosis in regular nursing group. Conclusions: The implementation of bundle nursing of citric acid extracorporeal anticoagulation during CRRT for severe burn patients shortens the length of ICU stay, reduces the total cost of treatment in ICU and the occurrence of treatment-related complications, relieves the economic burden of patients, and improves the continuity and quality of treatment.
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Affiliation(s)
- N Li
- State Key Laboratory of Trauma, Burns and Combined Injury, Institute of Burn Research, the First Affiliated Hospital of Army Medical University (the Third Military Medical University), Chongqing 400038, China
| | - H L Chen
- State Key Laboratory of Trauma, Burns and Combined Injury, Institute of Burn Research, the First Affiliated Hospital of Army Medical University (the Third Military Medical University), Chongqing 400038, China
| | - M J Li
- State Key Laboratory of Trauma, Burns and Combined Injury, Institute of Burn Research, the First Affiliated Hospital of Army Medical University (the Third Military Medical University), Chongqing 400038, China
| | - G X Luo
- State Key Laboratory of Trauma, Burns and Combined Injury, Institute of Burn Research, the First Affiliated Hospital of Army Medical University (the Third Military Medical University), Chongqing 400038, China
| | - Z Q Yuan
- State Key Laboratory of Trauma, Burns and Combined Injury, Institute of Burn Research, the First Affiliated Hospital of Army Medical University (the Third Military Medical University), Chongqing 400038, China
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Dai H, Chu X, Liang Q, Wang M, Li L, Zhou Y, Zheng Z, Wang W, Wang Z, Li H, Wang J, Zheng H, Zhao Y, Liu L, Yao H, Luo M, Wang Q, Kang S, Li Y, Wang K, Song F, Zhang R, Wu X, Cheng X, Zhang W, Wei Q, Li MJ, Chen K. Genome-wide association and functional interrogation identified a variant at 3p26.1 modulating ovarian cancer survival among Chinese women. Cell Discov 2021; 7:121. [PMID: 34930913 PMCID: PMC8688503 DOI: 10.1038/s41421-021-00342-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2021] [Accepted: 09/23/2021] [Indexed: 12/03/2022] Open
Abstract
Ovarian cancer survival varies considerably among patients, to which germline variation may also contribute in addition to mutational signatures. To identify genetic markers modulating ovarian cancer outcome, we performed a genome-wide association study in 2130 Chinese ovarian cancer patients and found a hitherto unrecognized locus at 3p26.1 to be associated with the overall survival (Pcombined = 8.90 × 10−10). Subsequent statistical fine-mapping, functional annotation, and eQTL mapping prioritized a likely casual SNP rs9311399 in the non-coding regulatory region. Mechanistically, rs9311399 altered its enhancer activity through an allele-specific transcription factor binding and a long-range interaction with the promoter of a lncRNA BHLHE40-AS1. Deletion of the rs9311399-associated enhancer resulted in expression changes in several oncogenic signaling pathway genes and a decrease in tumor growth. Thus, we have identified a novel genetic locus that is associated with ovarian cancer survival possibly through a long-range gene regulation of oncogenic pathways.
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Affiliation(s)
- Hongji Dai
- Department of Epidemiology and Biostatistics, National Clinical Research Center for Cancer, Key Laboratory of Molecular Cancer Epidemiology of Tianjin, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin, China
| | - Xinlei Chu
- Department of Epidemiology and Biostatistics, National Clinical Research Center for Cancer, Key Laboratory of Molecular Cancer Epidemiology of Tianjin, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin, China
| | - Qian Liang
- Department of Pharmacology, the Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China
| | - Mengyun Wang
- Cancer Institute, Fudan University Shanghai Cancer Center, Fudan University, Shanghai, China.,Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Lian Li
- Department of Epidemiology and Biostatistics, National Clinical Research Center for Cancer, Key Laboratory of Molecular Cancer Epidemiology of Tianjin, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin, China
| | - Yao Zhou
- Department of Pharmacology, the Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China
| | - Zhanye Zheng
- Department of Pharmacology, the Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China
| | - Wei Wang
- Department of Epidemiology and Biostatistics, National Clinical Research Center for Cancer, Key Laboratory of Molecular Cancer Epidemiology of Tianjin, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin, China
| | - Zhao Wang
- Department of Pharmacology, the Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China
| | - Haixin Li
- Cancer Biobank, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin, China
| | - Jianhua Wang
- Department of Pharmacology, the Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China
| | - Hong Zheng
- Department of Epidemiology and Biostatistics, National Clinical Research Center for Cancer, Key Laboratory of Molecular Cancer Epidemiology of Tianjin, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin, China
| | - Yanrui Zhao
- Department of Epidemiology and Biostatistics, National Clinical Research Center for Cancer, Key Laboratory of Molecular Cancer Epidemiology of Tianjin, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin, China
| | - Luyang Liu
- Department of Epidemiology and Biostatistics, National Clinical Research Center for Cancer, Key Laboratory of Molecular Cancer Epidemiology of Tianjin, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin, China
| | - Hongcheng Yao
- School of Biomedical Sciences, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong, SAR, China
| | - Menghan Luo
- Department of Pharmacology, the Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China
| | - Qiong Wang
- Department of Epidemiology and Biostatistics, National Clinical Research Center for Cancer, Key Laboratory of Molecular Cancer Epidemiology of Tianjin, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin, China
| | - Shan Kang
- Department of Obstetrics and Gynaecology, Hebei Medical University, Fourth Hospital, Shijiazhuang, China
| | - Yan Li
- Department of Molecular Biology, Hebei Medical University, Fourth Hospital, Shijiazhuang, China
| | - Ke Wang
- Department of Gynecologic Oncology, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin, China
| | - Fengju Song
- Department of Epidemiology and Biostatistics, National Clinical Research Center for Cancer, Key Laboratory of Molecular Cancer Epidemiology of Tianjin, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin, China
| | - Ruoxin Zhang
- Cancer Institute, Fudan University Shanghai Cancer Center, Fudan University, Shanghai, China.,Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Xiaohua Wu
- Cancer Institute, Fudan University Shanghai Cancer Center, Fudan University, Shanghai, China.,Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Xi Cheng
- Cancer Institute, Fudan University Shanghai Cancer Center, Fudan University, Shanghai, China.,Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Wei Zhang
- Center for Cancer Genomics and Precision Oncology, Wake Forest Baptist Comprehensive Cancer Center, Wake Forest Baptist Medical Center, Winston-Salem, NC, USA.,Department of Cancer Biology, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Qingyi Wei
- Cancer Institute, Fudan University Shanghai Cancer Center, Fudan University, Shanghai, China. .,Duke Cancer Institute, Duke University Medical Center, Durham, NC, USA. .,Department of Population Health Sciences, Duke University School of Medicine, Durham, NC, USA.
| | - Mulin Jun Li
- Department of Epidemiology and Biostatistics, National Clinical Research Center for Cancer, Key Laboratory of Molecular Cancer Epidemiology of Tianjin, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin, China. .,Department of Pharmacology, the Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China.
| | - Kexin Chen
- Department of Epidemiology and Biostatistics, National Clinical Research Center for Cancer, Key Laboratory of Molecular Cancer Epidemiology of Tianjin, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin, China.
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Jiang L, Jiang H, Dai S, Chen Y, Song Y, Tang CSM, Pang SYY, Ho SL, Wang B, Garcia-Barcelo MM, Tam PKH, Cherny SS, Li MJ, Sham PC, Li M. Deviation from baseline mutation burden provides powerful and robust rare-variants association test for complex diseases. Nucleic Acids Res 2021; 50:e34. [PMID: 34931221 PMCID: PMC8989543 DOI: 10.1093/nar/gkab1234] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2021] [Revised: 11/19/2021] [Accepted: 12/04/2021] [Indexed: 02/07/2023] Open
Abstract
Identifying rare variants that contribute to complex diseases is challenging because of the low statistical power in current tests comparing cases with controls. Here, we propose a novel and powerful rare variants association test based on the deviation of the observed mutation burden of a gene in cases from a baseline predicted by a weighted recursive truncated negative-binomial regression (RUNNER) on genomic features available from public data. Simulation studies show that RUNNER is substantially more powerful than state-of-the-art rare variant association tests and has reasonable type 1 error rates even for stratified populations or in small samples. Applied to real case-control data, RUNNER recapitulates known genes of Hirschsprung disease and Alzheimer's disease missed by current methods and detects promising new candidate genes for both disorders. In a case-only study, RUNNER successfully detected a known causal gene of amyotrophic lateral sclerosis. The present study provides a powerful and robust method to identify susceptibility genes with rare risk variants for complex diseases.
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Affiliation(s)
- Lin Jiang
- Program in Bioinformatics, Zhongshan School of Medicine and The Fifth Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.,Research Center of Medical Sciences, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China.,Key Laboratory of Tropical Disease Control (Sun Yat-sen University), Ministry of Education, Sun Yat-sen University, Guangzhou, China.,Center for Precision Medicine, Sun Yat-sen University, Guangzhou, China
| | - Hui Jiang
- Program in Bioinformatics, Zhongshan School of Medicine and The Fifth Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.,Key Laboratory of Tropical Disease Control (Sun Yat-sen University), Ministry of Education, Sun Yat-sen University, Guangzhou, China.,Center for Precision Medicine, Sun Yat-sen University, Guangzhou, China
| | - Sheng Dai
- Program in Bioinformatics, Zhongshan School of Medicine and The Fifth Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.,Key Laboratory of Tropical Disease Control (Sun Yat-sen University), Ministry of Education, Sun Yat-sen University, Guangzhou, China.,Center for Precision Medicine, Sun Yat-sen University, Guangzhou, China
| | - Ying Chen
- Program in Bioinformatics, Zhongshan School of Medicine and The Fifth Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.,Key Laboratory of Tropical Disease Control (Sun Yat-sen University), Ministry of Education, Sun Yat-sen University, Guangzhou, China.,Center for Precision Medicine, Sun Yat-sen University, Guangzhou, China
| | - Youqiang Song
- School of Biomedical Sciences, the University of Hong Kong, Hong Kong, SAR China.,State Key Laboratory of Brain and Cognitive Sciences, the University of Hong Kong, Hong Kong, SAR China
| | - Clara Sze-Man Tang
- Department of Surgery, the University of Hong Kong, Hong Kong, SAR China.,Dr. Li Dak-Sum Research Centre, The University of Hong Kong - Karolinska Institutet Collaboration in Regenerative Medicine, Hong Kong, SAR China
| | - Shirley Yin-Yu Pang
- Division of Neurology, Department of Medicine, the University of Hong Kong, Hong Kong, SAR China
| | - Shu-Leong Ho
- Division of Neurology, Department of Medicine, the University of Hong Kong, Hong Kong, SAR China
| | - Binbin Wang
- Department of Genetics, National Research Institute for Family Planning, Beijing, China
| | | | - Paul Kwong-Hang Tam
- Department of Surgery, the University of Hong Kong, Hong Kong, SAR China.,Dr. Li Dak-Sum Research Centre, The University of Hong Kong - Karolinska Institutet Collaboration in Regenerative Medicine, Hong Kong, SAR China.,Faculty of Medicine, Macau University of Science and Technology, Macau, SAR China
| | | | - Mulin Jun Li
- The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, Tianjin Medical University, Tianjin 300070, China
| | - Pak Chung Sham
- The Centre for PanorOmic Sciences, the University of Hong Kong, Hong Kong, SAR China.,State Key Laboratory of Brain and Cognitive Sciences, the University of Hong Kong, Hong Kong, SAR China.,Department of Psychiatry, the University of Hong Kong, Hong Kong, SAR China
| | - Miaoxin Li
- Program in Bioinformatics, Zhongshan School of Medicine and The Fifth Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.,Key Laboratory of Tropical Disease Control (Sun Yat-sen University), Ministry of Education, Sun Yat-sen University, Guangzhou, China.,Center for Precision Medicine, Sun Yat-sen University, Guangzhou, China.,The Centre for PanorOmic Sciences, the University of Hong Kong, Hong Kong, SAR China.,Guangdong Provincial Key Laboratory of Biomedical Imaging and Guangdong Provincial Engineering Research Center of Molecular Imaging, The Fifth Affiliated Hospital, Sun Yat-sen University, Zhuhai, China
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38
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Yi X, Zheng Z, Xu H, Zhou Y, Huang D, Wang J, Feng X, Zhao K, Fan X, Zhang S, Dong X, Wang Z, Shen Y, Cheng H, Shi L, Li MJ. Interrogating cell type-specific cooperation of transcriptional regulators in 3D chromatin. iScience 2021; 24:103468. [PMID: 34888502 PMCID: PMC8634045 DOI: 10.1016/j.isci.2021.103468] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2021] [Revised: 09/23/2021] [Accepted: 11/12/2021] [Indexed: 12/14/2022] Open
Abstract
Context-specific activities of transcription regulators (TRs) in the nucleus modulate spatiotemporal gene expression precisely. Using the largest ChIP-seq data and chromatin loops in the human K562 cell line, we initially interrogated TR cooperation in 3D chromatin via a graphical model and revealed many known and novel TRs manipulating context-specific pathways. To explore TR cooperation across broad tissue/cell types, we systematically leveraged large-scale open chromatin profiles, computational footprinting, and high-resolution chromatin interactions to investigate tissue/cell type-specific TR cooperation. We first delineated a landscape of TR cooperation across 40 human tissue/cell types. Network modularity analyses uncovered the commonality and specificity of TR cooperation in different conditions. We also demonstrated that TR cooperation information can better interpret the disease-causal variants identified by genome-wide association studies and recapitulate cell states during neural development. Our study characterizes shared and unique patterns of TR cooperation associated with the cell type specificity of gene regulation in 3D chromatin. Computational inference of transcriptional regulator (TR) cooperation in 3D chromatin A landscape of 3D TR cooperation across 40 human tissue/cell types TR cooperation can better interpret the disease-causal variants identified by GWAS Cooperation of certain TRs shapes context-specific gene regulation in cell development
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Affiliation(s)
- Xianfu Yi
- School of Biomedical Engineering and Technology, Tianjin Medical University, Tianjin 300070, China.,Department of Bioinformatics, The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, Tianjin Medical University, Tianjin 300070, China
| | - Zhanye Zheng
- Department of Pharmacology, Tianjin Key Laboratory of Inflammation Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin 300070, China
| | - Hang Xu
- Department of Bioinformatics, The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, Tianjin Medical University, Tianjin 300070, China
| | - Yao Zhou
- Department of Bioinformatics, The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, Tianjin Medical University, Tianjin 300070, China.,Department of Pharmacology, Tianjin Key Laboratory of Inflammation Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin 300070, China
| | - Dandan Huang
- Department of Bioinformatics, The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, Tianjin Medical University, Tianjin 300070, China.,Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin 300070, China
| | - Jianhua Wang
- Department of Bioinformatics, The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, Tianjin Medical University, Tianjin 300070, China.,Department of Pharmacology, Tianjin Key Laboratory of Inflammation Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin 300070, China
| | - Xiangling Feng
- Department of Bioinformatics, The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, Tianjin Medical University, Tianjin 300070, China.,Department of Pharmacology, Tianjin Key Laboratory of Inflammation Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin 300070, China
| | - Ke Zhao
- Department of Bioinformatics, The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, Tianjin Medical University, Tianjin 300070, China.,Department of Pharmacology, Tianjin Key Laboratory of Inflammation Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin 300070, China
| | - Xutong Fan
- Department of Bioinformatics, The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, Tianjin Medical University, Tianjin 300070, China.,Department of Pharmacology, Tianjin Key Laboratory of Inflammation Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin 300070, China
| | - Shijie Zhang
- Department of Bioinformatics, The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, Tianjin Medical University, Tianjin 300070, China.,Department of Pharmacology, Tianjin Key Laboratory of Inflammation Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin 300070, China
| | - Xiaobao Dong
- Department of Bioinformatics, The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, Tianjin Medical University, Tianjin 300070, China.,Department of Genetics, School of Basic Medical Sciences, Tianjin Medical University, Tianjin 300070, China
| | - Zhao Wang
- Department of Pharmacology, Tianjin Key Laboratory of Inflammation Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin 300070, China
| | - Yujun Shen
- Department of Pharmacology, Tianjin Key Laboratory of Inflammation Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin 300070, China
| | - Hui Cheng
- State Key Laboratory of Experimental Hematology, Chinese Academy of Medical Sciences, Tianjin 300070, China
| | - Lei Shi
- Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin 300070, China
| | - Mulin Jun Li
- Department of Bioinformatics, The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, Tianjin Medical University, Tianjin 300070, China.,Department of Pharmacology, Tianjin Key Laboratory of Inflammation Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin 300070, China.,Department of Epidemiology and Biostatistics, Tianjin Key Laboratory of Molecular Cancer Epidemiology, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin 300070, China
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Chen L, Li MJ. Editorial: Deciphering Non-Coding Regulatory Variants: Computational and Functional Validation. Front Bioeng Biotechnol 2021; 9:769614. [PMID: 34805122 PMCID: PMC8595122 DOI: 10.3389/fbioe.2021.769614] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2021] [Accepted: 10/11/2021] [Indexed: 11/26/2022] Open
Affiliation(s)
- Li Chen
- Department of Biostatistics and Health Data Science, Indiana University School of Medicine, Indianapolis, IN, United States.,Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, IN, United States
| | - Mulin Jun Li
- Department of Bioinformatics, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China
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40
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Chen HL, Li MJ, Luo YM, Li N. [Application of a standard communication system-based continuous home remote visit mode in the management of visits to severely burned patients in the post-pandemic era of coronavirus disease 2019]. Zhonghua Shao Shang Za Zhi 2021; 37:1070-1077. [PMID: 34794259 DOI: 10.3760/cma.j.cn501120-20210315-00088] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
Objective: To observe the application effects of a standard communication system-based continuous home remote visit mode in the management of visits to severely burned patients in the post-pandemic era of coronavirus disease 2019 (hereinafter referred to as post-pandemic era). Methods: A retrospective cohort study was conducted. A total of 69 severely burned patients who met the inclusion criteria and were admitted to the First Affiliated Hospital of Army Medical University (the Third Military Medical University) from February to December, 2020 and their 69 family members were recruited into this study. According to the difference of visit model, 33 severely burned patients who were admitted into burn intensive care unit (BICU) from February to June, 2020 and received completely restricted visits according to the requirements for epidemic prevention and control and their corresponding 33 family members were included into conventional visit group; 36 severely burned patients who were admitted into BICU from July to December, 2020 and received the standard communication system-based continuous home remote visits and their 36 corresponding family members were recruited into remote visit group. The family members in conventional visit group could only communicate with the primary nurses by telephone, while the patients and family members in remote visit group could communicate with the primary nurses, responsible doctors, rehabilitation therapists, and nutrition therapists through WeChat video call. The survey results of general information questionnaire and Hamilton Anxiety Scale (HAMA) scores of two groups of patients and their family members at BICU admission of patients, HAMA scores of the two groups of patients and their family members in the second week of BICU admission and at discharge from BICU of patients, the scores of the Visiting Effect Evaluation Scale of the two groups of patients and their family members and the scores of Chinese version of Critical Care Family Satisfaction Survey (C-CCFSS) of the two groups of family members at discharge from BICU, and the scores of Satisfaction Survey and Evaluation Scale During Hospitalization of patients within the first week after the discharge of patients from BICU were compared. Data were statistically analyzed with chi-square test, Fisher's exact probability test, and Mann-Whitney U test. Results: In remote visit group, there were 29 males and 7 females in patients, aged 48 (34, 53) years, and 15 males and 21 females in family members, aged 45 (30, 48) years. In conventional visit group, there were 24 males and 9 females in patients, aged 49 (38, 54) years, and 9 males and 24 females in family members, aged 44 (35, 48) years. At BICU admission of patients, the HAMA scores of the two groups of patients and family members were both similar (P>0.05). The total HAMA scores of patients and family members in remote visit group were significantly lower than those in conventional visit group in the second week when the patients were admitted to BICU (Z=-3.195, -3.018, P<0.01) and discharged from BICU (Z=-2.118, -2.380, P<0.05). At discharge from BICU of patients, the scores of each dimension in Visiting Effect Evaluation Scale of the patients in the two groups were similar (P>0.05); while scores of 3 dimensions including patient safety information, diagnosis and treatment quality information, and psychological support information in Visiting Effect Evaluation Scale of family members in remote visit group were significantly higher than those in conventional visit group (Z=-2.372, -2.209, -2.174, P<0.05), and only the scores of visit perception of family members were close to those in conventional visit group (P>0.05). At discharge from BICU of patients, the C-CCFSS scores of the family members in remote visit group was 99 (98, 108), which were significantly higher than 98 (97, 100) in conventional visit group (Z=-2.545, P<0.05). Within the first week after the discharge of patients from BICU, the scores of Satisfaction Survey and Evaluation Scale During Hospitalization of patients in remote visit group were 99 (98, 100), which were significantly higher than 96 (94, 98) in conventional visit group (Z=-5.213, P<0.01). Conclusions: In the management of visits to severely burned patients in the post-pandemic era, application of the standard communication system-based continuous home remote visit mode can improve the visit effect and satisfaction, and effectively alleviate the anxiety of patients and their family members.
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Affiliation(s)
- H L Chen
- State Key Laboratory of Trauma, Burns and Combined Injury, Institute of Burn Research, the First Affiliated Hospital of Army Medical University (the Third Military Medical University), Chongqing 400038, China
| | - M J Li
- State Key Laboratory of Trauma, Burns and Combined Injury, Institute of Burn Research, the First Affiliated Hospital of Army Medical University (the Third Military Medical University), Chongqing 400038, China
| | - Y M Luo
- State Key Laboratory of Trauma, Burns and Combined Injury, Institute of Burn Research, the First Affiliated Hospital of Army Medical University (the Third Military Medical University), Chongqing 400038, China
| | - N Li
- State Key Laboratory of Trauma, Burns and Combined Injury, Institute of Burn Research, the First Affiliated Hospital of Army Medical University (the Third Military Medical University), Chongqing 400038, China
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41
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Cao C, Wang J, Kwok D, Cui F, Zhang Z, Zhao D, Li MJ, Zou Q. webTWAS: a resource for disease candidate susceptibility genes identified by transcriptome-wide association study. Nucleic Acids Res 2021; 50:D1123-D1130. [PMID: 34669946 PMCID: PMC8728162 DOI: 10.1093/nar/gkab957] [Citation(s) in RCA: 94] [Impact Index Per Article: 31.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2021] [Revised: 09/24/2021] [Accepted: 10/05/2021] [Indexed: 12/20/2022] Open
Abstract
The development of transcriptome-wide association studies (TWAS) has enabled researchers to better identify and interpret causal genes in many diseases. However, there are currently no resources providing a comprehensive listing of gene-disease associations discovered by TWAS from published GWAS summary statistics. TWAS analyses are also difficult to conduct due to the complexity of TWAS software pipelines. To address these issues, we introduce a new resource called webTWAS, which integrates a database of the most comprehensive disease GWAS datasets currently available with credible sets of potential causal genes identified by multiple TWAS software packages. Specifically, a total of 235 064 gene-diseases associations for a wide range of human diseases are prioritized from 1298 high-quality downloadable European GWAS summary statistics. Associations are calculated with seven different statistical models based on three popular and representative TWAS software packages. Users can explore associations at the gene or disease level, and easily search for related studies or diseases using the MeSH disease tree. Since the effects of diseases are highly tissue-specific, webTWAS applies tissue-specific enrichment analysis to identify significant tissues. A user-friendly web server is also available to run custom TWAS analyses on user-provided GWAS summary statistics data. webTWAS is freely available at http://www.webtwas.net.
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Affiliation(s)
- Chen Cao
- Yangtze Delta Region Institute (Quzhou), University of Electronic Science and Technology of China, Quzhou, China.,Institute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China, Chengdu, China.,Department of Biochemistry & Molecular Biology, Alberta Children's Hospital Research Institute, University of Calgary, Calgary, Canada
| | - Jianhua Wang
- Department of Pharmacology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China
| | - Devin Kwok
- School of Computer Science, McGill University, Montreal, Canada
| | - Feifei Cui
- Yangtze Delta Region Institute (Quzhou), University of Electronic Science and Technology of China, Quzhou, China.,Institute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China, Chengdu, China
| | - Zilong Zhang
- Yangtze Delta Region Institute (Quzhou), University of Electronic Science and Technology of China, Quzhou, China.,Institute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China, Chengdu, China
| | - Da Zhao
- Yangtze Delta Region Institute (Quzhou), University of Electronic Science and Technology of China, Quzhou, China.,Institute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China, Chengdu, China
| | - Mulin Jun Li
- Department of Pharmacology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China
| | - Quan Zou
- Yangtze Delta Region Institute (Quzhou), University of Electronic Science and Technology of China, Quzhou, China.,Institute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China, Chengdu, China
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42
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Dai Z, Li R, Hou Y, Li Q, Zhao K, Li T, Li MJ, Wu X. Inducible CRISPRa screen identifies putative enhancers. J Genet Genomics 2021; 48:917-927. [PMID: 34531148 DOI: 10.1016/j.jgg.2021.06.012] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2021] [Revised: 05/21/2021] [Accepted: 06/07/2021] [Indexed: 12/28/2022]
Abstract
Enhancers are critical cis-regulatory elements that regulate spatiotemporal gene expression and control cell fates. However, the identification of enhancers in native cellular contexts still remains a challenge. Here, we develop an inducible CRISPR activation (CRISPRa) system by transgenic expression of doxycycline (Dox)-inducible dCas9-VPR in mouse embryonic stem cells (iVPR ESC). With this line, a simple introduction of specific guide RNAs targeting promoters or enhancers allows us to realize the effect of CRISPRa in an inducible, reversible, and Dox concentration-dependent manner. Taking advantage of this system, we induce tiled CRISPRa across genomic regions (105 kilobases) surrounding T (Brachyury), one of the key mesodermal development regulator genes. Moreover, we identify several CRISPRa-responsive elements with chromatin features of putative enhancers, including a region the homologous sequence in which humans harbors a body height risk variant. Genetic deletion of this region in ESC does affect subsequent T gene activation and osteogenic differentiation. Therefore, our inducible CRISPRa ESC line provides a convenient platform for high-throughput screens of putative enhancers.
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Affiliation(s)
- Zhongye Dai
- State Key Laboratory of Experimental Hematology, The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, Tianjin Key Laboratory of Cellular Homeostasis and Human Diseases, Department of Cell Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin 300070, China
| | - Rui Li
- State Key Laboratory of Experimental Hematology, The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, Tianjin Key Laboratory of Cellular Homeostasis and Human Diseases, Department of Cell Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin 300070, China
| | - Yuying Hou
- State Key Laboratory of Experimental Hematology, The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, Tianjin Key Laboratory of Cellular Homeostasis and Human Diseases, Department of Cell Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin 300070, China
| | - Qian Li
- State Key Laboratory of Experimental Hematology, The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, Tianjin Key Laboratory of Cellular Homeostasis and Human Diseases, Department of Cell Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin 300070, China
| | - Ke Zhao
- Department of Pharmacology, Tianjin Key Laboratory of Medical Epigenetics, Tianjin Medical University, Tianjin 300070, China
| | - Ting Li
- State Key Laboratory of Experimental Hematology, The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, Tianjin Key Laboratory of Cellular Homeostasis and Human Diseases, Department of Cell Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin 300070, China
| | - Mulin Jun Li
- Department of Pharmacology, Tianjin Key Laboratory of Medical Epigenetics, Tianjin Medical University, Tianjin 300070, China
| | - Xudong Wu
- State Key Laboratory of Experimental Hematology, The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, Tianjin Key Laboratory of Cellular Homeostasis and Human Diseases, Department of Cell Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin 300070, China; Department of Neurosurgery, Tianjin Medical University General Hospital, Tianjin 300052, China; Tianjin Key Laboratory of Epigenetics for Organ Development of Premature Infants, Tianjin 300450, China.
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43
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Huang D, Zhou Y, Yi X, Fan X, Wang J, Yao H, Sham PC, Hao J, Chen K, Li MJ. VannoPortal: multiscale functional annotation of human genetic variants for interrogating molecular mechanism of traits and diseases. Nucleic Acids Res 2021; 50:D1408-D1416. [PMID: 34570217 PMCID: PMC8728305 DOI: 10.1093/nar/gkab853] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2021] [Revised: 09/05/2021] [Accepted: 09/14/2021] [Indexed: 12/16/2022] Open
Abstract
Interpreting the molecular mechanism of genomic variations and their causal relationship with diseases/traits are important and challenging problems in the human genetic study. To provide comprehensive and context-specific variant annotations for biologists and clinicians, here, by systematically integrating over 4TB genomic/epigenomic profiles and frequently-used annotation databases from various biological domains, we develop a variant annotation database, called VannoPortal. In general, the database has following major features: (i) systematically integrates 40 genome-wide variant annotations and prediction scores regarding allele frequency, linkage disequilibrium, evolutionary signature, disease/trait association, tissue/cell type-specific epigenome, base-wise functional prediction, allelic imbalance and pathogenicity; (ii) equips with our recent novel index system and parallel random-sweep searching algorithms for efficient management of backend databases and information extraction; (iii) greatly expands context-dependent variant annotation to incorporate large-scale epigenomic maps and regulatory profiles (such as EpiMap) across over 33 tissue/cell types; (iv) compiles many genome-scale base-wise prediction scores for regulatory/pathogenic variant classification beyond protein-coding region; (v) enables fast retrieval and direct comparison of functional evidence among linked variants using highly interactive web panel in addition to plain table; (vi) introduces many visualization functions for more efficient identification and interpretation of functional variants in single web page. VannoPortal is freely available at http://mulinlab.org/vportal.
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Affiliation(s)
- Dandan Huang
- Department of Bioinformatics, The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, School of Basic Medical Sciences, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin 300070, China.,Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin 300070, China
| | - Yao Zhou
- Department of Bioinformatics, The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, School of Basic Medical Sciences, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin 300070, China.,Department of Pharmacology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin 300070, China
| | - Xianfu Yi
- School of Biomedical Engineering, Tianjin Medical University, Tianjin 300070, China
| | - Xutong Fan
- Department of Bioinformatics, The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, School of Basic Medical Sciences, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin 300070, China.,Department of Pharmacology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin 300070, China
| | - Jianhua Wang
- Department of Bioinformatics, The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, School of Basic Medical Sciences, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin 300070, China.,Department of Pharmacology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin 300070, China
| | - Hongcheng Yao
- Centre for PanorOmic Sciences-Genomics and Bioinformatics Cores, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong SAR 999077, China
| | - Pak Chung Sham
- Centre for PanorOmic Sciences-Genomics and Bioinformatics Cores, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong SAR 999077, China
| | - Jihui Hao
- Department of Pancreatic Cancer, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin's Clinical Research Center for Cancer, Tianjin 300060, China
| | - Kexin Chen
- Department of Epidemiology and Biostatistics, Tianjin Key Laboratory of Molecular Cancer Epidemiology, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin 300060, China
| | - Mulin Jun Li
- Department of Bioinformatics, The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, School of Basic Medical Sciences, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin 300070, China.,Department of Pharmacology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin 300070, China.,Department of Epidemiology and Biostatistics, Tianjin Key Laboratory of Molecular Cancer Epidemiology, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin 300060, China
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44
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Ding BJ, Liu L, Li MJ, Xia A, Song XW, Zhou KS, Zhou J, Xu PP, Liu JP, Zhou H, Song YP. [Cyclic thrombocytopenia: a case report and literature review]. Zhonghua Xue Ye Xue Za Zhi 2021; 42:770. [PMID: 34753235 PMCID: PMC8607038 DOI: 10.3760/cma.j.issn.0253-2727.2021.09.012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
Affiliation(s)
- B J Ding
- Department of Hematology, Affiliated Cancer Hospital of Zhengzhou University, Henan Cancer Hospital, Zhengzhou 450008, China
| | - L Liu
- Department of Hematology, First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, China
| | - M J Li
- Department of Hematology, Affiliated Cancer Hospital of Zhengzhou University, Henan Cancer Hospital, Zhengzhou 450008, China
| | - A Xia
- Department of Hematology, Affiliated Cancer Hospital of Zhengzhou University, Henan Cancer Hospital, Zhengzhou 450008, China
| | - X W Song
- Department of Hematology, Affiliated Cancer Hospital of Zhengzhou University, Henan Cancer Hospital, Zhengzhou 450008, China
| | - K S Zhou
- Department of Hematology, Affiliated Cancer Hospital of Zhengzhou University, Henan Cancer Hospital, Zhengzhou 450008, China
| | - J Zhou
- Department of Hematology, Affiliated Cancer Hospital of Zhengzhou University, Henan Cancer Hospital, Zhengzhou 450008, China
| | - P P Xu
- Department of Hematology, Affiliated Cancer Hospital of Zhengzhou University, Henan Cancer Hospital, Zhengzhou 450008, China
| | - J P Liu
- Department of Hematology, Affiliated Cancer Hospital of Zhengzhou University, Henan Cancer Hospital, Zhengzhou 450008, China
| | - H Zhou
- Department of Hematology, Affiliated Cancer Hospital of Zhengzhou University, Henan Cancer Hospital, Zhengzhou 450008, China
| | - Y P Song
- Department of Hematology, Affiliated Cancer Hospital of Zhengzhou University, Henan Cancer Hospital, Zhengzhou 450008, China
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Huang D, Wang Z, Zhou Y, Liang Q, Sham PC, Yao H, Li MJ. vSampler: fast and annotation-based matched variant sampling tool. Bioinformatics 2021; 37:1915-1917. [PMID: 33270826 DOI: 10.1093/bioinformatics/btaa883] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2020] [Revised: 07/28/2020] [Accepted: 09/30/2020] [Indexed: 11/13/2022] Open
Abstract
SUMMARY Sampling of control variants having matched properties with input variants is widely used in enrichment analysis of genome-wide association studies/quantitative trait loci and negative data construction for pathogenic/regulatory variant prediction methods. Spurious enrichment results because of confounding factors, such as minor allele frequency and linkage disequilibrium pattern, can be avoided by calibration of statistical significance based on matched controls. Here, we presented vSampler which can generate sets of randomly drawn variants with comprehensive choices of matching properties, such as tissue/cell type-specific epigenomic features. Importantly, the development of a novel data structure and sampling algorithms for vSampler makes it significantly fast than existing tools. AVAILABILITY AND IMPLEMENTATION vSampler web server and local program are available at http://mulinlab.org/vsampler. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Dandan Huang
- Department of Epidemiology and Biostatistics, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin 300070, China.,Department of Pharmacology, Tianjin Key Laboratory of Inflammation Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin 300070, China
| | - Zhao Wang
- Department of Pharmacology, Tianjin Key Laboratory of Inflammation Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin 300070, China
| | - Yao Zhou
- Department of Pharmacology, Tianjin Key Laboratory of Inflammation Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin 300070, China
| | - Qian Liang
- Department of Pharmacology, Tianjin Key Laboratory of Inflammation Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin 300070, China
| | | | - Hongcheng Yao
- School of Biomedical Sciences, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR 999077, China
| | - Mulin Jun Li
- Department of Epidemiology and Biostatistics, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin 300070, China.,Department of Pharmacology, Tianjin Key Laboratory of Inflammation Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin 300070, China
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46
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Xu PP, Ding BJ, Li MJ, Liu JP, Liu L, Xia A, Liu WQ, Zhou KS, Zhao HF, Zhou H, Song YP. [Hereditary coagulation factor XIII deficiency: three cases report and literaure review]. Zhonghua Xue Ye Xue Za Zhi 2021; 42:256-258. [PMID: 33910314 PMCID: PMC8081941 DOI: 10.3760/cma.j.issn.0253-2727.2021.03.014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Affiliation(s)
- P P Xu
- Department of Hematology, The Affiliated Cancer Hospital of Zhengzhou University (Henan Cancer Hospital), Zhengzhou 450008, China
| | - B J Ding
- Department of Hematology, The Affiliated Cancer Hospital of Zhengzhou University (Henan Cancer Hospital), Zhengzhou 450008, China
| | - M J Li
- Department of Hematology, The Affiliated Cancer Hospital of Zhengzhou University (Henan Cancer Hospital), Zhengzhou 450008, China
| | - J P Liu
- Department of Hematology, The Affiliated Cancer Hospital of Zhengzhou University (Henan Cancer Hospital), Zhengzhou 450008, China
| | - L Liu
- Department of Hematology, First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, China
| | - A Xia
- Department of Hematology, The Affiliated Cancer Hospital of Zhengzhou University (Henan Cancer Hospital), Zhengzhou 450008, China
| | - W Q Liu
- Department of Intensive Care Units, Henan Provincial People's Hospital, Zhengzhou 450003, China
| | - K S Zhou
- Department of Hematology, The Affiliated Cancer Hospital of Zhengzhou University (Henan Cancer Hospital), Zhengzhou 450008, China
| | - H F Zhao
- Department of Hematology, The Affiliated Cancer Hospital of Zhengzhou University (Henan Cancer Hospital), Zhengzhou 450008, China
| | - H Zhou
- Department of Hematology, The Affiliated Cancer Hospital of Zhengzhou University (Henan Cancer Hospital), Zhengzhou 450008, China
| | - Y P Song
- Department of Hematology, The Affiliated Cancer Hospital of Zhengzhou University (Henan Cancer Hospital), Zhengzhou 450008, China
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Shen L, Hu P, Zhang Y, Ji Z, Shan X, Ni L, Ning N, Wang J, Tian H, Shui G, Yuan Y, Li G, Zheng H, Yang XP, Huang D, Feng X, Li MJ, Liu Z, Wang T, Yu Q. Serine metabolism antagonizes antiviral innate immunity by preventing ATP6V0d2-mediated YAP lysosomal degradation. Cell Metab 2021; 33:971-987.e6. [PMID: 33798471 DOI: 10.1016/j.cmet.2021.03.006] [Citation(s) in RCA: 43] [Impact Index Per Article: 14.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/22/2020] [Revised: 02/02/2021] [Accepted: 03/05/2021] [Indexed: 01/08/2023]
Abstract
Serine metabolism promotes tumor oncogenesis and regulates immune cell functions, but whether it also contributes to antiviral innate immunity is unknown. Here, we demonstrate that virus-infected macrophages display decreased expression of serine synthesis pathway (SSP) enzymes. Suppressing the SSP key enzyme phosphoglycerate dehydrogenase (PHGDH) by genetic approaches or by treatment with the pharmaceutical inhibitor CBR-5884 and by exogenous serine restriction enhanced IFN-β-mediated antiviral innate immunity in vitro and in vivo. Mechanistic experiments showed that virus infection or serine metabolism deficiency increased the expression of the V-ATPase subunit ATP6V0d2 by inhibiting S-adenosyl methionine-dependent H3K27me3 occupancy at the promoter. ATP6V0d2 promoted YAP lysosomal degradation to relieve YAP-mediated blockade of the TBK1-IRF3 axis and, thus, enhance IFN-β production. These findings implicate critical functions of PHGDH and the key immunometabolite serine in blunting antiviral innate immunity and also suggest manipulation of serine metabolism as a therapeutic strategy against virus infection.
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Affiliation(s)
- Long Shen
- Key Laboratory of Immune Microenvironment and Disease (Ministry of Education), Department of Immunology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin 300070, China
| | - Penghui Hu
- Key Laboratory of Immune Microenvironment and Disease (Ministry of Education), Department of Immunology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin 300070, China
| | - Yanan Zhang
- Key Laboratory of Immune Microenvironment and Disease (Ministry of Education), Department of Immunology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin 300070, China
| | - Zemin Ji
- Key Laboratory of Immune Microenvironment and Disease (Ministry of Education), Department of Immunology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin 300070, China
| | - Xiao Shan
- Key Laboratory of Immune Microenvironment and Disease (Ministry of Education), Department of Immunology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin 300070, China
| | - Lina Ni
- Department of Pharmacology and Tianjin Key Laboratory of Inflammation Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin 300070, China
| | - Na Ning
- Department of Immunology, School of Basic Medicine, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Jing Wang
- Department of Immunology, School of Basic Medicine, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - He Tian
- State Key Laboratory of Molecular Developmental Biology, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing 100101, China
| | - Guanghou Shui
- State Key Laboratory of Molecular Developmental Biology, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing 100101, China
| | - Yukang Yuan
- Institutes of Biology and Medical Sciences, Soochow University, Suzhou, Jiangsu 215123, China
| | - Guoli Li
- Key Laboratory of Immune Microenvironment and Disease (Ministry of Education), Department of Immunology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin 300070, China
| | - Hui Zheng
- Institutes of Biology and Medical Sciences, Soochow University, Suzhou, Jiangsu 215123, China
| | - Xiang-Ping Yang
- Department of Immunology, School of Basic Medicine, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Dandan Huang
- The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, Department of Pharmacology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin 300070, China
| | - Xiangling Feng
- The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, Department of Pharmacology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin 300070, China
| | - Mulin Jun Li
- The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, Department of Pharmacology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin 300070, China
| | - Zhe Liu
- Key Laboratory of Immune Microenvironment and Disease (Ministry of Education), Department of Immunology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin 300070, China
| | - Ting Wang
- Department of Pharmacology and Tianjin Key Laboratory of Inflammation Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin 300070, China; The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, Department of Pharmacology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin 300070, China.
| | - Qiujing Yu
- Key Laboratory of Immune Microenvironment and Disease (Ministry of Education), Department of Immunology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin 300070, China; Department of Pharmacology and Tianjin Key Laboratory of Inflammation Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin 300070, China; The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, Department of Pharmacology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin 300070, China.
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Li M, Li MJ, Huang J, Le CY, Wang Y, Zhao LQ, Wang CF, Wan CW, Wang JW. Age-Related Changes of Material Mechanics and Bone Material Parameters of Rat Skulls. Fa Yi Xue Za Zhi 2021; 37:1-6. [PMID: 33780176 DOI: 10.12116/j.issn.1004-5619.2020.400814] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Received: 08/19/2020] [Indexed: 11/30/2022]
Abstract
Abstract Objective To study the relationship between material mechanics and bone material parameters of rat skulls and their correlation with age by examination of the parameters. Methods Forty-eight healthy male SD rats were divided into 2, 4, 6, 8, 17, 26, 52 and 104 week groups according to their age. Each group had six rats. The right cranium was compressed by KD Ⅱ-0.2 microcomputer controlled electronic universal testing machine, and material mechanics parameters (ultimate load, compression strength and compression modulus) were measured, then the skull slices were cut off and scanned by Micro-CT system to detect bone material parameters (skull thickness, bone mineral density, bone volume, and trabecular thickness). Results The differences in ultimate load, compression strength and compression modulus among all groups had statistical significance (P<0.05), and were positively correlated with age within 26 weeks (P<0.05). The differences in skull thickness, bone mineral density, bone volume and trabecular thickness among all groups had statistical significance (P<0.05), and were positively correlated with age within 52 weeks (P<0.05). All material mechanics parameters were positively correlated with bone material parameters (P<0.05). Conclusion There is a positive correlation between bone material parameters (skull thickness, bone mineral density, bone volume, trabecular thickness), material mechanics parameter (skull ultimate load, compression strength, compression modulus) and age in a certain range, which can be used to infer age.
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Affiliation(s)
- M Li
- School of Forensic Medicine, Guizhou Medical University, Guiyang 550004, China
| | - M J Li
- School of Forensic Medicine, Guizhou Medical University, Guiyang 550004, China.,Department of Pathology, First Affiliated Hospital of Guangxi Medical University, Nanning 530021, China
| | - J Huang
- School of Forensic Medicine, Guizhou Medical University, Guiyang 550004, China
| | - C Y Le
- School of Forensic Medicine, Guizhou Medical University, Guiyang 550004, China
| | - Y Wang
- School of Forensic Medicine, Guizhou Medical University, Guiyang 550004, China
| | - L Q Zhao
- School of Forensic Medicine, Guizhou Medical University, Guiyang 550004, China
| | - C F Wang
- School of Forensic Medicine, Guizhou Medical University, Guiyang 550004, China
| | - C W Wan
- School of Forensic Medicine, Guizhou Medical University, Guiyang 550004, China
| | - J W Wang
- School of Forensic Medicine, Guizhou Medical University, Guiyang 550004, China
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Liu N, Xu J, Liu H, Zhang S, Li M, Zhou Y, Qin W, Li MJ, Yu C. Hippocampal transcriptome-wide association study and neurobiological pathway analysis for Alzheimer's disease. PLoS Genet 2021; 17:e1009363. [PMID: 33630843 PMCID: PMC7906391 DOI: 10.1371/journal.pgen.1009363] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2020] [Accepted: 01/12/2021] [Indexed: 01/22/2023] Open
Abstract
Genome-wide association studies (GWASs) have identified multiple susceptibility loci for Alzheimer’s disease (AD), which is characterized by early and progressive damage to the hippocampus. However, the association of hippocampal gene expression with AD and the underlying neurobiological pathways remain largely unknown. Based on the genomic and transcriptomic data of 111 hippocampal samples and the summary data of two large-scale meta-analyses of GWASs, a transcriptome-wide association study (TWAS) was performed to identify genes with significant associations between hippocampal expression and AD. We identified 54 significantly associated genes using an AD-GWAS meta-analysis of 455,258 individuals; 36 of the genes were confirmed in another AD-GWAS meta-analysis of 63,926 individuals. Fine-mapping models further prioritized 24 AD-related genes whose effects on AD were mediated by hippocampal expression, including APOE and two novel genes (PTPN9 and PCDHA4). These genes are functionally related to amyloid-beta formation, phosphorylation/dephosphorylation, neuronal apoptosis, neurogenesis and telomerase-related processes. By integrating the predicted hippocampal expression and neuroimaging data, we found that the hippocampal expression of QPCTL and ERCC2 showed significant difference between AD patients and cognitively normal elderly individuals as well as correlated with hippocampal volume. Mediation analysis further demonstrated that hippocampal volume mediated the effect of hippocampal gene expression (QPCTL and ERCC2) on AD. This study identifies two novel genes associated with AD by integrating hippocampal gene expression and genome-wide association data and reveals candidate hippocampus-mediated neurobiological pathways from gene expression to AD. The hippocampus is a potential neuroimaging endophenotype for Alzheimer’s disease (AD). This study identifies genes whose expression in hippocampal tissue is associated with AD and establishes the pathways from hippocampal gene expression to hippocampal volume to AD. We demonstrate that 24 genes are associated with AD in hippocampal tissue, and these genes are enriched for AD-related biological processes of amyloid-beta formation, phosphorylation/dephosphorylation, neuronal apoptosis, neurogenesis and telomerase-related processes. We further show that hippocampal volume mediates the effects of the hippocampal gene expression of QPCTL and ERCC2 on AD. These findings improve our understanding of the genetic and neural mechanisms of AD.
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Affiliation(s)
- Nana Liu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Jiayuan Xu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Huaigui Liu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Shijie Zhang
- The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, Tianjin Key Laboratory of Medical Epigenetics, Department of Pharmacology, Tianjin Medical University, Tianjin, China
| | - Miaoxin Li
- Department of Medical Genetics, Center for Genome Research, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
- Centre for Genomic Sciences, The University of Hong Kong, Hong Kong Special Administrative Region, China
- Department of Psychiatry, The University of Hong Kong, Hong Kong Special Administrative Region, China
- Centre for Reproduction, Development and Growth, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region, China
| | - Yao Zhou
- The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, Tianjin Key Laboratory of Medical Epigenetics, Department of Pharmacology, Tianjin Medical University, Tianjin, China
| | - Wen Qin
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Mulin Jun Li
- The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, Tianjin Key Laboratory of Medical Epigenetics, Department of Pharmacology, Tianjin Medical University, Tianjin, China
- * E-mail: (MJL); (CY)
| | - Chunshui Yu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
- Chinese Academy of Sciences (CAS) Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, China
- * E-mail: (MJL); (CY)
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Zhou H, Yang JY, Xu PP, Liu L, Ding BJ, Liu JP, Li MJ, Song YP. [The involvement of neuropilin-1 in primary immune thrombocytopenia]. Zhonghua Xue Ye Xue Za Zhi 2021; 42:146-150. [PMID: 33858046 PMCID: PMC8071663 DOI: 10.3760/cma.j.issn.0253-2727.2021.02.010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/06/2020] [Indexed: 11/16/2022]
Abstract
Objective: To explore the relationship between the expression of neuropilin-1 (NRP-1) on Treg cells and its ligands semaphorins-3A (Sema3A) , transforming growth factor-β(1) (TGF-β(1)) as well as the balance of type 1 helper T cells (Th(1)) and type 2 helper T cells (Th(2)) cells. Methods: This study enrolled 62 patients with immune thrombocytopenia (ITP; 33 and 29 newly diagnosed and chronic ITP, respectively) from March 2014 to May 2015. Consequently, 30 healthy people in the same period were selected as the normal control group. The expression of NRP-1 in Treg cells was detected via flow cytometry. The Sema3A, TGF-β(1), IFN-γ, and IL-4 levels in plasma were detected by enzyme-linked immunosorbent assay. The real-time polymerase chain reaction technique was used to detect the mRNA expression levels of NRP-1, Sema3A, and TGF-β(1). The one-way analysis of variance and independent sample t-test was used for comparison between three and two groups, respectively. Correlations among the mRNA expression levels of NRP-1, Sema3A, and TGF-β(1) were assessed via Spearman correlation coefficients. Results: Treg cells in the newly diagnosed ITP group significantly increased compared with those in the chronic ITP and normal control groups. The expression of NRP-1 decreased[ (0.15 ± 0.03) %, (0.33 ± 0.15) %, and (0.46 ± 0.06) %; P<0.01], the plasma Sema3A level increased[ (8.10 ± 1.32) μg/L, (7.41±1.30) μg/L, and (2.88±0.82) μg/L; P<0.01], and the plasma TGF-β(1) level decreased[ (16.50±3.36) μg/L, (35.17±10.26) μg/L, and (41.00±10.02) μg/L; P<0.01]. Moreover, the level of plasma IFN-γ increased[ (17.21+2.80) ng/L, (10.23+1.59) ng/L, and (8.18+3.27) ng/L; P<0.01], and the ratios of Th(1)/Th(2) (IFN-γ/IL-4) increased (1.29±0.30, 0.72±0.16, and 0.61±0.27; P<0.01) . The mRNA expressions of NRP-1 and Sema3A in the newly diagnosed ITP and chronic ITP groups were lower than that in the normal control group (P<0.01) . Consequently, the NRP-1 mRNA expression was positively correlated with Sema3A and TGF-β(1) mRNA expression in the newly diagnosed ITP group. Conclusion: NRP-1 played an essential role in the pathogenesis of ITP.
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Affiliation(s)
- H Zhou
- Department of Hematology, The Affiliated Cancer Hospital of Zhengzhou University (Henan Cancer Hospital) , Zhengzhou 450008, China
| | - J Y Yang
- Department of Hematology, The Affiliated Cancer Hospital of Zhengzhou University (Henan Cancer Hospital) , Zhengzhou 450008, China
| | - P P Xu
- Department of Hematology, The Affiliated Cancer Hospital of Zhengzhou University (Henan Cancer Hospital) , Zhengzhou 450008, China
| | - L Liu
- Department of Hematology, First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, China
| | - B J Ding
- Department of Hematology, The Affiliated Cancer Hospital of Zhengzhou University (Henan Cancer Hospital) , Zhengzhou 450008, China
| | - J P Liu
- Department of Hematology, The Affiliated Cancer Hospital of Zhengzhou University (Henan Cancer Hospital) , Zhengzhou 450008, China
| | - M J Li
- Department of Hematology, The Affiliated Cancer Hospital of Zhengzhou University (Henan Cancer Hospital) , Zhengzhou 450008, China
| | - Y P Song
- Department of Hematology, The Affiliated Cancer Hospital of Zhengzhou University (Henan Cancer Hospital) , Zhengzhou 450008, China
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