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Yang M, Chen X, Cheng C, Yan W, Guo R, Wang Y, Zhang H, Chai J, Cheng Y, Zhang F. Cucurbitacin B induces ferroptosis in oral leukoplakia via the SLC7A11/mitochondrial oxidative stress pathway. PHYTOMEDICINE : INTERNATIONAL JOURNAL OF PHYTOTHERAPY AND PHYTOPHARMACOLOGY 2024; 129:155548. [PMID: 38583347 DOI: 10.1016/j.phymed.2024.155548] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/19/2023] [Revised: 02/01/2024] [Accepted: 03/18/2024] [Indexed: 04/09/2024]
Abstract
BACKGROUND Oral leukoplakia (OLK), characterized by abnormal epithelial hyperplasia, is the most common precancerous oral mucosa lesion and is closely related to oxidative stress. Cucurbitacin B (CuB), a tetracyclic triterpenoid molecule derived from plants, has shown promising anti-proliferative and antioxidant effects in preclinical studies. However, whether CuB can play an antiproliferative role in OLK by regulating oxidative stress remains elusive. PURPOSE To investigate the role of CuB in inhibiting the malignant progression of oral leukoplakia and to further explore its underlying mechanisms of action. METHODS In vitro, the effect of CuB on the proliferation, migration, apoptosis, and cell cycle of OLK cells DOK was detected. The core genes and key pathways of OLK and CuB were analyzed in the transcriptome database, by using immunofluorescence, qRT-PCR, and Western blot to evaluate the expression levels of the ferroptosis markers ROS, GSH, MDA, Fe2+, and marker genes SLC7A11, GPX4, and FTH1. Immunohistochemistry of human tissue was performed to investigate the expression of the SLC7A11. In vivo, the model of OLK was established in C57BL/6 mice and the biosafety of CuB treatment for OLK was further evaluated. RESULTS CuB substantially suppressed the proliferation of DOK cells. Bioinformatics analysis showed that the core targets of OLK crossing with CuB include SLC7A11 and that the essential pathways involve ROS and ferroptosis. In vitro experiments indicated that CuB might promote ferroptosis by down-regulating the expression of SLC7A11. We observed a gradual increase in SLC7A11 expression levels during the progression from normal oral mucosa to oral leukoplakia with varying degrees of epithelial dysplasia. In vivo experiments demonstrated that CuB inhibited the malignant progression of OLK by promoting ferroptosis in OLK mice and exhibited a certain level of biosafety. CONCLUSION This study demonstrated for the first time that CuB could effectively inhibit the malignant progression of OLK by inducing ferroptosis via activating the SLC7A11/ mitochondrial oxidative stress pathway. These findings indicate that CuB could serve as the lead compound for the future development of anti-oral leukoplakia drugs.
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Affiliation(s)
- Mengyuan Yang
- Shanxi Medical University School and Hospital of Stomatology, Shanxi Province Key Laboratory of Oral Diseases Prevention and New Materials, No.63 Xinjian South Road, Yingze District, Taiyuan, Shanxi 030001, China
| | - Xin Chen
- Shanxi Medical University School and Hospital of Stomatology, Shanxi Province Key Laboratory of Oral Diseases Prevention and New Materials, No.63 Xinjian South Road, Yingze District, Taiyuan, Shanxi 030001, China
| | - Chen Cheng
- Shanxi Medical University School and Hospital of Stomatology, Shanxi Province Key Laboratory of Oral Diseases Prevention and New Materials, No.63 Xinjian South Road, Yingze District, Taiyuan, Shanxi 030001, China
| | - Wenpeng Yan
- Shanxi Medical University School and Hospital of Stomatology, Shanxi Province Key Laboratory of Oral Diseases Prevention and New Materials, No.63 Xinjian South Road, Yingze District, Taiyuan, Shanxi 030001, China
| | - Rongrong Guo
- Shanxi Medical University School and Hospital of Stomatology, Shanxi Province Key Laboratory of Oral Diseases Prevention and New Materials, No.63 Xinjian South Road, Yingze District, Taiyuan, Shanxi 030001, China
| | - Yajun Wang
- Shanxi Medical University School and Hospital of Stomatology, Shanxi Province Key Laboratory of Oral Diseases Prevention and New Materials, No.63 Xinjian South Road, Yingze District, Taiyuan, Shanxi 030001, China
| | - Heng Zhang
- Shanxi Medical University School and Hospital of Stomatology, Shanxi Province Key Laboratory of Oral Diseases Prevention and New Materials, No.63 Xinjian South Road, Yingze District, Taiyuan, Shanxi 030001, China
| | - Jiawei Chai
- Shanxi Medical University School and Hospital of Stomatology, Shanxi Province Key Laboratory of Oral Diseases Prevention and New Materials, No.63 Xinjian South Road, Yingze District, Taiyuan, Shanxi 030001, China
| | - YaHsin Cheng
- Department of Physiology, School of Medicine, China Medical University, Taichung, Taiwan
| | - Fang Zhang
- Shanxi Medical University School and Hospital of Stomatology, Shanxi Province Key Laboratory of Oral Diseases Prevention and New Materials, No.63 Xinjian South Road, Yingze District, Taiyuan, Shanxi 030001, China.
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Ruan X, Zhang X, Liu L, Zhang J. Mechanism of Xiaoyao San in treating non-alcoholic fatty liver disease with liver depression and spleen deficiency: based on bioinformatics, metabolomics and in vivo experiments. J Biomol Struct Dyn 2024; 42:5128-5146. [PMID: 37440274 DOI: 10.1080/07391102.2023.2231544] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2023] [Accepted: 06/08/2023] [Indexed: 07/14/2023]
Abstract
Xiaoyao san (XYS) plays an important role in treatment of non-alcoholic fatty liver disease (NAFLD) with liver stagnation and spleen deficiency, but its specific mechanism is still unclear. This study aimed to investigate the material basis and mechanism by means of network pharmacology, metabolomics, systems biology and molecular docking methods. On this basis, NAFLD rat model with liver stagnation and spleen deficiency was constructed and XYS was used to intervene, and liver histopathology, biochemical detection, enzyme-linked immunosorbent assay, quantitative PCR assay and western blotting were used to further verify the mechanism. Through the above research methods, network pharmacology study showed that there were 94 targets in total for XYS in the treatment of NAFLD. Metabolomics study showed that NAFLD with liver depression and spleen deficiency had a total of 73 differential metabolites. Systems biology found that PTGS2 and PPARG were the core targets; Quercetin, kaempferol, naringenin, beta-sitosterol and stigmasterol were the core active components; AA, cAMP were the core metabolites. And molecular docking showed that the core active components can act well on the key targets. Animal experiments showed that XYS could improve liver histopathology, increase 5HT and NA, decrease INS and FBG, improve blood lipids and liver function, decrease AA, increase cAMP, down-regulate PTGS2, up-regulate PPARG, and decrease PGE2 and 15d-PGJ2. In conclusion, XYS might treat NAFLD with liver depression and spleen deficiency by down-regulating PTGS2, up-regulating PPARG, reducing AA content, increasing cAMP, improving insulin resistance, affecting glucose and lipid metabolism, inhibiting oxidative stress and inflammatory response.Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Xiaofeng Ruan
- School of Acupuncture - Moxibustion and Orthopedics, Hubei University of Chinese Medicine, Wuhan, China
| | - Xiaoming Zhang
- School of Acupuncture - Moxibustion and Orthopedics, Hubei University of Chinese Medicine, Wuhan, China
| | - Liming Liu
- School of Traditional Chinese Medicine, Hubei University of Chinese Medicine, Wuhan, China
- Department of Liver Medicine, Hubei No.3 People's Hospital of Jianghan University, Wuhan, China
| | - Jianjun Zhang
- School of Traditional Chinese Medicine, Hubei University of Chinese Medicine, Wuhan, China
- Department of Liver Medicine, Hubei No.3 People's Hospital of Jianghan University, Wuhan, China
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Wang Q, Wang Q, Huang Q, Zhang X, Qin Z, Yu Y, Dai Y, Han J, Yao X, He L, Lin P, Yao Z. Five-layer-funnel filtering mode discovers effective components of Chinese medicine formulas: Zhishi-Xiebai-Guizhi decoction as a case study. PHYTOMEDICINE : INTERNATIONAL JOURNAL OF PHYTOTHERAPY AND PHYTOPHARMACOLOGY 2024; 129:155678. [PMID: 38754214 DOI: 10.1016/j.phymed.2024.155678] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/23/2024] [Revised: 03/20/2024] [Accepted: 04/23/2024] [Indexed: 05/18/2024]
Abstract
BACKGROUND How to screen and identify the effective components in the complex substance system is one of the core issues in achieving the modernization of traditional Chinese medicine (TCM) formulas. However, it is still challenging to systematically screen out the effective components from the hundreds or thousands of components in a TCM formula. PURPOSE An innovative five-layer-funnel filtering mode stepwise integrating chemical profile, quantitative analysis, xenobiotic profile, network pharmacology and bioactivity evaluation was successfully presented to discover the effective components and implemented on a case study of Zhishi-Xiebai-Guizhi decoction (ZXG), a well-known TCM formula for coronary heart disease (CHD). METHODS Initially, the chemical profile of ZXG was systemically characterized. Subsequently, the representative constituents were quantitatively analyzed. In the third step, the multi-component xenobiotics profile of ZXG was systemically delineated, and the prototypes absorbed into the blood were identified and designated as the primary bioavailable components. Next, an integrated network of "bioavailable components-CHD targets-pathways-therapeutic effects" was constructed, and the crucial bioavailable components of ZXG against CHD were screened out. Lastly, the bioactivities of crucial bioavailable components were further evaluated to pinpoint effective components. RESULTS First of all, the chemical profile of ZXG was systemically characterized with the detection of 201 components. Secondly, 37 representative components were quantified to comprehensively describe its content distribution characteristics. Thirdly, among the quantified components, 24 bioavailable components of ZXG were identified based on the multi-component xenobiotic profile. Fourthly, an integrated network led to the identification of 11 crucial bioavailable components against CHD. Ultimately, 9 components (honokiol, magnolol, naringenin, magnoflorine, hesperidin, hesperetin, naringin, neohesperidin and narirutin) exhibiting myocardial protection in vitro were identified as effective components of ZXG for the first time. CONCLUSION Overall, this innovative strategy successfully identified the effective components of ZXG for the first time. It could not only significantly contribute to elucidating the therapeutic mechanism of ZXG in the treatment of CHD, but also serve as a helpful reference for the systematic discovery of effective components as well as ideal quality markers in the quality assessment of TCM formulas.
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Affiliation(s)
- Qi Wang
- International Cooperative Laboratory of Traditional Chinese Medicine Modernization and Innovative Drug Development of Ministry of Education (MOE) of China, Guangdong Province Key Laboratory of Pharmacodynamic Constituents of TCM and New Drugs Research, Institute of Traditional Chinese Medicine & Natural Products, College of Pharmacy, Jinan University, Guangzhou 510632, China
| | - Qiqi Wang
- International Cooperative Laboratory of Traditional Chinese Medicine Modernization and Innovative Drug Development of Ministry of Education (MOE) of China, Guangdong Province Key Laboratory of Pharmacodynamic Constituents of TCM and New Drugs Research, Institute of Traditional Chinese Medicine & Natural Products, College of Pharmacy, Jinan University, Guangzhou 510632, China
| | - Qiaoting Huang
- International Cooperative Laboratory of Traditional Chinese Medicine Modernization and Innovative Drug Development of Ministry of Education (MOE) of China, Guangdong Province Key Laboratory of Pharmacodynamic Constituents of TCM and New Drugs Research, Institute of Traditional Chinese Medicine & Natural Products, College of Pharmacy, Jinan University, Guangzhou 510632, China
| | - Xinya Zhang
- International Cooperative Laboratory of Traditional Chinese Medicine Modernization and Innovative Drug Development of Ministry of Education (MOE) of China, Guangdong Province Key Laboratory of Pharmacodynamic Constituents of TCM and New Drugs Research, Institute of Traditional Chinese Medicine & Natural Products, College of Pharmacy, Jinan University, Guangzhou 510632, China
| | - Zifei Qin
- Department of Pharmacology, the First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, China
| | - Yang Yu
- International Cooperative Laboratory of Traditional Chinese Medicine Modernization and Innovative Drug Development of Ministry of Education (MOE) of China, Guangdong Province Key Laboratory of Pharmacodynamic Constituents of TCM and New Drugs Research, Institute of Traditional Chinese Medicine & Natural Products, College of Pharmacy, Jinan University, Guangzhou 510632, China
| | - Yi Dai
- International Cooperative Laboratory of Traditional Chinese Medicine Modernization and Innovative Drug Development of Ministry of Education (MOE) of China, Guangdong Province Key Laboratory of Pharmacodynamic Constituents of TCM and New Drugs Research, Institute of Traditional Chinese Medicine & Natural Products, College of Pharmacy, Jinan University, Guangzhou 510632, China
| | - Jingyan Han
- Department of Integration of Chinese and Western Medicine, School of Basic Medical Sciences, Peking University, Beijing, China
| | - Xinsheng Yao
- International Cooperative Laboratory of Traditional Chinese Medicine Modernization and Innovative Drug Development of Ministry of Education (MOE) of China, Guangdong Province Key Laboratory of Pharmacodynamic Constituents of TCM and New Drugs Research, Institute of Traditional Chinese Medicine & Natural Products, College of Pharmacy, Jinan University, Guangzhou 510632, China
| | - Liangliang He
- International Cooperative Laboratory of Traditional Chinese Medicine Modernization and Innovative Drug Development of Ministry of Education (MOE) of China, Guangdong Province Key Laboratory of Pharmacodynamic Constituents of TCM and New Drugs Research, Institute of Traditional Chinese Medicine & Natural Products, College of Pharmacy, Jinan University, Guangzhou 510632, China.
| | - Pei Lin
- International Cooperative Laboratory of Traditional Chinese Medicine Modernization and Innovative Drug Development of Ministry of Education (MOE) of China, Guangdong Province Key Laboratory of Pharmacodynamic Constituents of TCM and New Drugs Research, Institute of Traditional Chinese Medicine & Natural Products, College of Pharmacy, Jinan University, Guangzhou 510632, China.
| | - Zhihong Yao
- International Cooperative Laboratory of Traditional Chinese Medicine Modernization and Innovative Drug Development of Ministry of Education (MOE) of China, Guangdong Province Key Laboratory of Pharmacodynamic Constituents of TCM and New Drugs Research, Institute of Traditional Chinese Medicine & Natural Products, College of Pharmacy, Jinan University, Guangzhou 510632, China; Guangzhou Key Laboratory of Formula-Pattern of Traditional Chinese Medicine, School of Traditional Chinese Medicine, Jinan University, Guangzhou 510632, China.
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Luo H, Li Y, Xie J, Xu C, Zhang Z, Li M, Xia B, Shi Z, Lin L. Effect and mechanism of Prunella vulgaris L. extract on alleviating lipopolysaccharide-induced acute mastitis in protecting the blood-milk barrier and reducing inflammation. JOURNAL OF ETHNOPHARMACOLOGY 2024; 328:117998. [PMID: 38484956 DOI: 10.1016/j.jep.2024.117998] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/19/2023] [Revised: 02/25/2024] [Accepted: 02/27/2024] [Indexed: 03/25/2024]
Abstract
ETHNOPHARMACOLOGICAL RELEVANCE According to ancient literature, Prunella vulgaris L. (P vulgaris) alleviates mastitis and has been used in China for many years; however, there are no relevant reports that confirm this or the mechanism of its efficacy. AIM OF THE STUDY To explore the anti-acute mastitis effect and potential mechanism of P vulgaris extract. MATERIALS AND METHODS First, the active ingredients and targets of P vulgaris against mastitis were predicted using network pharmacology. Next, the relevant active ingredients were enriched using macroporous resins and verified using UV and UPLC-Q-TOF-MS/MS. Lastly, a mouse model of acute mastitis was established by injecting lipopolysaccharides into the mammary gland and administering P vulgaris extract by oral gavage. The pathological changes in mammary tissue were observed by HE staining. Serum and tissue inflammatory factors were measured by ELISA method. MPO activity in mammary tissue was measured using colorimetry and MPO expression was detected by immunohistochemistry. The expression of tight junction proteins (ZO-1, claudin-3, and occludin) in mammary tissue was detected by immunofluorescence and Western blot. iNOS and COX-2 in mammary tissue were detected by Western blot. MAPK pathway and NF-κB pathway related proteins were also detected by Western blot. RESULTS Network pharmacology predicted that phenolic acids and flavonoids in P vulgaris had anti-mastitis effects. The contents of total flavonoids and total phenolic acids in P vulgaris extract were 64.5% and 29.4%, respectively. UPLC-Q-TOF-MS/MS confirmed that P vulgaris extract contained phenolic acids and flavonoids. The results of animal experiments showed that P vulgaris extract reduced lipopolysaccharide-induced inflammatory edema, inflammatory cell infiltration, and interstitial congestion of mammary tissue. It also reduced the levels of serum and tissue inflammatory factors TNF-α, IL-6, and IL-1β, and inhibited the activation of MPO. Furthermore, it downregulated the expression of MAPK and NF-κB pathway-related proteins. The expressions of ZO-1, occludin, and claudin-3 in mammary gland tissues were upregulated. CONCLUSIONS P vulgaris extract can maintain the integrity of mammary connective tissue and reduce its inflammatory response to prevent acute mastitis. Its mechanism probably involves regulating NF-κB and MAPK pathways.
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Affiliation(s)
- Hongshan Luo
- College of Pharmacy, Hunan University of Chinese Medicine, Changsha, 410208, China; Key Laboratory for Quality Evaluation of Bulk Herbs of Hunan Province, Hunan University of Chinese Medicine, Changsha, 410208, China.
| | - Yamei Li
- College of Pharmacy, Hunan University of Chinese Medicine, Changsha, 410208, China; Key Laboratory for Quality Evaluation of Bulk Herbs of Hunan Province, Hunan University of Chinese Medicine, Changsha, 410208, China.
| | - Jingchen Xie
- College of Pharmacy, Hunan University of Chinese Medicine, Changsha, 410208, China; Key Laboratory for Quality Evaluation of Bulk Herbs of Hunan Province, Hunan University of Chinese Medicine, Changsha, 410208, China.
| | - Chunfang Xu
- College of Pharmacy, Hunan University of Chinese Medicine, Changsha, 410208, China; Key Laboratory for Quality Evaluation of Bulk Herbs of Hunan Province, Hunan University of Chinese Medicine, Changsha, 410208, China.
| | - Zhimin Zhang
- College of Pharmacy, Hunan University of Chinese Medicine, Changsha, 410208, China; Key Laboratory for Quality Evaluation of Bulk Herbs of Hunan Province, Hunan University of Chinese Medicine, Changsha, 410208, China.
| | - Minjie Li
- College of Pharmacy, Hunan University of Chinese Medicine, Changsha, 410208, China; Key Laboratory for Quality Evaluation of Bulk Herbs of Hunan Province, Hunan University of Chinese Medicine, Changsha, 410208, China.
| | - Bohou Xia
- College of Pharmacy, Hunan University of Chinese Medicine, Changsha, 410208, China; Key Laboratory for Quality Evaluation of Bulk Herbs of Hunan Province, Hunan University of Chinese Medicine, Changsha, 410208, China.
| | - Zhe Shi
- College of Pharmacy, Hunan University of Chinese Medicine, Changsha, 410208, China; Key Laboratory for Quality Evaluation of Bulk Herbs of Hunan Province, Hunan University of Chinese Medicine, Changsha, 410208, China.
| | - Limei Lin
- College of Pharmacy, Hunan University of Chinese Medicine, Changsha, 410208, China; Key Laboratory for Quality Evaluation of Bulk Herbs of Hunan Province, Hunan University of Chinese Medicine, Changsha, 410208, China.
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Liu X, Ren Y, Qin S, Yang Z. Exploring the mechanism of 6-Methoxydihydrosanguinarine in the treatment of lung adenocarcinoma based on network pharmacology, molecular docking and experimental investigation. BMC Complement Med Ther 2024; 24:202. [PMID: 38783288 PMCID: PMC11119275 DOI: 10.1186/s12906-024-04497-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2024] [Accepted: 05/10/2024] [Indexed: 05/25/2024] Open
Abstract
BACKGROUND 6-Methoxydihydrosanguinarine (6-MDS) has shown promising potential in fighting against a variety of malignancies. Yet, its anti‑lung adenocarcinoma (LUAD) effect and the underlying mechanism remain largely unexplored. This study sought to explore the targets and the probable mechanism of 6-MDS in LUAD through network pharmacology and experimental validation. METHODS The proliferative activity of human LUAD cell line A549 was evaluated by Cell Counting Kit-8 (CCK8) assay. LUAD related targets, potential targets of 6-MDS were obtained from databases. Venn plot analysis were performed on 6-MDS target genes and LUAD related genes to obtain potential target genes for 6-MDS treatment of LUAD. The Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database was utilized to perform a protein-protein interaction (PPI) analysis, which was then visualized by Cytoscape. The hub genes in the network were singled out by CytoHubba. Metascape was employed for GO and KEGG enrichment analyses. molecular docking was carried out using AutoDock Vina 4.2 software. Gene expression levels, overall survival of hub genes were validated by the GEPIA database. Protein expression levels, promotor methylation levels of hub genes were confirmed by the UALCAN database. Timer database was used for evaluating the association between the expression of hub genes and the abundance of infiltrating immune cells. Furthermore, correlation analysis of hub genes expression with immune subtypes of LUAD were performed by using the TISIDB database. Finally, the results of network pharmacology analysis were validated by qPCR. RESULTS Experiments in vitro revealed that 6-MDS significantly reduced tumor growth. A total of 33 potential targets of 6-MDS in LUAD were obtained by crossing the LUAD related targets with 6-MDS targets. Utilizing CytoHubba, a network analysis tool, the top 10 genes with the highest centrality measures were pinpointed, including MMP9, CDK1, TYMS, CCNA2, ERBB2, CHEK1, KIF11, AURKB, PLK1 and TTK. Analysis of KEGG enrichment hinted that these 10 hub genes were located in the cell cycle signaling pathway, suggesting that 6-MDS may mainly inhibit the occurrence of LUAD by affecting the cell cycle. Molecular docking analysis revealed that the binding energies between 6-MDS and the hub proteins were all higher than - 6 kcal/Mol with the exception of AURKB, indicating that the 9 targets had strong binding ability with 6-MDS.These results were corroborated through assessments of mRNA expression levels, protein expression levels, overall survival analysis, promotor methylation level, immune subtypes andimmune infiltration. Furthermore, qPCR results indicated that 6-MDS can significantly decreased the mRNA levels of CDK1, CHEK1, KIF11, PLK1 and TTK. CONCLUSIONS According to our findings, it appears that 6-MDS could possibly serve as a promising option for the treatment of LUAD. Further investigations in live animal models are necessary to confirm its potential in fighting cancer and to delve into the mechanisms at play.
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Affiliation(s)
- Xingyun Liu
- The Affiliated Nanhua Hospital, Hengyang Medical School, University of South China, Hengyang, 421000, China
| | - Yanling Ren
- Key Specialty of Clinical Pharmacy, The First Affiliated Hospital of Guangdong Pharmaceutical University, Guangzhou, 510000, China
- NMPA Key Laboratory for Technology Research and Evaluation of Pharmacovigilance, Guangdong Pharmaceutical University, Guangzhou, 510086, China
| | - Shuanglin Qin
- School of Pharmacy, Xianning Medical College, Hubei University of Science and Technology, Xianning, 437000, China.
| | - Zerui Yang
- Key Specialty of Clinical Pharmacy, The First Affiliated Hospital of Guangdong Pharmaceutical University, Guangzhou, 510000, China.
- NMPA Key Laboratory for Technology Research and Evaluation of Pharmacovigilance, Guangdong Pharmaceutical University, Guangzhou, 510086, China.
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Krishna Murthy SB, Yang S, Bheda S, Tomar N, Li H, Yaghoobi A, Khan A, Kiryluk K, Motelow JE, Ren N, Gharavi AG, Milo Rasouly H. Assisting the analysis of insertions and deletions using regional allele frequencies. Funct Integr Genomics 2024; 24:104. [PMID: 38764005 DOI: 10.1007/s10142-024-01358-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2024] [Revised: 04/02/2024] [Accepted: 04/12/2024] [Indexed: 05/21/2024]
Abstract
Accurate estimation of population allele frequency (AF) is crucial for gene discovery and genetic diagnostics. However, determining AF for frameshift-inducing small insertions and deletions (indels) faces challenges due to discrepancies in mapping and variant calling methods. Here, we propose an innovative approach to assess indel AF. We developed CRAFTS-indels (Calculating Regional Allele Frequency Targeting Small indels), an algorithm that combines AF of distinct indels within a given region and provides "regional AF" (rAF). We tested and validated CRAFTS-indels using three independent datasets: gnomAD v2 (n=125,748 samples), an internal dataset (IGM; n=39,367), and the UK BioBank (UKBB; n=469,835). By comparing rAF against standard AF, we identified rare indels with rAF exceeding standard AF (sAF≤10-4 and rAF>10-4) as "rAF-hi" indels. Notably, a high percentage of rare indels were "rAF-hi", with a higher proportion in gnomAD v2 (11-20%) and IGM (11-22%) compared to the UKBB (5-9% depending on the CRAFTS-indels' parameters). Analysis of the overlap of regions based on their rAF with low complexity regions and with ClinVar classification supported the pertinence of rAF. Using the internal dataset, we illustrated the utility of CRAFTS-indel in the analysis of de novo variants and the potential negative impact of rAF-hi indels in gene discovery. In summary, annotation of indels with cohort specific rAF can be used to handle some of the limitations of current annotation pipelines and facilitate detection of novel gene disease associations. CRAFTS-indels offers a user-friendly approach to providing rAF annotation. It can be integrated into public databases such as gnomAD, UKBB and used by ClinVar to revise indel classifications.
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Affiliation(s)
- Sarath Babu Krishna Murthy
- Center for Precision Genetics and Genomics, Department of Medicine, Columbia University, New York, NY, USA
| | - Sandy Yang
- Center for Precision Genetics and Genomics, Department of Medicine, Columbia University, New York, NY, USA
| | - Shiraz Bheda
- Center for Precision Genetics and Genomics, Department of Medicine, Columbia University, New York, NY, USA
| | - Nikita Tomar
- Center for Precision Genetics and Genomics, Department of Medicine, Columbia University, New York, NY, USA
| | - Haiyue Li
- Center for Precision Genetics and Genomics, Department of Medicine, Columbia University, New York, NY, USA
| | - Amir Yaghoobi
- Center for Precision Genetics and Genomics, Department of Medicine, Columbia University, New York, NY, USA
| | - Atlas Khan
- Division of Nephrology, Department of Medicine, Columbia University, New York, NY, USA
| | - Krzysztof Kiryluk
- Division of Nephrology, Department of Medicine, Columbia University, New York, NY, USA
| | - Joshua E Motelow
- Division of Critical Care and Hospital Medicine, Department of Pediatrics, Columbia University Irving Medical Center, New York-Presbyterian Morgan Stanley Children's Hospital, New York, New York, USA
| | - Nick Ren
- Institute for Genomic Medicine, Columbia University, New York, NY, USA
| | - Ali G Gharavi
- Center for Precision Genetics and Genomics, Department of Medicine, Columbia University, New York, NY, USA
- Division of Nephrology, Department of Medicine, Columbia University, New York, NY, USA
| | - Hila Milo Rasouly
- Center for Precision Genetics and Genomics, Department of Medicine, Columbia University, New York, NY, USA.
- Division of Nephrology, Department of Medicine, Columbia University, New York, NY, USA.
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Low KJ, Watford A, Blair P, Nabney I, Powell J, Wynn SL, Foreman J, Firth H, Ingram J. Improving the care of children with GENetic Rare disease: Observational Cohort study (GenROC)-a study protocol. BMJ Open 2024; 14:e085237. [PMID: 38760043 PMCID: PMC11103197 DOI: 10.1136/bmjopen-2024-085237] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/13/2024] [Accepted: 04/18/2024] [Indexed: 05/19/2024] Open
Abstract
INTRODUCTION Around 2000 children are born in the UK per year with a neurodevelopmental genetic syndrome with significantly increased morbidity and mortality. Often little is known about expected growth and phenotypes in these children. Parents have responded by setting up social media groups to generate data themselves. Given the significant clinical evidence gaps, this research will attempt to identify growth patterns, developmental profiles and phenotypes, providing data on long-term medical and educational outcomes. This will guide clinicians when to investigate, monitor or treat symptoms and when to search for additional or alternative diagnoses. METHODS AND ANALYSIS This is an observational, multicentre cohort study recruiting between March 2023 and February 2026. Children aged 6 months up to 16 years with a pathogenic or likely pathogenic variant in a specified gene will be eligible. Children will be identified through the National Health Service and via self-recruitment. Parents or carers will complete a questionnaire at baseline and again 1 year after recruitment. The named clinician (in most cases a clinical geneticist) will complete a clinical proforma which will provide data from their most recent clinical assessment. Qualitative interviews will be undertaken with a subset of parents partway through the study. Growth and developmental milestone curves will be generated through the DECIPHER website (https://deciphergenomics.org) where 5 or more children have the same genetic syndrome (at least 10 groups expected). ETHICS AND DISSEMINATION The results will be presented at national and international conferences concerning the care of children with genetic syndromes. Results will also be submitted for peer review and publication.
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Affiliation(s)
- Karen Jaqueline Low
- Centre for Academic Child Health, University of Bristol, Bristol, UK
- Department of Clinical Genetics, University Hospitals Bristol and Weston NHS Trust, Bristol, UK
| | - Amy Watford
- Department of Clinical Genetics, University Hospitals Bristol and Weston NHS Trust, Bristol, UK
| | - Peter Blair
- Centre for Academic Child Health, University of Bristol, Bristol, UK
| | - Ian Nabney
- School of Computer Science, Electrical and Electronic Engineering and Engineering Maths, University of Bristol, Bristol, UK
| | - John Powell
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | - Sarah L Wynn
- Unique Rare Chromosome Disorder Support Group, Oxted, UK
| | - Julia Foreman
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, UK
| | - Helen Firth
- Clinical Genetics, Cambridge University Hospitals, Cambridge, UK
- Wellcome Genome Campus, Wellcome Sanger Institute, Hinxton, UK
| | - Jenny Ingram
- Centre for Academic Child Health, School of Social & Community Medicine, Bristol University, Bristol, UK
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Liu Y, Su W, Li P, Zeng X, Zheng Y, Wang Y, Peng W, Wu H. Exploring the Mechanism of Fufang Danshen Tablet against Atherosclerosis by Network Pharmacology and Experimental Validation. Pharmaceuticals (Basel) 2024; 17:643. [PMID: 38794213 PMCID: PMC11124970 DOI: 10.3390/ph17050643] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2024] [Revised: 05/04/2024] [Accepted: 05/14/2024] [Indexed: 05/26/2024] Open
Abstract
Atherosclerosis is the main pathological basis of cardiovascular diseases (CVDs). Fufang Danshen Tablet (FDT) is a traditional Chinese medicine that has been clinically used to treat CVDs for more than 40 years. Nevertheless, owing to the complexity of the ingredients, the pharmacological mechanism of FDT in the treatment of CVDs has not been fully elucidated. In this study, an integrated strategy of UFLC-Q-TOF-MS/MS, network pharmacology, molecular biology, and transcriptomics was used to elucidate the mechanisms of action of FDT in the treatment of atherosclerosis. In total, 22 absorbed constituents were identified in rat serum after oral administration of FDT. In silico, network pharmacology studies have shown that FDT regulates four key biological functional modules for the treatment of atherosclerosis: oxidative stress, cell apoptosis, energy metabolism, and immune/inflammation. In animal experiments, FDT exerted protective effects against atherosclerosis by reducing the plaque area and lipid levels in ApoE-/- mice. Furthermore, we found that FDT inhibited inflammatory macrophage accumulation by regulating the expression of Selp and Ccl2, which are both involved in monocyte adhesion and migration. The inhibition of monocyte recruitment by FDT is a new perspective to elucidate the anti-atherosclerotic mechanism of FDT, which has not been adopted in previous studies on FDT. Our results may help to elucidate the therapeutic mechanism of FDT against CVDs and provide potential therapeutic targets.
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Affiliation(s)
| | | | | | | | | | | | | | - Hao Wu
- Guangdong Engineering & Technology Research Center for Quality and Efficacy Reevaluation of Post-Market Traditional Chinese Medicine, Guangdong Provincial Key Laboratory of Plant Resources, School of Life Sciences, Sun Yat-sen University, Guangzhou 510275, China; (Y.L.); (W.S.); (P.L.); (X.Z.); (Y.Z.); (Y.W.); (W.P.)
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9
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Ciancia S, Madeo SF, Calabrese O, Iughetti L. The Approach to a Child with Dysmorphic Features: What the Pediatrician Should Know. CHILDREN (BASEL, SWITZERLAND) 2024; 11:578. [PMID: 38790573 PMCID: PMC11120268 DOI: 10.3390/children11050578] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/03/2024] [Revised: 05/01/2024] [Accepted: 05/06/2024] [Indexed: 05/26/2024]
Abstract
The advancement of genetic knowledge and the discovery of an increasing number of genetic disorders has made the role of the geneticist progressively more complex and fundamental. However, most genetic disorders present during childhood; thus, their early recognition is a challenge for the pediatrician, who will be also involved in the follow-up of these children, often establishing a close relationship with them and their families and becoming a referral figure. In this review, we aim to provide the pediatrician with a general knowledge of the approach to treating a child with a genetic syndrome associated with dysmorphic features. We will discuss the red flags, the most common manifestations, the analytic collection of the family and personal medical history, and the signs that should alert the pediatrician during the physical examination. We will offer an overview of the physical malformations most commonly associated with genetic defects and the way to describe dysmorphic facial features. We will provide hints about some tools that can support the pediatrician in clinical practice and that also represent a useful educational resource, either online or through apps downloaded on a smartphone. Eventually, we will offer an overview of genetic testing, the ethical considerations, the consequences of incidental findings, and the main indications and limitations of the principal technologies.
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Affiliation(s)
- Silvia Ciancia
- Pediatric Unit, Department of Medical and Surgical Sciences for Mothers, Children and Adults, University of Modena and Reggio Emilia, Largo del Pozzo 71, 41124 Modena, Italy
| | - Simona Filomena Madeo
- Pediatric Unit, Department of Medical and Surgical Sciences for Mothers, Children and Adults, University of Modena and Reggio Emilia, Largo del Pozzo 71, 41124 Modena, Italy
| | - Olga Calabrese
- Medical Genetics Unit, Department of Medical and Surgical Sciences for Mothers, Children and Adults, University of Modena and Reggio Emilia, 41124 Modena, Italy
| | - Lorenzo Iughetti
- Pediatric Unit, Department of Medical and Surgical Sciences for Mothers, Children and Adults, University of Modena and Reggio Emilia, Largo del Pozzo 71, 41124 Modena, Italy
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10
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Park JH, Cho YR. Computational drug repositioning with attention walking. Sci Rep 2024; 14:10072. [PMID: 38698208 PMCID: PMC11066070 DOI: 10.1038/s41598-024-60756-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2023] [Accepted: 04/26/2024] [Indexed: 05/05/2024] Open
Abstract
Drug repositioning aims to identify new therapeutic indications for approved medications. Recently, the importance of computational drug repositioning has been highlighted because it can reduce the costs, development time, and risks compared to traditional drug discovery. Most approaches in this area use networks for systematic analysis. Inferring drug-disease associations is then defined as a link prediction problem in a heterogeneous network composed of drugs and diseases. In this article, we present a novel method of computational drug repositioning, named drug repositioning with attention walking (DRAW). DRAW proceeds as follows: first, a subgraph enclosing the target link for prediction is extracted. Second, a graph convolutional network captures the structural features of the labeled nodes in the subgraph. Third, the transition probabilities are computed using attention mechanisms and converted into random walk profiles. Finally, a multi-layer perceptron takes random walk profiles and predicts whether a target link exists. As an experiment, we constructed two heterogeneous networks with drug-drug similarities based on chemical structures and anatomical therapeutic chemical classification (ATC) codes. Using 10-fold cross-validation, DRAW achieved an area under the receiver operating characteristic (ROC) curve of 0.903 and outperformed state-of-the-art methods. Moreover, we demonstrated the results of case studies for selected drugs and diseases to further confirm the capability of DRAW to predict drug-disease associations.
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Affiliation(s)
- Jong-Hoon Park
- Division of Software, Yonsei University Mirae Campus, Wonju-si, 26493, Gangwon-do, Korea
| | - Young-Rae Cho
- Division of Software, Yonsei University Mirae Campus, Wonju-si, 26493, Gangwon-do, Korea.
- Division of Digital Healthcare, Yonsei University Mirae Campus, Wonju-si, 26493, Gangwon-do, Korea.
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11
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Zhang XM, Xu KL, Kong JH, Dong G, Dong SJ, Yang ZX, Xu SJ, Wang L, Luo SY, Zhang YD, Zhou CC, Gu WY, Mei SY. Heterozygous CAPZA2 mutations cause global developmental delay, hypotonia with epilepsy: a case report and the literature review. J Hum Genet 2024; 69:197-203. [PMID: 38374166 DOI: 10.1038/s10038-024-01230-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2023] [Revised: 02/05/2024] [Accepted: 02/06/2024] [Indexed: 02/21/2024]
Abstract
CAPZA2 encodes the α2 subunit of CAPZA, which is vital for actin polymerization and depolymerization in humans. However, understanding of diseases associated with CAPZA2 remains limited. To date, only three cases have been documented with neurodevelopmental abnormalities such as delayed motor development, speech delay, intellectual disability, hypotonia, and a history of seizures. In this study, we document a patient who exhibited seizures, mild intellectual disability, and impaired motor development yet did not demonstrate speech delay or hypotonia. The patient also suffered from recurrent instances of respiratory infections, gastrointestinal and allergic diseases. A novel de novo splicing variant c.219+1 G > A was detected in the CAPZA2 gene through whole-exome sequencing. This variant led to exon 4 skipping in mRNA splicing, confirmed by RT-PCR and Sanger sequencing. To our knowledge, this is the third study on human CAPZA2 defects, documenting the fourth unambiguously diagnosed case. Furthermore, this splicing mutation type is reported here for the first time. Our research offers additional support for the existence of a CAPZA2-related non-syndromic neurodevelopmental disorder. Our findings augment our understanding of the phenotypic range associated with CAPZA2 deficiency and enrich the knowledge of the mutational spectrum of the CAPZA2 gene.
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Affiliation(s)
- Xiao-Man Zhang
- Henan Key Laboratory of Children's Genetics and Metabolic Diseases, Children's Hospital Affiliated to Zhengzhou University, Henan Children's Hospital, Zhengzhou Children's Hospital, Zhengzhou, China
| | - Kai-Li Xu
- Department of Pediatric Neurology, Children's Hospital Affiliated to Zhengzhou University, Henan Children's Hospital, Zhengzhou Children's Hospital, Zhengzhou, China
| | - Jing-Hui Kong
- Henan Key Laboratory of Children's Genetics and Metabolic Diseases, Children's Hospital Affiliated to Zhengzhou University, Henan Children's Hospital, Zhengzhou Children's Hospital, Zhengzhou, China
| | - Geng Dong
- Department of Clinical Laboratory, Children's Hospital Affiliated to Zhengzhou University, Henan Children's Hospital, Zhengzhou Children's Hospital, Zhengzhou, China
| | - Shi-Jie Dong
- Department of Radiology, Children's Hospital Affiliated to Zhengzhou University, Henan Children's Hospital, Zhengzhou Children's Hospital, Zhengzhou, China
| | - Zhi-Xiao Yang
- Department of Pediatric Neurology, Children's Hospital Affiliated to Zhengzhou University, Henan Children's Hospital, Zhengzhou Children's Hospital, Zhengzhou, China
| | - Shu-Jing Xu
- Department of Pediatric Neurology, Children's Hospital Affiliated to Zhengzhou University, Henan Children's Hospital, Zhengzhou Children's Hospital, Zhengzhou, China
| | - Li Wang
- Department of Pediatric Neurology, Children's Hospital Affiliated to Zhengzhou University, Henan Children's Hospital, Zhengzhou Children's Hospital, Zhengzhou, China
| | - Shu-Ying Luo
- Henan Key Laboratory of Children's Genetics and Metabolic Diseases, Children's Hospital Affiliated to Zhengzhou University, Henan Children's Hospital, Zhengzhou Children's Hospital, Zhengzhou, China
| | - Yao-Dong Zhang
- Henan Key Laboratory of Children's Genetics and Metabolic Diseases, Children's Hospital Affiliated to Zhengzhou University, Henan Children's Hospital, Zhengzhou Children's Hospital, Zhengzhou, China
| | - Chong-Chen Zhou
- Henan Key Laboratory of Children's Genetics and Metabolic Diseases, Children's Hospital Affiliated to Zhengzhou University, Henan Children's Hospital, Zhengzhou Children's Hospital, Zhengzhou, China
| | - Wei-Yue Gu
- Chigene Translational Medical Research Center Co. Ltd, Beijing, China
| | - Shi-Yue Mei
- Henan Key Laboratory of Children's Genetics and Metabolic Diseases, Children's Hospital Affiliated to Zhengzhou University, Henan Children's Hospital, Zhengzhou Children's Hospital, Zhengzhou, China.
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12
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Niewold TB, Aksentijevich I, Gorevic PD, Gibson G, Yao Q. Genetically transitional disease: conceptual understanding and applicability to rheumatic disease. Nat Rev Rheumatol 2024; 20:301-310. [PMID: 38418715 DOI: 10.1038/s41584-024-01086-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/19/2024] [Indexed: 03/02/2024]
Abstract
In genomic medicine, the concept of genetically transitional disease (GTD) refers to cases in which gene mutation is necessary but not sufficient to cause disease. In this Perspective, we apply this novel concept to rheumatic diseases, which have been linked to hundreds of genetic variants via association studies. These variants are in the 'grey zone' between monogenic variants with large effect sizes and common susceptibility alleles with small effect sizes. Among genes associated with rare autoinflammatory diseases, many low-frequency and/or low-penetrance variants are known to increase susceptibility to systemic inflammation. In autoimmune diseases, hundreds of HLA and non-HLA genetic variants have been revealed to be modest- to moderate-risk alleles. These diseases can be reclassified as GTDs. The same concept could apply to many other human diseases. GTD could improve the reporting of genetic testing results, diagnostic yields, genetic counselling and selection of therapy, as well as facilitating research using a novel approach to human genetic diseases.
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Affiliation(s)
- Timothy B Niewold
- Department of Rheumatology, Hospital for Special Surgery, New York, NY, USA
| | - Ivona Aksentijevich
- Inflammatory Disease Section, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Peter D Gorevic
- Division of Rheumatology, Allergy and Immunology, Stony Brook University Renaissance School of Medicine, Stony Brook, NY, USA
| | - Greg Gibson
- Center for Integrative Genomics, School of Biological Sciences, Georgia Institute of Technology, Atlanta, GA, USA
| | - Qingping Yao
- Division of Rheumatology, Allergy and Immunology, Stony Brook University Renaissance School of Medicine, Stony Brook, NY, USA.
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13
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Marchant RG, Bryen SJ, Bahlo M, Cairns A, Chao KR, Corbett A, Davis MR, Ganesh VS, Ghaoui R, Jones KJ, Kornberg AJ, Lek M, Liang C, MacArthur DG, Oates EC, O'Donnell-Luria A, O'Grady GL, Osei-Owusu IA, Rafehi H, Reddel SW, Roxburgh RH, Ryan MM, Sandaradura SA, Scott LW, Valkanas E, Weisburd B, Young H, Evesson FJ, Waddell LB, Cooper ST. Genome and RNA sequencing boost neuromuscular diagnoses to 62% from 34% with exome sequencing alone. Ann Clin Transl Neurol 2024; 11:1250-1266. [PMID: 38544359 DOI: 10.1002/acn3.52041] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2024] [Accepted: 02/24/2024] [Indexed: 05/15/2024] Open
Abstract
OBJECTIVE Most families with heritable neuromuscular disorders do not receive a molecular diagnosis. Here we evaluate diagnostic utility of exome, genome, RNA sequencing, and protein studies and provide evidence-based recommendations for their integration into practice. METHODS In total, 247 families with suspected monogenic neuromuscular disorders who remained without a genetic diagnosis after standard diagnostic investigations underwent research-led massively parallel sequencing: neuromuscular disorder gene panel, exome, genome, and/or RNA sequencing to identify causal variants. Protein and RNA studies were also deployed when required. RESULTS Integration of exome sequencing and auxiliary genome, RNA and/or protein studies identified causal or likely causal variants in 62% (152 out of 247) of families. Exome sequencing alone informed 55% (83 out of 152) of diagnoses, with remaining diagnoses (45%; 69 out of 152) requiring genome sequencing, RNA and/or protein studies to identify variants and/or support pathogenicity. Arrestingly, novel disease genes accounted for <4% (6 out of 152) of diagnoses while 36.2% of solved families (55 out of 152) harbored at least one splice-altering or structural variant in a known neuromuscular disorder gene. We posit that contemporary neuromuscular disorder gene-panel sequencing could likely provide 66% (100 out of 152) of our diagnoses today. INTERPRETATION Our results emphasize thorough clinical phenotyping to enable deep scrutiny of all rare genetic variation in phenotypically consistent genes. Post-exome auxiliary investigations extended our diagnostic yield by 81% overall (34-62%). We present a diagnostic algorithm that details deployment of genomic and auxiliary investigations to obtain these diagnoses today most effectively. We hope this provides a practical guide for clinicians as they gain greater access to clinical genome and transcriptome sequencing.
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Affiliation(s)
- Rhett G Marchant
- Faculty of Medicine and Health, The University of Sydney, Westmead, New South Wales, Australia
- Kids Neuroscience Centre, Kids Research, Children's Hospital at Westmead, Westmead, New South Wales, Australia
- Faculty of Medicine, The University of Queensland, Brisbane, Queensland, Australia
| | - Samantha J Bryen
- Faculty of Medicine and Health, The University of Sydney, Westmead, New South Wales, Australia
- Kids Neuroscience Centre, Kids Research, Children's Hospital at Westmead, Westmead, New South Wales, Australia
- Faculty of Medicine, The University of Queensland, Brisbane, Queensland, Australia
| | - Melanie Bahlo
- Functional Neuromics, Children's Medical Research Institute, Westmead, New South Wales, Australia
- Population Health and Immunity, The Walter and Eliza Hall Institute of Medical Research, Parkville, Victoria, Australia
| | - Anita Cairns
- Department of Medical Biology, The University of Melbourne, Parkville, Victoria, Australia
- Neurosciences Department, Queensland Children's Hospital, Brisbane, Queensland, Australia
| | - Katherine R Chao
- Broad Center for Mendelian Genomics, Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
| | - Alastair Corbett
- Neurology Department, Repatriation General Hospital Concord, Concord, New South Wales, Australia
| | - Mark R Davis
- Department of Diagnostic Genomics, PathWest Laboratory Medicine, Perth, WA, Australia
| | - Vijay S Ganesh
- Broad Center for Mendelian Genomics, Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
- Neuromuscular Division, Department of Neurology, Brigham and Women's Hospital, Boston, Massachusetts, USA
- Division of Genetics and Genomics, Boston Children's Hospital, Boston, Massachusetts, USA
| | - Roula Ghaoui
- Department of Neurology, Central Adelaide Local Health Network/Royal Adelaide Hospital, Adelaide, South Australia, Australia
- Adelaide Medical School, The University of Adelaide, Adelaide, South Australia, Australia
- Department of Genetics & Molecular Pathology, SA Pathology, Adelaide, South Australia, Australia
| | - Kristi J Jones
- Faculty of Medicine and Health, The University of Sydney, Westmead, New South Wales, Australia
- Kids Neuroscience Centre, Kids Research, Children's Hospital at Westmead, Westmead, New South Wales, Australia
- Clinical Genetics, Children's Hospital at Westmead, Westmead, New South Wales, Australia
| | - Andrew J Kornberg
- Department of Neurology, Royal Children's Hospital Melbourne, Parkville, Victoria, Australia
- Department of Paediatrics, University of Melbourne, Parkville, Victoria, Australia
- Neurosciences Group, Murdoch Children's Research Institute, Melbourne, Victoria, Australia
| | - Monkol Lek
- Broad Center for Mendelian Genomics, Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
- Department of Genetics, Yale School of Medicine, New Haven, Connecticut, USA
| | - Christina Liang
- Department of Neurology, Royal North Shore Hospital, St Leonards, New South Wales, Australia
- Neurogenetics, Northern Clinical School, Kolling Institute, The University of Sydney, Sydney, New South Wales, Australia
| | - Daniel G MacArthur
- Broad Center for Mendelian Genomics, Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
- Centre for Population Genomics, Garvan Institute of Medical Research/University of New South Wales, Sydney, New South Wales, Australia
- Centre for Population Genomics, Murdoch Children's Research Institute, Melbourne, Victoria, Australia
| | - Emily C Oates
- School of Biotechnology and Biomolecular Sciences, University of New South Wales, Randwick, New South Wales, Australia
| | - Anne O'Donnell-Luria
- Broad Center for Mendelian Genomics, Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
- Division of Genetics and Genomics, Boston Children's Hospital, Boston, Massachusetts, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Gina L O'Grady
- Starship Children's Health, Auckland District Health Board, Auckland, New Zealand
| | - Ikeoluwa A Osei-Owusu
- Broad Center for Mendelian Genomics, Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
| | - Haloom Rafehi
- Functional Neuromics, Children's Medical Research Institute, Westmead, New South Wales, Australia
- Population Health and Immunity, The Walter and Eliza Hall Institute of Medical Research, Parkville, Victoria, Australia
| | - Stephen W Reddel
- Neurology Department, Repatriation General Hospital Concord, Concord, New South Wales, Australia
- Brain and Mind Centre, The University of Sydney, Sydney, New South Wales, Australia
| | - Richard H Roxburgh
- Department of Neurology, Auckland District Health Board, Auckland, New Zealand
- Centre of Brain Research Neurogenetics Research Clinic, University of Auckland, Auckland, New Zealand
| | - Monique M Ryan
- Department of Neurology, Royal Children's Hospital Melbourne, Parkville, Victoria, Australia
- Department of Paediatrics, University of Melbourne, Parkville, Victoria, Australia
- Neurosciences Group, Murdoch Children's Research Institute, Melbourne, Victoria, Australia
| | - Sarah A Sandaradura
- Faculty of Medicine and Health, The University of Sydney, Westmead, New South Wales, Australia
- Kids Neuroscience Centre, Kids Research, Children's Hospital at Westmead, Westmead, New South Wales, Australia
- Clinical Genetics, Children's Hospital at Westmead, Westmead, New South Wales, Australia
| | - Liam W Scott
- Functional Neuromics, Children's Medical Research Institute, Westmead, New South Wales, Australia
- Population Health and Immunity, The Walter and Eliza Hall Institute of Medical Research, Parkville, Victoria, Australia
| | - Elise Valkanas
- Broad Center for Mendelian Genomics, Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA
- Program in Biological and Biomedical Sciences, Harvard Medical School, Boston, Massachusetts, USA
| | - Ben Weisburd
- Broad Center for Mendelian Genomics, Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
| | - Helen Young
- Kids Neuroscience Centre, Kids Research, Children's Hospital at Westmead, Westmead, New South Wales, Australia
- Department of Neurology, Children's Hospital at Westmead, Westmead, New South Wales, Australia
- Paediatrics, Royal North Shore Hospital, St Leonards, New South Wales, Australia
| | - Frances J Evesson
- Faculty of Medicine and Health, The University of Sydney, Westmead, New South Wales, Australia
- Kids Neuroscience Centre, Kids Research, Children's Hospital at Westmead, Westmead, New South Wales, Australia
- Faculty of Medicine, The University of Queensland, Brisbane, Queensland, Australia
| | - Leigh B Waddell
- Faculty of Medicine and Health, The University of Sydney, Westmead, New South Wales, Australia
- Kids Neuroscience Centre, Kids Research, Children's Hospital at Westmead, Westmead, New South Wales, Australia
| | - Sandra T Cooper
- Faculty of Medicine and Health, The University of Sydney, Westmead, New South Wales, Australia
- Kids Neuroscience Centre, Kids Research, Children's Hospital at Westmead, Westmead, New South Wales, Australia
- Faculty of Medicine, The University of Queensland, Brisbane, Queensland, Australia
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14
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Marygold SJ. The alpha-ketoacid dehydrogenase complexes of Drosophila melanogaster.. MICROPUBLICATION BIOLOGY 2024; 2024:10.17912/micropub.biology.001209. [PMID: 38741935 PMCID: PMC11089389 DOI: 10.17912/micropub.biology.001209] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Figures] [Subscribe] [Scholar Register] [Received: 04/18/2024] [Revised: 04/28/2024] [Accepted: 04/27/2024] [Indexed: 05/16/2024]
Abstract
The conserved family of alpha-ketoacid dehydrogenase complexes (AKDHCs) catalyze essential reactions in central metabolism and their dysregulation is implicated in several human diseases. Drosophila melanogaster provides an excellent model system to study the genetics and functions of these complexes. However, a systematic account of Drosophila AKDHCs and their composition has been lacking. Here, I identify and classify the genes encoding all Drosophila AKDHC subunits, update their functional annotations and integrate this work into the FlyBase database.
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Affiliation(s)
- Steven J Marygold
- FlyBase, Department of Physiology, Development and Neuroscience, University of Cambridge, Cambridge, U.K
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15
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Neuhofer CM, Prokisch H. Digenic Inheritance in Rare Disorders and Mitochondrial Disease-Crossing the Frontier to a More Comprehensive Understanding of Etiology. Int J Mol Sci 2024; 25:4602. [PMID: 38731822 PMCID: PMC11083678 DOI: 10.3390/ijms25094602] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2024] [Revised: 04/10/2024] [Accepted: 04/12/2024] [Indexed: 05/13/2024] Open
Abstract
Our understanding of rare disease genetics has been shaped by a monogenic disease model. While the traditional monogenic disease model has been successful in identifying numerous disease-associated genes and significantly enlarged our knowledge in the field of human genetics, it has limitations in explaining phenomena like phenotypic variability and reduced penetrance. Widening the perspective beyond Mendelian inheritance has the potential to enable a better understanding of disease complexity in rare disorders. Digenic inheritance is the simplest instance of a non-Mendelian disorder, characterized by the functional interplay of variants in two disease-contributing genes. Known digenic disease causes show a range of pathomechanisms underlying digenic interplay, including direct and indirect gene product interactions as well as epigenetic modifications. This review aims to systematically explore the background of digenic inheritance in rare disorders, the approaches and challenges when investigating digenic inheritance, and the current evidence for digenic inheritance in mitochondrial disorders.
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Affiliation(s)
- Christiane M. Neuhofer
- Institute of Human Genetics, University Medical Center, Technical University of Munich, Trogerstr. 32, 81675 Munich, Germany
- Institute of Neurogenomics, Computational Health Center, Helmholtz Centre Munich Neuherberg, Ingolstädter Landstraße 1, 85764 Oberschleißheim, Germany
- Institute of Human Genetics, Salzburger Landeskliniken, University Hospital of the Paracelsus Medical University, Müllner Hauptstraße 48, 5020 Salzburg, Austria
| | - Holger Prokisch
- Institute of Human Genetics, University Medical Center, Technical University of Munich, Trogerstr. 32, 81675 Munich, Germany
- Institute of Neurogenomics, Computational Health Center, Helmholtz Centre Munich Neuherberg, Ingolstädter Landstraße 1, 85764 Oberschleißheim, Germany
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16
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Wang K, Cui H, Liu K, He Q, Fu X, Li W, Han W. Exploring the anti-gout potential of sunflower receptacles alkaloids: A computational and pharmacological analysis. Comput Biol Med 2024; 172:108252. [PMID: 38493604 DOI: 10.1016/j.compbiomed.2024.108252] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2024] [Revised: 02/19/2024] [Accepted: 03/06/2024] [Indexed: 03/19/2024]
Abstract
Gout, a painful condition marked by elevated uric acid levels often linked to the diet's high purine and alcohol content, finds a potential treatment target in xanthine oxidase (XO), a crucial enzyme for uric acid production. This study explores the therapeutic properties of alkaloids extracted from sunflower (Helianthus annuus L.) receptacles against gout. By leveraging computational chemistry and introducing a novel R-based clustering algorithm, "TriDimensional Hierarchical Fingerprint Clustering with Tanimoto Representative Selection (3DHFC-TRS)," we assessed 231 alkaloid molecules from sunflower receptacles. Our clustering analysis pinpointed six alkaloids with significant gout-targeting potential, particularly emphasizing the fifth cluster's XO inhibition capabilities. Through molecular docking and the BatchDTA prediction model, we identified three top compounds-2-naphthylalanine, medroxalol, and fenspiride-with the highest XO affinity. Further molecular dynamics simulations assessed their enzyme active site interactions and binding free energies, employing MM-PBSA calculations. This investigation not only highlights the discovery of promising compounds within sunflower receptacle alkaloids via LC-MS but also introduces medroxalol as a novel gout treatment candidate, showcasing the synergy of computational techniques and LC-MS in drug discovery.
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Affiliation(s)
- Kaiyu Wang
- Edmond H. Fischer Signal Transduction Laboratory, School of Life Sciences, Jilin University, Changchun, 130012, Qianjin road 2699, China
| | - Huizi Cui
- Edmond H. Fischer Signal Transduction Laboratory, School of Life Sciences, Jilin University, Changchun, 130012, Qianjin road 2699, China
| | - Kaifeng Liu
- Key Laboratory for Molecular Enzymology and Engineering of Ministry of Education, School of Life Sciences, Jilin University, Changchun, 130012, Qianjin road 2699, China
| | - Qizheng He
- Key Laboratory for Molecular Enzymology and Engineering of Ministry of Education, School of Life Sciences, Jilin University, Changchun, 130012, Qianjin road 2699, China
| | - Xueqi Fu
- Edmond H. Fischer Signal Transduction Laboratory, School of Life Sciences, Jilin University, Changchun, 130012, Qianjin road 2699, China
| | - Wannan Li
- Edmond H. Fischer Signal Transduction Laboratory, School of Life Sciences, Jilin University, Changchun, 130012, Qianjin road 2699, China.
| | - Weiwei Han
- Key Laboratory for Molecular Enzymology and Engineering of Ministry of Education, School of Life Sciences, Jilin University, Changchun, 130012, Qianjin road 2699, China.
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17
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Gudmundsson S, Carlston CM, O'Donnell-Luria A. Interpreting variants in genes affected by clonal hematopoiesis in population data. Hum Genet 2024; 143:545-549. [PMID: 36739343 PMCID: PMC10400727 DOI: 10.1007/s00439-023-02526-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2022] [Accepted: 01/18/2023] [Indexed: 02/05/2023]
Abstract
Reference population databases like the Genome Aggregation Database (gnomAD) have improved our ability to interpret the human genome. Variant frequencies and frequency-derived tools (such as depletion scores) have become fundamental to variant interpretation and the assessment of variant-gene-disease relationships. Clonal hematopoiesis (CH) obstructs variant interpretation as somatic variants that provide proliferative advantage will affect variant frequencies, depletion scores, and downstream filtering. Further, default filtering of variants or genes associated with CH risks filtering bona fide germline variants as variants associated with CH can also cause Mendelian conditions. Here, we provide our insights on interpreting population variant data in genes affected by clonal hematopoiesis, as well as recommendations for careful review of 36 established CH genes associated with neurodevelopmental conditions.
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Affiliation(s)
- Sanna Gudmundsson
- Division of Genetics and Genomics, Department of Pediatrics, Boston Children's Hospital, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Center for Genomic Medicine, Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
| | - Colleen M Carlston
- Division of Genetics and Genomics, Department of Pediatrics, Boston Children's Hospital, Boston, MA, USA
- Center for Genomic Medicine, Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
| | - Anne O'Donnell-Luria
- Division of Genetics and Genomics, Department of Pediatrics, Boston Children's Hospital, Boston, MA, USA.
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
- Center for Genomic Medicine, Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA.
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18
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Caniza H, Cáceres JJ, Torres M, Paccanaro A. LanDis: the disease landscape explorer. Eur J Hum Genet 2024; 32:461-465. [PMID: 38200084 PMCID: PMC10999415 DOI: 10.1038/s41431-023-01511-9] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2023] [Revised: 11/01/2023] [Accepted: 11/23/2023] [Indexed: 01/12/2024] Open
Abstract
From a network medicine perspective, a disease is the consequence of perturbations on the interactome. These perturbations tend to appear in a specific neighbourhood on the interactome, the disease module, and modules related to phenotypically similar diseases tend to be located in close-by regions. We present LanDis, a freely available web-based interactive tool ( https://paccanarolab.org/landis ) that allows domain experts, medical doctors and the larger scientific community to graphically navigate the interactome distances between the modules of over 44 million pairs of heritable diseases. The map-like interface provides detailed comparisons between pairs of diseases together with supporting evidence. Every disease in LanDis is linked to relevant entries in OMIM and UniProt, providing a starting point for in-depth analysis and an opportunity for novel insight into the aetiology of diseases as well as differential diagnosis.
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Affiliation(s)
- Horacio Caniza
- Universidad Paraguayo Alemana de Ciencias Aplicadas, Facultad de Ciencias de la Ingeniería, San Lorenzo, Paraguay
- Department of Computer Science, Centre for Systems and Synthetic Biology, Royal Holloway University of London, Egham, UK
| | - Juan J Cáceres
- Department of Computer Science, Centre for Systems and Synthetic Biology, Royal Holloway University of London, Egham, UK
| | - Mateo Torres
- Escola de Matemática Aplicada, Fundação Getúlio Vargas, Rio de Janeiro, Brazil
| | - Alberto Paccanaro
- Department of Computer Science, Centre for Systems and Synthetic Biology, Royal Holloway University of London, Egham, UK.
- Escola de Matemática Aplicada, Fundação Getúlio Vargas, Rio de Janeiro, Brazil.
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19
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Fishburn AT, Florio CJ, Lopez NJ, Link NL, Shah PS. Molecular functions of ANKLE2 and its implications in human disease. Dis Model Mech 2024; 17:dmm050554. [PMID: 38691001 PMCID: PMC11103583 DOI: 10.1242/dmm.050554] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/03/2024] Open
Abstract
Ankyrin repeat and LEM domain-containing 2 (ANKLE2) is a scaffolding protein with established roles in cell division and development, the dysfunction of which is increasingly implicated in human disease. ANKLE2 regulates nuclear envelope disassembly at the onset of mitosis and its reassembly after chromosome segregation. ANKLE2 dysfunction is associated with abnormal nuclear morphology and cell division. It regulates the nuclear envelope by mediating protein-protein interactions with barrier to autointegration factor (BANF1; also known as BAF) and with the kinase and phosphatase that modulate the phosphorylation state of BAF. In brain development, ANKLE2 is crucial for proper asymmetric division of neural progenitor cells. In humans, pathogenic loss-of-function mutations in ANKLE2 are associated with primary congenital microcephaly, a condition in which the brain is not properly developed at birth. ANKLE2 is also linked to other disease pathologies, including congenital Zika syndrome, cancer and tauopathy. Here, we review the molecular roles of ANKLE2 and the recent literature on human diseases caused by its dysfunction.
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Affiliation(s)
- Adam T. Fishburn
- Department of Microbiology and Molecular Genetics, University of California, One Shields Avenue, Davis, CA 95616, USA
| | - Cole J. Florio
- Department of Microbiology and Molecular Genetics, University of California, One Shields Avenue, Davis, CA 95616, USA
| | - Nick J. Lopez
- Department of Microbiology and Molecular Genetics, University of California, One Shields Avenue, Davis, CA 95616, USA
| | - Nichole L. Link
- Department of Neurobiology, University of Utah, 20 South 2030 East, Salt Lake City, UT 84112, USA
| | - Priya S. Shah
- Department of Microbiology and Molecular Genetics, University of California, One Shields Avenue, Davis, CA 95616, USA
- Department of Chemical Engineering, University of California, One Shields Avenue, Davis, CA 95616, USA
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20
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Wang H, Tian Q, Zhang R, Du Q, Hu J, Gao T, Gao S, Fan K, Cheng X, Yan S, Zheng G, Dong H. Nobiletin alleviates atherosclerosis by inhibiting lipid uptake via the PPARG/CD36 pathway. Lipids Health Dis 2024; 23:76. [PMID: 38468335 PMCID: PMC10926578 DOI: 10.1186/s12944-024-02049-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2023] [Accepted: 02/18/2024] [Indexed: 03/13/2024] Open
Abstract
BACKGROUND Atherosclerosis (AS) is a persistent inflammatory condition triggered and exacerbated by several factors including lipid accumulation, endothelial dysfunction and macrophages infiltration. Nobiletin (NOB) has been reported to alleviate atherosclerosis; however, the underlying mechanism remains incompletely understood. METHODS This study involved comprehensive bioinformatic analysis, including multidatabase target prediction; GO and KEGG enrichment analyses for function and pathway exploration; DeepSite and AutoDock for drug binding site prediction; and CIBERSORT for immune cell involvement. In addition, target intervention was verified via cell scratch assays, oil red O staining, ELISA, flow cytometry, qRT‒PCR and Western blotting. In addition, by establishing a mouse model of AS, it was demonstrated that NOB attenuated lipid accumulation and the extent of atherosclerotic lesions. RESULTS (1) Altogether, 141 potentially targetable genes were identified through which NOB could intervene in atherosclerosis. (2) Lipid and atherosclerosis, fluid shear stress and atherosclerosis may be the dominant pathways and potential mechanisms. (3) ALB, AKT1, CASP3 and 7 other genes were identified as the top 10 target genes. (4) Six genes, including PPARG, MMP9, SRC and 3 other genes, were related to the M0 fraction. (5) CD36 and PPARG were upregulated in atherosclerosis samples compared to the normal control. (6) By inhibiting lipid uptake in RAW264.7 cells, NOB prevents the formation of foam cell. (7) In RAW264.7 cells, the inhibitory effect of oxidized low-density lipoprotein on foam cells formation and lipid accumulation was closely associated with the PPARG signaling pathway. (8) In vivo validation showed that NOB significantly attenuated intra-arterial lipid accumulation and macrophage infiltration and reduced CD36 expression. CONCLUSIONS Nobiletin alleviates atherosclerosis by inhibiting lipid uptake via the PPARG/CD36 pathway.
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Affiliation(s)
- Heng Wang
- Department of Vascular Surgery, The Second Hospital of Shanxi Medical University, Taiyuan, Shanxi, China
| | - Qinqin Tian
- Department of Vascular Surgery, The Second Hospital of Shanxi Medical University, Taiyuan, Shanxi, China
| | - Ruijing Zhang
- Department of Nephrology, The Second Hospital of Shanxi Medical University, Taiyuan, Shanxi, China
| | - Qiujing Du
- Jiangyin People's Hospital, Wuxi, Jiangsu, China
- Shanxi Bethune Hospital, Third Hospital of Shanxi Medical University, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital, Taiyuan, Shanxi, China
| | - Jie Hu
- Department of Vascular Surgery, The Second Hospital of Shanxi Medical University, Taiyuan, Shanxi, China
| | - Tingting Gao
- Department of Vascular Surgery, The Second Hospital of Shanxi Medical University, Taiyuan, Shanxi, China
| | - Siqi Gao
- Department of Vascular Surgery, The Second Hospital of Shanxi Medical University, Taiyuan, Shanxi, China
| | - Keyi Fan
- Department of Vascular Surgery, The Second Hospital of Shanxi Medical University, Taiyuan, Shanxi, China
| | - Xing Cheng
- Department of Vascular Surgery, The Second Hospital of Shanxi Medical University, Taiyuan, Shanxi, China
| | - Sheng Yan
- Department of Vascular Surgery, The Second Hospital of Shanxi Medical University, Taiyuan, Shanxi, China
| | - Guoping Zheng
- Department of Vascular Surgery, The Second Hospital of Shanxi Medical University, Taiyuan, Shanxi, China.
- Centre for Transplant and Renal Research, Westmead Institute for Medical Research, The University of Sydney, Sydney, NSW, Australia.
| | - Honglin Dong
- Department of Vascular Surgery, The Second Hospital of Shanxi Medical University, Taiyuan, Shanxi, China.
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21
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Faundes V, Repetto GM, Valdivia LE. Discovery of novel genetic syndromes in Latin America: Opportunities and challenges. Genet Mol Biol 2024; 47Suppl 1:e20230318. [PMID: 38466870 DOI: 10.1590/1678-4685-gmb-2023-0318] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2023] [Accepted: 02/06/2024] [Indexed: 03/13/2024] Open
Abstract
Latin America (LatAm) has a rich and historically significant role in delineating both novel and well-documented genetic disorders. However, the ongoing advancements in the field of human genetics pose challenges to the relatively slow adaption of LatAm in the field. Here, we describe past and present contributions of LatAm to the discovery of novel genetic disorders, often referred as novel gene-disease associations (NGDA). We also describe the current methodologies for discovery of NGDA, taking into account the latest developments in genomics. We provide an overview of opportunities and challenges for NGDA research in LatAm considering the steps currently performed to identify and validate such associations. Given the multiple and diverse needs of populations and countries in LatAm, it is imperative to foster collaborations amongst patients, indigenous people, clinicians and scientists. Such collaborative effort is essential for sustaining and enhancing the LatAm´s contributions to the field of NGDA.
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Affiliation(s)
- Víctor Faundes
- Universidad de Chile, Instituto de Nutrición y Tecnología de los Alimentos, Laboratorio de Genética y Enfermedades Metabólicas, Santiago, Chile
| | - Gabriela M Repetto
- Universidad del Desarrollo, Facultad de Medicina, Instituto de Ciencias e Innovación en Medicina, Centro de Genética y Genómica, Programa de Enfermedades Raras, Santiago, Chile
| | - Leonardo E Valdivia
- Universidad Mayor, Facultad de Ciencias, Centro de Biología Integrativa, Santiago, Chile
- Universidad Mayor, Facultad de Ciencias, Escuela de Biotecnología, Santiago, Chile
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22
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Rajderkar SS, Paraiso K, Amaral ML, Kosicki M, Cook LE, Darbellay F, Spurrell CH, Osterwalder M, Zhu Y, Wu H, Afzal SY, Blow MJ, Kelman G, Barozzi I, Fukuda-Yuzawa Y, Akiyama JA, Afzal V, Tran S, Plajzer-Frick I, Novak CS, Kato M, Hunter RD, von Maydell K, Wang A, Lin L, Preissl S, Lisgo S, Ren B, Dickel DE, Pennacchio LA, Visel A. Dynamic enhancer landscapes in human craniofacial development. Nat Commun 2024; 15:2030. [PMID: 38448444 PMCID: PMC10917818 DOI: 10.1038/s41467-024-46396-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2023] [Accepted: 02/25/2024] [Indexed: 03/08/2024] Open
Abstract
The genetic basis of human facial variation and craniofacial birth defects remains poorly understood. Distant-acting transcriptional enhancers control the fine-tuned spatiotemporal expression of genes during critical stages of craniofacial development. However, a lack of accurate maps of the genomic locations and cell type-resolved activities of craniofacial enhancers prevents their systematic exploration in human genetics studies. Here, we combine histone modification, chromatin accessibility, and gene expression profiling of human craniofacial development with single-cell analyses of the developing mouse face to define the regulatory landscape of facial development at tissue- and single cell-resolution. We provide temporal activity profiles for 14,000 human developmental craniofacial enhancers. We find that 56% of human craniofacial enhancers share chromatin accessibility in the mouse and we provide cell population- and embryonic stage-resolved predictions of their in vivo activity. Taken together, our data provide an expansive resource for genetic and developmental studies of human craniofacial development.
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Affiliation(s)
- Sudha Sunil Rajderkar
- Environmental Genomics & System Biology Division, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA, 94720, USA
| | - Kitt Paraiso
- Environmental Genomics & System Biology Division, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA, 94720, USA
| | - Maria Luisa Amaral
- Bioinformatics and Systems Biology Graduate Program, University of California San Diego, La Jolla, CA, USA
| | - Michael Kosicki
- Environmental Genomics & System Biology Division, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA, 94720, USA
| | - Laura E Cook
- Environmental Genomics & System Biology Division, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA, 94720, USA
| | - Fabrice Darbellay
- Environmental Genomics & System Biology Division, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA, 94720, USA
- Department of Genetic Medicine and Development, Faculty of Medicine, University of Geneva, 1211, Geneva, Switzerland
| | - Cailyn H Spurrell
- Environmental Genomics & System Biology Division, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA, 94720, USA
| | - Marco Osterwalder
- Environmental Genomics & System Biology Division, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA, 94720, USA
- Department for BioMedical Research (DBMR), University of Bern, 3008, Bern, Switzerland
- Department of Cardiology, Bern University Hospital, Bern, 3010, Switzerland
| | - Yiwen Zhu
- Environmental Genomics & System Biology Division, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA, 94720, USA
| | - Han Wu
- Environmental Genomics & System Biology Division, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA, 94720, USA
| | - Sarah Yasmeen Afzal
- Environmental Genomics & System Biology Division, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA, 94720, USA
- Lucile Packard Children's Hospital, Stanford University, Stanford, CA, 94304, USA
| | - Matthew J Blow
- U.S. Department of Energy Joint Genome Institute, 1 Cyclotron Road, Berkeley, CA, 94720, USA
| | - Guy Kelman
- Environmental Genomics & System Biology Division, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA, 94720, USA
- The Jerusalem Center for Personalized Computational Medicine, Hebrew University of Jerusalem, Jerusalem, Israel
| | - Iros Barozzi
- Environmental Genomics & System Biology Division, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA, 94720, USA
- Center for Cancer Research, Medical University of Vienna, Borschkegasse 8a 1090, Vienna, Austria
- Department of Surgery and Cancer, Imperial College London, London, UK
| | - Yoko Fukuda-Yuzawa
- Environmental Genomics & System Biology Division, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA, 94720, USA
- University Research Management Center, Tohoku University, Sendai, Miyagi, 980-8577, Japan
| | - Jennifer A Akiyama
- Environmental Genomics & System Biology Division, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA, 94720, USA
| | - Veena Afzal
- Environmental Genomics & System Biology Division, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA, 94720, USA
| | - Stella Tran
- Environmental Genomics & System Biology Division, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA, 94720, USA
| | - Ingrid Plajzer-Frick
- Environmental Genomics & System Biology Division, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA, 94720, USA
| | - Catherine S Novak
- Environmental Genomics & System Biology Division, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA, 94720, USA
| | - Momoe Kato
- Environmental Genomics & System Biology Division, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA, 94720, USA
| | - Riana D Hunter
- Environmental Genomics & System Biology Division, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA, 94720, USA
- UC San Francisco, Division of Experimental Medicine, 1001 Potrero Ave, San Francisco, CA, 94110, USA
| | - Kianna von Maydell
- Environmental Genomics & System Biology Division, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA, 94720, USA
| | - Allen Wang
- Center for Epigenomics, University of California San Diego School of Medicine, La Jolla, CA, USA
| | - Lin Lin
- Center for Epigenomics, University of California San Diego School of Medicine, La Jolla, CA, USA
| | - Sebastian Preissl
- Center for Epigenomics, University of California San Diego School of Medicine, La Jolla, CA, USA
- Institute of Experimental and Clinical Pharmacology and Toxicology, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Steven Lisgo
- Biosciences Institute, Faculty of Medical Sciences, Newcastle University, Newcastle, NE1 3BZ, UK
| | - Bing Ren
- Institute of Genome Medicine, Moores Cancer Center, University of California, San Diego School of Medicine, La Jolla, CA, USA
| | - Diane E Dickel
- Environmental Genomics & System Biology Division, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA, 94720, USA
- Octant Inc., Emeryville, CA, 94608, USA
| | - Len A Pennacchio
- Environmental Genomics & System Biology Division, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA, 94720, USA
- U.S. Department of Energy Joint Genome Institute, 1 Cyclotron Road, Berkeley, CA, 94720, USA
- Comparative Biochemistry Program, University of California, Berkeley, CA, 94720, USA
| | - Axel Visel
- Environmental Genomics & System Biology Division, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA, 94720, USA.
- U.S. Department of Energy Joint Genome Institute, 1 Cyclotron Road, Berkeley, CA, 94720, USA.
- School of Natural Sciences, University of California, Merced, CA, USA.
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23
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Yuan X, Huang H, Yu C, Tang Z, Li Y. Network pharmacology and experimental verification study on the mechanism of Hedyotis diffusa Willd in treating colorectal cancer. NAUNYN-SCHMIEDEBERG'S ARCHIVES OF PHARMACOLOGY 2024:10.1007/s00210-024-03024-8. [PMID: 38446216 DOI: 10.1007/s00210-024-03024-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/26/2024] [Accepted: 02/22/2024] [Indexed: 03/07/2024]
Abstract
This study aimed to evaluate the pharmacological mechanism of Hedyotis diffusa Willd against CRC (colorectal cancer) using network pharmacological analysis combined with experimental validation. The active components and potential targets of Hedyotis diffusa Willd were screened from the tax compliance management program public database using network pharmacology. The core anti-CRC targets were screened using a protein-protein interaction (PPI) network. The mRNA and protein expression of core target genes in normal colon and CRC tissues and their relationship with overall CRC survival were evaluated using The Cancer Genome Atlas (TCGA), Human Protein Atlas (HPA), and Gene Expression Profiling Interactive Analysis (GEPIA) databases. Functional and pathway enrichment analyses of the potential targets were performed using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). The first six core targets with stable binding were molecular-docked with the active components quercetin and β-sitosterol. Finally, the results of network pharmacology were verified using in vitro experiments. In total, 149 potential targets were identified by searching for seven types of active components and the intersection of all potential and CRC targets. PPI network analysis showed that ten target genes, including tumor protein p53 (TP53) and recombinant cyclin D1 (CCND1), were pivotal genes. GO enrichment analysis involved 2043 biological processes, 52 cellular components, and 191 molecular functions. KEGG enrichment analysis indicated that the anticancer effects of H. alba were mediated by tumor necrosis factor, interleukin-17, and nuclear factor-κB (NF-κB) signaling pathways. Validation of key targets showed that the validation results for most core genes were consistent with those in this study. Molecular docking revealed that the ten core target proteins could be well combined with quercetin and β-sitosterol and the structure remained stable after binding. The results of the in vitro experiment showed that β-sitosterol inhibited proliferation and induced apoptosis in SW620 cells. This study identified a potential target plant for CRC through network pharmacology and in vitro validation.
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Affiliation(s)
- Xiya Yuan
- Futian District, Shenzhen Hospital of Guangzhou University of Chinese Medicine, 6001 Beihuan Avenue, Shenzhen City, 518034, Guangdong, China
| | - Haifu Huang
- Futian District, Shenzhen Hospital of Guangzhou University of Chinese Medicine, 6001 Beihuan Avenue, Shenzhen City, 518034, Guangdong, China
| | - Changhui Yu
- Futian District, Shenzhen Hospital of Guangzhou University of Chinese Medicine, 6001 Beihuan Avenue, Shenzhen City, 518034, Guangdong, China
| | - Zhenhao Tang
- Futian District, Shenzhen Hospital of Guangzhou University of Chinese Medicine, 6001 Beihuan Avenue, Shenzhen City, 518034, Guangdong, China
| | - Yaoxuan Li
- Futian District, Shenzhen Hospital of Guangzhou University of Chinese Medicine, 6001 Beihuan Avenue, Shenzhen City, 518034, Guangdong, China.
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24
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Li Y, Li L, Wang X, Huang H, Han T. Determining the Mechanism of Banxia Xiexin Decoction for Gastric Cancer Treatment through Network Analysis and Experimental Validation. ACS OMEGA 2024; 9:10119-10131. [PMID: 38463316 PMCID: PMC10918669 DOI: 10.1021/acsomega.3c06330] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/25/2023] [Revised: 01/18/2024] [Accepted: 02/05/2024] [Indexed: 03/12/2024]
Abstract
Gastric cancer (GC) is a widespread malignancy. Banxia Xiexin decoction (BXD) has been used for GC treatment, but the specific mechanisms underlying its therapeutic effects remain controversial. This study used a comprehensive approach to network pharmacology combined with experimental validation to elucidate the mechanism of BXD's anti-GC effects. Initially, we used the UHPLC-LTQ-Orbitrap-MS/MS technology to identify the main chemical constituents of BXD, as well as potential targets associated with these constituents. Then, we employed the Genecard and Online Mendelian Inheritance in Man (OMIM) to determine the targets specifically related to GC. We employed a combination of Gene Ontology (GO), the Kyoto Encyclopedia of Genes and Genomes pathway, and protein-protein interaction analysis to predict the crucial targets of BXD and uncover the pathways involved in its therapeutic effects against GC. The results were subsequently verified through cell experiments. The analysis revealed 174 common targets shared by BXD and GC. GO enrichment analysis highlighted biological processes, such as autophagy, protein kinase activity, and apoptosis. Moreover, the enrichment analysis revealed several significant pathways that serve as the primary mechanisms by which BXD exerts its effects. Notably, these pathways include PI3K-Akt, HIF-1, and Pathways in cancer. Subsequent in vitro experiments demonstrated that BXD effectively hindered GC cell proliferation, stimulated autophagy, and facilitated apoptosis by PI3K-Akt-mTOR signaling pathway regulation. These findings reveal the effectiveness of BXD against GC through diverse components, targets, and pathways, indicating that BXD holds potential therapeutic value in GC treatment. This study uncovers the intricate biological mechanisms that underlie BXD's efficacy in treating GC through the integration of network pharmacology analysis and rigorous in vitro experiments.
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Affiliation(s)
- Yaxing Li
- Pharmacology
of Traditional Chinese Medical Formulas, College of Traditional Chinese
Medicine, Shandong University of Traditional
Chinese Medicine, Jinan, Shandong 250000, China
| | - Ling Li
- Pharmacology
of Traditional Chinese Medical Formulas, College of Traditional Chinese
Medicine, Shandong University of Traditional
Chinese Medicine, Jinan, Shandong 250000, China
| | - Xue Wang
- Pharmacology
of Traditional Chinese Medical Formulas, College of Traditional Chinese
Medicine, Shandong University of Traditional
Chinese Medicine, Jinan, Shandong 250000, China
| | - Hailiang Huang
- Rehabilitation
Medicine and Physiotherapy, School of Rehabilitation Medicine, Shandong University of Traditional Chinese Medicine, Jinan, Shandong 250000, China
| | - Tao Han
- Pharmacology
of Traditional Chinese Medical Formulas, College of Traditional Chinese
Medicine, Shandong University of Traditional
Chinese Medicine, Jinan, Shandong 250000, China
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25
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Lee JY, Oh SH, Keum C, Lee BL, Chung WY. Clinical application of prospective whole-exome sequencing in the diagnosis of genetic disease: Experience of a regional disease center in South Korea. Ann Hum Genet 2024; 88:101-112. [PMID: 37795942 DOI: 10.1111/ahg.12530] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2022] [Revised: 08/29/2023] [Accepted: 09/11/2023] [Indexed: 10/06/2023]
Abstract
INTRODUCTION Next-generation sequencing helps clinicians diagnose patients with suspected genetic disorders. The current study aimed to investigate the diagnostic yield and clinical utility of prospective whole-exome sequencing (WES) in rare diseases. METHODS WES was performed in 92 patients who presented with clinical symptoms suggestive of genetic disorders. The WES data were analyzed using an in-house developed software. The patients' phenotypic characteristics were classified according to the human phenotype ontology. RESULTS WES detected 64 variants, 13 were classified as pathogenic, 26 as likely pathogenic, and 25 as variants of uncertain significance. In 57 patients with these variants, 30 were identified as causal variants. The diagnostic yield was higher in patients with abnormalities in joint mobility and skin morphology than in those with cerebellar hypoplasia/atrophy, epilepsy, global developmental delay, dysmorphic features/facial dysmorphisms, and chronic kidney disease/abnormal renal morphology. CONCLUSION In this study, a WES-based variant interpretation system was employed to provide a definitive diagnosis for 28.3% of the patients suspected of having genetic disorders. WES is particularly useful for diagnosing rare diseases with symptoms that affect more than one system, when targeted genetic panels are difficult to employ.
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Affiliation(s)
- Ja Young Lee
- Department of Laboratory Medicine, Inje University College of Medicine, Busan, South Korea
| | - Seung-Hwan Oh
- Department of Laboratory Medicine, Pusan National University School of Medicine, Yangsan, South Korea
| | | | - Bo Lyun Lee
- Department of Pediatrics, Inje University College of Medicine, Busan, South Korea
| | - Woo Yeong Chung
- Department of Pediatrics, Inje University College of Medicine, Busan, South Korea
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26
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Kong Q, Wang B, Zhong Y, Chen W, Sun J, Liu B, Dong J. Modified Bushen Yiqi Formula mitigates pulmonary inflammation and airway remodeling by inhibiting neutrophils chemotaxis and IL17 signaling pathway in rats with COPD. JOURNAL OF ETHNOPHARMACOLOGY 2024; 321:117497. [PMID: 38048893 DOI: 10.1016/j.jep.2023.117497] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/10/2023] [Revised: 11/15/2023] [Accepted: 11/22/2023] [Indexed: 12/06/2023]
Abstract
ETHNOPHARMACOLOGICAL RELEVANCE Chronic obstructive pulmonary disease (COPD) is a major global health concern characterized by pulmonary inflammation and airway remodeling. Traditional Chinese medicine, such as Modified Jiawei Bushen Yiqi Formula (MBYF), has been used as a complementary therapy for COPD in China. AIM OF THE STUDY To investigate the therapeutic potential of MBYF in a rat model of COPD induced by cigarette smoke (CS) exposure and explore the underlying mechanism. MATERIALS AND METHODS The COPD rat model was established through 24 weeks of CS exposure, with MBYF administration starting in the 9th week. Pulmonary function, histological analysis, inflammatory cell count and molecular assays were employed to assess the effects of MBYF on airway remodeling, pulmonary inflammation, neutrophils chemotaxis and the IL17 signaling pathway. RESULTS MBYF treatment effectively delayed airway remodeling, as evidenced by improved pulmonary function parameters. Histological examination and bronchoalveolar lavage fluid analysis revealed that MBYF mitigated CS-induced pulmonary inflammation by reducing inflammatory cell infiltration. Pharmacological network analysis suggested that MBYF may act through the IL17 signaling pathway to regulate inflammatory responses. RNA-sequencing and molecular assays indicated that MBYF inhibited neutrophils chemotaxis through downregulating the CXCL1/CXCL5/CXCL8-CXCR2 axis, and suppressed IL17A, IL17F and its downstream cytokines, including IL6, TNFα, IL1β, and COX2. Furthermore, MBYF inhibited the activation of NF-κB and MAPKs in the IL17 signaling pathway. CONCLUSION MBYF exhibits potential as an adjunct or alternative treatment for COPD, effectively mitigating CS-induced pulmonary inflammation and airway remodeling through the inhibition of neutrophil chemotaxis and IL17 signaling pathway.
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Affiliation(s)
- Qing Kong
- Department of Integrative Medicine, Huashan Hospital, Fudan University, Shanghai, China; Institutes of Integrative Medicine, Fudan University, Shanghai, China; Department of Dermatology, Huashan Hospital, Fudan University, China.
| | - Bin Wang
- Department of Integrative Medicine, Huashan Hospital, Fudan University, Shanghai, China; Institutes of Integrative Medicine, Fudan University, Shanghai, China.
| | - Yuanyuan Zhong
- Department of Integrative Medicine, Huashan Hospital, Fudan University, Shanghai, China; Institutes of Integrative Medicine, Fudan University, Shanghai, China.
| | - Wenjing Chen
- Department of Integrative Medicine, Huashan Hospital, Fudan University, Shanghai, China; Institutes of Integrative Medicine, Fudan University, Shanghai, China.
| | - Jing Sun
- Department of Integrative Medicine, Huashan Hospital, Fudan University, Shanghai, China; Institutes of Integrative Medicine, Fudan University, Shanghai, China.
| | - Baojun Liu
- Department of Integrative Medicine, Huashan Hospital, Fudan University, Shanghai, China; Institutes of Integrative Medicine, Fudan University, Shanghai, China.
| | - Jingcheng Dong
- Department of Integrative Medicine, Huashan Hospital, Fudan University, Shanghai, China; Institutes of Integrative Medicine, Fudan University, Shanghai, China.
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Wang M, Li R, Bai M, Zhou X. Exploration of Ginkgo biloba leaves on non-small cell lung cancer based on network pharmacology and molecular docking. Medicine (Baltimore) 2024; 103:e37218. [PMID: 38428907 PMCID: PMC10906577 DOI: 10.1097/md.0000000000037218] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/13/2023] [Accepted: 01/18/2024] [Indexed: 03/03/2024] Open
Abstract
BACKGROUND Pharmacological studies have found Ginkgo biloba leaves have the effect of inhibiting neoplasms, it is clinically used in treating various neoplasms. However, the mechanism of Ginkgo biloba leaves in treating non-small cell lung cancer (NSCLC) remains unclear. METHODS The active components and corresponding targets of Ginkgo biloba leaves were obtained from the traditional Chinese medicine systems pharmacology database and analysis platform (TCMSP) database, and the targets of NSCLC were obtained from the GeneCards, OMIM, TTD, and DrugBank databases. The common targets of NSCLC and Ginkgo biloba leaves were obtained from VENNY 2.1.0. The STRING database was utilized to construct protein-protein intersections, by using the Cytoscape 3.7.1 software, the protein-protein intersection was optimized and the drug-disease network diagram was constructed. The DAVID database was utilized to perform GO and KEGG analysis. Finally, The Autodock Vina software was used to perform molecular docking of core components and targets. RESULTS The key components of Ginkgo biloba leaves in treating NSCLC include quercetin, luteolin, and kaempferol, which may act on Tp53, AKT1, and TNF. Bioinformatic annotation analysis results suggest that Ginkgo biloba leaves may implicated in PI3K-AKT and MAPK signaling pathways. The molecular docking results show the firm affinity between key ingredients and targets. CONCLUSION The potential mechanism of Ginkgo biloba leaves in treating NSCLC has been discussed in this study, which provides a theoretical basis for the clinical treatment of NSCLC and further experimental validation.
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Affiliation(s)
- Mingxiao Wang
- Respiratory Department, The Second Affiliated Hospital of Guizhou University of Traditional Chinese Medicine, Guiyang, China
| | - Ruochen Li
- Respiratory Department, The Second Affiliated Hospital of Guizhou University of Traditional Chinese Medicine, Guiyang, China
| | - Moiuqi Bai
- Respiratory Department, The Second Affiliated Hospital of Guizhou University of Traditional Chinese Medicine, Guiyang, China
| | - Xun Zhou
- Respiratory Department, The Second Affiliated Hospital of Guizhou University of Traditional Chinese Medicine, Guiyang, China
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Her Y, Pascual DM, Goldstone-Joubert Z, Marcogliese PC. Variant functional assessment in Drosophila by overexpression: what can we learn? Genome 2024. [PMID: 38412472 DOI: 10.1139/gen-2023-0135] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/29/2024]
Abstract
The last decade has been highlighted by the increased use of next-generation DNA sequencing technology to identify novel human disease genes. A critical downstream part of this process is assigning function to a candidate gene variant. Functional studies in Drosophila melanogaster, the common fruit fly, have made a prominent contribution in annotating variant impact in an in vivo system. The use of patient-derived knock-in flies or rescue-based, "humanization", approaches are novel and valuable strategies in variant testing but have been recently widely reviewed. An often-overlooked strategy for determining variant impact has been GAL4/upstream activation sequence-mediated tissue-defined overexpression in Drosophila. This mini-review will summarize the recent contribution of ectopic overexpression of human reference and variant cDNA in Drosophila to assess variant function, interpret the consequence of the variant, and in some cases infer biological mechanisms.
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Affiliation(s)
- Yina Her
- Department of Biochemistry and Medical Genetics, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
- Children's Hospital Research Institute of Manitoba (CHRIM), University of Manitoba, Winnipeg, MB, Canada
| | - Danielle M Pascual
- Department of Biochemistry and Medical Genetics, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
- Children's Hospital Research Institute of Manitoba (CHRIM), University of Manitoba, Winnipeg, MB, Canada
| | - Zoe Goldstone-Joubert
- Department of Biochemistry and Medical Genetics, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
- Children's Hospital Research Institute of Manitoba (CHRIM), University of Manitoba, Winnipeg, MB, Canada
| | - Paul C Marcogliese
- Department of Biochemistry and Medical Genetics, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
- Children's Hospital Research Institute of Manitoba (CHRIM), University of Manitoba, Winnipeg, MB, Canada
- Excellence in Neurodevelopment and Rehabilitation Research in Child Health (ENRRICH) Theme, Winnipeg, MB, Canada
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Rahit KMTH, Avramovic V, Chong JX, Tarailo-Graovac M. GPAD: a natural language processing-based application to extract the gene-disease association discovery information from OMIM. BMC Bioinformatics 2024; 25:84. [PMID: 38413851 PMCID: PMC10898068 DOI: 10.1186/s12859-024-05693-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2023] [Accepted: 02/09/2024] [Indexed: 02/29/2024] Open
Abstract
BACKGROUND Thousands of genes have been associated with different Mendelian conditions. One of the valuable sources to track these gene-disease associations (GDAs) is the Online Mendelian Inheritance in Man (OMIM) database. However, most of the information in OMIM is textual, and heterogeneous (e.g. summarized by different experts), which complicates automated reading and understanding of the data. Here, we used Natural Language Processing (NLP) to make a tool (Gene-Phenotype Association Discovery (GPAD)) that could syntactically process OMIM text and extract the data of interest. RESULTS GPAD applies a series of language-based techniques to the text obtained from OMIM API to extract GDA discovery-related information. GPAD can inform when a particular gene was associated with a specific phenotype, as well as the type of validation-whether through model organisms or cohort-based patient-matching approaches-for such an association. GPAD extracted data was validated with published reports and was compared with large language model. Utilizing GPAD's extracted data, we analysed trends in GDA discoveries, noting a significant increase in their rate after the introduction of exome sequencing, rising from an average of about 150-250 discoveries each year. Contrary to hopes of resolving most GDAs for Mendelian disorders by now, our data indicate a substantial decline in discovery rates over the past five years (2017-2022). This decline appears to be linked to the increasing necessity for larger cohorts to substantiate GDAs. The rising use of zebrafish and Drosophila as model organisms in providing evidential support for GDAs is also observed. CONCLUSIONS GPAD's real-time analyzing capacity offers an up-to-date view of GDA discovery and could help in planning and managing the research strategies. In future, this solution can be extended or modified to capture other information in OMIM and scientific literature.
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Affiliation(s)
- K M Tahsin Hassan Rahit
- Departments of Biochemistry, Molecular Biology and Medical Genetics, Cumming School of Medicine, University of Calgary, Calgary, AB, T2N 4N1, Canada
- Alberta Children's Hospital Research Institute, University of Calgary, Calgary, AB, T2N 4N1, Canada
| | - Vladimir Avramovic
- Departments of Biochemistry, Molecular Biology and Medical Genetics, Cumming School of Medicine, University of Calgary, Calgary, AB, T2N 4N1, Canada
- Alberta Children's Hospital Research Institute, University of Calgary, Calgary, AB, T2N 4N1, Canada
| | - Jessica X Chong
- Division of Genetic Medicine, Department of Pediatrics, University of Washington, Seattle, WA, 98195, USA
- Brotman-Baty Institute, Seattle, WA, 98195, USA
| | - Maja Tarailo-Graovac
- Departments of Biochemistry, Molecular Biology and Medical Genetics, Cumming School of Medicine, University of Calgary, Calgary, AB, T2N 4N1, Canada.
- Alberta Children's Hospital Research Institute, University of Calgary, Calgary, AB, T2N 4N1, Canada.
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Yan Z, Ge F, Liu Y, Zhang Y, Li F, Song J, Yu DJ. TransEFVP: A Two-Stage Approach for the Prediction of Human Pathogenic Variants Based on Protein Sequence Embedding Fusion. J Chem Inf Model 2024; 64:1407-1418. [PMID: 38334115 DOI: 10.1021/acs.jcim.3c02019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/10/2024]
Abstract
Studying the effect of single amino acid variations (SAVs) on protein structure and function is integral to advancing our understanding of molecular processes, evolutionary biology, and disease mechanisms. Screening for deleterious variants is one of the crucial issues in precision medicine. Here, we propose a novel computational approach, TransEFVP, based on large-scale protein language model embeddings and a transformer-based neural network to predict disease-associated SAVs. The model adopts a two-stage architecture: the first stage is designed to fuse different feature embeddings through a transformer encoder. In the second stage, a support vector machine model is employed to quantify the pathogenicity of SAVs after dimensionality reduction. The prediction performance of TransEFVP on blind test data achieves a Matthews correlation coefficient of 0.751, an F1-score of 0.846, and an area under the receiver operating characteristic curve of 0.871, higher than the existing state-of-the-art methods. The benchmark results demonstrate that TransEFVP can be explored as an accurate and effective SAV pathogenicity prediction method. The data and codes for TransEFVP are available at https://github.com/yzh9607/TransEFVP/tree/master for academic use.
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Affiliation(s)
- Zihao Yan
- School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing 210094, PR China
| | - Fang Ge
- State Key Laboratory of Organic Electronics and lnformation Displays & lnstitute of Advanced Materials (IAM), Nanjing University of Posts & Telecommunications, 9 Wenyuan Road, Nanjing 210023, PR China
| | - Yan Liu
- Department of Computer Science, Yangzhou University, Yangzhou 225100, PR China
| | - Yumeng Zhang
- School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai 200240, PR China
- Monash Biomedicine Discovery Institute and Department of Biochemistry and Molecular Biology, Monash University, Melbourne, Victoria 3800, Australia
| | - Fuyi Li
- South Australian immunoGENomics Cancer Institute (SAiGENCI), Faculty of Health and Medical Sciences, The University of Adelaide, Adelaide, South Australia 5005, Australia
- The Peter Doherty Institute for Infection and Immunity, The University of Melbourne, Melbourne, Victoria 3000, Australia
| | - Jiangning Song
- Monash Biomedicine Discovery Institute and Department of Biochemistry and Molecular Biology, Monash University, Melbourne, Victoria 3800, Australia
| | - Dong-Jun Yu
- School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing 210094, PR China
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Plessner M, Thiele L, Hofhuis J, Thoms S. Tissue-specific roles of peroxisomes revealed by expression meta-analysis. Biol Direct 2024; 19:14. [PMID: 38365851 PMCID: PMC10873952 DOI: 10.1186/s13062-024-00458-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2023] [Accepted: 01/30/2024] [Indexed: 02/18/2024] Open
Abstract
Peroxisomes are primarily studied in the brain, kidney, and liver due to the conspicuous tissue-specific pathology of peroxisomal biogenesis disorders. In contrast, little is known about the role of peroxisomes in other tissues such as the heart. In this meta-analysis, we explore mitochondrial and peroxisomal gene expression on RNA and protein levels in the brain, heart, kidney, and liver, focusing on lipid metabolism. Further, we evaluate a potential developmental and heart region-dependent specificity of our gene set. We find marginal expression of the enzymes for peroxisomal fatty acid oxidation in cardiac tissue in comparison to the liver or cardiac mitochondrial β-oxidation. However, the expression of peroxisome biogenesis proteins in the heart is similar to other tissues despite low levels of peroxisomal fatty acid oxidation. Strikingly, peroxisomal targeting signal type 2-containing factors and plasmalogen biosynthesis appear to play a fundamental role in explaining the essential protective and supporting functions of cardiac peroxisomes.
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Affiliation(s)
- Matthias Plessner
- Department of Biochemistry and Molecular Medicine, Medical School OWL, Bielefeld University, Bielefeld, Germany
| | - Leonie Thiele
- Department of Biochemistry and Molecular Medicine, Medical School OWL, Bielefeld University, Bielefeld, Germany
| | - Julia Hofhuis
- Department of Biochemistry and Molecular Medicine, Medical School OWL, Bielefeld University, Bielefeld, Germany
| | - Sven Thoms
- Department of Biochemistry and Molecular Medicine, Medical School OWL, Bielefeld University, Bielefeld, Germany.
- Department of Child and Adolescent Health, University Medical Center, Göttingen, Germany.
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32
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Chi W, Kiskinis E. Integrative analysis of epilepsy-associated genes reveals expression-phenotype correlations. Sci Rep 2024; 14:3587. [PMID: 38351047 PMCID: PMC10864290 DOI: 10.1038/s41598-024-53494-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2023] [Accepted: 02/01/2024] [Indexed: 02/16/2024] Open
Abstract
Epilepsy is a highly prevalent neurological disorder characterized by recurrent seizures. Patients exhibit broad genetic, molecular, and clinical diversity involving mild to severe comorbidities. The factors that contribute to this phenotypic diversity remain unclear. Here we used publicly available datasets to systematically interrogate the expression pattern of 230 epilepsy-associated genes across human tissues, developmental stages, and central nervous system (CNS) cellular subtypes. We grouped genes based on their curated phenotypes into 3 broad classes: core epilepsy genes (CEG), where seizures are the dominant phenotype, developmental and epileptic encephalopathy genes (DEEG) that are associated with developmental and epileptic encephalopathy, and seizure-related genes (SRG), which are characterized by the presence of seizures and gross brain malformations. We find that compared to the other two groups of genes, DEEGs are highly expressed within the adult CNS, exhibit the highest and most dynamic expression in various brain regions across development, and are significantly enriched in GABAergic neurons. Our analysis provides an overview of the expression pattern of epilepsy-associated genes with spatiotemporal resolution and establishes a broad expression-phenotype correlation in epilepsy.
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Affiliation(s)
- Wanhao Chi
- The Ken & Ruth Davee Department of Neurology, Feinberg School of Medicine, Northwestern University, Chicago, IL, 60611, USA.
| | - Evangelos Kiskinis
- The Ken & Ruth Davee Department of Neurology, Feinberg School of Medicine, Northwestern University, Chicago, IL, 60611, USA.
- Simpson Querrey Institute, Northwestern University, Chicago, IL, 60611, USA.
- Department of Neuroscience, Feinberg School of Medicine, Northwestern University, Chicago, IL, 60611, USA.
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Asadi-Pooya AA, Malekpour M, Taherifard E, Mallahzadeh A, Farjoud Kouhanjani M. Coexistence of temporal lobe epilepsy and idiopathic generalized epilepsy. Epilepsy Behav 2024; 151:109602. [PMID: 38160579 DOI: 10.1016/j.yebeh.2023.109602] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/12/2023] [Revised: 12/07/2023] [Accepted: 12/21/2023] [Indexed: 01/03/2024]
Abstract
OBJECTIVE We investigated the frequency of coexistence of temporal lobe epilepsy (TLE) and idiopathic generalized epilepsy (IGE) in a retrospective database study. We also explored the underlying pathomechanisms of the coexistence of TLE and IGE based on the available information, using bioinformatics tools. METHODS The first phase of the investigation was a retrospective study. All patients with an electro-clinical diagnosis of epilepsy were studied at the outpatient epilepsy clinic at Shiraz University of Medical Sciences, Shiraz, Iran, from 2008 until 2023. In the second phase, we searched the following databases for genetic variations (epilepsy-associated genetic polymorphisms) that are associated with TLE or syndromes of IGE: DisGeNET, genome-wide association study (GWAS) Catalog, epilepsy genetic association database (epiGAD), and UniProt. We also did a separate literature search using PubMed. RESULTS In total, 3760 patients with epilepsy were registered at our clinic; four patients with definitely mixed TLE and IGE were identified; 0.1% of all epilepsies. We could identify that rs1883415 of ALDH5A1, rs137852779 of EFHC1, rs211037 of GABRG2, rs1130183 of KCNJ10, and rs1045642 of ABCB1 genes are shared between TLE and syndromes of IGE. CONCLUSION While coexistence of TLE and IGE is a rare phenomenon, this could be explained by shared genetic variations.
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Affiliation(s)
- Ali A Asadi-Pooya
- Epilepsy Research Center, Shiraz University of Medical Sciences, Shiraz, Iran; Jefferson Comprehensive Epilepsy Center, Department of Neurology, Thomas Jefferson University, Philadelphia, PA, USA.
| | - Mahdi Malekpour
- Epilepsy Research Center, Shiraz University of Medical Sciences, Shiraz, Iran
| | - Ehsan Taherifard
- Epilepsy Research Center, Shiraz University of Medical Sciences, Shiraz, Iran
| | - Arashk Mallahzadeh
- Epilepsy Research Center, Shiraz University of Medical Sciences, Shiraz, Iran
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Biglari S, Moghaddam AS, Tabatabaiefar MA, Sherkat R, Youssefian L, Saeidian AH, Vahidnezhad F, Tsoi LC, Gudjonsson JE, Hakonarson H, Casanova JL, Béziat V, Jouanguy E, Vahidnezhad H. Monogenic etiologies of persistent human papillomavirus infections: A comprehensive systematic review. Genet Med 2024; 26:101028. [PMID: 37978863 PMCID: PMC10922824 DOI: 10.1016/j.gim.2023.101028] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2023] [Revised: 11/06/2023] [Accepted: 11/08/2023] [Indexed: 11/19/2023] Open
Abstract
PURPOSE Persistent human papillomavirus infection (PHPVI) causes cutaneous, anogenital, and mucosal warts. Cutaneous warts include common warts, Treeman syndrome, and epidermodysplasia verruciformis, among others. Although more reports of monogenic predisposition to PHPVI have been published with the development of genomic technologies, genetic testing is rarely incorporated into clinical assessments. To encourage broader molecular testing, we compiled a list of the various monogenic etiologies of PHPVI. METHODS We conducted a systematic literature review to determine the genetic, immunological, and clinical characteristics of patients with PHPVI. RESULTS The inclusion criteria were met by 261 of 40,687 articles. In 842 patients, 83 PHPVI-associated genes were identified, including 42, 6, and 35 genes with strong, moderate, and weak evidence for causality, respectively. Autosomal recessive inheritance predominated (69%). PHPVI onset age was 10.8 ± 8.6 years, with an interquartile range of 5 to 14 years. GATA2,IL2RG,DOCK8, CXCR4, TMC6, TMC8, and CIB1 are the most frequently reported PHPVI-associated genes with strong causality. Most genes (74 out of 83) belong to a catalog of 485 inborn errors of immunity-related genes, and 40 genes (54%) are represented in the nonsyndromic and syndromic combined immunodeficiency categories. CONCLUSION PHPVI has at least 83 monogenic etiologies and a genetic diagnosis is essential for effective management.
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Affiliation(s)
- Sajjad Biglari
- Department of Genetics and Molecular Biology, School of Medicine, Isfahan University of Medical Sciences, Isfahan, Iran; Division of Human Genetics, Children's Hospital of Philadelphia, Philadelphia, PA; Center for Applied Genomics, Children's Hospital of Philadelphia, Philadelphia, PA
| | | | - Mohammad Amin Tabatabaiefar
- Department of Genetics and Molecular Biology, School of Medicine, Isfahan University of Medical Sciences, Isfahan, Iran
| | - Roya Sherkat
- Immunodeficiency Diseases Research Center, Isfahan University of Medical Sciences, Isfahan, Iran
| | - Leila Youssefian
- Department of Pathology and Laboratory Medicine, UCLA Clinical Genomics Center, David Geffen School of Medicine at UCLA, Los Angeles, CA
| | - Amir Hossein Saeidian
- Division of Human Genetics, Children's Hospital of Philadelphia, Philadelphia, PA; Center for Applied Genomics, Children's Hospital of Philadelphia, Philadelphia, PA
| | | | - Lam C Tsoi
- Department of Dermatology, University of Michigan, Ann Arbor, MI
| | | | - Hakon Hakonarson
- Division of Human Genetics, Children's Hospital of Philadelphia, Philadelphia, PA; Center for Applied Genomics, Children's Hospital of Philadelphia, Philadelphia, PA; Department of Pediatrics, University of Pennsylvania, Perelman School of Medicine, Philadelphia, PA
| | - Jean-Laurent Casanova
- St Giles Laboratory of Human Genetics of Infectious Diseases, Rockefeller Branch, Rockefeller University, New York, NY; Laboratory of Human Genetics of Infectious Diseases, Necker Branch, Inserm U1163, Necker Hospital for Sick Children, Paris, France; Imagine Institute, Paris Cité University, France; Department of Pediatrics, Necker Hospital for Sick Children, Paris, France, EU; Howard Hughes Medical Institute, Chevy Chase, MD
| | - Vivien Béziat
- St Giles Laboratory of Human Genetics of Infectious Diseases, Rockefeller Branch, Rockefeller University, New York, NY; Laboratory of Human Genetics of Infectious Diseases, Necker Branch, Inserm U1163, Necker Hospital for Sick Children, Paris, France; Imagine Institute, Paris Cité University, France
| | - Emmanuelle Jouanguy
- St Giles Laboratory of Human Genetics of Infectious Diseases, Rockefeller Branch, Rockefeller University, New York, NY; Laboratory of Human Genetics of Infectious Diseases, Necker Branch, Inserm U1163, Necker Hospital for Sick Children, Paris, France; Imagine Institute, Paris Cité University, France
| | - Hassan Vahidnezhad
- Division of Human Genetics, Children's Hospital of Philadelphia, Philadelphia, PA; Center for Applied Genomics, Children's Hospital of Philadelphia, Philadelphia, PA; Department of Pediatrics, University of Pennsylvania, Perelman School of Medicine, Philadelphia, PA.
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Jose M, Fasaludeen A, Pavuluri H, Rudrabhatla PK, Chandrasekharan SV, Jose J, Banerjee M, Sundaram S, Radhakrishnan A, Menon RN. Metabolic causes of pediatric developmental & epileptic encephalopathies (DEE)- genetic variant analysis in a south Indian cohort. Seizure 2024; 115:20-27. [PMID: 38183824 DOI: 10.1016/j.seizure.2023.12.017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2023] [Revised: 12/12/2023] [Accepted: 12/25/2023] [Indexed: 01/08/2024] Open
Abstract
PURPOSE Drug-resistant epilepsy is seen in patients with inborn errors of metabolism and metabolic dysfunction in neurons is crucial to brain disorders associated with psychomotor impairment. Diagnostic rates of metabolic causes of developmental and epileptic encephalopathy (DEE) using next generation sequencing have been rarely studied in literature. METHODS A prospective hospital study was carried out in 384 children with DEE, who underwent genetic testing. Metabolic disorders were evaluated with biochemical blood/urine assays and when required CSF estimations performed. RESULTS A total of 154 pathogenic/likely pathogenic variants in 384 children were identified. Out of 384 children, 89 were clinically suspected to have probable or possible metabolic disorders. Pathogenic/likely pathogenic variants in metabolic genes were identified in 39 out of 89 (43.8 %) and promising VUS in 28 (31.4 %). These included variants for progressive myoclonus epilepsies (21; 53.8 %), DEE with focal/multifocal seizures (8; 20.5 %), generalized epilepsy (5;12.8 %), early myoclonic encephalopathy (2; 5.1 %), LGS (1; 2.6 %) and West syndrome (2; 5.1 %). CONCLUSION Our cohort demonstrates for the first time from the Indian subcontinent that identification of metabolic variants can guide investigations and has therapeutic implications in patients with variable DEE phenotypes. A high utility is noted with regard to diagnosis and prognostication, given the low yield of available biochemical tests, indicating cost-effectiveness of this approach.
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Affiliation(s)
- Manna Jose
- Department of Neurology, Sree Chitra Tirunal Institute for Medical Sciences and Technology, Trivandrum, Kerala, India
| | - Alfiya Fasaludeen
- Department of Neurology, Sree Chitra Tirunal Institute for Medical Sciences and Technology, Trivandrum, Kerala, India
| | - Harini Pavuluri
- Department of Neurology, Sree Chitra Tirunal Institute for Medical Sciences and Technology, Trivandrum, Kerala, India
| | - Pavan Kumar Rudrabhatla
- Department of Neurology, Sree Chitra Tirunal Institute for Medical Sciences and Technology, Trivandrum, Kerala, India
| | - Soumya V Chandrasekharan
- Department of Neurology, Sree Chitra Tirunal Institute for Medical Sciences and Technology, Trivandrum, Kerala, India
| | - Jithu Jose
- Department of Neurology, Sree Chitra Tirunal Institute for Medical Sciences and Technology, Trivandrum, Kerala, India
| | - Moinak Banerjee
- Human Molecular Genetics Laboratory, Rajiv Gandhi Centre for Biotechnology, Trivandrum, Kerala, India
| | - Soumya Sundaram
- Department of Neurology, Sree Chitra Tirunal Institute for Medical Sciences and Technology, Trivandrum, Kerala, India
| | - Ashalatha Radhakrishnan
- Department of Neurology, Sree Chitra Tirunal Institute for Medical Sciences and Technology, Trivandrum, Kerala, India
| | - Ramshekhar N Menon
- Department of Neurology, Sree Chitra Tirunal Institute for Medical Sciences and Technology, Trivandrum, Kerala, India.
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Weng C, Faure AJ, Escobedo A, Lehner B. The energetic and allosteric landscape for KRAS inhibition. Nature 2024; 626:643-652. [PMID: 38109937 PMCID: PMC10866706 DOI: 10.1038/s41586-023-06954-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2022] [Accepted: 12/07/2023] [Indexed: 12/20/2023]
Abstract
Thousands of proteins have been validated genetically as therapeutic targets for human diseases1. However, very few have been successfully targeted, and many are considered 'undruggable'. This is particularly true for proteins that function via protein-protein interactions-direct inhibition of binding interfaces is difficult and requires the identification of allosteric sites. However, most proteins have no known allosteric sites, and a comprehensive allosteric map does not exist for any protein. Here we address this shortcoming by charting multiple global atlases of inhibitory allosteric communication in KRAS. We quantified the effects of more than 26,000 mutations on the folding of KRAS and its binding to six interaction partners. Genetic interactions in double mutants enabled us to perform biophysical measurements at scale, inferring more than 22,000 causal free energy changes. These energy landscapes quantify how mutations tune the binding specificity of a signalling protein and map the inhibitory allosteric sites for an important therapeutic target. Allosteric propagation is particularly effective across the central β-sheet of KRAS, and multiple surface pockets are genetically validated as allosterically active, including a distal pocket in the C-terminal lobe of the protein. Allosteric mutations typically inhibit binding to all tested effectors, but they can also change the binding specificity, revealing the regulatory, evolutionary and therapeutic potential to tune pathway activation. Using the approach described here, it should be possible to rapidly and comprehensively identify allosteric target sites in many proteins.
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Affiliation(s)
- Chenchun Weng
- Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Barcelona, Spain
| | - Andre J Faure
- Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Barcelona, Spain
| | - Albert Escobedo
- Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Barcelona, Spain
| | - Ben Lehner
- Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Barcelona, Spain.
- University Pompeu Fabra (UPF), Barcelona, Spain.
- Institució Catalana de Recerca i Estudis Avançats (ICREA), Barcelona, Spain.
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, UK.
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Greenfest‐Allen E, Valladares O, Kuksa PP, Gangadharan P, Lee W, Cifello J, Katanic Z, Kuzma AB, Wheeler N, Bush WS, Leung YY, Schellenberg G, Stoeckert CJ, Wang L. NIAGADS Alzheimer's GenomicsDB: A resource for exploring Alzheimer's disease genetic and genomic knowledge. Alzheimers Dement 2024; 20:1123-1136. [PMID: 37881831 PMCID: PMC10916966 DOI: 10.1002/alz.13509] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2023] [Revised: 08/25/2023] [Accepted: 09/21/2023] [Indexed: 10/27/2023]
Abstract
INTRODUCTION The National Institute on Aging Genetics of Alzheimer's Disease Data Storage Site Alzheimer's Genomics Database (GenomicsDB) is a public knowledge base of Alzheimer's disease (AD) genetic datasets and genomic annotations. METHODS GenomicsDB uses a custom systems architecture to adopt and enforce rigorous standards that facilitate harmonization of AD-relevant genome-wide association study summary statistics datasets with functional annotations, including over 230 million annotated variants from the AD Sequencing Project. RESULTS GenomicsDB generates interactive reports compiled from the harmonized datasets and annotations. These reports contextualize AD-risk associations in a broader functional genomic setting and summarize them in the context of functionally annotated genes and variants. DISCUSSION Created to make AD-genetics knowledge more accessible to AD researchers, the GenomicsDB is designed to guide users unfamiliar with genetic data in not only exploring but also interpreting this ever-growing volume of data. Scalable and interoperable with other genomics resources using data technology standards, the GenomicsDB can serve as a central hub for research and data analysis on AD and related dementias. HIGHLIGHTS The National Institute on Aging Genetics of Alzheimer's Disease Data Storage Site (NIAGADS) offers to the public a unique, disease-centric collection of AD-relevant GWAS summary statistics datasets. Interpreting these data is challenging and requires significant bioinformatics expertise to standardize datasets and harmonize them with functional annotations on genome-wide scales. The NIAGADS Alzheimer's GenomicsDB helps overcome these challenges by providing a user-friendly public knowledge base for AD-relevant genetics that shares harmonized, annotated summary statistics datasets from the NIAGADS repository in an interpretable, easily searchable format.
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Affiliation(s)
- Emily Greenfest‐Allen
- Penn Neurodegeneration Genomics CenterPerelman School of MedicineUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
- Institute for Biomedical InformaticsPerelman School of MedicineUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
- Department of Pathology and Laboratory MedicinePerelman School of MedicineUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Otto Valladares
- Penn Neurodegeneration Genomics CenterPerelman School of MedicineUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
- Institute for Biomedical InformaticsPerelman School of MedicineUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
- Department of Pathology and Laboratory MedicinePerelman School of MedicineUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Pavel P. Kuksa
- Penn Neurodegeneration Genomics CenterPerelman School of MedicineUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
- Institute for Biomedical InformaticsPerelman School of MedicineUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
- Department of Pathology and Laboratory MedicinePerelman School of MedicineUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Prabhakaran Gangadharan
- Penn Neurodegeneration Genomics CenterPerelman School of MedicineUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
- Institute for Biomedical InformaticsPerelman School of MedicineUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
- Department of Pathology and Laboratory MedicinePerelman School of MedicineUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Wan‐Ping Lee
- Penn Neurodegeneration Genomics CenterPerelman School of MedicineUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
- Institute for Biomedical InformaticsPerelman School of MedicineUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
- Department of Pathology and Laboratory MedicinePerelman School of MedicineUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Jeffrey Cifello
- Penn Neurodegeneration Genomics CenterPerelman School of MedicineUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
- Department of Pathology and Laboratory MedicinePerelman School of MedicineUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Zivadin Katanic
- Penn Neurodegeneration Genomics CenterPerelman School of MedicineUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
- Institute for Biomedical InformaticsPerelman School of MedicineUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
- Department of Pathology and Laboratory MedicinePerelman School of MedicineUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Amanda B. Kuzma
- Penn Neurodegeneration Genomics CenterPerelman School of MedicineUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
- Institute for Biomedical InformaticsPerelman School of MedicineUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
- Department of Pathology and Laboratory MedicinePerelman School of MedicineUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Nicholas Wheeler
- Cleveland Institute for Computational BiologyDepartment of Population and Quantitative Health SciencesCase Western Reserve UniversityClevelandOhioUSA
| | - William S. Bush
- Cleveland Institute for Computational BiologyDepartment of Population and Quantitative Health SciencesCase Western Reserve UniversityClevelandOhioUSA
| | - Yuk Yee Leung
- Penn Neurodegeneration Genomics CenterPerelman School of MedicineUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
- Institute for Biomedical InformaticsPerelman School of MedicineUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
- Department of Pathology and Laboratory MedicinePerelman School of MedicineUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Gerard Schellenberg
- Penn Neurodegeneration Genomics CenterPerelman School of MedicineUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
- Institute for Biomedical InformaticsPerelman School of MedicineUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
- Department of Pathology and Laboratory MedicinePerelman School of MedicineUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Christian J. Stoeckert
- Institute for Biomedical InformaticsPerelman School of MedicineUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
- Department of GeneticsPerelman School of MedicineUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Li‐San Wang
- Penn Neurodegeneration Genomics CenterPerelman School of MedicineUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
- Institute for Biomedical InformaticsPerelman School of MedicineUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
- Department of Pathology and Laboratory MedicinePerelman School of MedicineUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
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Srinivasan M, Gangurde A, Chandane AY, Tagalpallewar A, Pawar A, Baheti AM. Integrating network pharmacology and in silico analysis deciphers Withaferin-A's anti-breast cancer potential via hedgehog pathway and target network interplay. Brief Bioinform 2024; 25:bbae032. [PMID: 38446743 PMCID: PMC10917074 DOI: 10.1093/bib/bbae032] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2023] [Revised: 12/09/2023] [Accepted: 12/22/2023] [Indexed: 03/08/2024] Open
Abstract
This study examines the remarkable effectiveness of Withaferin-A (WA), a withanolide obtained from Withania somnifera (Ashwagandha), in encountering the mortiferous breast malignancy, a global peril. The predominant objective is to investigate WA's intrinsic target proteins and hedgehog (Hh) pathway proteins in breast cancer targeting through the application of in silico computational techniques and network pharmacology predictions. The databases and webtools like Swiss target prediction, GeneCards, DisGeNet and Online Mendelian Inheritance in Man were exploited to identify the common target proteins. The culmination of the WA network and protein-protein interaction network were devised using Stitch and String web tools, through which the drug-target network of 30 common proteins was constructed employing Cytoscape-version 3.9. Enrichment analysis was performed by incorporating Gprofiler, Metascape and Cytoscape plugins. David compounded the Gene Ontology and Kyoto Encyclopedia of Genes and Genomes, and enrichment was computed through bioinformatics tools. The 20 pivotal proteins were docked harnessing Glide, Schrodinger Suite 2023-2. The investigation was governed by docking scores and affinity. The shared target proteins underscored the precise Hh and WA network roles with the affirmation enrichment P-value of <0.025. The implications for hedgehog and cancer pathways were profound with enrichment (P < 0.01). Further, the ADMET and drug-likeness assessments assisted the claim. Robust interactions were noticed with docking studies, authenticated through molecular dynamics, molecular mechanics generalized born surface area scores and bonds. The computational investigation emphasized WA's credible anti-breast activity, specifically with Hh proteins, implying stem-cell-level checkpoint restraints. Rigorous testament is imperative through in vitro and in vivo studies.
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Affiliation(s)
- Mythili Srinivasan
- Research Scholar, School of Health Sciences and Technology, Dr. Vishwanath Karad MIT World Peace University, Pune, Maharashtra 411038, India
| | - Apeksha Gangurde
- School of Health Sciences and Technology, Dr. Vishwanath Karad MIT World Peace University, Pune, Maharashtra 411038, India
| | - Ashwini Y Chandane
- Abhinav College of Pharmacy, Narhe, Ambegaon, Pune, Maharashtra 411041, India
| | - Amol Tagalpallewar
- School of Health Sciences and Technology, Dr. Vishwanath Karad MIT World Peace University, Pune, Maharashtra 411038, India
| | - Anil Pawar
- School of Health Sciences and Technology, Dr. Vishwanath Karad MIT World Peace University, Pune, Maharashtra 411038, India
| | - Akshay M Baheti
- School of Health Sciences and Technology, Dr. Vishwanath Karad MIT World Peace University, Pune, Maharashtra 411038, India
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Spurná Z, Čapková P, Punová L, DuchoslavovÁ J, Aleksijevic D, Venháčová P, Srovnal J, Štellmachová J, Curtisová V, Bitnerová V, Petřková J, Kolaříková K, Janíková M, Kratochvílová R, Vrtěl P, Vodička R, Vrtěl R, Zapletalová J. Clinical-genetic analysis of selected genes involved in the development of the human skeleton in 128 Czech patients with suspected congenital skeletal abnormalities. Gene 2024; 892:147881. [PMID: 37806643 DOI: 10.1016/j.gene.2023.147881] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2023] [Revised: 10/04/2023] [Accepted: 10/05/2023] [Indexed: 10/10/2023]
Abstract
BACKGROUND Congenital skeletal abnormalities are a heterogeneous group of diseases most commonly associated with small or disproportionate growth, cranial and facial dysmorphisms, delayed bone maturation, etc. Nonetheless, no detailed genotype-phenotype correlation in patients with specific genetic variants is readily available. Ergo, this study focuses on the analysis of patient phenotypes with candidate variants in genes involved in bone growth as detected by molecular genetic analysis. METHODS In this study we used molecular genetic methods to analyse the ACAN, COL2A1, FGFR3, IGFALS, IGF1, IGF1R, GHR, NPR2, STAT5B and SHOX genes in 128 Czech children with suspected congenital skeletal abnormalities. Pathogenic variants and variants of unclear clinical significance were identified and we compared their frequency in this study cohort to the European non-Finnish population. Furthermore, a prediction tool was utilised to determine their possible impact on the final protein. All clinical patient data was obtained during pre-test genetic counselling. RESULTS Pathogenic variants were identified in the FGFR3, GHR, COL2A1 and SHOX genes in a total of six patients. Furthermore, we identified 23 variants with unclear clinical significance and high allelic frequency in this cohort of patients with skeletal abnormalities. Five of them have not yet been reported in the scientific literature. CONCLUSION Congenital skeletal abnormalities may lead to a number of musculoskeletal, neurological, cardiovascular problems. Knowledge of specific pathogenic variants may help us in therapeutic procedures.
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Affiliation(s)
- Z Spurná
- Institute of Medical Genetics, Olomouc University Hospital, Olomouc, Czech Republic; Institute of Medical Genetics, Palacký University in Olomouc, Olomouc, Czech Republic
| | - P Čapková
- Institute of Medical Genetics, Olomouc University Hospital, Olomouc, Czech Republic; Institute of Medical Genetics, Palacký University in Olomouc, Olomouc, Czech Republic.
| | - L Punová
- Institute of Medical Genetics, Olomouc University Hospital, Olomouc, Czech Republic; Institute of Medical Genetics, Palacký University in Olomouc, Olomouc, Czech Republic
| | - J DuchoslavovÁ
- Institute of Medical Genetics, Olomouc University Hospital, Olomouc, Czech Republic; Institute of Medical Genetics, Palacký University in Olomouc, Olomouc, Czech Republic
| | - D Aleksijevic
- Paediatrics Department, Palacký University and University Hospital, Olomouc, Czech Republic
| | - P Venháčová
- Paediatrics Department, Palacký University and University Hospital, Olomouc, Czech Republic
| | - J Srovnal
- Institute of Medical Genetics, Olomouc University Hospital, Olomouc, Czech Republic; Institute of Medical Genetics, Palacký University in Olomouc, Olomouc, Czech Republic; Institute of Molecular and Translational Medicine, Czech Advanced Technology and Research Institute, Palacky University in Olomouc, Czech Republic; Cancer Research Czech Republic, Olomouc, Czech Republic
| | - J Štellmachová
- Institute of Medical Genetics, Olomouc University Hospital, Olomouc, Czech Republic; Institute of Medical Genetics, Palacký University in Olomouc, Olomouc, Czech Republic
| | - V Curtisová
- Institute of Medical Genetics, Olomouc University Hospital, Olomouc, Czech Republic; Institute of Medical Genetics, Palacký University in Olomouc, Olomouc, Czech Republic
| | - V Bitnerová
- Institute of Medical Genetics, Olomouc University Hospital, Olomouc, Czech Republic; Institute of Medical Genetics, Palacký University in Olomouc, Olomouc, Czech Republic
| | - J Petřková
- Institute of Medical Genetics, Olomouc University Hospital, Olomouc, Czech Republic; First Department of Internal Medicine - Cardiology, University Hospital Olomouc, Olomouc, Czech Republic; First Department of Internal Medicine - Cardiology, Palacký University in Olomouc, Olomouc, Czech Republic; Institute of Pathological Physiology, Palacký University in Olomouc, Olomouc, Czech Republic
| | - K Kolaříková
- Department of Neurology, University Hospital Olomouc, Czech Republic; Department of Neurology, Palacky University Olomouc, Czech Republic
| | - M Janíková
- Institute of Medical Genetics, Olomouc University Hospital, Olomouc, Czech Republic; Institute of Medical Genetics, Palacký University in Olomouc, Olomouc, Czech Republic; Institute of Clinical and Molecular Pathology, Palacký University in Olomouc, Olomouc, Czech Republic
| | - R Kratochvílová
- Institute of Medical Genetics, Olomouc University Hospital, Olomouc, Czech Republic
| | - P Vrtěl
- Institute of Medical Genetics, Olomouc University Hospital, Olomouc, Czech Republic; Institute of Medical Genetics, Palacký University in Olomouc, Olomouc, Czech Republic
| | - R Vodička
- Institute of Medical Genetics, Olomouc University Hospital, Olomouc, Czech Republic; Institute of Medical Genetics, Palacký University in Olomouc, Olomouc, Czech Republic
| | - R Vrtěl
- Institute of Medical Genetics, Olomouc University Hospital, Olomouc, Czech Republic; Institute of Medical Genetics, Palacký University in Olomouc, Olomouc, Czech Republic
| | - J Zapletalová
- Paediatrics Department, Palacký University and University Hospital, Olomouc, Czech Republic
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Hadjipanteli A, Theodosiou A, Papaevripidou I, Evangelidou P, Alexandrou A, Salameh N, Kallikas I, Kakoullis K, Frakala S, Oxinou C, Marnerides A, Kousoulidou L, Anastasiadou VC, Sismani C. Sodium Channel Gene Variants in Fetuses with Abnormal Sonographic Findings: Expanding the Prenatal Phenotypic Spectrum of Sodium Channelopathies. Genes (Basel) 2024; 15:119. [PMID: 38255008 PMCID: PMC10815715 DOI: 10.3390/genes15010119] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2023] [Revised: 01/08/2024] [Accepted: 01/17/2024] [Indexed: 01/24/2024] Open
Abstract
Voltage-gated sodium channels (VGSCs) are responsible for the initiation and propagation of action potentials in the brain and muscle. Pathogenic variants in genes encoding VGSCs have been associated with severe disorders including epileptic encephalopathies and congenital myopathies. In this study, we identified pathogenic variants in genes encoding the α subunit of VGSCs in the fetuses of two unrelated families with the use of trio-based whole exome sequencing, as part of a larger cohort study. Sanger sequencing was performed for variant confirmation as well as parental phasing. The fetus of the first family carried a known de novo heterozygous missense variant in the SCN2A gene (NM_001040143.2:c.751G>A p.(Val251Ile)) and presented intrauterine growth retardation, hand clenching and ventriculomegaly. Neonatally, the proband also exhibited refractory epilepsy, spasms and MRI abnormalities. The fetus of the second family was a compound heterozygote for two parentally inherited novel missense variants in the SCN4A gene (NM_000334.4:c.4340T>C, p.(Phe1447Ser), NM_000334.4:c.3798G>C, p.(Glu1266Asp)) and presented a severe prenatal phenotype including talipes, fetal hypokinesia, hypoplastic lungs, polyhydramnios, ear abnormalities and others. Both probands died soon after birth. In a subsequent pregnancy of the latter family, the fetus was also a compound heterozygote for the same parentally inherited variants. This pregnancy was terminated due to multiple ultrasound abnormalities similar to the first pregnancy. Our results suggest a potentially crucial role of the VGSC gene family in fetal development and early lethality.
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Affiliation(s)
- Andrea Hadjipanteli
- The Cyprus Institute of Neurology and Genetics, Cytogenetics and Genomics, 2371 Nicosia, Cyprus; (A.H.)
| | - Athina Theodosiou
- The Cyprus Institute of Neurology and Genetics, Cytogenetics and Genomics, 2371 Nicosia, Cyprus; (A.H.)
| | - Ioannis Papaevripidou
- The Cyprus Institute of Neurology and Genetics, Cytogenetics and Genomics, 2371 Nicosia, Cyprus; (A.H.)
| | - Paola Evangelidou
- The Cyprus Institute of Neurology and Genetics, Cytogenetics and Genomics, 2371 Nicosia, Cyprus; (A.H.)
| | - Angelos Alexandrou
- The Cyprus Institute of Neurology and Genetics, Cytogenetics and Genomics, 2371 Nicosia, Cyprus; (A.H.)
| | - Nicole Salameh
- The Cyprus Institute of Neurology and Genetics, Cytogenetics and Genomics, 2371 Nicosia, Cyprus; (A.H.)
| | | | | | | | - Christina Oxinou
- Christina Oxinou Histopathology/Cytology Laboratory, 1065 Nicosia, Cyprus
| | | | - Ludmila Kousoulidou
- The Cyprus Institute of Neurology and Genetics, Cytogenetics and Genomics, 2371 Nicosia, Cyprus; (A.H.)
| | | | - Carolina Sismani
- The Cyprus Institute of Neurology and Genetics, Cytogenetics and Genomics, 2371 Nicosia, Cyprus; (A.H.)
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Cacheiro P, Lawson S, Van den Veyver IB, Marengo G, Zocche D, Murray SA, Duyzend M, Robinson PN, Smedley D. Lethal phenotypes in Mendelian disorders. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.01.12.24301168. [PMID: 38260283 PMCID: PMC10802756 DOI: 10.1101/2024.01.12.24301168] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/24/2024]
Abstract
Essential genes are those whose function is required for cell proliferation and/or organism survival. A gene's intolerance to loss-of-function can be allocated within a spectrum, as opposed to being considered a binary feature, since this function might be essential at different stages of development, genetic backgrounds or other contexts. Existing resources that collect and characterise the essentiality status of genes are based on either proliferation assessment in human cell lines, embryonic and postnatal viability evaluation in different model organisms, and gene metrics such as intolerance to variation scores derived from human population sequencing studies. There are also several repositories available that document phenotypic annotations for rare disorders in humans such as the Online Mendelian Inheritance in Man (OMIM) and the Human Phenotype Ontology (HPO) knowledgebases. This raises the prospect of being able to use clinical data, including lethality as the most severe phenotypic manifestation, to further our characterisation of gene essentiality. Here we queried OMIM for terms related to lethality and classified all Mendelian genes into categories, according to the earliest age of death recorded for the associated disorders, from prenatal death to no reports of premature death. To showcase this curated catalogue of human essential genes, we developed the Lethal Phenotypes Portal (https://lethalphenotypes.research.its.qmul.ac.uk), where we also explore the relationships between these lethality categories, constraint metrics and viability in cell lines and mouse. Further analysis of the genes in these categories reveals differences in the mode of inheritance of the associated disorders, physiological systems affected and disease class. We highlight how the phenotypic similarity between genes in the same lethality category combined with gene family/group information can be used for novel disease gene discovery. Finally, we explore the overlaps and discrepancies between the lethal phenotypes observed in mouse and human and discuss potential explanations that include differences in transcriptional regulation, functional compensation and molecular disease mechanisms. We anticipate that this resource will aid clinicians in the diagnosis of early lethal conditions and assist researchers in investigating the properties that make these genes essential for human development.
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Affiliation(s)
- Pilar Cacheiro
- William Harvey Research Institute, Queen Mary University of London, London, UK
| | | | - Ignatia B. Van den Veyver
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
- Department of Obstetrics and Gynecology, Baylor College of Medicine, Houston, TX, USA
| | - Gabriel Marengo
- William Harvey Research Institute, Queen Mary University of London, London, UK
| | - David Zocche
- North West Thames Regional Genetics Service, Northwick Park & St Mark’s Hospitals, London, UK
| | | | | | - Peter N. Robinson
- Berlin Institute of Health at Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Damian Smedley
- William Harvey Research Institute, Queen Mary University of London, London, UK
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Li MT, Ke J, Guo SF, Shan LL, Gong JH, Qiao TC, Tian HY, Wu Y, Peng ZY, Zeng XQ, Han Y. Huzhangqingmaiyin protected vascular endothelial cells against cerebral small vessel disease through inhibiting inflammation. JOURNAL OF ETHNOPHARMACOLOGY 2024; 318:116905. [PMID: 37442491 DOI: 10.1016/j.jep.2023.116905] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/16/2023] [Revised: 07/09/2023] [Accepted: 07/10/2023] [Indexed: 07/15/2023]
Abstract
ETHNOPHARMACOLOGICAL RELEVANCE Huzhangqingmaiyin (HZQMY) is a Chinese medicine formula used to treat small vessel disease, but the mechanism is unclear. AIM OF THE STUDY This study aimed to reveal the protective effects of HZQMY on human brain microvascular endothelial cells (HBMECs) and explore the potential targets and mechanistic pathways using network pharmacology on treating cerebral small vessel disease (CSVD). MATERIALS AND METHODS HBMECs were cultured in vitro and an endothelial cell injury model was constructed by hypoxia for 12 h followed by reoxygenation for 8 h (H/R). Cell viability was measured by CCK-8 assay, migration ability of cells was detected by scratch assay, angiogenesis ability of endothelial cells was detected by tubulogenesis assay. Meanwhile, JC-1 staining was employed to determine the alteration of mitochondrial membrane potential, and finally, cell apoptosis was assessed by flow cytometry. To further explore the mechanism of action of HZQMY, the target proteins of a candidate active compound was first collected from the traditional Chinese medicine systems pharmacology database with analytical platform and Swiss target prediction database (www.swisstargetprediction.ch) by HPLC/MS determination of its main active components. CSVD associated targets were retrieved from four disease associated targets databases, OMIM, DisGenNET, GeneCards and GeneCLip, respectively. Using the website String, the genes overlapped between HZQMY and CSVD were imported into the database, PPI network plots were drawn using Cytoscape software. GO and KEGG analyses were performed to explore the possible pathways and targets of HZQMY. Its most probable targets were further explored with molecular docking and verified. RESULTS HZQMY at 0.5-2 μg/mL concentration range could promote cell proliferation, cell migration, angiogenesis, reduce mitochondrial membrane potential damage as well as inhibit apoptosis. Besides that, 29 active compounds were detected from HZQMY, including key components such as quercetin, polydatin, kaempferol, isorhamnetin and resveratrol. Core targets that might include IL-1β、ICAM-1、VCAM-1 and VEGF and so on. CONCLUSIONS HZQMY could regulate the levels of key targets such as IL-1β、ICAM-1、VCAM-1 and VEGF, so as to achieve the purpose of treating CSVD.
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Affiliation(s)
- Meng-Ting Li
- Department of Neurology, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, 200437, China
| | - Jia Ke
- Department of Neurology, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, 200437, China
| | - Shu-Fen Guo
- Department of Neurology, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, 200437, China
| | - Li-Li Shan
- Department of Neurology, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, 200437, China
| | - Jia-Hao Gong
- Shanghai Frontiers Science Center of TCM Chemical Biology, Institute of Interdisciplinary Integrative Medicine Research, Shanghai University of Traditional Chinese Medicine, Shanghai, 201203, China
| | - Tian-Ci Qiao
- Department of Neurology, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, 200437, China
| | - Hao-Yu Tian
- Department of Neurology, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, 200437, China
| | - Yang Wu
- Department of Neurology, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, 200437, China
| | - Zheng-Yu Peng
- Department of Neurology, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, 200437, China
| | - Xue-Qian Zeng
- Department of Neurology, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, 200437, China
| | - Yan Han
- Department of Neurology, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, 200437, China.
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Hekselman I, Vital A, Ziv-Agam M, Kerber L, Yairi I, Yeger-Lotem E. Affected cell types for hundreds of Mendelian diseases revealed by analysis of human and mouse single-cell data. eLife 2024; 13:e84613. [PMID: 38197427 PMCID: PMC10830129 DOI: 10.7554/elife.84613] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2022] [Accepted: 12/08/2023] [Indexed: 01/11/2024] Open
Abstract
Mendelian diseases tend to manifest clinically in certain tissues, yet their affected cell types typically remain elusive. Single-cell expression studies showed that overexpression of disease-associated genes may point to the affected cell types. Here, we developed a method that infers disease-affected cell types from the preferential expression of disease-associated genes in cell types (PrEDiCT). We applied PrEDiCT to single-cell expression data of six human tissues, to infer the cell types affected in Mendelian diseases. Overall, we inferred the likely affected cell types for 328 diseases. We corroborated our findings by literature text-mining, expert validation, and recapitulation in mouse corresponding tissues. Based on these findings, we explored characteristics of disease-affected cell types, showed that diseases manifesting in multiple tissues tend to affect similar cell types, and highlighted cases where gene functions could be used to refine inference. Together, these findings expand the molecular understanding of disease mechanisms and cellular vulnerability.
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Affiliation(s)
- Idan Hekselman
- Department of Clinical Biochemistry and Pharmacology, Ben-Gurion University of the NegevBe’er ShevaIsrael
| | - Assaf Vital
- Department of Clinical Biochemistry and Pharmacology, Ben-Gurion University of the NegevBe’er ShevaIsrael
| | - Maya Ziv-Agam
- Department of Clinical Biochemistry and Pharmacology, Ben-Gurion University of the NegevBe’er ShevaIsrael
| | - Lior Kerber
- Department of Clinical Biochemistry and Pharmacology, Ben-Gurion University of the NegevBe’er ShevaIsrael
| | - Ido Yairi
- Department of Clinical Biochemistry and Pharmacology, Ben-Gurion University of the NegevBe’er ShevaIsrael
| | - Esti Yeger-Lotem
- Department of Clinical Biochemistry and Pharmacology, Ben-Gurion University of the NegevBe’er ShevaIsrael
- The National Institute for Biotechnology in the Negev, Ben-Gurion University of the NegevBe’er ShevaIsrael
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Yu Z, Wu Z, Wang Z, Wang Y, Zhou M, Li W, Liu G, Tang Y. Network-Based Methods and Their Applications in Drug Discovery. J Chem Inf Model 2024; 64:57-75. [PMID: 38150548 DOI: 10.1021/acs.jcim.3c01613] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2023]
Abstract
Drug discovery is time-consuming, expensive, and predominantly follows the "one drug → one target → one disease" paradigm. With the rapid development of systems biology and network pharmacology, a novel drug discovery paradigm, "multidrug → multitarget → multidisease", has emerged. This new holistic paradigm of drug discovery aligns well with the essence of networks, leading to the emergence of network-based methods in the field of drug discovery. In this Perspective, we initially introduce the concept and data sources of networks and highlight classical methodologies employed in network-based methods. Subsequently, we focus on the practical applications of network-based methods across various areas of drug discovery, such as target prediction, virtual screening, prediction of drug therapeutic effects or adverse drug events, and elucidation of molecular mechanisms. In addition, we provide representative web servers for researchers to use network-based methods in specific applications. Finally, we discuss several challenges of network-based methods and the directions for future development. In a word, network-based methods could serve as powerful tools to accelerate drug discovery.
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Affiliation(s)
- Zhuohang Yu
- Shanghai Frontiers Science Center of Optogenetic Techniques for Cell Metabolism, Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, 130 Meilong Road, Shanghai 200237, China
| | - Zengrui Wu
- Shanghai Frontiers Science Center of Optogenetic Techniques for Cell Metabolism, Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, 130 Meilong Road, Shanghai 200237, China
| | - Ze Wang
- Shanghai Frontiers Science Center of Optogenetic Techniques for Cell Metabolism, Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, 130 Meilong Road, Shanghai 200237, China
| | - Yimeng Wang
- Shanghai Frontiers Science Center of Optogenetic Techniques for Cell Metabolism, Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, 130 Meilong Road, Shanghai 200237, China
| | - Moran Zhou
- Shanghai Frontiers Science Center of Optogenetic Techniques for Cell Metabolism, Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, 130 Meilong Road, Shanghai 200237, China
| | - Weihua Li
- Shanghai Frontiers Science Center of Optogenetic Techniques for Cell Metabolism, Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, 130 Meilong Road, Shanghai 200237, China
| | - Guixia Liu
- Shanghai Frontiers Science Center of Optogenetic Techniques for Cell Metabolism, Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, 130 Meilong Road, Shanghai 200237, China
| | - Yun Tang
- Shanghai Frontiers Science Center of Optogenetic Techniques for Cell Metabolism, Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, 130 Meilong Road, Shanghai 200237, China
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Harrison PW, Amode MR, Austine-Orimoloye O, Azov A, Barba M, Barnes I, Becker A, Bennett R, Berry A, Bhai J, Bhurji SK, Boddu S, Branco Lins PR, Brooks L, Ramaraju S, Campbell L, Martinez MC, Charkhchi M, Chougule K, Cockburn A, Davidson C, De Silva N, Dodiya K, Donaldson S, El Houdaigui B, Naboulsi T, Fatima R, Giron CG, Genez T, Grigoriadis D, Ghattaoraya G, Martinez JG, Gurbich T, Hardy M, Hollis Z, Hourlier T, Hunt T, Kay M, Kaykala V, Le T, Lemos D, Lodha D, Marques-Coelho D, Maslen G, Merino G, Mirabueno L, Mushtaq A, Hossain S, Ogeh D, Sakthivel MP, Parker A, Perry M, Piližota I, Poppleton D, Prosovetskaia I, Raj S, Pérez-Silva J, Salam A, Saraf S, Saraiva-Agostinho N, Sheppard D, Sinha S, Sipos B, Sitnik V, Stark W, Steed E, Suner MM, Surapaneni L, Sutinen K, Tricomi FF, Urbina-Gómez D, Veidenberg A, Walsh TA, Ware D, Wass E, Willhoft N, Allen J, Alvarez-Jarreta J, Chakiachvili M, Flint B, Giorgetti S, Haggerty L, Ilsley G, Keatley J, Loveland J, Moore B, Mudge J, Naamati G, Tate J, Trevanion S, Winterbottom A, Frankish A, Hunt SE, Cunningham F, Dyer S, Finn R, Martin F, Yates A. Ensembl 2024. Nucleic Acids Res 2024; 52:D891-D899. [PMID: 37953337 PMCID: PMC10767893 DOI: 10.1093/nar/gkad1049] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2023] [Revised: 10/20/2023] [Accepted: 10/24/2023] [Indexed: 11/14/2023] Open
Abstract
Ensembl (https://www.ensembl.org) is a freely available genomic resource that has produced high-quality annotations, tools, and services for vertebrates and model organisms for more than two decades. In recent years, there has been a dramatic shift in the genomic landscape, with a large increase in the number and phylogenetic breadth of high-quality reference genomes, alongside major advances in the pan-genome representations of higher species. In order to support these efforts and accelerate downstream research, Ensembl continues to focus on scaling for the rapid annotation of new genome assemblies, developing new methods for comparative analysis, and expanding the depth and quality of our genome annotations. This year we have continued our expansion to support global biodiversity research, doubling the number of annotated genomes we support on our Rapid Release site to over 1700, driven by our close collaboration with biodiversity projects such as Darwin Tree of Life. We have also strengthened support for key agricultural species, including the first regulatory builds for farmed animals, and have updated key tools and resources that support the global scientific community, notably the Ensembl Variant Effect Predictor. Ensembl data, software, and tools are freely available.
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Affiliation(s)
- Peter W Harrison
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, Cambridgeshire CB10 1SD, UK
| | - M Ridwan Amode
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, Cambridgeshire CB10 1SD, UK
| | - Olanrewaju Austine-Orimoloye
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, Cambridgeshire CB10 1SD, UK
| | - Andrey G Azov
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, Cambridgeshire CB10 1SD, UK
| | - Matthieu Barba
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, Cambridgeshire CB10 1SD, UK
| | - If Barnes
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, Cambridgeshire CB10 1SD, UK
| | - Arne Becker
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, Cambridgeshire CB10 1SD, UK
| | - Ruth Bennett
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, Cambridgeshire CB10 1SD, UK
| | - Andrew Berry
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, Cambridgeshire CB10 1SD, UK
| | - Jyothish Bhai
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, Cambridgeshire CB10 1SD, UK
| | - Simarpreet Kaur Bhurji
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, Cambridgeshire CB10 1SD, UK
| | - Sanjay Boddu
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, Cambridgeshire CB10 1SD, UK
| | - Paulo R Branco Lins
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, Cambridgeshire CB10 1SD, UK
| | - Lucy Brooks
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, Cambridgeshire CB10 1SD, UK
| | - Shashank Budhanuru Ramaraju
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, Cambridgeshire CB10 1SD, UK
| | - Lahcen I Campbell
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, Cambridgeshire CB10 1SD, UK
| | - Manuel Carbajo Martinez
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, Cambridgeshire CB10 1SD, UK
| | - Mehrnaz Charkhchi
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, Cambridgeshire CB10 1SD, UK
| | - Kapeel Chougule
- Cold Spring Harbor Laboratory, 1 Bungtown Rd, Cold Spring Harbor, NY 11724, USA
| | - Alexander Cockburn
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, Cambridgeshire CB10 1SD, UK
| | - Claire Davidson
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, Cambridgeshire CB10 1SD, UK
| | - Nishadi H De Silva
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, Cambridgeshire CB10 1SD, UK
| | - Kamalkumar Dodiya
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, Cambridgeshire CB10 1SD, UK
| | - Sarah Donaldson
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, Cambridgeshire CB10 1SD, UK
| | - Bilal El Houdaigui
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, Cambridgeshire CB10 1SD, UK
| | - Tamara El Naboulsi
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, Cambridgeshire CB10 1SD, UK
| | - Reham Fatima
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, Cambridgeshire CB10 1SD, UK
| | - Carlos Garcia Giron
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, Cambridgeshire CB10 1SD, UK
| | - Thiago Genez
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, Cambridgeshire CB10 1SD, UK
| | - Dionysios Grigoriadis
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, Cambridgeshire CB10 1SD, UK
| | - Gurpreet S Ghattaoraya
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, Cambridgeshire CB10 1SD, UK
| | - Jose Gonzalez Martinez
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, Cambridgeshire CB10 1SD, UK
| | - Tatiana A Gurbich
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, Cambridgeshire CB10 1SD, UK
| | - Matthew Hardy
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, Cambridgeshire CB10 1SD, UK
| | - Zoe Hollis
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, Cambridgeshire CB10 1SD, UK
| | - Thibaut Hourlier
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, Cambridgeshire CB10 1SD, UK
| | - Toby Hunt
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, Cambridgeshire CB10 1SD, UK
| | - Mike Kay
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, Cambridgeshire CB10 1SD, UK
| | - Vinay Kaykala
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, Cambridgeshire CB10 1SD, UK
| | - Tuan Le
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, Cambridgeshire CB10 1SD, UK
| | - Diana Lemos
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, Cambridgeshire CB10 1SD, UK
| | - Disha Lodha
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, Cambridgeshire CB10 1SD, UK
| | - Diego Marques-Coelho
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, Cambridgeshire CB10 1SD, UK
| | - Gareth Maslen
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, Cambridgeshire CB10 1SD, UK
| | - Gabriela Alejandra Merino
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, Cambridgeshire CB10 1SD, UK
| | - Louisse Paola Mirabueno
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, Cambridgeshire CB10 1SD, UK
| | - Aleena Mushtaq
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, Cambridgeshire CB10 1SD, UK
| | - Syed Nakib Hossain
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, Cambridgeshire CB10 1SD, UK
| | - Denye N Ogeh
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, Cambridgeshire CB10 1SD, UK
| | - Manoj Pandian Sakthivel
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, Cambridgeshire CB10 1SD, UK
| | - Anne Parker
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, Cambridgeshire CB10 1SD, UK
| | - Malcolm Perry
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, Cambridgeshire CB10 1SD, UK
| | - Ivana Piližota
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, Cambridgeshire CB10 1SD, UK
| | - Daniel Poppleton
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, Cambridgeshire CB10 1SD, UK
| | - Irina Prosovetskaia
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, Cambridgeshire CB10 1SD, UK
| | - Shriya Raj
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, Cambridgeshire CB10 1SD, UK
| | - José G Pérez-Silva
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, Cambridgeshire CB10 1SD, UK
| | - Ahamed Imran Abdul Salam
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, Cambridgeshire CB10 1SD, UK
| | - Shradha Saraf
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, Cambridgeshire CB10 1SD, UK
| | - Nuno Saraiva-Agostinho
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, Cambridgeshire CB10 1SD, UK
| | - Dan Sheppard
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, Cambridgeshire CB10 1SD, UK
| | - Swati Sinha
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, Cambridgeshire CB10 1SD, UK
| | - Botond Sipos
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, Cambridgeshire CB10 1SD, UK
| | - Vasily Sitnik
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, Cambridgeshire CB10 1SD, UK
| | - William Stark
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, Cambridgeshire CB10 1SD, UK
| | - Emily Steed
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, Cambridgeshire CB10 1SD, UK
| | - Marie-Marthe Suner
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, Cambridgeshire CB10 1SD, UK
| | - Likhitha Surapaneni
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, Cambridgeshire CB10 1SD, UK
| | - Kyösti Sutinen
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, Cambridgeshire CB10 1SD, UK
| | - Francesca Floriana Tricomi
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, Cambridgeshire CB10 1SD, UK
| | - David Urbina-Gómez
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, Cambridgeshire CB10 1SD, UK
| | - Andres Veidenberg
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, Cambridgeshire CB10 1SD, UK
| | - Thomas A Walsh
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, Cambridgeshire CB10 1SD, UK
| | - Doreen Ware
- Cold Spring Harbor Laboratory, 1 Bungtown Rd, Cold Spring Harbor, NY 11724, USA
- USDA ARS NAA Robert W. Holley Center for Agriculture and Health, Agricultural Research Service, Ithaca, NY 14853, USA
| | - Elizabeth Wass
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, Cambridgeshire CB10 1SD, UK
| | - Natalie L Willhoft
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, Cambridgeshire CB10 1SD, UK
| | - Jamie Allen
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, Cambridgeshire CB10 1SD, UK
| | - Jorge Alvarez-Jarreta
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, Cambridgeshire CB10 1SD, UK
| | - Marc Chakiachvili
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, Cambridgeshire CB10 1SD, UK
| | - Bethany Flint
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, Cambridgeshire CB10 1SD, UK
| | - Stefano Giorgetti
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, Cambridgeshire CB10 1SD, UK
| | - Leanne Haggerty
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, Cambridgeshire CB10 1SD, UK
| | - Garth R Ilsley
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, Cambridgeshire CB10 1SD, UK
| | - Jon Keatley
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, Cambridgeshire CB10 1SD, UK
| | - Jane E Loveland
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, Cambridgeshire CB10 1SD, UK
| | - Benjamin Moore
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, Cambridgeshire CB10 1SD, UK
| | - Jonathan M Mudge
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, Cambridgeshire CB10 1SD, UK
| | - Guy Naamati
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, Cambridgeshire CB10 1SD, UK
| | - John Tate
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, Cambridgeshire CB10 1SD, UK
| | - Stephen J Trevanion
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, Cambridgeshire CB10 1SD, UK
| | - Andrea Winterbottom
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, Cambridgeshire CB10 1SD, UK
| | - Adam Frankish
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, Cambridgeshire CB10 1SD, UK
| | - Sarah E Hunt
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, Cambridgeshire CB10 1SD, UK
| | - Fiona Cunningham
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, Cambridgeshire CB10 1SD, UK
| | - Sarah Dyer
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, Cambridgeshire CB10 1SD, UK
| | - Robert D Finn
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, Cambridgeshire CB10 1SD, UK
| | - Fergal J Martin
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, Cambridgeshire CB10 1SD, UK
| | - Andrew D Yates
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, Cambridgeshire CB10 1SD, UK
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Wang Z, Zhao G, Zhu Z, Wang Y, Xiang X, Zhang S, Luo T, Zhou Q, Qiu J, Tang B, Xia K, Li B, Li J. VarCards2: an integrated genetic and clinical database for ACMG-AMP variant-interpretation guidelines in the human whole genome. Nucleic Acids Res 2024; 52:D1478-D1489. [PMID: 37956311 PMCID: PMC10767961 DOI: 10.1093/nar/gkad1061] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2023] [Revised: 10/21/2023] [Accepted: 10/25/2023] [Indexed: 11/15/2023] Open
Abstract
VarCards, an online database, combines comprehensive variant- and gene-level annotation data to streamline genetic counselling for coding variants. Recognising the increasing clinical relevance of non-coding variations, there has been an accelerated development of bioinformatics tools dedicated to interpreting non-coding variations, including single-nucleotide variants and copy number variations. Regrettably, most tools remain as either locally installed databases or command-line tools dispersed across diverse online platforms. Such a landscape poses inconveniences and challenges for genetic counsellors seeking to utilise these resources without advanced bioinformatics expertise. Consequently, we developed VarCards2, which incorporates nearly nine billion artificially generated single-nucleotide variants (including those from mitochondrial DNA) and compiles vital annotation information for genetic counselling based on ACMG-AMP variant-interpretation guidelines. These annotations include (I) functional effects; (II) minor allele frequencies; (III) comprehensive function and pathogenicity predictions covering all potential variants, such as non-synonymous substitutions, non-canonical splicing variants, and non-coding variations and (IV) gene-level information. Furthermore, VarCards2 incorporates 368 820 266 documented short insertions and deletions and 2 773 555 documented copy number variations, complemented by their corresponding annotation and prediction tools. In conclusion, VarCards2, by integrating over 150 variant- and gene-level annotation sources, significantly enhances the efficiency of genetic counselling and can be freely accessed at http://www.genemed.tech/varcards2/.
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Affiliation(s)
- Zheng Wang
- National Clinical Research Center for Geriatric Disorders, Department of Geriatrics, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China
- Hunan Key Laboratory of Molecular Precision Medicine, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China
| | - Guihu Zhao
- National Clinical Research Center for Geriatric Disorders, Department of Geriatrics, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China
- Bioinformatics Center, Furong Laboratory & Xiangya Hospital, Central South University, Changsha, Hunan 410008, China
| | - Zhaopo Zhu
- Center for Medical Genetics & Hunan Key Laboratory, School of Life Sciences, Central South University, Changsha, Hunan 410008, China
| | - Yijing Wang
- National Clinical Research Center for Geriatric Disorders, Department of Geriatrics, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China
- Bioinformatics Center, Furong Laboratory & Xiangya Hospital, Central South University, Changsha, Hunan 410008, China
| | - Xudong Xiang
- National Clinical Research Center for Geriatric Disorders, Department of Geriatrics, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China
| | - Shiyu Zhang
- Xiangya School of Medicine, Central South University, Changsha, Hunan 410013, China
| | - Tengfei Luo
- Center for Medical Genetics & Hunan Key Laboratory, School of Life Sciences, Central South University, Changsha, Hunan 410008, China
| | - Qiao Zhou
- National Clinical Research Center for Geriatric Disorders, Department of Geriatrics, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China
- Bioinformatics Center, Furong Laboratory & Xiangya Hospital, Central South University, Changsha, Hunan 410008, China
| | - Jian Qiu
- National Clinical Research Center for Geriatric Disorders, Department of Geriatrics, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China
- Hunan Key Laboratory of Molecular Precision Medicine, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China
| | - Beisha Tang
- National Clinical Research Center for Geriatric Disorders, Department of Geriatrics, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China
- Department of Neurology, & Multi-Omics Research Center for Brain Disorders, The First Affiliated Hospital, University of South China, Hengyang, Hunan, China
| | - Kun Xia
- Center for Medical Genetics & Hunan Key Laboratory, School of Life Sciences, Central South University, Changsha, Hunan 410008, China
| | - Bin Li
- National Clinical Research Center for Geriatric Disorders, Department of Geriatrics, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China
- Bioinformatics Center, Furong Laboratory & Xiangya Hospital, Central South University, Changsha, Hunan 410008, China
| | - Jinchen Li
- National Clinical Research Center for Geriatric Disorders, Department of Geriatrics, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China
- Center for Medical Genetics & Hunan Key Laboratory, School of Life Sciences, Central South University, Changsha, Hunan 410008, China
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China
- Bioinformatics Center, Furong Laboratory & Xiangya Hospital, Central South University, Changsha, Hunan 410008, China
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47
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Li R, Wang M, Tian J, Liu M, Li G, Zhou X. Exploration of kiwi root on non-small cell lung cancer based on network pharmacology and molecular docking. Medicine (Baltimore) 2024; 103:e36852. [PMID: 38181243 PMCID: PMC10766307 DOI: 10.1097/md.0000000000036852] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/13/2023] [Accepted: 12/13/2023] [Indexed: 01/07/2024] Open
Abstract
BACKGROUND Kiwi root is a Chinese herb clinically used in the treatment of lung neoplasm; however, the multi-target mechanism of kiwi root in the treatment of non-small cell lung cancer (NSCLC) remains to be elucidated. Thus, this study aimed to investigate the molecular mechanisms of kiwi root in the treatment of NSCLC through network pharmacology and molecular docking techniques. METHODS The active components and targets of kiwi root were obtained from the TCMSP database, and NSCLC-related targets were obtained from the GeneCards, OMIM, and DrugBank databases. The intersection targets of NSCLC and kiwi root were obtained from VENNY 2.1.0. Then, the common targets were imported into the STRING database, and by using the Cytoscape 3.7.1 software, drug-disease network diagrams were created. Afterwards, the DAVID database was utilized to perform bioinformatic annotation. Finally, molecular docking of key components and key targets was performed by Autodock Tools. RESULTS A total of 4083 NSCLC-related disease genes were collected from the GeneCards, OMIM,and DrugBank databases, and 177 non-duplicated drug targets were acquired from the TCMSP database. A total of 138 intersection target genes were obtained, in which TP53, AKT1, and TNF were the key targets. CONCLUSION Through network pharmacology techniques, the mechanism of kiwi root in the treatment of NSCLC has been uncovered and provides a theoretical basis for the clinical treatment of NSCLC with kiwi root, which requires further experimental validation.
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Affiliation(s)
- Ruochen Li
- Respiratory Department, The Second Affiliated Hospital of Guizhou University of Traditional Chinese Medicine, Guiyang, China
| | - Mingxiao Wang
- Respiratory Department, The Second Affiliated Hospital of Guizhou University of Traditional Chinese Medicine, Guiyang, China
| | - Jin Tian
- Respiratory Department, The Second Affiliated Hospital of Guizhou University of Traditional Chinese Medicine, Guiyang, China
| | - Minghui Liu
- Respiratory Department, The Second Affiliated Hospital of Guizhou University of Traditional Chinese Medicine, Guiyang, China
| | - Gaigai Li
- Respiratory Department, The Second Affiliated Hospital of Guizhou University of Traditional Chinese Medicine, Guiyang, China
| | - Xun Zhou
- Respiratory Department, The Second Affiliated Hospital of Guizhou University of Traditional Chinese Medicine, Guiyang, China
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48
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Cui C, Zhong B, Fan R, Cui Q. HMDD v4.0: a database for experimentally supported human microRNA-disease associations. Nucleic Acids Res 2024; 52:D1327-D1332. [PMID: 37650649 PMCID: PMC10767894 DOI: 10.1093/nar/gkad717] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2023] [Revised: 08/07/2023] [Accepted: 08/19/2023] [Indexed: 09/01/2023] Open
Abstract
MicroRNAs (miRNAs) are a class of important small non-coding RNAs with critical molecular functions in almost all biological processes, and thus, they play important roles in disease diagnosis and therapy. Human MicroRNA Disease Database (HMDD) represents an important and comprehensive resource for biomedical researchers in miRNA-related medicine. Here, we introduce HMDD v4.0, which curates 53530 miRNA-disease association entries from literatures. In comparison to HMDD v3.0 released five years ago, HMDD v4.0 contains 1.5 times more entries. In addition, some new categories have been curated, including exosomal miRNAs implicated in diseases, virus-encoded miRNAs involved in human diseases, and entries containing miRNA-circRNA interactions. We also curated sex-biased miRNAs in diseases. Furthermore, in a case study, disease similarity analysis successfully revealed that sex-biased miRNAs related to developmental anomalies are associated with a number of human diseases with sex bias. HMDD can be freely visited at http://www.cuilab.cn/hmdd.
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Affiliation(s)
- Chunmei Cui
- Department of Biomedical Informatics, Center for Noncoding RNA Medicine, State Key Laboratory of Vascular Homeostasis and Remodeling, School of Basic Medical Sciences, Peking University, 38 Xueyuan Rd, Beijing 100191, China
| | - Bitao Zhong
- Department of Biomedical Informatics, Center for Noncoding RNA Medicine, State Key Laboratory of Vascular Homeostasis and Remodeling, School of Basic Medical Sciences, Peking University, 38 Xueyuan Rd, Beijing 100191, China
| | - Rui Fan
- Department of Biomedical Informatics, Center for Noncoding RNA Medicine, State Key Laboratory of Vascular Homeostasis and Remodeling, School of Basic Medical Sciences, Peking University, 38 Xueyuan Rd, Beijing 100191, China
| | - Qinghua Cui
- Department of Biomedical Informatics, Center for Noncoding RNA Medicine, State Key Laboratory of Vascular Homeostasis and Remodeling, School of Basic Medical Sciences, Peking University, 38 Xueyuan Rd, Beijing 100191, China
- School of Sports Medicine, Wuhan Institute of Physical Education, No. 461 Luoyu Rd. Wuchang District, Wuhan 430079, Hubei Province, China
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49
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Bertolini E, Babbi G, Savojardo C, Martelli PL, Casadio R. MultifacetedProtDB: a database of human proteins with multiple functions. Nucleic Acids Res 2024; 52:D494-D501. [PMID: 37791887 PMCID: PMC10767882 DOI: 10.1093/nar/gkad783] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2023] [Revised: 08/29/2023] [Accepted: 09/15/2023] [Indexed: 10/05/2023] Open
Abstract
MultifacetedProtDB is a database of multifunctional human proteins deriving information from other databases, including UniProt, GeneCards, Human Protein Atlas (HPA), Human Phenotype Ontology (HPO) and MONDO. It collects under the label 'multifaceted' multitasking proteins addressed in literature as pleiotropic, multidomain, promiscuous (in relation to enzymes catalysing multiple substrates) and moonlighting (with two or more molecular functions), and difficult to be retrieved with a direct search in existing non-specific databases. The study of multifunctional proteins is an expanding research area aiming to elucidate the complexities of biological processes, particularly in humans, where multifunctional proteins play roles in various processes, including signal transduction, metabolism, gene regulation and cellular communication, and are often involved in disease insurgence and progression. The webserver allows searching by gene, protein and any associated structural and functional information, like available structures from PDB, structural models and interactors, using multiple filters. Protein entries are supplemented with comprehensive annotations including EC number, GO terms (biological pathways, molecular functions, and cellular components), pathways from Reactome, subcellular localization from UniProt, tissue and cell type expression from HPA, and associated diseases following MONDO, Orphanet and OMIM classification. MultiFacetedProtDB is freely available as a web server at: https://multifacetedprotdb.biocomp.unibo.it/.
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Affiliation(s)
- Elisa Bertolini
- Biocomputing Group, Dept. of Pharmacy and Biotechnology, University of Bologna, Italy
| | - Giulia Babbi
- Biocomputing Group, Dept. of Pharmacy and Biotechnology, University of Bologna, Italy
| | - Castrense Savojardo
- Biocomputing Group, Dept. of Pharmacy and Biotechnology, University of Bologna, Italy
| | - Pier Luigi Martelli
- Biocomputing Group, Dept. of Pharmacy and Biotechnology, University of Bologna, Italy
| | - Rita Casadio
- Biocomputing Group, Dept. of Pharmacy and Biotechnology, University of Bologna, Italy
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50
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Zhai Z, Lin Z, Meng X, Zheng X, Du Y, Li Z, Zhang X, Liu C, Zhou L, Zhang X, Tian Z, Ma Q, Li J, Li Q, Pan J. DiSignAtlas: an atlas of human and mouse disease signatures based on bulk and single-cell transcriptomics. Nucleic Acids Res 2024; 52:D1236-D1245. [PMID: 37930831 PMCID: PMC10767933 DOI: 10.1093/nar/gkad961] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2023] [Revised: 10/09/2023] [Accepted: 10/13/2023] [Indexed: 11/08/2023] Open
Abstract
Molecular signatures are usually sets of biomolecules that can serve as diagnostic, prognostic, predictive, or therapeutic markers for a specific disease. Omics data derived from various high-throughput molecular biology technologies offer global, unbiased and appropriately comparable data, which can be used to identify such molecular signatures. To address the need for comprehensive disease signatures, DiSignAtlas (http://www.inbirg.com/disignatlas/) was developed to provide transcriptomics-based signatures for a wide range of diseases. A total of 181 434 transcriptome profiles were manually curated from studies involving 1836 nonredundant disease types in humans and mice. Then, 10 306 comparison datasets comprising both disease and control samples, including 328 single-cell RNA sequencing datasets, were established. Furthermore, a total of 3 775 317 differentially expressed genes in humans and 1 723 674 in mice were identified as disease signatures by analysing transcriptome profiles using commonly used pipelines. In addition to providing multiple methods for the retrieval of disease signatures, DiSignAtlas provides downstream functional enrichment analysis, cell type analysis and signature correlation analysis between diseases or species when available. Moreover, multiple analytical and comparison tools for disease signatures are available. DiSignAtlas is expected to become a valuable resource for both bioscientists and bioinformaticians engaged in translational research.
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Affiliation(s)
- Zhaoyu Zhai
- Precision Medicine Center, The Second Affiliated Hospital of Chongqing Medical University, Chongqing 400010, China
- Basic Medicine Research and Innovation Center for Novel Target and Therapeutic Intervention, Ministry of Education, Institute of Life Sciences, Chongqing Medical University, Chongqing 400016, China
| | - Zhewei Lin
- Basic Medicine Research and Innovation Center for Novel Target and Therapeutic Intervention, Ministry of Education, Institute of Life Sciences, Chongqing Medical University, Chongqing 400016, China
| | - Xuehang Meng
- Basic Medicine Research and Innovation Center for Novel Target and Therapeutic Intervention, Ministry of Education, Institute of Life Sciences, Chongqing Medical University, Chongqing 400016, China
| | - Xiao Zheng
- Basic Medicine Research and Innovation Center for Novel Target and Therapeutic Intervention, Ministry of Education, Institute of Life Sciences, Chongqing Medical University, Chongqing 400016, China
| | - Yujia Du
- Basic Medicine Research and Innovation Center for Novel Target and Therapeutic Intervention, Ministry of Education, Institute of Life Sciences, Chongqing Medical University, Chongqing 400016, China
| | - Zhi Li
- Basic Medicine Research and Innovation Center for Novel Target and Therapeutic Intervention, Ministry of Education, Institute of Life Sciences, Chongqing Medical University, Chongqing 400016, China
| | - Xuelu Zhang
- Basic Medicine Research and Innovation Center for Novel Target and Therapeutic Intervention, Ministry of Education, Institute of Life Sciences, Chongqing Medical University, Chongqing 400016, China
| | - Chang Liu
- Basic Medicine Research and Innovation Center for Novel Target and Therapeutic Intervention, Ministry of Education, Institute of Life Sciences, Chongqing Medical University, Chongqing 400016, China
| | - Lu Zhou
- Basic Medicine Research and Innovation Center for Novel Target and Therapeutic Intervention, Ministry of Education, Institute of Life Sciences, Chongqing Medical University, Chongqing 400016, China
| | - Xu Zhang
- Basic Medicine Research and Innovation Center for Novel Target and Therapeutic Intervention, Ministry of Education, Institute of Life Sciences, Chongqing Medical University, Chongqing 400016, China
| | - Zhihao Tian
- Basic Medicine Research and Innovation Center for Novel Target and Therapeutic Intervention, Ministry of Education, Institute of Life Sciences, Chongqing Medical University, Chongqing 400016, China
| | - Qinfeng Ma
- Basic Medicine Research and Innovation Center for Novel Target and Therapeutic Intervention, Ministry of Education, Institute of Life Sciences, Chongqing Medical University, Chongqing 400016, China
| | - Jinhao Li
- Hepatobiliary Surgery, The Second Affiliated Hospital of Chongqing Medical University, Chongqing 400010, China
| | - Qiang Li
- Basic Medicine Research and Innovation Center for Novel Target and Therapeutic Intervention, Ministry of Education, Institute of Life Sciences, Chongqing Medical University, Chongqing 400016, China
| | - Jianbo Pan
- Precision Medicine Center, The Second Affiliated Hospital of Chongqing Medical University, Chongqing 400010, China
- Basic Medicine Research and Innovation Center for Novel Target and Therapeutic Intervention, Ministry of Education, Institute of Life Sciences, Chongqing Medical University, Chongqing 400016, China
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