1
|
Sun Q, Yang Y, Rosen JD, Chen J, Li X, Guan W, Jiang MZ, Wen J, Pace RG, Blackman SM, Bamshad MJ, Gibson RL, Cutting GR, O'Neal WK, Knowles MR, Kooperberg C, Reiner AP, Raffield LM, Carson AP, Rich SS, Rotter JI, Loos RJF, Kenny E, Jaeger BC, Min YI, Fuchsberger C, Li Y. MagicalRsq-X: A cross-cohort transferable genotype imputation quality metric. Am J Hum Genet 2024:S0002-9297(24)00116-2. [PMID: 38636510 DOI: 10.1016/j.ajhg.2024.04.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2024] [Revised: 03/29/2024] [Accepted: 04/01/2024] [Indexed: 04/20/2024] Open
Abstract
Since genotype imputation was introduced, researchers have been relying on the estimated imputation quality from imputation software to perform post-imputation quality control (QC). However, this quality estimate (denoted as Rsq) performs less well for lower-frequency variants. We recently published MagicalRsq, a machine-learning-based imputation quality calibration, which leverages additional typed markers from the same cohort and outperforms Rsq as a QC metric. In this work, we extended the original MagicalRsq to allow cross-cohort model training and named the new model MagicalRsq-X. We removed the cohort-specific estimated minor allele frequency and included linkage disequilibrium scores and recombination rates as additional features. Leveraging whole-genome sequencing data from TOPMed, specifically participants in the BioMe, JHS, WHI, and MESA studies, we performed comprehensive cross-cohort evaluations for predominantly European and African ancestral individuals based on their inferred global ancestry with the 1000 Genomes and Human Genome Diversity Project data as reference. Our results suggest MagicalRsq-X outperforms Rsq in almost every setting, with 7.3%-14.4% improvement in squared Pearson correlation with true R2, corresponding to 85-218 K variant gains. We further developed a metric to quantify the genetic distances of a target cohort relative to a reference cohort and showed that such metric largely explained the performance of MagicalRsq-X models. Finally, we found MagicalRsq-X saved up to 53 known genome-wide significant variants in one of the largest blood cell trait GWASs that would be missed using the original Rsq for QC. In conclusion, MagicalRsq-X shows superiority for post-imputation QC and benefits genetic studies by distinguishing well and poorly imputed lower-frequency variants.
Collapse
Affiliation(s)
- Quan Sun
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Yingxi Yang
- Department of Statistics and Data Science, Yale University, New Haven, CT 06520, USA
| | - Jonathan D Rosen
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Jiawen Chen
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Xihao Li
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Wyliena Guan
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Min-Zhi Jiang
- Department of Applied Physical Sciences, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Jia Wen
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Rhonda G Pace
- Marsico Lung Institute/UNC CF Research Center, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Scott M Blackman
- Division of Pediatric Endocrinology, Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA
| | - Michael J Bamshad
- Department of Pediatrics, University of Washington, Seattle, WA 98105, USA; Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA
| | - Ronald L Gibson
- Department of Pediatrics, University of Washington, Seattle, WA 98105, USA
| | - Garry R Cutting
- Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA
| | - Wanda K O'Neal
- Marsico Lung Institute/UNC CF Research Center, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Michael R Knowles
- Marsico Lung Institute/UNC CF Research Center, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Charles Kooperberg
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA 98109, USA
| | - Alexander P Reiner
- Department of Epidemiology, University of Washington, Seattle, WA 98195, USA
| | - Laura M Raffield
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - April P Carson
- Department of Epidemiology, University of Alabama at Birmingham, Birmingham, AL 35249, USA
| | - Stephen S Rich
- Center for Public Health Genomics, Department of Public Health Sciences, University of Virginia School of Medicine, Charlottesville, VA 22908, USA
| | - Jerome I Rotter
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA 90502, USA
| | - Ruth J F Loos
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York City, NY 10029, USA; Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, 2200 Copenhagen, Denmark
| | - Eimear Kenny
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York City, NY 10029, USA
| | - Byron C Jaeger
- Wake Forest School of Medicine, Department of Biostatistics and Data Science, Wake Forest University, Winston-Salem, NC 27109, USA
| | - Yuan-I Min
- Department of Medicine, University of Mississippi Medical Center, Jackson, MS 39216, USA
| | - Christian Fuchsberger
- Institute for Biomedicine, Eurac Research (affiliated with the University of Lübeck), Bolzano, Italy.
| | - Yun Li
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA; Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
| |
Collapse
|
2
|
Jiang MZ, Liu C, Xu C, Jiang H, Wang Y, Liu SJ. Gut microbial interactions based on network construction and bacterial pairwise cultivation. Sci China Life Sci 2024:10.1007/s11427-023-2537-0. [PMID: 38600293 DOI: 10.1007/s11427-023-2537-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/17/2023] [Accepted: 01/27/2024] [Indexed: 04/12/2024]
Abstract
Association networks are widely applied for the prediction of bacterial interactions in studies of human gut microbiomes. However, the experimental validation of the predicted interactions is challenging due to the complexity of gut microbiomes and the limited number of cultivated bacteria. In this study, we addressed this challenge by integrating in vitro time series network (TSN) associations and co-cultivation of TSN taxon pairs. Fecal samples were collected and used for cultivation and enrichment of gut microbiome on YCFA agar plates for 13 days. Enriched cells were harvested for DNA extraction and metagenomic sequencing. A total of 198 metagenome-assembled genomes (MAGs) were recovered. Temporal dynamics of bacteria growing on the YCFA agar were used to infer microbial association networks. To experimentally validate the interactions of taxon pairs in networks, we selected 24 and 19 bacterial strains from this study and from the previously established human gut microbial biobank, respectively, for pairwise co-cultures. The co-culture experiments revealed that most of the interactions between taxa in networks were identified as neutralism (51.67%), followed by commensalism (21.67%), amensalism (18.33%), competition (5%) and exploitation (3.33%). Genome-centric analysis further revealed that the commensal gut bacteria (helpers and beneficiaries) might interact with each other via the exchanges of amino acids with high biosynthetic costs, short-chain fatty acids, and/or vitamins. We also validated 12 beneficiaries by adding 16 additives into the basic YCFA medium and found that the growth of 66.7% of these strains was significantly promoted. This approach provides new insights into the gut microbiome complexity and microbial interactions in association networks. Our work highlights that the positive relationships in gut microbial communities tend to be overestimated, and that amino acids, short-chain fatty acids, and vitamins are contributed to the positive relationships.
Collapse
Affiliation(s)
- Min-Zhi Jiang
- State Key Laboratory of Microbial Technology, Shandong University, Qingdao, 266000, China
| | - Chang Liu
- State Key Laboratory of Microbial Technology, Shandong University, Qingdao, 266000, China
| | - Chang Xu
- State Key Laboratory of Microbial Technology, Shandong University, Qingdao, 266000, China
| | - He Jiang
- State Key Laboratory of Microbial Technology, Shandong University, Qingdao, 266000, China
| | - Yulin Wang
- State Key Laboratory of Microbial Technology, Shandong University, Qingdao, 266000, China.
| | - Shuang-Jiang Liu
- State Key Laboratory of Microbial Technology, Shandong University, Qingdao, 266000, China.
- State Key Laboratory of Microbial Resources, and Environmental Microbiology Research Center (EMRC), Institute of Microbiology, Chinese Academy of Sciences, Beijing, 100101, China.
- University of Chinese Academy of Sciences, Beijing, 100049, China.
| |
Collapse
|
3
|
Xu C, Jiang H, Feng LJ, Jiang MZ, Wang YL, Liu SJ. Christensenella minuta interacts with multiple gut bacteria. Front Microbiol 2024; 15:1301073. [PMID: 38440147 PMCID: PMC10910051 DOI: 10.3389/fmicb.2024.1301073] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2023] [Accepted: 01/30/2024] [Indexed: 03/06/2024] Open
Abstract
Introduction Gut microbes form complex networks that significantly influence host health and disease treatment. Interventions with the probiotic bacteria on the gut microbiota have been demonstrated to improve host well-being. As a representative of next-generation probiotics, Christensenella minuta (C. minuta) plays a critical role in regulating energy balance and metabolic homeostasis in human bodies, showing potential in treating metabolic disorders and reducing inflammation. However, interactions of C. minuta with the members of the networked gut microbiota have rarely been explored. Methods In this study, we investigated the impact of C. minuta on fecal microbiota via metagenomic sequencing, focusing on retrieving bacterial strains and coculture assays of C. minuta with associated microbial partners. Results Our results showed that C. minuta intervention significantly reduced the diversity of fecal microorganisms, but specifically enhanced some groups of bacteria, such as Lactobacillaceae. C. minuta selectively enriched bacterial pathways that compensated for its metabolic defects on vitamin B1, B12, serine, and glutamate synthesis. Meanwhile, C. minuta cross-feeds Faecalibacterium prausnitzii and other bacteria via the production of arginine, branched-chain amino acids, fumaric acids and short-chain fatty acids (SCFAs), such as acetic. Both metagenomic data analysis and culture experiments revealed that C. minuta negatively correlated with Klebsiella pneumoniae and 14 other bacterial taxa, while positively correlated with F. prausnitzii. Our results advance our comprehension of C. minuta's in modulating the gut microbial network. Conclusions C. minuta disrupts the composition of the fecal microbiota. This disturbance is manifested through cross-feeding, nutritional competition, and supplementation of its own metabolic deficiencies, resulting in the specific enrichment or inhibition of the growth of certain bacteria. This study will shed light on the application of C. minuta as a probiotic for effective interventions on gut microbiomes and improvement of host health.
Collapse
Affiliation(s)
- Chang Xu
- State Key Laboratory of Microbial Technology, Shandong University, Qingdao, China
| | - He Jiang
- State Key Laboratory of Microbial Technology, Shandong University, Qingdao, China
| | - Li-Juan Feng
- State Key Laboratory of Microbial Technology, Shandong University, Qingdao, China
| | - Min-Zhi Jiang
- State Key Laboratory of Microbial Technology, Shandong University, Qingdao, China
| | - Yu-Lin Wang
- State Key Laboratory of Microbial Technology, Shandong University, Qingdao, China
| | - Shuang-Jiang Liu
- State Key Laboratory of Microbial Technology, Shandong University, Qingdao, China
- State Key Laboratory of Microbial Resources, Institute of Microbiology, Chinese Academy of Sciences, Beijing, China
| |
Collapse
|
4
|
Liu C, Du MX, Xie LS, Wang WZ, Chen BS, Yun CY, Sun XW, Luo X, Jiang Y, Wang K, Jiang MZ, Qiao SS, Sun M, Cui BJ, Huang HJ, Qu SP, Li CK, Wu D, Wang LS, Jiang C, Liu HW, Liu SJ. Gut commensal Christensenella minuta modulates host metabolism via acylated secondary bile acids. Nat Microbiol 2024; 9:434-450. [PMID: 38233647 DOI: 10.1038/s41564-023-01570-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2022] [Accepted: 11/29/2023] [Indexed: 01/19/2024]
Abstract
A strong correlation between gut microbes and host health has been observed in numerous gut metagenomic cohort studies. However, the underlying mechanisms governing host-microbe interactions in the gut remain largely unknown. Here we report that the gut commensal Christensenella minuta modulates host metabolism by generating a previously undescribed class of secondary bile acids with 3-O-acylation substitution that inhibit the intestinal farnesoid X receptor. Administration of C. minuta alleviated features of metabolic disease in high fat diet-induced obese mice associated with a significant increase in these acylated bile acids, which we refer to as 3-O-acyl-cholic acids. Specific knockout of intestinal farnesoid X receptor in mice counteracted the beneficial effects observed in their wild-type counterparts. Finally, we showed that 3-O-acyl-CAs were prevalent in healthy humans but significantly depleted in patients with type 2 diabetes. Our findings indicate a role for C. minuta and acylated bile acids in metabolic diseases.
Collapse
Affiliation(s)
- Chang Liu
- State Key Laboratory of Microbial Technology, Shandong University, Qingdao, P. R. China
- State Key Laboratory of Microbial Resources, Institute of Microbiology, Chinese Academy of Sciences, Beijing, P. R. China
| | - Meng-Xuan Du
- State Key Laboratory of Microbial Technology, Shandong University, Qingdao, P. R. China
| | - Li-Sheng Xie
- College of Life Science, Hebei University, Baoding, P. R. China
| | - Wen-Zhao Wang
- State Key Laboratory of Mycology, Institute of Microbiology, Chinese Academy of Sciences, Beijing, P. R. China
| | - Bao-Song Chen
- State Key Laboratory of Mycology, Institute of Microbiology, Chinese Academy of Sciences, Beijing, P. R. China
| | - Chu-Yu Yun
- Department of Physiology and Pathophysiology, School of Basic Medical Sciences, State Key Laboratory of Vascular Homeostasis and Remodeling, Peking University, Beijing, P. R. China
| | - Xin-Wei Sun
- State Key Laboratory of Microbial Technology, Shandong University, Qingdao, P. R. China
| | - Xi Luo
- Department of Physiology and Pathophysiology, School of Basic Medical Sciences, State Key Laboratory of Vascular Homeostasis and Remodeling, Peking University, Beijing, P. R. China
| | - Yu Jiang
- State Key Laboratory of Microbial Technology, Shandong University, Qingdao, P. R. China
| | - Kai Wang
- Department of Physiology and Pathophysiology, School of Basic Medical Sciences, State Key Laboratory of Vascular Homeostasis and Remodeling, Peking University, Beijing, P. R. China
| | - Min-Zhi Jiang
- State Key Laboratory of Microbial Technology, Shandong University, Qingdao, P. R. China
| | - Shan-Shan Qiao
- State Key Laboratory of Mycology, Institute of Microbiology, Chinese Academy of Sciences, Beijing, P. R. China
| | - Min Sun
- The Second Hospital of Shandong University, Jinan, P. R. China
| | - Bao-Juan Cui
- The Second Hospital of Shandong University, Jinan, P. R. China
| | - Hao-Jie Huang
- State Key Laboratory of Microbial Technology, Shandong University, Qingdao, P. R. China
| | | | | | - Dalei Wu
- State Key Laboratory of Microbial Technology, Shandong University, Qingdao, P. R. China
| | - Lu-Shan Wang
- State Key Laboratory of Microbial Technology, Shandong University, Qingdao, P. R. China
| | - Changtao Jiang
- Department of Physiology and Pathophysiology, School of Basic Medical Sciences, State Key Laboratory of Vascular Homeostasis and Remodeling, Peking University, Beijing, P. R. China.
- Center of Basic Medical Research, Institute of Medical Innovation and Research, Third Hospital, Peking University, Beijing, P. R. China.
| | - Hong-Wei Liu
- State Key Laboratory of Mycology, Institute of Microbiology, Chinese Academy of Sciences, Beijing, P. R. China.
| | - Shuang-Jiang Liu
- State Key Laboratory of Microbial Technology, Shandong University, Qingdao, P. R. China.
- State Key Laboratory of Microbial Resources, Institute of Microbiology, Chinese Academy of Sciences, Beijing, P. R. China.
| |
Collapse
|
5
|
Zheng W, Jiang X, Jiang MZ. [Summary of the 14 th National Pediatric Gastrointestinal Diseases Conference in 2023]. Zhonghua Er Ke Za Zhi 2023; 61:1055-1056. [PMID: 37899349 DOI: 10.3760/cma.j.cn112140-20230828-00143] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 10/31/2023]
Affiliation(s)
- W Zheng
- Department of Gastroenterology, Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, National Children's Regional Medical Center,Hangzhou 310052, China
| | - X Jiang
- Department of Pediatrics, the Second Affiliated Hospital of Air Force Medical University, Xi'an 710038, China
| | - M Z Jiang
- Department of Gastroenterology and Pediatric Endoscopy Center, Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, National Children's Regional Medical Center, Hangzhou 310052, China
| |
Collapse
|
6
|
Yang X, Jiang MZ. [Etiology and clinical management progress of acute liver failure in children]. Zhonghua Er Ke Za Zhi 2023; 61:941-944. [PMID: 37803866 DOI: 10.3760/cma.j.cn112140-20230806-00084] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 10/08/2023]
Affiliation(s)
- X Yang
- Department of Gastroenterology, Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou 310052, China
| | - M Z Jiang
- Department of Gastroenterology, Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou 310052, China
| |
Collapse
|
7
|
Yang X, Wen J, Yang H, Jones IR, Zhu X, Liu W, Li B, Clelland CD, Luo W, Wong MY, Ren X, Cui X, Song M, Liu H, Chen C, Eng N, Ravichandran M, Sun Y, Lee D, Van Buren E, Jiang MZ, Chan CSY, Ye CJ, Perera RM, Gan L, Li Y, Shen Y. Functional characterization of Alzheimer's disease genetic variants in microglia. Nat Genet 2023; 55:1735-1744. [PMID: 37735198 PMCID: PMC10939305 DOI: 10.1038/s41588-023-01506-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2022] [Accepted: 08/20/2023] [Indexed: 09/23/2023]
Abstract
Candidate cis-regulatory elements (cCREs) in microglia demonstrate the most substantial enrichment for Alzheimer's disease (AD) heritability compared to other brain cell types. However, whether and how these genome-wide association studies (GWAS) variants contribute to AD remain elusive. Here we prioritize 308 previously unreported AD risk variants at 181 cCREs by integrating genetic information with microglia-specific 3D epigenome annotation. We further establish the link between functional variants and target genes by single-cell CRISPRi screening in microglia. In addition, we show that AD variants exhibit allelic imbalance on target gene expression. In particular, rs7922621 is the effective variant in controlling TSPAN14 expression among other nominated variants in the same cCRE and exerts multiple physiological effects including reduced cell surface ADAM10 and altered soluble TREM2 (sTREM2) shedding. Our work represents a systematic approach to prioritize and characterize AD-associated variants and provides a roadmap for advancing genetic association to experimentally validated cell-type-specific phenotypes and mechanisms.
Collapse
Affiliation(s)
- Xiaoyu Yang
- Institute for Human Genetics, University of California, San Francisco, San Francisco, CA, USA
| | - Jia Wen
- Department of Genetics, University of North Carolina, Chapel Hill, NC, USA
| | - Han Yang
- Institute for Human Genetics, University of California, San Francisco, San Francisco, CA, USA
| | - Ian R Jones
- Institute for Human Genetics, University of California, San Francisco, San Francisco, CA, USA
- Pharmaceutical Sciences and Pharmacogenomics Graduate Program, University of California, San Francisco, San Francisco, CA, USA
| | - Xiaodong Zhu
- Helen and Robert Appel Alzheimer's Disease Research Institute, Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York City, NY, USA
| | - Weifang Liu
- Department of Genetics, University of North Carolina, Chapel Hill, NC, USA
- Department of Biostatistics, University of North Carolina, Chapel Hill, NC, USA
| | - Bingkun Li
- Institute for Human Genetics, University of California, San Francisco, San Francisco, CA, USA
| | - Claire D Clelland
- Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
- Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Wenjie Luo
- Helen and Robert Appel Alzheimer's Disease Research Institute, Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York City, NY, USA
| | - Man Ying Wong
- Helen and Robert Appel Alzheimer's Disease Research Institute, Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York City, NY, USA
| | - Xingjie Ren
- Institute for Human Genetics, University of California, San Francisco, San Francisco, CA, USA
| | - Xiekui Cui
- Institute for Human Genetics, University of California, San Francisco, San Francisco, CA, USA
| | - Michael Song
- Institute for Human Genetics, University of California, San Francisco, San Francisco, CA, USA
- Pharmaceutical Sciences and Pharmacogenomics Graduate Program, University of California, San Francisco, San Francisco, CA, USA
| | - Hongjiang Liu
- Institute for Human Genetics, University of California, San Francisco, San Francisco, CA, USA
| | - Cady Chen
- Institute for Human Genetics, University of California, San Francisco, San Francisco, CA, USA
| | - Nicolas Eng
- Institute for Human Genetics, University of California, San Francisco, San Francisco, CA, USA
| | | | - Yang Sun
- Institute for Human Genetics, University of California, San Francisco, San Francisco, CA, USA
- Division of Rheumatology, Department of Medicine, University of California, San Francisco, San Francisco, CA, USA
| | - David Lee
- Institute for Human Genetics, University of California, San Francisco, San Francisco, CA, USA
- Division of Rheumatology, Department of Medicine, University of California, San Francisco, San Francisco, CA, USA
| | - Eric Van Buren
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Min-Zhi Jiang
- Department of Genetics, University of North Carolina, Chapel Hill, NC, USA
| | - Candace S Y Chan
- Tetrad Graduate Program, University of California, San Francisco, San Francisco, CA, USA
| | - Chun Jimmie Ye
- Institute for Human Genetics, University of California, San Francisco, San Francisco, CA, USA
- Division of Rheumatology, Department of Medicine, University of California, San Francisco, San Francisco, CA, USA
- Rosalind Russell/Ephraim P. Engleman Rheumatology Research Center, University of California, San Francisco, San Francisco, CA, USA
- Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA, USA
- Parker Institute for Cancer Immunotherapy, San Francisco, CA, USA
- Chan Zuckerberg Biohub, San Francisco, CA, USA
- Bakar Computational Health Sciences Institute, University of California, San Francisco, San Francisco, CA, USA
| | - Rushika M Perera
- Department of Anatomy, University of California, San Francisco, San Francisco, CA, USA
- Department of Pathology, University of California, San Francisco, San Francisco, CA, USA
- Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, CA, USA
| | - Li Gan
- Helen and Robert Appel Alzheimer's Disease Research Institute, Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York City, NY, USA
| | - Yun Li
- Department of Genetics, University of North Carolina, Chapel Hill, NC, USA.
- Department of Biostatistics, University of North Carolina, Chapel Hill, NC, USA.
- Department of Computer Science, University of North Carolina, Chapel Hill, NC, USA.
| | - Yin Shen
- Institute for Human Genetics, University of California, San Francisco, San Francisco, CA, USA.
- Department of Neurology, University of California, San Francisco, San Francisco, CA, USA.
- Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA.
| |
Collapse
|
8
|
Jiang MZ, Gaynor SM, Li X, Van Buren E, Stilp A, Buth E, Wang FF, Manansala R, Gogarten SM, Li Z, Polfus LM, Salimi S, Bis JC, Pankratz N, Yanek LR, Durda P, Tracy RP, Rich SS, Rotter JI, Mitchell BD, Lewis JP, Psaty BM, Pratte KA, Silverman EK, Kaplan RC, Avery C, North K, Mathias RA, Faraday N, Lin H, Wang B, Carson AP, Norwood AF, Gibbs RA, Kooperberg C, Lundin J, Peters U, Dupuis J, Hou L, Fornage M, Benjamin EJ, Reiner AP, Bowler RP, Lin X, Auer PL, Raffield LM. Whole Genome Sequencing Based Analysis of Inflammation Biomarkers in the Trans-Omics for Precision Medicine (TOPMed) Consortium. bioRxiv 2023:2023.09.10.555215. [PMID: 37745480 PMCID: PMC10515765 DOI: 10.1101/2023.09.10.555215] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/26/2023]
Abstract
Inflammation biomarkers can provide valuable insight into the role of inflammatory processes in many diseases and conditions. Sequencing based analyses of such biomarkers can also serve as an exemplar of the genetic architecture of quantitative traits. To evaluate the biological insight, which can be provided by a multi-ancestry, whole-genome based association study, we performed a comprehensive analysis of 21 inflammation biomarkers from up to 38,465 individuals with whole-genome sequencing from the Trans-Omics for Precision Medicine (TOPMed) program. We identified 22 distinct single-variant associations across 6 traits - E-selectin, intercellular adhesion molecule 1, interleukin-6, lipoprotein-associated phospholipase A2 activity and mass, and P-selectin - that remained significant after conditioning on previously identified associations for these inflammatory biomarkers. We further expanded upon known biomarker associations by pairing the single-variant analysis with a rare variant set-based analysis that further identified 19 significant rare variant set-based associations with 5 traits. These signals were distinct from both significant single variant association signals within TOPMed and genetic signals observed in prior studies, demonstrating the complementary value of performing both single and rare variant analyses when analyzing quantitative traits. We also confirm several previously reported signals from semi-quantitative proteomics platforms. Many of these signals demonstrate the extensive allelic heterogeneity and ancestry-differentiated variant-trait associations common for inflammation biomarkers, a characteristic we hypothesize will be increasingly observed with well-powered, large-scale analyses of complex traits.
Collapse
Affiliation(s)
- Min-Zhi Jiang
- Department of Genetics, University of North Carolina at Chapel Hill, 120 Mason Farm Road, Chapel Hill, NC, 27599, USA
| | - Sheila M. Gaynor
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, 655 Huntington Avenue, Boston, MA, 02115, USA
- Regeneron Genetics Center, Tarrytown, NY, 10591, USA
| | - Xihao Li
- Department of Genetics, University of North Carolina at Chapel Hill, 120 Mason Farm Road, Chapel Hill, NC, 27599, USA
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Eric Van Buren
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, 655 Huntington Avenue, Boston, MA, 02115, USA
| | - Adrienne Stilp
- Department of Biostatistics, University of Washington, Seattle, WA, 98105, USA
| | - Erin Buth
- Department of Biostatistics, University of Washington, Seattle, WA, 98105, USA
| | - Fei Fei Wang
- Department of Biostatistics, University of Washington, Seattle, WA, 98105, USA
| | - Regina Manansala
- Centre for Health Economics Research & Modelling Infectious Diseases (CHERMID), Vaccine & Infectious Disease Institute (VAXINFECTIO) WHO Collaborating Centre, University of Antwerp, Antwerp, BE
| | | | - Zilin Li
- School of Mathematics and Statistics, Northeast Normal University, Changchun, Jilin, 130024, China
| | - Linda M. Polfus
- Department of Preventive Medicine, Center for Genetic Epidemiology, University of Southern California, Los Angeles, CA, 90033, USA
| | - Shabnam Salimi
- Department of Epidemiology and Public Health, Division of Gerontology, University of Maryland School of Medicine, Baltimore, MD, 21201, USA
| | - Joshua C. Bis
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, 4333 Brooklyn Ave NE, Box 359458, Seattle, WA, 98195, USA
| | - Nathan Pankratz
- Department of Laboratory Medicine and Pathology, University of Minnesota Medical School, Minneapolis, MN, 55455, USA
| | - Lisa R. Yanek
- Department of Medicine, General Internal Medicine, Johns Hopkins University School of Medicine, 1830 E Monument St Rm 8024, Baltimore, MD, 21287, USA
| | - Peter Durda
- Department of Pathology & Laboratory Medicine, University of Vermont Larner College of Medicine, 360 South Park Drive, Colchester, VT, 05446, USA
| | - Russell P. Tracy
- Department of Pathology & Laboratory Medicine, University of Vermont Larner College of Medicine, 360 South Park Drive, Colchester, VT, 05446, USA
| | - Stephen S. Rich
- Center for Public Health Genomics, University of Virginia School of Medicine, 200 Jeanette Lancaster Way, Charlottesville, VA, 22903, USA
| | - Jerome I. Rotter
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, 1124 W. Carson Street, Torrance, CA, 90502, USA
| | - Braxton D. Mitchell
- Department of Medicine, Division of Endocrinology, Diabetes, and Nutrition, University of Maryland School of Medicine, 670 W. Baltimore St., Baltimore, MD, 21201, USA
| | - Joshua P. Lewis
- Department of Medicine, Division of Endocrinology, Diabetes, and Nutrition, University of Maryland School of Medicine, 670 W. Baltimore St., Baltimore, MD, 21201, USA
| | - Bruce M. Psaty
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, 4333 Brooklyn Ave NE, Box 359458, Seattle, WA, 98195, USA
- Departments of Epidemiology and Health Systems and Population Health, University of Washington, 4333 Brooklyn Ave NE, Seattle, WA, 98101, USA
| | - Katherine A. Pratte
- Department of Medicine, Division of Pulmonary, Critical Care, and Sleep Medicine, National Jewish Health, Denver, CO, 80206, USA
| | - Edwin K. Silverman
- Department of Medicine, Channing Division of Network Medicine, Brigham and Women’s Hospital, 181 Longwood Avenue, Boston, MA, 02115, USA
| | - Robert C. Kaplan
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, 10461, USA
| | - Christy Avery
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Kari North
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Rasika A. Mathias
- Department of Medicine, Allergy and Clinical Immunology, Johns Hopkins University School of Medicine, 5501 Hopkins Bayview Cir JHAAC Room 3B53, Baltimore, MD, 21287, USA
| | - Nauder Faraday
- Department of Anesthesiology and Critical Care Medicine, Johns Hopkins University School of Medicine, 600 N Wolfe St, Baltimore, MD, 21287, USA
| | - Honghuang Lin
- Department of Medicine, University of Massachusetts Chan Medical School, 55 Lake Ave North, Worcester, MA, 01655, USA
| | - Biqi Wang
- Department of Medicine, University of Massachusetts Chan Medical School, 55 Lake Ave North, Worcester, MA, 01655, USA
| | - April P. Carson
- Department of Medicine, University of Mississippi Medical Center, 350 W. Woodrow Wilson Avenue, Suite 701, Jackson, MS, 39213, USA
| | - Arnita F. Norwood
- Department of Medicine, University of Mississippi Medical Center, 350 W. Woodrow Wilson Avenue, Suite 701, Jackson, MS, 39213, USA
| | - Richard A. Gibbs
- Department of Molecular and Human Genetics, Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, 77030, USA
| | - Charles Kooperberg
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, 98109, USA
| | - Jessica Lundin
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, 98109, USA
| | - Ulrike Peters
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, 98109, USA
| | - Josée Dupuis
- Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, Québec, H3A 1G1, Canada
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, 02118, USA
| | - Lifang Hou
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, 60611, USA
| | - Myriam Fornage
- Brown Foundation Institute of Molecular Medicine, McGovern Medical School, University of Texas Health Science Center at Houston, Houston, TX, 77030, USA
| | - Emelia J. Benjamin
- Department of Medicine, Cardiovascular Medicine, Boston Medical Center, Boston University Chobanian and Avedisian School of Medicine, Boston, MA, 02118, USA
- Department of Epidemiology, Boston University School of Public Health, Boston, MA, 02118, USA
- Boston University and National Heart, Lung, and Blood Institute’s Framingham Heart Study, Framingham, MA, 01702, USA
| | - Alexander P. Reiner
- Department of Epidemiology, University of Washington, Seattle, WA, 98105, USA
| | - Russell P. Bowler
- Department of Medicine, Division of Pulmonary, Critical Care, and Sleep Medicine, National Jewish Health, Denver, CO, 80206, USA
| | - Xihong Lin
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, 655 Huntington Avenue, Boston, MA, 02115, USA
| | - Paul L. Auer
- Division of Biostatistics, Institute for Health and Equity, and Cancer Center, Medical College of Wisconsin, Milwaukee, WI, 53226, USA
| | - Laura M. Raffield
- Department of Genetics, University of North Carolina at Chapel Hill, 120 Mason Farm Road, Chapel Hill, NC, 27599, USA
| | | |
Collapse
|
9
|
Ying JJ, Shu XL, Long G, Jiang MZ. [The association between Helicobacter pylori virulence factor genotypes and gastroduodenal diseases in children]. Zhonghua Er Ke Za Zhi 2023; 61:827-832. [PMID: 37650165 DOI: 10.3760/cma.j.cn112140-20230328-00216] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 09/01/2023]
Abstract
Objective: To investigate the association between Helicobacter pylori (Hp) virulence factor genotypes and the degree and activity of gastric mucosa pathological changes in pediatric gastroduodenal diseases. Methods: This retrospective cohort study was conducted from May 2020 to October 2020. The frozen strains of Hp, which were cultured with the gastric mucosa of 68 children with gastroscopy confirmed gastroduodenal diseases who visited the children's hospital of Zhejiang University School of Medicine from April 2012 to December 2014, were resuscitated. After extracting DNA from these Hp strains, PCR amplification and agarose gel electrophoresis were performed to determine the detection rate of cytotoxin-associated protein A (cagA),vacuolating cytotoxin A (vacA)(s1a、s1b/s2,m1/m2), outer inflammatory protein A (oipA),blood group antigen binding adhesin (babA),duodenal ulcer promoting protein A (dupA) genes; oipA genes were sequenced to determine the gene status. The patients were divided into different groups according to the findings of gastroscopy and gastric mucosa pathology. The detection rates of various virulence factor genotypes among different groups were compared using χ2 tests or Fisher's exact tests. Results: The 68 Hp strains all completed genetic testing. According to the diagnostic findings of gastroscopy, the 68 cases were divided into 47 cases of superficial gastritis and 21 cases of peptic ulcer. Regarding the pathological changes of gastric mucosa, 8 cases were mild, and 60 cases were moderate and severe according to the degree of inflammation; 61 cases were active and 7 cases inactive according to the activity of inflammation. The overall detection rates of cagA, vacA, vacA s1/m2, functional oipA, babA2, and dupA virulence factor genes were 100% (68/68), 100% (68/68), 94% (64/68), 99% (67/68), 82% (56/68), and 71% (48/68), respectively. In the superficial gastritis group, their detection rates were 100% (47/47), 100% (47/47), 96% (45/47), 98% (46/47), 81% (38/47), and 70% (33/47), respectively; in the peptic ulcer group, their detection rates were 100% (21/21), 100% (21/21), 90% (19/21), 100% (21/21), 86% (18/21), and 71% (15/21), respectively. There was no statistically significant difference between the two groups (all P>0.05). In the mild gastric mucosa inflammation group, the detection rates of the above six genotypes were 8/8, 8/8, 8/8, 7/8, 7/8, and 5/8, respectively; and in the moderate to severe inflammation groups, the detection rates were 100% (60/60), 100% (60/60), 93% (56/60), 100% (60/60), 82% (49/60), and 72% (43/60), respectively, with no statistically significant difference between the two groups (all P>0.05). In the active inflammation group, the detection rate of six genotypes were 100% (61/61), 100% (61/61), 93% (57/61), 98% (60/61), 82% (50/61), and 72% (44/61), respectively; and in the inactive inflammation group, they were 7/7, 7/7, 7/7, 7/7, 6/7, and 4/7, respectively. Again, there was no statistically significant difference between the two groups (all P>0.05). There was no statistically significant difference in the detection rate of combinations of 4 or 5 virulence factor genes among the different groups (all P>0.05). Conclusions: CagA, vacA, vacA s1/m2, functional oipA, babA2, and dupA genes are not associated with superficial gastritis and peptic ulcer in children, or with the degree and activity of gastric mucosa pathological inflammation. Different gene combinations of cagA, vacA, oipA, babA2, and dupA have no significant effects on predicting the clinical outcome of Hp infection in children.
Collapse
Affiliation(s)
- J J Ying
- Gastrointestinal Laboratory, Children's Hospital, Zhejiang University School of Medicine,National Clinical Research Center for Child Health, National Children's Regional Medical Center, Hangzhou 310052, China
| | - X L Shu
- Gastrointestinal Laboratory, Children's Hospital, Zhejiang University School of Medicine,National Clinical Research Center for Child Health, National Children's Regional Medical Center, Hangzhou 310052, China
| | - G Long
- Gastrointestinal Laboratory, Children's Hospital, Zhejiang University School of Medicine,National Clinical Research Center for Child Health, National Children's Regional Medical Center, Hangzhou 310052, China
| | - M Z Jiang
- Department of Gastroenterology and Pediatric Endoscopy Center, Children's Hospital, Zhejiang University School of Medicine,National Clinical Research Center for Child Health, National Children's Regional Medical Center, Hangzhou 310052, China
| |
Collapse
|
10
|
Jiang MZ. [Further standardize the diagnosis and treatment of Helicobacter pylori infection in children]. Zhonghua Er Ke Za Zhi 2023; 61:577-579. [PMID: 37385798 DOI: 10.3760/cma.j.cn112140-20230510-00326] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Subscribe] [Scholar Register] [Indexed: 07/01/2023]
Affiliation(s)
- M Z Jiang
- Department of Gastroenterology and Pediatric Endoscopy Center, Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, National Children's Regional Medical Center, Hangzhou 310052, China
| |
Collapse
|
11
|
Luo LL, Chen B, Shu XL, Zheng W, Long G, Jiang MZ. [The relationship between genetic polymorphism of CYP2C19 and the efficacy of Helicobacter pylori eradication therapy in children]. Zhonghua Er Ke Za Zhi 2023; 61:600-605. [PMID: 37385802 DOI: 10.3760/cma.j.cn112140-20221230-01076] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Subscribe] [Scholar Register] [Indexed: 07/01/2023]
Abstract
Objective: To investigate the relationship between genetic polymorphisms of cytochrome P450 2C19 (CYP2C19) and the efficacy of Helicobacter pylori (Hp) eradication therapy in children. Methods: The retrospective cohort study was conducted on 125 children with gastroscopy and positive rapid urease test (RUT) from September 2016 to December 2018 who presented to the Children's Hospital of Zhejiang University School of Medicine due to gastrointestinal symptoms including nausea, vomiting, abdominal pain, bloating, acid reflux, heartburn, chest pain, vomiting blood and melena. Hp culture and drug susceptibility test were carried out with gastric antrum mucosa before treatment. All the patients completed 2 weeks of standardized Hp eradication therapy and had 13C urea breath test 1 month after that, which was used to evaluate the curative effect. The DNA of gastric mucosa after RUT was analyzed and CYP2C19 gene polymorphism was detected. Children were grouped according to metabolic type. Combined with the results of Hp culture and drug susceptibility, the relationship between CYP2C19 gene polymorphism and the efficacy of Hp eradicative treatment was analyzed in children. Chi square test was used for row and column variables, and Fisher exact test was used for comparison between groups. Results: One hundred and twenty five children were enrolled in the study, of whom 76 were males and 49 females. The genetic polymorphism of CYP2C19 in these children found poor metabolizer (PM) of 30.4% (38/125), intermediate metabolizer (IM) of 20.8% (26/125), normal metabolizer (NM) of 47.2% (59/125), rapid metabolizer (RM) of 1.6% (2/125), and ultrarapid metabolizer (UM) of 0. There were statistically significant in positive rate of Hp culture among these groups (χ2=124.00, P<0.001). In addition, the successful rates of Hp eradication in PM, IM, NM and RM genotypes were 84.2% (32/38), 53.8% (14/26), 67.8% (40/59), and 0, respectively, with significant differences (χ2=11.35, P=0.010); those in IM genotype was significantly lower than that in PM genotype (P=0.011). With the same standard triple Hp eradicative regimen, the successful rate of Hp eradication for IM type was 8/19, which was lower than that of PM (80.0%, 24/30) and NM type (77.3%, 34/44) (P=0.007 and 0.007, respectively). There was a significant difference in the efficacy of Hp eradication treatment among different genotypes (χ2=9.72, P=0.008). According to the clarithromycin susceptibility result, the successful rate of Hp eradication treatment for IM genotype was 4/15 in the sensitive group and 4/4 in the drug-resistant group (χ2=6.97, P=0.018). Conclusions: The genetic polymorphism of CYP2C19 in children is closely related to the efficacy of Hp eradication treatment. PM has a higher successful rate of eradication treatment than the other genotypes.
Collapse
Affiliation(s)
- L L Luo
- Gastrointestinal Laboratory, Children's Hospital, Zhejiang University School of Medicine,National Clinical Research Center for Child Health, National Children's Regional Medical Center, Hangzhou 310052, China
| | - B Chen
- Gastrointestinal Laboratory, Children's Hospital, Zhejiang University School of Medicine,National Clinical Research Center for Child Health, National Children's Regional Medical Center, Hangzhou 310052, China
| | - X L Shu
- Gastrointestinal Laboratory, Children's Hospital, Zhejiang University School of Medicine,National Clinical Research Center for Child Health, National Children's Regional Medical Center, Hangzhou 310052, China
| | - W Zheng
- Department of Gastroenterology, Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, National Children's Regional Medical Center, Hangzhou 310052, China
| | - G Long
- Gastrointestinal Laboratory, Children's Hospital, Zhejiang University School of Medicine,National Clinical Research Center for Child Health, National Children's Regional Medical Center, Hangzhou 310052, China
| | - M Z Jiang
- Department of Gastroenterology and Pediatric Endoscopy Center, Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, National Children's Regional Medical Center, Hangzhou 310052, China
| |
Collapse
|
12
|
Jiang MZ, Aguet F, Ardlie K, Chen J, Cornell E, Cruz D, Durda P, Gabriel SB, Gerszten RE, Guo X, Johnson CW, Kasela S, Lange LA, Lappalainen T, Liu Y, Reiner AP, Smith J, Sofer T, Taylor KD, Tracy RP, VanDenBerg DJ, Wilson JG, Rich SS, Rotter JI, Love MI, Raffield LM, Li Y. Canonical correlation analysis for multi-omics: Application to cross-cohort analysis. PLoS Genet 2023; 19:e1010517. [PMID: 37216410 PMCID: PMC10237647 DOI: 10.1371/journal.pgen.1010517] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2022] [Revised: 06/02/2023] [Accepted: 05/01/2023] [Indexed: 05/24/2023] Open
Abstract
Integrative approaches that simultaneously model multi-omics data have gained increasing popularity because they provide holistic system biology views of multiple or all components in a biological system of interest. Canonical correlation analysis (CCA) is a correlation-based integrative method designed to extract latent features shared between multiple assays by finding the linear combinations of features-referred to as canonical variables (CVs)-within each assay that achieve maximal across-assay correlation. Although widely acknowledged as a powerful approach for multi-omics data, CCA has not been systematically applied to multi-omics data in large cohort studies, which has only recently become available. Here, we adapted sparse multiple CCA (SMCCA), a widely-used derivative of CCA, to proteomics and methylomics data from the Multi-Ethnic Study of Atherosclerosis (MESA) and Jackson Heart Study (JHS). To tackle challenges encountered when applying SMCCA to MESA and JHS, our adaptations include the incorporation of the Gram-Schmidt (GS) algorithm with SMCCA to improve orthogonality among CVs, and the development of Sparse Supervised Multiple CCA (SSMCCA) to allow supervised integration analysis for more than two assays. Effective application of SMCCA to the two real datasets reveals important findings. Applying our SMCCA-GS to MESA and JHS, we identified strong associations between blood cell counts and protein abundance, suggesting that adjustment of blood cell composition should be considered in protein-based association studies. Importantly, CVs obtained from two independent cohorts also demonstrate transferability across the cohorts. For example, proteomic CVs learned from JHS, when transferred to MESA, explain similar amounts of blood cell count phenotypic variance in MESA, explaining 39.0% ~ 50.0% variation in JHS and 38.9% ~ 49.1% in MESA. Similar transferability was observed for other omics-CV-trait pairs. This suggests that biologically meaningful and cohort-agnostic variation is captured by CVs. We anticipate that applying our SMCCA-GS and SSMCCA on various cohorts would help identify cohort-agnostic biologically meaningful relationships between multi-omics data and phenotypic traits.
Collapse
Affiliation(s)
- Min-Zhi Jiang
- Department of Applied Physical Sciences, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - François Aguet
- Illumina Artificial Intelligence Laboratory, Illumina, Inc., San Diego, California, United States of America
| | - Kristin Ardlie
- The Broad Institute of MIT and Harvard, Cambridge, Massachusetts, United States of America
| | - Jiawen Chen
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Elaine Cornell
- Laboratory for Clinical Biochemistry Research, University of Vermont, Burlington, Vermont, United States of America
| | - Dan Cruz
- Department of Medicine, Cardiology, Beth Israel Deaconess Medical Center, Boston, Massachusetts, United States of America
| | - Peter Durda
- Department of Pathology & Laboratory Medicine, University of Vermont, Colchester, Vermont, United States of America
| | - Stacey B. Gabriel
- The Broad Institute of MIT and Harvard, Cambridge, Massachusetts, United States of America
| | - Robert E. Gerszten
- Department of Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts, United States of America
| | - Xiuqing Guo
- Department of Pediatrics, The Institute for Translational Genomics and Population Sciences, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, University of California at Los Angeles, Torrance, California, United States of America
| | - Craig W. Johnson
- Department of Biostatistics, University of Washington at Seattle, Seattle, Washington, United States of America
| | - Silva Kasela
- New York Genome Center, New York, New York, United States of America
| | - Leslie A. Lange
- Department of Epidemiology, Department of Medicine, Division of Biomedical Informatics and Personalized Medicine, Lifecourse Epidemiology of Adiposity & Diabetes Center, Aurora, Colorado, United States of America
| | - Tuuli Lappalainen
- New York Genome Center, New York, New York, United States of America
| | - Yongmei Liu
- Department of Medicine, Cardiology and Neurology, Duke University Medical Center, Durham, North Carolina, United States of America
| | - Alex P. Reiner
- Department of Epidemiology, University of Washington, Seattle, Washington, United States of America
| | - Josh Smith
- Northwest Genomic Center, University of Washington, Seattle, Washington, United States of America
| | - Tamar Sofer
- Department of Biostatistics, Harvard Medical School, Medicine-Brigham and Women’s Hospital, Boston, Massachusetts, United States of America
| | - Kent D. Taylor
- Department of Pediatrics, The Institute for Translational Genomics and Population Sciences, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, University of California at Los Angeles, Torrance, California, United States of America
| | - Russell P. Tracy
- Department of Pathology & Laboratory Medicine, University of Vermont, Colchester, Vermont, United States of America
| | - David J. VanDenBerg
- Department of Preventive Medicine, University of Southern California, Los Angeles, California, United States of America
| | - James G. Wilson
- Department of Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts, United States of America
| | - Stephen S. Rich
- Center for Public Health Genomics, Department of Public Health Sciences, University of Virginia, Charlottesville, Virginia, United States of America
| | - Jerome I. Rotter
- Department of Pediatrics, Genomic Outcomes, The Institute for Translational Genomics and Population Sciences, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, University of California at Los Angeles, Torrance, California, United States of America
| | - Michael I. Love
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Laura M. Raffield
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Yun Li
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | | |
Collapse
|
13
|
Zheng W, Peng KR, Li FB, Zhao H, Jiang MZ. [The effect of Helicobacter pylori infection on duodenal bulbar microbiota in children with duodenal ulcer]. Zhonghua Er Ke Za Zhi 2023; 61:49-55. [PMID: 36594121 DOI: 10.3760/cma.j.cn112140-20220328-00251] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Subscribe] [Scholar Register] [Indexed: 01/04/2023]
Abstract
Objective: To investigate the characteristics of duodenal bulbar microbiota in children with duodenal ulcer and Helicobacter pylori (Hp) infection. Methods: This prospective cohort study enrolled 23 children with duodenal ulcers diagnosed by gastroscopy who were admitted to the Children's Hospital of Zhejiang University School of Medicine due to abdominal pain, abdominal distension, and vomiting from January 2018 to August 2018. They were divided into Hp-positive and Hp-negative groups according to the presence or absence of Hp infection. Duodenal bulbar mucosa was sampled to detect the bacterial DNA by high-throughput sequencing. The statistical difference in α diversity and β diversity, and the relative abundance in taxonomic level between the two groups were compared. Microbial functions were predicted using the software PICRUSt. T-test, Rank sum test or χ2 test were used for comparison between the two groups. Results: A total of 23 children diagnosed with duodenal ulcer were enrolled in this study, including 15 cases with Hp infection ((11.2±3.3) years of age, 11 males and 4 females) and 8 cases without Hp infection ((10.1±4.4) years of age, 6 males and 2 females). Compared with Hp-negative group, the Hp-positive group had higher Helicobacter abundance (0.551% (0.258%, 5.368%) vs. 0.143% (0.039%, 0.762%), Z=2.00, P=0.045) and lower abundance of Fusobacterium, Streptococcus and unclassified- Comamonadaceae (0.010% (0.001%, 0.031%) vs. 0.049% (0.011%, 0.310%), Z=-2.24, P=0.025; 0.031% (0.015%, 0.092%) vs. 0.118% (0.046%, 0.410%), Z=-2.10, P=0.036; 0.046% (0.036%, 0.062%) vs. 0.110% (0.045%, 0.176%), Z=-2.01, P=0.045). Linear discriminant analysis (LDA) effect sized showed that at the genus level, only Helicobacter was significantly enriched in Hp-positive group (LDA=4.89, P=0.045), while Streptococcus and Fusobacterium significantly enriched in Hp-negative group (LDA=3.28, 3.11;P=0.036,0.025, respectively). PICRUSt microbial function prediction showed that the expression of oxidative phosphorylation and disease-related pathways (pathways in cancer, renal cell carcinoma, amoebiasis, type 1 diabetes mellitus) in Hp-positive group were significantly higher than that in Hp-negative group (all P<0.05), while the expression of pathways such as energy metabolism and phosphotransferase system pathways were significantly lower than that in Hp-negative group (all P<0.05). Conclusion: In children with Hp-infected duodenal ulcers, the mucosal microbiota of the duodenal bulb is altered, characterized by an increased abundance of Helicobacter and a decreased abundance of Clostridium and Streptococcus, and possibly alters the biological function of the commensal microbiota through specific metabolic pathways.
Collapse
Affiliation(s)
- W Zheng
- Department of Gastroenterology, Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, National Children's Regional Medical Center, Hangzhou 310052, China
| | - K R Peng
- Department of Gastroenterology, Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, National Children's Regional Medical Center, Hangzhou 310052, China
| | - F B Li
- Department of Gastroenterology, Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, National Children's Regional Medical Center, Hangzhou 310052, China
| | - H Zhao
- Department of Gastroenterology, Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, National Children's Regional Medical Center, Hangzhou 310052, China
| | - M Z Jiang
- Department of Gastroenterology and Pediatric Endoscopy Center, Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, National Children's Regional Medical Center, Hangzhou 310052, China
| |
Collapse
|
14
|
Wheeler MM, Stilp AM, Rao S, Halldórsson BV, Beyter D, Wen J, Mihkaylova AV, McHugh CP, Lane J, Jiang MZ, Raffield LM, Jun G, Sedlazeck FJ, Metcalf G, Yao Y, Bis JB, Chami N, de Vries PS, Desai P, Floyd JS, Gao Y, Kammers K, Kim W, Moon JY, Ratan A, Yanek LR, Almasy L, Becker LC, Blangero J, Cho MH, Curran JE, Fornage M, Kaplan RC, Lewis JP, Loos RJF, Mitchell BD, Morrison AC, Preuss M, Psaty BM, Rich SS, Rotter JI, Tang H, Tracy RP, Boerwinkle E, Abecasis GR, Blackwell TW, Smith AV, Johnson AD, Mathias RA, Nickerson DA, Conomos MP, Li Y, Þorsteinsdóttir U, Magnússon MK, Stefansson K, Pankratz ND, Bauer DE, Auer PL, Reiner AP. Whole genome sequencing identifies structural variants contributing to hematologic traits in the NHLBI TOPMed program. Nat Commun 2022; 13:7592. [PMID: 36481753 PMCID: PMC9732337 DOI: 10.1038/s41467-022-35354-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2021] [Accepted: 11/29/2022] [Indexed: 12/13/2022] Open
Abstract
Genome-wide association studies have identified thousands of single nucleotide variants and small indels that contribute to variation in hematologic traits. While structural variants are known to cause rare blood or hematopoietic disorders, the genome-wide contribution of structural variants to quantitative blood cell trait variation is unknown. Here we utilized whole genome sequencing data in ancestrally diverse participants of the NHLBI Trans Omics for Precision Medicine program (N = 50,675) to detect structural variants associated with hematologic traits. Using single variant tests, we assessed the association of common and rare structural variants with red cell-, white cell-, and platelet-related quantitative traits and observed 21 independent signals (12 common and 9 rare) reaching genome-wide significance. The majority of these associations (N = 18) replicated in independent datasets. In genome-editing experiments, we provide evidence that a deletion associated with lower monocyte counts leads to disruption of an S1PR3 monocyte enhancer and decreased S1PR3 expression.
Collapse
Affiliation(s)
- Marsha M. Wheeler
- grid.34477.330000000122986657Department of Genome Sciences, University of Washington, Seattle, WA 98105 USA
| | - Adrienne M. Stilp
- grid.34477.330000000122986657Department of Biostatistics, University of Washington, Seattle, WA 98105 USA
| | - Shuquan Rao
- grid.2515.30000 0004 0378 8438Division of Hematology/Oncology, Boston Children’s Hospital, Boston, MA 02115 USA ,grid.65499.370000 0001 2106 9910Department of Pediatric Oncology, Dana-Farber Cancer Institute, Boston, MA 02115 USA ,grid.511171.2Harvard Stem Cell Institute, Boston, MA 02138 USA ,grid.66859.340000 0004 0546 1623Broad Institute, Cambridge, MA 02142 USA ,grid.38142.3c000000041936754XDepartment of Pediatrics, Harvard Medical School, Boston, MA 02115 USA ,grid.506261.60000 0001 0706 7839State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, 300020 China
| | - Bjarni V. Halldórsson
- grid.421812.c0000 0004 0618 6889deCODE genetics/Amgen Inc., Reykjavik, Iceland ,grid.9580.40000 0004 0643 5232School of Technology, Reykjavik University, Reykjavík, Iceland
| | - Doruk Beyter
- grid.421812.c0000 0004 0618 6889deCODE genetics/Amgen Inc., Reykjavik, Iceland
| | - Jia Wen
- grid.10698.360000000122483208Departments of Biostatistics, Genetics, Computer Science, Applied Physical Sciences, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599 USA
| | - Anna V. Mihkaylova
- grid.34477.330000000122986657Department of Biostatistics, University of Washington, Seattle, WA 98105 USA
| | - Caitlin P. McHugh
- grid.34477.330000000122986657Department of Biostatistics, University of Washington, Seattle, WA 98105 USA
| | - John Lane
- grid.17635.360000000419368657Department of Laboratory Medicine and Pathology, University of Minnesota Medical School, Minneapolis, MN 55455 USA
| | - Min-Zhi Jiang
- grid.10698.360000000122483208Departments of Biostatistics, Genetics, Computer Science, Applied Physical Sciences, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599 USA
| | - Laura M. Raffield
- grid.410711.20000 0001 1034 1720Department of Genetics, University of North Carolina, Chapel Hill, NC 27599 USA
| | - Goo Jun
- grid.267308.80000 0000 9206 2401Human Genetics Center, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX 77030 USA
| | - Fritz J. Sedlazeck
- grid.39382.330000 0001 2160 926XHuman Genome Sequencing Center, Baylor College of Medicine, Houston, TX USA
| | - Ginger Metcalf
- grid.39382.330000 0001 2160 926XHuman Genome Sequencing Center, Baylor College of Medicine, Houston, TX USA
| | - Yao Yao
- grid.2515.30000 0004 0378 8438Division of Hematology/Oncology, Boston Children’s Hospital, Boston, MA 02115 USA ,grid.65499.370000 0001 2106 9910Department of Pediatric Oncology, Dana-Farber Cancer Institute, Boston, MA 02115 USA ,grid.511171.2Harvard Stem Cell Institute, Boston, MA 02138 USA ,grid.66859.340000 0004 0546 1623Broad Institute, Cambridge, MA 02142 USA ,grid.38142.3c000000041936754XDepartment of Pediatrics, Harvard Medical School, Boston, MA 02115 USA
| | - Joshua B. Bis
- grid.34477.330000000122986657Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA 98101 USA
| | - Nathalie Chami
- grid.59734.3c0000 0001 0670 2351The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY 10029 USA
| | - Paul S. de Vries
- grid.267308.80000 0000 9206 2401Human Genetics Center, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX 77030 USA ,grid.267308.80000 0000 9206 2401Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX 77030 USA
| | - Pinkal Desai
- grid.5386.8000000041936877XDivision of Hematology and Oncology, Weill Cornell Medical College, New York, NY 10065 USA
| | - James S. Floyd
- grid.34477.330000000122986657Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA 98101 USA
| | - Yan Gao
- grid.251313.70000 0001 2169 2489Jackson Heart Study, Department of Medicine, University of Mississippi, Jackson, MS 39216 USA
| | - Kai Kammers
- grid.21107.350000 0001 2171 9311GeneSTAR Research Program, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21287 USA
| | - Wonji Kim
- grid.62560.370000 0004 0378 8294Channing Division of Network Medicine, Brigham and Women’s Hospital, Boston, MA 2115 USA
| | - Jee-Young Moon
- grid.251993.50000000121791997Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY 10461 USA
| | - Aakrosh Ratan
- grid.27755.320000 0000 9136 933XCenter for Public Health Genomics, University of Virginia, Charlottesville, VA 22908 USA
| | - Lisa R. Yanek
- grid.21107.350000 0001 2171 9311GeneSTAR Research Program, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21287 USA
| | - Laura Almasy
- grid.25879.310000 0004 1936 8972Children’s Hospital of Philadelphia and University of Pennsylvania School of Medicine, Philadelphia, PA 19104 USA
| | - Lewis C. Becker
- grid.21107.350000 0001 2171 9311GeneSTAR Research Program, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21287 USA
| | - John Blangero
- grid.449717.80000 0004 5374 269XDepartment of Human Genetics and South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley School of Medicine, Brownsville, TX 78520 USA
| | - Michael H. Cho
- grid.62560.370000 0004 0378 8294Channing Division of Network Medicine, Brigham and Women’s Hospital, Boston, MA 2115 USA
| | - Joanne E. Curran
- grid.449717.80000 0004 5374 269XDepartment of Human Genetics and South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley School of Medicine, Brownsville, TX 78520 USA
| | - Myriam Fornage
- grid.267308.80000 0000 9206 2401Brown Foundation Institute of Molecular Medicine, McGovern Medical School, University of Texas Health Science Center at Houston, Houston, TX 77030 USA
| | - Robert C. Kaplan
- grid.251993.50000000121791997Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY 10461 USA
| | - Joshua P. Lewis
- grid.411024.20000 0001 2175 4264Department of Medicine, Division of Endocrinology, Diabetes, and Nutrition, University of Maryland School of Medicine, Baltimore, MD USA
| | - Ruth J. F. Loos
- grid.59734.3c0000 0001 0670 2351The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY 10029 USA ,grid.59734.3c0000 0001 0670 2351Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY USA ,grid.59734.3c0000 0001 0670 2351The Mindich Child Health and Development Institute, Icahn School of Medicine at Mount Sinai, New York, NY USA ,grid.5254.60000 0001 0674 042XNovo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Braxton D. Mitchell
- grid.411024.20000 0001 2175 4264Department of Medicine, Division of Endocrinology, Diabetes, and Nutrition, University of Maryland School of Medicine, Baltimore, MD USA
| | - Alanna C. Morrison
- grid.267308.80000 0000 9206 2401Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX 77030 USA
| | - Michael Preuss
- grid.59734.3c0000 0001 0670 2351The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY 10029 USA
| | - Bruce M. Psaty
- grid.34477.330000000122986657Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA 98101 USA
| | - Stephen S. Rich
- grid.27755.320000 0000 9136 933XCenter for Public Health Genomics, University of Virginia, Charlottesville, VA 22908 USA
| | - Jerome I. Rotter
- grid.513199.6The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA 90502 USA
| | - Hua Tang
- grid.168010.e0000000419368956Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305 USA
| | - Russell P. Tracy
- grid.59062.380000 0004 1936 7689Departments of Pathology & Laboratory Medicine and Biochemistry, Larner College of Medicine at the University of Vermont, Colchester, VT 5446 USA
| | - Eric Boerwinkle
- grid.267308.80000 0000 9206 2401Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX 77030 USA
| | - Goncalo R. Abecasis
- grid.214458.e0000000086837370TOPMed Informatics Research Center, University of Michigan, Department of Biostatistics, Ann Arbor, MI 48109 USA
| | - Thomas W. Blackwell
- grid.214458.e0000000086837370TOPMed Informatics Research Center, University of Michigan, Department of Biostatistics, Ann Arbor, MI 48109 USA
| | - Albert V. Smith
- grid.214458.e0000000086837370TOPMed Informatics Research Center, University of Michigan, Department of Biostatistics, Ann Arbor, MI 48109 USA
| | - Andrew D. Johnson
- grid.279885.90000 0001 2293 4638Population Sciences Branch, Division of Intramural Research, National Heart, Lung and Blood Institute, Framingham, MA 1702 USA
| | - Rasika A. Mathias
- grid.21107.350000 0001 2171 9311GeneSTAR Research Program, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21287 USA
| | - Deborah A. Nickerson
- grid.34477.330000000122986657Department of Genome Sciences, University of Washington, Seattle, WA 98105 USA
| | - Matthew P. Conomos
- grid.34477.330000000122986657Department of Biostatistics, University of Washington, Seattle, WA 98105 USA
| | - Yun Li
- grid.10698.360000000122483208Departments of Biostatistics, Genetics, Computer Science, Applied Physical Sciences, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599 USA
| | - Unnur Þorsteinsdóttir
- grid.421812.c0000 0004 0618 6889deCODE genetics/Amgen Inc., Reykjavik, Iceland ,grid.14013.370000 0004 0640 0021Faculty of Medicine, University of Iceland, 101 Reykjavik, Iceland
| | - Magnús K. Magnússon
- grid.421812.c0000 0004 0618 6889deCODE genetics/Amgen Inc., Reykjavik, Iceland ,grid.14013.370000 0004 0640 0021Faculty of Medicine, University of Iceland, 101 Reykjavik, Iceland
| | - Kari Stefansson
- grid.421812.c0000 0004 0618 6889deCODE genetics/Amgen Inc., Reykjavik, Iceland ,grid.14013.370000 0004 0640 0021Faculty of Medicine, University of Iceland, 101 Reykjavik, Iceland
| | - Nathan D. Pankratz
- grid.17635.360000000419368657Department of Laboratory Medicine and Pathology, University of Minnesota Medical School, Minneapolis, MN 55455 USA
| | - Daniel E. Bauer
- grid.2515.30000 0004 0378 8438Division of Hematology/Oncology, Boston Children’s Hospital, Boston, MA 02115 USA ,grid.65499.370000 0001 2106 9910Department of Pediatric Oncology, Dana-Farber Cancer Institute, Boston, MA 02115 USA ,grid.511171.2Harvard Stem Cell Institute, Boston, MA 02138 USA ,grid.66859.340000 0004 0546 1623Broad Institute, Cambridge, MA 02142 USA ,grid.38142.3c000000041936754XDepartment of Pediatrics, Harvard Medical School, Boston, MA 02115 USA
| | - Paul L. Auer
- grid.30760.320000 0001 2111 8460Division of Biostatistics, Institute for Health and Equity, and Cancer Center, Medical College of Wisconsin, Milwaukee, WI 53226 USA
| | - Alex P. Reiner
- grid.34477.330000000122986657Department of Epidemiology, University of Washington, Seattle, WA 98105 USA
| |
Collapse
|
15
|
Sun Q, Yang Y, Rosen JD, Jiang MZ, Chen J, Liu W, Wen J, Raffield LM, Pace RG, Zhou YH, Wright FA, Blackman SM, Bamshad MJ, Gibson RL, Cutting GR, Knowles MR, Schrider DR, Fuchsberger C, Li Y. MagicalRsq: Machine-learning-based genotype imputation quality calibration. Am J Hum Genet 2022; 109:1986-1997. [PMID: 36198314 PMCID: PMC9674945 DOI: 10.1016/j.ajhg.2022.09.009] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2022] [Accepted: 09/16/2022] [Indexed: 01/26/2023] Open
Abstract
Whole-genome sequencing (WGS) is the gold standard for fully characterizing genetic variation but is still prohibitively expensive for large samples. To reduce costs, many studies sequence only a subset of individuals or genomic regions, and genotype imputation is used to infer genotypes for the remaining individuals or regions without sequencing data. However, not all variants can be well imputed, and the current state-of-the-art imputation quality metric, denoted as standard Rsq, is poorly calibrated for lower-frequency variants. Here, we propose MagicalRsq, a machine-learning-based method that integrates variant-level imputation and population genetics statistics, to provide a better calibrated imputation quality metric. Leveraging WGS data from the Cystic Fibrosis Genome Project (CFGP), and whole-exome sequence data from UK BioBank (UKB), we performed comprehensive experiments to evaluate the performance of MagicalRsq compared to standard Rsq for partially sequenced studies. We found that MagicalRsq aligns better with true R2 than standard Rsq in almost every situation evaluated, for both European and African ancestry samples. For example, when applying models trained from 1,992 CFGP sequenced samples to an independent 3,103 samples with no sequencing but TOPMed imputation from array genotypes, MagicalRsq, compared to standard Rsq, achieved net gains of 1.4 million rare, 117k low-frequency, and 18k common variants, where net gains were gained numbers of correctly distinguished variants by MagicalRsq over standard Rsq. MagicalRsq can serve as an improved post-imputation quality metric and will benefit downstream analysis by better distinguishing well-imputed variants from those poorly imputed. MagicalRsq is freely available on GitHub.
Collapse
Affiliation(s)
- Quan Sun
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Yingxi Yang
- Department of Statistics and Data Science, Yale University, New Haven, CT 06520, USA
| | - Jonathan D Rosen
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Min-Zhi Jiang
- Department of Applied Physical Sciences, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Jiawen Chen
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Weifang Liu
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Jia Wen
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Laura M Raffield
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Rhonda G Pace
- Marsico Lung Institute/UNC CF Research Center, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Yi-Hui Zhou
- Department of Biological Sciences, North Carolina State University, Raleigh, NC 27695, USA
| | - Fred A Wright
- Department of Biological Sciences, North Carolina State University, Raleigh, NC 27695, USA; Bioinformatics Research Center and Department of Statistics, North Carolina State University, Raleigh, NC 27695, USA
| | - Scott M Blackman
- Division of Pediatric Endocrinology, Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA
| | - Michael J Bamshad
- Department of Pediatrics, University of Washington, Seattle, WA 98105, USA; Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA
| | - Ronald L Gibson
- Department of Pediatrics, University of Washington, Seattle, WA 98105, USA
| | - Garry R Cutting
- Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA
| | - Michael R Knowles
- Marsico Lung Institute/UNC CF Research Center, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Daniel R Schrider
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Christian Fuchsberger
- Institute for Biomedicine, Eurac Research (affiliated with the University of Lübeck), Bolzano, Italy.
| | - Yun Li
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA; Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
| |
Collapse
|
16
|
Jiang MZ, Zhu HZ, Zhou N, Liu C, Jiang CY, Wang Y, Liu SJ. Droplet microfluidics-based high-throughput bacterial cultivation for validation of taxon pairs in microbial co-occurrence networks. Sci Rep 2022; 12:18145. [PMID: 36307549 PMCID: PMC9616874 DOI: 10.1038/s41598-022-23000-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2022] [Accepted: 10/21/2022] [Indexed: 12/31/2022] Open
Abstract
Co-occurrence networks inferred from the abundance data of microbial communities are widely applied to predict microbial interactions. However, the high workloads of bacterial isolation and the complexity of the networks themselves constrained experimental demonstrations of the predicted microbial associations and interactions. Here, we integrate droplet microfluidics and bar-coding logistics for high-throughput bacterial isolation and cultivation from environmental samples, and experimentally investigate the relationships between taxon pairs inferred from microbial co-occurrence networks. We collected Potamogeton perfoliatus plants (including roots) and associated sediments from Beijing Olympic Park wetland. Droplets of series diluted homogenates of wetland samples were inoculated into 126 96-well plates containing R2A and TSB media. After 10 days of cultivation, 65 plates with > 30% wells showed microbial growth were selected for the inference of microbial co-occurrence networks. We cultivated 129 bacterial isolates belonging to 15 species that could represent the zero-level OTUs (Zotus) in the inferred co-occurrence networks. The co-cultivations of bacterial isolates corresponding to the prevalent Zotus pairs in networks were performed on agar plates and in broth. Results suggested that positively associated Zotu pairs in the co-occurrence network implied complicated relations including neutralism, competition, and mutualism, depending on bacterial isolate combination and cultivation time.
Collapse
Affiliation(s)
- Min-Zhi Jiang
- grid.27255.370000 0004 1761 1174State Key Laboratory of Microbial Technology, Shandong University, Qingdao, 266000 People’s Republic of China
| | - Hai-Zhen Zhu
- grid.9227.e0000000119573309State Key Laboratory of Microbial Resources, and Environmental Microbiology Research Center (EMRC), Institute of Microbiology, Chinese Academy of Sciences, Beijing, 100101 People’s Republic of China
| | - Nan Zhou
- grid.9227.e0000000119573309State Key Laboratory of Microbial Resources, and Environmental Microbiology Research Center (EMRC), Institute of Microbiology, Chinese Academy of Sciences, Beijing, 100101 People’s Republic of China
| | - Chang Liu
- grid.9227.e0000000119573309State Key Laboratory of Microbial Resources, and Environmental Microbiology Research Center (EMRC), Institute of Microbiology, Chinese Academy of Sciences, Beijing, 100101 People’s Republic of China
| | - Cheng-Ying Jiang
- grid.9227.e0000000119573309State Key Laboratory of Microbial Resources, and Environmental Microbiology Research Center (EMRC), Institute of Microbiology, Chinese Academy of Sciences, Beijing, 100101 People’s Republic of China
| | - Yulin Wang
- grid.27255.370000 0004 1761 1174State Key Laboratory of Microbial Technology, Shandong University, Qingdao, 266000 People’s Republic of China
| | - Shuang-Jiang Liu
- grid.27255.370000 0004 1761 1174State Key Laboratory of Microbial Technology, Shandong University, Qingdao, 266000 People’s Republic of China ,grid.9227.e0000000119573309State Key Laboratory of Microbial Resources, and Environmental Microbiology Research Center (EMRC), Institute of Microbiology, Chinese Academy of Sciences, Beijing, 100101 People’s Republic of China ,grid.410726.60000 0004 1797 8419University of Chinese Academy of Sciences, Beijing, 100049 People’s Republic of China
| |
Collapse
|
17
|
Liu C, Du MX, Abuduaini R, Yu HY, Li DH, Wang YJ, Zhou N, Jiang MZ, Niu PX, Han SS, Chen HH, Shi WY, Wu L, Xin YH, Ma J, Zhou Y, Jiang CY, Liu HW, Liu SJ. Correction: Enlightening the taxonomy darkness of human gut microbiomes with a cultured biobank. Microbiome 2022; 10:163. [PMID: 36192813 PMCID: PMC9528141 DOI: 10.1186/s40168-022-01370-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/16/2023]
Affiliation(s)
- Chang Liu
- State Key Laboratory of Microbial Resources, Institute of Microbiology, Chinese Academy of Sciences, No.1 Beichenxi Road, Chaoyang District, Beijing, 100101, PR China.
- Environmental Microbiology Research Center, Institute of Microbiology, Chinese Academy of Sciences, No.1 Beichenxi Road, Chaoyang District, Beijing, 100101, China.
| | - Meng-Xuan Du
- State Key Laboratory of Microbial Resources, Institute of Microbiology, Chinese Academy of Sciences, No.1 Beichenxi Road, Chaoyang District, Beijing, 100101, PR China
| | - Rexiding Abuduaini
- State Key Laboratory of Microbial Resources, Institute of Microbiology, Chinese Academy of Sciences, No.1 Beichenxi Road, Chaoyang District, Beijing, 100101, PR China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Hai-Ying Yu
- State Key Laboratory of Microbial Resources, Institute of Microbiology, Chinese Academy of Sciences, No.1 Beichenxi Road, Chaoyang District, Beijing, 100101, PR China
| | - Dan-Hua Li
- State Key Laboratory of Microbial Resources, Institute of Microbiology, Chinese Academy of Sciences, No.1 Beichenxi Road, Chaoyang District, Beijing, 100101, PR China
- Environmental Microbiology Research Center, Institute of Microbiology, Chinese Academy of Sciences, No.1 Beichenxi Road, Chaoyang District, Beijing, 100101, China
| | - Yu-Jing Wang
- State Key Laboratory of Microbial Resources, Institute of Microbiology, Chinese Academy of Sciences, No.1 Beichenxi Road, Chaoyang District, Beijing, 100101, PR China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Nan Zhou
- State Key Laboratory of Microbial Resources, Institute of Microbiology, Chinese Academy of Sciences, No.1 Beichenxi Road, Chaoyang District, Beijing, 100101, PR China
- Environmental Microbiology Research Center, Institute of Microbiology, Chinese Academy of Sciences, No.1 Beichenxi Road, Chaoyang District, Beijing, 100101, China
| | - Min-Zhi Jiang
- State Key Laboratory of Microbial Resources, Institute of Microbiology, Chinese Academy of Sciences, No.1 Beichenxi Road, Chaoyang District, Beijing, 100101, PR China
| | - Peng-Xia Niu
- State Key Laboratory of Microbial Resources, Institute of Microbiology, Chinese Academy of Sciences, No.1 Beichenxi Road, Chaoyang District, Beijing, 100101, PR China
- Environmental Microbiology Research Center, Institute of Microbiology, Chinese Academy of Sciences, No.1 Beichenxi Road, Chaoyang District, Beijing, 100101, China
| | - Shan-Shan Han
- State Key Laboratory of Microbial Resources, Institute of Microbiology, Chinese Academy of Sciences, No.1 Beichenxi Road, Chaoyang District, Beijing, 100101, PR China
| | - Hong-He Chen
- State Key Laboratory of Microbial Resources, Institute of Microbiology, Chinese Academy of Sciences, No.1 Beichenxi Road, Chaoyang District, Beijing, 100101, PR China
- Environmental Microbiology Research Center, Institute of Microbiology, Chinese Academy of Sciences, No.1 Beichenxi Road, Chaoyang District, Beijing, 100101, China
| | - Wen-Yu Shi
- State Key Laboratory of Microbial Resources, Institute of Microbiology, Chinese Academy of Sciences, No.1 Beichenxi Road, Chaoyang District, Beijing, 100101, PR China
- Microbial Resources and Big Data Center, Institute of Microbiology, Chinese Academy of Sciences, No.1 Beichenxi Road, Chaoyang District, Beijing, 100101, China
| | - Linhuan Wu
- State Key Laboratory of Microbial Resources, Institute of Microbiology, Chinese Academy of Sciences, No.1 Beichenxi Road, Chaoyang District, Beijing, 100101, PR China
- Microbial Resources and Big Data Center, Institute of Microbiology, Chinese Academy of Sciences, No.1 Beichenxi Road, Chaoyang District, Beijing, 100101, China
| | - Yu-Hua Xin
- State Key Laboratory of Microbial Resources, Institute of Microbiology, Chinese Academy of Sciences, No.1 Beichenxi Road, Chaoyang District, Beijing, 100101, PR China
- China General Microorganism Culture Collection, Institute of Microbiology, Chinese Academy of Sciences, No.1 Beichenxi Road, Chaoyang District, Beijing, 100101, China
| | - Juncai Ma
- State Key Laboratory of Microbial Resources, Institute of Microbiology, Chinese Academy of Sciences, No.1 Beichenxi Road, Chaoyang District, Beijing, 100101, PR China
- Microbial Resources and Big Data Center, Institute of Microbiology, Chinese Academy of Sciences, No.1 Beichenxi Road, Chaoyang District, Beijing, 100101, China
| | - Yuguang Zhou
- State Key Laboratory of Microbial Resources, Institute of Microbiology, Chinese Academy of Sciences, No.1 Beichenxi Road, Chaoyang District, Beijing, 100101, PR China
- China General Microorganism Culture Collection, Institute of Microbiology, Chinese Academy of Sciences, No.1 Beichenxi Road, Chaoyang District, Beijing, 100101, China
| | - Cheng-Ying Jiang
- State Key Laboratory of Microbial Resources, Institute of Microbiology, Chinese Academy of Sciences, No.1 Beichenxi Road, Chaoyang District, Beijing, 100101, PR China
- Environmental Microbiology Research Center, Institute of Microbiology, Chinese Academy of Sciences, No.1 Beichenxi Road, Chaoyang District, Beijing, 100101, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Hong-Wei Liu
- University of Chinese Academy of Sciences, Beijing, 100049, China
- State Key Laboratory of Mycology, Institute of Microbiology, Chinese Academy of Sciences, No. 1 Beichenxi Road, Chaoyang District, Beijing, 100101, China
| | - Shuang-Jiang Liu
- State Key Laboratory of Microbial Resources, Institute of Microbiology, Chinese Academy of Sciences, No.1 Beichenxi Road, Chaoyang District, Beijing, 100101, PR China.
- Environmental Microbiology Research Center, Institute of Microbiology, Chinese Academy of Sciences, No.1 Beichenxi Road, Chaoyang District, Beijing, 100101, China.
- University of Chinese Academy of Sciences, Beijing, 100049, China.
| |
Collapse
|
18
|
Wu YH, Jiang MZ. [Relationship between gastric mucosal cholesterol and Helicobacter pylori infection and its immune evasion mechanism]. Zhonghua Er Ke Za Zhi 2022; 60:719-722. [PMID: 35768365 DOI: 10.3760/cma.j.cn112140-20220401-00269] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Affiliation(s)
- Y H Wu
- Pediatric Endoscopy Center and Department of Gastroenterology, the Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, National Children's Regional Medical Center, Hangzhou 310052, China
| | - M Z Jiang
- Pediatric Endoscopy Center and Department of Gastroenterology, the Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, National Children's Regional Medical Center, Hangzhou 310052, China
| |
Collapse
|
19
|
Bie SX, Jiang MZ. [Analysis of clinical characteristics of 126 children with recurrent intussusception]. Zhonghua Er Ke Za Zhi 2022; 60:655-659. [PMID: 35768352 DOI: 10.3760/cma.j.cn112140-20220321-00229] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Objective: To analyze and summarize the clinical features in children with recurrent intussusception. Methods: This retrospective cohort study collected the clinical data of 126 children with recurrent intussusception who were admitted to the Children's Hospital of Zhejiang University School of Medicine due to "abdominal pain, paroxysmal crying, vomiting, bloody stools" from January 1, 2015 to November 30, 2019. The clinical manifestations of recurrent intussusception between ≤3 years old group and >3 years old group were compared, the etiology and age characteristics of pathologic lead points (PLP) were analyzed, and the clinical characteristics of PLP group and non-PLP group were also compared. The χ2 test and Mann-Whitney U test were used to compare the differences between groups. Results: A total of 126 children with recurrent intussusception were included, of whom 76 were males and 50 were females, with the age of 2.9 (1.7, 5.1) years. The proportion of children aged more than 1 year was 87.3% (110/126), and 48.4% (61/126) more than 3 years. Clinical manifestations mostly lacked the typical triad of symptoms. The percentage of paroxysmal crying in ≤ 3 years old group was significantly higher than that in >3 years old group (52.3% (34/65) vs. 24.6% (15/61), χ2=10.17, P=0.001), while the percentage of abdominal pain was significantly lower than that in the >3 years old group (46.1% (30/65) vs. 75.4% (46/61), χ2=11.25, P=0.001). The rate of positive ultrasound examination was 17.5% (22/126), and 63.6% (14/22) of them were diagnosed. The positive rate of CT examination was 4/13, of which 2 cases were diagnosed. In this study, 37 children were diagnosed with PLP by colonoscopy, laparoscopy or laparotomy, and 89 children were found without PLP. The positive rate of PLP in >3 years old group was significantly higher than that in ≤3 years old group (37.7% (23/61) vs. 21.5% (14/65), χ2=3.96, P=0.046). Meckel's diverticulum and juvenile polyp were the main contributors of PLP in ≤3 years old group, accounting for 7/14 and 3/14 respectively, while lymphoma and juvenile polyp accounted for 34.8% (8/23) and 26.1% (6/23), respectively in >3 years old group. Compared with non-PLP group, PLP group had higher age (5.2 (1.6, 6.7) vs. 2.7 (1.8, 4.2) years, Z=-2.26, P=0.01). However, there were no significant differences in gender and recurrence frequency between the two groups (both P>0.05). Conclusions: Recurrent intussusception is more common in children more than 1 year old, and has a wide spectrum of non-specific clinical presentations. Imaging examinations can be used to identify PLP. The most recurrent intussusception is idiopathic, but the presence of PLP should be alerted for, such as Meckel's diverticulum, lymphoma and juvenile polyp. Colonoscopy sometimes is necessary, surgical exploration and treatment should be carried out in time.
Collapse
Affiliation(s)
- S X Bie
- Pediatric Endoscopy Center and Department of Gastroenterology, the Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, National Children's Regional Medical Center, Hangzhou 310052, China
| | - M Z Jiang
- Pediatric Endoscopy Center and Department of Gastroenterology, the Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, National Children's Regional Medical Center, Hangzhou 310052, China
| |
Collapse
|
20
|
Sun XW, Abdugheni R, Huang HJ, Wang YJ, Jiang MZ, Liu C, Zhou N, Jiang H, Liu SJ. Bacteroides propionicigenes sp. nov., isolated from human faeces. Int J Syst Evol Microbiol 2022; 72. [DOI: 10.1099/ijsem.0.005397] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023] Open
Abstract
An anaerobic bacterial strain, designated as NSJ-90T, was isolated from the faeces of a healthy adult in China. Cells of strain NSJ-90T were Gram-stain-negative, non-motile, non-spore-forming and rod-shaped. Based on 16S rRNA gene sequence analysis, strain NSJ-90T belonged to the genus
Bacteroides
and was phylogenetically closely related to
Bacteroides clarus
YIT 12056T (16S rRNA gene identity was 97.04 %). The DNA G+C content of strain NSJ-90T was 44.85 mol% (calculated from the genome). The average nucleotide identity between strain NSJ-90T and
B. clarus
YIT 12056T was 87.60 %. The major cellular fatty acids (>10 %) of strain NSJ-90T were iso-C15 : 0, anteiso-C15 : 0 and iso-C17 : 0 3-OH. Menaquinone-10 was detected as the respiratory quinone. The major products of glucose fermentation were acetic, propionic and isovaleric acids. Based on its phylogenetic, phenotypic and chemotaxonomic characteristics, we propose that strain NSJ-90T represents a novel species of the genus
Bacteroides
, for which the name Bacteroides propionicigenes sp. nov. is proposed. The type strain is NSJ-90T (=CGMCC 1.17886T=KCTC 25305T).
Collapse
Affiliation(s)
- Xin-Wei Sun
- State Key Laboratory of Microbial Biotechnology, Shandong University, Qingdao 266000, PR China
| | - Rashidin Abdugheni
- University of Chinese Academy of Sciences, Beijing 100049, PR China
- State Key Laboratory of Microbial Resources, and Environmental Microbiology Research Center (EMRC), Institute of Microbiology, Chinese Academy of Sciences, Beijing 100101, PR China
| | - Hao-Jie Huang
- State Key Laboratory of Microbial Resources, and Environmental Microbiology Research Center (EMRC), Institute of Microbiology, Chinese Academy of Sciences, Beijing 100101, PR China
- State Key Laboratory of Microbial Biotechnology, Shandong University, Qingdao 266000, PR China
| | - Yu-Jing Wang
- University of Chinese Academy of Sciences, Beijing 100049, PR China
- State Key Laboratory of Microbial Resources, and Environmental Microbiology Research Center (EMRC), Institute of Microbiology, Chinese Academy of Sciences, Beijing 100101, PR China
| | - Min-Zhi Jiang
- State Key Laboratory of Microbial Biotechnology, Shandong University, Qingdao 266000, PR China
| | - Chang Liu
- State Key Laboratory of Microbial Resources, and Environmental Microbiology Research Center (EMRC), Institute of Microbiology, Chinese Academy of Sciences, Beijing 100101, PR China
| | - Nan Zhou
- State Key Laboratory of Microbial Resources, and Environmental Microbiology Research Center (EMRC), Institute of Microbiology, Chinese Academy of Sciences, Beijing 100101, PR China
| | - He Jiang
- State Key Laboratory of Microbial Biotechnology, Shandong University, Qingdao 266000, PR China
| | - Shuang-Jiang Liu
- University of Chinese Academy of Sciences, Beijing 100049, PR China
- State Key Laboratory of Microbial Resources, and Environmental Microbiology Research Center (EMRC), Institute of Microbiology, Chinese Academy of Sciences, Beijing 100101, PR China
- State Key Laboratory of Microbial Biotechnology, Shandong University, Qingdao 266000, PR China
| |
Collapse
|
21
|
Zheng W, Jiang X, Wang BX, Jiang MZ. [Summary of the Forum on Standardized Diagnosis, Treatment and Management of Pediatric Diseases: the 12th National Pediatric Gastrointestinal Diseases Conference]. Zhonghua Er Ke Za Zhi 2021; 59:893-894. [PMID: 34587691 DOI: 10.3760/cma.j.cn112140-20210730-00637] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Affiliation(s)
- W Zheng
- Department of Gastroenterology, the Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, National Children's Regional Medical Center,Hangzhou 310052, China
| | - X Jiang
- Department of Pediatrics, the Second Affiliated Hospital of Air Force Medical University (Tangdu Hospital), Xi'an 710038, China
| | - B X Wang
- Department of Pediatrics, the Second Affiliated Hospital of Air Force Medical University (Tangdu Hospital), Xi'an 710038, China
| | - M Z Jiang
- Department of Gastroenterology, the Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, National Children's Regional Medical Center,Hangzhou 310052, China
| |
Collapse
|
22
|
Zhu HZ, Jiang MZ, Zhou N, Jiang CY, Liu SJ. Submerged macrophytes recruit unique microbial communities and drive functional zonation in an aquatic system. Appl Microbiol Biotechnol 2021; 105:7517-7528. [PMID: 34519857 DOI: 10.1007/s00253-021-11565-8] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2021] [Revised: 06/21/2021] [Accepted: 09/01/2021] [Indexed: 11/30/2022]
Abstract
Aquatic and wetland systems are widely used for landscapes and water regeneration. Microbiomes and submerged macrophytes (hydrophytes) play essential roles in conversions of organic and inorganic compounds in those ecosystems. The systems were extensively investigated for microbial diversities and compositions. However, little is known about how hydrophytes recruited diverse microbiota and affected functional zonation in aquatic systems. To address this issue, epiphytic leaf and root, sediment, and surrounding water samples were collected from the dragon-shape aquatic system in Beijing Olympic Park. Metagenomic DNAs were extracted and subjected to sequencing. Results showed that epiphytic leaf and root microbiomes and metabolic marker genes were remarkably different from that of surrounding environment. Twenty indicator bacterial genera for epiphytic microbiomes were identified and 50 metabolic marker genes were applied to evaluate the function of epiphytic leaf and root, water, and sediment microbiomes. Co-occurrence analysis revealed highly modularized pattern of metabolic marker genes and indicator bacterial genera related to metabolic functions. These results suggested that hydrophytes shaped microbiomes and drove functional zonation in aquatic systems. KEY POINTS: • Microbiomes of hydrophytes and their surrounding environments were investigated. • Twenty indicator bacterial genera highly specific to epiphytic biofilms were identified. • Epiphytes recruited unique microbiomes and drove functional zonation in aquatic systems.
Collapse
Affiliation(s)
- Hai-Zhen Zhu
- State Key Laboratory of Microbial Resources and Environmental Microbiology Research Center, Institute of Microbiology, Chinese Academy of Sciences, Beichen Xilu No.1, Chaoyang District, Beijing, 100101, People's Republic of China
| | - Min-Zhi Jiang
- State Key Laboratory of Microbial Resources and Environmental Microbiology Research Center, Institute of Microbiology, Chinese Academy of Sciences, Beichen Xilu No.1, Chaoyang District, Beijing, 100101, People's Republic of China.,State Key Laboratory of Microbial Technology, Shandong University, Tsingdao, 266237, People's Republic of China
| | - Nan Zhou
- State Key Laboratory of Microbial Resources and Environmental Microbiology Research Center, Institute of Microbiology, Chinese Academy of Sciences, Beichen Xilu No.1, Chaoyang District, Beijing, 100101, People's Republic of China
| | - Cheng-Ying Jiang
- State Key Laboratory of Microbial Resources and Environmental Microbiology Research Center, Institute of Microbiology, Chinese Academy of Sciences, Beichen Xilu No.1, Chaoyang District, Beijing, 100101, People's Republic of China.,University of Chinese Academy of Sciences, Beijing, 100049, People's Republic of China
| | - Shuang-Jiang Liu
- State Key Laboratory of Microbial Resources and Environmental Microbiology Research Center, Institute of Microbiology, Chinese Academy of Sciences, Beichen Xilu No.1, Chaoyang District, Beijing, 100101, People's Republic of China. .,State Key Laboratory of Microbial Technology, Shandong University, Tsingdao, 266237, People's Republic of China. .,University of Chinese Academy of Sciences, Beijing, 100049, People's Republic of China.
| |
Collapse
|
23
|
Zheng W, Peng KR, Li FB, Zhao H, Jiang LQ, Chen FB, Jiang MZ. [Characteristics of gastric mucosa microbiota in children with chronic gastritis and duodenal ulcer]. Zhonghua Er Ke Za Zhi 2021; 59:551-556. [PMID: 34405636 DOI: 10.3760/cma.j.cn112140-20210331-00270] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
Objective: To investigate the differences of gastric mucosa microbiota between children with chronic gastritis and duodenal ulcer under the condition of Helicobacter pylori (Hp) infection. Methods: This prospective cohort study involved 57 children with Hp infection diagnosed by gastric endoscopy who were admitted to the Children's Hospital of Zhejiang University School of Medicine due to "abdominal pain, abdominal distension and vomiting" between January 2018 to August 2018. According to gastroscopy and pathological examination, the children were divided into chronic gastritis group and duodenal ulcer group. Gastric mucosa from Hp infected patients were sampled, and the flora DNA was analyzed by high-throughput sequencing. The statistical difference of α diversity, β diversity between two groups were analyzed. The relative abundance of the two groups in each taxonomic level was analyzed statistically. T test, Rank sum test or χ2 test was used for comparison between the two groups. Results: A total of 57 children diagnosed with Hp infection were enrolled in this study, including 42 cases of chronic gastritis (the age was (9.3±2.8) years, 22 males and 20 females) and 15 cases of duodenal ulcer (the age was (11.1±3.3) years, 9 males and 6 females). Alpha diversity index Chao and ACE in Hp infected chronic gastritis group were significantly higher than those in Hp infected duodenal ulcer group (217±50 vs. 183±64, t=2.088, P=0.009;218±47 vs. 192±76, t=1.566, P=0.016, respectively). The Beta-diversity index such as nonmetric multidimensional scaling (NMDS) analysis were significantly different in the two groups (analysis of similarity R=0.304, P=0.028). Among the main bacteria genera, there were 6 genera with significant differences between the two groups, which were Prevotella (0.190% (0.008%-1.983%) vs. 0.021% (0.005%-2.398%), Z=-2.537, P=0.011), Alloprevotella (0.097% (0.010%-0.813%) vs. 0.015% (0.003%-0.576%), Z=-2.492, P=0.013), Haemophilus (0.109% (0.004%-0.985%) vs. 0.014% (0.004%-0.356%), Z=-2.900, P=0.004), Neisseria (0.074% (0.004%-0.999%) vs. 0.024% (0.003%-0.255%), Z=-2.718, P=0.007), Streptococcus (0.166% (0.008%-1.869%) vs. 0.045% (0.006%-0.879%), Z=-2.537, P=0.010), and an unclassified-Microbacteriaceae (0.214% (0.060%-1.762%) vs. 0.117% (0.010%-0.954%), Z=-2.120, P=0.034). Linear discriminant analysis (LDA) effect sized analysis showed that at the genus level, only Prevotella was significantly enriched in the duodenal ulcer group (LDA=2.90, P=0.010), while Streptococcus, Neisseria and Haemophilus were significantly enriched in the chronic gastritis group (LDA=2.83, 2.82, 2.69, P=0.011, 0.007, 0.004, respectively). Conclusions: The gastric mucosal microbiota in duodenal ulcer associated with Hp is significantly different from that in chronic gastritis. Hp may promote the occurrence of peptic ulcer together with gastric microbiota.
Collapse
Affiliation(s)
- W Zheng
- Department of Gastroenterology, Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, National Children's Regional Medical Center, Hangzhou 310052, China
| | - K R Peng
- Department of Gastroenterology, Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, National Children's Regional Medical Center, Hangzhou 310052, China
| | - F B Li
- Department of Gastroenterology, Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, National Children's Regional Medical Center, Hangzhou 310052, China
| | - H Zhao
- Department of Gastroenterology, Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, National Children's Regional Medical Center, Hangzhou 310052, China
| | - L Q Jiang
- Department of Gastroenterology, Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, National Children's Regional Medical Center, Hangzhou 310052, China
| | - F B Chen
- Department of Gastroenterology, Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, National Children's Regional Medical Center, Hangzhou 310052, China
| | - M Z Jiang
- Department of Gastroenterology, Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, National Children's Regional Medical Center, Hangzhou 310052, China
| |
Collapse
|
24
|
Jiang MZ. [Strengthen the research on the relationship between gut microbiota and digestive system diseases in children]. Zhonghua Er Ke Za Zhi 2021; 59:537-540. [PMID: 34405633 DOI: 10.3760/cma.j.cn112140-20210517-00431] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Affiliation(s)
- M Z Jiang
- Department of Gastroenterology, Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, National Children's Regional Medical Center, Hangzhou 310052, China
| |
Collapse
|
25
|
Liu C, Du MX, Abuduaini R, Yu HY, Li DH, Wang YJ, Zhou N, Jiang MZ, Niu PX, Han SS, Chen HH, Shi WY, Wu L, Xin YH, Ma J, Zhou Y, Jiang CY, Liu HW, Liu SJ. Enlightening the taxonomy darkness of human gut microbiomes with a cultured biobank. Microbiome 2021; 9:119. [PMID: 34020714 PMCID: PMC8140505 DOI: 10.1186/s40168-021-01064-3] [Citation(s) in RCA: 43] [Impact Index Per Article: 14.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/21/2021] [Accepted: 03/30/2021] [Indexed: 05/07/2023]
Abstract
BACKGROUND In gut microbiome studies, the cultured gut microbial resource plays essential roles, such as helping to unravel gut microbial functions and host-microbe interactions. Although several major studies have been performed to elucidate the cultured human gut microbiota, up to 70% of the Unified Human Gastrointestinal Genome species have not been cultured to date. Large-scale gut microbial isolation and identification as well as availability to the public are imperative for gut microbial studies and further characterizing human gut microbial functions. RESULTS In this study, we constructed a human Gut Microbial Biobank (hGMB; homepage: hgmb.nmdc.cn ) through the cultivation of 10,558 isolates from 31 sample mixtures of 239 fresh fecal samples from healthy Chinese volunteers, and deposited 1170 strains representing 400 different species in culture collections of the International Depository Authority for long-term preservation and public access worldwide. Following the rules of the International Code of Nomenclature of Prokaryotes, 102 new species were characterized and denominated, while 28 new genera and 3 new families were proposed. hGMB represented over 80% of the common and dominant human gut microbial genera and species characterized from global human gut 16S rRNA gene amplicon data (n = 11,647) and cultured 24 "most-wanted" and "medium priority" taxa proposed by the Human Microbiome Project. We in total sequenced 115 genomes representing 102 novel taxa and 13 previously known species. Further in silico analysis revealed that the newly sequenced hGMB genomes represented 22 previously uncultured species in the Unified Human Gastrointestinal Genome (UHGG) and contributed 24 representatives of potentially "dark taxa" that had not been discovered by UHGG. The nonredundant gene catalogs generated from the hGMB genomes covered over 50% of the functionally known genes (KEGG orthologs) in the largest global human gut gene catalogs and approximately 10% of the "most wanted" functionally unknown proteins in the FUnkFams database. CONCLUSIONS A publicly accessible human Gut Microbial Biobank (hGMB) was established that contained 1170 strains and represents 400 human gut microbial species. hGMB expands the gut microbial resources and genomic repository by adding 102 novel species, 28 new genera, 3 new families, and 115 new genomes of human gut microbes. Video abstract.
Collapse
Affiliation(s)
- Chang Liu
- State Key Laboratory of Microbial Resources, Institute of Microbiology, Chinese Academy of Sciences, No.1 Beichenxi Road, Chaoyang District, Beijing, 100101, PR China.
- Environmental Microbiology Research Center, Institute of Microbiology, Chinese Academy of Sciences, No.1 Beichenxi Road, Chaoyang District, Beijing, 100101, China.
| | - Meng-Xuan Du
- State Key Laboratory of Microbial Resources, Institute of Microbiology, Chinese Academy of Sciences, No.1 Beichenxi Road, Chaoyang District, Beijing, 100101, PR China
| | - Rexiding Abuduaini
- State Key Laboratory of Microbial Resources, Institute of Microbiology, Chinese Academy of Sciences, No.1 Beichenxi Road, Chaoyang District, Beijing, 100101, PR China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Hai-Ying Yu
- State Key Laboratory of Microbial Resources, Institute of Microbiology, Chinese Academy of Sciences, No.1 Beichenxi Road, Chaoyang District, Beijing, 100101, PR China
| | - Dan-Hua Li
- State Key Laboratory of Microbial Resources, Institute of Microbiology, Chinese Academy of Sciences, No.1 Beichenxi Road, Chaoyang District, Beijing, 100101, PR China
- Environmental Microbiology Research Center, Institute of Microbiology, Chinese Academy of Sciences, No.1 Beichenxi Road, Chaoyang District, Beijing, 100101, China
| | - Yu-Jing Wang
- State Key Laboratory of Microbial Resources, Institute of Microbiology, Chinese Academy of Sciences, No.1 Beichenxi Road, Chaoyang District, Beijing, 100101, PR China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Nan Zhou
- State Key Laboratory of Microbial Resources, Institute of Microbiology, Chinese Academy of Sciences, No.1 Beichenxi Road, Chaoyang District, Beijing, 100101, PR China
- Environmental Microbiology Research Center, Institute of Microbiology, Chinese Academy of Sciences, No.1 Beichenxi Road, Chaoyang District, Beijing, 100101, China
| | - Min-Zhi Jiang
- State Key Laboratory of Microbial Resources, Institute of Microbiology, Chinese Academy of Sciences, No.1 Beichenxi Road, Chaoyang District, Beijing, 100101, PR China
| | - Peng-Xia Niu
- State Key Laboratory of Microbial Resources, Institute of Microbiology, Chinese Academy of Sciences, No.1 Beichenxi Road, Chaoyang District, Beijing, 100101, PR China
- Environmental Microbiology Research Center, Institute of Microbiology, Chinese Academy of Sciences, No.1 Beichenxi Road, Chaoyang District, Beijing, 100101, China
| | - Shan-Shan Han
- State Key Laboratory of Microbial Resources, Institute of Microbiology, Chinese Academy of Sciences, No.1 Beichenxi Road, Chaoyang District, Beijing, 100101, PR China
| | - Hong-He Chen
- State Key Laboratory of Microbial Resources, Institute of Microbiology, Chinese Academy of Sciences, No.1 Beichenxi Road, Chaoyang District, Beijing, 100101, PR China
- Environmental Microbiology Research Center, Institute of Microbiology, Chinese Academy of Sciences, No.1 Beichenxi Road, Chaoyang District, Beijing, 100101, China
| | - Wen-Yu Shi
- State Key Laboratory of Microbial Resources, Institute of Microbiology, Chinese Academy of Sciences, No.1 Beichenxi Road, Chaoyang District, Beijing, 100101, PR China
- Microbial Resources and Big Data Center, Institute of Microbiology, Chinese Academy of Sciences, No.1 Beichenxi Road, Chaoyang District, Beijing, 100101, China
| | - Linhuan Wu
- State Key Laboratory of Microbial Resources, Institute of Microbiology, Chinese Academy of Sciences, No.1 Beichenxi Road, Chaoyang District, Beijing, 100101, PR China
- Microbial Resources and Big Data Center, Institute of Microbiology, Chinese Academy of Sciences, No.1 Beichenxi Road, Chaoyang District, Beijing, 100101, China
| | - Yu-Hua Xin
- State Key Laboratory of Microbial Resources, Institute of Microbiology, Chinese Academy of Sciences, No.1 Beichenxi Road, Chaoyang District, Beijing, 100101, PR China
- China General Microorganism Culture Collection, Institute of Microbiology, Chinese Academy of Sciences, No.1 Beichenxi Road, Chaoyang District, Beijing, 100101, China
| | - Juncai Ma
- State Key Laboratory of Microbial Resources, Institute of Microbiology, Chinese Academy of Sciences, No.1 Beichenxi Road, Chaoyang District, Beijing, 100101, PR China
- Microbial Resources and Big Data Center, Institute of Microbiology, Chinese Academy of Sciences, No.1 Beichenxi Road, Chaoyang District, Beijing, 100101, China
| | - Yuguang Zhou
- State Key Laboratory of Microbial Resources, Institute of Microbiology, Chinese Academy of Sciences, No.1 Beichenxi Road, Chaoyang District, Beijing, 100101, PR China
- China General Microorganism Culture Collection, Institute of Microbiology, Chinese Academy of Sciences, No.1 Beichenxi Road, Chaoyang District, Beijing, 100101, China
| | - Cheng-Ying Jiang
- State Key Laboratory of Microbial Resources, Institute of Microbiology, Chinese Academy of Sciences, No.1 Beichenxi Road, Chaoyang District, Beijing, 100101, PR China
- Environmental Microbiology Research Center, Institute of Microbiology, Chinese Academy of Sciences, No.1 Beichenxi Road, Chaoyang District, Beijing, 100101, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Hong-Wei Liu
- University of Chinese Academy of Sciences, Beijing, 100049, China
- State Key Laboratory of Mycology, Institute of Microbiology, Chinese Academy of Sciences, No. 1 Beichenxi Road, Chaoyang District, Beijing, 100101, China
| | - Shuang-Jiang Liu
- State Key Laboratory of Microbial Resources, Institute of Microbiology, Chinese Academy of Sciences, No.1 Beichenxi Road, Chaoyang District, Beijing, 100101, PR China.
- Environmental Microbiology Research Center, Institute of Microbiology, Chinese Academy of Sciences, No.1 Beichenxi Road, Chaoyang District, Beijing, 100101, China.
- University of Chinese Academy of Sciences, Beijing, 100049, China.
| |
Collapse
|
26
|
Yu HY, Gao DM, Zhou W, Xia BB, He ZY, Wu B, Jiang MZ, Wang ML, Zhao J. Expression, Purification, and Bioactivity of a Soluble Recombinant Ovine Interferon-tau in Escherichia Coli. J Vet Res 2021; 65:101-108. [PMID: 33817402 PMCID: PMC8009580 DOI: 10.2478/jvetres-2021-0011] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2020] [Accepted: 01/27/2021] [Indexed: 11/20/2022] Open
Abstract
INTRODUCTION Ovine interferon-tau (oIFN-τ) is a newly discovered type I interferon. This study used biochemical techniques to transform the oIFN-τ gene into Escherichia coli to obtain the mass and soluble expression of the recombinant protein. MATERIAL AND METHODS First, total RNA was extracted from fresh sheep embryonic tissues with TRIzol reagent and then used as a template to reverse transcribe and amplify the mature oIFN-τ gene with RT-PCR. The amplified product was next digested with the HindIII and XhoI restriction enzymes and inserted into the pET-32a(+) vector to construct the prokaryotic expression plasmid. The corrected in-frame recombinant plasmid, pET-32a(+)-oIFN-τ, was transformed into E. coli Rosetta (DE3) competent cells. After induction with isopropyl-beta-D-thiogalactopyranoside (IPTG), the recombinant protein was detected in bacteria. Finally, the bacteria were lysed by sonication, and the recombinant protein was purified by nickel affinity chromatography and DEAE anion exchange chromatography. RESULTS The protein was confirmed to be oIFN-τ, which mainly existed in the soluble lysate fraction, as proven by SDS-PAGE and Western blot assays. CONCLUSION Purified IFN-τ exists mostly in a soluble form, and its anti-vesicular stomatitis virus (VSV) activity reached 7.08×10(6)IU/mL.
Collapse
Affiliation(s)
- Hai-Yang Yu
- Department of Microbiology, Anhui Medical University, Hefei, Anhui Province, 230032, P.R. China
| | - Dong-Mei Gao
- Department of Clinical Laboratory, Third Affiliated Hospital of Anhui Medical University, Hefei, Anhui Province, 230032, P.R. China
| | - Wei Zhou
- Wuhu Interferon Bio-products Industry Research Institute Co., Ltd., Wuhu, Anhui Province, 241007, P.R. China
| | - Bing-Bing Xia
- Wuhu Interferon Bio-products Industry Research Institute Co., Ltd., Wuhu, Anhui Province, 241007, P.R. China
| | - Zhi-Yuan He
- Wuhu Interferon Bio-products Industry Research Institute Co., Ltd., Wuhu, Anhui Province, 241007, P.R. China
| | - Bo Wu
- Wuhu Interferon Bio-products Industry Research Institute Co., Ltd., Wuhu, Anhui Province, 241007, P.R. China
| | - Min-Zhi Jiang
- Wuhu Interferon Bio-products Industry Research Institute Co., Ltd., Wuhu, Anhui Province, 241007, P.R. China
| | - Ming-Li Wang
- Department of Microbiology, Anhui Medical University, Hefei, Anhui Province, 230032, P.R. China
- Wuhu Interferon Bio-products Industry Research Institute Co., Ltd., Wuhu, Anhui Province, 241007, P.R. China
| | - Jun Zhao
- Department of Microbiology, Anhui Medical University, Hefei, Anhui Province, 230032, P.R. China
- Wuhu Interferon Bio-products Industry Research Institute Co., Ltd., Wuhu, Anhui Province, 241007, P.R. China
- Wuhu Overseas Students Pioneer Park, Wuhu, Anhui Province, 241007, P.R. China
| |
Collapse
|
27
|
Yang T, Jiang MZ. [Progress in diagnosis and treatment of functional constipation in children]. Zhonghua Er Ke Za Zhi 2020; 58:611-614. [PMID: 32605352 DOI: 10.3760/cma.j.cn112140-20200203-00059] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Affiliation(s)
- T Yang
- Department of Gastroenterology, Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, National Children's Regional Medical Center, Hangzhou 310052, China (Yang Ting is working on the Department of Pediatrics, Taizhou Central Hospital, Taizhou University Hospital, Taizhou 318015, China)
| | - M Z Jiang
- Department of Gastroenterology, Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, National Children's Regional Medical Center, Hangzhou 310052, China
| |
Collapse
|
28
|
Sun MF, Gu WZ, Peng KR, Liu MN, Shu XL, Jiang LQ, Jiang MZ. [Eosinophilic esophagitis in children: analysis of 22 cases]. Zhonghua Er Ke Za Zhi 2017; 55:499-503. [PMID: 28728257 DOI: 10.3760/cma.j.issn.0578-1310.2017.07.006] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
Objective: Eosinophilic esophagitis (EoE) is a chronic immune-mediated esophageal disease.The current domestic reports of EoE in children is rare.The aim of this study was to analyze the clinical features, the diagnosis and treatment advance of EoE in children by case analysis and literature review. Method: Clinical data of 22 children with EoE from January, 2011 to December, 2015 in Children's Hospital, Zhejiang University School of Medicine were recorded, retrospective analysis was performed on clinical presentation, gastroendoscopy and histopathological examination features and the treatment. Result: (1) Clinical data: EoE can occur at any age in children (5 months to 13 years). The most common clinical manifestations of EoE are vomiting and abdominal pain, 45% (10/22) and 41%(9/22) respectively. (2) Endoscopy and pathological features of esophageal mucosa: 11 cases with coarse mucous membrane (50%), 6 cases with congestion or erosion of esophageal membrane (27%), 5 cases with longitudinal crack (23%), 3 cases with ring uplift (14%), 3 cases with granular uplift (14%), 3 cases with normal mucosa(14%). Histopathologic manifestation is eosinophil infiltration and the eosinophil counts were all more than or equal to 15/HP. (3) Laboratory results: 13 cases had increasing eosinophil counts and eosinophils proportion (62%). (4)Allergy history: among 22 cases, 7 patients had allergy history (32%). (5) Situation of treatment and remission: 16 cases had clinical remission by oral omeprazole; 2 cases had clinical remission by oral Omeprazole and Montelukast sodium; 1 case acquired remission by elimination diet; 1 case acquired remission by elimination diet and oral prednisone. 2 cases dropped out; Only 2 patients received gastroendoscopy re-examination after 3 months and revealed esophageal mucosal histologic complete recovery. Conclusion: The clinical symptoms of EoE in children varies.Esophageal mucosal features of gastroendoscopy examination in children with EoE were longitudinal crack, white exudates or plaques, paper mucosa, ring uplift and granular uplift.Most patients could achieve remission by using proton-pump inhibitors, only few children needed elimination diet and change formula, or even oral glucocorticoids.
Collapse
Affiliation(s)
- M F Sun
- Department of Gastroenterology, Children's Hospital, Zhejiang University School of Medicine, Hangzhou 310003, China
| | | | | | | | | | | | | |
Collapse
|
29
|
Jiang MZ, Wang TL, Yu JD, Zhou XL, Ou BY. Role of proximal gastric acid reflux in causation of respiratory symptoms in children with gastroesophageal reflux. Indian Pediatr 2007; 44:575-9. [PMID: 17827632] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/17/2023]
Abstract
OBJECTIVES The association of gastroesophageal reflux (GER) and respiratory disorders is well known but the mechanism is still unclear. This study aims to evaluate the presence and severity of proximal gastric acid reflux in children having GER with or without respiratory symptoms. METHODS 24 hour esophageal pH monitoring with a dual pH probe placed in the proximal and distal esophagus was performed in 23 and 31 children having GER with or without respiratory symptoms, respectively. RESULTS No significant difference in the parameters of pH monitoring in either proximal or distal esophagus was observed between GER patients with or without respiratory symptoms. The proportion of patients having proximal GER among those with respiratory symptoms was not significantly different from those without respiratory symptoms (P > 0.05). CONCLUSION Proximal esophageal acid reflux does not seem to play a role in the development of persistent respiratory symptoms in children with GER. Distal esophageal acid reflux is the predominant form of reflux in children with GER regardless of the occurrence of respiratory symptoms.
Collapse
Affiliation(s)
- M Z Jiang
- Department of Gastroenterology, Childrens Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang 310 003, China.
| | | | | | | | | |
Collapse
|
30
|
Tsukahara H, Hiraoka M, Kobata R, Hata I, Ohshima Y, Jiang MZ, Noiri E, Mayumi M. Increased oxidative stress in rats with chronic nitric oxide depletion: measurement of urinary 8-hydroxy-2'-deoxyguanosine excretion. Redox Rep 2001; 5:23-8. [PMID: 10905540 DOI: 10.1179/rer.2000.5.1.23] [Citation(s) in RCA: 18] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/31/2022] Open
Abstract
Urinary 8-hydroxy-2'-deoxyguanosine (8-OHdG) has been reported to serve as a sensitive biomarker of oxidative stress. We examined the effect of chronic blockade of nitric oxide (NO) on urinary excretion of 8-OHdG in rats. Two types of NO synthase inhibitor were used: N(G)-nitro-L-arginine methyl ester (L-NAME) as a non-selective inhibitor and aminoguanidine (AG) as a selective inhibitor of the inducible isoform. Oral administration of L-NAME (20, 50 and 80 mg/dl of drinking water), but not AG (400 mg/dl), for 4 weeks induced systemic hypertension and a significant reduction in urinary excretion of NO2-/NO3-. Rats treated with L-NAME also showed a significant increase in urinary 8-OHdG excretion compared with the control animals. The effects of L-NAME (50 mg/dl) on blood pressure and urinary excretion of NO2/NO3- and 8-OHdG were restored by a large dose of L-arginine (2.0 g/dl). Chronic AG administration did not significantly alter urinary 8-OHdG excretion. On combining all the data, there was a significant negative correlation between urinary NO2-/NO,- and 8-OHdG. These observations suggest the importance of constitutive NO synthase activity in the maintenance of oxidant buffering capacity in rats. Oral administration of L-NAME may serve as a model of hypertension due to chronic NO deficiency with increased oxidative stress.
Collapse
Affiliation(s)
- H Tsukahara
- Department of Pediatrics, Fukui Medical University,Japan.
| | | | | | | | | | | | | | | |
Collapse
|
31
|
Abstract
We examined the effect of nitric oxide (NO) on cell adhesion using cultured human pulmonary microvascular endothelial cells (PMVEC). Attachment of these cells to fibronectin was significantly inhibited by NO donors, spermine NONOate and S-nitroso-N-acetyl-penicillamine or L-arginine, but not 8-bromoguanosine-3',5'-cyclic-monophosphate. Similar results were obtained with the electrical cell-substrate impedance sensor (ECIS) technique. Addition of NO donors or L-arginine, but not 8-bromoguanosine-3',5'-cyclic-monophosphate or N2,2'-O-dibutyrylguanosine-3',5'-cyclic-monophosphate, to confluent PMVEC monolayers resulted in a transient decrease in cell adhesion, which was quantitated by the ECIS. Exposure to 1 U/ml alpha-thrombin reduced the monolayer electrical resistance by approximately 50%. The observed response was significantly suppressed by pretreatment of cells with intracellular calcium chelator, 1,2-bis(2-aminophenoxy)ethane-N,N,N',N'-tetraacetic acid or NO synthase inhibitor, N(G)-nitro-L-arginine methyl ester, but not guanylate cyclase inhibitor, 6-anilino-5,8-quinoline-quinone. Selective knockout of endothelial NO synthase with antisense oligodeoxynucleotides also significantly reduced thrombin-induced decrease in monolayer resistance. Our findings indicate that thrombin stimulates calcium-dependent release of NO from PMVEC, which mediates the retraction of endothelial cells via a cGMP-independent pathway. Our results suggest that NO modulates cell-matrix and/or cell-cell adhesion in PMVEC and that this molecule might modify microvascular permeability in the human lung.
Collapse
Affiliation(s)
- H Tsukahara
- Department of Pediatrics, Fukui Medical University, Japan.
| | | | | | | | | |
Collapse
|
32
|
Jiang MZ, Li SH, Zhang YF. [Beta-receptor and inflammation]. Sheng Li Ke Xue Jin Zhan 1995; 26:370-2. [PMID: 8745572] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 02/01/2023]
|
33
|
Jiang MZ, Sittig DF. Developing interactive computer-based simulations: an object-oriented development methodology enhances computer-assisted instruction. Comput Methods Programs Biomed 1995; 47:189-96. [PMID: 8529349 DOI: 10.1016/0169-2607(95)01644-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
The purpose of this research was to investigate the application of object-oriented technology and AI techniques to enhance development of computer-based training simulations. Towards that end, a comprehensive computer-assisted instructional unit was developed to teach the skills and concepts of window-based applications, the OS/2 desktop, and the use of a patient care information system. By taking advantage of sophisticated computer graphics for the visual representation of objects and the behavioral modeling capabilities of the object-oriented language, domain knowledge modeling and human-computer interactions were implemented without complex natural language processing techniques. The results of this research indicate that nurses and physicians are able to learn the basic skills and concepts of computer systems and how to query for patient information. The new methodology described for building these computer-assisted instructional simulations significantly eased the training and teaching of large numbers of nurses and physicians and simplified their transition to a complex, computer-based hospital information system environment.
Collapse
Affiliation(s)
- M Z Jiang
- Motorola Inc., Software Technology Centre, Schaumberg, IL, USA
| | | |
Collapse
|
34
|
Zhang ZH, Li ST, Jiang MZ, Wen Y, Bu X. [Effects of lidocaine on contraction of isolated rabbit aortic rings]. Yao Xue Xue Bao 1994; 29:652-655. [PMID: 7900535] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 05/22/2023]
Abstract
The mechanism of relaxing effects of lidocaine (Lid) on the contraction of isolated rabbit thoracic aortic rings was studied. Verapamil (Ver) was used for comparison. Lid and Ver showed obvious relaxing effect on contraction evoked by high K+ depolarization. In the study of contractions induced by noradrenaline (NA), both Lid and Ver were shown to suppress the component elicited by calcium release from the intra-cellular store, but not that induced by calcium influx. Lid shifted the dose-response curves for KCl and NA to the right nonparallelly and depressed their maximal responses. The inhibition to KCl was more potent than that to NA. This suggests that Lid has selective blocking effects on PDC channel, but not the ROC channel. Lid shifted the dose-response curve for CaCl2 to the right nonparallelly and depressed its maximal response. The results indicate that the calcium antagonistic property of Lid may be one of the mechanisms of its vascular smooth muscle relaxing effect.
Collapse
Affiliation(s)
- Z H Zhang
- Department of Pharmacology, Air-Force Hospital, Xian
| | | | | | | | | |
Collapse
|
35
|
Jiang MZ. [Clinical analysis of 170 cases of rheumatoid arthritis]. Zhonghua Nei Ke Za Zhi 1982; 21:336-8. [PMID: 7128295] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 01/23/2023]
|