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Xuezhong Zhou

Bio: Xuezhong Zhou is an academic researcher from Beijing Jiaotong University. The author has contributed to research in topics: Computer science & Disease. The author has an hindex of 19, co-authored 112 publications receiving 3652 citations. Previous affiliations of Xuezhong Zhou include Peking Union Medical College & Information Technology Institute.


Papers
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Journal ArticleDOI
Yukinori Okada1, Yukinori Okada2, Di Wu2, Di Wu3, Di Wu1, Gosia Trynka1, Gosia Trynka2, Towfique Raj2, Towfique Raj1, Chikashi Terao4, Katsunori Ikari, Yuta Kochi, Koichiro Ohmura4, Akari Suzuki, Shinji Yoshida, Robert R. Graham5, A. Manoharan5, Ward Ortmann5, Tushar Bhangale5, Joshua C. Denny6, Robert J. Carroll6, Anne E. Eyler6, Jeff Greenberg7, Joel M. Kremer, Dimitrios A. Pappas8, Lei Jiang9, Jian Yin9, Lingying Ye9, Ding Feng Su9, Jian Yang10, Gang Xie11, E.C. Keystone11, Harm-Jan Westra12, Tõnu Esko2, Tõnu Esko1, Tõnu Esko13, Andres Metspalu13, Xuezhong Zhou14, Namrata Gupta1, Daniel B. Mirel1, Eli A. Stahl15, Dorothee Diogo1, Dorothee Diogo2, Jing Cui2, Jing Cui1, Katherine P. Liao1, Katherine P. Liao2, Michael H. Guo1, Michael H. Guo2, Keiko Myouzen, Takahisa Kawaguchi4, Marieke J H Coenen16, Piet L. C. M. van Riel16, Mart A F J van de Laar17, Henk-Jan Guchelaar18, Tom W J Huizinga18, Philippe Dieudé19, Xavier Mariette20, S. Louis Bridges21, Alexandra Zhernakova12, Alexandra Zhernakova18, René E. M. Toes18, Paul P. Tak22, Paul P. Tak23, Paul P. Tak24, Corinne Miceli-Richard20, So Young Bang25, Hye Soon Lee25, Javier Martin26, Miguel A. Gonzalez-Gay, Luis Rodriguez-Rodriguez27, Solbritt Rantapää-Dahlqvist28, Lisbeth Ärlestig28, Hyon K. Choi2, Hyon K. Choi29, Yoichiro Kamatani30, Pilar Galan19, Mark Lathrop31, Steve Eyre32, Steve Eyre33, John Bowes32, John Bowes33, Anne Barton32, Niek de Vries22, Larry W. Moreland34, Lindsey A. Criswell35, Elizabeth W. Karlson2, Atsuo Taniguchi, Ryo Yamada4, Michiaki Kubo, Jun Liu2, Sang Cheol Bae25, Jane Worthington33, Jane Worthington32, Leonid Padyukov36, Lars Klareskog36, Peter K. Gregersen37, Soumya Raychaudhuri2, Soumya Raychaudhuri1, Barbara E. Stranger38, Philip L. De Jager2, Philip L. De Jager1, Lude Franke12, Peter M. Visscher10, Matthew A. Brown10, Hisashi Yamanaka, Tsuneyo Mimori4, Atsushi Takahashi, Huji Xu9, Timothy W. Behrens5, Katherine A. Siminovitch11, Shigeki Momohara, Fumihiko Matsuda4, Kazuhiko Yamamoto39, Robert M. Plenge2, Robert M. Plenge1 
20 Feb 2014-Nature
TL;DR: A genome-wide association study meta-analysis in a total of >100,000 subjects of European and Asian ancestries provides empirical evidence that the genetics of RA can provide important information for drug discovery, and sheds light on fundamental genes, pathways and cell types that contribute to RA pathogenesis.
Abstract: A major challenge in human genetics is to devise a systematic strategy to integrate disease-associated variants with diverse genomic and biological data sets to provide insight into disease pathogenesis and guide drug discovery for complex traits such as rheumatoid arthritis (RA)1. Here we performed a genome-wide association study meta-analysis in a total of >100,000 subjects of European and Asian ancestries (29,880 RA cases and 73,758 controls), by evaluating ~10 million single-nucleotide polymorphisms. We discovered 42 novel RA risk loci at a genome-wide level of significance, bringing the total to 101 (refs 2, 3, 4). We devised an in silico pipeline using established bioinformatics methods based on functional annotation5, cis-acting expression quantitative trait loci6 and pathway analyses7, 8, 9—as well as novel methods based on genetic overlap with human primary immunodeficiency, haematological cancer somatic mutations and knockout mouse phenotypes—to identify 98 biological candidate genes at these 101 risk loci. We demonstrate that these genes are the targets of approved therapies for RA, and further suggest that drugs approved for other indications may be repurposed for the treatment of RA. Together, this comprehensive genetic study sheds light on fundamental genes, pathways and cell types that contribute to RA pathogenesis, and provides empirical evidence that the genetics of RA can provide important information for drug discovery.

1,910 citations

Journal ArticleDOI
TL;DR: It is found that the symptom-based similarity of two diseases correlates strongly with the number of shared genetic associations and the extent to which their associated proteins interact.
Abstract: In the post-genomic era, the elucidation of the relationship between the molecular origins of diseases and their resulting phenotypes is a crucial task for medical research. Here, we use a large-scale biomedical literature database to construct a symptom-based human disease network and investigate the connection between clinical manifestations of diseases and their underlying molecular interactions. We find that the symptom-based similarity of two diseases correlates strongly with the number of shared genetic associations and the extent to which their associated proteins interact. Moreover, the diversity of the clinical manifestations of a disease can be related to the connectivity patterns of the underlying protein interaction network. The comprehensive, high-quality map of disease-symptom relations can further be used as a resource helping to address important questions in the field of systems medicine, for example, the identification of unexpected associations between diseases, disease etiology research or drug design.

504 citations

Journal ArticleDOI
TL;DR: SymMap integrates TCM with modern medicine in common aspects at both the phenotypic and molecular levels and inferred all pairwise relationships among SymMap components using statistical tests to give pharmaceutical scientists the ability to rank and filter promising results to guide drug discovery.
Abstract: Recently, the pharmaceutical industry has heavily emphasized phenotypic drug discovery (PDD), which relies primarily on knowledge about phenotype changes associated with diseases. Traditional Chinese medicine (TCM) provides a massive amount of information on natural products and the clinical symptoms they are used to treat, which are the observable disease phenotypes that are crucial for clinical diagnosis and treatment. Curating knowledge of TCM symptoms and their relationships to herbs and diseases will provide both candidate leads and screening directions for evidence-based PDD programs. Therefore, we present SymMap, an integrative database of traditional Chinese medicine enhanced by symptom mapping. We manually curated 1717 TCM symptoms and related them to 499 herbs and 961 symptoms used in modern medicine based on a committee of 17 leading experts practicing TCM. Next, we collected 5235 diseases associated with these symptoms, 19 595 herbal constituents (ingredients) and 4302 target genes, and built a large heterogeneous network containing all of these components. Thus, SymMap integrates TCM with modern medicine in common aspects at both the phenotypic and molecular levels. Furthermore, we inferred all pairwise relationships among SymMap components using statistical tests to give pharmaceutical scientists the ability to rank and filter promising results to guide drug discovery. The SymMap database can be accessed at http://www.symmap.org/ and https://www.bioinfo.org/symmap.

234 citations

Journal ArticleDOI
TL;DR: The CDW platform would be a promising infrastructure to make full use of the TCM clinical data for scientific hypothesis generation, and promote the development of TCM from individualized empirical knowledge to large-scale evidence-based medicine.

210 citations

Journal ArticleDOI
Yi Feng1, Zhaohui Wu1, Xuezhong Zhou, Zhongmei Zhou1, Weiyu Fan 
TL;DR: An overview of recent KDD studies in TCM field is provided, demonstrating that KDTCM is effective in obtaining medical discoveries and much more work needs to be done in order to discover real diamonds from TCM domain.

189 citations


Cited by
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01 Jan 2002

9,314 citations

Journal ArticleDOI
TL;DR: The remarkable range of discoveriesGWASs has facilitated in population and complex-trait genetics, the biology of diseases, and translation toward new therapeutics are reviewed.
Abstract: Application of the experimental design of genome-wide association studies (GWASs) is now 10 years old (young), and here we review the remarkable range of discoveries it has facilitated in population and complex-trait genetics, the biology of diseases, and translation toward new therapeutics. We predict the likely discoveries in the next 10 years, when GWASs will be based on millions of samples with array data imputed to a large fully sequenced reference panel and on hundreds of thousands of samples with whole-genome sequencing data.

2,669 citations

Journal ArticleDOI
15 Jun 2017-Cell
TL;DR: It is proposed that gene regulatory networks are sufficiently interconnected such that all genes expressed in disease-relevant cells are liable to affect the functions of core disease-related genes and that most heritability can be explained by effects on genes outside core pathways.

2,257 citations

Journal ArticleDOI
TL;DR: A new method is introduced, stratified LD score regression, for partitioning heritability from GWAS summary statistics while accounting for linked markers, which is computationally tractable at very large sample sizes and leverages genome-wide information.
Abstract: Recent work has demonstrated that some functional categories of the genome contribute disproportionately to the heritability of complex diseases. Here we analyze a broad set of functional elements, including cell type-specific elements, to estimate their polygenic contributions to heritability in genome-wide association studies (GWAS) of 17 complex diseases and traits with an average sample size of 73,599. To enable this analysis, we introduce a new method, stratified LD score regression, for partitioning heritability from GWAS summary statistics while accounting for linked markers. This new method is computationally tractable at very large sample sizes and leverages genome-wide information. Our findings include a large enrichment of heritability in conserved regions across many traits, a very large immunological disease-specific enrichment of heritability in FANTOM5 enhancers and many cell type-specific enrichments, including significant enrichment of central nervous system cell types in the heritability of body mass index, age at menarche, educational attainment and smoking behavior.

1,939 citations

Journal ArticleDOI
TL;DR: The first trans-ancestry association study of IBD is reported, with genome-wide or Immunochip genotype data from an extended cohort of 86,640 European individuals and immunochip data from 9,846 individuals of East Asian, Indian or Iranian descent, implicate 38 loci in IBD risk for the first time.
Abstract: Ulcerative colitis and Crohn's disease are the two main forms of inflammatory bowel disease (IBD). Here we report the first trans-ancestry association study of IBD, with genome-wide or Immunochip genotype data from an extended cohort of 86,640 European individuals and Immunochip data from 9,846 individuals of East Asian, Indian or Iranian descent. We implicate 38 loci in IBD risk for the first time. For the majority of the IBD risk loci, the direction and magnitude of effect are consistent in European and non-European cohorts. Nevertheless, we observe genetic heterogeneity between divergent populations at several established risk loci driven by differences in allele frequency (NOD2) or effect size (TNFSF15 and ATG16L1) or a combination of these factors (IL23R and IRGM). Our results provide biological insights into the pathogenesis of IBD and demonstrate the usefulness of trans-ancestry association studies for mapping loci associated with complex diseases and understanding genetic architecture across diverse populations.

1,826 citations