4.5 Article

Gene and pathway-based second-wave analysis of genome-wide association studies

期刊

EUROPEAN JOURNAL OF HUMAN GENETICS
卷 18, 期 1, 页码 111-117

出版社

NATURE PUBLISHING GROUP
DOI: 10.1038/ejhg.2009.115

关键词

genome-wide association studies; gene and pathway-based analysis; complex diseases; combining P-values; gene-set enrichment analysis

资金

  1. National Institutes of Health [NIAMS P01 AR052915-01A1, NIAMS P50 AR054144-01, CORT, HL74735,, ES09912]
  2. National Institutes of Health Tech Research and Development Program of China(863) [2007AA02Z312]
  3. Shanghai Commission of Science and Technology [04dz14003]
  4. Hi-Tech Research and Development Program of China(863) [2007AA02Z312]
  5. NATIONAL HEART, LUNG, AND BLOOD INSTITUTE [R01HL074735] Funding Source: NIH RePORTER
  6. NATIONAL INSTITUTE OF ARTHRITIS AND MUSCULOSKELETAL AND SKIN DISEASES [P50AR054144, P01AR052915] Funding Source: NIH RePORTER
  7. NATIONAL INSTITUTE OF ENVIRONMENTAL HEALTH SCIENCES [R01ES009912] Funding Source: NIH RePORTER
  8. NATIONAL INSTITUTE ON AGING [K01AG034259] Funding Source: NIH RePORTER

向作者/读者索取更多资源

Despite the great success of genome-wide association studies (GWAS) in identification of the common genetic variants associated with complex diseases, the current GWAS have focused on single-SNP analysis. However, single-SNP analysis often identifies only a few of the most significant SNPs that account for a small proportion of the genetic variants and offers only a limited understanding of complex diseases. To overcome these limitations, we propose gene and pathway-based association analysis as a new paradigm for GWAS. As a proof of concept, we performed a comprehensive gene and pathway-based association analysis of 13 published GWAS. Our results showed that the proposed new paradigm for GWAS not only identified the genes that include significant SNPs found by single-SNP analysis, but also detected new genes in which each single SNP conferred a small disease risk; however, their joint actions were implicated in the development of diseases. The results also showed that the new paradigm for GWAS was able to identify biologically meaningful pathways associated with the diseases, which were confirmed by a gene-set-rich analysis using gene expression data. European Journal of Human Genetics (2010) 18, 111-117; doi:10.1038/ejhg.2009.115; published online 8 July 2009

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