4.8 Article

Detection and interpretation of shared genetic influences on 42 human traits

期刊

NATURE GENETICS
卷 48, 期 7, 页码 709-+

出版社

NATURE RESEARCH
DOI: 10.1038/ng.3570

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资金

  1. National Human Genome Research Institute of the National Institutes of Health [R44HG006981]
  2. National Institute of Mental Health [R01MH106842]
  3. French National Foundation
  4. LABEX (Laboratory of Excellence program investment for the future) DISTALZ grant
  5. INSERM
  6. Institut Pasteur de Lille, Universite de Lille 2
  7. Lille University Hospital
  8. Medical Research Council [503480]
  9. Alzheimer's Research UK [503176]
  10. Wellcome Trust [082604/2/07/Z]
  11. German Federal Ministry of Education and Research (BMBF): Competence Network Dementia (CND) [01GI0102, 01GI0711, 01GI0420]
  12. NIH/NIA [R01 AG033193, U01 AG032984, U24 AG021886, U01 AG016976]
  13. NIA [AG081220]
  14. AGES [N01-AG-12100]
  15. NHLBI [R01 HL105756]
  16. Icelandic Heart Association
  17. Erasmus Medical Center
  18. Erasmus University
  19. Alzheimer's Association [ADGC-10-196728]

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We performed a scan for genetic variants associated with multiple phenotypes by comparing large genome-wide association studies (GWAS) of 42 traits or diseases. We identified 341 loci (at a false discovery rate of 10%) associated with multiple traits. Several loci are associated with multiple phenotypes; for example, a nonsynonymous variant in the zinc transporter SLC39A8 influences seven of the traits, including risk of schizophrenia (rs13107325: log-transformed odds ratio (log OR) = 0.15, P = 2 x 10(-12)) and Parkinson disease (log OR = -0.15, P = 1.6 x 10(-7)), among others. Second, we used these loci to identify traits that have multiple genetic causes in common. For example, variants associated with increased risk of schizophrenia also tended to be associated with increased risk of inflammatory bowel disease. Finally, we developed a method to identify pairs of traits that show evidence of a causal relationship. For example, we show evidence that increased body mass index causally increases triglyceride levels.

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