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PLoS Genet. 2014 Jan 30;10(1):e1004147. doi: 10.1371/journal.pgen.1004147. eCollection 2014 Jan.

Re-sequencing expands our understanding of the phenotypic impact of variants at GWAS loci.

Author information

1
Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles, Los Angeles, California, United States of America.
2
Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, Michigan, United States of America.
3
The Genome Institute at Washington University, St. Louis, Missouri, United States of America.
4
Genome Technology Branch, National Human Genome Research Institute, Bethesda, Maryland, United States of America.
5
Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, United Kingdom ; Faculty of Medicine, St Mary's Campus, Imperial College London, London, United Kingdom.
6
Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, United Kingdom ; Institute of Health Sciences, University of Oulu, Oulu, Finland ; Biocenter Oulu, University of Oulu, Oulu, Finland ; Unit of Primary Care, Oulu University Hospital, Oulu, Finland ; Department of Children and Young People and Families, National Institute for Health and Welfare, Oulu, Finland.
7
Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, United Kingdom ; Institute of Health Sciences, University of Oulu, Oulu, Finland ; Biocenter Oulu, University of Oulu, Oulu, Finland.
8
Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Churchill Hospital, Headington, Oxford, United Kingdom ; Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom ; Oxford NIHR Biomedical Research Centre, Churchill Hospital, Headington, Oxford, United Kingdom.
9
Institute for Molecular Medicine Finland, FIMM, University of Helsinki, Helsinki, Finland ; The Program for Human and Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, Massachusetts, United States of America.
10
Department of Children and Young People and Families, National Institute for Health and Welfare, Oulu, Finland ; Institute of Clinical Medicine/Obstetrics and Gynecology, University of Oulu, Oulu, Finland.
11
Department of Children and Young People and Families, National Institute for Health and Welfare, Oulu, Finland.
12
Institute for Molecular Medicine Finland, FIMM, University of Helsinki, Helsinki, Finland ; Hjelt Institute, University of Helsinki, Helsinki, Finland ; Wellcome Trust Sanger Institute, Hinxton, United Kingdom.
13
Department of Health and Research Policy, Stanford University, Stanford, California, United States of America.

Abstract

Genome-wide association studies (GWAS) have identified >500 common variants associated with quantitative metabolic traits, but in aggregate such variants explain at most 20-30% of the heritable component of population variation in these traits. To further investigate the impact of genotypic variation on metabolic traits, we conducted re-sequencing studies in >6,000 members of a Finnish population cohort (The Northern Finland Birth Cohort of 1966 [NFBC]) and a type 2 diabetes case-control sample (The Finland-United States Investigation of NIDDM Genetics [FUSION] study). By sequencing the coding sequence and 5' and 3' untranslated regions of 78 genes at 17 GWAS loci associated with one or more of six metabolic traits (serum levels of fasting HDL-C, LDL-C, total cholesterol, triglycerides, plasma glucose, and insulin), and conducting both single-variant and gene-level association tests, we obtained a more complete understanding of phenotype-genotype associations at eight of these loci. At all eight of these loci, the identification of new associations provides significant evidence for multiple genetic signals to one or more phenotypes, and at two loci, in the genes ABCA1 and CETP, we found significant gene-level evidence of association to non-synonymous variants with MAF<1%. Additionally, two potentially deleterious variants that demonstrated significant associations (rs138726309, a missense variant in G6PC2, and rs28933094, a missense variant in LIPC) were considerably more common in these Finnish samples than in European reference populations, supporting our prior hypothesis that deleterious variants could attain high frequencies in this isolated population, likely due to the effects of population bottlenecks. Our results highlight the value of large, well-phenotyped samples for rare-variant association analysis, and the challenge of evaluating the phenotypic impact of such variants.

PMID:
24497850
PMCID:
PMC3907339
DOI:
10.1371/journal.pgen.1004147
[Indexed for MEDLINE]
Free PMC Article
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