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Nat Genet. 2015 Jun;47(6):640-2. doi: 10.1038/ng.3270. Epub 2015 Apr 27.

Analysis of loss-of-function variants and 20 risk factor phenotypes in 8,554 individuals identifies loci influencing chronic disease.

Author information

1
Human Genetics Center, University of Texas Health Science Center, Houston, Texas, USA.
2
Human Genome Sequencing Center, Baylor College of Medicine, Houston, Texas, USA.
3
1] National Heart, Lung, and Blood Institute (NHLBI) Framingham Heart Study, Framingham, Massachusetts, USA. [2] Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts, USA.
4
Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, Washington, USA.
5
1] Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, Washington, USA. [2] Department of Statistics, University of Auckland, Auckland, New Zealand.
6
Department of Medicine (Geriatrics), University of Mississippi Medical Center, Jackson, Mississippi, USA.
7
1] Human Genetics Center, University of Texas Health Science Center, Houston, Texas, USA. [2] Human Genome Sequencing Center, Baylor College of Medicine, Houston, Texas, USA.

Abstract

A typical human exome harbors dozens of loss-of-function (LOF) variants, which can lower disease risk factor levels and affect drug efficacy. We hypothesized that LOF variants are enriched in genes influencing risk factor levels and the onset of common chronic diseases, such as cardiovascular disease and diabetes. To test this hypothesis, we sequenced the exomes of 8,554 individuals and analyzed the effects of predicted LOF variants on 20 chronic disease risk factor phenotypes. Analysis of this sample as discovery and replication strata of equal size verified two relationships in well-studied genes (PCSK9 and APOC3) and identified eight new loci. Previously unknown relationships included elevated fasting glucose in carriers of heterozygous LOF variation in TXNDC5, which encodes a biomarker for type 1 diabetes progression, and apparent recessive effects of C1QTNF8 on serum magnesium levels. These data demonstrate the utility of functional-variant annotation within a large sample of deeply phenotyped individuals for gene discovery.

PMID:
25915599
PMCID:
PMC4470468
DOI:
10.1038/ng.3270
[Indexed for MEDLINE]
Free PMC Article

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