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Sci Adv. 2016 Aug 31;2(8):e1600800. doi: 10.1126/sciadv.1600800. eCollection 2016 Aug.

Loss-of-function variants influence the human serum metabolome.

Author information

1
Human Genetics Center, University of Texas Health Science Center at Houston, Houston, TX 77030, USA.
2
Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX 77030, USA.
3
Department of Medicine (Geriatrics), University of Mississippi Medical Center, Jackson, MS 39216, USA.
4
Human Genetics Center, University of Texas Health Science Center at Houston, Houston, TX 77030, USA.; Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX 77030, USA.

Abstract

The metabolome is a collection of small molecules resulting from multiple cellular and biological processes that can act as biomarkers of disease, and African-Americans exhibit high levels of genetic diversity. Exome sequencing of a sample of deeply phenotyped African-Americans allowed us to analyze the effects of annotated loss-of-function (LoF) mutations on 308 serum metabolites measured by untargeted liquid and gas chromatography coupled with mass spectrometry. In an independent sample, we identified and replicated four genes harboring six LoF mutations that significantly affected five metabolites. These sites were related to a 19 to 45% difference in geometric mean metabolite levels, with an average effect size of 25%. We show that some of the affected metabolites are risk predictors or diagnostic biomarkers of disease and, using the principle of Mendelian randomization, are in the causal pathway of disease. For example, LoF mutations in SLCO1B1 elevate the levels of hexadecanedioate, a fatty acid significantly associated with increased blood pressure levels and risk of incident heart failure in both African-Americans and an independent sample of European-Americans. We show that SLCO1B1 LoF mutations significantly increase the risk of incident heart failure, thus implicating the metabolite in the causal pathway of disease. These results reveal new avenues into gene function and the understanding of disease etiology by integrating -omic technologies into a deeply phenotyped population study.

KEYWORDS:

Metabolomics; loss-of-function; metabolite; rare genetic variant

PMID:
27602404
PMCID:
PMC5007069
DOI:
10.1126/sciadv.1600800
[Indexed for MEDLINE]
Free PMC Article

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