A typical human exome harbors dozens of loss-of-function (LOF) variants1, which can lower disease risk factor levels and affect drug efficacy2. 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.
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Monday, April 27, 2015
New genes found to influence risk of diabetes, heart disease
A typical human exome harbors dozens of loss-of-function (LOF) variants1, which can lower disease risk factor levels and affect drug efficacy2. 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.