Background: Associations of both common and rare genetic variants with fasting blood lipids have been extensively studied. However, most of the rare coding variants associated with lipids are population-specific, and exploration of genetic data from diverse population samples may enhance the identification of novel associations with rare variants.

Results: We searched for novel coding genetic variants associated with fasting lipid levels in 894 samples from the Genetics of Lipid Lowering Drugs and Diet Network (GOLDN) with exome-wide sequencing-based genotype data. In single variant tests, one variant (rs11171663 in ITGA7) was associated with fasting triglyceride levels (P = 7.66E-08), explaining approximately 3.2% of the total trait variance. In gene-based tests, we found statistically significant associations between ITGA7 (P = 1.77E-07) and SLCO2A1 (P = 7.18E-07) and triglycerides, as well as between POT1 (P = 3.00E-07) and low-density lipoprotein cholesterol. In another independent replication cohort consisting of 3,183 African American samples from Hypertension Genetic Epidemiology Network (HyperGEN) and the Genetic Epidemiology Network of Arteriopathy (GENOA), the top genes achieved P-values of 0.04 (ITGA7), 0.08 (SLCO2A1), and 0.02 (POT1). In GOLDN, gene transcript levels of ITGA7 and SLCO2A1 were associated with fasting triglycerides (P = 0.07 and P = 0.02), highlighting functional relevance of our findings.

Conclusion: In this study, we present preliminary evidence of novel rare variant determinants of fasting lipids, and reveal potential underlying molecular mechanisms. Moreover, these results were replicated in an independent cohort. Our findings may inform novel biomarkers of disease risk and treatment targets.

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Published in Frontiers in Genetics, v. 10, article 158, p. 1-7.

Copyright © 2019 Geng, Irvin, Hidalgo, Aslibekyan, Srinivasasainagendra, An, Frazier-Wood, Tiwari, Dave, Ryan, Ordovas, Straka, Feitosa, Hopkins, Borecki, Province, Mitchell, Arnett and Zhi.

This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

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The GOLDN study has been funded by the National Institutes of Health (NIH) National Heart, Lung, and Blood Institute (NHLBI) Grants U01HL072524 and R01HL091357. SA is additionally funded by NHLBI K01 HL136700 and JO by the U.S. Department of Agriculture, under agreement Nos. 8050-51000-098-00D and USDA-AFRI 2017-67017-26719. HyperGEN and GENOA have been funded by NIH R01HL055673 and U01HL075572. The HAPI Heart Study was supported by NIH grants U01 HL072515 and P30 DK072488. Whole genome sequencing of Amish subjects was provided by the Trans-Omics for Precision Medicine program through the National Heart, Lung and Blood Institute (NHLBI) and funded by 3R01HL121007-01S1, 3R01HL-117626-02S1, and 3R01HL-120393-02S1. XG and DZ are partially supported by Agriculture and Food Research Initiative Competitive Grant no. 2015-67015-22975 from the USDA National Institute of Food and Agriculture, and USDA Aquaculture Research Program Competitive Grant no. 2014-70007-22395.

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The datasets generated for this study can be found in dbGaP https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000741.v2.p1. The other datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fgene.2019.00158/full#supplementary-material