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. 2017 Nov;58(11):2162-2170.
doi: 10.1194/jlr.M079822. Epub 2017 Sep 4.

Polygenic determinants in extremes of high-density lipoprotein cholesterol

Jacqueline S Dron  1   2 , Jian Wang  2 , Cécile Low-Kam  3 , Sumeet A Khetarpal  4 , John F Robinson  2 , Adam D McIntyre  2 , Matthew R Ban  2 , Henian Cao  2 , David Rhainds  3 , Marie-Pierre Dubé  3 , Daniel J Rader  5 , Guillaume Lettre  3 , Jean-Claude Tardif  3 , Robert A Hegele  6   2   7
Affiliations

Polygenic determinants in extremes of high-density lipoprotein cholesterol

Jacqueline S Dron et al. J Lipid Res. 2017 Nov.

Abstract

HDL cholesterol (HDL-C) remains a superior biochemical predictor of CVD risk, but its genetic basis is incompletely defined. In patients with extreme HDL-C concentrations, we concurrently evaluated the contributions of multiple large- and small-effect genetic variants. In a discovery cohort of 255 unrelated lipid clinic patients with extreme HDL-C levels, we used a targeted next-generation sequencing panel to evaluate rare variants in known HDL metabolism genes, simultaneously with common variants bundled into a polygenic trait score. Two additional cohorts were used for validation and included 1,746 individuals from the Montréal Heart Institute Biobank and 1,048 individuals from the University of Pennsylvania. Findings were consistent between cohorts: we found rare heterozygous large-effect variants in 18.7% and 10.9% of low- and high-HDL-C patients, respectively. We also found common variant accumulation, indicated by extreme polygenic trait scores, in an additional 12.8% and 19.3% of overall cases of low- and high-HDL-C extremes, respectively. Thus, the genetic basis of extreme HDL-C concentrations encountered clinically is frequently polygenic, with contributions from both rare large-effect and common small-effect variants. Multiple types of genetic variants should be considered as contributing factors in patients with extreme dyslipidemia.

Keywords: common variants; complex trait; dyslipidemias; genes in lipid dysfunction; genetics; genomics; next-generation sequencing; polygenic risk score; rare variants.

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Conflict of interest statement

R.A.H. is a consultant and speakers’ bureau member for Aegerion, Amgen, Boston Heart Diagnostics, Cerenis, Eli Lilly, Gemphire, Pfizer, and Sanofi. The other authors have no disclosures.

Figures

Fig. 1.
Fig. 1.
Summary of rare large-effect variant types in the Lipid Genetics Clinic cohort. Forty-three unique variants were identified in primary genes, and 10 unique variants were identified in secondary genes; there were 68 variants total. A: Total number of unique variants per gene per patient group. B: Frequency of variant type for each unique variant for the low-HDL-C M+ patients (left) and high-HDL-C M+ patients (right).
Fig. 2.
Fig. 2.
PTS analysis for low- and high-HDL-C/M− patients. Violin plots (similar to box plots, except that they also show the probability density of the data at different values) illustrate the distribution of polygenic scores for individuals in the control, low-HDL-C/M−, and high-HDL-C/M− groups in the Lipid Genetics Clinic cohort (A), the MHI Biobank cohort (B), and UPenn cohort (C). Red diamonds mark the mean PTS of the group. The total area of a single plot represents 100% of individuals in that group; wider sections of each plot represent an increased number of individuals with scores at that point, and narrower sections represent a decreased number of individuals. The top dashed line and bottom dashed line represent the threshold for the top 10th and bottom 10th percentiles of PTSs in the control population, respectively. The boxes indicate the percentage of individuals falling above or below the percentile thresholds. †Percentile groups with significant ORs (Tables 3, 4); **P < 0.01; ***P < 0.0001.
Fig. 3.
Fig. 3.
Mean HDL-C level in low- and high-HDL-C/M− patients from the Lipid Genetics Clinic by PTS decile. There is a strong linear relationship between increasing PTSs and HDL-C levels, as is indicated by the R2 value of 0.8696 (P < 0.0001). Vertical bars indicate standard errors of the mean.
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