Effects of Genetic Variants Associated with Familial Hypercholesterolemia on Low-Density Lipoprotein-Cholesterol Levels and Cardiovascular Outcomes in the Million Veteran Program.

Supplemental Digital Content is available in the text. Background: Familial hypercholesterolemia (FH) is characterized by inherited high levels of LDL-C (low-density lipoprotein cholesterol) and premature coronary heart disease. Over a thousand low-frequency variants in LDLR, APOB, and PCSK9 have been implicated in FH, but few have been examined at the population level. We aim to estimate the phenotypic effects of a subset of FH variants on LDL-C and clinical outcomes among 331 107 multiethnic participants. Methods: We examined the individual and collective association between putatively pathogenic FH variants included on the Million Veteran Program biobank array and the maximum LDL-C level over an interval of 15 years (maxLDL). We assessed the collective effect on clinical outcomes by leveraging data from 61.7 million clinical encounters. Results: We found 8 out of 16 putatively pathogenic FH variants with ≥30 observed carriers to be significantly associated with elevated maxLDL (9.4–80.2 mg/dL). Phenotypic effects were similar for European Americans and African Americans, despite substantial differences in carrier frequencies. Based on observed effects on maxLDL, we identified a total of 748 carriers (1:443) who had elevated maxLDL (36.5±1.4 mg/dL; P =1.2×10^–152), and higher prevalence of clinical diagnoses related to hypercholesterolemia and coronary heart disease in a phenome-wide scan. Adjusted for maxLDL, FH variants collectively associated with higher prevalence of coronary heart disease (odds ratio, 1.59; 95% CI, 1.36–1.86, P =1.1×10^–8) but not peripheral artery disease. Conclusions: The distribution and phenotypic effects of putatively pathogenic FH variants were heterogeneous within and across variants. More robust evidence of genotype-phenotype associations of FH variants in multiethnic populations is needed to accurately infer at-risk individuals from genetic screening. [ABSTRACT FROM AUTHOR]