Pulse lineResearch With Heart Logo

Exome sequence association study of levels and longitudinal change of cardiovascular risk factor phenotypes in European Americans and African Americans from the Atherosclerosis Risk in Communities Study.

TitleExome sequence association study of levels and longitudinal change of cardiovascular risk factor phenotypes in European Americans and African Americans from the Atherosclerosis Risk in Communities Study.
Publication TypeJournal Article
Year of Publication2021
AuthorsFeofanova EV, Lim E, Chen H, Lee MJ, Liu C-T, L Cupples A, Boerwinkle E
JournalGenet Epidemiol
Volume45
Issue6
Pagination651-663
Date Published2021 Sep
ISSN1098-2272
Abstract

Cardiovascular disease (CVD) is responsible for 31% of all deaths worldwide. Among CVD risk factors are age, race, increased systolic blood pressure (BP), and dyslipidemia. Both BP and blood lipids levels change with age, with a dose-dependent relationship between the cumulative exposure to hyperlipidemia and the risk of CVD. We performed an exome sequence association study using longitudinal data with up to 7805 European Americans (EAs) and 3171 African Americans (AAs) from the Atherosclerosis Risk in Communities (ARIC) study. We assessed associations of common (minor allele frequency > 5%) nonsynonymous and splice-site variants and gene-based sets of rare variants with levels and with longitudinal change of seven CVD risk factor phenotypes (BP traits: systolic BP, diastolic BP, pulse pressure; lipids traits: triglycerides, total cholesterol, high-density lipoprotein cholesterol [HDL-C], low-density lipoprotein cholesterol [LDL-C]). Furthermore, we investigated the relationship of the identified variants and genes with select CVD endpoints. We identified two novel genes: DCLK3 associated with the change of HDL-C levels in AAs and RAB7L1 associated with the change of LDL-C levels in EAs. RAB7L1 is further associated with an increased risk of heart failure in ARIC EAs. Investigation of the contribution of genetic factors to the longitudinal change of CVD risk factor phenotypes promotes our understanding of the etiology of CVD outcomes, stressing the importance of incorporating the longitudinal structure of the cohort data in future analyses.

DOI10.1002/gepi.22390
Alternate JournalGenet Epidemiol
PubMed ID34167169
Grant List75N92019D00031 / HL / NHLBI NIH HHS / United States
HHSN268201500001 / / National Institutes of Health, Department of Health and Human Services /
HHSN268201700001I / HL / NHLBI NIH HHS / United States
HHSN268201700002I / HL / NHLBI NIH HHS / United States
HHSN268201700003I / HL / NHLBI NIH HHS / United States
HHSN268201700004I / HL / NHLBI NIH HHS / United States
HHSN268201700005I / HL / NHLBI NIH HHS / United States
N01-HC-25195 / / National Institutes of Health, Department of Health and Human Services /
5RC2HL102419 / GF / NIH HHS / United States
R01HL086694 / GF / NIH HHS / United States
U54HG003273 / GF / NIH HHS / United States
75N92019D00031 / HL / NHLBI NIH HHS / United States
HHSN268201700001I / HL / NHLBI NIH HHS / United States
HHSN268201700002I / HL / NHLBI NIH HHS / United States
HHSN268201700003I / HL / NHLBI NIH HHS / United States
HHSN268201700004I / HL / NHLBI NIH HHS / United States
HHSN268201700005I / HL / NHLBI NIH HHS / United States