Genome-Wide Meta-Analysis of Variant-by-Diuretic Interactions as Modulators of Lipid Traits in Persons of European and African Ancestry

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Citation

de Las Fuentes, Lisa; Sung, Yun J.; Sitlani, Colleen M.; Avery, Christy L.; Bartz, Traci M.; de Keyser, Catherine E.; Evans, Daniel S.; Li, Xiaohong; Musani, Solomon K.; & Ruiter, Rikje, et al. (2020). Genome-Wide Meta-Analysis of Variant-by-Diuretic Interactions as Modulators of Lipid Traits in Persons of European and African Ancestry. Pharmacogenomics Journal, 20(3), 482-493. PMCID: PMC7260079

Abstract

Hypertension (HTN) is a significant risk factor for cardiovascular morbidity and mortality. Metabolic abnormalities, including adverse cholesterol and triglycerides (TG) profiles, are frequent comorbid findings with HTN and contribute to cardiovascular disease. Diuretics, which are used to treat HTN and heart failure, have been associated with worsening of fasting lipid concentrations. Genome-wide meta-analyses with 39,710 European-ancestry (EA) individuals and 9925 African-ancestry (AA) individuals were performed to identify genetic variants that modify the effect of loop or thiazide diuretic use on blood lipid concentrations. Both longitudinal and cross sectional data were used to compute cohort-specific interaction results, which were then combined through meta-analysis in each ancestry. These ancestry-specific results were further combined through trans-ancestry meta-analysis. Analysis of EA data identified two genome-wide significant (p < 5 × 10(-8)) loci with single nucleotide variant (SNV)-loop diuretic interaction on TG concentrations (including COL11A1). Analysis of AA data identified one genome-wide significant locus adjacent to BMP2 with SNV-loop diuretic interaction on TG concentrations. Trans-ancestry analysis strengthened evidence of association for SNV-loop diuretic interaction at two loci (KIAA1217 and BAALC). There were few significant SNV-thiazide diuretic interaction associations on TG concentrations and for either diuretic on cholesterol concentrations. Several promising loci were identified that may implicate biologic pathways that contribute to adverse metabolic side effects from diuretic therapy.

URL

http://dx.doi.org/10.1038/s41397-019-0132-y

Reference Type

Journal Article

Year Published

2020

Journal Title

Pharmacogenomics Journal

Author(s)

de Las Fuentes, Lisa
Sung, Yun J.
Sitlani, Colleen M.
Avery, Christy L.
Bartz, Traci M.
de Keyser, Catherine E.
Evans, Daniel S.
Li, Xiaohong
Musani, Solomon K.
Ruiter, Rikje
Smith, Albert V.
Sun, Fangui J.
Trompet, Stella
Xu, Hanfei
Arnett, Donna K.
Bis, Joshua C.
Broeckel, Ulrich
Busch, Evan L.
Chen, Y.-D. Ida
Correa, Adolfo
Cummings, Steven R.
Floyd, James S.
Ford, Ian
Guo, Xiuging
Harris, Tamara B.
Ikram, Mohammad A.
Lange, Leslie A.
Launer, Lenore J.
Reiner, Alexander P.
Schwander, Karen
Smith, Nicholas L.
Sotoodehnia, Nona
Stewart, Jill R.
Stott, David J.
Stürmer, Til
Taylor, Kent D.
Uitterlinden, André G.
Vasan, Ramachandran S.
Wiggins, Kerri L.
Cupples, L. Adrienne
Gudnason, Vilmundur G.
Heckbert, Susan R.
Jukema, J. Wouter
Liu, Yongmei
Psaty, Bruce M.
Rao, Dabeeru C.
Rotter, Jerome I.
Stricker, Bruno H.
Wilson, James G.
Whitsel, Eric A.

Article Type

Regular

PMCID

PMC7260079

Continent/Country

United States of America

State

Nonspecific

Race/Ethnicity

African Ancestry
European Ancestry

ORCiD

Avery - 0000-0002-1044-8162
Stewart, J - 0000-0002-3474-5233