Potential use of pharmacogenetics in cardiology: genome-wide association studies of amiodarone-induced thyroid disorders

Abstract Background Amiodarone is a commonly prescribed antiarrhythmic drug used to manage supraventricular and ventricular arrhythmias. The use of amiodarone is associated with a broad range of adverse effects, including amiodarone-induced hypothyroidism (AIH) or amiodarone-induced thyrotoxicosis (...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:European heart journal 2024-10, Vol.45 (Supplement_1)
Hauptverfasser: Rand, S, Tragante, V, Sorensen, E, Ostrowski, S R, Pedersen, O B, Olesen, M S, Bundgaard, H, Ghouse, J
Format: Artikel
Sprache:eng
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:Abstract Background Amiodarone is a commonly prescribed antiarrhythmic drug used to manage supraventricular and ventricular arrhythmias. The use of amiodarone is associated with a broad range of adverse effects, including amiodarone-induced hypothyroidism (AIH) or amiodarone-induced thyrotoxicosis (AIT) (1). Both conditions are linked with increased mortality and have no known reliable risk predictors (2). Purpose We investigated the genetic underpinnings of amiodarone-induced thyroid disorders, and the clinical validity and utility of screening for genetic variants. Methods We conducted the first genome-wide association studies (GWAS) of AIH and AIT using data from three large biobanks. We compared the AUCs for SNPs identified through the above GWAS with polygenic risk scores for both hypo- and hyperthyroidism. Finally, we tested the clinical validity and utility of screening for risk variants. Results We found two risk loci for AIH. The lead variant at the first locus, rs1443438, was intronic to FOXE1 (OR 0.39, MAF = 35%, P = 1.59 × 10-42). The other lead variant, rs2209796, was located 93 kb upstream to FOXA2 (OR 0.56, MAF = 29%, P = 2.64 × 10-15: Figure 1). For AIT, we found one risk locus. The lead variant, rs2268803, was intronic to CAPZB (OR 1.81, MAF = 42%, P = 2.43 × 10-8: Figure 1). Next, we added GWAS SNPs or polygenic risk scores to risk prediction models consisting of age, sex and 4 principal components (PCs), and compared AUC estimates between risk models. Using GWAS SNPs, we found that the AIT variant increased the AUC with 6% (95%CI 1.1 – 10.3, AUC: 0.72) and 9% (95%CI 6.2 – 11.2, AUC: 0.75) for AIH, compared to the benchmark model. Both GWAS SNP models were superior to polygenic risk scores in terms of AUC (P for difference
ISSN:0195-668X
1522-9645
DOI:10.1093/eurheartj/ehae666.3359