Genetic predictors of lifelong medication-use patterns in cardiometabolic diseases - Kiiskinen Tuomo; Helkkula Pyry; Krebs Kristi; Karjalainen Juha; Saarentaus Elmo; Mars Nina; Lehisto Arto; Zhou Wei; Cordioli Mattia; Jukarainen Sakari; Rämö Joel T.; Mehtonen Juha; et al. (Nature Portfolio, 2025)
A new analysis of large biobanks uncovers genetic variants associated with longitudinal changes in medication for cardiometabolic diseases and presents polygenic scores of medication-use behavior.Little is known about the genetic determinants of medication use in preventing cardiometabolic diseases. Using the Finnish nationwide drug purchase registry with follow-up since 1995, we performed genome-wide association analyses of longitudinal patterns of medication use in hyperlipidemia, hypertension and type 2 diabetes in up to 193,933 individuals (55% women) in the FinnGen study. In meta-analyses of up to 567,671 individuals combining FinnGen with the Estonian Biobank and the UK Biobank, we discovered 333 independent loci (P < 5 x 10-9) associated with medication use. Fine-mapping revealed 494 95% credible sets associated with the total number of medication purchases, changes in medication combinations or treatment discontinuation, including 46 credible sets in 40 loci not associated with the underlying treatment targets. The polygenic risk scores (PRS) for cardiometabolic risk factors were strongly associated with the medication-use behavior. A medication-use enhanced multitrait PRS for coronary artery disease matched the performance of a risk factor-based multitrait coronary artery disease PRS in an independent sample (UK Biobank, n = 343,676). In summary, we demonstrate medication-based strategies for identifying cardiometabolic risk loci and provide genome-wide tools for preventing cardiovascular diseases.