Longitudinal associations between use of antihypertensive, antidiabetic, and lipid-lowering medications and biological aging.

Tang B, Li X, Wang Y, Sjölander A, Johnell K, Thambisetty M, Ferrucci L, Reynolds CA, Finkel D, Jylhävä J, Pedersen NL, Hägg S

Geroscience - (-) - [2023-04-10; online 2023-04-10]

Aging is a major risk factor for many chronic diseases. This study aimed to examine the effects of antihypertensive, lipid-lowering, and antidiabetic drugs on biological aging. We included 672 participants and 2746 repeated measurements from the Swedish Adoption/Twin Study of Aging. Self-reported medicine uses were categorized into antidiabetic, antihypertensive, and lipid-lowering drugs. A total of 12 biomarkers for biological aging (BA biomarkers) were included as outcomes. Conditional generalized estimating equations were applied conditioning on individuals to estimate the drug effect on BA biomarker level within the same person when using or not using the drug. Chronological age, body mass index, smoking status, number of multiple medication uses, blood pressure, blood glucose level, and apoB/apoA ratio were adjusted for as covariates in the model. Overall, using antihypertensive drugs was associated with a decrease in one DNA-methylation age (PCGrimAge: beta = - 0.39, 95%CI = - 0.67 to - 0.12). When looking into drug subcategories, calcium channel blockers (CCBs) were associated with a decrease in several DNA-methylation ages (PCHorvathAge beta = - 1.28, 95%CI = - 2.34 to - 0.21; PCSkin&bloodAge beta = - 1.34, 95%CI = - 2.61 to - 0.07; PCPhenoAge beta = - 1.74, 95%CI = - 2.58 to - 0.89; PCGrimAge beta = - 0.57, 95%CI = - 0.96 to - 0.17) and in functional biological ages (functional age index beta = - 2.18, 95%CI = - 3.65 to - 0.71; frailty index beta = - 1.31, 95%CI = - 2.43 to - 0.18). However, the results within other drug subcategories were inconsistent. Calcium channel blockers may decrease biological aging captured by the BA biomarkers measured at epigenetic and functional level. Future studies are warranted to confirm these effects and understand the underlying biological mechanisms.

NGI SNP genotyping [Service]

NGI Uppsala (SNP&SEQ Technology Platform) [Service]

National Genomics Infrastructure [Service]

PubMed 37032369

DOI 10.1007/s11357-023-00784-8

Crossref 10.1007/s11357-023-00784-8

pii: 10.1007/s11357-023-00784-8

Publications 9.2.2