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


Journal

GeroScience
ISSN: 2509-2723
Titre abrégé: Geroscience
Pays: Switzerland
ID NLM: 101686284

Informations de publication

Date de publication:
06 2023
Historique:
received: 18 01 2023
accepted: 26 03 2023
medline: 4 8 2023
pubmed: 10 4 2023
entrez: 9 4 2023
Statut: ppublish

Résumé

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.

Identifiants

pubmed: 37032369
doi: 10.1007/s11357-023-00784-8
pii: 10.1007/s11357-023-00784-8
pmc: PMC10400489
doi:

Substances chimiques

Antihypertensive Agents 0
Calcium Channel Blockers 0
Hypoglycemic Agents 0
Lipids 0
DNA 9007-49-2

Types de publication

Journal Article Research Support, Non-U.S. Gov't Research Support, N.I.H., Extramural Research Support, N.I.H., Intramural

Langues

eng

Sous-ensembles de citation

IM

Pagination

2065-2078

Subventions

Organisme : NIA NIH HHS
ID : RF1 AG067996
Pays : United States

Informations de copyright

© 2023. The Author(s).

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Auteurs

Bowen Tang (B)

Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, 171 77, Stockholm, Sweden.

Xia Li (X)

Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, 171 77, Stockholm, Sweden.
School of Public Health and Emergency Management, Southern University of Science and Technology, Shenzhen, China.

Yunzhang Wang (Y)

Department of Clinical Sciences, Danderyd Hospital, Karolinska Institutet, Solna, Sweden.

Arvid Sjölander (A)

Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, 171 77, Stockholm, Sweden.

Kristina Johnell (K)

Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, 171 77, Stockholm, Sweden.

Madhav Thambisetty (M)

Brain Aging and Behavior Section, National Institute on Aging, Baltimore, USA.

Luigi Ferrucci (L)

Longitudinal Studies Section, National Institute on Aging, Baltimore, USA.

Chandra A Reynolds (CA)

Department of Psychology, University of California, Riverside, CA, USA.

Deborah Finkel (D)

Aging Research Network-Jönköping (ARN-J), School of Health and Welfare, Jönköping University, Jönköping, Sweden.
Center for Economic and Social Research, University of Southern California, Los Angeles, CA, USA.

Juulia Jylhävä (J)

Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, 171 77, Stockholm, Sweden.
Faculty of Social Sciences (Health Sciences) and Gerontology Research Center (GEREC), University of Tampere, Tampere, Finland.

Nancy L Pedersen (NL)

Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, 171 77, Stockholm, Sweden.

Sara Hägg (S)

Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, 171 77, Stockholm, Sweden. sara.hagg@ki.se.

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Classifications MeSH