Evidence map›Paper›PMID 38464171›Full record

ArticleResearch square2024

Epigenetic age acceleration is associated with blood lipid levels in a multi-ancestry sample of older U.S. adults.

Lisha Lin, Jenna Kiryakos, Farah Ammous, Scott M Ratliff, Erin B Ware, Jessica D Faul, Sharon L R Kardia, Wei Zhao, Kira S Birditt, Jennifer A Smith

Open access · greenAbstract readPreprint
In one paragraph

Article in Research square, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed, 2 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

10 authors at 1 institution in 2 countries.

Lisha LinDepartment of Epidemiology, School of Public Health, University of Michigan.
Jenna KiryakosDepartment of Epidemiology, School of Public Health, University of Michigan.
Farah AmmousDepartment of Epidemiology, School of Public Health, University of Michigan.
Scott M RatliffDepartment of Epidemiology, School of Public Health, University of Michigan.
Erin B WareSurvey Research Center, Institute for Social Research, University of Michigan.
Jessica D FaulSurvey Research Center, Institute for Social Research, University of Michigan.
Sharon L R KardiaDepartment of Epidemiology, School of Public Health, University of Michigan.
Wei ZhaoDepartment of Epidemiology, School of Public Health, University of Michigan.
Kira S BirdittSurvey Research Center, Institute for Social Research, University of Michigan.
Jennifer A SmithDepartment of Epidemiology, School of Public Health, University of Michigan.
University of Michigan · US

Funding

HRS Yrs29-34: Y33 SSA CoFundingU01AG009740 · NIA · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Jessica Faul, KENNETH M LANGA · 1990 to 2026
$555.8M
USC/UCLA Center on Biodemography &Population HealthP30AG017265 · NIA · UNIVERSITY OF SOUTHERN CALIFORNIA · PI JENNIFER A AILSHIRE · 1999 to 2026
$17.9M
DNA Methylation, Genetics, and Modifiable Risk Factors of Dementia in a Nationally Representative, Multi-Ethnic Cohort - Diversity SupplementR01AG067592 · NIA · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI BAKULSKI, KELLY, WARE, ERIN BAKSHIS · 2020 to 2025
$3.8M
A Social Epigenomic Approach to Health Disparities in Cardiovascular Risk FactorsR01HL141292 · NHLBI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI SMITH, JENNIFER ANN · 2018 to 2021
$2.9M
Biological Underpinnings of Socioeconomic Differentials in Health and MortalityR01AG060110 · NIA · UNIVERSITY OF SOUTHERN CALIFORNIA · PI CRIMMINS, EILEEN M · 2018 to 2022
$2.6M
Characterizing disparities in late-onset Alzheimer's disease risk through polygenic risk and epidemiologic factors in the Health and Retirement SurveyR01AG055406 · NIA · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI BAKULSKI, KELLY, WARE, ERIN BAKSHIS · 2017 to 2020
$1.7M
NHLBI NIH HHS R01 HL141292NIA NIH HHS P30 AG017265NIA NIH HHS R01 AG055406NIA NIH HHS R01 AG060110NIA NIH HHS R01 AG067592NIA NIH HHS U01 AG009740
6 · The paper itself

Abstract

Background: Dyslipidemia, which is characterized by an unfavorable lipid profile, is a key risk factor for cardiovascular disease (CVD). Understanding the relationships between epigenetic aging and lipid levels may help guide early prevention and treatment efforts for dyslipidemia. Methods: We used weighted linear regression to cross-sectionally investigate the associations between five measures of epigenetic age acceleration estimated from whole blood DNA methylation (HorvathAge Acceleration, HannumAge Acceleration, PhenoAge Acceleration, GrimAge Acceleration, and DunedinPACE) and four blood lipid measures (total cholesterol (TC), LDL-C, HDL-C, and triglycerides (TG)) in 3,813 participants (mean age = 70 years) from the Health and Retirement Study (HRS). As a sensitivity analysis, we examined the same associations in participants who fasted prior to the blood draw (n = and f) and in participants who did not take lipid-lowering medication (n = 1,869). Using interaction models, we also examined whether the relationships between epigenetic age acceleration and blood lipids differ by demographic factors including age, sex, and educational attainment. Results: After adjusting for age, race/ethnicity, sex, fasting status, and lipid-lowering medication use, greater epigenetic age acceleration was associated with lower TC, HDL-C, and LDL-C, and higher TG (p < 0.05). GrimAge acceleration and DunedinPACE associations with all lipids remained significant after further adjusting for body mass index, smoking status, and educational attainment. These associations were stronger in participants who fasted and who did not use lipid-lowering medication, particularly for LDL-C. We observed the largest number of interactions between DunedinPACE and demographic factors, where the associations with lipids were stronger in younger participants, females, and those with higher educational attainment. Conclusion: Epigenetic age acceleration, a powerful biomarker of cellular aging, is highly associated with blood lipid levels in older adults. A greater understanding of how these associations differ across demographic groups can help shed light on the relationships between aging and downstream cardiovascular diseases. The inverse associations between epigenetic age and TC and LDL-C could be due to sample limitations or the non-linear relationship between age and these lipids, as both TC and LDL-C decrease faster at older ages. More studies are needed to further understand the temporal relationships between epigenetic age acceleration on blood lipids and other health outcomes.

Indexed as

agingcholesterolDNA methylationEpigenetic age accelerationHDL cholesterolLDL cholesterollipidstriglycerides

Identifiers

PMID38464171
PMCPMC10925395
OpenAlexW4392221440

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.