Abstract 4362302: Premature Menopause and Polygenic Risk on Incident Coronary Artery Disease among Postmenopausal Women

Introduction: Cardiovascular disease (CVD) remains the leading cause of death among women. Premature menopause (onset <40 years) is a recognized risk-enhancing factor for coronary artery disease (CAD). In parallel, CAD polygenic risk scores (PRS) quantify inherited susceptibility to CAD. However, the extent to which genetic risk interacts with reproductive aging in CAD risk among women is underexplored. Aims: The aim of this study is to assess how menopausal timing and CAD genetic risk jointly affect CAD risk among postmenopausal women. Methods: Postmenopausal women in the UK Biobank without prior histories of CAD or surgical premature menopause were included in this analysis. CAD PRS was computed using GPSMult, a previously validated multi-ancestry CAD PRS. Participants were assigned genetic risk levels by PRS quintile into low (Q1), intermediate (Q2–4), or high (Q5) risk. They were then stratified into six groups by menopausal timing (premature or non-premature) and PRS category (low, intermediate, or high). CAD incidence was assessed using age-based cumulative incidence curves with aligned number-at-risk tables. Results: This study included 105,351 postmenopausal women in the UK Biobank, of whom 3216 (3.05%) experienced premature menopause. Over median [interquartile range] follow-up of 6.99 [6.23-7.62] years, 1102 (1.05%) experienced incident CAD. Relative to women without premature menopause, premature menopause was associated with 1.70 (95% CI 1.30-2.23) risk for CAD. Relative to intermediate, high CAD PRS was associated with 2.32 (95% CI 2.05-2.63) risk for CAD. Together, they were associated with additive risk for CAD (p-interaction 0.27). The highest cumulative incidence (2.86%) was observed in women with both premature menopause and high CAD PRS (Fig 1). Those without premature menopause and high CAD PRS had a cumulative incidence (2.09%) exceeding those with premature menopause and intermediate CAD PRS (1.67%). Conclusion: Combining polygenic risk with menopausal timing yields a deeper understanding of CAD susceptibility in women. While premature menopause and elevated genetic risk independently increase CAD incidence, the combination identifies a subgroup of women at particularly elevated risk in both premature and non-premature menopause subgroups. These findings highlight the potential utility of incorporating reproductive history and genetic risk into personalized cardiovascular risk assessment and early prevention strategies.

Authors

Institutions

Publication Details

Journal
Circulation
Published
2025-11-03
DOI
https://doi.org/10.1161/circ.152.suppl_3.4362302
Primary Topic
Cardiovascular Health and Risk Factors
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Abstract 4362302: Premature Menopause and Polygenic Risk on Incident Coronary Artery Disease among Postmenopausal Women

Michael C. Honigberg, Yunfeng Ruan, Pradeep Natarajan, Kaavya Paruchuri et al.
Circulation
Cardiovascular Health and Risk Factors
article

Abstract 4362302: Premature Menopause and Polygenic Risk on Incident Coronary Artery Disease among Postmenopausal Women

Michael C. Honigberg, Yunfeng Ruan, Pradeep Natarajan, Kaavya Paruchuri, Aniruddh P. Patel, Whitney Hornsby, Shriienidhie Ganesh
article en

Abstract

Introduction: Cardiovascular disease (CVD) remains the leading cause of death among women. Premature menopause (onset <40 years) is a recognized risk-enhancing factor for coronary artery disease (CAD). In parallel, CAD polygenic risk scores (PRS) quantify inherited susceptibility to CAD. However, the extent to which genetic risk interacts with reproductive aging in CAD risk among women is underexplored. Aims: The aim of this study is to assess how menopausal timing and CAD genetic risk jointly affect CAD risk among postmenopausal women. Methods: Postmenopausal women in the UK Biobank without prior histories of CAD or surgical premature menopause were included in this analysis. CAD PRS was computed using GPSMult, a previously validated multi-ancestry CAD PRS. Participants were assigned genetic risk levels by PRS quintile into low (Q1), intermediate (Q2–4), or high (Q5) risk. They were then stratified into six groups by menopausal timing (premature or non-premature) and PRS category (low, intermediate, or high). CAD incidence was assessed using age-based cumulative incidence curves with aligned number-at-risk tables. Results: This study included 105,351 postmenopausal women in the UK Biobank, of whom 3216 (3.05%) experienced premature menopause. Over median [interquartile range] follow-up of 6.99 [6.23-7.62] years, 1102 (1.05%) experienced incident CAD. Relative to women without premature menopause, premature menopause was associated with 1.70 (95% CI 1.30-2.23) risk for CAD. Relative to intermediate, high CAD PRS was associated with 2.32 (95% CI 2.05-2.63) risk for CAD. Together, they were associated with additive risk for CAD (p-interaction 0.27). The highest cumulative incidence (2.86%) was observed in women with both premature menopause and high CAD PRS (Fig 1). Those without premature menopause and high CAD PRS had a cumulative incidence (2.09%) exceeding those with premature menopause and intermediate CAD PRS (1.67%). Conclusion: Combining polygenic risk with menopausal timing yields a deeper understanding of CAD susceptibility in women. While premature menopause and elevated genetic risk independently increase CAD incidence, the combination identifies a subgroup of women at particularly elevated risk in both premature and non-premature menopause subgroups. These findings highlight the potential utility of incorporating reproductive history and genetic risk into personalized cardiovascular risk assessment and early prevention strategies.

CirculationVol. 152(Suppl_3)
Broad Institute (US), Massachusetts General Hospital (US), University School (US), Case Western Reserve University (US)
Openalex Percentile: Top 52%
Cardiovascular Health and Risk Factors
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.