Abstract 4361633: Incorporation of Genetic Risk Factors for Coronary Heart Disease into Clinical Risk Calculators Improved Risk Prediction in Three Major Race/Ethnicity Groups in the United States

M Mohammadreza Naderian J Johanna Smith (Mayo Clinic in Rochester, Rochester, Minnesota, United States) M Marwan Hamed (Mayo Clinic, Rochester, Minnesota, United States) O Ozan Dikilitas (Mayo Clinic, Rochester, Minnesota, United States) J Joshua Cortopassi (UNIVERSITY ALABAMA BIRMINGHAM, Birmiham, Alabama, United States) A Angelica Espinoza (Northwestern University - Chicago, La Grange Park, Illinois, United States) Q Qiping Feng R Ryan Irvin (UNIVERSITY ALABAMA BIRMINGHAM, Birmiham, Alabama, United States) G Gail Jarvik (University of Washington, Seattle, Washington, United States) L Leah Kottyan N Nita Limdi (UNIVERSITY ALABAMA BIRMINGHAM, Birmingham, Alabama, United States) E Elizabeth McNally (Northwestern University, Chicago, Illinois, United States) E Emily Miller (Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, United States) B bahram namjou (CINCINNATI CHILDRENS HOSPTIAL, Cincinnati, Ohio, United States) M Megan Puckelwartz (Northwestern University, Chicago, Illinois, United States) R Robb Rowley (National Institutes of Health, Bethesda, Maryland, United States) H Hemant Tiwari (University of Alabama, Birmingham, AL, USA.) W Wei-Qi Wei A Atlas Khan J John Connolly G Georgia Wiesner (VANDERBILT UNIVERSITY MEDICAL, Nashville, Tennessee, United States) T Teri Manolio (National Institutes of Health, Bethesda, Maryland, United States) R Richard Sharp (World Wildlife Fund, Global Science) I Iftikhar Kullo (Mayo Clinic in Rochester, Rochester, Minnesota, United States)

Abstract

Background: We investigated the impact of genetic risk factors for coronary heart disease (CHD) -polygenic risk score (PRS), familial hypercholesterolemia (FH), and family history (FamHx)- on CHD risk estimates, across the age spectrum, in two diverse cohorts of US adults -eMERGE IV (eIV) and All of Us (AoU). Methods: CHD was defined as myocardial infarction, unstable angina, and coronary revascularization. Self-identified race/ethnicity (SIRE) was used as a population descriptor. We calculated a PRS for CHD (PRS CHD , PGS004698), ascertained FH as the presence of pathogenic/likely pathogenic variants in FH genes, and defined FamHx as early-onset CHD in first-degree relatives. We employed Pooled Cohort Equations (PCE) to estimate the 10y risk of CHD for adults ≥40y and modeled the association of conventional risk factors with CHD in adults <40y. AoU served as the training set, and eIV as the testing set. We analyzed the impact of PRS CHD and FamHx on CHD risk estimates by a) using multivariable logistic regression and Cox proportional hazard models, assessing discrimination and the extent of risk reclassification; and b) net benefit analysis and decision curves to assess the performance of prediction models across actionable thresholds. Results: We analyzed data for 19348 participants from eIV (age 50±15, 68% female, 41% non-White) and 239645 participants from AoU (age 55±17, 61% female, 48% non-White). Genetic risk factors were significantly associated with CHD. PRS CHD performance varied by SIRE groups, while FamHx was consistent. The effects of PRS CHD and FamHx on CHD were independent and additive (Figure 1). In adults ≥40y, incorporating PRS CHD and FamHx into PCE improved discrimination (C-statistic increased from 0.719 to 0.753; P -diff=9.1×10 -3 , Figure 2) and reclassified risk in 19% and 20% of participants at the 7.5% and 10% 10y CHD risk thresholds, respectively. Between the 7.5% and 10% 10y CHD risk thresholds, incorporating PRS CHD and FamHx into the PCE improved the net benefit of the risk prediction models across White, Black, and Hispanic/Latino groups (Figure 3). Conclusion: PRS CHD and FamHx were independently and additively associated with CHD in two large diverse cohorts in the US. Incorporating PRS CHD and FamHx into PCE improved risk discrimination, reclassified risk in a significant portion of participants, and improved net benefit of the PCE across all three major SIRE groups, motivating the addition of these factors to clinical risk calculators.

Article Details

Journal Circulation
Volume / Issue Vol. 152, Issue Suppl_3
Published November 04, 2025
ISSN 0009-7322
Publisher Lippincott Williams & Wilkins

Journal Info

Circulation

Lippincott Williams & Wilkins

ISSN: 0009-7322 Health Sciences

Authors (24)

M

Mohammadreza Naderian

J

Johanna Smith

Mayo Clinic in Rochester, Rochester, Minnesota, United States

M

Marwan Hamed

Mayo Clinic, Rochester, Minnesota, United States

O

Ozan Dikilitas

Mayo Clinic, Rochester, Minnesota, United States

J

Joshua Cortopassi

UNIVERSITY ALABAMA BIRMINGHAM, Birmiham, Alabama, United States

A

Angelica Espinoza

Northwestern University - Chicago, La Grange Park, Illinois, United States

Q

Qiping Feng

R

Ryan Irvin

UNIVERSITY ALABAMA BIRMINGHAM, Birmiham, Alabama, United States

G

Gail Jarvik

University of Washington, Seattle, Washington, United States

L

Leah Kottyan

N

Nita Limdi

UNIVERSITY ALABAMA BIRMINGHAM, Birmingham, Alabama, United States

E

Elizabeth McNally

Northwestern University, Chicago, Illinois, United States

E

Emily Miller

Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, United States

B

bahram namjou

CINCINNATI CHILDRENS HOSPTIAL, Cincinnati, Ohio, United States

M

Megan Puckelwartz

Northwestern University, Chicago, Illinois, United States

R

Robb Rowley

National Institutes of Health, Bethesda, Maryland, United States

H

Hemant Tiwari

University of Alabama, Birmingham, AL, USA.

W

Wei-Qi Wei

A

Atlas Khan

J

John Connolly

G

Georgia Wiesner

VANDERBILT UNIVERSITY MEDICAL, Nashville, Tennessee, United States

T

Teri Manolio

National Institutes of Health, Bethesda, Maryland, United States

R

Richard Sharp

World Wildlife Fund, Global Science

I

Iftikhar Kullo

Mayo Clinic in Rochester, Rochester, Minnesota, United States