Evidence map›Paper›PMID 33844929›Full record

Trial reportCirculation. Genomic and precision medicine2021

Heterogeneity of the Predictive Polygenic Risk Scores for Coronary Heart Disease Age-at-Onset in Three Different Coronary Heart Disease Family-Based Ascertainments.

Mary F Feitosa, Allison L Kuipers, Mary K Wojczynski, Lihua Wang, Emma Barinas-Mitchell, Alexander M Kulminski, Bharat Thyagarajan, Joseph H Lee, Thomas Perls, Kaare Christensen and 3 more

Abstract readClinical TrialMulticenter Study
In one paragraph

Trial report in Circulation. Genomic and precision medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
  2. Article
  3. Utility of Polygenic Risk Scores in Families with Exceptional Longevity.medRxiv : the preprint server for health sciences · 2025
    Article
  4. Article
  5. Article
  6. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors.

Mary F FeitosaDivision of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, MO (M.F.F., M.K.W., L.W., M.A.P.).
Allison L KuipersDepartment of Epidemiology (A.L.K., E.B.-M., A.B.N., J.M.Z.), University of Pittsburgh, PA.
Mary K WojczynskiDivision of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, MO (M.F.F., M.K.W., L.W., M.A.P.).
Lihua WangDivision of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, MO (M.F.F., M.K.W., L.W., M.A.P.).
Emma Barinas-MitchellDepartment of Epidemiology (A.L.K., E.B.-M., A.B.N., J.M.Z.), University of Pittsburgh, PA.
Alexander M KulminskiBiodemography of Aging Research Unit, Social Science Research Institute, Duke University, Durham, NC (A.M.K.).
Bharat ThyagarajanDepartment of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis (B.T.).
Joseph H LeeSergievsky Center, Taub Institute, Department of Epidemiology and Department of Neurology, Columbia University, NY (J.H.L.).
Thomas PerlsDepartment of Medicine, Boston University School of Medicine, MA (T.P.).
Kaare ChristensenDanish Aging Research Center, University of Southern Denmark, Odense C (K.C.).
Anne B NewmanDepartment of Epidemiology (A.L.K., E.B.-M., A.B.N., J.M.Z.), University of Pittsburgh, PA.
Joseph M ZmudaDepartment of Epidemiology (A.L.K., E.B.-M., A.B.N., J.M.Z.), University of Pittsburgh, PA.
Michael A ProvinceDivision of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, MO (M.F.F., M.K.W., L.W., M.A.P.).

Funding

The Long Life Family StudyU19AG063893 · NIA · WASHINGTON UNIVERSITY · PI PAOLA SEBASTIANI · 2019 to 2026
$125.4M
Washington University Nutrition Obesity Research CenterP30DK056341 · NIDDK · WASHINGTON UNIVERSITY · PI Dominic N Reeds · 1999 to 2026
$30.2M
Long Life Family Study: Data Management and Coordinating CenterU01AG023746 · NIA · WASHINGTON UNIVERSITY · PI PROVINCE, MICHAEL A. · 2004 to 2018
$29.2M
The Long Life Family StudyU01AG023755 · NIA · BOSTON MEDICAL CENTER · PI PERLS, THOMAS T · 2004 to 2018
$13.2M
Plasma beta-amyloid in long lived families: genetics and risk of ADU01AG023749 · NIA · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI COSENTINO, STEPHANIE ANN, LEE, JOSEPH HYUNGWOO · 2004 to 2018
$13.0M
Multicenter Study on Exceptional Survival in Families: The Long Life Family StudyU01AG023744 · NIA · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI NEWMAN, ANNE B., ZMUDA, JOSEPH M. · 2004 to 2018
$12.0M
Long Life Family Study: Duke Univ./Univ. of Southern Denmark Field CenterU01AG023712 · NIA · DUKE UNIVERSITY · PI CHRISTENSEN, KAARE · 2004 to 2018
$10.4M
Genetic Architecture of Adiposity in Multiple Large CohortsR01DK089256 · NIDDK · WASHINGTON UNIVERSITY · PI BARANSKI, THOMAS JOHN, LIU, CHING-TI · 2010 to 2016
$4.6M
Probing The Dark Matter of the Genome in the NHLBI Family Heart StudyR01HL117078 · NHLBI · WASHINGTON UNIVERSITY · PI PROVINCE, MICHAEL A. · 2013 to 2016
$3.0M
NHLBI NIH HHS R01 HL117078NIA NIH HHS U01 AG023712NIA NIH HHS U01 AG023744NIA NIH HHS U01 AG023746NIA NIH HHS U01 AG023749NIA NIH HHS U01 AG023755NIA NIH HHS U19 AG063893NIDDK NIH HHS P30 DK056341NIDDK NIH HHS R01 DK089256
6 · The paper itself

Abstract

backgroundPolygenic risk scores (PRS) for coronary heart disease (CHD) may contribute to assess the overall risk of CHD. We evaluated how PRS may influence CHD risk when the distribution of age-at-onset, sex, and family health history differ significantly.

methodsOur study included 3 family-based ascertainments: LLFS (Long Life Family Study, N

resultsHealthy-aging LLFS presented ≈17 years delayed for CHD age-at-onset compared with FamHS-high risk (

conclusionsDifferences in CHD family-based ascertainments show evidence of PRS interacting with sex to predict CHD risk. In women, CHD age-at-onset was associated with PRS, CHD family history, and interactions of PRS with family history. In men, PRS and CHD family history were the major effects on the CHD age-at-onset. Understanding the heterogeneity of risks associated with CHD end points at both the personal and familial levels may shed light on the underlying genetic effects influencing CHD and lead to more personalized risk prediction.

Indexed as

Coronary DiseaseFamilyAgedAged, 80 and overAge of OnsetFemaleHumansMaleMiddle AgedRisk FactorsSex Factorsagingcardiovascular diseasescoronary artery diseaserisk factors

Identifiers

PMID33844929
PMCPMC8214825

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

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.