Evidence map›Paper›PMID 31913407›Full record

ArticleJAMA cardiology2020

Polygenic Risk, Fitness, and Obesity in the Coronary Artery Risk Development in Young Adults (CARDIA) Study.

Venkatesh L Murthy, Rui Xia, Abigail S Baldridge, Mercedes R Carnethon, Stephen Sidney, Claude Bouchard, Mark A Sarzynski, João A C Lima, Gregory D Lewis, Sanjiv J Shah and 2 more

Open access · bronzeAbstract read
In one paragraph

Article in JAMA cardiology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
2.7field-weighted citation impact, top 9% of its field
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

15 citing papers in PubMed, 29 citations in OpenAlex.

  1. Trial
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  4. The Genetic Blueprint of Obesity: From Pathogenesis to Novel Therapies.Obesity reviews : an official journal of the International Association for the Study of Obesity · 2025
    Review
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  10. Polygenic risk scores enhance prediction of body mass index increase in individuals with a first episode of psychosis.European psychiatry : the journal of the Association of European Psychiatrists · 2023
    Article
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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

12 authors at 9 institutions in 1 country.

Venkatesh L MurthyDivision of Cardiovascular Medicine, Department of Medicine, University of Michigan, Ann Arbor.
Rui XiaBrown Foundation Institute of Molecular Medicine, McGovern Medical School, The University of Texas Health Science Center at Houston.
Abigail S BaldridgeDepartment of Preventative Medicine, Feinberg School of Medicine, Northwestern University, Chicago, Illinois.
Mercedes R CarnethonKaiser Permanente Northern California Division of Research, Oakland.
Stephen SidneyKaiser Permanente Northern California Division of Research, Oakland.
Claude BouchardHuman Genomics Laboratory, Pennington Biomedical Research Center, Baton Rouge, Louisiana.
Mark A SarzynskiDepartment of Exercise Science, University of South Carolina, Columbia.
João A C LimaDepartment of Medicine, The Johns Hopkins School of Medicine, Baltimore, Maryland.
Gregory D LewisCardiology Division, Department of Medicine, Massachusetts General Hospital, Boston.
Sanjiv J ShahDepartment of Preventative Medicine, Feinberg School of Medicine, Northwestern University, Chicago, Illinois.
Myriam FornageBrown Foundation Institute of Molecular Medicine, McGovern Medical School, The University of Texas Health Science Center at Houston.
Ravi V ShahCardiology Division, Department of Medicine, Massachusetts General Hospital, Boston.
Kaiser Permanente · USMassachusetts General Hospital · USNorthwestern University · USBrown Foundation · USJohns Hopkins University · USMichigan Medicine · USPennington Biomedical Research Center · USThe University of Texas Health Science Center at Houston · USUniversity of South Carolina · US

Funding

Implications of metabolism on healthy aging in African and Caucasian Americans: the Health ABC studyR01AG059729 · NIA · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI MURTHY, VENKATESH LOCHARLA, NEWMAN, ANNE B. · 2018 to 2022
$3.1M
Molecular markers of early cardiometabolic health transitions in the CARDIA studyR01HL136685 · NHLBI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI MURTHY, VENKATESH LOCHARLA, SHAH, RAVI · 2017 to 2021
$2.6M
NHLBI NIH HHS HHSN268201800003INHLBI NIH HHS HHSN268201800004INHLBI NIH HHS HHSN268201800005INHLBI NIH HHS HHSN268201800006INHLBI NIH HHS HHSN268201800007INHLBI NIH HHS R01 HL136685NIA NIH HHS R01 AG059729
6 · The paper itself

Abstract

Importance: Obesity is a major determinant of disease burden worldwide. Polygenic risk scores (PRSs) have been posited as key predictors of obesity. How a PRS can be translated to the clinical encounter (especially in the context of fitness, activity, and parental history of overweight) remains unclear. Objective: To quantify the relative importance of a PRS, fitness, activity, parental history of overweight, and body mass index (BMI) (calculated as weight in kilograms divided by height in meters squared) in young adulthood on BMI trends over 25 years. Design, Setting, and Participants: This population-based prospective cohort study at 4 US centers included white individuals and black individuals with assessments of polygenic risk of obesity, fitness, activity, and BMI in young adulthood (in their 20s) and up to 25 years of follow-up. Data collected between March 1985 and August 2011 were analyzed from April 25, 2019, to September 29, 2019. Main Outcomes and Measures: Body mass index at the initial visit and 25 years later. Results: This study evaluated an obesity PRS from a recently reported study of 1608 white individuals (848 women [52.7%]) and 909 black individuals (548 women [60.3%]) across the United States. At baseline (year 0), mean (SD) overall BMI was 24.2 (4.5), which increased to 29.6 (6.9) at year 25. Among white individuals, the PRS (combined with age, sex, self-reported parental history of overweight, and principal components of ancestry) explained 11.9% (at year 0) and 13.6% (at year 25) of variation in BMI. Although the addition of fitness increased the explanatory capability of the model (24.0% variance at baseline and up to 18.1% variance in BMI at year 25), baseline BMI in young adulthood was the strongest factor, explaining 52.3% of BMI in midlife in combination with age, sex, and self-reported parental history of overweight. Accordingly, models that included baseline BMI (especially BMI surveillance over time) were better in predicting BMI at year 25 compared with the PRS. In fully adjusted models, the effect sizes for fitness and the PRS on BMI were comparable in opposing directions. The added explanatory capacity of the PRS among black individuals was lower than among white individuals. Among white individuals, addition of baseline BMI and surveillance of BMI over time was associated with improved precision of predicted BMI at year 25 (mean error in predicted BMI 0 kg/m2 [95% CI, -11.4 to 11.4] to 0 kg/m2 [95% CI, -8.5 to 8.5] for baseline BMI and mean error 0 kg/m2 [95% CI, -5.3 to 5.3] for BMI surveillance). Conclusions and Relevance: Cardiorespiratory fitness in young adulthood and a PRS are modestly associated with midlife BMI, although future BMI is associated with BMI in young adulthood. Fitness has a comparable association with future BMI as does the PRS. Caution should be exercised in the widespread use of polygenic risk for obesity prevention in adults, and close clinical surveillance and fitness may have prime roles in limiting the adverse consequences of elevated BMI on health.

Indexed as

Body Mass IndexCardiorespiratory FitnessRisk AssessmentAdolescentAdultBlack or African AmericanCohort StudiesFemaleFollow-Up StudiesHumansMaleObesityParentsPregnancyUnited StatesWhite People

Identifiers

PMID31913407
PMCPMC6990863
OpenAlexW3000738488

What OpenQuestion holds

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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.