Evidence map›Paper›PMID 41720915›Full record

ArticleInternational journal of obesity (2005)2026

Genetic determinants of BMI, diet, and fitness interact to partially explain anthropometric obesity traits but not the metabolic consequences of obesity in men and women.

Carmen E Arrington, Debra K M Tacad, Hooman Allayee, Kristen J Sutton, Catherine Dombroski, Nancy L Keim, John W Newman, Brian J Bennett

Registry-linked trialAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in International journal of obesity (2005), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT02367287 (Assessing the Impact of Diet on Inflammation in Healthy and Obese Adults in a Cross-Sectional Phenotyping Study), which is not on this 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.

NCT02367287 completednot on this map

Assessing the Impact of Diet on Inflammation in Healthy and Obese Adults in a Cross-Sectional Phenotyping Study

TypeobservationalSponsorUSDA, Western Human Nutrition Research CenterRan2015 to 2019Enrolled393ConditionsObesity, Inflammation
3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

8 authors.

Carmen E ArringtonDepartment of Nutrition, University of California-Davis, Davis, CA, USA.ORCID 0000-0001-7403-5976
Debra K M TacadWest Coast Metabolomics Center, University of California-Davis, Davis, CA, USA.ORCID 0000-0002-7383-1564
Hooman AllayeeDepartment of Medicine, David Geffen School of Medicine of UCLA, Los Angeles, CA, USA.
Kristen J SuttonDepartment of Biomedical Informatics, University of Colorado Anschutz Medical Campus, Aurora, CO, USA.ORCID 0000-0002-3704-3560
Catherine DombroskiDepartment of Neurobiology, Physiology and Behavior, University of California-Davis, Davis, CA, USA.
Nancy L KeimDepartment of Nutrition, University of California-Davis, Davis, CA, USA.
John W NewmanWest Coast Metabolomics Center, University of California-Davis, Davis, CA, USA.ORCID 0000-0001-9632-6571
Brian J BennettDepartment of Nutrition, University of California-Davis, Davis, CA, USA. brian.bennett@usda.gov.ORCID 0000-0002-0766-3195

Funding

USDA project 2032-10700-003-000-DUSDA project 2032–51530-025-00D
6 · The paper itself

Abstract

backgroundUnderstanding how genetic factors interact with diet and lifestyle to influence obesity is critical as we move towards models of precision nutrition and medicine.

objectivesTo assess how genetic and lifestyle factors influence the variation in body composition and metabolic syndrome (Metsyn) risk factors.

methodsA cross-sectional sample of age/sex/BMI-balanced 18-66 year old men and women (n = 211) from the USDA Nutritional Phenotyping Study were included in the analysis (NCT02367287). BMI polygenic risk scores (PRS) were calculated with the pgs_calc pipeline. Associations with body composition and Metsyn traits were assessed by linear regression and ANCOVA. Explained variance was evaluated using sum of squares and partial R², with model constraint using Bayesian information criteria.

resultsThe PRS independently explained 15.6% of BMI variance and, after adjusting for age, sex, and genetic population structure, accounted for 11.3% of BMI variance (p

conclusionsThe genetic factors influencing BMI appear to differ from those contributing to measures of adiposity and metabolic consequences of obesity. Genetic risk of high BMI was validated in this cohort, but sex, RMR, and fitness are the more refined determinants of adiposity and dysregulated metabolism in this healthy population. Future research should be sure to utilize genetic risk predictors specifically associated with maladaptive obesity traits rather than more broad associated phenotypes. CLINICAL TRIAL REGISTRY: NCT02367287.

Indexed as

Body Mass IndexDietObesityPhysical FitnessAdolescentAdultAgedBody CompositionCross-Sectional StudiesFemaleGenetic Predisposition to DiseaseGenetic Risk ScoreHumansMaleMetabolic SyndromeMiddle Aged

Identifiers

PMID41720915
PMCPMC13056523

What Socratic holds

Textmetadata
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Registered trials

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 Socratic graph.