Evidence map›Paper›PMID 30575882›Full record

ArticleJAMA2018

Association of Genetic Variants Related to Gluteofemoral vs Abdominal Fat Distribution With Type 2 Diabetes, Coronary Disease, and Cardiovascular Risk Factors.

Luca A Lotta, Laura B L Wittemans, Verena Zuber, Isobel D Stewart, Stephen J Sharp, Jian'an Luan, Felix R Day, Chen Li, Nicholas Bowker, Lina Cai and 9 more

Open access · bronzeAbstract readComparative Study
In one paragraph

Article in JAMA, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 150 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
150citing papers in PubMed, 4 pooled it
16.6field-weighted citation impact, top 1% 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

150 citing papers in PubMed, 4 syntheses or guidelines pooled it, 232 citations in OpenAlex.

  1. Pooled it
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  5. Trial
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  8. Article
  9. Review
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  20. Atrial cardiomyopathy: markers and outcomes.European heart journal · 2026
    Article

90 more citing papers are in PubMed but not listed here.

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

19 authors at 3 institutions in 1 country.

Luca A LottaMRC Epidemiology Unit, University of Cambridge, Cambridge, United Kingdom.
Laura B L WittemansMRC Epidemiology Unit, University of Cambridge, Cambridge, United Kingdom.
Verena ZuberMRC Biostatistics Unit, University of Cambridge, Cambridge, United Kingdom.
Isobel D StewartMRC Epidemiology Unit, University of Cambridge, Cambridge, United Kingdom.
Stephen J SharpMRC Epidemiology Unit, University of Cambridge, Cambridge, United Kingdom.
Jian'an LuanMRC Epidemiology Unit, University of Cambridge, Cambridge, United Kingdom.
Felix R DayMRC Epidemiology Unit, University of Cambridge, Cambridge, United Kingdom.
Chen LiMRC Epidemiology Unit, University of Cambridge, Cambridge, United Kingdom.
Nicholas BowkerMRC Epidemiology Unit, University of Cambridge, Cambridge, United Kingdom.
Lina CaiMRC Epidemiology Unit, University of Cambridge, Cambridge, United Kingdom.
Emanuella De Lucia RolfeMRC Epidemiology Unit, University of Cambridge, Cambridge, United Kingdom.
Kay-Tee KhawDepartment of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom.
John R B PerryMRC Epidemiology Unit, University of Cambridge, Cambridge, United Kingdom.
Stephen O'RahillyMetabolic Research Laboratories, Institute of Metabolic Science, University of Cambridge, Cambridge, United Kingdom.
Robert A ScottMRC Epidemiology Unit, University of Cambridge, Cambridge, United Kingdom.
David B SavageMetabolic Research Laboratories, Institute of Metabolic Science, University of Cambridge, Cambridge, United Kingdom.
Stephen BurgessMRC Biostatistics Unit, University of Cambridge, Cambridge, United Kingdom.
Nicholas J WarehamMRC Epidemiology Unit, University of Cambridge, Cambridge, United Kingdom.
Claudia LangenbergMRC Epidemiology Unit, University of Cambridge, Cambridge, United Kingdom.
MRC Epidemiology Unit · GBUniversity of Cambridge · GBWellcome/MRC Institute of Metabolic Science · GB

Funding

British Heart Foundation RG/13/13/30194Cancer Research UK 14136Medical Research Council G0401527Medical Research Council G1000143Medical Research Council MC_UU_00002/7Medical Research Council MC_UU_12012/5Medical Research Council MC_UU_12015/1Medical Research Council MC_UU_12015/2Medical Research Council MR/L003120/1Medical Research Council MR/N003284/1Wellcome Trust 204623/Z/16/Z
6 · The paper itself

Abstract

Importance: Body fat distribution, usually measured using waist-to-hip ratio (WHR), is an important contributor to cardiometabolic disease independent of body mass index (BMI). Whether mechanisms that increase WHR via lower gluteofemoral (hip) or via higher abdominal (waist) fat distribution affect cardiometabolic risk is unknown. Objective: To identify genetic variants associated with higher WHR specifically via lower gluteofemoral or higher abdominal fat distribution and estimate their association with cardiometabolic risk. Design, Setting, and Participants: Genome-wide association studies (GWAS) for WHR combined data from the UK Biobank cohort and summary statistics from previous GWAS (data collection: 2006-2018). Specific polygenic scores for higher WHR via lower gluteofemoral or via higher abdominal fat distribution were derived using WHR-associated genetic variants showing specific association with hip or waist circumference. Associations of polygenic scores with outcomes were estimated in 3 population-based cohorts, a case-cohort study, and summary statistics from 6 GWAS (data collection: 1991-2018). Exposures: More than 2.4 million common genetic variants (GWAS); polygenic scores for higher WHR (follow-up analyses). Main Outcomes and Measures: BMI-adjusted WHR and unadjusted WHR (GWAS); compartmental fat mass measured by dual-energy x-ray absorptiometry, systolic and diastolic blood pressure, low-density lipoprotein cholesterol, triglycerides, fasting glucose, fasting insulin, type 2 diabetes, and coronary disease risk (follow-up analyses). Results: Among 452 302 UK Biobank participants of European ancestry, the mean (SD) age was 57 (8) years and the mean (SD) WHR was 0.87 (0.09). In genome-wide analyses, 202 independent genetic variants were associated with higher BMI-adjusted WHR (n = 660 648) and unadjusted WHR (n = 663 598). In dual-energy x-ray absorptiometry analyses (n = 18 330), the hip- and waist-specific polygenic scores for higher WHR were specifically associated with lower gluteofemoral and higher abdominal fat, respectively. In follow-up analyses (n = 636 607), both polygenic scores were associated with higher blood pressure and triglyceride levels and higher risk of diabetes (waist-specific score: odds ratio [OR], 1.57 [95% CI, 1.34-1.83], absolute risk increase per 1000 participant-years [ARI], 4.4 [95% CI, 2.7-6.5], P < .001; hip-specific score: OR, 2.54 [95% CI, 2.17-2.96], ARI, 12.0 [95% CI, 9.1-15.3], P < .001) and coronary disease (waist-specific score: OR, 1.60 [95% CI, 1.39-1.84], ARI, 2.3 [95% CI, 1.5-3.3], P < .001; hip-specific score: OR, 1.76 [95% CI, 1.53-2.02], ARI, 3.0 [95% CI, 2.1-4.0], P < .001), per 1-SD increase in BMI-adjusted WHR. Conclusions and Relevance: Distinct genetic mechanisms may be linked to gluteofemoral and abdominal fat distribution that are the basis for the calculation of the WHR. These findings may improve risk assessment and treatment of diabetes and coronary disease.

Indexed as

Abdominal FatGenetic Predisposition to DiseaseGenetic VariationWaist-Hip RatioAdiposityBody Mass IndexCardiovascular DiseasesCoronary DiseaseDiabetes Mellitus, Type 2FemaleGenome-Wide Association StudyHumansMaleMiddle AgedRisk Factors

Identifiers

PMID30575882
PMCPMC6583513
OpenAlexW2905879876

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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.