Association of Genetic Variants Related to Gluteofemoral vs Abdominal Fat Distribution With Type 2 Diabetes, Coronary Disease, and Cardiovascular Risk Factors
Open accessAbstract
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.
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Weight-related cardiometabolic abnormalities occur due to excess visceral adipose tissue, which secretes hormones and proinflammatory cytokines, leading to low-grade systemic inflammation.
“Weight-related cardiometabolic abnormalities occur due to excess visceral adipose tissue (and possibly an impaired ability to deposit fat into the peripheral adipose tissue such as the gluteofemoral fat compartment), which secretes hormones and proinflammatory cytokines, leading to low-grade systemic inflammation.23,24,27”
From Obesity Management in Adults (2023) · cites this paper as [27]
The Discussion (page unavailable) supports a possible role for excess abdominal fat and impaired gluteofemoral fat storage in cardiometabolic risk. It does not say that visceral fat secretes hormones and proinflammatory cytokines that cause low-grade systemic inflammation, so the proposed mechanism is unsupported by this paper. (LLM, conf=0.88)
Experimental — accuracy not yet measuredEffective performance across differing sensor locations allows leveraging large-scale unlabeled datasets typically collected at the wrist to jumpstart recognition for rarer leg-based activities such as classifying freeze of gait.
“Effective performance across differing sensor locations allows for leveraging large scale unlabeled datasetswhich are typically collected at the wrist (such as Capture-24 [4,18,81], Fenland [46,51], and Biobank [14]), to jumpstart recognition for rarer leg-based activities such as classifying freeze of gait.”
From Assessing the State of Self-Supervised Human Activity Recognition Using Wearables (2022) · cites this paper as [46]
The Study Design and Outcomes passages describe genetic analyses and DEXA fat-mass measurements using UK Biobank and Fenland data. Our copy does not address wrist-worn sensor datasets, performance across sensor locations, or freeze-of-gait recognition; searches for wrist sensors and freeze of gait found no supporting passage. No page numbers were available in our copy. (LLM, conf=0.75)
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- Authors
- Lotta, L. A., Wittemans, L. B. L., Zuber, V., Stewart, I. D., Sharp, S. J., Luan, J., Day, F. R., Li, C., Bowker, N., Cai, L., De Lucia Rolfe, E., Khaw, K.-T., Perry, J. R. B., O’Rahilly, S., Scott, R. A., Savage, D. B., Burgess, S., Wareham, N. J., & Langenberg, C.
- Affiliations
- University of Cambridge (GB)
- MRC Epidemiology Unit, University of Cambridge, Cambridge, United Kingdom
- Corresponding author
- Lotta, Luca A.
- Langenberg, Claudia
- ORCID
- Venue
- JAMA
- Publisher
- American Medical Association (AMA)
- Published
- 2018-12-25
- Volume
- 320
- Issue
- 24
- Pages
- 2553
- ISSN
- 0002-9955 (ISSN-L)
- 0098-7484
- PMC
- PMC6583513
- OpenAlex
- W2905879876
- Cited by
- 229
- References
- 46
- Citations by year
- 2026: 19 · 2025: 35 · 2024: 29 · 2023: 31 · 2022: 34 · 2021: 42 · 2020: 19 · 2019: 19
- FWCI
- 12.39
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- other-oa
- Locations
- JAMA (publishedVersion, other-oa)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Apollo (University of Cambridge) (submittedVersion, other-oa)
- Spiral (Imperial College London) (submittedVersion)
- Apollo
- Funders
- Wellcome Trust (204623/Z/16/Z, 107064/Z/15/Z, WT107064, WT095515)
- European Federation of Pharmaceutical Industries and Associations (115372)
- Cancer Research UK (14136)
- National Institute for Health and Care Research (NF-SI-0617-10113, NF-SI-0512-10165, NF-SI-0513-10109, MC_UU_12015/1, NF-SI-0512-10114, NF-SI-0512-10135, NF-SI-0617-10149)
- British Heart Foundation (RG/13/13/30194)
- European Commission (602068)
- Cambridge University Hospitals (146281)
- Medical Research Council (MC_UU_12015/1, MC_PC_13046, MC_PC_13048, MC_UU_12015, MR/L003120/1, MC_UU_12015/2, MR/N003284/1, MC UU12012/5, 1950385, MR/L00002/1)
- NIHR Cambridge Biomedical Research Centre
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes, Cardiovascular Risks, and Lipoproteins
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetics and Physical Performance
- Keywords
- waist-to-hip ratio, abdominal fat distribution, type 2 diabetes, coronary disease, cardiovascular risk factors, polygenic risk score, genetic variants, cardiometabolic risk, blood pressure, LDL cholesterol, triglycerides, insulin, body fat distribution, hip circumference, waist circumference, dual-energy X-ray absorptiometry, body mass index, UK Biobank
- MeSH terms
- Cardiovascular Diseases, Coronary Disease, Diabetes Mellitus, Type 2, Female, Humans, Male, Middle Aged, Risk Factors, Genetic Variation, Body Mass Index, Genetic Predisposition to Disease, Waist-Hip Ratio, Abdominal Fat, Adiposity, Genome-Wide Association Study
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