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<p>Obesity is a heterogeneous condition not adequately captured by a single adiposity trait. We conducted a multi-trait genome-wide association analysis using individual-level data from 452,768 UK Biobank participants to study obesity in relation to cardiometabolic health. We defined continuous ‘uncoupling phenotypes’, ranging from high adiposity with healthy cardiometabolic profiles to low adiposity with unhealthy ones. We identified 266 variants across 205 genomic loci where adiposity-increasing alleles were simultaneously associated with lower cardiometabolic risk. A genetic risk score (GRS<sub>uncoupling</sub>) aggregating these variants was associated with a lower risk of cardiometabolic disorders, including dyslipidemia and ischemic heart disease, despite higher obesity risk; unlike an adiposity score based on body fat percentage-associated variants (GRS<sub>BFP</sub>). The 266 variants formed eight genetic subtypes of obesity, each with distinct risk profiles and pathway signatures. Proteomic analyses revealed signatures separating adiposity- and health-driven effects. Our findings reveal new mechanisms that uncouple obesity from cardiometabolic comorbidities and lay a foundation for genetically informed subtyping of obesity to support precision medicine.</p>

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Genetic subtyping of obesity reveals biological insights into the uncoupling of adiposity from its cardiometabolic comorbidities

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年9月12日

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  • Nathalie Chami,
  • Zhe Wang,
  • Victor Svenstrup,
  • Virginia Diez Obrero,
  • Daiane Hemerich,
  • Yi Huang,
  • Hesam Dashti,
  • Eleonora Manitta,
  • Michael H. Preuss,
  • Kari E. North,
  • Louise Aas Holm,
  • Cilius E. Fonvig,
  • Jens-Christian Holm,
  • Torben Hansen,
  • Camilla Scheele,
  • Alexander Rauch,
  • Roelof A. J. Smit,
  • Melina Claussnitzer,
  • Ruth J. F. Loos

摘要

Obesity is a heterogeneous condition not adequately captured by a single adiposity trait. We conducted a multi-trait genome-wide association analysis using individual-level data from 452,768 UK Biobank participants to study obesity in relation to cardiometabolic health. We defined continuous ‘uncoupling phenotypes’, ranging from high adiposity with healthy cardiometabolic profiles to low adiposity with unhealthy ones. We identified 266 variants across 205 genomic loci where adiposity-increasing alleles were simultaneously associated with lower cardiometabolic risk. A genetic risk score (GRSuncoupling) aggregating these variants was associated with a lower risk of cardiometabolic disorders, including dyslipidemia and ischemic heart disease, despite higher obesity risk; unlike an adiposity score based on body fat percentage-associated variants (GRSBFP). The 266 variants formed eight genetic subtypes of obesity, each with distinct risk profiles and pathway signatures. Proteomic analyses revealed signatures separating adiposity- and health-driven effects. Our findings reveal new mechanisms that uncouple obesity from cardiometabolic comorbidities and lay a foundation for genetically informed subtyping of obesity to support precision medicine.