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Giuseppe Giordano

Research team manager

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A phenome-wide comparative analysis of genetic discordance between obesity and type 2 diabetes


  • Daniel E Coral
  • Juan Fernandez-Tajes
  • Neli Tsereteli
  • Hugo Pomares-Millan
  • Hugo Fitipaldi
  • Pascal M Mutie
  • Naeimeh Atabaki-Pasdar
  • Sebastian Kalamajski
  • Alaitz Poveda
  • Tyne W Miller-Fleming
  • Xue Zhong
  • Giuseppe N Giordano
  • Ewan R Pearson
  • Nancy J Cox
  • Paul W Franks

Summary, in English

Obesity and type 2 diabetes are causally related, yet there is considerable heterogeneity in the consequences of both conditions and the mechanisms of action are poorly defined. Here we show a genetic-driven approach defining two obesity profiles that convey highly concordant and discordant diabetogenic effects. We annotate and then compare association signals for these profiles across clinical and molecular phenotypic layers. Key differences are identified in a wide range of traits, including cardiovascular mortality, fat distribution, liver metabolism, blood pressure, specific lipid fractions and blood levels of proteins involved in extracellular matrix remodelling. We find marginal differences in abundance of Bacteroidetes and Firmicutes bacteria in the gut. Instrumental analyses reveal prominent causal roles for waist-to-hip ratio, blood pressure and cholesterol content of high-density lipoprotein particles in the development of diabetes in obesity. We prioritize 17 genes from the discordant signature that convey protection against type 2 diabetes in obesity, which may represent logical targets for precision medicine approaches.


  • Genetic and Molecular Epidemiology
  • EXODIAB: Excellence of Diabetes Research in Sweden
  • Department of Clinical Sciences, Malmö
  • eSSENCE: The e-Science Collaboration
  • EpiHealth: Epidemiology for Health

Publishing year





Nature Metabolism

Document type

Journal article


Springer Nature


  • Endocrinology and Diabetes
  • Medical Genetics


  • Genetic variation
  • Machine learning
  • Metabolism
  • Obesity
  • Type 2 diabetes



Research group

  • Genetic and Molecular Epidemiology


  • ISSN: 2522-5812