Disentangling the consequences of type 2 diabetes on targeted metabolite profiles using causal inference and interaction qtl analyses

HIGHLIGHTS

• What: The authors investigate the interplay between metabolomics and T2D risk in the UK Biobank dataset using the Nightingale panel composed of 249 metabolites 92% of which correspond to lipids (HDL IDL LDL VLDL) and lipoproteins. This work provides map of the consequences of T2D on Nightingale targeted metabolite levels and on their genetic regulation enabling better understanding of the T2D trajectory leading to complications. The authors show causal impact of 79 metabolites on T2D risk while twice as many metabolites were causally affected by T2D liability. The authors aim to address these questions and elucidate the . . .
  

   

  

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