<p>Type 2 diabetes (T2D) is a prevalent disease arising from complex molecular mechanisms. Here we leverage T2D genetic associations to identify causal molecular mechanisms in an ancestry-aware and tissue-aware manner. Using two-sample Mendelian randomization corroborated by colocalization across four global ancestries, we analyse 20,307 gene and 1,630 protein expression levels using blood-derived <i>cis</i>-quantitative trait loci (QTLs). We detect causal effects of genetically predicted levels of 335 genes and 46 proteins on T2D risk, with 16.4% and 50% replication in independent cohorts, respectively. Using gene expression <i>cis</i>-QTLs derived from seven T2D-relevant tissues, we identify causal links between the expression of 676 genes and T2D risk, refining known associations such as <i>BAK1</i> and describing additional ones like <i>CPXM1</i>. Causal effects are mostly shared across ancestries but are highly heterogeneous across tissues. Our findings provide insights into cross-ancestry and tissue-informed multi-omics causal inference approaches and demonstrate their power in uncovering molecular processes driving T2D.</p>

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Unravelling the molecular mechanisms causal to type 2 diabetes across global populations and disease-relevant tissues

  • Ozvan Bocher,
  • Ana Luiza Arruda,
  • Satoshi Yoshiji,
  • Chi Zhao,
  • Alicia Huerta-Chagoya,
  • Chen-Yang Su,
  • Xianyong Yin,
  • Davis Cammann,
  • Henry J. Taylor,
  • Jingchun Chen,
  • Ken Suzuki,
  • Ravi Mandla,
  • Ta-Yu Yang,
  • Fumihiko Matsuda,
  • Josep M. Mercader,
  • Jason Flannick,
  • James B. Meigs,
  • Alexis C. Wood,
  • Marijana Vujkovic,
  • Benjamin F. Voight,
  • Cassandra N. Spracklen,
  • Jerome I. Rotter,
  • Andrew P. Morris,
  • Eleftheria Zeggini

摘要

Type 2 diabetes (T2D) is a prevalent disease arising from complex molecular mechanisms. Here we leverage T2D genetic associations to identify causal molecular mechanisms in an ancestry-aware and tissue-aware manner. Using two-sample Mendelian randomization corroborated by colocalization across four global ancestries, we analyse 20,307 gene and 1,630 protein expression levels using blood-derived cis-quantitative trait loci (QTLs). We detect causal effects of genetically predicted levels of 335 genes and 46 proteins on T2D risk, with 16.4% and 50% replication in independent cohorts, respectively. Using gene expression cis-QTLs derived from seven T2D-relevant tissues, we identify causal links between the expression of 676 genes and T2D risk, refining known associations such as BAK1 and describing additional ones like CPXM1. Causal effects are mostly shared across ancestries but are highly heterogeneous across tissues. Our findings provide insights into cross-ancestry and tissue-informed multi-omics causal inference approaches and demonstrate their power in uncovering molecular processes driving T2D.