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

## TL;DR

This study identifies genes and proteins that causally affect type 2 diabetes risk across different populations and tissues.

## Contribution

The study introduces a cross-ancestry and tissue-aware causal inference approach to uncover molecular mechanisms of T2D.

## Key findings

- 335 genes and 46 proteins show causal effects on T2D risk with partial replication in independent cohorts.
- 676 genes are causally linked to T2D risk in disease-relevant tissues, including newly identified genes like CPXM1.
- Causal effects are shared across ancestries but vary significantly across tissues.

## Abstract

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.

Analysing the causal links of gene expression and protein abundance on type 2 diabetes risk in blood and seven tissues related to the disease from individuals of four ancestries, the authors advance our understanding of the genetic architecture of type 2 diabetes