Back

Harnessing confounding and genetic pleiotropy to identify causes of disease through proteomics and Mendelian randomisation - 'MR Fish'.

Warwick, A. N.; Hingorani, A.; Khawaja, A. P.; Gordillo-Maranon, M.; Olvera-Barrios, A.; Stuart, K. V.; Egan, C.; Tufail, A.; Sofat, R.; Kuan, V.; Finan, C.; Schmidt, A. F.

2024-07-11 genetic and genomic medicine
10.1101/2024.07.11.24310200 medRxiv
Show abstract

We propose an extension of the Mendelian randomisation (MR) paradigm ( MR-Fish) in which the confounded disease association of an index protein ( the bait) is harnessed to identify the causal role of different proteins ( the catch) for the same disease. Using C-reactive protein (CRP) as the bait, cis-MR analyses refuted a causal relationship of CRP with a wide range of diseases that associate with CRP in observational studies, including type 2 diabetes (T2DM) and coronary heart disease (CHD), suggesting these associations are confounded. Using MR-Fish, and leveraging large-scale proteomics data, we find evidence of a causal relationship with multiple diseases for several proteins encoded by genes that are trans hits in genome wide association analysis of CRP. These include causal associations of IL6R and FTO with CHD and T2DM; as well as ZDHHC18 with several circulating blood lipid fractions. Among the proteins encoded by genes that are trans-for-CRP we identified 28 that are druggable. Our findings point to a general approach using MR analysis with proteomics data to identify causal pathways and therapeutic targets from non-causal observational associations of an index protein with a disease.

Matching journals

The top 4 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.