Back

Joint analysis reveals shared autoimmune disease associations and identifies common mechanisms

Lincoln, M. R.; Connally, N.; Axisa, P.-P.; Gasperi, C.; Mitrovic, M.; van Heel, D.; Wijmenga, C.; Withoff, S.; Jonkers, I. H.; Padyukov, L.; Consortium, I. M. G.; Rich, S. S.; Graham, R. R.; Gaffney, P. M.; Langefeld, C. D.; Hafler, D. A.; Chun, S. G.; Sunyaev, S. R.; Cotsapas, C.

2021-05-18 genetic and genomic medicine
10.1101/2021.05.13.21257044 medRxiv
Show abstract

Autoimmune and inflammatory diseases are polygenic disorders of the immune system. Many genomic loci harbor risk alleles for several diseases, but the limited resolution of genetic mapping prevents determining if the same allele is responsible, indicating a shared underlying mechanism. Using a collection of 129,058 cases and controls across six diseases, we show that [~]40% of overlapping associations are due to the same allele. We improve fine-mapping resolution for shared alleles two-fold by combining cases and controls across diseases, allowing us to identify more eQTLs driven by the shared alleles. The patterns of sharing indicate widespread shared mechanisms, but not a single global autoimmune mechanism. Our approach can be applied to any set of traits, and is particularly valuable as sample collections become depleted. One sentence summaryGenetic mapping in autoimmune diseases increases genetic mapping resolution and reveals shared mechanisms

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.