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Genetic mapping across autoimmune diseases reveals shared associations and mechanisms

  • Matthew R. Lincoln,
  • Noah Connally,
  • Pierre-Paul Axisa,
  • Christiane Gasperi,
  • Mitja Mitrovic,
  • David van Heel,
  • Cisca Wijmenga,
  • Sebo Withoff,
  • Iris H. Jonkers,
  • Leonid Padyukov,
  • Ashley H. Beecham,
  • Nikolaos A. Patsopoulos,
  • Chris Cotsapas,
  • David Booth,
  • An Goris,
  • Annette Oturai,
  • Janna Saarela,
  • Betrand Fontaine,
  • Bertrand Hemmer,
  • Martin Claes,
  • Frauke Zipp,
  • Sandra D’Alfonso,
  • Filippo Martinelli-Boneschi,
  • Bruce Taylor,
  • Hanne F. Harbo,
  • Ingrid Kockum,
  • Jan Hillert,
  • Tomas Olsson,
  • Jorge R. Oksenberg,
  • Rogier Hintzen,
  • Lisa F. Barcellos,
  • Lars Alfredsson,
  • Federica Esposito,
  • Roland Martin,
  • Jonathan L. Haines,
  • Margaret A. Pericak-Vance,
  • Adrian J. Ivinson,
  • Graeme Stewart,
  • David Hafler,
  • Stephen L. Hauser,
  • Alastair Compston,
  • Gil McVean,
  • Philip De Jager,
  • Stephen J. Sawcer,
  • Jakob L. McCauley,
  • Stephen S. Rich,
  • Robert R. Graham,
  • Patrick M. Gaffney,
  • Carl D. Langefeld,
  • Timothy J. Vyse,
  • David A. Hafler,
  • Sung Chun,
  • Shamil R. Sunyaev,
  • Chris Cotsapas

摘要

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 whether the same allele is responsible, indicating a shared underlying mechanism. Here, using a collection of 129,058 cases and controls across 6 diseases, we show that ~40% of overlapping associations are due to the same allele. We improve fine-mapping resolution for shared alleles twofold by combining cases and controls across diseases, allowing us to identify more expression quantitative trait loci driven by the shared alleles. The patterns indicate widespread sharing of pathogenic 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.