A systems biology approach uncovers cell-specific gene regulatory effects of genetic associations in multiple sclerosis

International Multiple Sclerosis Genetics Consortium

Research output: Contribution to journalArticle

Abstract

Genome-wide association studies (GWAS) have identified more than 50,000 unique associations with common human traits. While this represents a substantial step forward, establishing the biology underlying these associations has proven extremely difficult. Even determining which cell types and which particular gene(s) are relevant continues to be a challenge. Here, we conduct a cell-specific pathway analysis of the latest GWAS in multiple sclerosis (MS), which had analyzed a total of 47,351 cases and 68,284 healthy controls and found more than 200 non-MHC genome-wide associations. Our analysis identifies pan immune cell as well as cell-specific susceptibility genes in T cells, B cells and monocytes. Finally, genotype-level data from 2,370 patients and 412 controls is used to compute intra-individual and cell-specific susceptibility pathways that offer a biological interpretation of the individual genetic risk to MS. This approach could be adopted in any other complex trait for which genome-wide data is available.

Original languageEnglish
Article number2236
JournalNature communications
Volume10
Issue number1
DOIs
Publication statusPublished - Dec 1 2019

Fingerprint

Systems Biology
Regulator Genes
biology
genes
genome
Multiple Sclerosis
Genes
cells
Genome-Wide Association Study
Genome
monocytes
magnetic permeability
T-cells
Monocytes
B-Lymphocytes
Genotype
T-Lymphocytes
Cells

All Science Journal Classification (ASJC) codes

  • Chemistry(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Physics and Astronomy(all)

Cite this

A systems biology approach uncovers cell-specific gene regulatory effects of genetic associations in multiple sclerosis. / International Multiple Sclerosis Genetics Consortium.

In: Nature communications, Vol. 10, No. 1, 2236, 01.12.2019.

Research output: Contribution to journalArticle

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