Impact of genetic risk loci for multiple sclerosis on expression of proximal genes in patients.

James T, Lindén M, Morikawa H, Fernandes SJ, Ruhrmann S, Huss M, Brandi M, Piehl F, Jagodic M, Tegnér J, Khademi M, Olsson T, Gomez-Cabrero D, Kockum I

Hum. Mol. Genet. 27 (5) 912-928 [2018-03-01; online 2018-01-13]

Despite advancements in genetic studies, it is difficult to understand and characterize the functional relevance of disease-associated genetic variants, especially in the context of a complex multifactorial disease such as multiple sclerosis (MS). As a large proportion of expression quantitative trait loci (eQTLs) are context-specific, we performed RNA-Seq in peripheral blood mononuclear cells from MS patients (n = 145) to identify eQTLs in regions centered on 109 MS risk single nucleotide polymorphisms and 7 associated human leukocyte antigen variants. We identified 77 statistically significant eQTL associations, including pseudogenes and non-coding RNAs. Thirty-eight out of 40 testable eQTL effects were colocalized with the disease association signal. As many eQTLs are tissue specific, we aimed to detail their significance in different cell types. Approximately 70% of the eQTLs were replicated and characterized in at least one major peripheral blood mononuclear cell-derived cell type. Furthermore, 40% of eQTLs were found to be more pronounced in MS patients compared with non-inflammatory neurological diseases patients. In addition, we found two single nucleotide polymorphisms to be significantly associated with the proportions of three different cell types. Mapping to enhancer histone marks and predicted transcription factor binding sites added additional functional evidence for eight eQTL regions. As an example, we found that rs71624119, shared with three other autoimmune diseases and located in a primed enhancer (H3K4me1) with potential binding for STAT transcription factors, significantly associates with ANKRD55 expression. This study provides many novel and validated targets for future functional characterization of MS and other diseases.

Bioinformatics Support for Computational Resources [Service]

NGI Stockholm (Genomics Applications) [Service]

NGI Stockholm (Genomics Production) [Service]

National Genomics Infrastructure [Service]

PubMed 29325110

DOI 10.1093/hmg/ddy001

Crossref 10.1093/hmg/ddy001

pii: 4792999