| Literature DB >> 29325110 |
Tojo James1,2, Magdalena Lindén1,2,3, Hiromasa Morikawa2,4,5, Sunjay Jude Fernandes2,4, Sabrina Ruhrmann1,2, Mikael Huss6, Maya Brandi6, Fredrik Piehl1,2, Maja Jagodic1,2, Jesper Tegnér2,4,5,7, Mohsen Khademi1,2, Tomas Olsson1,2, David Gomez-Cabrero4,8,9, Ingrid Kockum1,2.
Abstract
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.Entities:
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Year: 2018 PMID: 29325110 DOI: 10.1093/hmg/ddy001
Source DB: PubMed Journal: Hum Mol Genet ISSN: 0964-6906 Impact factor: 6.150