Abstract
Genetic studies have identified 61 variants associated with the risk of developing Type 1 Diabetes (T1D). The functions of most of the non-HLA (Human Leukocyte Antigen) genetic variants remain unknown. We found that only 16 of these risk variants could potentially be linked to a protein-coding change. Therefore, we investigated whether these variants affected susceptibility by regulating changes in gene expression. To do so, we examined whole transcriptome profiles of 600 samples from the Type 1 Diabetes Genetics Consortium (T1DGC). These comprised four different immune cell types (Epstein-Barr virus (EBV)-transformed B cells, either basal or after stimulation; and cluster of differentiation (CD)4+ and CD8+ T cells). Many of the T1D-associated risk variants regulated expression of either neighboring (cis-) or distant (trans-) genes. In brief, 24 of the non-HLA T1D variants affected the expression of 31 nearby genes (cis) while 25 affected 38 distant genes (trans). The effects were highly significant (False Discovery Rate p < 0.001). In addition, we searched in public databases for expression effects of T1D single nucleotide polymorphisms (SNPs) in other immune cell types such as CD14+ monocytes, lipopolysaccharide (LPS) stimulated monocytes, and CD19+ B cells. In this paper, we review the (expression quantitative trait loci (eQTLs) associated with each of the 60 T1D variants and provide a summary of the genes impacted by T1D risk alleles in various immune cells. We then review the methodological steps involved in analyzing the function of genome wide association studies (GWAS)-identified variants, with emphasis on those affecting gene expression. We also discuss recent advancements in the methodologies and their advantages. We conclude by suggesting future study designs that will aid in the study of T1D risk variants.
Highlights
Four [1,2,3,4] genome wide association studies (GWAS), a linkage study [5], and five [6,7,8,9,10] other studies have identified 61 genetic variants that confer risk of Type 1 Diabetes (T1D)
We review the methodological steps involved in analyzing the function of genome wide association studies (GWAS)-identified variants, with emphasis on those affecting gene expression
We looked for reported Expression Quantitative Trait Locus (eQTL) involving either lead T1D single nucleotide polymorphisms (SNPs) or any SNPs in high linkage disequilibrium (LD) (i.e., r2 > 0.8) with the lead T1D SNPs
Summary
Four [1,2,3,4] genome wide association studies (GWAS), a linkage study [5], and five [6,7,8,9,10] other studies have identified 61 genetic variants that confer risk of Type 1 Diabetes (T1D). The false discovery rate (FDR) method [20] was employed to allow for multiple testing; genes with FDR < 0.05 were deemed significant The aims of this analysis were to identify genes that were up or down regulated according to the risk SNP genotypes and to identify pathways and networks affected. The associations in peripheral blood serve as validation for associations found in other cell types These studies had reported adjusted (FDR) and unadjusted p-values for the SNP-gene associations that were deemed significant by them using suitable FDR thresholds. We searched in these databases for gene expression effects of only T1D. Enrichment analysis was performed using the Molecular Signature Database (MsigDB) [28] to describe the possible biological mechanism of the identified cis- and trans- regulated genes
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