Changes to islet cell identity in response to type 2 diabetes (T2D) have been reported in rodent models, but are less well characterized in humans. We assessed the effects of aspects of the diabetic microenvironment on hormone staining, total gene expression, splicing regulation and the alternative splicing patterns of key genes in EndoC-βH1 human beta cells. Genes encoding islet hormones [somatostatin (SST), insulin (INS), Glucagon (GCG)], differentiation markers [Forkhead box O1 (FOXO1), Paired box 6, SRY box 9, NK6 Homeobox 1, NK6 Homeobox 2] and cell stress markers (DNA damage inducible transcript 3, FOXO1) were dysregulated in stressed EndoC-βH1 cells, as were some serine arginine rich splicing factor splicing activator and heterogeneous ribonucleoprotein particle inhibitor genes. Whole transcriptome analysis of primary T2D islets and matched controls demonstrated dysregulated splicing for ~25% of splicing events, of which genes themselves involved in messenger ribonucleic acid processing and regulation of gene expression comprised the largest group. Approximately 5% of EndoC-βH1 cells exposed to these factors gained SST positivity in vitro. An increased area of SST staining was also observed ex vivo in pancreas sections recovered at autopsy from donors with type 1 diabetes (T1D) or T2D (9.3% for T1D and 3% for T2D, respectively compared with 1% in controls). Removal of the stressful stimulus or treatment with the AKT Serine/Threonine kinase inhibitor SH-6 restored splicing factor expression and reversed both hormone staining effects and patterns of gene expression. This suggests that reversible changes in hormone expression may occur during exposure to diabetomimetic cellular stressors, which may be mediated by changes in splicing regulation.

The identification of multiple signals at individual loci could explain additional phenotypic variance ('missing heritability') of common traits, and help identify causal genes. We examined gene expression levels as a model trait because of the large number of strong genetic effects acting in cis. Using expression profiles from 613 individuals, we performed genome-wide single nucleotide polymorphism (SNP) analyses to identify cis-expression quantitative trait loci (eQTLs), and conditional analysis to identify second signals. We examined patterns of association when accounting for multiple SNPs at a locus and when including additional SNPs from the 1000 Genomes Project. We identified 1298 cis-eQTLs at an approximate false discovery rate 0.01, of which 118 (9%) showed evidence of a second independent signal. For this subset of 118 traits, accounting for two signals resulted in an average 31% increase in phenotypic variance explained (Wilcoxon P< 0.0001). The association of SNPs with cis gene expression could increase, stay similar or decrease in significance when accounting for linkage disequilibrium with second signals at the same locus. Pairs of SNPs increasing in significance tended to have gene expression increasing alleles on opposite haplotypes, whereas pairs of SNPs decreasing in significance tended to have gene expression increasing alleles on the same haplotypes. Adding data from the 1000 Genomes Project showed that apparently independent signals could be potentially explained by a single association signal. Our results show that accounting for multiple variants at a locus will increase the variance explained in a substantial fraction of loci, but that allelic heterogeneity will be difficult to define without resequencing loci and functional work.