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AimsIndividuals with type 1 diabetes (T1D) carry a markedly increased risk of stroke, with distinct clinical and neuroimaging characteristics as compared to those without diabetes. Using whole-genome sequencing (WGS) and whole-exome sequencing (WES), we aimed to find rare and low-frequency genomic variants associated with stroke in T1D. The lead findings were followed up in various datasets to replicate the findings and to assess their specificity to diabetes.Methods and ResultsWe studied stroke genetics in 1,051 individuals with T1D using WGS or WES. We analysed the genome with single-variant analyses, gene aggregate analyses, and aggregate analyses on genomic windows, enhancers and promoters. Furthermore, we attempted replication in T1D using a genome-wide association study (N=3,945) and direct genotyping (N=3,600), and in the general population from the FinnGen project and UK Biobank summary statistics. We identified a rare missense mutation onSREBF1associated with hemorrhagic stroke (rs114001633, p.Pro227Leu,p-value=8.96×10-9), which further replicated in T1D. Using gene aggregate analysis with protein altering or protein truncating variants, we identified exome-wide significant genes:ANK1andLRRN1displayed replication evidence in T1D, whileLRRN1,HAS1andUACAreplicated in the general population (UK Biobank). Furthermore, we performed sliding-window analyses and identified 14 genome-wide significant windows for stroke on 4q33-34.1, of which two replicated in T1D, and a suggestive genomic window onLINC01500, which replicated in T1D. Finally, with the regulatory region aggregate analyses, we identified a stroke-associatedTRPM2-ASpromoter (p-value=5.78×10-6), which we validated with an in vitro cell-based assay.TRPM2has been previously linked to ischemic stroke.ConclusionsHere, we report the first genome-wide analysis on stroke in individuals with diabetes. We identified multiple stroke risk loci with evidence of replication: 4q33-34.1,SREBF1, andANK1for stroke in T1D; andHAS1,UACA,LRRN1,LINC01500, andTRPM2-ASpromoter for stroke potentially generalizable to the non-diabetic population.

Dyslipidemia is a major risk factor for cardiovascular disease. While common genetic variants are known to modestly affect the serum lipid concentrations, rare genetic mutations can cause monogenic forms of hypercholesteremia and other genetic disorders of lipid metabolism. Aiming to identify low-frequency protein-altering variants (PAVs) affecting lipoprotein and lipid traits, we analyzed whole-exome and whole-genome sequencing data of 481 and 573 individuals with type 1 diabetes, respectively. The phenotypic data consisted of 97 serum lipid, apolipoprotein, or other metabolic phenotypes obtained with clinical laboratory measurements and nuclear magnetic resonance (NMR) technology. Single variant analysis identified a novel association between LIPC p.Thr405Met (rs113298164) and serum apolipoprotein-A1 levels (p=7.8×10−8). In the APOB gene, we identified novel associations at two protein-truncating variants (PTVs) resulting in lower serum apolipoprotein B levels (p=5.6×10−4). The burden of PAVs was significantly associated with lipid phenotypes in LIPC, RBM47, TRMT5, and GTF3C5 (p−6). The RBM47 gene is required for apolipoprotein-B post-translational modifications, and in our data, the association between RBM47 and apolipoprotein C-III levels was led by a rare 21 base pair Ala496-Ala502 deletion; as replication, the burden of rare deleterious variants in RBM47 was associated with TG-to-HDLC ratio in WES of 20,917 individuals (p=0.0093). Two PAVs in GTF3C5 were highly Finnish-enriched and associated with cardiovascular phenotypes in external data, whereby the TRMT5 p.Ser185Cys lead variant was associated with stroke phenotypes. Altogether, we identified both novel variant associations in known lipid genes, as well as novel genes implicated in lipoprotein metabolism.

A subset of individuals with type 1 diabetes mellitus (T1DM) are predisposed to developing diabetic kidney disease (DKD), which is the most common cause globally of end-stage kidney disease (ESKD). Emerging evidence suggests epigenetic changes in DNA methylation may have a causal role in both T1DM and DKD. The aim of this investigation was to assess differences in blood-derived DNA methylation patterns between individuals with T1DM-ESKD and individuals with long-duration T1DM but no evidence of kidney disease upon repeated testing. Blood-derived DNA from individuals (107 cases, 253 controls and 14 experimental controls) were bisulphite treated before DNA methylation patterns from both groups were generated and analysed using Illumina's Infinium MethylationEPIC BeadChip arrays (n=862,927 sites). Differentially methylated CpG sites (dmCpGs) were identified (false discovery rate adjusted p≤x10-8 and fold change ±2) by comparing methylation levels between ESKD cases and T1DM controls at single site resolution. Gene annotation and functionality was investigated to enrich and rank methylated regions associated with ESKD in T1DM. Top-ranked genes within which several dmCpGs were located and supported by in silico functional data, and replication where possible, include; AFF3, ARID5B, CUX1, ELMO1, FKBP5, HDAC4, ITGAL, LY9, PIM1, RUNX3, SEPTIN9, and UPF3A. Top-ranked enrichment pathways included pathways in cancer, TGF-β signalling and Th17 cell differentiation. Epigenetic alterations provide a dynamic link between an individual's genetic background and their environmental exposures. This robust evaluation of DNA methylation in carefully phenotyped individuals, has identified biomarkers associated with ESKD, revealing several genes and implicated key pathways associated with ESKD in individuals with T1DM.