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Biomedical Data Commons (BMDC) prioritizes B-lymphocyte non-coding genetic variants in Type 1 Diabetes.

ABSTRACT: The repurposing of biomedical data is inhibited by its fragmented and multi-formatted nature that requires redundant investment of time and resources by data scientists. This is particularly true for Type 1 Diabetes (T1D), one of the most intensely studied common childhood diseases. Intense investigation of the contribution of pancreatic β-islet and T-lymphocytes in T1D has been made. However, genetic contributions from B-lymphocytes, which are known to play a role in a subset of T1D patients, remain relatively understudied. We have addressed this issue through the creation of Biomedical Data Commons (BMDC), a knowledge graph that integrates data from multiple sources into a single queryable format. This increases the speed of analysis by multiple orders of magnitude. We develop a pipeline using B-lymphocyte multi-dimensional epigenome and connectome data and deploy BMDC to assess genetic variants in the context of Type 1 Diabetes (T1D). Pipeline-identified variants are primarily common, non-coding, poorly conserved, and are of unknown clinical significance. While variants and their chromatin connectivity are cell-type specific, they are associated with well-studied disease genes in T-lymphocytes. Candidates include established variants in the HLA-DQB1 and HLA-DRB1 and IL2RA loci that have previously been demonstrated to protect against T1D in humans and mice providing validation for this method. Others are included in the well-established T1D GRS2 genetic risk scoring method. More intriguingly, other prioritized variants are completely novel and form the basis for future mechanistic and clinical validation studies The BMDC community-based platform can be expanded and repurposed to increase the accessibility, reproducibility, and productivity of biomedical information for diverse applications including the prioritization of cell type-specific disease alleles from complex phenotypes.

SUBMITTER: Piekos SN

PROVIDER: S-EPMC8483327 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:SIRT1 has been demonstrated in nutrient-sensing and insulin-signaling pathways in in vivo and in vitro experiments, but there is minimal information concerning the association between gene polymorphisms of SIRT1 and type 2 diabetes mellitus (T2DM) in a Chinese Han population. Using case-control design, we recruited 310 unrelated T2DM patients from inpatients at Shanghai Jiao Tong University Affiliated Sixth People's Hospital, while 301 healthy controls were volunteers from the community for regular medical checkup. All participants were genotyped within the SIRT1 region. The following five SNPs rs10509291, rs12778366, rs10997870, rs10823112, and rs4746720 cover 100% of common genetic variations (minor allele frequency≥0.05) within the SIRT1 gene (r2≥0.8). The genotypes of SIRT1 gene polymorphisms were analyzed by the Snapshot assay and DNA sequencing. The resulting data show that there was significant genetic differentiation in rs10823112 [p=0.003; OR (95% CI)=1.515 (1.152-1.994) for genotype], rs4746720 [p=0.024; OR (95% CI)=1.37 (1.037-1.674) for genotype], and rs10509291 [p=0.002; OR (95% CI)=1.551 (1.179-2.04) for genotype] between T2DM and control subjects. However, the result of rs4746720 was no longer significant after correction for multiple testing (p after Bonferroni correction=0.12); the results of rs10509291and rs10823112 were still significantly different between the two groups (p after Bonferroni correction=0.01 and 0.015, respectively). Linear regression analyses adjusting for age, gender, and body mass index (BMI) showed that HbA1c and HOMA-IR in subjects with rs10509291 AA genotype were higher than those with TT genotype in T2DM group (p=0.045, p=0.035, respectively). Together, our data show that genetic variation of the SIRT1 gene is related to insulin resistance and increase risk of T2DM in Chinese Han population. The risk allele A at SIRT1 rs10509291 was closely associated with T2DM, and subjects who were homozygous of the A allele were more likely to develop T2DM.

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Biomedical Data Commons (BMDC) prioritizes B-lymphocyte non-coding genetic variants in Type 1 Diabetes.

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