An Integrative Phenotype–Genotype Approach Using Phenotypic Characteristics from the UAE National Diabetes Study Identifies HSD17B12 as a Candidate Gene for Obesity and Type 2 Diabetes

Abstract

The United Arab Emirates National Diabetes and Lifestyle Study (UAEDIAB) has identified obesity, hypertension, obstructive sleep apnea, and dyslipidemia as common phenotypic characteristics correlated with diabetes mellitus status. As these phenotypes are usually linked with genetic variants, we hypothesized that these phenotypes share single nucleotide polymorphism (SNP)-clusters that can be used to identify causal genes for diabetes. We explored the National Human Genome Research Institute-European Bioinformatics Institute Catalog of Published Genome-Wide Association Studies (NHGRI-EBI GWAS) to list SNPs with documented association with the UAEDIAB-phenotypes as well as diabetes. The shared chromosomal regions affected by SNPs were identified, intersected, and searched for Enriched Ontology Clustering. The potential SNP-clusters were validated using targeted DNA next-generation sequencing (NGS) in two Emirati diabetic patients. RNA sequencing from human pancreatic islets was used to study the expression of identified genes in diabetic and non-diabetic donors. Eight chromosomal regions containing 46 SNPs were identified in at least four out of the five UAEDIAB-phenotypes. A list of 34 genes was shown to be affected by those SNPs. Targeted NGS from two Emirati patients confirmed that the identified genes have similar SNP-clusters. ASAH1, LRP4, FES, and HSD17B12 genes showed the highest SNPs rate among the identified genes. RNA-seq analysis revealed high expression levels of HSD17B12 in human islets and to be upregulated in type 2 diabetes (T2D) donors. Our integrative phenotype-genotype approach is a novel, simple, and powerful tool to identify clinically relevant potential biomarkers in diabetes. HSD17B12 is a novel candidate gene for pancreatic β-cell function.

Derangement of cell cycle markers in peripheral blood mononuclear cells of asthmatic patients as a reliable biomarker for asthma control

“…The integrative phenotype–genotype approach is a novel, simple, and powerful tool to identify clinically relevant potential biomarkers. We recently used this approach to identify clinically essential biomarkers in complex and heterogeneous diseases like diabetes 7 .…”

Chromosomal regions strongly associated with waist circumference and body mass index in metabolic syndrome in a family-based study

“…In summary, the obtained results suggest that regions 8q22-24, 11q23-25, and 12q13-15 are very likely to contain genes like VPS13B, APOA5, ZPR1, BUD13, and FAIM2 that control obesity-related factors in Iranian families with MetS 21,22,27,28,31,32 . A more refined analysis with high-density short tandem repeat (STR) markers in the regions of interest around the marker with the most robust evidence for linkage and association, which possibly focuses on very informative families identified in this study, is needed to pave the way to identify responsible genes.…”

“…The genome-wide analysis has recently identified genetic variants in association with waist circumference (WC) and BMI 13 , 14 . These studies found some chromosomal regions such as 8(q22.1-q24.3) containing VPS13B gene 15 – 22 , 11(q23.3-q25) containing APOA5, ZPR1, and BUD13 genes 23 – 28 , 12(q13.12-q15) containing FAIM2 gene 18 , 29 – 32 , and 16(q23.3-q24.3) containing MAF gene 31 – 33 with high LOD scores concerning BMI and WC (Table 1 ). Even some genetic variations were reported concerning MetS in the Japanese population 34 .…”

Cellular exocytosis gene (EXOC6/6B): a potential molecular link for the susceptibility and mortality of COVID-19 in diabetic patients

“…The details of the study design and sampling of the UAEDIAB study are described elsewhere [15]. The study was approved by the Ethics Committee of Sharjah University and the Ministry of…”

“…Four Emirati diabetic patients (age 60 ± 1, HbA1c >10.5%), fasting blood glucose values >13 mmol/L, BMI >40 and weight 120 ± 3 kgs) were subjected for targeted DNA next-generation sequencing using the S5 semi-conductor based DNA sequencer as described previously [26] [17].…”