Genome wide association study of uric acid in Indian population and interaction of identified variants with type 2 diabetes

Abnormal level of Serum Uric Acid (SUA) is an important marker and risk factor for complex diseases including Type 2 diabetes. Since genetic determinant of uric acid in Indians is totally unexplored, we tried to identify common variants associated with SUA in Indians using Genome Wide Association Study (GWAS). Association of five known variants in SLC2A9 and SLC22A11 genes with SUA level in 4,834 normoglycemics (1,109 in discovery and 3,725 in validation phase) was revealed with different effect size in Indians compared to other major ethnic population of the world. Combined analysis of 1,077 T2DM subjects (772 in discovery and 305 in validation phase) and normoglycemics revealed additional GWAS signal in ABCG2 gene. Differences in effect sizes of ABCG2 and SLC2A9 gene variants were observed between normoglycemics and T2DM patients. We identified two novel variants near long non-coding RNA genes AL356739.1 and AC064865.1 with nearly genome wide significance level. Meta-analysis and in silico replication in 11,745 individuals from AUSTWIN consortium improved association for rs12206002 in AL356739.1 gene to sub-genome wide association level. Our results extends association of SLC2A9, SLC22A11 and ABCG2 genes with SUA level in Indians and enrich the assemblages of evidence for SUA level and T2DM interrelationship

Common variants in CLDN2 and MORC4 genes confer disease susceptibility in patients with chronic pancreatitis

A recent Genome-wide Association Study (GWAS) identified association with variants in X-linked CLDN2 and MORC4 and PRSS1-PRSS2 loci with Chronic Pancreatitis (CP) in North American patients of European ancestry. We selected 9 variants from the reported GWAS and replicated the association with CP in Indian patients by genotyping 1807 unrelated Indians of Indo-European ethnicity, including 519 patients with CP and 1288 controls. The etiology of CP was idiopathic in 83.62% and alcoholic in 16.38% of 519 patients. Our study confirmed a significant association of 2 variants in CLDN2 gene (rs4409525—OR 1.71, P = 1.38 x 10-09; rs12008279—OR 1.56, P = 1.53 x 10-04) and 2 variants in MORC4 gene (rs12688220—OR 1.72, P = 9.20 x 10-09; rs6622126—OR 1.75, P = 4.04x10-05) in Indian patients with CP. We also found significant association at PRSS1-PRSS2 locus (OR 0.60; P = 9.92 x 10-06) and SAMD12-TNFRSF11B (OR 0.49, 95% CI [0.31–0.78], P = 0.0027). A variant in the gene MORC4 (rs12688220) showed significant interaction with alcohol (OR for homozygous and heterozygous risk allele -14.62 and 1.51 respectively, P = 0.0068) suggesting gene-environment interaction. A combined analysis of the genes CLDN2 and MORC4 based on an effective risk allele score revealed a higher percentage of individuals homozygous for the risk allele in CP cases with 5.09 fold enhanced risk in individuals with 7 or more effective risk alleles compared with individuals with 3 or less risk alleles (P = 1.88 x 10-14). Genetic variants in CLDN2 and MORC4 genes were associated with CP in Indian patients

DNA methylation profiling reveals the presence of population-specific signatures correlating with phenotypic characteristics

Phenotypic characteristics are known to vary substantially among different ethnicities around the globe. These variations are mediated by number of stochastic events and cannot be attributed to genetic architecture alone. DNA methylation is a well-established mechanism that sculpts our epigenome influencing phenotypic variation including disease manifestation. Since DNA methylation is an important determinant for health issues of a population, it demands a thorough investigation of the natural differences in genome wide DNA methylation patterns across different ethnic groups. This study is based on comparative analyses of methylome from five different ethnicities with major focus on Indian subjects. The current study uses hierarchical clustering approaches, principal component analysis and locus specific differential methylation analysis on Illumina 450K methylation data to compare methylome of different ethnic subjects. Our data indicates that the variations in DNA methylation patterns of Indians are less among themselves compared to other global population. It empirically correlated with dietary, cultural and demographical divergences across different ethnic groups. Our work further suggests that Indians included in this study, despite their genetic similarity with the Caucasian population, are in close proximity with Japanese in terms of their methylation signatures