Common variants of SLAMF1 and ITLN1 on 1q21 are associated with type 2 diabetes in Indian population

Association of Intelectin 1 Gene rs2274907 A > T Polymorphism with Obesity, Type 2 Diabetes, Serum Intelectin-1 Levels and Lipid Profiles in Turkish Adults

The anti-inflammatory adipokine intelectin-1, which is encoded by the ITLN1 gene, is hypothesized to be linked to the pathogenesis of type 2 diabetes (T2DM) and obesity. The purpose of this study was to examine the effect of the ITLN1 gene polymorphism rs2274907 on obesity and T2DM in Turkish adults. The impact of genotype on lipid profiles and serum intelectin levels in the obese and diabetes groups was also investigated. Randomly selected 2266 adults (mean age, 55.0 ± 11.7 years; 51.2% women) participating in the population-based Turkish adult risk factor study were cross-sectionally analyzed. The genotyping of rs2274907 A > T polymorphism was performed by using the hybridization probe based LightSNiP assay in real-time PCR. T2DM were defined using the criteria of the American Diabetes Association. Obesity was described as Body mass index ≥ 30 kg/m2. Statistical analyses were used to investigate the association of genotypes with clinical and biochemical measurements. According to findings, there was no vital connection between the rs2274907 polymorphism and obesity, T2DM, or serum intelectin-1 level. The TA+AA carriers had significantly higher triglyceride levels (p = 0.007) compared with the TT carriers in both obese and T2DM women when adjusted for relevant covariates. ITLN1 rs2274907 polymorphism is not correlated with the risk of obesity and T2DM and not affect serum ITLN1 levels in Turkish adults. However, this polymorphism appears to be important in regulating triglyceride levels in obese and diabetic women.

Integrated bioinformatics analysis reveals novel key biomarkers in diabetic nephropathy

Objectives:

The underlying molecular mechanisms of diabetic nephropathy have yet not been investigated clearly. In this investigation, we aimed to identify key genes involved in the pathogenesis and prognosis of diabetic nephropathy.

Methods:

We downloaded next-generation sequencing data set GSE142025 from Gene Expression Omnibus database having 28 diabetic nephropathy samples and nine normal control samples. The differentially expressed genes between diabetic nephropathy and normal control samples were analyzed. Biological function analysis of the differentially expressed genes was enriched by Gene Ontology and REACTOME pathways. Then, we established the protein–protein interaction network, modules, miRNA-differentially expressed gene regulatory network and transcription factor-differentially expressed gene regulatory network. Hub genes were validated by using receiver operating characteristic curve analysis.

Results:

A total of 549 differentially expressed genes were detected including 275 upregulated and 274 downregulated genes. The biological process analysis of functional enrichment showed that these differentially expressed genes were mainly enriched in cell activation, integral component of plasma membrane, lipid binding, and biological oxidations. Analyzing the protein–protein interaction network, miRNA-differentially expressed gene regulatory network and transcription factor-differentially expressed gene regulatory network, we screened hub genes MDFI, LCK, BTK, IRF4, PRKCB, EGR1, JUN, FOS, ALB, and NR4A1 by the Cytoscape software. The receiver operating characteristic curve analysis confirmed that hub genes were of diagnostic value.

Conclusions:

Taken above, using integrated bioinformatics analysis, we have identified key genes and pathways in diabetic nephropathy, which could improve our understanding of the cause and underlying molecular events, and these key genes and pathways might be therapeutic targets for diabetic nephropathy.

Association between intelectin-1 variation and human kidney stone disease in northeastern Thai population

An interplay of multiple genetic and environmental factors implicates an incidence of human kidney stone disease (KSD). However, the genetic factors associated with KSD are not completely known or understood. To identify KSD-associated genetic variations among the northeastern Thai patients, a genome-wide association study (GWAS) was conducted. We initially employed genotyping of single nucleotide polymorphism (SNP) using Genome-Wide Human SNP Array 6.0 in 105 patients and in 105 normal control subjects. To overcome the limitation of small sample size, we set forth to analyze SNPs as clusters based on the concept of linkage disequilibrium (LD) and haplotype. Using this analysis, 29 genes were identified. Three candidate SNPs, including rs2039415, rs2274907, and rs3747515, were selected on the basis of haplotype analysis, potentially functional SNPs, and the functions of associated genes. Further genotyping of these SNPs in a larger sample size (altogether 216 patients and 216 control subjects) showed that the candidate SNP rs2274907 remained significantly different between case and control subjects in both genotype frequencies (OR 2.44, 95% CI 1.38-4.30; p = 0.0015) and allele frequencies (OR 1.54, 95% CI 1.17-2.03; p = 0.0021). The non-synonymous SNP rs2274907 (c.326T > A) located in exon 4 of the ITLN1 gene results in a substitution of valine (V) by aspartate (D) at position 109 (p.V109D). This substitution could affect the predicted hydrogen (H)-bonds between lysine (K) 107 and glutamine (Q) 104, which supports its association with KSD in this population.

Circulating adiponectin mediates the association between omentin gene polymorphism and cardiometabolic health in Asian Indians

BACKGROUND

Plasma omentin levels have been shown to be associated with circulating adiponectin concentrations and cardiometabolic disease-related outcomes. In this study, we aim to examine the association of omentin gene polymorphism with serum adiponectin levels and cardiometabolic health status using a genetic approach, and investigate whether these associations are modified by lifestyle factors.

METHODS

The study included 945 normal glucose tolerant and 941 unrelated individuals with type 2 diabetes randomly selected from the Chennai Urban Rural Epidemiology Study (CURES), in southern India. Study participants were classified into cardiometabolically healthy and unhealthy, where cardiometabolically healthy were those without hypertension, diabetes, and dyslipidemia. Fasting serum adiponectin levels were measured by radioimmunoassay. The omentin A326T (rs2274907) single nucleotide polymorphism (SNP) was screened by polymerase chain reaction-restriction fragment length polymorphism and direct sequencing.

RESULTS

The 'A' allele of the omentin SNP was significantly associated with lower adiponectin concentrations after adjusting for age, sex, body mass index (BMI), waist circumference (WC) and cardiometabolic health status (p = 1.90 x 10-47). There was also a significant association between circulating adiponectin concentrations and cardiometabolic health status after adjusting for age, sex, BMI, WC and Omentin SNP (p = 7.47x10-10). However, after adjusting for age, sex, BMI, WC and adiponectin levels, the association of 'A' allele with cardiometabolic health status disappeared (p = 0.79) suggesting that adiponectin serves as a mediator of the association between omentin SNP and cardiometabolic health status. There were no significant interactions between the SNP and dietary factors on adiponectin levels and cardiometabolic health status (p>0.25, for all comparisons).

CONCLUSIONS

Our findings show that adiponectin might function as a mechanistic link between omentin SNP and increased risk of cardiometabolic diseases independent of common and central obesity in Asian Indians. Before strategies to promote adiponectin modulation could be implemented, further studies are required to confirm the molecular mechanisms involved in this triangular relationship between omentin gene, adiponectin and cardiometabolic diseases.

Circulatory Omentin-1 levels but not genetic variants influence the pathophysiology of Type 2 diabetes

OBJECTIVE

Omentin-1, an anti-inflammatory protein, is secreted by the visceral adipose tissue. Altered levels of Omentin-1 are associated with obesity and Type 2 Diabetes (T2D). Although Omentin-1 is implicated in the insulin signaling pathway, the relationship between the genetic variants of Omentin-1 and T2D is not yet explored. The current study evaluates the association of Omentin-1 polymorphisms (rs2274907 A/T and rs1333062 G/T), its transcript and protein levels, and genotype-phenotype correlation with metabolic parameters and T2D susceptibility.

METHODS

Plasma and Peripheral Blood Mononuclear Cells (PBMCs) were separated from venous blood taken from 250 controls and 250 T2D patients recruited from Gujarat, India. Genomic DNA was isolated from PBMCs and genotyping of Omentin-1 variants was performed by Polymerase Chain Reaction-Restriction Fragment Length Polymorphism (PCR-RFLP). RNA was isolated from Visceral Adipose Tissue (VAT) samples of 12 controls and 10 patients, and transcript levels of Omentin-1 were assessed by qPCR. Plasma Omentin-1 levels were estimated by ELISA. Fasting Blood Glucose, Body Mass Index (BMI) and plasma lipid profile were considered for the genotype-phenotype correlation analysis.

RESULTS

Our study revealed no association of Omentin-1 genetic variants with T2D risk (p > 0.05). However, the AT genotype of Omentin-1 rs2274907 A/T polymorphism was associated with increased BMI (p = 0.0247). Plasma Omentin-1 levels were significantly decreased (p < 0.0001) however, increased VAT Omentin-1 transcript levels (p = 0.0127) were observed in T2D patients.

CONCLUSION

Our findings suggest that decreased circulatory Omentin-1 levels could pose a risk towards T2D susceptibility.

Integrative Analyses of Genes Associated with Subcutaneous Insulin Resistance

Insulin resistance is present in the majority of patients with non-insulin-dependent diabetes mellitus (NIDDM) and obesity. In this study, we aimed to investigate the key genes and potential molecular mechanism in insulin resistance. Expression profiles of the genes were extracted from the Gene Expression Omnibus (GEO) database. Pathway and Gene Ontology (GO) enrichment analyses were conducted at Enrichr. The protein–protein interaction (PPI) network was settled and analyzed using the Search Tool for the Retrieval of Interacting Genes (STRING) database constructed by Cytoscape software. Modules were extracted and identified by the PEWCC1 plugin. The microRNAs (miRNAs) and transcription factors (TFs) which control the expression of differentially expressed genes (DEGs) were analyzed using the NetworkAnalyst algorithm. A database (GSE73108) was downloaded from the GEO databases. Our results identified 873 DEGs (435 up-regulated and 438 down-regulated) genetically associated with insulin resistance. The pathways which were enriched were pathways in complement and coagulation cascades and complement activation for up-regulated DEGs, while biosynthesis of amino acids and the Notch signaling pathway were among the down-regulated DEGs. Showing GO enrichment were cardiac muscle cell–cardiac muscle cell adhesion and microvillus membrane for up-regulated DEGs and negative regulation of osteoblast differentiation and dendrites for down-regulated DEGs. Subsequently, myosin VB (MYO5B), discs, large homolog 2(DLG2), axin 2 (AXIN2), protein tyrosine kinase 7 (PTK7), Notch homolog 1 (NOTCH1), androgen receptor (AR), cyclin D1 (CCND1) and Rho family GTPase 3 (RND3) were diagnosed as the top hub genes in the up- and down-regulated PPI network and modules. In addition, GATA binding protein 6 (GATA6), ectonucleotide pyrophosphatase/phosphodiesterase 5 (ENPP5), cyclin D1 (CCND1) and tubulin, beta 2A (TUBB2A) were diagnosed as the top hub genes in the up- and down-regulated target gene–miRNA network, while tubulin, beta 2A (TUBB2A), olfactomedin-like 1 (OLFML1), prostate adrogen-regulated mucin-like protein 1 (PARM1) and aldehyde dehydrogenase 4 family, member A1 (ALDH4A1)were diagnosed as the top hub genes in the up- and down-regulated target gene–TF network. The current study based on the GEO database provides a novel understanding regarding the mechanism of insulin resistance and may provide novel therapeutic targets.

Common variants of ARID1A and KAT2B are associated with obesity in Indian adolescents

Obesity involves alterations in transcriptional programs that can change in response to genetic and environmental signals through chromatin modifications. Since chromatin modifications involve different biochemical, neurological and molecular signaling pathways related to energy homeostasis, we hypothesize that genetic variations in chromatin modifier genes can predispose to obesity. Here, we assessed the associations between 179 variants in 35 chromatin modifier genes and overweight/obesity in 1283 adolescents (830 normal weight and 453 overweight/obese). This was followed up by the replication analysis of associated signals (18 variants in 8 genes) in 2247 adolescents (1709 normal weight and 538 overweight/obese). Our study revealed significant associations of two variants rs6598860 (OR = 1.27, P = 1.58 × 10^–4) and rs4589135 (OR = 1.22, P = 3.72 × 10^–4) in ARID1A with overweight/obesity. We also identified association of rs3804562 (β = 0.11, P = 1.35 × 10^–4) in KAT2B gene with BMI. In conclusion, our study suggests a potential role of ARID1A and KAT2B genes in the development of obesity in adolescents and provides leads for further investigations.

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.

Early B-cell factor 1 (EBF1) is critical for transcriptional control of SLAMF1 gene in human B cells

Signaling lymphocytic activation molecule family member 1 (SLAMF1)/CD150 is a co-stimulatory receptor expressed on a variety of hematopoietic cells, in particular on mature lymphocytes activated by specific antigen, costimulation and cytokines. Changes in CD150 expression level have been reported in association with autoimmunity and with B-cell chronic lymphocytic leukemia. We characterized the core promoter for SLAMF1 gene in human B-cell lines and explored binding sites for a number of transcription factors involved in B cell differentiation and activation. Mutations of SP1, STAT6, IRF4, NF-kB, ELF1, TCF3, and SPI1/PU.1 sites resulted in significantly decreased promoter activity of varying magnitude, depending on the cell line tested. The most profound effect on the promoter strength was observed upon mutation of the binding site for Early B-cell factor 1 (EBF1). This mutation produced a 10-20 fold drop in promoter activity and pinpointed EBF1 as the master regulator of human SLAMF1 gene in B cells. We also identified three potent transcriptional enhancers in human SLAMF1 locus, each containing functional EBF1 binding sites. Thus, EBF1 interacts with specific binding sites located both in the promoter and in the enhancer regions of the SLAMF1 gene and is critical for its expression in human B cells.