Comprehensive functional network analysis and screening of deleterious pathogenic variants in non-syndromic hearing loss causative genes

Hearing loss (HL) is a significant public health problem and causes the most frequent congenital disability in developed societies. The genetic analysis of non-syndromic hearing loss (NSHL) may be considered as a complement to the existent plethora of diagnostic modalities available. The present study focuses on exploring more target genes with respective non-synonymous single nucleotide polymorphisms (nsSNPs) involved in the development of NSHL. The functional network analysis and variant study have successfully been carried out from the gene pool retrieved from reported research articles of the last decade. The analyses have been done through STRING. According to predicted biological processes, various variant analysis tools have successfully classified the NSHL causative genes and identified the deleterious nsSNPs, respectively. Among the predicted pathogenic nsSNPs with rsIDs rs80356586 (I515T), rs80356596 (L1011P), rs80356606 (P1987R) in OTOF have been reported in NSHL earlier. The rs121909642 (P722S), rs267606805 (P722H) in FGFR1, rs121918506 (E565A) and rs121918509 (A628T, A629T) in FGFR2 have not been reported in NSHL yet, which should be clinically experimented in NSHL. This also indicates this variant’s novelty as its association in NSHL. The findings and the analyzed data have delivered some vibrant genetic pathogenesis of NSHL. These data might be used in the diagnostic and prognostic purposes in non-syndromic congenitally deaf children.     

In Silico profiling of deleterious amino acid substitutions of potential pathological importance in haemophlia A and haemophlia B

Background

In this study, instead of current biochemical methods, the effects of deleterious amino acid substitutions in F8 and F9 gene upon protein structure and function were assayed by means of computational methods and information from the databases. Deleterious substitutions of F8 and F9 are responsible for Haemophilia A and Haemophilia B which is the most common genetic disease of coagulation disorders in blood. Yet, distinguishing deleterious variants of F8 and F9 from the massive amount of nonfunctional variants that occur within a single genome is a significant challenge.

Methods

We performed an in silico analysis of deleterious mutations and their protein structure changes in order to analyze the correlation between mutation and disease. Deleterious nsSNPs were categorized based on empirical based and support vector machine based methods to predict the impact on protein functions. Furthermore, we modeled mutant proteins and compared them with the native protein for analysis of protein structure stability.

Results

Out of 510 nsSNPs in F8, 378 nsSNPs (74%) were predicted to be ''intolerant'' by SIFT, 371 nsSNPs (73%) were predicted to be ''damaging'' by PolyPhen and 445 nsSNPs (87%) as ''less stable'' by I-Mutant2.0. In F9, 129 nsSNPs (78%) were predicted to be intolerant by SIFT, 131 nsSNPs (79%) were predicted to be damaging by PolyPhen and 150 nsSNPs (90%) as less stable by I-Mutant2.0. Overall, we found that I-Mutant which emphasizes support vector machine based method outperformed SIFT and PolyPhen in prediction of deleterious nsSNPs in both F8 and F9.

Conclusions

The models built in this work would be appropriate for predicting the deleterious amino acid substitutions and their functions in gene regulation which would be useful for further genotype-phenotype researches as well as the pharmacogenetics studies. These in silico tools, despite being helpful in providing information about the nature of mutations, may also function as a first-pass filter to determine the substitutions worth pursuing for further experimental research in other coagulation disorder causing genes.     

IL12RB2 Gene Is Associated with the Age of Type 1 Diabetes Onset in Croatian Family Trios

Background

Common complex diseases are influenced by both genetic and environmental factors. Many genetic factors overlap between various autoimmune diseases. The aim of the present study is to determine whether four genetic variants known to be risk variants for several autoimmune diseases could be associated with an increased susceptibility to type 1 diabetes mellitus.

Methods and Findings

We genotyped four genetic variants (rs2358817, rs1049550, rs6679356, rs9865818) within VTCN1, ANXA11, IL12RB2 and LPP genes respectively, in 265 T1DM family trios in Croatian population. We did not detect association of these polymorphisms with T1DM. However, quantitative transmission disequilibrium test (QTDT, orthogonal model) revealed a significant association between the age of onset of T1DM and IL12RB2 rs6679356 variant. An earlier onset of T1DM was associated with the rs6679356 minor dominant allele C (p = 0.005). The association remained significant even after the Bonferroni correction for multiple testing and permutation.

Conclusions

Variants originally associated with juvenile idiopathic arthritis (VTCN1 gene), sarcoidosis (ANXA11 gene), primary biliary cirrhosis (IL12RB2 gene) and celiac disease (LPP gene) were not associated with type 1 diabetes in our dataset. Nevertheless, association of IL12RB2 rs6679356 polymorphism with the age of T1DM onset suggests that this gene plays a role in defining the time of disease onset.     

In-Silico Computing of the Most Deleterious nsSNPs in HBA1 Gene

Background

α-Thalassemia (α-thal) is a genetic disorder caused by the substitution of single amino acid or large deletions in the HBA1 and/or HBA2 genes.

Method

Using modern bioinformatics tools as a systematic in-silico approach to predict the deleterious SNPs in the HBA1 gene and its significant pathogenic impact on the functions and structure of HBA1 protein was predicted.

Results and Discussion

A total of 389 SNPs in HBA1 were retrieved from dbSNP database, which includes: 201 non-coding synonymous (nsSNPs), 43 human active SNPs, 16 intronic SNPs, 11 mRNA 3′ UTR SNPs, 9 coding synonymous SNPs, 9 5′ UTR SNPs and other types. Structural homology-based method (PolyPhen) and sequence homology-based tool (SIFT), SNPs&Go, PROVEAN and PANTHER revealed that 2.4% of the nsSNPs are pathogenic.

Conclusions

A total of 5 nsSNPs (G60V, K17M, K17T, L92F and W15R) were predicted to be responsible for the structural and functional modifications of HBA1 protein. It is evident from the deep comprehensive in-silico analysis that, two nsSNPs such as G60Vand W15R in HBA1 are highly deleterious. These “2 pathogenic nsSNPs” can be considered for wet-lab confirmatory analysis.     

Bacterial Bile Metabolising Gene Abundance in Crohn's,Ulcerative Colitis and Type 2 Diabetes Metagenomes

We performed an analysis to determine the importance of bile acid modification genes in the gut microbiome of inflammatory bowel disease and type 2 diabetic patients. We used publicly available metagenomic datasets from the Human Microbiome Project and the MetaHIT consortium, and determined the abundance of bile salt hydrolase gene (bsh), 7 alpha-dehydroxylase gene (adh) and 7-alpha hydroxysteroid dehydrogenase gene (hsdh) in fecal bacteria in diseased populations of Crohn''s disease (CD), Ulcerative Colitis (UC) and Type 2 diabetes mellitus (T2DM). Phylum level abundance analysis showed a significant reduction in Firmicute-derived bsh in UC and T2DM patients but not in CD patients, relative to healthy controls. Reduction of adh and hsdh genes was also seen in UC and T2DM patients, while an increase was observed in the CD population as compared to healthy controls. A further analysis of the bsh genes showed significant differences in the correlations of certain Firmicutes families with disease or healthy populations. From this observation we proceeded to analyse BSH protein sequences and identified BSH proteins clusters representing the most abundant strains in our analysis of Firmicute bsh genes. The abundance of the bsh genes corresponding to one of these protein clusters was significantly reduced in all disease states relative to healthy controls. This cluster includes bsh genes derived from Lachospiraceae, Clostridiaceae, Erysipelotrichaceae and Ruminococcaceae families. This metagenomic analysis provides evidence of the importance of bile acid modifying enzymes in health and disease. It further highlights the importance of identifying gene and protein clusters, as the same gene may be associated with health or disease, depending on the strains expressing the enzyme, and differences in the enzymes themselves.     

Association of the I264T Variant in the Sulfide Quinone Reductase-Like (SQRDL) Gene with Osteoporosis in Korean Postmenopausal Women

To identify novel susceptibility variants for osteoporosis in Korean postmenopausal women, we performed a genome-wide association analysis of 1180 nonsynonymous single nucleotide polymorphisms (nsSNPs) in 405 individuals with osteoporosis and 722 normal controls of the Korean Association Resource cohort. A logistic regression analysis revealed 72 nsSNPs that showed a significant association with osteoporosis (p<0.05). The top 10 nsSNPs showing the lowest p-values (p = 5.2×10^-4–8.5×10^-3) were further studied to investigate their effects at the protein level. Based on the results of an in silico prediction of the protein’s functional effect based on amino acid alterations and a sequence conservation evaluation of the amino acid residues at the positions of the nsSNPs among orthologues, we selected one nsSNP in the SQRDL gene (rs1044032, SQRDL I264T) as a meaningful genetic variant associated with postmenopausal osteoporosis. To assess whether the SQRDL I264T variant played a functional role in the pathogenesis of osteoporosis, we examined the in vitro effect of the nsSNP on bone remodeling. Overexpression of the SQRDL I264T variant in the preosteoblast MC3T3-E1 cells significantly increased alkaline phosphatase activity, mineralization, and the mRNA expression of osteoblastogenesis markers, Runx2, Sp7, and Bglap genes, whereas the SQRDL wild type had no effect or a negative effect on osteoblast differentiation. Overexpression of the SQRDL I264T variant did not affect osteoclast differentiation of the primary-cultured monocytes. The known effects of hydrogen sulfide (H₂S) on bone remodeling may explain the findings of the current study, which demonstrated the functional role of the H₂S-catalyzing enzyme SQRDL I264T variant in osteoblast differentiation. In conclusion, the results of the statistical and experimental analyses indicate that the SQRDL I264T nsSNP may be a significant susceptibility variant for osteoporosis in Korean postmenopausal women that is involved in osteoblast differentiation.     

Prediction of the Damage-Associated Non-Synonymous Single Nucleotide Polymorphisms in the Human MC1R Gene

The melanocortin 1 receptor (MC1R) is involved in the control of melanogenesis. Polymorphisms in this gene have been associated with variation in skin and hair color and with elevated risk for the development of melanoma. Here we used 11 computational tools based on different approaches to predict the damage-associated non-synonymous single nucleotide polymorphisms (nsSNPs) in the coding region of the human MC1R gene. Among the 92 nsSNPs arranged according to the predictions 62% were classified as damaging in more than five tools. The classification was significantly correlated with the scores of two consensus programs. Alleles associated with the red hair color (RHC) phenotype and with the risk of melanoma were examined. The R variants D84E, R142H, R151C, I155T, R160W and D294H were classified as damaging by the majority of the tools while the r variants V60L, V92M and R163Q have been predicted as neutral in most of the programs The combination of the prediction tools results in 14 nsSNPs indicated as the most damaging mutations in MC1R (L48P, R67W, H70Y, P72L, S83P, R151H, S172I, L206P, T242I, G255R, P256S, C273Y, C289R and R306H); C273Y showed to be highly damaging in SIFT, Polyphen-2, MutPred, PANTHER and PROVEAN scores. The computational analysis proved capable of identifying the potentially damaging nsSNPs in MC1R, which are candidates for further laboratory studies of the functional and pharmacological significance of the alterations in the receptor and the phenotypic outcomes.     

Exploration of deleterious single nucleotide polymorphisms in late-onset Alzheimer disease susceptibility genes

Non-synonymous single nucleotide polymorphisms (nsSNPs) are considered as biomarkers to disease susceptibility. In the present study, nsSNPs in CLU, PICALM and BIN1 genes were screened for their functional impact on concerned proteins and their plausible role in Alzheimer disease (AD) susceptibility. Initially, SNPs were retrieved from dbSNP database, followed by identification of potentially deleterious nsSNPs and prediction of their effect on proteins by PolyPhen and SIFT. Protein stability and the probability of mutation occurrence were predicted using I-Mutant and PANTHER respectively. SNPs3D and FASTSNP were used for the functional analysis of nsSNPs. The functional impact on the 3D structure of proteins was evaluated by SWISSPDB viewer and NOMAD-Ref server. On analysis, 3 nsSNPs with IDs rs12800974 (T158P) of PICALM and rs11554585 (R397C) and rs11554585 (N106D) of BIN1 were predicted to be functionally significant with higher scores of I-Mutant, SIFT, PolyPhen, PANTHER, FASTSNP and SNPs3D. The mutant models of these nsSNPs also showed very high energies and RMSD values compared to their native structures. Current study proposes that the three nsSNPs identified in this study constitute a unique resource of potential genetic factors for AD susceptibility.     

A genome-wide association search for type 2 diabetes genes in African Americans

African Americans are disproportionately affected by type 2 diabetes (T2DM) yet few studies have examined T2DM using genome-wide association approaches in this ethnicity. The aim of this study was to identify genes associated with T2DM in the African American population. We performed a Genome Wide Association Study (GWAS) using the Affymetrix 6.0 array in 965 African-American cases with T2DM and end-stage renal disease (T2DM-ESRD) and 1029 population-based controls. The most significant SNPs (n = 550 independent loci) were genotyped in a replication cohort and 122 SNPs (n = 98 independent loci) were further tested through genotyping three additional validation cohorts followed by meta-analysis in all five cohorts totaling 3,132 cases and 3,317 controls. Twelve SNPs had evidence of association in the GWAS (P<0.0071), were directionally consistent in the Replication cohort and were associated with T2DM in subjects without nephropathy (P<0.05). Meta-analysis in all cases and controls revealed a single SNP reaching genome-wide significance (P<2.5×10⁻⁸). SNP rs7560163 (P = 7.0×10⁻⁹, OR (95% CI) = 0.75 (0.67–0.84)) is located intergenically between RND3 and RBM43. Four additional loci (rs7542900, rs4659485, rs2722769 and rs7107217) were associated with T2DM (P<0.05) and reached more nominal levels of significance (P<2.5×10⁻⁵) in the overall analysis and may represent novel loci that contribute to T2DM. We have identified novel T2DM-susceptibility variants in the African-American population. Notably, T2DM risk was associated with the major allele and implies an interesting genetic architecture in this population. These results suggest that multiple loci underlie T2DM susceptibility in the African-American population and that these loci are distinct from those identified in other ethnic populations.     

Association of four insulin resistance genes with type 2 diabetes mellitus and hypertension in the Chinese Han population

Insulin resistance plays an important role in the development of type 2 diabetes mellitus (T2DM) and hypertension. The purpose of the present study was to evaluate the association between four insulin resistance genes (ADIPOQ, LEPR, RETN, and TRIB3) and both T2DM and hypertension. A total of 768 Han Chinese subjects were recruited into this study, including 188 cases who had T2DM alone, 223 cases who had hypertension alone, 181 cases with both T2DM and hypertension, and 176 control subjects with neither T2DM nor hypertension. Twenty-three tag SNPs in four insulin resistance genes were genotyped and analyzed for association with T2DM and hypertension. One intron SNP (rs13306519) in LEPR and one 3′UTR SNP (rs1063537) in ADIPOQ demonstrated a significant association with T2DM (P = 0.024 and 0.014 respectively). Another intron SNP (rs12037879) in LEPR and a promoter region SNP (rs266729) in ADIPOQ were significantly associated with hypertension (P = 0.041 and 0.042, respectively). These associations survived the permutation test (P = 0.023, 0.018, 0.026, and 0.035, respectively). These associations were still found to be significant in the additive model after adjusting for potential confounding factors including age, sex, BMI, HDL, LDL, total cholesterol, and triglyceride levels (P = 0.024, 0.016, 0.04, and 0.043, respectively). No other gene variants were found to be significantly associated with T2DM or hypertension (P > 0.05). None of the studied gene variants were found to be significantly associated with T2DM+ hypertension (P > 0.05). A significant interaction was observed between two SNPs rs13306519 in LEPR and rs266729 in ADIPOQ for T2DM (P_int = 0.012, OR_int = 2.67) and hypertension (P_int = 0.0041, OR_int = 2.23). These findings suggest that variants in ADIPOQ and LEPR are risk factors for T2DM and hypertension in the Chinese population and that variants in RETN and TRIB3 are not major risk factors for these diseases.     

In Silico Analysis of Functional Single Nucleotide Polymorphisms in the Human TRIM22 Gene

Tripartite motif protein 22 (TRIM22) is an evolutionarily ancient protein that plays an integral role in the host innate immune response to viruses. The antiviral TRIM22 protein has been shown to inhibit the replication of a number of viruses, including HIV-1, hepatitis B, and influenza A. TRIM22 expression has also been associated with multiple sclerosis, cancer, and autoimmune disease. In this study, multiple in silico computational methods were used to identify non-synonymous or amino acid-changing SNPs (nsSNP) that are deleterious to TRIM22 structure and/or function. A sequence homology-based approach was adopted for screening nsSNPs in TRIM22, including six different in silico prediction algorithms and evolutionary conservation data from the ConSurf web server. In total, 14 high-risk nsSNPs were identified in TRIM22, most of which are located in a protein interaction module called the B30.2 domain. Additionally, 9 of the top high-risk nsSNPs altered the putative structure of TRIM22''s B30.2 domain, particularly in the surface-exposed v2 and v3 regions. These same regions are critical for retroviral restriction by the closely-related TRIM5α protein. A number of putative structural and functional residues, including several sites that undergo post-translational modification, were also identified in TRIM22. This study is the first extensive in silico analysis of the highly polymorphic TRIM22 gene and will be a valuable resource for future targeted mechanistic and population-based studies.     

TNF-alpha −308G/A and −238G/A polymorphisms and its protein network associated with type 2 diabetes mellitus

Several reports document the role of tumor necrosis factor alpha (TNF-α) and lipid metabolism in the context of acute inflammation as a causative factor in obesity-associated insulin resistance and as one of the causative parameter of type 2 diabetes mellitus (T2DM). Our aim was to investigate the association between −308G/A and −238G/A polymorphisms located in the promoter region of the TNF-α gene in T2DM in the Indian population with bioinformatics analysis of TNF-α protein networking with an aim to find new target sites for the treatment of T2DM. Demographics of 100 diabetes patients and 100 healthy volunteers were collected in a structured proforma and 3 ml blood samples were obtained from the study group, after approval of Institutional Ethics Committee of the hospital (IEC). The information on clinical parameters was obtained from medical records. Genomic DNA was extracted; PCR–RFLP was performed using TNF-α primers specific to detect the presence of SNPs. Various bioinformatics tools such as STRING software were used to determine its network with other associated genes. The PCR–RFLP studies showed that among the −238G/A types the GG genotype was 87%, GA genotype was 12% and AA genotype was 1%. Almost a similar pattern of results was obtained with TNF-α −308G/A polymorphism. The results obtained were evaluated statistically to determine the significance. By constructing TNF-α protein interaction network we could analyze ontology and hubness of the network to identify the networking of this gene which may influence the functioning of other genes in promoting T2DM. We could identify new targets in T2DM which may function in association with TNF-α. Through hub analysis of TNF-α protein network we have identified three novel proteins RIPK1, BIRC2 and BIRC3 which may contribute to TNF-mediated T2DM pathogenesis. In conclusion, our study indicated that some of the genotypes of TNF-α −308G/A, −238G/A were not significantly associated to type 2 diabetes mellitus, but TNF-α −308G/A polymorphism was reported to be a potent risk factor for diabetes in higher age (>45) groups. Also, the novel hub proteins may serve as new targets against TNF-α T2DM pathogenesis.     

Association of Pro12Ala Polymorphism of Peroxisome Proliferator-Activated Receptor gamma 2 (<Emphasis Type="Italic">PPARγ2</Emphasis>) Gene with Type 2 Diabetes Mellitus in Ethnic Kashmiri Population

Type 2 diabetes mellitus (T2DM) is characterized by chronic hyperglycemia associated with insulin resistance and relative insulin deficiency. T2DM is believed to be attributable to the combined effect of genetic and environmental factors. Peroxisome proliferator-activated receptor gamma 2 (PPARγ2) is one of the main candidate genes that are implicated in T2DM. A common proline 12 alanine (Pro12Ala) polymorphism in PPARγ2 has been shown to be associated with T2DM. The aim of this work was to investigate the possible role of PPARγ2 gene polymorphism, as a genetic risk factor for T2DM. The study comprised 200 ethnic unrelated subjects (100 T2DM patients and 100 controls). PCR–RFLP technique was used for genotyping analysis. The frequency of the Pro allele was 79 and 91.5 % for controls and cases, respectively (P < 0.05; OR 3.2; 95 % CI 1.64–6.3). The Pro12Ala polymorphism was in Hardy–Weinberg equilibrium in both patients and controls (χ ² = 0.13, P > 0.05). We found a significant association of Pro12Ala polymorphism of PPARγ2 gene with T2DM, however the genotypes showed statistically significant association only with few clinical parameters including body mass index, total cholesterol, and low-density lipoprotein (P < 0.05). The study signifies that Pro allele in PPARγ2 may be a genotypic risk factor that confers susceptibility to T2DM in ethnic Kashmiri population.     

Analysing the Effect of Mutation on Protein Function and Discovering Potential Inhibitors of CDK4: Molecular Modelling and Dynamics Studies

The cyclin-dependent kinase 4 (CDK4)-cyclin D1 complex plays a crucial role in the transition from the G1 phase to S phase of the cell cycle. Among the CDKs, CDK4 is one of the genes most frequently affected by somatic genetic variations that are associated with various forms of cancer. Thus, because the abnormal function of the CDK4-cyclin D1 protein complex might play a vital role in causing cancer, CDK4 can be considered a genetically validated therapeutic target. In this study, we used a systematic, integrated computational approach to identify deleterious nsSNPs and predict their effects on protein-protein (CDK4-cyclin D1) and protein-ligand (CDK4-flavopiridol) interactions. This analysis resulted in the identification of possible inhibitors of mutant CDK4 proteins that bind the conformations induced by deleterious nsSNPs. Using computational prediction methods, we identified five nsSNPs as highly deleterious: R24C, Y180H, A205T, R210P, and R246C. From molecular docking and molecular dynamic studies, we observed that these deleterious nsSNPs affected CDK4-cyclin D1 and CDK4-flavopiridol interactions. Furthermore, in a virtual screening approach, the drug 5_7_DIHYDROXY_ 2_ (3_4_5_TRI HYDROXYPHENYL) _4H_CHROMEN_ 4_ONE displayed good binding affinity for proteins with the mutations R24C or R246C, the drug diosmin displayed good binding affinity for the protein with the mutation Y180H, and the drug rutin displayed good binding affinity for proteins with the mutations A205T and R210P. Overall, this computational investigation of the CDK4 gene highlights the link between genetic variation and biological phenomena in human cancer and aids in the discovery of molecularly targeted therapies for personalized treatment.     

Comprehensive in-silico analysis of deleterious SNPs in APOC2 and APOA5 and their differential expression in cancer and cardiovascular diseases conditions

Genetic variations in APOC2 and APOA5 genes involve activating lipoprotein lipase (LPL), responsible for the hydrolysis of triglycerides (TG) in blood and whose impaired functions affect the TG metabolism and are associated with metabolic diseases. In this study, we investigate the biological significance of genetic variations at the DNA sequence and structural level using various computational tools. Subsequently, 8 (APOC2) and 17 (APOA5) non-synonymous SNPs (nsSNPs) were identified as high-confidence deleterious SNPs based on the effects of the mutations on protein conservation, stability, and solvent accessibility. Furthermore, based on our docking results, the interaction of native and mutant forms of the corresponding proteins with LPL depicts differences in root mean square deviation (RMSD), and binding affinities suggest that these mutations may affect their function. Furthermore, in vivo, and in vitro studies have shown that differential expression of these genes in disease conditions due to the influence of nsSNPs abundance may be associated with promoting the development of cancer and cardiovascular diseases. Preliminary screening using computational methods can be a helpful start in understanding the effects of mutations in APOC2 and APOA5 on lipid metabolism; however, further wet-lab experiments would further strengthen the conclusions drawn from the computational study.     

ACACβ gene (rs2268388) and AGTR1 gene (rs5186) polymorphism and the risk of nephropathy in Asian Indian patients with type 2 diabetes

Patients with type 2 diabetes (T2DM) are usually obese and concurrent obesity results into activation of the renin–angiotensin-system (RAS) which is a risk factor for diabetic nephropathy (DN). Gene–gene interaction between acetyl-coenzymeA carboxylase beta (ACACβ) gene, which is involved in fatty acid metabolism and angiotensin II receptors (AGTR1) gene, which mediates RAS proteins actions on renal tissue, polymorphism with DN have not been studied earlier. The present study was designed with the aim to examine the association of an ACACβ (rs2268388) and AGTR1 (rs5186) gene polymorphism with the risk of DN in Asian Indians. 1,158 patients with T2DM belonging to two independently ascertained North Indian and one South Indian cohorts were genotyped for ACACβ (rs2268388) and AGTR1 (rs5186) polymorphism using real time PCR-based Taq-man assay and PCR–RFLP assays. In all the three cohorts, a significantly higher frequency of T allele and TT genotypes of ACACβ and C allele and CC genotypes of AGTR1 were found in patients with DN as compared to patients without nephropathy. Further, T allele of ACACβ and C allele of AGTR1 were found to be significantly associated with proteinuria, a hallmark of DN. We also found significant epistatic interactions between these two genes. TT genotypes of ACACβ gene and CC genotype of AGTR1 gene confers the risk of DN and both genes had significant epistatic interaction in Asian Indian patients with T2DM.     

Independent case-control study in KCNJ11 gene polymorphism with Type 2 diabetes Mellitus

BackgroundType 2 Diabetes Mellitus (T2DM) is the most common form of diabetes in the aging population. This chronic metabolic disorder has discovered many candidate genes, and KCNJ11 was one of the genes associated with insulin secretion pathways mediated by potassium channels. There have been limited studies on the rs5210 polymorphism in T2DM patients, and none of them have been conducted in Saudi Arabia.AimThe aim of this study is to investigate at genotyping levels of rs5210 polymorphism in the KCNJ11 gene in older population with T2DM in the Saudi Population.MethodsBased on the sample size design, this case-control study included 102 T2DM cases and 102 controls. Using the PCR-RFLP assay, 204 patients extracted DNA was genotyped for the rs5210 polymorphism. SPSS software was used for statistical analysis, including t-tests, HWE, genotyping, and multiple logistic regression analysis.ResultsThe t-tests performed on T2DM cases and controls revealed a significant association in age, weight, BMI, FBG, Hb1Ac, SBP, DBP, HDLC, TC, and TG parameters (p < 0.05). HWE analysis found to be in consistent with rs5210 polymorphism. Allelic association was found in the rs5210 polymorphism (OR-1.64 [95 %CI: 1.08–2.49]; p = 0.01); however, no association (p > 0.05) was observed in the multivariate logistic regression assessment performed in this study.ConclusionThese results indicate that the rs5210 polymorphism was primarily associated with allele frequencies, which could be attributable to the small sample size. Large sample size studies will be required to determine whether KCNJ11 gene polymorphisms may be required as a risk marker for T2DM in the Saudi population.