Telomere length attrition has been implicated in various complex disorders including Type 2 Diabetes (T2D). However, very few candidate gene association studies have been carried out worldwide targeting telomere maintenance genes. in the present study, variants in various critical telomere maintenance pathway genes for T2D susceptibility in Northwest Indian population were explored. With case-control candidate gene association study design, twelve variants from seven telomere maintenance genes were evaluated. Amongst these five variants, rs9419958 (OBFC1), rs4783704 (TERF2), rs16847897 (TERC/ LRRC31), rs10936599 (TERC/MYNN), and rs74019828 (CSNK2A2) showed significant association with T2D (at p-value ≤ 0.003, threshold set after Bonferroni correction) in the studied population. In silico analyses of these variants indicated interesting functional roles that warrant experimental validations. Findings showed that variants in telomere maintenance genes are associated with pathogenesis of T2D in Northwest Indian population. We anticipate further, such candidate gene association studies in other Indian populations and worldwide would contribute in understanding the missing heritability of T2D.
Background Telomere genetics has recently been emerged as an important field in molecular oncology. Various genome-wide association studies in different population groups have revealed that polymorphisms in Telomere maintenance gene ( TERT ) gene located on 5p15.33 is associated with susceptibility to leukemia and lung cancer risk. However, association of TERT with leukemia and lung cancer risk in north Indian population groups is still unknown. This study observed the association between genetic variant rs2853677 of TERT and leukemia and lung cancer in the state of Jammu and Kashmir, India. Methods A total of 781 subjects, out of which 381 cases (203 leukemic patients and 178 non-small cell lung cancer patients NSCLC) and 400 healthy controls were recruited for the study. Genetic variant rs2853677of TERT was detected using the real-time and Taqman Chemistry. Hardy-Weinberg Equilibrium was assessed using the chi square test. The allele and genotype- specific risks were estimated as odds ratio with 95% confidence interval. Results We observed that variant rs2853677 was strongly associated with lung cancer and leukemia risk with an odds ratio (OR) =1.8 (1.03–3.2 at 95% CI); p value (adjusted) = 0.03; odds ratio (OR) =2.9 (1.4–5.5.at 95% CI); p value (adjusted) = 0.002, respectively. Conclusion The results of this study suggested that rs2853677 of TERT signifies association in multiple cancers and suggests that it can become potential marker for diagnosis of non-small cell lung cancer and leukemia. The study will provide an insight in understanding the genetic etiology and highlights the role of telomere-associated pathways in non-small cell lung cancer and leukemia. However, it would be quite interesting to explore the contribution of this variant in other cancers as well. Electronic supplementary material The online version of this article (10.1186/s12885-019-5685-2) contains supplementary material, which is available to authorized users.
Bioinformatics is an amalgamation of biology, mathematics and computer science. It is a science which gathers the information from biology in terms of molecules and applies the informatic techniques to the gathered information for understanding and organizing the data in a useful manner. With the help of bioinformatics, the experimental data generated is stored in several databases available online like nucleotide database, protein databases, GENBANK and others. The data stored in these databases is used as reference for experimental evaluation and validation. Till now several online tools have been developed to analyze the genomic, transcriptomic, proteomics, epigenomics and metabolomics data. Some of them include Human Splicing Finder (HSF), Exonic Splicing Enhancer Mutation taster, and others. A number of SNPs are observed in the non-coding, intronic regions and play a role in the regulation of genes, which may or may not directly impose an effect on the protein expression. Many mutations are thought to influence the splicing mechanism by affecting the existing splice sites or creating a new sites. To predict the effect of mutation (SNP) on splicing mechanism/signal, HSF was developed. Thus, the tool is helpful in predicting the effect of mutations on splicing signals and can provide data even for better understanding of the intronic mutations that can be further validated experimentally. Additionally, rapid advancement in proteomics have steered researchers to organize the study of protein structure, function, relationships, and dynamics in space and time. Thus the effective integration of all of these technological interventions will eventually lead to steering up of next-generation systems biology, which will provide valuable biological insights in the field of research, diagnostic, therapeutic and development of personalized medicine.
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