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      Determination of individual type 2 diabetes risk profile in the North East Indian population & its association with anthropometric parameters

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          Abstract

          Background & objectives:

          Diabetes genomics research has illuminated single nucleotide polymorphism (SNP) in several genes including, fat mass and obesity associated ( FTO) (rs9939609 and rs9926289), potassium voltage-gated channel subfamily J member 11 (rs5219), SLC30A8 (rs13266634) and peroxisome proliferator-activated receptor gamma 2 (rs1805192). The present study was conducted to investigate the involvement of these polymorphisms in conferring susceptibility to type 2 diabetes (T2D) in the North East Indian population, and also to establish their association with anthropometric parameters.

          Methods:

          DNA was extracted from blood samples of 155 patients with T2D and 100 controls. Genotyping was performed by polymerase chain reaction-restriction fragment length polymorphism and DNA sequencing. To confirm the association between the inheritance of SNP and T2D development, logistic regression analysis was performed.

          Results:

          For the rs9939609 variant (FTO), the dominant model AA/(AT+TT) revealed significant association with T2D [odds ratio (OR)=2.03, P=0.021], but was non-significant post correction for multiple testing ( P=0.002). For the rs13266634 variant ( SLC30A8), there was considerable but non-significant difference in the distribution pattern of genotypic polymorphisms between the patients and the controls ( P=0.004). Significant association was observed in case of the recessive model (CC+CT)/TT (OR=4.56 P=0.001), after adjusting for age, gender and body mass index. In addition, a significant association ( P=0.001) of low-density lipoprotein (mg/dl) could be established with the FTO (rs9926289) polymorphism assuming dominant model.

          Interpretation & conclusions:

          The current study demonstrated a modest but significant effect of SLC30A8 (rs13266634) polymorphisms on T2D predisposition. Considering the burgeoning prevalence of T2D in the Indian population, the contribution of these genetic variants studied, to the ever-increasing number of T2D cases, appears to be relatively low. This study may serve as a foundation for performing future genome-wide association studies (GWAS) involving larger populations.

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          Molecular Cloning: A Laboratory Manual

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            Common Variation in the Fat Mass and Obesity-Associated (FTO) Gene Confers Risk of Obesity and Modulates BMI in the Chinese Population

            OBJECTIVE— Genetic variants in the fat mass and obesity-associated (FTO) gene have been linked with obesity and type 2 diabetes in European populations. We aimed to test the role of FTO genetic variants in obesity and type 2 diabetes in the Chinese population. RESEARCH DESIGN AND METHODS— We genotyped 19 single-nucleotide polymorphisms (SNPs) spanning from the 3′ end of the neighboring RPGRIP1L gene to the 5′ flanking region of the FTO gene. We analyzed their associations with obesity (638 case and 1,610 control subjects), type 2 diabetes (759 case and 784 control subjects), and obesity-related traits in nondiabetic subjects. RESULTS— Among the 19 SNPs, the rs9939609 A allele was strongly associated with obesity (P = 7.0 × 10−4) and BMI (P = 0.0024) in the Chinese population. The odds ratio for obesity was 2.60 (95% CI 1.24–5.46) (P = 0.011) for the AA genotype and 1.32 (1.05–1.66) (P = 0.018) for the AT genotype compared with the TT genotype. Each additional copy of the rs9936609 A allele was associated with a BMI increase of ∼0.37 kg/m2. The rs9939609 A allele was substantially less common in the Chinese population than in the European population (12.6 vs. 45%). We did not find significant associations of the 19 SNPs with type 2 diabetes or other obesity-related traits. CONCLUSIONS— Genetic variation in the FTO gene is strongly associated with obesity and BMI in the Chinese population. The risk variant is less common in the Chinese population, but its effect size on BMI is comparable with that in the European population.
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              Genome-Wide Association Study Identifies a Novel Locus Contributing to Type 2 Diabetes Susceptibility in Sikhs of Punjabi Origin From India

              We performed a genome-wide association study (GWAS) and a multistage meta-analysis of type 2 diabetes (T2D) in Punjabi Sikhs from India. Our discovery GWAS in 1,616 individuals (842 case subjects) was followed by in silico replication of the top 513 independent single nucleotide polymorphisms (SNPs) (P < 10−3) in Punjabi Sikhs (n = 2,819; 801 case subjects). We further replicated 66 SNPs (P < 10−4) through genotyping in a Punjabi Sikh sample (n = 2,894; 1,711 case subjects). On combined meta-analysis in Sikh populations (n = 7,329; 3,354 case subjects), we identified a novel locus in association with T2D at 13q12 represented by a directly genotyped intronic SNP (rs9552911, P = 1.82 × 10−8) in the SGCG gene. Next, we undertook in silico replication (stage 2b) of the top 513 signals (P < 10−3) in 29,157 non-Sikh South Asians (10,971 case subjects) and de novo genotyping of up to 31 top signals (P < 10−4) in 10,817 South Asians (5,157 case subjects) (stage 3b). In combined South Asian meta-analysis, we observed six suggestive associations (P < 10−5 to < 10−7), including SNPs at HMG1L1/CTCFL, PLXNA4, SCAP, and chr5p11. Further evaluation of 31 top SNPs in 33,707 East Asians (16,746 case subjects) (stage 3c) and 47,117 Europeans (8,130 case subjects) (stage 3d), and joint meta-analysis of 128,127 individuals (44,358 case subjects) from 27 multiethnic studies, did not reveal any additional loci nor was there any evidence of replication for the new variant. Our findings provide new evidence on the presence of a population-specific signal in relation to T2D, which may provide additional insights into T2D pathogenesis.
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                Author and article information

                Journal
                Indian J Med Res
                Indian J. Med. Res
                IJMR
                The Indian Journal of Medical Research
                Wolters Kluwer - Medknow (India )
                0971-5916
                October 2019
                : 150
                : 4
                : 390-398
                Affiliations
                [1 ] Department of Bioengineering & Technology, Gauhati University, Guwahati, Assam, India
                [2 ] Department of Statistics, Gauhati University, Guwahati, Assam, India
                [3 ] Department of Endocrinology, Excelcare Hospitals, Guwahati, Assam, India
                [4 ] Department of Genetics & Molecular Medicine, Kamineni Academy of Medical Sciences & Research Center, Hyderabad, Telangana, India
                Author notes
                For correspondence: Dr Sofia Banu, Department of Bioengineering & Technology, Gauhati University, Guwahati 781 014, Assam, India e-mail: sofiabanu2@ 123456gmail.com
                [†]

                Equal contribution

                Article
                IJMR-150-390
                10.4103/ijmr.IJMR_888_17
                6902361
                31823921
                544d4506-e1e5-4d80-8172-9b1d8cdad6c3
                Copyright: © 2019 Indian Journal of Medical Research

                This is an open access journal, and articles are distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 License, which allows others to remix, tweak, and build upon the work non-commercially, as long as appropriate credit is given and the new creations are licensed under the identical terms.

                History
                : 31 May 2017
                Categories
                Original Article

                Medicine
                body mass index,hba1c,hyperglycaemia,obesity,polymorphism,type 2 diabetes
                Medicine
                body mass index, hba1c, hyperglycaemia, obesity, polymorphism, type 2 diabetes

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