Literature DB >> 32296102

Telomere Maintenance Genes are associated with Type 2 Diabetes Susceptibility in Northwest Indian Population Group.

Itty Sethi1, Varun Sharma1, Indu Sharma1, Gurvinder Singh2, Gh Rasool Bhat1, A J S Bhanwer2, Swarkar Sharma3, Ekta Rai4.   

Abstract

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.

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Year:  2020        PMID: 32296102      PMCID: PMC7160122          DOI: 10.1038/s41598-020-63510-w

Source DB:  PubMed          Journal:  Sci Rep        ISSN: 2045-2322            Impact factor:   4.379


Introduction

Type 2 Diabetes (T2D) is a common progressive metabolic complex disorder, affecting 77 million individuals in India only[1]. Substantial evidences suggest that genetic factors strongly influence the risk of T2D[2-5] and efforts are made worldwide in understanding these factors. An early endeavour to identify the genetic variants and loci was centred on candidate genes, often associated with insulin pathways[6]. Recent large scale Genome wide association studies (GWAS) over the past decade, have indicated ~144 genetic variants associated with T2D worldwide[7]. GWAS captured majority of the common alleles but yet all these together explain only ~20% heritability of the disease[3]. An extensive effort is warranted for the identification of other variants and genetic loci that are contributing in the disease etiology[3,8,9]. We believe answer to the major missing heritability components of the T2D lies in genetic heterogeneity and is dependent on diverse populations yet to be evaluated extensively. Further, it is important to overlap pathway based candidate gene study approach with GWAS to bring out signals that might have been masked due to stringent criteria in GWAS. Telomere attrition pathway has been associated with many complex disorders including T2D[10,11]. Various functional studies have implicated telomere attrition in insulin resistance, impaired glucose tolerance, obesity, inflammation[12] as well as it has been found as an independent risk factor for T2D[13,14]. In fact, T2D and telomere attrition share common environmental risk factors including stress, less physical activity, and sedentary life style[15]. The telomere length is regulated and maintained by protein complexes (reviewed in Sethi et al., 2016)[15]. Few studies have indicated that the genes involved in the regulation of telomere length might also have implication in the telomere length attrition in T2D individuals[16-20]. However, such studies are limited in number. This makes the study of genes involved in telomere attrition important candidates for evaluation of their role in T2D susceptibility. In addition, India is a pivot of ethnicities and a foremost contributor to the world population with ample diversity yet least explored of all region especially lacking GWAS data for most of these population groups. Thus, exploring the association of telomere maintenance genes in Indian population for T2D susceptibility is anticipated to contribute extensively in knowledge of T2D susceptibility, especially with respect to telomere biology. With this background, the first case-control association study was performed to explore the role of telomere maintenance genes in the development of T2D in the North-west Indian population. Keeping account of potential functional implication of genes involved in telomere maintenance and regulation (reviewed in Sethi et al.)[15] variants were selected in some of the genes from shelterin, CST (CTC1, STN1 and TEN1) and telomerase complex. The selected genes and their variant were Telomerase RNA component (TERC) – rs16847897, rs10936599, rs10936601, Telomerase Reverse Transcriptase (TERT) – rs2736100, Casein Kinase 2 subunit alpha 2 (CSNK2A2) – rs74019828, Telomeric Repeat Binding Factor 2 (TERF2) – rs4783704, Telomerase Associated Protein 1 (TEP1) – rs3093872, rs4982038, rs3093921, Telomeric Repeat Binding Factor 1 (TERF1) – rs2010441, rs6982126 and Oligonucleotide/Oligosaccharide-Binding Fold-Containing Protein 1 (OBFC1) – rs9419958 (Supplementary Table S1).

Result and Discussion

A total of 1354 individuals (682 cases and 672 healthy controls) from Northwest Indian population were evaluated in the study. The epidemiological and clinical parameters were described in Table 1. The population enrolled in this study was genotyped for 12 Variants from 7 telomere maintenance genes including OBFC1 (rs9419958), TERF2 (rs4783704), CSNK2A2 (rs74019828), TEP1 (rs3093872, rs4982038, rs3093921), TERT (rs2736100), TERC (rs16847897, rs10936599, rs10936601) and TERF1 (rs2010441, rs6982126) described as in Supplementary Table S1. After performing the quality control (QC) analysis[21,22], the final data set remains with the 6 variants that pass the QC analyses and lie in HWE. Those variants were selected whose call rate was >90%. Randomly selected samples were also re-genotyped to check the precision of genotyping and showed no discrepancy. The variants which deviated from the HWE were also removed from the analyses part. The samples then further tested for association with T2D. Among the 6 variants, 5 variants were found to be significantly associated with T2D (Table 2). The associated variants were not found to be correlated with the age (Supplementary Table S2). The clinical characteristics of genotypes for each variant were compared and no variant has obvious effect on the clinical characteristics associated with T2D. The risk allele (C) of rs4783704 showed a p-value of 0.03 with low BMI that did not hold significance statistically after Bonferroni corrections (Supplementary Table S3). Yet it is interesting, as the number of males is more (n = 774) than females (n = 580) in the total population and literature has indicated that males develop T2D with lower BMI than females in early stages of life[23]. Therefore, it is an interesting perspective that needs further exploration in much larger sample size and in other Indian population groups. Genetic variations may influence the gene regulations by modifying the epigenome, transcription factor binding sites, and splicing factor binding sites[7,24,25]. The possible functional role of the variants in tissues that are chiefly involved in sugar metabolism that is, pancreas, pancreatic islets, adipose-subcutaneous tissue and muscle cells using databases GTEx v.7, UCSC, Haploreg v4.1, HSF (v.3.1) and ESE v.3[26-28] was investigated. Result for each of the associated variant has been described separately below and summarized in Tables 2 and 3.
Table 1

Distribution of epidemiological parameters between Type 2 Diabetes patients and Healthy Controls populations from North India.

S.No.CharacteristicCases*Controlsp-value
1.Age58.1 ± 8.0258.58 ± 10.870.35
2.Gender - Male444 (65.1%)330 (49.1%)
Gender - Female238 (34.9%)342 (50.9%)
3.BMI-kg/m226.4 ± 4.3925.45 ± 4.019E-04
4.Systolic Blood Pressure (SBP)-mmHg135.07 ± 17.15127.88 ± 14.327.22E-11
5.Diastolic Blood Pressure (DBP)-mmHg86.64 ± 10.4582.68 ± 7.521.86E-10
6.Blood Glucose (Post Prandial)-mg/dl216.56 ± 68.66120.32 ± 20.831.2E-107
7.Triglycerides256.98 ± 173.99178.72 ± 109.24.84E-15
8.High Density Lipoproteins (HDL)49.92 ± 28.0448.12 ± 21.90.3
9.Very Low Density Lipoprotein (VLDL)51.39 ± 34.7935.98 ± 22.181.73E-14
10.Cholesterol170.89 ± 50.44163.68 ± 47.920.04

*Other clinical conditions removed.

Table 2

Allelic Distribution. Logistic regression analysis of significant variants of genes in our study, adjusted for age, gender and BMI.

VARIANTrs9419958rs4783704rs16847897rs10936599rs74019828
NEAREST GENE (VARIANT)OBFC1TERF2TERCTERCCSNK2A2
POLYMORPHISM (ref/alt-GRCh38/hg38)T/CC/TG/CC/TG/A
ANCESTRAL ALLELETCCCG
ALLELE DISTRIBUTIONTCCTGTCAG
CASES (n = 682)0.040.960.130.870.430.570.160.840.070.93
CONTROLS (n = 672)0.070.930.160.840.380.620.270.730.150.85
ALLELIC ODDS RATIO (95% CI)1.98 (1.38–2.85)1.32 (1.06–1.65)1.23 (1.05–1.44)1.76 (1.46–2.12)2.10 (1.63–2.72)
RISK ALLELECCCCG
GENOTYPIC MODELRecessive (CC vs TT + CT)Recessive CC vs TT + CT)Dominant (CC + GC vs GG)Recessive (CC vs TT + CT)Recessive (GG vs AA + GA)
p-VALUE*5.8E-50.0012.4E-91.63E-126.57E-9
ODDS RATIO (95% CI)2.30 (1.53–3.46)1.52 (1.17–1.97)2.23 (1.71–2.90)2.44 (1.90–3.12)2.37 (1.77–3.18)

*Adjusted for Age, Gender, and BMI.

Table 3

Putative Role of the associated variants with T2D in studied population (North-west India) utilizing the information from the various databases including GTEX, UCSC genome browser and HSF.

VariantLocation of the variant w.r.t nearest geneAllele Ref/Alt (Risk allele)*eQTL geneeQTL TissueeQTL sample sizeeQTL NESeQTL p-valueeQTL m-valuePutative role (cis- eQTL) of variantRegulatory role of variant (ENCODE and Haploreg data)Splicing effect[28,46]
rs94199581st intron variant of OBFC1/STN1T/C (C)OBFC1/STN1Pancreas2200.2211.9E-31Significant and Up regulationH3K27ac_Enh/H3K4me3_Pro / H3K4me1_Enh/ H3K9ac_Pro/7_Enh/4_PromD2/TSSA/9_TxresgCreation of ESE intronic site/ SF2/ASF (IgM-BRCA1)-91.23
Adipose-subcutaneous3850.2261.1E-41Significant and Up regulationH3K27ac_Enh/H3K4me3_Pro / H3K4me1_Enh/ H3K9ac_Pro/TSSAFlnk/3_PromD1
Skeletal Muscle4910.00570.90Non-SignificantH3K27ac_Enh/H3K4me3_Pro / H3K4me1_Enh/ H3K9ac_Pro/TSSAFlnk/3_PromD1
rs4783704intergenic variant of TERF2 and CYB5BC/T (C)N/APancreasN/AN/AN/AN/AN/A22_PromPCreation of ESE intronic site/ Creation of new site for SRp55–86.86 and 9G8–60.67
Adipose-subcutaneousH3K27ac_Enh/ H3K4me1_Enh/14_EnhA2
Skeletal MuscleH3K27ac_Enh/ H3K9ac_Pro/16_EnhW1
Transcription factors binding sites including TCF7L2, TCF12; DNase hypersensitive #
rs16847897upstream to TERC; 7th intron variant of LRRC31G/C (C)LRRC34Pancreas220−0.1690.10.924Non-SignificantNo Role w.r.t studied tissuesCreation of binding site for SF2/ASF (IgM-BRCA1)-75.85 and SRp55 site broken-100
Adipose-subcutaneous385−0.2083.7E-51Significant and Down regulation
Skeletal Muscle491−0.1390.030.965Significant and Down regulation
rs10936599upstream to TERC; exon variant of MYNNC/T (C)LRRC34Pancreas220−0.020.90.298Non-Significant

H3K27ac_Enh/H3K4me3_Pro/ H3K4me1_Enh/H3K9ac_Pro (Pancreas)

H3K27ac_Enh/H3K4me3_Pro/ H3K4me1_Enh/H3K9ac_Pro (Adipose-subcutaneous)

H3K27ac_Enh/H3K4me3_Pro/ H3K4me1_Enh/H3K9ac_Pro (Skeletal Muscle)

Creation of ESE intronic site/Creation of new site for SRp40–82.10 and SC35–82.42
Adipose-subcutaneous385−0.287.6E-81Significant and Down regulation
Skeletal Muscle491−0.1230.070.841Non-Significant
MYNNPancreas2200.1710.050.938Non-Significant
Adipose-subcutaneous3850.0990.030.97Significant and Up regulation
Skeletal Muscle4910.1062.2E-30.99Significant and Up regulation
rs740198284th intron variant of CSNK2A2G/A (G)N/AN/AN/AN/AN/AN/AN/ANo Role w.r.t studied tissuesCreation of new binding site for SC35–75.17

*Risk allele in this study; NES – Normalized Effect Size in eQTL; m-value – posterior probability that effect exists in each tissue, ranges between 0 and 1; H3K27Ac_Enh – chemical modification (acetylation) of the histone proteins (H3) at lysine 27 and associated with transcriptional initiation and open chromatin structure (active enhancer); H3K4me3 – chemical modification (methylation) of the histone proteins (H3) at lysine 4, marks promoters that are active or poised to be activated; H3K4me1 – chemical modification (methylation) of the histone proteins (H3) at lysine 4 and is associated with enhancers, and downstream of transcription starts.; H3K9ac – chemical modification (acetylation) of the histone proteins (H3) at lysine 9 and is associated with transcriptional initiation and open chromatin structure; Enh – Enhancers; Pro – Promoters; TSSA – active transcription start site; TxReg – transcription regulatory; PromD1 – promoter downstream TSS; TSSAFlk – Flanking TSS; 22PromP – poised promoter; EnhW1 – weak enhancer; EnhA2 – active enhancer 2; the H3K4me1/2/3 and H3K36me2/3 are linked with genomic region which actively transcribing and H3K9me3, H3K27me3 and H4K20me3 with non-transcribing region; ESE – Exonic Splicing Enhancers; SR – Serine-Arginine rich proteins; 9G8, SC35 – SR splicing factor; SF2/ASF (IgM-BRCA1) – Serine-Arginine rich proteins; #Supplementary Fig. S1.

Distribution of epidemiological parameters between Type 2 Diabetes patients and Healthy Controls populations from North India. *Other clinical conditions removed. Allelic Distribution. Logistic regression analysis of significant variants of genes in our study, adjusted for age, gender and BMI. *Adjusted for Age, Gender, and BMI. Putative Role of the associated variants with T2D in studied population (North-west India) utilizing the information from the various databases including GTEX, UCSC genome browser and HSF. H3K27ac_Enh/H3K4me3_Pro/ H3K4me1_Enh/H3K9ac_Pro (Pancreas) H3K27ac_Enh/H3K4me3_Pro/ H3K4me1_Enh/H3K9ac_Pro (Adipose-subcutaneous) H3K27ac_Enh/H3K4me3_Pro/ H3K4me1_Enh/H3K9ac_Pro (Skeletal Muscle) *Risk allele in this study; NES – Normalized Effect Size in eQTL; m-value – posterior probability that effect exists in each tissue, ranges between 0 and 1; H3K27Ac_Enh – chemical modification (acetylation) of the histone proteins (H3) at lysine 27 and associated with transcriptional initiation and open chromatin structure (active enhancer); H3K4me3 – chemical modification (methylation) of the histone proteins (H3) at lysine 4, marks promoters that are active or poised to be activated; H3K4me1 – chemical modification (methylation) of the histone proteins (H3) at lysine 4 and is associated with enhancers, and downstream of transcription starts.; H3K9ac – chemical modification (acetylation) of the histone proteins (H3) at lysine 9 and is associated with transcriptional initiation and open chromatin structure; Enh – Enhancers; Pro – Promoters; TSSA – active transcription start site; TxReg – transcription regulatory; PromD1 – promoter downstream TSS; TSSAFlk – Flanking TSS; 22PromP – poised promoter; EnhW1 – weak enhancer; EnhA2 – active enhancer 2; the H3K4me1/2/3 and H3K36me2/3 are linked with genomic region which actively transcribing and H3K9me3, H3K27me3 and H4K20me3 with non-transcribing region; ESE – Exonic Splicing Enhancers; SR – Serine-Arginine rich proteins; 9G8, SC35 – SR splicing factor; SF2/ASF (IgM-BRCA1) – Serine-Arginine rich proteins; #Supplementary Fig. S1.

rs9419958

The variant rs9419958 is located in the intronic region of the OBFC1 gene, a component of CST complex which assists in the efficient replication of telomeres and negatively regulates the telomere length by inhibiting the action of telomerase[29,30]. The variant was reported to be associated with telomere attrition[31]. In our study, the major allele (C) of variant rs9419958 (T/C) showed significantly increased risk for T2D with odds ratio (OR) of 2.3 (95% CI = 1.53–3.46) and p-value of 6.5E-5 (Table 2). As a result of cis-eQTL analysis, the risk allele (C) is associated with up regulation of the expression of the gene in pancreas (p-value = 1.9E-3 and normalized effect size (NES) = 0.221) and adipose-subcutaneous tissue (p-value = 1.1E-4 and NES = 0.226). The gene is responsible for terminating the telomerase activity at the telomeric ends[32] hence it is possible that the overexpression of the gene might lead to early termination of telomerase activity leading to attrition[30,33]. The locus showed the presence for histone marks (H3K27ac_Enh/H3K4me3_Pro/H3K4me1_Enh/H3K9ac_Pro), promoter and transcription regulatory activity, active transcription start site (TSS) (from chromatin 15 and 25 state model) and change in splicing factor binding sites of exonic splicing enhancers (ESE) intronic site and SF2/ASF (IgM-BRCA1) suggesting the locus plays an important role in epigenetic regulation (Table 3 and Supplementary Fig. S2).

rs4783704

The variant rs4783704 is an intergenic variant (TERF2 and CYB5B), upstream to TERF2 gene. TERF2 is a component of shelterin complex and implicated in the formation and stability of T-loop[15]. The variant was reported to be associated with T2D in a candidate gene association study conducted in Caucasian women[16]. In the present study, the major allele (C) of variant rs4783704 (C/T) showed significant risk for T2D with odds ratio (OR) of 1.52 (95% CI = 1.17–1.97) and p-value of 0.001 (Table 2). The region showed the presence of histone marks (H3K27ac_Enh/H3K4me1_Enh/H3K9ac_Pro), promoter activity (22_PromP), enhancer activity (14_EnhA2), DNase hypersensitivity, binding sites for splicing factors, SRp55 and 9 G and a strong binding site for transcription factors (Table 3 and Supplementary Figs. S1 and S2). One of the transcription factors is TCF7L2 (Supplementary Fig. S1) which is worldwide robustly associated with T2D and involved in several pathways including blood glucose homeostasis, insulin secretion and biosynthesis pathway and wingless type (wnt) signalling[34,35].

rs16847897

The variant rs16847897 is located upstream to Telomerase RNA component (TERC) and in the intronic region of the Leucine-rich repeat-containing protein 31 (LRRC31). TERC is a component of telomerase complex and act as RNA template during the replication process of telomeres[36]. LRRC31 belongs to a superfamily of LRRC – LRCC31, LRCC34 and LRRIQ4. The superfamily is involved in diverse roles including cell cycle regulation, chromosome stability, apoptosis and DNA repair[37]. Our study showed that the major allele (C) of variant rs16847897 (G/C) is associated with significant increased risk for T2D with odds ratio (OR) of 2.23 (95% CI = 1.71–2.9) and p-value of 2.4E-9 (Table 2). A study showed that the risk allele (C) is a part of the TERC haplotype GTC (rs12696304-G, rs10936601-T, and rs16847897-C) which is associated with increased risk of T2D and telomere attrition[15,38,39]. Our in silico analysis revealed that the risk allele (C) of variant rs16847897 is down regulating the expression of the LRRC34 gene in adipose-subcutaneous tissue (p-value = 3.7E-5 and NES = −0.208) and skeletal muscle (p-value = 0.03NES = −0.139) and also is a binding site for splicing factors (SF2/ASF (IgM-BRCA1) and SRp55) (Table 3 and Supplementary Fig. S2).

rs10936599

The variant rs10936599 is located upstream to TERC and in the 2nd exon of Myoneurin (MYNN) gene. MYNN belongs to BTB/POZ and zinc finger domain-containing protein family that is involved in the control of developmental events, and activation and suppression of transcription of distinct genes[40]. The variant has been found to be associated with telomere length attrition[10]. So far, only one candidate gene association study with T2D has been conducted where this variant did not show association with T2D in Caucasian women[16]. In the present study, the major allele (C) of variant rs10936599 (C/T) is significantly associated with high risk for T2D with odds ratio (OR) of 2.44 (95% CI = 1.9–3.12) and p-value of 1.63E-12 (Table 2). As a result of our in silico analysis, resistant allele (T) of this variant significantly down regulates the expression of LRRC34 gene in adipose-subcutaneous tissue (p-value = 7.6E-8 and NES = −0.28). It is also shown to up regulate the expression of MYNN gene in adipose-subcutaneous tissue (p-value = 0.03 and NES = 0.099) and skeletal muscle (p-value = 2.2E-3 and NES = 0.106). The locus also observed to have histone marks (H3K27ac_Enh/H3K4me3_Pro/H3K4me1_Enh/H3K9ac_Pro) and splicing factor binding sites (ESE intronic site, SRp40 and SC35) (Table 3 and Supplementary Fig. S2).

rs74019828

The variant rs74019828 is located at the 8th intron of the Casein Kinase 2 Alpha 2 (CSNK2A2). CSNK2A2 gene encodes a constitutively active catalytic subunit of a serine/threonine protein kinase enzyme. It plays a role in the regulation of telomere length by phosphorylating TRF1, which enhances its binding to telomeres and negatively regulates the telomere length[18]. The variant is associated with telomere attrition in a Punjabi diabetic Sikh cohort[18]. In our study, the major allele (G) of variant rs74019828 (G/A) was significantly associated with higher risk for T2D with odds ratio (OR) of 2.37 (95% CI = 1.77–3.18) and p-value of 6.57E-9 (Table 2). In silico analysis showed that the risk allele is associated with the formation of new splice sites for the splicing factor, SC35 (Table 3 and Supplementary Fig. S2). The subgroup analysis by gender was performed. Here, it was observed that the association of variants varies among males and females in the studied population (Supplementary Table S4). The significantly associated variants with T2D in Northwest Indian population were also found to be significantly associated with T2D in males sub-group. However, in females only the two variants namely, rs10936599 and rs74019828 showed significant association with T2D that needs further exploration in larger sample size for conclusions. The existence of interaction among the variants of telomere maintenance genes for the risk of developing T2D in the studied population was explored. The risk genotype of the associated variants was compared with the other possible combinations in cases and controls. The interactions were carried out stepwise. Interaction of variants, with respect to their location, i.e. within three complexes namely, telomerase, CST and shelterin was carried out followed by pairwise interaction of variants, irrespective of the location in the genes. The interaction among the risk genotypic combination in associated variants involved in the telomere maintenance genes was found to be significant. The variants (rs16847897 and rs10936599) of telomerase complex showed highly significant association (p-value = 9.4E-34, OR = 5.04 (3.88–6.55) at 95%CI) with T2D. A significant association (p-value = <0.001, OR = 6.03 (4.59–7.91) at 95%CI) was also found among the variants (rs16847897, rs10936599 and rs9419958) of telomerase and CST complexes. Likewise, the variants (rs16847897, rs10936599, rs9419958, rs74019828 and rs4783704) of telomerase, CST and shelterin complexes also showed significant association (p-value = 1E-36, OR = 8.63 (6.19–12.04) at 95%CI) with T2D. The risk for T2D ranges from 1.85 to 8.63 folds (Supplementary Table S5).

Conclusion

Worldwide so far, 129 loci have been associated with T2D by candidate gene association studies and GWAS[7], however, these genes are involved predominantly in insulin secretion/action pathway. The high incidence of T2D necessitates the exploration of other pathways which could lead to T2D predisposition and Telomere maintenance pathway is one of these[15]. In present study, the association of the variants of telomere maintenance gene with T2D was explored and five variants showed significant association with T2D (ranging OR = 1.52–2.44 and p-value ≤ E-3). The subgroup analysis by gender showed interesting results. All the variants showed significant association in the male subgroup however, only two variants namely, rs10936599 and rs74019828 remain significant in the female group. It is an interesting perspective and should be explored in future studies in larger sample size and independent population groups. In silico analyses of these variants indicated the presence of one or more regulatory sites (histone marks/promoter and enhancer activity/transcription factor binding sites/splicing factor binding sites) and three variants (rs9419958 of OBFC1, rs16847897 and rs10936599 of TERC) showed significant cis-eQTL effect. The interaction analysis also showed significant association with T2D (p-value ranging from E-06 to E-36) and 1.85 to 8.63 fold risk for developing T2D. This first study from India (Northwest) elucidates the role of telomere maintenance genes in T2D. The findings from Northwest India suggest the importance of telomere maintenance pathway in T2D susceptibility and propose replication of it worldwide in all population group subsets for better understanding of the underlying mechanism played by the telomere maintenance genes in T2D etiology. Moreover, the putative functional annotations of these variants indicate these might have strong regulatory role in telomere maintenance pathway which further warrants functional validation studies of these variant.

Materials and Methods

Ethical statement

The present study was conducted after attaining approval by Institutional Ethics Review Board (IERB) of Shri Mata Vaishno Devi University (SMVDU). The study was performed in accordance with the relevant guidelines and regulations. A written informed consent was acquired from all the participants enrolled in the present study.

Subjects

A total of 1354 randomly collected samples were analysed in the present study which includes 682 diabetic individuals and 672 healthy individuals belonging to Northwest Indian population groups. A diagnostic criterion was made according to the International Diabetes Federation (IDF). Epidemiological characteristics were summarized in Table 1. The control group has postprandial glucose levels below 11 mmol/ L.

Selection of variants and genotyping

In the present study, the variants were selected (Supplementary Table S1) which have been implicated in telomere length attrition via genome-wide association studies (GWAS) and replication studies using the candidate gene approach. All the experiment work was conducted as per the set guidelines and regulations by Institutional Ethics Review Board (IERB), Shri Mata Vaishno Devi University (SMVDU). With written informed consent from the subjects, 2 ml of blood by venepuncture was collected. Genomic DNA extraction was performed by a conventional phenol-chloroform method and FlexiGene® DNA kit, QIAGEN (catalogue No. 51206) method. The quantity and quality check of genomic DNA was analysed by carrying out UV spectrophotometer (eppendorf Biospectrometer®, Hamburg Germany) analysis and Gel electrophoresis respectively. The genomic DNA was stored at 4 °C till further use at a concentration of 10 ng/µl. Genotyping was carried out on a high-throughput Agena MassARRAY platform (The MassARRAY® System by Agena Bioscience™, San Diego, CA). A customized panel of 12 variants from critical telomere maintenance pathway genes was made. The panel was made by using Agena Bioscience Assay Design Suite (version 2.0). The sequence of primers has been provided in Supplementary Table S6. The recommended (standardized) protocol was followed for the genotyping. The genotype calls were analyzed by using the software Sequenom Typer 4.0. All genotype calls were cross checked to evaluate and exclude the call errors via spectrograms. The subjects were excluded from the study if the missing genotypes were higher than 10%. Those that deviated from the Hardy-Weinberg Equilibrium (HWE) (p-value <0.05) were also excluded from the study.

Statistical analyses

Clinical characteristics between cases and controls were compared by t-test. Statistical analyses on the genotype data was performed by using the PLINK v. 1.07 and gPLINK[41] and IBM SPSS statistics 20 software[42]. Each variant was tested for Hardy-Weinberg equilibrium using chi-square test. Correlation of variants with age was performed by Pearson Correlation analysis. The association of variants with T2D was confirmed by binary logistic regression adjusted for confounding factors like age, gender and Body Mass Index (BMI). The odds ratios (ORs) were calculated with respect to the risk allele found in this study. The comparison of clinical characteristics of different genotypes for each variant was performed by one way ANOVA, adjusted for age and gender. The interaction analysis was performed by logistic regression analysis using IBM SPSS statistics 20 software and adjusted for age, gender and BMI.

Putative functional role of the variants

The combined expression Quantitative Trait Loci (eQTL) analysis of the variants was explored by using University of California Santa Cruz (UCSC) Genome Browser (https://genome.ucsc.edu) and GTEx portal (https://www.gtexportal.org) [43,44]. The transcriptional regulatory role like histone modifications, DNase hypersentivity and binding sites for the transcription factor was analysed by UCSC Genome Browser, Encyclopedia of DNA Elements (ENCODE) (V3) and Haploreg v4.1 database[26,45]. The effect of variant on splicing by using the web tool Human Spicing Finder (HSF) 3.1and ESE finder (3.0)[28,46] was also analysed. Telomere Maintenance Genes are associated with Type 2 Diabetes Susceptibility in Northwest Indian Population Group.
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1.  A short leucocyte telomere length is associated with development of insulin resistance.

Authors:  Simon Verhulst; Christine Dalgård; Carlos Labat; Jeremy D Kark; Masayuki Kimura; Kaare Christensen; Simon Toupance; Abraham Aviv; Kirsten O Kyvik; Athanase Benetos
Journal:  Diabetologia       Date:  2016-03-28       Impact factor: 10.122

2.  Rise in insulin resistance is associated with escalated telomere attrition.

Authors:  Jeffrey P Gardner; Shengxu Li; Sathanur R Srinivasan; Wei Chen; Masayuki Kimura; Xiaobin Lu; Gerald S Berenson; Abraham Aviv
Journal:  Circulation       Date:  2005-04-25       Impact factor: 29.690

3.  Concordance for type 1 (insulin-dependent) and type 2 (non-insulin-dependent) diabetes mellitus in a population-based cohort of twins in Finland.

Authors:  J Kaprio; J Tuomilehto; M Koskenvuo; K Romanov; A Reunanen; J Eriksson; J Stengård; Y A Kesäniemi
Journal:  Diabetologia       Date:  1992-11       Impact factor: 10.122

4.  Leukocyte telomere length correlates with glucose control in adults with recently diagnosed type 2 diabetes.

Authors:  Erica Carine Campos Caldas Rosa; Renan Renato Cruz Dos Santos; Luis Fernando Amarante Fernandes; Francisco de Assis Rocha Neves; Michella Soares Coelho; Angelica Amorim Amato
Journal:  Diabetes Res Clin Pract       Date:  2017-10-28       Impact factor: 5.602

Review 5.  Genetics of type 2 diabetes-pitfalls and possibilities.

Authors:  Rashmi B Prasad; Leif Groop
Journal:  Genes (Basel)       Date:  2015-03-12       Impact factor: 4.096

Review 6.  Prioritising Causal Genes at Type 2 Diabetes Risk Loci.

Authors:  Antje K Grotz; Anna L Gloyn; Soren K Thomsen
Journal:  Curr Diab Rep       Date:  2017-09       Impact factor: 4.810

7.  Genome-wide association analyses identify 143 risk variants and putative regulatory mechanisms for type 2 diabetes.

Authors:  Angli Xue; Yang Wu; Zhihong Zhu; Futao Zhang; Kathryn E Kemper; Zhili Zheng; Loic Yengo; Luke R Lloyd-Jones; Julia Sidorenko; Yeda Wu; Allan F McRae; Peter M Visscher; Jian Zeng; Jian Yang
Journal:  Nat Commun       Date:  2018-07-27       Impact factor: 14.919

Review 8.  Environmental/lifestyle factors in the pathogenesis and prevention of type 2 diabetes.

Authors:  Hubert Kolb; Stephan Martin
Journal:  BMC Med       Date:  2017-07-19       Impact factor: 8.775

9.  The genetic architecture of type 2 diabetes.

Authors:  Christian Fuchsberger; Jason Flannick; Tanya M Teslovich; Anubha Mahajan; Vineeta Agarwala; Kyle J Gaulton; Clement Ma; Pierre Fontanillas; Loukas Moutsianas; Davis J McCarthy; Manuel A Rivas; John R B Perry; Xueling Sim; Thomas W Blackwell; Neil R Robertson; N William Rayner; Pablo Cingolani; Adam E Locke; Juan Fernandez Tajes; Heather M Highland; Josee Dupuis; Peter S Chines; Cecilia M Lindgren; Christopher Hartl; Anne U Jackson; Han Chen; Jeroen R Huyghe; Martijn van de Bunt; Richard D Pearson; Ashish Kumar; Martina Müller-Nurasyid; Niels Grarup; Heather M Stringham; Eric R Gamazon; Jaehoon Lee; Yuhui Chen; Robert A Scott; Jennifer E Below; Peng Chen; Jinyan Huang; Min Jin Go; Michael L Stitzel; Dorota Pasko; Stephen C J Parker; Tibor V Varga; Todd Green; Nicola L Beer; Aaron G Day-Williams; Teresa Ferreira; Tasha Fingerlin; Momoko Horikoshi; Cheng Hu; Iksoo Huh; Mohammad Kamran Ikram; Bong-Jo Kim; Yongkang Kim; Young Jin Kim; Min-Seok Kwon; Juyoung Lee; Selyeong Lee; Keng-Han Lin; Taylor J Maxwell; Yoshihiko Nagai; Xu Wang; Ryan P Welch; Joon Yoon; Weihua Zhang; Nir Barzilai; Benjamin F Voight; Bok-Ghee Han; Christopher P Jenkinson; Teemu Kuulasmaa; Johanna Kuusisto; Alisa Manning; Maggie C Y Ng; Nicholette D Palmer; Beverley Balkau; Alena Stančáková; Hanna E Abboud; Heiner Boeing; Vilmantas Giedraitis; Dorairaj Prabhakaran; Omri Gottesman; James Scott; Jason Carey; Phoenix Kwan; George Grant; Joshua D Smith; Benjamin M Neale; Shaun Purcell; Adam S Butterworth; Joanna M M Howson; Heung Man Lee; Yingchang Lu; Soo-Heon Kwak; Wei Zhao; John Danesh; Vincent K L Lam; Kyong Soo Park; Danish Saleheen; Wing Yee So; Claudia H T Tam; Uzma Afzal; David Aguilar; Rector Arya; Tin Aung; Edmund Chan; Carmen Navarro; Ching-Yu Cheng; Domenico Palli; Adolfo Correa; Joanne E Curran; Denis Rybin; Vidya S Farook; Sharon P Fowler; Barry I Freedman; Michael Griswold; Daniel Esten Hale; Pamela J Hicks; Chiea-Chuen Khor; Satish Kumar; Benjamin Lehne; Dorothée Thuillier; Wei Yen Lim; Jianjun Liu; Yvonne T van der Schouw; Marie Loh; Solomon K Musani; Sobha Puppala; William R Scott; Loïc Yengo; Sian-Tsung Tan; Herman A Taylor; Farook Thameem; Gregory Wilson; Tien Yin Wong; Pål Rasmus Njølstad; Jonathan C Levy; Massimo Mangino; Lori L Bonnycastle; Thomas Schwarzmayr; João Fadista; Gabriela L Surdulescu; Christian Herder; Christopher J Groves; Thomas Wieland; Jette Bork-Jensen; Ivan Brandslund; Cramer Christensen; Heikki A Koistinen; Alex S F Doney; Leena Kinnunen; Tõnu Esko; Andrew J Farmer; Liisa Hakaste; Dylan Hodgkiss; Jasmina Kravic; Valeriya Lyssenko; Mette Hollensted; Marit E Jørgensen; Torben Jørgensen; Claes Ladenvall; Johanne Marie Justesen; Annemari Käräjämäki; Jennifer Kriebel; Wolfgang Rathmann; Lars Lannfelt; Torsten Lauritzen; Narisu Narisu; Allan Linneberg; Olle Melander; Lili Milani; Matt Neville; Marju Orho-Melander; Lu Qi; Qibin Qi; Michael Roden; Olov Rolandsson; Amy Swift; Anders H Rosengren; Kathleen Stirrups; Andrew R Wood; Evelin Mihailov; Christine Blancher; Mauricio O Carneiro; Jared Maguire; Ryan Poplin; Khalid Shakir; Timothy Fennell; Mark DePristo; Martin Hrabé de Angelis; Panos Deloukas; Anette P Gjesing; Goo Jun; Peter Nilsson; Jacquelyn Murphy; Robert Onofrio; Barbara Thorand; Torben Hansen; Christa Meisinger; Frank B Hu; Bo Isomaa; Fredrik Karpe; Liming Liang; Annette Peters; Cornelia Huth; Stephen P O'Rahilly; Colin N A Palmer; Oluf Pedersen; Rainer Rauramaa; Jaakko Tuomilehto; Veikko Salomaa; Richard M Watanabe; Ann-Christine Syvänen; Richard N Bergman; Dwaipayan Bharadwaj; Erwin P Bottinger; Yoon Shin Cho; Giriraj R Chandak; Juliana C N Chan; Kee Seng Chia; Mark J Daly; Shah B Ebrahim; Claudia Langenberg; Paul Elliott; Kathleen A Jablonski; Donna M Lehman; Weiping Jia; Ronald C W Ma; Toni I Pollin; Manjinder Sandhu; Nikhil Tandon; Philippe Froguel; Inês Barroso; Yik Ying Teo; Eleftheria Zeggini; Ruth J F Loos; Kerrin S Small; Janina S Ried; Ralph A DeFronzo; Harald Grallert; Benjamin Glaser; Andres Metspalu; Nicholas J Wareham; Mark Walker; Eric Banks; Christian Gieger; Erik Ingelsson; Hae Kyung Im; Thomas Illig; Paul W Franks; Gemma Buck; Joseph Trakalo; David Buck; Inga Prokopenko; Reedik Mägi; Lars Lind; Yossi Farjoun; Katharine R Owen; Anna L Gloyn; Konstantin Strauch; Tiinamaija Tuomi; Jaspal Singh Kooner; Jong-Young Lee; Taesung Park; Peter Donnelly; Andrew D Morris; Andrew T Hattersley; Donald W Bowden; Francis S Collins; Gil Atzmon; John C Chambers; Timothy D Spector; Markku Laakso; Tim M Strom; Graeme I Bell; John Blangero; Ravindranath Duggirala; E Shyong Tai; Gilean McVean; Craig L Hanis; James G Wilson; Mark Seielstad; Timothy M Frayling; James B Meigs; Nancy J Cox; Rob Sladek; Eric S Lander; Stacey Gabriel; Noël P Burtt; Karen L Mohlke; Thomas Meitinger; Leif Groop; Goncalo Abecasis; Jose C Florez; Laura J Scott; Andrew P Morris; Hyun Min Kang; Michael Boehnke; David Altshuler; Mark I McCarthy
Journal:  Nature       Date:  2016-07-11       Impact factor: 69.504

10.  An Expanded Genome-Wide Association Study of Type 2 Diabetes in Europeans.

Authors:  Robert A Scott; Laura J Scott; Reedik Mägi; Letizia Marullo; Kyle J Gaulton; Marika Kaakinen; Natalia Pervjakova; Tune H Pers; Andrew D Johnson; John D Eicher; Anne U Jackson; Teresa Ferreira; Yeji Lee; Clement Ma; Valgerdur Steinthorsdottir; Gudmar Thorleifsson; Lu Qi; Natalie R Van Zuydam; Anubha Mahajan; Han Chen; Peter Almgren; Ben F Voight; Harald Grallert; Martina Müller-Nurasyid; Janina S Ried; Nigel W Rayner; Neil Robertson; Lennart C Karssen; Elisabeth M van Leeuwen; Sara M Willems; Christian Fuchsberger; Phoenix Kwan; Tanya M Teslovich; Pritam Chanda; Man Li; Yingchang Lu; Christian Dina; Dorothee Thuillier; Loic Yengo; Longda Jiang; Thomas Sparso; Hans A Kestler; Himanshu Chheda; Lewin Eisele; Stefan Gustafsson; Mattias Frånberg; Rona J Strawbridge; Rafn Benediktsson; Astradur B Hreidarsson; Augustine Kong; Gunnar Sigurðsson; Nicola D Kerrison; Jian'an Luan; Liming Liang; Thomas Meitinger; Michael Roden; Barbara Thorand; Tõnu Esko; Evelin Mihailov; Caroline Fox; Ching-Ti Liu; Denis Rybin; Bo Isomaa; Valeriya Lyssenko; Tiinamaija Tuomi; David J Couper; James S Pankow; Niels Grarup; Christian T Have; Marit E Jørgensen; Torben Jørgensen; Allan Linneberg; Marilyn C Cornelis; Rob M van Dam; David J Hunter; Peter Kraft; Qi Sun; Sarah Edkins; Katharine R Owen; John R B Perry; Andrew R Wood; Eleftheria Zeggini; Juan Tajes-Fernandes; Goncalo R Abecasis; Lori L Bonnycastle; Peter S Chines; Heather M Stringham; Heikki A Koistinen; Leena Kinnunen; Bengt Sennblad; Thomas W Mühleisen; Markus M Nöthen; Sonali Pechlivanis; Damiano Baldassarre; Karl Gertow; Steve E Humphries; Elena Tremoli; Norman Klopp; Julia Meyer; Gerald Steinbach; Roman Wennauer; Johan G Eriksson; Satu Mӓnnistö; Leena Peltonen; Emmi Tikkanen; Guillaume Charpentier; Elodie Eury; Stéphane Lobbens; Bruna Gigante; Karin Leander; Olga McLeod; Erwin P Bottinger; Omri Gottesman; Douglas Ruderfer; Matthias Blüher; Peter Kovacs; Anke Tonjes; Nisa M Maruthur; Chiara Scapoli; Raimund Erbel; Karl-Heinz Jöckel; Susanne Moebus; Ulf de Faire; Anders Hamsten; Michael Stumvoll; Panagiotis Deloukas; Peter J Donnelly; Timothy M Frayling; Andrew T Hattersley; Samuli Ripatti; Veikko Salomaa; Nancy L Pedersen; Bernhard O Boehm; Richard N Bergman; Francis S Collins; Karen L Mohlke; Jaakko Tuomilehto; Torben Hansen; Oluf Pedersen; Inês Barroso; Lars Lannfelt; Erik Ingelsson; Lars Lind; Cecilia M Lindgren; Stephane Cauchi; Philippe Froguel; Ruth J F Loos; Beverley Balkau; Heiner Boeing; Paul W Franks; Aurelio Barricarte Gurrea; Domenico Palli; Yvonne T van der Schouw; David Altshuler; Leif C Groop; Claudia Langenberg; Nicholas J Wareham; Eric Sijbrands; Cornelia M van Duijn; Jose C Florez; James B Meigs; Eric Boerwinkle; Christian Gieger; Konstantin Strauch; Andres Metspalu; Andrew D Morris; Colin N A Palmer; Frank B Hu; Unnur Thorsteinsdottir; Kari Stefansson; Josée Dupuis; Andrew P Morris; Michael Boehnke; Mark I McCarthy; Inga Prokopenko
Journal:  Diabetes       Date:  2017-05-31       Impact factor: 9.337

View more
  5 in total

1.  Preliminary genome wide screening identifies new variants associated with coronary artery disease in Indian population.

Authors:  Keshavamurthy Ganapathy Bhat; Vivek Singh Guleria; Ratheesh Kumar J; Garima Rastogi; Varun Sharma; Anuka Sharma
Journal:  Am J Transl Res       Date:  2022-07-15       Impact factor: 3.940

2.  Shortening of leucocyte telomere length is independently correlated with high body mass index and subcutaneous obesity (predominantly truncal), in Asian Indian women with abnormal fasting glycemia.

Authors:  Surya Prakash Bhatt; Anoop Misra; Ravindra Mohan Pandey; Ashish Datt Upadhyay
Journal:  BMJ Open Diabetes Res Care       Date:  2022-07

3.  Terc Gene Cluster Variants Predict Liver Telomere Length in Mice.

Authors:  Dana Zeid; Sean Mooney-Leber; Laurel R Seemiller; Lisa R Goldberg; Thomas J Gould
Journal:  Cells       Date:  2021-10-01       Impact factor: 6.600

4.  Telomere Attrition With Concomitant hTERT Overexpression Involved in the Progression of Gastric Cancer May Have Prognostic and Clinical Implications in High-Risk Population Group From North India.

Authors:  Ifra Mushtaq; Gh Rasool Bhat; Bilal Rah; Syed Besina; Sheikh Zahoor; Muneer A Wani; Mubashir A Shah; Sadaf Bashir; Muzamil Farooq; Rafiq A Rather; Dil Afroze
Journal:  Front Oncol       Date:  2022-07-13       Impact factor: 5.738

5.  MassARRAY-based single nucleotide polymorphism analysis in breast cancer of north Indian population.

Authors:  Divya Bakshi; Ashna Nagpal; Varun Sharma; Indu Sharma; Ruchi Shah; Bhanu Sharma; Amrita Bhat; Sonali Verma; Gh Rasool Bhat; Deepak Abrol; Rahul Sharma; Samantha Vaishnavi; Rakesh Kumar
Journal:  BMC Cancer       Date:  2020-09-07       Impact factor: 4.430

  5 in total

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