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2000
Volume 21, Issue 2
  • ISSN: 1875-6921
  • E-ISSN:

Abstract

Type 2 Diabetes Mellitus (T2DM) has been a severe public health issue worldwide for many years. The primary cause and risk factor of T2DM is hereditary and complicated interaction between epigenetics. Identification and understanding of genetic markers may help to detect, prevent, and manage T2DM. This review examined the effect of single-gene and gene-gene interactions for predicting diabetes mellitus. Based on the literature survey, common and unique Single Nucleotide Polymorphisms (SNPs) and genes were explored in the Indian Populations, including and . Identifying common and specific markers may help in risk prediction and early detection of T2DM. Future research and Genome-wide association studies are also required to predict the gene-gene interaction, generate large data sets for removing non-representative groups, and focus only on specific marker-associated traits.

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2024-08-01
2024-11-23
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References

  1. HuntD. HemmingsenB. MatzkeA. The WHO global diabetes compact: A new initiative to support people living with diabetes.Lancet Diabetes Endocrinol.20219632532710.1016/S2213‑8587(21)00111‑X 33862005
    [Google Scholar]
  2. GoyalR. SinghalM. JialalI. Type 2 Diabetes.In: StatPearls.StatPearls Publishing2023
    [Google Scholar]
  3. HivertM.F. VassyJ.L. MeigsJ.B. Susceptibility to type 2 diabetes mellitus—From genes to prevention.Nat. Rev. Endocrinol.201410419820510.1038/nrendo.2014.11 24535206
    [Google Scholar]
  4. International Diabetes Federation.IDF Diabetes Atlas2015
    [Google Scholar]
  5. Classification and Diagnosis of Diabetes. Diabetes Care201740S11S2410.2337/dc17‑S005 27979889
    [Google Scholar]
  6. SchusterD. Obesity and the development of type 2 diabetes: The effects of fatty tissue inflammation.Diabetes Metab. Syndr. Obes.2010325326210.2147/DMSO.S7354 21437093
    [Google Scholar]
  7. ChenL. MaglianoD.J. ZimmetP.Z. The worldwide epidemiology of type 2 diabetes mellitus—Present and future perspectives.Nat. Rev. Endocrinol.20128422823610.1038/nrendo.2011.183 22064493
    [Google Scholar]
  8. RasouliN. KernP.A. Adipocytokines and the metabolic complications of obesity.J. Clin. Endocrinol. Metab.200893s64s7310.1210/jc.2008‑1613 18987272
    [Google Scholar]
  9. LuharS. KondalD. JonesR. Lifetime risk of diabetes in metropolitan cities in India.Diabetologia202164352152910.1007/s00125‑020‑05330‑1 33225415
    [Google Scholar]
  10. HuF.B. Globalization of Diabetes.Diabetes Care20113461249125710.2337/dc11‑0442 21617109
    [Google Scholar]
  11. SinclairA. SaeediP. KaundalA. KarurangaS. MalandaB. WilliamsR. Diabetes and global ageing among 65-99- year-old adults: Findings from the International Diabetes Federation Diabetes Atlas, 9th edition.Diabetes Res Clin Pract202016210807810.1016/j.diabres.2020.108078
    [Google Scholar]
  12. ChoN.H. ShawJ.E. KarurangaS. IDF Diabetes Atlas: Global estimates of diabetes prevalence for 2017 and projections for 2045.Diabetes Res. Clin. Pract.201813827128110.1016/j.diabres.2018.02.023 29496507
    [Google Scholar]
  13. OberoiS. KansraP. Economic menace of diabetes in India: A systematic review.Int. J. Diabetes Dev. Ctries.202040446447510.1007/s13410‑020‑00838‑z 32837090
    [Google Scholar]
  14. SarwarN. GaoP. SeshasaiS.R. Diabetes mellitus, fasting blood glucose concentration, and risk of vascular disease: A collaborative meta-analysis of 102 prospective studies.Lancet201037597332215222210.1016/S0140‑6736(10)60484‑9 20609967
    [Google Scholar]
  15. SinghG.M. DanaeiG. FarzadfarF. The age-specific quantitative effects of metabolic risk factors on cardiovascular diseases and diabetes: A pooled analysis.PLoS One201387e6517410.1371/journal.pone.0065174 23935815
    [Google Scholar]
  16. AnjanaR.M. DeepaM. PradeepaR. Prevalence of diabetes and prediabetes in 15 states of India: Results from the ICMR–INDIAB population-based cross-sectional study.Lancet Diabetes Endocrinol.20175858559610.1016/S2213‑8587(17)30174‑2 28601585
    [Google Scholar]
  17. CorsiD.J. SubramanianS.V. Socioeconomic gradients and distribution of diabetes, hypertension, and obesity in India.JAMA Netw. Open201924e19041110.1001/jamanetworkopen.2019.0411 30951154
    [Google Scholar]
  18. JosephA. ThirupathammaM. MathewsE. AlaguM. Genetics of type 2 diabetes mellitus in Indian and global population: A review.Egypt. J. Med. Hum. Genet.202223113510.1186/s43042‑022‑00346‑1 37192883
    [Google Scholar]
  19. KhanI.A. PoornimaS. JahanP. RaoP. HasanQ. Type 2 Diabetes Mellitus and the association of candidate genes in Asian Indian population from Hyderabad, India.J. Clin. Diagn. Res.2015911GC01GC0510.7860/JCDR/2015/14471.6855 26673680
    [Google Scholar]
  20. HallE. Dekker NitertM. VolkovP. The effects of high glucose exposure on global gene expression and DNA methylation in human pancreatic islets.Mol. Cell. Endocrinol.2018472576710.1016/j.mce.2017.11.019 29183809
    [Google Scholar]
  21. LingC. RönnT. Epigenetics in human obesity and Type 2 Diabetes.Cell Metab.20192951028104410.1016/j.cmet.2019.03.009 30982733
    [Google Scholar]
  22. AlbertiK.G.M.M. ZimmetP. ShawJ. The metabolic syndrome—A new worldwide definition.Lancet200536694911059106210.1016/S0140‑6736(05)67402‑8 16182882
    [Google Scholar]
  23. MoledinaN. LeungA.A. Endocrinology.Approach to Internal Medicine. HuiD. LeungA.A. MaC. Springer202236539610.1007/978‑3‑030‑72980‑6_11
    [Google Scholar]
  24. BanH.J. HeoJ.Y. OhK.S. ParkK.J. Identification of type 2 diabetes-associated combination of SNPs using support vector machine.BMC Genet.20101112610.1186/1471‑2156‑11‑26 20416077
    [Google Scholar]
  25. WitkaB.Z. OktavianiD.J. MarcellinoM. BarlianaM.I. AbdulahR. Type 2 Diabetes-associated genetic polymorphisms as potential disease predictors.Diabetes Metab. Syndr. Obes.2019122689270610.2147/DMSO.S230061 31908510
    [Google Scholar]
  26. ChanJ.C.N. CheungC.K. SwaminathanR. NichollsM.G. CockramC.S. Obesity, albuminuria and hypertension among Hong Kong Chinese with non-insulin-dependent diabetes mellitus (NIDDM).Postgrad. Med. J.19936980920421010.1136/pgmj.69.809.204 8497435
    [Google Scholar]
  27. DabeleaD. DeGroatJ. SorrelmanC. Diabetes in Navajo youth: Prevalence, incidence, and clinical characteristics: The SEARCH for Diabetes in youth study.Diabetes Care2009S141S14710.2337/dc09‑S206
    [Google Scholar]
  28. LiuL.L. YiJ.P. BeyerJ. Type 1 and Type 2 diabetes in Asian and Pacific Islander U.S. youth: The SEARCH for Diabetes in Youth Study.Diabetes Care200932Suppl. 2S133S14010.2337/dc09‑S205
    [Google Scholar]
  29. KarterA.J. SchillingerD. AdamsA.S. Elevated rates of diabetes in Pacific Islanders and Asian subgroups: The Diabetes Study of Northern California (DISTANCE).Diabetes Care201336357457910.2337/dc12‑0722 23069837
    [Google Scholar]
  30. SattarN. GillJ.M.R. Type 2 diabetes in migrant south Asians: Mechanisms, mitigation, and management.Lancet Diabetes Endocrinol.20153121004101610.1016/S2213‑8587(15)00326‑5 26489808
    [Google Scholar]
  31. McKeigueP.M. ShahB. MarmotM.G. Relation of central obesity and insulin resistance with high diabetes prevalence and cardiovascular risk in South Asians.Lancet1991337873838238610.1016/0140‑6736(91)91164‑P 1671422
    [Google Scholar]
  32. HainesL. WanK.C. LynnR. BarrettT.G. ShieldJ.P.H. Rising incidence of type 2 diabetes in children in the U.K.Diabetes Care20073051097110110.2337/dc06‑1813 17259470
    [Google Scholar]
  33. FuchsbergerC. FlannickJ. TeslovichT.M. The genetic architecture of type 2 diabetes.Nature20165367614414710.1038/nature18642 27398621
    [Google Scholar]
  34. McCarthyM.I. Genomics, type 2 diabetes, and obesity.N. Engl. J. Med.2010363242339235010.1056/NEJMra0906948 21142536
    [Google Scholar]
  35. DimasA.S. LagouV. BarkerA. Impact of type 2 diabetes susceptibility variants on quantitative glycemic traits reveals mechanistic heterogeneity.Diabetes20146362158217110.2337/db13‑0949 24296717
    [Google Scholar]
  36. FlannickJ. FlorezJ.C. Type 2 diabetes: Genetic data sharing to advance complex disease research.Nat. Rev. Genet.201617953554910.1038/nrg.2016.56 27402621
    [Google Scholar]
  37. FranksP.W. PearsonE. FlorezJ.C. Gene-environment and gene-treatment interactions in type 2 diabetes: Progress, pitfalls, and prospects.Diabetes Care20133651413142110.2337/dc12‑2211 23613601
    [Google Scholar]
  38. Shitomi-JonesL.M. AkamL. HunterD. SinghP. MastanaS. Genetic risk scores for the determination of Type 2 Diabetes Mellitus (T2DM) in North India.Int. J. Environ. Res. Public Health2023204372910.3390/ijerph20043729 36834424
    [Google Scholar]
  39. PelleM.C. ProvenzanoM. ZaffinaI. Role of a Dual Glucose-Dependent Insulinotropic Peptide (GIP)/glucagon-like peptide-1 receptor agonist (Twincretin) in glycemic control: From pathophysiology to treatment.Life (Basel)20211212910.3390/life12010029 35054422
    [Google Scholar]
  40. HimanshuD. AliW. WamiqueM. Type 2 diabetes mellitus: Pathogenesis and genetic diagnosis.J. Diabetes Metab. Disord.20201921959196610.1007/s40200‑020‑00641‑x 33520871
    [Google Scholar]
  41. van LeeuwenN. NijpelsG. BeckerM.L. A gene variant near ATM is significantly associated with metformin treatment response in type 2 diabetes: A replication and meta-analysis of five cohorts.Diabetologia20125571971197710.1007/s00125‑012‑2537‑x 22453232
    [Google Scholar]
  42. GallW.E. BeebeK. LawtonK.A. Alpha-hydroxybutyrate is an early biomarker of insulin resistance and glucose intolerance in a nondiabetic population.PLoS One201055e1088310.1371/journal.pone.0010883
    [Google Scholar]
  43. TricòD. PrinsenH. GianniniC. Elevated α-hydroxybutyrate and branched-chain amino acid levels predict deterioration of glycemic control in adolescents.J. Clin. Endocrinol. Metab.201710272473248110.1210/jc.2017‑00475 28482070
    [Google Scholar]
  44. MitchellK.J. What is complex about complex disorders?Genome Biol.201213123710.1186/gb‑2012‑13‑1‑237 22269335
    [Google Scholar]
  45. MahajanA. TaliunD. ThurnerM. Fine-mapping type 2 diabetes loci to single-variant resolution using high-density imputation and islet-specific epigenome maps.Nat. Genet.201850111505151310.1038/s41588‑018‑0241‑6 30297969
    [Google Scholar]
  46. BellouV. BelbasisL. TzoulakiI. EvangelouE. Risk factors for type 2 diabetes mellitus: An exposure-wide umbrella review of meta-analyses.PLoS One2018133e019412710.1371/journal.pone.0194127 29558518
    [Google Scholar]
  47. CareyV.J. WaltersE.E. ColditzG.A. Body fat distribution and risk of non-insulin-dependent diabetes mellitus in women. The Nurses’ Health Study.Am. J. Epidemiol.1997145761461910.1093/oxfordjournals.aje.a009158 9098178
    [Google Scholar]
  48. SinhaR. DufourS. PetersenK.F. Assessment of skeletal muscle triglyceride content by (1)H nuclear magnetic resonance spectroscopy in lean and obese adolescents: Relationships to insulin sensitivity, total body fat, and central adiposity.Diabetes20025141022102710.2337/diabetes.51.4.1022 11916921
    [Google Scholar]
  49. HillierT.A. PedulaK.L. Complications in young adults with early-onset type 2 diabetes: Losing the relative protection of youth.Diabetes Care200326112999300510.2337/diacare.26.11.2999 14578230
    [Google Scholar]
  50. WeinsteinA.R. SessoH.D. LeeI.M. Relationship of physical activity vs body mass index with type 2 diabetes in women.JAMA2004292101188119410.1001/jama.292.10.1188 15353531
    [Google Scholar]
  51. LynchJ. HelmrichS.P. LakkaT.A. Moderately intense physical activities and high levels of cardiorespiratory fitness reduce the risk of non-insulin-dependent diabetes mellitus in middle-aged men.Arch. Intern. Med.1996156121307131410.1001/archinte.1996.00440110073010 8651839
    [Google Scholar]
  52. MishraS. PericherlaS. ManthuruthilS. MishraS. HannoR. Effect of physical activity on insulin resistance, inflammation and oxidative stress in Diabetes Mellitus.J. Clin. Diagn. Res.2013781764176610.7860/JCDR/2013/6518.3306 24086908
    [Google Scholar]
  53. StrasserB. Physical activity in obesity and metabolic syndrome.Ann. N. Y. Acad. Sci.20131281114115910.1111/j.1749‑6632.2012.06785.x 23167451
    [Google Scholar]
  54. RossR. Does exercise without weight loss improve insulin sensitivity?Diabetes Care200326394494510.2337/diacare.26.3.944 12610063
    [Google Scholar]
  55. ChangK. KhandpurN. NeriD. Association between childhood consumption of ultraprocessed food and adiposity trajectories in the avon longitudinal study of parents and children birth cohort.JAMA Pediatr.20211759e21157310.1001/jamapediatrics.2021.1573 34125152
    [Google Scholar]
  56. HotamisligilG.S. Inflammation, metaflammation and immunometabolic disorders.Nature2017542764017718510.1038/nature21363 28179656
    [Google Scholar]
  57. PillonN.J. LoosR.J.F. MarshallS.M. ZierathJ.R. Metabolic consequences of obesity and type 2 diabetes: Balancing genes and environment for personalized care.Cell202118461530154410.1016/j.cell.2021.02.012 33675692
    [Google Scholar]
  58. CzechM.P. Insulin action and resistance in obesity and type 2 diabetes.Nat. Med.201723780481410.1038/nm.4350 28697184
    [Google Scholar]
  59. HeiskanenM.A. MotianiK.K. MariA. Exercise training decreases pancreatic fat content and improves beta cell function regardless of baseline glucose tolerance: A randomised controlled trial.Diabetologia20186181817182810.1007/s00125‑018‑4627‑x 29717337
    [Google Scholar]
  60. ChurchT.S. BlairS.N. CocrehamS. Effects of aerobic and resistance training on hemoglobin A1c levels in patients with type 2 diabetes: A randomized controlled trial.JAMA2010304202253226210.1001/jama.2010.1710 21098771
    [Google Scholar]
  61. SigalR.J. KennyG.P. BouléN.G. Effects of aerobic training, resistance training, or both on glycemic control in type 2 diabetes: A randomized trial.Ann. Intern. Med.2007147635736910.7326/0003‑4819‑147‑6‑200709180‑00005 17876019
    [Google Scholar]
  62. CuffD.J. MeneillyG.S. MartinA. IgnaszewskiA. TildesleyH.D. FrohlichJ.J. Effective exercise modality to reduce insulin resistance in women with type 2 diabetes.Diabetes Care200326112977298210.2337/diacare.26.11.2977 14578226
    [Google Scholar]
  63. CassidyS. ThomaC. HallsworthK. High intensity intermittent exercise improves cardiac structure and function and reduces liver fat in patients with type 2 diabetes: A randomised controlled trial.Diabetologia2016591566610.1007/s00125‑015‑3741‑2 26350611
    [Google Scholar]
  64. ColbergS.R. SigalR.J. YardleyJ.E. Physical activity/exercise and Diabetes: A position statement of the American Diabetes Association.Diabetes Care201639112065207910.2337/dc16‑1728 27926890
    [Google Scholar]
  65. ShethJ. TrivediS. ShahA. Are we predisposed to Type 2 Diabetes risk: A case-control study from Urban population in Western India.Endocrinol Metab J2017530012210.15406/emij.2017.05.00122
    [Google Scholar]
  66. ViswanathanV. ZhuY. BalaK. Association between ACE gene polymorphism and diabetic nephropathy in South Indian patients.JOP2001228387 11867868
    [Google Scholar]
  67. BhavaniB.A. PadmaT. SastryB.K.S. ReddyN.K. NausheenK. The Insertion I/Deletion D polymorphism of Angiotensin-Converting Enzyme (ACE) gene increase the susceptibility to Hypertension and/or Diabetes.Int. J. Hum. Genet.20055424725210.1080/09723757.2005.11885934
    [Google Scholar]
  68. RazaS.T. FatimaJ. AhmedF. Association of angiotensin-converting enzyme (ACE) and fatty acid binding protein 2 (FABP2) genes polymorphism with type 2 diabetes mellitus in Northern India.J. Renin Angiotensin Aldosterone Syst.201415457257910.1177/1470320313481082 23468166
    [Google Scholar]
  69. SinghP.P. NazI. GilmourA. SinghM. MastanaS. Association of APOE (Hha1) and ACE (I/D) gene polymorphisms with type 2 diabetes mellitus in North West India.Diabetes Res. Clin. Pract.20067419510210.1016/j.diabres.2006.03.013 16621107
    [Google Scholar]
  70. KumarA. MohindruK. SehajpalP.K. Angiotensin 1 converting enzyme polymorphism and diabetic nephropathy in north India.Int. J. Hum. Genet.20055427928310.1080/09723757.2005.11885939
    [Google Scholar]
  71. RazaS.T. AbbasS. AhmedF. FatimaJ. ZaidiZ.H. MahdiF. Association of MTHFR and PPARγ2 gene polymorphisms in relation to type 2 diabetes mellitus cases among north Indian population.Gene2012511237537910.1016/j.gene.2012.09.072 23036708
    [Google Scholar]
  72. YajnikC.S. JanipalliC.S. BhaskarS. FTO gene variants are strongly associated with type 2 diabetes in South Asian Indians.Diabetologia200952224725210.1007/s00125‑008‑1186‑6 19005641
    [Google Scholar]
  73. TabassumR. ChavaliS. DwivediO.P. TandonN. BharadwajD. Genetic variants of FOXA2: risk of type 2 diabetes and effect on metabolic traits in North Indians.J. Hum. Genet.20085311-1295796510.1007/s10038‑008‑0335‑6 18797817
    [Google Scholar]
  74. MahajanA. TabassumR. ChavaliS. Obesity-dependent association of TNF-LTA locus with type 2 diabetes in North Indians.J. Mol. Med. (Berl.)201088551552210.1007/s00109‑010‑0594‑5 20177654
    [Google Scholar]
  75. ChavaliS. MahajanA. TabassumR. Association of variants in genes involved in pancreatic β-cell development and function with type 2 diabetes in North Indians.J. Hum. Genet.2011561069570010.1038/jhg.2011.83 21814221
    [Google Scholar]
  76. BodhiniD. RadhaV. DeepaR. The G1057D polymorphism of IRS-2 gene and its relationship with obesity in conferring susceptibility to type 2 diabetes in Asian Indians.Int. J. Obes.20073119710210.1038/sj.ijo.0803356 16652127
    [Google Scholar]
  77. JahnaviS. PoovazhagiV. KanthimathiS. Novel ABCC8 (SUR1) gene mutations in Asian Indian children with congenital hyperinsulinemic hypoglycemia.Ann. Hum. Genet.201478531131910.1111/ahg.12070 25117148
    [Google Scholar]
  78. RadhaV. VimaleswaranK.S. BabuH.N.S. Role of genetic polymorphism peroxisome proliferator-activated receptor-gamma2 Pro12Ala on ethnic susceptibility to diabetes in South-Asian and Caucasian subjects: Evidence for heterogeneity.Diabetes Care20062951046105110.2337/dc05‑1473 16644635
    [Google Scholar]
  79. SinghS. VenketeshS. VermaJ.S. VermaM. LellammaC.O. GoelR.C. Paraoxonase (PON1) activity in north west Indian Punjabis with coronary artery disease & type 2 diabetes mellitus.Indian J. Med. Res.20071256783787 17704557
    [Google Scholar]
  80. SinghP. SinghM. GaurS. KaurT. The ApoAI-CIII-AIV gene cluster and its relation to lipid levels in type 2 diabetes mellitus and coronary heart disease: Determination of a novel susceptible haplotype.Diab. Vasc. Dis. Res.20074212412910.3132/dvdr.2007.030 17654446
    [Google Scholar]
  81. AchyutB.R. SrivastavaA. BhattacharyaS. MittalB. Genetic association of interleukin-1β (−511C/T) and interleukin-1 receptor antagonist (86 bp repeat) polymorphisms with Type 2 diabetes mellitus in North Indians.Clin. Chim. Acta20073771-216316910.1016/j.cca.2006.09.012 17069782
    [Google Scholar]
  82. BanerjeeM. BidH.K. KonwarR. AgrawalC.G. Association of IL-4 and IL-1RN (receptor antagonist) gene variants and the risk of type 2 diabetes mellitus: A study in the north Indian population.Indian J. Med. Sci.200862725926610.4103/0019‑5359.42021 18688110
    [Google Scholar]
  83. VimaleswaranK.S. RadhaV. GhoshS. Peroxisome proliferator‐activated receptor‐γ co‐activator‐1α (PGC‐1α) gene polymorphisms and their relationship to Type 2 diabetes in Asian Indians.Diabet. Med.200522111516152110.1111/j.1464‑5491.2005.01709.x 16241916
    [Google Scholar]
  84. VimaleswaranK.S. RadhaV. AnjanaM. Effect of polymorphisms in the PPARGC1A gene on body fat in Asian Indians.Int. J. Obes.200630688489110.1038/sj.ijo.0803228 16446747
    [Google Scholar]
  85. SharmaR. MatharooK. KapoorR. BhanwerA.J.S. Association of PGC-1α gene with type 2 diabetes in three unrelated endogamous groups of North-West India (Punjab): A case-control and meta-analysis study.Mol. Genet. Genomics2018293231732910.1007/s00438‑017‑1385‑2 29063962
    [Google Scholar]
  86. BhatA. KoulA. RaiE. SharmaS. DharM.K. BamezaiR.N.K. PGC-1α Thr394Thr and Gly482Ser variants are significantly associated with T2DM in two North Indian populations: A replicate case-control study.Hum. Genet.2007121560961410.1007/s00439‑007‑0352‑0 17390150
    [Google Scholar]
  87. AliS. ChopraR. ManvatiS. Replication of type 2 diabetes candidate genes variations in three geographically unrelated Indian population groups.PLoS One201383e5888110.1371/journal.pone.0058881 23527042
    [Google Scholar]
  88. AbateN. ChandaliaM. SatijaP. ENPP1/PC-1 K121Q polymorphism and genetic susceptibility to type 2 diabetes.Diabetes20055441207121310.2337/diabetes.54.4.1207 15793263
    [Google Scholar]
  89. ChauhanG. SpurgeonC.J. TabassumR. Impact of common variants of PPARG, KCNJ11, TCF7L2, SLC30A8, HHEX, CDKN2A, IGF2BP2, and CDKAL1 on the risk of type 2 diabetes in 5,164 Indians.Diabetes20105982068207410.2337/db09‑1386 20424228
    [Google Scholar]
  90. ReddyB.M. KommojuU.J. SamyS.K. Association of CDKAL1, CDKN2A/B & HHEX gene polymorphisms with type 2 diabetes mellitus in the population of Hyderabad, India.Indian J. Med. Res.2016143445546310.4103/0971‑5916.184303 27377502
    [Google Scholar]
  91. ChidambaramM. RadhaV. MohanV. Replication of recently described type 2 diabetes gene variants in a South Indian population.Metabolism201059121760176610.1016/j.metabol.2010.04.024 20580033
    [Google Scholar]
  92. BodhiniD. RadhaV. DharM. NarayaniN. MohanV. The rs12255372(G/T) and rs7903146(C/T) polymorphisms of the TCF7L2 gene are associated with type 2 diabetes mellitus in Asian Indians.Metabolism20075691174117810.1016/j.metabol.2007.04.012 17697858
    [Google Scholar]
  93. ChandakG.R. JanipalliC.S. BhaskarS. Common variants in the TCF7L2 gene are strongly associated with type 2 diabetes mellitus in the Indian population.Diabetologia2006501636710.1007/s00125‑006‑0502‑2 17093941
    [Google Scholar]
  94. TabassumR. ChauhanG. DwivediO.P. Genome-wide association study for type 2 diabetes in Indians identifies a new susceptibility locus at 2q21.Diabetes201362397798610.2337/db12‑0406 23209189
    [Google Scholar]
  95. KommojuU.J. MarudaJ. KadarkaraiS. No detectable association of IGF2BP2 and SLC30A8 genes with type 2 diabetes in the population of Hyderabad, India.Meta Gene20131152310.1016/j.mgene.2013.09.003 25606370
    [Google Scholar]
  96. SaxenaR. SaleheenD. BeenL.F. Genome-wide association study identifies a novel locus contributing to type 2 diabetes susceptibility in Sikhs of Punjabi origin from India.Diabetes20136251746175510.2337/db12‑1077 23300278
    [Google Scholar]
  97. PhaniN.M. VohraM. RajeshS. Implications of critical PPARγ2, ADIPOQ and FTO gene polymorphisms in type 2 diabetes and obesity-mediated susceptibility to type 2 diabetes in an Indian population.Mol. Genet. Genomics2016291119320410.1007/s00438‑015‑1097‑4 26243686
    [Google Scholar]
  98. RyukJ.A. ZhangX. KoB.S. DailyJ.W. ParkS. Association of β3-adrenergic receptor rs4994 polymorphisms with the risk of type 2 diabetes: A systematic review and meta-analysis.Diabetes Res. Clin. Pract.2017129869610.1016/j.diabres.2017.03.034 28521197
    [Google Scholar]
  99. GuptaV. VinayD.G. RafiqS. Association analysis of 31 common polymorphisms with type 2 diabetes and its related traits in Indian sib pairs.Diabetologia201255234935710.1007/s00125‑011‑2355‑6 22052079
    [Google Scholar]
  100. LalrohluiF. SharmaV. SharmaI. MACF1 gene variant rs2296172 is associated with T2D susceptibility in Mizo population from Northeast India.Int. J. Diabetes Dev. Ctries.202040222322610.1007/s13410‑019‑00788‑1
    [Google Scholar]
  101. BainsV. KaurH. BadaruddozaB. Association analysis of polymorphisms in LEP (rs7799039 and rs2167270) and LEPR (rs1137101) gene towards the development of type 2 diabetes in North Indian Punjabi population.Gene202075414484610.1016/j.gene.2020.144846 32512158
    [Google Scholar]
  102. MatharooK. AroraP. BhanwerA.J.S. Association of adiponectin (AdipoQ) and sulphonylurea receptor (ABCC8) gene polymorphisms with Type 2 Diabetes in North Indian population of Punjab.Gene2013527122823410.1016/j.gene.2013.05.075 23764562
    [Google Scholar]
  103. NairA.K. SugunanD. KumarH. AnilkumarG. Case-control analysis of SNPs in GLUT4, RBP4 and STRA6: Association of SNPs in STRA6 with type 2 diabetes in a South Indian population.PLoS One201057e1144410.1371/journal.pone.0011444 20625434
    [Google Scholar]
  104. SharmaR. MatharooK. KapoorR. ChopraH. BhanwerA. Ethnic differences in CAPN10 SNP-19 in type 2 diabetes: A North-West Indian case control study and evidence from meta-analysis.Genet. Res.201395514615510.1017/S0016672313000207 24429295
    [Google Scholar]
  105. BelosludtsevK.N. BelosludtsevaN.V. DubininM.V. Diabetes mellitus, mitochondrial dysfunction and Ca2+-dependent permeability transition pore.Int. J. Mol. Sci.20202118655910.3390/ijms21186559 32911736
    [Google Scholar]
  106. MurphyR. TurnbullD.M. WalkerM. HattersleyA.T. Clinical features, diagnosis and management of maternally inherited diabetes and deafness (MIDD) associated with the 3243AG mitochondrial point mutation.Diabet. Med.200825438339910.1111/j.1464‑5491.2008.02359.x 18294221
    [Google Scholar]
  107. van den OuwelandJ.M.W. LemkesH.H.P.J. RuitenbeekW. Mutation in mitochondrial tRNALeu(UUR) gene in a large pedigree with maternally transmitted type II diabetes mellitus and deafness.Nat. Genet.19921536837110.1038/ng0892‑368 1284550
    [Google Scholar]
  108. YeeM.L. WongR. DattaM. Mitochondrial disease: An uncommon but important cause of diabetes mellitus.Endocrinol. Diabetes Metab. Case Rep.2018201818009110.1530/EDM‑18‑0091 30306776
    [Google Scholar]
  109. LowellB.B. ShulmanG.I. Mitochondrial dysfunction and type 2 diabetes.Science2005307570838438710.1126/science.1104343 15662004
    [Google Scholar]
  110. Vijaya PadmaV. AnithaS. SanthiniE. Mitochondrial and nuclear gene mutations in the type 2 diabetes patients of Coimbatore population.Mol. Cell. Biochem.20103451-222322910.1007/s11010‑010‑0576‑5 20730618
    [Google Scholar]
  111. DuraisamyP. ElangoS. VishwanandhaV.P. BalamuruganR. Prevalence of mitochondrial tRNA gene mutations and their association with specific clinical phenotypes in patients with type 2 diabetes mellitus of Coimbatore.Genet. Test. Mol. Biomarkers2010141495510.1089/gtmb.2009.0024 20143911
    [Google Scholar]
  112. BhatA. KoulA. SharmaS. The possible role of 10398A and 16189C mtDNA variants in providing susceptibility toT2DM in two North Indian populations: A replicative study.Hum. Genet.2007120682182610.1007/s00439‑006‑0272‑4 17066297
    [Google Scholar]
  113. LalrohluiF. ZohmingthangaJ. hruaii V, Kumar NS. Genomic profiling of mitochondrial DNA reveals novel complex gene mutations in familial type 2 diabetes mellitus individuals from Mizo ethnic population, Northeast India.Mitochondrion20205171410.1016/j.mito.2019.12.001 31862415
    [Google Scholar]
  114. SharmaV. SharmaI. SinghV.P. mtDNA G10398A variation provides risk to type 2 diabetes in population group from the Jammu region of India.Meta Gene2014226927310.1016/j.mgene.2014.02.003 25606409
    [Google Scholar]
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