Type 2 diabetes heritability in the Tehran families: Tehran cardiometabolic genetic study

References

• 1.
  Karimi R, Nezhadali M, Hedayati M. Association of visfatin gene polymorphism rs4730153 with anthropometric characteristics, visfatin level, insulin resistance and lipid metabolism in Iranian diabetic/pre-diabetic population. Koomesh 2021; 23: 541-547. (Persian).##https://doi.org/10.52547/koomesh.23.5.541.
• 2.
  Mtiraoui N, Turki A, Nemr R, Echtay A, Izzidi I, Al-Zaben GS, et al. Contribution of common variants of ENPP1, IGF2BP2, KCNJ11, MLXIPL, PPAR, SLC30A8 and TCF7L2 to the risk of type 2 diabetes in Lebanese and Tunisian Arabs. Diabetes Metab 2012; 38: 444-449.
• 3.
  Hosseinpour-Niazi S, Bakhshi B, Zahedi AS, Akbarzadeh M, Daneshpour MS, Mirmiran P, et al. TCF7L2 polymorphisms, nut consumption, and the risk of metabolic syndrome: a prospective population based study. Nutr Metab (Lond) 2021; 18: 1-11.
• 4.
  Khan IA, Poornima S, Jahan P, Rao P, Hasan Q. Type 2 diabetes mellitus and the association of candidate genes in Asian Indian population from Hyderabad, India. J Clin Diagnos Res 2015; 9: GC01.
• 5.
  Zahedi AS, Akbarzadeh M, Sedaghati-Khayat B, Seyedhamzehzadeh A, Daneshpour MS. GCKR common functional polymorphisms are associated with metabolic syndrome and its components: a 10-year retrospective cohort study in Iranian adults. Diabetol Metab Syndr 2021; 13: 1-10.
• 6.
  Alharbi KK, Abudawood M, Khan IA. Amino-acid amendment of Arginine-325-Tryptophan in rs13266634 genetic polymorphism studies of the SLC30A8 gene with type 2 diabetes-mellitus patients featuring a positive family history in the Saudi population. J King Saud Univ 2021; 33: 101258.##https://doi.org/10.1016/j.jksus.2020.101258.
• 7.
  Daneshpour MS, Hedayati M, Sedaghati-Khayat B, Guity K, Zarkesh M, Akbarzadeh M, et al. Genetic identification for non-communicable disease: Findings from 20 years of the Tehran Lipid and Glucose Study. Int J Endocrinol Metab 2018; 16: e84744.
• 8.
  Gopalakrishnan S, Geetha ARU. Study on the impact of family history of diabetes among type 2 diabetes mellitus patients in an urban area of Kancheepuram district, Tamil Nadu. Int J Commun Med Public Health 2017; 4.##https://doi.org/10.18203/2394-6040.ijcmph20174819.
• 9.
  Guttmacher AE, Collins FS, Carmona RH. The family history-more important than ever. N Engl J Med 2004; 351: 2333-2336.
• 10.
  Najafipour M, Zareizadeh M, Najafipour F. Epidemiologic study of familial type 2 diabetes in Tehran. J Adv Pharm Technol Res 2018; 9: 56.
• 11.
  Whitford DL, McGee H, O'Sullivan B. Will people with type 2 diabetes speak to family members about health risk? Diabetes Care 2009; 32: 251-253.
• 12.
  Balkau B, Roussel R, Wagner S, Tichet J, Froguel P, Fagherazzi G, et al. Transmission of Type 2 diabetes to sons and daughters: the DESIR cohort. Diabet Med 2017; 34: 1615-1622.
• 13.
  Prasad RB, Groop L. Genetics of type 2 diabetes-pitfalls and possibilities. Genes (Basel) 2015; 6: 87-123.
• 14.
  Doustmohamadian S, Kia NS, Fatahi S. Associated factors of poor glycemic control in Iranian diabetic patients TT, Koomesh 2021; 23: 372-378. (Persian).
• 15.
  Alharbi KK, Al-Sulaiman AM, Bin Shedaid MK, Al-Shangiti AM, Marie M, Al-Sheikh YA, et al. MTNR1B genetic polymorphisms as risk factors for gestational diabetes mellitus: a case-control study in a single tertiary care center. Ann Saudi Med 2019; 39: 309-318.
• 16.
  Yap CX, Sidorenko J, Wu Y, Kemper KE, Yang J, Wray NR, et al. Dissection of genetic variation and evidence for pleiotropy in male pattern baldness. Nat Commun 2018; 9: 1-12.
• 17.
  Yang J, Zeng J, Goddard ME, Wray NR, Visscher PM. Concepts, estimation and interpretation of SNP-based heritability. Nat Genet 2017; 49: 1304-1310.
• 18.
  Konigsberg LW. Quantitative variation and genetics. In: Human Biology: An Evolutionary and Biocultural Perspective: Second Edition. John Wiley Sons 2012; p. 143-73.##https://doi.org/10.1002/9781118108062.ch5.
• 19.
  Daneshpour MS, Fallah MS, Sedaghati-Khayat B, Guity K, Khalili D, Hedayati M, et al. Rationale and design of a genetic study on cardiometabolic risk factors: protocol for the Tehran cardiometabolic genetic study (TCGS). JMIR Res Protoc 2017; 6: e28.
• 20.
  Azizi F, Madjid M, Rahmani M, Emami H, Mirmiran P, Hadjipour R. Tehran Lipid and Glucose Study (TLGS): rationale and design. 2000. (Persian).
• 21.
  Buse JB, Wexler DJ, Tsapas A, Rossing P, Mingrone G, Mathieu C, et al. 2019 update to: Management of hyperglycaemia in type 2 diabetes, 2018. A consensus report by the American Diabetes Association (ADA) and the European Association for the Study of Diabetes (EASD). Diabetologia 2020; 63: 221-228.
• 22.
  Elston RC, Gray-McGuire C. A review of the'Statistical Analysis for Genetic Epidemiology'(SAGE) software package. Hum Genomics 2004; 1: 1-4.
• 23.
  Rainer J, Taliun D, D'Elia Y, Pattaro C, Domingues FS, Weichenberger CX. FamAgg: an R package to evaluate familial aggregation of traits in large pedigrees. Bioinformatics 2016; 32: 1583-1585.
• 24.
  Team RC. R: A language and environment for statistical computing. 2013.
• 25.
  Ramezankhani A, Harati H, Bozorgmanesh M, Tohidi M, Khalili D, Azizi F, et al. Diabetes mellitus: findings from 20 years of the Tehran lipid and glucose study. Int J Endocrinol Metab 2018; 16.##https://doi.org/10.5812/ijem.84784.
• 26.
  Zhao JH. gap: Genetic analysis package. J Stat Softw 2007; 23: 1-18.
• 27.
  Akbarzadeh M, Dehkordi SR, Roudbar MA, Sargolzaei M, Guity K, Sedaghati-Khayat B, et al. GWAS findings improved genomic prediction accuracy of lipid profile traits: Tehran Cardiometabolic Genetic Study. Sci Rep 2021; 11: 1-9.
• 28.
  de Los Campos G, Vazquez AI, Fernando R, Klimentidis YC, Sorensen D. Prediction of complex human traits using the genomic best linear unbiased predictor. PLoS Genet 2013; 9: e1003608.
• 29.
  Gelman A, Rubin DB. Inference from iterative simulation using multiple sequences. Stat Sci 1992; 7: 457-472.##https://doi.org/10.1214/ss/1177011136.
• 30.
  Ziegler A, Konig IR, Pahlke F. A Statistical Approach to Genetic Epidemiology: Concepts and Applications, with an E-learning platform. John Wiley & Sons; 2010.##https://doi.org/10.1002/9783527633654.
• 31.
  Go RC, Elston RC, Kaplan EB. Efficiency and robustness of pedigree segregation analysis. Am J Hum Genet 1978; 30: 28.
• 32.
  Zavala C, Morton NE, Rao DC, Lalouel JM, Gamboa IA, Tejeda A, et al. Complex segregation analysis of diabetes mellitus. Hum Hered 1979; 29: 325-333.
• 33.
  Green A, Morton NE, Iselius L, Svejgaard A, Platz P, Ryder LP, et al. Genetic studies of insulindependent diabetes mellitus: segregation and linkage analyses. Tissue Antigens 1982; 19: 213-221.
• 34.
  Turner RC, Hattersley AT, Shaw JT, Levy JC. Type II diabetes: clinical aspects of molecular biological studies. Diabetes 1995; 44: 1-10.
• 35.
  Hanson RL, Elston RC, Pettitt DJ, Bennett PH, Knowler WC. Segregation analysis of non-insulin-dependent diabetes mellitus in Pima Indians: evidence for a major-gene effect. Am J Hum Genet 1995; 57: 160.
• 36.
  Ramezankhani A, Guity K, Azizi F, Hadaegh F. Sex differences in the association between spousal metabolic risk factors with incidence of type 2 diabetes: a longitudinal study of the Iranian population. Biol Sex Differ 2019; 10: 1-8.
• 37.
  Swan HJC. The framingham offspring study: A commentary. J Am Coll Cardiol 2000; 35: 13B-17B.##https://doi.org/10.1016/S0735-1097(00)80065-0.
• 38.
  Lyssenko V, Groop L, Prasad RB. Genetics of type 2 diabetes: it matters from which parent we inherit the risk. Rev Diabet Stud RDS 2015; 12: 233.
• 39.
  Uusitupa MI, Stankov A, Peltonen M, Eriksson JG, Lindstrm J, Aunola S, et al. Impact of positive family history and genetic risk variants on the incidence of diabetes: the Finnish Diabetes Prevention Study. Diabetes Care 2011; 34: 418-423.
• 40.
  Li JK, Ng MC, So WY, Chiu CK, Ozaki R, Tong PC, et al. Phenotypic and genetic clustering of diabetes and metabolic syndrome in Chinese families with type 2 diabetes mellitus. Diabetes Metab Res Rev 2006; 22: 46-52.
• 41.
  De Silva SN, Weerasuriya N, De Alwis NM, De Silva MW, Fernando DJ. Excess maternal transmission and familial aggregation of Type 2 diabetes in Sri Lanka. Diabetes Res Clin Pract 2002; 58: 173-177.
• 42.
  Rahim M, Rahim M, Rahim M, Sharafat S, Shaikh Z, Mamsa S, et al. Maternal and paternal transmission of diabetes: influence of nutritional factors. J Diabetes Metab 2015; 6.##https://doi.org/10.4172/2155-6156.1000504.
• 43.
  Anokute CC. Suspected synergism between consanguinity and familial aggregation in type 2 diabetes mellitus in Saudi Arabia. J R Soc Health 1992; 112: 167-169.
• 44.
  Al-Sinani S, Al-Shafaee M, Al-Mamari A, Woodhouse N, Al-Shafie O, Hassan M, et al. Familial clustering of type 2 diabetes among Omanis. Oman Med J 2014; 29: 51.
• 45.
  Bener A, Yousafzai MT, Al-Hamaq AO. Familial aggregation of T2DM among Arab diabetic population. Int J Diabetes Dev Ctries 2012; 32: 90-92.##https://doi.org/10.1007/s13410-012-0071-5.
• 46.
  Asamoah EA, Obirikorang C, Acheampong E, Annani-Akollor ME, Laing EF, Owiredu EW, et al. Heritability and genetics of type 2 diabetes mellitus in sub-saharan africa: a systematic review and meta-analysis. J Diabetes Res 2020; 2020.
• 47.
  Yang J, Benyamin B, McEvoy BP, Gordon S, Henders AK, Nyholt DR, et al. Common SNPs explain a large proportion of the heritability for human height. Nat Genet 2010; 42: 565-569.
• 48.
  Akbarzadeh M, Moghimbeigi A, Morris N, Daneshpour MS, Mahjub H, Soltanian AR. A Bayesian structural equation model in general pedigree data analysis. Stat Anal Data Min ASA Data Sci J 2019; 12: 404-411.