Ассоциация полиморфизмов генов TCF7L2, FABP2, KCNQ1, ADIPOQ с прогнозом развития сахарного диабета 2-го типа
________________________________________________
For citation: Mel'nikova E.S., Rymar O.D., Ivanova A.A., et al. Therapeutic Archive. 2020; 92 (10): 40–47. DOI: 10.26442/00403660.2020.10.000393
Материалы доступны только для специалистов сферы здравоохранения. Авторизуйтесь или зарегистрируйтесь.
Материалы и методы. На основе проспективного наблюдения репрезентативной популяционной выборки жителей Новосибирска (HAPIEE) сформированы 2 группы по принципу «случай–контроль» (случай – лица, у которых за 10 лет наблюдения выявлен СД 2, и контроль – лица, у которых за 10-летний период не развились нарушения углеводного обмена). Группа СД 2 (n=443, средний возраст 56,2±6,7 года, мужчины – 29,6%, женщины – 70,4%), группа контроля (n=532, средний возраст 56,1±7,1 года, мужчины – 32,7%, женщины – 67,3%). ДНК выделена методом фенол-хлороформной экстракции. Генотипирование выполнено методом полимеразной цепной реакции с последующим анализом полиморфизма длин рестрикционных фрагментов, полимеразной цепной реакции с обратной транскрипцией. Статистическая обработка проведена с использованием программного пакета SPSS 16.0.
Результаты и обсуждение. Не обнаружено значимого влияния rs1799883 гена FABP2, rs2237892 гена KCNQ1 и rs6773957 гена ADIPOQ на риск развития СД 2. Генотипы ТТ и TC rs7903146 гена TCF7L2 являются генотипами риска развития СД 2 (относительный риск – ОР 3,90, 95% доверительный интервал – ДИ 2,31–6,61, р<0,001; ОР 1,86, 95% ДИ 1,42–2,43, р<0,001 соответственно). Генотип СС rs7903146 гена TCF7L2 ассоциирован с протективным эффектом в отношении СД 2 (ОР 0,37, 95% ДИ 0,29–0,49, р<0,001). При включении в модель оценки риска развития СД 2 rs7903146 гена TCF7L2 он сохраняет свою значимость и у мужчин, и у женщин.
Заключение. Полиморфизм rs7903146 гена TCF7L2 подтвердил свою ассоциацию с прогнозом развития СД 2, что указывает на возможность его рассмотрения в качестве кандидата на внесение в рискометр СД 2. Разработаны варианты рискометров для оценки прогноза развития СД 2 у мужчин и женщин в возрасте 45–69 лет в течение 10 лет наблюдения. Ассоциация с прогнозом развития СД 2 полиморфизмов rs1799883 гена FABP2, rs2237892 гена KCNQ1 и rs6773957 гена ADIPOQ – не обнаружена.
Ключевые слова: сахарный диабет 2-го типа, однонуклеотидный полиморфизм, rs7903146, TCF7L2, rs1799883, FABP2, rs2237892, KCNQ1, rs6773957, ADIPOQ, прогноз, рискометр.
________________________________________________
Aim. To study the possibility of using polymorphisms of genes TCF7L2, FABP2, KCNQ1, ADIPOQ as markers for predicting the development of type 2 diabetes mellitus (T2D) in the population of Novosibirsk.
Materials and methods. On the basis of prospective observation of a representative population sample of residents of Novosibirsk (HAPIEE), 2 groups were formed according to the “case-control” principle (case – people who had diabetes mellitus 2 over 10 years of observation, and control – people who did not developed disorders of carbohydrate metabolism). T2D group (n=443, mean age 56.2±6.7 years, men – 29.6%, women – 70.4%), control group (n=532, mean age 56.1±7.1 years, men – 32.7%, women – 67.3%). DNA was isolated by phenol-chloroform extraction. Genotyping was performed by the method of polymerase chain reaction with subsequent analysis of restriction fragment length polymorphism, polymerase chain reaction in real time. Statistical processing was carried out using the SPSS 16.0 software package.
Results and discussion. No significant effect of rs1799883 of the FABP2 gene, rs2237892 of the KCNQ1 gene, and rs6773957 of the ADIPOQ gene on the risk of developing T2D was found. Genotypes TT and TC rs7903146 of the TCF7L2 gene are genotypes for the risk of developing T2D (relative risk – RR 3.90, 95% confidence interval – CI 2.31–6.61, p<0.001; RR 1.86, 95% CI 1.42–2.43, p<0.001, respectively). The CC genotype rs7903146 of the TCF7L2 gene is associated with a protective effect against T2D (RR 0.37, 95% CI 0.29–0.49, p<0.001). When the TCF7L2 gene is included in the model for assessing the risk of developing T2D rs7903146, it retains its significance in both men and women.
Conclusion. The rs7903146 polymorphism of the TCF7L2 gene confirmed its association with the prognosis of the development of T2D, which indicates the possibility of considering it as a candidate for inclusion in a diabetes risk meter. Variants of risk meters have been developed to assess the prognosis of the development of diabetes mellitus 2 in men and women aged 45–69 years during 10 years of follow-up. The association with the prognosis of the development of T2D polymorphisms rs1799883 of the FABP2 gene, rs2237892 of the KCNQ1 gene and rs6773957 of the ADIPOQ gene was not found.
Key words: type 2 diabetes mellitus, single nucleotide polymorphism, rs7903146, TCF7L2, rs1799883, FABP2, rs2237892, KCNQ1, rs6773957, ADIPOQ, prognosis, risk meter.
2. Воевода М.И., Иванова А.А., Шахтшнейдер Е.В. и др. Молекулярная генетика MODY. Терапевтический архив. 2016;88(4):117-24 [Voevoda MI, Ivanova AA, Shahtshnejder EV, et al. Molekular genetics of maturity-onset diabetes of the young. Therapeutic Arhive. 2016;88(4):117-24 (In Russ.)]. doi: 10.17116/terarkh2016884117-124
3. OMIM. Accessed May 14, 2019. http://omim.org/
4. HuGE Navigator. Accessed May 14, 2019. http://www.cdc.gov/genomics/hugenet/hugenavigator.htm
5. Sikhayeva N, Iskakova A, Saigi-Morgui N, et al. Association between 28 single nucleotide polymorphisms and type 2 diabetes mellitus in the Kazakh population: a case-control study. BMC medical genetics. 2017;18(1):76. doi: 10.1186/s12881-017-0443-2
6. Мустафина С.В., Симонова Г.И., Рымар О.Д. Сравнительная характеристика шкал риска сахарного диабета 2 типа. Сахарный диабет. 2014;3:17-22. [Mustafina SV, Simonova GI, Rymar OD. Comparative characteristics of diabetes risk scores. Diabetes Mellitus. 2014;3:17-22 (In Russ.)]. doi: 10.14341/DM2014317-22
7. Wang J, Stancáková A, Kuusisto J, Laakso M. Identification of undiagnosed type 2 diabetic individuals by the finnish diabetes risk score and biochemical and genetic markers: a population-based study of 7232 Finnish men. J Clin Endocrin Metab. 2010;95(8):3858-62. doi: 10.1210/ jc.2010-0012
8. Мустафина С.В., Рымар О.Д., Сазонова О.В. и др. Валидизация финской шкалы риска «FINDRISC» на европеоидной популяции Сибири. Сахарный диабет. 2016;19(2):113-8 [Mustafina SV, Rymar OD, Sazonova OV, et al. Validation of the Finnish diabetes risk score (FINDRISC) for the Caucasian population of Siberia. Diabetes Mellitus. 2016;19(2):113-8 (In Russ.)]. doi: 10.14341/DM200418-10
9. Mühlenbruch K, Jeppesen C, Joost HG, et al. The value of genetic information for diabetes risk prediction – differences according to sex, age, family history and obesity. PLoS One. 2013;8(5):e64307. doi: 10.1371/journal.pone.0064307
10. Goto A, Noda M, Goto M, et al.; JPHC Study Group. Predictive performance of a genetic risk score using 11 susceptibility alleles for the incidence of Type 2 diabetes in a general Japanese population: a nested case-control study. Diabetic Med: J British Diabetic Assotiation. 2018;35(5):602-11. doi: 10.1111/dme.13602
11. Lin X, Song K, Lim N, et al. Risk prediction of prevalent diabetes in a Swiss population using a weighted genetic score – the CoLaus Study. Diabetologia. 2009;52(4):600-8. doi: 10.1007/s00125-008-1254-y
12. Meigs JB, Shrader P, Sullivan LM, et al. Genotype score in addition to common risk factors for prediction of type 2 diabetes. N Engl J Med. 2008;359(21):2208-19. doi: 10.1056/NEJMoa0804742
13. Lyssenko V, Jonsson A, Almgren P, et al. Clinical risk factors, DNA variants, and the development of type 2 diabetes. N Engl J Med. 2008;359(21):2220-32. doi: 10.1056/NEJMoa0801869
14. Abbas S, Raza ST, Chandra A, et al. Association of ACE, FABP2 and GST genes polymorphism with essential hypertension risk among a North Indian population. Ann Hum Biol. 2015;42(5):461-9. doi: 10.3109/03014460.2014.968206
15. Орлов П.С., Иванощук Д.Е., Михайлова С.В. и др. Исследование ассоциаций новых генетических маркеров сахарного диабета второго типа на Западно-Сибирской популяции европеоидов. Сибирский научный мед. журн. 2015;35(2):74-9 [Orlov PS, Ivanoshchuk DI, Mikhaylova SV, et al. Association study of new genetic markers of type 2 diabets mellitus in West Siberian Caucasian population. Sibirskii nauchnyi med. zhurn. 2015;35(2):74-9 (In Russ.)].
16. Ding W, Xu L, Zhang L, et al. Meta-analysis of association between TCF7L2 polymorphism rs7903146 and type 2 diabetes mellitus. BMC Med Genetics. 2018;19(1):38. doi: 10.1186/s12881-018-0553-5
17. Grant SF, Thorleifsson G, Reynisdottir I, et al. Variant of transcription factor 7-like 2 (TCF7L2) gene confers risk of type 2 diabetes. Nat Genetics 2006;38(3):320-3. doi: 10.1038/ng1732
18. Cauchi S, Meyre D, Choquet H, et al.; DESIR Study Group. Transcription factor TCF7L2 genetic study in the french population. Diabetes. 2006;55(10):2903-8. doi: 10.2337/db06-0474
19. Yan Y, North KE, Ballantyne CM, et al. Transcription factor 7-like 2 (TCF7L2) polymorphism and context-specific risk of type 2 diabetes in african american and caucasian adults the atherosclerosis risk in communities study. Diabetes. 2009;58(1):285-9. doi: 10.2337/db08-0569
20. Horikoshi M, Hara K, Ito C, et al. A genetic variation of the transcription factor 7-like 2 gene is associated with risk of type 2 diabetes in the Japanese population. Diabetologia. 2007;50(4):747-51. doi: 10.1007/s00125-006-0588-6
21. Barra GB, Dutra LAS, Watanabe S, et al. Association of the rs7903146 single nucleotide polymorphism at the transcription factor 7-like 2 (TCF7L2) locus with type 2 diabetes in brazilian subjects. Arq Bras Endocrinol Metabol. 2012;56(8):479-84. doi: 10.1590/S0004-27302012000800003
22. Meng Q, Ge S, Yan W, et al. Screening for potential serum-based proteomic biomarkers for human type 2 diabetes mellitus using maldi-tof ms. Proteomics. Clin Applicat. 2017;11(3-4). doi: 10.1002/prca.201600079
23. Бондарь И.А., Филипенко М.Л., Шабельникова О.Ю., Соколова Е.А. Ассоциация полиморфных маркеров rs7903146 гена TCF7L2 и rs1801282 гена PPARG (PRO12ALA) с сахарным диабетом 2 типа в Новосибирской области. Сахарный диабет. 2013;4:17-22 [Bondar' IA, Filipenko ML, Shabel'nikova OJu, Sokolova EA. Rs7903146 variant of TCF7L2 gene and rs18012824 variant of PPARG2 gene (Pro12Ala) are associated with type 2 diabetes mellitus in Novosibirsk population. Diabetes Mellitus. 2013;4:17-22 (In Russ.)]. doi: 10.14341/dm2013417-22
24. World Health Organization. Fact files: ten facts on obesity. 2016. Accessed May 14, 2019. https://www.who.int/features/factfiles/obesity/en/
25. Qiu CJ, Ye XZ, Yu XJ, et al. Association between FABP2 Ala54Thr polymorphisms and type 2 diabetes mellitus risk: a HuGE Review and Meta-Analysis. J Cell Molecul Med. 2014;18(12):2530-5. doi: 10.1111/jcmm.12385
26. Liu Y, Wu G, Han L, et al. Association of the FABP2 Ala54Thr polymorphism with type 2 diabetes, obesity, and metabolic syndrome: a population-based case-control study and a systematic meta-analysis. Genetics and molecular research: GMR. 2015;14(1):1155-68. doi: 10.4238/2015
27. Zhao T, Zhao J, Yang W. Association of the fatty acid-binding protein 2 gene Ala54Thr polymorphism with insulin resistance and blood glucose: a meta-analysis in 13451 subjects. Diabetes/metabolism Res Rev. 2010;26(5):357-64. doi: 10.1002/dmrr.1085
28. Li YY, Wang XM, Lu XZ. KCNQ1 rs2237892 C→T gene polymorphism and type 2 diabetes mellitus in the Asian population: a meta-analysis of 15,736 patients. J Cell Molecul Med. 2014;18(2):274-82. doi: 10.1111/jcmm.12185.
29. Liu Y, Zhou DZ, Zhang D, et al. Variants in KCNQ1 are associated with susceptibility to type 2 diabetes in the population of mainland China. Diabetologia. 2009;52(7):1315-21. doi: 10.1007 / s00125-009-1375-y
30. Han X, Luo Y, Ren Q, et al. Implication of genetic variants near SLC30A8, HHEX, CDKAL1, CDKN2A/B, IGF2BP2, FTO, TCF2, KCNQ1, and WFS1 in type 2 diabetes in a Chinese population. BMC Med Genetics. 2010;11:81. doi: 10.1186/1471-2350-11-81
31. Unoki H, Takahashi A, Kawaguchi T, et al. SNPs in KCNQ1 are associated with susceptibility to type 2 diabetes in East Asian and European populations. Nat Genetics. 2008;40(9):1098-102. doi: 10.1038/ng.208
32. Jonsson AA, Isomaa B, Tuomi T, et al. Variant in the KCNQ1 gene predicts future type 2 diabetes and mediates impaired insulin secretion. Diabetes. 2009;58(10):2409-13. doi: 10.2337/db09-0246
33. Hu C, Wang C, Zhang R, et al. Variations in KCNQ1 are associated with type 2 diabetes and beta cell function in a Chinese population. Diabetologia. 2009;52(7):1322-5. doi: 10.1007/s00125-009-1335-6
34. Zhou Q, Chen B, Ji T, et al. Association of genetic variants in RETN, NAMPT and ADIPOQ gene with glycemic, metabolic traits and diabetes risk in a Chinese population. Gene. 2018;642:439-46. doi: 10.1016/j.gene.2017.10.084
35. Qian Y, Dong M, Lu F, et al. Joint effect of CENTD2 and KCNQ1 polymorphisms on the risk of type 2 diabetes mellitus among Chinese Han population. Mol Cell Endocrinol. 2015;407:46-51. doi: 10.1016/j.mce.2015.02.026
36. Lee YH, Kang ES, Kim SH, et al. Association between polymorphisms in SLC30A8, HHEX, CDKN2A/B, IGF2BP2, FTO, WFS1, CDKAL1, KCNQ1 and type 2 diabetes in the Korean population. J Hum Genetics. 2008;53(11-12):991-8. doi: 10.1007/s10038-008-0341-8
37. Yasuda K, Miyake K, Horikawa Y, et al. Variants in KCNQ1 are associated with susceptibility to type 2 diabetes mellitus. Nat Genetics. 2008;40(9):1092-7. doi: 10.1038/ng.207
38. Mussig K, Staiger H, Machicao F, et al. Association of type 2 diabetes candidate polymorphisms in KCNQ1 with incretin and insulin secretion. Diabetes. 2009;58(7):1715-20. doi: 10.2337/db08-1589
39. Been LF, Ralhan S, Wander GS, et al. Variants in KCNQ1 increase type II diabetes susceptibility in South Asians: a study of 3,310 subjects from India and the US. BMC Med Genetics. 2011;12:18. doi: 10.1186/1471-2350-12-18
40. Chu H, Wang M, Zhong D, et al. ADIPOQ polymorphisms are associated with type 2 diabetes mellitus: a meta-analysis study. Diabetes Metab Res Rev. 2013;29(7):532-45. doi: 10.1002/dmrr.2424
41. Goto A, Noda M, Goto M, et al.; JPHC Study Group. Plasma adiponectin levels, ADIPOQ variants, and incidence of type 2 diabetes: A nested case-control study. Diabetes Res Clin Pract. 2017;127:256-64. doi: 10.1016/j.diabres.2017.03.020
42. Ramya K, Ayyappa KA, Ghosh S, et al. Genetic association of ADIPOQ gene variants with type 2 diabetes, obesity and serum adiponectin levels in south Indian population. Gene. 2013;532(2):253-62. doi: 10.1016/j.gene.2013.09.012
43. Малютина С.К., Максимов В.Н., Орлов П.С. и др. Ассоциации артериального давления и артериальной гипертензии с генетическими маркерами, отобранными по данным полногеномных исследований. Рус. журн. кардиологии. 2018;23(10):8–13 [Malyutina SK, Maksimov VN, Orlov PS, et al. The association of blood pressure and hypertension with genetic markers identified in genome-wide association studies. Russian Journal of Cardiology. 2018;23(10):8–13 (In Russ.)]. doi: 10.15829/1560-4071-2018-10-8-13
44. Menzaghi C, Salvemini L, Paroni G, et al. Circulating high molecular weight adiponectin isoform is heritable and shares a common genetic background with insulin resistance in nondiabetic White Caucasians from Italy: evidence from a family-based study. J Int Med. 2010;267(3):287-94. doi: 10.1111/j.1365-2796.2009.02141
45. Siitonen N, Pulkkinen L, Lindström J, et al. Association of ADIPOQ gene variants with body weight, type 2 diabetes and serum adiponectin concentrations: the Finnish Diabetes Prevention Study. BMC Med Genetics. 2011;12:5. doi: 10.1186/1471-2350-12-5
________________________________________________
1. Cho NH, Shaw JE, Karuranga S, et al. IDF Diabetes Atlas: Global estimates of diabetes prevalence for 2017 and projections for 2045. Diabet Res Clin Pract. 2018;138:271-81. doi: 10.1016/j.diabres.2018.02.023
2. Воевода М.И., Иванова А.А., Шахтшнейдер Е.В. и др. Молекулярная генетика MODY. Терапевтический архив. 2016;88(4):117-24 [Voevoda MI, Ivanova AA, Shahtshnejder EV, et al. Molekular genetics of maturity-onset diabetes of the young. Therapeutic Arhive. 2016;88(4):117-24 (In Russ.)]. doi: 10.17116/terarkh2016884117-124
3. OMIM. Accessed May 14, 2019. http://omim.org/
4. HuGE Navigator. Accessed May 14, 2019. http://www.cdc.gov/genomics/hugenet/hugenavigator.htm
5. Sikhayeva N, Iskakova A, Saigi-Morgui N, et al. Association between 28 single nucleotide polymorphisms and type 2 diabetes mellitus in the Kazakh population: a case-control study. BMC medical genetics. 2017;18(1):76. doi: 10.1186/s12881-017-0443-2
6. Mustafina SV, Simonova GI, Rymar OD. Comparative characteristics of diabetes risk scores. Diabetes Mellitus. 2014;3:17-22 (In Russ.) doi: 10.14341/DM2014317-22
7. Wang J, Stancáková A, Kuusisto J, Laakso M. Identification of undiagnosed type 2 diabetic individuals by the finnish diabetes risk score and biochemical and genetic markers: a population-based study of 7232 Finnish men. J Clin Endocrin Metab. 2010;95(8):3858-62. doi: 10.1210/ jc.2010-0012
8. Mustafina SV, Rymar OD, Sazonova OV, et al. Validation of the Finnish diabetes risk score (FINDRISC) for the Caucasian population of Siberia. Diabetes Mellitus. 2016;19(2):113-8 (In Russ.) doi: 10.14341/DM200418-10
9. Mühlenbruch K, Jeppesen C, Joost HG, et al. The value of genetic information for diabetes risk prediction – differences according to sex, age, family history and obesity. PLoS One. 2013;8(5):e64307. doi: 10.1371/journal.pone.0064307
10. Goto A, Noda M, Goto M, et al.; JPHC Study Group. Predictive performance of a genetic risk score using 11 susceptibility alleles for the incidence of Type 2 diabetes in a general Japanese population: a nested case-control study. Diabetic Med: J British Diabetic Assotiation. 2018;35(5):602-11. doi: 10.1111/dme.13602
11. Lin X, Song K, Lim N, et al. Risk prediction of prevalent diabetes in a Swiss population using a weighted genetic score – the CoLaus Study. Diabetologia. 2009;52(4):600-8. doi: 10.1007/s00125-008-1254-y
12. Meigs JB, Shrader P, Sullivan LM, et al. Genotype score in addition to common risk factors for prediction of type 2 diabetes. N Engl J Med. 2008;359(21):2208-19. doi: 10.1056/NEJMoa0804742
13. Lyssenko V, Jonsson A, Almgren P, et al. Clinical risk factors, DNA variants, and the development of type 2 diabetes. N Engl J Med. 2008;359(21):2220-32. doi: 10.1056/NEJMoa0801869
14. Abbas S, Raza ST, Chandra A, et al. Association of ACE, FABP2 and GST genes polymorphism with essential hypertension risk among a North Indian population. Ann Hum Biol. 2015;42(5):461-9. doi: 10.3109/03014460.2014.968206
15. Orlov PS, Ivanoshchuk DI, Mikhaylova SV, et al. Association study of new genetic markers of type 2 diabets mellitus in West Siberian Caucasian population. Sibirskii nauchnyi med. zhurn. 2015;35(2):74-9 (In Russ.)
16. Ding W, Xu L, Zhang L, et al. Meta-analysis of association between TCF7L2 polymorphism rs7903146 and type 2 diabetes mellitus. BMC Med Genetics. 2018;19(1):38. doi: 10.1186/s12881-018-0553-5
17. Grant SF, Thorleifsson G, Reynisdottir I, et al. Variant of transcription factor 7-like 2 (TCF7L2) gene confers risk of type 2 diabetes. Nat Genetics 2006;38(3):320-3. doi: 10.1038/ng1732
18. Cauchi S, Meyre D, Choquet H, et al.; DESIR Study Group. Transcription factor TCF7L2 genetic study in the french population. Diabetes. 2006;55(10):2903-8. doi: 10.2337/db06-0474
19. Yan Y, North KE, Ballantyne CM, et al. Transcription factor 7-like 2 (TCF7L2) polymorphism and context-specific risk of type 2 diabetes in african american and caucasian adults the atherosclerosis risk in communities study. Diabetes. 2009;58(1):285-9. doi: 10.2337/db08-0569
20. Horikoshi M, Hara K, Ito C, et al. A genetic variation of the transcription factor 7-like 2 gene is associated with risk of type 2 diabetes in the Japanese population. Diabetologia. 2007;50(4):747-51. doi: 10.1007/s00125-006-0588-6
21. Barra GB, Dutra LAS, Watanabe S, et al. Association of the rs7903146 single nucleotide polymorphism at the transcription factor 7-like 2 (TCF7L2) locus with type 2 diabetes in brazilian subjects. Arq Bras Endocrinol Metabol. 2012;56(8):479-84. doi: 10.1590/S0004-27302012000800003
22. Meng Q, Ge S, Yan W, et al. Screening for potential serum-based proteomic biomarkers for human type 2 diabetes mellitus using maldi-tof ms. Proteomics. Clin Applicat. 2017;11(3-4). doi: 10.1002/prca.201600079
23. Bondar' IA, Filipenko ML, Shabel'nikova OJu, Sokolova EA. Rs7903146 variant of TCF7L2 gene and rs18012824 variant of PPARG2 gene (Pro12Ala) are associated with type 2 diabetes mellitus in Novosibirsk population. Diabetes Mellitus. 2013;4:17-22 (In Russ.) doi: 10.14341/dm2013417-22
24. World Health Organization. Fact files: ten facts on obesity. 2016. Accessed May 14, 2019. https://www.who.int/features/factfiles/obesity/en/
25. Qiu CJ, Ye XZ, Yu XJ, et al. Association between FABP2 Ala54Thr polymorphisms and type 2 diabetes mellitus risk: a HuGE Review and Meta-Analysis. J Cell Molecul Med. 2014;18(12):2530-5. doi: 10.1111/jcmm.12385
26. Liu Y, Wu G, Han L, et al. Association of the FABP2 Ala54Thr polymorphism with type 2 diabetes, obesity, and metabolic syndrome: a population-based case-control study and a systematic meta-analysis. Genetics and molecular research: GMR. 2015;14(1):1155-68. doi: 10.4238/2015
27. Zhao T, Zhao J, Yang W. Association of the fatty acid-binding protein 2 gene Ala54Thr polymorphism with insulin resistance and blood glucose: a meta-analysis in 13451 subjects. Diabetes/metabolism Res Rev. 2010;26(5):357-64. doi: 10.1002/dmrr.1085
28. Li YY, Wang XM, Lu XZ. KCNQ1 rs2237892 C→T gene polymorphism and type 2 diabetes mellitus in the Asian population: a meta-analysis of 15,736 patients. J Cell Molecul Med. 2014;18(2):274-82. doi: 10.1111/jcmm.12185.
29. Liu Y, Zhou DZ, Zhang D, et al. Variants in KCNQ1 are associated with susceptibility to type 2 diabetes in the population of mainland China. Diabetologia. 2009;52(7):1315-21. doi: 10.1007 / s00125-009-1375-y
30. Han X, Luo Y, Ren Q, et al. Implication of genetic variants near SLC30A8, HHEX, CDKAL1, CDKN2A/B, IGF2BP2, FTO, TCF2, KCNQ1, and WFS1 in type 2 diabetes in a Chinese population. BMC Med Genetics. 2010;11:81. doi: 10.1186/1471-2350-11-81
31. Unoki H, Takahashi A, Kawaguchi T, et al. SNPs in KCNQ1 are associated with susceptibility to type 2 diabetes in East Asian and European populations. Nat Genetics. 2008;40(9):1098-102. doi: 10.1038/ng.208
32. Jonsson AA, Isomaa B, Tuomi T, et al. Variant in the KCNQ1 gene predicts future type 2 diabetes and mediates impaired insulin secretion. Diabetes. 2009;58(10):2409-13. doi: 10.2337/db09-0246
33. Hu C, Wang C, Zhang R, et al. Variations in KCNQ1 are associated with type 2 diabetes and beta cell function in a Chinese population. Diabetologia. 2009;52(7):1322-5. doi: 10.1007/s00125-009-1335-6
34. Zhou Q, Chen B, Ji T, et al. Association of genetic variants in RETN, NAMPT and ADIPOQ gene with glycemic, metabolic traits and diabetes risk in a Chinese population. Gene. 2018;642:439-46. doi: 10.1016/j.gene.2017.10.084
35. Qian Y, Dong M, Lu F, et al. Joint effect of CENTD2 and KCNQ1 polymorphisms on the risk of type 2 diabetes mellitus among Chinese Han population. Mol Cell Endocrinol. 2015;407:46-51. doi: 10.1016/j.mce.2015.02.026
36. Lee YH, Kang ES, Kim SH, et al. Association between polymorphisms in SLC30A8, HHEX, CDKN2A/B, IGF2BP2, FTO, WFS1, CDKAL1, KCNQ1 and type 2 diabetes in the Korean population. J Hum Genetics. 2008;53(11-12):991-8. doi: 10.1007/s10038-008-0341-8
37. Yasuda K, Miyake K, Horikawa Y, et al. Variants in KCNQ1 are associated with susceptibility to type 2 diabetes mellitus. Nat Genetics. 2008;40(9):1092-7. doi: 10.1038/ng.207
38. Mussig K, Staiger H, Machicao F, et al. Association of type 2 diabetes candidate polymorphisms in KCNQ1 with incretin and insulin secretion. Diabetes. 2009;58(7):1715-20. doi: 10.2337/db08-1589
39. Been LF, Ralhan S, Wander GS, et al. Variants in KCNQ1 increase type II diabetes susceptibility in South Asians: a study of 3,310 subjects from India and the US. BMC Med Genetics. 2011;12:18. doi: 10.1186/1471-2350-12-18
40. Chu H, Wang M, Zhong D, et al. ADIPOQ polymorphisms are associated with type 2 diabetes mellitus: a meta-analysis study. Diabetes Metab Res Rev. 2013;29(7):532-45. doi: 10.1002/dmrr.2424
41. Goto A, Noda M, Goto M, et al.; JPHC Study Group. Plasma adiponectin levels, ADIPOQ variants, and incidence of type 2 diabetes: A nested case-control study. Diabetes Res Clin Pract. 2017;127:256-64. doi: 10.1016/j.diabres.2017.03.020
42. Ramya K, Ayyappa KA, Ghosh S, et al. Genetic association of ADIPOQ gene variants with type 2 diabetes, obesity and serum adiponectin levels in south Indian population. Gene. 2013;532(2):253-62. doi: 10.1016/j.gene.2013.09.012
43. Malyutina SK, Maksimov VN, Orlov PS, et al. The association of blood pressure and hypertension with genetic markers identified in genome-wide association studies. Russian Journal of Cardiology. 2018;23(10):8–13 (In Russ.) doi: 10.15829/1560-4071-2018-10-8-13
44. Menzaghi C, Salvemini L, Paroni G, et al. Circulating high molecular weight adiponectin isoform is heritable and shares a common genetic background with insulin resistance in nondiabetic White Caucasians from Italy: evidence from a family-based study. J Int Med. 2010;267(3):287-94. doi: 10.1111/j.1365-2796.2009.02141
45. Siitonen N, Pulkkinen L, Lindström J, et al. Association of ADIPOQ gene variants with body weight, type 2 diabetes and serum adiponectin concentrations: the Finnish Diabetes Prevention Study. BMC Med Genetics. 2011;12:5. doi: 10.1186/1471-2350-12-5
1 Научно-исследовательский институт терапии и профилактической медицины – филиал ФГБНУ «Федеральный исследовательский центр Институт цитологии и генетики» Сибирского отделения РАН, Новосибирск, Россия;
2 Отдел эпидемиологии и общественного здоровья Университетского колледжа Лондона, Лондон, Соединенное Королевство
________________________________________________
E.S. Mel'nikova1, O.D. Rymar1, A.A. Ivanova1, S.V. Mustafina1, M.Ju. Shapkina1, M. Bobak2, S.K. Maljutina1, M.I. Voevoda1, V.N. Maksimov1
1 Research Institute of Internal and Preventive Medicine – Branch of the Institute of Cytology and Genetics, Novosibirsk, Russia;
2 Department of Epidemiology & Public Health, University College London, London, United Kingdom