Disorders of carbohydrate metabolism and candidate genes for the pathophysiology of polycystic ovary syndrome. A literature review

Cover Page


Cite item

Full Text

Open Access Open Access
Restricted Access Access granted
Restricted Access Subscription or Fee Access

Abstract

Polycystic ovary syndrome is a common heterogeneous disease with metabolic disorders. In the last decade, the study of polycystic ovary syndrome pathogenesis has been associated with the modern development of molecular genetics, transcriptomics, and sequencing methods. Numerous studies have shown that the study of genetic markers and epigenetic changes in metabolic disorders, oxidative stress, chronic inflammation, and mitochondrial dysfunction in polycystic ovary syndrome is an important direction in the pathogenesis and etiology of the disease. The aim of this literature review was to describe candidate genes involved in the pathophysiology of polycystic ovary syndrome and associated with disorders of carbohydrate metabolism according to modern domestic and foreign literature over the past five years. The candidate gene data presented were assessed based on the main aspects of polycystic ovary syndrome pathophysiology, namely, metabolic dysfunction, androgen and gonadotropin imbalance, and inflammation. The insulin genes (variable number of tandem repeats), such as INS-VNTR, IRS-1, IRS-2, and INSR, adiponectin and calpain-10 genes, as well as CY1A1, CYP11A1, PON1, DENND1A and TCF7L2 genes are associated with metabolic disorders in polycystic ovary syndrome. Genetic variants of genes involved in regulating the expression and mechanism of action of insulin, as well as its receptors and substrates (IRS-1, IRS-2, INSR), have been suggested as possible factors involved in the development and severity of the clinical and metabolic manifestations of polycystic ovary syndrome. The presented data on PPARγ gene (and its coactivator PGC-1α) expression levels in women with polycystic ovary syndrome revealed the presence of PPARγ gene polymorphisms associated with insulin resistance. Thus, the data presented in this review from genome-wide association studies (GWAS) and the study of candidate genes showed that numerous pleiotropic effects cause carbohydrate metabolism disorders in polycystic ovary syndrome. The study of genetic markers and epigenetic changes in the development of metabolic disorders, oxidative stress, chronic inflammation, and mitochondrial dysfunction in polycystic ovary syndrome is an important direction in the pathogenesis of the disease.

Full Text

Restricted Access

About the authors

Elena I. Abashova

The Research Institute of Obstetrics, Gynecology and Reproductology named after D.O. Ott

Author for correspondence.
Email: abashova@yandex.ru
ORCID iD: 0000-0003-2399-3108
SPIN-code: 2133-0310

MD, Cand. Sci. (Med.)

Russian Federation, Saint Petersburg

Maria I. Yarmolinskaya

The Research Institute of Obstetrics, Gynecology and Reproductology named after D.O. Ott

Email: m.yarmolinskaya@gmail.com
ORCID iD: 0000-0002-6551-4147
SPIN-code: 3686-3605

MD, Dr. Sci. (Med.), Professor of the Russian Academy of Sciences

Russian Federation, Saint Petersburg

Natalia S. Osinovskaya

The Research Institute of Obstetrics, Gynecology and Reproductology named after D.O. Ott

Email: natosinovskaya@mail.ru
ORCID iD: 0000-0001-7831-9327
SPIN-code: 3190-2307

Cand. Sci. (Biol.)

Russian Federation, Saint Petersburg

References

  1. Teede HJ, Tay CT, Laven JJE, et al. Recommendations from the 2023 International Evidence-based Guideline for the assessment and management of polycystic ovary syndrome. J Clin Endocrinol Metab. 2023;108(10):2447–2469. doi: 10.1210/clinem/dgad463
  2. Neven ACH, Laven J, Teede HJ, et al. A summary on polycystic ovary syndrome: diagnostic criteria, prevalence, clinical manifestations, and management according to the latest international guidelines. Semin Reprod Med. 2018;36(1):5–12. doi: 10.1055/s-0038-1668085
  3. Rotterdam ESHRE/ASRM-Sponsored PCOS consensus workshop group. Revised 2003 consensus on diagnostic criteria and long-term health risks related to polycystic ovary syndrome (PCOS). Hum Reprod. 2004;19(1):41–47. doi: 10.1093/humrep/deh098
  4. Rossiyskoe obshchestvo akusherov-ginekologov, Rossiyskaya assotsiatsiya endokrinologov. Sindrom polikistoznykh yaichnikov. Klinicheskie rekomendatsii. 2021. (In Russ.) [cited 2023 Nov 5]. Available from: https://roag-portal.ru/recommendations_gynecology
  5. Broskey NT, Tam CS, Sutton EF, et al. Metabolic inflexibility in women with PCOS is similar to women with type 2 diabetes. Nutr Metab (Lond). 2018;15:75. doi: 10.1186/s12986-018-0312-9
  6. Hoeger KM, Dokras A, Piltonen T. Update on PCOS: consequences, challenges, and guiding treatment. J Clin Endocrinol Metab. 2021;106(3):e1071–e1083. doi: 10.1210/clinem/dgaa839
  7. Greenwood EA, Pasch LA, Cedars MI, et al. Insulin resistance is associated with depression risk in polycystic ovary syndrome. Fertil Steril. 2018;110(1):27–34. doi: 10.1016/j.fertnstert.2018.03.009
  8. Abashova EI, Yarmolinskaya MI. Phenotypes of polycystic ovary syndrome in women of reproductive age: clinical picture, diagnosis, therapy strategy. Obstetrics and Gynecology. 2021;(12):4–12. (In Russ.)
  9. Ollila MM, West S, Keinänen-Kiukaanniemi S, et al. Overweight and obese but not normal weight women with PCOS are at increased risk of type 2 diabetes mellitus-a prospective, population-based cohort study. Hum Reprod. 2017;32(2):423–431. doi: 10.1093/humrep/dew329
  10. Cassar S., Misso M., Shaw C., et al. Insulin resistance in polycystic ovary syndrome: a systematic review and meta-analysis of euglycaemic-hyperinsulinaemic clamp studies. Hum. Reprod. 2016;31:2619–2631. doi: 10.1093/humrep/dew243
  11. Kakoly NS, Khomami MB, Joham AE, et al. Ethnicity, obesity and the prevalence of impaired glucose tolerance and type 2 diabetes in PCOS: a systematic review and meta-regression. Hum Reprod Update. 2018:24(4):455–467. doi: 10.1093/humupd/ dmy007
  12. Abashova EI, Yarmolinskaya MI, Bulgakova OL, et al. Analysis of carbohydrate profile indicators in women of reproductive age with different pcos phenotypes. Problemy reproduktsii. 2022;28(4):31–38. (In Russ.) doi: 10.17116/repro20222804131
  13. Chernukha GE, Miroshina ED, Kuznetsov SYu, et al. Body mass index, body composition, and metabolic profile of patients with polycystic ovary syndrome. Obstetrics and Gynegology 2021;(10):103–111. (In Russ.) doi: 10.18565/aig.2021.10.103-111
  14. Andreeva EN, Sheremetyeva EV, Fursenko VA. Obesity – threat to the reproductive potential of Russia. Obesity and metabolism. 2019;16(3):20–28. (In Russ.) doi: 10.14341/omet10340
  15. Persson S, Elenis E, Turkmen S, et al. Higher risk of type 2 diabetes in women with hyperandrogenic polycystic ovary syndrome. Fertil Steril. 2021;116(3):862–871. doi: 10.1016/j.fertnstert.2021.04.018
  16. Lim SS, Hutchison SK, Van Ryswyk E, et al. Lifestyle changes in women with polycystic ovary syndrome. Cochrane Database Syst Rev. 2019;3(3). doi: 10.1002/14651858.CD007506.pub4
  17. Zhu S, Zhang B, Jiang X, et al. Metabolic disturbances in non-obese women with polycystic ovary syndrome: a systematic review and meta-analysis. Fertil Steril. 2019;111(1):168–177. doi: 10.1016/j.fertnstert.2018.09.013
  18. Vink JM, Sadrzadeh S, Lambalk CB, et al. Heritability of polycystic ovary syndrome in a Dutch twin-family study. J Clin. Endocrinol. Metab. 2006;91:2100–2104. doi: 10.1210/jc.2005-1494
  19. Stepto NK, Moreno-Asso A, McIlvenna LC, et al. Molecular mechanisms of insulin resistance in polycystic ovary syndrome. Unraveling the conundrum in skeletal muscle? J Clin Endocrinol Metab. 2019;104:5372–5381. doi: 10.1210/jc.2019-00167
  20. Gilbert EW, Tay CT, Hiam DS, et al. Comorbidities and complications of polycystic ovary syndrome: an overview of systematic reviews. Clin. Endocrinol. 2018;89:683–699. doi: 10.1111/cen.13828
  21. Hiam D, Moreno-Asso A, Teede HJ, et al. The genetics of polycystic ovary syndrome: an overview of candidate gene systematic reviews and genome-wide association studies. J Clin Med. 2019;8(10):1606. doi: 10.3390/jcm8101606
  22. Day FR, Hinds DA, Tung JY, et al. Causal mechanisms and balancing selection inferred from genetic associations with polycystic ovary syndrome. Nat. Commun. 2015;6:8464. doi: 10.1038/ncomms9464
  23. Liu Z, Wang Z, Hao C, et al. Effects of ADIPOQ polymorphisms on PCOS risk: a meta-analysis. Reprod Biol Endocrinol. 2018;16:120. doi: 10.1186/s12958-018-0439-6
  24. Yilmaz B, Vellanki P, Ata B, et al. Metabolic syndrome, hypertension, and hyperlipidemia in mothers, fathers, sisters, and brothers of women with polycystic ovary syndrome: a systematic review and meta-analysis. Fertil Steril. 2018;109:356–364. doi: 10.1016/j.fertnstert.2017.10.018
  25. Dapas M, Lin FTJ, Nadkarni GN, et al. Distinct subtypes of polycystic ovary syndrome with novel genetic associations: an unsupervised, phenotypic clustering analysis. PLoS Med. 2020;17(6). doi: 10.1371/journal.pmed.1003132
  26. Moran LJ., Norman RJ, Teede HJ. Metabolic risk in PCOS: phenotype and adiposity impact. Trends Endocrinol Metab. 2015;26:136–143. doi: 10.1016/j.tem.2014.12.003
  27. Liao D, Yu H, Han L, et al. Association of PON1 gene polymorphisms with polycystic ovarian syndrome risk: a meta-analysis of case-control studies. J Endocrinol Investig. 2018;41:1289–1300. doi: 10.1007/s40618-018-0866-4
  28. Shi X, Xie X, Jia Y, et al. Associations of insulin receptor and insulin receptor substrates genetic polymorphisms with polycystic ovary syndrome: a systematic review and meta-analysis. J Obstet Gynaecol Res. 2016; 42:844–854. doi: 10.1111/jog.13002
  29. González F, Considine RV, Abdelhadi OA, et al. Saturated fat ingestion promotes lipopolysaccharide-mediated inflammation and insulin resistance in polycystic ovary syndrome. J Clin Endocrinol Metab. 2019;104(3):934–946. doi: 10.1210/jc.2018-01143
  30. Tosi F, Villani M, Migazzi M, et al. Insulin-mediated substrate use in women with different phenotypes of PCOS: the role of androgens. J Clin Endocrinol Metab. 2021;106(9):e3414–e3425. doi: 10.1210/clinem/dgab380
  31. Dumesic DA, Phan JD, Leung KL, et al. Adipose insulin resistance in normal-weight women with polycystic ovary syndrome. J Clin Endocrinol Metab. 2019;104(6):2171–2183. doi: 10.1210/jc.2018-02086
  32. Hansen SL, Svendsen PF, Jeppesen JF, et al. Molecular mechanisms in skeletal muscle underlying insulin resistance in women who are lean with polycystic ovary syndrome. J Clin Endocrinol Metab. 2019;104(5):1841–1854. doi: 10.1210/jc.2018-01771
  33. Nilsson E, Benrick A, Kokosar M, et al. Transcriptional and epigenetic changes influencing skeletal muscle metabolism in women with polycystic ovary syndrome. J Clin Endocrinol Metab. 2018;103(12):4465–4477. doi: 10.1210/jc.2018-00935
  34. Zhu S, Li Z, Hu C, et al. Imaging-based body fat distribution in polycystic ovary syndrome: a systematic review and meta-analysis. Front Endocrinol. 2021;12. doi: 10.3389/fendo.2021.697223
  35. Kokosar M, Benrick A, Perfilyev A, et al. A single bout of electroacupuncture remodels epigenetic and transcriptional changes in adipose tissue in polycystic ovary syndrome. Sci Rep. 2018;8(1):1878. doi: 10.1038/s41598-017-17919-5
  36. Polak AM, Adamska A, Krentowska A, et al. Body composition, serum concentrations of androgens and insulin resistance in different polycystic ovary syndrome phenotypes. J Clin Med. 2020;9(3):732. doi: 10.3390/jcm9030732
  37. Corbould A. Chronic testosterone treatment induces selective insulin resistance in subcutaneous adipocytes of women. J Endocrinol. 2007;192(3):585–594. doi: 10.1677/joe.1.07070
  38. Puttabyatappa M, Lu C, Martin JD, et al. Developmental programming: impact of prenatal testosterone excess on steroidal machinery and cell differentiation markers in visceral adipocytes of female sheep. Reprod Sci. 2018;25(7):1010–1023. doi: 10.1177/1933719117746767
  39. Moghetti P, Tosi F, Bonin C, et al. Divergences in insulin resistance between the different phenotypes of the polycystic ovary syndrome. J Clin Endocrinol Metab. 2013;98(4):E628–E637. doi: 10.1210/jc.2012-3908
  40. Abashova EI, Yarmolinskaya MI, Bulgakova OL, et al. Carbohydrate profile and aromatase ovarian activity in various pcos phenotypes. Zhenskoe zdorov’e i reproduktsiya. 2022;(1(52)). (In Russ.) [cited 2023 Nov 5]. Available from: https://whfordoctors.su/statyi/uglevodnyj-profil-i-aktivnost-aromatazy-ovarialnyh-follikulov-pri-razlichnyh-fenotipah-sindroma-polikistoznyh-jaichnikov/
  41. Hayes MG, Urbanek M, Ehrmann DA, et al. Genome-wide association of polycystic ovary syndrome implicates alterations in gonadotropin secretion in European ancestry populations. Nat Commun. 2015;6:7502. doi: 10.1038/ncomms8502
  42. Shi Y, Zhao H, Shi Y, et al. Genome-wide association study identifies eight new risk loci for polycystic ovary syndrome. Nat Genet. 2012;44(9):1020–1025. doi: 10.1038/ng.2384
  43. Chen ZJ, Zhao H, He L, et al. Genome-wide association study identifies susceptibility loci for polycystic ovary syndrome on chromosome 2p16.3, 2p21 and 9q33.3. Nat Genet. 2011;43(1):55–59. doi: 10.1038/ng.732
  44. Day F, Karaderi T, Jones MR, et al. Large-scale genome-wide meta-analysis of polycystic ovary syndrome suggests shared genetic architecture for different diagnosis criteria PLoS Genet. 2018;14(12). doi: 10.1371/journal.pgen.1007813
  45. Hwang JY, Lee EJ, Jin Go M, et al. Genome-wide association study identifies GYS2 as a novel genetic factor for polycystic ovary syndrome through obesity-related condition. J Hum Genet. 2012;57(10):660–664. doi: 10.1038/jhg.2012.92
  46. Lee H, Oh JY, Sung YA, et al. Genome-wide association study identified new susceptibility loci for polycystic ovary syndrome. Hum Reprod. 2015;30(3):723–731. doi: 10.1093/humrep/deu352
  47. Wilkening S, Chen B, Bermejo JL, et al. Is there still a need for candidate gene approaches in the era of genome-wide association studies? Genomics. 2009;93(5):415–419. doi: 10.1016/j.ygeno.2008.12.011
  48. Sharma M, Barai RS, Kundu I, et al. PCOSKBR2: a database of genes, diseases, pathways, and networks associated with polycystic ovary syndrome. Sci Rep. 2020;10(1):14738. doi: 10.1038/s41598-020-71418-8
  49. Afiqah-Aleng N, Harun S, A-Rahman MRA, et al. PCOSBase: a manually curated database of polycystic ovarian syndrome. Database (Oxford). 2017;2017. doi: 10.1093/database/bax098
  50. Jesintha Mary M, Vetrivel U, Munuswamy D, et al. PCOSDB: Polycystic ovary syndrome database for manually curated disease associated genes. Bioinformation. 2016;12(1):4–8. doi: 10.6026/97320630012004
  51. Chernukha GE, Naidukova AA, Kaprina EK, et al. Molecular genetic predictors of polycystic ovary syndrome and its androgenic phenotypes. Obstetrics and Gynecology. 2021;(4):120–127. (In Russ.) doi: 10.18565/aig.2021.4.120-127
  52. Beglova AY, Elgina SI, Gordeeva LA. Polymorphism of the CYP11A1, CYP17A1, and CYP19A1 genes in reproductive-aged women with polycystic ovary syndrome. Obstetrics and Gynecology. 2019;(12):148–153. (In Russ.) doi: 10.18565/aig.2019.12.148-153
  53. Tabeeva GI, Nemova YI, Naidukova AA, et al. FMR1 gene polymorphism in polycystic ovary syndrome. Obstetrics and Gynecology. 2016;(3):50–57. (In Russ.) doi: 10.18565/aig.2016.3.50-56
  54. Choi K, Kim YB. Molecular mechanism of insulin resistance in obesity and type 2 diabetes. Korean J Intern Med. 2010;25(2):119–129. doi: 10.3904/kjim.2010.25.2.119
  55. Xu J, Dun J, Yang J, et al. Letrozole rat model mimics human polycystic ovarian syndrome and changes in insulin signal pathways. Med Sci Monit. 2020;26. doi: 10.12659/MSM.923073
  56. Zeng X, Xie YJ, Liu YT, et al. Polycystic ovarian syndrome: correlation between hyperandrogenism, insulin resistance and obesity. Clin Chim Acta. 2020;502:214–221. doi: 10.1016/j.cca.2019.11.003
  57. Shaaban Z, Khoradmehr A, Amiri-Yekta A, et al. Pathophysiologic mechanisms of insulin secretion and signaling-related genes in etiology of polycystic ovary syndrome. Genet Res (Camb). 2021;2021. doi: 10.1155/2021/7781823
  58. Franks S, Webber LJ, Goh M, et al. Ovarian morphology is a marker of heritable biochemical traits in sisters with polycystic ovaries. J Clin Endocrinol Metab. 2008;93(9):3396–3402. doi: 10.1210/jc.2008-0369
  59. Rasool SUA, Ashraf S, Nabi M, et al. Insulin gene VNTR class III allele is a risk factor for insulin resistance in Kashmiri women with polycystic ovary syndrome. Meta Gene. 2019;21. doi: 10.1016/j.mgene.2019.100597
  60. Dunaif A, Wu X, Lee A, et al. Defects in insulin receptor signaling in vivo in the polycystic ovary syndrome (PCOS). Am J Physiol Endocrinol Metab. 2001;281(2):E392–E399. doi: 10.1152/ajpendo.2001.281.2.E392
  61. Xing C, Zhang J, Zhao H, et al. Effect of sex hormone-binding globulin on polycystic ovary syndrome: mechanisms, manifestations, genetics, and treatment. Int J Womens Health. 2022;14:91–105. doi: 10.2147/IJWH.S344542
  62. Lee MH, Yoon JA, Kim HR, et al. Hyperandrogenic milieu dysregulates the expression of insulin signaling factors and glucose transporters in the endometrium of patients with polycystic ovary syndrome. Reprod Sci. 2019. doi: 10.1177/1933719119833487
  63. Dakshinamoorthy J, Jain PR, Ramamoorthy T, et al. Association of GWAS identified INSR variants (rs2059807 & rs1799817) with polycystic ovarian syndrome in Indian women. Int J Biol Macromol. 2020;144:663–670. doi: 10.1016/j.ijbiomac.2019.10.235
  64. Hu M, Zhang Y, Guo X, et al. Hyperandrogenism and insulin resistance induce gravid uterine defects in association with mitochondrial dysfunction and aberrant reactive oxygen species production. Am J Physiol Endocrinol Metab. 2019;316(5):E794–E809. doi: 10.1152/ajpendo.00359.2018
  65. Huang T, Shu Y, Cai YD. Genetic differences among ethnic groups. BMC Genomics. 2015;16:1093. doi: 10.1186/s12864-015-2328-0
  66. Valkenburg O, Lao O, Schipper I, et al. Genetic ancestry affects the phenotype of normogonadotropic anovulatory (WHOII) subfertility. J Clin Endocrinol Metab. 2011;96(7):E1181–E1187. doi: 10.1210/jc.2010-2641
  67. Mersha TB, Abebe T. Self-reported race/ethnicity in the age of genomic research: its potential impact on understanding health disparities. Hum Genomics. 2015;9(1):1. doi: 10.1186/s40246-014-0023-x
  68. Gao J, Xue JD, Li ZC, et al. The association of DENND1A gene polymorphisms and polycystic ovary syndrome risk: a systematic review and meta-analysis. Arch Gynecol Obstet. 2016;294(5):1073–1080. doi: 10.1007/s00404-016-4159-x
  69. Shen W, Li T, Hu Y, et al. Calpain-10 genetic polymorphisms and polycystic ovary syndrome risk: a meta-analysis and meta-regression. Gene. 2013;531(2):426–434. doi: 10.1016/j.gene.2013.08.072
  70. Yan MS, Liang GY, Xia BR, et al. Association of insulin gene variable number of tandem repeats regulatory polymorphism with polycystic ovary syndrome. Hum Immunol. 2014;75(10):1047–1052. doi: 10.1016/j.humimm.2014.09.001
  71. Feng C, Lv PP, Yu TT, et al. The association between polymorphism of INSR and polycystic ovary syndrome: a meta-analysis. Int J Mol Sci. 2015;16(2):2403–2425. doi: 10.3390/ijms16022403
  72. Psilopatis I, Vrettou K, Nousiopoulou E, et al. The role of peroxisome proliferator-activated receptors in polycystic ovary syndrome. J Clin Med. 2023;12(8):2912. doi: 10.3390/jcm12082912
  73. Han L, Shen WJ, Bittner S, et al. PPARs: regulators of metabolism and as therapeutic targets in cardiovascular disease. Part II: PPAR-β/δ and PPAR-γ. Future Cardiol. 2017;13(3):279–296. doi: 10.2217/fca-2017-0019
  74. Brunmeir R, Xu F. Functional regulation of PPARs through post-translational modifications. Int J Mol Sci. 2018;19(6):1738. doi: 10.3390/ijms19061738
  75. Christofides A, Konstantinidou E, Jani C, et al. The role of peroxisome proliferator-activated receptors (PPAR) in immune responses. Metabolism. 2021;114. doi: 10.1016/j.metabol.2020.154338
  76. Panda PK, Rane R, Ravichandran R, et al. Genetics of PCOS: a systematic bioinformatics approach to unveil the proteins responsible for PCOS. Genom Data. 2016;8:52–60. doi: 10.1016/j.gdata.2016.03.008
  77. Jacob R, Ramachandran C, Jude C, et al. Peroxisome proliferator activated receptor gamma polymorphism Pro12Ala in polycystic ovary syndrome (PCOS) of South Indian population. Asian Pacific Journal of Reproduction. 2016;5(3):210–213. doi: 10.1016/j.apjr.2016.04.002
  78. Zhang H, Bi Y, Hu C, et al. Association between the Pro12Ala polymorphism of PPAR-γ gene and the polycystic ovary syndrome: a meta-analysis of case-control studies. Gene. 2012;503(1):12–17. doi: 10.1016/j.gene.2012.04.083
  79. Giandalia A, Pappalardo MA, Russo GT, et al. Influence of peroxisome proliferator-activated receptor-γ exon 2 and exon 6 and insulin receptor substrate (IRS)-1 Gly972Arg polymorphisms on insulin resistance and beta-cell function in southern mediterranean women with polycystic ovary syndrome. J Clin Transl Endocrinol. 2018;13:1–8. doi: 10.1016/j.jcte.2018.05.002
  80. Liang J, Lan J, Li M, et al. Associations of leptin receptor and peroxisome proliferator-activated receptor gamma polymorphisms with polycystic ovary syndrome: a meta-analysis. Ann Nutr Metab. 2019;75(1):1–8. doi: 10.1159/000500996
  81. Liu Q, Tang B, Zhu Z, et al. A genome-wide cross-trait analysis identifies shared loci and causal relationships of type 2 diabetes and glycaemic traits with polycystic ovary syndrome. Diabetologia. 2022;65(9):1483–1494. doi: 10.1007/s00125-022-05746-x
  82. Prasad RB, Kristensen K, Katsarou A, et al. Association of single nucleotide polymorphisms with insulin secretion, insulin sensitivity, and diabetes in women with a history of gestational diabetes mellitus. BMC Med Genomics. 2021;14(1):274. doi: 10.1186/s12920-021-01123-6
  83. Moffett RC, Naughton V. Emerging role of GIP and related gut hormones in fertility and PCOS. Peptides. 2020;125. doi: 10.1016/j.peptides.2019.170233
  84. Bell GA, Sundaram R, Mumford SL, et al. Maternal polycystic ovarian syndrome and early offspring development. Hum Reprod. 2018;33(7):1307–1315. doi: 10.1093/humrep/dey087
  85. Chen Y, Guo J, Zhang Q, et al. Insulin resistance is a risk factor for early miscarriage and macrosomia in patients with polycystic ovary syndrome from the first embryo transfer cycle: a retrospective cohort study. Front Endocrinol. 2022;13. doi: 10.3389/fendo.2022.853473
  86. Abashova EI, Yarmolinskaya MI, Bulgakova OL, et al. Analysis of peculiarities of miscarriage in women of reproductive age with different PCOS phenotypes. Russian Journal of Human Reproduction. 2022;28(5):29-38. (In Russ.) doi: 10.17116/repro20222805129
  87. Ahlqvist E, Storm P, Käräjämäki A, et al. Novel subgroups of adult-onset diabetes and their association with outcomes: a data-driven cluster analysis of six variables. Lancet Diabetes Endocrinol. 2018;6(5):361–369. doi: 10.1016/S2213-8587(18)30051-2
  88. Suzuki K, Hatzikotoulas K, Southam L, et al. Multi-ancestry genome-wide study in >2.5 million individuals reveals heterogeneity in mechanistic pathways of type 2 diabetes and complications. medRxiv. 2023. doi: 10.1101/2023.03.31.23287839. Preprint
  89. Pervjakova N, Moen GH, Borges MC, et al. Multi-ancestry genome-wide association study of gestational diabetes mellitus highlights genetic links with type 2 diabetes. Hum Mol Genet. 2022;31(19):3377–3391. doi: 10.1093/hmg/ddac050
  90. Plows JF, Stanley JL, Baker PN, et al. The pathophysiology of gestational diabetes mellitus. Int J Mol Sci. 2018;19(11):3342. doi: 10.3390/ijms19113342

Supplementary files

Supplementary Files
Action
1. JATS XML
Download

Copyright (c) 2023 Eсо-Vector

License URL: https://eco-vector.com/for_authors.php#07
СМИ зарегистрировано Федеральной службой по надзору в сфере связи, информационных технологий и массовых коммуникаций (Роскомнадзор).
Регистрационный номер и дата принятия решения о регистрации СМИ: серия ПИ № ФС 77 - 66759 от 08.08.2016 г. 
СМИ зарегистрировано Федеральной службой по надзору в сфере связи, информационных технологий и массовых коммуникаций (Роскомнадзор).
Регистрационный номер и дата принятия решения о регистрации СМИ: серия Эл № 77 - 6389 от 15.07.2002 г.


This website uses cookies

You consent to our cookies if you continue to use our website.

About Cookies