{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,31]],"date-time":"2026-07-31T14:45:06Z","timestamp":1785509106355,"version":"3.56.0"},"reference-count":49,"publisher":"MDPI AG","issue":"10","license":[{"start":{"date-parts":[[2025,9,25]],"date-time":"2025-09-25T00:00:00Z","timestamp":1758758400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Bashkir State Medical University Strategic Academic Leadership Program","award":["PRIORITY-2030"],"award-info":[{"award-number":["PRIORITY-2030"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Genes"],"abstract":"<jats:p>Background\/Objectives: Type 2 diabetes (T2D) is a clinically and genetically heterogeneous disease. In this study, we aimed to stratify patients with T2D from the Volga-Ural region of Eurasia into distinct subgroups based on clinical characteristics and to investigate the genetic underpinnings of these clusters. Methods: A total of 254 Tatar individuals with T2D and 361 ethnically matched controls were recruited. Clinical clustering was performed using k-means and hierarchical algorithms on five variables: age at diagnosis, body mass index (BMI), glycated hemoglobin (HbA1c), insulin resistance (HOMA-IR), and \u03b2-cell function (HOMA-B). Genetic association analysis was conducted using logistic regression under an additive model, adjusted for age and sex, and corrected for multiple comparisons using the Benjamini\u2013Hochberg method. Results: Four distinct T2D subtypes were identified\u2014mild age-related diabetes (MARD, n = 25), mild obesity-related diabetes (MOD, n = 72), severe insulin-resistant diabetes (SIRD, n = 66), and severe insulin-deficient diabetes (SIDD, n = 52)\u2014each with unique clinical and comorbidity profiles. SIDD patients exhibited the highest burden of microvascular complications and lowest estimated glomerular filtration rate. Nine genetic variants showed significant associations with T2D and\/or specific subtypes, including loci in genes related to neurotransmission (e.g., HTR1B, CHRM5), appetite regulation (NPY2R), insulin signaling (TCF7L2, PTEN), and other metabolic pathways. Some variants demonstrated subtype-specific associations, underscoring the genetic heterogeneity of T2D. Conclusions: Our findings support the utility of clinical clustering in uncovering biologically and clinically meaningful T2D subtypes and reveal genetic variants that may contribute to this heterogeneity. These insights may inform future precision medicine approaches for T2D diagnosis and management.<\/jats:p>","DOI":"10.3390\/genes16101131","type":"journal-article","created":{"date-parts":[[2025,9,25]],"date-time":"2025-09-25T08:56:44Z","timestamp":1758790604000},"page":"1131","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Exploring Genetic Heterogeneity in Type 2 Diabetes Subtypes"],"prefix":"10.3390","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9918-6962","authenticated-orcid":false,"given":"Yanina","family":"Timasheva","sequence":"first","affiliation":[{"name":"Institute of Biochemistry and Genetics of Ufa Federal Research Centre of Russian Academy of Sciences, 450054 Ufa, Russia"},{"name":"Department of Medical Genetics and Fundamental Medicine, Faculty of General Medicine, Bashkir State Medical University, 450008 Ufa, Russia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2944-4428","authenticated-orcid":false,"given":"Olga","family":"Kochetova","sequence":"additional","affiliation":[{"name":"Institute of Biochemistry and Genetics of Ufa Federal Research Centre of Russian Academy of Sciences, 450054 Ufa, Russia"},{"name":"Department of Biology, Faculty of Stomatology, Bashkir State Medical University, 450008 Ufa, Russia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3553-7126","authenticated-orcid":false,"given":"Zhanna","family":"Balkhiyarova","sequence":"additional","affiliation":[{"name":"Section of Statistical Multi-Omics, Department of Clinical & Experimental Medicine, School of Biosciences & Medicine, University of Surrey, Guildford GU2 7XH, UK"},{"name":"Department of Endocrinology, Faculty of General Medicine, Bashkir State Medical University, 450008 Ufa, Russia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Diana","family":"Avzaletdinova","sequence":"additional","affiliation":[{"name":"Department of Endocrinology, Faculty of General Medicine, Bashkir State Medical University, 450008 Ufa, Russia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1695-5173","authenticated-orcid":false,"given":"Gulnaz","family":"Korytina","sequence":"additional","affiliation":[{"name":"Institute of Biochemistry and Genetics of Ufa Federal Research Centre of Russian Academy of Sciences, 450054 Ufa, Russia"},{"name":"Department of Biology, Faculty of Stomatology, Bashkir State Medical University, 450008 Ufa, Russia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tatiana","family":"Kochetova","sequence":"additional","affiliation":[{"name":"Department of Biology, Faculty of Stomatology, Bashkir State Medical University, 450008 Ufa, Russia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0609-4082","authenticated-orcid":false,"given":"Arie","family":"Nouwen","sequence":"additional","affiliation":[{"name":"Department of Psychology, Middlesex University, London NW4 4BT, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2025,9,25]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"2086","DOI":"10.2337\/dbi20-0001","article-title":"Subtypes of Type 2 Diabetes Determined from Clinical Parameters","volume":"69","author":"Ahlqvist","year":"2020","journal-title":"Diabetes"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"684","DOI":"10.1016\/S2213-8587(19)30187-1","article-title":"Risk of diabetes-associated diseases in subgroups of patients with recent-onset diabetes: A 5-year follow-up study","volume":"7","author":"Zaharia","year":"2019","journal-title":"Lancet. Diabetes Endocrinol."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"9","DOI":"10.1016\/S2213-8587(18)30316-4","article-title":"Novel subgroups of patients with adult-onset diabetes in Chinese and US populations","volume":"7","author":"Zou","year":"2019","journal-title":"Lancet. Diabetes Endocrinol."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"65","DOI":"10.1007\/s00125-021-05543-y","article-title":"Subgroups of patients with young-onset type 2 diabetes in India reveal insulin deficiency as a major driver","volume":"65","author":"Prasad","year":"2022","journal-title":"Diabetologia"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"84","DOI":"10.14341\/probl13259","article-title":"Clinical features and complication rates in type 2 diabetes mellitus clusters on five variables: Glycated hemoglobin, age at diagnosis, body mass index, HOMA-IR, HOMA-B","volume":"69","author":"Bondar","year":"2023","journal-title":"Probl. Endokrinol."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"100182","DOI":"10.1016\/j.lansea.2023.100182","article-title":"Polygenic scores of diabetes-related traits in subgroups of type 2 diabetes in India: A cohort study","volume":"14","author":"Yajnik","year":"2023","journal-title":"Lancet Reg. Health Southeast Asia"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"1534","DOI":"10.1038\/s41588-021-00948-2","article-title":"Genome-wide association analyses highlight etiological differences underlying newly defined subtypes of diabetes","volume":"53","author":"Dwivedi","year":"2021","journal-title":"Nat. Genet."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"1758","DOI":"10.1007\/s00125-022-05769-4","article-title":"Phenotypic and genetic classification of diabetes","volume":"65","author":"Deutsch","year":"2022","journal-title":"Diabetologia"},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Timasheva, Y., Balkhiyarova, Z., Avzaletdinova, D., Rassoleeva, I., Morugova, T.V., Korytina, G., Prokopenko, I., and Kochetova, O. (2023). Integrating common risk factors with polygenic scores improves the prediction of type 2 diabetes. Int. J. Mol. Sci., 24.","DOI":"10.3390\/ijms24020984"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"1224","DOI":"10.1134\/S1022795424700765","article-title":"Polymorphic Variants of Long Noncoding RNA Genes in the Development of Type 2 Diabetes Mellitus","volume":"60","author":"Kochetova","year":"2024","journal-title":"Russ. J. Genet."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"1","DOI":"10.14341\/DM12211","article-title":"Standards of specialized diabetes care","volume":"22","author":"Dedov","year":"2019","journal-title":"Diabetes Mellit."},{"key":"ref_12","unstructured":"World Health Organization (1995). Physical Status: The Use and Interpretation of Anthropometry, World Health Organization."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"160","DOI":"10.4103\/2230-8210.146874","article-title":"Assessment of insulin sensitivity\/resistance","volume":"19","author":"Gutch","year":"2015","journal-title":"Indian J. Endocrinol. Metab."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"245","DOI":"10.4274\/Jcrpe.1127","article-title":"A study of insulin resistance by HOMA-IR and its cut-off value to identify metabolic syndrome in urban Indian adolescents","volume":"5","author":"Singh","year":"2013","journal-title":"J. Clin. Res. Pediatr. Endocrinol."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"1593","DOI":"10.1038\/s41588-018-0248-z","article-title":"An atlas of genetic associations in UK Biobank","volume":"50","author":"Rawlik","year":"2018","journal-title":"Nat. Genet."},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Timasheva, Y., Kochetova, O., Balkhiyarova, Z., Korytina, G., Prokopenko, I., and Nouwen, A. (2024). Polygenic Score Approach to Predicting Risk of Metabolic Syndrome. Genes, 16.","DOI":"10.3390\/genes16010022"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"289","DOI":"10.1111\/j.2517-6161.1995.tb02031.x","article-title":"Controlling the False Discovery Rate\u2014A Practical and Powerful Approach to Multiple Testing","volume":"57","author":"Benjamini","year":"1995","journal-title":"J. R. Stat. Soc. Ser. B"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"100120","DOI":"10.1016\/j.mocell.2024.100120","article-title":"A concise guide to essential R packages for analyses of DNA, RNA, and proteins","volume":"47","author":"Chua","year":"2024","journal-title":"Mol. Cells"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"7","DOI":"10.1186\/s13742-015-0047-8","article-title":"Second-generation PLINK: Rising to the challenge of larger and richer datasets","volume":"4","author":"Chang","year":"2015","journal-title":"Gigascience"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"256","DOI":"10.1159\/000508558","article-title":"Power and Sample Size Calculations for Genetic Association Studies in the Presence of Genetic Model Misspecification","volume":"84","author":"Moore","year":"2020","journal-title":"Hum. Hered."},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Anney, R.J.L., Lotfi-Miri, M., Olsson, C.A., Reid, S.C., Hemphill, S.A., and Patton, G.C. (2007). Variation in the gene coding for the M5 Muscarinic receptor (CHRM5) influences cigarette dose but is not associated with dependence to drugs of addiction: Evidence from a prospective population based cohort study of young adults. BMC Genet., 8.","DOI":"10.1186\/1471-2156-8-46"},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Merzah, M., Natae, S., S\u00e1ndor, J., and Fiatal, S. (2024). Single Nucleotide Variants (SNVs) of the Mesocorticolimbic System Associated with Cardiovascular Diseases and Type 2 Diabetes: A Systematic Review. Genes, 15.","DOI":"10.3390\/genes15010109"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"56","DOI":"10.1186\/1746-1596-9-56","article-title":"Meta-analyses between 18 candidate genetic markers and overweight\/obesity","volume":"9","author":"Tang","year":"2014","journal-title":"Diagn. Pathol."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"172","DOI":"10.1038\/s41588-017-0022-7","article-title":"Loss-of-function variants in ADCY3 increase risk of obesity and type 2 diabetes","volume":"50","author":"Grarup","year":"2018","journal-title":"Nat. Genet."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"836","DOI":"10.1016\/j.biopsych.2015.12.012","article-title":"Ablation of Type III Adenylyl Cyclase in Mice Causes Reduced Neuronal Activity, Altered Sleep Pattern, and Depression-like Phenotypes","volume":"80","author":"Chen","year":"2016","journal-title":"Biol. Psychiatry"},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Tong, T., Shen, Y., Lee, H.W., Yu, R., and Park, T. (2016). Adenylyl cyclase 3 haploinsufficiency confers susceptibility to diet-induced obesity and insulin resistance in mice. Sci. Rep., 6.","DOI":"10.1038\/srep34179"},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Pitman, J.L., Wheeler, M.C., Lloyd, D.J., Walker, J.R., Glynne, R.J., and Gekakis, N. (2014). A gain-of-function mutation in adenylate cyclase 3 protects mice from diet-induced obesity. PLoS ONE, 9.","DOI":"10.1371\/journal.pone.0110226"},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Vaisse, C., Reiter, J.F., and Berbari, N.F. (2017). Cilia and Obesity. Cold Spring Harb. Perspect. Biol., 9.","DOI":"10.1101\/cshperspect.a028217"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"105","DOI":"10.1038\/ng.520","article-title":"New genetic loci implicated in fasting glucose homeostasis and their impact on type 2 diabetes risk","volume":"42","author":"Dupuis","year":"2010","journal-title":"Nat. Genet."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"865","DOI":"10.1016\/j.ajhg.2017.04.014","article-title":"Whole-Genome Sequencing Coupled to Imputation Discovers Genetic Signals for Anthropometric Traits","volume":"100","author":"Tachmazidou","year":"2017","journal-title":"Am. J. Hum. Genet."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"10","DOI":"10.3892\/ijmm.2021.5065","article-title":"Molecular modelling of novel ADCY3 variant predicts a molecular target for tackling obesity","volume":"49","author":"Toumba","year":"2022","journal-title":"Int. J. Mol. Med."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"320","DOI":"10.1038\/ng1732","article-title":"Variant of transcription factor 7-like 2 (TCF7L2) gene confers risk of type 2 diabetes","volume":"38","author":"Grant","year":"2006","journal-title":"Nat. Genet."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"881","DOI":"10.1038\/nature05616","article-title":"A genome-wide association study identifies novel risk loci for type 2 diabetes","volume":"445","author":"Sladek","year":"2007","journal-title":"Nature"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"1220","DOI":"10.2337\/db20-0573","article-title":"The Role of TCF7L2 in Type 2 Diabetes","volume":"70","author":"Gragnoli","year":"2021","journal-title":"Diabetes"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"44","DOI":"10.1016\/j.molmet.2019.03.003","article-title":"Targeted deletion of Tcf7l2 in adipocytes promotes adipocyte hypertrophy and impaired glucose metabolism","volume":"24","author":"Geoghegan","year":"2019","journal-title":"Mol. Metab."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"129","DOI":"10.1007\/s00125-020-05292-4","article-title":"Adipocyte-specific deletion of Tcf7l2 induces dysregulated lipid metabolism and impairs glucose tolerance in mice","volume":"64","author":"Leclerc","year":"2021","journal-title":"Diabetologia"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"71","DOI":"10.1111\/dom.15984","article-title":"A randomized phase I study of BI 1820237, a novel neuropeptide Y receptor type 2 agonist, alone or in combination with low-dose liraglutide in otherwise healthy men with overweight or obesity","volume":"27","author":"Beetz","year":"2025","journal-title":"Diabetes Obes. Metab."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1016\/S0009-8981(02)00301-7","article-title":"Neuropeptide Y and its receptors as potential therapeutic drug targets","volume":"326","author":"Silva","year":"2002","journal-title":"Clin. Chim. Acta Int. J. Clin. Chem."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"E1062","DOI":"10.1152\/ajpendo.00450.2006","article-title":"Effects of PYY1-36 and PYY3-36 on appetite, energy intake, energy expenditure, glucose and fat metabolism in obese and lean subjects","volume":"292","author":"Sloth","year":"2007","journal-title":"Am. J. Physiol. Endocrinol. Metab."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"2737","DOI":"10.1210\/en.2019-00100","article-title":"Modified Peptide YY Molecule Attenuates the Activity of NPY\/AgRP Neurons and Reduces Food Intake in Male Mice","volume":"160","author":"Jones","year":"2019","journal-title":"Endocrinology"},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"191","DOI":"10.1016\/j.biochi.2019.01.008","article-title":"Vasopressin receptors in islets enhance glucose tolerance, pancreatic beta-cell secretory function, proliferation and survival","volume":"158","author":"Mohan","year":"2019","journal-title":"Biochimie"},{"key":"ref_42","doi-asserted-by":"crossref","unstructured":"Mohan, S., Lafferty, R., Tanday, N., Flatt, P.R., Moffett, R.C., and Irwin, N. (2021). Beneficial impact of Ac3IV, an AVP analogue acting specifically at V1a and V1b receptors, on diabetes islet morphology and transdifferentiation of alpha- and beta-cells. PLoS ONE, 16.","DOI":"10.1371\/journal.pone.0261608"},{"key":"ref_43","first-page":"364","article-title":"Genes Involved in Neurodevelopment, Neuroplasticity and Major Depression: No Association for CACNA1C, CHRNA7 and MAPK1","volume":"17","author":"Mandelli","year":"2019","journal-title":"Clin. Psychopharmacol. Neurosci. Off. Sci. J. Korean Coll. Neuropsychopharmacol."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"2515","DOI":"10.1007\/s00213-022-06141-5","article-title":"Methylation and expression quantitative trait locus rs6296 in the HTR1B gene is associated with susceptibility to opioid use disorder","volume":"239","author":"Li","year":"2022","journal-title":"Psychopharmacology"},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"e15012","DOI":"10.1111\/nmo.15012","article-title":"Serotonin Receptors Polymorphisms Are Associated With Cyclic Vomiting Syndrome","volume":"37","author":"Binienda","year":"2025","journal-title":"Neurogastroenterol. Motil."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"349","DOI":"10.1177\/0269881111414452","article-title":"Influence and interaction of genetic polymorphisms in the serotonin system and life stress on antidepressant drug response","volume":"26","author":"Xu","year":"2012","journal-title":"J. Psychopharmacol."},{"key":"ref_47","first-page":"100723","article-title":"The prediction of self-harm behaviors in young adults with multi-modal data: An XGBoost approach","volume":"16","author":"Xu","year":"2024","journal-title":"J. Affect. Disord. Rep."},{"key":"ref_48","doi-asserted-by":"crossref","unstructured":"Yang, P., Yang, M., Li, P., Cao, D., Gong, D., Lv, J., Pu, L., Huang, S., and Liang, Y. (2021). A Meta-Analysis of 5-Hydroxytryptamine Receptor 1B Polymorphisms With Risk of Major Depressive Disorder and Suicidal Behavior. Front. Psychiatry, 12.","DOI":"10.3389\/fpsyt.2021.696655"},{"key":"ref_49","doi-asserted-by":"crossref","unstructured":"Dolcini, J., Chiavarini, M., Firmani, G., Ponzio, E., D\u2019Errico, M.M., and Barbadoro, P. (2024). Consumption of Bottled Water and Chronic Diseases: A Nationwide Cross-Sectional Study. Int. J. Environ. Res. Public Health, 21.","DOI":"10.3390\/ijerph21081074"}],"container-title":["Genes"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2073-4425\/16\/10\/1131\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,9]],"date-time":"2025-10-09T18:49:25Z","timestamp":1760035765000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2073-4425\/16\/10\/1131"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,9,25]]},"references-count":49,"journal-issue":{"issue":"10","published-online":{"date-parts":[[2025,10]]}},"alternative-id":["genes16101131"],"URL":"https:\/\/doi.org\/10.3390\/genes16101131","relation":{},"ISSN":["2073-4425"],"issn-type":[{"value":"2073-4425","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,9,25]]}}}