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Exploring Genetic Heterogeneity in Type 2 Diabetes Subtypes.

Yanina Timasheva1,2, Olga Kochetova1,3, Zhanna Balkhiyarova4,5

  • 1Institute of Biochemistry and Genetics of Ufa Federal Research Centre of Russian Academy of Sciences, 450054 Ufa, Russia.

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This study identified four distinct type 2 diabetes (T2D) subtypes in the Volga-Ural region, revealing genetic variants linked to T2D heterogeneity and informing precision medicine for diabetes management.

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Area of Science:

  • Genetics and genomics
  • Endocrinology and metabolism
  • Population health

Background:

  • Type 2 diabetes (T2D) is a complex disease with significant clinical and genetic variability.
  • Understanding T2D heterogeneity is crucial for developing targeted therapeutic strategies.
  • Previous research has not fully elucidated the distinct subtypes within specific populations.

Purpose of the Study:

  • To stratify Type 2 Diabetes patients from the Volga-Ural region into distinct clinical subgroups.
  • To investigate the genetic factors contributing to the identified T2D subtypes.
  • To explore the clinical and comorbidity profiles associated with each T2D subtype.

Main Methods:

  • Recruited 254 Tatar individuals with T2D and 361 controls from the Volga-Ural region.
  • Employed k-means and hierarchical clustering on clinical variables (age at diagnosis, BMI, HbA1c, HOMA-IR, HOMA-B) to identify T2D subtypes.
  • Conducted genetic association analysis using logistic regression, adjusting for covariates and correcting for multiple comparisons.

Main Results:

  • Identified four distinct T2D subtypes: mild age-related diabetes (MARD), mild obesity-related diabetes (MOD), severe insulin-resistant diabetes (SIRD), and severe insulin-deficient diabetes (SIDD).
  • SIDD patients presented with the highest microvascular complication burden and lowest estimated glomerular filtration rate.
  • Nine genetic variants showed significant associations with T2D and/or specific subtypes, including genes involved in neurotransmission, appetite regulation, and insulin signaling.

Conclusions:

  • Clinical clustering effectively identifies biologically and clinically meaningful T2D subtypes.
  • Specific genetic variants contribute to the observed heterogeneity in T2D.
  • Findings support precision medicine approaches for T2D diagnosis and management.