T2D Research

Markelova et al. 2025 Genetic and Phenotypic Heterogeneity of T2D Across Russian Ancestry Groups

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tagsreference, type-2-diabetes, genetics, ancestry, russian-population
aliasesMarkelova et al. 2025 Genetic and Phenotypic Heterogeneity of T2D Across Russian Ancestry Groups

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Markelova et al. 2025 Genetic and Phenotypic Heterogeneity of T2D Across Russian Ancestry Groups

Author’s own prior work — the same cohort is used in the current PBMC project.

We genotyped 275 participants (185 healthy, 90 T2D) from three Russian ancestry groups — Chechens, Tatars, and Yakuts — and applied Smith et al.’s partitioned polygenic score (pPGS) framework to assess ancestry-specific differences in T2D-associated genetic mechanisms. The study demonstrates that the predominant mechanisms underlying T2D differ across populations within the same country. The current PBMC project extends this work by adding multi-modal immune profiling (scRNA-seq, scATAC-seq) to the same cohort.

Bibliographic Details

  • Citation: Markelova, E.E. et al. 2025. “Genetic and phenotypic heterogeneity of type 2 diabetes across Russian ancestry groups.” Frontiers in Endocrinology 16:1672403. DOI: 10.3389/fendo.2025.1672403.
  • Source path: _raw/Markelova2025_genetic.pdf.
  • Study population: 275 eligible subjects (185 healthy donors, 90 T2D patients) from three self-reported ancestry groups in Russia — Chechens, Tatars, and Yakuts. Median age 45, 58.5% women.
  • Genotyping: Illumina GSA-5 array with 548,502 SNPs after QC.

Study Design

  • Participants were genotyped on the Illumina GSA-5 array; data were converted to VCF and aligned to hg38.
  • An ancestry reference dataset (N=1,878) was assembled from public sources covering the range of ancestries present in Russia.
  • Global ancestry was assessed using PCA and ADMIXTURE (K=9). All participants’ inferred ancestries matched self-report.
  • pPGSs for 12 T2D genetic clusters from Smith et al. (2024) were calculated for each participant using 285 variants with weights >0.7802.

Key Findings

  • Yakuts exhibited significantly higher pPGS for Beta Cell 1, Hyper Insulin, and Liver-Lipid clusters, and lower Obesity pPGS compared to Chechens and Tatars.
  • Chechens and Tatars had higher scores for obesity-related mechanisms, consistent with prior reports of higher BMI but lower T2D prevalence in North Caucasus populations.
  • Tatars showed the lowest Hyper Insulin and SHBG-LpA pPGSs.
  • The Beta Cell 1 and Hyper Insulin pPGSs — which are associated with opposing phenotypic traits (reduced vs. increased insulin response) — both appeared elevated in Yakuts but showed no correlation, suggesting distinct genetic mechanisms drive these traits.
  • No significant pPGS differences were found between healthy individuals and T2D patients overall (except Chechen SHBG-LpA: OR 4.64), likely due to small sample size and the fact pPGSs were designed to differentiate mechanisms, not disease status.

Paper-Relevant Interpretation

  • This paper provides direct evidence that genetic ancestry shapes the predominant T2D mechanisms within a population — a foundation for ancestry-aware T2D research. For the PBMC ancestry paper (which uses the same cohort), it provides the pre-existing genetic backbone for direct integration with PBMC immune data.
  • The Yakut findings align with established East Asian T2D patterns (beta-cell dysfunction dominant), while Chechen/Tatar patterns align more with European obesity/insulin resistance mechanisms — demonstrating ancestry-specific T2D heterogeneity within a single country.
  • Because the PBMC project studies the same individuals, pPGS and PBMC immune features can be correlated within-person — enabling direct testing of whether T2D genetic mechanism clusters predict immune phenotype, rather than relying on cross-cohort inference.
  • The pPGS framework offers a methodological template: just as we partitioned genetic risk into mechanism clusters, immune features could be partitioned into ancestry-associated and T2D-associated components.

Limitations (Author’s Assessment)

  • Small sample sizes within each ancestry group limit power for rare-variant detection and between-group comparisons.
  • The pPGS framework from Smith et al. was developed primarily in European-ancestry populations; transferability to Russian minority populations requires further validation.
  • The study does not include PBMC or immune data — it is a genotyping-only study. Relevance to PBMC immune differences is indirect, through the principle that ancestry influences T2D pathophysiology.
  • T2D status information was unavailable for the public ancestry reference samples used in extended pPGS distribution analysis.

Sources

  • _raw/Markelova2025_genetic.pdf

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