Ancestry-Associated Immune Differences
This page tracks how immune measurements may differ across ancestry groups and how those differences should be interpreted in the T2D PBMC paper.
Interpretation Rules
- Treat genetic ancestry, self-identified race, ethnicity, geography, and recruitment site as related but distinct variables.
- Ask whether each source directly models ancestry or only reports group labels.
- Record environmental, socioeconomic, clinical, and technical variables that could explain apparent ancestry-associated differences.
- Avoid presenting ancestry-associated observations as genetic causation unless the study design supports that inference.
Evidence Questions
- Was ancestry genetically inferred, self-reported, or approximated by cohort/geography?
- Were analyses stratified by ancestry, adjusted for ancestry, or merely described demographically?
- Were cell type proportions, expression, pathway activity, or stimulation responses compared across groups?
- Were batch, site, sequencing depth, medication, BMI, glycemia, and comorbidities controlled?
Genetic Ancestry Context
- Genetic ancestry does not only influence immune traits directly — it also shapes the predominant T2D mechanism within a population, which in turn may influence T2D-associated immune phenotypes.
- Our prior work (Markelova et al. 2025) showed that T2D genetic cluster prevalence varies by ancestry (beta-cell dysfunction dominant in Yakut/East-Asian-like populations, obesity/insulin-resistance dominant in Chechen/European-like populations) in the same cohort studied in the current PBMC project. This means pPGS and PBMC data are available for direct within-person correlation — ancestry groups with different T2D mechanism profiles can be tested for corresponding differences in PBMC immune correlates of T2D.
- The pPGS framework (Smith et al. 2024) used in our prior work offers a methodological parallel for the PBMC ancestry paper: instead of partitioning genetic risk into mechanism clusters, PBMC immune features could be partitioned into ancestry-associated and T2D-associated components.
- Yabe et al. 2015 demonstrates that T2D pathophysiology itself differs by ancestry: East Asians show β-cell-dysfunction-dominant T2D, while Europeans show insulin-resistance-dominant T2D. This means ancestry-associated T2D immune differences may be partially mediated by the different underlying disease mechanisms rather than by ancestry directly.
- If the predominant T2D mechanism (β-cell dysfunction vs. insulin resistance) produces different systemic inflammatory profiles, then ancestry groups enriched for one mechanism versus another may show different T2D-associated PBMC immune signatures even in the absence of direct ancestry effects on immune cell biology.
- Yabe et al. also report differential medication patterns by population (sulfonylureas (SUs) + dipeptidyl peptidase-4 inhibitors (DPP-4i) standard in Japan, metformin first-line in Europe), which is a potential confounder for ancestry-PBMC comparisons that should be explicitly modeled.