Highlights
- Every 20% absolute increase in Indigenous American (AMR) genomic ancestry is associated with a 33% higher risk of type 2 diabetes, even after adjusting for lifestyle and socioeconomic factors.
- Individuals with 100% AMR ancestry face a four-fold increase in the odds of type 2 diabetes compared to those with minimal AMR ancestry.
- The genetic predisposition to glycemic dysregulation is more pronounced in women and younger adults, suggesting a need for earlier screening in these groups.
- While lifestyle and adiposity contribute to the epidemic, genomic ancestry remains a significant, independent driver of diabetes prevalence in the Mexican population.
The Epidemiological Landscape: Diabetes in the Mexican Population
Mexico currently faces one of the most severe type 2 diabetes (T2D) epidemics globally. The prevalence of the disease has reached critical levels, placing an immense burden on the national healthcare system and contributing significantly to premature mortality and disability. While rapid urbanization, dietary shifts, and sedentary lifestyles are well-recognized contributors to this crisis, they do not fully account for the disproportionately high rates of diabetes observed across the Mexican population. Researchers have long suspected that the unique genetic architecture of the Mexican people—a result of centuries of admixture between Indigenous American, European, and African populations—plays a foundational role in this susceptibility.
Study Design: The Mexico City Prospective Study (MCPS)
To quantify the impact of genetic ancestry on metabolic health, researchers conducted a cross-sectional analysis using data from the Mexico City Prospective Study (MCPS). This massive cohort included 134,548 individuals recruited between 1998 and 2004. The study integrated sociodemographic surveys, clinical measurements, and detailed genomic sequencing to provide a high-resolution view of the relationship between Indigenous American (AMR) ancestry and glycemic status.
The researchers defined type 2 diabetes based on self-reported diagnosis, use of glucose-lowering medication, or an HbA1c level of 6.5% or higher. Prediabetes was identified in individuals with an HbA1c between 5.7% and 6.4%. By using logistic regression models, the team was able to estimate the odds of developing these conditions relative to the percentage of AMR ancestry, while carefully controlling for confounding variables such as age, sex, and body mass index (BMI).
The Dose-Response Relationship of AMR Ancestry
The study found a striking dose-response relationship between genomic ancestry and diabetes risk. The mean AMR ancestry among participants was 66.2%. When the cohort was divided into tenths based on ancestry percentage, a clear trend emerged: in the lowest decile (mean AMR 34.8%), the prevalence of T2D was 13.5%; in the highest decile (mean AMR 94.7%), the prevalence jumped to 23.4%.
Quantitative Impact on Disease Risk
After adjusting for age and sex, each 20% absolute increase in AMR ancestry was associated with a 45% increase in the odds of type 2 diabetes (OR 1.45; 95% CI 1.43-1.48) and a 28% increase in the odds of prediabetes (OR 1.28; 95% CI 1.26-1.30). This finding underscores that the risk is not binary but scales linearly with the proportion of Indigenous American genetic markers.
Independence from Lifestyle and Adiposity
One of the most significant findings of this research is that the risk associated with AMR ancestry persists even when accounting for traditional risk factors. When the models were further adjusted for socioeconomic status, lifestyle habits, and adiposity (BMI), the odds ratio for T2D remained high at 1.33 per 20% increase in AMR. This suggests that while obesity and lifestyle are critical, there is an underlying biological susceptibility inherent to the AMR genomic profile that operates independently of environmental factors.
Age and Sex Disparities in Genetic Risk
The data revealed intriguing interactions between genomic risk and demographic factors. The association between higher AMR ancestry and diabetes was notably stronger in women than in men. Furthermore, the genetic effect appeared more potent in younger participants than in older ones. This suggests that the genetic predisposition may lead to an earlier onset of the disease, which is particularly concerning for long-term public health, as early-onset diabetes is associated with a higher risk of lifetime complications, including renal failure and cardiovascular disease.
Biological Plausibility and the Role of Polygenic Risk
The study also utilized a type 2 diabetes polygenic risk score (PRS) to see if known genetic variants could explain the ancestry effect. While the PRS accounted for some of the risk, it did not eliminate the association between AMR ancestry and diabetes. This indicates that there are likely many yet-to-be-identified genetic variants specific to Indigenous American populations that contribute to metabolic risk. These may include variants affecting insulin sensitivity, beta-cell function, or lipid metabolism that are not well-captured by current genetic arrays primarily designed for European-ancestry populations.
Clinical and Public Health Implications
The findings have profound implications for healthcare policy in Mexico and other regions with significant AMR populations. First, they suggest that the majority of the Mexican population has a baseline genetic susceptibility to diabetes that is significantly higher than that of European populations. This renders the standard international prevention guidelines potentially insufficient for the Mexican context.
Health systems must consider earlier and more aggressive screening programs. If a large segment of the population is genetically predisposed to transition from prediabetes to T2D at a younger age, intervention must occur much sooner in the life course. Furthermore, the findings support the development of population-targeted preventive strategies that are culturally and biologically tailored to the needs of admixed and Indigenous communities.
Expert Commentary and Methodological Considerations
While the MCPS provides one of the most robust datasets available, some experts note that the cross-sectional nature of this specific analysis means that it captures a snapshot in time. However, the sheer scale of 134,548 participants provides immense statistical power. The use of HbA1c as a diagnostic tool, alongside genetic sequencing, adds a layer of objective clinical data that strengthens the study’s conclusions. A limitation acknowledged by the researchers is the potential for unmeasured environmental confounders, though the rigorous adjustment for socioeconomic status and BMI mitigates much of this concern.
This research serves as a call to action for the inclusion of diverse ancestries in genomic research. For too long, metabolic studies have been dominated by cohorts of European descent, leading to a gap in our understanding of how diabetes manifests in other populations. The MCPS data helps close this gap and provides a blueprint for precision public health in Latin America.
Conclusion
The Mexico City Prospective Study demonstrates that Indigenous American genomic ancestry is a fundamental driver of the type 2 diabetes epidemic in Mexico. With odds ratios reaching over 4.0 for those with 100% AMR ancestry, the genetic component of this disease cannot be ignored. Moving forward, the integration of genomic risk into public health planning will be essential for curbing the prevalence of diabetes and improving the metabolic health of the Mexican population.
Funding and References
The study was funded by the Mexican Health Ministry, the National Council of Science and Technology for Mexico, Wellcome Trust, Cancer Research UK, British Heart Foundation, Kidney Research UK, and the UK Medical Research Council.
Reference: Berumen J, Kuri-Morales P, Torres JM, et al. The effect of Indigenous American genomic ancestry on type 2 diabetes in Mexico: an analysis of 134,548 individuals from the Mexico City Prospective Study. Lancet Public Health. 2026 Feb;11(2):e111-e119. doi: 10.1016/S2468-2667(25)00305-6.
