High prevalence of humoral autoimmunity in first-degree relatives of Mexican type 1 diabetes patients

Clinical characterization of data-driven diabetes subgroups in Mexicans using a reproducible machine learning approach

INTRODUCTION

Previous reports in European populations demonstrated the existence of five data-driven adult-onset diabetes subgroups. Here, we use self-normalizing neural networks (SNNN) to improve reproducibility of these data-driven diabetes subgroups in Mexican cohorts to extend its application to more diverse settings.

RESEARCH DESIGN AND METHODS

We trained SNNN and compared it with k-means clustering to classify diabetes subgroups in a multiethnic and representative population-based National Health and Nutrition Examination Survey (NHANES) datasets with all available measures (training sample: NHANES-III, n=1132; validation sample: NHANES 1999-2006, n=626). SNNN models were then applied to four Mexican cohorts (SIGMA-UIEM, n=1521; Metabolic Syndrome cohort, n=6144; ENSANUT 2016, n=614 and CAIPaDi, n=1608) to characterize diabetes subgroups in Mexicans according to treatment response, risk for chronic complications and risk factors for the incidence of each subgroup.

RESULTS

SNNN yielded four reproducible clinical profiles (obesity related, insulin deficient, insulin resistant, age related) in NHANES and Mexican cohorts even without C-peptide measurements. We observed in a population-based survey a high prevalence of the insulin-deficient form (41.25%, 95% CI 41.02% to 41.48%), followed by obesity-related (33.60%, 95% CI 33.40% to 33.79%), age-related (14.72%, 95% CI 14.63% to 14.82%) and severe insulin-resistant groups. A significant association was found between the SLC16A11 diabetes risk variant and the obesity-related subgroup (OR 1.42, 95% CI 1.10 to 1.83, p=0.008). Among incident cases, we observed a greater incidence of mild obesity-related diabetes (n=149, 45.0%). In a diabetes outpatient clinic cohort, we observed increased 1-year risk (HR 1.59, 95% CI 1.01 to 2.51) and 2-year risk (HR 1.94, 95% CI 1.13 to 3.31) for incident retinopathy in the insulin-deficient group and decreased 2-year diabetic retinopathy risk for the obesity-related subgroup (HR 0.49, 95% CI 0.27 to 0.89).

CONCLUSIONS

Diabetes subgroup phenotypes are reproducible using SNNN; our algorithm is available as web-based tool. Application of these models allowed for better characterization of diabetes subgroups and risk factors in Mexicans that could have clinical applications.

Diabetes is associated with a higher risk of mortality among women in a middle-income country: Results form the Mexican Teacher's cohort study

AIMS

In Mexico City, the mortality rate among patients with diabetes appears to be four times that of people without diabetes. Our study aimed to refine analyses of the impact of diabetes on mortality in a large cohort of women from different areas in Mexico with healthcare insurance.

METHODS

Our study followed 111,299 women with comprehensive healthcare coverage from the Mexican Teachers' Cohort. After a median follow-up of 7.8years, 5514 (5%) prevalent self-reported diabetes cases and 4023 incident cases were identified, while deaths were identified through employers' databases and next-of-kin reports, with dates and causes of death for 1121 women obtained from mortality databases. Hazard ratios (HRs) for total and cause-specific mortality were estimated by Cox regression models, using follow-up time as the time scale and allowing for time-variable diabetes status after adjusting for age, socioeconomic status, use of health services, and anthropometric and lifestyle variables.

RESULTS

In multivariable-adjusted models, the HR for all-cause mortality was 3.28 (95% CI: 2.86-3.75) in women with vs. without diabetes. The impact of diabetes on mortality was higher in rural vs. urban areas (HR: 4.72 vs. 2.98, respectively). HRs were 1.57 and 23.44 for cancer and renal disease mortality, respectively.

CONCLUSION

In women with healthcare coverage in Mexico, the magnitude of the association between diabetes and all-cause mortality was higher than that observed in high-income countries, but less than what has previously been reported for Mexico. Such elevated mortality suggests a lack of adequate access to quality diabetes care in the population despite comprehensive healthcare coverage.