BACKGROUND: Apolipoprotein E (APOE) alleles are well-established genetic risk factors for Alzheimer's disease (AD), but their effects on AD biomarkers (amyloid beta [Aβ]42/40, phosphorylated tau [p-tau]181, neurofilament light chain [NfL], and glial fibrillary acidic protein [GFAP]) may vary across populations due to ancestry-, age-, and sex-related differences. We hypothesized that these effects vary across Hispanic/Latino background groups with distinct ancestral admixture.

METHODS: We analyzed ε2 and ε4 allele associations with AD biomarkers using survey-weighted linear regression models, adjusting for demographic covariates. Secondary analyses examined genetic analysis group- and ancestry-specific effects.

RESULTS: ε4 was associated with lower Aβ42/40 and higher p-tau181and GFAP levels, but not with NfL, suggesting its role in Aβ and tau deposition and neuroinflammation. ε4 associations were stronger in those with higher European and lower African ancestry.

DISCUSSION: These findings expand on prior studies suggesting that genetic ancestry modifies APOE-associated AD risk in Hispanic/Latino populations and highlight the importance of capturing ancestry-based heterogeneity in AD biomarker research.

Prediction models for cognitive aging measures have largely evaluated demographic variables and APOE carrier status in populations of European ancestry. To comprehensively assess prediction models among Hispanic/Latinos, we considered 12 models (6 predictor sets and 2 methods) for global cognitive score change (GCSC) and mild cognitive impairment (MCI) in the Study of Latinos-Investigation of Neurocognitive Aging (SOL-INCA) (N = 5856). Based on the average mean squared error (MSE) for GCSC or average area under the curve (AUC) for MCI across 100 randomly split testing and training sets, performance was similar across models, but slightly better for the following models: the chronic conditions model and genetic model (mean MSEs = 0.2464) using gradient-boosted trees for GCSC prediction and the chronic conditions model (mean AUC = 62%) and metabolite model (mean AUC = 60%) using logistic regression for MCI prediction. Using the Shapley Additive Explanations (SHAP) method, age at baseline, time between exams, and sex were the most important predictors for GCSC, followed by diabetes and global ancestral proportions. Diabetes and the metabolite ribitol had the highest influence on prediction of MCI. Although prediction performance was not especially high and did not vary greatly across models, incorporating information on diabetes, ancestry and metabolites may help improve prediction of GCSC and MCI.

BACKGROUND: The APOE ε4 allele has weaker association with ADRD outcomes in Hispanic/Latino populations compared to non-Hispanic White and East Asian populations.

METHODS: We used whole-genome sequencing data from 13,025 Hispanic/Latino adults to infer population groups (clusters) from short DNA sequences at the APOE gene region. We estimated the associations between these clusters and mild cognitive impairment (MCI) and age-adjusted significant cognitive decline assessed via the Study of Latinos-Investigation of Neurocognitive Aging (SOL-INCA) study (n = 5334). We compared these associations to those of the conventional APOE alleles.

RESULTS: We identified three clusters of individuals. Relative to the largest Cluster 1, being in Cluster 3 had higher likelihood of having significant cognitive decline, with odds ratio (OR) = 1.47, 95% confidence interval (CI) [1.18, 1.84], p < 0.001. The association with having prevalent MCI at the SOL-INCA exam was not statistically significant, with OR = 1.33, 95% CI [0.97, 1.83], p = 0.08. Associations of the ε4 allele with these traits were not statistically significant.

DISCUSSION: The new APOE profile has stronger risk association with age-adjusted significant cognitive decline in SOL-INCA Hispanics/Latinos compared to the ε4 allele.