Yidan Zhang

Introduction: Both genetic and modifiable lifestyle factors contribute to dementia risk, yet their separate and joint predictive value for dementia and its intermediate markers (cognitive function and brain structure), is unclear. This study evaluated APOE ε4 status, AD polygenic risk (excluding APOE), and the updated LIBRA2 index (14 modifiable factors) in predicting dementia, cognition, and brain imaging biomarkers. Methods: To examine associations of APOE ε4, PRS- APOE , and LIBRA2 with incident cases of dementia and AD, Cox models were applied to data of 345,785 UK Biobank participants at baseline (median follow-up: 13.8 years). Models were adjusted for age, sex, and other key covariates. Linear regression was used to examine associations with cognition (N=42,120) and dementia-related MRI markers (N = 31,180, such as fractional anisotropy/mean diffusivity, white matter hyperintensities, gray matter volume, hippocampus, and entorhinal cortex) among individuals without dementia. Results: During follow-up, 6,300 participants developed dementia (132 cases per 100,000 person-years), including 2,803 cases of Alzheimer’s disease. All three predictors were independently associated with incident dementia and AD. Compared to non-carriers, APOE ε4 carriers had a threefold increased risk of dementia (HR = 3.02, 95% CI: 2.88–3.18) and over a fourfold increased risk of AD (HR = 4.33, 95% CI: 4.01–4.68). Each 1 standard deviation (SD) increase in PRS-APOE was associated with a 26% higher risk of dementia (HR = 1.26, 95% CI: 1.23–1.29) and a 35% higher risk of AD (HR = 1.35, 95% CI: 1.30–1.40). Each 1-SD increase in LIBRA2 score was linked to a 33% increase in dementia risk (HR = 1.33, 95% CI: 1.30–1.36) and 20% for AD (HR = 1.20, 95% CI: 1.15–1.24). Beyond individual effects, we evaluated model-level discrimination using the C-index. Representative results for dementia showed modest improvement over the base model (C-index = 0.811) with PRS-APOE (0.816) or LIBRA2 (0.819), and greater improvement with APOE ε4 (0.836). Combining APOE ε4 and LIBRA2 yielded near-optimal discrimination (0.843), close to the full model (0.846). While APOE ε4 was the dominant predictor of dementia diagnosis, LIBRA2 showed unique strongest predictive power for processing speed and neuroimaging markers. LIBRA2 was linked to a wide range of neuroimaging markers (e.g., WMH, WM integrity, grey matter, ventricles), while PRS-APOE was only associated with ventricular volume. APOE ε4 was related to couple of white matter measures. Significant LIBRA2-APOE interactions were observed in relation to both all-cause dementia and AD. The association between LIBRA2 and dementia risk was stronger among APOE ε4 non-carriers (interaction HR = 0.845, 95% CI: 0.807–0.884 for all-cause dementia; HR = 0.851, 95% CI: 0.792–0.914 for AD; both p adj < 0.001), suggesting that unfavorable lifestyle may have a greater impact in individuals without genetic risk. No significant interactions were found in cognitive or imaging models. Conclusion: The APOE ε4 genotype was the strongest single predictor of dementia and cognitive outcomes. In contrast, the LIBRA2 index was most strongly associated with processing speed and neuroimaging markers, demonstrating its critical role in non-diagnostic brain health outcomes. These findings highlight the complementary and domain-specific contributions of genetic and lifestyle factors in dementia risk modeling.

Cognitive function is shaped by both genetic and environmental factors. The Lifestyle for Brain Health (LIBRA) index, based on epidemiological evidence, targets modifiable risk and protective factors during midlife and early old age. This study compares the explanatory power of polygenic risk scores (PGSs) and the LIBRA score in relation to cognitive function among middle-aged and older adults in the Maastricht Study.We analyzed 17 cognition-related PGSs individually and combined significant PGSs into a multi-PGS model. The performance of the LIBRA model, individual PGS models, the multi-PGS model, and integrated LIBRA-genotype models was evaluated. The intelligence PGS exhibited the strongest association with cognitive function (β = 0.109, 95% CI: 0.094–0.124). Five PGSs remained significant and were incorporated into the multi-PGS model. Compared to the LIBRA-only model, genetic models, including either the top single-PGS or multi-PGS, showed improved performance, with Adjusted R² increasing by 2.5–3.1%. The LIBRA + multi-PGS model provided the highest explanatory power, with a 4% increase in Adjusted R², validated by 10-fold cross-validation.These results underscore the value of integrating PGSs, particularly multi-PGS models, with the LIBRA score to enhance the prediction of cognitive outcomes. This genetic-environmental approach offers potential for better understanding and predicting cognitive function in middle-aged to early old-aged populations, with implications for clinical and public health applications.

Cognitive function is shaped by both genetic and environmental factors. The Lifestyle for Brain Health (LIBRA) index, based on epidemiological evidence, targets modifiable risk and protective factors during midlife and early old age. This study compares the explanatory power of polygenic risk scores (PGSs) and the LIBRA score in relation to cognitive function among middle-aged and older adults in the Maastricht Study. We analyzed 17 cognition-related PGSs individually and combined significant PGSs into a multi-PGS model. The performance of the LIBRA model, individual PGS models, the multi-PGS model, and integrated LIBRA-genotype models was evaluated. The intelligence PGS exhibited the strongest association with cognitive function (β = 0.109, 95% CI: 0.094-0.124). Five PGSs remained significant and were incorporated into the multi-PGS model. Compared to the LIBRA-only model, genetic models, including either the top single-PGS or multi-PGS, showed improved performance, with Adjusted R² increasing by 2.5% to 3.1%. The LIBRA + multi-PGS model provided the highest explanatory power, with a 4% increase in Adjusted R², validated by 10-fold cross-validation. These results underscore the value of integrating PGSs, particularly multi-PGS models, with the LIBRA score to enhance the prediction of cognitive outcomes. This genetic-environmental approach offers potential for better understanding and predicting cognitive function in middle-aged to early old-aged populations, with implications for clinical and public health applications.

Background: Variation in the Apolipoprotein E (APOE) gene is a key genetic determinant of Alzheimer’s disease (AD) risk and is associated with AD-related neuroimaging changes. Lifestyle factors are also associated with AD risk and may interact with APOE to influence neuroimaging biomarkers. However, evidence on these interactions remains limited and inconsistent, particularly regarding composite healthy lifestyle scores in large-scale cohorts. Methods: We analyzed neuroimaging data from 21,014 UK Biobank participants (mean age: 55) to examine neuroimaging markers relevant to AD and assess the independent and interactive effects of APOE ε2/ ε4 dosage and healthy lifestyle risk factors. These biomarkers included diffusion tensor imaging (DTI) metrics-fractional anisotropy (FA) and mean diffusivity (MD), white matter hyperintensity (WMH) burden, and volumetric measures of medial temporal lobe regions such as the entorhinal cortex, parahippocampal region, amygdala, and hippocampus. Results: In the APOE dosage model, ε4 dosage was associated with lower bilateral hippocampal volume, left parahippocampal volume and lower WM integrity, particularly in the posterior thalamic radiation and cingulum-hippocampus and sagittal stratum. A higher healthy lifestyle score was broadly associated with lower WMH burden and higher WM integrity. No statistically significant evidence was found for effect modification by lifestyle on the association between APOE and MRI markers. Conclusions: Our results do not provide support for the idea that healthy lifestyle factors buffer or mitigate the detrimental effects of the APOE dosage on MRI markers, but rather support a primarily outright association between APOE ε4 dosage and worse MRI markers.