Investigating causal effects of HDL-C on cognitive function through cross-sectional and Mendelian randomization analyses: concentration-response patterns and clues for Alzheimer's disease prevention.
IF 6.1 3区 生物学Q1 MATHEMATICAL & COMPUTATIONAL BIOLOGY
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引用次数: 0
Abstract
Background: Disrupted cholesterol homeostasis may accelerate cognitive aging. This study investigated the relationship between serum HDL-C levels and cognitive function, utilizing cross-sectional data and Mendelian randomization (MR) analysis.
Methods: A cross-sectional study was conducted using data from the National Health and Nutrition Examination Survey (NHANES) 2011-2014, including 19,931 participants. Among them, 2,777 individuals aged 60 years and older with complete HDL-C levels and cognitive function data were included. Cognitive function was assessed using tests such as the Consortium to Establish a Registry for Alzheimer's Disease Immediate and Delayed Recall, the Animal Fluency Test, and the Digit Symbol Substitution Test. Additionally, MR analysis was employed to assess the causal relationship between genetically predicted HDL-C and dementia.
Results: Gender-stratified analyses revealed sex-specific patterns in the relationship between HDL-C and cognitive function. In fully adjusted linear models, men showed consistently positive associations across all cognitive domains, including delayed recall (β = 0.10, 95% CI 0.04-0.17, p < 0.001), immediate recall (β = 0.06, 95% CI 0.00-0.12, p = 0.047), verbal fluency (β = 0.20, 95% CI 0.14-0.26, p < 0.001), processing speed (β = 0.09, 95% CI 0.05-0.14, p < 0.001), and overall composite score (β = 0.45, 95% CI 0.29-0.62, p < 0.001). In women, these associations were attenuated or non-significant for immediate recall, delayed recall, and composite cognition, suggesting non-linearity. Further concentration-response analyses revealed a linear positive association in men and an inverted U-shaped relationship in women. MR analyses indicated a protective association between genetically predicted HDL-C and Alzheimer's disease risk (OR = 0.51, 95% CI 0.29-0.89, p = 0.019). However, sensitivity analyses revealed attenuation after MR-PRESSO outlier correction (β=-0.013, p = 0.756), and inconsistent estimates across methods, with significant heterogeneity (Q-test p < 0.001) and evidence of pleiotropy. In multivariable analysis, adjusting for LDL-C and TG, IVW (β = 0.290, p = 0.048) and Lasso regression (β = 0.752, p = 0.008) indicated weak positive correlations. However, MR-Egger (β = 0.752, p = 0.008) revealed potential pleiotropic interference (intercept p = 0.050).
Conclusions: Our findings suggest that maintaining optimal serum HDL-C levels may help preserve cognitive function in older adults. Notably, sex-specific associations were observed, warranting further investigation into underlying mechanisms.
期刊介绍:
BioData Mining is an open access, open peer-reviewed journal encompassing research on all aspects of data mining applied to high-dimensional biological and biomedical data, focusing on computational aspects of knowledge discovery from large-scale genetic, transcriptomic, genomic, proteomic, and metabolomic data.
Topical areas include, but are not limited to:
-Development, evaluation, and application of novel data mining and machine learning algorithms.
-Adaptation, evaluation, and application of traditional data mining and machine learning algorithms.
-Open-source software for the application of data mining and machine learning algorithms.
-Design, development and integration of databases, software and web services for the storage, management, retrieval, and analysis of data from large scale studies.
-Pre-processing, post-processing, modeling, and interpretation of data mining and machine learning results for biological interpretation and knowledge discovery.