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Updated: May 20, 2025

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Nutritional interventions for preventing cognitive decline in patients with mild cognitive impairment and Alzheimer's
Qian He1, Adam N Bennett1, Chuyun Zhang1
1Department of Biomedical Sciences, City University of Hong Kong, Hong Kong Special Administrative Region of China.
Background:
As the population ages rapidly, cognitive impairment, especially in conditions like Alzheimer's disease (AD) and mild cognitive impairment (MCI), has become a crucial public health issue. Nutritional interventions have garnered attention as a promising non-pharmacological strategy for maintaining cognitive function and decelerating its decline.
Objective:
This study aimed to evaluate the effectiveness of various nutritional interventions in preventing cognitive impairment and elucidate intricate biological pathways linking nutritional interventions to cognitive function through a comprehensive approach involving systematic review, network meta-analysis (NMA), and Mendelian randomization (MR) analysis.
Methods:
We utilized pair-wise comparisons and NMA to evaluate the efficacy of different nutritional interventions on cognitive function in patients with decreased cognitive abilities. A systematic search in three biomedical databases was performed for double-blinded, randomized controlled trials (RCTs) or head-to-head comparisons up to December 31, 2024. The NMA has been registered at the International Prospective Register of Systematic Reviews (PROSPERO; CRD42022331173). Moreover, to clarify the biological mechanisms linking nutritional interventions to cognitive impairment, we conducted two-sample MR analyses to assess the potential causal relationships between 9 genetically predicted nutrient levels derived from extensive genome-wide association studies (GWASs) and 12 biomarkers linked to brain aging.
Results:
This study encompassed 52 trials with 8452 participants, 9 GWASs examining genetically predicted nutrient levels with a total of 603,996 participants, and 12 GWASs investigating brain aging biomarkers with a total of 2,405,530 participants. The NMA demonstrated that the multi-ingredient intervention outperformed other interventions significantly (standardized mean difference [SMD] = 2.03; 95 % credible interval [95 % CrI] = 0.97-3.09, P = 0.0002). In the MR analysis, the findings indicated that the multi-ingredient intervention was linked to reduced C-reactive protein (CRP) levels (odds ratios [OR] = 0.96, 95 % confidence interval [95 % CI] = 0.93-0.99, P = 0.014), suggesting that the multi-ingredient intervention may mitigate cognitive impairment by reducing inflammation.
Conclusions:
Our NMA amalgamated evidence underscoring multi-ingredient interventions as the most efficacious strategy for attenuating cognitive decline in individuals with MCI and AD. Furthermore, the MR analysis unveiled the mechanisms underpinning the protective effects of multi-ingredient interventions, potentially offering benefits even in the early stages of neurodegeneration by mitigating oxidative stress and inflammation.
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