Zhao Yong-Li, Hao Yi-Ning, Ge Yi-Jun, Zhang Yi, Huang Lang-Yu, Fu Yan, Zhang Dan-Dan, Ou Ya-Nan, Cao Xi-Peng, Feng Jian-Feng, Cheng Wei, Tan Lan, Yu Jin-Tai
Department of Neurology, Institute of Neurology, State Key Laboratory of Medical Neurobiology and MOE Frontier Center for Brain Science, Shanghai Medical College, Huashan Hospital, Fudan University, 12th Wulumuqi Zhong Road, Shanghai, 200040, China.
Department of Neurology, Qingdao Municipal Hospital, Qingdao University, No. 5 Donghai Middle Road, Qingdao, 266071, China.
Alzheimers Res Ther. 2025 Jan 7;17(1):13. doi: 10.1186/s13195-025-01670-5.
Evidence indicates that cognitive function is influenced by potential environmental factors. We aimed to determine the variables influencing cognitive function.
Our study included 164,463 non-demented adults (89,644 [54.51%] female; mean [SD] age, 56.69 [8.14] years) from the UK Biobank who completed four cognitive assessments at baseline. 364 variables were finally extracted for analysis through a rigorous screening process. We performed univariate analyses to identify variables significantly associated with each cognitive function in two equal-sized split discovery and replication datasets. Subsequently, the identified variables in univariate analyses were further assessed in a multivariable model. Additionally, for the variables identified in multivariable model, we explored the associations with longitudinal cognitive decline. Moreover, one- and two- sample Mendelian randomization (MR) analyses were conducted to confirm the genetic associations. Finally, the quality of the pooled evidence for the associations between variables and cognitive function was evaluated.
252 variables (69%) exhibited significant associations with at least one cognitive function in the discovery dataset. Of these, 231 (92%) were successfully replicated. Subsequently, our multivariable analyses identified 41 variables that were significantly associated with at least one cognitive function, spanning categories such as education, socioeconomic status, lifestyle factors, body measurements, mental health, medical conditions, early life factors, and household characteristics. Among these 41 variables, 12 were associated with more than one cognitive domain, and were further identified in all subgroup analyses. And LASSO, rigde, and principal component analysis indicated the robustness of the primary results. Moreover, among these 41 variables, 12 were significantly associated with a longitudinal cognitive decline. Furthermore, 22 were supported by one-sample MR analysis, and 5 were further confirmed by two-sample MR analysis. Additionally, the quality of the pooled evidence for the associations between 10 variables and cognitive function was rated as high. Based on these 10 identified variables, adopting a more favorable lifestyle was significantly associated with 38% and 34% decreased risks of dementia and Alzheimer's disease (AD).
Overall, our study constructed an evidence database of variables associated with cognitive function, which could contribute to the prevention of cognitive impairment and dementia.
有证据表明认知功能受潜在环境因素影响。我们旨在确定影响认知功能的变量。
我们的研究纳入了来自英国生物银行的164463名无痴呆症成年人(89644名[54.51%]女性;平均[标准差]年龄56.69[8.14]岁),他们在基线时完成了四项认知评估。通过严格筛选过程最终提取364个变量进行分析。我们在两个规模相等的发现和重复数据集中进行单变量分析,以确定与每种认知功能显著相关的变量。随后,在多变量模型中进一步评估单变量分析中确定的变量。此外,对于多变量模型中确定的变量,我们探讨了其与纵向认知衰退的关联。此外,进行了单样本和两样本孟德尔随机化(MR)分析以确认基因关联。最后,评估了变量与认知功能之间关联的汇总证据质量。
252个变量(69%)在发现数据集中与至少一种认知功能表现出显著关联。其中,231个(92%)成功得到重复验证。随后,我们的多变量分析确定了41个与至少一种认知功能显著相关的变量,涵盖教育、社会经济地位、生活方式因素、身体测量、心理健康、医疗状况、早年因素和家庭特征等类别。在这41个变量中,12个与多个认知领域相关,并在所有亚组分析中进一步得到确认。LASSO、岭回归和主成分分析表明主要结果具有稳健性。此外,在这41个变量中,12个与纵向认知衰退显著相关。此外,22个得到单样本MR分析支持,5个进一步得到两样本MR分析确认。此外,10个变量与认知功能之间关联的汇总证据质量被评为高。基于这10个确定的变量,采取更有利的生活方式与痴呆症和阿尔茨海默病(AD)风险降低38%和34%显著相关。
总体而言,我们的研究构建了一个与认知功能相关变量的证据数据库,这可能有助于预防认知障碍和痴呆症。