Variables associated with cognitive function: an exposome-wide and mendelian randomization analysis - Yong-Li Zhao; Yi-Ning Hao; Yi-Jun Ge; Yi Zhang; Lang-Yu Huang; Yan Fu; Dan-Dan Zhang; Ya-Nan Ou; Xi-Peng Cao; Jian-Feng Feng; Wei Cheng; Lan Tan; et al. (Alzheimer’s Research & Therapy)
Abstract Background Evidence indicates that cognitive function is influenced by potential environmental factors. We aimed to determine the variables influencing cognitive function. Methods 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. Results 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). Conclusion Overall, our study constructed an evidence database of variables associated with cognitive function, which could contribute to the prevention of cognitive impairment and dementia.