Genetic evidence that the causal association of educational attainment with reduced risk of Alzheimer's disease is driven by intelligence. (20th December 2022)

• Record Type: Journal Article
• Authors: Thorp, Jackson G; Mitchell, Brittany L; Gerring, Zachary F; Ong, Jue‐Sheng; Gharahkhani, Puya; Derks, Eske M; Lupton, Michelle K
• Is Part Of: Alzheimer's & dementia. Volume 18(2022)Supplement 3
• Page Start: n/a
• Page End: n/a
• Publication Date: 2022-12-20
• Subjects: Alzheimer's disease -- Periodicals; Alzheimer Disease -- Periodicals; Dementia -- Periodicals; Démence; Maladie d'Alzheimer; Périodique électronique (Descripteur de forme); Ressource Internet (Descripteur de forme); 616.83
• DOI: 10.1002/alz.061144
• Languages: English
• ISSNs: 1552-5260

Abstract

Abstract: Background: Alzheimer's disease (AD) is predicted to affect 132 million people by 2050. Targeting modifiable lifestyle risk factors that are associated with an increased risk of AD could prevent a large proportion of dementia cases, allowing people to reach the end of their life dementia free. However, evidence obtained from observational studies does not take into account how risk factors are correlated with one another, and whether they causally contribute to increased AD risk. In this study, we determine whether the relationship between twelve previously speculated AD risk factors and AD susceptibility is consistent with causality using large‐scale genetic data (table 1). Method: We conduct multivariable Mendelian Randomization (MR) analyses to identify causal risk factors of AD while controlling for genetic pleiotropy, using genetic instruments from the most well powered GWAS studies currently available. We also use GWAS‐by‐subtraction implemented with genomic structural equation modelling (genomic SEM) to understand the cognitive and non‐cognitive components of the causal association of EA on AD risk. Result: We identified significant positive correlations between AD and physical activity and loneliness, and significant negative correlations with educational attainment (EA), intelligence and household income. Using GWAS‐by‐subtraction to partition EA into cognitive (intelligence) and noncognitive genetic factors, we showed a significant genetic correlation between AD and the cognitive factor, but not the noncognitive factor (figure 1). Univariable MR found EA, intelligence, household income and the cognitive factor to all be causally protective against AD. Multivariable MR analysis showed that higher intelligence lowers AD risk, independent of EA and household income. There was no evidence that EA lowers AD risk, independent of intelligence. In addition the cognitive (intelligence) component of EA decreased AD risk with no significant influence of the noncognitive factor (table 2). Conclusion: From the risk factors tested only the cognitive component of EA (i.e., intelligence) is an independent causal risk factor for AD. To reduce incidence of AD this cognitive aspect of EA would need to be modified. It is questionable whether substantial modification of intelligence is achievable through simple interventions such as improving access to extended education.