Genetics Impact Risk of Alzheimer's Disease through Mechanisms Modulating Structural Brain Morphology in Late Life

In recent years, Alzheimer’s disease (AD) has become a significant health problem affecting the elderly population worldwide. Its related neuropathological changes can begin decades before the appearance of clinical symptoms. To explore more comprehensively the relationship between AD risk and brain morphology, a research team conducted a bidirectional two-sample Mendelian Randomisation (MR) study to investigate whether genetic susceptibility increases AD risk by affecting brain structure.

Research Background Pathological changes in AD usually first appear in the medial temporal lobe and then spread to the frontal lobe, parietal lobe, and the neocortex of the temporal lobe as well as subcortical regions. β-amyloid protein accumulation may have started in the brain 20 years prior to clinical diagnosis of the disease. Thus, integrating biological data prior to the appearance of disease symptoms is crucial for understanding the etiology, timeline, and progression of AD, and for developing early detection and screening strategies.

Research Purpose The aim of this study was to evaluate the influence of genetic susceptibility on overall and localized cortical thickness, estimated total intracranial volume, subcortical structure volume, and total white matter volume, and to explore whether these structural changes were associated with an increased risk of AD.

Source of the Paper This study was written by Roxanna Korologou-Linden and others, and was published in the Journal of Neurology, Neurosurgery & Psychiatry. The research was conducted by scientists from the Medical Research Council Integrative Epidemiology Unit of Bristol University, among other institutions, and was published in 2024.

Research Methods The study used a bidirectional two-sample Mendelian Randomisation method to estimate the causal relationship between genetic susceptibility to AD and cortical thickness and subcortical structure volume. Data came from several independent cohorts, including the Adolescent Brain Cognitive Development (ABCD), the Generation R, the IMAGEN, the Avon Longitudinal Study of Parents and Children (ALSPAC), and the UK Biobank (UKB). These studies included 37,680 participants aged between 8 and 81 years. In addition, data from the ENIGMA Consortium was utilized, which involved 37,741 participants.

Research Process a) Research Process The research unfolded through the following steps: 1. Sample Selection and Data Acquisition: Significant related Single Nucleotide Polymorphisms (SNPs) were extracted from the largest scale Genome-Wide Association Studies (GWAS) of AD. Brain structure imaging data were obtained from different study cohorts. 2. Mendelian Randomization Analysis: A two-sample Mendelian Randomisation was conducted to estimate whether genetic susceptibility to AD affects brain structure based on SNPs’ genetic association with AD. SNPs associated with AD were extracted from multiple cohorts and data formalization and standardization were performed. 3. Statistical Analysis: Random effect inverse variance weighted regression analysis was used to calculate the estimated effect of SNPs on brain structure. Stratified analysis was performed for different age groups to observe the effect of age on results.

b) Main Results It was found that the influence of AD risk allele on cortical and subcortical brain structures depend on age. These effects begin to manifest during adulthood, with evidence being less strong in children and young adults. Some non-typical AD-related brain structures (like the thalamus in the striatum) also showed significant genetic effects. Additionally, the study’s findings did not support the hypothesis that morphological changes in brain structure significantly impact AD risk.

c) Conclusion and Research Value The study indicates that the genetic susceptibility of AD primarily affects the risk of AD by influencing brain structure indices in older age, rather than by increasing structural brain reserve. Future research should focus on structural and functional brain morphology changes starting in adulthood to better understand AD mechanisms. These findings are significant for developing new early detection and prevention strategies.

d) Research Highlights - Bidirectional Mendelian Randomization Method: For the first time, a bidirectional two-sample Mendelian Randomisation method was used to explore the bidirectional causality between genetic susceptibility to AD and brain structure. - Large-scale Cohort Data: Data from large-scale cohorts spanning a wide age range from children to the elderly was used. - Multi-sample Analysis: Cross-cohort multi-sample analysis was used to enhance statistical power and robustness of the results. - New Findings: Significant genetic effects for some non-typical AD-related brain structures, such as the thalamus, were discovered.

Other Valuable Information The study also noted that, while genetic susceptibility to AD had significant effects on some structural brain reserves, these effects were mainly evident in middle age and beyond, with lesser presence earlier in life. Future research needs to verify these results through longitudinal design and integrate biological and clinical data to understand more fully the early pathological changes of AD and their impact on brain structure