The influence of genetic predisposition for Alzheimer's disease on default mode network co‐activation in young adults: A Human Connectome Project replication study. (December 2021) - Mentink, Lara J.
Abstract: Background: A landmark study by Filippini et al., where authors reported an increased default mode network (DMN) co‐activation during rest in young APOE ε4‐carriers, failed to replicate [1, 2]. The rise of genome‐wide association studies (GWAS) in Alzheimer's disease (AD) has shown there is a significant polygenic contribution of common genetic variants to AD, in addition to the larger effects of APOE variants. Therefore, in our replication study, we used polygenic risk scores (PRS) to better understand how polygenic variation may influence brain structure and function. Method: We included participants with inferred European ancestry from the HCP S1200 dataset. We followed the methods of [1] for the resting‐state fMRI analysis. For structural MRI analysis, we assessed gray matter volume with FreeSurfer instead of gray matter density using voxel‐based morphometry. PRS allows data‐driven investigation of the aggregated effects of many common risk variants as determined in a large European GWAS [3]. We used the threshold determined as optimal for predicting AD status using PRS in Jansen et al., (P<1.69x10 ‐5 ). Permutation Analysis of Linear Models (PALM) was used to test the association between PRS and both DMN co‐activation and gray matter volume. PALM controls for biases induced by the family structure of the HCP sample. Results were family‐wise error rate corrected at p < 0.05. Result: There was no significant association between DMN co‐activation and PRS (N=454). For the morphometric analyses (N=625), no association between gray matter volume and PRS was found. For both analyses, including covariates (different combinations of age, sex, education level, head motion) did not alter the results. Conclusion: We did not find evidence that genetic predisposition for AD, indicated by PRS, impacts DMN co‐activation in young adults. However, we may not be able to find any measurable effect decades before a clinical expression of AD. Repeating the analysis in an older cohort will inform us whether the influence of genetic predisposition for AD changes with age. 1) Filippini et al., PNAS, 2009. 2) Mentink et al., Default mode network co‐activation in young APOE ε4‐carriers: a Human Connectome Project replication study. AAIC 2020. 3) Jansen et al., Nature Genetics, 2019