Abstract We investigated the structural brain networks of 562 young adults in relation to polygenic risk for Alzheimer’s disease, using magnetic resonance imaging (MRI) and genotype data from the Avon Longitudinal Study of Parents and Children. Diffusion MRI data were used to perform whole-brain tractography and to generate structural brain networks for the whole-brain connectome, and for the default mode, limbic and visual subnetworks. The mean clustering coefficient, mean betweenness centrality, characteristic path length, global efficiency and mean nodal strength were calculated for these networks, for each participant. The connectivity of the rich-club, feeder and local connections was also calculated. Polygenic risk scores (PRS), estimating each participant’s genetic risk, were calculated at genome-wide level and for nine specific disease pathways. Correlations were calculated between the PRS and a) the graph theoretical metrics of the structural networks and b) the rich-club, feeder and local connectivity of the whole-brain networks. In the visual subnetwork, the mean nodal strength was negatively correlated with the genomewide PRS (r=−0.19, p =1.3×10 −5 ), the mean betweenness centrality was positively correlated with the plasma lipoprotein particle assembly PRS (r=0.16, p =9.2×10 −4 ), and the mean clustering coefficient was negatively correlated with the tau protein binding PRS (r=−0.16, p =9.2×10 −4 ). In the default mode network, the mean nodal strength was negatively correlated with the genomewide PRS (r=−0.14, p =1.5×10 −3 ). The rich-club and feeder connectivities were negatively correlated with the genome-wide PRS (r=−0.16, p =3.7×10 −4 ; r=−0.15, p =8.8×10 −4 ). Our results indicate small reductions in brain connectivity in young adults at risk of developing Alzheimer’s disease in later life.

The impact of genetic risk for Alzheimer’s disease on the structural brain networks of young adults