ABSTRACT
Background: Neuropsychiatric symptoms are common in dementia and linked to adverse outcomes. Inflammation is increasingly recognized as playing a role as a driver of early disease progression in Alzheimer's disease (AD) and related dementias. Inflammation has also been linked to primary psychiatric disorders, however its association with neuropsychiatric symptoms in neurodegenerative dementias remains uncertain. Methods: We conducted a systematic literature review investigating associations between inflammation and neuropsychiatric symptoms in neurodegenerative dementias, including AD, Lewy body, Frontotemporal, Parkinson's (PD) and Huntington's disease dementias. Results: Ninety-nine studies met our inclusion criteria, and the majority (n = 59) investigated AD and/or mild cognitive impairment (MCI). Thirty-five studies included PD, and only 6 investigated non-AD dementias. Inflammation was measured in blood, CSF, by genotype, brain tissue and PET imaging. Overall, studies exhibited considerable heterogeneity and evidence for specific inflammatory markers was inconsistent, with lack of replication and few longitudinal studies with repeat biomarkers. Depression was the most frequently investigated symptom. In AD, some studies reported increases in peripheral IL-6, TNF-a associated with depressive symptoms. Preliminary investigations using PET measures of microglial activation found an association with agitation. In PD, studies reported positive associations between TNF-a, IL-6, CRP, MCP-1, IL-10 and depression. Conclusion: Central and peripheral inflammation may play a role in neuropsychiatric symptoms in neurodegenerative dementias; however, the evidence is inconsistent. There is a need for multi-site longitudinal studies with detailed assessments of neuropsychiatric symptoms combined with replicable peripheral and central markers of inflammation.
ABSTRACT
Introduction: 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. Methods: Diffusion MRI data were used to perform whole-brain tractography and 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. Results: In the visual subnetwork, the mean nodal strength was negatively correlated with the genome-wide PRS (r = -0.19, p = 1.4 × 10-3), the mean betweenness centrality was positively correlated with the plasma lipoprotein particle assembly PRS (r = 0.16, p = 5.5 × 10-3), and the mean clustering coefficient was negatively correlated with the tau-protein binding PRS (r = -0.16, p = 0.016). In the default mode network, the mean nodal strength was negatively correlated with the genome-wide PRS (r = -0.14, p = 0.044). The rich-club and feeder connectivities were negatively correlated with the genome-wide PRS (r = -0.16, p = 0.035; r = -0.15, p = 0.036). Discussion: We identified small reductions in brain connectivity in young adults at risk of developing Alzheimer's disease in later life.
ABSTRACT
Diffusion magnetic resonance imaging (dMRI) is an imaging technique which probes the random motion of water molecules in tissues and has been widely applied to investigate changes in white matter microstructure in Alzheimer's Disease. This paper aims to systematically review studies that examined the effect of Alzheimer's risk genes on white matter microstructure. We assimilated findings from 37 studies and reviewed their diffusion pre-processing and analysis methods. Most studies estimate the diffusion tensor (DT) and compare derived quantitative measures such as fractional anisotropy and mean diffusivity between groups. Those with increased AD genetic risk are associated with reduced anisotropy and increased diffusivity across the brain, most notably the temporal and frontal lobes, cingulum and corpus callosum. Structural abnormalities are most evident amongst those with established Alzheimer's Disease. Recent studies employ signal representations and analysis frameworks beyond DT MRI but show that dMRI overall lacks specificity to disease pathology. However, as the field advances, these techniques may prove useful in pre-symptomatic diagnosis or staging of Alzheimer's disease.