RESUMEN
Analyzing Alzheimer's disease (AD) pathology within anatomical subregions is a significant challenge, often carried out by pathologists using a standardized, semi-quantitative approach. To augment traditional methods, a high-throughput, high-resolution pipeline was created to classify the distribution of AD pathology within hippocampal subregions. USC ADRC post-mortem tissue sections from 51 patients were stained with 4G8 for amyloid, Gallyas for neurofibrillary tangles (NFTs) and Iba1 for microglia. Machine learning (ML) techniques were utilized to identify and classify amyloid pathology (dense, diffuse and APP (amyloid precursor protein)), NFTs, neuritic plaques and microglia. These classifications were overlaid within manually segmented regions (aligned with the Allen Human Brain Atlas) to create detailed pathology maps. Cases were separated into low, intermediate, or high AD stages. Further data extraction enabled quantification of plaque size and pathology density alongside ApoE genotype, sex, and cognitive status. Our findings revealed that the increase in pathology burden across AD stages was driven mainly by diffuse amyloid. The pre and para-subiculum had the highest levels of diffuse amyloid while NFTs were highest in the A36 region in high AD cases. Moreover, different pathology types had distinct trajectories across disease stages. In a subset of AD cases, microglia were elevated in intermediate and high compared to low AD. Microglia also correlated with amyloid pathology in the Dentate Gyrus. The size of dense plaques, which may represent microglial function, was lower in ApoE4 carriers. In addition, individuals with memory impairment had higher levels of both dense and diffuse amyloid. Taken together, our findings integrating ML classification approaches with anatomical segmentation maps provide new insights on the complexity of disease pathology in AD progression. Specifically, we identified diffuse amyloid pathology as being a major driver of AD in our cohort, regions of interest and microglial responses that might advance AD diagnosis and treatment.
RESUMEN
Exposure to early life adversity (ELA), including childhood maltreatment, is one of the most significant risk factors for the emergence of neuropsychiatric disorders in adolescence and adulthood. Despite this relationship being well established, the underlying mechanisms remain unclear. One way to achieve this understanding is to identify molecular pathways and processes that are perturbed as a consequence of childhood maltreatment. Ideally, these perturbations would be evident as changes in DNA, RNA or protein profiles in easily accessible biological samples collected in the shadow of childhood maltreatment. In this study, we isolated circulating extracellular vesicles (EVs) from plasma collected from adolescent rhesus macaques that had either experienced nurturing maternal care (CONT) or maternal maltreatment (MALT) in infancy. RNA sequencing of RNA in plasma EVs and gene enrichment analysis revealed that genes related to translation, ATP synthesis, mitochondrial function and immune response were downregulated in MALT samples, while genes involved in ion transport, metabolism and cell differentiation were upregulated. Interestingly, we found that a significant proportion of EV RNA aligned to the microbiome and that MALT altered the diversity of microbiome-associated RNA signatures found in EVs. Part of this altered diversity suggested differences in prevalence of bacterial species in CONT and MALT animals noted in the RNA signatures of the circulating EVs. Our findings provide evidence that immune function, cellular energetics and the microbiome may be important conduits via which infant maltreatment exerts effects on physiology and behavior in adolescence and adulthood. As a corollary, perturbations of RNA profiles related to immune function, cellular energetics and the microbiome may serve as biomarkers of responsiveness to ELA. Our results demonstrate that RNA profiles in EVs can serve as a powerful proxy to identify biological processes that might be perturbed by ELA and that may contribute to the etiology of neuropsychiatric disorders in the aftermath of ELA.