Genetics of ischemic stroke functional outcome.

Ischemic stroke, which accounts for 87% of cerebrovascular accidents, is responsible for massive global burden both in terms of economic cost and personal hardship. Many stroke survivors face long-term disability-a phenotype associated with an increasing number of genetic variants. While clinical variables such as stroke severity greatly impact recovery, genetic polymorphisms linked to functional outcome may offer physicians a unique opportunity to deliver personalized care based on their patient's genetic makeup, leading to improved outcomes. A comprehensive catalogue of the variants at play is required for such an approach. In this review, we compile and describe the polymorphisms associated with outcome scores such as modified Rankin Scale and Barthel Index. Our search identified 74 known genetic polymorphisms spread across 48 features associated with various poststroke disability metrics. The known variants span diverse biological systems and are related to inflammation, vascular homeostasis, growth factors, metabolism, the p53 regulatory pathway, and mitochondrial variation. Understanding how these variants influence functional outcome may be helpful in maximizing poststroke recovery.

Transcriptional landscape of human microglia implicates age, sex, and APOE-related immunometabolic pathway perturbations.

Microglia have fundamental roles in health and disease; however, effects of age, sex, and genetic factors on human microglia have not been fully explored. We applied bulk and single-cell approaches to comprehensively characterize human microglia transcriptomes and their associations with age, sex, and APOE. We identified a novel microglial signature, characterized its expression in bulk tissue and single-cell microglia transcriptomes. We discovered microglial co-expression network modules associated with age, sex, and APOE-ε4 that are enriched for lipid and carbohydrate metabolism genes. Integrated analyses of modules with single-cell transcriptomes revealed significant overlap between age-associated module genes and both pro-inflammatory and disease-associated microglial clusters. These modules and clusters harbor known neurodegenerative disease genes including APOE, PLCG2, and BIN1. Meta-analyses with published bulk and single-cell microglial datasets further supported our findings. Thus, these data represent a well-characterized human microglial transcriptome resource and highlight age, sex, and APOE-related microglial immunometabolism perturbations with potential relevance in neurodegeneration.

Plasma Biomarkers of Alzheimer's Disease in African Americans.

BACKGROUND/OBJECTIVE: The aim of this study was to determine if plasma concentrations of 5 surrogate markers of Alzheimer's disease (AD) pathology and neuroinflammation are associated with disease status in African Americans. METHODS: We evaluated 321 African Americans (159 AD, 162 controls) from the Florida Consortium for African-American Alzheimer's Disease Studies (FCA3DS). Five plasma proteins reflecting AD neuropathology or inflammation (Aß42, tau, IL6, IL10, TNFα) were tested for associations with AD, age, sex, APOE and MAPT genotypes, and for pairwise correlations. RESULTS: Plasma tau levels were higher in AD when adjusted for biological and technical covariates. APOEɛ4 was associated with lower plasma Aß42 and tau levels. Older age was associated with higher plasma Aß42, tau, and TNFα. Females had lower IL10 levels. Inflammatory proteins had strong pairwise correlations amongst themselves and with Aß42. CONCLUSION: We identified effects of demographic and genetic variants on five potential plasma biomarkers in African Americans. Plasma inflammatory biomarkers and Aß42 may reflect correlated pathologies and elevated plasma tau may be a biomarker of AD in this population.

Genome-wide analysis identifies a novel LINC-PINT splice variant associated with vascular amyloid pathology in Alzheimer's disease.

Cerebral amyloid angiopathy (CAA) contributes to accelerated cognitive decline in Alzheimer's disease (AD) dementia and is a common finding at autopsy. The APOEε4 allele and male sex have previously been reported to associate with increased CAA in AD. To inform biomarker and therapeutic target discovery, we aimed to identify additional genetic risk factors and biological pathways involved in this vascular component of AD etiology. We present a genome-wide association study of CAA pathology in AD cases and report sex- and APOE-stratified assessment of this phenotype. Genome-wide genotypes were collected from 853 neuropathology-confirmed AD cases scored for CAA across five brain regions, and imputed to the Haplotype Reference Consortium panel. Key variables and genome-wide genotypes were tested for association with CAA in all individuals and in sex and APOEε4 stratified subsets. Pathway enrichment was run for each of the genetic analyses. Implicated loci were further investigated for functional consequences using brain transcriptome data from 1,186 samples representing seven brain regions profiled as part of the AMP-AD consortium. We confirmed association of male sex, AD neuropathology and APOEε4 with increased CAA, and identified a novel locus, LINC-PINT, associated with lower CAA amongst APOEε4-negative individuals (rs10234094-C, beta = -3.70 [95% CI -0.49--0.24]; p = 1.63E-08). Transcriptome profiling revealed higher LINC-PINT expression levels in AD cases, and association of rs10234094-C with altered LINC-PINT splicing. Pathway analysis indicates variation in genes involved in neuronal health and function are linked to CAA in AD patients. Further studies in additional and diverse cohorts are needed to assess broader translation of our findings.

Transcriptomic analysis to identify genes associated with selective hippocampal vulnerability in Alzheimer's disease.

Selective vulnerability of different brain regions is seen in many neurodegenerative disorders. The hippocampus and cortex are selectively vulnerable in Alzheimer's disease (AD), however the degree of involvement of the different brain regions differs among patients. We classified corticolimbic patterns of neurofibrillary tangles in postmortem tissue to capture extreme and representative phenotypes. We combined bulk RNA sequencing with digital pathology to examine hippocampal vulnerability in AD. We identified hippocampal gene expression changes associated with hippocampal vulnerability and used machine learning to identify genes that were associated with AD neuropathology, including SERPINA5, RYBP, SLC38A2, FEM1B, and PYDC1. Further histologic and biochemical analyses suggested SERPINA5 expression is associated with tau expression in the brain. Our study highlights the importance of embracing heterogeneity of the human brain in disease to identify disease-relevant gene expression.

Correction to: Deciphering cellular transcriptional alterations in Alzheimer's disease brains.

An amendment to this paper has been published and can be accessed via the original article.

Deciphering cellular transcriptional alterations in Alzheimer's disease brains.

Large-scale brain bulk-RNAseq studies identified molecular pathways implicated in Alzheimer's disease (AD), however these findings can be confounded by cellular composition changes in bulk-tissue. To identify cell intrinsic gene expression alterations of individual cell types, we designed a bioinformatics pipeline and analyzed three AD and control bulk-RNAseq datasets of temporal and dorsolateral prefrontal cortex from 685 brain samples. We detected cell-proportion changes in AD brains that are robustly replicable across the three independently assessed cohorts. We applied three different algorithms including our in-house algorithm to identify cell intrinsic differentially expressed genes in individual cell types (CI-DEGs). We assessed the performance of all algorithms by comparison to single nucleus RNAseq data. We identified consensus CI-DEGs that are common to multiple brain regions. Despite significant overlap between consensus CI-DEGs and bulk-DEGs, many CI-DEGs were absent from bulk-DEGs. Consensus CI-DEGs and their enriched GO terms include genes and pathways previously implicated in AD or neurodegeneration, as well as novel ones. We demonstrated that the detection of CI-DEGs through computational deconvolution methods is promising and highlight remaining challenges. These findings provide novel insights into cell-intrinsic transcriptional changes of individual cell types in AD and may refine discovery and modeling of molecular targets that drive this complex disease.