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Bekris, L.

Publications and source records attributed to Bekris, L..

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Multimodal single-cell/nucleus RNA-sequencing data analysis uncovers molecular networks between disease-associated microglia and astrocytes with implications for drug repurposing in Alzheimer's disease

Systematic identification of molecular networks in disease relevant immune cells of the nervous system is critical for elucidating the underlying pathophysiology of Alzheimers disease (AD). Two key immune cell types, disease-associated microglia (DAM) and disease-associated astrocytes (DAA), are biologically involved in AD pathobiology. Therefore, uncovering molecular determinants of DAM and DAA will enhance our understanding of AD biology, potentially identifying novel therapeutic targets for AD treatment. Here, we present an integrative, network-based methodology to uncover conserved molecular networks between DAM and DAA. Specifically, we leverage single-cell and single-nucleus RNA sequencing data from both AD transgenic mouse models and AD patient brains, drug-target networks, metabolite-enzyme associations, and the human protein-protein interactome, along with large-scale patient data validation from the MarketScan Medicare Supplemental Database. We find that common and unique molecular network regulators between DAM (i.e, PAK1, MAPK14, and SYK) and DAA (i.e., NFKB1, FOS, and JUN) are significantly enriched by multiple neuro-inflammatory pathways and well-known genetic variants (i.e., BIN1) from genome-wide association studies. Further network analysis reveal shared immune pathways between DAM and DAA, including Fc gamma R-mediated phagocytosis, Th17 cell differentiation, and chemokine signaling. Furthermore, integrative metabolite-enzyme network analyses imply that fatty acids (i.e., elaidic acid) and amino acids (i.e., glutamate, serine, and phenylalanine) may trigger molecular alterations between DAM and DAA. Finally, we prioritize repurposed drug candidates for potential treatment of AD by agents that specifically reverse dysregulated gene expression of DAM or DAA, including an antithrombotic anticoagulant triflusal, a beta2-adrenergic receptor agonist salbutamol, and the steroid medications (fluticasone and mometasone). Individuals taking fluticasone (an approved anti-inflammatory and inhaled corticosteroid) displayed a significantly decreased incidence of AD (hazard ratio (HR) = 0.858, 95% confidence interval [CI] 0.829-0.888, P < 0.0001) in retrospective case-control validation. Furthermore, propensity score matching cohort studies also confirmed an association of mometasone with reduced incidence of AD in comparison to fluticasone (HR =0.921, 95% CI 0.862-0.984, P < 0.0001).

neuroscience

AlzGPS: A Genome-wide Positioning Systems Platform to Catalyze Multi-omics for Alzheimer's Therapeutic Discovery

BackgroundOver15 million family members and caregivers have expended $220 billion for care of patients with AD and other dementias, and the attrition rate for AD clinical trials (2002-2012) is estimated at 99.6%. While recent DNA/RNA sequencing and other multi-omics technologies have advanced the understanding of the biology and pathophysiology of AD, no effective disease-modifying or preventive therapies, for AD have emerged in the past two decades. A new approach to integration of the genome, transcriptome, proteome, and human interactome in the drug discovery and development process is essential for this endeavor. MethodsIn this study, we developed AlzGPS (Genome-wide Positioning Systems platform for Alzheimers Therapeutic Discovery, https://alzgps.lerner.ccf.org), a comprehensive systems biology tool to enable searching, visualizing, and analyzing multi-omics, various types of heterogeneous biological networks, and clinical databases for target identification and effective prevention and treatment of AD. ResultsVia AlzGPS: (1) we curated more than 100 AD multi-omics data sets capturing DNA, RNA, protein, and small molecules profiles underlying AD pathogenesis (e.g., early vs. late stage and tau vs. amyloid endophenotype); (2) we constructed endophenotype disease modules by incorporating multi-omics findings and human protein-protein interactome networks; (3) we identified repurposable drugs from [~]3,000 FDA approved/investigational drugs for AD using state-of-the-art network proximity analyses; (4) we curated 300 literature references for highly repurposable drugs; (5) we included information from over 200 ongoing AD clinicals noting drug mechanisms and primary drug targets, and linking them to our integrated multi-omics view for targets and network analyses results for the drugs; (6) we implemented a highly interactive web-interface for database browsing and network visualization. ConclusionsNetwork visualization enabled by the AlzGPS includes brain-specific neighborhood networks for genes-of-interest, endophenotype disease module networks for data sets-of-interest, and mechanism-of-action networks for drugs targeting disease modules. By virtue of combining systems pharmacology and network-based integrative analysis of multi-omics data, the AlzGPS offers actionable systems biology tools for accelerating therapeutic development in AD.

systems biology