Biology subjects

Pearse, R. V.

Publications and source records attributed to Pearse, R. V..

4 recordsLinked to original sources

bioRxiv2023

INPP5D/SHIP1 regulates inflammasome activation in human microglia

Microglia and neuroinflammation are implicated in the development and progression of Alzheimers disease (AD). To better understand microglia-mediated processes in AD, we studied the function of INPP5D/SHIP1, a gene linked to AD through GWAS. Immunostaining and single nucleus RNA sequencing confirmed that INPP5D expression in the adult human brain is largely restricted to microglia. Examination of prefrontal cortex across a large cohort revealed reduced full length INPP5D protein levels in AD patient brains compared to cognitively normal controls. The functional consequences of reduced INPP5D activity were evaluated in human induced pluripotent stem cell derived microglia (iMGLs), using both pharmacological inhibition of the phosphatase activity of INPP5D and genetic reduction in copy number. Unbiased transcriptional and proteomic profiling of iMGLs suggested an upregulation of innate immune signaling pathways, lower levels of scavenger receptors, and altered inflammasome signaling with INPP5D reduction. INPP5D inhibition induced the secretion of IL-1{beta} and IL-18, further implicating inflammasome activation. Inflammasome activation was confirmed through visualization of inflammasome formation through ASC immunostaining in INPP5D-inhibited iMGLs, increased cleaved caspase-1 and through rescue of elevated IL-1{beta} and IL-18 with caspase-1 and NLRP3 inhibitors. This work implicates INPP5D as a regulator of inflammasome signaling in human microglia.

neuroscience↗

bioRxiv2023

Cell-type-specific regulation of APOE levels in human neurons by the Alzheimer's disease risk gene SORL1

SORL1 is strongly implicated in the pathogenesis of Alzheimers disease (AD) through human genetic studies that point to an association of reduced SORL1 levels with higher risk for AD. To interrogate the role(s) of SORL1 in human brain cells, SORL1 null iPSCs were generated, followed by differentiation to neuron, astrocyte, microglia, and endothelial cell fates. Loss of SORL1 led to alterations in both overlapping and distinct pathways across cell types, with the greatest effects in neurons and astrocytes. Intriguingly, SORL1 loss led to a dramatic neuron-specific reduction in APOE levels. Further, analyses of iPSCs derived from a human aging cohort revealed a neuron-specific linear correlation between SORL1 and APOE RNA and protein levels, a finding validated in human post-mortem brain. Pathway analysis implicated intracellular transport pathways and TGF- {beta}/SMAD signaling in the function of SORL1 in neurons. In accord, enhancement of retromer-mediated trafficking and autophagy rescued elevated phospho-tau observed in SORL1 null neurons but did not rescue APOE levels, suggesting that these phenotypes are separable. Stimulation and inhibition of SMAD signaling modulated APOE RNA levels in a SORL1-dependent manner. These studies provide a mechanistic link between two of the strongest genetic risk factors for AD.

neuroscience↗

bioRxiv2022

Cell-subtype specific effects of genetic variation in the aging and Alzheimer cortex

The relationship between genetic variation and gene expression in individual brain cell types and subtypes has remained elusive. Here, we generated single-nucleus RNA sequencing data from the dorsolateral prefrontal cortex of 424 individuals of advanced age; analyzing 1.5 million nuclear transcriptomes, we assessed the effect of genetic variants on RNA expression in cis (cis-eQTL) for 7 cell types and 81 cell subtypes. This effort identified 10,004 eGenes at the cell type level and 8,138 eGenes at the cell subtype level. Many eGenes are only detected within cell subtypes. A new variant influences APOE expression only in microglia and is associated with greater cerebral amyloid angiopathy but not Alzheimer pathology, accounting for the effect of APOE{varepsilon}4, providing mechanistic insights into both pathologies. While eQTLs are readily detected, only a TMEM106B variant robustly affects the proportion of cell subtypes. Integration of these results with GWAS highlighted the targeted cell type and likely causal gene within susceptibility loci for Alzheimers, Parkinsons, schizophrenia, and educational attainment.

genomics↗

bioRxiv2022

Predictive Network Analysis Identifies JMJD6 and Other Novel Key Drivers in Alzheimer Disease

Despite decades of genetic studies on late onset Alzheimers disease (LOAD), the molecular mechanisms of Alzheimers disease (AD) remain unclear. Furthermore, different cell types in the central nervous system (CNS) play distinct roles in the onset and progression of AD pathology. To better comprehend the complex etiology of AD, we used an integrative approach to build robust predictive (causal) network models which were cross-validated over multiple large human multi-omics datasets in AD. We employed a published method to delineate bulk-tissue gene expression into single cell-type gene expression and integrated clinical and pathologic traits of AD, single nucleotide variation, and deconvoluted gene expression for the construction of predictive network models for each cell type in AD. With these predictive causal models, we are able to identify and prioritize robust key drivers of the AD-associated network state. In this study, we focused on neuron-specific network models and prioritized 19 predicted key drivers modulating AD pathology. These targets were validated via shRNA knockdown in human induced pluripotent stem cell (iPSC) derived neurons (iNs), in which 10 out of the 19 neuron-related targets (JMJD6, NSF, NUDT2, YWHAZ, RBM4, DCAF12, NDRG4, STXBP1, ATP1B1, and FIBP) significantly modulated levels of amyloid-beta and/or phosphorylated tau peptides in the postmitotic iNs. Most notably, knockdown of JMJD6 significantly altered the neurotoxic ratios of A{beta}42 to 40 and p231-tau to total tau, indicating its potential therapeutic relevance to both amyloid and tau pathology in AD. Molecular validation by RNA sequencing (RNAseq) in iNs further confirmed the network structure, showing significant enrichment in differentially expressed genes after knockdown of the validated targets. Interestingly, our network model predicts that these 10 key drivers are upstream regulators of REST and VGF, two recently identified key regulators of AD pathogenesis.

neuroscience↗