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Bennett, D. A.

Publications and source records attributed to Bennett, D. A..

At least 55 records · Page 3Linked to original sources

Cell type-specific associations with Alzheimer's Disease conserved across racial and ethnic groups

Genomic studies at single-cell resolution have implicated multiple cell types associated with clinical and pathological traits in Alzheimers Disease (AD), but have not examined common features across broad, multi-ethnic populations, and across multiple regions. To bridge this gap, we performed single-nucleus RNA-seq and ATAC-seq profiling of cortical and subcortical brain regions from post-mortem samples across Non-Latin White, African American, and Latin donors (the latter of any race). Using discrete and continuous dissection of molecular programs, we elucidate cell-type-specific glial and neuronal signatures associated with AD across multiple population groups. Notably, we found that multiple microglial (GPNMB+, CD74+, and CR1+ subgroups) and astrocyte (SERPINH1+ and WIF1+ subgroups) signatures are associated with worse clinical and pathological phenotypes across all three population groups. We also report continuous gene expression factors in oligodendrocytes that are not captured by discrete clusters, yet still show strong associations with disease phenotypes. Finally, we observe these discrete cellular identities and continuous gene programs separate cognitively impaired donors into 6 molecularly distinct subgroups that span racial and ethnic population groups. Overall, our study identifies key cell types and gene programs implicated in AD that are shared across population groups, and provides an initial data set that underscores how representative sampling can capture conserved signatures as well as disease heterogeneity, leading to better prioritization of key cell types for further investigation.

neuroscience↗

A proteogenomic tool uncovers protein markers for human microglial states

Human microglial heterogeneity has been largely described using transcriptomic data. Here, we introduce a microglial proteomic data resource and a Cellular Indexing of Transcriptomes and Epitopes by Sequencing panel enhanced with antibodies targeting 17 microglial cell surface proteins (mCITE-Seq). We evaluated mCITE-Seq on HMC3 microglia-like cells, induced-pluripotent stem cell-derived microglia (iMG), and freshly isolated primary human microglia. We identified novel protein microglial markers such as CD51 and relate expression of 101 cell surface proteins to transcriptional programs. This results in the identification and validation of three protein marker combinations with which to purify microglia enriched with each of 23 transcriptional programs; for example, CD49D, HLA-DR and CD32 enrich for GPNMBhigh ("disease associated") microglia. Further, we identify and validate proteins - SIRPA, PDPN and CD162 - that differentiate microglia from infiltrating macrophages. The mCITE-Seq panel enables the transition from RNA-based classification and facilitates the functional characterization and harmonization of model systems.

neuroscience↗

Evidence for cPLA2 activation in Alzheimer's Disease Synaptic Pathology

BackgroundSynapses are essential for learning and memory, and their loss predicts cognitive decline in Alzheimers disease (AD). Synaptic loss is associated with excitotoxicity, neuroinflammation, amyloid-{beta}, and tau pathology, but the molecular mechanisms remain unclear. There is an urgent need to identify new targets to modify the disease and slow synaptic loss and cognitive decline. This study examines if calcium-dependent phospholipase A2 (cPLA2) is implicated in AD synaptic loss. cPLA2 catalyzes membrane phospholipids to release arachidonic acid, which can be metabolized into inflammatory eicosanoids. MethodscPLA2 levels were examined in synaptosomes isolated from the postmortem frontal cortex of individuals with no cognitive impairment (NCI), mild cognitive impairment (MCI), and AD dementia from the Religious Orders Study (ROS). Eicosanoids in synaptosomes were analyzed using lipidomics. Immunofluorescent staining investigated cPLA2 interactions with synaptic markers. Human iPSCs-derived neurons were used to study cPLA2 overactivation after exposure to amyloid-{beta} 42 oligomers (A{beta}42O), its relationships with synaptic markers, and the effects of cPLA2 inhibitors. ResultsWe observed elevated cPLA2 (cPLA2 and cPLA2{beta}) in AD synaptosomes and positive correlations with postsynaptic density protein 95 (PSD-95) and cognitive dysfunction. Eicosanoids were increased in AD synaptosomes and correlated with cPLA2, indicating cPLA2 activity at synapses/synaptosomes. Phosphorylated cPLA2 (p-cPLA2) colocalized with PSD-95 in synaptosomes, and with postsynaptic Ca2+/calmodulin-dependent protein kinase II (CaMKII) and dendritic microtubule-associated protein 2 (MAP2) in NCI and AD brains, where their levels were reduced in AD. P-cPLA2 colocalizes with MAP2 at the neuronal soma associated with neuritic plaques and neurodegeneration in AD. A{beta}42O activates cPLA2 in human iPSCs-derived neurons, leading to p-cPLA2 relocation from the cytosol to synaptic and dendritic sites to colocalize with CaMKII and MAP2, resulting in their reduction. P-cPLA2 also colocalized with PSD-95 in A{beta}42O-exposed neurons, accompanied with increased PSD-95 intensity at soma membrane. These processes were reversed by the cPLA2 inhibitor ASB14780. ConclusionscPLA2 overactivation at synapses, dendrites, and excitatory neuronal somas is associated with synaptic loss, neuritic plaques and neurodegeneration, potentially contributing to cognitive decline in AD. Future research needs to explore the role of cPLA2 as a disease-modifying target for AD.

neuroscience↗

A factor-based analysis of individual human microglia uncovers regulators of an Alzheimer-related transcriptional signature

Human microglial heterogeneity is only beginning to be appreciated at the molecular level. Here, we present a large, single-cell atlas of expression signatures from 441,088 live microglia broadly sampled across a diverse set of brain regions and neurodegenerative and neuroinflammatory diseases obtained from 161 donors sampled at autopsy or during a neurosurgical procedure. Using single-cell hierarchical Poisson factorization (scHPF), we derived a 23-factor model for continuous gene expression signatures across microglia which capture specific biological processes (e.g., metabolism, phagocytosis, antigen presentation, inflammatory signaling, disease-associated states). Using external datasets, we evaluated the aspects of microglial phenotypes that are encapsulated in various in vitro and in vivo microglia models and identified and replicated the role of two factors in human postmortem tissue of Alzheimers disease (AD). Further, we derived a complex network of transcriptional regulators for all factors, including regulators of an AD-related factor enriched for the mouse disease-associated microglia 2 (DAM2) signature: ARID5B, CEBPA, MITF, and PPARG. We replicated the role of these four regulators in the AD-related factor and then designed a multiplexed MERFISH panel to assess our microglial factors using spatial transcriptomics. We find that, unlike cells with high expression of the interferon-response factor, cells with high expression of the AD DAM2-like factor are widely distributed in neocortical tissue. We thus propose a novel analytic framework that provides a taxonomic approach for microglia that is more biologically interpretable and use it to uncover new therapeutic targets for AD.

neuroscience↗

Translating the Post-Mortem Brain Multi-Omics Molecular Taxonomy of Alzheimer's Dementia to Living Humans

Alzheimers disease (AD) dementia is characterized by significant molecular and phenotypic heterogeneity, which confounds its mechanistic understanding, diagnosis, and effective treatment. In this study, we harness the most comprehensive dataset of paired ante-mortem blood omics, clinical, psychological, and post-mortem brain multi-omics data and neuroimaging to extensively characterize and translate the molecular taxonomy of AD dementia to living individuals. First, utilizing a comprehensive integration of eight complementary molecular layers from brain multi-omics data (N = 1,189), we identified three distinct molecular AD dementia subtypes exhibiting strong associations with cognitive decline, sex, psychological traits, brain morphology, and characterized by specific cellular and molecular drivers involving immune, vascular, and oligodendrocyte precursor cells. Next, in a significant translational effort, we developed predictive models to convert these advanced brain-derived molecular profiles (AD dementia pseudotimes and subtypes) into blood-, MRI- and psychological traits-based markers. The translation results underscore both the promise of these models and the opportunities for further enhancement. Our findings enhance the understanding of AD heterogeneity, underscore the value of multi-scale molecular approaches for elucidating causal mechanisms, and lay the groundwork for the development of novel therapies in living persons that target multi-level brain molecular subtypes of AD dementia.

neuroscience↗

Multi-omic subtypes of Alzheimer's dementia are differentially associated with psychological traits

ImportancePsychological traits reflecting neuroticism, depressive symptoms, loneliness, and purpose in life are risk factors of AD dementia; however, the underlying biologic mechanisms of these associations remain largely unknown. ObjectiveTo examine whether one or more multi-omic brain molecular subtypes of AD is associated with neuroticism, depressive symptoms, loneliness, and/or purpose in life. DesignTwo cohort-based studies; Religious Orders Study (ROS) and Rush Memory and Aging Project (MAP), both ongoing longitudinal clinical pathological studies that began enrollment in 1994 and 1997. SettingOlder priests, nuns, and brothers from across the U.S. (ROS) and older adults from across the greater Chicago metropolitan area (MAP). Participants822 decedents with multi-omic data from the dorsolateral prefrontal cortex. Exposure(s)Pseudotime, representing molecular distance from no cognitive impairment (NCI) to AD dementia, and three multi-omic brain molecular subtypes of AD dementia representing 3 omic pathways from no cognitive impairment (NCI) to AD dementia that differ by their omic constituents. Main outcome(s) and measure(s)We first ran four separate linear regressions with neuroticism, depressive symptoms, loneliness, purpose in life as the outcomes, and pseudotime as the predictor, adjusting for age, sex and education. We then ran four separate analyses of covariance (ANCOVAs) with Bonferroni-corrected post-hoc tests to test whether the three multi-omic AD subtypes are differentially associated with the four traits, adjusting for the same covariates. ResultPseudotime was positively associated (p<0.05) with neuroticism and loneliness. AD subtypes were differentially associated with the traits: AD subtypes 1 and 3 were associated with neuroticism; AD subtype 2 with depressive symptoms; AD subtype 3 with loneliness, and AD subtype 2 with purpose in life. Conclusions and RelevanceThree multi-omic brain molecular subtypes of AD dementia differentially share omic features with four psychological risk factors of AD dementia. Our data provide novel insights into the biology underlying well-established associations between psychological traits and AD dementia. Key pointsO_ST_ABSQuestionC_ST_ABSAre three distinct multi-omic brain molecular subtypes of Alzheimers disease (AD) dementia associated with four well-established psychological AD risk factors (neuroticism, depressive symptoms, loneliness and purpose in life)? FindingsWe found differential associations: AD subtypes 1 and 3 were associated with neuroticism, AD subtype 2 was associated with depressive symptoms, AD subtype 3 was associated with loneliness; and AD subtype 2 was associated with purpose in life. MeaningPsychological risk factors might be associated with AD dementia via shared multi-omic molecular pathways.

molecular biology↗

PLXNB1 and other signaling drives a pathologic astrocyte state contributing to cognitive decline in Alzheimer's Disease

Alzheimers disease (AD) is marked by the coordinated emergence of disease-associated cell states across multiple cell types. Here, we first performed a meta-analysis of single-nucleus transcriptomic (snRNAseq) data from 869 brains of diverse decedents, confirming the critical role of an SLC38A2highSMTNhighCACNA1Dhighastrocyte subset, Astrocyte 10 (Ast10), in AD and aging-related cognitive decline. We then investigated the signaling drivers of Ast10s emergence in the aging brain, focusing on interactions among microglial and astrocytic subsets. Analysis of the snRNAseq data prioritized a set of ligands and receptors that are robustly predictive of Ast10 proportions across participants, and we confirm our predictions in multiple studies. Independent validation with spatial transcriptomics reveals striking colocalization of these prioritized ligands with the Ast10 signature in AD brain tissue, but not with other astrocytic states. Genetic ablation of a top receptor PLXNB1 in murine and human iPSC-derived astrocytes decreased the Ast10 signature, confirming its regulatory role. Finally, we find that Ast10 may contribute to cognitive decline through synaptic loss and is associated with cognitive decline independent of AD. Thus, Ast10 and its regulators are potential points of convergence for multiple neurodegenerative mechanisms and may be promising targets for therapeutic development to preserve cognitive function.

neuroscience↗

Cell type transcriptomics reveal shared genetic mechanisms in Alzheimer's and Parkinson's disease

Historically, Alzheimers disease (AD) and Parkinsons disease (PD) have been investigated as two distinct disorders of the brain. However, a few similarities in neuropathology and clinical symptoms have been documented over the years. Traditional single gene-centric genetic studies, including GWAS and differential gene expression analyses, have struggled to unravel the molecular links between AD and PD. To address this, we tailor a pattern-learning framework to analyze synchronous gene co-expression at sub-cell-type resolution. Utilizing recently published single-nucleus AD (70,634 nuclei) and PD (340,902 nuclei) datasets from postmortem human brains, we systematically extract and juxtapose disease-critical gene modules. Our findings reveal extensive molecular similarities between AD and PD gene cliques. In neurons, disrupted cytoskeletal dynamics and mitochondrial stress highlight convergence in key processes; glial modules share roles in T-cell activation, myelin synthesis, and synapse pruning. This multi-module sub-cell-type approach offers insights into the molecular basis of shared neuropathology in AD and PD.

neuroscience↗

Gene module-trait network analysis uncovers cell type specific systems and genes relevant to Alzheimers Disease

Alzheimers Disease (AD) is marked by the accumulation of pathology, neuronal loss, and gliosis and frequently accompanied by cognitive decline. Understanding brain cell interactions is key to identifying new therapeutic targets to slow its progression. Here, we used systems biology methods to analyze single-nucleus RNA sequencing (snRNASeq) data generated from dorsolateral prefrontal cortex (DLPFC) tissues of 424 participants in the Religious Orders Study or the Rush Memory and Aging Project (ROSMAP). We identified modules of co-regulated genes in seven major cell types, assigned them to coherent cellular processes, and assessed which modules were associated with AD traits such as cognitive decline, tangle density, and amyloid-{beta} deposition. Coexpression network structure was conserved in the majority of modules across cell types, but we also found distinct communities with altered connectivity, especially when compared to bulk RNASeq, suggesting cell-specific gene co-regulation. These coexpression modules can also capture signatures of cell subpopulations and be influenced by cell proportions. Using a Bayesian network framework, we modeled the direction of relationships between the modules and AD progression. We highlight two key modules, a microglia module (mic_M46), associated with tangles; and an astrocyte module (ast_M19), associated with cognitive decline. Our work provides cell-specific molecular networks modeling the molecular events leading to AD.

systems biology↗

Molecular hallmarks of excitatory and inhibitory neuronal resilience and resistance to Alzheimer's disease

BackgroundA significant proportion of individuals maintain healthy cognitive function despite having extensive Alzheimers disease (AD) pathology, known as cognitive resilience. Understanding the molecular mechanisms that protect these individuals can identify therapeutic targets for AD dementia. This study aims to define molecular and cellular signatures of cognitive resilience, protection and resistance, by integrating genetics, bulk RNA, and single-nucleus RNA sequencing data across multiple brain regions from AD, resilient, and control individuals. MethodsWe analyzed data from the Religious Order Study and the Rush Memory and Aging Project (ROSMAP), including bulk (n=631) and multi-regional single nucleus (n=48) RNA sequencing. Subjects were categorized into AD, resilient, and control based on {beta}-amyloid and tau pathology, and cognitive status. We identified and prioritized protected cell populations using whole genome sequencing-derived genetic variants, transcriptomic profiling, and cellular composition distribution. ResultsTranscriptomic results, supported by GWAS-derived polygenic risk scores, place cognitive resilience as an intermediate state in the AD continuum. Tissue-level analysis revealed 43 genes enriched in nucleic acid metabolism and signaling that were differentially expressed between AD and resilience. Only GFAP (upregulated) and KLF4 (downregulated) showed differential expression in resilience compared to controls. Cellular resilience involved reorganization of protein folding and degradation pathways, with downregulation of Hsp90 and selective upregulation of Hsp40, Hsp70, and Hsp110 families in excitatory neurons. Excitatory neuronal subpopulations in the entorhinal cortex (ATP8B1+ and MEF2Chigh) exhibited unique resilience signaling through neurotrophin (modulated by LINGO1) and angiopoietin (ANGPT2/TEK) pathways. We identified MEF2C, ATP8B1, and RELN as key markers of resilient excitatory neuronal populations, characterized by selective vulnerability in AD. Protective rare variant enrichment highlighted vulnerable populations, including somatostatin (SST) inhibitory interneurons, validated through immunofluorescence showing co-expression of rare variant associated RBFOX1 and KIF26B in SST+ neurons in the dorsolateral prefrontal cortex. The maintenance of excitatory-inhibitory balance emerges as a key characteristic of resilience. ConclusionsWe identified molecular and cellular hallmarks of cognitive resilience, an intermediate state in the AD continuum. Resilience mechanisms include preservation of neuronal function, maintenance of excitatory/inhibitory balance, and activation of protective signaling pathways. Specific excitatory neuronal populations appear to play a central role in mediating cognitive resilience, while a subset of vulnerable SST interneurons likely provide compensation against AD-associated dysregulation. This study offers a framework to leverage natural protective mechanisms to mitigate neurodegeneration and preserve cognition in AD.

neuroscience↗

Sex-specific Associations of Gene Expression with Alzheimer's Disease Neuropathology and Ante-mortem Cognitive Performance

The biological mechanisms underlying womens increased Alzheimers disease (AD) prevalence remain undefined. Previous case/control studies have identified sex-biased molecular pathways, but sex-specific relationships between gene expression and AD endophenotypes, particularly sex chromosomes, are underexplored. With bulk transcriptomic data across 3 brain regions from 767 decedents, we investigated sex-specific associations between gene expression and post-mortem {beta}-amyloid and tau as well as antemortem longitudinal cognition. Of 23,118 significant gene associations, 10% were significant in one sex and not the other (sex-specific). Most sex-specific gene associations were identified in females (73%) and associated with tau tangles and longitudinal cognition (90%). Four X-linked genes, MCF2, HDAC8, FTX, and SLC10A3, demonstrated significant sex differences in their associations with AD endophenotypes (i.e., significant sex x gene interaction). Our results also uncovered sex-specific biological pathways, including a female-specific role of neuroinflammation and neuronal development, reinforcing the potential for sex-aware analyses to enhance precision medicine approaches in AD.

neuroscience↗

Cell Type Differentiation Using Network Clustering Algorithms

Single cell RNA-seq (scRNA-seq) technologies provide unprecedented resolution representing transcriptomics at the level of single cell. One of the biggest challenges in scRNA-seq data analysis is the cell type annotation, which is usually inferred by cell separation approaches. In-silico algorithms that accurately identify individual cell types in ongoing single-cell sequencing studies are crucial for unlocking cellular heterogeneity and understanding the biological basis of diseases. In this study, we focus on robustly identifying cell types in single-cell RNA sequencing data; we conduct a comparative analysis using methods established in biology, like Seurat, Leiden, and WGCNA, as well as Infomap, statistical inference via Stochastic Block Models (SBM), and single-cell Graph Neural Networks (scGNN). We also analyze preprocessing pipelines to identify and optimize key components in the process. Leveraging two independent datasets, PBMC and ROSMAP, we employ clustering algorithms on cell-cell networks derived from gene expression data. Our findings reveal that while clusters detected by WGCNA exhibit limited correspondence with cell types, those identified by multiresolution Infomap and Leiden, and SBM show a closer alignment, with Infomap standing out as a particularly effective approach. Infomap notably offers valuable insights for the precise characterization of cellular landscapes related to neurodegenration and immunology in scRNA-seq.

bioinformatics↗

Single-cell transcriptomic landscape of the neuroimmune compartment in amyotrophic lateral sclerosis brain and spinal cord

Development of therapeutic approaches that target specific microglia responses in amyotrophic lateral sclerosis (ALS) is crucial due to the involvement of microglia in ALS progression. Our study identifies the predominant microglia subset in human ALS primary motor cortex and spinal cord as an undifferentiated phenotype with dysregulated respiratory electron transport. Moreover, we find that the interferon response microglia subset is enriched in donors with aggressive disease progression, while a previously described potentially protective microglia phenotype is depleted in ALS. Additionally, we observe an enrichment of non-microglial immune cell, mainly NK/T cells, in ALS central nervous system, primarily in the spinal cord. These findings pave the way for the development of microglia subset-specific therapeutic interventions to slow or even stop ALS progression.

neuroscience↗

Spatial Transcriptomic Analysis Identifies a SERPINA3-Expressing Astrocytic State Associated with the Human Neuritic Plaque Microenvironment

Single-nucleus transcriptomic studies have revealed glial cell states associated with Alzheimers disease; however, these nuclei are dissociated from the complex architecture of the human neocortex. Here, we successfully performed an unbiased distance-based analytic strategy on spatially-registered transcriptomic data. Leveraging immunohistochemistry in the same tissue section, our analyses prioritized SERPINA3 and other genes, such as metallothioneins, as altered in the vicinity of neuritic amyloid plaques. Results were validated at the protein level by immunofluorescence, highlighting that a reactive SERPINA3+ astrocyte subtype, Ast.5, plays a role in the plaque microenvironment.

neuroscience↗

Spatial Expression of Long Non-Coding RNAs in Human Brains of Alzheimer's Disease

BackgroundLong non-coding RNAs (lncRNAs) are critical regulators of physiological and pathological processes, with their dysregulation increasingly implicated in aging and Alzheimers disease (AD). To investigate the spatial and cellular distribution of lncRNAs in the aging brain, we leveraged published spatial transcriptomics (ST), single-nucleus RNA sequencing (snRNA-seq), and bulk RNA-seq datasets from the dorsolateral prefrontal cortex (DLPFC) of ROSMAP participants with and without pathological AD. ResultsLncRNAs exhibited greater subregion-specific expression than mRNAs, with enrichment in antisense and lincRNA biotypes. Subregion-enriched lncRNAs were generally not cell-type specific, and vice versa. Differential expression analysis of ST data identified AD-associated lncRNAs with distinct spatial patterns and moderate overlap with differentially expressed (DE) lncRNAs from bulk RNA-seq. Gene set enrichment revealed their involvement in chromatin remodeling, epigenetic regulation, and RNA metabolism. We also identified AD DE lncRNAs across major brain cell types using snRNA-seq but overlap with ST DE lncRNAs was limited. Among previously reported lncRNAs, OIP5-AS1 was consistently upregulated in AD in all cortical subregions. Antisense oligonucleotide (ASO) knockdown of OIP5-AS1 in iPSC-derived microglia led to upregulation of pro-inflammatory genes and downregulation of DNA replication and repair pathways. Immunoassays confirmed increased secretion of pro-inflammatory cytokines. The knockdown expression pattern was enriched for microglia-specific AD DE genes and microglia states. ConclusionsThis study provides a spatial and cellular map of lncRNAs in the aging human cortex and identifies subregion-and cell-type-enriched DE lncRNAs in AD. Our findings implicate OIP5-AS1 in microglial activation, suggesting its potential contribution to AD pathogenesis.

neuroscience↗

The YTHDF Proteins Shape the Brain Gene Signatures of Alzheimer's Disease

The gene signatures of Alzheimers Disease (AD) brains reflect an output of a complex interplay of genetic, epigenetic, epi-transcriptomic, and post-transcriptional regulation., yet the dominant factor shaping these signatures remains unclear. To identify the most significant factor that shapes the AD brain signatures, we integrated cellular and molecular features with differential gene expression in in an explainable machine learning framework. Our result indicates that YTHDF proteins, the canonical readers of N6-methyladenosine RNA modification (m6A), are the most influential predictors of the AD brain signatures. We then show that protein modules containing YTHDFs are downregulated in human AD brains, and knocking down and pharmacologically inhibiting YTHDFs in iPSC-derived 2D and 3D neuronal models recapitulate the AD-associated transcriptional signatures. Furthermore, eCLIP-seq analysis revealed that YTHDF proteins influence AD signatures through both m6A-dependent and independent pathways. These results highlight the central role of YTHDF proteins in shaping the gene signatures of AD brains.

neuroscience↗

An analysis of RNA quality metrics in human brain tissue

Human brain tissue studies have historically used a range of metrics to assess RNA quality. However, few large-scale cross-comparisons of pre-sequencing quality metrics with RNA-seq quality have been published. Here, we analyze how well metrics gathered before RNA sequencing (post-mortem interval (PMI) and RNA integrity number RIN) relate to analyses of RNA quality after sequencing (Percent of counts in Top Ten genes (PTT), 5 bias, and 3 bias) as well as with individual gene counts across the transcriptome. We conduct this analysis across four different human cortical brain tissue collections sequenced with varying library preparation protocols. PMI and RIN have a low inverse correlation, and both PMI and RIN show consistent and opposing correlations with PTT. Unlike PMI, RIN shows strong consistent correlations with measurements of 3 and 5 bias, and RIN also correlates with 3,933 genes across datasets, in comparison to 138 genes for PMI. Neuronal and immune response genes correlate positively and negatively with RIN respectively, suggesting that different gene sets have divergent relationships with RIN in brain tissue. In summary, these analyses suggest that conventional metrics of RNA quality have varying degrees of value, and that PMI has an overall minimal but reproducible effect on RNA quality.

neuroscience↗

HEXIM1 is correlated with Alzheimer's disease pathology and regulates immediate early gene dynamics in neurons

Cognitive processes require de novo gene transcription in neurons. Memory requires the rapid and robust transcription of a class of genes called immediate early genes (IEGs). IEG transcription is facilitated by the formation of a poised basal state, in which RNA polymerase II (RNAP2) initiates transcription, but remains paused downstream of the promoter. Upon neuronal depolarization, the paused RNAP2 is released to complete the synthesis of messenger RNA (mRNA) transcripts, a process stimulated by positive transcription elongation factor b (P-TEFb). In many cell types, P-TEFb is sequestered into a large inactive complex containing Hexamethylene bisacetamide inducible 1 (HEXIM1), but the impact of this interaction on neuronal gene transcription is not yet fully understood. In this study, we found that neuronal expression levels of HEXIM1 mRNA are highly correlated with impaired cognition in Alzheimers disease. It is also induced in the hippocampus during memory formation, and following depolarization in neurons. The role of HEXIM1 in neuronal gene transcription was then explored in murine neuronal cultures where we found that calcium frees P-TEFb from the HEXIM1 inhibitory complex. Modulation of P-TEFb by inhibiting the activity of the cyclin-dependent kinase 9 (CDK9) subunit of this complex significantly impacts IEG induction, particularly during repeated depolarization. Our findings indicate that HEXIM1 in complex with P-TEFb plays an important role in establishing and resetting the poised RNAP2 state, enabling efficient activation of genes necessary for synaptic plasticity.

neuroscience↗