Biology subjects

Bennett, D. A.

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

At least 37 records · Page 2Linked to original sources

bioRxiv2025

Aged brain multi-omic integration captures immunometabolic and sex variation

Resolving the molecular basis for heterogeneous ageing in the human brain requires integrating its diverse molecular layers. Here we applied a tensor-decomposition framework to jointly analyse single-nucleus RNA-seq, DNA methylation, H3K9ac histone acetylation and proteomic data from 276 post-mortem human cortices. The analysis uncovered two dominant, multi-omic themes. First, we identified an immunometabolic axis characterised by microglial activation, suppression of PI3K-Akt-mTOR signalling and epigenetic signatures that suggest repurposing of developmental transcription factors such as BARHL1. Second, we decomposed the effect of sex into a multi-omic program linked to cellular plasticity: although driven by canonical sex-chromosome genes, this axis was epigenetically enriched for pathways regulating stem-cell pluripotency and exhibited a female-biased shift toward precursor-like states in the oligodendrocyte lineage. Together, these findings deliver a high-resolution atlas of glial ageing and demonstrate that broad risk factors manifest as complex, cell-specific vulnerabilities; an insight critical for the development of targeted therapeutic strategies.

neuroscience↗

bioRxiv2025

Molecular and neuropathological determinants of neuronal dysfunction in Alzheimer's disease

The biological basis of neuronal excitatory/inhibitory (E/I) imbalance in Alzheimers disease (AD) remains unclear. Using a comprehensive cohort with ante-mortem functional neuroimaging and post-mortem molecular data from the same participants, we mapped individual, whole-brain E/I imbalances through biophysical modeling. E/I ratios in regions supporting higher-order cognitive functions were significantly associated with cognitive performance and decline, with mediation by global neuropathological burden. We also observed a significant inverted U-shaped relationship between E/I ratios and neurofibrillary tangle severity, peaking at the limbic stage (Braak III-IV) in 14 brain areas, including the bilateral hippocampus and superior frontal gyrus. In addition, we identified 89 genes and 101 proteins that predict regional E/I ratios, with pathways related to synaptic signaling and immune response overrepresented. The generalizability of these molecular predictors was confirmed in two independent cohorts, achieving good classification performance for neuropathology severity and AD dementia. Lastly, the estimated E/I imbalances in AD aligned with whole-brain distributions of microglia and oligodendrocyte precursor cells, suggesting that spatial cellular organization contributes to vulnerability to neuronal dysfunction. Overall, this study provides critical insights into the cellular, molecular, and neuropathological signatures of circuit-level dysfunction in AD.

neuroscience↗

bioRxiv2025

Single-cell nanodroplet processing proteomics pipeline for analysis of human-derived microglia

Single-cell omics tools provide unique insights into heterogeneous cell populations and their responses to stimuli. For example, single-cell RNA sequencing has identified several transcriptionally distinct populations of microglia, which are resident immune cells of the central nervous system (CNS) that are responsive to CNS injury, infection, and neurodegeneration. To date, single cell studies of microglia have focused on RNA-sequencing or cytometry by time of flight (CyTOF) which provide indirect readouts of protein abundance or quantification of a limited number of targets. Herein, we present a workflow based on FACS-assisted isolation, cryopreservation and nanodroplet-based processing for single-cell mass spectrometry proteomics analysis of the postmortem human brain cortex-derived microglia. From a single microglial cell, 1039 proteins could be identified on average. As a proof-of-principle we applied single-cell proteomics for exploring the heterogeneity of brain microglia at the cellular level. This pilot proteomics data partially recapitulates the prior microglia subtypes. Specifically, we determined mitochondrial proteins, in particular members of NADH dehydrogenase (Complex I), cytochrome b-c1 (Complex III), cytochrome c oxidase (Complex IV), F1-ATPase (Complex V), and Na+/K+-ATPase complex drive variation across microglia. This pipeline offers the potential for identifying functionally and analytically relevant protein targets for microglia in Alzheimers disease and other neurological disorders. Significance of StudyMicroglia are a key brain cell type that may contribute to pathogenesis in neurodegenerative disease. Transcriptomic profiling of microglia from the central nervous system of humans and animal models has identified several subtypes of microglia, and complementary proteomic profiling of microglia is likely to provide functionally and therapeutically relevant targets, however single-proteomics studies of human-derived microglia are lacking. This work describes a label-free, single-cell proteomics approach for microglia isolated by fluorescence-activated cell sorting from a human donor that yields comparable numbers of identifications in comparison to prior single-cell RNA sequencing studies of microglia. This approach holds promise for enabling large-scale proteomics-based subtyping of microglia and studying their roles in neurodegenerative diseases.

molecular biology↗

bioRxiv2025

Inflammatory reprogramming of human brain endothelial cells compromises blood-brain barrier integrity in Alzheimer's disease

Blood-brain barrier (BBB) dysfunction is an early feature of Alzheimers disease (AD), yet the endothelial gene-regulatory programs involved remain incompletely understood. We integrate postmortem human single-nucleus transcriptomics with iPSC-based BBB models to define a conserved, inflammation-driven pathway that compromises barrier integrity. We identify an NF-{kappa}B-associated endothelial gene module endoM2 that is elevated in AD, inversely correlated with cognition, and enriched for inflammation and endothelial-to-mesenchymal transition signatures. Cytokine stimulation of iPSC-derived brain endothelial cells induces morphological remodeling, lipid accumulation, junctional disruption, and transcriptomic shifts that mirror endoM2. A targeted drug screen identifies the NF-{kappa}B inhibitor BAY11-7082 as protective against cytokine-induced changes. In our perfusable iPSC-derived BBB-Chip that recapitulates human BBB signatures, single-cell profiling reveals inflammatory endothelial state-specific programs reflecting those in AD brains and demonstrates that BAY11-7082 suppresses cytokine-triggered dysfunction and reverses inflammation-associated gene activation. Together, these findings position cerebrovascular inflammation as a therapeutic target to preserve BBB integrity in AD.

neuroscience↗

bioRxiv2025

Mapping disease critical spatially variable gene programs by integrating spatial transcriptomics with human genetics

Spatial gene expression patterns underlie tissue organization, development, and disease, yet current methods for detecting spatially variable genes (SVGs) lack the flexibility to capture multi-scale structure, ensure robustness across platforms, and integrate with genetic data to assess disease relevance. We present Spacelink, a unified framework that models spatial variability of a gene at both whole-tissue and cell-type resolution using an adaptive mixture of data-driven spatial kernels and summarizes it using an Effective Spatial Variability (ESV) metric. Spacelink achieved up to 3.2x higher detection power over eight existing global SVG and cell-type SVG methods while showing consistently superior FDR control across 34 different simulation settings and also showed superior cross-platform concordance in matched tissue Visium and CosMx datasets. Applied to 3 healthy CosMx human tissues (brain cortex, lymph node, liver), Spacelink revealed that SVGs are highly informative for 113 complex traits and diseases (average GWAS sample size = 340,406). Spacelink showed up to 2.2x higher disease informativeness over competing methods in tissue-relevant complex diseases and traits, conditional on putative non-spatial expression-level confounders. Applied to a mouse organogenesis Stereo-seq atlas (8 developmental stages), Spacelink identified 145 genes with stage-associated ESV within brain independent of mean expression, that are enriched in pathways like Wnt signaling and Rap1 signaling characterizing early and late development, respectively. Integration with in vivo Perturb-seq targeting 35 de novo ASD risk genes revealed that perturbations in excitatory neurons and astrocytes preferentially altered spatially structured downstream gene programs (1.7-2.2x higher average ESV across stages than other cell types), many of which were enriched for polygenic autism GWAS loci. In neurodegeneration, analysis of 32 Visium dorsolateral prefrontal cortex samples spanning Alzheimers disease (AD) pathology stages identified 334 genes with decreasing ESV along amyloid burden (enriched for glycolysis) and 216 genes with decreasing ESV along tau tangle accumulation (enriched for apoptotic pathways). Several AD risk genes (PKM, CLU, GPI) showed conserved reductions in spatial variability with AD pathology in both human and 5xFAD mouse, with PKM linking to a colocalized splicing QTL and amyloid burden QTL variant. These results highlight the utility of Spacelink in decoding spatially variable gene programs that connect tissue architecture to disease genetics.

genomics↗

bioRxiv2025

Integration of aged brain multi-omics reveals cross-system mechanisms underlying Alzheimer's disease heterogeneity

The molecular correlates of Alzheimers disease (AD) are increasingly being defined by omics. Yet, the findings from different data types or cohorts are often difficult to reconcile. Collecting multiple omics from the same individuals allows a comprehensive view of disease-related molecular mechanisms, while addressing conflicting findings derived from single omics. Such same-sample multi-omics can reveal, for instance, when changes observed in the transcriptome share distinct but coordinated signals in epigenetics and proteomics, relationships otherwise unclear. Here, we apply a data-driven multi-omic framework to integrate epigenomic, transcriptomic, proteomic, metabolomic, and cell-type-specific population data from up to 1,358 aged human brain samples from the Religious Orders Study (ROS) and Rush Memory and Aging Project (MAP). We demonstrate the existence of sprawling cross-omics cross-system biological factors that also relate to AD phenotypes. The strongest AD-associated factor (factor 8) involved elevated immune activity at the epigenetic level, decreased expression of heat shock genes in the transcriptome, and disrupted energy metabolism and cytoskeletal dynamics in the proteome. We also showed immune-related factors (factors 2 and 3) with discordant enrichments, reflecting reactive-like glial subpopulations and protective contributions from surveillance microglia. Both were negatively associated with AD pathology, suggesting potential immune resilience mechanisms. Finally, unsupervised clustering of participants revealed eleven molecular subtypes of the aging brain, including three clusters strongly associated with AD but displaying distinct molecular signatures and phenotypic characteristics. Our findings provide a comprehensive map of molecular mechanisms underlying AD heterogeneity, highlighting the complex role of neuroinflammatory processes, and yielding potential novel biomarkers and therapeutic targets for precision medicine approaches to AD treatment.

molecular biology↗

bioRxiv2025

Stress-Responsive Transcriptomic Signatures in Human iPSC-Derived Microglia Reveal Links to Alzheimer's Disease Risk Genes

Commercially available human iPSC lines with inducible CRISPR interference (CRISPRi) systems offer scalable platforms for gene function studies. One widely available line, the AICS-0090 dCas9-KRAB iPSC line developed by the Allen Institute, has been extensively validated for genomic integrity and stem cell potency. However, its utility in modeling specialized immune cell types such as microglia -- and in assessing their functional responses to disease-relevant stimuli -- has not been fully established. Here, we evaluated the AICS-0090 line for its ability to differentiate into microglia-like cells, support efficient gene knockdown, and respond to environmental stressors. We assessed its differentiation capacity by qPCR, flow cytometry, and immunocytochemistry, confirming reproducible expression of microglial surface markers at early and late timepoints. Gene knockdown efficiency was validated both at the single-gene level and in pooled CRISPRi screens. Focusing on functional responsiveness, we exposed the microglia-like cells to two distinct stimuli: amyloid-{beta} (A{beta}), a disease-associated trigger in Alzheimers disease, and lipopolysaccharide (LPS), a classical inflammatory signal. Transcriptomic and functional analyses revealed stimulus-specific responses: A{beta} induced limited activation of stress and inflammation pathways, whereas LPS elicited broader transcriptional reprogramming and cytokine release. Signatures from both conditions partially overlapped with ex vivo human and mouse microglial states. Together, these findings support the use of the AICS-0090 dCas9-KRAB iPSC-derived microglia-like cells as a flexible and tractable model for gene function interrogation under defined inflammatory contexts, with potential for future applications in neuroimmune modeling and perturbation-based screening.

neuroscience↗

bioRxiv2025

Automated image segmentation uncovers the role of CD74high human microglia in cognitive decline

The role of activated microglia in Alzheimers disease (AD) is well established; the proportion of stage III activated microglia has been associated with AD and cognitive decline, but this morphologically defined subtype is relatively uncommon (1-2% of microglia) and its cellular function is unknown. Single-cell RNA-sequencing revealed CD74 as a marker gene that is enriched in immunologically active microglial subtypes associated with AD. Here, we evaluated the relationship between CD74 expression, AD- related traits, and microglial morphology using dorsolateral prefrontal cortex samples from two brain collections (ROSMAP: n=63, NYBB: n=91). An image segmentation pipeline using CellProfiler was developed to extract features from entire tissue sections. The pipeline automatically delineated gray and white matter regions and segmented 1,120,780 gray matter microglia. In a meta-analysis of the two datasets, we find an increase in frequency of microglia with high CD74 expression (CD74high) in relation to AD dementia (p = 0.038), particularly in the phase of terminal, accelerated cognitive decline before death. These microglia have a more rounded, amoeboid shape (ROSMAP: p = 1.4x10-6; NYBB: p = 2x10-13) which is a characteristic morphology of activated stage III microglia. Results were consistent across both datasets, highlighting the robustness of our cellular segmentation approach. This study identifies a potential role for CD74high microglia and the CD74 ligand MIF in cognitive decline, and it provides evidence for a partially overlapping but distinct role for CD74high microglia and morphologically defined stage III microglia, whose functional properties have remained poorly understood. These CD74high microglia appear to be enriched for genes involved in cytokine response for class I and II antigen presentation, as well as regulation of T cell proliferation. These findings begin to link microglial subtypes defined by single-cell transcriptomic data with those characterized by classical morphological criteria to resolve the roles of different microglial functions to distinct stages in the trajectory to AD.

neuroscience↗

bioRxiv2025

Angiopoietin signalling is a central axis of amyloid-driven vascular dysfunction in Alzheimer's disease

The neurovascular unit is critical for brain health, and its dysfunction has been linked to Alzheimers disease (AD). However, a cell-type-resolved understanding of how diverse vascular cells become dysfunctional and contribute to disease has been missing. Here, we applied Vessel Isolation and Nuclei Extraction for Sequencing (VINE-seq) to build a comprehensive transcriptomic atlas from 101 individuals along AD progression. Our analysis of over 842,646 parenchymal and vascular nuclei reveals that vascular dysfunction in AD is driven by transcriptional changes rather than shifts in cell proportions, with brain endothelial cells (BECs) and smooth muscle cells (SMCs) most affected. Strikingly, these molecular signatures emerge early at the mild cognitive impairment (MCI) stage, implicating vascular dysfunction early in AD pathogenesis. Stratifying by pathology reveals distinct vascular responses to {beta}-amyloid and tau: {beta}-amyloid burden primarily perturbs BECs and SMCs, while tau pathology predominantly impacts glial cells. We identify dysregulated angiopoietin signaling across multiple vascular cell types as a key axis, with antagonistic ANGPT2 in vascular cells and ANGPT1 in astrocytes becoming progressively dysregulated with AD. Together, this work provides a foundational resource that reveals early and pathology-specific pathways of vascular dysfunction in AD. Key MessagesO_LIVINE-seq analysis from 101 individuals creates a comprehensive human brain vascular atlas across Alzheimers disease (AD) progression. C_LIO_LIAD vascular dysfunction is driven by transcriptional changes rather than shifts in cell proportions, with BECs and SMCs most affected. C_LIO_LITranscriptional signatures of vascular dysfunction emerge early at the mild cognitive impairment (MCI) stage, preceding severe cognitive symptoms and aligning more closely with AD than cognitively normal individuals. C_LIO_LIA{beta} and tau associate with distinct vascular changes: A{beta} mainly perturbs endothelial and smooth muscle cells, while tau impacts microglia and astrocytes. C_LIO_LIAngiopoietin signaling (antagonistic ANGPT2 in vascular cells vs. ANGPT1 in astrocytes) becomes progressively dysregulated during AD progression. C_LI

neuroscience↗

bioRxiv2025

Finding ancestry-specific chromatin architecture in Alzheimer's disease

Genetic risk for Alzheimers Disease (AD) varies across populations. We hypothesized that three-dimensional (3D) genome architecture variations could offer novel epigenetic understanding of ancestry-specific genetic risk. Herein, we performed Hi-C analyses of frontal cortex from APOE {varepsilon}4/{varepsilon}4 individuals with African (AF) or European (EU) ancestry who also had single nuclei ATAC-seq and RNA-seq data available. Ancestry-specific 3D genome architecture was found at both compartment and chromatin loop levels. EU genomes have more active compartments than AF genomes, consistent with our previous report of higher chromatin accessibility in EU than AF genome. Of the over one million chromatin loops identified by the DeepLoop pipeline, we called 12,082 putative EU-specific and 2885 putative AF- specific loops. The AF-specific loops are smaller (median size =158 kb) and likely represent promoter-enhancer interactions, while EU-specific loops are larger (median size = 496 kb) and enriched for CTCF loops. We found that differently expressed genes between AF and EU ancestries were significantly enriched at the putative ancestry-specific loop loci (Fisher-test; p<2.2x10-16; OR=5.13). High confidence HiC-QTLs (N=38) were identified after filtering with CTCF consensus sequence and chromatin accessibility-QTLs. Our study demonstrates variations in 3D genome structure between ancestries, which may contribute to the ancestry-specific genetic risk.

genetics↗

bioRxiv2025

Characterizing Post-Mortem Brain Molecular Taxonomy of Cognitive Resilience and Translating it to Living Humans

Here, we define cognitive resilience as slower or faster cognitive decline after we regress out the effects of common brain neuropathologies. Its understanding could provide important insights into the biology underlying cognitive health, enabling the development of more effective strategies to prevent cognitive decline and dementia. However, this requires the development of a practical method to quantify resilience and measure it in living individuals, as well as identifying heterogenous pathways associated with resilience in different individuals. Here, we approach this problem by using a data-driven framework to quantify and characterize molecular signatures underlying cognitive resilience. Using multimodal contrastive trajectory inference (mcTI) on bulk RNA sequencing and tandem mass tag (TMT) proteomic data from 898 post- mortem brain samples from the Religious Orders Study and the Rush Memory and Aging Project (ROSMAP), we derived individual-level molecular pseudotime values reflecting the molecular path from high to low resilience across individuals. Additionally, we identified two distinct molecular subtypes of resilience, each characterized by unique transcriptomic and proteomic signatures, and differing associations with several phenotypes. To translate our brain-derived pseudotime and subtypes to living individuals, we developed prediction models with paired genetics, ante-mortem blood omics, clinical, psychosocial, imaging and device data from the same individuals, demonstrating the potential to predict brain molecular resilience profiles in living persons. Our findings establish a framework for quantifying resilience based on multi- level molecular signatures, identify molecularly distinct resilience subtypes, and demonstrate the feasibility of translating brain-derived molecular profiles to living individuals--laying the groundwork for the development of targeted resilience-promoting interventions in cognitive aging.

neuroscience↗

bioRxiv2025

TPClust: Temporal Profile-Guided Subtyping Using High-Dimensional Omics Data

Clustering is widely used to identify subtypes in heterogeneous populations, yet most approaches rarely integrate longitudinal phenotypic trajectories with high-dimensional molecular profiles, limiting their ability to resolve biologically and clinically meaningful heterogeneity in progressive diseases. We developed TPClust, a supervised, semi-parametric clustering method that integrates high-dimensional omics data with longitudinal phenotypes including outcomes and covariates for outcome-guided subtyping. TPClust jointly models latent subtype membership and longitudinal outcome trajectories using multinomial logistic regression informed by molecular features selected via structured regularization, along with spline-based regression to capture subtype-specific, time-varying covariate effects. Simulations demonstrate valid inference for time-varying effects and robust feature selection. Applied to transcriptomic profiles and longitudinal cognitive data from 1,020 older adults in the Religious Orders Study and the Rush Memory and Aging Project, TPClust identified four aging subtypes including intermediate subtypes not captured by unimodal approaches with distinct cognitive trajectories, time-varying risk profiles, clinical and neuropathological features, and multimodal molecular signatures.

bioinformatics↗

bioRxiv2025

CD33-CD45 Interaction Reveals a Mechanistic Link to Alzheimer's Disease Susceptibility

The innate immune gene CD33, encoding a myeloid inhibitory sialic acid-binding receptor, is associated with Alzheimers disease (AD) susceptibility. The AD-associated rs3865444CC risk variant reduces splicing of the sialic acid-binding domain and increases expression of the full-length (sialic acid-binding) CD33 isoform seven-fold compared to the rs3865444AA protective genotype. Here we identify CD45 as an immune cell-specific sialic acid-dependent cis CD33 binding partner, whose phosphatase activity is inhibited by CD33. Overexpression of CD33 or loss of CD45 contributes to impaired microglial clearance of amyloid beta and amyloid beta-induced loss of dendritic spines in microglial-neuronal co-cultures, aligning with a detrimental effect of CD33-mediated inhibition of CD45. CD33-CD45 interaction frequency was increased in monocytes from individuals with the rs3865444CC risk variant compared to rs3865444AA, as well as in AD compared to controls, independent of genotype. Furthermore, an interaction between CD33 and PTPRC (encoding CD45) gene expression in human brain tissue was associated with a pathological diagnosis of AD and global burden of AD pathology. Our findings thus establish a functional interaction between CD33 and CD45 relevant to AD susceptibility and systemic myeloid dysfunction in this disease.

neuroscience↗

bioRxiv2025

Early neuronal reprogramming and cell cycle reentry shape Alzheimer's disease progression

Alzheimers disease (AD) is a progressive neurodegenerative disorder characterized by hallmark pathologies, synaptic dysfunction, neuronal loss, gliosis and cognitive decline-dementia. Recent large-scale cell atlases of human AD brains exposed vulnerability of specific neuronal subtypes and highlighted early, coordinated glial responses, suggesting glial involvement in disease progression. However, the timing and nature of neuronal changes, differences between neuronal subtypes, and their coordination with glia remain unclear. Here, we used non-negative matrix factorization to identify co-expression gene programs in single-nucleus RNA profiles from the prefrontal cortex of 437 samples from donors whose clinical symptoms ranged between no cognitive impairment and AD dementia. This approach identified early coordinated transcriptional changes across all neuronal subtypes, preceding clinical symptoms of cognitive decline, and validated in independent snRNA-seq, proteomics, and ELISA datasets. We found neurons in AD undergo rapid modulation of synaptic genes, accompanied by convergence of neurons into two distinct programs: An oxidative stress and apoptosis program abundant in vulnerable neuronal subtypes, and a DNA damage and cell-cycle reentry program associated with resilient subtypes. Moreover, neuronal reprogramming was closely tied to glial responses, and diverged between AD to non-AD brain aging, suggesting neuro-glial coordinated reprogramming shapes the AD cascade and influences disease outcomes.

neuroscience↗

bioRxiv2025

Cytokine expression profile in the human brain of older adults

Alzheimers disease (AD) is a complex neurodegenerative condition linked to chronic neuroinflammation. This study investigates the cytokine gene expression profile in cortical tissue samples from elderly individuals with and without AD to identify potential biomarkers and enhance our understanding of disease pathogenesis. Utilizing high-depth RNA sequencing data, we identified a set of cytokines whose expression significantly associated with different aspects of the AD phenotype, including measures of neurofibrillary tangles, amyloid-{beta} deposition, and a person-specific rate of cognitive decline. Single-nucleus transcriptomics data facilitated the identification of specific cell types, such as microglia and oligodendrocytes, that significantly contribute to the inflammatory response in AD. Additionally, we observed a strong correlation between the expression of certain cytokines and genetic risk for the disease. Our findings indicate that cytokine-mediated neuroinflammation plays a vital role in AD progression and that modulating the immune response may offer a promising strategy for developing new therapies.

molecular biology↗

bioRxiv2025

Brain Multi-Omic Subtypes of Neuroticism Reveal Molecular Signatures linked to Alzheimer's Disease

ImportanceMolecular mechanisms linking neuroticism with Alzheimers disease traits are unknown. ObjectiveTo identify molecular subtypes of neuroticism and examine their association with ADRD traits. DesignThree ongoing cohort studies were used; Religious Orders Study (ROS), Rush Memory and Aging Project (MAP) and Minority Aging Research Study (MARS), that began enrollment in 1994, 1997, and 2004, respectively. SettingOlder priests, nuns, and brothers from across the U.S. (ROS), older adults (MAP) and older African-American adults (MARS) from across the greater Chicago metropolitan area. Participants1,028 decedents with multi-omic data from the dorsolateral prefrontal cortex (DLPFC), the anterior cingulate cortex (AC), and the posterior cingulate gyrus (PCG). Exposure(s)Eight layers of omics (DNA methylation and histone acetylation from DLPFC; RNA seq from AC, DLPFC, and PCG, single-nucleus RNA, TMT proteomics and metabolomics from DLPFC) and Neuroticism using the 12-item version from the NEO Five-Factor Inventory. Main outcome(s) and measure(s)Person-specific multi-omic molecular pseudotime representing molecular progression from low to high phenotypic expression of neuroticism, and three multi-omic brain molecular subtypes of neuroticism which represent distinct omic pathways from no/low neuroticism to high neuroticism that differ by their omic constituents. Participants are exclusively assigned to the subtype which aligns mostly with their multi-omic profile. ResultsThe top drivers of subtype differentiation were transcriptomic alterations across three brain regions (DLPFC, AC, PCG) which extensively and differentially characterized the subtypes. The subtypes were also differentially associated with AD pathology, temporal lobe atrophy, and AD dementia, with subtype N1 showing the strongest associations. Conclusions and RelevanceNeuroticism may be driven by three distinct molecular subtypes, with subtype N1 driving ADRD-related associations, N2 showing some ADRD associations, and N3 being completely independent of these outcomes. Our data provide novel insights into the biology of individual differences in predispositions of neuroticism and its associations with ADRD traits. Key pointsO_ST_ABSQuestionC_ST_ABSWhat are the brain multi-omics molecular signatures linking neuroticism with Alzheimers diseases and related dementias (AD/ADRDs)? FindingsWe identified three distinct brain multi-omic molecular subtypes reflecting different molecular pathways underlying neuroticism. Top omic features of the subtypes were extensively and differentially characterized by transcriptomic alterations across three brain regions - dorsolateral prefrontal cortex, anterior cingulate cortex, and posterior cingulate gyrus. Subtype N1 was strongly associated with AD pathology, AD dementia, and temporal lobe atrophy. MeaningThe association we typically observe between phenotypic neuroticism and ADRD clinical traits might be largely driven by a molecular pathway underlying this trait.

neuroscience↗

bioRxiv2025

TDP-43 toxic gain of function links ALS/FTLD-TDP and Alzheimer's Disease through splicing

Loss of nuclear TDP-43 splicing activity is a common feature across neurodegenerative diseases including amyotrophic lateral sclerosis (ALS) and frontotemporal lobar degeneration (FTLD), but its relevance to Alzheimers disease (AD) remains unclear. Here, we show that TDP-43 pathology in AD is broadly associated with splicing abnormalities, including aberrant splicing of amyloid precursor protein (APP). TDP-43 drives the formation of elongated APP isoforms, disrupting alternative splicing across ALS, FTLD-TDP and AD, providing a compelling mechanism for a long-standing observation of APP isoform dysregulation. We further establish a mechanistic link between TDP-43, APP splicing, and A{beta} pathology. Surprisingly, the disruption to alternative APP splicing is mediated by a toxic gain of cytoplasmic TDP-43 function, rather than loss of its nuclear role. Using proximity proteomics and base editing in human iPSC-derived neurons, we show that TDP-43 pathology causes cytoplasmic co-sequestration of splicing regulators SCAF11, SRSF5, and TIAL1. Knockdown of these regulators also results in APP mis-splicing and increased A{beta} burden, without affecting other TDP-43 targets such as STMN2 or UNC13A. Together, our findings suggest that TDP-43-mediated splicing dysfunction upstream of APP contributes to the pathogenesis of seemingly disparate neurodegenerative diseases, uniting AD and ALS/FTLD-TDP through a shared molecular mechanism.

neuroscience↗

bioRxiv2025

Single Cell Landscape of Sex-specific Drivers of Alzheimers Disease

BackgroundSex differences in Alzheimers disease (AD) have been documented for decades, and many sex-specific molecular contributors to AD have been discovered through bulk omics analysis of brain tissues. RNA sequencing (RNAseq) at single cell resolution provides an opportunity to characterize transcript associations with AD in a cell type-specific matter. Here, we investigated sex-specific gene expression associations with neuropathology and cognitive manifestation of AD (endophenotypes) leveraging a large single-nucleus transcriptomic dataset consisting of 1.64 million nuclei from dorsolateral prefrontal cortex (DLPFC) tissue of 424 unique donors from the Religious Orders Study and Memory and Aging Project (ROS/MAP; AD Knowledge Portal syn2580853). MethodsROS/MAP single-nucleus RNAseq data (snRNA-seq) were processed through a rigorous pipeline. In total, eight major cell types from DLPFC were identified. We first performed sex-stratified and sex-interaction association analyses by fitting negative binomial mixed models in relation to {beta}-amyloid load (A{beta}), paired helical filament tau tangle density (tau), global cognitive performance at last visit, and longitudinal cognitive trajectory. We then conducted gene-set enrichment analysis to identify functional signaling pathways enriched for sex-specific associations. Lastly, we compared differential gene expression patterns and intercellular communication profiles between sexes and diagnostic groups among major cell types. For replication, sex-specific associations were examined using snRNA-seq derived from DLPFC tissue-derived of an independent set of 84 donors from The Seattle Alzheimers Disease Brain Cell Atlas (SEA-AD) study. Results68% of the ROS/MAP participants were female, and 52% were diagnosed with AD dementia. We first identified several disease-dependent or sex-dependent cell subpopulations. Then we identified 2,660 sex-specific associations involving 2,110 genes with A{beta} (51%), tau (21%), and cognitive performance (29%). 60% female-specific associations were for A{beta}, and 49% male-specific associations were with tau. The vast majority (93%) of female protective associations were from neurons, and most (76%) of female risk associations were from glial cells. Nine of the female-specific associations involving eight unique genes were replicated in the SEA-AD cohort, including ADGRV1 and OR3A3 with A{beta}; IFI27L1, LYRM1, STAP2, and TSTD2 with tau; PDYN with global cognition; and TMEM50B with longitudinal cognitive decline. All replicated associations except TMEM50B were observed in neurons. Furthermore, the preponderance of protective female-specific associations in neurons was also recapitulated in the SEA-AD cohort. Sex-specific associations were enriched for genes in the immune, inflammation, and damage-related stress response pathways, and microglia presented the most sex-specific enriched pathways. Finally, we identified six ITGB1-mediated microglia-specific incoming signals that may play a role in female-specific risk for A{beta} accumulation. ConclusionOur study highlights the transcriptome-wide, single-cell landscape of sex-specific molecular associations with AD neuropathology and cognitive decline. We delineate the full scope of sex-specific transcript associations, differential expression, signaling pathway, and cell-cell communication network changes in each major DLPFC cell type, while identifying and replicating several female-specific gene associations in neurons to help direct future mechanistic studies.

neuroscience↗