Biology subjects

De Jager, P. L.

Publications and source records attributed to De Jager, P. L..

At least 19 recordsLinked to original sources

bioRxiv2026

Altered microglial communication in brains with Alzheimers Disease pathology

Microglia are the resident immune cells of the central nervous system and are highly versatile, continuously monitoring the brain microenvironment with their motile processes and responding to perturbations in diverse ways. Recent studies have revealed substantial functional heterogeneity among microglial states, suggesting that analyzing individual subpopulations is essential to capture specialized signaling programs and disease-associated interactions that would otherwise be obscured in bulk analyses. To better understand how these cells interact, we performed a ligand-receptor communication analysis using single-nucleus RNA sequencing data from the dorsolateral prefrontal cortex, comprising 16 microglial subpopulations together with other myeloid cells identified in brain tissue, including macrophages and monocytes. We characterized the signaling roles of these cell populations, compared individuals with and without neuropathologically defined Alzheimers disease, and associated cell-pair interactions with AD-related clinical and neuropathological traits. We found that AD was characterized by altered microglial composition and rewiring of intercellular communication, including disease-specific signaling pathways and distinct interaction hubs. Lipid-associated microglia were associated with tau pathology, whereas nuclear receptor signaling microglia were linked to hippocampal sclerosis. These findings were replicated in three independent datasets. Overall, this work provides an initial but comprehensive map of microglial communication in the aging human brain and identifies candidate signaling interactions for future functional validation.

neuroscience↗

bioRxiv2026

Post-translational modifications in the brain are critical contributors to Alzheimers disease neuropathology and cognitive decline

Post-translational modifications (PTMs) in APP and MAPT contribute to plaques and tangles in Alzheimers disease (AD). Yet broader proteome-wide PTMs in the AD brain are relatively unexplored. Therefore, this study highlights associations between PTMs, quantified by mass spectrometry in prefrontal cortex tissue, and Alzheimers disease neuropathology and cognition. Leveraging PTMs quantified from prefrontal cortices in 101 Rush Memory and Aging Project participants. We assessed associations with post-mortem amyloid-{beta} and tau burden, global cognition, and cognitive decline. First, APP and MAPT PTM associations were assessed on these outcomes given their known relevance in AD, followed by assessment of protein-wide effects of PTMs. Then, kinase enrichment analysis was performed on each outcome to assess which kinases might contribute to the results. We observed a novel association of APP-K687 acetylation, a known mutation hotspot driving pathology, with amyloid-{beta} load ({beta}=0.44, P=3.9e-8), while confirming known MAPT PTMs with tangle burden. Further, we identified 20+ novel PTMs associations with AD neuropathology, including ENO2-K256 ubiquitination ({beta}=0.353, P=1.13e-6), PSMD13-K31 ubiquitination ({beta}=0.568, P=1.34e-6), and PLXND1-K1826 ubiquitination ({beta}=0.577, P=7.08e-8) for tangle burden and SYP-K23 ubiquitination ({beta}=1.50, P=4.7e-8), TMEFF2-C80 cysteine oxidation ({beta}=1.64, P=1.1e-8), and STX1B-T121 phosphorylation ({beta}=0.898, P=3.3e-7) for amyloid-{beta} load. Further, kinase enrichment analyses highlight the complexity of disease-related proteome changes with some kinases like CDK5 showing expected over-enrichment (amyloid z=3.44, P=3.0e-4; tau z=4.98, P=3.3e-7) but others like PKC family kinases showing divergent enrichment between amyloid (z=8.98-11.55, P<1.0e-18) and tau (z=-2.83--3.88, P<0.006). This study provides an atlas of brain PTMs within crucial proteins like MAPT and APP and at the proteome-wide level, that impact AD neuropathology and clinical presentation. Further, we explored what kinases might be driving phosphorylation results, emphasizing the complex proteome changes which impact AD. In sum, these results highlight robust post-translational alterations in the AD brain and provide novel targets for future mechanistic studies.

neuroscience↗

bioRxiv2025

mfSuSiE enables multi-cell-type fine-mapping and multi-omic integration of chromatin accessibility QTLs in aging brain.

Molecular quantitative trait locus (QTL) studies increasingly profile chromatin accessibility, histone modifications, DNA methylation, RNA modifications such as N6-methyladenosine (m6A), and transcription across multiple cell types using high-throughput sequencing, generating dense base-pair-resolved measurements. The conventional approach of testing each variant against each molecular feature independently suffers from severe multiple testing burden and ignores linkage disequilibrium and spatial correlation. Existing fine-mapping methods only partially address these challenges and are sub-optimal for analyzing such datasets: multivariate approaches such as mvSuSiE jointly analyze multiple molecular contexts but are designed for a single trait value per context and cannot accommodate thousands of base-resolution measurements per context, while functional approaches such as fSuSiE model spatial structure across thousands of measurements but analyze each context separately. Here, we introduce mfSuSiE, which integrates multivariate analysis with wavelet-based functional regression to jointly fine-map thousands of base-resolution traits across multiple cell types. In simulations, mfSuSiE identified causal variants and affected molecular features more accurately than fSuSiE, while mvSuSiE cannot be applied to this type of data. Applied to single-nucleus chromatin accessibility data from six brain cell types from postmortem aging human brains, mfSuSiE substantially increased discovery and resolution, with substantial power gains for cell types with limited samples. Multi-cell-type analysis revealed extensive sharing of regulatory effects on chromatin accessibility (caQTL). Importantly, mfSuSiE produces Bayesian inference compatible with the SuSiE framework, enabling systematic multi-omic integration. Applied to Alzheimers disease loci, we integrated caQTL with expression QTLs, epigenomic QTLs, and GWAS, observing regulatory patterns suggesting complex mechanisms at loci including EARS2, CHRNE, SCIMP, and RABEP1.

genetics↗

bioRxiv2025

INPP5D/SHIP1 is a dual regulator of endo-lysosome function and selective phagocytosis in human microglia

INPP5D, which encodes SHIP1, is genetically associated with Alzheimers disease (AD) risk and regulates microglial immune function. Here we identified SHIP1 as a regulator of endo-lysosomal homeostasis in human microglia. INPP5D haploinsufficiency impaired endosome maturation and lysosomal degradation, leading to lipid droplet accumulation, lysosomal stress, and NLRP3 inflammasome activation. SHIP1-deficient microglia shifted from an immune-responsive state toward a disease-associated state with elevated cargo-selective phagocytosis. Although amyloid-{beta} uptake was unaffected, SHIP1-deficient microglia accumulated intracellular amyloid-{beta} and exhibited exacerbated lipid droplet accumulation, consistent with defective lysosomal processing. Proteomic analysis of genetically diverse human microglia revealed that the protective INPP5D rs10933431 variant is associated with elevated phosphatase-domain containing SHIP1, and protein profiles consistent with enhanced endolysosomal trafficking. In mice xenografted with SHIP1-deficient human microglia, high amyloid-{beta} burden exacerbated lysosomal, lipid droplet and inflammasome phenotypes. Together, these findings identify disrupted endo-lysosomal trafficking and degradative capacity as mechanisms linking INPP5D dysfunction to disease-associated microglial states in AD.

neuroscience↗

bioRxiv2025

Transcriptional regulation of disease-relevant microglial activation programs

Microglia, the brains innate immune cells, can adopt a wide variety of activation states relevant to health and disease. Dysregulation of microglial activation occurs in numerous brain disorders, and driving or inhibiting specific states could be therapeutic. To discover regulators of microglia activation states, we conducted CRISPR interference screens in iPSC-derived microglia for inhibitors and activators of six microglial states. We characterized 31 regulators at the single-cell transcriptomic and cell-surface proteome level in two distinct iPSC-derived microglia models, uncovering new protein markers of relevant states. We functionally characterized several multi- state regulators. ZNF532 and PRDM1 knockdown drive disease-associated, lipid-rich signatures and enhance phagocytosis while showing opposing effects on antigen-presentation signatures. DNMT1 knockdown results in widespread loss of methylation, activating negative regulators of interferon signaling. These findings provide a framework to direct microglial activation to selectively enrich microglial activation states, define their functional outputs, and inform future therapies. HighlightsO_LICRISPRi screening reveals novel regulators of six microglia activation states C_LIO_LIMulti-modal single-cell screens highlight new markers of microglial states C_LIO_LIDifferent iPSC-microglia models show different landscapes of activation states at baseline C_LIO_LILoss of DNMT1 leads to widespread DNA demethylation, promoting some states but limiting the interferon-response state C_LIO_LILoss of PRDM1 or ZNF532 drives the microglial disease-associated state C_LI

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

BAG3 coordinates astrocytic proteostasis of Alzheimer's disease-linked proteins via proteasome, autophagy, and retromer complex interactions

BackgroundBcl-2-associated athanogene 3 (BAG3) is a mediator of chaperone assisted selective autophagy, and in the brain, most highly expressed in astrocytes. However, its role in astrocytes remains poorly defined. Given the genetic and pathological links of BAG3 to proteostasis and neurodegenerative diseases, we investigated how BAG3 contributes to astrocyte function and Alzheimers disease (AD). MethodsSnRNA-seq of the human brain determined cell type expression of BAG3. CRISPR/Cas9 gene editing in human iPSCs, followed by tandem mass tag-mass spectrometry and RNA-sequencing was performed to assess proteomic and transcriptomic changes following BAG3 loss. Co-immunoprecipitation of BAG3 in human astrocytes defined the interactome, with top interactors being validated by western blot (WB), AlphaFold modeling, and proximity ligation assays. In astrocytes, autophagic flux, lysosomal phenotypes, proteasome activity, and endocytic uptake were measured in BAG3 KO and BAG3 WT. Finally, BAG3 expression was assessed in postmortem AD brain by WB and snRNA-seq, and its functional relevance to amyloid-{beta} (A{beta}) degradation was tested in co-cultures of BAG3 KO iAs with familial AD neurons. ResultsIn human brain and iPSC models, BAG3 was most highly expressed in astrocytes. Further, BAG3 loss caused greater proteomic disruption in astrocytes than in neurons. In the absence of BAG3, astrocytes showed reduced autophagy, diminished lysosome abundance and activity, and decreased proteasome function. To uncover molecular binding partners of BAG3 that might influence these phenotypes, we performed co-immunoprecipitation, revealing interactions with HSPB8 and other heat shock proteins, proteasome regulators (PSMD5, PSMF1), and the retromer component, VPS35. Integration of BAG3 KO transcriptomic and proteomic datasets pinpointed AD-relevant proteins under post-translational control of BAG3, which included GFAP, BIN1, and HSPB8. HSPB8 levels were markedly reduced in BAG3-deficient astrocytes with overexpression partially rescuing its levels. Loss of astrocytic BAG3 impaired A{beta} clearance in co-culture with APP/PSEN1 mutant neurons, directly linking BAG3 to a disease-relevant astrocyte function. Finally, analysis of postmortem brain tissue revealed BAG3 marks a stress-responsive astrocyte subtype in the brain of aged individuals with AD. ConclusionsBAG3 binds to key regulators of autophagy, proteasome activity, and retromer function to coordinate astrocyte proteostasis, lysosomal function, and A{beta} clearance. These findings position BAG3 as a potential therapeutic target and coordinator of glial protein quality control in neurodegeneration.

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

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

Phosphoproteomics unveils the signaling dynamics in neuronal cells stimulated with insulin and insulin-like growth factors

BackgroundGiven the role of metabolism in brain health and disease, investigating the role of insulin (INS) and insulin-like growth factors (IGFs) as potential therapeutic strategies for neurodegenerative diseases is currently underway. Yet, the signaling pathways associated with INS and IGFs in the brain remain elusive, particularly for the human brain. Unraveling these pathways is critical for harnessing their therapeutic potential in metabolism-associated brain disorders. MethodsThis study employed phosphoproteomics using human neuroblastoma cell line, SH-SY5Y, to unravel the signaling network of INS, IGF-1, and IGF-2. Briefly, cells were stimulated at 10 and 60-minutes with the ligands, followed by protein extraction, trypsin digestion, tandem mass tag (TMT)-labelling and phosphopeptides enrichment using an immobilized metal affinity chromatography (IMAC) and liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis. Data was processed using R statistical software. Protein annotations were obtained from the UniprotKB database, and pathway enrichment analysis was performed using Ingenuity Pathway Analysis (IPA). ResultsPhosphoproteomics performed at 10 and 60 minutes identified 34358 phosphosites of which 3284 were significant at 10 min and 2374 at 60 min (p.adj <0.05) across all three ligands. Ligand stimulation induced modulation in phosphorylation at both the receptor level and downstream signaling targets at serine (S), threonine (T) and tyrosine (Y) residues. Phosphorylation of LIMA1-Y229, a regulator of actin-cytoskeletal function, was the most prominent Y phosphosite across all ligands. IPA identified Rho GTPase, the molecular switches that regulate actin cytoskeletal dynamics, as the most significantly enriched pathway, with IGF-1 predominantly driving phosphorylation of Rho GTPase effectors such as Rho Guanine nucleotide exchange factors (ARHGEFs), Rho GTPase activating proteins (ARHGAPs) and CDC42. Myocardin related transcription factor A (MRTFA), a transcriptional target of Rho GTPase, was increased in ligand-stimulated cells at 10 min, and inhibition of Rho/SRF pathway by CCG1423 prevents nuclear localization of IGF-1-induced MRTFA. ConclusionsThis study demonstrates that INS, IGF-1 and IGF-2 regulate Rho GTPase and MRTFA activation, thereby contributing to the control of actin cytoskeletal dynamics in neuronal cells. Given the role of INS and IGFs in neuronal survival and neurodegenerative conditions, elucidating the mechanisms is of critical importance, as it offers insights into disease pathogenesis and potential therapeutic targets.

biochemistry↗

bioRxiv2025

A Radiomic Approach to Clinical MRI Refines the Thalamus-Cognition Link in Multiple Sclerosis

Background and ObjectivesRadiomics extracts imaging features that may not be detectable through conventional volumetric analyses. Given their role in multiple sclerosis (MS), we applied radiomics to thalamic nuclei and examined their associations with cognitive performance. MethodsA total of 601 individuals were included (342 people with MS-PwMS from two cohorts, and 259 healthy controls-HC). Radiomic features (RF) and volumes were extracted from the whole thalamus, five thalamic nuclei, and the putamen segmented on 3D T1-weighted images. Cognitive performance was assessed using the Symbol Digit Modalities Test (SDMT) and Paced Auditory Serial Addition Test (PASAT) in PwMS, and the Digit Symbol Substitution Test (DSST) in HC. In the first MS cohort, multivariate linear regression in a discovery set (N=103) identified thalamus-derived RF associated with SDMT, which were retested in a replication set (N=63). Their associations with PASAT in a second MS cohort (N=176) and DSST in HC were also evaluated. We then tested whether the same RF, when extracted from the putamen, were associated with SDMT. LASSO models assessed the combined predictive value of RF and volumes. Figure 2 presents an overview of the involvement of different cohorts in the study, outlining the specific study objectives and the statistical analysis approaches employed. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=110 SRC="FIGDIR/small/657698v1_fig2.gif" ALT="Figure 2"> View larger version (40K): org.highwire.dtl.DTLVardef@6f1dd8org.highwire.dtl.DTLVardef@11069c6org.highwire.dtl.DTLVardef@905512org.highwire.dtl.DTLVardef@1c12171_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOFigure 2.C_FLOATNO Overview of the involvement of different cohorts in the study, specific study objectives and the statistical analysis approaches employed. Abbreviations: SDMT: Symbol Digit Modalities Test, PASAT: Paced Auditory Serial Addition Test, DSST: Digit Symbol Substitution Test, LASSO: Least Absolute Shrinkage and Selection Operator. C_FIG ResultsTwenty-eight RF-ROI pairs were associated with SDMT in the replication set (FDR<0.05). Of these, 24 were also associated with PASAT (FDR[≤]0.03), and 2 with DSST. Only ventral nuclei volume showed replicated associations among volumetrics. Only 4 putamen-derived pairs were associated with SDMT (FDR=0.04). LASSO results confirmed RF outperformed volumes. DiscussionRF extracted from the thalamus are strongly associated with cognitive performance in PwMS, outperforming volumetric measures and supporting their potential as sensitive imaging biomarkers.

neuroscience↗

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

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↗

bioRxiv2025

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↗

bioRxiv2025

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↗