Biology subjects

Roussos, P.

Publications and source records attributed to Roussos, P..

At least 19 recordsLinked to original sources

bioRxiv2026

Human Choroid Plexus Organoids Progress to Postnatal-like Maturation and Reveal a Closing Window of Developmental Plasticity

The choroid plexus (ChP) produces cerebrospinal fluid (CSF) and forms the blood-CSF barrier, yet the developmental programme driving its maturation in humans remains poorly understood. Using a 15-timepoint single-cell RNA sequencing atlas of human ChP organoids benchmarked against human tissue, we resolve an ordered differentiation process comprising cell cycle exit, ciliogenesis and ion transporter expression. Maturation culminates in a transcriptional state with features of human adult ChP, establishing the first in vitro ChP model to reach postnatal-like milestones. Centrosome proteomics identified previously uncharacterised, stage-specific regulators of ciliogenesis. To probe developmental plasticity, we perturbed ChP organoids with valproic acid (VPA), a clinically used antiepileptic and established teratogen. Early VPA-mediated disruption of multiciliogenesis and secretion recovered upon drug withdrawal, whereas late treatment washout resulted in persistent impairment of mature transporters. Together, these findings resolve the developmental programme by which the ChP reaches functionally mature identity and identify a stage-dependent plasticity window during its maturation.

developmental biology↗

bioRxiv2026

Cross-source proteogenomic profiling of human microglia reveals a conserved core membrane protein and HERV signature

Microglia are essential immune cells of the brain parenchyma which are responsible for maintaining homeostasis and responding to brain injury. When activated, they induce immune signaling and become phagocytic. In the context of neurodegenerative diseases, they exhibit both pro- and anti-inflammatory properties. Human endogenous retroviruses (HERVs) are the remnants of ancient retroviral germline infections that integrated into the human genome, and their expression has been directly linked to microglial-mediated neurodegenerative diseases. Despite this, HERV expression is not consistently included in analyses characterizing microglia. Investigating the function of microglia across different diseases is critical for elucidating mechanisms of disease progression and for the development of effective therapeutic interventions. Approaches to studying microglia include isolation from post-mortem brain tissues, differentiation from peripheral blood monocytes or differentiation of induced pluripotent stem cells (iPSC). Ex vivo brain derived microglia (BdMG) are considered most physiologically relevant, but constraints including the unpredictable timing of availability, labor-intensive protocols, and low yields reduce their practicality. Existing alternatives are iPSC-derived microglia (iMG) and monocyte-derived microglia (MDMi) models that circumvent sample accessibility and scalability issues. Here, we explored the transcriptome and proteome of these three microglia sources and identified a common microglia surface marker expression profile, establishing that MDMi and iMG exhibit similar phenotypes relative to BdMG. We also identified a common HERV expression profile across BdMG, iMG and MDMi, indicating deeper similarities across different sources. Altogether, our findings indicate that given the phenotypic similarities of the 2 models, MDMi represent a practical and reliable model for investigating microglial function with iMG models serving for more molecular based approaches, such as CRISPRa/i.

neuroscience↗

bioRxiv2026

Early microglial priming in Alzheimer's disease revealed by ME-seq

Epigenetic modifications, particularly DNA methylation, change dynamically with aging and are implicated in Alzheimers Disease (AD), yet how methylation interfaces with transcriptional and chromatin regulation at single-cell resolution remains poorly understood. Progress has been limited by a lack of scalable technologies capable of jointly profiling these regulatory layers. Here, we present ME-seq, a highly scalable technologies capable of simultaneously profiling DNA methylation, gene expression, and chromatin accessibility, while achieving a 100-fold reduction in cost. We generated over 400,000 single-nucleus trimodal profiles from the aging and AD mouse brain across ages, producing the first such atlas of neurodegeneration. We found AD progression triggers pronounced, disease-specific shifts in cellular composition, characterized by accelerated epigenetic aging and the expansion of disease-associated microglia (DAM). Integrative analyses, including aging clocks, revealed that DNA methylation acts as an early priming layer preceding transcriptional activation with IRF1 identified as a methylation-sensitive transcription factor serving as a gatekeeper for DAM activation. Our results establish ME-seq as a transformative tool for large-scale epigenomic dissection, revealing DNA methylation as a primary coordinator of cell-state transitions in the aging brain. Graphic abstract O_FIG O_LINKSMALLFIG WIDTH=195 HEIGHT=200 SRC="FIGDIR/small/702946v1_ufig1.gif" ALT="Figure 1"> View larger version (70K): org.highwire.dtl.DTLVardef@67435dorg.highwire.dtl.DTLVardef@177c22aorg.highwire.dtl.DTLVardef@16c6fd9org.highwire.dtl.DTLVardef@231b92_HPS_FORMAT_FIGEXP M_FIG C_FIG

genomics↗

bioRxiv2025

Cell-type-resolved NRXN1 isoforms across human brain tissues and hiPSC organoids

NRXN1 undergoes extensive alternative splicing that generates a highly diverse repertoire of isoforms, diversifying protein-protein interactions, shaping synaptic specialization, and contributing to neuropsychiatric disease when disrupted. However, the splicing landscape of NRXN1 across distinct human brain cell types remains poorly defined. Because NRXN1 expression level is relatively low in adult brains and human induced pluripotent stem cell (hiPSC) derived neurons, single-cell long-read cDNA sequencing often provides insufficient coverage to capture its full isoform diversity, particularly across heterogeneous cell populations. To address this gap, we developed an integrative sequencing strategy that combines single-cell transcriptomics, targeted enrichment of NRXN1 transcripts, and long-read sequencing. This approach reveals a comprehensive catalog of cell-type resolved NRXN1 isoforms across adult and fetal human postmortem brains as well as hiPSC-derived cortical organoids. From the adult prefrontal cortex (PFC) region, our analyses reveal distinct splicing programs across interneuron subtypes, pyramidal neurons, and glial lineages. Comparisons between prenatal and adult brains indicate that NRXN1 isoform profiles are established during early development and remain stable throughout neuronal maturation. In hiPSC organoid models, splicing profiles partially mirror both developmental and mature brain patterns, with a subset of splice sites exhibiting cell type - and stage-specific divergence. In the cerebellum of an autism case and in organoids derived from schizophrenia patients, carrying non-recurrent heterozygous NRXN1 deletions, we identify disrupted isoform expression and mutant NRXN1 isoforms and characterize their distribution across diverse cell types. Using this integrated long-read sequencing framework in patient-derived organoids, we further show that antisense oligonucleotide (ASO) targeting of mutant splice junctions reduces gain-of-function NRXN1 isoforms and reshapes splicing patterns in a cell type-specific manner, providing a platform for evaluating ASO efficiency. Together, these findings help understand the cell type-specific splicing landscape of NRXN1 and establish a framework for decoding cell type-specific isoform diversity and assessing transcript-targeted therapies for genes with low expression levels.

neuroscience↗

bioRxiv2025

Fast Probabilistic Whitening Transformation for Ultra-High Dimensional Genetic Data

Statistical methods often make assumptions about independence between the samples or features of a dataset. Yet correlation structure is ubiquitous in real data, so these assumptions are often not met in practice. Whitening transformations are widely applied to remove this correlation structure. Existing approaches to whitening are based on standard linear algebra, rather than a probabilistic model, and application to high dimensional datasets with n samples and p features is problematic as p approaches or exceeds n. Moreover, the computational time becomes prohibitive since the naive transform is cubic in p. Here we propose a probabilistic model for data whitening and examine its properties based on first principles as p increases. We demonstrate the statistical properties of the probabilistic model and derive a remarkably efficient algorithm that is linear instead of cubic time in the number of features. We examine the out-of-sample performance of the probabilistic whitening model on simulated data, and real genotype data. In an application to impute z-statistics from unobserved genetic variants from a genome-wide association study of schizophrenia, the probabilistic whitening transformation, had the lowest mean square error while being up to an order of magnitude faster than other methods. Using this approach, we also identify tandem repeats that explain genetic regulatory signals for disease-relevant genes. Analyses are implemented in our novel open source R packages decorrelate and imputez.

genetics↗

bioRxiv2025

Fast, flexible analysis of differences in cellular composition with crumblr

Changes in cell type composition play an important role in human health and disease. Recent advances in single-cell technology have enabled the measurement of cell type composition at increasing cell lineage resolution across large cohorts of individuals. Yet this raises new challenges for statistical analysis of these compositional data to identify changes in cell type frequency. We introduce crumblr (DiseaseNeurogenomics.github.io/crumblr), a scalable statistical method for analyzing count ratio data using precision-weighted linear mixed models incorporating random effects for complex study designs. Uniquely, crumblr performs statistical testing at multiple levels of the cell lineage hierarchy using a multivariate approach to increase power over tests of one cell type. In simulations, crumblr increases power compared to existing methods while controlling the false positive rate. We demonstrate the application of crumblr to published single-cell RNA-seq datasets for aging, tuberculosis infection in T cells, bone metastases from prostate cancer, and SARS-CoV-2 infection.

bioinformatics↗

bioRxiv2024

Comprehensive profiling of small RNAs and their changes and linkages to mRNAs in schizophrenia and bipolar disorder

We investigated small non-coding RNAs (sncRNAs) from the prefrontal cortex of 93 individuals diagnosed with schizophrenia (SCZ) or bipolar disorder (BD) and 77 controls. We uncovered recurring complex sncRNA profiles, with 98% of all sncRNAs being accounted for by miRNA isoforms (60.6%), tRNA-derived fragments (17.8%), rRNA-derived fragments (11.4%), and Y RNA-derived fragments (8.3%). In SCZ, 15% of all sncRNAs exhibit statistically significant changes in their abundance. In BD, the fold changes (FCs) are highly correlated with those in SCZ but less acute. Non-templated nucleotide additions to the 3'-ends of many miRNA isoforms determine their FC independently of miRNA identity or genomic locus of origin. In both SCZ and BD, disease- and age-associated sncRNAs and mRNAs reveal accelerated aging. Co-expression modules between sncRNAs and mRNAs align with the polarities of SCZ changes and implicate sncRNAs in critical processes, including synaptic signaling, neurogenesis, memory, behavior, and cognition.

neuroscience↗

bioRxiv2024

High-risk neuropsychiatric copy number variants are associated with convergent transcriptomic changes in human brain cells

Large, recurrent copy number variants (CNVs) are among the strongest risk factors for neuropsychiatric conditions, contributing to multiple phenotypes with overlapping psychiatric and cognitive symptoms. However, the molecular basis of this convergent risk remains unknown. We evaluated the human brain transcriptome in carriers of nine high-risk neuropsychiatric CNVs and matched non-carriers using single nucleus RNA-sequencing. Brain tissue from carriers displayed widespread disruptions of gene expression, with thousands of differentially expressed genes, mostly located outside of the respective CNV regions. There were greater changes in deletions compared to reciprocal duplications. Functional enrichment analysis revealed changes in mitochondrial energy metabolism and synaptic function that converged across CNVs and cell types. For mirror CNVs, the direction of effects was often reversed between deletions and duplications and showed correlation with CNV gene dosage. These findings suggest that a shared pathophysiology underlies risk for convergent brain phenotypes across CNVs and point toward promising therapeutic targets.

genetics↗

bioRxiv2024

A conserved cell-type gradient across the human mediodorsal and paraventricular thalamus

The mediodorsal thalamus (MD) and adjacent midline nuclei are important for cognition and mental illness, but their cellular composition is not well defined. Using single-nucleus and spatial transcriptomics, we identified a conserved excitatory neuron gradient, with distinct spatial mapping of individual clusters. One end of the gradient was expanded in human MD compared to mice, which may be related to the expansion of granular prefrontal cortex in hominids. Moreover, neurons preferentially mapping onto the parvocellular division MD were associated with genetic risk for schizophrenia and bipolar disorder. Midbrain-derived inhibitory interneurons were enriched in human MD and implicated in genetic risk for major depressive disorder.

neuroscience↗

bioRxiv2024

Dynamic alterations in gene co-expression networks and gene-transcript associations characterize co-morbidities in cocaine use disorder

BackgroundIndividuals with cocaine use disorder (CUD) who attempt abstinence experience craving and relapse, which poses challenges in treatment. Longitudinal studies linking behavioral manifestations in CUD to the blood transcriptome in living individuals are limited. Therefore, we investigated the connection between drug use behaviors during abstinence with blood transcriptomics. MethodsWe conducted a comprehensive longitudinal study involving 12 subjects (9 males, 3 females) with CUD and RNA sequencing on blood collected at a drug-free baseline, and 3, 6 & 9 months thereafter. We categorized subjects into 2 responder groups (high-low) based on scores of drug use variables, and 3 responder groups (low-intermediate-high) on days of abstinence. We investigated differential expression and gene-transcript associations across responder groups at each time point. Lastly, we examined genes that are both co-expressed and showed dynamic expression with time. ResultsGenes with significant transcript associations between high and. intermediate days of abstinence at 9 months were notably enriched for cannabis use disorder, drinks weekly, and coronary artery disease risk genes. Time-specific gene co-expression analysis prioritized transcripts related to immune processes, cell cycle, RNA-protein synthesis, and second messenger signaling for days of abstinence. ConclusionWe demonstrate that abstinence reflects robust changes in drug use behaviors and the blood transcriptome in CUD. We also highlight the importance of longitudinal studies to capture complex biological processes during abstinence in CUD.

genomics↗

bioRxiv2023

Transcriptional correlates of cocaine-associated learning in striatal ARC ensembles.

Learned associations between the rewarding effects of drugs and the context in which they are experienced underlie context-induced relapse. Previous work demonstrates the importance of sparse neuronal populations - called neuronal ensembles - in associative learning and cocaine seeking, but it remains unknown whether the encoding vs. retrieval of cocaine-associated memories involves similar or distinct mechanisms of ensemble activation and reactivation in nucleus accumbens (NAc). We use ArcCreERT2 mice to establish that mostly distinct NAc ensembles are recruited by initial vs. repeated exposures to cocaine, which are then differentially reactivated and exert distinct effects during cocaine-related memory retrieval. Single-nuclei RNA-sequencing of these ensembles demonstrates predominant recruitment of D1 medium spiny neurons and identifies transcriptional properties that are selective to cocaine-recruited NAc neurons and could explain distinct excitability features. These findings fundamentally advance our understanding of how cocaine drives pathological memory formation during repeated exposures.

neuroscience↗

bioRxiv2023

QuadST: A Powerful and Robust Approach for Identifying Cell-Cell Interaction-Changed Genes on Spatially Resolved Transcriptomics

Spatially resolved transcriptomics (SRT) have enabled profiling spatial organization of cells and their transcriptome in situ. Various analytical methods have been developed to uncover cell-cell interaction processes using SRT data. To improve upon existing efforts, we developed a novel statistical framework called QuadST for the robust and powerful identification of interaction-changed genes (ICGs) for cell-type-pair specific interactions on a single-cell SRT dataset. QuadST is motivated by the idea that in the presence of cell-cell interaction, gene expression level can vary with cell-cell distance between cell type pairs, which can be particularly pronounced within and in the vicinity of cell-cell interaction distance. Specifically, QuadST infers ICGs in a specific cell type pairs interaction based on a quantile regression model, which allows us to assess the strength of distance-expression association across entire distance quantiles conditioned on gene expression level. To identify ICGs, QuadST performs a hypothesis testing with an empirically estimated FDR, whose upper bound is determined by the ratio of cumulative associations at symmetrically smaller and larger distance quantiles simultaneously across all genes. Simulation studies illustrate that QuadST provides consistent FDR control and better power performance than other compared methods. Its application on SRT datasets profiled from mouse brains demonstrates that QuadST can identify ICGs presumed to play a role in specific cell type pair interactions (e.g., synaptic pathway genes among excitatory neuron cell interactions). These results suggest that QuadST can be a useful tool to discover genes and regulatory processes involved in specific cell type pair interactions.

bioinformatics↗

bioRxiv2023

A public resource of single cell transcriptomes and multiscale networks from persons with and without Alzheimer's disease

The emergence of technologies that can support high-throughput profiling of single cell transcriptomes offers to revolutionize the study of brain tissue from persons with and without Alzheimers disease (AD). Integration of these data with additional complementary multiomics data such as genetics, proteomics and clinical data provides powerful opportunities to link observed cell subpopulations and molecular network features within a broader disease-relevant context. We report here single nucleus RNA sequencing (snRNA-seq) profiles generated from superior frontal gyrus cortical tissue samples from 101 exceptionally well characterized, aged subjects from the Banner Brain and Body Donation Program in combination with whole genome sequences. We report findings that link common AD risk variants with CR1 expression in oligodendrocytes as well as alterations in peripheral hematological lab parameters, with these observations replicated in an independent, prospective cohort study of ageing and dementia. We also observed an AD-associated CD83(+) microglial subtype with unique molecular networks that encompass many known regulators of AD-relevant microglial biology, and which are associated with immunoglobulin IgG4 production in the transverse colon. These findings illustrate the power of multi-tissue molecular profiling to contextualize snRNA-seq brain transcriptomics and reveal novel disease biology. The transcriptomic, genetic, phenotypic, and network data resources described within this study are available for access and utilization by the scientific community.

genomics↗

bioRxiv2023

Dopaminoceptive D1 and D2 neurons in ventral hippocampus arbitrate approach and avoidance in anxiety

The hippocampus 1-7, as well as dopamine circuits 8-11, coordinate decision-making in anxiety-eliciting situations. Yet, little is known about how dopamine modulates hippocampal representations of emotionally-salient stimuli to inform appropriate resolution of approach versus avoidance conflicts. We here study dopaminoceptive neurons in mouse ventral hippocampus (vHipp), molecularly distinguished by their expression of dopamine D1 or D2 receptors. We show that these neurons are transcriptionally distinct and topographically organized across vHipp subfields and cell types. In the ventral subiculum where they are enriched, both D1 and D2 neurons are recruited during anxiogenic exploration, yet with distinct profiles related to investigation and behavioral selection. In turn, they mediate opposite approach/avoidance responses, and are differentially modulated by dopaminergic transmission in that region. Together, these results suggest that vHipp dopamine dynamics gate exploratory behaviors under contextual uncertainty, implicating dopaminoception in the complex computation engaged in vHipp to govern emotional states.

neuroscience↗

bioRxiv2023

ZBTB7A regulates MDD-specific chromatin signatures and astrocyte-mediated stress vulnerability in orbitofrontal cortex

Hyperexcitability in the orbitofrontal cortex (OFC) is a key clinical feature of anhedonic domains of Major Depressive Disorder (MDD). However, the cellular and molecular substrates underlying this dysfunction remain unknown. Here, cell-population-specific chromatin accessibility profiling in human OFC unexpectedly mapped genetic risk for MDD exclusively to non-neuronal cells, and transcriptomic analyses revealed significant glial dysregulation in this region. Characterization of MDD-specific cis-regulatory elements identified ZBTB7A - a transcriptional regulator of astrocyte reactivity - as an important mediator of MDD-specific chromatin accessibility and gene expression. Genetic manipulations in mouse OFC demonstrated that astrocytic Zbtb7a is both necessary and sufficient to promote behavioral deficits, cell-type-specific transcriptional and chromatin profiles, and OFC neuronal hyperexcitability induced by chronic stress - a major risk factor for MDD. These data thus highlight a critical role for OFC astrocytes in stress vulnerability and pinpoint ZBTB7A as a key dysregulated factor in MDD that mediates maladaptive astrocytic functions driving OFC hyperexcitability.

neuroscience↗

bioRxiv2023

Efficient differential expression analysis of large-scale single cell transcriptomics data using dreamlet

Advances in single-cell and -nucleus transcriptomics have enabled generation of increasingly large-scale datasets from hundreds of subjects and millions of cells. These studies promise to give unprecedented insight into the cell type specific biology of human disease. Yet performing differential expression analyses across subjects remains difficult due to challenges in statistical modeling of these complex studies and scaling analyses to large datasets. Our open-source R package dreamlet (DiseaseNeurogenomics.github.io/dreamlet) uses a pseudobulk approach based on precision-weighted linear mixed models to identify genes differentially expressed with traits across subjects for each cell cluster. Designed for data from large cohorts, dreamlet is substantially faster and uses less memory than existing workflows, while supporting complex statistical models and controlling the false positive rate. We demonstrate computational and statistical performance on published datasets, and a novel dataset of 1.4M single nuclei from postmortem brains of 150 Alzheimers disease cases and 149 controls.

genomics↗

bioRxiv2023

Evaluating performance and applications of sample-wise cell deconvolution methods on human brain transcriptomic data

Sample-wise deconvolution methods have been developed to estimate cell-type proportions and gene expressions in bulk-tissue samples. However, the performance of these methods and their biological applications has not been evaluated, particularly on human brain transcriptomic data. Here, nine deconvolution methods were evaluated with sample-matched data from bulk-tissue RNAseq, single-cell/nuclei (sc/sn) RNAseq, and immunohistochemistry. A total of 1,130,767 nuclei/cells from 149 adult postmortem brains and 72 organoid samples were used. The results showed the best performance of dtangle for estimating cell proportions and bMIND for estimating sample-wise cell-type gene expression. For eight brain cell types, 25,273 cell-type eQTLs were identified with deconvoluted expressions (decon-eQTLs). The results showed that decon-eQTLs explained more schizophrenia GWAS heritability than bulk-tissue or single-cell eQTLs alone. Differential gene expression associated with multiple phenotypes were also examined using the deconvoluted data. Our findings, which were replicated in bulk-tissue RNAseq and sc/snRNAseq data, provided new insights into the biological applications of deconvoluted data.

genomics↗

bioRxiv2023

Genetic regulation of cell-type specific chromatin accessibility shapes the etiology of brain diseases

Nucleotide variants in cell type-specific gene regulatory elements in the human brain are major risk factors of human disease. We measured chromatin accessibility in sorted neurons and glia from 1,932 samples of human postmortem brain and identified 34,539 open chromatin regions with chromatin accessibility quantitative trait loci (caQTL). Only 10.4% of caQTL are shared between neurons and glia, supporting the cell type specificity of genetic regulation of the brain regulome. Incorporating allele specific chromatin accessibility improves statistical fine-mapping and refines molecular mechanisms underlying disease risk. Using massively parallel reporter assays in induced excitatory neurons, we screened 19,893 brain QTLs, identifying the functional impact of 476 regulatory variants. Combined, this comprehensive resource captures variation in the human brain regulome and provides novel insights into brain disease etiology. One sentence summaryCell-type specific chromatin accessibility QTL reveals regulatory mechanisms underlying brain diseases.

genomics↗