Biology subjects

Devlin, B.

Publications and source records attributed to Devlin, B..

At least 19 recordsLinked to original sources

bioRxiv2026

Microglia sculpt dopamine receptor-mediated adolescent behaviors in a social experience dependent manner

Adverse childhood experiences like social isolation (SI) contribute to long term negative health outcomes and the development of severe psychiatric disorder. Adolescence is a unique period of coordinated social and motivational system development driven by dopamine (DA) signaling. Microglia, immune cells of the brain, may play a unique role in regulating SI-induced DA system changes and associated behavioral dysfunction. Male microglia refine dopamine D1 receptors (D1rs) in the nucleus accumbens (NAc) of adolescent male rats shaping play behavior. Here we characterized the molecular developmental impacts of postweaning SI from P21-P38, with a resocialization period to P54. We tested the role of microglial engulfment of D1rs in mediating behavioral consequences of SI using neutrophil inhibitory factor (NIF) to block complement-mediated engulfment required for D1r pruning. We found sex specific impacts of SI on brain development and the DA system. In SI males, microglia engulf more NAc D1rs than group housed (GH) controls. Within GH animals, NAc D1r density is positively correlated to play and allogrooming. In SI animals, NAc D1r density is negatively correlated to biting behavior, and is not correlated to play or allogrooming. Pharmacologically inhibiting microglial engulfment of D1r via bilateral NAc NIF injection prevents observed D1r:behavior correlations in GH and SI animals. NIF treatment interacts with SI, exaggerating aggressive-like behavior, showing a role for microglia in regulating aggressive-like behavior via complement pruning in adolescence. Microglia may play a unique role in regulating behavior that drive negative health outcomes in the face of developmental stress, including SI.

neuroscience↗

bioRxiv2026

Autism genes converge on three functional programs organized by neuronal subclass, developmental timing, and cortical patterning

Our companion sequencing study uncovered 253 genes robustly associated with autism spectrum disorder (ASD), yet the biological programs they impact, and the cellular, developmental, and spatial contexts in which they converge, remain unresolved. Here we systematically contextualize genes associated with ASD across neurodevelopment and cortical areas, integrating developmental single-cell and spatial atlases with gene- and isoform co-expression, regulatory, proteomic, and synaptic networks. Genetic burden concentrates within temporally-resolved neuronal subclasses: newborn excitatory neurons, immature interneurons, and maturing intratelencephalic lineages. Genes associated with ASD converge on three functional programs--gene regulation, neuronal morphogenesis, and synaptic transmembrane signaling machinery--resolved from 28 ASD-associated networks, several of which are directly regulated by ASD genes including MEF2C, SOX11, and FOXP2. These programs are spatially patterned, with risk genes exhibiting an increasing anterior-to-posterior cortical expression gradient, anchored in the primary visual cortex and driven by excitatory neuron gene-regulatory programs. Finally, ASD risk genes associated with more severe developmental phenotypes show broader excitatory neuron enrichment and less interneuron involvement. Together, these findings anchor ASD genetic vulnerability to specific neurodevelopmental lineages, epochs, and molecular substrates, and delineate the features that distinguish ASD from comorbidities with broader developmental impacts.

genomics↗

bioRxiv2026

Proteomic profiling across early postnatal development of midbrain dopamine axons innervating the dorsal striatum

Precise wiring and tuning of dopamine axons in the brain is crucial for normal development of basal ganglia circuits. This process takes place both pre and postnatally, with early postnatal windows reflecting important periods of terminal maturation. Protein expression and precise localization are vital to this process, underlying changes in axon structure and function. Yet, technical hurdles have prohibited mapping protein expression and localization as dopamine axons mature to form functional release sites. Here we employ targeted proximity labeling in midbrain dopamine neurons and track isolated distal axonal proteins in the striatum across development, from the neonatal period through adolescence. Our approach enabled high-precision evaluation of the axonal proteome, supported by a combination of Cre-recombinase based restriction and spatial separation. We map co-varying subpopulations of axonal proteins differentially expressed across development. Microtubule-associated proteins decreased over time, revealing temporal dynamics of dopaminergic axon stabilization at the proteomic level. Conversely, proteins supporting coordinated action potential firing increased over time, likely contributing to the characteristic tonic firing of dopamine neurons emerging over development. Intersecting our findings with recent GWAS of psychiatric and neurological disorders provided functional confirmation of disease and disorder risk. This analysis highlighted early expression and localization of risk gene products, providing spatial-temporal points of convergence for disease-associated variants specifically to the initial stages of postnatal neurodevelopment of dopamine neurons. Together, these findings provide the essential grounding for understanding postnatal dopaminergic axon development and contextualize neurodevelopmental functions for numerous risk gene products.

neuroscience↗

bioRxiv2026

Inferring disruption of directed graphs using LIKA reveals altered protein phosphorylation networks in schizophrenia

MotivationKinases regulate a multitude of protein functions, and their dysregulation is pivotal for many human diseases. Direct measurement of kinase activity, however, is often challenging; therefore, inferring activity from the behavior of their substrates is a widely adopted strategy. Nonetheless, traditional methods typically oversimplify the underlying network, ignoring that any particular substrate can be phosphorylated by multiple kinases. ResultsWe present LIKA, a likelihood-based framework for inferring kinase activity from phosphoproteomic data. By modeling the many-to-many structure of kinase-substrate interactions, LIKA achieves high efficiency, even with limited data, while capturing network complexity. Simulation and cell line analyses confirm the robustness and accuracy of LIKA. Importantly, analysis of a phosphoproteomic dataset from schizophrenia and control subjects reveals novel dysregulated kinases. Availability and ImplementationThe implementation code and publicly available data are provided at: https://github.com/lujingz/LIKA.

bioinformatics↗

bioRxiv2026

Spatial transcriptomics implicates the thalamus and cortex in autism and schizophrenia

The past decade has seen tremendous progress in the identification of genes associated with complex neuropsychiatric disorders, including autism spectrum disorder (ASD) and schizophrenia. Expression patterns of these genes in single cell data strongly implicate excitatory and inhibitory neurons; however, there are limited data on the brain regions involved - a critical question for neurobiology. Spatial transcriptomics provide an opportunity to perform systematic multiregional analyses to provide insights into this question. Here, we have generated a spatial transcriptomics dataset encompassing the diverse anatomical territories of the adult mouse brain sagittal midsection. We compare neuropsychiatric gene enrichment by applying Gene Fraction Enrichment Score (GFES), a novel statistic method that controls for differing neuronal proportions across regions. ASD-associated genes identified by exome sequencing were most enriched in the thalamus followed by the cortex. Schizophrenia genes from genome-wide association studies were also enriched in the thalamus, along with the hippocampus and cortex. These findings add to the evidence that the thalamus plays a major role in neuropsychiatric disorders whilst supporting roles for the cortex and hippocampus. The results highlight shared and distinct patterns for pleiotropic brain disorders that could elucidate common underlying mechanisms and circuitry.

neuroscience↗

bioRxiv2026

Maternal high-fat diet drives sex-specific microglia remodeling of serotonergic reward circuits

Maternal nutrition shapes offspring brain development and influences neurodevelopmental disorder risk, but the underlying mechanisms remain unclear. In mice, maternal high-fat diet exposure disrupted microglia-serotonin interactions during a critical postnatal period, producing persistent, sex-specific mesolimbic alterations. Male but not female offspring showed increased serotonergic fiber density in the nucleus accumbens (NAc), coincident with reduced microglial phagocytosis of serotonergic projections. Microglial 5-HT2C receptor signaling is a key regulator of this process. Viral over expression in microglia, mimicking diet-induced upregulation, was sufficient to cause serotonergic hyperinnervation. By adulthood, male offspring displayed increased NAc serotonin release and projection-specific changes in dorsal raphe physiology. These circuit alterations accelerated reward-motivated learning, a phenotype reproduced by chemogenetic activation of NAc-projecting serotonergic neurons. Together, these findings reveal a novel mechanism by which maternal diet programs serotonergic circuit assembly and behavior in a sex-specific manner, providing a potential link between early-life metabolic inflammation and lifelong serotonergic dysfunction.

neuroscience↗

bioRxiv2026

Estimating protein isoform abundances with PAQu

A single gene can encode multiple versions of a protein, dubbed isoforms, with varying functionality. Cellular control of isoform abundances is critical for multiple aspects of biology and is only partially regulated by transcript levels. While long-read sequencing facilitates transcript quantification, quantifying the resulting protein isoforms on a large scale is a major challenge, complicating biological interpretation of transcript alterations. Standard "bottom up" mass spectrometry can assess only short portions of isoforms called peptides, and these peptides often map onto more than one isoform. We introduce PAQu, a novel Bayesian method that leverages multiomic information from the peptidome and transcriptome to provide accurate estimates of isoform abundance even when peptide mapping is ambiguous. PAQu offers several advantages over existing methods in a unified framework. It provides uncertainty quantification, integrates multiomic information for improved accuracy, and provides a rigorous framework for hypothesis testing. Extensive simulations show that PAQu consistently outperforms competing methods in detecting differentially expressed protein isoforms and estimating their abundances. We use PAQu to investigate differences in isoform abundance levels between people with schizophrenia and control subjects, confirming a long held hypothesis that levels of the C4A isoform of Complement Component 4 are increased in schizophrenia while C4B is not. These results demonstrate that PAQu can identify significant variations in isoform abundance levels not previously possible.

genomics↗

bioRxiv2025

DAWN-SCAPE: Discovering Associations With Networks through Shared Contextual Analysis of Phenotype and Expression

The molecular basis of phenotypes is often explored by contrasting gene expression from relevant tissue taken from individuals classified into phenotypic extremes, such as affected versus unaffected individuals. Analysis of this differential expression (DE) typically identifies many genes of interest. However, it is not clear which genes differ between extremes because they alter phenotypic liability and which show differences as a result of the extreme phenotype itself. We propose a formal model to distinguish between genes that are upstream and "cause" differential expression versus those for which differential expression is a result of the initial manifestation of phenotype. Relying on two sets of p-values, one from differential expression analysis and one from gene-specific association with phenotype (AP), and a gene coexpression or other gene-based network that serves as a bridge, our method identifies communities of genes more likely upstream or downstream of the phenotype. Our method consists of three major steps: 1) gene network construction, 2) evaluation of DE and AP signal within the network to infer hidden states, and 3) detection of gene communities. We apply our method to data that were generated to assess the biological basis of autism spectrum disorder (ASD) and Alzheimers disease (AD). Our results highlight neuronal and synaptic biology as being upstream of ASD, whereas downstream processes are all non-neuronal. For AD, our results are consistent with existing hypotheses; yet, they also lend support for a recent unifying hypothesis involving cofilin/actin biology.

genomics↗

bioRxiv2025

A framework to infer de novo exonic variants when parental genotypes are missing enhances association studies of autism

MotivationGene-damaging mutations are highly informative for studies seeking to discover genes underlying developmental disorders. Traditionally, these de novo variants are recognized by evaluating high-quality DNA sequence from affected offspring and parents. However, when parental sequence is unavailable, methods are required to infer de novo status and use this inference for association studies. ResultsWe use data from autism spectrum disorder to illustrate and evaluate methods. Separating de novo from rare inherited variants is challenging because the latter are far more common. Using a classifier for unbalanced data and variants of known inheritance class, we build an inheritance model and then a de novo score for variants when parental data are missing. Next, we propose a new Random Draw (RD) model to use this score for gene discovery. Built into an existing inferential framework, RD produces a more powerful gene-based association test and controls the false discovery rate. Availability and ImplementationThe implementation code and publicly available data are provided at: https://github.com/HaeunM/TADA-RD.

bioinformatics↗

bioRxiv2025

Transcriptomes of higher order thalamic nuclei in obsessive compulsive disorder

Obsessive-compulsive disorder (OCD) is a chronic psychiatric illness associated with altered function in cortico-striatal-thalamo-cortical (CSTC) circuits. In this pilot study, we examined differential RNA expression in the thalamus using postmortem human brain tissue samples from 11 subjects with OCD and 10 unaffected subjects. We individually dissected the mediodorsal magnocellular, mediodorsal parvocellular, and ventral anterior nuclei, which participate in orbitofrontal and anterior cingulate CSTC circuits most frequently associated with OCD, and the posterior ventrolateral nucleus, which participates in premotor and motor circuits that are increasingly implicated in OCD. Preselected GABAergic, glutamatergic and ion channel genes were analyzed via qPCR. Two genes required for GABA synthesis and release, GAD1 and SLC32A1, were found to be downregulated in OCD subjects across all nuclei, and potassium channel KCNN3 was upregulated. In parallel, we performed an exploratory total RNAseq differential expression analysis. We identified few (12 - 52) differentially expressed genes (DEGs) in each nucleus, and only one DEG in a pooled analysis of all nuclei. No DEGs were significant after correction for multiple comparisons. Investigation by model selection indicated that OCD diagnosis was not a useful factor in modelling gene expression in our dataset. OCD was also not associated with any modules of co-expressed genes identified using weighted gene correlation network analysis. Overall, we found minimal evidence of differential RNA expression in these thalamic nuclei in OCD. These findings contrast with our previous work including many of the same subjects where we found widespread differential mRNA expression in the orbitofrontal cortex and striatum in OCD.

neuroscience↗

bioRxiv2025

PACS1 syndrome variant alters proteomic landscape of developing cortical organoids

PACS1 syndrome is a neurodevelopmental disorder (NDD) resulting from a unique de novo p.R203W variant in Phosphofurin Acidic Cluster Sorting protein 1 (PACS1). PACS1 encodes a multifunctional sorting protein required for localizing furin to the trans-Golgi network. Although few studies have started to investigate the impact of the PACS1 p.R203W variant, the mechanisms by which the variant affects neurodevelopment are still poorly understood. In recent years, autism spectrum disorder (ASD) patient-derived brain organoids have been increasingly used to identify pathogenic mechanisms and possible therapeutic targets. While most of these studies evaluate the mechanisms by which ASD-risk genes affect the transcriptome, studies considering the proteome are limited. Here, we examine the effect of PACS1 p.R203W on the proteomic landscape of brain organoids using tandem mass tag (TMT) mass-spectrometry. Time series analysis between PACS1(+/+) and PACS1(+/R203W) organoids uncovered several proteins with dysregulated abundance or phosphorylation status, including known PACS1 interactors. Although we observed low overlap between proteins with altered expression and phosphorylation, the resulting dysregulated processes converged. The presence of the PACS1 p.R203W variant accelerated the emergence of proteins related to synaptogenesis and impaired vesicle loading and recycling. The earlier presence of these proteins and their related processes could lead to defective and/or incomplete synaptic function. Key dysregulated proteins observed in PACS1(+/R203W) organoids have been associated with several neurological diseases, and many are classified as NDD-causative and ASD-risk genes. Our results highlight that proteomic analyses not only enhance our understanding of general NDD mechanisms by complementing transcriptomic studies, but could also uncover additional targets, and therefore facilitate therapy development.

neuroscience↗

bioRxiv2024

Neuron Derived Cytokine Interleukin-34 Controls Developmental Microglia Function

Neuron-microglia interactions dictate the development of neuronal circuits in the brain. However, the factors that regulate these processes across development are largely unknown. Here, we find that IL34, a neuron-derived cytokine, is upregulated in early development and maintains neuroprotective, mature microglia in the anterior cingulate cortex (ACC) of mice. We show that IL34 is upregulated in the second week of postnatal life and is expressed primarily in excitatory neurons. Excitatory-neuron specific knock-out of IL34 reduced microglia number and TMEM119 expression and increased aberrant microglial phagocytosis of excitatory thalamocortical synapses in the ACC. Acute, low dose blocking of IL34 at postnatal day 15 similarly decreased TMEM119 and inappropriately increased microglial phagocytosis of synapses. Viral overexpression of IL34 induced TMEM119 expression and prevented appropriate microglial phagocytosis of synapses. These findings establish IL34 as a key regulator of neuron-microglia crosstalk in postnatal brain development, controlling both microglial maturation and synapse engulfment.

neuroscience↗

bioRxiv2023

Evaluating and Improving Health Equity and Fairness of Polygenic Scores

Polygenic scores (PGS) are quantitative metrics for predicting phenotypic values, such as human height or disease status. Some PGS methods require only summary statistics of a relevant genome-wide association study (GWAS) for their score. One such method is Lassosum, which inherits the model selection advantages of Lasso to select a meaningful subset of the GWAS single nucleotide polymorphisms as predictors from their association statistics. However, even efficient scores like Lassosum, when derived from European-based GWAS, are poor predictors of phenotype for subjects of non-European ancestry; that is, they have limited portability to other ancestries. To increase the portability of Lassosum, when GWAS information and estimates of linkage disequilibrium are available for both ancestries, we propose Joint-Lassosum. In the simulation settings we explore, Joint-Lassosum provides more accurate PGS compared with other methods, especially when measured in terms of fairness. Like all PGS methods, Joint-Lassosum requires selection of predictors, which are determined by data-driven tuning parameters. We describe a new approach to selecting tuning parameters and note its relevance for model selection for any PGS. We also draw connections to the literature on algorithmic fairness and discuss how Joint-Lassosum can help mitigate fairness-related harms that might result from the use of PGS scores in clinical settings. While no PGS method is likely to be universally portable, due to the diversity of human populations and unequal information content of GWAS for different ancestries, Joint-Lassosum is an effective approach for enhancing portability and reducing predictive bias.

genetics↗

bioRxiv2021

Expansion of RNA sequence diversity and RNA editing rates throughout human cortical development

Post-transcriptional modifications by RNA editing are essential for neurodevelopment, yet their developmental and regulatory features remain poorly resolved. We constructed a full temporal view of base-specific RNA editing in the developing human cortex, from early progenitors through fully mature cells found in the adult brain. Developmental regulation of RNA editing is characterized by an increase in editing rates for more than 10,000 selective editing sites, shifting between mid-fetal development and infancy, and a massive expansion of RNA hyper-editing sites that amass in the cortex through postnatal development into advanced age. These sites occur disproportionally in 3UTRs of essential neurodevelopmental genes. These profiles are preserved in non-human primate and murine models, illustrating evolutionary conserved regulation of RNA editing in mammalian cortical development. RNA editing levels are commonly genetically regulated (editing quantitative trait loci, edQTLs) consistently across development or predominantly during prenatal or postnatal periods. Both consistent and temporal-predominant edQTLs co-localize with risk loci associated with neurological traits and disorders, including attention deficit hyperactivity disorder, schizophrenia, and sleep disorders. These findings expand the repertoire of highly regulated RNA editing sites in the brain and provide insights of how epitranscriptional sequence diversity by RNA editing contributes to neurodevelopment.

developmental biology↗

bioRxiv2021

An approach to gene-based testing accounting for dependence of tests among nearby genes

In genome-wide association studies (GWAS), it has become commonplace to test millions of SNPs for phenotypic association. Gene-based testing can improve power to detect weak signal by reducing multiple testing and pooling signal strength. While such tests account for linkage disequilibrium (LD) structure of SNP alleles within each gene, current approaches do not capture LD of SNPs falling in different nearby genes, which can induce correlation of gene-based test statistics. We introduce an algorithm to account for this correlation. When a genes test statistic is independent of others, it is assessed separately; when test statistics for nearby genes are strongly correlated, their SNPs are agglomerated and tested as a locus. To provide insight into SNPs and genes driving association within loci, we develop an interactive visualization tool to explore localized signal. We demonstrate our approach in the context of weakly powered GWAS for autism spectrum disorder, which is contrasted to more highly powered GWAS for schizophrenia and educational attainment. To increase power for these analyses, especially those for autism, we use adaptive p-value thresholding (AdaPT), guided by high-dimensional metadata modeled with gradient boosted trees, highlighting when and how it can be most useful. Notably our workflow is based on summary statistics.

genetics↗

bioRxiv2020

De novo structural mutation rates and gamete-of-origin biases revealed through genome sequencing of 2,396 families

Each human genome includes de novo mutations that arose during gametogenesis. While these germline mutations represent a fundamental source of new genetic diversity, they can also create deleterious alleles that impact fitness. The germline mutation rate for single nucleotide variants and factors that significantly influence this rate, such as parental age, are now well established. However, far less is known about the frequency, distribution, and features that impact de novo structural mutations. We report a large, family-based study of germline mutations, excluding aneuploidy, that affect genome structure among 572 genomes from 33 families in a multigenerational CEPH-Utah cohort and 2,363 cases of non-familial autism spectrum disorder (ASD), 1,938 unaffected siblings, and both parents (9,599 genomes in total). We find that de novo structural mutations detected by alignment-based, short-read WGS occurred at an overall rate of at least 0.160 events per genome in unaffected individuals and was significantly higher (0.206 per genome) in ASD cases. In both probands and unaffected samples, nearly 73% of de novo structural mutations arose in paternal gametes, and predict most de novo structural mutations to be caused by mutational mechanisms that do not require sequence homology. After multiple testing correction we did not observe a statistically significant correlation between parental age and the rate of de novo structural variation in offspring. These results highlight that a spectrum of mutational mechanisms contribute to germline structural mutations, and that these mechanisms likely have markedly different rates and selective pressures than those leading to point mutations.

genomics↗

bioRxiv2020

Sex differences in the human brain transcriptome of cases with schizophrenia

While schizophrenia differs between males and females in age of onset, symptomatology and the course of the disease, the molecular mechanisms underlying these differences remain uncharacterized. In order to address questions about the sex-specific effects of schizophrenia, we performed a large-scale transcriptome analysis of RNA-seq data from 437 controls and 341 cases from two distinct cohorts from the CommonMind Consortium. Analysis across the cohorts identifies a reproducible gene expression signature of schizophrenia that is highly concordant with previous work. Differential expression across sex is reproducible across cohorts and identifies X- and Y-linked genes, as well as those involved in dosage compensation. Intriguingly, the sex expression signature is also enriched for genes involved in neurexin family protein binding and synaptic organization. Differential expression analysis testing a sex-by-diagnosis interaction effect did not identify any genome-wide signature after multiple testing corrections. Gene coexpression network analysis was performed to reduce dimensionality and elucidate interactions among genes. We found enrichment of co-expression modules for sex-by-diagnosis differential expression signatures, which were highly reproducible across the two cohorts and involve a number of diverse pathways, including neural nucleus development, neuron projection morphogenesis, and regulation of neural precursor cell proliferation. Overall, our results indicate that the effect size of sex differences in schizophrenia gene expression signatures is small and underscore the challenge of identifying robust sex-by-diagnosis signatures, which will require future analyses in larger cohorts.

genomics↗

bioRxiv2020

H-MAGMA, inheriting a shaky statistical foundation, yields excess false positives

The snp-wise mean model of Multi-marker Analysis of GenoMic Annotation is often used to perform gene-level testing for association with disease and other phenotypes. This methodology, in turn, forms the foundation for H-MAGMA. Unfortunately, that foundation is unsound, with implications for H-MAGMA results published in Nature Neuroscience regarding genes associated with psychiatric disorders: e.g., only 125 of H-MAGMAs 275 reported discoveries for autism replicate when the foundations flaws are corrected.

genetics↗