Biology subjects

Brown, A. R.

Publications and source records attributed to Brown, A. R..

18 recordsLinked to original sources

bioRxiv2026

Glutamatergic and Redox Abnormalities in Major Depressive Disorder: Links to Childhood Maltreatment and Perceived Stress

Background: Childhood sexual abuse (CSA) increases the risk for major depressive disorder (MDD), yet the underlying neurobiological mechanisms remain poorly understood. We examined (1) associations of medial prefrontal cortex (mPFC) glutamatergic metabolites and redox balance with childhood maltreatment and MDD; and (2) whether these neurochemical measures predicted future perceived stress. Methods: Using proton and phosphorus 4T magnetic resonance spectroscopy, we quantified glutamate, glutamine, their sum (Glx), and the NAD/NADH ratio within the same mPFC voxel in 71 women across four groups: healthy controls (HC; n=27), current MDD without CSA (n=14), current MDD with CSA (n=14), and remitted MDD with CSA (n=16). Results: Glutamate and Glx levels were lower in both CSA-exposed groups (n=30) compared with HC (n=27), whereas women with MDD without CSA did not differ significantly from HC. Among CSA-exposed women, greater maltreatment severity was associated with lower glutamine, and greater maltreatment multiplicity with lower glutamate and Glx, specifically in women with current MDD. The association between depressive symptom severity and glutamine differed by CSA history. A significant interaction between baseline NAD/NADH ratio and clinical group predicted perceived stress at 6-month follow-up, adjusting for baseline perceived stress. Specifically, lower baseline NAD/NADH ratio predicted greater subsequent perceived stress in MDD without CSA, but not in the other clinical groups. Conclusions: Our findings suggest that mPFC glutamatergic metabolites and redox balance show distinct patterns of association with CSA history, depression status, and subsequent perceived stress, highlighting neurochemical heterogeneity in MDD and molecular markers of risk.

neuroscience↗

bioRxiv2026

Fine-mapping candidate neuropsychiatric regulatory variants using cell type-aware comparative genomics

AbstractMeasures of nucleotide sequence conservation across species are useful for identifying functional genomic loci, but can fail when regulatory function is maintained, often in a cell type-specific manner, even when sequence is not. We introduce CTACIT, the Cell Type-Aware Conservation Inference Toolkit, to identify trait-associated regulatory variants. CTACIT integrates sequence conservation scores with cell type-specific open chromatin data collected from a few mammalian species to impute function for hundreds more. Applying CTACIT to neuropsychiatric trait loci identifies higher heritability enrichment and more fine-mapped variants than nucleotide conservation and human chromatin data alone. Our in vivo reporter assays validate predictions for enhancers with risk variants near the DRD2 schizophrenia risk locus. By integrating genome conservation and multi-species open chromatin data, CTACIT prioritizes variants within regions of conserved regulatory function for in vivo characterization and addresses a major challenge in translating disease associations to mechanistic understanding. One-Sentence SummaryRegulatory functions conserved across mammals underlying caudate cell type evolution reveal functions of human risk variants.

genomics↗

bioRxiv2026

Biased signaling at NTSR1 differentially regulates inhibitory synaptic transmission in the extended amygdala and suppresses motivated feeding in mice

Maladaptive consummatory behaviors can arise from dysregulated circuits, like those in the extended amygdala, governing motivation and feeding behaviors. Neurotensin (NTS), expressed throughout the central, peripheral, and enteric nervous systems, has well-established roles in energy balance and feeding. SBI-553, a biased allosteric modulator of NTSR1, recruits {beta}-arrestin while attenuating Gq-mediated signaling. We used SBI-553 to examine NTS modulation GABAergic signaling in the central amygdala (CeA) and bed nucleus of the stria terminalis (BNST) and probed its effects on food consumption in mice. We found that NTS and SBI-553 differentially modulate GABAergic neurotransmission across extended amygdala subregions. In vivo, SBI-553 reduces palatable food consumption in both fed and food-deprived mice, with greater reductions under fasted conditions, altering activation across CeA subregions in a sex- and feeding-state-dependent manner. In the BNST, differences in SBI-553 altered cFos activity were observed between feeding states. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=157 SRC="FIGDIR/small/722083v3_ufig1.gif" ALT="Figure 1"> View larger version (48K): org.highwire.dtl.DTLVardef@1825c16org.highwire.dtl.DTLVardef@16be6acorg.highwire.dtl.DTLVardef@f5561eorg.highwire.dtl.DTLVardef@e8f82c_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LINTS enhances GABAergic transmission in the CeAL and the ovBNST C_LIO_LISBI-553 blocks NTS-induced increases in sIPSC frequency in the CeAL but not in the ovBNST C_LIO_LISBI-553 attenuates the feeding of a palatable high-carbohydrate food C_LIO_LIThe effect of SBI-553 on feeding is driven by energy deficit/motivation to feed C_LI

neuroscience↗

bioRxiv2026

A Large Animal Model of Heritable Pulmonary Arterial Hypertension UsingGene-edited BMPR2 Sheep

Pulmonary Arterial Hypertension (PAH) is a rare vascular disorder characterized by elevated pressure in pulmonary arteries, eventually leading to right ventricular failure. Approximately 50% of pediatric disease and 20% of adult disease can be linked to a genetic mutation, with nearly 70% of these cases involving mutations in the bone morphogenetic protein receptor type 2 (BMPR2) locus. Investigations using rodent models have made significant advances in our understanding of BMPR2 signaling; however, limited data exist regarding the onset and course of PAH, and etiologies for phenotypic expression in these patients remain unknown. In this work, we describe the development of a novel ovine model of heritable PAH. Because homozygous disruption of BMPR2 is embryonic lethal, we developed heterozygous BMPR2 sheep by using a PAM-disrupting synonymous single stranded oligodeoxyribonucleotide alongside a single guide RNA and Cas9 mediated gene editing strategy. The resulting BMPR2(+/-) lambs demonstrated cardiac and pulmonary vascular pathology that are consistent with BMPR2 mutation-driven PAH observed in humans. Given the genetic and physiological similarities of BMPR2(+/-)sheep to humans with heritable PAH, this large animal model will serve as a vital platform for mechanistic molecular studies and will provide a much-needed pre-clinical model for extensive treatment evaluations.

molecular biology↗

bioRxiv2025

Challenges in predicting chromatin accessibility differences between species

Enhancers are transcriptional regulatory elements that help drive phenotypic diversity, yet they often undergo rapid sequence evolution despite functional conservation, posing a challenge for predicting their function across species. Machine learning models that predict quantitative enhancer activity using DNA sequence have not previously been evaluated for their ability to predict quantitative differences across orthologous regions. Here, we trained convolutional neural networks (CNNs) on a regression task to predict chromatin accessibility, which is a proxy for enhancer activity, in the liver across five mammals, and we developed a novel framework to evaluate cross-species performance. We demonstrated that training on multiple species improves model generalization to both species used in training and held-out species. However, the models consistently achieved poor performance in predicting quantitative differences in accessibility between species at orthologous regions. Our study highlights the challenges in using regression models to predict chromatin accessibility changes between species.

genomics↗

bioRxiv2025

A molecular and spinal circuit basis for the functional segregation of itch and pain

Recent advances reveal an extensive cellular diversity within the dorsal horn. How this complexity processes distinct sensations, like itch and pain, remains a fundamental question. We discovered hidden within a population of neurons expressing the gastrin-releasing peptide receptor (Grpr+), thought to be itch-specific, are highly homologous yet functionally distinct subtypes distinguished by expression of Tachykinin-1 (Tac1). While the Tac1- subtype mediates itch, the Tac1+ subtype mediates mechanical allodynia across diverse pain states. Inhibitory populations and differential sensitivities to GRP serve as key modulators of the Grpr+ neuron subtypes, shaping modality specific output. Leveraging computationally designed genomic enhancers to silence the Tac1- population reverses itch while silencing the Tac1+ subtype reverses mechanical allodynia broadly. The work demonstrates the nuance of differential sensory modality coding within the dorsal horn and the power of genomic enhancer-based strategies for modality-specific targeting.

neuroscience↗

bioRxiv2025

Context-dependent regulatory variants in Alzheimer's disease

Noncoding genetic variants underlie many complex diseases, yet identifying and interpreting their functional impacts remains challenging. Late-onset Alzheimers disease (LOAD), a polygenic neurodegenerative disorder, exemplifies this challenge. The disease is strongly associated with noncoding variation, including common variants enriched in microglial enhancers and rare variants nominated at loci implicated in neurodevelopment and synaptic function. These variants may perturb regulatory sequences by disrupting transcription factor (TF) motifs or altering local regulatory sequence context, with potential consequences for gene expression and chromatin accessibility. However, assessing their impact is complicated by the context-dependent functions of regulatory sequences, underscoring the need to systematically examine variant effects across diverse tissues, cell types, and cellular states. Here, we combined in vitro and in vivo massively parallel reporter assays (MPRAs) with interpretable machine-learning models to systematically characterize common and rare variants across myeloid and neuron-enriched neural contexts. Parallel profiling of variants in four immune states in vitro and three mouse brain regions in vivo revealed that individual variants can differentially and even oppositely modulate reporter activity across cellular contexts, while a subset showed immune-state-dependent effects. Within the assayed candidate set, the relative effect sizes of common and rare variants reversed between contexts, with common variants showing larger effects in THP-1 macrophages and rare variants in brain tissue. Interpretable sequence-to-function models prioritized context-biased variants and generated motif-level hypotheses, including predicted transcription-factor motif disruption and subtler changes in local motif context. To probe endogenous consequences at a prioritized locus, we used CRISPR interference to perturb a rare-variant-containing enhancer at the SEC63-OSTM1 locus, revealing metabolic and biosynthetic transcriptional programs resembling those induced by SEC63 promoter perturbation, together with a stimulation-specific interferon response. These findings show that LOAD-associated noncoding variants exhibit context-dependent effects on reporter activity and predicted chromatin accessibility, and provide a framework for linking genetic association to regulatory activity, sequence grammar and endogenous transcriptional state.

genomics↗

bioRxiv2025

Combining Machine Learning and Multiplexed, In Situ Profiling to Engineer Cell Type and Behavioral Specificity

A promising strategy for the precise control of neural circuits is to use cis-regulatory enhancers to drive transgene expression in specific cells. However, enhancer discovery faces key challenges: low in vivo success rates, species-specific differences in activity, challenges with multiplexing adeno-associated viruses (AAVs), and the lack of spatial detail from single-cell sequencing. In order to accelerate enhancer discovery for the dorsal spinal cord--a region critical for pain and itch processing--we developed an end-to-end platform, ESCargoT (Engineered Specificity of Cargo Transcription), combining machine learning (ML)-guided enhancer prioritization, modular AAV assembly, and multiplexed, in situ screening. Using cross-species chromatin accessibility data, we trained ML models to predict enhancer activity in oligodendrocytes and in 15 dorsal horn neuronal subtypes. We first demonstrated that an initial enhancer, Excit-1, targeted excitatory dorsal horn neurons and drove reversal of mechanical allodynia in an inflammatory pain model. To enable parallel profiling of a 27-enhancer-AAV library delivered intraspinally in mice, we developed a Spatial Parallel Reporter Assay (SPRA) by integrating a novel Golden-Gate assembly pipeline with multiplexed, in situ screening. Regression adjustment for spatial confounding enabled specificity comparisons between enhancers, demonstrating the ability to screen enhancers targeting diverse cell types (oligodendrocytes, motoneurons, dorsal neuron subtypes) in one experiment. We then validated two candidates, targeting Exc-LMO3 and Exc-SKOR2 neurons, respectively. In a companion paper by Noh et al, our colleagues show that the functional specificity of the Exc-SKOR2-targeting enhancer, unlike Excit-1, is capable of blocking the sensation of chemical itch in mice. These enhancers were derived from the macaque genome but displayed functional sensitivity in mice. This platform enables spatially resolved, multiplexed in vivo enhancer profiling to accelerate discovery of cell-targeting tools and gene therapy development.

neuroscience↗

bioRxiv2025

Xylazine and fentanyl co-administration delays wound healing in mice

Xylazine, a veterinary sedative increasingly found in the unregulated drug supply, is associated with severe skin wounds in humans, particularly when co-used with fentanyl. Despite growing concern, the mechanisms underlying these wounds remain unclear. To investigate how xylazine and fentanyl affect wound healing, we administered subcutaneous injections of saline, xylazine (3.2 mg/kg), fentanyl (1.0 mg/kg), or their combination to female C57BL/6J mice for 28 days. After a standardized punch biopsy, wound closure was tracked for 14 days, with continued drug exposure. Mice receiving the xylazine-fentanyl combination exhibited significantly delayed wound healing compared to all other groups, as shown by slower closure rates and increased area under the healing curve. A follow-up study without chronic pretreatment showed that acute xylazine-fentanyl exposure still altered healing dynamics, although it did not significantly delay time to closure. Neither drug alone impaired healing at the tested doses. These findings suggest that prior exposure to xylazine and fentanyl contributes to impaired wound healing and support the hypothesis that xylazine-associated wounds may arise from delayed healing of pre-existing skin injuries rather than spontaneous formation. This is the first preclinical model of xylazine-related wound impairment and provides a foundation for future research into biological mechanisms and potential interventions for these emerging soft tissue injuries.

pharmacology and toxicology↗

bioRxiv2023

Evolutionary constraint and innovation across hundreds of placental mammals

Evolutionary constraint and acceleration are powerful, cell-type agnostic measures of functional importance. Previous studies in mammals were limited by species number and reliance on human-referenced alignments. We explore the evolution of placental mammals, including humans, through reference-free whole-genome alignment of 240 species and protein-coding alignments for 428 species. We estimate 10.7% of the human genome is evolutionarily constrained. We resolve constraint to single nucleotides, pinpointing functional positions, and refine and expand by over seven-fold the catalog of ultraconserved elements. Overall, 48.5% of constrained bases are as yet unannotated, suggesting yet-to-be-discovered functional importance. Using species-level phenotypes and an updated phylogeny, we associate coding and regulatory variation with olfaction and hibernation. Focusing on biodiversity conservation, we identify genomic metrics that predict species at risk of extinction.

genomics↗

bioRxiv2022

An in vivo massively parallel platform for deciphering tissue-specific regulatory function

Genetic studies are rapidly identifying non-protein-coding human disease-associated loci. Understanding the regulatory mechanisms underlying these loci remains a challenge because the causal variants and the tissues in which they act are often unclear. Massively parallel reporter assays (MPRAs) have the potential to link differences in genome sequence, including genetic variants, to tissue-specific regulatory function. Although MPRA and similar technologies have been widely adopted in cell culture, there have been several barriers to widespread use in animals. We overcome these challenges with a new whole-animal MPRA (WhAMPRA), where systemic intravenous AAV effectively transduces the plasmid MPRA library to mouse tissues. Our WhAMPRA approach revealed models of tissue-specific regulation that generally match machine learning model predictions. In addition, we measured the regulatory effects of disrupting MEF2C transcription factor binding sites and impacts of late onset Alzheimers disease-associated genetic variations. Overall, our WhAMPRA technology simultaneously determines the transcriptional functions of hundreds of enhancers in vivo across multiple tissues.

genomics↗

bioRxiv2022

Relating enhancer genetic variation across mammals to complex phenotypes using machine learning

Protein-coding differences between mammals often fail to explain phenotypic diversity, suggesting involvement of enhancers, often rapidly evolving regions that regulate gene expression. Identifying associations between enhancers and phenotypes is challenging because enhancer activity is context-dependent and may be conserved without much sequence conservation. We developed TACIT (Tissue-Aware Conservation Inference Toolkit) to associate open chromatin regions (OCRs) with phenotypes using predictions in hundreds of mammalian genomes from machine learning models trained to learn tissue-specific regulatory codes. Applying TACIT for motor cortex and parvalbumin-positive interneurons to neurological phenotypes revealed dozens of new OCR-phenotype associations. Many associated OCRs were near relevant genes, including brain size-associated OCRs near genes mutated in microcephaly or macrocephaly. Our work creates a forward genomics foundation for identifying candidate enhancers associated with phenotype evolution. One Sentence SummaryA new machine learning-based approach associates enhancers with the evolution of brain size and behavior across mammals.

genomics↗

bioRxiv2021

A community-science approach identifies genetic variants associated with three color morphs in ball pythons (Python regius)

Color morphs in ball pythons (Python regius) provide a unique and largely untapped resource for understanding the genetics of coloration in reptiles. Here we use a community-science approach to investigate the genetics of three color morphs affecting production of the pigment melanin. These morphs--Albino, Lavender Albino, and Ultramel--show a loss of melanin in the skin and eyes, ranging from severe (Albino) to moderate (Lavender Albino) to mild (Ultramel). To identify genetic variants causing each morph, we recruited shed skins of pet ball pythons via social media, extracted DNA from the skins, and searched for putative loss-of-function variants in homologs of genes controlling melanin production in other vertebrates. We report that the Albino morph is associated with missense and non-coding variants in the gene TYR. The Lavender Albino morph is associated with a deletion in the gene OCA2. The Ultramel morph is associated with a missense variant and a putative deletion in the gene TYRP1. Our study is one of the first to identify genetic variants associated with color morphs in ball pythons and shows that pet samples recruited from the community can provide a resource for genetic studies in this species.

genetics↗

bioRxiv2021

Machine learning sequence prioritization for cell type-specific enhancer design

Recent discoveries of extreme cellular diversity in the brain warrant rapid development of technologies to access specific cell populations, enabling characterization of their roles in behavior and in disease states. Available approaches for engineering targeted technologies for new neuron subtypes are low-yield, involving intensive transgenic strain or virus screening. Here, we introduce SNAIL (Specific Nuclear-Anchored Independent Labeling), a new virus-based strategy for cell labeling and nuclear isolation from heterogeneous tissue. SNAIL works by leveraging machine learning and other computational approaches to identify DNA sequence features that confer cell type-specific gene activation and using them to make a probe that drives an affinity purification-compatible reporter gene. As a proof of concept, we designed and validated two novel SNAIL probes that target parvalbumin-expressing (PV) neurons. Furthermore, we show that nuclear isolation using SNAIL in wild type mice is sufficient to capture characteristic open chromatin features of PV neurons in the cortex, striatum, and external globus pallidus. Expansion of this technology has broad applications in cell type-specific observation, manipulation, and therapeutics across species and disease models.

genomics↗

bioRxiv2020

A Quantitative Measurement to Describe the Relative Proximity of Fluorescent Biomarkers

Determining the relationship between biomarkers via fluorescence microscopy is a key step in the characterisation of cellular phenotypes. We define a simple distance-based measurement termed a perimeter distance mean (PDmean) which quantifies the relative proximity of objects in one fluorescent channel to objects in a second fluorescent channel in 2D or 3D microscopy datasets. PDmean measurements were able to accurately identify known changes in colocalisation in computer-generated and real-world microscopy datasets. We argue that this approach provides substantial advantages over currently used distance-based colocalisation analysis methods. We also introduce PyBioProx, an extensible open-source Python module and graphical user interface that produces PDmean measurements.

bioinformatics↗

bioRxiv2020

Predicting lineage-specific differences in open chromatin across dozens of mammalian genomes

BackgroundEvolutionary conservation is an invaluable tool for inferring functional significance in the genome, including regions that are crucial across many species and those that have undergone convergent evolution. Computational methods to test for sequence conservation are dominated by algorithms that examine the ability of one or more nucleotides to align across large evolutionary distances. While these nucleotide alignment-based approaches have proven powerful for protein-coding genes and some non-coding elements, they fail to capture conservation at many enhancers, distal regulatory elements that control spatio-temporal patterns of gene expression. The function of enhancers is governed by a complex, often tissue- and cell type-specific, code that links combinations of transcription factor binding sites and other regulation-related sequence patterns to regulatory activity. Thus, function of orthologous enhancer regions can be conserved across large evolutionary distances, even when nucleotide turnover is high. ResultsWe present a new machine learning-based approach for evaluating enhancer conservation that leverages the combinatorial sequence code of enhancer activity rather than relying on the alignment of individual nucleotides. We first train a convolutional neural network model that is able to predict tissue-specific open chromatin, a proxy for enhancer activity, across mammals. Then, we apply that model to distinguish instances where the genome sequence would predict conserved function versus a loss regulatory activity in that tissue. We present criteria for systematically evaluating model performance for this task and use them to demonstrate that our models accurately predict tissue-specific conservation and divergence in open chromatin between primate and rodent species, vastly out-performing leading nucleotide alignment-based approaches. We then apply our models to predict open chromatin at orthologs of brain and liver open chromatin regions across hundreds of mammals and find that brain enhancers associated with neuron activity and liver enhancers associated with liver regeneration have a stronger tendency than the general population to have predicted lineage-specific open chromatin. ConclusionThe framework presented here provides a mechanism to annotate tissue-specific regulatory function across hundreds of genomes and to study enhancer evolution using predicted regulatory differences rather than nucleotide-level conservation measurements.

genetics↗

bioRxiv2020

The Regulatory Evolution of the Primate Fine-Motor System

In mammals, fine motor control is essential for skilled behavior, and is subserved by specialized subdivisions of the primary motor cortex (M1) and other components of the brains motor circuitry. We profiled the epigenomic state of several components of the Rhesus macaque motor system, including subdivisions of M1 corresponding to hand and orofacial control. We compared this to open chromatin data from M1 in rat, mouse, and human. We found broad similarities as well as unique specializations in open chromatin regions (OCRs) between M1 subdivisions and other brain regions, as well as species- and lineage-specific differences reflecting their evolutionary histories. By distinguishing shared mammalian M1 OCRs from primate- and human-specific specializations, we highlight gene regulatory programs that could subserve the evolution of skilled motor behaviors such as speech and tool use.

neuroscience↗

bioRxiv2020

Addiction-associated genetic variants implicate brain cell type- and region-specific cis-regulatory elements in addiction neurobiology

Recent large genome-wide association studies (GWAS) have identified multiple confident risk loci linked to addiction-associated behavioral traits. Genetic variants linked to addiction-associated traits lie largely in non-coding regions of the genome, likely disrupting cis-regulatory element (CRE) function. CREs tend to be highly cell type-specific and may contribute to the functional development of the neural circuits underlying addiction. Yet, a systematic approach for predicting the impact of risk variants on the CREs of specific cell populations is lacking. To dissect the cell types and brain regions underlying addiction-associated traits, we applied LD score regression to compare GWAS to genomic regions collected from human and mouse assays for open chromatin, which is associated with CRE activity. We found enrichment of addiction-associated variants in putative CREs marked by open chromatin in neuronal (NeuN+) nuclei collected from multiple prefrontal cortical areas and striatal regions known to play major roles in reward and addiction. To further dissect the cell type-specific basis of addiction-associated traits, we also identified enrichments in human orthologs of open chromatin regions of mouse neuronal subtypes: cortical excitatory, D1, D2, and PV. Lastly, we developed machine learning models from mouse cell type-specific regions of open chromatin to further dissect human NeuN+ open chromatin regions into cortical excitatory or striatal D1 and D2 neurons and predict the functional impact of addiction-associated genetic variants. Our results suggest that different neuronal subtypes within the reward system play distinct roles in the variety of traits that contribute to addiction. Significance StatementWe combine statistical genetic and machine learning techniques to find that the predisposition to for nicotine, alcohol, and cannabis use behaviors can be partially explained by genetic variants in conserved regulatory elements within specific brain regions and neuronal subtypes of the reward system. This computational framework can flexibly integrate open chromatin data across species to screen for putative causal variants in a cell type-and tissue-specific manner across numerous complex traits.

genomics↗