BaDoi Nguyen Phan

Age is the primary risk factor for neurodegenerative diseases, which are characterized by cell-type-specific vulnerability ¹ . Yet brain-aging mechanisms remain unclear given the complex, interacting age-associated pathways across diverse neural cell types. Here, we dissect cell type- cell state-specific aging gene regulatory programs and their contribution to cellular vulnerability by leveraging epigenomics, AI methodology, and natural lifespan diversity across placental mammals. Applying the TACIT method, we associated lifespans of 240 placental mammals to the predicted open chromatin levels of over 3 million orthologous loci across 18 cortical cell types. We identified thousands of lifespan-associated open chromatin regions, enriched near genes associated with hallmarks of aging, which stratified greatly by cell type. For example, regions near mitochondrial genes showed differential selective pressure in long-lived species in energetically-demanding layer V ET neurons, while regions near inflammatory response genes were under selective pressure in glial populations. We next asked whether regions linked to vulnerable or resilient neurons in the human brain were under differential selective pressure in longer lived species. Using an adaptive representation learning approach, we decompose intrinsic aging programs from systemic effects in the prefrontal cortex and define an aging signature predictive of cell-type-specific vulnerability. In Alzheimer’s disease, this intrinsic aging signature more strongly predicts vulnerability than systemic effects. Active regions in vulnerable neurons showed lower predicted activity in species with longer lifespans, suggesting selective pressure to down-regulate the vulnerability-associated networks. Overall, our findings argue against a single master regulator of aging, instead implicating different hallmarks across different cell types.

We previously demonstrated that male progeny of cocaine-experienced sires resisted cocaine, expressed as delayed acquisition of cocaine self-administration. Here, we sought to determine whether this phenotype extended to another psychostimulant, methamphetamine (meth). Sires self-administered meth or cocaine or received yoked-saline infusions for 60 days, after which they were mated to naïve females. Some behaviors previously altered in cocaine-sired male rats, including object memory and anxiety-like behavior, were not influenced by paternal meth taking. In contrast to cocaine resistance in cocaine-sired male rats, meth-sired male offspring demonstrated increased susceptibility to meth taking, with no effect in females. Single nuclei RNA- and ATAC-sequencing of the nucleus accumbens was used to identify molecular drivers of phenotypes in cocaine- and meth-sired offspring. Sequencing results revealed unique profiles of gene expression and open chromatin in offspring nucleus accumbens. Differential gene expression in cocaine-resistant, cocaine-sired offspring and meth-susceptible, meth-sired offspring illuminates potential novel treatment targets for psychostimulant use disorders.

Background/Objectives: Transcription factor 4 (TCF4) is a proneural basic helix–loop–helix transcription factor that plays a critical role in brain development and is associated with a variety of psychiatric disorders, including autism spectrum disorder (ASD), major depressive disorder, and schizophrenia. Autosomal dominant mutations in TCF4 result in a profound neurodevelopmental disorder called Pitt–Hopkins Syndrome (PTHS). Germline TCF4 loss-of-function (LOF) studies using human and mouse models have identified dysregulation in neural cell proliferation, genesis, and specification, which leads to disruption in neuronal, astroglial, and oligodendroglial lineages. In this study, we focused on the role of TCF4 in the genesis of the astrocyte lineage, specifically in the context of modeling PTHS. Methods: We investigated the expression of astrocyte marker genes in primary astrocyte cultures and whole-brain lysates, as well as assessed pan- and subclass-specific astrocyte markers, using immunohistochemical (IHC) analysis in a heterozygous mouse model of PTHS. Lastly, we tracked ventrally derived astrocytes using an Nkx2.1 reporter mouse to investigate misallocation of ventrally derived astrocytes into the dorsal cortex, a phenotype previously observed when both Tcf4 alleles were conditionally deleted in the Nkx2.1 lineage. Results: We show that germline heterozygous mutations in Tcf4 had no effect on the expression of astrocyte markers via qPCR or astrocyte cell density with IHC analysis. Germline heterozygous Tcf4 LOF also did not result in misallocation of ventrally derived astrocytes into the dorsal cortex. Conclusions: These data indicate that germline heterozygous TCF4 LOF, which models PTHS, does not appear to significantly affect the astrocyte lineage at the cell population level.

: Measures 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 Summary: Regulatory functions conserved across mammals underlying caudate cell type evolution reveal functions of human risk variants.

The opioid crisis has emphasized the need for more effective treatments for opioid use disorder (OUD) ^1–3 , which is characterized by habitual opioid use to avoid withdrawal symptoms ^4,5 . Both physical and affective symptoms contribute to opioid withdrawal yet whether different neural mechanisms mediate these different symptom domains and contribute distinctly to opioid relapse is unknown. While neurons expressing mu opioid receptors (MORs) gate opioids’ reinforcing effects ^6–8 by increasing dopamine (DA) release in nucleus accumbens (NAc), sharp decreases in NAc DA release are associated with withdrawal ^9–11 , the cellular and circuit mechanisms of which are unknown. Here we describe an unusual population of evolutionarily-conserved MOR+ neurons in the NAc expressing the transcription factor Tshz1 . Increased activity in these neurons is required for withdrawal aversion learning. Deletion of MORs in Tshz1 neurons prevented withdrawal-induced decreases in DA release and affective aversion, but not physical symptoms associated with withdrawal. Pharmacological activation of mGluR8, which is preferentially expressed in Tshz1 neurons, reduced withdrawal aversion. Thus, by dissociating the circuit mechanisms contributing to the physical and affective components of opioid withdrawal focusing on the critical role of Tshz1 neurons, we have identified a novel druggable target with therapeutic potential for treating key OUD withdrawal symptoms.

Opioid withdrawal is a common and distressing manifestation of opioid dependence which, if left untreated, frequently results in relapse, accidental overdose, and suicide. While much is known about the role of mesolimbic and mesocortical dopaminergic neurons in mu opioid receptor-mediated reward, much less is understood about the impact of chronic opioid use on parallel aversive pathways mediated by the kappa opioid receptor and its endogenous ligand dynorphin. In the present study, we interrogate kappa opioid receptor-expressing ventral tegmental area neurons and their dynorphinergic inputs in vitro and in vivo, to elucidate the circuit mechanisms by which chronic opioids promote withdrawal behaviors in mice. Through a combination of genetic, molecular, and custom machine learning analytical approaches, we uncovered the effects of chronic morphine on kappa opioid receptor mRNA expression in the ventral tegmental area as well as dynorphin mRNA expression in several retrogradely traced dynorphinergic input regions. We find that chronic morphine exposure diminishes opioid-induced c-Fos expression selectively in midbrain kappa opioid receptor-expressing neurons. In addition, chemogenetic activation of kappa opioid receptor-expressing ventral tegmental area neurons was sufficient to attenuate diverse opioid withdrawal-associated behaviors, negative affect, and gastrointestinal distress in mice. Finally, we uncovered a glutamatergic subpopulation of kappa opioid receptor-expressing ventral tegmental area neurons projecting to the ventrolateral periaqueductal gray which, when activated, selectively relieved opioid withdrawal-associated gastrointestinal distress. These discoveries highlight a critical role for midbrain kappa opioid receptor-expressing neurons and the downstream ventrolateral periaqueductal gray in opioid withdrawal-associated disruption of hedonic homeostasis and gastrointestinal regulation.

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.

Transcription factor 4 (TCF4) is a proneural basic helix-loop-helix transcription factor that plays a critical role in brain development and is associated with a variety of psychiatric disorders including autism spectrum disorder (ASD), major depressive disorder, and schizophrenia. Autosomal dominant mutations in TCF4 result in a profound neurodevelopmental disorder called Pitt-Hopkins Syndrome (PTHS). Germline TCF4 loss-of-function (LOF) studies using human and mouse models have identified dysregulation in neural cell proliferation, genesis, and specification which lead to disruption in neuronal, astroglial and oligodendroglial lineages. In this study, we focused on the role of TCF4 in the genesis of the astrocyte lineage, specifically in the context of modeling PTHS. We show that germline heterozygous mutations in Tcf4 had no effect on the expression of astrocyte marker genes in primary astrocyte cultures and whole brain lysates. Immunohistochemical (IHC) analysis of pan- and subclass-specific astrocyte markers showed Tcf4 mutation had no effect on the proportions of astrocytes in the dorsal cortex and corpus callosum. Lastly, we tracked ventrally-derived astrocytes using an Nkx2.1 reporter mouse and observed that germline Tcf4 LOF did not result in misallocation of ventrally-derived astrocytes into the dorsal cortex, a phenotype previously observed when both Tcf4 alleles were conditionally deleted in the Nkx2.1 lineage. These data indicate that germline heterozygous TCF4 LOF, which models PTHS, does not appear to affect the astrocyte lineage at the cell population level.

Noncoding genetic variants underlie many complex diseases, yet identifying and interpreting their functional impacts remains challenging. Late-onset Alzheimer’s 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 that are hypothesized to influence neurodevelopment and synaptic plasticity. These variants often perturb regulatory sequences by disrupting transcription factor (TF) motifs or altering local TF interactions, thereby reshaping 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 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 regulatory function depending on cell-type and cell-state contexts. Common variants associated with LOAD tended to exert stronger effects in immune contexts, whereas rare variants showed more pronounced impacts in brain contexts. Interpretable sequence-to-function deep-learning models elucidated how genetic variation leads to cell-type-specific differences in regulatory activity, pinpointing both direct transcription-factor motif disruptions and subtler tuning of motif context. To probe the broader functional consequences of a locus prioritized by our reporter assays and models, we used CRISPR interference to silence an enhancer within the SEC63-OSTM1 locus that harbors four functional rare variants, revealing its gatekeeper role in inflammation and amyloidogenesis. These findings underscore the context-dependent nature of noncoding variant effects in LOAD and provide a generalizable framework for the mechanistic interpretation of risk alleles in complex diseases.

Summary: 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.