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Opioid craving and the vulnerability to relapse is associated with severe and persistent disruptions to sleep and circadian rhythms. Investigations into the cellular and molecular pathways in the human brain underlying the relationship between circadian rhythms and OUD remain limited. In human subjects with OUD, previous transcriptomics work implicated a role for circadian regulation of synaptic processes in key cognitive- and reward-related brain regions, dorsolateral prefrontal cortex (DLPFC) and nucleus accumbens (NAc). To provide further insights into the synaptic alterations associated with OUD, we used mass-spectrometry based proteomics to deeply profile protein alterations in tissue homogenates and synaptosomes from both NAc and DLPFC of unaffected and OUD subjects. Between unaffected and OUD subjects, we identified 43 differentially expressed (DE) proteins in NAc homogenates and 55 DE proteins in DLPFC homogenates. In synaptosomes, we found 56 DE proteins in NAc of OUD subjects and 161 DE proteins in DLPFC. Examining synaptosome enrichment of specific proteins enabled us to identify brain region- and synapse-specific pathway alterations in NAc and DLPFC associated with OUD. Across both regions, we found OUD-associated protein alterations primarily in pathways involved in GABAergic and glutamatergic synaptic functions, as well as circadian rhythms. Using time-of-death (TOD) analyses, where the TOD of each subject is used as a time-point across a 24-hour cycle, we were able to map circadian-related changes in the synaptic proteomes in NAc and DLPFC associated with OUD. In OUD, TOD analysis revealed significant circadian changes in endoplasmic reticulum to Golgi vesicle-mediated transport and protein membrane trafficking in NAc synapses, accompanied by changes in platelet derived growth factor receptor beta signaling in DLPFC synapses. Together, our results lend further support for molecular disruption of circadian regulation of synaptic signaling in the human brain as a key factor in opioid addiction.

Substance use disorders (SUDs) are associated with disruptions in sleep and circadian rhythms that persist during abstinence and may contribute to relapse risk. Repeated use of substances such as psychostimulants and opioids may lead to significant alterations in molecular rhythms in the nucleus accumbens (NAc), a brain region central to reward and motivation. Previous studies have identified rhythm alterations in the transcriptome of the NAc and other brain regions following the administration of psychostimulants or opioids. However, little is known about the impact of substance use on the diurnal rhythms of the proteome in the NAc. We used liquid chromatography coupled to tandem mass spectrometry-based (LC-MS/MS) quantitative proteomics, along with a data-independent acquisition (DIA) analysis pipeline, to investigate the effects of cocaine or morphine administration on diurnal rhythms of proteome in the mouse NAc. Overall, our data reveals cocaine and morphine differentially alters diurnal rhythms of the proteome in the NAc, with largely independent differentially expressed proteins dependent on time-of-day. Pathways enriched from cocaine altered protein rhythms were primarily associated with glucocorticoid signaling and metabolism, whereas morphine was associated with neuroinflammation. Collectively, these findings are the first to characterize the diurnal regulation of the NAc proteome and demonstrate a novel relationship between phase-dependent regulation of protein expression and the differential effects of cocaine and morphine on the NAc proteome.

Background Diurnal rhythms in gene expression have been detected in the human brain. Previous studies found that males and females exhibit 24-hour rhythms in known circadian genes, with earlier peak expression in females. Whether there are sex differences in large-scale transcriptional rhythms in the cortex that align with observed sex differences in physiological and behavioral rhythms is currently unknown. Methods Diurnal rhythmicity of gene expression was determined for males and females using RNA sequencing data from human postmortem dorsolateral prefrontal cortex (DLPFC) and anterior cingulate cortex (ACC). Sex differences among rhythmic genes were determined using significance cutoffs, threshold-free analyses, and R2 difference. Phase concordance was assessed across the DLPFC and ACC for males and females. Pathway and transcription factor analyses were also conducted on significantly rhythmic genes. Results Canonical circadian genes had diurnal rhythms in both sexes with similar amplitude and phase. When analyses were expanded to the entire transcriptome, significant sex differences in transcriptional rhythms emerged. There were nearly twice as many rhythmic transcripts in the DLPFC in males and nearly 4 times as many rhythmic transcripts in the ACC in females. Results suggest a diurnal rhythm in synaptic transmission specific to the ACC in females (e.g., GABAergic [gamma-aminobutyric acidergic] and cholinergic neurotransmission). For males, there was phase concordance between the DLPFC and ACC, while phase asynchrony was found in females. Conclusions There are robust sex differences in molecular rhythms of genes in the DLPFC and ACC, providing potential mechanistic insights into how neurotransmission and synaptic function are modulated in a circadian-dependent and sex-specific manner.

Summary Circadian oscillations of gene expression regulate daily physiological processes, and their disruption is linked to many diseases. Circadian rhythms can be disrupted in a variety of ways, including differential phase, amplitude and rhythm fitness. Although many differential circadian biomarker detection methods have been proposed, a workflow for systematic detection of multifaceted differential circadian characteristics with accurate false positive control is not currently available. We propose a comprehensive and interactive pipeline to capture the multifaceted characteristics of differentially rhythmic biomarkers. Analysis outputs are accompanied by informative visualization and interactive exploration. The workflow is demonstrated in multiple case studies and is extensible to general omics applications. Availability and implementation R package, Shiny app and source code are available in GitHub (https://github.com/DiffCircaPipeline) and Zenodo (https://doi.org/10.5281/zenodo.7507989) Supplementary information Supplementary data are available at Bioinformatics online.

Dopaminergic agonism effectively treats dysglycemia, with dopaminergic agonist bromocriptine approved as a type 2 diabetes therapy. Though bromocriptine’s actions have been mainly attributed to stimulation of dopamine D2 receptors (D2R) in the brain, we previously showed that bromocriptine also targets metabolically-relevant peripheral tissues including the endocrine pancreas. Here, we employ bromocriptine as a tool to elucidate roles of dopaminergic and adrenergic signaling in regulation of pancreatic hormone secretion. Using bromocriptine, we demonstrate a new mechanism for metabolic actions in pancreatic α-cells and β-cells via D2R and adrenergic α2A receptor (α2A-AR) signaling. In β-cells, bromocriptine acts jointly on D2R and α2A-AR to reduce glucose-stimulated insulin secretion (GSIS) , while in α-cells, bromocriptine acts via D2R to reduce glucagon secretion. Bromocriptine reduces cAMP in β-cells via concurrent actions on D2R and α2A-AR, further emphasizing shared roles of adrenergic and dopaminergic receptor agonism in GSIS regulation. At the receptor level, α2A-AR activation by bromocriptine leads to receptor recruitment of an ensemble of G proteins driven mainly via G protein signaling with no β-arrestin2 recruitment. In contrast, D2R recruits both G proteins and β-arrestin2 upon bromocriptine stimulation, demonstrating signaling unique to each receptor. Docking studies also reveal that bromocriptine binding to α2A-AR is distinct from bromocriptine-bound D2R, providing a structural basis for bromocriptine’s dual actions on β-cell α2A-AR and D2R. Together, joint dopaminergic and adrenergic receptor actions on α-cell and β-cell hormone release provide a new therapeutic mechanism to improve dysglycemia in diabetes. Disclosure S. Bertera: None. L. Friggeri: None. R. Logan: None. R. Free: None. R. Bottino: Employee; Imagine Pharma. Funding Department of Defense (PR141292) , National Institutes of Health (R01DK124219, R01DK097160, RDA046138) , the John F. and Nancy A. Emmerling Fund of The Pittsburgh Foundation, Intramural Research Program of the National Institute of Neurological Disorders and Stroke (ZIA-NS002263) , Veterans Affairs VA-ORD-BLR&D (I01BX002678) , the Deutsche Forschungsgemeinschaft (SFB1423, project number 421152132) .

Valproate (VPA) has been used in the treatment of bipolar disorder since the 1990s. However, the therapeutic targets of VPA have remained elusive. Here we employ a preclinical model to identify the therapeutic targets of VPA. We find compounds that inhibit histone deacetylase proteins (HDACs) are effective in normalizing manic-like behavior, and that class I HDACs (e.g., HDAC1 and HDAC2) are most important in this response. Using an RNAi approach, we find that HDAC2, but not HDAC1, inhibition in the ventral tegmental area (VTA) is sufficient to normalize behavior. Furthermore, HDAC2 overexpression in the VTA prevents the actions of VPA. We used RNA sequencing in both mice and human induced pluripotent stem cells (iPSCs) derived from bipolar patients to further identify important molecular targets. Together, these studies identify HDAC2 and downstream targets for the development of novel therapeutics for bipolar mania.

Severe and persistent disruptions to sleep and circadian rhythms are common in people with opioid use disorder (OUD). Preclinical evidence suggests altered molecular rhythms in the brain modulate opioid reward and relapse. However, whether molecular rhythms are disrupted in the brains of people with OUD remained an open question, critical to understanding the role of circadian rhythms in opioid addiction. Using subjects' times of death as a marker of time of day, we investigated transcriptional rhythms in the brains of subjects with OUD compared to unaffected comparison subjects. We discovered rhythmic transcripts in both the dorsolateral prefrontal cortex (DLPFC) and nucleus accumbens (NAc), key brain areas involved in OUD, that were largely distinct between OUD and unaffected subjects. Fewer rhythmic transcripts were identified in DLPFC of subjects with OUD compared to unaffected subjects, whereas in the NAc, nearly double the number of rhythmic transcripts was identified in subjects with OUD. In NAc of subjects with OUD, rhythmic transcripts peaked either in the evening or near sunrise, and were associated with an opioid, dopamine, and GABAergic neurotransmission. Associations with altered neurotransmission in NAc were further supported by co-expression network analysis which identified OUD-specific modules enriched for transcripts involved in dopamine, GABA, and glutamatergic synaptic functions. Additionally, rhythmic transcripts in DLPFC and NAc of subjects with OUD were enriched for genomic loci associated with sleep-related GWAS traits, including sleep duration and insomnia. Collectively, our findings connect transcriptional rhythm changes in opioidergic, dopaminergic, GABAergic signaling in the human brain to sleep-related traits in opioid addiction.

Background Prevalence rates of opioid use disorder (OUD) have increased dramatically, accompanied by a surge of overdose deaths. While opioid dependence has been extensively studied in preclinical models, an understanding of the biological alterations that occur in the brains of people who chronically use opioids and who are diagnosed with OUD remains limited. To address this limitation, RNA sequencing was conducted on the dorsolateral prefrontal cortex and nucleus accumbens, regions heavily implicated in OUD, from postmortem brains in subjects with OUD. Methods We performed RNA sequencing on the dorsolateral prefrontal cortex and nucleus accumbens from unaffected comparison subjects (n = 20) and subjects diagnosed with OUD (n = 20). Our transcriptomic analyses identified differentially expressed transcripts and investigated the transcriptional coherence between brain regions using rank-rank hypergeometric orderlap. Weighted gene coexpression analyses identified OUD-specific modules and gene networks. Integrative analyses between differentially expressed transcripts and genome-wide association study datasets using linkage disequilibrium scores assessed the genetic liability of psychiatric-related phenotypes in OUD. Results Rank-rank hypergeometric overlap analyses revealed extensive overlap in transcripts between the dorsolateral prefrontal cortex and nucleus accumbens in OUD, related to synaptic remodeling and neuroinflammation. Identified transcripts were enriched for factors that control proinflammatory cytokine, chondroitin sulfate, and extracellular matrix signaling. Cell-type deconvolution implicated a role for microglia as a potential driver for opioid-induced neuroplasticity. Linkage disequilibrium score analysis suggested genetic liabilities for risky behavior, attention-deficit/hyperactivity disorder, and depression in subjects with OUD. Conclusions Overall, our findings suggest connections between the brain’s immune system and opioid dependence in the human brain.

BackgroundPrevalence rates of opioid use disorder (OUD) have increased dramatically, accompanied by a surge of overdose deaths. While opioid dependence has been extensively studied in preclinical models, an understanding of the biological alterations that occur in the brains of people who chronically use opioids and who are diagnosed with OUD remains limited. To address this limitation, RNA-sequencing (RNA-seq) was conducted on the dorsolateral prefrontal cortex (DLPFC) and nucleus accumbens (NAc), regions heavily implicated in OUD, from postmortem brains in subjects with OUD.MethodsWe performed RNA-seq on the DLPFC and NAc from unaffected comparison subjects (n=20) and subjects diagnosed with OUD (n=20). Our transcriptomic analyses identified differentially expressed (DE) transcripts and investigated the transcriptional coherence between brain regions using rank-rank hypergeometric ordering (RRHO). Weighted gene co-expression analyses (WGCNA) also identified OUD-specific modules and gene networks. Integrative analyses between DE transcripts and GWAS datasets using linkage disequilibrium score (LDSC) assessed the genetic liability psychiatric-related phenotypes.ResultsRRHO analyses revealed extensive overlap in transcripts between DLPFC and NAc in OUD, primarily relating to synaptic remodeling and neuroinflammation. Identified transcripts were enriched for factors that control pro-inflammatory cytokine-mediated, chondroitin sulfate, and extracellular matrix signaling. Cell-type deconvolution implicated a role for microglia as a critical driver for opioid-induced neuroplasticity. Using LDSC, we discovered genetic liabilities for risky behavior, attention deficit hyperactivity disorder, and depression.ConclusionsOverall, our findings reveal new connections between the brain’s immune system and opioid dependence in the human brain.