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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.

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.

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.

Dopamine (DA) and norepinephrine (NE) are catecholamines primarily studied in the central nervous system that also act in the pancreas as peripheral regulators of metabolism. Pancreatic catecholamine signaling has also been increasingly implicated as a mechanism responsible for the metabolic disturbances produced by antipsychotic drugs (APDs). Critically, however, the mechanisms by which catecholamines modulate pancreatic hormone release are not completely understood. We show that human and mouse pancreatic α- and β-cells express the catecholamine biosynthetic and signaling machinery, and that α-cells synthesize DA de novo. This locally-produced pancreatic DA signals via both α- and β-cell adrenergic and dopaminergic receptors with different affinities to regulate glucagon and insulin release. Significantly, we show DA functions as a biased agonist at α2A-adrenergic receptors, preferentially signaling via the canonical G protein-mediated pathway. Our findings highlight the interplay between DA and NE signaling as a novel form of regulation to modulate pancreatic hormone release. Lastly, pharmacological blockade of DA D2-like receptors in human islets with APDs significantly raises insulin and glucagon release. This offers a new mechanism where APDs act directly on islet α- and β-cell targets to produce metabolic disturbances.