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Abstract In brain, the striatum is a heterogenous region involved in reward and goal-directed behaviors. Striatal dysfunction is linked to psychiatric disorders, including opioid use disorder (OUD). Striatal subregions are divided based on neuroanatomy, each with unique roles in OUD. In OUD, the dorsal striatum is involved in altered reward processing, formation of habits, and development of negative affect during withdrawal. Using single nuclei RNA-sequencing, we identified both canonical (e.g., dopamine receptor subtype) and less abundant cell populations (e.g., interneurons) in human dorsal striatum. Pathways related to neurodegeneration, interferon response, and DNA damage were significantly enriched in striatal neurons of individuals with OUD. DNA damage markers were also elevated in striatal neurons of opioid-exposed rhesus macaques. Sex-specific molecular differences in glial cell subtypes associated with chronic stress were found in OUD, particularly female individuals. Together, we describe different cell types in human dorsal striatum and identify cell type-specific alterations in OUD.

Abstract Antipsychotic (AP)-naive first-episode psychosis (FEP) patients display early dysglycemia, including insulin resistance and prediabetes. Metabolic dysregulation may therefore be intrinsic to psychosis spectrum disorders (PSDs), independent of the metabolic effects of APs. However, the potential biological pathways that overlap between PSDs and dysglycemic states remain to be identified. Using meta-analytic approaches of transcriptomic datasets, we investigated whether AP-naive FEP patients share overlapping gene expression signatures with non-psychiatrically ill early dysglycemia individuals. We meta-analyzed peripheral transcriptomic datasets of AP-naive FEP patients and non-psychiatrically ill early dysglycemia subjects to identify common gene expression signatures. Common signatures underwent pathway enrichment analysis and were then used to identify potential new pharmacological compounds via Integrative Library of Integrated Network-Based Cellular Signatures (iLINCS). Our search results yielded 5 AP-naive FEP studies and 4 early dysglycemia studies which met inclusion criteria. We discovered that AP-naive FEP and non-psychiatrically ill subjects exhibiting early dysglycemia shared 221 common signatures, which were enriched for pathways related to endoplasmic reticulum stress and abnormal brain energetics. Nine FDA-approved drugs were identified as potential drug treatments, of which the antidiabetic metformin, the first-line treatment for type 2 diabetes, has evidence to attenuate metabolic dysfunction in PSDs. Taken together, our findings support shared gene expression changes and biological pathways associating PSDs with dysglycemic disorders. These data suggest that the pathobiology of PSDs overlaps and potentially contributes to dysglycemia. Finally, we find that metformin may be a potential treatment for early metabolic dysfunction intrinsic to PSDs.

Abstract 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.

Summary: Bromocriptine is approved as a diabetes therapy, yet its therapeutic mechanisms remain unclear. Though bromocriptine’s actions have been mainly attributed to the stimulation of brain dopamine D2 receptors (D2R), bromocriptine also targets the pancreas. Here, we employ bromocriptine as a tool to elucidate the roles of catecholamine signaling in regulating pancreatic hormone secretion. In β-cells, bromocriptine acts on D2R and α2A-adrenergic receptor (α2A-AR) to reduce glucose-stimulated insulin secretion (GSIS). Moreover, in α-cells, bromocriptine acts via D2R to reduce glucagon secretion. α2A-AR activation by bromocriptine recruits an ensemble of G proteins with no β-arrestin2 recruitment. In contrast, D2R recruits G proteins and β-arrestin2 upon bromocriptine stimulation, demonstrating receptor-specific signaling. Docking studies reveal distinct bromocriptine binding to α2A-AR versus 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.

Microglia are resident macrophages of the brain, performing roles related to brain homeostasis, including modulation of synapses, trophic support, phagocytosis of apoptotic cells and debris, as well as brain protection and repair. Studies assessing morphological and transcriptional features of microglia found regional differences as well as sex differences in some investigated brain regions. However, markers used to isolate microglia in many previous studies are not expressed exclusively by microglia or cannot be used to identify and isolate microglia in all contexts. Here, fluorescent activated cell sorting was used to isolate cells expressing the microglia-specific marker TMEM119 from prefrontal cortex (PFC), striatum, and midbrain in mice. RNA-sequencing was used to assess the transcriptional profile of microglia, focusing on brain region and sex differences. We found striking brain region differences in microglia-specific transcript expression. Most notable was the distinct transcriptional profile of midbrain microglia, with enrichment for pathways related to immune function; these midbrain microglia exhibited a profile similar to disease-associated or immune-surveillant microglia. Transcripts more highly expressed in PFC isolated microglia were enriched for synapse-related pathways while microglia isolated from the striatum were enriched for pathways related to microtubule polymerization. We also found evidence for a gradient of expression of microglia-specific transcripts across the rostral-to-caudal axes of the brain, with microglia extracted from the striatum exhibiting a transcriptional profile intermediate between that of the PFC and midbrain. We also found sex differences in expression of microglia-specific transcripts in all 3 brain regions, with many selenium-related transcripts more highly expressed in females across brain regions. These results suggest that the transcriptional profile of microglia varies between brain regions under homeostatic conditions, suggesting that microglia perform diverse roles in different brain regions and even based on sex.

Abstract 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.

The progress in the field of high-dimensional cytometry has greatly increased the number of markers that can be simultaneously analyzed producing datasets with large numbers of parameters. Traditional biaxial manual gating might not be optimal for such datasets. To overcome this, a large number of automated tools have been developed to aid with cellular clustering of multi-dimensional datasets. Here were review two large categories of such tools; unsupervised and supervised clustering tools. After a thorough review of the popularity and use of each of the available unsupervised clustering tools, we focus on the top six tools to discuss their advantages and limitations. Furthermore, we employ a publicly available dataset to directly compare the usability, speed, and relative effectiveness of the available unsupervised and supervised tools. Finally, we discuss the current challenges for existing methods and future direction for the new generation of cell type identification approaches.

Microglia are resident macrophages of the brain, performing roles related to brain homeostasis, including modulation of synapses, trophic support, phagocytosis of apoptotic cells and debris, as well as brain protection and repair. Studies assessing morphological and transcriptional features of microglia found regional differences as well as sex differences in some investigated brain regions. However, markers used to isolate microglia in many previous studies are not expressed exclusively by microglia or cannot be used to identify and isolate microglia in all contexts. Here, fluorescent activated cell sorting was used to isolate cells expressing the microglia-specific marker TMEM119 from prefrontal cortex (PFC), striatum, and midbrain in mice. RNA-sequencing was used to assess the transcriptional profile of microglia, focusing on brain region and sex differences. We found striking brain region differences in microglia-specific transcript expression. Most notable was the distinct transcriptional profile of midbrain microglia, with enrichment for pathways related to immune function; these midbrain microglia exhibited a profile similar to disease-associated or immune-surveillant microglia. Transcripts more highly expressed in PFC isolated microglia were enriched for synapse-related pathways while microglia isolated from the striatum were enriched for pathways related to microtubule polymerization. We also found evidence for a gradient of expression of microglia-specific transcripts across the rostral-to-caudal axes of the brain, with microglia extracted from the striatum exhibiting a transcriptional profile intermediate between that of the PFC and midbrain. We also found sex differences in expression of microglia-specific transcripts in all 3 brain regions, with many selenium-related transcripts more highly expressed in females across brain regions. These results suggest that the transcriptional profile of microglia varies between brain regions under homeostatic conditions, suggesting that microglia perform diverse roles in different brain regions and even based on sex. [ABSTRACT FROM AUTHOR]