Genome-wide meta-analysis of ascertainment and symptom structures of major depression in case-enriched and community cohorts.

BACKGROUND: Diagnostic criteria for major depressive disorder allow for heterogeneous symptom profiles but genetic analysis of major depressive symptoms has the potential to identify clinical and etiological subtypes. There are several challenges to integrating symptom data from genetically informative cohorts, such as sample size differences between clinical and community cohorts and various patterns of missing data. METHODS: We conducted genome-wide association studies of major depressive symptoms in three cohorts that were enriched for participants with a diagnosis of depression (Psychiatric Genomics Consortium, Australian Genetics of Depression Study, Generation Scotland) and three community cohorts who were not recruited on the basis of diagnosis (Avon Longitudinal Study of Parents and Children, Estonian Biobank, and UK Biobank). We fit a series of confirmatory factor models with factors that accounted for how symptom data was sampled and then compared alternative models with different symptom factors. RESULTS: The best fitting model had a distinct factor for Appetite/Weight symptoms and an additional measurement factor that accounted for the skip-structure in community cohorts (use of Depression and Anhedonia as gating symptoms). CONCLUSION: The results show the importance of assessing the directionality of symptoms (such as hypersomnia versus insomnia) and of accounting for study and measurement design when meta-analyzing genetic association data.

The genetic architecture of substance use and its diverse correlations with mental health traits.

Although harmful substance use is common and represented by shared symptom features and high genetic correlations, the underlying genetic relationships between substance use traits have not been fully explored. We have investigated the genetic architecture of substance use traits through exploratory and confirmatory factor analyses using genomic structural equation modeling (Genomic SEM), and explored genetic correlations between different aspects of substance use and mental health-related traits. Genomic SEM was used to identify latent factors representing the relationships between 14 substance use traits (alcohol, nicotine, cannabis and opioid use), and to confirm or modify existing latent factors for 38 mental health-related traits. A bi-factor model best explained the genetic overlap between substance use traits, including a general substance use factor and two sub-factors representing genetic liability specific to alcohol use or smoking. The SNP-based heritability of these factors ranged from 2 to 7 % and each factor had 10 or more independent significant SNPs identified. Bivariate correlations revealed patterns of genetic overlap with other mental health-related factors unique to each substance use factor. Variations in the genetic overlap between psychiatric traits and different aspects of substance use can be used to further investigate the pleiotropy present between these traits, and explore commonalities in etiology.

Xylazine is an agonist at kappa opioid receptors and exhibits sex-specific responses to opioid antagonism.

Xylazine is in the unregulated drug supply at increasing rates, usually combined with fentanyl, necessitating understanding of its pharmacology. Despite commentary from politicians, and public health officials, it is unknown how xylazine impacts naloxone efficacy, and. few studies have examined it alone. Here, we examine the impact of xylazine alone and in combination with fentanyl on several behaviors in mice. Surprisingly, naloxone precipitates withdrawal from xylazine and fentanyl/xylazine coadministration, with enhanced sensitivity in females. Further, xylazine is a full agonist at kappa opioid receptors, a potential mechanism for its naloxone sensitivity. Finally, we demonstrate surprising effects of xylazine to kappa opioid antagonism, which are relevant for public health considerations. These data address an ongoing health crisis and will help inform critical policy and healthcare decisions.

Next-generation pediatric care: nanotechnology-based and AI-driven solutions for cardiovascular, respiratory, and gastrointestinal disorders.

BACKGROUND: Global pediatric healthcare reveals significant morbidity and mortality rates linked to respiratory, cardiac, and gastrointestinal disorders in children and newborns, mostly due to the complexity of therapeutic management in pediatrics and neonatology, owing to the lack of suitable dosage forms for these patients, often rendering them "therapeutic orphans". The development and application of pediatric drug formulations encounter numerous challenges, including physiological heterogeneity within age groups, limited profitability for the pharmaceutical industry, and ethical and clinical constraints. Many drugs are used unlicensed or off-label, posing a high risk of toxicity and reduced efficacy. Despite these circumstances, some regulatory changes are being performed, thus thrusting research innovation in this field. DATA SOURCES: Up-to-date peer-reviewed journal articles, books, government and institutional reports, data repositories and databases were used as main data sources. RESULTS: Among the main strategies proposed to address the current pediatric care situation, nanotechnology is specially promising for pediatric respiratory diseases since they offer a non-invasive, versatile, tunable, site-specific drug release. Tissue engineering is in the spotlight as strategy to address pediatric cardiac diseases, together with theragnostic systems. The integration of nanotechnology and theragnostic stands poised to refine and propel nanomedicine approaches, ushering in an era of innovative and personalized drug delivery for pediatric patients. Finally, the intersection of drug repurposing and artificial intelligence tools in pediatric healthcare holds great potential. This promises not only to enhance efficiency in drug development in general, but also in the pediatric field, hopefully boosting clinical trials for this population. CONCLUSIONS: Despite the long road ahead, the deepening of nanotechnology, the evolution of tissue engineering, and the combination of traditional techniques with artificial intelligence are the most recently reported strategies in the specific field of pediatric therapeutics.

Corrigendum: Therapeutically targeting type I interferon directly to XCR1+ dendritic cells reveals the role of cDC1s in anti-drug antibodies.

[This corrects the article DOI: 10.3389/fimmu.2023.1272055.].

The Black Lives Matter movement mitigates bias against racial minority actors.

Watching movies is among the most popular entertainment and cultural activities. How do viewers react when a movie sequel increases racial minority actors in the main cast ("minority increase")? On the one hand, such sequels may receive better evaluations if viewers appreciate racially inclusive casting for its novel elements (the value-in-diversity perspective) and moral appeal (the fairness perspective on diversity). On the other hand, discrimination research suggests that if viewers harbor biases against racial minorities, sequels with minority increase may receive worse evaluations. To examine these competing possibilities, we analyze a unique panel dataset of movie series released from 1998 to 2021 and conduct text analysis of 312,457 reviews of these movies. Consistent with discrimination research, we find that movies with minority increase receive lower ratings and more toxic reviews. Importantly, these effects weaken after the advent of the Black Lives Matter (BLM) movement, especially when the movement's intensity is high. These results are reliable across various robustness checks (e.g., propensity score matching, random implementation test). We conceptually replicate the bias mitigation effect of BLM in a preregistered experiment: Heightening the salience of BLM increases White individuals' acceptance of racial minority increase in a movie sequel. This research demonstrates the power of social movements in fostering diversity, equality, and inclusion.

Nuclear pyruvate dehydrogenase complex regulates histone acetylation and transcriptional regulation in the ethylene response.

Ethylene plays its essential roles in plant development, growth, and defense responses by controlling the transcriptional reprograming, in which EIN2-C-directed regulation of histone acetylation is the first key step for chromatin to perceive ethylene signaling. But how the nuclear acetyl coenzyme A (acetyl CoA) is produced to ensure the ethylene-mediated histone acetylation is unknown. Here we report that ethylene triggers the accumulation of the pyruvate dehydrogenase complex (PDC) in the nucleus to synthesize nuclear acetyl CoA to regulate ethylene response. PDC is identified as an EIN2-C nuclear partner, and ethylene triggers its nuclear accumulation. Mutations in PDC lead to an ethylene hyposensitivity that results from the reduction of histone acetylation and transcription activation. Enzymatically active nuclear PDC synthesizes nuclear acetyl CoA for EIN2-C-directed histone acetylation and transcription regulation. These findings uncover a mechanism by which PDC-EIN2 converges the mitochondrial enzyme-mediated nuclear acetyl CoA synthesis with epigenetic and transcriptional regulation for plant hormone response.

Genome-wide association study identifies 30 obsessive-compulsive disorder associated loci.

Obsessive-compulsive disorder (OCD) affects ~1% of the population and exhibits a high SNP-heritability, yet previous genome-wide association studies (GWAS) have provided limited information on the genetic etiology and underlying biological mechanisms of the disorder. We conducted a GWAS meta-analysis combining 53,660 OCD cases and 2,044,417 controls from 28 European-ancestry cohorts revealing 30 independent genome-wide significant SNPs and a SNP-based heritability of 6.7%. Separate GWAS for clinical, biobank, comorbid, and self-report sub-groups found no evidence of sample ascertainment impacting our results. Functional and positional QTL gene-based approaches identified 249 significant candidate risk genes for OCD, of which 25 were identified as putatively causal, highlighting WDR6, DALRD3, CTNND1 and genes in the MHC region. Tissue and single-cell enrichment analyses highlighted hippocampal and cortical excitatory neurons, along with D1- and D2-type dopamine receptor-containing medium spiny neurons, as playing a role in OCD risk. OCD displayed significant genetic correlations with 65 out of 112 examined phenotypes. Notably, it showed positive genetic correlations with all included psychiatric phenotypes, in particular anxiety, depression, anorexia nervosa, and Tourette syndrome, and negative correlations with a subset of the included autoimmune disorders, educational attainment, and body mass index.. This study marks a significant step toward unraveling its genetic landscape and advances understanding of OCD genetics, providing a foundation for future interventions to address this debilitating disorder.

The genetic landscape of substance use disorders.

Substance use disorders represent a significant public health concern with considerable socioeconomic implications worldwide. Twin and family-based studies have long established a heritable component underlying these disorders. In recent years, genome-wide association studies of large, broadly phenotyped samples have identified regions of the genome that harbour genetic risk variants associated with substance use disorders. These regions have enabled the discovery of putative causal genes and improved our understanding of genetic relationships among substance use disorders and other traits. Furthermore, the integration of these data with clinical information has yielded promising insights into how individuals respond to medications, allowing for the development of personalized treatment approaches based on an individual's genetic profile. This review article provides an overview of recent advances in the genetics of substance use disorders and demonstrates how genetic data may be used to reduce the burden of disease and improve public health outcomes.

Mucosal-associated invariant T cells modulate innate immune cells and inhibit colon cancer growth.

Mucosal-associated invariant T (MAIT) cells are innate-like T cells that can be activated by microbial antigens and cytokines and are abundant in mucosal tissues including the colon. MAIT cells have cytotoxic and pro-inflammatory functions and have potentials for use as adoptive cell therapy. However, studies into their anti-cancer activity, including their role in colon cancer, are limited. Using an animal model of colon cancer, we showed that peritumoral injection of in vivo-expanded MAIT cells into RAG1-/- mice with MC38-derived tumours inhibits tumour growth compared to control. Multiplex cytokine analyses showed that tumours from the MAIT cell-treated group have higher expression of markers for eosinophil-activating cytokines, suggesting a potential association between eosinophil recruitment and tumour inhibition. In a human peripheral leukocyte co-culture model, we showed that leukocytes stimulated with MAIT ligand showed an increase in eotaxin-1 production and activation of eosinophils, associated with increased cancer cell killing. In conclusion, we showed that MAIT cells have a protective role in a murine colon cancer model, associated with modulation of the immune response to cancer, potentially involving eosinophil-associated mechanisms. Our results highlight the potential of MAIT cells for non-donor restricted colon cancer immunotherapy.