Translational Psychiatry

IntroductionRodent chronic-stress models are central to preclinical depression research, yet behavioral phenotypes are often assessed assay-by-assay, which can reduce cross-cohort comparability and mask heterogeneity across symptom domains (e.g., anhedonia, anxiety-like behavior, and behavioral despair). An integrative behavioral index may provide a more robust and interpretable measure of overall stress-induced severity and facilitate stratification of susceptible versus resilient individuals. MethodsWe developed the Multimodal Behavior Scoring (MBS) algorithm to integrate outcomes from standard assays--sucrose preference test (SPT), open field test (OFT), and forced swim test (FST)--into a unified severity score. MBS was evaluated in two independent paradigms, chronic unpredictable mild stress (CUMS) and chronic social defeat stress (CSDS), quantifying group discrimination, reproducibility (intraclass correlation coefficient, ICC), and phenotypic stratification. ResultsMBS robustly separated stressed from control mice (CUMS: +39.8%, p<0.0001; CSDS: +121.8%, p<0.0001) and showed high cross-cohort reproducibility (ICC>0.88). MBS further identified stress-resilient subpopulations and uncovered paradigm-specific behavioral signatures, with despair-dominant patterns in CUMS (FST-MBS, r=0.61) and anxiety-centric patterns in CSDS (OFT-MBS, r=-0.74). Excluding TST did not reduce discrimination performance. ConclusionMBS provides an integrative framework for quantifying depression-like behavioral severity and heterogeneity, enabling streamlined protocols and improving the translational utility of preclinical cohorts for biomarker discovery and antidepressant screening.

Major depressive disorder (MDD) is a heritable psychiatric disorder which is considered one of the leading causes of disability world-wide. Improved understanding of its genetic component could inform novel treatment developments, but so far, gaining functional insights from genome-wide association studies has been difficult. In this study, we sought to generate hypotheses about plausible mechanisms through which genetic variants could influence MDD using a novel approach. Considering the cisregions of protein coding genes as the loci of interest, we applied local genetic correlation analysis to study the genetic relationship between MDD and a range of brain, endocrine, and immune related endophenotypes across several modalities (tissue specific gene expression and splicing, regional brain volumes, and brain network connectivity). We identify significant genetic relations between MDD and endophenotypes within the cis-regions of multiple genes, and perform endophenotype specific enrichment analyses of the top associated genes. Our results offer potential mechanisms through which MDD related variants in these genomic regions could act, and convergent evidence from multiple endophenotypes implicate FLOT1 as a gene which may exhibit wide-ranging pleiotropic effects and be particularly interesting for functional follow-up. Here, we have illustrated how local genetic correlation analysis applied to lower level endophenotypes has the power to prioritise genes and functional paths which warrant further investigation for their possible role in MDD aetiology.

Fragile X syndrome (FXS) is the principal monogenic syndrome leading to inherited intellectual disability and autism. It is caused by the silencing of FMR1 gene that leads to the loss in the expression of its encoded protein, the fragile X messenger ribonucleoprotein 1 (FMRP). In synapses, FMRP has a key role in local mRNA modulation to maintain synaptic plasticity. The Fmr1 KO (FX) mouse model shows cognitive impairment and some of the synaptic traits present in individuals with FXS together with alterations in gut microbiota. Previous studies revealed that pharmacological and genetic cannabinoid type-1 receptor (CB1R) inhibition significantly prevented central key alterations in FX mice. Here, we aimed to evaluate the effect of a sub-chronic treatment with the largely peripherally-restricted CB1R antagonist AM6545. We found that AM6545 reduced memory deficits and restored enhanced hippocampal mGluR5-dependent long-term depression and aberrant dendritic spine density in FX mice. At the peripheral level, AM6545 modified altered FX mice fecal microbiota composition, while in the hippocampus AM6545 treatment upregulated hippocampal Htr4, the gene encoding for serotonin receptor 4 (5-HT4R) This upregulation positively correlated with memory performance. Notably, acute pharmacological blockade of 5-HT4R abolished the pro-cognitive effect produced by AM6545. Together, our results suggest that peripheral CB1R inhibition ameliorates key alterations in FX mouse model and modifies the expression of serotonergic receptors important for cognitive performance.

BackgroundMore than 180 million cases of COVID-19 have been reported worldwide. It has been proposed that neuropsychiatric disorders may be risk factors and/or consequences of COVID-19 infection. However, observational studies could be affected by confounding bias. MethodsWe performed bi-directional two-sample Mendelian randomization (MR) analysis to evaluate causal relationships between liability to COVID-19 (and severe/critical infection) and a wide range of neuropsychiatric disorders or traits. We employed GWAS summary statistics from the COVID-19 Host Genetics Initiative. A variety of MR methods including those accounting for horizontal pleiotropy were employed. ResultsOverall, we observed evidence that liability to COVID-19 or severe infection may be causally associated with higher risks of post-traumatic stress disorder (PTSD), bipolar disorder (BD) (especially BD II), schizophrenia (SCZ), attention deficit hyperactivity disorder (ADHD) and suicidal thought (ST) when compared to the general population. On the other hand, liability to a few psychiatric traits/disorders, for example ADHD, alcohol and opioid use disorders may be causally associated with higher risks of COVID-19 infection or severe disease. In genetic correlation analysis, cannabis use disorder, ADHD, and anxiety showed significant and positive genetic correlation with critical or hospitalized infection. All the above findings passed multiple testing correction at a false discovery rate (FDR)<0.05. For pneumonia, in general we observed a different pattern of causal associations. We observed bi-directional positive associations with depression- and anxiety-related phenotypes. ConclusionsIn summary, this study provides evidence for tentative bi-directional causal associations between liability to COVID-19 (and severe infection) and a number of neuropsychiatric disorders. Further replications and prospective studies are required to verify the findings.

Omics signatures for psychiatric conditions have been under-investigated. This study aimed to identify serum metabolites associated with symptoms of depression or anxiety in Hispanic/Latino adults and to develop and assess metabolite risk scores (MRSs) of these phenotypes. Using data from the Hispanic Community Health Study/Study of Latinos (HCHS/SOL), we conducted a metabolome-wide association study of 768 metabolites with depression and anxiety symptoms. We used two separate assay batches measured from baseline samples collected between June 2008 and July 2011 for discovery (batch 1: n=4,002 adults) and replication (batch 2: n=2,178 adults). We estimated the associations via survey-based generalized linear regression, and applied Least Absolute Shrinkage and Selection Operator (LASSO) regression for metabolite selection and for obtaining metabolite risk score (MRS) weights. In analyses adjusted for age, sex, field center and Hispanic/Latino background, we identified five metabolites with replicated associations with depression symptoms and six metabolites with anxiety symptoms. Key pathways related to the identified metabolites included arginine and proline, vitamin A, phospholipid, fatty acid and tyrosine metabolism. MRSs were associated with higher depression symptom score (1.07 points, 95% CI: 0.67 - 1.46, per 1 SD increase in depression MRS) and anxiety symptom score (1.05 points, 95% CI: 0.67 - 1.43, per 1 SD increase in anxiety MRS) in the replication dataset. Our study supports the associations between serum metabolites and symptoms of depression and anxiety in Hispanic/Latino adults. The MRSs developed in this study may facilitate earlier and more objective screening of individuals for depression and anxiety apart from traditional risk factors.

Hypothalamic-pituitary-adrenal axis (HPA axis) dysregulation is a risk factor for poor mental and physical health. Animal studies indicate that DNA methylation may be one mechanism through which stress can influence the function of the HPA axis, however human studies have not identified consistent individual loci. Machine learning can be used to develop methylation profile scores (MPSs), but this method has not yet been applied to HPA axis function. Using a novel machine learning pipeline, we developed an MPS to predict the salivary cortisol response (AUCi) to the Trier Social Stress Test (TSST) from whole blood Illumina Infinium HumanMethylation 450K BeadChip data (N = 84, mean age = 34, 49% female). The MPS was associated with the cortisol response in an independent, cross-tissue cohort (N = 53, mean age = 20, 51% female), both before ({beta} = 0.33, 95% CI [0.09, 0.54]) and after a social stressor ({beta} = 0.3, 95% CI [0.09, 0.47]). Functional characterisation revealed several immune, stress, and disease-related pathways and genes, including tolerance induction to self antigen, chronic myeloid leukemia, NR3C2, and PSMB4 (putatively causal in depression). We have developed and validated a novel epigenetic biomarker for stress reactivity, identifying a set of genomic loci where DNA methylation is associated with the cortisol response. Future research could investigate if HPA axis-related MPSs could be used alongside traditional risk factors to improve clinical risk assessment.

Background: The Neuro-Immune-Metabolic-Oxidative Stress (NIMETOX) theory identified systemic dysregulation in Major Depressive Disorder (MDD), yet the precise gut-derived metabolic triggers initiating this cascade remain elusive. This study investigated the interplay between fecal short-chain fatty acids (SCFAs), systemic immune activation, and clinical phenotypes to identify a potential gut-immune biotype for MDD. Methods: Fecal SCFA profiles and serum immune-inflammatory markers were quantified in 102 patients with MDD and 38 matched healthy controls. A multistage statistical approach was employed: binary logistic regression and 10-fold cross-validated linear discriminant analysis (LDA) were utilized to evaluate diagnostic accuracy, while multivariable regression models were applied to identify robust predictors of clinical phenotypes, including the overall severity of depression (OSOD), physiosomatic symptoms, and recurrence of illness (ROI). Results: MDD patients exhibited a significant depletion of protective straight-chain SCFAs (acetate, propionate, butyrate) and an elevation in branched-chain SCFAs (BSCFAs), indicating a pathological shift from saccharolytic to proteolytic fermentation. This metabolic shift correlated with elevated acute phase-inflammatory index (API) and epidermal growth factor (EGF). A multidimensional model combining BSCFAs, acetate, API, EGF, and T helper 2 discriminated MDD from controls with adequate accuracy (AUC = 0.874). Furthermore, elevated BSCFAs and decreased protective SCFAs strongly predicted higher OSOD, more severe physiosomatic symptoms, and increased ROI. Notably, 5-Hydroxytryptamine receptor 1A agonists were independently associated with elevated BSCFAs. Conclusion: MDD is characterized by a distinct gut-immune biotype tightly linked to toxic proteolytic gut fermentation. This metabolic-immune fingerprint offers an objective diagnostic tool and highlights the need for microbiome-targeted interventions in precision psychiatry.

Neuroticism has been described as a broad and pervasive personality dimension or heterogeneous trait measuring components of mood instability, such as worry; anxiety; irritability; moodiness; self-consciousness and sadness. Consistent with depression and anxiety-related disorders, increased neuroticism places an individual vulnerable for other unipolar and bipolar mood disorders and therefore highly relevant in epidemiologic research. However, the measurement of neuroticism remains a challenge. We aimed to adapt the 12-item Eysenck Personality Questionnaire-Revised Neuroticism (EPQ-RN) scale for use in epidemiologic studies by identifying psychometrically efficient items using item response theory. The 12-item EPQ-RN scale was evaluated by estimating an IRT model on data from 401,527 UK Biobank participants aged 39 to 73 years (M = 56.41 years; SD = 8.06), 53.68% female. The IRT model yielded two item characteristics: item discrimination, an indicator of how well an item differentiates between respondents, and item difficulty, an indicator of the amount of the latent construct (neuroticism) needed to endorse an item. The EPQ-RN exhibited psychometric inefficiency with poor discrimination at extremes of the scale range. High and low scores are relatively poorly represented and uninformative suggesting that high neuroticism scores derived from the scale are a function of cumulative mid-range values. Following systematic item deletion, a 3-item scale was found to have high levels of discrimination, but offered a narrow range of difficulty i.e. was not sensitive to low levels of neuroticism. A 7-item scale was found to be most informative; providing high levels of discrimination across the range of neuroticism scores.

BackgroundSchizophrenia often features low-grade neuroinflammation. Because latent toxoplasmosis (LT) is common in this population, we tested whether LT yields a biomarker pattern resembling that reported in schizophrenia. MethodsWe quantified 15 cytokines and 15 blood markers of brain injury in 65 LT-positive individuals and 103 matched LT-negative controls using multiplex immunoassays. Multivariate effects of infection, age, sex, and their interaction were assessed by MANCOVA and PERMANOVA. Effects on individual biomarkers were tested by partial Kendall correlation (controlling for age and sex). Differences in the internal correlation structure were evaluated with Mantel tests on dissimilarity matrices derived from partial correlations. ResultsLT was associated with higher KLK6, S100B, and TDP-43 and lower MIF; several other markers showed nonsignificant but sizable trends. Cytokines showed reduced IFN-{gamma}, IL-1{beta}, and MCP-1 and elevated IL-13 and IL-17 in the infected group. Sex-stratified analyses suggested stronger effects on brain-injury markers in women and on cytokines in men. Correlation structure also diverged: infected individuals exhibited more negative links between brain-injury markers and cytokines, whereas controls showed predominantly positive associations (Mantel r = 0.461, p = 0.043). The LT profile overlapped with schizophrenia in elevated KLK6 and S100B and, in men, reduced GDNF, but contrasted for MIF and for the overall cytokine pattern (no consistent IL-6/TNF- elevation). ConclusionsLT entails neuroinflammatory and neuroimmune alterations that only partly recapitulate schizophrenia; the biomarker pattern and interrelationships differ, arguing against LT as the main driver of schizophrenia-related neuroinflammation.

Obsessive-Compulsive Disorder (OCD) and Major Depressive Disorder (MDD) frequently co-occur, with depressive symptoms affecting OCD progression and vice versa. Identifying biomarkers is crucial for improving diagnosis and treatment. While the gut microbiotas role in psychiatric disorders is well-studied, this research focuses on alterations in the oral microbiota and their relationship with BDNF (Brain-Derived Neurotrophic Factor) DNA methylation in OCD and MDD patients compared to healthy controls. Our findings reveal significant changes in microbiota composition with OCD patients showing increased Actinobacteriota and Firmicutes abundances (p<0.05; CTRL=n.24, OCD=n.21), while MDD patients exhibiting increased Actinobacteriota and Firmicutes, with reduced Bacteroidota and Proteobacteria abundances (p<0.05; CTRL=n.24, MDD=n.16). These alterations, including potential post-streptococcal autoimmunity, highlight the microbiotas role in OCD and MDD pathophysiology. Selective changes in BDNF DNA methylation were observed in both disorders at CpG sites in exon I and IV, significantly reduced in OCD and MDD (p<0.05; CTRL=n.24, OCD=n.23, MDD=n.16) and, following miRNome analysis showed altered expression of BDNF-targeting microRNAs, with miR-16-5p and miR-29a-3p upregulated in OCD (p<0.05; CTRL=n.24, OCD=n.17), and miR-29a-3p upregulated and miR-191-5p downregulated in MDD (p<0.05; CTRL=n.24, MDD=n.16). These findings suggest disorder-specific microbiota and epigenetic profiles, positioning saliva as a non-invasive tool for biomarker identification. This research advances understanding of microbial-epigenetic interactions in OCD and MDD, potentially guiding early diagnosis and targeted therapies.

Selective serotonin reuptake inhibitors (SSRIs) are often prescribed during pregnancy. Yet, epidemiological studies link in-utero SSRI exposure with neurodevelopmental disorders, such as autism and ADHD. The potential molecular mechanisms by which SSRIs impact early neurodevelopment are not fully understood. We exposed neuroepithelial stem cells derived from four human induced pluripotent stem cells lines to fluoxetine, citalopram, sertraline, and paroxetine. We then assessed cellular viability, reactive oxygen species (ROS) levels, mitochondrial function using adenosine triphosphate (ATP) assays, and performed high-throughput metabolomics at two timepoints: proliferation and neural differentiation stages. The key metabolic findings were validated in the in-vitro model and in a complementary population-based cohort, the Barwon Infant Study, consisting of 1074 mother-child pairs with analysed cord-blood metabolomes. Sertraline and paroxetine significantly decreased ROS and ATP levels, indicating mitochondrial alteration. Metabolomic profiling revealed consistent elevation of three lysophosphatidylcholines (LPCs 16:0, 18:0, 18:1) across all SSRIs except citalopram. We further observed elevated LPC levels in the cord blood of infants prenatally exposed to SSRIs, with a dose-dependent correlation to autism and ADHD-related symptoms at age two. Furthermore, the three LPCs modulated ROS and ATP levels in the neural cells. These findings provide insights into SSRI-induced molecular changes, highlight candidate metabolites that may warrant further investigation as indicators of SSRI exposure, and emphasise the need for exploring prenatal SSRI exposure effects and neurodevelopmental outcomes.

Difficulties with sociability include a tendency to avoid social contacts and activities, and to prefer being alone rather than being with others. While sociability is a continuously distributed trait in the population, decreased sociability represent a common early manifestation of multiple neuropsychiatric disorders such as Schizophrenia (SCZ), Bipolar Disorder (BP), Major Depressive Disorder (MDD), Autism Spectrum Disorders (ASDs), and Alzheimers disease (AD). We aimed to investigate the genetic underpinnings of sociability as a continuous trait in the general population. In this respect, we performed a genome-wide association study (GWAS) using a sociability score based on 4 social functioning-related self-report questions in the UK Biobank sample (n=342,461) to test the effect of individual genetic variants. This was followed by LD score analyses to investigate the genetic correlation with psychiatric disorders (SCZ, BP, MDD, ASDs) and a neurological disorder (AD) as well as related phenotypes (Loneliness and Social Anxiety). The phenotypic data indeed showed that the sociability score was decreased in individuals with ASD, (probable) MDD, BP and SCZ, but not in individuals with AD. Our GWAS showed 604 genome-wide significant SNPs, coming from 18 independent loci (SNP-based h2=0.06). Genetic correlation analyses showed significant correlations with SCZ (rg=0.15, p=9.8e-23), MDD (rg=0.68, p=6.6e-248) and ASDs (rg=0.27, p=4.5e-28), but no correlation with BP (rg=0.01, p=0.45) or AD (rg=0.04, p=0.55). Our sociability trait was also genetically correlated with Loneliness (rg=0.45, p=2.4e-8) and Social Anxiety (rg=0.48, p=0.002). Our study shows that there is a significant genetic component to variation in population levels of sociability, which is relevant to some psychiatric disorders (SCZ, MDD, ASDs), but not to BP and AD.

An emerging element in psychiatry is the gut-brain-axis, the bi-directional communication pathways between the gut microbiome and the brain. A prominent hypothesis, mostly based on preclinical studies, is that individual differences in the gut microbiome composition and drug-induced dysbiosis may be associated with vulnerability to psychiatric disorders including substance use disorder. However, most studies used small sample size, ignored individual differences, or used animal models with limited relevance to addiction. Here, we test the hypothesis that pre-existing microbiome composition and drug-induced changes in microbiome composition can predict addiction-like behaviors using an advanced animal model of extended access to cocaine self-administration in a large cohort of heterogenous stock (HS) rats. Adult male and female HS rats were allowed to self-administer cocaine under short (2h/day) and long access (6h/day) for ~7 weeks under various schedule of reinforcement to identify individuals that are resistant or vulnerable to addiction-like behaviors and fecal samples were collected before the first session and after the last session to assess differences in the microbiome composition. Linear discriminant analysis (LDA) identified sex-dependent and sex-independent differences at the phylum, order, and species level that are differentially abundant in resistant vs. vulnerable individuals, including high level of actinobacteria both before the first exposure to cocaine and after 7 weeks of cocaine self-administration in resistant animals. Predictions of functional gene content using PICRUSt revealed differential regulation of short-chain fatty acid processing in the vulnerable group after self-administration. These results identify microbiome constituents as well as metabolic pathways that are associated with resistance or vulnerability to addiction-like behaviors in rats. Identification of microbes and tangential metabolic pathways involved in cocaine resilience/vulnerability may represent an innovative strategy for the development of novel biomarkers and medication for the treatment of cocaine use disorder.

Stressful events are a leading factor in development of depression. The medial prefrontal cortex (mPFC) is strongly associated with depression etiology and exposure to uncontrollable stressors results in synaptic dysfunction and loss. Learned helplessness is a behavioral paradigm that measures effects of repeated exposure to uncontrollable, inescapable stress on later responses to escapable stress. We therefore performed a proteomic analysis of mPFC synaptosomes in a mouse learned helplessness model to identify molecular changes that could contribute to functional consequences of inescapable stress. Male and female mice were evaluated at baseline and following exposure to escapable or inescapable stress followed by an active avoidance test. Label-free mass spectrometry followed by pathway and protein-protein interaction network analyses identified alterations in signaling pathways involved in energy metabolism, neurotransmitter signaling, and protein shuttling. Furthermore, phosphoproteomics revealed alterations related to synaptic function, neurotransmitter signaling and protein internalization, as well as changes in activity of kinases previously identified as mediators of antidepressant efficacy (GSK3B) and receptor internalization (ADRBK1). We more deeply examined alterations in the Acetylcholine Receptor Signaling Pathway, and identified muscarinic receptor proteins (Chrm1, Chrm2, Chrm4) and key proteins involved in their translocation to and from the membrane. These results identify substantial changes in the mPFC proteome following exposure to inescapable stressors. In addition, mPFC muscarinic cholinergic signaling is well placed to mediate responses to an inescapable stressor. This proteomic study will be useful in guiding studies of human mPFC relevant to depression. Data are available via ProteomeXchange with identifier PXD073765.

BackgroundDeficits in social cognition consistently underlie functional disabilities in a wide range of psychiatric disorders. Neuroimaging studies have suggested that the anterior insula is a common core brain region that is impaired across neurological and psychiatric disorders, which include social cognition deficits. Nevertheless, neurobiological mechanisms of the anterior insula for social cognition remain elusive. MethodsTo determine the role of anterior insula in social cognition, we manipulated expression of Cyp26B1, an anterior insula-enriched molecule that is crucial for retinoic acid degradation and involved in the pathology of neuropsychiatric conditions. Social cognition was mainly assayed using the three-chamber social interaction test. We conducted multimodal analyses at the molecular, cellular, circuitry, and behavioral levels. ResultsAt the molecular/cellular level, anterior insula-mediated social novelty recognition is maintained by proper activity of the layer 5 pyramidal neurons, for which retinoic acid-mediated gene transcription can play a role. We also demonstrate that oxytocin influences the anterior insula-mediated social novelty recognition, not by direct projection of oxytocin neurons, nor by direct diffusion of oxytocin to the anterior insula, which contrasts the modes of oxytocin regulation onto the posterior insula. Instead, oxytocin affects oxytocin receptor-expressing neurons in the dorsal raphe nucleus where serotonergic neurons are projected to the anterior insula. Furthermore, we show that serotonin 5HT2C receptor expressed in the anterior insula influences social novelty recognition. ConclusionsAnterior insula plays a pivotal role in social novelty recognition that is partly regulated by a local retinoic acid cascade, but also remotely regulated by oxytocin via a non-classic mechanism.

A major obstacle in the pre-clinical study of mood-related disorders and novel affective state therapeutic evaluation is the lack of animal models that fully recapitulate human symptomatology. In this study, we developed a touchscreen-based Go/No Go cognitive judgement bias (CJB) task for mice. In this task, animals first learned to discriminate between two visual stimuli displayed on the touchscreen: one associated with a reward (S+) and one associated with a time-out and flashing house light (S-). Once mice learned to respond to the S+ and to withhold responding to the S- consistently, a set of four ambiguous stimuli ranging in visual similarity to the S+ and S- stimuli were randomly interspersed in the stimulus presentation sequence. Responses to these ambiguous stimuli were interpreted as a greater expectation of positive ( optimistic bias) or negative ( pessimistic bias) outcomes as a function of their similarity to the S+ or S- stimuli. The acute administration of the SSRIs fluoxetine and citalopram and the 5HT-2C receptor antagonist SB204048 did not produce any effects on CJB task performance. However, the noradrenaline/dopamine reuptake inhibitor, bupropion, increased responses to the ambiguous stimuli consistent with induction of an optimistic bias and the pro-depressant tetrabenazine yielded the opposite effect. This study underscores the capacity of mice to respond to visually ambiguous stimuli in an ambiguity-dependent manner, a phenomenon observed across various species, including humans. Furthermore, it establishes and validates an operant behavioural task to assess CJB in mice delivered using the touchscreen platform which has significant intrinsic cross-species translational potential.

The heterogeneity of chronic post-COVID neuropsychiatric symptoms (PCNPS), especially after infection by the Omicron strain, has not been adequately explored. Our pre-registered hypotheses are 1. chronic PCNPS in patients infected with SARS-CoV-2 over a year ago during the Omicron wave showed a similar clustering pattern with symptoms in patients infected with pre-Omicron strain; 2. these chronic PCNPS are associated with a) clinical risk factors, such as, severity of the acute infection; b) socioeconomic status e.g., level of deprivation; and c) pre-infection vaccination status. We assessed 1205 subjects using app-based questionnaires and cognitive tasks. Partial network analysis on chronic PCNPS in this cohort produced two major symptom clusters (cognitive complaint-fatigue cluster and anxiety-depression symptoms cluster) and a minor headache-dizziness symptoms cluster, like our pre-Omicron cohort. Subjects with high number of symptoms (4 or more) can be further grouped into two distinct phenotypes: a cognitive complaint-fatigue predominant phenotype (CF) and another with symptoms across multiple clusters (AD-CF). Multiple logistic regression showed that both phenotypes are predicted by the level of deprivation before infection (adjusted p-value for CF and AD-CF = 0.025 and 0.0054 respectively). While the severity of acute COVID (adjusted p-value = 0.023) and the number of pre-existing medical conditions predict only the CF phenotypes (adjusted p-value = 0.003), past suicidal ideas predict the AD-CF phenotype (adjusted p-value < 0.001). Pre-infection vaccination status did not predict either phenotype. Our finding suggests that we should recognize the heterogeneity under the umbrella of chronic PCNPS, and a holistic bio-psycho-social approach is essential in understanding them.

Spontaneous stereotypies (abnormal, repetitive, and seemingly goal-less behaviors) in captive animals resemble stereotypies documented in patients with neurodevelopmental disorders, including evidence of homologous cortico-striatal dysfunction and shared behavioral deficits. While environmental risk factors for stereotypies are well documented, their developmental pathophysiology remains unclear. However, as previously found for compulsive behavior, there is growing evidence that REDOX imbalance may be linked to stereotypy. To examine the nature of this relationship, we first tested whether plasma glutathione level, the gold-standard biomarker of REDOX imbalance, is predictive of stereotypy severity in N=19 C57BL/6 mice. After confirming the presence of this relationship, we used a proteomics approach (Olink) to identify a broader biomarker profile of dysfunction. We found expression of 9 proteins to correlate with plasma glutathione level, and expression of 15 proteins to correlate with stereotypy severity. A subset of these proteins additionally correlated with stereotypy severity in a validation cohort of CD1 mice (N=28). Further supporting a role for REDOX imbalance in the developmental pathophysiology of stereotypies, the identified proteins were associated with REDOX physiology, dopamine physiology, and stereotypy-presenting human neurodevelopmental disorders. These data suggest REDOX imbalance may contribute to the developmental pathophysiology of abnormal repetitive behaviors and highlight promising novel targets for intervention.

Anxiety and depressive disorders impose a major global burden, prompting interest in non-pharmacological interventions that may influence affective processes. Music exposure has often been reported to affect anxiety- and depression-like behaviors, but preclinical findings remain heterogeneous and have not been quantitatively synthesized. Prior work has also focused almost entirely on mean behavioral responses, largely overlooking inter-individual variability as a biologically meaningful dimension. We conducted a preregistered systematic review and multilevel meta-analysis of experimental studies testing music exposure in laboratory rodents. Following PRISMA and PRISMA-EcoEvo guidelines, we synthesized 298 effect sizes from 20 studies using multilevel models to account for non-independence among effect sizes. We quantified effects on mean behavior with the log response ratio (lnRR) and effects on variability with the log variability ratio (ln V R). Overall, music exposure was associated with a statistically significant reduction in anxiety- and depression-like behaviors, corresponding to an average decrease of about 18% relative to controls. This mean effect was detected across outcome types and life stages despite substantial heterogeneity. By contrast, music exposure did not produce a statistically significant overall change in inter-individual behavioral variability. Instead, variability responses were context dependent: behavioral assay type and music meta-genre significantly moderated ln V R, with anxiety-like assays tending to show increased variability and depression-like assays tending to show reduced variability under music exposure. These results suggest that music exposure reliably shifts average affect-related behavior without uniformly changing behavioral stability across individuals. Because the evidence comes mainly from short-term exposures in young adult laboratory rodents, generalization beyond similar contexts should remain cautious.

Suicide is an urgent public health crisis that claimed over 48,000 lives in the US in 2022. The importance of genetics in suicide risk has been established by classical twin and family studies, and confirmed with recent large genome-wide association studies (GWAS). While the GWAS are beginning to reveal genetic risk due to common variants each with small effect on liability, these results explain only a fraction of the genetic risk. As with other complex health conditions, some of this unexplained risk is likely due to rarer variants with larger effect on liability. Using whole genome sequencing (WGS) data from 1,054 population-ascertained Utah suicide deaths, we investigated intragenic deletions as a class of genomic variation highly likely to disrupt gene function. To minimize the chance of false positive results, studied deletions were limited to those found in three large publicly-available control datasets (1000 Genomes, GnomAD, and Centers for Common Disease Genomics). Additional internal replication also required deletions to occur at least twice in WGS from an initial cohort of 670 suicide deaths then again in a second cohort of 384 suicide deaths. All results meeting these filters were manually validated. There were 11 validated deletions with at least 2-fold increase in frequency over occurrence in controls (range 2.28 to 4.46). These results implicated genes associated with risk of mental health conditions (MPST, IL4R, CDH13), epilepsy (CLCA4), intellectual disability (ZNF44), neuronal function (OSBPL2), metabolic function (FBOX36), lipid metabolism (TM9SF3), immune related functions (PIPOX, IL4R), and transcriptional repression (ZHX3). SNPs in genes implicated by the deletions have also been associated with mental health conditions, neuronal function, immune response, and other critical biological pathways including neuroinflammation and cellular response to stress. Demographic and clinical associations of suicide deaths with specific genetic deletions, highlight the prevalence of mood, anxiety and bipolar disorders and variations in age at suicide death among affected individuals. This work is the largest genome-wide analyses of WGS variation in suicide deaths to date. Pending replication, results will guide future functional studies with the eventual goals of increased understanding of mechanisms leading to risk.