Multimodal integration of neuroimaging and genetic data for the diagnosis of mood disorders based on computer vision models.

Mood disorders, particularly major depressive disorder (MDD) and bipolar disorder (BD), are often underdiagnosed, leading to substantial morbidity. Harnessing the potential of emerging methodologies, we propose a novel multimodal fusion approach that integrates patient-oriented brain structural magnetic resonance imaging (sMRI) scans with DNA whole-exome sequencing (WES) data. Multimodal data fusion aims to improve the detection of mood disorders by employing established deep-learning architectures for computer vision and machine-learning strategies. We analyzed brain imaging genetic data of 321 East Asian individuals, including 147 patients with MDD, 78 patients with BD, and 96 healthy controls. We developed and evaluated six fusion models by leveraging common computer vision models in image classification: Vision Transformer (ViT), Inception-V3, and ResNet50, in conjunction with advanced machine-learning techniques (XGBoost and LightGBM) known for high-dimensional data analysis. Model validation was performed using a 10-fold cross-validation. Our ViT ⊕ XGBoost fusion model with MRI scans, genomic Single Nucleotide polymorphism (SNP) data, and unweighted polygenic risk score (PRS) outperformed baseline models, achieving an incremental area under the curve (AUC) of 0.2162 (32.03% increase) and 0.0675 (+8.19%) and incremental accuracy of 0.1455 (+25.14%) and 0.0849 (+13.28%) compared to SNP-only and image-only baseline models, respectively. Our findings highlight the opportunity to refine mood disorder diagnostics by demonstrating the transformative potential of integrating diverse, yet complementary, data modalities and methodologies.

Ndufs4 KO mice: A model to study comorbid mood disorders associated with mitochondrial dysfunction.

The Ndufs4 knockout (KO) mouse is a validated and robust preclinical model of mitochondrial diseases (specifically Leigh syndrome), that displays a narrow window of relative phenotypical normality, despite its inherent mitochondrial complex I dysfunction and severe phenotype. Preclinical observations related to psychiatric comorbidities that arise in patients with mitochondrial diseases and indeed in Leigh syndrome are, however, yet to be investigated in this model. Strengthening this narrative is the fact that major depression and bipolar disorder are known to present with deficits in mitochondrial function. We therefore screened the behavioural profile of male and female Ndufs4 KO mice (relative to heterozygous; HET and wildtype; WT mice) between postnatal days 28 and 35 for locomotor, depressive- and anxiety-like alterations and linked it with selected brain biomarkers, viz. serotonin, kynurenine, and redox status in brain areas relevant to psychiatric pathologies (i.e., prefrontal cortex, hippocampus, and striatum). The Ndufs4 KO mice initially displayed depressive-like behaviour in the tail suspension test on PND31 but not on PND35 in the forced swim test. In the mirror box test, increased risk resilience was observed. Serotonin levels of KO mice, compared to HET controls, were increased on PND36, together with increased tryptophan to serotonin and kynurenine turnover. Kynurenine to kynurenic acid turnover was however decreased, while reduced versus oxidized glutathione ratio (GSH/GSSG) was increased. When considering the comorbid psychiatric traits of patients with mitochondrial disorders, this work elaborates on the neuropsychiatric profile of the Ndufs KO mouse. Secondly, despite locomotor differences, Ndufs4 KO mice present with a behavioural profile not unlike rodent models of bipolar disorder, namely variable mood states and risk-taking behaviour. The model may elucidate the bio-energetic mechanisms underlying mood disorders, especially in the presence of mitochondrial disease. Studies are however required to further validate the model's translational relevance.

Evaluation of bidirectional relationships between risk preference and mood disorders: A 2-sample Mendelian randomization study.

BACKGROUND: Risk preference is often defined as the tendency to engage in risky activities. Increasing evidence shows that risk preference is associated with mood disorders. However, the causality and direction of this association are not clear. METHODS: Genome-wide association study summary data of risk preference in 939,908 participants from UK Biobank and 23andMe were used to identify general risk preference. Data for 413,466 individuals taken from The Psychiatric Genomics Consortium were used to identify bipolar disorder (BP). Data for 807,553 individuals taken from The Psychiatric Genomics Consortium were used to identify major depressive disorder (MDD). The weighted median, inverse-variance weighting, and Mendelian randomization-Egger methods were used for the Mendelian randomization analysis to estimate a causal effect and detect directional pleiotropy. RESULTS: GWAS summary data were obtained from three combined samples, containing 939,908, 413,466 and 807,553 individuals of European ancestry. Mendelian randomization evidence suggested that risk preference increased the onset of BP, and BP also increased risk preference (P < 0.001). In contrast, there were no reliable results to describe the relationship of risk preference with MDD (P > 0.05). Furthermore, there was no significant relationship between MDD and risk preference. CONCLUSION: Using large-scale GWAS data, robust evidence supports a mutual relationship between risk preference and BP, but no relationship between risk preference and MDD was observed. This study indicates a potential marker for the early identification of MDD and BP. Additionally, it shows that reducing risk preferences for patients with BP may be a valuable intervention for treating BP.

Whole blood mitochondrial copy number in clinical populations with mood disorders: A meta-analysis: Blood mitochondrial copy number and mood disorders.

Major depressive disorder (MDD) and bipolar disorder (BD), are globally prevalent, contributing to significant disease burden and adverse health outcomes. These mood disorders are associated with changes in many aspects of brain reward pathways, yet cellular and molecular changes in the brain are not readily available in clinical populations. Therefore, the use of biomarkers as proxies for changes in the brain are necessary. The proliferation of mitochondria in blood has emerged as a potentially useful biomarker, yet a clear consensus on how these mood disorders impact mitochondrial DNA copy number (mtDNAcn) has not been reached. To determine the current available consensus on the relationship of mood disorder diagnosis and blood mtDNcn, we performed a meta-analysis of available literature measuring this biomarker. Following PRISMA guidelines for a systematic search, 22 papers met inclusion criteria for meta-analysis (10 MDD, 10 BD, 2 both MDD and BD). We extracted demographic, disorder, and methodological information with mtDNAcn. Using the metafor package for R, calculated effect sizes were used in random effects or meta regression models for MDD and BD. Overall, our data suggest blood mtDNAcn may be a useful biomarker for mood disorders, with MDD and BD Type II associated with higher mtDNAcn, and BD Type I associated with lower mtDNAcn. Initially, we observed a trending increase in mtDNAcn in patients with MDD, which reached significance when one study with outlying demographic characteristics was excluded. Subgroup and meta-regression analysis indicated the relationship between mtDNAcn and diagnosis in patients with BD is dependent on BD type, while no relationship is detectable when BD types are mixed. Further study of blood mtDNAcn could predict downstream health outcomes or treatment responsivity in individuals with mood disorders.

Mitochondrial health, NLRP3 inflammasome activation, and white matter integrity in adolescent mood disorders: A pilot study.

Adolescence is a particularly important period for brain development and is also when mood disorders typically emerge. Several psychiatric illnesses exhibit mitochondrial dysfunction, elevated inflammation, and impaired white matter integrity. This study explored the intersection of mitochondrial health, NLRP3 inflammasome activation, and white matter integrity in a small cohort of 29 adolescent patients with mood disorders (bipolar disorder (BD): n = 11, major depressive disorder (MDD): n = 19) and 19 healthy controls. In this sample, adolescents with mood disorders showed lower fractional anisotropy of the ventral cingulum bundle than healthy controls. Across all adolescents, we demonstrated a significant relationship between mitochondrial electron transport chain gene expression, and NLRP3 inflammasome gene expression and activation. Furthermore, circulating cell free mitochondrial DNA was associated with lower white matter integrity in the anterior thalamic radiation. Exploratory subgroup analyses revealed that adolescents with bipolar disorder exhibited lower levels of mitochondrial gene expression and volume, along with increased sensitivity to NLRP3 inflammasome activation compared to adolescents with unipolar depression. Overall, our results reveal relationships between peripherally-measured endpoints of mitochondrial health and NLRP3 inflammasome activation, and centrally measured endpoints of white matter integrity in adolescents. Together with subtle patterns of aberrant neural and biological structure and function in association with mood disorder diagnoses, these results may shed light on the pathophysiology of disease in this early phase of illness.

An overview of human single-cell RNA sequencing studies in neurobiological disease.

Neurobiological disorders are highly prevalent medical conditions that contribute to significant morbidity and mortality. Single-cell RNA sequencing (scRNA-seq) is a technique that measures gene expression in individual cells. In this review, we survey scRNA-seq studies of tissues from patients suffering from neurobiological disease. This includes postmortem human brains and organoids derived from peripheral cells. We highlight a range of conditions, including epilepsy, cognitive disorders, substance use disorders, and mood disorders. These findings provide new insights into neurobiological disease in multiple ways, including discovering novel cell types or subtypes involved in disease, proposing new pathophysiological mechanisms, uncovering novel drug targets, or identifying potential biomarkers. We discuss the quality of these findings and suggest potential future directions and areas open for additional research, including studies of non-cortical brain regions and additional conditions such as anxiety disorders, mood disorders, and sleeping disorders. We argue that additional scRNA-seq of tissues from patients suffering from neurobiological disease could advance our understanding and treatment of these conditions.

Psychopathology in adults with copy number variants.

BACKGROUND: Copy number variants (CNVs) have been associated with the risk of schizophrenia, autism and intellectual disability. However, little is known about their spectrum of psychopathology in adulthood. METHODS: We investigated the psychiatric phenotypes of adult CNV carriers and compared probands, who were ascertained through clinical genetics services, with carriers who were not. One hundred twenty-four adult participants (age 18-76), each bearing one of 15 rare CNVs, were recruited through a variety of sources including clinical genetics services, charities for carriers of genetic variants, and online advertising. A battery of psychiatric assessments was used to determine psychopathology. RESULTS: The frequencies of psychopathology were consistently higher for the CNV group compared to general population rates. We found particularly high rates of neurodevelopmental disorders (NDDs) (48%), mood disorders (42%), anxiety disorders (47%) and personality disorders (73%) as well as high rates of psychiatric multimorbidity (median number of diagnoses: 2 in non-probands, 3 in probands). NDDs [odds ratio (OR) = 4.67, 95% confidence interval (CI) 1.32-16.51; p = 0.017) and psychotic disorders (OR = 6.8, 95% CI 1.3-36.3; p = 0.025) occurred significantly more frequently in probands (N = 45; NDD: 39[87%]; psychosis: 8[18%]) than non-probands (N = 79; NDD: 20 [25%]; psychosis: 3[4%]). Participants also had somatic diagnoses pertaining to all organ systems, particularly conotruncal cardiac malformations (in individuals with 22q11.2 deletion syndrome specifically), musculoskeletal, immunological, and endocrine diseases. CONCLUSIONS: Adult CNV carriers had a markedly increased rate of anxiety and personality disorders not previously reported and high rates of psychiatric multimorbidity. Our findings support in-depth psychiatric and medical assessments of carriers of CNVs and the establishment of multidisciplinary clinical services.

Investigating the potential impact of PCSK9-inhibitors on mood disorders using eQTL-based Mendelian randomization.

Prescription of PCSK9-inhibitors has increased in recent years but not much is known about its off-target effects. PCSK9-expression is evident in non-hepatic tissues, notably the brain, and genetic variation in the PCSK9 locus has recently been shown to be associated with mood disorder-related traits. We investigated whether PCSK9 inhibition, proxied by a genetic reduction in expression of PCSK9 mRNA, might have a causal adverse effect on mood disorder-related traits. We used genetic variants in the PCSK9 locus associated with reduced PCSK9 expression (eQTLs) in the European population from GTEx v8 and examined the effect on PCSK9 protein levels and three mood disorder-related traits (major depressive disorder, mood instability, and neuroticism), using summary statistics from the largest European ancestry genome-wide association studies. We conducted summary-based Mendelian randomization analyses to estimate the causal effects, and attempted replication using data from eQTLGen, Brain-eMETA, and the CAGE consortium. We found that genetically reduced PCSK9 gene-expression levels were significantly associated with reduced PCSK9 protein levels but not with increased risk of mood disorder-related traits. Further investigation of nearby genes demonstrated that reduced USP24 gene-expression levels was significantly associated with increased risk of mood instability (p-value range = 5.2x10-5-0.03), and neuroticism score (p-value range = 2.9x10-5-0.02), but not with PCSK9 protein levels. Our results suggest that genetic variation in this region acts on mood disorders through a PCSK9-independent pathway, and therefore PCSK9-inhibitors are unlikely to have an adverse impact on mood disorder-related traits.

Comparing the Relationships of Genetically Proxied PCSK9 Inhibition With Mood Disorders, Cognition, and Dementia Between Men and Women: A Drug-Target Mendelian Randomization Study.

Background PCSK9 (proprotein convertase subtilisin/kexin type 9) inhibitors are important therapeutic options for reducing cardiovascular disease risk; however, questions remain regarding potential differences in the neuropsychiatric impact of long-term PCSK9 inhibition between men and women. Methods and Results Using PCSK9 gene single-nucleotide polymorphisms from European ancestry-based genome-wide association studies of low-density lipoprotein cholesterol (N=1 320 016), circulating PCSK9 protein levels (N=10 186), tissue-specific PCSK9 gene expression, sex-specific genome-wide association studies of anxiety, depression, cognition, insomnia, and dementia (ranging from 54 321 to 194 174), we used drug-target inverse variance-weighted Mendelian randomization (MR) and complementary MR methods (MR Egger, weighted median, and weighted mode) to investigate potential neuropsychiatric consequences of genetically proxied PCSK9 inhibition in men and women. We failed to find evidence surpassing correction for multiple comparisons of relationships between genetically proxied PCSK9 inhibition and the risk for the 12 neuropsychiatric end points in either men or women. Drug-target analyses were generally well-powered to detect effect estimates at several hypothesized thresholds for both combined-sex and sex-specific end points, especially analyses using PCSK9 instruments derived from protein and expression quantitative trait loci. Further, MR estimates across complementary MR methods and additional models using genetic instruments derived from circulating PCSK9 protein levels and tissue-specific PCSK9 expression were in alignment, strengthening causal inference. Conclusions Genetically proxied PCSK9 inhibition showed a neutral neuropsychiatric side effect profile with no major sex-specific differences. Given statistical power considerations, replication with larger samples, as well as data from other ancestral populations, are necessary. These findings may have important clinical implications for lipid-lowering drug-prescribing practices and side effect monitoring of approved and future PCSK9 therapies.

Genetics As a Key to Understand Mood Disorders.

Mood disorders are mental health class that health professionals use to broadly describe all types of depression and bipolar disorders. Heritability of both bipolar and depressive disorder is in the range of 50%, which means that genes alone are not sufficient to explain all the cases of mood disorders, but they confer a substantial risk which is combined with environmental stressors to determine the final illness. In the recent years, a number of studies considered the idea to develop a strategic plan to employ the tools of genetics to advance the understanding, treatment, and outcomes for mood disorders.

Stigmatizing attitudes toward Disruptive Mood Dysregulation Disorder (DMDD) in parents vs. non-parents: Effects of medication and genetic etiology.

Stigmatizing attitudes toward children with psychopathology represent a barrier to treatment and well-being, yet almost no research has investigated what contributes to these attitudes. This study examines the effects of medication treatment and genetic etiology on stigmatizing attitudes toward a relatively new and controversial disorder-Disruptive Mood Dysregulation Disorder (DMDD). Participants (159 parents, 225 non-parents) completed a vignette study on Amazon's Mechanical Turk (MTurk) in which a child displayed behaviors consistent with DMDD. The child was described as either taking psychiatric medication or not, and the vignette described the child's condition as either genetic or did not mention etiology. Participants who were parents reported greater stigma when the etiology (genetic prime vs. no prime) matched the perceived appropriate treatment (medication vs. no medication). Among parents, a child treated with medication who had a genetic disorder, and a child who was not treated with medication and for whom genetic etiology was not primed, were most stigmatized. No differences emerged among non-parents. These findings highlight the importance of considering multiple factors (parental status, congruence between treatment and perceived disorder etiology) when investigating mental health stigma and underscore the need to further investigate such nuances to inform anti-stigma interventions.

Ventral prefrontal serotonin 1A receptor binding: a neural marker of vulnerability for mood disorder and suicidal behavior?

Mood disorders and suicidal behavior have moderate heritability and are associated with altered corticolimbic serotonin 1A receptor (5-HT1A) brain binding. However, it is unclear whether this reflects genetic effects or epigenetic effects of childhood adversity, compensatory mechanisms, or illness stress-related changes. We sought to separate such effects on 5-HT1A binding by examining high familial risk individuals (HR) who have passed through the age of greatest risk for psychopathology onset with and without developing mood disorder or suicidal behavior. PET imaging quantified 5-HT1A binding potential BPND using [11C]CUMI-101 in healthy volunteers (HV, N = 23) and three groups with one or more relatives manifesting early-onset mood disorder and suicide attempt: 1. unaffected HR (N = 23); 2. HR with lifetime mood disorder and no suicide attempt (HR-MOOD, N = 26); and 3. HR-MOOD with previous suicide attempt (HR-MOOD + SA, N = 20). Findings were tested in an independent cohort not selected for family history (HV, MOOD, and MOOD + SA, total N = 185). We tested for regional BPND differences and whether brain-wide patterns distinguished between groups. Low ventral prefrontal 5-HT1A BPND was associated with lifetime mood disorder diagnosis and suicide attempt, but only in subjects with a family history of mood disorder and suicide attempt. Brain-wide 5-HT1A BPND patterns including low ventral prefrontal and mesiotemporal cortical binding distinguished HR-MOOD + SA from HV. A biological endophenotype associated with resilience was not observed. Low ventral prefrontal 5-HT1A BPND may reflect familial mood disorder and suicide-related pathology. Further studies are needed to determine if higher ventral prefrontal 5-HT1A BPND confers resilience, reducing risk of suicidal behavior in the context of familial risk, and thereby offer a potential prevention target.

Identifying Pediatric Mood Disorders From Transdiagnostic Polygenic Risk Scores: A Study of Children and Adolescents.

Objective: Mood disorders often co-occur with attention-deficit/hyperactive disorder (ADHD), disruptive behavior disorders (DBDs), and aggression. We aimed to determine if polygenic risk scores (PRSs) based on external genome-wide association studies (GWASs) of these disorders could improve genetic identification of mood disorders.Methods: We combined 6 independent family studies that had genetic data and diagnoses for mood disorders that were made using different editions of the Diagnostic and Statistical Manual of Mental Disorders (DSM). We identified mood disorders, either concurrently or in the future, in participants between 6 and 17 years of age using PRSs calculated using summary statistics of GWASs for ADHD, ADHD with DBD, major depressive disorder (MDD), bipolar disorder (BPD), and aggression to compute PRSs.Results: In our sample of 485 youths, 356 (73%) developed a subthreshold or full mood disorder and 129 (27%) did not. The cross-validated mean areas under the receiver operating characteristic curve (AUCs) for the 7 models identifying participants with any mood disorder ranged from 0.552 in the base model of age and sex to 0.648 in the base model + all 5 PRSs. When included in the base model individually, the ADHD PRS (OR = 1.65, P < .001), Aggression PRS (OR = 1.27, P = .02), and MDD PRS (OR = 1.23, P = .047) were significantly associated with the development of any mood disorder.Conclusions: Using PRSs for ADHD, MDD, BPD, DBDs, and aggression, we could modestly identify the presence of mood disorders. These findings extend evidence for transdiagnostic genetic components of psychiatric illness and demonstrate that PRSs calculated using traditional diagnostic boundaries can be useful within a transdiagnostic framework.

Characterizing mood disorders in the AFFECT study: a large, longitudinal, and phenotypically rich genetic cohort in the US.

There has recently been marked progress in identifying genetic risk factors for major depression (MD) and bipolar disorder (BD); however, few systematic efforts have been made to elucidate heterogeneity that exists within and across these diagnostic taxa. The Affective disorders, Environment, and Cognitive Trait (AFFECT) study presents an opportunity to identify and associate the structure of cognition and symptom-level domains across the mood disorder spectrum in a prospective study from a diverse US population.Participants were recruited from the 23andMe, Inc research participant database and through social media; self-reported diagnosis of MD or BD by a medical professional and medication status data were used to enrich for mood-disorder cases. Remote assessments were used to acquire an extensive range of phenotypes, including mood state, transdiagnostic symptom severity, task-based measures of cognition, environmental exposures, personality traits. In this paper we describe the study design, and the demographic and clinical characteristics of the cohort. In addition we report genetic ancestry, SNP heritability, and genetic correlations with other large cohorts of mood disorders.A total of 48,467 participants were enrolled: 14,768 with MD, 9864 with BD, and 23,835 controls. Upon enrollment, 47% of participants with MD and 27% with BD indicated being in an active mood episode. Cases reported early ages of onset (mean = 13.2 and 14.3 years for MD and BD, respectively), and high levels of recurrence (78.6% and 84.9% with >5 episodes), psychotherapy, and psychotropic medication use. SNP heritability on the liability scale for the ascertained MD participants (0.19-0.21) was consistent with the high level of disease severity in this cohort, while BD heritability estimates (0.16-0.22) were comparable to reports in other large scale genomic studies of mood disorders. Genetic correlations between the AFFECT cohort and other large-scale cohorts were high for MD but not for BD. By incorporating transdiagnostic symptom assessments, repeated measures, and genomic data, the AFFECT study represents a unique resource for dissecting the structure of mood disorders across multiple levels of analysis. In addition, the fully remote nature of the study provides valuable insights for future virtual and decentralized clinical trials within mood disorders.

The molecular pathophysiology of mood disorders: From the analysis of single molecular layers to multi-omic integration.

Next-generation sequencing now enables the rapid and affordable production of reliable biological data at multiple molecular levels, collectively referred to as "omics". To maximize the potential for discovery, computational biologists have created and adapted integrative multi-omic analytical methods. When applied to diseases with traceable pathophysiology such as cancer, these new algorithms and statistical approaches have enabled the discovery of clinically relevant molecular mechanisms and biomarkers. In contrast, these methods have been much less applied to the field of molecular psychiatry, although diagnostic and prognostic biomarkers are similarly needed. In the present review, we first briefly summarize main findings from two decades of studies that investigated single molecular processes in relation to mood disorders. Then, we conduct a systematic review of multi-omic strategies that have been proposed and used more recently. We also list databases and types of data available to researchers for future work. Finally, we present the newest methodologies that have been employed for multi-omics integration in other medical fields, and discuss their potential for molecular psychiatry studies.

Contribution of Age, Brain Region, Mood Disorder Pathology, and Interindividual Factors on the Methylome of Human Microglia.

BACKGROUND: Transcriptome studies have revealed age-, disease-, and region-associated microglial phenotypes reflecting changes in microglial function during development, aging, central nervous system homeostasis, and pathology. The molecular mechanisms that contribute to these transcriptomic changes are largely unknown. The aim of this study was to characterize the DNA methylation landscape of human microglia and the factors that contribute to variations in the microglia methylome. We hypothesized that both age and brain region would have a large impact on DNA methylation in microglia. METHODS: Microglia from postmortem brain tissue of four different brain regions of 22 donors, encompassing 1 patient with schizophrenia, 13 patients with mood disorder pathology, and 8 control subjects, were isolated and assayed using a genome-wide methylation array. RESULTS: We found that human microglial cells have a methylation profile distinct from bulk brain tissue and neurons, and age explained a considerable part of the variation. Additionally, we showed that interindividual factors had a much larger effect on the methylation landscape of microglia than brain region, which was also seen at the transcriptome level. In our exploratory analysis, we found various differentially methylated regions that were related to disease status (mood disorder vs. control). This included differentially methylated regions that are linked to gene expression in microglia, as well as to myeloid cell function or neuropsychiatric disorders. CONCLUSIONS: Although based on relatively small samples, these findings suggest that the methylation profile of microglia is responsive to interindividual variations and thereby plays an important role in the heterogeneity of microglia observed at the transcriptome level.

A meta-analysis of polygenic risk scores for mood disorders, neuroticism, and schizophrenia in antidepressant response.

About two-thirds of patients with major depressive disorder (MDD) fail to achieve symptom remission after the initial antidepressant treatment. Despite a role of genetic factors was proven, the specific underpinnings are not fully understood yet. Polygenic risk scores (PRSs), which summarise the additive effect of multiple risk variants across the genome, might provide insights into the underlying genetics. This study aims to investigate the possible association of PRSs for bipolar disorder, MDD, neuroticism, and schizophrenia (SCZ) with antidepressant non-response or non-remission in patients with MDD. PRSs were calculated at eight genome-wide P-thresholds based on publicly available summary statistics of the largest genome-wide association studies. Logistic regressions were performed between PRSs and non-response or non-remission in six European clinical samples, adjusting for age, sex, baseline symptom severity, recruitment sites, and population stratification. Results were meta-analysed across samples, including up to 3,637 individuals. Bonferroni correction was applied. In the meta-analysis, no result was significant after Bonferroni correction. The top result was found for MDD-PRS and non-remission (p = 0.004), with patients in the highest vs. lowest PRS quintile being more likely not to achieve remission (OR=1.5, 95% CI=1.11-1.98, p = 0.007). Nominal associations were also found between MDD-PRS and non-response (p = 0.013), as well as between SCZ-PRS and non-remission (p = 0.035). Although PRSs are still not able to predict non-response or non-remission, our results are in line with previous works; methodological improvements in PRSs calculation may improve their predictive performance and have a meaningful role in precision psychiatry.

Molecular Link between Circadian Rhythmicity and Mood Disorders.

BACKGROUND: The internal clock is driven by circadian genes [e.g., Clock, Bmal1, Per1-3, Cry1-2], hormones [e.g., melatonin, cortisol], as well as zeitgeber ['synchronisers']. Chronic disturbances in the circadian rhythm in Objectives: The aim of this review is to summarise the current knowledge and literature regarding circadian rhythms in the context of mood disorders, focussing on the role of circadian genes, hormones, and neurotransmitters. METHODS: The review presents the current knowledge and literature regarding circadian rhythms in mood disorders using the Pubmed database. Articles with a focus on circadian rhythms and mood disorders [n=123], particularly from 1973 to 2020, were included. RESULTS: The article suggests a molecular link between disruptions in the circadian rhythm and mood disorders. Circadian disturbances, caused by the dysregulation of circadian genes, hormones, and neurotransmitters, often result in a clinical picture resembling depression. CONCLUSION: The article suggests a molecular link between disruptions in the circadian rhythm and mood disorders. Circadian disturbances, caused by the dysregulation of circadian genes, hormones, and neurotransmitters, often result in a clinical picture resembling depression.