New insights from the last decade of research in psychiatric genetics: discoveries, challenges and clinical implications

Polygenic overlap between subjective well-being and psychiatric disorders and cross-ancestry validation

Subjective well-being (SWB) is important for understanding human behaviour and health. Although the connection between SWB and psychiatric disorders has been studied, common genetic mechanisms remain unclear. This study aimed to explore the genetic relationship between SWB and psychiatric disorders. Bivariate causal mixture modelling (MiXeR), polygenic risk score (PRS) and Mendelian randomization (MR) analyses showed substantial polygenic overlap and associations between SWB and the psychiatric disorders. Subsequent replication studies in East Asian populations confirmed the polygenic overlap between schizophrenia and SWB. The conditional and conjunctional false discovery rate analyses identified additional or shared genetic loci associated with SWB or psychiatric disorders. Functional annotation revealed enrichment of specific brain tissues and genes associated with SWB. The identified genetic loci showed cross-ancestry transferability between the European and Korean populations. Our findings provide valuable insights into the common genetic mechanisms underlying SWB and psychiatric disorders.

Psychological state at the time of psychiatric genetic counseling impacts patient empowerment: A pre-post analysis

Psychiatric genetic counseling (GC) has been associated with patient-reported increases in empowerment (perceived control, emotional regulation, and hope). We sought to evaluate the extent to which patients' psychological state at the time of GC is related to changes in empowerment. Participants with a history of major depressive disorder and/or bipolar disorder that had been refractory to treatment underwent psychiatric GC remotely from 2022 to 2023. GC was performed by four genetic counselors and included discussion of perceived causes of illness, multifactorial inheritance, and protective factors. Empowerment, depression, and anxiety were measured immediately prior to GC via online survey by the GCOS-16, PHQ-9, and GAD-7, respectively. Empowerment was re-assessed 2 weeks later. In total, 66/161 (41.0%) invited individuals completed both the baseline and follow-up surveys. Participants completing both surveys were 54.6% female, 84.8% white, and ranged in age from 22 to 78 years (mean = 54.8 years). Overall, a significant change in mean empowerment was not observed (p = 0.38); however, there were moderating effects by baseline psychological state. A multiple linear regression model incorporating PHQ-9, GAD-7 and baseline GCOS-16 score predicted change in empowerment with a large effect (F = 5.49, R2 = 0.21, p < 0.01). A higher score on the PHQ-9 was associated with decreases in empowerment from pre to post GC. Higher scores on the GAD-7 and lower baseline GCOS-16 scores were associated with increases in empowerment. Further, two-way ANOVA was conducted to assess change in empowerment between subgroups based on the level of anxiety and depression. Those with low depression and high anxiety reported significant increases in empowerment (F = 6.64, p = 0.01). These findings suggest that psychiatric GC may be especially helpful to individuals experiencing anxiety and low baseline empowerment. Alternative approaches may be needed to best meet the needs of those experiencing significant depression.

Genetic insights into the role of mitochondria-related genes in mental disorders: An integrative multi-omics analysis

BACKGROUND

Mitochondrial dysfunction has been implicated in the development of mental disorders, yet the underlying mechanisms remain unclear. In this study, we employed summary-data-based Mendelian randomization (SMR) analysis to explore the associations between mitochondrial-related genes and seven common mental disorders across gene expression, DNA methylation, and protein levels.

METHOD

Summary statistics from genome-wide association studies were used for seven mental disorders, including attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder, anxiety, bipolar disorder, major depressive disorder, post-traumatic stress disorder, and schizophrenia (SCZ). Instrumental variables associated with 1136 mitochondria-related genes were derived from summary statistics for DNA methylation, gene expression, and protein quantitative trait loci. SMR analyses and colocalization analyses were then conducted across these three biological levels to explore the associations with each of the seven mental disorders.

RESULTS

We identified mitochondria-related genes associated with mental disorders with multi-omics evidence: RMDN1 for ADHD, and ACADVL, ETFA, MMAB, and PPA2 for SCZ. Specifically, an increase of one standard deviation in the level of RMDN1 was linked to a 12 % decrease in the risk of developing ADHD (OR = 0.88, 95 % CI: 0.83-0.94). Increased levels of ETFA (OR = 1.79, 95 % CI: 1.24-2.60) and MMAB (OR = 1.10, 95 % CI: 1.05-1.16) were significantly associated with increased risk of SCZ. Conversely, high levels of ACADVL (OR = 0.50, 95 % CI: 0.33-0.77) and PPA2 (OR = 0.68, 95 % CI: 0.55-0.85) were associated with a reduced risk of SCZ.

CONCLUSIONS

These findings suggested that dysfunction in mitochondria-related genes may underlie the molecular mechanisms of ADHD and SCZ, providing novel biomarkers for diagnosis and therapeutic interventions.

Novel multimodal precision medicine approaches and the relevance of developmental trajectories in bipolar disorder

There is a pressing need to establish objective measures to improve diagnosis, prediction, prevention and treatment of bipolar disorder (BD). Multimodal artificial intelligence (AI) tools could provide these means by incorporating various layers of data orthogonally related to BD, including genomics and other omics, environmental exposures, imaging measures, electronic health records, cognition, sensing devices and clinical variables. These rapidly evolving AI models hold promise to capture the multidimensional complexity of BD and delineate clinically relevant developmental trajectories that could guide clinical care and therapeutic strategies. In this review, we describe the potential of mapping developmental trajectories underlying BD, outline how novel multimodal models could improve the prediction of BD and related outcomes, and discuss specific clinical use cases and key ethical and practical challenges regarding the development and potential implementation of these multimodal AI solutions to advance precision medicine approaches in BD.

Psychiatric Genetics in Clinical Practice: Essential Knowledge for Mental Health Professionals

OBJECTIVE

The authors provide recommendations on incorporating recent advances in psychiatric genetics into clinical practice for mental health clinicians.

METHOD

The International Society for Psychiatric Genetics Education Committee met monthly to come to a consensus on priority topics in psychiatric genetics. Topics were then assigned to small teams of subspecialty experts to summarize the current knowledge base and create an illustrative clinical case. Topics included, familial aggregation, common and rare genetic variants, epigenetics, gene-environment interactions, pharmacogenomics, genetic counseling, and ethical and social implications. Each section was reviewed and revised by all committee members and then finalized by the Committee Chair.

RESULTS

Key findings highlight the importance of understanding the genetic architecture of psychiatric disorders, the potential applications of genetic information in risk assessment, diagnosis, treatment selection, and patient education, as well as the ethical and social considerations surrounding the use of genetic data. The committee emphasizes the need for a nuanced approach that integrates genetic factors with environmental and experiential factors in a holistic model of care.

CONCLUSION

As psychiatric genetics continues to evolve rapidly, mental health clinicians must stay informed about the latest findings and their clinical implications. Ongoing education, collaboration with genetics professionals, and effective communication strategies are crucial to harness the power of genetics while avoiding potential pitfalls such as genetic determinism and stigma. The committee recommends a balanced perspective that recognizes the complex interplay of genetic and non-genetic factors in shaping mental health outcomes.

Admixed gene expression models expand molecular and neurological insights into 6 major psychiatric disorders

Our understanding of the influence of ancestral background on genetically determined expression remains limited, especially when gene expression models are applied to studies from different or multiple populations. We performed transcriptome wide association studies (TWAS) in 6 different psychiatric conditions, leveraging gene expression models trained in cohorts with different proportions of African, European, and Indigenous American genetic ancestries. For comparison we repeated each TWAS using a model trained in individuals of predominantly European ancestry. We identified 1,416 statistically significant TWAS associations (FDR p < 0.05) across the 6 diagnoses, of which 62% were uniquely detected by the admixed gene models. We observed > 92% correlation in the gene-level effects on disease risk, a statistic that remained robust for TWAS results that only reached statistical significance in one population. Using admixed gene expression models validated and greatly extended the yield of TWAS. The resulting transcriptomic signatures implicated neuroimaging features associated with diagnostic symptoms.

MRI-based cortical gray/white matter contrast in young adults who endorse psychotic experiences or are at genetic risk for psychosis

Research has reported group-level differences in cortical grey/white matter contrast (GWC) in individuals with psychotic disorders. However, no studies to date have explored GWC in individuals at elevated risk for psychosis. In this study, we examined brain microstructure differences between young adults with psychotic-like experiences or a high genetic risk for psychosis and unaffected individuals. Moreover, we investigated the association between GWC and the number of and experiences of psychosis-like symptoms. The sample was obtained from the Avon Longitudinal Study of Parents and Children (ALSPAC): the psychotic experiences study, consisting of young adults with psychotic-like symptoms (n = 119) and unaffected individuals (n = 117), and the schizophrenia recall-by-genotype study, consisting of individuals with a high genetic risk for psychosis (n = 95) and those with low genetic risk for psychosis (n = 95). Statistical analyses were performed using FSL's Permutation Analysis of Linear Models (PALM), controlling for age and sex. The results showed no statistically significant differences in GWC between any of the groups and no significant associations between GWC and the number and experiences of psychosis-like symptoms. In conclusion, the results indicate there are no differences in GWC in individuals with high, low or no risk for psychosis.

Contrasting genetic predisposition and diagnosis in psychiatric disorders: A multi-omic single-nucleus analysis of the human OFC

Psychiatric disorders like schizophrenia, bipolar disorder, and major depressive disorder exhibit substantial genetic and clinical overlap. However, their molecular architecture remains elusive due to their polygenic nature and complex brain cell interactions. We integrated clinical data with genetic susceptibility to investigate gene expression and chromatin accessibility in the orbitofrontal cortex of 92 postmortem human brain samples at the single-nucleus (sn) level. Using snRNA-seq and snATAC-seq, we analyzed ~800,000 and 400,000 nuclei, respectively. We observed cell-type-specific dysregulation related to clinical diagnosis and genetic risk. Dysregulation in gene expression and chromatin accessibility associated with diagnosis was pronounced in excitatory neurons. Conversely, genetic risk predominantly affected glial and endothelial cells. Notably, INO80E and HCN2 genes exhibited dysregulation in excitatory neurons' superficial layers 2/3 influenced by schizophrenia polygenic risk. This study unveils the complex genetic and epigenetic landscape of psychiatric disorders, emphasizing the importance of cell-type-specific analyses in understanding their pathogenesis and contrasting genetic predisposition with clinical diagnosis.

Childhood trajectories of emotional and behavioral difficulties are related to polygenic liability for mood and anxiety disorders

BACKGROUND

Symptoms related to mood and anxiety disorders (emotional disorders) often present in childhood and adolescence. Some of the genetic liability for mental disorders, and emotional and behavioral difficulties seems to be shared. Yet, it is unclear how genetic liability for emotional disorders and related traits influence trajectories of childhood behavioral and emotional difficulties, and if specific developmental patterns are associated with higher genetic liability for these disorders.

METHODS

This study uses data from a genotyped sample of children (n = 54,839) from the Norwegian Mother, Father, and Child Cohort Study (MoBa). We use latent growth models (1.5-5 years) and latent profile analyses (1.5-8 years) to quantify childhood trajectories and profiles of emotional and behavioral difficulties and diagnoses. We examine associations between these trajectories and profiles with polygenic scores for bipolar disorder (PGSBD), anxiety (PGSANX), depression (PGSDEP), and neuroticism (PGSNEUR).

RESULTS

Associations between PGSDEP, PGSANX, and PGSNEUR, and emotional and behavioral difficulties in childhood were more persistent than age-specific across early childhood (1.5-5 years). Higher PGSANX and PGSDEP were associated with steeper increases in behavioral difficulties across early childhood. Latent profile analyses identified five profiles with different associations with emotional disorder diagnosis. All PGS were associated with the probability of classification into profiles characterized by some form of difficulties (vs. a normative reference profile), but only PGSBD was uniquely associated with a single developmental profile.

CONCLUSIONS

Genetic risk for mood disorders and related traits contribute to both a higher baseline level of, and a more rapid increase in, emotional and behavioral difficulties across early and middle childhood, with some indications for disorder-specific profiles. Our findings may inform research on developmental pathways to emotional disorders and the improvement of initiatives for early identification and targeted intervention.

A framework for understanding adverse adolescent experiences

Adolescence (ages 10-24) is characterized by cognitive, behavioural and social development. Childhood environments are typically centred on home and care settings, whereas adolescents increasingly engage with peer and community environments. These changing environments confer risks of experiencing specific adversities at different ages. Despite the unique characteristics of adversities in adolescence and potential associations with lifespan outcomes, few frameworks exist to systematize adversities in adolescents. Here we review current research and propose an approach specific to this developmental period: the adverse adolescent experiences (AAEs) framework. Building on existing models (for example, the adverse childhood experiences framework), the AAEs focus on potentially traumatizing experiences during adolescence. The framework builds on Bronfenbrenner's ecological systems theory to conceptualize adversities at intrapersonal, interpersonal, community and societal levels. We argue that this approach can enhance our understanding of adolescent adversity, facilitate the study of its potential effects, and guide prevention and intervention efforts.

Neurobiological Perturbations in Bipolar Disorder Compared With Schizophrenia: Evidence From Cell Cultures and Brain Organoids

Bipolar disorder (BD) and schizophrenia (SCZ) are uniquely human disorders with a complex pathophysiology that involves adverse neuropathological events in brain development. High disease polygenicity and limited access to live human brain tissue make these disorders exceedingly challenging to study mechanistically. Cellular cultures and brain organoids generated from human-derived pluripotent stem cells preserve the genetic background of the donor cells and recapitulate some of the defining characteristics of human brain architecture and early spatiotemporal development. These model systems have already proven successful in deciphering some of the neuropathological perturbations in BD and SCZ, and methodological advancements, such as the functional integration of 2 or more region-specific organoids and organoid transplantation in animals, promise to deliver increasingly refined insights. Here, we review a selection of recent discoveries achieved by stem cell-based models, with a particular focus on patterns of cellular and molecular convergence and divergence between BD and SCZ. First, we provide a brief overview of the evidence from glial and neuronal cell cultures and brain organoids, centering our discussion on several key functional domains, including neuroinflammation, neuronal excitability, and mitochondrial function. Then, we review recent findings demonstrating the power of integrating stem cell-based systems with gene editing technologies to elucidate the functional consequences of risk variants identified through genetic association studies. We end with a discussion of current challenges and some promising avenues for future research.

Mapping the genetic landscape of psychiatric disorders with the MiXeR toolset

Psychiatric disorders have complex genetic architectures with substantial genetic overlap across conditions, which may partly explain their high levels of comorbidity. This presents significant challenges to research; genome-wide association studies (GWAS) have uncovered hundreds of loci associated with single disorders, yet the genetic landscape of psychiatric disorders has remained largely obscured. By moving beyond the conventional infinitesimal model, uni-, bi-, and trivariate MiXeR tools, applied to GWAS summary statistics, have enabled us to more comprehensively describe the genetic architecture of complex disorders and traits, and their overlap. Further, the GSA-MiXeR tool improves biological interpretation of GWAS findings to better understand causal mechanisms. Here, we outline the methodology underlying the MiXeR tools, together with instructions for their optimal use. We review results from studies investigating the genetic architecture of psychiatric disorders and their overlap using the MiXeR toolset. These studies have revealed generally high polygenicity and low discoverability among psychiatric disorders, particularly in contrast to somatic disorders. There is also pervasive genetic overlap across psychiatric disorders and behavioral traits, while their overlap with somatic traits is smaller, in line with differences in polygenicity. Finally, GSA-MiXeR has quantified the contribution of gene-sets to the heritability of psychiatric disorders, prioritizing small, biologically coherent gene-sets. Together, these findings have implications for our understanding of the complex relationships between psychiatric disorders and related traits. MiXeR tools have provided new insights into the genetic architecture of psychiatric disorders, generating a better understanding of their underlying biological mechanisms and potential for clinical utility.

Interaction between Neighborhood Exposome and Genetic Risk in Child Psychotic-like Experiences

Persistent distressing psychotic-like experiences (PLE) among children may be driven by genetics and neighborhood environmental exposures. However, the gene-environment interaction to persistent distressing PLE is unknown. The study included 6,449 participants from the Adolescent Brain and Cognitive Development Study. Genetic risk was measured by a multi-ancestry schizophrenia polygenic risk score (SCZ-PRS). Multi-dimensional neighborhood-level exposures were used to form a neighborhood exposome (NE) score. SCZ-PRS was not statistically significantly associated with odds of persistent distressing PLE (OR = 1.04, 95% CI: 0.97, 1.13, P = 0.280), whereas NE score was (OR = 1.15, 95% CI: 1.05, 1.26, P = 0.003). The association between NE score and persistent distressing PLE was statistically significantly attenuated as SCZ-PRS increased (OR for interaction = 0.92, 95% CI: 0.86, 1.00, P = 0.039). The findings indicate that persistent distressing PLE may be driven by detrimental neighborhood exposures, particularly among children with low genetic risks.

A neuro-immune axis of transcriptomic dysregulation within the subgenual anterior cingulate cortex in schizophrenia

Many genes are linked to psychiatric disorders, but genome-wide association studies (GWAS) and differential gene expression (DGE) analyses in post-mortem brain tissue often implicate distinct gene sets. This disconnect impedes therapeutic development, which relies on integrating genetic and genomic insights. We address this issue using a novel multivariate technique that reduces DGE bias by leveraging gene co-expression networks and controlling for confounds such as drug exposure. Deep RNA sequencing was performed in bulk post-mortem sgACC from individuals with bipolar disorder (BD; N=35), major depression (MDD; N=51), schizophrenia (SCZ; N=44), and controls (N=55). Toxicology data dimensionality was reduced using multiple correspondence analysis; case-control gene expression was then analyzed using 1) traditional DGE and 2) group regularized canonical correlation analysis (GRCCA) - a multivariate regression method that accounts for feature interdependence. Gene set enrichment analyses compared results with established neuropsychiatric risk genes, gene ontology pathways, and cell type enrichments. GRCCA revealed a significant association with SCZ ( P perm =0.001; no significant BD or MDD association), and the resulting gene weight vector correlated with DGE SCZ-control t-statistics ( R =0.53; P <0.05). Both methods indicated down-regulation of immune and microglial genes and upregulation of ion transport and excitatory neuron genes. However, GRCCA - at both the gene and transcript level - showed stronger enrichments (FDR<0.05). Notably, GRCCA results were enriched for SCZ GWAS-implicated genes (FDR<0.05), while DGE results were not. These findings identify a SCZ-specific sgACC gene expression pattern that highlights SCZ risk genes and implicates neuro-immune pathways, thus demonstrating the utility of multivariate approaches to integrate genetic and genomic signals.

Combined loss of brevican, neurocan, tenascin-C and tenascin-R leads to impaired fear retrieval due to perineuronal net loss

In conditions such as neurodegenerative diseases, posttraumatic stress disorder (PTSD), addiction and spinal cord injuries, restricted synaptic plasticity hinders the formation of new neuronal connections, preventing the compensation and treatment of adverse behaviors. Perineuronal nets (PNNs) significantly restrict synaptic plasticity by inhibiting synapse formation. The digestion of PNNs has been associated with short-term cognitive improvements and reduced long-term memory, offering potential therapeutic benefits in PTSD. This study investigates the correlation between PNNs and fear memory processes in extracellular matrix (ECM) mutant mice, particularly focusing on the amygdala-medial prefrontal cortex (mPFC) circuit, which is crucial for fear memory generation and maintenance. Fear conditioning was conducted on mice lacking four key ECM-molecules: brevican, neurocan, tenascin-C and tenascin-R (4x KO). These mice exhibited severe impairments in memory consolidation, as evident by their inability to retrieve previously learned fear memories, coupled with reduced PNN density and disturbed synaptic integrity along their PNNs. Additionally, changes in neural activity in the basolateral amygdala (BL) and reductions in VGAT+ synaptic puncta in the amygdala-mPFC circuit were observed. In contrast, tenascin single KOs showed intact fear behavior and memory compared to their control groups. Impaired fear memory consolidation can be advantageous in certain conditions, such as PTSD, making the 4x KO mice an intriguing model for future fear conditioning studies and highlighting brevican, neurocan, Tnc, and Tnr as compelling targets for further investigation. This study underscores the significance of ECM regulation for synaptic organization and the potential of PNN modulation as a therapeutic target for fear memory-related conditions.

Post-traumatic stress disorder: evolving conceptualization and evidence, and future research directions

The understanding of responses to traumatic events has been greatly influenced by the introduction of the diagnosis of post-traumatic stress disorder (PTSD). In this paper we review the initial versions of the diagnostic criteria for this condition and the associated epidemiological findings, including sociocultural differences. We consider evidence for post-traumatic reactions occurring in multiple contexts not previously defined as traumatic, and the implications that these observations have for the diagnosis. More recent developments such as the DSM-5 dissociative subtype and the ICD-11 diagnosis of complex PTSD are reviewed, adding to evidence that there are several distinct PTSD phenotypes. We describe the psychological foundations of PTSD, involving disturbances to memory as well as to identity. A broader focus on identity may be able to accommodate group and communal influences on the experience of trauma and PTSD, as well as the impact of resource loss. We then summarize current evidence concerning the biological foundations of PTSD, with a particular focus on genetic and neuroimaging studies. Whereas progress in prevention has been disappointing, there is now an extensive evidence supporting the efficacy of a variety of psychological treatments for established PTSD, including trauma-focused interventions - such as trauma-focused cognitive behavior therapy (TF-CBT) and eye movement desensitization and reprocessing (EMDR) - and non-trauma-focused therapies, which also include some emerging identity-based approaches such as present-centered and compassion-focused therapies. Additionally, there are promising interventions that are neither psychological nor pharmacological, or that combine a pharmacological and a psychological approach, such as 3,4-methylenedioxymethamphetamine (MDMA)-assisted psychotherapy. We review advances in the priority areas of adapting interventions in resource-limited settings and across cultural contexts, and of community-based approaches. We conclude by identifying future directions for work on trauma and mental health.

The current clinical approach to feeding and eating disorders aimed to increase personalization of management

Feeding and eating disorders (FEDs) are a heterogeneous grouping of disorders at the mind-body interface, with typical onset from childhood into emerging adulthood. They occur along a spectrum of disordered eating and compensatory weight management behaviors, and from low to high body weight. Psychiatric comorbidities are the norm. In contrast to other major psychiatric disorders, first-line treatments for FEDs are mainly psychological and/or nutrition-focused, with medications playing a minor adjunctive role. Patients, carers and clinicians all have identified personalization of treatment as a priority. Yet, for all FEDs, the evidence base supporting this personalization is limited. Importantly, disordered eating and related behaviors can have serious physical consequences and may put the patient's life at risk. In these cases, immediate safety and risk management considerations may at least for a period need to be prioritized over other efforts at personalization of care. This paper systematically reviews several key domains that may be relevant to the characterization of the individual patient with a FED aimed at personalization of management. These domains include symptom profile, clinical subtypes, severity, clinical staging, physical complications and consequences, antecedent and concomitant psychiatric conditions, social functioning and quality of life, neurocognition, social cognition and emotion, dysfunctional cognitive schemata, personality traits, family history, early environmental exposures, recent environmental exposures, stigma, and protective factors. Where possible, validated assessment measures for use in clinical practice are identified. The limitations of the current evidence are pointed out, and possible directions for future research are highlighted. These also include novel and emerging approaches aimed at providing more fine-grained and sophisticated ways to personalize treatment of FEDs, such as those that utilize neurobiological markers. We additionally outline remote measurement technologies designed to delineate patients' illness and recovery trajectories and facilitate development of novel intervention approaches.

Digital phenotyping from wearables using AI characterizes psychiatric disorders and identifies genetic associations

Psychiatric disorders are influenced by genetic and environmental factors. However, their study is hindered by limitations on precisely characterizing human behavior. New technologies such as wearable sensors show promise in surmounting these limitations in that they measure heterogeneous behavior in a quantitative and unbiased fashion. Here, we analyze wearable and genetic data from the Adolescent Brain Cognitive Development (ABCD) study. Leveraging >250 wearable-derived features as digital phenotypes, we show that an interpretable AI framework can objectively classify adolescents with psychiatric disorders more accurately than previously possible. To relate digital phenotypes to the underlying genetics, we show how they can be employed in univariate and multivariate genome-wide association studies (GWASs). Doing so, we identify 16 significant genetic loci and 37 psychiatric-associated genes, including ELFN1 and ADORA3, demonstrating that continuous, wearable-derived features give greater detection power than traditional case-control GWASs. Overall, we show how wearable technology can help uncover new linkages between behavior and genetics.

Echocardiography with Strain Assessment in Psychiatric Diseases: A Narrative Review

Mental disorders (MDs) are among the major causes of morbidity and mortality worldwide. Individuals with severe MDs have a shorter life expectancy, primarily due to cardiovascular diseases. Echocardiography facilitates the evaluation of alterations in cardiac morphology and function, resulting from various cardiac pathologies. The aim of this review was to explore the current evidence base behind the myocardial deformation observed in echocardiography in patients with MDs. We primarily focused on the data regarding speckle tracking echocardiography. PubMed, using medical subject headings, was searched to identify studies on this topic. The collected data demonstrated changes in myocardial function in schizophrenia, bipolar disorder, depression, anxiety disorder, stressor-related disorder, post-traumatic stress disorder, eating disorders, sleep-wake disorders, substance-related and addictive disorders, neurocognitive disorders, and borderline personality disorder. The recurrent findings included impaired Left Ventricular Ejection Fraction and Left Ventricular Hypertrophy. Global Longitudinal Strain was significantly altered in patients with anorexia nervosa, bipolar disorder, and substance-related disorders. All reported studies support the consideration of cardiology consultations and a multidisciplinary approach in the care of patients with MDs with suspected cardiac dysfunction. Further investigation is warranted to determine the significance and prognostic value of myocardial deformation and strain measurements among individuals with MDs, focusing on the value of early detection, especially in asymptomatic cases.

Advancing Neuroscience and Therapy: Insights into Genetic and Non-Genetic Neuromodulation Approaches

Neuromodulation stands as a cutting-edge approach in the fields of neuroscience and therapeutic intervention typically involving the regulation of neural activity through physical and chemical stimuli. The purpose of this review is to provide an overview and evaluation of different neuromodulation techniques, anticipating a clearer understanding of the future developmental trajectories and the challenges faced within the domain of neuromodulation that can be achieved. This review categorizes neuromodulation techniques into genetic neuromodulation methods (including optogenetics, chemogenetics, sonogenetics, and magnetogenetics) and non-genetic neuromodulation methods (including deep brain stimulation, transcranial magnetic stimulation, transcranial direct current stimulation, transcranial ultrasound stimulation, photobiomodulation therapy, infrared neuromodulation, electromagnetic stimulation, sensory stimulation therapy, and multi-physical-factor stimulation techniques). By systematically evaluating the principles, mechanisms, advantages, limitations, and efficacy in modulating neuronal activity and the potential applications in interventions of neurological disorders of these neuromodulation techniques, a comprehensive picture is gradually emerging regarding the advantages and challenges of neuromodulation techniques, their developmental trajectory, and their potential clinical applications. This review highlights significant advancements in applying these techniques to treat neurological and psychiatric disorders. Genetic methods, such as sonogenetics and magnetogenetics, have demonstrated high specificity and temporal precision in targeting neuronal populations, while non-genetic methods, such as transcranial magnetic stimulation and photobiomodulation therapy, offer noninvasive and versatile clinical intervention options. The transformative potential of these neuromodulation techniques in neuroscience research and clinical practice is underscored, emphasizing the need for integration and innovation in technologies, the optimization of delivery methods, the improvement of mediums, and the evaluation of toxicity to fully harness their therapeutic potential.

Shared polygenic susceptibility to treatment response in severe affective and psychotic disorders: Evidence from GWAS data sets

While schizophrenia (SCZ), bipolar disorder (BD) and major depressive disorder (MDD) genetically correlate, the pleiotropy underlying response/resistance to drugs used in these disorders has not been investigated. The aim of this study is to analyze the genetic relationship between treatment-resistant schizophrenia (TRS), response to lithium in BD (respLi) and response to antidepressants in MDD (respAD) using the conditional/conjunctional false discovery rate (cond/conjFDR) methodology, based on the hypothesis that shared mechanisms related to a common psychopathology factor underlie these phenotypes. A cross-trait polygenic enrichment for TRS conditioned on associations with respLi was observed. The conjFDR analysis identified rs11631065 (chr15:66654304) as a shared locus between them. One of the genes at this locus is MAP2K1, previously reported as associated with TRS after conditioning on body mass index genome-wide association study (GWAS). The set of genes at TRS-respLi conjFDR < 0.95 showed enrichment in response to psychotropic drugs in severe mental disorders from GWAS Catalog as well as in neurodevelopment and synaptic pathways. In conclusion, our study constitutes the first evidence of a transdiagnostic genetic signal associated with response to different pharmacological treatments in psychotic and affective disorders. It is necessary to confirm these results when larger GWAS of these phenotypes are available.

The genetic architecture of differentiating behavioral and emotional problems in early life

BACKGROUND

Early in life, behavioral and cognitive traits associated with risk for developing a psychiatric condition are broad and undifferentiated. As children develop, these traits differentiate into characteristic clusters of symptoms and behaviors that ultimately form the basis of diagnostic categories. Understanding this differentiation process - in the context of genetic risk for psychiatric conditions, which is highly generalized - can improve early detection and intervention.

METHODS

We modeled the differentiation of behavioral and emotional problems from age 1.5-5 years (behavioral problems - emotional problems = differentiation score) in a pre-registered study of ∼79,000 children from the population-based Norwegian Mother, Father, and Child Cohort Study. We used genomic structural equation modeling to identify genetic signal in differentiation and total problems, investigating their links with 11 psychiatric and neurodevelopmental conditions. We examined associations of polygenic scores (PGS) with both outcomes and assessed the relative contributions of direct and indirect genetic effects in ∼33,000 family trios.

RESULTS

Differentiation was primarily genetically correlated with psychiatric conditions via a "neurodevelopmental" factor. Total problems were primarily associated with the "neurodevelopmental" factor and "p"-factor. PGS analyses revealed an association between liability to ADHD and differentiation (β=0.11 [0.10,0.12]), and a weaker association with total problems (β=0.06 [0.04,0.07]). Trio-PGS analyses showed predominantly direct genetic effects on both outcomes.

CONCLUSIONS

We uncovered genomic signal in the differentiation process, mostly related to common variants associated with neurodevelopmental conditions. Investigating the differentiation of early life behavioral and emotional problems may enhance our understanding of the developmental emergence of different psychiatric and neurodevelopmental conditions.

Cross-species translational paradigms for assessing positive valence system as defined by the RDoC matrix

Functions associated with processing reward-related information are fundamental drivers of motivation, learning, and goal-directed behavior. Such functions have been classified as the positive valence system under the Research Domain and Criteria (RDoC) criteria and are negatively impacted across a range of psychiatric disorders and mental illnesses. The positive valence system is composed of three comprehensive categories containing related but dissociable functions that are organized into either Reward Responsiveness, Reward Learning, or Reward Valuation. The presence of overlapping behavioral dysfunction across diagnostic mental disorders is in-part what motivated the RDoC initiative, which emphasized that the study of mental illness focus on investigating relevant behavior and cognitive functions and their underlying mechanisms, rather than separating efforts on diagnostic categories (i.e., transdiagnostic). Moreover, the RDoC approach is well-suited for preclinical neuroscience research, as the rise in genetic toolboxes and associated neurotechnologies enables researchers to probe specific cellular targets with high specificity. Thus, there is an opportunity to dissect whether behaviors and cognitive functions are supported by shared or distinct neural mechanisms. For preclinical research to effectively inform our understandings of human behavior however, the cognitive and behavioral paradigms should have predictive, neurobiological, and pharmacological predictive validity to the human test. Touchscreen-based testing systems provide a further advantage for this endeavor enabling tasks to be presented to animals using the same media and task design as in humans. Here, we outline the primary categories of the positive valence system and review the work that has been done cross-species to investigate the neurobiology and neurochemistry underlying reward-related functioning. Additionally, we provide clinical tasks outlined by RDoC, along with validity and/or need for further validation for analogous rodent paradigms with a focus on implementing the touchscreen-based cognitive testing systems.

Sexual Trauma, Polygenic Scores, and Mental Health Diagnoses and Outcomes

Importance

Leveraging real-world clinical biobanks to investigate the associations between genetic and environmental risk factors for mental illness may help direct clinical screening efforts and evaluate the portability of polygenic scores across environmental contexts.

Objective

To examine the associations between sexual trauma, polygenic liability to mental health outcomes, and clinical diagnoses of schizophrenia, bipolar disorder, and major depressive disorder in a clinical biobank setting.

Design, Setting, and Participants

This genetic association study was conducted using clinical and genotyping data from 96 002 participants across hospital-linked biobanks located at Vanderbilt University Medical Center (VUMC), Nashville, Tennessee (including 58 262 individuals with high genetic similarity to the 1000 Genomes Project [1KG] Northern European from Utah reference population [1KG-EU-clustered] and 11 047 with high genetic similarity to the 1KG African-ancestry reference population of Yoruba in Ibadan, Nigeria [1KG-YRI-clustered]), and Mass General Brigham (MGB), Boston, Massachusetts (26 693 individuals with high genetic similarity to the combined European-ancestry superpopulation [1KG-EU-clustered]). Clinical data analyzed included diagnostic billing codes and clinical notes spanning from 1976 to 2023. Data analysis was performed from 2022 to 2024.

Exposures

Clinically documented sexual trauma disclosures and polygenic scores for schizophrenia, bipolar disorder, and major depressive disorder.

Main Outcomes and Measures

Diagnoses of schizophrenia, bipolar disorder, and major depressive disorder, determined by aggregating related diagnostic billing codes, were the dependent variables in logistic regression models including sexual trauma disclosure status, polygenic scores, and their interactions as the independent variables.

Results

Across the VUMC and MGB biobanks, 96 002 individuals were included in analyses (VUMC 1KG-EU-clustered: 33 011 [56.7%] female; median [range] age, 56.8 [10.0 to >89] years; MGB 1KG-EU-clustered: 14 647 [54.9%] female; median [range] age, 58.0 [10.0 to >89] years; VUMC 1KG-YRI-clustered: 6961 [63.0%] female; median [range] age, 44.6 [10.1 to >89] years). Sexual trauma history was associated with all mental health conditions across institutions (ORs ranged from 8.83 [95% CI, 5.50-14.18] for schizophrenia in the VUMC 1KG-YRI-clustered cohort to 17.65 [95% CI, 12.77-24.40] for schizophrenia in the VUMC 1KG-EU-clustered cohort). Sexual trauma history and polygenic scores jointly explained 3.8% to 8.8% of mental health phenotypic variance. Schizophrenia and bipolar disorder polygenic scores had greater associations with mental health outcomes in individuals with no documented disclosures of sexual trauma (schizophrenia interaction: OR, 0.70 [95% CI, 0.56-0.88]; bipolar disorder interaction: OR, 0.83 [95% CI, 0.74-0.94]).

Conclusions and Relevance

Sexual trauma and mental health polygenic scores, while correlated with one another, were independent and joint risk factors for severe mental illness in a large, diverse hospital biobank population. Furthermore, associations of schizophrenia and bipolar disorder polygenic scores with respective diagnoses were greater in those without disclosures, suggesting that genetic predisposition to mental illness as measured by polygenic scores may be less impactful in the presence of this severe environmental risk factor.

Genetic analysis of psychosis Biotypes: shared Ancestry-adjusted polygenic risk and unique genomic associations

The Bipolar-Schizophrenia Network for Intermediate Phenotypes (B-SNIP) created psychosis Biotypes based on neurobiological measurements in a multi-ancestry sample. These Biotypes cut across DSM diagnoses of schizophrenia, schizoaffective disorder, and bipolar disorder with psychosis. Two recently developed post hoc ancestry adjustment methods of Polygenic Risk Scores (PRSs) generate Ancestry-Adjusted PRSs (AAPRSs), which allow for PRS analysis of multi-ancestry samples. Applied to schizophrenia PRS, we found the Khera AAPRS method to show superior portability and comparable prediction accuracy as compared with the Ge method. The three Biotypes of psychosis disorders had similar AAPRSs across ancestries. In genomic analysis of Biotypes, 12 genes, and isoforms showed significant genomic associations with specific Biotypes in a Transcriptome-Wide Association Study (TWAS) of genetically regulated expression (GReX) in the adult brain and fetal brain. TWAS inflation was addressed by the inclusion of genotype principal components in the association analyses. Seven of these 12 genes/isoforms satisfied Mendelian Randomization (MR) criteria for putative causality, including four genes TMEM140, ARTN, C1orf115, CYREN, and three transcripts ENSG00000272941, ENSG00000257176, ENSG00000287733. These genes are enriched in the biological pathways of Rearranged during Transfection (RET) signaling, Neural Cell Adhesion Molecule 1 (NCAM1) interactions, and NCAM signaling for neurite out-growth. The specific associations with Biotypes suggest that pharmacological clinical trials and biological investigations might benefit from analyzing Biotypes separately.

Identification of gene co-expression modules from zebrafish brain data: Applications in psychiatry illustrated through alcohol-related traits

Cumulative evidence suggests that zebrafish is a useful model in psychiatric research. Weighted Gene Co-expression Network Analysis (WGCNA) enables the reduction of genome-wide expression data to modules of highly co-expressed genes, which are hypothesized to interact within molecular networks. In this study, we first applied WGCNA to zebrafish brain expression data across different experimental conditions. Then, we characterized the different co-expression modules by gene-set enrichment analysis and hub gene-phenotype association. Finally, we analyzed association of polygenic risk scores (PRSs) based on genes of some interesting co-expression modules with alcohol dependence in 524 patients and 729 controls from Galicia, using competitive tests. Our approach revealed 34 co-expression modules in the zebrafish brain, with some showing enrichment in human synaptic genes, brain tissues, or brain developmental stages. Moreover, certain co-expression modules were enriched in psychiatry-related GWAS and comprised hub genes associated with psychiatry-related traits in both human GWAS and zebrafish models. Expression patterns of some co-expression modules were associated with the tested experimental conditions, mainly with substance withdrawal and cold stress. Notably, a PRS based on genes from co-expression modules exclusively associated with substance withdrawal in zebrafish showed a stronger association with human alcohol dependence than PRSs based on randomly selected brain-expressed genes. In conclusion, our analysis led to the identification of co-expressed gene modules that may model human brain gene networks involved in psychiatry-related traits. Specifically, we detected a cluster of co-expressed genes whose expression was exclusively associated with substance withdrawal in zebrafish, which significantly contributed to alcohol dependence susceptibility in humans.

Research Review: A review of the past decade of family and genomic studies on adolescent mental health

BACKGROUND

Mental health problems and traits capturing psychopathology are common and often begin during adolescence. Decades of twin studies indicate that genetic factors explain around 50% of individual differences in adolescent psychopathology. In recent years, significant advances, particularly in genomics, have moved this work towards more translational findings.

METHODS

This review provides an overview of the past decade of genetically sensitive studies on adolescent development, covering both family and genomic studies in adolescents aged 10-24 years. We focus on five research themes: (1) co-occurrence or comorbidity between psychopathologies, (2) stability and change over time, (3) intergenerational transmission, (4) gene-environment interplay, and (5) psychological treatment outcomes.

RESULTS

First, research shows that much of the co-occurrence of psychopathologies in adolescence is explained by genetic factors, with widespread pleiotropic influences on many traits. Second, stability in psychopathology across adolescence is largely explained by persistent genetic influences, whereas change is explained by emerging genetic and environmental influences. Third, contemporary twin-family studies suggest that different co-occurring genetic and environmental mechanisms may account for the intergenerational transmission of psychopathology, with some differences across psychopathologies. Fourth, genetic influences on adolescent psychopathology are correlated with a wide range of environmental exposures. However, the extent to which genetic factors interact with the environment remains unclear, as findings from both twin and genomic studies are inconsistent. Finally, a few studies suggest that genetic factors may play a role in psychological treatment response, but these findings have not yet been replicated.

CONCLUSIONS

Genetically sensitive research on adolescent psychopathology has progressed significantly in the past decade, with family and twin findings starting to be replicated at the genomic level. However, important gaps remain in the literature, and we conclude by providing suggestions of research questions that still need to be addressed.

Genetic Analysis of Psychosis Biotypes: Shared Ancestry-Adjusted Polygenic Risk and Unique Genomic Associations

The Bipolar-Schizophrenia Network for Intermediate Phenotypes (B-SNIP) created psychosis Biotypes based on neurobiological measurements in a multi-ancestry sample. These Biotypes cut across DSM diagnoses of schizophrenia, schizoaffective disorder and bipolar disorder with psychosis. Two recently developed post hoc ancestry adjustment methods of Polygenic Risk Scores (PRSs) generate Ancestry-Adjusted PRSs (AAPRSs), which allow for PRS analysis of multi-ancestry samples. Applied to schizophrenia PRS, we found the Khera AAPRS method to show superior portability and comparable prediction accuracy as compared with the Ge method. The three Biotypes of psychosis disorders had similar AAPRSs across ancestries. In genomic analysis of Biotypes, 12 genes and isoforms showed significant genomic associations with specific Biotypes in Transcriptome-Wide Association Study (TWAS) of genetically regulated expression (GReX) in adult brain and fetal brain. TWAS inflation was addressed by inclusion of genotype principal components in the association analyses. Seven of these 12 genes/isoforms satisfied Mendelian Randomization (MR) criteria for putative causality, including four genes TMEM140, ARTN, C1orf115, CYREN, and three transcripts ENSG00000272941, ENSG00000257176, ENSG00000287733. These genes are enriched in the biological pathways of Rearranged during Transfection (RET) signaling, Neural Cell Adhesion Molecule 1 (NCAM1) interactions, and NCAM signaling for neurite out-growth. The specific associations with Biotypes suggest that pharmacological clinical trials and biological investigations might benefit from analyzing Biotypes separately.

Identification of novel genomic loci for anxiety symptoms and extensive genetic overlap with psychiatric disorders

AIMS

Anxiety disorders are prevalent and anxiety symptoms (ANX) co-occur with many psychiatric disorders. We aimed to identify genomic loci associated with ANX, characterize its genetic architecture, and genetic overlap with psychiatric disorders.

METHODS

We included a genome-wide association study of ANX (meta-analysis of UK Biobank and Million Veterans Program, n = 301,732), schizophrenia (SCZ), bipolar disorder (BIP), major depression (MD), attention-deficit/hyperactivity disorder (ADHD), and autism spectrum disorder (ASD), and validated the findings in the Norwegian Mother, Father, and Child Cohort (n = 95,841). We employed the bivariate causal mixture model and local analysis of covariant association to characterize the genetic architecture including overlap between the phenotypes. Conditional and conjunctional false discovery rate analyses were performed to boost the identification of loci associated with anxiety and shared with psychiatric disorders.

RESULTS

Anxiety was polygenic with 12.9k genetic variants and overlapped extensively with psychiatric disorders (4.1k-11.4k variants) with predominantly positive genetic correlations between anxiety and psychiatric disorders. We identified 119 novel loci for anxiety by conditioning on the psychiatric disorders, and loci shared between anxiety and MDn = 47 , BIPn = 33 , SCZn = 71 , ADHDn = 20 , and ASDn = 5 . Genes annotated to anxiety loci exhibit enrichment for a broader range of biological pathways including cell adhesion and neurofibrillary tangle compared with genes annotated to the shared loci.

CONCLUSIONS

Anxiety is highly polygenic phenotype with extensive genetic overlap with psychiatric disorders, and we identified novel loci for anxiety implicating new molecular pathways. The shared genetic architecture may underlie the extensive cross-disorder comorbidity of anxiety, and the identified molecular underpinnings may lead to potential drug targets.

Screening for depression in the general population through lipid biomarkers

BACKGROUND

Anxiety and depression significantly contribute to the overall burden of mental disorders, with depression being one of the leading causes of disability. Despite this, no biochemical test has been implemented for the diagnosis of these mental disorders, while recent studies have highlighted lipids as potential biomarkers.

METHODS

Using a streamlined high-throughput lipidome analysis method, direct-infusion mass spectrometry, we evaluated blood plasma lipid levels in 604 individuals from a general urban population and analysed their association with self-reported anxiety and depression symptoms. We also assessed lipidome profiles in 32 patients with clinical depression, matched to 21 healthy controls.

FINDINGS

We found a significant correlation between lipid abundances and the severity of self-reported depression symptoms. Moreover, lipid alterations detected in high scoring volunteers mirrored the lipidome profiles identified in patients with clinical depression included in our study. Based on these findings, we developed a lipid-based predictive model distinguishing individuals reporting severe depressive symptoms from non-depressed subjects with high accuracy.

INTERPRETATION

This study demonstrates the possibility of generalizing lipid alterations from a clinical cohort to the general population and underscores the potential of lipid-based biomarkers in assessing depressive states.

FUNDING

This study was sponsored by the Moscow Center for Innovative Technologies in Healthcare, №2707-2, №2102-11.

Association between blood mitochondrial DNA copy number and mental disorders: A bidirectional two-sample mendelian randomization study

BACKGROUND

Mitochondria is essential for cellular energy production, oxidative stress, and apoptosis. Mitochondrial DNA (mtDNA) encodes essential proteins for mitochondrial function. Although several studies have explored the association between changes in mtDNA copy number (mtDNA-CN) and risk of mental disorders, the results remain debated. This study used a bidirectional two-sample Mendelian randomization (MR) analysis to examine the genetic causality between mtDNA-CN and mental disorders.

METHODS

Genome-wide association study (GWAS) data for mtDNA-CN were sourced from UK biobank, involving 383,476 European cases. GWAS data for seven mental disorders-attention deficit/hyperactivity disorder, autism spectrum disorder (ASD), schizophrenia, bipolar disorder, major depressive disorder, anxiety, and obsessive-compulsive disorder-were primarily obtained from the Psychiatric Genomics Consortium. Causal associations were assessed using inverse variance weighting, with sensitivity analyses via the weighted median and MR-Egger methods. Reverse MR considered the seven mental disorders as exposures. All analyses were replicated with additional mtDNA-CN GWAS data from 465,809 individuals in the Heart and Ageing Research in Genomic Epidemiology consortium and the UK Biobank.

RESULTS

Forward MR observed a 27 % decrease in the risk of ASD per standard deviation increase in genetically determined blood mtDNA-CN (OR = 0.73, 95%CI: 0.58-0.92, p = 0.002), with no causal effects on other disorders. Additionally, reverse MR did not indicate a causal association between any of the mental disorders and mtDNA-CN. Validation analyses corroborated these findings, indicating their robustness.

CONCLUSIONS

Our study supports the potential causal association between mtDNA-CN and the risk of ASD, suggesting that mtDNA-CN could serve as a promising biomarker for early screening of ASD.

Mitochondrial related Mendelian randomization identifies causal associations between metabolic disorders and childhood neurodevelopmental disorders

Childhood neurodevelopmental disorders (NDDs), including autism spectrum disorder (ASD), attention-deficit hyperactivity disorder, and Tourette syndrome, are a predominant cause of health-related disabilities in children and adolescents. Nevertheless, disease biomarkers are still limited. The aim of this study was to evaluate the potential, causal relationship between mitochondrial DNA copy number (mtDNA-CN), metabolic disorders, and childhood NDDs using the two-sample Mendelian randomization (MR) method. Genetic associations with mtDNA-CN, disorders of lipoprotein metabolism, and disorders of iron metabolism were selected as exposures, and genome-wide association data from ASD, attention-deficit hyperactivity disorder, and Tourette syndrome were utilized as outcomes. Results of the study suggested that a high degree of disordered lipoprotein metabolism related increases in ASD risk result from a decrease in mtDNA-CN (disordered lipoprotein metabolism-mtDNA: inverse variance weighting β: -0.03, 95% confidence interval: -0.05 to -0.02, P = 2.08 × 10-5; mtDNA-CN-ASD: inverse variance weighting odds ratio: 0.83, 95% confidence interval: 0.69-0.99, P = .034). The research findings implied that mtDNA-CN can mediate disorders of lipoprotein metabolism, potentially influencing the development of ASD. The potential impact of the results of this study for the prevention and treatment of childhood NDDs warrants validation in robust randomized clinical trials.

Mutational landscape of risk variants in comorbid depression and obesity: a next-generation sequencing approach

Major depression (MD) and obesity are complex genetic disorders that are frequently comorbid. However, the study of both diseases concurrently remains poorly addressed and therefore the underlying genetic mechanisms involved in this comorbidity remain largely unknown. Here we examine the contribution of common and rare variants to this comorbidity through a next-generation sequencing (NGS) approach. Specific genomic regions of interest in MD and obesity were sequenced in a group of 654 individuals from the PISMA-ep epidemiological study. We obtained variants across the entire frequency spectrum and assessed their association with comorbid MD and obesity, both at variant and gene levels. We identified 55 independent common variants and a burden of rare variants in 4 genes (PARK2, FGF21, HIST1H3D and RSRC1) associated with the comorbid phenotype. Follow-up analyses revealed significantly enriched gene-sets associated with biological processes and pathways involved in metabolic dysregulation, hormone signaling and cell cycle regulation. Our results suggest that, while risk variants specific to the comorbid phenotype have been identified, the genes functionally impacted by the risk variants share cell biological processes and signaling pathways with MD and obesity phenotypes separately. To the best of our knowledge, this is the first study involving a targeted sequencing approach toward the study of the comorbid MD and obesity. The framework presented here allowed a deep characterization of the genetics of the co-occurring MD and obesity, revealing insights into the mutational and functional profile that underlies this comorbidity and contributing to a better understanding of the relationship between these two disabling disorders.

Genetic testing in psychiatry, the perceptions of healthcare workers and patients: a mini review

Background

Genetic testing in psychiatry has gained attention, raising questions about its application and impact. Understanding stakeholders' perspectives, including healthcare providers and patients, is vital for informed policy development. The aim of this systematic review was to focus on the perceptions and concerns of patients and healthcare workers in psychiatry regarding the use of genetic testing.

Methods

We conducted a systematic review following PRISMA guidelines, for the period 1/2/2014, to 1/1/2024, via PubMed and Embase databases identifying 50 articles in total. After excluding duplicates (n = 12), 38 articles went through screening. After careful full-text article assessment for eligibility and applying the inclusion and exclusion criteria, only fifteen (n = 15) of the articles were included.

Results

Among 15 selected studies involving 3,156 participants (2,347 healthcare professionals; 809 patients), thematic analysis identified four primary themes: Organizational-implementation concerns, Ethical Considerations, Concerns on changes in clinical praxis, and Legal implications. Despite these concerns, seven out of eleven studies indicated that healthcare workers viewed genetic testing in psychiatry positively. Patients' perspectives varied, with two of the four studies reflecting positive attitudes. No pervasive negative sentiment was observed.

Conclusion

Our review highlights the multidimensional perspectives of healthcare professionals and patients surrounding the application of genetic testing in psychiatry. These considerations need to be addressed to facilitate the implementation of genetic testing in clinical praxis in psychiatry. Further research is needed for validation of the results and to guide policies and clinicians in the integration of genetic testing into mental healthcare practice.

Phenotype harmonization and analysis for The Populations Underrepresented in Mental illness Association Studies (the PUMAS Project)

Background

The Populations Underrepresented in Mental illness Association Studies (PUMAS) project is attempting to remediate the historical underrepresentation of African and Latin American populations in psychiatric genetics through large-scale genetic association studies of individuals diagnosed with a serious mental illness [SMI, including schizophrenia (SCZ), schizoaffective disorder (SZA) bipolar disorder (BP), and severe major depressive disorder (MDD)] and matched controls. Given growing evidence indicating substantial symptomatic and genetic overlap between these diagnoses, we sought to enable transdiagnostic genetic analyses of PUMAS data by conducting phenotype alignment and harmonization for 89,320 participants (48,165 cases and 41,155 controls) from four cohorts, each of which used different ascertainment and assessment methods: PAISA n=9,105; PUMAS-LATAM n=14,638; NGAP n=42,953 and GPC n=22,624. As we describe here, these efforts have yielded harmonized datasets enabling us to analyze PUMAS genetic variation data at three levels: SMI overall, diagnoses, and individual symptoms.

Methods

In aligning item-level phenotypes obtained from 14 different clinical instruments, we incorporated content, branching nature, and time frame for each phenotype; standardized diagnoses; and selected 19 core SMI item-level phenotypes for analyses. The harmonization was evaluated in PUMAS cases using multiple correspondence analysis (MCA), co-occurrence analyses, and item-level endorsement.

Outcomes

We mapped >6,895 item-level phenotypes in the aggregated PUMAS data, in which SCZ (44.97%) and severe BP (BP-I, 31.53%) were the most common diagnoses. Twelve of the 19 core item-level phenotypes occurred at frequencies of > 10% across all diagnoses, indicating their potential utility for transdiagnostic genetic analyses. MCA of the 14 phenotypes that were present for all cohorts revealed consistency across cohorts, and placed MDD and SCZ into separate clusters, while other diagnoses showed no significant phenotypic clustering.

Interpretation

Our alignment strategy effectively aggregated extensive phenotypic data obtained using diverse assessment tools. The MCA yielded dimensional scores which we will use for genetic analyses along with the item level phenotypes. After successful harmonization, residual phenotypic heterogeneity between cohorts reflects differences in branching structure of diagnostic instruments, recruitment strategies, and symptom interpretation (due to cultural variation).

A survey in Austria supports the significance of genetic counseling and pharmacogenetic testing for mental illness

Introduction

Genetic counseling and testing in psychiatry warrant attention, but research results on attitude, knowledge, personal experience and interest are limited. There are only a few studies that have compared the opinions of the general population and experts regarding genetic counseling and genetic testing in mental illness.

Methods

This study aimed to investigate these gaps through a cross-sectional survey conducted in Austria, involving a sample of the web-active population, representative according to gender, age and geographical location (n=1,000, 24.5% of them had a psychiatric diagnosis), and experts (n=145, 83.4% of them psychiatrists). Two questionnaires were developed. Pearson chi-square statistics were used to compare responses, and regression analyses were employed to measure the strength of psycho-sociodemographic influences on answers.

Results

The findings revealed that public considered genetic counseling to be more important than experts did (68.8% versus 54.2%; Pearson chi-square 12.183; df=1; p<0.001). The general population believed that genetic testing is useful for diagnosing mental disorders, which contrasted with experts' opinions (67.9% versus 17.2%; Pearson chi-square 137.236; df=1; p<0.001). Both groups agreed on the potential benefits of pharmacogenetic testing (79% versus 80%). A small number of individuals from the public had sought genetic counseling (8%), and only a minority of experts had specific training and experience in this field (28%).

Discussion

This is the first survey study on the topic conducted in Austria, with limited international studies available. Austrian experts place less value on genetic counseling compared to their counterparts in other countries. Despite recognized importance placed on genetic counseling and testing, utilization rates remain low. The value of pharmacogenetics is predicted to increase in the future. Consequently, it is crucial for medical training programs to emphasize the significance of genetic counseling and enhance the understanding of genetic aspects related to mental illnesses to enable experts to provide adequate psychoeducation and personalized care to the extent possible to patients and their families.

Ormerod MB, Aukrust P, Melle I, Steen NE, Andreassen OA, Ueland T. Longitudinal course of inflammatory-cognitive subgroups across first treatment severe mental illness and healthy controls

BACKGROUND

While inflammation is associated with cognitive impairment in severe mental illnesses (SMI), there is substantial heterogeneity and evidence of transdiagnostic subgroups across schizophrenia (SZ) and bipolar (BD) spectrum disorders. There is however, limited knowledge about the longitudinal course of this relationship.

METHODS

Systemic inflammation (C-Reactive Protein, CRP) and cognition (nine cognitive domains) was measured from baseline to 1 year follow-up in first treatment SZ and BD (n = 221), and healthy controls (HC, n = 220). Linear mixed models were used to evaluate longitudinal changes separately in CRP and cognitive domains specific to diagnostic status (SZ, BD, HC). Hierarchical clustering was applied on the entire sample to investigate the longitudinal course of transdiagnostic inflammatory-cognitive subgroups.

RESULTS

There were no case-control differences or change in CRP from baseline to follow-up. We confirm previous observations of case-control differences in cognition at both time-points and domain specific stability/improvement over time regardless of diagnostic status. We identified transdiagnostic inflammatory-cognitive subgroups at baseline with differing demographics and clinical severity. Despite improvement in cognition, symptoms and functioning, the higher inflammation - lower cognition subgroup (75% SZ; 48% BD; 38% HC) had sustained inflammation and lower cognition, more symptoms, and lower functioning (SMI only) at follow-up. This was in comparison to a lower inflammation - higher cognition subgroup (25% SZ, 52% BD, 62% HC), where SMI participants showed cognitive functioning at HC level with a positive clinical course.

CONCLUSIONS

Our findings support heterogenous and transdiagnostic inflammatory-cognitive subgroups that are stable over time, and may benefit from targeted interventions.

Associations between antagonistic SNPs for neuropsychiatric disorders and human brain structure

A previously published genome-wide association study (GWAS) meta-analysis across eight neuropsychiatric disorders identified antagonistic single-nucleotide polymorphisms (SNPs) at eleven genomic loci where the same allele was protective against one neuropsychiatric disorder and increased the risk for another. Until now, these antagonistic SNPs have not been further investigated regarding their link to brain structural phenotypes. Here, we explored their associations with cortical surface area and cortical thickness (in 34 brain regions and one global measure each) as well as the volumes of eight subcortical structures using summary statistics of large-scale GWAS of brain structural phenotypes. We assessed if significantly associated brain structural phenotypes were previously reported to be associated with major neuropsychiatric disorders in large-scale case-control imaging studies by the ENIGMA consortium. We further characterized the effects of the antagonistic SNPs on gene expression in brain tissue and their association with additional cognitive and behavioral phenotypes, and performed an exploratory voxel-based whole-brain analysis in the FOR2107 study (n = 754 patients with major depressive disorder and n = 847 controls). We found that eight antagonistic SNPs were significantly associated with brain structural phenotypes in regions such as anterior parts of the cingulate cortex, the insula, and the superior temporal gyrus. Case-control differences in implicated brain structural phenotypes have previously been reported for bipolar disorder, major depressive disorder, and schizophrenia. In addition, antagonistic SNPs were associated with gene expression changes in brain tissue and linked to several cognitive-behavioral traits. In our exploratory whole-brain analysis, we observed significant associations of gray matter volume in the left superior temporal pole and left superior parietal region with the variants rs301805 and rs1933802, respectively. Our results suggest that multiple antagonistic SNPs for neuropsychiatric disorders are linked to brain structural phenotypes. However, to further elucidate these findings, future case-control genomic imaging studies are required.

How Real-World Data Can Facilitate the Development of Precision Medicine Treatment in Psychiatry

Precision medicine has the ambition to improve treatment response and clinical outcomes through patient stratification and holds great potential for the treatment of mental disorders. However, several important factors are needed to transform current practice into a precision psychiatry framework. Most important are 1) the generation of accessible large real-world training and test data including genomic data integrated from multiple sources, 2) the development and validation of advanced analytical tools for stratification and prediction, and 3) the development of clinically useful management platforms for patient monitoring that can be integrated into health care systems in real-life settings. This narrative review summarizes strategies for obtaining the key elements-well-powered samples from large biobanks integrated with electronic health records and health registry data using novel artificial intelligence algorithms-to predict outcomes in severe mental disorders and translate these models into clinical management and treatment approaches. Key elements are massive mental health data and novel artificial intelligence algorithms. For the clinical translation of these strategies, we discuss a precision medicine platform for improved management of mental disorders. We use cases to illustrate how precision medicine interventions could be brought into psychiatry to improve the clinical outcomes of mental disorders.

The genetic landscape of basal ganglia and implications for common brain disorders

The basal ganglia are subcortical brain structures involved in motor control, cognition, and emotion regulation. We conducted univariate and multivariate genome-wide association analyses (GWAS) to explore the genetic architecture of basal ganglia volumes using brain scans obtained from 34,794 Europeans with replication in 4,808 white and generalization in 5,220 non-white Europeans. Our multivariate GWAS identified 72 genetic loci associated with basal ganglia volumes with a replication rate of 55.6% at P < 0.05 and 87.5% showed the same direction, revealing a distributed genetic architecture across basal ganglia structures. Of these, 50 loci were novel, including exonic regions of APOE, NBR1 and HLAA. We examined the genetic overlap between basal ganglia volumes and several neurological and psychiatric disorders. The strongest genetic overlap was between basal ganglia and Parkinson's disease, as supported by robust LD-score regression-based genetic correlations. Mendelian randomization indicated genetic liability to larger striatal volume as potentially causal for Parkinson's disease, in addition to a suggestive causal effect of greater genetic liability to Alzheimer's disease on smaller accumbens. Functional analyses implicated neurogenesis, neuron differentiation and development in basal ganglia volumes. These results enhance our understanding of the genetic architecture and molecular associations of basal ganglia structure and their role in brain disorders.

[Genetic diagnostics of mental health disorders in adulthood]

This review article provides insights into the role of genetic diagnostics in adult mental health disorders. The importance of genetic factors in the development of mental illnesses, from rare genetic syndromes to common complex genetic disorders, is described. Current clinical characteristics that may warrant a genetic diagnostic work-up are highlighted, including intellectual disability, autism spectrum disorders and severe psychiatric conditions with specific comorbidities, such as organ malformations or epilepsy. The review discusses when genetic diagnostics are recommended according to current guidelines as well as situations where they might be considered even in the absence of explicit guideline recommendations. This is followed by an overview of the procedures and the currently used diagnostic methods. Current limitations and possible developments in the field of genetic diagnostics in psychiatry are discussed, including the fact that, for many mental health conditions, genetic testing is not yet part of standard clinical practice; however, in summary genetic causes should be considered more frequently in certain clinical constellations, and genetic diagnostics and counselling should be offered where appropriate.

Blood metabolites, neurocognition and psychiatric disorders: a Mendelian randomization analysis to investigate causal pathways

BACKGROUND

Neurocognitive dysfunction is observationally associated with the risk of psychiatric disorders. Blood metabolites, which are readily accessible, may become highly promising biomarkers for brain disorders. However, the causal role of blood metabolites in neurocognitive function, and the biological pathways underlying their association with psychiatric disorders remain unclear.

METHODS

To explore their putative causalities, we conducted bidirectional two-sample Mendelian randomization (MR) using genetic variants associated with 317 human blood metabolites (nmax = 215,551), g-Factor (an integrated index of multiple neurocognitive tests with nmax = 332,050), and 10 different psychiatric disorders (n = 9,725 to 807,553) from the large-scale genome-wide association studies of European ancestry. Mediation analysis was used to assess the potential causal pathway among the candidate metabolite, neurocognitive trait and corresponding psychiatric disorder.

RESULTS

MR evidence indicated that genetically predicted acetylornithine was positively associated with g-Factor (0.035 standard deviation units increase in g-Factor per one standard deviation increase in acetylornithine level; 95% confidence interval, 0.021 to 0.049; P = 1.15 × 10-6). Genetically predicted butyrylcarnitine was negatively associated with g-Factor (0.028 standard deviation units decrease in g-Factor per one standard deviation increase in genetically proxied butyrylcarnitine; 95% confidence interval, -0.041 to -0.015; P = 1.31 × 10-5). There was no evidence of associations between genetically proxied g-Factor and metabolites. Furthermore, the mediation analysis via two-step MR revealed that the causal pathway from acetylornithine to bipolar disorder was partly mediated by g-Factor, with a mediated proportion of 37.1%. Besides, g-Factor mediated the causal pathway from butyrylcarnitine to schizophrenia, with a mediated proportion of 37.5%. Other neurocognitive traits from different sources provided consistent findings.

CONCLUSION

Our results provide genetic evidence that acetylornithine protects against bipolar disorder through neurocognitive abilities, while butyrylcarnitine has an adverse effect on schizophrenia through neurocognition. These findings may provide insight into interventions at the metabolic level for risk of neurocognitive and related disorders.

Proposed Physiological Mechanisms Underlying the Association between Adverse Childhood Experiences and Mental Health Conditions: A Narrative Review

Adverse childhood experiences (ACEs; e.g., physical abuse) can impact lifelong mental health both directly and intergenerationally, with effects transmitted from the parent to the child. Several physiological mechanisms have been proposed to explain the impacts of ACEs on mental health. The purpose of this narrative review was to synthesize and critique the peer-reviewed literature on physiological mechanisms proposed to underlie the impacts of ACEs on mental health, specifically: (1) hypothalamic-pituitary-adrenal axis functioning, (2) inflammation, (3) genetic inheritance and differential susceptibility, (4) epigenetics, (5) brain structure and function, (6) oxidative stress, and (7) metabolic profiles. We searched Google Scholar using variations of the terms "adverse childhood experiences", "mechanisms", and "mental health" to locate relevant peer-reviewed literature. We also mined citations of the identified literature to find additional important sources. The role of inflammation in the etiology of mental health conditions among those exposed to ACEs appeared promising, followed by hypothalamic-pituitary-adrenal axis functioning, brain structure and function, genetics, epigenetics, metabolism, and lastly, oxidative stress. Replication studies that examine the associations among ACEs, genetic inheritance and differential susceptibility, epigenetics, oxidative stress, and metabolism are required to better define links with mental health.

Genetic association and causal effects between inflammatory bowel disease and conjunctivitis

Background

Inflammatory bowel disease (IBD) is often clinically associated with conjunctivitis, which may result from genetic associations and causal effects.

Methods

Genetic correlations were investigated through the genome-wide association study (GWAS) data on IBD and conjunctivitis using the linkage disequilibrium score regression (LDSC) and heritability estimated in summary statistics (HESS). The causal effect analysis was performed using four methods of Mendelian randomization (MR) and the genetic risk loci common to both diseases were identified by the statistical method of conditional/conjoint false discovery rate (cond/conjFDR), followed by genetic overlap analysis. Finally, a multi-trait GWAS analysis (MTAG) was performed to validate the identified shared loci.

Results

IBD (including CD and UC) and conjunctivitis showed a significant overall correlation at the genomic level; however, the local correlation of IBD and CD with conjunctivitis was significant and limited to chromosome 11. MR analysis suggested a significant positive and non-significant negative correlation between IBD (including CD and UC) and conjunctivitis. The conjFDR analysis confirmed the genetic overlap between the two diseases. Additionally, MTAG was employed to identify and validate multiple genetic risk loci.

Conclusion

The present study provides evidence of genetic structure and causal effects for the co-morbidity between IBD (both CD and UC) and conjunctivitis, expanding the epidemiologic understanding of the two diseases.

Clinical and genetic contributions to medical comorbidity in bipolar disorder: a study using electronic health records-linked biobank data

Bipolar disorder is a chronic and complex polygenic disease with high rates of comorbidity. However, the independent contribution of either diagnosis or genetic risk of bipolar disorder to the medical comorbidity profile of individuals with the disease remains unresolved. Here, we conducted a multi-step phenome-wide association study (PheWAS) of bipolar disorder using phenomes derived from the electronic health records of participants enrolled in the Mayo Clinic Biobank and the Mayo Clinic Bipolar Disorder Biobank. First, we explored the conditions associated with a diagnosis of bipolar disorder by conducting a phenotype-based PheWAS followed by LASSO-penalized regression to account for correlations within the phenome. Then, we explored the conditions associated with bipolar disorder polygenic risk score (BD-PRS) using a PRS-based PheWAS with a sequential exclusion approach to account for the possibility that diagnosis, instead of genetic risk, may drive such associations. 53,386 participants (58.7% women) with a mean age at analysis of 67.8 years (SD = 15.6) were included. A bipolar disorder diagnosis (n = 1479) was associated with higher rates of psychiatric conditions, injuries and poisonings, endocrine/metabolic and neurological conditions, viral hepatitis C, and asthma. BD-PRS was associated with psychiatric comorbidities but, in contrast, had no positive associations with general medical conditions. While our findings warrant confirmation with longitudinal-prospective studies, the limited associations between bipolar disorder genetics and medical conditions suggest that shared environmental effects or environmental consequences of diagnosis may have a greater impact on the general medical comorbidity profile of individuals with bipolar disorder than its genetic risk.

The Wnt signaling pathway in major depressive disorder: A systematic review of human studies

Despite uncertainty about the specific molecular mechanisms driving major depressive disorder (MDD), the Wnt signaling pathway stands out as a potentially influential factor in the pathogenesis of MDD. Known for its role in intercellular communication, cell proliferation, and fate, Wnt signaling has been implicated in diverse biological phenomena associated with MDD, spanning neurodevelopmental to neurodegenerative processes. In this systematic review, we summarize the functional differences in protein and gene expression of the Wnt signaling pathway, and targeted genetic association studies, to provide an integrated synthesis of available human data examining Wnt signaling in MDD. Thirty-three studies evaluating protein expression (n = 15), gene expression (n = 9), or genetic associations (n = 9) were included. Only fifteen demonstrated a consistently low overall risk of bias in selection, comparability, and exposure. We found conflicting observations of limited and distinct Wnt signaling components across diverse tissue sources. These data do not demonstrate involvement of Wnt signaling dysregulation in MDD. Given the well-established role of Wnt signaling in antidepressant response, we propose that a more targeted and functional assessment of Wnt signaling is needed to understand its role in depression pathophysiology. Future studies should include more components, assess multiple tissues concurrently, and follow a standardized approach.

Dynamic convergence of autism disorder risk genes across neurodevelopment

Over a hundred risk genes underlie risk for autism spectrum disorder (ASD) but the extent to which they converge on shared downstream targets to increase ASD risk is unknown. To test the hypothesis that cellular context impacts the nature of convergence, here we apply a pooled CRISPR approach to target 29 ASD loss-of-function genes in human induced pluripotent stem cell (hiPSC)-derived neural progenitor cells, glutamatergic neurons, and GABAergic neurons. Two distinct approaches (gene-level and network-level analyses) demonstrate that convergence is greatest in mature glutamatergic neurons. Convergent effects are dynamic, varying in strength, composition, and biological role between cell types, increasing with functional similarity of the ASD genes examined, and driven by cell-type-specific gene co-expression patterns. Stratification of ASD genes yield targeted drug predictions capable of reversing gene-specific convergent signatures in human cells and ASD-related behaviors in zebrafish. Altogether, convergent networks downstream of ASD risk genes represent novel points of individualized therapeutic intervention.