Risk in Relatives, Heritability, SNP-Based Heritability, and Genetic Correlations in Psychiatric Disorders: A Review

Exploring the relationship between depression and delinquency: a sibling comparison design using the NLSY

Relative to the general population, adolescents with psychiatric disorders such as major depression disorder are incarcerated (and reincarcerated) at higher rates. Current research is mixed on whether this association is a cause, consequence, or the product of selection. For example, aggression can lead to more depressive symptoms, yet depression is associated with antisocial behaviors (e.g., delinquency). To better understand the relationship between depression and delinquent behavior, we used the discordant kinship model to examine data from sibling pairs in the National Longitudinal Surveys of Youth 1979, a nationally representative study. By explicitly modeling within- and between-family variance, we reduced the influence of genetic and shared-environmental confounds on our analysis. Our results suggest that the relationship between depression and delinquency is not causal, but rather a product of selection.

Genome-wide study of half a million individuals with major depression identifies 697 independent associations, infers causal neuronal subtypes and biological targets for novel pharmacotherapies

In a genome-wide association study (GWAS) of 685,808 individuals with major depression (MD) and 4,364,225 controls from 29 countries and across diverse and admixed ancestries, we identify 697 independent associations at 636 genetic loci, 293 of which are novel. Using fine-mapping and functional genomic datasets, we find 308 high-confidence gene associations and enrichment of postsynaptic density and receptor clustering. Leveraging new single-cell gene expression data, we conducted a causal neural cell type enrichment analysis that implicated excitatory and inhibitory midbrain and forebrain neurons, peptidergic neurons, and medium spiny neurons in MD. Critically, our findings are enriched for the targets of antidepressants and provide potential antidepressant repurposing opportunities (e.g., pregabalin and modafinil). Polygenic scores (PGS) from European ancestries explained up to 5.7% of the variance in liability to MD in European samples and PGS trained using either European or multi-ancestry data significantly predicted case control status across all four diverse ancestries. These findings represent a major advance in our understanding of MD across global populations. We provide evidence that MD GWAS reveals known and novel biological targets that may be used to target and develop pharmacotherapies addressing the considerable unmet need for effective treatment.

Health, behavior, and social outcomes among offspring of parents with criminal convictions: a register-based study from Sweden

BACKGROUND

There is currently insufficient understanding of the health and behavior of children whose parents engage in criminal behavior. We examined associations between parental criminal convictions and wide range of offspring health, behavioral, and social outcomes by age 18 in a large, national sample, aiming to get a comprehensive picture of the risks among children of offending parents.

METHODS

We studied 1,013,385 individuals born in Sweden between 1987 and 1995, and their parents. Using data from several longitudinal nationwide registers, we investigated parental convictions and 85 offspring outcomes until the end of 2013, grouped into birth-related conditions, psychiatric and somatic disorders, accidents and injuries, mortality, school achievement, violent victimization, and criminality. Cox proportional hazards regression and logistic regression models were used to examine the associations. The role of genetic factors in intergenerational associations was studied in children-of-siblings analyses. We also examined the co-occurrence of multiple outcomes using Poisson regression.

RESULTS

A total of 223,319 (22.0%) individuals had one parent convicted and 31,241 (3.1%) had both parents convicted during the first 18 years of their life. The strongest associations were found between parental convictions and offspring behavioral problems, substance use disorders, poor school achievement, violent victimization, and criminality, with an approximately 2 to 2.5-fold increased risk in children with one convicted parent and 3- to 4-fold increased risk in children with two convicted parents. The risks were particularly elevated among children of incarcerated parents with a history of violent convictions. The associations appeared to be at least partly explained by genetic influences. Parental convictions were also associated with an increased likelihood of experiencing multiple outcomes.

CONCLUSIONS

Our findings help to calibrate the risks of a wide range of adverse outcomes associated with parental convictions and may be used to guide prevention efforts and identify key areas for future research.

Examining Differences in the Genetic and Functional Architecture of Attention-Deficit/Hyperactivity Disorder Diagnosed in Childhood and Adulthood

Background

Attention-deficit/hyperactivity disorder (ADHD) is a neurodevelopmental disorder with diagnostic criteria requiring symptoms to begin in childhood. We investigated whether individuals diagnosed as children differ from those diagnosed in adulthood with respect to shared and unique architecture at the genome-wide and gene expression level of analysis.

Methods

We used genomic structural equation modeling (SEM) to investigate differences in genetic correlations (rg) of childhood-diagnosed (ncases = 14,878) and adulthood-diagnosed (ncases = 6961) ADHD with 98 behavioral, psychiatric, cognitive, and health outcomes. We went on to apply transcriptome-wide SEM to identify functional annotations and patterns of gene expression associated with genetic risk sharing or divergence across the ADHD subgroups.

Results

Compared with the childhood subgroup, adulthood-diagnosed ADHD exhibited a significantly larger negative rg with educational attainment, the noncognitive skills of educational attainment, and age at first sexual intercourse. We observed a larger positive rg for adulthood-diagnosed ADHD with major depression, suicidal ideation, and a latent internalizing factor. At the gene expression level, transcriptome-wide SEM analyses revealed 22 genes that were significantly associated with shared genetic risk across the subtypes that reflected a mixture of coding and noncoding genes and included 15 novel genes relative to the ADHD subgroups.

Conclusions

This study demonstrated that ADHD diagnosed later in life shows much stronger genetic overlap with internalizing disorders and related traits. This may indicate the potential clinical relevance of distinguishing these subgroups or increased misdiagnosis for those diagnosed later in life. Top transcriptome-wide SEM results implicated genes related to neuronal function and clinical characteristics (e.g., sleep).

MIR137 polygenic risk for schizophrenia and ephrin-regulated pathway: Role in lateral ventricles and corpus callosum volume

Background/Objective. Enlarged lateral ventricle (LV) volume and decreased volume in the corpus callosum (CC) are hallmarks of schizophrenia (SZ). We previously showed an inverse correlation between LV and CC volumes in SZ, with global functioning decreasing with increased LV volume. This study investigates the relationship between LV volume, CC abnormalities, and the microRNA MIR137 and its regulated genes in SZ, because of MIR137's essential role in neurodevelopment. Methods. Participants were 1224 SZ probands and 1466 unaffected controls from the GENUS Consortium. Brain MRI scans, genotype, and clinical data were harmonized across cohorts and employed in the analyses. Results. Increased LV volumes and decreased CC central, mid-anterior, and mid-posterior volumes were observed in SZ probands. The MIR137-regulated ephrin pathway was significantly associated with CC:LV ratio, explaining a significant proportion (3.42 %) of CC:LV variance, and more than for LV and CC separately. Other pathways explained variance in either CC or LV, but not both. CC:LV ratio was also positively correlated with Global Assessment of Functioning, supporting previous subsample findings. SNP-based heritability estimates were higher for CC central:LV ratio (0.79) compared to CC or LV separately. Discussion. Our results indicate that the CC:LV ratio is highly heritable, influenced in part by variation in the MIR137-regulated ephrin pathway. Findings suggest that the CC:LV ratio may be a risk indicator in SZ that correlates with global functioning.

Genetic and phenotypic similarity across major psychiatric disorders: a systematic review and quantitative assessment

There is widespread overlap across major psychiatric disorders, and this is the case at different levels of observations, from genetic variants to brain structures and function and to symptoms. However, it remains unknown to what extent these commonalities at different levels of observation map onto each other. Here, we systematically review and compare the degree of similarity between psychiatric disorders at all available levels of observation. We searched PubMed and EMBASE between January 1, 2009 and September 8, 2022. We included original studies comparing at least four of the following five diagnostic groups: Schizophrenia, Bipolar Disorder, Major Depressive Disorder, Autism Spectrum Disorder, and Attention Deficit Hyperactivity Disorder, with measures of similarities between all disorder pairs. Data extraction and synthesis were performed by two independent researchers, following the PRISMA guidelines. As main outcome measure, we assessed the Pearson correlation measuring the degree of similarity across disorders pairs between studies and biological levels of observation. We identified 2975 studies, of which 28 were eligible for analysis, featuring similarity measures based on single-nucleotide polymorphisms, gene-based analyses, gene expression, structural and functional connectivity neuroimaging measures. The majority of correlations (88.6%) across disorders between studies, within and between levels of observation, were positive. To identify a consensus ranking of similarities between disorders, we performed a principal component analysis. Its first dimension explained 51.4% (95% CI: 43.2, 65.4) of the variance in disorder similarities across studies and levels of observation. Based on levels of genetic correlation, we estimated the probability of another psychiatric diagnosis in first-degree relatives and showed that they were systematically lower than those observed in population studies. Our findings highlight that genetic and brain factors may underlie a large proportion, but not all of the diagnostic overlaps observed in the clinic.

Classification of Schizophrenia, Bipolar Disorder and Major Depressive Disorder with Comorbid Traits and Deep Learning Algorithms

Recent GWASs have demonstrated that comorbid disorders share genetic liabilities. But whether and how these shared liabilities can be used for the classification and differentiation of comorbid disorders remains unclear. In this study, we use polygenic risk scores (PRSs) estimated from 42 comorbid traits and the deep neural networks (DNN) architecture to classify and differentiate schizophrenia (SCZ), bipolar disorder (BIP) and major depressive disorder (MDD). Multiple PRSs were obtained for individuals from the schizophrenia (SCZ) (cases = 6,317, controls = 7,240), bipolar disorder (BIP) (cases = 2,634, controls 4,425) and major depressive disorder (MDD) (cases = 1,704, controls = 3,357) datasets, and classification models were constructed with and without the inclusion of PRSs of the target (SCZ, BIP or MDD). Models with the inclusion of target PRSs performed well as expected. Surprisingly, we found that SCZ could be classified with only the PRSs from 35 comorbid traits (not including the target SCZ and directly related traits) (accuracy 0.760 ± 0.007, AUC 0.843 ± 0.005). Similar results were obtained for BIP (33 traits, accuracy 0.768 ± 0.007, AUC 0.848 ± 0.009), and MDD (36 traits, accuracy 0.794 ± 0.010, AUC 0.869 ± 0.004). Furthermore, these PRSs from comorbid traits alone could effectively differentiate unaffected controls, SCZ, BIP, and MDD patients (average categorical accuracy 0.861 ± 0.003, average AUC 0.961 ± 0.041). These results suggest that the shared liabilities from comorbid traits alone may be sufficient to classify SCZ, BIP and MDD. More importantly, these results imply that a data-driven and objective diagnosis and differentiation of SCZ, BIP and MDD may be feasible.

UNC5C: Novel Gene Associated with Psychiatric Disorders Impacts Dysregulation of Axon Guidance Pathways

The UNC-5 family of netrin receptor genes, predominantly expressed in brain tissues, plays a pivotal role in various neuronal processes. Mutations in genes involved in axon development contribute to a wide spectrum of human diseases, including developmental, neuropsychiatric, and neurodegenerative disorders. The NTN1/DCC signaling pathway, interacting with UNC5C, plays a crucial role in central nervous system axon guidance and has been associated with psychiatric disorders during adolescence in humans. Whole-exome sequencing analysis unveiled two compound heterozygous causative mutations within the UNC5C gene in a patient diagnosed with psychiatric disorders. In silico analysis demonstrated that neither of the observed variants affected the allosteric linkage between UNC5C and NTN1. In fact, these mutations are located within crucial cytoplasmic domains, specifically ZU5 and the region required for the netrin-mediated axon repulsion of neuronal growth cones. These domains play a critical role in forming the supramodular protein structure and directly interact with microtubules, thereby ensuring the functionality of the axon repulsion process. We emphasize that these mutations disrupt the aforementioned processes, thereby associating the UNC5C gene with psychiatric disorders for the first time and expanding the number of genes related to psychiatric disorders. Further research is required to validate the correlation of the UNC5C gene with psychiatric disorders, but we suggest including it in the genetic analysis of patients with psychiatric disorders.

Genetic risk for hospitalization of African American patients with severe mental illness reveals HLA loci

Background

Mood disorders such as major depressive and bipolar disorders, along with posttraumatic stress disorder (PTSD), schizophrenia (SCZ), and other psychotic disorders, constitute serious mental illnesses (SMI) and often lead to inpatient psychiatric care for adults. Risk factors associated with increased hospitalization rate in SMI (H-SMI) are largely unknown but likely involve a combination of genetic, environmental, and socio-behavioral factors. We performed a genome-wide association study in an African American cohort to identify possible genes associated with hospitalization due to SMI (H-SMI).

Methods

Patients hospitalized for psychiatric disorders (H-SMI; n=690) were compared with demographically matched controls (n=4467). Quality control and imputation of genome-wide data were performed following the Psychiatric Genetic Consortium (PGC)-PTSD guidelines. Imputation of the Human Leukocyte Antigen (HLA) locus was performed using the HIBAG package.

Results

Genome-wide association analysis revealed a genome-wide significant association at 6p22.1 locus in the ubiquitin D (UBD/FAT10) gene (rs362514, p=9.43x10-9) and around the HLA locus. Heritability of H-SMI (14.6%) was comparable to other psychiatric disorders (4% to 45%). We observed a nominally significant association with 2 HLA alleles: HLA-A*23:01 (OR=1.04, p=2.3x10-3) and HLA-C*06:02 (OR=1.04, p=1.5x10-3). Two other genes (VSP13D and TSPAN9), possibly associated with immune response, were found to be associated with H-SMI using gene-based analyses.

Conclusion

We observed a strong association between H-SMI and a locus that has been consistently and strongly associated with SCZ in multiple studies (6p21.32-p22.1), possibly indicating an involvement of the immune system and the immune response in the development of severe transdiagnostic SMI.

Polygenic risk for major depression, attention deficit hyperactivity disorder, neuroticism, and schizophrenia are correlated with experience of intimate partner violence

Research has suggested that mental illness may be a risk factor for, as well as a sequela of, experiencing intimate partner violence (IPV). The association between IPV and mental illness may also be due in part to gene-environment correlations. Using polygenic risk scores for six psychiatric disorders - attention-deficit hyperactivity disorder (ADHD), autism spectrum disorder (ASD), bipolar disorder (BPD), major depressive disorder (MDD), neuroticism, and schizophrenia-and a combined measure of overall genetic risk for mental illness, we tested whether women's genetic risk for mental illness was associated with the experience of three types of intimate partner violence. In this cohort of women of European ancestry (N = 11,095), participants in the highest quintile of genetic risk for ADHD (OR range: 1.38-1.49), MDD (OR range: 1.28-1.43), neuroticism (OR range: (1.18-1.25), schizophrenia (OR range: 1.30-1.34), and overall genetic risk (OR range: 1.30-1.41) were at higher risk for experiencing more severe emotional and physical abuse, and, except schizophrenia, more severe sexual abuse, as well as more types of abuse and chronic abuse. In addition, participants in the highest quintile of genetic risk for neuroticism (OR = 1.43 95% CI: 1.18, 1.72), schizophrenia (OR = 1.33 95% CI: 1.10, 1.62), and the overall genetic risk (OR = 1.40 95% CI: 1.15, 1.71) were at higher risk for experiencing intimate partner intimidation and control. Participants in the highest quintile of genetic risk for ADHD, ASD, MDD, schizophrenia, and overall genetic risk, compared to the lowest quintile, were at increased risk for experiencing harassment from a partner (OR range: 1.22-1.92). No associations were found between genetic risk for BPD with IPV. A better understanding of the salience of the multiple possible pathways linking genetic risk for mental illness with risk for IPV may aid in preventing IPV victimization or re-victimization.

Mood and microbes: a comprehensive review of intestinal microbiota's impact on depression

Depression is considered a multifaceted and intricate mental disorder of growing concern due to its significant impact on global health issues. The human gut microbiota, also known as the "second brain," has an important role in the CNS by regulating it through chemical, immunological, hormonal, and neurological processes. Various studies have found a significant bidirectional link between the brain and the gut, emphasizing the onset of depression therapies. The biological and molecular processes underlying depression and microbiota are required, as the bidirectional association may represent a novel study. However, profound insights into the stratification and diversity of the gut microbiota are still uncommon. This article investigates the emerging evidence of a bacterial relationship between the gut and the brain's neurological system and its potential pathogenicity and relevance. The interplay of microbiota, immune system, nervous system neurotransmitter synthesis, and neuroplasticity transitions is also widely studied. The consequences of stress, dietary fibers, probiotics, prebiotics, and antibiotics on the GB axis are being studied. Multiple studies revealed the processes underlying this axis and led to the development of effective microbiota-based drugs for both prevention and treatment. Therefore, the results support the hypothesis that gut microbiota influences depression and provide a promising area of research for an improved knowledge of the etiology of the disease and future therapies.

The schizophrenia syndrome, circa 2024: What we know and how that informs its nature

With new data about different aspects of schizophrenia being continually generated, it becomes necessary to periodically revisit exactly what we know. Along with a need to review what we currently know about schizophrenia, there is an equal imperative to evaluate the construct itself. With these objectives, we undertook an iterative, multi-phase process involving fifty international experts in the field, with each step building on learnings from the prior one. This review assembles currently established findings about schizophrenia (construct, etiology, pathophysiology, clinical expression, treatment) and posits what they reveal about its nature. Schizophrenia is a heritable, complex, multi-dimensional syndrome with varying degrees of psychotic, negative, cognitive, mood, and motor manifestations. The illness exhibits a remitting and relapsing course, with varying degrees of recovery among affected individuals with most experiencing significant social and functional impairment. Genetic risk factors likely include thousands of common genetic variants that each have a small impact on an individual's risk and a plethora of rare gene variants that have a larger individual impact on risk. Their biological effects are concentrated in the brain and many of the same variants also increase the risk of other psychiatric disorders such as bipolar disorder, autism, and other neurodevelopmental conditions. Environmental risk factors include but are not limited to urban residence in childhood, migration, older paternal age at birth, cannabis use, childhood trauma, antenatal maternal infection, and perinatal hypoxia. Structural, functional, and neurochemical brain alterations implicate multiple regions and functional circuits. Dopamine D-2 receptor antagonists and partial agonists improve psychotic symptoms and reduce risk of relapse. Certain psychological and psychosocial interventions are beneficial. Early intervention can reduce treatment delay and improve outcomes. Schizophrenia is increasingly considered to be a heterogeneous syndrome and not a singular disease entity. There is no necessary or sufficient etiology, pathology, set of clinical features, or treatment that fully circumscribes this syndrome. A single, common pathophysiological pathway appears unlikely. The boundaries of schizophrenia remain fuzzy, suggesting the absence of a categorical fit and need to reconceptualize it as a broader, multi-dimensional and/or spectrum construct.

A resource of induced pluripotent stem cell (iPSC) lines including clinical, genomic, and cellular data from genetically isolated families with mood and psychotic disorders

Genome-wide (GWAS) and copy number variant (CNV) association studies have reproducibly identified numerous risk alleles associated with bipolar disorder (BD), major depressive disorder (MDD), and schizophrenia (SCZ), but biological characterization of these alleles lags gene discovery, owing to the inaccessibility of live human brain cells and inadequate animal models for human psychiatric conditions. Human-derived induced pluripotent stem cells (iPSCs) provide a renewable cellular reagent that can be differentiated into living, disease-relevant cells and 3D brain organoids carrying the full complement of genetic variants present in the donor germline. Experimental studies of iPSC-derived cells allow functional characterization of risk alleles, establishment of causal relationships between genes and neurobiology, and screening for novel therapeutics. Here we report the creation and availability of an iPSC resource comprising clinical, genomic, and cellular data obtained from genetically isolated families with BD and related conditions. Results from the first 324 study participants, 61 of whom have validated pluripotent clones, show enrichment of rare single nucleotide variants and CNVs overlapping many known risk genes and pathogenic CNVs. This growing iPSC resource is available to scientists pursuing functional genomic studies of BD and related conditions.

Allostatic load in early adolescence: gene / environment contributions and relevance for mental health

Background

Allostatic load is the cumulative "wear and tear" on the body due to chronic adversity. We aimed to test poly-environmental (exposomic) and polygenic contributions to allostatic load and their combined contribution to early adolescent mental health.

Methods

We analyzed data on N = 5,035 diverse youth (mean age 12) from the Adolescent Brain Cognitive Development Study (ABCD). Using dimensionality reduction method, we calculated and overall allostatic load score (AL) using body mass index [BMI], waist circumference, blood pressure, blood glycemia, blood cholesterol, and salivary DHEA. Childhood exposomic risk was quantified using multi-level environmental exposures before age 11. Genetic risk was quantified using polygenic risk scores (PRS) for metabolic system susceptibility (type 2 diabetes [T2D]) and stress-related psychiatric disease (major depressive disorder [MDD]). We used linear mixed effects models to test main, additive, and interactive effects of exposomic and polygenic risk (independent variables) on AL (dependent variable). Mediation models tested the mediating role of AL on the pathway from exposomic and polygenic risk to youth mental health. Models adjusted for demographics and genetic principal components.

Results

We observed disparities in AL with non-Hispanic White youth having significantly lower AL compared to Hispanic and Non-Hispanic Black youth. In the diverse sample, childhood exposomic burden was associated with AL in adolescence (beta=0.25, 95%CI 0.22-0.29, P<.001). In European ancestry participants (n=2,928), polygenic risk of both T2D and depression was associated with AL (T2D-PRS beta=0.11, 95%CI 0.07-0.14, P<.001; MDD-PRS beta=0.05, 95%CI 0.02-0.09, P=.003). Both polygenic scores showed significant interaction with exposomic risk such that, with greater polygenic risk, the association between exposome and AL was stronger. AL partly mediated the pathway to youth mental health from exposomic risk and from MDD-PRS, and fully mediated the pathway from T2D-PRS.

Conclusions

AL can be quantified in youth using anthropometric and biological measures and is mapped to exposomic and polygenic risk. Main and interactive environmental and genetic effects support a diathesis-stress model. Findings suggest that both environmental and genetic risk be considered when modeling stress-related health conditions.

Genetic contributions to brain serotonin transporter levels in healthy adults

The serotonin transporter (5-HTT) critically shapes serotonin neurotransmission by regulating extracellular brain serotonin levels; it remains unclear to what extent 5-HTT levels in the human brain are genetically determined. Here we applied [11C]DASB positron emission tomography to image brain 5-HTT levels and evaluated associations with five common serotonin-related genetic variants that might indirectly regulate 5-HTT levels (BDNF rs6265, SLC6A4 5-HTTLPR, HTR1A rs6295, HTR2A rs7333412, and MAOA rs1137070) in 140 healthy volunteers. In addition, we explored whether these variants could predict in vivo 5-HTT levels using a five-fold cross-validation random forest framework. MAOA rs1137070 T-carriers showed significantly higher brain 5-HTT levels compared to C-homozygotes (2-11% across caudate, putamen, midbrain, thalamus, hippocampus, amygdala and neocortex). We did not observe significant associations for the HTR1A rs6295 and HTR2A rs7333412 genotypes. Our previously observed lower subcortical 5-HTT availability for rs6265 met-carriers remained in the presence of these additional variants. Despite this significant association, our prediction models showed that genotype moderately improved prediction of 5-HTT in caudate, but effects were not statistically significant after adjustment for multiple comparisons. Our observations provide additional evidence that serotonin-related genetic variants modulate adult human brain serotonin neurotransmission.

Epigenetic regulation in major depression and other stress-related disorders: molecular mechanisms, clinical relevance and therapeutic potential

Major depressive disorder (MDD) is a chronic, generally episodic and debilitating disease that affects an estimated 300 million people worldwide, but its pathogenesis is poorly understood. The heritability estimate of MDD is 30-40%, suggesting that genetics alone do not account for most of the risk of major depression. Another factor known to associate with MDD involves environmental stressors such as childhood adversity and recent life stress. Recent studies have emerged to show that the biological impact of environmental factors in MDD and other stress-related disorders is mediated by a variety of epigenetic modifications. These epigenetic modification alterations contribute to abnormal neuroendocrine responses, neuroplasticity impairment, neurotransmission and neuroglia dysfunction, which are involved in the pathophysiology of MDD. Furthermore, epigenetic marks have been associated with the diagnosis and treatment of MDD. The evaluation of epigenetic modifications holds promise for further understanding of the heterogeneous etiology and complex phenotypes of MDD, and may identify new therapeutic targets. Here, we review preclinical and clinical epigenetic findings, including DNA methylation, histone modification, noncoding RNA, RNA modification, and chromatin remodeling factor in MDD. In addition, we elaborate on the contribution of these epigenetic mechanisms to the pathological trait variability in depression and discuss how such mechanisms can be exploited for therapeutic purposes.

Universal probe-based SNP genotyping with visual readout: a robust and versatile method

Detection of single nucleotide polymorphisms (SNPs) is critical for personalized clinical diagnosis, treatment, and medication. Current clinical detection methods suffer from primer dimerization and require the redesigning of reaction systems for different targets, resulting in a time-consuming and laborious process. Here, we present a robust and versatile method for SNP typing by using tailed primers and universal small molecule probes in combination with a visualized lateral flow assay (LFA). This approach enables not only rapid typing of different targets, but also eliminates the interference of primer dimers and enhances the accuracy and reliability of the results. Our proposed universal assay has been successfully applied to the typing of four SNP loci of clinical samples to verify the accuracy and universality, and the results are consistent with those obtained by Sanger sequencing. Therefore, our study establishes a new universal "typing formula" using nucleic acid tags and small molecule probes that provides a powerful genotyping platform for genetic analysis and molecular diagnostics.

Imputed Gene Expression versus Single Nucleotide Polymorphism in Predicting Gray Matter Phenotypes

Genetics plays an important role in psychiatric disorders. A clinically relevant question is whether we can predict psychiatric traits from genetics, which holds promise for early detection and tailored intervention. Imputed gene expression, also known as genetically-regulated expression (GRE), reflects the tissue-specific regulatory effects of multiple single nucleotide polymorphisms (SNPs) on genes. In this work, we explored the utility of GRE for trait association studies and how the GRE-based polygenic risk score (gPRS) compared with SNP-based PRS (sPRS) in predicting psychiatric traits. A total of 13 schizophrenia-related gray matter networks identified in another study served as the target brain phenotypes for assessing genetic associations and prediction accuracies in 34,149 individuals from the UK Biobank cohort. GRE was computed leveraging MetaXcan and GTEx tools for 56,348 genes across 13 available brain tissues. We then estimated the effects of individual SNPs and genes separately on each tested brain phenotype in the training set. The effect sizes were then used to compute gPRS and sPRS in the testing set, whose correlations with the brain phenotypes were used to assess the prediction accuracy. The results showed that, with the testing sample size set to 1,138, for training sample sizes from 1,138 up to 33,011, overall both gPRS and sPRS successfully predicted the brain phenotypes with significant correlations observed in the testing set, and higher accuracies noted for larger training sets. In addition, gPRS outperformed sPRS by showing significantly higher prediction accuracies across 13 brain phenotypes, with greater improvement noted for training sample sizes below ∼15,000. These findings support that GRE may serve as the primary genetic variable in brain phenotype association and prediction studies. Future imaging genetic studies may consider GRE as an option depending on the available sample size.

Polygenic Risk for Schizophrenia, Major Depression, and Post-traumatic Stress Disorder and Hippocampal Subregion Volumes in Middle Childhood

Studies demonstrate that individuals with diagnoses for Major Depressive Disorder (MDD), Post-traumatic Stress Disorder (PTSD), and Schizophrenia (SCZ) may exhibit smaller hippocampal gray matter relative to otherwise healthy controls, although the effect sizes vary in each disorder. Existing work suggests that hippocampal abnormalities in each disorder may be attributable to genetic liability and/or environmental variables. The following study uses baseline data from the Adolescent Brain and Cognitive Development[Formula: see text] Study (ABCD Study[Formula: see text]) to address three open questions regarding the relationship between genetic risk for each disorder and hippocampal volume reductions: (a) whether polygenic risk scores (PGRS) for MDD, PTSD, and SCZ are related to hippocampal volume; (b) whether PGRS for MDD, PTSD, and SCZ are differentially related to specific hippocampal subregions along the longitudinal axis; and (c) whether the association between PGRS for MDD, PTSD, and SCZ and hippocampal volume is moderated by sex and/or environmental adversity. In short, we did not find associations between PGRS for MDD, PTSD, and SCZ to be significantly related to any hippocampal subregion volumes. Furthermore, neither sex nor enviornmental adversity significantly moderated these associations. Our study provides an important null finding on the relationship genetic risk for MDD, PTSD, and SCZ to measures of hippocampal volume.

A meta-analysis of genetic effects associated with neurodevelopmental disorders and co-occurring conditions

A systematic understanding of the aetiology of neurodevelopmental disorders (NDDs) and their co-occurrence with other conditions during childhood and adolescence remains incomplete. In the current meta-analysis, we synthesized the literature on (1) the contribution of genetic and environmental factors to NDDs, (2) the genetic and environmental overlap between different NDDs, and (3) the co-occurrence between NDDs and disruptive, impulse control and conduct disorders (DICCs). Searches were conducted across three platforms: Web of Science, Ovid Medline and Ovid Embase. Studies were included only if 75% or more of the sample consisted of children and/or adolescents and the studies had measured the aetiology of NDDs and DICCs using single-generation family designs or genomic methods. Studies that had selected participants on the basis of unrelated diagnoses or injuries were excluded. We performed multilevel, random-effects meta-analyses on 296 independent studies, including over four million (partly overlapping) individuals. We further explored developmental trajectories and the moderating roles of gender, measurement, geography and ancestry. We found all NDDs to be substantially heritable (family-based heritability, 0.66 (s.e. = 0.03); SNP heritability, 0.19 (s.e. = 0.03)). Meta-analytic genetic correlations between NDDs were moderate (grand family-based genetic correlation, 0.36 (s.e. = 0.12); grand SNP-based genetic correlation, 0.39 (s.e. = 0.19)) but differed substantially between pairs of disorders. The genetic overlap between NDDs and DICCs was strong (grand family-based genetic correlation, 0.62 (s.e. = 0.20)). While our work provides evidence to inform and potentially guide clinical and educational diagnostic procedures and practice, it also highlights the imbalance in the research effort that has characterized developmental genetics research.

DRAGON-Data: a platform and protocol for integrating genomic and phenotypic data across large psychiatric cohorts

BACKGROUND

Current psychiatric diagnoses, although heritable, have not been clearly mapped onto distinct underlying pathogenic processes. The same symptoms often occur in multiple disorders, and a substantial proportion of both genetic and environmental risk factors are shared across disorders. However, the relationship between shared symptoms and shared genetic liability is still poorly understood.

AIMS

Well-characterised, cross-disorder samples are needed to investigate this matter, but few currently exist. Our aim is to develop procedures to purposely curate and aggregate genotypic and phenotypic data in psychiatric research.

METHOD

As part of the Cardiff MRC Mental Health Data Pathfinder initiative, we have curated and harmonised phenotypic and genetic information from 15 studies to create a new data repository, DRAGON-Data. To date, DRAGON-Data includes over 45 000 individuals: adults and children with neurodevelopmental or psychiatric diagnoses, affected probands within collected families and individuals who carry a known neurodevelopmental risk copy number variant.

RESULTS

We have processed the available phenotype information to derive core variables that can be reliably analysed across groups. In addition, all data-sets with genotype information have undergone rigorous quality control, imputation, copy number variant calling and polygenic score generation.

CONCLUSIONS

DRAGON-Data combines genetic and non-genetic information, and is available as a resource for research across traditional psychiatric diagnostic categories. Algorithms and pipelines used for data harmonisation are currently publicly available for the scientific community, and an appropriate data-sharing protocol will be developed as part of ongoing projects (DATAMIND) in partnership with Health Data Research UK.

Beyond monoamines: I. Novel targets and radiotracers for Positron emission tomography imaging in psychiatric disorders

With the emergence of positron emission tomography (PET) in the late 1970s, psychiatry had access to a tool capable of non-invasive assessment of human brain function. Early applications in psychiatry focused on identifying characteristic brain blood flow and metabolic derangements using radiotracers such as [¹⁵ O]H₂ O and [¹⁸ F]FDG. Despite the success of these techniques, it became apparent that more specific probes were needed to understand the neurochemical bases of psychiatric disorders. The first neurochemical PET imaging probes targeted sites of action of neuroleptic (dopamine D₂ receptors) and psychoactive (serotonin receptors) drugs. Based on the centrality of monoamine dysfunction in psychiatric disorders and the measured success of monoamine-enhancing drugs in treating them, the next 30 years witnessed the development of an armamentarium of PET radiopharmaceuticals and imaging methodologies for studying monoamines. Continued development of monoamine-enhancing drugs over this time however was less successful, realizing only modest gains in efficacy and tolerability. As patent protection for many widely prescribed and profitable psychiatric drugs lapsed, drug development pipelines shifted away from monoamines in search of novel targets with the promises of improved efficacy, or abandoned altogether. Over this period, PET radiopharmaceutical development activities closely paralleled drug development priorities resulting in the development of new PET imaging agents for non-monoamine targets. Part one of this review will briefly survey novel PET imaging targets with relevance to the field of psychiatry, which include the metabotropic glutamate receptor type 5 (mGluR5), purinergic P₂ X₇ receptor, type 1 cannabinoid receptor (CB₁ ), phosphodiesterase 10A (PDE10A), and describe radiotracers developed for these and other targets that have matured to human subject investigations. Current limitations of the targets and techniques will also be discussed.

Polygenic architecture of rare coding variation across 394,783 exomes

Both common and rare genetic variants influence complex traits and common diseases. Genome-wide association studies have identified thousands of common-variant associations, and more recently, large-scale exome sequencing studies have identified rare-variant associations in hundreds of genes1-3. However, rare-variant genetic architecture is not well characterized, and the relationship between common-variant and rare-variant architecture is unclear4. Here we quantify the heritability explained by the gene-wise burden of rare coding variants across 22 common traits and diseases in 394,783 UK Biobank exomes5. Rare coding variants (allele frequency < 1 × 10-3) explain 1.3% (s.e. = 0.03%) of phenotypic variance on average-much less than common variants-and most burden heritability is explained by ultrarare loss-of-function variants (allele frequency < 1 × 10-5). Common and rare variants implicate the same cell types, with similar enrichments, and they have pleiotropic effects on the same pairs of traits, with similar genetic correlations. They partially colocalize at individual genes and loci, but not to the same extent: burden heritability is strongly concentrated in significant genes, while common-variant heritability is more polygenic, and burden heritability is also more strongly concentrated in constrained genes. Finally, we find that burden heritability for schizophrenia and bipolar disorder6,7 is approximately 2%. Our results indicate that rare coding variants will implicate a tractable number of large-effect genes, that common and rare associations are mechanistically convergent, and that rare coding variants will contribute only modestly to missing heritability and population risk stratification.

Concerns about the use of polygenic embryo screening for psychiatric and cognitive traits

Private companies have begun offering services to allow parents undergoing in-vitro fertilisation to screen embryos for genetic risk of complex diseases, including psychiatric disorders. This procedure, called polygenic embryo screening, raises several difficult scientific and ethical issues, as discussed in this Personal View. Polygenic embryo screening depends on the statistical properties of polygenic risk scores, which are complex and not well studied in the context of this proposed clinical application. The clinical, social, and ethical implications of polygenic embryo screening have barely been discussed among relevant stakeholders. To our knowledge, the International Society of Psychiatric Genetics is the first professional biomedical organisation to issue a statement regarding polygenic embryo screening. For the reasons discussed in this Personal View, the Society urges caution and calls for additional research and oversight on the use of polygenic embryo screening.

Early childhood developmental vulnerability associated with parental mental disorder comorbidity

OBJECTIVES

Parental mental health has a profound influence on the mental health and well-being of their offspring. With comorbid mental disorders generally the rule rather than the exception, increased knowledge of the impact of parental mental disorder comorbidity on early child development may facilitate improved targeting and delivery of early intervention for vulnerable offspring.

METHODS

Participants were 66,154 children and their parents in the New South Wales Child Development Study - a prospective, longitudinal, record-linkage study of a population cohort of children born in NSW between 2002 and 2004. Early childhood developmental vulnerability was assessed at age ~5 years using the Australian Early Development Census, and information on parental mental disorders was obtained from administrative health records. Binomial and multinomial logistic regression were used to assess the relationship between parental mental disorders and early childhood developmental vulnerability on emotional and behavioural domains, as well as membership of latent developmental risk classes reflecting particular classes of vulnerability.

RESULTS

Multiple diagnoses of mental disorders in mothers and fathers were associated with an increased likelihood of early childhood emotional and behavioural developmental vulnerability in offspring, relative to parents without mental disorder. The likelihood of offspring vulnerability increased with the number of parental comorbidities, particularly maternal comorbidities.

CONCLUSION

Early childhood developmental vulnerability was strongly associated with parental mental ill-health, with the strength of associations increasing in line with a greater number of mental disorder diagnoses among mothers and fathers. New and expectant parents diagnosed with multiple mental disorders should be prioritised for intervention, including attention to the developmental well-being of their offspring.

Novel functional genomics approaches bridging neuroscience and psychiatry

The possibility of establishing a metric of individual genetic risk for a particular disease or trait has sparked the interest of the clinical and research communities, with many groups developing and validating genomic profiling methodologies for their potential application in clinical care. Current approaches for calculating genetic risk to specific psychiatric conditions consist of aggregating genome-wide association studies-derived estimates into polygenic risk scores, which broadly represent the number of inherited risk alleles for an individual. While the traditional approach for polygenic risk score calculation aggregates estimates of gene-disease associations, novel alternative approaches have started to consider functional molecular phenotypes that are closer to genetic variation and are less penalized by the multiple testing required in genome-wide association studies. Moving the focus from genotype-disease to genotype-gene regulation frameworks, these novel approaches incorporate prior knowledge regarding biological processes involved in disease and aggregate estimates for the association of genotypes and phenotypes using multi-omics data modalities. In this review, we discuss and list different functional genomics tools that can be used and integrated to inform researchers and clinicians for a better understanding and diagnosis of psychopathology. We suggest that these novel approaches can help generate biologically driven hypotheses for polygenic signals that can ultimately serve the clinical community as potential biomarkers of psychiatric disease susceptibility.

Specificity of Psychiatric Polygenic Risk Scores and their Effects on Associated Risk Phenotypes

Background

Polygenic risk scores (PRSs) are indices of genetic liability for illness, but their clinical utility for predicting risk for a specific psychiatric disorder is limited. Genetic overlap among disorders and their effects on allied phenotypes may be a possible explanation, but this has been difficult to quantify given focus on singular disorders and/or allied phenotypes.

Methods

We constructed PRSs for 5 psychiatric disorders (schizophrenia, bipolar disorder, major depressive disorder, autism spectrum disorder, attention-deficit/hyperactivity disorder) and 3 nonpsychiatric control traits (height, type II diabetes, irritable bowel disease) in the UK Biobank (N = 31,616) and quantified associations between PRSs and phenotypes allied with mental illness: behavioral (symptoms, cognition, trauma) and brain measures from magnetic resonance imaging. We then evaluated the extent of specificity among PRSs and their effects on these allied phenotypes.

Results

Correlations among psychiatric PRSs replicated previous work, with overlap between schizophrenia and bipolar disorder, which was distinct from overlap between autism spectrum disorder and attention-deficit/hyperactivity disorder; overlap between psychiatric and control PRSs was minimal. There was, however, substantial overlap of PRS effects on allied phenotypes among psychiatric disorders and among psychiatric disorders and control traits, where the extent and pattern of overlap was phenotype specific.

Conclusions

Results show that genetic distinctions between psychiatric disorders and between psychiatric disorders and control traits exist, but this does not extend to their effects on allied phenotypes. Although overlap can be informative, work is needed to construct PRSs that will function at the level of specificity needed for clinical application.

Genetics in psychiatry: Methods, clinical applications and future perspectives

Psychiatric disorders and related traits have a demonstrated genetic component, with heritability estimated by twin studies generally between 80% and 40%. Their pathogenesis is complex and multi-determined: environmental factors interact with a polygenic architecture, making difficult the development of models able to stratify patients or predict mental health outcomes. Despite this difficult challenge, relevant progress has been made in the field of psychiatric genetics in recent years. This review aims to present the main current methods in psychiatric genetics, their output, limitations, clinical applications, and possible future developments. Genome-wide association studies (GWASs) performed in increasingly large samples have led to the identification of replicated genetic loci associated with the risk of major psychiatric disorders, including schizophrenia and mood disorders. Statistical and biological approaches have been developed to improve our understanding of the etiopathogenetic mechanisms behind genome-wide significant associations, as well as for estimating the cumulative effect of risk variants at the individual level and the genetic overlap between different disorders, as pleiotropy is the rule rather than the exception. Clinical applications are available in the pharmacogenetics field. The main issues that remain to be addressed include improving ethnic diversity in genetic studies and the optimization of statistical power through methodological improvements, such as the definition of dimensional phenotypes with specific biological correlates and the integration of different types of omics data.

Associations between low parental education, childhood adversities and sickness absence in midlife public sector employees

AIMS

Parental education and childhood adversities are associated with long-term work disability but their contribution to sickness absence is largely unknown. We aimed to examine the associations between parental education, childhood adversities and self-certified and medically-certified sickness absence among midlife employees.

METHODS

The Helsinki Health Study baseline survey data (2000-2002) of 40-to-60-year-old municipal employees were linked with sickness absence data from the employer's register. Self-certified (1-3 days) and medically-certified (>3 days) sickness absence spells were followed from 2003 until the end of 2008. The study included 5728 employees. The analyses were made by Poisson regression and the results are presented as rate ratios (RRs) and their 95% confidence intervals (CIs).

RESULTS

Low maternal education was associated with self-certified sickness absence (RR 1.32, 95% CI 1.13-1.55) among women only whereas both low maternal (1.49, 1.26-1.77) and low paternal education (1.48, 1.32-1.67) were associated with medically-certified sickness absence. Adjustment for own occupational class mainly abolished these associations. Having experienced any childhood adversity was associated with self-certified (1.18, 1.12-1.25) and medically-certified (1.22, 1.15-1.30) sickness absence. In addition, childhood economic difficulties, childhood illness, parental divorce, parental mental illness, parental alcohol problems and bullying were each associated both with self-certified and with medically-certified sickness absence. The associations mainly remained after adjustments for occupational class, marital status, working condition, body mass index and health behaviours.

CONCLUSIONS

Low parental education and childhood adversities contributed to midlife sickness absence. Promoting well-being of families with children might help sustain adult work ability and prevent sickness absence still in midlife.

Genetic heterogeneity and subtypes of major depression

Major depression (MD) is a heterogeneous disorder; however, the extent to which genetic factors distinguish MD patient subgroups (genetic heterogeneity) remains uncertain. This study sought evidence for genetic heterogeneity in MD. Using UK Biobank cohort, the authors defined 16 MD subtypes within eight comparison groups (vegetative symptoms, symptom severity, comorbid anxiety disorder, age at onset, recurrence, suicidality, impairment, and postpartum depression; N ~ 3000-47000). To compare genetic component of these subtypes, subtype-specific genome-wide association studies were performed to estimate SNP-heritability, and genetic correlations within subtype comparison and with other related disorders/traits. The findings indicated that MD subtypes were divergent in their SNP-heritability, and genetic correlations both within subtype comparisons and with other related disorders/traits. Three subtype comparisons (vegetative symptoms, age at onset, and impairment) showed significant differences in SNP-heritability; while genetic correlations within subtype comparisons ranged from 0.55 to 0.86, suggesting genetic profiles are only partially shared among MD subtypes. Furthermore, subtypes that are more clinically challenging, e.g., early-onset, recurrent, suicidal, more severely impaired, had stronger genetic correlations with other psychiatric disorders. MD with atypical-like features showed a positive genetic correlation (+0.40) with BMI while a negative correlation (-0.09) was found in those without atypical-like features. Novel genomic loci with subtype-specific effects were identified. These results provide the most comprehensive evidence to date for genetic heterogeneity within MD, and suggest that the phenotypic complexity of MD can be effectively reduced by studying the subtypes which share partially distinct etiologies.

Evaluating risk for alcohol use disorder: Polygenic risk scores and family history

BACKGROUND

Early identification of individuals at high risk for alcohol use disorder (AUD) coupled with prompt interventions could reduce the incidence of AUD. In this study, we investigated whether Polygenic Risk Scores (PRS) can be used to evaluate the risk for AUD and AUD severity (as measured by the number of DSM-5 AUD diagnostic criteria met) and compared their performance with a measure of family history of AUD.

METHODS

We studied individuals of European ancestry from the Collaborative Study on the Genetics of Alcoholism (COGA). DSM-5 diagnostic criteria were available for 7203 individuals, of whom 3451 met criteria for DSM-IV alcohol dependence or DSM-5 AUD and 1616 were alcohol-exposed controls aged ≥21 years with no history of AUD or drug dependence. Further, 4842 individuals had a positive first-degree family history of AUD (FH+), 2722 had an unknown family history (FH?), and 336 had a negative family history (FH-). PRS were derived from a meta-analysis of a genome-wide association study of AUD from the Million Veteran Program and scores from the problem subscale of the Alcohol Use Disorders Identification Test in the UK Biobank. We used mixed models to test the association between PRS and risk for AUD and AUD severity.

RESULTS

AUD cases had higher PRS than controls with PRS increasing as the number of DSM-5 diagnostic criteria increased (p-values ≤ 1.85E-05 ) in the full COGA sample, the FH+ subsample, and the FH? subsample. Individuals in the top decile of PRS had odds ratios (OR) for developing AUD of 1.96 (95% CI: 1.54 to 2.51, p-value = 7.57E-08 ) and 1.86 (95% CI: 1.35 to 2.56, p-value = 1.32E-04 ) in the full sample and the FH+ subsample, respectively. These values are comparable to previously reported ORs for a first-degree family history (1.91 to 2.38) estimated from national surveys. PRS were also significantly associated with the DSM-5 AUD diagnostic criterion count in the full sample, the FH+ subsample, and the FH? subsample (p-values ≤6.7E-11 ). PRS remained significantly associated with AUD and AUD severity after accounting for a family history of AUD (p-values ≤6.8E-10 ).

CONCLUSIONS

Both PRS and family history were associated with AUD and AUD severity, indicating that these risk measures assess distinct aspects of liability to AUD traits.

Machine Learning algorithm unveils glutamatergic alterations in the post-mortem schizophrenia brain

Schizophrenia is a disorder of synaptic plasticity and aberrant connectivity in which a major dysfunction in glutamate synapse has been suggested. However, a multi-level approach tackling diverse clusters of interacting molecules of the glutamate signaling in schizophrenia is still lacking. We investigated in the post-mortem dorsolateral prefrontal cortex (DLPFC) and hippocampus of schizophrenia patients and non-psychiatric controls, the levels of neuroactive d- and l-amino acids (l-glutamate, d-serine, glycine, l-aspartate, d-aspartate) by HPLC. Moreover, by quantitative RT-PCR and western blotting we analyzed, respectively, the mRNA and protein levels of pre- and post-synaptic key molecules involved in the glutamatergic synapse functioning, including glutamate receptors (NMDA, AMPA, metabotropic), their interacting scaffolding proteins (PSD-95, Homer1b/c), plasma membrane and vesicular glutamate transporters (EAAT1, EAAT2, VGluT1, VGluT2), enzymes involved either in glutamate-dependent GABA neurotransmitter synthesis (GAD65 and 67), or in post-synaptic NMDA receptor-mediated signaling (CAMKIIα) and the pre-synaptic marker Synapsin-1. Univariable analyses revealed that none of the investigated molecules was differently represented in the post-mortem DLPFC and hippocampus of schizophrenia patients, compared with controls. Nonetheless, multivariable hypothesis-driven analyses revealed that the presence of schizophrenia was significantly affected by variations in neuroactive amino acid levels and glutamate-related synaptic elements. Furthermore, a Machine Learning hypothesis-free unveiled other discriminative clusters of molecules, one in the DLPFC and another in the hippocampus. Overall, while confirming a key role of glutamatergic synapse in the molecular pathophysiology of schizophrenia, we reported molecular signatures encompassing elements of the glutamate synapse able to discriminate patients with schizophrenia and normal individuals.

Is Bicuspid Aortic Valve Morphology Genetically Determined? A Family-Based Study

Bicuspid aortic valve (BAV) is a common congenital heart disease, with a 10-fold higher prevalence in first-degree relatives. BAV has different phenotypes based on the morphology of cusp fusion. These phenotypes are associated with different clinical courses and prognoses. Currently, the determinants of the valve phenotype are unknown. In this study we evaluated the role of genetics using familial cohorts. Patients with BAV and their first-degree relatives were evaluated by echocardiography. The concordance in BAV phenotype between pairs of family members was calculated and compared with the concordance expected by chance. We then performed a systematic literature review to identify additional reports and calculated the overall concordance rate. During the study period, 70 cases from 31 families and 327 sporadic cases were identified. BAV was diagnosed in 14% of the screened relatives. The proportions of the morphologies identified was: 12.3% for type 0, 66.2% for type 1-LR, 15.4% for type 1-RN, 4.6% for type 1-NL, and 1.5% for type 2. For the assessment of morphologic concordance, we included 120 pairs of first-degree relatives with BAV from our original cohort and the literature review. Concordance was found only in 62% of the pairs which was not significantly higher than expected by chance. In conclusion, our finding demonstrates intrafamilial variability in BAV morphology, suggesting that morphology is determined by factors other than Mendelian genetics. As prognosis differs by morphology, our findings may suggest that clinical outcomes may vary even between first-degree relatives.

Heritability of Sleep and Its Disorders in Childhood and Adolescence

Purpose of Review

This review summarizes recent literature on the heritability of sleep and sleep disorders in childhood and adolescence. We also identify gaps in the literature and priorities for future research.

Recent Findings

Findings indicate that age, measurement method, reporter, and timing of sleep measurements can influence heritability estimates. Recent genome-wide association studies (GWAS) have identified differences in the heritability of sleep problems when ancestral differences are considered, but sample sizes are small compared to adult GWAS. Most studies focus on sleep variables in the full range rather than on disorder. Studies using objective measures of sleep typically comprised small samples.

Summary

Current evidence demonstrates a wide range of heritability estimates across sleep phenotypes in childhood and adolescence, but research in larger samples, particularly using objective sleep measures and GWAS, is needed. Further understanding of environmental mechanisms and the interaction between genes and environment is key for future research.

Mechanisms of neuroplasticity linking early adversity to depression: developmental considerations

Early exposure to psychosocial adversity is among the most potent predictors of depression. Because depression commonly emerges prior to adulthood, we must consider the fundamental principles of developmental neuroscience when examining how experiences of childhood adversity, including abuse and neglect, can lead to depression. Considering that both the environment and the brain are highly dynamic across the period spanning gestation through adolescence, the purpose of this review is to discuss and integrate stress-based models of depression that center developmental processes. We offer a general framework for understanding how psychosocial adversity in early life disrupts or calibrates the biobehavioral systems implicated in depression. Specifically, we propose that the sources and nature of the environmental input shaping the brain, and the mechanisms of neuroplasticity involved, change across development. We contend that the effects of adversity largely depend on the developmental stage of the organism. First, we summarize leading neurobiological models that focus on the effects of adversity on risk for mental disorders, including depression. In particular, we highlight models of allostatic load, acceleration maturation, dimensions of adversity, and sensitive or critical periods. Second, we expound on and review evidence for the formulation that distinct mechanisms of neuroplasticity are implicated depending on the timing of adverse experiences, and that inherent within certain windows of development are constraints on the sources and nature of these experiences. Finally, we consider other important facets of adverse experiences (e.g., environmental unpredictability, perceptions of one's experiences) before discussing promising research directions for the future of the field.

The genetic basis of major depression

Major depressive disorder (MDD) is a common, debilitating, phenotypically heterogeneous disorder with heritability ranges from 30% to 50%. Compared to other psychiatric disorders, its high prevalence, moderate heritability, and strong polygenicity have posed major challenges for gene-mapping in MDD. Studies of common genetic variation in MDD, driven by large international collaborations such as the Psychiatric Genomics Consortium, have confirmed the highly polygenic nature of the disorder and implicated over 100 genetic risk loci to date. Rare copy number variants associated with MDD risk were also recently identified. The goal of this review is to present a broad picture of our current understanding of the epidemiology, genetic epidemiology, molecular genetics, and gene-environment interplay in MDD. Insights into the impact of genetic factors on the aetiology of this complex disorder hold great promise for improving clinical care.

Shared genetic architecture across psychiatric disorders

Psychiatric disorders overlap substantially at the genetic level, with family-based methods long pointing toward transdiagnostic risk pathways. Psychiatric genomics has progressed rapidly in the last decade, shedding light on the biological makeup of cross-disorder risk at multiple levels of analysis. Over a hundred genetic variants have been identified that affect multiple disorders, with many more to be uncovered as sample sizes continue to grow. Cross-disorder mechanistic studies build on these findings to cluster transdiagnostic variants into meaningful categories, including in what tissues or when in development these variants are expressed. At the upper-most level, methods have been developed to estimate the overall shared genetic signal across pairs of traits (i.e. single-nucleotide polymorphism-based genetic correlations) and subsequently model these relationships to identify overarching, genomic risk factors. These factors can subsequently be associated with external traits (e.g. functional imaging phenotypes) to begin to understand the makeup of these transdiagnostic risk factors. As psychiatric genomic efforts continue to expand, we can begin to gain even greater insight by including more fine-grained phenotypes (i.e. symptom-level data) and explicitly considering the environment. The culmination of these efforts will help to inform bottom-up revisions of our current nosology.

Major Depressive Disorder and Lifestyle: Correlated Genetic Effects in Extended Twin Pedigrees

In recent years, evidence has accumulated with regard to the ubiquity of pleiotropy across the genome, and shared genetic etiology is thought to play a large role in the widespread comorbidity among psychiatric disorders and risk factors. Recent methods investigate pleiotropy by estimating genetic correlation from genome-wide association summary statistics. More comprehensive estimates can be derived from the known relatedness between genetic relatives. Analysis of extended twin pedigree data allows for the estimation of genetic correlation for additive and non-additive genetic effects, as well as a shared household effect. Here we conduct a series of bivariate genetic analyses in extended twin pedigree data on lifetime major depressive disorder (MDD) and three indicators of lifestyle, namely smoking behavior, physical inactivity, and obesity, decomposing phenotypic variance and covariance into genetic and environmental components. We analyze lifetime MDD and lifestyle data in a large multigenerational dataset of 19,496 individuals by variance component analysis in the ‘Mendel’ software. We find genetic correlations for MDD and smoking behavior (r_G = 0.249), physical inactivity (r_G = 0.161), body-mass index (r_G = 0.081), and obesity (r_G = 0.155), which were primarily driven by additive genetic effects. These outcomes provide evidence in favor of a shared genetic etiology between MDD and the lifestyle factors.

SERINC2 increases the risk of bipolar disorder in the Chinese population

BACKGROUND

Although common variants in a large collection of patients are associated with increased risk for bipolar disorder (BD), studies have only been able to predict 25%-45% of risks, suggesting that lots of variants that contribute to the risk for BD haven't been identified. Our study aims to identify novel BD risk genes.

METHODS

We performed whole-exome sequencing of 27 individuals from 6 BD multi-affected Chinese families to identify candidate variants. Targeted sequencing of one of the novel risk genes, SERINC2, in additional sporadic 717 BD patients and 312 healthy controls (HC) validated the association. Magnetic resonance imaging (MRI) were performed to evaluate the effect of the variant to brain structures from 213 subjects (4 BD subjects from a multi-affected family, 130 sporadic BD subjects and 79 HC control).

RESULTS

BD pedigrees had an increased burden of uncommon variants in extracellular matrix (ECM) and calcium ion binding. By large-scale sequencing we identified a novel recessive BD risk gene, SERINC2, which plays a role in synthesis of sphingolipid and phosphatidylserine (PS). MRI image results show the homozygous nonsense variant in SERINC2 affects the volume of white matter in cerebellum.

CONCLUSIONS

Our study identified SERINC2 as a risk gene of BD in the Chinese population.

Fate or coincidence: do COPD and major depression share genetic risk factors?

Major depressive disorder (MDD) is a common comorbidity in chronic obstructive pulmonary disease (COPD), affecting up to 57% of patients with COPD. Although the comorbidity of COPD and MDD is well established, the causal relationship between these two diseases is unclear. A large-scale electronic health record clinical biobank and genome-wide association study summary statistics for MDD and lung function traits were used to investigate potential shared underlying genetic susceptibility between COPD and MDD. Linkage disequilibrium score regression was used to estimate genetic correlation between phenotypes. Polygenic risk scores (PRS) for MDD and lung function traits were developed and used to perform a phenome-wide association study (PheWAS). Multi-trait-based conditional and joint analysis identified single-nucleotide polymorphisms (SNPs) influencing both lung function and MDD. We found genetic correlations between MDD and all lung function traits were small and not statistically significant. A PRS-MDD was significantly associated with an increased risk of COPD in a PheWAS [odds ratio (OR) = 1.12, 95% confidence interval (CI): 1.09-1.16] when adjusting for age, sex and genetic ancestry, but this relationship became attenuated when controlling for smoking history (OR = 1.08, 95% CI: 1.04-1.13). No significant associations were found between the lung function PRS and MDD. Multi-trait-based conditional and joint analysis identified three SNPs that may contribute to both traits, two of which were previously associated with mood disorders and COPD. Our findings suggest that the observed relationship between COPD and MDD may not be driven by a strong shared genetic architecture.

The Power to Detect Cultural Transmission in the Nuclear Twin Family Design With and Without Polygenic Risk Scores and in the Transmitted-Nontransmitted (Alleles) Design

We compare the power of two different approaches to detect passive genotype-environment (GE) covariance originating from cultural and genetic transmission operating simultaneously. In the traditional nuclear twin family (NTF) design, cultural transmission is estimated from the phenotypic covariance matrices of the mono- and dizygotic twins and their parents. Here, phenotyping is required in all family members. A more recent method is the transmitted-nontransmitted (T-NT) allele design, which exploits measured genetic variants in parents and offspring to test for effects of nontransmitted alleles from parents. This design requires two-generation genome-wide data and a powerful genome-wide association study (GWAS) for the phenotype in addition to phenotyping in offspring. We compared the power of both designs. Using exact data simulation, we demonstrate three points: how the power of the T-NT design depends on the predictive power of polygenic risk scores (PRSs); that when the NTF design can be applied, its power to detect cultural transmission and GE covariance is high relative to T-NT; and that, given effect sizes from contemporary GWAS, adding PRSs to the NTF design does not yield an appreciable increase in the power to detect cultural transmission. However, it may be difficult to collect phenotypes of parents and the possible importance of gene × age interaction, and secular generational effects can cause complications for many important phenotypes. The T-NT design avoids these complications.