GENOME-WIDE ASSOCIATION STUDY (GWAS) AND GENOME-WIDE BY ENVIRONMENT INTERACTION STUDY (GWEIS) OF DEPRESSIVE SYMPTOMS IN AFRICAN AMERICAN AND HISPANIC/LATINA WOMEN

Exploring the Interplay of Social Safety Nets, Race, Ethnicity, and Nativity on Psychological Distress Among Low-Income Mothers

Low-income mothers face numerous challenges that increase their vulnerability to psychological distress. Their perceived or actual difficulty in accessing vital support networks, whether public or private, can significantly amplify this distress. Socially assigned identities, such as nativity, ethnicity, and race, intersect with socioeconomic factors, influencing mental health outcomes. Using data from the Future of Families and Child Wellbeing Study, our research investigated the impact of public and private safety nets on maternal psychological health. We found that, even after accounting for socioeconomic factors, non-Hispanic, US-born White mothers experienced higher levels of psychological distress compared to minoritized mothers. The role of safety nets varied by race and ethnicity, with private safety nets providing unique protection to Black and Hispanic mothers, while support was associated with increased distress only among White mothers. These findings highlight the need to consider sociocultural history when assessing safety net impacts on mental health.

Genotype × environment interactions in gene regulation and complex traits

Genotype × environment interactions (GxE) have long been recognized as a key mechanism underlying human phenotypic variation. Technological developments over the past 15 years have dramatically expanded our appreciation of the role of GxE in both gene regulation and complex traits. The richness and complexity of these datasets also required parallel efforts to develop robust and sensitive statistical and computational approaches. Although our understanding of the genetic architecture of molecular and complex traits has been maturing, a large proportion of complex trait heritability remains unexplained. Furthermore, there are increasing efforts to characterize the effect of environmental exposure on human health. We therefore review GxE in human gene regulation and complex traits, advocating for a comprehensive approach that jointly considers genetic and environmental factors in human health and disease.

Inflammation and immune system pathways as biological signatures of adolescent depression-the IDEA-RiSCo study

The biological mechanisms underlying the onset of major depressive disorder (MDD) have predominantly been studied in adult populations from high-income countries, despite the onset of depression typically occurring in adolescence and the majority of the world's adolescents living in low- and middle-income countries (LMIC). Taking advantage of a unique adolescent sample in an LMIC (Brazil), this study aimed to identify biological pathways characterizing the presence and increased risk of depression in adolescence, and sex-specific differences in such biological signatures. We collected blood samples from a risk-stratified cohort of 150 Brazilian adolescents (aged 14-16 years old) comprising 50 adolescents with MDD, 50 adolescents at high risk of developing MDD but without current MDD, and 50 adolescents at low risk of developing MDD and without MDD (25 females and 25 males in each group). We conducted RNA-Seq and pathway analysis on whole blood. Inflammatory-related biological pathways, such as role of hypercytokinemia/hyperchemokinemia in the pathogenesis of influenza (z-score = 3.464, p < 0.001), interferon signaling (z-score = 2.464, p < 0.001), interferon alpha/beta signaling (z-score = 3.873, p < 0.001), and complement signaling (z-score = 2, p = 0.002) were upregulated in adolescents with MDD compared with adolescents without MDD independently from their level of risk. The up-regulation of such inflammation-related pathways was observed in females but not in males. Inflammatory-related pathways involved in the production of cytokines and in interferon and complement signaling were identified as key indicators of adolescent depression, and this effect was present only in females.

Systematic exploration of a decade of publications on psychiatric genetics in Latin America

Psychiatric disorders have a great impact in terms of mortality, morbidity, and disability across the lifespan. Considerable effort has been devoted to understanding their complex and heterogeneous genetic architecture, including diverse ancestry populations. Our aim was to review the psychiatric genetics research published with Latin American populations from 2010 to 2019, and classify it according to country of origin, type of analysis, source of funding, and other variables. We found that most publications came from Brazil, Mexico, and Colombia. Also, local funds are generally not large enough for genome-wide studies in Latin America, with the exception of Brazil and Mexico; larger studies are often done in collaboration with international partners, mostly funded by US agencies. In most of the larger studies, the participants are individuals of Latin American ancestry living in the United States, which limits the potential for exploring the complex gene-environment interaction. Family studies, traditionally strong in Latin America, represent about 30% of the total research publications. Scarce local resources for research in Latin America have probably been an important limitation for conducting bigger and more complex studies, contributing to the reduced representation of these populations in global psychiatric genetics studies. Increasing diversity must be a goal to improve generalizability and applicability in clinical settings.

Cohort profile: BioMD-Y (biopsychosocial factors of major depression in youth) - a biobank study on the molecular genetics and environmental factors of depression in children and adolescents in Munich

PURPOSE

BioMD-Y is a comprehensive biobank study of children and adolescents with major depression (MD) and their healthy peers in Germany, collecting a host of both biological and psychosocial information from the participants and their parents with the aim of exploring genetic and environmental risk and protective factors for MD in children and adolescents.

PARTICIPANTS

Children and adolescents aged 8-18 years are recruited to either the clinical case group (MD, diagnosis of MD disorder) or the typically developing control group (absence of any psychiatric condition).

FINDINGS TO DATE

To date, four publications on both genetic and environmental risk and resilience factors (including FKBP5, glucocorticoid receptor activation, polygenic risk scores, psychosocial and sociodemographic risk and resilience factors) have been published based on the BioMD-Y sample.

FUTURE PLANS

Data collection is currently scheduled to continue into 2026. Research questions will be further addressed using available measures.

Multi-ancestry genome-wide association study of major depression aids locus discovery, fine mapping, gene prioritization and causal inference

Most genome-wide association studies (GWAS) of major depression (MD) have been conducted in samples of European ancestry. Here we report a multi-ancestry GWAS of MD, adding data from 21 cohorts with 88,316 MD cases and 902,757 controls to previously reported data. This analysis used a range of measures to define MD and included samples of African (36% of effective sample size), East Asian (26%) and South Asian (6%) ancestry and Hispanic/Latin American participants (32%). The multi-ancestry GWAS identified 53 significantly associated novel loci. For loci from GWAS in European ancestry samples, fewer than expected were transferable to other ancestry groups. Fine mapping benefited from additional sample diversity. A transcriptome-wide association study identified 205 significantly associated novel genes. These findings suggest that, for MD, increasing ancestral and global diversity in genetic studies may be particularly important to ensure discovery of core genes and inform about transferability of findings.

Enhanced polygenic risk score incorporating gene-environment interaction suggests the association of major depressive disorder with cardiac and lung function

BACKGROUND

Depression has been linked to an increased risk of cardiovascular and respiratory diseases; however, its impact on cardiac and lung function remains unclear, especially when accounting for potential gene-environment interactions.

METHODS

We developed a novel polygenic and gene-environment interaction risk score (PGIRS) integrating the major genetic effect and gene-environment interaction effect of depression-associated loci. The single nucleotide polymorphisms (SNPs) demonstrating major genetic effect or environmental interaction effect were obtained from genome-wide SNP association and SNP-environment interaction analyses of depression. We then calculated the depression PGIRS for non-depressed individuals, using smoking and alcohol consumption as environmental factors. Using linear regression analysis, we assessed the associations of PGIRS and conventional polygenic risk score (PRS) with lung function (N = 42 886) and cardiac function (N = 1791) in the subjects with or without exposing to smoking and alcohol drinking.

RESULTS

We detected significant associations of depression PGIRS with cardiac and lung function, contrary to conventional depression PRS. Among smokers, forced vital capacity exhibited a negative association with PGIRS (β = -0.037, FDR = 1.00 × 10-8), contrasting with no significant association with PRS (β = -0.002, FDR = 0.943). In drinkers, we observed a positive association between cardiac index with PGIRS (β = 0.088, FDR = 0.010), whereas no such association was found with PRS (β = 0.040, FDR = 0.265). Notably, in individuals who both smoked and drank, forced expiratory volume in 1-second demonstrated a negative association with PGIRS (β = -0.042, FDR = 6.30 × 10-9), but not with PRS (β = -0.003, FDR = 0.857).

CONCLUSIONS

Our findings underscore the profound impact of depression on cardiac and lung function, highlighting the enhanced efficacy of considering gene-environment interactions in PRS-based studies.

A multidimensional social risk atlas of depression and anxiety: An observational and genome-wide environmental interaction study

Background

Mental disorders are largely socially determined, yet the combined impact of multidimensional social factors on the two most common mental disorders, depression and anxiety, remains unclear.

Methods

We constructed a polysocial risk score (PsRS), a multidimensional social risk indicator including components from three domains: socioeconomic status, neighborhood and living environment and psychosocial factors. Supported by the UK Biobank cohort, we randomly divided 110 332 participants into the discovery cohort (60%; n = 66 200) and the replication cohort (40%; n = 44 134). We tested the associations between 13 single social factors with Patient Health Questionnaire (PHQ) score, Generalized Anxiety Disorder Scale (GAD) score and self-reported depression and anxiety. The significant social factors were used to calculate PsRS for each mental disorder by considering weights from the multivariable linear model. Generalized linear models were applied to explore the association between PsRS and depression and anxiety. Genome-wide environmental interaction study (GWEIS) was further performed to test the effect of interactions between PsRS and SNPs on the risk of mental phenotypes.

Results

In the discovery cohort, PsRS was positively associated with PHQ score (β = 0.37; 95% CI = 0.35-0.38), GAD score (β = 0.27; 95% CI = 0.25-0.28), risk of self-reported depression (OR = 1.29; 95% CI = 1.28-1.31) and anxiety (OR = 1.19; 95% CI = 1.19-1.23). Similar results were observed in the replication cohort. Emotional stress, lack of social support and low household income were significantly associated with the development of depression and anxiety. GWEIS identified multiple candidate loci for PHQ score, such as rs149137169 (ST18) (Pdiscovery = 1.08 × 10-8, Preplication = 3.25 × 10-6) and rs3759812 (MYO9A) (Pdiscovery = 3.87 × 10-9, Preplication = 6.21 × 10-5). Additionally, seven loci were detected for GAD score, such as rs114006170 (TMPRSS11D) (Pdiscovery = 1.14 × 10-9, Preplication = 7.36 × 10-5) and rs77927903 (PIP4K2A) (Pdiscovery = 2.40 × 10-9, Preplication = 0.002).

Conclusions

Our findings reveal the positive effects of multidimensional social factors on the risk of depression and anxiety. It is important to address key social disadvantage in mental health promotion and treatment.

Trauma Matters: Integrating Genetic and Environmental Components of PTSD

Trauma is ubiquitous, but only a subset of those who experience trauma will develop posttraumatic stress disorder (PTSD). In this review, it is argued that to determine who is at risk of developing PTSD, it is critical to examine the genetic etiology of the disorder and individual trauma profiles of those who are susceptible. First, the state of current PTSD genetic research is described, with a particular focus on studies that present evidence for trauma type specificity, or for differential genetic etiology according to gender or race. Next, approaches that leverage non-traditional phenotyping approaches are reviewed to identify PTSD-associated variants and biology, and the relative advantages and limitations inherent in these studies are reflected on. Finally, it is discussed how trauma might influence the heritability of PTSD, through type, risk factors, genetics, and associations with PTSD symptomology.

A person-centered data analytic approach to dopaminergic polygenic moderation of child maltreatment exposure

The present study illustrates the utility of latent class analysis, a person-centered data analytic approach, as an innovative method for identifying naturally occurring patterns of polygenic risk, specifically within the dopaminergic system. Moreover, this study tests whether latent classes of polygenic variation moderate the effect of child maltreatment exposure on internalizing symptoms among African ancestry youth. African ancestry youth were selected for this study because youth of color are overrepresented in the child welfare system and because African ancestry individuals are significantly underrepresented in genomics research. Results identified three latent classes of dopaminergic gene variation. Class 1 was marked predominately by homozygous minor alleles, Class 2 was characterized by homozygous major and heterozygous presentations, and Class 3 was marked by heterozygous alleles on the DAT-1 single-nucleotide polymorphisms (SNPs) and a combination of homozygous major and minor alleles on the other SNPs. Results indicated that a greater number of maltreatment subtypes experienced were associated with higher internalizing symptoms only for children with the latent polygenic Class 2 pattern. This latent class was distinctly characterized by more homozygous major or heterozygous allelic presentations along all three DAT-1 SNPs. This significant latent polygenic class by environment interaction was replicated in an independent replication sample. Together, findings suggest that African ancestry children with a pattern of dopaminergic variation characterized by this specific combination of polygenic variation are more vulnerable to developing internalizing symptoms following maltreatment exposure, relative to their peers with other dopamine-related polygenic patterns.

Pathophysiological Roles of Auxiliary Calcium Channel α2δ Subunits

α2δ proteins serve as auxiliary subunits of voltage-gated calcium channels, which are essential components of excitable cells such as skeletal and heart muscles, nerve cells of the brain and the peripheral nervous system, as well as endocrine cells. Over the recent years, α2δ proteins have been identified as critical regulators of synaptic functions, including the formation and differentiation of synapses. These functions require signalling mechanisms which are partly independent of calcium channels. Hence, in light of these features it is not surprising that the genes encoding for the four α2δ isoforms have recently been linked to neurological and neurodevelopmental disorders including epilepsy, autism spectrum disorders, schizophrenia, and depressive and bipolar disorders. Despite the increasing number of identified disease-associated mutations, the underlying pathophysiological mechanisms are only beginning to emerge. However, a thorough understanding of the pathophysiological role of α2δ proteins ideally serves two purposes: first, it will contribute to our understanding of general pathological mechanisms in synaptic disorders. Second, it may support the future development of novel and specific treatments for brain disorders. In this context, it is noteworthy that the antiepileptic and anti-allodynic drugs gabapentin and pregabalin both act via binding to α2δ proteins and are among the top sold drugs for treating neuropathic pain. In this book chapter, we will discuss recent developments in our understanding of the functions of α2δ proteins, both as calcium channel subunits and as independent regulatory entities. Furthermore, we present and summarize recently identified and likely pathogenic mutations in the genes encoding α2δ proteins and discuss potential underlying pathophysiological consequences at the molecular and structural level.

Air pollution, genetic factors and the risk of depression

Both genetics and ambient air pollutants contribute to depression, but the degree to which genetic susceptibility modifies the effect of air pollution on depression remains unknown. We aimed to investigate the effect of the modification of genetic susceptibility on depression. Notably, 490,780 participants who were free of depression at baseline in the UK Biobank study were recruited from 2006 to 2010. A land use regression (LUR) model was performed to estimate the concentrations of particulate matter with diameters ranging from ≤2.5-≤10 μm (PM_2.5, PM_2.5-10 and PM₁₀), nitrogen dioxide (NO₂), and nitrogen oxides (NO_x). The International Classification of Diseases 10th Revision (ICD-10) code was used to identify depression cases. Cox proportional hazard models adjusted for covariates were used to investigate the association between ambient air pollutants and depression. Moreover, the polygenic risk score (PRS) was calculated to evaluate cumulative genetic effects, and additive interaction models were established to explore whether genetic susceptibility modified the effects of air pollutants on depression. PM_2.5, PM₁₀, NO₂ and NO_x exposure were significantly positively associated with the risk of depression, and the hazard ratios and 95 % confidence intervals for a 10-μg/m³ increase in PM_2.5, PM₁₀, NO₂ and NO_x concentrations were 2.12 (1.82, 2.47), 1.12 (1.03, 1.23), 1.07 (1.05, 1.10) and 1.04 (1.03, 1.05), respectively. Air pollutants and genetic variants exerted significant additive effects on the risk of depression (relative excess risk due to the interaction [RERI]: 0.15 for PM_2.5, 0.12 for PM₁₀, 0.10 for NO₂, and 0.12 for NO_x; attributable proportion due to the interaction [AP]: 0.12 for PM_2.5, 0.10 for PM₁₀, 0.08 for NO₂, and 0.09 for NO_x). Air pollution exposure was significantly associated with the risk of depression, and participants with a higher genetic risk were more likely to develop depression when exposed to high levels of air pollution.

Genome-by-Trauma Exposure Interactions in Adults With Depression in the UK Biobank

Importance

Self-reported trauma exposure has consistently been found to be a risk factor for major depressive disorder (MDD), and several studies have reported interactions with genetic liability. To date, most studies have examined gene-environment interactions with trauma exposure using genome-wide variants (single-nucleotide variations [SNVs]) or polygenic scores, both typically capturing less than 3% of phenotypic risk variance.

Objective

To reexamine genome-by-trauma interaction associations using genetic measures using all available genotyped data and thus, maximizing accounted variance.

Design, Setting, and Participants

The UK Biobank study was conducted from April 2007 to May 1, 2016 (follow-up mental health questionnaire). The current study used available cross-sectional genomic and trauma exposure data from UK Biobank. Participants who completed the mental health questionnaire and had available genetic, trauma experience, depressive symptoms, and/or neuroticism information were included. Data were analyzed from April 1 to August 30, 2021.

Exposures

Trauma and genome-by-trauma exposure interactions.

Main Outcomes and Measures

Measures of self-reported depression, neuroticism, and trauma exposure with whole-genome SNV data are available from the UK Biobank study. Here, a mixed-model statistical approach using genetic, trauma exposure, and genome-by-trauma exposure interaction similarity matrices was used to explore sources of variation in depression and neuroticism.

Results

Analyses were conducted on 148 129 participants (mean [SD] age, 56 [7] years) of which 76 995 were female (52.0%). The study approach estimated the heritability (SE) of MDD to be approximately 0.160 (0.016). Subtypes of self-reported trauma exposure (catastrophic, adult, childhood, and full trauma) accounted for a significant proportion of the variance of MDD, with heritability (SE) ranging from 0.056 (0.013) to 0.176 (0.025). The proportion of MDD risk variance accounted for by significant genome-by-trauma interaction revealed estimates (SD) ranging from 0.074 (0.006) to 0.201 (0.009). Results from sex-specific analyses found genome-by-trauma interaction variance estimates approximately 5-fold greater for MDD in male participants (0.441 [0.018]) than in female participants (0.086 [0.009]).

Conclusions and Relevance

This cross-sectional study used an approach combining all genome-wide SNV data when exploring genome-by-trauma interactions in individuals with MDD; findings suggest that such interactions were associated with depression manifestation. Genome-by-trauma interaction accounts for greater trait variance in male individuals, which points to potential differences in depression etiology between the sexes. The methodology used in this study can be extrapolated to other environmental factors to identify modifiable risk environments and at-risk groups to target with interventions.

Integrative analysis of genomic and exposomic influences on youth mental health

BACKGROUND

Understanding complex influences on mental health problems in young people is needed to inform early prevention strategies. Both genetic and environmental factors are known to influence youth mental health, but a more comprehensive picture of their interplay, including wide-ranging environmental exposures - that is, the exposome - is needed. We perform an integrative analysis of genomic and exposomic data in relation to internalizing and externalizing symptoms in a cohort of 4,314 unrelated youth from the Adolescent Brain and Cognitive Development (ABCD) Study.

METHODS

Using novel GREML-based approaches, we model the variance in internalizing and externalizing symptoms explained by additive and interactive influences from the genome (G) and modeled exposome (E) consisting of up to 133 variables at the family, peer, school, neighborhood, life event, and broader environmental levels, including genome-by-exposome (G × E) and exposome-by-exposome (E × E) effects.

RESULTS

A best-fitting integrative model with G, E, and G × E components explained 35% and 63% of variance in youth internalizing and externalizing symptoms, respectively. Youth in the top quintile of model-predicted risk accounted for the majority of individuals with clinically elevated symptoms at follow-up (60% for internalizing; 72% for externalizing). Of note, different domains of environmental exposures were most impactful for internalizing (life events) and externalizing (contextual including family, school, and peer-level factors) symptoms. In addition, variance explained by G × E contributions was substantially larger for externalizing (33%) than internalizing (13%) symptoms.

CONCLUSIONS

Advanced statistical genetic methods in a longitudinal cohort of youth can be leveraged to address fundamental questions about the role of 'nature and nurture' in developmental psychopathology.

Exploring polygenic-environment and residual-environment interactions for depressive symptoms within the UK Biobank

Substantial advances have been made in identifying genetic contributions to depression, but little is known about how the effect of genes can be modulated by the environment, creating a gene-environment interaction. Using multivariate reaction norm models (MRNMs) within the UK Biobank (N = 61294-91644), we investigate whether the polygenic and residual variance components of depressive symptoms are modulated by 17 a priori selected covariate traits-12 environmental variables and 5 biomarkers. MRNMs, a mixed-effects modelling approach, provide unbiased polygenic-covariate interaction estimates for a quantitative trait by controlling for outcome-covariate correlations and residual-covariate interactions. A continuous depressive symptom variable was the outcome in 17 MRNMs-one for each covariate trait. Each MRNM had a fixed-effects model (fixed effects included the covariate trait, demographic variables, and principal components) and a random effects model (where polygenic-covariate and residual-covariate interactions are modelled). Of the 17 selected covariates, 11 significantly modulate deviations in depressive symptoms through the modelled interactions, but no single interaction explains a large proportion of phenotypic variation. Results are dominated by residual-covariate interactions, suggesting that covariate traits (including neuroticism, childhood trauma, and BMI) typically interact with unmodelled variables, rather than a genome-wide polygenic component, to influence depressive symptoms. Only average sleep duration has a polygenic-covariate interaction explaining a demonstrably nonzero proportion of the variability in depressive symptoms. This effect is small, accounting for only 1.22% (95% confidence interval: [0.54, 1.89]) of variation. The presence of an interaction highlights a specific focus for intervention, but the negative results here indicate a limited contribution from polygenic-environment interactions.

Circulating miRNAs as Potential Biomarkers for Patient Stratification in Bipolar Disorder: A Combined Review and Data Mining Approach

Bipolar disorder is a debilitating psychiatric condition that is shaped in a concerted interplay between hereditary and triggering risk factors. Profound depression and mania define the disorder, but high clinical heterogeneity among patients complicates diagnosis as well as pharmacological intervention. Identification of peripheral biomarkers that capture the genomic response to the exposome may thus progress the development of personalized treatment. MicroRNAs (miRNAs) play a prominent role in of post-transcriptional gene regulation in the context of brain development and mental health. They are coordinately modulated by multifarious effectors, and alteration in their expression profile has been reported in a variety of psychiatric conditions. Intriguingly, miRNAs can be released from CNS cells and enter circulatory bio-fluids where they remain remarkably stable. Hence, peripheral circulatory miRNAs may act as bio-indicators for the combination of genetic risk, environmental exposure, and/or treatment response. Here we provide a comprehensive literature search and data mining approach that summarize current experimental evidence supporting the applicability of miRNAs for patient stratification in bipolar disorder.

A genome-wide association study of suicide attempts in the million veterans program identifies evidence of pan-ancestry and ancestry-specific risk loci

To identify pan-ancestry and ancestry-specific loci associated with attempting suicide among veterans, we conducted a genome-wide association study (GWAS) of suicide attempts within a large, multi-ancestry cohort of U.S. veterans enrolled in the Million Veterans Program (MVP). Cases were defined as veterans with a documented history of suicide attempts in the electronic health record (EHR; N = 14,089) and controls were defined as veterans with no documented history of suicidal thoughts or behaviors in the EHR (N = 395,064). GWAS was performed separately in each ancestry group, controlling for sex, age and genetic substructure. Pan-ancestry risk loci were identified through meta-analysis and included two genome-wide significant loci on chromosomes 20 (p = 3.64 × 10-9) and 1 (p = 3.69 × 10-8). A strong pan-ancestry signal at the Dopamine Receptor D2 locus (p = 1.77 × 10-7) was also identified and subsequently replicated in a large, independent international civilian cohort (p = 7.97 × 10-4). Additionally, ancestry-specific genome-wide significant loci were also detected in African-Americans, European-Americans, Asian-Americans, and Hispanic-Americans. Pathway analyses suggested over-representation of many biological pathways with high clinical significance, including oxytocin signaling, glutamatergic synapse, cortisol synthesis and secretion, dopaminergic synapse, and circadian rhythm. These findings confirm that the genetic architecture underlying suicide attempt risk is complex and includes both pan-ancestry and ancestry-specific risk loci. Moreover, pathway analyses suggested many commonly impacted biological pathways that could inform development of improved therapeutics for suicide prevention.

Early adversity as the prototype gene × environment interaction in mental disorders?

Childhood adversity (CA) as a significant stressor has consistently been associated with the development of mental disorders. The interaction between CA and genetic variants has been proposed to play a substantial role in disease etiology. In this review, we focus on the gene by environment (GxE) paradigm, its background and interpretation and stress the necessity of its implementation in psychiatric research. Further, we discuss the findings supporting GxCA interactions, ranging from candidate gene studies to polygenic and genome-wide approaches, their strengths and limitations. To illustrate potential underlying epigenetic mechanisms by which GxE effects are translated, we focus on results from FKBP5 × CA studies and discuss how molecular evidence can supplement previous GxE findings. In conclusion, while GxE studies constitute a valuable line of investigation, more harmonized GxE studies in large, deep-phenotyped, longitudinal cohorts, and across different developmental stages are necessary to further substantiate and understand reported GxE findings.

Sensitive period-regulating genetic pathways and exposure to adversity shape risk for depression

Animal and human studies have documented the existence of developmental windows (or sensitive periods) when experience can have lasting effects on brain structure or function, behavior, and disease. Although sensitive periods for depression likely arise through a complex interplay of genes and experience, this possibility has not yet been explored in humans. We examined the effect of genetic pathways regulating sensitive periods, alone and in interaction with common childhood adversities, on depression risk. Guided by a translational approach, we: (1) performed association analyses of three gene sets (60 genes) shown in animal studies to regulate sensitive periods using summary data from a genome-wide association study of depression (n = 807,553); (2) evaluated the developmental expression patterns of these genes using data from BrainSpan (n = 31), a transcriptional atlas of postmortem brain samples; and (3) tested gene-by-development interplay (dGxE) by analyzing the combined effect of common variants in sensitive period genes and time-varying exposure to two types of childhood adversity within a population-based birth cohort (n = 6254). The gene set regulating sensitive period opening associated with increased depression risk. Notably, 6 of the 15 genes in this set showed developmentally regulated gene-level expression. We also identified a statistical interaction between caregiver physical or emotional abuse during ages 1-5 years and genetic risk for depression conferred by the opening genes. Genes involved in regulating sensitive periods are differentially expressed across the life course and may be implicated in depression vulnerability. Our findings about gene-by-development interplay motivate further research in large, more diverse samples to further unravel the complexity of depression etiology through a sensitive period lens.

We Know Even More Things: A Decade Review of Parenting Research

In this article, we highlight the important ideas that have emerged from research on parenting and adolescent development over the past decade. Beginning with research on authoritative parenting, we examine key elements of this parenting style and its influence across diverse contexts and populations. We turn our attention to four topics that have generated much research in the past decade: (1) how parenting contributes to adolescent peer and romantic relationships; (2) the impact of parenting on adolescent brain development; (3) gene-environment interactions in parenting research; and (4) parents' involvement in adolescents' social media use. We discuss contemporary challenges and ways parents can promote healthy development. We consider the integration of research, practice, and policy that best supports parents and adolescents.

Gene × environment interaction in major depressive disorder

Major depressive disorder (MDD) is a multifactorial disorder, where multiple susceptibility genes interact with environmental factors, predisposing individuals to the development of the illness. In this article, we reviewed different gene × environment interaction (G×E) studies shifting from a candidate gene to a genome-wide approach. Among environmental factors, childhood adversities and stressful life events have been suggested to exert crucial impacts on MDD. Importantly, the diathesis-stress conceptualization of G×E has been challenged by the differential susceptibility theory. Finally, we summarized several limitations of G×E studies and suggested how future G×E studies might reveal complex interactions between genes and environments in MDD.

The Genetic Architecture of Depression in Individuals of East Asian Ancestry: A Genome-Wide Association Study

Importance

Most previous genome-wide association studies (GWAS) of depression have used data from individuals of European descent. This limits the understanding of the underlying biology of depression and raises questions about the transferability of findings between populations.

Objective

To investigate the genetics of depression among individuals of East Asian and European descent living in different geographic locations, and with different outcome definitions for depression.

Design, Setting, and Participants

Genome-wide association analyses followed by meta-analysis, which included data from 9 cohort and case-control data sets comprising individuals with depression and control individuals of East Asian descent. This study was conducted between January 2019 and May 2021.

Exposures

Associations of genetic variants with depression risk were assessed using generalized linear mixed models and logistic regression. The results were combined across studies using fixed-effects meta-analyses. These were subsequently also meta-analyzed with the largest published GWAS for depression among individuals of European descent. Additional meta-analyses were carried out separately by outcome definition (clinical depression vs symptom-based depression) and region (East Asian countries vs Western countries) for East Asian ancestry cohorts.

Main Outcomes and Measures

Depression status was defined based on health records and self-report questionnaires.

Results

There were a total of 194 548 study participants (approximate mean age, 51.3 years; 62.8% women). Participants included 15 771 individuals with depression and 178 777 control individuals of East Asian descent. Five novel associations were identified, including 1 in the meta-analysis for broad depression among those of East Asian descent: rs4656484 (β = -0.018, SE = 0.003, P = 4.43x10-8) at 1q24.1. Another locus at 7p21.2 was associated in a meta-analysis restricted to geographically East Asian studies (β = 0.028, SE = 0.005, P = 6.48x10-9 for rs10240457). The lead variants of these 2 novel loci were not associated with depression risk in European ancestry cohorts (β = -0.003, SE = 0.005, P = .53 for rs4656484 and β = -0.005, SE = 0.004, P = .28 for rs10240457). Only 11% of depression loci previously identified in individuals of European descent reached nominal significance levels in the individuals of East Asian descent. The transancestry genetic correlation between cohorts of East Asian and European descent for clinical depression was r = 0.413 (SE = 0.159). Clinical depression risk was negatively genetically correlated with body mass index in individuals of East Asian descent (r = -0.212, SE = 0.084), contrary to findings for individuals of European descent.

Conclusions and Relevance

These results support caution against generalizing findings about depression risk factors across populations and highlight the need to increase the ancestral and geographic diversity of samples with consistent phenotyping.

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.

Traumatic events during childhood and its risks to substance use in adulthood: an observational and genome-wide by environment interaction study in UK Biobank

We aimed to explore the underlying genetic mechanisms of traumatic events during childhood affecting the risks of adult substance use in present study. Using UK Biobank cohort, linear regression model was first applied to assess the relationships between cigarette smoking and alcohol drinking in adults with traumatic events during childhood, including felt hated by family member (41,648-111,465), felt loved (46,394-124,481) and sexually molested (47,598-127,766). Using traumatic events as exposure variables, genome-wide by environment interaction study was then performed by PLINK 2.0 to identify cigarette smoking and alcohol drinking associated genes interacting with traumatic events during childhood. We found that the frequency of cigarette smoking was significantly associated with felt hated by family member (coefficient = 0.42, P < 1.0 × 10^-9), felt loved (coefficient = -0.31, P < 1.0 × 10^-9) and sexually molested (coefficient = 0.46, P < 1.0 × 10^-9). We also observed weaker associations of alcohol drinking with felt hated by family member (coefficient = 0.08, P = 3.10 × 10^-6) and felt loved (coefficient = -0.06, P = 3.15 × 10^-7). GWEIS identified multiple candidate loci interacting with traumatic events, such as CTNNA3 (rs189142060, P = 4.23 × 10^-8) between felt hated by family member and the frequency of cigarette smoking, GABRG3 (rs117020886, P = 2.77 × 10^-8) between felt hated by family member and the frequency of alcohol drinking. Our results suggested the significant impact of traumatic events during childhood on the risk of cigarette smoking and alcohol drinking.

Maternal smoking during pregnancy and risks to depression and anxiety in offspring: An observational study and genome-wide gene-environment interaction analysis in UK biobank cohort

BACKGROUND

Maternal smoking during pregnancy (MSDP) has been reported to be associated with increased anxiety and depression behaviors in offspring. However, there is still scant evidence to support the link between MSDP and anxiety/depression.

METHODS

Using the subjects from the UK Biobank cohort (n = 371,903-432,881). Logistic regression analyses were first conducted to test the correlation between MSDP and anxiety/depression in offspring. Second, genome-wide gene-environment interaction study (GWGEIS) analyses were conducted by PLINK, using MSDP as environmental factor. Genetic correlation analysis of anxiety/depression and smoking was conducted by the LDSC software using the published genome-wide association study (GWAS) summary data of four smoking traits (n = 337,334-1,232,091), anxiety (n = 31,880) and depression (n = 490,359). Finally, pathway enrichment analysis was carried out to detect the pathway involved in the development of offspring anxiety caused by the interaction of MSDP × SNPs.

RESULTS

Observational analyses showed that anxiety and depression status in offspring were significantly associated with MSDP (all p < 0.0001). Further GWEGI analyses observed significant MSDP-gene interaction effects at UNC80 gene for anxiety (p = 9.09 × 10^-9). LDSC did not detect significant genetic correlation between anxiety and smoking traits. Pathway analysis identified 19 significant pathways for anxiety, such as MANALO_HYPOXIA_UP (FDR = 5.50 × 10^-4), REACTOME_ADHERENS_JUNCTIONS_INTERACTIONS (FDR = 0.0304) and ONDER_CDH1_TARGETS_2_UP (FDR = 0.0371).

CONCLUSION

Our study results suggested the important impact of MDSP on the risk of anxiety in offspring, partly attributing to environment-gene interactions effects.

Insomnia affects the levels of plasma bilirubin and protein metabolism: an observational study and GWGEIS in UK Biobank cohort

STUDY OBJECTIVES

We aim to explore the mechanism of relationship between insomnia and liver metabolism by examining the gene × insomnia interactions.

METHODS

Individual level genotypic and phenotypic data were obtained from the UK Biobank cohort. Regression analysis was first conducted to test the association of insomnia with plasma total bilirubin (TBil; n = 186,793), direct bilirubin (DBil; n = 159,854) and total protein (TP; n = 171,574) in UK Biobank cohort. Second, genome-wide gene-environment interaction study (GWGEIS) was conducted by PLINK 2.0, and FUMA platform was used to identify enriched pathway terms.

RESULTS

In UK Biobank cohort, we found that TP (P < 2.00 × 10^-16), DBil (P = 1.72 × 10^-3) and TBil (P = 3.38 × 10^-5) were significantly associated with insomnia. GWGEIS of both DBil and TBil observed significant G × INSOMNIA effects between insomnia and UDP Glucuronosyltransferase Family 1 (rs6431558, P = 6.26 × 10^-11) gene. GWGEIS of TP also detected several significant genes interacting with insomnia, such as KLF15, (rs70940816, P = 6.77 × 10^-10) and DOK7, (rs2344205, P = 1.37 × 10^-9). Multiple gene ontology (GO) terms were identified for bilirubin, such as GO_URONIC_ACID_METABOLIC_PROCESS (adjusted P = 4.15 × 10^-26).

CONCLUSION

Our study results suggested negative associations between insomnia and DBil and TBil; and a positive association between insomnia and TP.

Prediction of Probable Major Depressive Disorder in the Taiwan Biobank: An Integrated Machine Learning and Genome-Wide Analysis Approach

In light of recent advancements in machine learning, personalized medicine using predictive algorithms serves as an essential paradigmatic methodology. Our goal was to explore an integrated machine learning and genome-wide analysis approach which targets the prediction of probable major depressive disorder (MDD) using 9828 individuals in the Taiwan Biobank. In our analysis, we reported a genome-wide significant association with probable MDD that has not been previously identified: FBN1 on chromosome 15. Furthermore, we pinpointed 17 single nucleotide polymorphisms (SNPs) which show evidence of both associations with probable MDD and potential roles as expression quantitative trait loci (eQTLs). To predict the status of probable MDD, we established prediction models with random undersampling and synthetic minority oversampling using 17 eQTL SNPs and eight clinical variables. We utilized five state-of-the-art models: logistic ridge regression, support vector machine, C4.5 decision tree, LogitBoost, and random forests. Our data revealed that random forests had the highest performance (area under curve = 0.8905 ± 0.0088; repeated 10-fold cross-validation) among the predictive algorithms to infer complex correlations between biomarkers and probable MDD. Our study suggests that an integrated machine learning and genome-wide analysis approach may offer an advantageous method to establish bioinformatics tools for discriminating MDD patients from healthy controls.

Gender Differences in Depression: Biological, Affective, Cognitive, and Sociocultural Factors

The odds ratio (OR) for gender differences in major depression is 1.95, averaged meta-analytically over all ages and nations. The gender difference appears by age 12, OR = 2.37, and peaks at OR = 3.02 for ages 13-15. Using the ABC (affective, biological, cognitive) model as a framework within a vulnerability-stress approach, we consider the evidence for biological vulnerabilities (genes, pubertal hormones, and pubertal timing), affective vulnerabilities (temperament), and cognitive vulnerabilities (negative cognitive style, objectified body consciousness, and rumination). The impact of stress is central to the vulnerability-stress model, and we review evidence on gender differences in stress exposure, emphasizing gender differences in sex-related traumas such as child sexual abuse and rape. Finally, we examine sociocultural factors that may contribute to the gender difference, including the media and gender inequality. An implication for research methods is that single-gender designs should be questioned. Regarding clinical implications, the vulnerabilities and stressors identified in this review should contribute to personalized interventions with depressed individuals, especially depressed women.

Translating Across Circuits and Genetics Toward Progress in Fear- and Anxiety-Related Disorders

(Reprinted with permission from Am J Psychiatry 2020; 177:214-222).

Na+ leak-current channel (NALCN) at the junction of motor and neuropsychiatric symptoms in Parkinson's disease

Parkinson's disease (PD) is a debilitating movement disorder often accompanied by neuropsychiatric symptoms that stem from the loss of dopaminergic function in the basal ganglia and altered neurotransmission more generally. Akinesia, postural instability, tremors and frozen gait constitute the major motor disturbances, whereas neuropsychiatric symptoms include altered circadian rhythms, disordered sleep, depression, psychosis and cognitive impairment. Evidence is emerging that the motor and neuropsychiatric symptoms may share etiologic factors. Calcium/ion channels (CACNA1C, NALCN), synaptic proteins (SYNJ1) and neuronal RNA-binding proteins (RBFOX1) are among the risk genes that are common to PD and various psychiatric disorders. The Na⁺ leak-current channel (NALCN) is the focus of this review because it has been implicated in dystonia, regulation of movement, cognitive impairment, sleep and circadian rhythms. It regulates the resting membrane potential in neurons, mediates pace-making activity, participates in synaptic vesicle recycling and is functionally co-localized to the endoplasmic reticulum (ER)-several of the major processes adversely affected in PD. Here, we summarize the literature on mechanisms and pathways that connect the motor and neuropsychiatric symptoms of PD with a focus on recurring relationships to the NALCN. It is hoped that the various connections outlined here will stimulate further discussion, suggest additional areas for exploration and ultimately inspire novel treatment strategies.

Socioeconomic Deprivation Index Is Associated With Psychiatric Disorders: An Observational and Genome-wide Gene-by-Environment Interaction Analysis in the UK Biobank Cohort

BACKGROUND

Psychiatric disorders are among the largest and fastest-growing categories of the global disease burden. However, limited effort has been made to further elucidate associations between socioeconomic factors and psychiatric disorders from a genetic perspective.

METHODS

We randomly divided 501,882 participants in the UK Biobank cohort with socioeconomic Townsend deprivation index (TDI) data into a discovery cohort and a replication cohort. For both cohorts, we first conducted regression analyses to evaluate the associations between the TDI and common psychiatric disorders or traits, including anxiety, bipolar disorder, self-harm, and depression (based on self-reported depression and Patient Health Questionnaire scores). We then performed a genome-wide gene-by-environment interaction study using PLINK 2.0 with the TDI as an environmental factor to explore interaction effects.

RESULTS

In the discovery cohort, significant associations were observed between the TDI and psychiatric disorders (p < 4.00 × 10^-16), including anxiety (odds ratio [OR] = 1.08, 95% confidence interval [CI] = 1.07-1.10), bipolar disorder (OR = 1.42, 95% CI = 1.36-1.48), self-harm (OR = 1.21, 95% CI = 1.19-1.23), self-reported depression (OR = 1.22, 95% CI = 1.20-1.24), and Patient Health Questionnaire scores (β = .07, SE = 0.004). We observed similar significant associations in the replication cohort. In addition, multiple candidate loci were identified by the genome-wide gene-by-environment interaction study, including rs10886438 at 10q26.11 (GRK5) (p = 5.72 × 10^-11) for Patient Health Questionnaire scores and rs162553 at 2p22.2 (CYP1B1) (p = 2.25 × 10^-9) for self-harm.

CONCLUSIONS

Our findings suggest the relevance of the TDI to psychiatric disorders. The genome-wide gene-by-environment interaction study identified several candidate genes interacting with the TDI, providing novel clues for understanding the biological mechanism of associations between the TDI and psychiatric disorders.

The Genetics of Major Depression: Perspectives on the State of Research and Opportunities for Precision Medicine

Major depression (MD) is a leading cause of disability worldwide; it arises from the action and interaction between genetic and environmental factors, and is often comorbid with other psychiatric and medical conditions. To date, upwards of 100 genetic loci have been associated with MD, giving clues to biological underpinnings. Although recent progress has yielded modest insight into the genetic architecture of MD, most studies have been in populations with European ancestry, seriously limiting precision medicine efforts. Broadening diversity of study populations will empower genomic research by expanding discovery and enhancing our understanding of the role of genomic variation in disease etiology. To fully realize the potential of pharmacogenetics and precision medicine, we will need to address the major gaps in our knowledge of the genetic and environmental risk architecture of MD across ancestries, including sex differences, to improve etiologic understanding, diagnosis, prevention, and treatment for all.

Genome-wide gene-environment interactions in neuroticism: an exploratory study across 25 environments

Gene-environment interactions (GxE) are often suggested to play an important role in the aetiology of psychiatric phenotypes, yet so far, only a handful of genome-wide environment interaction studies (GWEIS) of psychiatric phenotypes have been conducted. Representing the most comprehensive effort of its kind to date, we used data from the UK Biobank to perform a series of GWEIS for neuroticism across 25 broadly conceptualised environmental risk factors (trauma, social support, drug use, physical health). We investigated interactions on the level of SNPs, genes, and gene-sets, and computed interaction-based polygenic risk scores (PRS) to predict neuroticism in an independent sample subset (N = 10,000). We found that the predictive ability of the interaction-based PRSs did not significantly improve beyond that of a traditional PRS based on SNP main effects from GWAS, but detected one variant and two gene-sets showing significant interaction signal after correction for the number of analysed environments. This study illustrates the possibilities and limitations of a comprehensive GWEIS in currently available sample sizes.

How do established developmental risk-factors for schizophrenia change the way the brain develops?

The recognition that schizophrenia is a disorder of neurodevelopment is widely accepted. The original hypothesis was coined more than 30 years ago and the wealth of supportive epidemiologically data continues to grow. A number of proposals have been put forward to suggest how adverse early exposures in utero alter the way the adult brain functions, eventually producing the symptoms of schizophrenia. This of course is extremely difficult to study in developing human brains, so the bulk of what we know comes from animal models of such exposures. In this review, I will summarise the more salient features of how the major epidemiologically validated exposures change the way the brain is formed leading to abnormal function in ways that are informative for schizophrenia symptomology. Surprisingly few studies have examined brain ontogeny from embryo to adult in such models. However, where there is longitudinal data, various convergent mechanisms are beginning to emerge involving stress and immune pathways. There is also a surprisingly consistent alteration in how very early dopamine neurons develop in these models. Understanding how disparate epidemiologically-validated exposures may produce similar developmental brain abnormalities may unlock convergent early disease-related pathways/processes.

Associations between social determinants of health, perceived discrimination, and body mass index on symptoms of depression among young African American mothers

PURPOSE

The association between symptoms of depression and risks for cardiovascular disease (CVD) remains equivocal for African American (AA) mothers. We examined the association between social determinants of health (perceived discrimination), and cardiovascular risk (BMI) on symptoms of depression in a sample of young AA mothers.

METHODS

Secondary data from 219 adult AA mothers between the ages of 21 and 46 with an average BMI of 29.8 and yearly family income of $14,999 were analyzed using a latent growth model that evaluated four time points to assess changes in symptoms of depression.

RESULTS

Initial BMI was significantly associated with initial symptoms of depression (b = 0.12, p = .019). Perceived discrimination (unfair treatment) was associated with higher initial symptoms of depression (b = 1.14, p = .017).

CONCLUSION

The findings suggest that elevated BMI and perceived discrimination are associated with higher reported symptoms of depression among young, socioeconomically disadvantaged AA mothers. These results advance the scientific understanding of young AA mothers' risk for symptoms of depression and CVD by elucidating the impact of perceived discrimination and social experiences on mental health. Further studies of SDoH and CVD risk factors and perceived racism and depression are needed to shed light on the long-term mental health impact on AA mothers and their children.

Maternal antenatal depression and child mental health: Moderation by genomic risk for attention-deficit/hyperactivity disorder

Maternal antenatal depression strongly influences child mental health but with considerable inter-individual variation that is, in part, linked to genotype. The challenge is to effectively capture the genotypic influence. We outline a novel approach to describe genomic susceptibility to maternal antenatal depression focusing on child emotional/behavioral difficulties. Two cohorts provided measures of maternal depression, child genetic variation, and child mental health symptoms. We constructed a conventional polygenic risk score (PRS) for attention-deficit/hyperactivity disorder (ADHD) (PRSADHD) that significantly moderated the association between maternal antenatal depression and internalizing problems at 60 months (p = 2.94 × 10-4, R2 = .18). We then constructed an interaction PRS (xPRS) based on a subset of those single nucleotide polymorphisms from the PRSADHD that most accounted for the moderation of the association between maternal antenatal depression and child outcome. The interaction between maternal antenatal depression and this xPRS accounted for a larger proportion of the variance in child emotional/behavioral problems than models based on any PRSADHD (p = 5.50 × 10-9, R2 = .27), with similar findings in the replication cohort. The xPRS was significantly enriched for genes involved in neuronal development and synaptic function. Our study illustrates a novel approach to the study of genotypic moderation on the impact of maternal antenatal depression on child mental health and highlights the utility of the xPRS approach. These findings advance our understanding of individual differences in the developmental origins of mental health.

Construction and Analysis of a Diagnostic Model Based on Differential Expression Genes in Patients With Major Depressive Disorder

Background: Major depressive disorder (MDD) is a common and severe psychiatric disorder with a heavy burden on the individual and society. However, the prevalence varies significantly owing to the lack of auxiliary diagnostic biomarkers. To identify the shared differential expression genes (DEGs) with potential diagnostic value in both the hippocampus and whole blood, a systematic and integrated bioinformatics analysis was carried out. Methods: Two datasets from the Gene Expression Omnibus database (GSE53987 and GSE98793) were downloaded and analyzed separately. A weighted gene co-expression network analysis was performed to construct the co-expression gene network of DEGs from GSE53987, and the most disease-related module was extracted. The shared DEGs from the module and GSE98793 were identified using a Venn diagram. Functional pathway prediction was used to identify the most disease-related DEGs. Finally, several DEGs were chosen, and their potential diagnostic value was determined by receiver operating characteristic curve analysis. Results: After weighted gene co-expression network analysis, the most MDD-related module (MEgrey) was identified, and 623 DEGs were extracted from this module. The intersection between MEgrey and GSE98793 was calculated, and 163 common DEGs were identified. The co-expression network of 163 DEGs from these was then reconstructed. All hub genes were identified based on the connective degree of the reconstructed co-expression network. Based on the results of functional pathway enrichment, 17 candidate hub genes were identified. Finally, logistic regression and receiver operating characteristic curves showed that three candidate hub genes (CEP350, SMAD5, and HSPG2) had relatively high auxiliary value in the diagnosis of MDD. Conclusion: Our results showed that the combination of CEP350, SMAD5, and HSPG2 has a relatively high diagnostic value for MDD. Pathway enrichment analysis also showed that these genes may play an important role in the pathogenesis of MDD. These results suggest a potentially important role for this gene combination in clinical practice.

DCC gene network in the prefrontal cortex is associated with total brain volume in childhood

BACKGROUND

Genetic variation in the guidance cue DCC gene is linked to psychopathologies involving dysfunction in the prefrontal cortex. We created an expression-based polygenic risk score (ePRS) based on the DCC coexpression gene network in the prefrontal cortex, hypothesizing that it would be associated with individual differences in total brain volume.

METHODS

We filtered single nucleotide polymorphisms (SNPs) from genes coexpressed with DCC in the prefrontal cortex obtained from an adult postmortem donors database (BrainEAC) for genes enriched in children 1.5 to 11 years old (BrainSpan). The SNPs were weighted by their effect size in predicting gene expression in the prefrontal cortex, multiplied by their allele number based on an individual's genotype data, and then summarized into an ePRS. We evaluated associations between the DCC ePRS and total brain volume in children in 2 community-based cohorts: the Maternal Adversity, Vulnerability and Neurodevelopment (MAVAN) and University of California, Irvine (UCI) projects. For comparison, we calculated a conventional PRS based on a genome-wide association study of total brain volume.

RESULTS

Higher ePRS was associated with higher total brain volume in children 8 to 10 years old (β = 0.212, p = 0.043; n = 88). The conventional PRS at several different thresholds did not predict total brain volume in this cohort. A replication analysis in an independent cohort of newborns from the UCI study showed an association between the ePRS and newborn total brain volume (β = 0.101, p = 0.048; n = 80). The genes included in the ePRS demonstrated high levels of coexpression throughout the lifespan and are primarily involved in regulating cellular function.

LIMITATIONS

The relatively small sample size and age differences between the main and replication cohorts were limitations.

CONCLUSION

Our findings suggest that the DCC coexpression network in the prefrontal cortex is critically involved in whole brain development during the first decade of life. Genes comprising the ePRS are involved in gene translation control and cell adhesion, and their expression in the prefrontal cortex at different stages of life provides a snapshot of their dynamic recruitment.

An Overview of the Heterogeneity of Major Depressive Disorder: Current Knowledge and Future Prospective

Major depressive disorder (MDD) is estimated to impose maximum debilitating effects on the society by 2030, with its critical effects on health, functioning, quality of life and concomitant high levels of morbidity and mortality. Yet, the disease is inadequately understood, diagnosed and treated. Moreover, with the recent drastic rise in the pace of life, stress has materialized as one of the most potent environmental factors for depression. In this scenario, it is important to understand the modern pathogenetic hypotheses and mechanisms, and possibly try to shift from the traditional approaches in depression therapy. These include the elaboration of pathophysiological changes in heterogeneous systems such as genetic, epigenetic, serotonergic, noradrenergic, gamma-aminobutyric acid, glutamatergic and endocannabinoid systems, neurotrophic factors, HPA axis, immune system as well as cellular stress mechanisms. These components interact with each other in a complex matrix and further elucidation of their mechanism and cascade pathways are needed. This might aid in the identification of MDD subtypes as well as the development of sophisticated biomarkers. Further, characterization might also aid in developing multitargeted therapies that hold much promise as compared to the conventional monoamine based treatment. New candidate pharmacons, refined psychotherapeutic modalities, advanced neuro-surgical and imaging techniques as well as the implementation of pharmacokinetic, pharmacogenetic prescribing guidelines constitute the emerging expanses of MDD treatment.

miR-218 in Adolescence Predicts and Mediates Vulnerability to Stress

BACKGROUND

Adolescence is a period of increased vulnerability to psychiatric disorders, including depression. Discovering novel biomarkers to identify individuals who are at high risk is very much needed. Our previous work shows that the microRNA miR-218 mediates susceptibility to stress and depression in adulthood by targeting the netrin-1 guidance cue receptor gene Dcc in the medial prefrontal cortex (mPFC).

METHODS

Here, we investigated whether miR-218 regulates Dcc expression in adolescence and could serve as an early predictor of lifetime stress vulnerability in male mice.

RESULTS

miR-218 expression in the mPFC increases from early adolescence to adulthood and correlates negatively with Dcc levels. In blood, postnatal miR-218 expression parallels changes occurring in the mPFC. Notably, circulating miR-218 levels in adolescence associate with vulnerability to social defeat stress in adulthood, with high levels associated with social avoidance severity. Indeed, downregulation of miR-218 in the mPFC in adolescence promotes resilience to stress in adulthood.

CONCLUSIONS

miR-218 expression in adolescence may serve both as a marker of risk and as a target for early interventions.

Polygenic prediction of PTSD trajectories in 9/11 responders

BACKGROUND

Genetics hold promise of predicting long-term post-traumatic stress disorder (PTSD) outcomes following trauma. The aim of the current study was to test whether six hypothesized polygenic risk scores (PRSs) developed to capture genetic vulnerability to psychiatric conditions prospectively predict PTSD onset, severity, and 18-year course after trauma exposure.

METHODS

Participants were 1490 responders to the World Trade Center (WTC) disaster (mean age at 9/11 = 38.81 years, s.d. = 8.20; 93.5% male; 23.8% lifetime WTC-related PTSD diagnosis). Prospective longitudinal data on WTC-related PTSD symptoms were obtained from electronic medical records and modelled as PTSD trajectories using growth mixture model analysis. Independent regression models tested whether six hypothesized psychiatric PRSs (PTSD-PRS, Re-experiencing-PRS, Generalized Anxiety-PRS, Schizophrenia-PRS, Depression-PRS, and Neuroticism-PRS) are predictive of WTC-PTSD outcomes: lifetime diagnoses, average symptom severity, and 18-year symptom trajectory. All analyses were adjusted for population stratification, 9/11 exposure severity, and multiple testing.

RESULTS

Depression-PRS predicted PTSD diagnostic status (OR 1.37, CI 1.17-1.61, adjusted p = 0.001). All PRSs, except PTSD-PRS, significantly predicted average PTSD symptoms (β = 0.06-0.10, adjusted p < 0.05). Re-experiencing-PRS, Generalized Anxiety-PRS and Schizophrenia-PRS predicted the high severity PTSD trajectory class (ORs 1.21-1.28, adjusted p < 0.05). Finally, PRSs prediction was independent of 9/11 exposure severity and jointly accounted for 3.7 times more variance in PTSD symptoms than the exposure severity.

CONCLUSIONS

Psychiatric PRSs prospectively predicted WTC-related PTSD lifetime diagnosis, average symptom severity, and 18-year trajectory in responders to 9/11 disaster. Jointly, PRSs were more predictive of subsequent PTSD than the exposure severity. In the future, PRSs may help identify at-risk responders who might benefit from targeted prevention approaches.

AVPR1A main effect and OXTR-by-environment interplay in individual differences in depression level

Background

Multiple studies of depression indicated a significant role of gene-by-environment interactions; however, they are mainly limited to the examination of modulating effect of recent stressful life events. Other environmental factors occurring at different stages of ante- and postnatal development may affect the association between multiple genes and depression. The study aimed to analyze the main and haplotype-based effect of serotonergic system and HPA-axis gene polymorphisms on depression and to detect gene-by-environment interaction models explaining individual variance in depression in mentally healthy young adults from Russia.

Methods

Depression score was assessed using Beck Depression Inventory (BDI) in 623 healthy individuals (81% women; 17-25 years) of Caucasian origin (Russians, Tatars, Udmurts) from Russia. The main- and gene-based effects of 12 SNPs in SLC6A4 (5-HTTLPR, rs1042173), HTR2A (rs7322347), OXTR (rs7632287, rs2254298, rs13316193, rs53576, rs2228485, rs237911), AVPR1A (rs3803107, rs1042615), and AVPR1B (rs33911258) genes, and gene-by-environment interactions were tested with linear regression models (PLINK v.1.9) adjusted for multiple comparisons.

Results

We observed ethnicity-specific main effect of the AVPR1A rs3803107 (P = 0.003; P_FDR = 0.047) and gene-based effect of the OXTR gene (Р = 0.005; P_perm = 0.034) on BDI-measured depression, and modifying effect of paternal care on OXTR rs53576 (P = 0.004; P_FDR = 0.012) and birth order on OXTR rs237911 (P = 0.006; P_FDR = 0.018) association with depression level.

Limitations

A hypothesis driven candidate gene approach, which examined a limited number of genetic variants in a moderately large sample, was used.

Conclusions

Our preliminary findings indicate that familial environment may play a permissive role modulating the manifestation of OXTR-based depression variance in mentally healthy subjects.

The Netrin-1/DCC Guidance Cue Pathway as a Molecular Target in Depression: Translational Evidence

The Netrin-1/DCC guidance cue pathway plays a critical role in guiding growing axons toward the prefrontal cortex during adolescence and in the maturational organization and adult plasticity of prefrontal cortex connectivity. In this review, we put forward the idea that alterations in prefrontal cortex architecture and function, which are intrinsically linked to the development of major depressive disorder, originate in part from the dysregulation of the Netrin-1/DCC pathway by a mechanism that involves microRNA-218. We discuss evidence derived from mouse models of stress and from human postmortem brain and genome-wide association studies indicating an association between the Netrin-1/DCC pathway and major depressive disorder. We propose a potential role of circulating microRNA-218 as a biomarker of stress vulnerability and major depressive disorder.

Parenting Interacts with Oxytocin Polymorphisms to Predict Adolescent Social Anxiety Symptom Development: A Novel Polygenic Approach

Guided by a developmental psychopathology framework, research has increasingly focused on the interplay of genetics and environment as a predictor of different forms of psychopathology, including social anxiety. In these efforts, the polygenic nature of complex phenotypes such as social anxiety is increasingly recognized, but studies applying polygenic approaches are still scarce. In this study, we applied Principal Covariates Regression as a novel approach to creating polygenic components for the oxytocin system, which has recently been put forward as particularly relevant to social anxiety. Participants were 978 adolescents (49.4% girls; M_age T₁ = 13.8 years). Across 3 years, questionnaires were used to assess adolescent social anxiety symptoms and multi-informant reports of parental psychological control and autonomy support. All adolescents were genotyped for 223 oxytocin single nucleotide polymorphisms (SNPs) in 14 genes. Using Principal Covariates Regression, these SNPs could be reduced to five polygenic components. Four components reflected the underlying linkage disequilibrium and ancestry structure, whereas the fifth component, which consisted of small contributions of many SNPs across multiple genes, was strongly positively associated with adolescent social anxiety symptoms, pointing to an index of genetic risk. Moreover, significant interactions were found with this polygenic component and the environmental variables of interest. Specifically, adolescents who scored high on this polygenic component and experienced less adequate parenting (i.e., high psychological control or low autonomy support) showed the highest levels of social anxiety. Implications of these findings are discussed in the context of individual-by-environment models.

Convergent Functional Genomics approach to prioritize molecular targets of risk in early life stress-related psychiatric disorders

There is an overwhelming evidence proving that mental disorders are not the product of a single risk factor - i.e. genetic variants or environmental factors, including exposure to maternal perinatal mental health problems or childhood adverse events - rather the product of a trajectory of cumulative and multifactorial insults occurring during development, such as exposures during the foetal life to adverse mental condition in the mother, or exposures to adverse traumatic events during childhood or adolescence. In this review, we aim to highlight the potential utility of a Convergent Functional Genomics (CFG) approach to clarify the complex brain-relevant molecular mechanisms and alterations induced by early life stress (ELS). We describe different studies based on CFG in psychiatry and neuroscience, and we show how this 'hypothesis-free' tool can prioritize a stringent number of genes modulated by ELS, that can be tested as potential candidates for Gene x Environment (GxE) interaction studies. We discuss the results obtained by using a CFG approach identifying FoxO1 as a gene where genetic variability can mediate the effect of an adverse environment on the development of depression. Moreover, we also demonstrate that FoxO1 has a functional relevance in stress-induced reduction of neurogenesis, and can be a potential target for the prevention or treatment of stress-related psychiatric disorders. Overall, we suggest that CFG approach could include trans-species and tissues data integration and we also propose the application of CFG to examine in depth and to prioritize top candidate genes that are affected by ELS across lifespan and generations.

Genetic Liability for Depression, Social Factors and Their Interaction Effect in Depressive Symptoms and Depression Over Time in Older Adults

OBJECTIVES

The objectives of this study were to investigate the effect of genetic and social factors on depressive symptoms and depression over time and to test whether social factors moderate the relationship between depressive symptoms and its underlying genetics in later life.

METHODS

The study included 2,279 participants with a mean follow-up of 15 years from the Longitudinal Aging Study Amsterdam with genotyping data. The personal genetic loading for depression was estimated for each participant by calculating a polygenic risk scores (PRS-D), based on 23,032 single nucleotide polymorphisms associated with major depression in a large genome-wide association study. Partner status, network size, received and given emotional support were assessed via questionnaires and depressive symptoms were assessed using the CES-D Scale. A CES-D Scale of 16 and higher was considered as clinically relevant depression.

RESULTS

Higher PRS-D was associated with more depressive symptoms whereas having a partner and having a larger network size were independently associated with less depressive symptoms. After extra adjustment for education, cognitive function and functional limitations, giving more emotional support was also associated with less depressive symptoms. No evidence for gene-environment interaction between PRS-D and social factors was found. Similar results were found for clinically relevant depression.

CONCLUSION

Genetic and social factors are independently associated with depressive symptoms over time in older adults. Strategies that boost social functioning should be encouraged in the general population of older adults regardless of the genetic liability for depression.

Neuronal α2δ proteins and brain disorders

α2δ proteins are membrane-anchored extracellular glycoproteins which are abundantly expressed in the brain and the peripheral nervous system. They serve as regulatory subunits of voltage-gated calcium channels and, particularly in nerve cells, regulate presynaptic and postsynaptic functions independently from their role as channel subunits. α2δ proteins are the targets of the widely prescribed anti-epileptic and anti-allodynic drugs gabapentin and pregabalin, particularly for the treatment of neuropathic pain conditions. Recently, the human genes (CACNA2D1-4) encoding for the four known α2δ proteins (isoforms α2δ-1 to α2δ-4) have been linked to a large variety of neurological and neuropsychiatric disorders including epilepsy, autism spectrum disorders, bipolar disorders, schizophrenia, and depressive disorders. Here, we provide an overview of the hitherto identified disease associations of all known α2δ genes, hypothesize on the pathophysiological mechanisms considering their known physiological roles, and discuss the most immanent future research questions. Elucidating their specific physiological and pathophysiological mechanisms may open the way for developing entirely novel therapeutic paradigms for treating brain disorders.

Genome-wide gene-environment analyses of major depressive disorder and reported lifetime traumatic experiences in UK Biobank

Depression is more frequent among individuals exposed to traumatic events. Both trauma exposure and depression are heritable. However, the relationship between these traits, including the role of genetic risk factors, is complex and poorly understood. When modelling trauma exposure as an environmental influence on depression, both gene-environment correlations and gene-environment interactions have been observed. The UK Biobank concurrently assessed Major Depressive Disorder (MDD) and self-reported lifetime exposure to traumatic events in 126,522 genotyped individuals of European ancestry. We contrasted genetic influences on MDD stratified by reported trauma exposure (final sample size range: 24,094-92,957). The SNP-based heritability of MDD with reported trauma exposure (24%) was greater than MDD without reported trauma exposure (12%). Simulations showed that this is not confounded by the strong, positive genetic correlation observed between MDD and reported trauma exposure. We also observed that the genetic correlation between MDD and waist circumference was only significant in individuals reporting trauma exposure (rg = 0.24, p = 1.8 × 10-7 versus rg = -0.05, p = 0.39 in individuals not reporting trauma exposure, difference p = 2.3 × 10-4). Our results suggest that the genetic contribution to MDD is greater when reported trauma is present, and that a complex relationship exists between reported trauma exposure, body composition, and MDD.

Sex-Specific Role for the Long Non-coding RNA LINC00473 in Depression

Depression is a common disorder that affects women at twice the rate of men. Here, we report that long non-coding RNAs (lncRNAs), a recently discovered class of regulatory transcripts, represent about one-third of the differentially expressed genes in the brains of depressed humans and display complex region- and sex-specific patterns of regulation. We identified the primate-specific, neuronal-enriched gene LINC00473 as downregulated in prefrontal cortex (PFC) of depressed females but not males. Using viral-mediated gene transfer to express LINC00473 in adult mouse PFC neurons, we mirrored the human sex-specific phenotype by inducing stress resilience solely in female mice. This sex-specific phenotype was accompanied by changes in synaptic function and gene expression selectively in female mice and, along with studies of human neuron-like cells in culture, implicates LINC00473 as a CREB effector. Together, our studies identify LINC00473 as a female-specific driver of stress resilience that is aberrant in female depression.