Prediction of antipsychotics efficacy based on a polygenic risk score: a real-world cohort study.

Background: Response to antipsychotics is subject to a wide interindividual variability, due to genetic and non-genetic factors. Several single nucleotide polymorphisms (SNPs) have been associated with response to antipsychotics in genome-wide association studies (GWAS). Polygenic risk scores (PRS) are a powerful tool to aggregate into a single measure the small effects of multiple risk alleles. Materials and methods: We studied the association between a PRS composed of SNPs associated with response to antipsychotics in GWAS studies (PRSresponse) in a real-world sample of patients (N = 460) with different diagnoses (schizophrenia spectrum, bipolar, depressive, neurocognitive, substance use disorders and miscellaneous). Two other PRSs composed of SNPs previously associated with risk of schizophrenia (PRSschizophrenia1 and PRSschizophrenia2) were also tested for their association with response to treatment. Results: PRSresponse was significantly associated with response to antipsychotics considering the whole cohort (OR = 1.14, CI = 1.03-1.26, p = 0.010), the subgroup of patients with schizophrenia, schizoaffective disorder or bipolar disorder (OR = 1.18, CI = 1.02-1.37, p = 0.022, N = 235), with schizophrenia or schizoaffective disorder (OR = 1.24, CI = 1.04-1.47, p = 0.01, N = 176) and with schizophrenia (OR = 1.27, CI = 1.04-1.55, p = 0.01, N = 149). Sensitivity and specificity were sub-optimal (schizophrenia 62%, 61%; schizophrenia spectrum 56%, 55%; schizophrenia spectrum plus bipolar disorder 60%, 56%; all patients 63%, 58%, respectively). PRSschizophrenia1 and PRSschizophrenia2 were not significantly associated with response to treatment. Conclusion: PRSresponse defined from GWAS studies is significantly associated with response to antipsychotics in a real-world cohort; however, the results of the sensitivity-specificity analysis preclude its use as a predictive tool in clinical practice.

Cholesterol-metabolism, plant sterols, and long-term cognitive decline in older people - Effects of sex and APOEe4.

Neurodegenerative, vascular, and dementia diseases are linked to dysregulations in cholesterol metabolism. Dietary plant sterols, or phytosterols, may interfere to neurodegeneration and cognitive decline, and have cholesterol-lowering, anti-inflammatory, and antioxidant qualities. Here, we investigated the potential associations between circulating cholesterol precursors and metabolites, triglycerides, and phytosterols with cognitive decline in older people by performing multivariate analysis on 246 participants engaged in a population-based prospective study. In our analysis we considered the potential effect of sex and APOEe4. We reveal particular dysregulations of diet-derived phytosterols and endogenous cholesterol synthesis and metabolism, and their variations over time linked to cognitive decline in the general population. These results are significant to the development of interventions to avoid cognitive decline in older adults and suggest that levels of circulating sterols should be taken into account when evaluating risk.

GWAS Meta-Analysis of Suicide Attempt: Identification of 12 Genome-Wide Significant Loci and Implication of Genetic Risks for Specific Health Factors.

OBJECTIVE: Suicidal behavior is heritable and is a major cause of death worldwide. Two large-scale genome-wide association studies (GWASs) recently discovered and cross-validated genome-wide significant (GWS) loci for suicide attempt (SA). The present study leveraged the genetic cohorts from both studies to conduct the largest GWAS meta-analysis of SA to date. Multi-ancestry and admixture-specific meta-analyses were conducted within groups of significant African, East Asian, and European ancestry admixtures. METHODS: This study comprised 22 cohorts, including 43,871 SA cases and 915,025 ancestry-matched controls. Analytical methods across multi-ancestry and individual ancestry admixtures included inverse variance-weighted fixed-effects meta-analyses, followed by gene, gene-set, tissue-set, and drug-target enrichment, as well as summary-data-based Mendelian randomization with brain expression quantitative trait loci data, phenome-wide genetic correlation, and genetic causal proportion analyses. RESULTS: Multi-ancestry and European ancestry admixture GWAS meta-analyses identified 12 risk loci at p values <5×10-8. These loci were mostly intergenic and implicated DRD2, SLC6A9, FURIN, NLGN1, SOX5, PDE4B, and CACNG2. The multi-ancestry SNP-based heritability estimate of SA was 5.7% on the liability scale (SE=0.003, p=5.7×10-80). Significant brain tissue gene expression and drug set enrichment were observed. There was shared genetic variation of SA with attention deficit hyperactivity disorder, smoking, and risk tolerance after conditioning SA on both major depressive disorder and posttraumatic stress disorder. Genetic causal proportion analyses implicated shared genetic risk for specific health factors. CONCLUSIONS: This multi-ancestry analysis of suicide attempt identified several loci contributing to risk and establishes significant shared genetic covariation with clinical phenotypes. These findings provide insight into genetic factors associated with suicide attempt across ancestry admixture populations, in veteran and civilian populations, and in attempt versus death.

Genetic structure of major depression symptoms across clinical and community cohorts.

Diagnostic criteria for major depressive disorder allow for heterogeneous symptom profiles but genetic analysis of major depressive symptoms has the potential to identify clinical and aetiological subtypes. There are several challenges to integrating symptom data from genetically-informative cohorts, such as sample size differences between clinical and community cohorts and various patterns of missing data. We conducted genome-wide association studies of major depressive symptoms in three clinical cohorts that were enriched for affected participants (Psychiatric Genomics Consortium, Australian Genetics of Depression Study, Generation Scotland) and three community cohorts (Avon Longitudinal Study of Parents and Children, Estonian Biobank, and UK Biobank). We fit a series of confirmatory factor models with factors that accounted for how symptom data was sampled and then compared alternative models with different symptom factors. The best fitting model had a distinct factor for Appetite/Weight symptoms and an additional measurement factor that accounted for missing data patterns in the community cohorts (use of Depression and Anhedonia as gating symptoms). The results show the importance of assessing the directionality of symptoms (such as hypersomnia versus insomnia) and of accounting for study and measurement design when meta-analysing genetic association data.

Uncovering the genetic architecture of broad antisocial behavior through a genome-wide association study meta-analysis.

Despite the substantial heritability of antisocial behavior (ASB), specific genetic variants robustly associated with the trait have not been identified. The present study by the Broad Antisocial Behavior Consortium (BroadABC) meta-analyzed data from 28 discovery samples (N = 85,359) and five independent replication samples (N = 8058) with genotypic data and broad measures of ASB. We identified the first significant genetic associations with broad ASB, involving common intronic variants in the forkhead box protein P2 (FOXP2) gene (lead SNP rs12536335, p = 6.32 × 10-10). Furthermore, we observed intronic variation in Foxp2 and one of its targets (Cntnap2) distinguishing a mouse model of pathological aggression (BALB/cJ strain) from controls (BALB/cByJ strain). Polygenic risk score (PRS) analyses in independent samples revealed that the genetic risk for ASB was associated with several antisocial outcomes across the lifespan, including diagnosis of conduct disorder, official criminal convictions, and trajectories of antisocial development. We found substantial genetic correlations of ASB with mental health (depression rg = 0.63, insomnia rg = 0.47), physical health (overweight rg = 0.19, waist-to-hip ratio rg = 0.32), smoking (rg = 0.54), cognitive ability (intelligence rg = -0.40), educational attainment (years of schooling rg = -0.46) and reproductive traits (age at first birth rg = -0.58, father's age at death rg = -0.54). Our findings provide a starting point toward identifying critical biosocial risk mechanisms for the development of ASB.

Gene set enrichment analysis of pathophysiological pathways highlights oxidative stress in psychosis.

Polygenic risk prediction remains an important aim of genetic association studies. Currently, the predictive power of schizophrenia polygenic risk scores (PRSs) is not large enough to allow highly accurate discrimination between cases and controls and thus is not adequate for clinical integration. Since PRSs are rarely used to reveal biological functions or to validate candidate pathways, to fill this gap, we investigated whether their predictive ability could be improved by building genome-wide (GW-PRSs) and pathway-specific PRSs, using distance- or expression quantitative trait loci (eQTLs)- based mapping between genetic variants and genes. We focused on five pathways (glutamate, oxidative stress, GABA/interneurons, neuroimmune/neuroinflammation and myelin) which belong to a critical hub of schizophrenia pathophysiology, centred on redox dysregulation/oxidative stress. Analyses were first performed in the Lausanne Treatment and Early Intervention in Psychosis Program (TIPP) study (n = 340, cases/controls: 208/132), a sample of first-episode of psychosis patients and matched controls, and then validated in an independent study, the epidemiological and longitudinal intervention program of First-Episode Psychosis in Cantabria (PAFIP) (n = 352, 224/128). Our results highlighted two main findings. First, GW-PRSs for schizophrenia were significantly associated with early psychosis status. Second, oxidative stress was the only significantly associated pathway that showed an enrichment in both the TIPP (p = 0.03) and PAFIP samples (p = 0.002), and exclusively when gene-variant linking was done using eQTLs. The results suggest that the predictive accuracy of polygenic risk scores could be improved with the inclusion of information from functional annotations, and through a focus on specific pathways, emphasizing the need to build and study functionally informed risk scores.

Environmental factors in offspring of parents with mood disorders and their role in parent-child transmission: findings from a 14-year prospective high-risk study.

BACKGROUND: The factors involved in the transmission of mood disorders are only partially elucidated. Aside from genes, the family environment might play a crucial role in parent-child transmission. Our goals were to (1) assess the associations of parental bipolar disorder (BPD) and Major Depressive Disorder (MDD) with individual or shared family environmental factors, including traumatic events in offspring, parental separation, family cohesion and parental attitudes; and 2) test whether these factors were mediators of the association between exposure to parental mood disorders and the onset of these disorders in offspring. METHODS: The sample stems from an ongoing family high-risk study of mood disorders conducted in the French-speaking part of Switzerland. Given the strong impact of the age of onset of parental disorders on their transmission to children, parental disorders were dichotomized according to the onset (cut-off 21 years). Probands with early-onset (n = 30) and later-onset BPD (n = 51), early-onset (n = 21) and later-onset MDD (n = 47) and controls (n = 65), along with their spouses (n = 193) and offspring (n = 388; < 18 years on study inclusion), were assessed over a mean follow-up duration of 14 years (s.d: 4.6). The environmental measures were based on reports by offspring collected before the onset of their first mood episode. RESULTS: Offspring of probands with later-onset BPD and offspring of probands with both early-onset and later-onset MDD reported traumatic events more frequently than comparison offspring, whereas exposure to parental separation was more frequent in all groups of high-risk offspring. Moreover, several familial environment scores including parenting attitudes differed between offspring of probands with BPD and comparison offspring. However, none of these factors were mediators of the parent-child transmission of BPD. Among the environmental factors, traumatic events were shown to be modest mediators of the transmission of early-onset MDD. CONCLUSIONS: Our data do not support the implication of the assessed environmental factors in the parent-child transmission of BPD. In contrast to BPD, traumatic events partially mediate the parent-child transmission of early-onset MDD, which has important implications for intervention and prevention. Early therapeutic efforts in offspring exposed to these events are likely to reduce their deleterious impact on the risk of subsequent MDD.

Transcriptome-based polygenic score links depression-related corticolimbic gene expression changes to sex-specific brain morphology and depression risk.

Studies in post-mortem human brain tissue have associated major depressive disorder (MDD) with cortical transcriptomic changes, whose potential in vivo impact remains unexplored. To address this translational gap, we recently developed a transcriptome-based polygenic risk score (T-PRS) based on common functional variants capturing 'depression-like' shifts in cortical gene expression. Here, we used a non-clinical sample of young adults (n = 482, Duke Neurogenetics Study: 53% women; aged 19.8 ± 1.2 years) to map T-PRS onto brain morphology measures, including Freesurfer-derived subcortical volume, cortical thickness, surface area, and local gyrification index, as well as broad MDD risk, indexed by self-reported family history of depression. We conducted side-by-side comparisons with a PRS independently derived from a Psychiatric Genomics Consortium (PGC) MDD GWAS (PGC-PRS), and sought to link T-PRS with diagnosis and symptom severity directly in PGC-MDD participants (n = 29,340, 59% women; 12,923 MDD cases, 16,417 controls). T-PRS was associated with smaller amygdala volume in women (t = -3.478, p = 0.001) and lower prefrontal gyrification across sexes. In men, T-PRS was associated with hypergyrification in temporal and occipital regions. Prefrontal hypogyrification mediated a male-specific indirect link between T-PRS and familial depression (b = 0.005, p = 0.029). PGC-PRS was similarly associated with lower amygdala volume and cortical gyrification; however, both effects were male-specific and hypogyrification emerged in distinct parietal and temporo-occipital regions, unassociated with familial depression. In PGC-MDD, T-PRS did not predict diagnosis (OR = 1.007, 95% CI = [0.997-1.018]) but correlated with symptom severity in men (rho = 0.175, p = 7.957 × 10-4) in one cohort (N = 762, 48% men). Depression-like shifts in cortical gene expression have sex-specific effects on brain morphology and may contribute to broad depression vulnerability in men.

The association between genetically determined ABO blood types and major depressive disorder.

ABO blood types and their corresponding antigens have long been assumed to be related to different human diseases. So far, smaller studies on the relationship between mental disorders and blood types yielded contradicting results. In this study we analyzed the association between ABO blood types and lifetime major depressive disorder (MDD). We performed a pooled analysis with data from 26 cohorts that are part of the MDD working group of the Psychiatric Genomics Consortium (PGC). The dataset included 37,208 individuals of largely European ancestry of which 41.6% were diagnosed with lifetime MDD. ABO blood types were identified using three single nucleotide polymorphisms in the ABO gene: rs505922, rs8176746 and rs8176747. Regression analyses were performed to assess associations between the individual ABO blood types and MDD diagnosis as well as putative interaction effects with sex. The models were adjusted for sex, cohort and the first ten genetic principal components. The percentage of blood type A was slightly lower in cases than controls while blood type O was more prominent in cases. However, these differences were not statistically significant. Our analyses found no evidence of an association between ABO blood types and major depressive disorder.

Obesity and atypical depression symptoms: findings from Mendelian randomization in two European cohorts.

Studies considering the causal role of body mass index (BMI) for the predisposition of major depressive disorder (MDD) based on a Mendelian Randomization (MR) approach have shown contradictory results. These inconsistent findings may be attributable to the heterogeneity of MDD; in fact, several studies have documented associations between BMI and mainly the atypical subtype of MDD. Using a MR approach, we investigated the potential causal role of obesity in both the atypical subtype and its five specific symptoms assessed according to the Statistical Manual of Mental Disorders (DSM), in two large European cohorts, CoLaus|PsyCoLaus (n = 3350, 1461 cases and 1889 controls) and NESDA|NTR (n = 4139, 1182 cases and 2957 controls). We first tested general obesity measured by BMI and then the body fat distribution measured by waist-to-hip ratio (WHR). Results suggested that BMI is potentially causally related to the symptom increase in appetite, for which inverse variance weighted, simple median and weighted median MR regression estimated slopes were 0.68 (SE = 0.23, p = 0.004), 0.77 (SE = 0.37, p = 0.036), and 1.11 (SE = 0.39, p = 0.004). No causal effect of BMI or WHR was found on the risk of the atypical subtype or for any of the other atypical symptoms. Our findings show that higher obesity is likely causal for the specific symptom of increase in appetite in depressed participants and reiterate the need to study depression at the granular level of its symptoms to further elucidate potential causal relationships and gain additional insight into its biological underpinnings.

Genetic comorbidity between major depression and cardio-metabolic traits, stratified by age at onset of major depression.

It is imperative to understand the specific and shared etiologies of major depression and cardio-metabolic disease, as both traits are frequently comorbid and each represents a major burden to society. This study examined whether there is a genetic association between major depression and cardio-metabolic traits and if this association is stratified by age at onset for major depression. Polygenic risk scores analysis and linkage disequilibrium score regression was performed to examine whether differences in shared genetic etiology exist between depression case control status (N cases = 40,940, N controls = 67,532), earlier (N = 15,844), and later onset depression (N = 15,800) with body mass index, coronary artery disease, stroke, and type 2 diabetes in 11 data sets from the Psychiatric Genomics Consortium, Generation Scotland, and UK Biobank. All cardio-metabolic polygenic risk scores were associated with depression status. Significant genetic correlations were found between depression and body mass index, coronary artery disease, and type 2 diabetes. Higher polygenic risk for body mass index, coronary artery disease, and type 2 diabetes was associated with both early and later onset depression, while higher polygenic risk for stroke was associated with later onset depression only. Significant genetic correlations were found between body mass index and later onset depression, and between coronary artery disease and both early and late onset depression. The phenotypic associations between major depression and cardio-metabolic traits may partly reflect their overlapping genetic etiology irrespective of the age depression first presents.

Minimal phenotyping yields genome-wide association signals of low specificity for major depression.

Minimal phenotyping refers to the reliance on the use of a small number of self-reported items for disease case identification, increasingly used in genome-wide association studies (GWAS). Here we report differences in genetic architecture between depression defined by minimal phenotyping and strictly defined major depressive disorder (MDD): the former has a lower genotype-derived heritability that cannot be explained by inclusion of milder cases and a higher proportion of the genome contributing to this shared genetic liability with other conditions than for strictly defined MDD. GWAS based on minimal phenotyping definitions preferentially identifies loci that are not specific to MDD, and, although it generates highly predictive polygenic risk scores, the predictive power can be explained entirely by large sample sizes rather than by specificity for MDD. Our results show that reliance on results from minimal phenotyping may bias views of the genetic architecture of MDD and impede the ability to identify pathways specific to MDD.

Major depression subtypes are differentially associated with migraine subtype, prevalence and severity.

OBJECTIVE: Migraine and major depressive disorder show a high rate of comorbidity, but little is known about the associations between the subtypes of major depressive disorder and migraine. In this cross-sectional study we aimed at investigating a) the lifetime associations between the atypical, melancholic, combined and unspecified subtype of major depressive disorder and migraine with and without aura and b) the associations between major depressive disorder and its subtypes and the severity of migraine. METHODS: A total of 446 subjects with migraine (migraine without aura: n = 294; migraine with aura: n = 152) and 2511 controls from the population-based CoLaus/PsyCoLaus study, Switzerland, were included. Associations between major depressive disorder subtypes and migraine characteristics were tested using binary logistic or linear regression. RESULTS: Melancholic, combined and unspecified major depressive disorder were associated with increased frequency of migraine with aura, whereas only melancholic major depressive disorder was associated with increased frequency of migraine without aura. Lifetime and unspecified major depressive disorder were associated with severe migraine intensity among subjects with migraine with aura but not migraine without aura, while combined major depressive disorder was associated with higher migraine frequency independently from migraine subtype. CONCLUSION: This study suggests that melancholic but not atypical major depressive disorder is associated with migraine and migraine subtypes. Future studies exploring pathophysiological mechanisms shared between melancholic depression and migraine are warranted.

A pharmacogenetic risk score for the evaluation of major depression severity under treatment with antidepressants.

The severity of symptoms as well as efficacy of antidepressants in major depressive disorder (MDD) is modified by single nucleotide polymorphisms (SNPs) in different genes, which may contribute in an additive or synergistic fashion. We aimed to investigate depression severity in participants with MDD under treatment with antidepressants in relation to the combinatory effect of selected genetic variants combined using a genetic risk score (GRS). The sample included 150 MDD patients on regular AD therapy from the population-based Swiss PsyCoLaus cohort. We investigated 44 SNPs previously associated with antidepressant response by ranking them with regard to their association to the Center for Epidemiologic Studies Short Depression Scale (CES-D) score using random forest. The three top scoring SNPs (rs12248560, rs878567, rs17710780) were subsequently combined into an unweighted GRS, which was included in linear and logistic regression models using the CES-D score, occurrence of a major depressive episode (MDE) during follow-up and regular antidepressant treatment during the 6 months preceding follow-up assessment as outcomes. The GRS was associated with MDE occurrence (p = .02) and ln CES-D score (p = .001). The HTR1A rs878567 variant was associated with ln CES-D after adjustment for demographic and clinical variables [p = .02, lower scores for minor allele (G) carriers]. Additionally, rs12248560 (CYP2C19) CC homozygotes showed a six-fold higher likelihood of regular AD therapy at follow-up compared to minor allele homozygotes [TT; ultrarapid metabolizers (p = .03)]. Our study suggests that the cumulative consideration of pharmacogenetic risk variants more reliably reflects the impact of the genetic background on depression severity than individual SNPs.

Exome Chip Meta-analysis Fine Maps Causal Variants and Elucidates the Genetic Architecture of Rare Coding Variants in Smoking and Alcohol Use.

BACKGROUND: Smoking and alcohol use have been associated with common genetic variants in multiple loci. Rare variants within these loci hold promise in the identification of biological mechanisms in substance use. Exome arrays and genotype imputation can now efficiently genotype rare nonsynonymous and loss of function variants. Such variants are expected to have deleterious functional consequences and to contribute to disease risk. METHODS: We analyzed ∼250,000 rare variants from 16 independent studies genotyped with exome arrays and augmented this dataset with imputed data from the UK Biobank. Associations were tested for five phenotypes: cigarettes per day, pack-years, smoking initiation, age of smoking initiation, and alcoholic drinks per week. We conducted stratified heritability analyses, single-variant tests, and gene-based burden tests of nonsynonymous/loss-of-function coding variants. We performed a novel fine-mapping analysis to winnow the number of putative causal variants within associated loci. RESULTS: Meta-analytic sample sizes ranged from 152,348 to 433,216, depending on the phenotype. Rare coding variation explained 1.1% to 2.2% of phenotypic variance, reflecting 11% to 18% of the total single nucleotide polymorphism heritability of these phenotypes. We identified 171 genome-wide associated loci across all phenotypes. Fine mapping identified putative causal variants with double base-pair resolution at 24 of these loci, and between three and 10 variants for 65 loci. Twenty loci contained rare coding variants in the 95% credible intervals. CONCLUSIONS: Rare coding variation significantly contributes to the heritability of smoking and alcohol use. Fine-mapping genome-wide association study loci identifies specific variants contributing to the biological etiology of substance use behavior.

Genomic history of the Sardinian population.

The population of the Mediterranean island of Sardinia has made important contributions to genome-wide association studies of complex disease traits and, based on ancient DNA studies of mainland Europe, Sardinia is hypothesized to be a unique refuge for early Neolithic ancestry. To provide new insights on the genetic history of this flagship population, we analyzed 3,514 whole-genome sequenced individuals from Sardinia. Sardinian samples show elevated levels of shared ancestry with Basque individuals, especially samples from the more historically isolated regions of Sardinia. Our analysis also uniquely illuminates how levels of genetic similarity with mainland ancient DNA samples varies subtly across the island. Together, our results indicate that within-island substructure and sex-biased processes have substantially impacted the genetic history of Sardinia. These results give new insight into the demography of ancestral Sardinians and help further the understanding of sharing of disease risk alleles between Sardinia and mainland populations.

Psychosocial Stress Over the Lifespan, Psychological Factors, and Cardiometabolic Risk in the Community.

OBJECTIVE: The complex relationship between psychosocial stress over the lifetime, psychological factors, and cardiometabolic risk is still poorly understood. Accordingly, our aims were (1) to independently assess the associations between childhood adversity, life-event stress in remote (earlier than the last 5 years), and recent adulthood and cardiometabolic risk, and (2) to determine the role of psychological factors including personality, coping, and depression in these associations. METHODS: The sample included 2674 adults, aged 35 to 66 years, randomly selected from urban area. Participants underwent a physical examination including the assessment of obesity markers, blood pressure, and blood lipid and glucose levels. Stress during adulthood was determined using the severity scores of 52 stressful life events. Information on adverse childhood experiences and major depressive disorders was collected using semistructured interviews, whereas personality traits and coping mechanisms were evaluated through questionnaires. RESULTS: Both childhood adversity and stress in remote adulthood were associated with elevated body mass index (ß [95% confidence interval {CI}] = 0.249 [0.029 to 0.468]; 0.020 [0.006 to 0.034]), waist circumference (ß [95% CI] = 0.061 [0.024 to 0.099]; 0.08 [0.04 to 0.11]), and the global cardiometabolic risk score (ß [95% CI] = 0.278 [0.017 to 0.540]; 0.017 [0.001 to 0.033]) after adjustment for sociodemographic, lifestyle, and psychological factors. In addition, childhood adversity was associated with low high density lipoprotein levels (ß [95% CI] = -0.021 [-0.042 to 0.000]), as well as increased fat mass and systolic blood pressure levels (ß [95% CI] = 0.506 [0.165 to 0.846]; 0.952 [0.165 to 1.740]) and stress in remote adulthood with apolipoprotein B levels (ß [95% CI] = 0.607 [0.312 to 0.901]). Psychological factors did not account for these associations and were not effect modifiers. CONCLUSIONS: Our data demonstrate that psychosocial stress during childhood and remote adulthood favor adiposity and abnormal lipid metabolism.

Genome-wide gene-environment interaction in depression: A systematic evaluation of candidate genes: The childhood trauma working-group of PGC-MDD.

Gene by environment (GxE) interaction studies have investigated the influence of a number of candidate genes and variants for major depressive disorder (MDD) on the association between childhood trauma and MDD. Most of these studies are hypothesis driven and investigate only a limited number of SNPs in relevant pathways using differing methodological approaches. Here (1) we identified 27 genes and 268 SNPs previously associated with MDD or with GxE interaction in MDD and (2) analyzed their impact on GxE in MDD using a common approach in 3944 subjects of European ancestry from the Psychiatric Genomics Consortium who had completed the Childhood Trauma Questionnaire. (3) We subsequently used the genome-wide SNP data for a genome-wide case-control GxE model and GxE case-only analyses testing for an enrichment of associated SNPs. No genome-wide significant hits and no consistency among the signals of the different analytic approaches could be observed. This is the largest study for systematic GxE interaction analysis in MDD in subjects of European ancestry to date. Most of the known candidate genes/variants could not be supported. Thus, their impact on GxE interaction in MDD may be questionable. Our results underscore the need for larger samples, more extensive assessment of environmental exposures, and greater efforts to investigate new methodological approaches in GxE models for MDD.

Common variants at 2q11.2, 8q21.3, and 11q13.2 are associated with major mood disorders.

Bipolar disorder (BPD) and major depressive disorder (MDD) are primary major mood disorders. Recent studies suggest that they share certain psychopathological features and common risk genes, but unraveling the full genetic architecture underlying the risk of major mood disorders remains an important scientific task. The public genome-wide association study (GWAS) data sets offer the opportunity to examine this topic by utilizing large amounts of combined genetic data, which should ultimately allow a better understanding of the onset and development of these illnesses. Genome-wide meta-analysis was performed by combining two GWAS data sets on BPD and MDD (19,637 cases and 18,083 controls), followed by replication analyses for the loci of interest in independent 12,364 cases and 76,633 controls from additional samples that were not included in the two GWAS data sets. The single-nucleotide polymorphism (SNP) rs10791889 at 11q13.2 was significant in both discovery and replication samples. When combining all samples, this SNP and multiple other SNPs at 2q11.2 (rs717454), 8q21.3 (rs10103191), and 11q13.2 (rs2167457) exhibited genome-wide significant association with major mood disorders. The SNPs in 2q11.2 and 8q21.3 were novel risk SNPs that were not previously reported, and SNPs at 11q13.2 were in high LD with potential BPD risk SNPs implicated in a previous GWAS. The genome-wide significant loci at 2q11.2 and 11q13.2 exhibited strong effects on the mRNA expression of certain nearby genes in cerebellum. In conclusion, we have identified several novel loci associated with major mood disorders, adding further support for shared genetic risk between BPD and MDD. Our study highlights the necessity and importance of mining public data sets to explore risk genes for complex diseases such as mood disorders.

Genetic Association of Major Depression With Atypical Features and Obesity-Related Immunometabolic Dysregulations.

Importance: The association between major depressive disorder (MDD) and obesity may stem from shared immunometabolic mechanisms particularly evident in MDD with atypical features, characterized by increased appetite and/or weight (A/W) during an active episode. Objective: To determine whether subgroups of patients with MDD stratified according to the A/W criterion had a different degree of genetic overlap with obesity-related traits (body mass index [BMI] and levels of C-reactive protein [CRP] and leptin). Design, Setting, and Patients: This multicenter study assembled genome-wide genotypic and phenotypic measures from 14 data sets of the Psychiatric Genomics Consortium. Data sets were drawn from case-control, cohort, and population-based studies, including 26 628 participants with established psychiatric diagnoses and genome-wide genotype data. Data on BMI were available for 15 237 participants. Data were retrieved and analyzed from September 28, 2015, through May 20, 2017. Main Outcomes and Measures: Lifetime DSM-IV MDD was diagnosed using structured diagnostic instruments. Patients with MDD were stratified into subgroups according to change in the DSM-IV A/W symptoms as decreased or increased. Results: Data included 11 837 participants with MDD and 14 791 control individuals, for a total of 26 628 participants (59.1% female and 40.9% male). Among participants with MDD, 5347 (45.2%) were classified in the decreased A/W and 1871 (15.8%) in the increased A/W subgroups. Common genetic variants explained approximately 10% of the heritability in the 2 subgroups. The increased A/W subgroup showed a strong and positive genetic correlation (SE) with BMI (0.53 [0.15]; P = 6.3 × 10-4), whereas the decreased A/W subgroup showed an inverse correlation (-0.28 [0.14]; P = .06). Furthermore, the decreased A/W subgroup had a higher polygenic risk for increased BMI (odds ratio [OR], 1.18; 95% CI, 1.12-1.25; P = 1.6 × 10-10) and levels of CRP (OR, 1.08; 95% CI, 1.02-1.13; P = 7.3 × 10-3) and leptin (OR, 1.09; 95% CI, 1.06-1.12; P = 1.7 × 10-3). Conclusions and Relevance: The phenotypic associations between atypical depressive symptoms and obesity-related traits may arise from shared pathophysiologic mechanisms in patients with MDD. Development of treatments effectively targeting immunometabolic dysregulations may benefit patients with depression and obesity, both syndromes with important disability.