Major Depressive Disorder Polygenic Scores Research Articles

Descriptives and genetic correlates of eating disorder diagnostic transitions and presumed remission in the Danish registry.

Eating disorders (EDs) are serious psychiatric disorders with an estimated 3.3 million healthy life-years lost worldwide yearly. Understanding the course of illness, diagnostic transitions and remission, and their associated genetic correlates could inform both ED etiology and treatment. The authors investigated occurrences of ED transitions and presumed remission and their genetic correlates as captured by polygenic scores (PGSs) in a large Danish register-based cohort. The sample was compromised of 10,565 individuals with a diagnosis of anorexia nervosa (AN), bulimia nervosa (BN), or eating disorder not otherwise specified (EDNOS) with at least two registered hospital contacts between 1995 and 2018. Based on medical records, occurrence of diagnostic transitions and periods of presumed remission were identified. Associations between 422 PGS and diagnostic transitions and presumed remission were evaluated using Cox proportional hazard models. A minority of ED cases (14.1%-23.1%) experienced a diagnostic transition. Presumed remission ranged between 86.9%-89.8%. Higher (one SD increase) PGS for major depressive disorder and multisite chronic pain were positively associated with transitioning from AN to either BN or EDNOS. Higher PGS on a measure of body fat percentage and financial difficulties were positively associated with presumed remission from AN. Higher PGS for mood swings was positively associated with presumed remission from EDNOS whereas higher PGS for health rating showed the opposite. The authors found that most ED patients did not experience diagnostic transitions but were more likely to experience a period of presumed remission. Both diagnostic transitions and presumed remission have significant polygenic component.

Polygenic liabilities and treatment trajectories in early-onset depression: a Danish register-based study.

The clinical course of major depressive disorder (MDD) is heterogeneous, and early-onset MDD often has a more severe and complex clinical course. Our goal was to determine whether polygenic scores (PGSs) for psychiatric disorders are associated with treatment trajectories in early-onset MDD treated in secondary care. Data were drawn from the iPSYCH2015 sample, which includes all individuals born in Denmark between 1981 and 2008 who were treated in secondary care for depression between 1995 and 2015. We selected unrelated individuals of European ancestry with an MDD diagnosis between ages 10-25 (N = 10577). Seven-year trajectories of hospital contacts for depression were modeled using Latent Class Growth Analysis. Associations between PGS for MDD, bipolar disorder, schizophrenia, ADHD, and anorexia and trajectories of MDD contacts were modeled using multinomial logistic regressions. We identified four trajectory patterns: brief contact (65%), prolonged initial contact (20%), later re-entry (8%), and persistent contact (7%). Relative to the brief contact trajectory, higher PGS for ADHD was associated with a decreased odds of membership in the prolonged initial contact (odds ratio = 1.06, 95% confidence interval = 1.01-1.11) and persistent contact (1.12, 1.03-1.21) trajectories, while PGS-AN was associated with increased odds of membership in the persistent contact trajectory (1.12, 1.03-1.21). We found significant associations between polygenic liabilities for psychiatric disorders and treatment trajectories in patients with secondary-treated early-onset MDD. These findings help elucidate the relationship between a patient's genetics and their clinical course; however, the effect sizes are small and therefore unlikely to have predictive value in clinical settings.

Descriptives and genetic correlates of eating disorder diagnostic transitions and presumed remission in the Danish registry.

Eating disorders (EDs) are serious psychiatric disorders with an estimated 3.3 million healthy life-years lost worldwide yearly. Understanding the course of illness, diagnostic transitions and remission, and their associated genetic correlates could inform both ED etiology and treatment. The authors investigated occurrences of ED transitions and presumed remission and their genetic correlates as captured by polygenic scores (PGSs) in a large Danish register-based cohort. The sample compromised of 10,565 individuals with a diagnosis of anorexia nervosa (AN), bulimia nervosa (BN), or eating disorder not otherwise specified (EDNOS) with at least two registered hospital contacts between 1995 and 2018. Based on medical records, occurrence of diagnostic transitions and periods of presumed remission were identified. Associations between 422 PGS and diagnostic transitions and presumed remission were evaluated using Cox proportional hazard models. A minority of ED cases (14.1%-23.1%) experienced a diagnostic transition. Presumed remission ranged between 86.9%-89.8%. Higher (one SD increase) PGS for major depressive disorder and multisite chronic pain were positively associated with transitioning from AN to either BN or EDNOS. Higher PGS on a measure of body fat percentage and financial difficulties were positively associated with presumed remission from AN. Higher PGS for mood swings was positively associated with presumed remission from EDNOS whereas higher PGS for health rating showed the opposite. The authors found that most ED patients did not experience diagnostic transitions but were more likely to experience a period of presumed remission. Both diagnostic transitions and presumed remission have significant polygenic component.

Application of polygenic scores to a deeply phenotyped sample enriched for substance use disorders reveals extensive pleiotropy with psychiatric and somatic traits

Co-occurring psychiatric, medical, and substance use disorders (SUDs) are common, but the complex pathways leading to such comorbidities are poorly understood. A greater understanding of genetic influences on this phenomenon could inform precision medicine efforts. We used the Yale-Penn dataset, a cross-sectional sample enriched for individuals with SUDs, to examine pleiotropic effects of genetic liability for psychiatric and somatic traits. Participants completed an in-depth interview that provides information on demographics, environment, medical illnesses, and psychiatric and SUDs. Polygenic scores (PGS) for psychiatric disorders and somatic traits were calculated in European-ancestry (EUR; n = 5691) participants and, when discovery datasets were available, for African-ancestry (AFR; n = 4918) participants. Phenome-wide association studies (PheWAS) were then conducted. In AFR participants, the only PGS with significant associations was bipolar disorder (BD), all of which were with substance use phenotypes. In EUR participants, PGS for major depressive disorder (MDD), generalized anxiety disorder (GAD), post-traumatic stress disorder (PTSD), schizophrenia (SCZ), body mass index (BMI), coronary artery disease (CAD), and type 2 diabetes (T2D) all showed significant associations, the majority of which were with phenotypes in the substance use categories. For instance, PGSMDD was associated with over 200 phenotypes, 15 of which were depression-related (e.g., depression criterion count), 55 of which were other psychiatric phenotypes, and 126 of which were substance use phenotypes; and PGSBMI was associated with 138 phenotypes, 105 of which were substance related. Genetic liability for psychiatric and somatic traits is associated with numerous phenotypes across multiple categories, indicative of the broad genetic liability of these traits.

Common polygenic variation in the early medication change (EMC) cohort affects disorder risk, but not the antidepressant treatment response

BackgroundGiven the great interest in identifying reliable predictors of the response to antidepressant drugs, the present study investigated whether polygenic scores (PGS) for Major Depressive Disorder (MDD) and antidepressant treatment response (ADR) were related to the complex trait of antidepressant response in the Early Medication Change (EMC) cohort. MethodsIn this secondary analysis of the EMC trial (N = 889), 481 MDD patients were included and compared to controls from a population-based cohort. Patients were treated over eight weeks within a pre-defined treatment-algorithm. We investigated patients' genetic variation associated with MDD and ADR, using PGS and examined the association of PGS with treatment outcomes (early improvement, response, remission). Additionally, the influence of two cytochrome P450 drug-metabolizing enzymes (CYP2C19, CYP2D6) was determined. ResultsPGS for MDD was significantly associated with disorder status (NkR2 = 2.48 %, p < 1*10−12), with higher genetic burden in EMC patients compared to controls. The PGS for ADR did not explain remission status. The PGS for MDD and ADR were also not associated with treatment outcomes. In addition, there were no effects of common CYP450 gene variants on ADR. LimitationsThe study was limited by variability in the outcome parameters due to differences in treatment and insufficient sample size in the used ADR genome-wide association study (GWAS). ConclusionsThe present study confirms a polygenic contribution to MDD burden in the EMC patients. Larger GWAS with homogeneity in antidepressant treatments are needed to explore the genetic variation associated with ADR and realize the potential of PGS to contribute to specific response subtypes.

Maternal depression and the polygenic p factor: A family perspective on direct and indirect effects

Within-family studies typically assess indirect genetic effects of parents on children, however social support theory points to a critical role of partners and children on women's depression. To address this research gap and account for the high heterogeneity of depression, we calculated a general psychiatric factor using eleven major psychiatric polygenic scores (polygenic p), in up to 25,000 parent-offspring trios from the Norwegian Mother, Father and Child Cohort Study (MoBa). Multilevel modeling of trio polygenic p was used to distinguish direct and indirect genetic effects on mothers depression during pregnancy (gestational age 17 and 30 weeks), infancy (6 months, 18 months) and early childhood (3 years, 5 years, and 8 years). We found mothers polygenic p predicts their depression symptoms (b = 0.092; 95 % CI [0.087,0.098]), outperforming prediction using a single major depressive disorder polygenic score (b = 0.070, 95 % CI [0.066,0.075]). Jointly modeling trio polygenic p revealed indirect genetic effects of fathers (b = 0.022, 95 % CI [0.014,0.030]) and children (b = 0.021, 95 % CI [0.010,0.037]) on mothers' depression. Our results support the generalizability of polygenic effects across mental health and highlight the role of close family members on women's depression.

The antecedents and outcomes of persistent and remitting adolescent depressive symptom trajectories: a longitudinal, population-based English study

Depression often first emerges in adolescence and, for many, is a lifelong disorder. The long-term clinical course of depression is highly variable. We aimed to examine the adult outcomes of adolescent-onset trajectories of clinically significant depressive symptoms and to identify factors differentiating trajectories that persist and desist in adulthood. We included participants from the English population-based Avon Longitudinal Study of Parents and Children with data on depressive symptoms. Self-reported depression symptoms were assessed on ten occasions when participants were age 10·5-25 years using the short Mood and Feelings Questionnaire, and major depressive disorder episodes were assessed at age 13·0 years, 15·0 years, 17·5 years, and 25·0 years. We characterised trajectories of depression symptoms using latent class growth analysis, for which we required depression data at least once from each of three key phases: ages 10·5-13·5 years; 16·5-18·5 years; and 21-25 years. We examined adult outcomes by assessing lifetime suicidal self-harm and functional impairment at age 24·0 years, and employment, education, and the self-reported Strengths and Difficulties Questionnaire at age 25·0 years. We studied 4234 participants: 2651 (63%) female, 1582 (37%) male, and one individual with missing sex data. The mean age was 10·6 years (SD 0·2) at baseline and 25·8 years (SD 0·5) at the final timepoint. Data on ethnicity were not available in our data set. We identified four depression trajectory classes: adolescent-persistent depression with onset early in adolescence (7%, n≈279), adolescent-limited depression with onset later in adolescence and remittance by adult life (14%, n≈592), adult-increasing depression (25%, n≈1056), and stable-low levels of depression (54%, n≈2307). The adolescent-persistent class was associated with poor adult outcomes for functional impairment (62%), suicidal self-harm (27%), mental health difficulties (25%), and not being in education, employment, or training (16%). Adolescent-limited depression was associated with transient adolescent stress, but by early adulthood functional impairment and mental health difficulties were similar to the stable-low group. Major depressive disorder polygenic score (odds ratio [OR] 1·36, 95% CI 1·04-1·79), adolescent educational attainment (OR 0·47, 0·30-0·74), and any early childhood adversity (OR 2·60, 1·42-4·78), that persisted into adulthood (OR 1·60, 1·38-1·87) distinguished the adolescent-persistent and adolescent-limited groups. The future course of adolescent depression can be differentiated by age at onset during adolescence, adolescent academic attainment, early and persistent adversity, and genetic loading. A detailed social and educational history could be helpful in making clinical decisions about the intensity of interventions for young people with clinically elevated depressive symptoms who seek help. Medical Research Council, Wolfson Centre for Young People's Mental Health, Wolfson Foundation.

Phenotypic and genetic markers of psychopathology in a population-based sample of older adults

Although psychiatric phenotypes are hypothesized to organize into a two-factor internalizing–externalizing structure, few studies have evaluated the structure of psychopathology in older adults, nor explored whether genome-wide polygenic scores (PGSs) are associated with psychopathology in a domain-specific manner. We used data from 6003 individuals of European ancestry from the Health and Retirement Study, a large population-based sample of older adults in the United States. Confirmatory factor analyses were applied to validated measures of psychopathology and PGSs were derived from well-powered genome-wide association studies (GWAS). Genomic SEM was implemented to construct latent PGSs for internalizing, externalizing, and general psychopathology. Phenotypically, the data were best characterized by a single general factor of psychopathology, a factor structure that was replicated across genders and age groups. Although externalizing PGSs (cannabis use, antisocial behavior, alcohol dependence, attention deficit hyperactivity disorder) were not associated with any phenotypes, PGSs for major depressive disorder, neuroticism, and anxiety disorders were associated with both internalizing and externalizing phenotypes. Moreover, the variance explained in the general factor of psychopathology increased by twofold (from 1% to 2%) using the latent internalizing or latent one-factor PGSs, derived using weights from Genomic Structural Equation Modeling (SEM), compared with any of the individual PGSs. Collectively, results suggest that genetic risk factors for and phenotypic markers of psychiatric disorders are transdiagnostic in older adults of European ancestry. Alternative explanations are discussed, including methodological limitations of GWAS and phenotypic measurement of psychiatric outcome in large-scale population-based studies.

Genetic risk for major depressive disorder and loneliness in sex-specific associations with coronary artery disease

Major depressive disorder (MDD) and loneliness are phenotypically and genetically correlated with coronary artery disease (CAD), but whether these associations are explained by pleiotropic genetic variants or shared comorbidities is unclear. To tease apart these scenarios, we first assessed the medical morbidity pattern associated with genetic risk factors for MDD and loneliness by conducting a phenome-wide association study in 18,385 European-ancestry individuals in the Vanderbilt University Medical Center biobank, BioVU. Polygenic scores for MDD and loneliness were developed for each person using previously published meta-GWAS summary statistics, and were tested for association with 882 clinical diagnoses ascertained via billing codes in electronic health records. We discovered strong associations with heart disease diagnoses, and next embarked on targeted analyses of CAD in 3893 cases and 4197 controls. We found odds ratios of 1.11 (95% CI, 1.04–1.18; P 8.43 × 10−4) and 1.13 (95% CI, 1.07–1.20; P 4.51 × 10−6) per 1-SD increase in the polygenic scores for MDD and loneliness, respectively. Results were similar in patients without psychiatric symptoms, and the increased risk persisted in females even after adjusting for multiple conventional risk factors and a polygenic score for CAD. In a final sensitivity analysis, we statistically adjusted for the genetic correlation between MDD and loneliness and re-computed polygenic scores. The polygenic score unique to loneliness remained associated with CAD (OR 1.09, 95% CI 1.03–1.15; P 0.002), while the polygenic score unique to MDD did not (OR 1.00, 95% CI 0.95–1.06; P 0.97). Our replication sample was the Atherosclerosis Risk in Communities (ARIC) cohort of 7197 European-ancestry participants (1598 incident CAD cases). In ARIC, polygenic scores for MDD and loneliness were associated with hazard ratios of 1.07 (95% CI, 0.99–1.14; P = 0.07) and 1.07 (1.01–1.15; P = 0.03), respectively, and we replicated findings from the BioVU sensitivity analyses. We conclude that genetic risk factors for MDD and loneliness act pleiotropically to increase CAD risk in females.

Predicting loneliness with polygenic scores of social, psychological and psychiatric traits

Loneliness is a heritable trait that accompanies multiple disorders. The association between loneliness and mental health indices may partly be due to inherited biological factors. We constructed polygenic scores for 27 traits related to behavior, cognition and mental health and tested their prediction for self-reported loneliness in a population-based sample of 8798 Dutch individuals. Polygenic scores for major depressive disorder (MDD), schizophrenia and bipolar disorder were significantly associated with loneliness. Of the Big Five personality dimensions, polygenic scores for neuroticism and conscientiousness also significantly predicted loneliness, as did the polygenic scores for subjective well-being, tiredness and self-rated health. When including all polygenic scores simultaneously into one model, only 2 major depression polygenic scores remained as significant predictors of loneliness. When controlling only for these 2 MDD polygenic scores, only neuroticism and schizophrenia remain significant. The total variation explained by all polygenic scores collectively was 1.7%. The association between the propensity to feel lonely and the susceptibility to psychiatric disorders thus pointed to a shared genetic etiology. The predictive power of polygenic scores will increase as the power of the genome-wide association studies on which they are based increases and may lead to clinically useful polygenic scores that can inform on the genetic predisposition to loneliness and mental health.

Genome-wide meta-analyses of stratified depression in Generation Scotland and UK Biobank

Few replicable genetic associations for Major Depressive Disorder (MDD) have been identified. Recent studies of MDD have identified common risk variants by using a broader phenotype definition in very large samples, or by reducing phenotypic and ancestral heterogeneity. We sought to ascertain whether it is more informative to maximize the sample size using data from all available cases and controls, or to use a sex or recurrent stratified subset of affected individuals. To test this, we compared heritability estimates, genetic correlation with other traits, variance explained by MDD polygenic score, and variants identified by genome-wide meta-analysis for broad and narrow MDD classifications in two large British cohorts - Generation Scotland and UK Biobank. Genome-wide meta-analysis of MDD in males yielded one genome-wide significant locus on 3p22.3, with three genes in this region (CRTAP, GLB1, and TMPPE) demonstrating a significant association in gene-based tests. Meta-analyzed MDD, recurrent MDD and female MDD yielded equivalent heritability estimates, showed no detectable difference in association with polygenic scores, and were each genetically correlated with six health-correlated traits (neuroticism, depressive symptoms, subjective well-being, MDD, a cross-disorder phenotype and Bipolar Disorder). Whilst stratified GWAS analysis revealed a genome-wide significant locus for male MDD, the lack of independent replication, and the consistent pattern of results in other MDD classifications suggests that phenotypic stratification using recurrence or sex in currently available sample sizes is currently weakly justified. Based upon existing studies and our findings, the strategy of maximizing sample sizes is likely to provide the greater gain.

Polygenic Score for Cardiometabolic and Psychiatric Phenotypes Predict Response to Treatment with Selective Serotonin Reuptake Inhibitors in Major Depressive Disorder

Selective serotonin reuptake inhibitors (SSRIs) are the first line antidepressants to treat major depressive disorder (MDD). Among other factors, the co-morbidity of depression with other psychiatric and cardiometabolic disorders may negatively influence antidepressants treatment response. Moreover, response to antidepressants is considered as a complex trait with substantial contribution from a large number of common genetic variants of small effect. Hence, polygenic scores (PGSs) could be a useful tool to estimate the overall effect of genetically driven factors on the treatment outcome.Here, we evaluated whether PGSs derived from 25 recognized comorbid cardiometabolic and psychiatric disorders, personality traits and educational parameters predict treatment response to SSRIs in MDD. In order to create the PGSs, we used genome-wide genotype data obtained from 865 MDD patients who received SSRIs treatment and GWAS summary statistics for the 25 disorders and phenotypes. The PGSs were calculated within a P-value threshold (PT) as the sum of the single nucleotide polymorphisms effect allele multiplied by its corresponding GWAS effect size (β- coefficient or log (OR)) weighted by the sum of the GWAS effect sizes.Clinical, demographic and SSRIs treatment response data were collected from 865 MDD patients by the ISPC. Baseline and follow-up SSRIs treatment response were measured using the 17-item Hamilton Rating Scale for Depression (HRSD-17). After 4 weeks of treatment, patients with at least 50% reduction in HRSD-17 from the baseline score were classified as responders and patients with a score of less than or equal to seven were considered as remitters. Once the PGSs were calculated, binary logistic regression analyses were performed between the dependent variables (response or remission to SSRIs) and the PGSs in each of the 25 disorders and phenotypes adjusted for the covariates (age, sex and study sites). Finally, we reported the best-predictive PGS for each disorder and phenotype that predicts the treatment outcome with the smallest p-value. A statistically significant association was determined at P < 0.05.We found that the PGSs for MDD, depressive symptoms, type 2 diabetes, body mass index, plasma levels of fasting proinsulin or fasting glucose, openness personality trait, subjective wellbeing and educational attainment significantly (P < 0.05) predicted both response and remission to SSRIs treatment in MDD patients. Additionally, the PGS for coronary artery disease, plasma level of total cholesterol, agreeableness and conscientiousness personality traits showed a significant association with remission, but not with response. Our findings suggest that the influence of cardiometabolic and psychiatric co-morbidities on antidepressants treatment response could be at least partly determined at a genetic level.

The effects of the interplay of genetics and early environmental risk on the course of internalizing symptoms from late childhood through adolescence.

Internalizing symptoms during adolescence and beyond is a major public health concern, particularly because severe symptoms can lead to the diagnosis of a number of serious psychiatric conditions. This study utilizes a unique sample with a complex statistical method in order to explore Gene × Environment interactions found in internalizing symptoms during adolescence. Data for this study were drawn from a longitudinal prevention intervention study (n = 798) of Baltimore city school children. Internalizing symptom data were collected using self-report and blood or saliva samples genotyped using Affymetrix 6.0 microarrays. A major depression polygenic score was created for each individual using information from the major depressive disorder Psychiatric Genetics Consortium and used as a predictor in a latent trait-state-occasion model. The major depressive disorder polygenic score was a significant predictor of the stable latent trait variable, which captures time-independent phenotypic variability. In addition, an early childhood stressor of death or divorce was a significant predictor of occasion-specific variables. A Gene × Environment interaction was not a significant predictor of the latent trait or occasion variables. These findings support the importance of genetics on the stable latent trait portion of internalizing symptoms across adolescence.