Depression Polygenic Risk Scores Research Articles

Polygenic Risk and Episode Polarity Among Individuals With Bipolar Disorder.

The authors investigated associations between polygenic liabilities for bipolar disorder, major depression, and schizophrenia and episode polarity among individuals with bipolar disorder. The sample consisted of 2,705 individuals diagnosed with bipolar disorder at Danish psychiatric hospitals between January 1995 and March 2017. DNA was obtained from dried blood spots collected at birth as part of routine screening. Polygenic risk scores (PRSs) for bipolar disorder, major depression, and schizophrenia were generated using a meta-PRS method combining internally and externally trained components. Associations between PRS and polarity at first episode, polarity at any episode, and number of episodes with a given polarity were evaluated for each disorder-specific PRS using logistic and negative binominal regressions adjusted for the other two PRSs, age, sex, genotype platform, and five ancestral principal components. PRS for bipolar disorder was positively associated with any manic episodes (odds ratio=1.23, 95% CI=1.09-1.38). PRS for depression was positively associated with any depressive (odds ratio=1.11, 95% CI=1.01-1.23) and mixed (odds ratio=1.15, 95% CI=1.03-1.28) episodes and negatively associated with any manic episodes (odds ratio=0.76, 95% CI=0.69-0.84). PRS for schizophrenia was positively associated with any manic episodes (odds ratio=1.13, 95% CI=1.01-1.27), but only when psychotic symptoms were present (odds ratio for psychotic mania: 1.27, 95% CI=1.05-1.54; odds ratio for nonpsychotic mania: 1.06, 95% CI=0.93-1.20). These patterns were similar for first-episode polarity and for the number of episodes within each pole. PRSs for bipolar disorder, major depression, and schizophrenia are associated with episode polarity and psychotic symptoms in a congruent manner among individuals with bipolar disorder.

Polygenic Risk and Social Support in Predicting Depression Under Stress.

Despite substantial progress in identifying genomic variation associated with major depression, the mechanisms by which genomic and environmental factors jointly influence depression risk remain unclear. Genomically conferred sensitivity to the social environment may be one mechanism linking genomic variation and depressive symptoms. The authors assessed whether social support affects the likelihood of depression development differently across the spectrum of genomic risk in two samples that experienced substantial life stress: 1,011 first-year training physicians (interns) in the Intern Health Study (IHS) and 435 recently widowed Health and Retirement Study (HRS) participants. Participants' depressive symptoms and social support were assessed with questionnaires that were administered before and after the life stressor. Polygenic risk scores (PRSs) for major depressive disorder were calculated for both samples. Depressive symptom scores increased by 126% after the start of internship in the IHS sample and by 34% after widowing in the HRS sample. There was an interaction between depression PRS and change in social support in the prediction of depressive symptoms in both the IHS sample (incidence rate ratio [IRR]=0.96, 95% CI=0.93, 0.98) and the HRS sample (IRR=0.78, 95% CI=0.66, 0.92), with higher depression PRS associated with greater sensitivity to changes in social support. Johnson-Neyman intervals indicated a crossover effect, with losses and gains in social support moderating the effect of PRS on depressive symptoms. (Johnson-Neyman interval in the IHS sample, -0.02, 0.71; in the HRS sample, -0.49, 1.92). The study findings suggest that individuals with high genomic risk for developing increased depressive symptoms under adverse social conditions also benefit more from nurturing social environments.

Polygenic Contributions to Suicidal Thoughts and Behaviors in a Sample Ascertained for Alcohol Use Disorders

Introduction: Suicidal thoughts and behaviors have partially distinct genetic etiologies. Methods: We used PRS-CS to create polygenic risk scores (PRSs) from GWAS of non-suicidal self-injury, broad-sense self-harm ideation, nonfatal suicide attempt, death by suicide, and depression. Using mixed-effect models, we estimated whether these PRSs were associated with a range of suicidal thoughts and behaviors in the Collaborative Study on the Genetics of Alcoholism (N = 7,526). Results: All PRSs were significantly associated with suicidal ideation and suicide attempt (betas = 0.08–0.44, false discovery rate [FDR] <0.023). All PRSs except non-suicidal self-injury PRS were associated with active suicidal ideation (betas = 0.14–0.22, FDR <0.003). Several associations remained significant in models where all significant PRSs were included as simultaneous predictors, and when all PRSs predicted suicide attempt, the PRS together explained 6.2% of the variance in suicide attempt. Significant associations were also observed between some PRSs and persistent suicidal ideation, non-suicidal self-injury, compounded suicide attempt, and desire to die. Conclusion: Our findings suggest that PRS for depression does not explain the entirety of the variance in suicidal thoughts and behaviors, with PRS specifically for suicidal thoughts and behaviors making additional and sometimes unique contributions.

Maternal genetic risk for depression and child human capital

We here address the causal relationship between the maternal genetic risk for depression and child human capital using UK birth-cohort data. We find that an increase of one standard deviation (SD) in the maternal polygenic risk score for depression reduces their children's cognitive and non-cognitive skill scores by 5 to 7% of a SD throughout adolescence. Our results are robust to a battery of sensitivity tests addressing, among others, concerns about pleiotropy and dynastic effects. Our Gelbach decomposition analysis suggests that the strongest mediator is genetic nurture (through maternal depression itself), with genetic inheritance playing only a marginal role.

Abstract 10480: Depression and Coronary Artery Disease Share Genetic Risk Factors Enriched in Inflammation and Cardiomyopathy-Associated Pathways

Coronary artery disease (CAD) and depression are highly prevalent (7% and 8% respectively), comorbid diseases. Approximately 40% of adults who are initially diagnosed with either CAD or depression will also develop the other condition. We have observed that the polygenic risk scores for depression were significantly associated with CAD in a large hospital population even in patients without any psychiatric diagnoses and after adjusting for known CAD risk factors. This suggests that some proportion of genes that increase susceptibility to depression act pleiotropically to increase CAD risk. To identify the genes increasing risk for both CAD and depression we performed a cross-tissue S-MultiXcan analysis on the summary statistics for CAD (CARDIoGRAMplusC4D Consortium) and depression (PGC and UK Biobank). We identified 185 genes associated with both depression and CAD, representing a three-fold enrichment of shared associations ( P value &lt;1.718e-43). Next we performed a pathway enrichment analysis and observed that these genes were enriched for inflammation and cardiomyopathy-associated pathways. We then used electronic health records at Vanderbilt, to test the prevalence of cardiomyopathy in patients with comorbid depression and CAD. We found that the depression-CAD cohort had a significantly increased prevalence of cardiomyopathy diagnoses ( OR = 1.27, 95%C.I. = 1.17-1.30, P value = 3.69 e-9) compared to patients with CAD after we controlled for Type 2 Diabetes, hypertension, smoking and median BMI. We replicated these findings across two external cohorts - All of Us and Massachusetts General Hospital health records. Using a Genomic structural equation model (GSEM), we observed that inflammatory markers white blood cell (WBC) count and platelet count explained 1% and 16% of the SNP-based genetic correlation between depression and CAD, respectively in a single factor. The mediation paths models using the summary statistics data show that WBC and platelets mediate approximately 1% and 13% of comorbidity and together explain 14.4% of the total genetic correlation between depression-CAD. These results highlight cardiomyopathy and inflammation as an important biological link in the comorbid manifestation of CAD and depression.

Polygenic heterogeneity in antidepressant treatment and placebo response

The genetic architecture of antidepressant response is poorly understood. Polygenic risk scores (PRS), exploration of placebo response and the use of sub-scales might provide insights. Here, we investigate the association between PRSs for relevant complex traits and response to vortioxetine treatment and placebo using clinical scales, including sub-scales and self-reported assessments. We collected a clinical test sample of Major Depressive Disorder (MDD) patients treated with vortioxetine (N = 907) or placebo (N = 455) from seven randomized, double-blind, clinical trials. In parallel, we obtained data from an observational web-based study of vortioxetine-treated patients (N = 642) with self-reported response. PRSs for antidepressant response, psychiatric disorders, and symptom traits were derived using summary statistics from well-powered genome-wide association studies (GWAS). Association tests were performed between the PRSs and treatment response in each of the two test samples and empirical p-values were evaluated. In the clinical test sample, no PRSs were significantly associated with response to vortioxetine treatment or placebo following Bonferroni correction. However, clinically assessed treatment response PRS was nominally associated with vortioxetine treatment and placebo response given by several secondary outcome scales (improvement on HAM-A, HAM-A Psychic Anxiety sub-scale, CPFQ & PDQ), (P ≤ 0.026). Further, higher subjective well-being PRS (P ≤ 0.033) and lower depression PRS (P = 0.01) were nominally associated with higher placebo response. In the self-reported test sample, higher schizophrenia PRS was significantly associated with poorer self-reported response (P = 0.0001). The identified PRSs explain a low proportion of the variance (1.2–5.3%) in placebo and treatment response. Although the results were limited, we believe that PRS associations bear unredeemed potential as a predictor for treatment response, as more well-powered and phenotypically similar GWAS bases become available.

Risk factor profiles for depression following childbirth or a chronic disease diagnosis: case-control study.

Progress towards understanding the aetiology of major depression is compromised by its clinical heterogeneity. The variety of contexts underlying the development of a major depressive episode may contribute to such heterogeneity. To compare risk factor profiles for three subgroups of major depression according to episode context. Using self-report questionnaires and administrative records from the UK Biobank, we characterised three contextual subgroups of major depression: postpartum depression (3581 cases), depression following diagnosis of a chronic disease (409 cases) and a more typical (named heterogeneous) major depression phenotype excluding the two other contexts (34 699 cases). Controls with the same exposure were also defined. We tested each subgroup for association with the polygenic risk scores (PRS) for major depression and with other risk factors previously associated with major depression (bipolar disorder PRS, neuroticism, reported trauma in childhood and adulthood, socioeconomic status, family history of depression, education). Major depression PRS was associated with all subgroups, but postpartum depression cases had higher PRS than heterogeneous major depression cases (OR = 1.06, 95% CI 1.02-1.10). Relative to heterogeneous depression, postpartum depression was more weakly associated with adulthood trauma and neuroticism. Depression following diagnosis of a chronic disease had weaker association with neuroticism and reported trauma in adulthood and childhood relative to heterogeneous depression. The observed differences in risk factor profiles according to the context of a major depressive episode help provide insight into the heterogeneity of depression. Future studies dissecting such heterogeneity could help reveal more refined aetiological insights.

Associations of polygenic risks, depression, and obesity-related traits in Taiwan Biobank

BackgroundThe comorbidity of obesity and major depressive disorder (MDD) may be attributable to a bidirectional relationship and shared genetic influence. We aimed to examine the polygenic associations between obesity and MDD and to characterize their corresponding impacts on the obesity mechanism. MethodsGenome-wide genotyping was available in 106,604 unrelated individuals from Taiwan Biobank. Polygenic risk score (PRS) for body mass index (BMI) and MDD was derived to evaluate their effects on obesity-related traits. Stratified analyses were performed for the modified effect of depression on the polygenic associations. ResultsThe MDD PRS was positively associated with waistline (beta in per SD increase in PRS = 0.12), hipline (beta = 0.08), waist-hip ratio (WHR) (beta = 0.05), body fat rate (beta = 0.08), BMI (beta = 0.05), overweight (OR = 1.02 for BMI ≥ 25), and obesity (OR = 1.05 for BMI ≥ 30). For the synergism between depression and BMI PRS, the presence of active depression symptoms defined by the PHQ-4 (p for interaction < 0.05 for waistline, WHR, and BMI) was more salient than lifetime MDD. LimitationsLimitations include recall bias for MDD due to a retrospective self-reporting questionnaire, a low response rate of the PHQ-4 for evaluating active psychological symptoms, and limited generalizability to non-Taiwanese ancestries. ConclusionsThe shared genetic etiology of obesity and depression was demonstrated. The amplified effect of BMI polygenic effect on obesity for individuals with active depressive symptoms was also characterized. The study may be helpful for designing public health interventions to reduce the disease burden caused by obesity and depression.

Polygenic risk score and peer victimisation independently predict depressive symptoms in adolescence: results from the Quebec Longitudinal Study of Children Development.

Peer victimisation has been associated with depressive symptoms during adolescence, however not all peer victimised adolescents will exhibit such symptoms. This study tested whether having a genetic predisposition to developing depression increased the risk of experiencing depressive symptoms in peer victimised youth. To date, no study has explored such gene-environment interaction using a polygenic risk score for depression (PRS-depression) in the context of peer victimisation and depressive symptoms in adolescence. The sample included 748 participants born in 1997/98 from the Quebec Longitudinal Study of Child Development with genotype data and prospectively collected information on peer victimisation (12-13 years) obtained from both self- and teacher-reports, as well as self-reported depressive symptoms (15-17 years). The PRS-depression was based on the genome-wide association meta-analysis of broad depression by Howard etal. (2019). Self- and teacher-reported peer victimisation in early adolescence were both associated with depressive symptoms in adolescence (β = 0.34, p < .001; β = 0.14, p = .001 respectively), and this association remained significant when accounting for PRS-depression (β = 0.33, p < .001; β = 0.13, p = .002 respectively). PRS-depression was independently associated with depressive symptoms, but there was no significant PRS-depression by peer victimisation interaction (self-reported and teacher-reported). PRS-depression was correlated with self-reported, but not teacher-reported, peer victimisation. Our findings suggested that a partial measure of an individual's genetic predisposition to depression, as measured by PRS-depression, and being exposed to peer victimisation (self- and teacher-reported) were independently associated with depressive symptoms in adolescence. Furthermore, PRS-depression did not exacerbate the risk of depressive symptoms among adolescents who had been peer victimised. Lastly, we found evidence of a gene-environment correlation between PRS-depression and self-reported peer victimisation. Future studies are needed to replicate this finding and to further understand the role of genetic predispositions in experiencing depressive symptoms following peer victimisation.

Telomere Length Associations With Clinical Diagnosis, Age, and Polygenic Risk Scores for Anxiety Disorder, Depression, and Bipolar Disorder

BackgroundAccelerated biological aging might contribute to the lower life expectancy of individuals with mental disorders. The aim of this study was to characterize telomere length, a biological hallmark of aging, in individuals with mental disorders. MethodsThe UK Biobank is a multicenter community-based observational study that recruited >500,000 middle-aged and older adults. Average leukocyte telomere length (telomere repeat copy number/single-copy gene ratio) was measured using quantitative polymerase chain reaction. Polygenic risk scores (PRSs) were calculated for individuals of European ancestry. We estimated differences in telomere length between individuals with anxiety disorder, depression, or bipolar disorder and people without mental disorders and examined associations with psychotropic medication use, age, and PRSs for these 3 disorders. ResultsThe analyses included up to 308,725 participants. Individuals with depression had shorter telomeres than people without mental disorders (β = −0.011, 95% CI, −0.019 to −0.004, Bonferroni-corrected p = .027). Associations between bipolar disorder and telomere length differed by lithium use. There was limited evidence that individuals with an anxiety disorder had shorter telomeres. There was no evidence that associations between age and telomere length differed between individuals with and without these disorders. PRSs for depression, but not anxiety disorder or bipolar disorder, were associated with shorter telomeres (β = −0.006, 95% CI, −0.010 to −0.003, Bonferroni-corrected p = .001). ConclusionsDifferences in telomere length were observed primarily for individuals with depression or bipolar disorder and in individuals with a higher PRS for depression. There was no evidence that the association between age and telomere length differed between individuals with and without an anxiety disorder, depression, or bipolar disorder.

The interaction of early life factors and depression-associated loci affecting the age at onset of the depression

Multiple previous studies explored the associations between early life factors and the age at onset of the depression. However, they only focused on the influence of environmental or genetic factors, without considering the interactions between them. Based on previous genome-wide association study (GWAS) data, we first calculated polygenic risk score (PRS) for depression. Regression analyses were conducted to assess the interacting effects of depression PRS and 5 early life factors, including felt hated by family member (N = 40,112), physically abused by family (N = 40,464), felt loved (N = 35633), and sexually molested (N = 41,595) in childhood and maternal smoking during pregnancy (N = 38,309), on the age at onset of the depression. Genome-wide environment interaction studies (GWEIS) were then performed to identify the genes interacting with early life factors for the age at onset of the depression. In regression analyses, we observed significant interacting effects of felt loved as a child and depression PRS on the age at onset of depression in total sample (β = 0.708, P = 5.03 × 10−3) and males (β = 1.421, P = 7.64 × 10−4). GWEIS identified a novel candidate loci interacting with felt loved as a child at GSAP (rs2068031, P = 4.24 × 10–8) and detected several genes with suggestive significance association, such as CMYA5 (rs7343, P = 2.03 × 10–6) and KIRREL3 (rs535603, P = 4.84 × 10–6) in males. Our results indicate emotional care in childhood may affect the age at onset of depression, especially in males, and GSAP plays an important role in their interaction.

Exploring the clinical and genetic associations of adult weight trajectories using electronic health records in a racially diverse biobank: a phenome-wide and polygenic risk study

SummaryBackgroundWeight trajectories might reflect individual health status. In this study, we aimed to examine the clinical and genetic associations of adult weight trajectories using electronic health records (EHRs) in the BioMe Biobank.MethodsWe constructed four weight trajectories based on a-priori definitions of weight changes (5% or 10%) using annual weight in EHRs (stable weight, weight gain, weight loss, and weight cycle); the final weight dataset included 21 487 participants with 162 783 annual weight measures. To confirm accurate assignment of weight trajectories, we manually reviewed weight trajectory plots for 100 random individuals. We then did a hypothesis-free phenome-wide association study (PheWAS) to identify diseases associated with each weight trajectory. Next, we estimated the single-nucleotide polymorphism-based heritability (hSNP2) of weight trajectories using GCTA-GREML, and we did a hypothesis-driven analysis of anorexia nervosa and depression polygenic risk scores (PRS) on these weight trajectories, given both diseases are associated with weight changes. We extended our analyses to the UK Biobank to replicate findings from a patient population to a generally healthy population.FindingsWe found high concordance between manually assigned weight trajectories and those assigned by the algorithm (accuracy ≥98%). Stable weight was consistently associated with lower disease risks among those passing Bonferroni-corrected p value in our PheWAS (p≤4·4 × 10−5). Additionally, we identified an association between depression and weight cycle (odds ratio [OR] 1·42, 95% CI 1·31–1·55, p≤7·7 × 10−16). The adult weight trajectories were heritable (using 5% weight change as the cutoff: hSNP2 of 2·1%, 95% CI 0·9–3·3, for stable weight; 4·1%, 1·4–6·8, for weight gain; 5·5%, 2·8–8·2, for weight loss; and 4·7%, 2·3–7·1%, for weight cycle). Anorexia nervosa PRS was positively associated with weight loss trajectory among individuals without eating disorder diagnoses (OR1SD 1·16, 95% CI 1·07–1·26, per 1 SD higher PRS, p=0·011), and the association was not attenuated by obesity PRS. No association was found between depression PRS and weight trajectories after permutation tests. All main findings were replicated in the UK Biobank (p<0·05).InterpretationOur findings suggest the importance of considering weight from a longitudinal aspect for its association with health and highlight a crucial role of weight management during disease development and progression.FundingKlarman Family Foundation, US National Institute of Mental Health (NIMH).

Machine learning for prediction of schizophrenia using genetic and demographic factors in the UK biobank

Machine learning (ML) holds promise for precision psychiatry, but its predictive performance is unclear. We assessed whether ML provided added value over logistic regression for prediction of schizophrenia, and compared models built using polygenic risk scores (PRS) or clinical/demographic factors.LASSO and ridge-penalised logistic regression, support vector machines (SVM), random forests, boosting, neural networks and stacked models were trained to predict schizophrenia, using PRS for schizophrenia (PRSSZ), sex, parental depression, educational attainment, winter birth, handedness and number of siblings as predictors. Models were evaluated for discrimination using area under the receiver operator characteristic curve (AUROC) and relative importance of predictors using permutation feature importance (PFI). In a secondary analysis, fitted models were tested for association with schizophrenia-related traits which had not been used in model development.Following learning curve analysis, 738 cases and 3690 randomly sampled controls were selected from the UK Biobank. ML models combining all predictors showed the highest discrimination (linear SVM, AUROC = 0.71), but did not significantly outperform logistic regression. AUROC was robust over 100 random resamples of controls. PFI identified PRSSZ as the most important predictor. Highest variance in fitted models was explained by schizophrenia-related traits including fluid intelligence (most associated: linear SVM), digit symbol substitution (RBF SVM), BMI (XGBoost), smoking status (XGBoost) and deprivation (linear SVM).In conclusion, ML approaches did not provide substantial added value for prediction of schizophrenia over logistic regression, as indexed by AUROC; however, risk scores derived with different ML approaches differ with respect to association with schizophrenia-related traits.

Role of polygenic and environmental factors in the co-occurrence of depression and psychosis symptoms: a network analysis

Depression and psychosis are often comorbid; they also have overlapping genetic and environmental risk factors, including trauma and area-level exposures. The present study aimed to advance understanding of this comorbidity via a network approach, by (1) identifying bridge nodes that connect clusters of lifetime depression and psychosis symptoms and (2) evaluating the influence of polygenic and environmental risk factors in these symptoms. This study included data from European ancestry participants in UK Biobank, a large population-based sample (N = 77,650). In Step 1, a network model identified bridge nodes between lifetime symptoms of depression and psychosis and functional impairment. In Step 2, genetic and environmental risk factors were incorporated to examine the degree to which symptoms associated with polygenic risk scores for depression and schizophrenia, lifetime exposure to trauma and area-level factors (including deprivation, air pollution and greenspace). Feelings of worthlessness, beliefs in unreal conspiracy against oneself, depression impairment and psychosis impairment emerged as bridges between depression and psychosis symptoms. Polygenic risk scores for depression and schizophrenia were predominantly linked with depression and psychosis impairment, respectively, rather than with specific symptoms. Cumulative trauma emerged as a bridge node associating deprivation with feelings of worthlessness and beliefs in unreal conspiracy, indicating that the experience of trauma is prominently linked with the co-occurrence of depression and psychosis symptoms related to negative views of oneself and others. These key symptoms and risk factors provide insights into the lifetime co-occurrence of depression and psychosis.

DNA methylome-wide association study of genetic risk for depression implicates antigen processing and immune responses

BackgroundDepression is a disabling and highly prevalent condition where genetic and epigenetic, such as DNA methylation (DNAm), differences contribute to disease risk. DNA methylation is influenced by genetic variation but the association between polygenic risk of depression and DNA methylation is unknown.MethodsWe investigated the association between polygenic risk scores (PRS) for depression and DNAm by conducting a methylome-wide association study (MWAS) in Generation Scotland (N = 8898, mean age = 49.8 years) with replication in the Lothian Birth Cohorts of 1921 and 1936 and adults in the Avon Longitudinal Study of Parents and Children (ALSPAC) (Ncombined = 2049, mean age = 79.1, 69.6 and 47.2 years, respectively). We also conducted a replication MWAS in the ALSPAC children (N = 423, mean age = 17.1 years). Gene ontology analysis was conducted for the cytosine-guanine dinucleotide (CpG) probes significantly associated with depression PRS, followed by Mendelian randomisation (MR) analysis to infer the causal relationship between depression and DNAm.ResultsWidespread associations (NCpG = 71, pBonferroni < 0.05, p < 6.3 × 10−8) were found between PRS constructed using genetic risk variants for depression and DNAm in CpG probes that localised to genes involved in immune responses and neural development. The effect sizes for the significant associations were highly correlated between the discovery and replication samples in adults (r = 0.79) and in adolescents (r = 0.82). Gene Ontology analysis showed that significant CpG probes are enriched in immunological processes in the human leukocyte antigen system. Additional MWAS was conducted for each lead genetic risk variant. Over 47.9% of the independent genetic risk variants included in the PRS showed associations with DNAm in CpG probes located in both the same (cis) and distal (trans) locations to the genetic loci (pBonferroni < 0.045). Subsequent MR analysis showed that there are a greater number of causal effects found from DNAm to depression than vice versa (DNAm to depression: pFDR ranged from 0.024 to 7.45 × 10−30; depression to DNAm: pFDR ranged from 0.028 to 0.003).ConclusionsPRS for depression, especially those constructed from genome-wide significant genetic risk variants, showed methylome-wide differences associated with immune responses. Findings from MR analysis provided evidence for causal effect of DNAm to depression.

Genetic Association of Attention-Deficit/Hyperactivity Disorder and Major Depression With Suicidal Ideation and Attempts in Children: The Adolescent Brain Cognitive Development Study

BackgroundSuicide is among the leading causes of death in children and adolescents. There are well-known risk factors of suicide, including childhood abuse, family conflicts, social adversity, and psychopathology. While suicide risk is also known to be heritable, few studies have investigated genetic risk in younger individuals. MethodsUsing polygenic risk score analysis, we examined whether genetic susceptibility to major psychiatric disorders is associated with suicidal behaviors among 11,878 children enrolled in the ABCD (Adolescent Brain Cognitive Development) Study. Suicidal ideation and suicide attempt data were assessed using the youth report of the Kiddie Schedule for Affective Disorders and Schizophrenia for DSM-5. After performing robust quality control of genotype data, unrelated individuals of European descent were included in analyses (n = 4344). ResultsAmong 8 psychiatric disorders we examined, depression polygenic risk scores were associated with lifetime suicide attempts both in the baseline (odds ratio = 1.55, 95% CI = 1.10–2.18, p = 1.27 × 10−2) and in the follow-up year (odds ratio = 1.38, 95% CI = 1.08–1.77, p = 1.05 × 10−2), after adjusting for children’s age, sex, socioeconomic backgrounds, family history of suicide, and psychopathology. In contrast, attention-deficit/hyperactivity disorder polygenic risk scores were associated with lifetime suicidal ideation (odds ratio = 1.15, 95% CI = 1.05–1.26, p = 3.71 × 10−3), suggesting a distinct contribution of the genetic risk underlying attention-deficit/hyperactivity disorder and depression on suicidal behaviors of children. ConclusionsThe largest genetic sample of suicide risk data in U.S. children suggests a significant genetic basis of suicide risk related to attention-deficit/hyperactivity disorder and depression. Further research is warranted to examine whether incorporation of genomic risk may facilitate more targeted screening and intervention efforts.

Genetic Evidence Supporting a Causal Role of Depression in Alzheimer’s Disease

BackgroundDepression has been associated with a higher risk of Alzheimer’s disease (AD) in several prospective studies; however, mechanisms underlying this association remain unclear. MethodsWe examined genetic correlation between depression and AD using linkage disequilibrium score regression. We then tested for evidence of causality between depression and AD using Mendelian randomization and genome-wide association study results. Subsequently, cis and trans quantitative trait locus analyses for the depression genome-wide association study signals were performed to resolve the genetic signals to specific DNA methylation sites, brain transcripts, and proteins. These transcripts and proteins were then examined for associations with AD and its endophenotypes. Finally, the associations between depression polygenic risk score and AD endophenotypes were examined. ResultsWe detected a significant genetic correlation between depression and AD, suggesting that they have a shared genetic basis. Furthermore, we found that depression had a causal role in AD through Mendelian randomization but did not find evidence for a causal role of AD on depression. Moreover, we identified 75 brain transcripts and 28 brain proteins regulated by the depression genome-wide association study signals through quantitative trait locus analyses. Of these, 46 transcripts and seven proteins were associated with rates of cognitive decline over time, AD pathologies, and AD diagnosis in two separate cohorts, thus implicating them in AD. In addition, we found that a higher depression polygenic risk score was associated with a faster decline of episodic memory over time. ConclusionsDepression appears to have a causal role in AD, and this causal relationship is likely driven, in part, by the 53 brain transcripts and proteins identified in this study.

Combining schizophrenia and depression polygenic risk scores improves the genetic prediction of lithium response in bipolar disorder patients

Lithium is the gold standard therapy for Bipolar Disorder (BD) but its effectiveness differs widely between individuals. The molecular mechanisms underlying treatment response heterogeneity are not well understood, and personalized treatment in BD remains elusive. Genetic analyses of the lithium treatment response phenotype may generate novel molecular insights into lithium’s therapeutic mechanisms and lead to testable hypotheses to improve BD management and outcomes. We used fixed effect meta-analysis techniques to develop meta-analytic polygenic risk scores (MET-PRS) from combinations of highly correlated psychiatric traits, namely schizophrenia (SCZ), major depression (MD) and bipolar disorder (BD). We compared the effects of cross-disorder MET-PRS and single genetic trait PRS on lithium response. For the PRS analyses, we included clinical data on lithium treatment response and genetic information for n = 2283 BD cases from the International Consortium on Lithium Genetics (ConLi+Gen; www.ConLiGen.org). Higher SCZ and MD PRSs were associated with poorer lithium treatment response whereas BD-PRS had no association with treatment outcome. The combined MET2-PRS comprising of SCZ and MD variants (MET2-PRS) and a model using SCZ and MD-PRS sequentially improved response prediction, compared to single-disorder PRS or to a combined score using all three traits (MET3-PRS). Patients in the highest decile for MET2-PRS loading had 2.5 times higher odds of being classified as poor responders than patients with the lowest decile MET2-PRS scores. An exploratory functional pathway analysis of top MET2-PRS variants was conducted. Findings may inform the development of future testing strategies for personalized lithium prescribing in BD.

Influence of polygenic risk scores for schizophrenia and resilience on the cognition of individuals at-risk for psychosis

Cognitive impairment is a core feature of schizophrenia which precedes the onset of full psychotic symptoms, even in the ultra-high-risk stage (UHR). Polygenic risk scores (PRS) can be computed for many psychiatric disorders and phenotyping traits, including scores for resilience. We explored the correlations between several PRS and neurocognition in UHR individuals. We included 107 UHR individuals; 29.9% of them converted to psychosis (UHR-C) while 57.0% did not (UHR-NC) during the 1-year follow-up. Cognitive performances were assessed with the Wechsler Adult Intelligence Scale estimating the Intelligence Quotient (IQ), the Trail Making Test, the verbal fluency, the Stroop test, and the Wisconsin card sorting test. Linear regression models were used to test their association with the PRS for schizophrenia, bipolar disorder, major depression, ADHD, cross-disorders, cognitive performance, intelligence, education attainment, and resilience to schizophrenia. UHR-C had a lower IQ than UHR-NC. The PRS for schizophrenia negatively correlated with IQ, while the PRS for cognitive performance and for resilience positively correlated with IQ. PRS for schizophrenia showed a significant correlation with working memory and processing speed indices. PRS for schizophrenia showed a higher effect on IQ in UHR-NC, and UHR-NC with high PRS for schizophrenia had a similar IQ as UHR-C. Conversely, UHR-C with a high PRS for resilience performed as well as UHR-NC. Our findings suggest that cognitive deficits may predate the onset of psychosis. The genetic architecture of schizophrenia seems to impacts the cognition in UHR-NC. Cognition is also mediated by PRS for resilience.

Suicidal ideation and planning among Mexican adolescents are associated with depression polygenic risk scores.

Suicide is a major public health problem in Mexico and around the world. Genetic predisposition for major depressive disorder (MDD) has been associated with increased risk for suicidal behaviors (SB) in populations of European ancestry (EA). Here, we examine whether MDD polygenic risk scores (MDD PRS), derived from a genome-wide association study involving EA individuals, predict SB, including ideation, planning, and attempt, among Mexican youth using a longitudinal design. At baseline, participants (N=1,128, 12-17 years, 55% women) were interviewed and genotyped as part of a general population survey on adolescent mental health. Eight years later, they were recontacted for a follow up visit (N=437, 20-25 years, 63% women). At both assessments, individuals reported on their engagement in SB within the past year. MDD PRS were significantly positively associated with SB, particularly suicide ideation and planning during adolescence, accounting for ~4-5% of the variance in these outcomes. In contrast, associations between MDD PRS and SB during young adulthood did not reach statistical significance. Our results suggest that increased genetic liability for depression increased risk for SB, particularly during adolescence, expanding our knowledge of the genetic underpinnings of SB.