Dissection of major depressive disorder using polygenic risk scores for schizophrenia in two independent cohorts

Polygenic risk for neuroticism is associated with less efficient control in more difficult situations

Neuroticism is a heritable trait and a risk factor for mental health due to its relevance to poor control of negative events. To examine the relationship between genetic propensity for neuroticism and control processing, we used the polygenic risk score (PRS) approach and a stop signal task during fMRI. We hypothesized that genetic propensity for neuroticism may moderate control processing as a function of control difficulty. PRSs for neuroticism were computed from a transdiagnostic group of individuals (n=406) who completed the stop signal task. The level of control difficulty was a function of the stop signal asynchrony: shorter asynchrony allows easier stopping whereas longer asynchrony makes stopping difficult. The relationship between PRS for neuroticism and neural activity for controlling responses was examined by the stop signal asynchrony. Although PRS for neuroticism did not relate to the overall inhibitory control, individuals with high PRS for neuroticism showed greater activity in left dorsal prefrontal cortex, middle temporal gyrus, and dorsal posterior cingulate cortex for difficult control. Thus, the genetic propensity for neuroticism affects neural processing in a difficult control context, which may help to explain why individuals with high levels of neuroticism exert poor control of negative events in difficult situations.

Identification of schizophrenia symptom-related gene modules by postmortem brain transcriptome analysis

Schizophrenia is a multifactorial disorder, the genetic architecture of which remains unclear. Although many studies have examined the etiology of schizophrenia, the gene sets that contribute to its symptoms have not been fully investigated. In this study, we aimed to identify each gene set associated with corresponding symptoms of schizophrenia using the postmortem brains of 26 patients with schizophrenia and 51 controls. We classified genes expressed in the prefrontal cortex (analyzed by RNA-seq) into several modules by weighted gene co-expression network analysis (WGCNA) and examined the correlation between module expression and clinical characteristics. In addition, we calculated the polygenic risk score (PRS) for schizophrenia from Japanese genome-wide association studies, and investigated the association between the identified gene modules and PRS to evaluate whether genetic background affected gene expression. Finally, we conducted pathway analysis and upstream analysis using Ingenuity Pathway Analysis to clarify the functions and upstream regulators of symptom-related gene modules. As a result, three gene modules generated by WGCNA were significantly correlated with clinical characteristics, and one of these showed a significant association with PRS. Genes belonging to the transcriptional module associated with PRS significantly overlapped with signaling pathways of multiple sclerosis, neuroinflammation, and opioid use, suggesting that these pathways may also be profoundly implicated in schizophrenia. Upstream analysis indicated that genes in the detected module were profoundly regulated by lipopolysaccharides and CREB. This study identified schizophrenia symptom-related gene sets and their upstream regulators, revealing aspects of the pathophysiology of schizophrenia and identifying potential therapeutic targets.

The Potential of Polygenic Risk Scores to Predict Antidepressant Treatment Response in Major Depression: A Systematic Review

BACKGROUND

Understanding the genetic underpinnings of antidepressant treatment response in unipolar major depressive disorder (MDD) can be useful in identifying patients at risk for poor treatment response or treatment resistant depression. A polygenic risk score (PRS) is a useful tool to explore genetic liability of a complex trait such as antidepressant treatment response. Here, we review studies that use PRSs to examine genetic overlap between any trait and antidepressant treatment response in unipolar MDD.

METHODS

A systematic search of literature was conducted in PubMed, Embase, and PsycINFO. Our search included studies examining associations between PRSs of psychiatric as well as non-psychiatric traits and antidepressant treatment response in patients with unipolar MDD. A quality assessment of the included studies was performed.

RESULTS

In total, eleven articles were included which contained PRSs for 30 traits. Studies varied in sample size and endpoints used for antidepressant treatment response. Overall, PRSs for attention-deficit hyperactivity disorder, the personality trait openness, coronary artery disease, obesity, and stroke have been associated with antidepressant treatment response in patients with unipolar MDD.

LIMITATIONS

The endpoints used by included studies differed significantly, therefore it was not possible to perform a meta-analysis.

CONCLUSIONS

Associations between a PRS and antidepressant treatment response have been reported for a number of traits in patients with unipolar MDD. PRSs could be informative to predict antidepressant treatment response in this population, given advances in the field. Most importantly, there is a need for larger study cohorts and the use of standardized outcome measures.

Higher polygenic risk scores for schizophrenia may be suggestive of treatment non-response in major depressive disorder

Up to 60% of patients with major depressive disorder (MDD) do not respond to the first treatment with antidepressants. Response to antidepressants is a polygenic trait, although its underpinning genetics has not been fully clarified. This study aimed to investigate if polygenic risk scores (PRSs) for major psychiatric disorders and trait neuroticism (NEU) were associated with non-response or resistance to antidepressants in MDD. PRSs for bipolar disorder, MDD, NEU, and schizophrenia (SCZ) were computed in 1,148 patients with MDD. Summary statistics from the largest meta-analyses of genome-wide association studies were used as base data. Patients were classified as responders, non-responders to one treatment, non-responders to two or more treatments (treatment-resistant depression or TRD). Regression analyses were adjusted for population stratification and recruitment sites. PRSs did not predict either non-response vs response or TRD vs response after Bonferroni correction. However, SCZ-PRS was nominally associated with non-response (p = 0.003). Patients in the highest SCZ-PRS quintile were more likely to be non-responders than those in the lowest quintile (OR = 2.23, 95% CI = 1.21-4.10, p = 0.02). Patients in the lowest SCZ-PRS quintile showed higher response rates when they did not receive augmentation with second-generation antipsychotics (SGAs), while those in the highest SCZ-PRS quintile had a poor response independently from the treatment strategy (p = 0.009). A higher genetic liability to SCZ may reduce treatment response in MDD, and patients with low SCZ-PRSs may show higher response rates without SGA augmentation. Multivariate approaches and methodological refinements will be necessary before clinical implementations of PRSs.

Epigenetic biotypes of post-traumatic stress disorder in war-zone exposed veteran and active duty males

Post-traumatic stress disorder (PTSD) is a heterogeneous condition evidenced by the absence of objective physiological measurements applicable to all who meet the criteria for the disorder as well as divergent responses to treatments. This study capitalized on biological diversity observed within the PTSD group observed following epigenome-wide analysis of a well-characterized Discovery cohort (N = 166) consisting of 83 male combat exposed veterans with PTSD, and 83 combat veterans without PTSD in order to identify patterns that might distinguish subtypes. Computational analysis of DNA methylation (DNAm) profiles identified two PTSD biotypes within the PTSD+ group, G1 and G2, associated with 34 clinical features that are associated with PTSD and PTSD comorbidities. The G2 biotype was associated with an increased PTSD risk and had higher polygenic risk scores and a greater methylation compared to the G1 biotype and healthy controls. The findings were validated at a 3-year follow-up (N = 59) of the same individuals as well as in two independent, veteran cohorts (N = 54 and N = 38), and an active duty cohort (N = 133). In some cases, for example Dopamine-PKA-CREB and GABA-PKC-CREB signaling pathways, the biotypes were oppositely dysregulated, suggesting that the biotypes were not simply a function of a dimensional relationship with symptom severity, but may represent distinct biological risk profiles underpinning PTSD. The identification of two novel distinct epigenetic biotypes for PTSD may have future utility in understanding biological and clinical heterogeneity in PTSD and potential applications in risk assessment for active duty military personnel under non-clinician-administered settings, and improvement of PTSD diagnostic markers.

Polygenic scores for schizophrenia and general cognitive ability: associations with six cognitive domains, premorbid intelligence, and cognitive composite score in individuals with a psychotic disorder and in healthy controls

Cognitive impairments are considered core features in schizophrenia and other psychotic disorders. Cognitive impairments are, to a lesser degree, also documented in healthy first-degree relatives. Although recent studies have shown (negative) genetic correlations between schizophrenia and general cognitive ability, the association between polygenic risk for schizophrenia and individual cognitive phenotypes remains unclear. We here investigated the association between a polygenic score for schizophrenia (SCZ_PGS) and six well-defined cognitive domains, in addition to a composite measure of cognitive ability and a measure of premorbid intellectual ability in 731 participants with a psychotic disorder and 851 healthy controls. We also investigated the association between a PGS for general cognitive ability (COG_PGS) and the same cognitive domains in the same sample. We found no significant associations between the SCZ_PGS and any cognitive phenotypes, in either patients with a psychotic disorder or healthy controls. For COG_PGS we observed stronger associations with cognitive phenotypes in healthy controls than in participants with psychotic disorders. In healthy controls, the association between COG_PGS (at the p value threshold of ≥0.01) and working memory remained significant after Bonferroni correction (β = 0.12, p = 8.6 × 10^-5). Altogether, the lack of associations between SCZ_PGS and COG_PGS with cognitive performance in participants with psychotic disorders suggests that either environmental factors or unassessed genetic factors play a role in the development of cognitive impairments in psychotic disorders. Working memory should be further studied as an important cognitive phenotype.

Stratifying major depressive disorder by polygenic risk for schizophrenia in relation to structural brain measures

BACKGROUND

Substantial clinical heterogeneity of major depressive disorder (MDD) suggests it may group together individuals with diverse aetiologies. Identifying distinct subtypes should lead to more effective diagnosis and treatment, while providing more useful targets for further research. Genetic and clinical overlap between MDD and schizophrenia (SCZ) suggests an MDD subtype may share underlying mechanisms with SCZ.

METHODS

The present study investigated whether a neurobiologically distinct subtype of MDD could be identified by SCZ polygenic risk score (PRS). We explored interactive effects between SCZ PRS and MDD case/control status on a range of cortical, subcortical and white matter metrics among 2370 male and 2574 female UK Biobank participants.

RESULTS

There was a significant SCZ PRS by MDD interaction for rostral anterior cingulate cortex (RACC) thickness (β = 0.191, q = 0.043). This was driven by a positive association between SCZ PRS and RACC thickness among MDD cases (β = 0.098, p = 0.026), compared to a negative association among controls (β = -0.087, p = 0.002). MDD cases with low SCZ PRS showed thinner RACC, although the opposite difference for high-SCZ-PRS cases was not significant. There were nominal interactions for other brain metrics, but none remained significant after correcting for multiple comparisons.

CONCLUSIONS

Our significant results indicate that MDD case-control differences in RACC thickness vary as a function of SCZ PRS. Although this was not the case for most other brain measures assessed, our specific findings still provide some further evidence that MDD in the presence of high genetic risk for SCZ is subtly neurobiologically distinct from MDD in general.

A polygenic score for body mass index is associated with depressive symptoms via early life stress: Evidence for gene-environment correlation

Increasing childhood obesity rates are associated with not only adverse physical, but also mental health outcomes, including depression. These negative outcomes may be caused and/or exacerbated by the bullying and shaming overweight individuals experience. As body mass index (BMI) can be highly heritable, we hypothesized that a genetic risk for higher BMI, will predict higher early life stress (ELS), which in turn will predict higher depressive symptoms in adulthood. Such a process will reflect an evocative gene-environment correlation (rGE) wherein an individual's genetically influenced phenotype evokes a reaction from the environment that subsequently shapes the individual's health. We modeled genetic risk using a polygenic score of BMI derived from a recent large GWAS meta-analysis. Self-reports were used for the assessment of ELS and depressive symptoms in adulthood. The discovery sample consisted of 524 non-Hispanic Caucasian university students from the Duke Neurogenetics Study (DNS; 278 women, mean age 19.78 ± 1.23 years) and the independent replication sample consisted of 5930 white British individuals from the UK biobank (UKB; 3128 women, mean age 62.66 ± 7.38 years). A significant mediation effect was found in the DNS (indirect effect = 0.207, bootstrapped SE = .10, bootstrapped 95% CI: 0.014 to 0.421), and then replicated in the UKB (indirect effect = 0.04, bootstrapped SE = .01, bootstrapped 95% CI: 0.018 to 0.066). Higher BMI polygenic scores predicted higher ELS, which in turn predicted higher depressive symptoms. Our findings suggest that evocative rGE may contribute to weight-related mental health problems and stress the need for interventions that aim to reduce weight bias, specifically during childhood.

A genome-wide association study-derived polygenic score for interleukin-1β is associated with hippocampal volume in two samples

Accumulating research suggests that the pro-inflammatory cytokine interleukin-1β (IL-1β) has a modulatory effect on the hippocampus, a brain structure important for learning and memory as well as linked with both psychiatric and neurodegenerative disorders. Here, we used an imaging genetics strategy to test an association between an IL-1β polygenic score and hippocampal volume in two independent samples. Our polygenic score was derived using summary statistics from a recent genome-wide association study of circulating cytokines that included IL-1β (N = 3,309). In the first sample of 512 non-Hispanic Caucasian university students (274 women, mean age 19.78 ± 1.24 years) from the Duke Neurogenetics Study, we identified a significant positive correlation between IL-1β polygenic scores and hippocampal volume. This positive association was successfully replicated in a second sample of 7,960 white British volunteers (4,158 women, mean age 62.63 ± 7.45 years) from the UK Biobank. Our results lend further support in humans, to the link between IL-1β and the structure of the hippocampus.

Associations between schizophrenia genetic risk, anxiety disorders and manic/hypomanic episode in a longitudinal population cohort study

BACKGROUND

Studies involving clinically recruited samples show that genetic liability to schizophrenia overlaps with that for several psychiatric disorders including bipolar disorder, major depression and, in a population study, anxiety disorder and negative symptoms in adolescence.AimsWe examined whether, at a population level, association between schizophrenia liability and anxiety disorders continues into adulthood, for specific anxiety disorders and as a group. We explored in an epidemiologically based cohort the nature of adult psychopathology sharing liability to schizophrenia.

METHOD

Schizophrenia polygenic risk scores (PRSs) were calculated for 590 European-descent individuals from the Christchurch Health and Development Study. Logistic regression was used to examine associations between schizophrenia PRS and four anxiety disorders (social phobia, specific phobia, panic disorder and generalised anxiety disorder), schizophrenia/schizophreniform disorder, manic/hypomanic episode, alcohol dependence, major depression, and - using linear regression - total number of anxiety disorders. A novel population-level association with hypomania was tested in a UK birth cohort (Avon Longitudinal Study of Parents and Children).

RESULTS

Schizophrenia PRS was associated with total number of anxiety disorders and with generalised anxiety disorder and panic disorder. We show a novel population-level association between schizophrenia PRS and manic/hypomanic episode.

CONCLUSIONS

The relationship between schizophrenia liability and anxiety disorders is not restricted to psychopathology in adolescence but is present in adulthood and specifically linked to generalised anxiety disorder and panic disorder. We suggest that the association between schizophrenia liability and hypomanic/manic episodes found in clinical samples may not be due to bias.Declarations of interestNone.

Genes associated with anhedonia: a new analysis in a large clinical trial (GENDEP)

A key feature of major depressive disorder (MDD) is anhedonia, which is a predictor of response to antidepressant treatment. In order to shed light on its genetic underpinnings, we conducted a genome-wide association study (GWAS) followed by investigation of biological pathway enrichment using an anhedonia dimension for 759 patients with MDD in the GENDEP study. The GWAS identified 18 SNPs associated at genome-wide significance with the top one being an intronic SNP (rs9392549) in PRPF4B (pre-mRNA processing factor 4B) located on chromosome 6 (P = 2.07 × 10-9) while gene-set enrichment analysis returned one gene ontology term, axon cargo transport (GO: 0008088) with a nominally significant P value (1.15 × 10-5). Furthermore, our exploratory analysis yielded some interesting, albeit not statistically significant genetic correlation with Parkinson's Disease and nucleus accumbens gray matter. In addition, polygenic risk scores (PRSs) generated from our association analysis were found to be able to predict treatment efficacy of the antidepressants in this study. In conclusion, we found some markers significantly associated with anhedonia, and some suggestive findings of related pathways and biological functions, which could be further investigated in other studies.

Association of Whole-Genome and NETRIN1 Signaling Pathway-Derived Polygenic Risk Scores for Major Depressive Disorder and White Matter Microstructure in the UK Biobank

Background

Major depressive disorder is a clinically heterogeneous psychiatric disorder with a polygenic architecture. Genome-wide association studies have identified a number of risk-associated variants across the genome and have reported growing evidence of NETRIN1 pathway involvement. Stratifying disease risk by genetic variation within the NETRIN1 pathway may provide important routes for identification of disease mechanisms by focusing on a specific process, excluding heterogeneous risk-associated variation in other pathways. Here, we sought to investigate whether major depressive disorder polygenic risk scores derived from the NETRIN1 signaling pathway (NETRIN1-PRSs) and the whole genome, excluding NETRIN1 pathway genes (genomic-PRSs), were associated with white matter microstructure.

Methods

We used two diffusion tensor imaging measures, fractional anisotropy (FA) and mean diffusivity (MD), in the most up-to-date UK Biobank neuroimaging data release (FA: n = 6401; MD: n = 6390).

Results

We found significantly lower FA in the superior longitudinal fasciculus (β = −.035, p_corrected = .029) and significantly higher MD in a global measure of thalamic radiations (β = .029, p_corrected = .021), as well as higher MD in the superior (β = .034, p_corrected = .039) and inferior (β = .029, p_corrected = .043) longitudinal fasciculus and in the anterior (β = .025, p_corrected = .046) and superior (β = .027, p_corrected = .043) thalamic radiation associated with NETRIN1-PRS. Genomic-PRS was also associated with lower FA and higher MD in several tracts.

Conclusions

Our findings indicate that variation in the NETRIN1 signaling pathway may confer risk for major depressive disorder through effects on a number of white matter tracts.

Aspects of Additional Psychiatric Disorders in Severe Depression/Melancholia: A Comparison between Suicides and Controls and General Pattern

OBJECTIVE

Additional and comorbid diagnoses are common among suicide victims with major depressive disorder (MDD) and have been shown to increase the suicide risk. The aim of the present study was first, to investigate whether patients with severe depression/melancholia who had died by suicide showed more additional psychiatric disorders than a matched control group. Second, general rates of comorbid and additional diagnoses in the total group of patients were estimated and compared with literature on MDD.

METHOD

A blind record evaluation was performed on 100 suicide victims with severe depression/melancholia (MDD with melancholic and/or psychotic features: MDD-M/P) and matched controls admitted to the Department of Psychiatry, Lund, Sweden between 1956 and 1969 and monitored to 2010. Diagnoses in addition to severe depression were noted.

RESULTS

Less than half of both the suicides and controls had just one psychiatric disorder (47% in the suicide and 46% in the control group). The average number of diagnoses was 1.80 and 1.82, respectively. Additional diagnoses were not related to an increased suicide risk. Anxiety was the most common diagnosis. Occurrence of suspected schizophrenia/schizotypal or additional obsessive-compulsive symptoms were more common than expected, but alcohol use disorders did not appear very frequent.

CONCLUSIONS

The known increased risk of suicide in MDD with comorbid/additional diagnoses does not seem to apply to persons with MDD-M/P (major depressive disorder-depression/Melancholia). Some diagnoses, such as schizophrenia/schizotypal disorders, were more frequent than expected, which is discussed, and a genetic overlap with MDD-M/P is proposed.

Polygenic Risk Scores in Clinical Psychology: Bridging Genomic Risk to Individual Differences

Genomewide association studies (GWASs) across psychiatric phenotypes have shown that common genetic variants generally confer risk with small effect sizes (odds ratio < 1.1) that additively contribute to polygenic risk. Summary statistics derived from large discovery GWASs can be used to generate polygenic risk scores (PRS) in independent, target data sets to examine correlates of polygenic disorder liability (e.g., does genetic liability to schizophrenia predict cognition?). The intuitive appeal and generalizability of PRS have led to their widespread use and new insights into mechanisms of polygenic liability. However, when currently applied across traits they account for small amounts of variance (<3%), are relatively uninformative for clinical treatment, and, in isolation, provide no insight into molecular mechanisms. Larger GWASs are needed to increase the precision of PRS, and novel approaches integrating various data sources (e.g., multitrait analysis of GWASs) may improve the utility of current PRS.

Genetics Factors in Major Depression Disease

Depressive disorders (DDs) are one of the most widespread forms of psychiatric pathology. According to the World Health Organization, about 350 million people in the world are affected by this condition. Family and twin studies have demonstrated that the contribution of genetic factors to the risk of the onset of DDs is quite large. Various methodological approaches (analysis of candidate genes, genome-wide association analysis, genome-wide sequencing) have been used, and a large number of the associations between genes and different clinical DD variants and DD subphenotypes have been published. However, in most cases, these associations have not been confirmed in replication studies, and only a small number of genes have been proven to be associated with DD development risk. To ascertain the role of genetic factors in DD pathogenesis, further investigations of the relevant conditions are required. Special consideration should be given to the polygenic characteristics noted in whole-genome studies of the heritability of the disorder without a pronounced effect of the major gene. These observations accentuate the relevance of the analysis of gene-interaction roles in DD development and progression. It is important that association studies of the inherited variants of the genome should be supported by analysis of dynamic changes during DD progression. Epigenetic changes that cause modifications of a gene's functional state without changing its coding sequence are of primary interest. However, the opportunities for studying changes in the epigenome, transcriptome, and proteome during DD are limited by the nature of the disease and the need for brain tissue analysis, which is possible only postmortem. Therefore, any association studies between DD pathogenesis and epigenetic factors must be supplemented through the use of different animal models of depression. A threefold approach comprising the combination of gene association studies, assessment of the epigenetic state in DD patients, and analysis of different "omic" changes in animal depression models will make it possible to evaluate the contribution of genetic, epigenetic, and environmental factors to the development of different forms of depression and to help develop ways to decrease the risk of depression and improve the treatment of DD.

Effects of environmental risks and polygenic loading for schizophrenia on cortical thickness

There are established differences in cortical thickness (CT) in schizophrenia (SCZ) and bipolar (BD) patients when compared to healthy controls (HC). However, it is unknown to what extent environmental or genetic risk factors impact on CT in these populations. We have investigated the effect of Environmental Risk Scores (ERS) and Polygenic Risk Scores for SCZ (PGRS-SCZ) on CT. Structural MRI scans were acquired at 3T for patients with SCZ or BD (n=57) and controls (n=41). Cortical reconstructions were generated in FreeSurfer (v5.3). The ERS was created by determining exposure to cannabis use, childhood adverse events, migration, urbanicity and obstetric complications. The PGRS-SCZ were generated, for a subset of the sample (Patients=43, HC=32), based on the latest PGC GWAS findings. ANCOVAs were used to test the hypotheses that ERS and PGRS-SCZ relate to CT globally, and in frontal and temporal lobes. An increase in ERS was negatively associated with CT within temporal lobe for patients. A higher PGRS-SCZ was also related to global cortical thinning for patients. ERS effects remained significant when including PGRS-SCZ as a fixed effect. No relationship which survived FDR correction was found for ERS and PGRS-SCZ in controls. Environmental risk for SCZ was related to localised cortical thinning in patients with SCZ and BD, while increased PGRS-SCZ was associated with global cortical thinning. Genetic and environmental risk factors for SCZ appear therefore to have differential effects. This provides a mechanistic means by which different risk factors may contribute to the development of SCZ and BD.