Polygenic risk scores in bipolar disorder subgroups

Psychiatric Polygenic Risk Scores Across Youth With Bipolar Disorder, Youth at High Risk for Bipolar Disorder, and Controls

OBJECTIVE

There is a pronounced gap in knowledge regarding polygenic underpinnings of youth bipolar disorder (BD). This study aimed to compare polygenic risk scores (PRSs) in youth with BD, youth at high clinical and/or familial risk for BD (HR), and controls.

METHOD

Participants were 344 youths of European ancestry (13-20 years old), including 136 youths with BD, 121 HR youths, and 87 controls. PRSs for BD, schizophrenia, major depressive disorder, and attention-deficit/hyperactivity disorder were constructed using independent genome-wide summary statistics from adult cohorts. Multinomial logistic regression was used to examine the association between each PRS and diagnostic status (BD vs HR vs controls). All genetic analyses controlled for age, sex, and 2 genetic principal components.

RESULTS

The BD group showed significantly higher BD-PRS than the control group (odds ratio = 1.54, 95% CI = 1.13-2.10, p = .006), with the HR group numerically intermediate. BD-PRS explained 7.9% of phenotypic variance. PRSs for schizophrenia, major depressive disorder, and attention-deficit/hyperactivity disorder were not significantly different among groups. In the BD group, BD-PRS did not significantly differ in relation to BD subtype, age of onset, psychosis, or family history of BD.

CONCLUSION

BD-PRS derived from adult genome-wide summary statistics is elevated in youth with BD. Absence of significant between-group differences in PRSs for other psychiatric disorders supports the specificity of BD-PRS in youth. These findings add to the biological validation of BD in youth and could have implications for early identification and diagnosis. To enhance clinical utility, future genome-wide association studies that focus specifically on early-onset BD are warranted, as are studies integrating additional genetic and environmental factors.

DIVERSITY & INCLUSION STATEMENT

We worked to ensure sex and gender balance in the recruitment of human participants. One or more of the authors of this paper self-identifies as a member of one or more historically underrepresented sexual and/or gender groups in science. One or more of the authors of this paper self-identifies as a member of one or more historically underrepresented racial and/or ethnic groups in science. We actively worked to promote sex and gender balance in our author group. We actively worked to promote inclusion of historically underrepresented racial and/or ethnic groups in science in our author group. The author list of this paper includes contributors from the location and/or community where the research was conducted who participated in the data collection, design, analysis, and/or interpretation of the work.

Association of polygenic risk for bipolar disorder with resting-state network functional connectivity in youth with and without bipolar disorder

Little is known regarding the polygenic underpinnings of anomalous resting-state functional connectivity (rsFC) in youth bipolar disorder (BD). The current study examined the association of polygenic risk for BD (BD-PRS) with whole-brain rsFC at the large-scale network level in youth with and without BD. 99 youth of European ancestry (56 BD, 43 healthy controls [HC]), ages 13-20 years, completed resting-state fMRI scans. BD-PRS was calculated using summary statistics from the latest adult BD genome-wide association study. Data-driven independent component analyses of the resting-state fMRI data were implemented to examine the association of BD-PRS with rsFC in the overall sample, and separately in BD and HC. In the overall sample, higher BD-PRS was associated with lower rsFC of the salience network and higher rsFC of the frontoparietal network with frontal and parietal regions. Within the BD group, higher BD-PRS was associated with higher rsFC of the default mode network with orbitofrontal cortex, and altered rsFC of the visual network with frontal and occipital regions. Within the HC group, higher BD-PRS was associated with altered rsFC of the frontoparietal network with frontal, temporal and occipital regions. In conclusion, the current study found that BD-PRS generated based on adult genetic data was associated with altered rsFC patterns of brain networks in youth. Our findings support the usefulness of BD-PRS to investigate genetically influenced neuroimaging markers of vulnerability to BD, which can be observed in youth with BD early in their course of illness as well as in healthy youth.

Polygenic Risk Scores for Bipolar Disorder: Progress and Perspectives

Bipolar disorder (BD) is a common and highly heritable psychiatric disorder, the study of BD genetic characteristics can help with early prevention and individualized treatment. At the same time, BD is a highly heterogeneous polygenic genetic disorder with significant genetic overlap with other psychiatric disorders. In recent years, polygenic risk scores (PRS) derived from genome-wide association studies (GWAS) data have been widely used in genetic studies of various complex diseases and can be used to explore the genetic susceptibility of diseases. This review discusses phenotypic associations and genetic correlations with other conditions of BD based on PRS, and provides ideas for genetic studies and prevention of BD.

Association of polygenic risk for bipolar disorder with grey matter structure and white matter integrity in youth

There is a gap in knowledge regarding the polygenic underpinnings of brain anomalies observed in youth bipolar disorder (BD). This study examined the association of a polygenic risk score for BD (BD-PRS) with grey matter structure and white matter integrity in youth with and without BD. 113 participants were included in the analyses, including 78 participants with both T1-weighted and diffusion-weighted MRI images, 32 participants with T1-weighted images only, and 3 participants with diffusion-weighted images only. BD-PRS was calculated using PRS-CS-auto and was based on independent adult genome-wide summary statistics. Vertex- and voxel-wise analyses examined the associations of BD-PRS with grey matter metrics (cortical volume [CV], cortical surface area [CSA], cortical thickness [CTh]) and fractional anisotropy [FA] in the combined sample, and separately in BD and HC. In the combined sample of participants with T1-weighted images (n = 110, 66 BD, 44 HC), higher BD-PRS was associated with smaller grey matter metrics in frontal and temporal regions. In within-group analyses, higher BD-PRS was associated with lower CTh of frontal, temporal, and fusiform gyrus in BD, and with lower CV and CSA of superior frontal gyrus in HC. In the combined sample of participants with diffusion-weighted images (n = 81, 49 BD, 32 HC), higher BD-PRS was associated with lower FA in widespread white matter regions. In summary, BD-PRS calculated based on adult genetic data was negatively associated with grey matter structure and FA in youth in regions implicated in BD, which may suggest neuroimaging markers of vulnerability to BD. Future longitudinal studies are needed to examine whether BD-PRS predicts neurodevelopmental changes in BD vs. HC and its interaction with course of illness and long-term medication use.

Polygenic Risk and Episode Polarity Among Individuals With Bipolar Disorder

OBJECTIVE

The authors investigated associations between polygenic liabilities for bipolar disorder, major depression, and schizophrenia and episode polarity among individuals with bipolar disorder.

METHODS

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.

RESULTS

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.

CONCLUSIONS

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.

The Polygenic Risk Score Knowledge Base offers a centralized online repository for calculating and contextualizing polygenic risk scores

The process of identifying suitable genome-wide association (GWA) studies and formatting the data to calculate multiple polygenic risk scores on a single genome can be laborious. Here, we present a centralized polygenic risk score calculator currently containing over 250,000 genetic variant associations from the NHGRI-EBI GWAS Catalog for users to easily calculate sample-specific polygenic risk scores with comparable results to other available tools. Polygenic risk scores are calculated either online through the Polygenic Risk Score Knowledge Base (PRSKB; https://prs.byu.edu ) or via a command-line interface. We report study-specific polygenic risk scores across the UK Biobank, 1000 Genomes, and the Alzheimer's Disease Neuroimaging Initiative (ADNI), contextualize computed scores, and identify potentially confounding genetic risk factors in ADNI. We introduce a streamlined analysis tool and web interface to calculate and contextualize polygenic risk scores across various studies, which we anticipate will facilitate a wider adaptation of polygenic risk scores in future disease research.

Role of Polygenic Risk Score in the Familial Transmission of Bipolar Disorder in Youth

IMPORTANCE

Establishing genetic contributions to the transmission of bipolar disorder (BD) from parents to offspring may inform the risk of developing this disorder and further serve to validate BD in youth.

OBJECTIVE

To evaluate the specific association of BD polygenic risk scores (PRSs) on the familial transmission and validity of pediatric BD.

DESIGN, SETTING, AND PARTICIPANTS

This community-based case-control longitudinal study (Pittsburgh Biological Offspring Study) included parents with BD I/II and their offspring and parents without BD (healthy or non-BD psychopathology) and their offspring. Participants were recruited between March 2001 and May 2007, and analysis took place from December 2020 to September 2021.

EXPOSURES

PRSs for BD, major depressive disorder, schizophrenia, and attention-deficit/hyperactivity disorder.

MAIN OUTCOMES AND MEASURES

Participants were prospectively evaluated using standardized interviews blind to parental diagnosis. DNA was extracted from saliva and genotyped. PRSs were constructed based on independent large-scale genome-wide association studies.

RESULTS

A total of 156 parents with BD I/II and 180 parents without BD (mean [SD] age, 39.6 [7.9] years; 241 female [72%]) as well as 251 offspring of parents with BD and 158 offspring of parents without BD (mean [SD] age, 10.4 [4.7] years; 213 female [52%]) of European ancestry were analyzed. Participants were assessed a mean of 6.7 times during a mean (SD) of 13 (3.4) years of follow-up (84% retention). More offspring of parents with BD developed BD (58 [23.1%] vs 8 [5.1%]; P < .001) and depression (126 [50.2%] vs 52 [32.9%]; P < .001) compared with offspring of parents without BD. BD PRS was higher in both parents and offspring with BD than parents and offspring without BD (parents: odds ratio, 1.50; 95% CI, 1.19-1.89; P < .001; explained 4.8% of the phenotypic variance vs offspring: hazard ratio, 1.34; 95% CI, 1.03-1.7; P = .02; explained 5.0% of the phenotypic variance). BD PRS did not differ across BD subtypes. In a model combining parental and offspring BD PRS, the parental BD PRS association with offspring BD was fully mediated by offspring BD PRS (hazard ratio, 1.40; 95% CI, 1.05-1.86; P = .02). Parental BD had a stronger direct association than parental or offspring BD PRS with offspring BD risk (hazard ratio, 5.21; 95% CI, 1.86-14.62; P = .002), explaining 30% of the variance. Parental and offspring BD PRS explained 6% of the BD onset variance beyond parental diagnosis. There were no significant between-group differences in PRSs for major depressive disorder, schizophrenia, and attention-deficit/hyperactivity disorder in parents or offspring and they were not significantly associated with BD onset.

CONCLUSIONS AND RELEVANCE

The findings of this study add to the extant clinical validation of BD in youth. Parental BD and offspring BD PRS independently associated with the risk of BD in offspring. Although this is promising, the association of BD PRS was relatively small and cannot be used alone to determine BD risk until further developments occur.

Polygenic risk scores across the extended psychosis spectrum

As early detection of symptoms in the subclinical to clinical psychosis spectrum may improve health outcomes, knowing the probabilistic susceptibility of developing a disorder could guide mitigation measures and clinical intervention. In this context, polygenic risk scores (PRSs) quantifying the additive effects of multiple common genetic variants hold the potential to predict complex diseases and index severity gradients. PRSs for schizophrenia (SZ) and bipolar disorder (BD) were computed using Bayesian regression and continuous shrinkage priors based on the latest SZ and BD genome-wide association studies (Psychiatric Genomics Consortium, third release). Eight well-phenotyped groups (n = 1580; 56% males) were assessed: control (n = 305), lower (n = 117) and higher (n = 113) schizotypy (both groups of healthy individuals), at-risk for psychosis (n = 120), BD type-I (n = 359), BD type-II (n = 96), schizoaffective disorder (n = 86), and SZ groups (n = 384). PRS differences were investigated for binary traits and the quantitative Positive and Negative Syndrome Scale. Both BD-PRS and SZ-PRS significantly differentiated controls from at-risk and clinical groups (Nagelkerke's pseudo-R2: 1.3-7.7%), except for BD type-II for SZ-PRS. Out of 28 pairwise comparisons for SZ-PRS and BD-PRS, 9 and 12, respectively, reached the Bonferroni-corrected significance. BD-PRS differed between control and at-risk groups, but not between at-risk and BD type-I groups. There was no difference between controls and schizotypy. SZ-PRSs, but not BD-PRSs, were positively associated with transdiagnostic symptomology. Overall, PRSs support the continuum model across the psychosis spectrum at the genomic level with possible irregularities for schizotypy. The at-risk state demands heightened clinical attention and research addressing symptom course specifiers. Continued efforts are needed to refine the diagnostic and prognostic accuracy of PRSs in mental healthcare.

Structural neuroimaging phenotypes of a novel multi-gene risk score in youth bipolar disorder

BACKGROUND

Bipolar disorder (BD) is among the most heritable psychiatric disorders, particularly in early-onset cases, owing to multiple genes of small effect. Here we examine a multi-gene risk score (MGRS), to address the gap in multi-gene research in early-onset BD.

METHODS

MGRS was derived from 34 genetic variants relevant to neuropsychiatric diseases and related systemic processes. Multiple MGRS were calculated across a spectrum of inclusion p-value thresholds, based on allelic associations with BD. Youth participants (123 BD, 103 healthy control [HC]) of European descent were included, of which 101 participants (58 BD, 43 HC) underwent MRI T1-weighted structural neuroimaging. Hierarchical regressions examined for main effects and MGRS-by-diagnosis interaction effects on 6 regions-of-interest (ROIs). Vertex-wise analysis also examined MGRS-by-diagnosis interactions.

RESULTS

MGRS based on allelic association p≤0.60 was most robust, explaining 6.8% of variance (t(226)=3.46, p=.001). There was an MGRS-by-diagnosis interaction effect on ventrolateral prefrontal cortex surface area (vlPFC; β=.21, p=.0007). Higher MGRS was associated with larger vlPFC surface area in BD vs. HC. There were 8 significant clusters in vertex-wise analyses, primarily in fronto-temporal regions, including vlPFC.

LIMITATIONS

Cross-sectional design, modest sample size.

CONCLUSIONS

There was a diagnosis-by-MGRS interaction effect on vlPFC surface area, a region involved in emotional processing, emotional regulation, and reward response. Vertex-wise analysis also identified several clusters overlapping this region. This preliminary study provides an example of an approach to imaging-genetics that is intermediate between candidate gene and genome-wide association studies, enriched for genetic variants with established relevance to neuropsychiatric diseases.

Interaction between adverse childhood experiences and polygenic risk in patients with bipolar disorder

The interaction between genes and environment often occurs when they depend on one another. We hypothesized that adverse childhood experiences (ACEs) would interact with genetic predispositions to bipolar disorder (BD), demonstrating earlier age at onset (AAO) and worse clinical outcomes. We aimed to clarify the effects of the interaction between ACEs and genetic susceptibility using polygenic risk score (PRS) on AAO and clinical outcomes. Single nucleotide polymorphisms and clinical data, including ACEs, were obtained from the Bipolar Genomic Study, which contains a large sample of BD participants. A total of 1615 subjects with BD I were obtained and divided into two groups according to the presence or absence of ACEs and an additional four groups based on the number of ACEs (none versus one versus two versus ≥ three types). ACEs was evaluated using the childhood life events scale (CLES). BD-PRS was obtained from the Psychiatric Genomics Consortium, which compared BD patients and healthy controls. The BD-PRS was higher in the group with ACEs than without ACEs at most p-value thresholds. In multivariate linear regression analyses, both groups with more ACEs and higher BD-PRS were independently and interactively associated with an earlier AAO of BD; however, only greater ACEs were associated with worsened clinical outcome. These findings highlight the clinical importance of evaluating ACEs and polygenic risk in research of the etiology of BD.

Polygenic risk for autism spectrum disorder affects left amygdala activity and negative emotion in schizophrenia

Although the diagnoses based on phenomenology have many practical advantages, accumulating evidence shows that schizophrenia and autism spectrum disorder (ASD) share some overlap in genetics and clinical presentation. It remains largely unknown how ASD-associated polygenetic risk contributes to the pathogenesis of schizophrenia. In the present study, we calculated high-resolution ASD polygenic risk scores (ASD PRSs) and selected optimal ten ASD PRS with minimal P values in the association analysis of PRSs, with schizophrenia to assess the effect of ASD PRS on brain neural activity in schizophrenia cases and controls. We found that amplitude of low-frequency fluctuation in left amygdala was positively associated with ASD PRSs in our cohort. Correlation analysis of ASD PRSs with facial emotion recognition test identified the negative correlation of ASD PRSs with negative emotions in schizophrenia cases and controls. Finally, functional enrichment analysis of PRS genes revealed that neural system function and development, as well as signal transduction, were mainly enriched in PRS genes. Our results provide empirical evidence that polygenic risk for ASD contributes to schizophrenia by the intermediate phenotypes of left amygdala function and emotion recognition. It provides a promising strategy to understand the relationship between phenotypes and genotypes shared in mental disorders.

Childhood maltreatment and polygenic risk in bipolar disorders

BACKGROUND

Childhood maltreatment is a well-known risk factor for developing a more severe and complex form of bipolar disorders (BD). However, knowledge is scarce about the interactions between childhood maltreatment and underlying genetic vulnerability on the clinical expression of BD.

METHOD

We assigned a BD-polygenic risk score (BD-PRS), calculated from the Psychiatric Genomics Consortium, to each individual in a sample of 402 cases with BD. The lifetime clinical expression of BD was characterized using structured interviews and patients completed the Childhood Trauma Questionnaire (CTQ) to assess the severity of childhood maltreatment.

RESULTS

Cases who reported more severe childhood maltreatment had a lower BD-PRS (rho = -0.12, P = .01), especially when considering emotional abuse (rho = -0.16, P = .001). An interaction between BD-PRS and childhood maltreatment was observed for the risk of rapid cycling (P = .01). No further interactions between BD-PRS and childhood maltreatment were observed for other clinical characteristics (age at onset, suicide attempts, number of mood episodes, mixed features, substance use disorders and psychotic symptoms).

CONCLUSION

Our study is the first to show that less genetic risk may be needed to develop a more unstable form of BD when exposed to childhood maltreatment. Our study supports childhood trauma as an independent risk factor for BD.

Proof-of-concept study of a multi-gene risk score in adolescent bipolar disorder

BACKGROUND

Few studies have examined multiple genetic variants concurrently for the purpose of classifying bipolar disorder (BD); the literature among youth is particularly sparse. We selected 35 genetic variants, previously implicated in BD or associated characteristics, from which to identify the most robustly predictive group of genes.

METHODS

215 Caucasian adolescents (114 BD and 101 healthy controls (HC), ages 13-20 years) were included. Psychiatric diagnoses were determined based on semi-structured diagnostic interviews. Genomic DNA was extracted from saliva for genotyping. Two models were used to calculate a multi-gene risk score (MGRS). Model 1 used forward and backward regressions, and model 2 used a PLINK generated method.

RESULTS

In model 1, GPX3 rs3792797 was significant in the forward regression, DRD4 exonIII was significant in the backward regression; IL1β rs16944 and DISC1 rs821577 were significant in both the forward and backward regressions. These variants are involved in dopamine neurotransmission; inflammation and oxidative stress; and neuronal development. Model 1 MGRS did not significantly discriminate between BD and HC. In model 2, ZNF804A rs1344706 was significantly associated with BD; however, this association did not predict diagnosis when entered into the weighted model.

LIMITATIONS

This study was limited by the number of genetic variants examined and the modest sample size.

CONCLUSIONS

Whereas regression approaches identified four genetic variants that significantly discriminated between BD and HC, those same variants no longer discriminated between BD and HC when computed as a MGRS. Future larger studies are needed evaluating intermediate phenotypes such as neuroimaging and blood-based biomarkers.

Whole-exome sequencing identifies variants associated with structural MRI markers in patients with bipolar disorders

BACKGROUND

Bipolar disorder (BD) is one of the most heritable psychiatric disorders. A growing number of whole-exome sequencing (WES) studies for BD has been performed, however, no research has examined the association between single nucleotide variants (SNVs) from WES and structural magnetic resonance imaging (MRI) data.

METHODS

We sequenced whole-exomes in 53 patients with BD and 82 healthy control participants at an initial discovery stage and investigated the impacts of SNVs in risk genes from WES analysis on the cortical gray-matter thickness and integrity of white matter tracts and in the following stage. Cortical thickness and white matter integrity were investigated using the FreeSurfer and TRACULA (Tracts Constrained by UnderLying Anatomy).

RESULTS

We identified 122 BD-related genes including KMT2C, AHNAK, CDH23, DCHS1, FRAS1, MACF1 and RYR3 and observed 27 recurrent copy number alteration regions including gain on 8p23.1 and loss on 15q11.1 - q11.2. Among them, single nucleotide polymorphism (SNP) rs4639425 in KMT2C gene, which regulates histone H3 lysine 4 (H3K4) methylation involved in chromatin remodeling, was associated with widespread alterations of white matter integrity including the cingulum, uncinate fasciculus, cortico-spinal tract, and superior longitudinal fasciculus.

LIMITATION

The small sample size of patients with BD in the genome data may cause our study to be underpowered when searching for putative rare mutations.

CONCLUSION

This study first combined a WES approach and neuroimaging findings in psychiatric disorders. We postulate the rs4639425 may be associated with BD-related microstructural changes of white matter tracts.

Genetic risk for bipolar disorder and psychopathology from childhood to early adulthood

BACKGROUND

Studying the phenotypic manifestations of increased genetic liability for Bipolar Disorder (BD) can increase understanding of this disorder.

AIMS

We assessed whether genetic risk for BD was associated with childhood psychopathology and features of hypomania in young adulthood within a large population-based birth cohort.

METHODS

We used data from the second Psychiatric Genetics Consortium Genome Wide Association Study (GWAS) for Bipolar Disorder to construct a polygenic risk score (PRS) for each individual in the Avon Longitudinal Study of Parents and Children (ALSPAC). Linear and logistic regression models were used to assess associations between the BD-PRS and emotional/behavioural difficulties, attention deficit hyperactivity disorder (ADHD) and borderline personality disorder (BPD) traits in childhood, as well as hypomania in early adulthood (sample sizes from 2654 to 6111).

RESULTS

The BD-PRS was not associated with total hypomania score, but was weakly associated with a binary measure of hypomania (OR = 1.13, 95%CI 0.98,1.32; p = 0.097), and particularly at higher hypomania symptom thresholds (strongest evidence OR = 1.33, 95%CI 1.07, 1.65; p = 0.01). The BD-PRS was also associated with ADHD (OR = 1.31, 95%CI 1.10, 1.57; p = 0.018), but not with other childhood psychopathology.

LIMITATIONS

The PRS only captures common genetic variation and currently explains a relatively small proportion of the variance for BD.

CONCLUSIONS

The BD-PRS was associated with ADHD in childhood, and weakly with adult hypomania, but not with other psychopathology examined. Our findings suggest that genetic risk for BD does not appear to manifest in childhood to the same extent as schizophrenia genetic risk has been reported to do.

Investigating polygenic burden in age at disease onset in bipolar disorder: Findings from an international multicentric study

OBJECTIVES

Bipolar disorder (BD) with early disease onset is associated with an unfavorable clinical outcome and constitutes a clinically and biologically homogenous subgroup within the heterogeneous BD spectrum. Previous studies have found an accumulation of early age at onset (AAO) in BD families and have therefore hypothesized that there is a larger genetic contribution to the early-onset cases than to late onset BD. To investigate the genetic background of this subphenotype, we evaluated whether an increased polygenic burden of BD- and schizophrenia (SCZ)-associated risk variants is associated with an earlier AAO in BD patients.

METHODS

A total of 1995 BD type 1 patients from the Consortium of Lithium Genetics (ConLiGen), PsyCourse and Bonn-Mannheim samples were genotyped and their BD and SCZ polygenic risk scores (PRSs) were calculated using the summary statistics of the Psychiatric Genomics Consortium as a training data set. AAO was either separated into onset groups of clinical interest (childhood and adolescence [≤18 years] vs adulthood [>18 years]) or considered as a continuous measure. The associations between BD- and SCZ-PRSs and AAO were evaluated with regression models.

RESULTS

BD- and SCZ-PRSs were not significantly associated with age at disease onset. Results remained the same when analyses were stratified by site of recruitment.

CONCLUSIONS

The current study is the largest conducted so far to investigate the association between the cumulative BD and SCZ polygenic risk and AAO in BD patients. The reported negative results suggest that such a polygenic influence, if there is any, is not large, and highlight the importance of conducting further, larger scale studies to obtain more information on the genetic architecture of this clinically relevant phenotype.

The use of polygenic risk scores to identify phenotypes associated with genetic risk of bipolar disorder and depression: A systematic review

BACKGROUND

Identifying the phenotypic manifestations of increased genetic liability for depression (MDD) and bipolar disorder (BD) can enhance understanding of their aetiology. The polygenic risk score (PRS) derived using data from genome-wide-association-studies can be used to explore how genetic risk is manifest in different samples.

AIMS

In this systematic review, we review studies that examine associations between the MDD and BD polygenic risk scores and phenotypic outcomes.

METHODS

Following PRISMA guidelines, we searched EMBASE, Medline and PsycINFO (from August 2009 - 14th March 2016) and references of included studies. Study inclusion was based on predetermined criteria and data were extracted independently and in duplicate.

RESULTS

Twenty-five studies were included. Overall, both polygenic risk scores were associated with other psychiatric disorders (not the discovery sample disorder) such as depression, schizophrenia and bipolar disorder, greater symptom severity of depression, membership of a creative profession and greater educational attainment. Both depression and bipolar polygenic risk scores explained small amounts of variance in most phenotypes (< 2%).

LIMITATIONS

Many studies did not report standardised effect sizes. This prevented us from conducting a meta-analysis.

CONCLUSIONS

Polygenic risk scores for BD and MDD are associated with a range of phenotypes and outcomes. However, they only explain a small amount of the variation in these phenotypes. Larger discovery and adequately powered target samples are required to increase power of the PRS approach. This could elucidate how genetic risk for bipolar disorder and depression is manifest and contribute meaningfully to stratified medicine.

Personalized management of bipolar disorder

Bipolar disorder (BD) is one of the most serious psychiatric disorders. The rates of disability, the risk of suicide attempts and their high lethality, as well as frequent and severe psychiatric and medical comorbidities, put it among the major causes of mortality and disability worldwide. At the same time, many patients can do well when treated properly. In this review, we focus on those aspects of the clinical care that offer the potential of individualized approach, in the context of the recent technology driven advances in the comprehension of the neurobiological underpinnings of BD. We first review those clinical and biological factors that can help identifying individuals at high risk of developing BD. Among these are a family history of BD and/or completed suicide, prodromal symptoms (in childhood and/or adolescence) such as anxiety and mood lability, early onset, and poor response to antidepressants. Panels of genetic markers are also being studied to identify subjects at risk for BD. Further, neuroimaging studies have found an increased gray matter density in the right Inferior Frontal Gyrus (rIFG) as a possible risk marker of BD. We then examine clinical factors that influence the initiation, selection and possibly discontinuation of long-term treatment. Lastly, we discuss the risk of side effects in BD, and their relevance for treatment adherence and for treatment monitoring. In summary, we discuss how a personalized approach in BD can be implemented through the identification of specific clinical and molecular predictors. We show that the realization of a personalized management of BD is not only of a theoretical value, but has substantial clinical repercussions, resulting in a significant reduction of the long-term morbidity and mortality associated to BD.

Identification of Susceptible Loci and Enriched Pathways for Bipolar II Disorder Using Genome-Wide Association Studies

BACKGROUND

This study aimed to identify susceptible loci and enriched pathways for bipolar disorder subtype II.

METHODS

We conducted a genome-wide association scan in discovery samples with 189 bipolar disorder subtype II patients and 1773 controls, and replication samples with 283 bipolar disorder subtype II patients and 500 controls in a Taiwanese Han population using Affymetrix Axiom Genome-Wide CHB1 Array. We performed single-marker and gene-based association analyses, as well as calculated polygeneic risk scores for bipolar disorder subtype II. Pathway enrichment analyses were employed to reveal significant biological pathways.

RESULTS

Seven markers were found to be associated with bipolar disorder subtype II in meta-analysis combining both discovery and replication samples (P<5.0×10^-6), including markers in or close to MYO16, HSP90AB3P, noncoding gene LOC100507632, and markers in chromosomes 4 and 10. A novel locus, ETF1, was associated with bipolar disorder subtype II (P<6.0×10^-3) in gene-based association tests. Results of risk evaluation demonstrated that higher genetic risk scores were able to distinguish bipolar disorder subtype II patients from healthy controls in both discovery (P=3.9×10^-4~1.0×10^-3) and replication samples (2.8×10^-4~1.7×10^-3). Genetic variance explained by chip markers for bipolar disorder subtype II was substantial in the discovery (55.1%) and replication (60.5%) samples. Moreover, pathways related to neurodevelopmental function, signal transduction, neuronal system, and cell adhesion molecules were significantly associated with bipolar disorder subtype II.

CONCLUSION

We reported novel susceptible loci for pure bipolar subtype II disorder that is less addressed in the literature. Future studies are needed to confirm the roles of these loci for bipolar disorder subtype II.