Association of schizophrenia polygenic risk score with manic and depressive psychosis in bipolar disorder

Differential serum levels of CACNA1C, circadian rhythm and stress response molecules in subjects with bipolar disorder: Associations with genetic and clinical factors

BACKGROUND

Many patients with bipolar disorder (BD) do not respond to or have difficulties tolerating lithium and/or other mood stabilizing agents. There is a need for personalized treatments based on biomarkers in guiding treatment options. The calcium voltage-gated channel CACNA1C is a promising candidate for developing personalized treatments. CACNA1C is implicated in BD by genome-wide association studies and several lines of evidence suggest that targeting L-type calcium channels could be an effective treatment strategy. However, before such individualized treatments can be pursued, biomarkers predicting treatment response need to be developed.

METHODS

As a first step in testing the hypothesis that CACNA1C genotype is associated with serum levels of CACNA1C, we conducted ELISA measures on serum samples from 100 subjects with BD and 100 control subjects.

RESULTS

We observed significantly higher CACNA1C (p < 0.01) protein levels in subjects with BD. The risk single nucleotide polymorpshism (SNP) (rs11062170) showed functional significance as subjects homozygous for the risk allele (CC) had significantly greater CACNA1C protein levels compared to subjects with one (p = 0.013) or no copies (p = 0.009). We observed higher somatostatin (SST) (p < 0.003) protein levels and lower levels of the clock protein aryl hydrocarbon receptor nuclear translocator-like (ARTNL) (p < 0.03) and stress signaling factor corticotrophin releasing hormone (CRH) (p < 0.001) in BD. SST and period 2 (PER2) protein levels were associated with both alcohol dependence and lithium response.

CONCLUSIONS

Our findings represent the first evidence for increased serum levels of CACNA1C in BD. Along with altered levels of SST, ARNTL, and CRH our findings suggest CACNA1C is associated with circadian rhythm and stress response disturbances in BD.

Association of prescription data with clinical manifestations and polygenic risk scores in patients with bipolar I disorder: An exploratory study

BACKGROUND

We assessed the association of prescription data with clinical manifestations and polygenic risk scores (PRS) in patients with bipolar I disorder.

METHODS

We enrolled 1471 individuals with BID and divided them into several groups according to treatment options and clinical manifestations. BD-PRS of each patient was calculated using the Psychiatric Genomics Consortium data. Data on single nucleotide polymorphisms, clinical manifestations, and prescriptions were extracted from BiGS.

RESULTS

Chronicity, suicidality, substance misuse, mixed symptoms, and deterioration of life functioning were significantly more severe in the group that was not prescribed any mood stabilizers (MS). Chronicity, psychotic symptoms, suicidality, and deterioration of life functioning were significantly severe in the group that received two or more antipsychotics (APs). BD-PRS between the group with AP(s) only and that with other treatment options significantly differed. BD-PRS of the group with AP(s) only was significantly lower than that with other treatment options. Our linear regression results showed that high severity of particular clinical aspects, lower BD-PRS, and prescriptions with fewer MSs or more APs were independently associated with poor life functioning.

LIMITATIONS

This study had a cross-sectional design, without differentiating the bipolar phase, which could influence our results.

CONCLUSIONS

Poor life functioning in patients with BID was associated with a high severity of particular clinical aspects, BD-PRS, and prescriptions including fewer MSs or more APs. BD-PRS was significantly higher in the group receiving only AP(s) than that in the groups receiving other drugs.

Heterogeneity analysis provides evidence for a genetically homogeneous subtype of bipolar-disorder

Bipolar Disorder (BD) is a complex disease. It is heterogeneous, both at the phenotypic and genetic level, although the extent and impact of this heterogeneity is not fully understood. In this paper, we leverage recent advances in heterogeneity analysis to look for genetically-driven subgroups (i.e., biclusters) within the broad phenotype of Bipolar Disorder. We first apply this covariate-corrected biclustering algorithm to a cohort of 2524 BD cases and 4106 controls from the Bipolar Disease Research Network (BDRN) within the Psychiatric Genomics Consortium (PGC). We find evidence of genetic heterogeneity delineating a statistically significant bicluster comprising a subset of BD cases which exhibits a disease-specific pattern of differential-expression across a subset of SNPs. This disease-specific genetic pattern (i.e., 'genetic subgroup') replicates across the remaining data-sets collected by the PGC containing 5781/8289, 3581/7591, and 6825/9752 cases/controls, respectively. This genetic subgroup (discovered without using any BD subtype information) was more prevalent in Bipolar type-I than in Bipolar type-II. Our methodology has successfully identified a replicable homogeneous genetic subgroup of bipolar disorder. This subgroup may represent a collection of correlated genetic risk-factors for BDI. By investigating the subgroup's bicluster-informed polygenic-risk-scoring (PRS), we find that the disease-specific pattern highlighted by the bicluster can be leveraged to eliminate noise from our GWAS analyses and improve risk prediction. This improvement is particularly notable when using only a relatively small subset of the available SNPs, implying improved SNP replication. Though our primary focus is only the analysis of disease-related signal, we also identify replicable control-related heterogeneity.

Functional network characteristics in anxiety- and mania-based subgroups of bipolar I disorder

BACKGROUND

Bipolar disorder I (BD-I) is a heterogeneous disorder with a high prevalence of comorbid anxiety. The aim of this study was to investigate whether anxiety and mania symptoms define distinct subgroups within BD-I and to explore potential differences in functional network characteristics between these subgroups.

METHODS

Subgroups were identified using scores from clinical anxiety and mania scales. After dimension reduction of these scores, data-driven clustering analysis with cross-validation was employed to reveal the existence of subgroups. Resting-state functional magnetic resonance imaging (rs-fMRI) scans were pre-processed using fMRIPrep. After parcellation and network construction, global and regional graph theoretical measures were calculated per subgroup.

RESULTS

Clustering results revealed that, based on anxiety symptomatology, subjects fell into two distinct subgroups, whereas mania symptoms divided subjects into four unique subgroups. These subgroups varied notably on several symptom scales. Network assortativity was significantly associated with anxiety subgroups. Post-hoc pairwise comparisons did not reveal significant global functional network differences between the anxiety subgroups or between mania subgroups. Regional network differences between clinical subgroups were especially apparent for strength and degree in the temporal and frontal lobes.

LIMITATIONS

Small sample size of some subgroups is a limitation of this study as is the categorical rather than continuous representation of anxiety and mania symptoms.

CONCLUSIONS

BD-I populations may be stratified into robust subgroups based on anxiety and mania symptoms, showing differences in functional network connectivity. Our findings highlight new avenues of research for investigating heterogeneity in psychiatric populations.

Serum signature of antibodies to Toxoplasma gondii, rubella virus, and cytomegalovirus in females with bipolar disorder: A cross-sectional study

BACKGROUND AND AIM

Immunity alterations have been observed in bipolar disorder (BD). However, whether serum positivity of antibodies to Toxoplasma gondii (T gondii), rubella, and cytomegalovirus (CMV) shared clinical relevance with BD, remains controversial. This study aimed to investigate this association.

METHODS

Antibody seropositivity of IgM and IgG to T gondii, rubella virus, and CMV of females with BD and controls was extracted based on medical records from January 2018 to January 2023. Family history, type of BD, onset age, and psychotic symptom history were also collected.

RESULTS

585 individuals with BD and 800 healthy controls were involved. Individuals with BD revealed a lower positive rate of T gondii IgG in the 10-20 aged group (OR = 0.10), and a higher positive rate of rubella IgG in the 10-20 (OR = 5.44) and 20-30 aged group (OR = 3.15). BD with family history preferred a higher positive rate of T gondii IgG (OR = 24.00). Type-I BD owned a decreased positive rate of rubella IgG (OR = 0.37) and an elevated positive rate of CMV IgG (OR = 2.12) compared to type-II BD, while BD with early onset showed contrast results compared to BD without early onset (Rubella IgG, OR = 2.54; CMV IgG, OR = 0.26). BD with psychotic symptom history displayed a lower positive rate of rubella IgG (OR = 0.50).

LIMITATIONS

Absence of male evidence and control of socioeconomic status and environmental exposure.

CONCLUSIONS

Differential antibody seropositive rates of T gondii, rubella, and cytomegalovirus in BD were observed.

Progress and Implications from Genetic Studies of Bipolar Disorder

With the advancements in gene sequencing technologies, including genome-wide association studies, polygenetic risk scores, and high-throughput sequencing, there has been a tremendous advantage in mapping a detailed blueprint for the genetic model of bipolar disorder (BD). To date, intriguing genetic clues have been identified to explain the development of BD, as well as the genetic association that might be applied for the development of susceptibility prediction and pharmacogenetic intervention. Risk genes of BD, such as CACNA1C, ANK3, TRANK1, and CLOCK, have been found to be involved in various pathophysiological processes correlated with BD. Although the specific roles of these genes have yet to be determined, genetic research on BD will help improve the prevention, therapeutics, and prognosis in clinical practice. The latest preclinical and clinical studies, and reviews of the genetics of BD, are analyzed in this review, aiming to summarize the progress in this intriguing field and to provide perspectives for individualized, precise, and effective clinical practice.

Exploring intra-diagnosis heterogeneity and inter-diagnosis commonality in genetic architectures of bipolar disorders: association of polygenic risks of major psychiatric illnesses and lifetime phenotype dimensions

BACKGROUND

Bipolar disorder (BD) shows heterogeneous illness presentation both cross-sectionally and longitudinally. This phenotypic heterogeneity might reflect underlying genetic heterogeneity. At the same time, overlapping characteristics between BD and other psychiatric illnesses are observed at clinical and biomarker levels, which implies a shared biological mechanism between them. Incorporating these two issues in a single study design, this study investigated whether phenotypically heterogeneous subtypes of BD have a distinct polygenic basis shared with other psychiatric illnesses.

METHODS

Six lifetime phenotype dimensions of BD identified in our previous study were used as target phenotypes. Associations between these phenotype dimensions and polygenic risk scores (PRSs) of major psychiatric illnesses from East Asian (EA) and other available populations were analyzed.

RESULTS

Each phenotype dimension showed a different association pattern with PRSs of mental illnesses. PRS for EA schizophrenia showed a significant negative association with the cyclicity dimension (p = 0.044) but a significant positive association with the psychotic/irritable mania dimension (p = 0.001). PRS of EA major depressive disorder demonstrated a significant negative association with the elation dimension (p = 0.003) but a significant positive association with the comorbidity dimension (p = 0.028).

CONCLUSION

This study demonstrates that well-defined phenotype dimensions of lifetime-basis in BD have distinct genetic risks shared with other major mental illnesses. This finding supports genetic heterogeneity in BD and suggests a pleiotropy among BD subtypes and other psychiatric disorders beyond BD. Further genomic analyses adopting deep phenotyping across mental illnesses in ancestrally diverse populations are warranted to clarify intra-diagnosis heterogeneity and inter-diagnoses commonality issues in psychiatry.

Differential Serum Levels of CACNA1C, Circadian Rhythm and Stress Response Molecules in Subjects with Bipolar Disorder: Associations with Genetic and Clinical Factors

Background

Many patients with bipolar disorder (BD) do not respond to or have difficulties tolerating lithium and/or other mood stabilizing agents. There is a need for personalized treatments based on biomarkers in guiding treatment options. The calcium voltage-gated channel CACNA1C is a promising candidate for developing personalized treatments. CACNA1C is implicated in BD by genome-wide association studies and several lines of evidence suggest that targeting L-type calcium channels could be an effective treatment strategy. However, before such individualized treatments can be pursued, biomarkers predicting treatment response need to be developed.

Methods

As a first step in testing the hypothesis that CACNA1C genotype is associated with serum levels of CACNA1C, we conducted ELISA measures on serum samples from 100 subjects with BD and 100 control subjects.

Results

We observed significantly higher CACNA1C (p<0.01) protein levels in subjects with BD. The risk SNP (rs11062170) showed functional significance as subjects homozygous for the risk allele (CC) had significantly greater CACNA1C protein levels compared to subjects with one (p=0.013) or no copies (p=0.009). We observed higher somatostatin (SST) (p<0.003) protein levels and lower levels of the clock protein ARTNL (p<0.03) and stress signaling factor corticotrophin releasing hormone (CRH) (p<0.001) in BD. SST and PER2 protein levels were associated with both alcohol dependence and lithium response.

Conclusions

Our findings represent the first evidence for increased serum levels of CACNA1C in BD. Along with altered levels of SST, ARNTL, and CRH our findings suggest CACNA1C is associated with circadian rhythm and stress response disturbances in BD.

Dissecting the impact of complement component 4A in bipolar disorder

The genetic overlap between schizophrenia (SZ) and bipolar disorder (BD) is substantial. Polygenic risk scores have been shown to dissect different symptom dimensions within and across these two disorders. Here, we focused on the most strongly associated SZ risk locus located in the extended MHC region, which is largely explained by copy numbers of the gene coding for complement component 4A (C4A). First, we utilized existing brain tissue collections (N = 1,202 samples) and observed no altered C4A expression in BD samples. The generated C4A seeded co-expression networks displayed no genetic enrichment for BD. To study if genetically predicted C4A expression discriminates between subphenotypes of BD, we applied C4A expression scores to symptom dimensions in a total of 4,739 BD cases with deep phenotypic data. We identified a significant association between C4A expression and psychotic mood episodes in BD type 1 (BDI). No significant association was observed between C4A expression and the occurrence of non-affective psychotic episodes in BDI, the psychosis dimensions in the total BD sample, or any other subphenotype of BD. Overall, these results points to a distinct role of C4A in BD that is restricted to vulnerability for developing psychotic symptoms during mood episodes in BDI.

The Nature of the Familial Risk for Psychosis in Bipolar Disorder

BACKGROUND AND HYPOTHESIS

To clarify whether the familial liability to psychosis associated with bipolar disorder (BD) is nonspecific or has a greater effect on risk for psychosis in cases with prominent mood symptoms and/or a remitting course.

STUDY DESIGN

We examined, in 984 809 offspring raised in intact families in Sweden, born 1980-1996 and followed-up through 2018, by multivariable Cox proportional hazards regression, risk in offspring of parents with BD for 7 psychotic disorders: Psychotic MD (PMD), psychotic BD (PBD), schizoaffective disorder (SAD), acute psychoses, psychosis NOS, delusional disorder (DD) and schizophrenia (SZ). Diagnoses were obtained from national registers.

STUDY RESULTS

In the offspring of BD parents, the hazard ratios (HR) for these 7 disorders formed an inverted U-shaped curve, rising from 2.98 for PMD, to peak at 4.49 for PBD and 5.25 for SAD, and then declining to a HR of 3.48 for acute psychoses and 3.22 for psychosis NOS, to a low of 2.19 for DD and 2.33 for SZ. A similar pattern of risks was seen in offspring of mothers and fathers affected with BD and in offspring predicted from age at onset in their BD parent.

CONCLUSIONS

The BD-associated risk for psychosis impacts most strongly on mood disorders, moderately on episodic psychotic syndromes, and least on chronic psychotic disorders. These results support prior clinical studies suggesting a qualitative difference in the familial substrate for psychosis occurring in BD and SZ.

Geographical variation in treated psychotic and other mental disorders in Finland by region and urbanicity

PURPOSE

In Finland, prevalence of schizophrenia is higher in the eastern and northern regions and co-occurs with the distribution of schizophrenia polygenic risk scores. Both genetic and environmental factors have been hypothesized to contribute to this variation. We aimed to examine the prevalence of psychotic and other mental disorders by region and degree of urbanicity, and the impacts of socio-economic adjustments on these associations.

METHODS

Nationwide population registers from 2011 to 2017 and healthcare registers from 1975 to 2017. We used 19 administrative and three aggregate regions based on the distribution of schizophrenia polygenic risk scores, and a seven-level urban-rural classification. Prevalence ratios (PRs) were calculated by Poisson regression models and adjusted for gender, age, and calendar year (basic adjustments), and Finnish origin, residential history, urbanicity, household income, economic activity, and physical comorbidity (additional adjustments) on an individual level. Average marginal effects were used to visualize interaction effects between region and urbanicity.

RESULTS

A total of 5,898,180 individuals were observed. All mental disorders were slightly more prevalent (PR 1.03 [95% CI, 1.02-1.03]), and psychotic disorders (1.11 [1.10-1.12]) and schizophrenia (1.19 [1.17-1.21]) considerably more prevalent in eastern and northern than in western coastal regions. After the additional adjustments, however, the PRs were 0.95 (0.95-0.96), 1.00 (0.99-1.01), and 1.03 (1.02-1.04), respectively. Urban residence was associated with increased prevalence of psychotic disorders across all regions (adjusted PR 1.21 [1.20-1.22]).

CONCLUSION

After adjusting for socioeconomic and sociodemographic factors, the within-country distribution of mental disorders no longer followed the traditional east-west gradient. Urban-rural differences, on the other hand, persisted after the adjustments.

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.

Improve the model of disease subtype heterogeneity by leveraging external summary data

Researchers are often interested in understanding the disease subtype heterogeneity by testing whether a risk exposure has the same level of effect on different disease subtypes. The polytomous logistic regression (PLR) model provides a flexible tool for such an evaluation. Disease subtype heterogeneity can also be investigated with a case-only study that uses a case-case comparison procedure to directly assess the difference between risk effects on two disease subtypes. Motivated by a large consortium project on the genetic basis of non-Hodgkin lymphoma (NHL) subtypes, we develop PolyGIM, a procedure to fit the PLR model by integrating individual-level data with summary data extracted from multiple studies under different designs. The summary data consist of coefficient estimates from working logistic regression models established by external studies. Examples of the working model include the case-case comparison model and the case-control comparison model, which compares the control group with a subtype group or a broad disease group formed by merging several subtypes. PolyGIM efficiently evaluates risk effects and provides a powerful test for disease subtype heterogeneity in situations when only summary data, instead of individual-level data, is available from external studies due to various informatics and privacy constraints. We investigate the theoretic properties of PolyGIM and use simulation studies to demonstrate its advantages. Using data from eight genome-wide association studies within the NHL consortium, we apply it to study the effect of the polygenic risk score defined by a lymphoid malignancy on the risks of four NHL subtypes. These results show that PolyGIM can be a valuable tool for pooling data from multiple sources for a more coherent evaluation of disease subtype heterogeneity.

Use of multiple polygenic risk scores for distinguishing schizophrenia-spectrum disorder and affective psychosis categories in a first-episode sample; the EU-GEI study

BACKGROUND

Schizophrenia (SZ), bipolar disorder (BD) and depression (D) run in families. This susceptibility is partly due to hundreds or thousands of common genetic variants, each conferring a fractional risk. The cumulative effects of the associated variants can be summarised as a polygenic risk score (PRS). Using data from the EUropean Network of national schizophrenia networks studying Gene-Environment Interactions (EU-GEI) first episode case-control study, we aimed to test whether PRSs for three major psychiatric disorders (SZ, BD, D) and for intelligent quotient (IQ) as a neurodevelopmental proxy, can discriminate affective psychosis (AP) from schizophrenia-spectrum disorder (SSD).

METHODS

Participants (842 cases, 1284 controls) from 16 European EU-GEI sites were successfully genotyped following standard quality control procedures. The sample was stratified based on genomic ancestry and analyses were done only on the subsample representing the European population (573 cases, 1005 controls). Using PRS for SZ, BD, D, and IQ built from the latest available summary statistics, we performed simple or multinomial logistic regression models adjusted for 10 principal components for the different clinical comparisons.

RESULTS

In case-control comparisons PRS-SZ, PRS-BD and PRS-D distributed differentially across psychotic subcategories. In case-case comparisons, both PRS-SZ [odds ratio (OR) = 0.7, 95% confidence interval (CI) 0.54-0.92] and PRS-D (OR = 1.31, 95% CI 1.06-1.61) differentiated AP from SSD; and within AP categories, only PRS-SZ differentiated BD from psychotic depression (OR = 2.14, 95% CI 1.23-3.74).

CONCLUSIONS

Combining PRS for severe psychiatric disorders in prediction models for psychosis phenotypes can increase discriminative ability and improve our understanding of these phenotypes. Our results point towards the potential usefulness of PRSs in specific populations such as high-risk or early psychosis phases.

Pharmacotherapy exposure as a marker of disease complexity in bipolar disorder: Associations with clinical & genetic risk factors

Individuals with bipolar disorder (BD) require chronic pharmacotherapy, typically including medication switches or polypharmacy due to persisting symptoms or intolerable side effects. Here, we quantified pharmacotherapy exposure (PE) of Mayo Clinic BD Biobank participants using the number of cross-sectional (at enrollment) and lifetime BD-specific medications and medication classes, to understand the relationship between PE and markers of disease severity or treatment failure, psychiatric comorbidities, and polygenic risk scores (PRS) for six major psychiatric disorders. Being female (p < 0.05), older (p < 0.01), having history of suicide attempts (p < 0.0001), and comorbid attention-deficit/hyperactivity disorder (p < 0.05) or generalized anxiety disorder (p < 0.05) were uniformly associated with higher PE. Lifetime exposure to unique medication classes among participants with BD-I was significantly lower than for those with schizoaffective disorder (estimate = -2.1, p < 0.0001) while significantly higher than for those with BD-II (estimate = 0.5, p < 0.01). Further, higher PRS for schizophrenia (SCZ) and anxiety resulted in greater lifetime medication counts (p < 0.01), both driven by antipsychotic (p < 0.001) and anxiolytic use (p < 0.05). Our results provide initial evidence of the utility of PE as a measure of disease complexity or treatment resistance, and that PE may be predicted by higher genetic risk for SCZ and anxiety.

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.

Linking nervous and immune systems in psychiatric illness: A meta-analysis of the kynurenine pathway

Tryptophan is an essential amino acid absorbed by the gut depending on a homoeostatic microbiome. Up to 95% of unbound tryptophan is converted into tryptophan catabolites (TRYCATs) through the kynurenine system. Recent studies identified conflicting associations between altered levels of TRYCATs and genetic polymorphisms in major depressive disorder (MDD), schizophrenia (SCZ), and bipolar disorder (BD). This meta-analysis aimed to understand how tryptophan catabolic pathways are altered in MDD, SCZ, and BD. When compared to healthy controls, participants with MDD had moderately lower levels of tryptophan associated with a moderate increase of kynurenine/tryptophan ratios and no differences in kynurenine. While significant differences were found in SCZ for any of the TRYCATs, studies on kynurenic acid found opposing directions of effect sizes depending on the sample source. Unique changes in levels of TRYCATs were also observed in BD. Dynamic changes in levels of cytokines and other immune/inflammatory elements modulate the transcription and activity of kynurenine system enzymes, which lastly seems to be impacting glutamatergic neurotransmission via N-methyl-D-aspartate and α-7 nicotine receptors.

Diurnal Alterations in Gene Expression Across Striatal Subregions in Psychosis

BACKGROUND

Psychosis is a defining feature of schizophrenia and highly prevalent in bipolar disorder. Notably, individuals with these illnesses also have major disruptions in sleep and circadian rhythms, and disturbances of sleep and circadian rhythms can precipitate or exacerbate psychotic symptoms. Psychosis is associated with the striatum, though to our knowledge, no study to date has directly measured molecular rhythms and determined how they are altered in the striatum of subjects with psychosis.

METHODS

We performed RNA sequencing and both differential expression and rhythmicity analyses to investigate diurnal alterations in gene expression in human postmortem striatal subregions (nucleus accumbens, caudate, and putamen) in subjects with psychosis (n = 36) relative to unaffected comparison subjects (n = 36).

RESULTS

Across regions, we found differential expression of immune-related transcripts and a substantial loss of rhythmicity in core circadian clock genes in subjects with psychosis. In the nucleus accumbens, mitochondrial-related transcripts had decreased expression in subjects with psychosis, but only in those who died at night. Additionally, we found a loss of rhythmicity in small nucleolar RNAs and a gain of rhythmicity in glutamatergic signaling in the nucleus accumbens of subjects with psychosis. Between-region comparisons indicated that rhythmicity in the caudate and putamen was far more similar in subjects with psychosis than in matched comparison subjects.

CONCLUSIONS

Together, these findings reveal differential and rhythmic gene expression differences across the striatum that may contribute to striatal dysfunction and psychosis in psychotic disorders.

Psychotic symptoms in bipolar disorder and their impact on the illness: A systematic review

BACKGROUND

Lifetime psychotic symptoms are present in over half of the patients with bipolar disorder (BD) and can have an adverse effect on its course, outcome, and treatment. However, despite a considerable amount of research, the impact of psychotic symptoms on BD remains unclear, and there are very few systematic reviews on the subject.

AIM

To examine the extent of psychotic symptoms in BD and their impact on several aspects of the illness.

METHODS

The Preferred Reporting Items for Systematic Reviews and Meta-analyses guidelines were followed. An electronic literature search of six English-language databases and a manual search was undertaken to identify published articles on psychotic symptoms in BD from January 1940 to December 2021. Combinations of the relevant Medical Subject Headings terms were used to search for these studies. Articles were selected after a screening phase, followed by a review of the full texts of the articles. Assessment of the methodological quality of the studies and the risk of bias was conducted using standard tools.

RESULTS

This systematic review included 339 studies of patients with BD. Lifetime psychosis was found in more than a half to two-thirds of the patients, while current psychosis was found in a little less than half of them. Delusions were more common than hallucinations in all phases of BD. About a third of the patients reported first-rank symptoms or mood-incongruent psychotic symptoms, particularly during manic episodes. Psychotic symptoms were more frequent in bipolar type I compared to bipolar type II disorder and in mania or mixed episodes compared to bipolar depression. Although psychotic symptoms were not more severe in BD, the severity of the illness in psychotic BD was consistently greater. Psychosis was usually associated with poor insight and a higher frequency of agitation, anxiety, and hostility but not with psychiatric comorbidity. Psychosis was consistently linked with increased rates and the duration of hospitalizations, switching among patients with depression, and poorer outcomes with mood-incongruent symptoms. In contrast, psychosis was less likely to be accompanied by a rapid-cycling course, longer illness duration, and heightened suicidal risk. There was no significant impact of psychosis on the other parameters of course and outcome.

CONCLUSION

Though psychotic symptoms are very common in BD, they are not always associated with an adverse impact on BD and its course and outcome.

Diagnostic progression to schizophrenia in 35,255 patients with obsessive-compulsive disorder: a longitudinal follow-up study

Evidence suggests a continuity between obsessive-compulsive disorder (OCD) and schizophrenia. However, the factors that may predict diagnostic progression from OCD to schizophrenia remain unclear. A total of 35,255 adolescents and adults with OCD (ICD-9-CM code: 300.3) were enrolled between 2001 and 2010 and followed up at the end of 2011 for the identification of de novo schizophrenia (ICD-9-CM code: 295). The Kaplan-Meier method was used to estimate incidence rates, and the Cox regression was used to determine the significance of candidate predictors. At the end of the 11-year follow-up period, the crude cumulative progression rate from OCD to schizophrenia was 6%, and the estimated progression rate totaled 7.80%. Male sex (hazard ratio: 1.23), obesity (1.77), autism spectrum disorder (1.69), bipolar disorder (1.69), posttraumatic stress disorder (1.65), cluster A personality disorder (2.50), and a family history of schizophrenia (2.57) also were related to an elevated likelihood of subsequent progression to schizophrenia in patients with OCD. Further study is necessary to elucidate the exact pathomechanisms underlying diagnostic progression to schizophrenia in patients with OCD.

Associations between cognition and subsequent mood episodes in patients with bipolar disorder and their unaffected relatives: A systematic review

BACKGROUND

Bipolar disorder (BD) is highly recurrent and prevention of relapse and illness onset is an urgent treatment priority. This systematic review examined whether cognitive assessments can aid prediction of recurrence in patients with BD and/or illness onset in individuals at familial risk.

METHODS

The review included longitudinal studies of patients with BD or individuals at familial risk of mood disorder that examined the association between cognitive functions and subsequent relapse or illness onset, respectively. We followed the procedures of the Preferred Reporting Items for Systematic reviews and Meta-Analysis (PRISMA) 2020 statement. Searches were conducted on PubMed/MEDLINE, EMBASE and PsychInfo databases from inception up until May 10th 2021.

RESULTS

We identified 19 eligible studies; 12 studies investigated cognitive predictors of recurrence in BD (N = 36-76) and seven investigated cognitive predictors of illness onset in at-risk individuals (N = 84-234). In BD, general cognitive impairment, poorer verbal memory and executive function and positive bias were associated with subsequent (hypo)manic relapse -but with not depressive relapse or mood episodes in general. In first-degree relatives, impairments in attention, verbal memory and executive functions and positive bias were associated with subsequent illness onset.

LIMITATIONS

The findings should be considered preliminary given the small-to-moderate sample sizes and scarcity of studies.

CONCLUSIONS

Subject to replication, the associations between cognitive impairment and (hypo)mania relapse and illness onset may provide a platform for personalised treatment and prophylactic strategies.

Association of Attention-Deficit/Hyperactivity Disorder and Depression Polygenic Scores with Lithium Response: A Consortium for Lithium Genetics Study

Response to lithium varies widely between individuals with bipolar disorder (BD). Polygenic risk scores (PRSs) can uncover pharmacogenomics effects and may help predict drug response. Patients (N = 2,510) with BD were assessed for long-term lithium response in the Consortium on Lithium Genetics using the Retrospective Criteria of Long-Term Treatment Response in Research Subjects with Bipolar Disorder score. PRSs for attention-deficit/hyperactivity disorder (ADHD), major depressive disorder (MDD), and schizophrenia (SCZ) were computed using lassosum and in a model including all three PRSs and other covariates, and the PRS of ADHD (β = -0.14; 95% confidence interval [CI]: -0.24 to -0.03; p value = 0.010) and MDD (β = -0.16; 95% CI: -0.27 to -0.04; p value = 0.005) predicted worse quantitative lithium response. A higher SCZ PRS was associated with higher rates of medication nonadherence (OR = 1.61; 95% CI: 1.34-1.93; p value = 2e-7). This study indicates that genetic risk for ADHD and depression may influence lithium treatment response. Interestingly, a higher SCZ PRS was associated with poor adherence, which can negatively impact treatment response. Incorporating genetic risk of ADHD, depression, and SCZ in combination with clinical risk may lead to better clinical care for patients with BD.

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.

Genetic contributions to bipolar disorder: current status and future directions

Bipolar disorder (BD) is a highly heritable mental disorder and is estimated to affect about 50 million people worldwide. Our understanding of the genetic etiology of BD has greatly increased in recent years with advances in technology and methodology as well as the adoption of international consortiums and large population-based biobanks. It is clear that BD is also highly heterogeneous and polygenic and shows substantial genetic overlap with other psychiatric disorders. Genetic studies of BD suggest that the number of associated loci is expected to substantially increase in larger future studies and with it, improved genetic prediction of the disorder. Still, a number of challenges remain to fully characterize the genetic architecture of BD. First among these is the need to incorporate ancestrally-diverse samples to move research away from a Eurocentric bias that has the potential to exacerbate health disparities already seen in BD. Furthermore, incorporation of population biobanks, registry data, and electronic health records will be required to increase the sample size necessary for continued genetic discovery, while increased deep phenotyping is necessary to elucidate subtypes within BD. Lastly, the role of rare variation in BD remains to be determined. Meeting these challenges will enable improved identification of causal variants for the disorder and also allow for equitable future clinical applications of both genetic risk prediction and therapeutic interventions.

Investigation of inflammation related gene polymorphism of the mannose-binding lectin 2 in schizophrenia and bipolar disorder

OBJECTIVES

To investigate the association between mannose-binding lectin 2 (MBL2) codon 54 polymorphism and clinical features of patients diagnosed with schizophrenia (SCZ) or bipolar disorder (BD).

METHODS

One hundred and eighteen patients with SCZ, 100 patients with BD, and 100 healthy volunteers were included in the case-control study. The patients consecutively admitted to the outpatient clinic in December 2017-May 2018 and were evaluated with some scales for clinical parameters. Polymerase chain reaction and RFLP were used to determine MBL2 polymorphism in DNA material.

RESULTS

The MBL2 gene polymorphism distributions in SCZ or BD patients were significantly different from the control group. The heterozygous genotype percentages were significantly higher in the control group than in the SCZ or BD patients (OR: 0.450; 95% Cl: 0.243-0.830; p=0.010; OR: 0.532; 95%Cl: 0.284-0.995; p=0.047, respectively), and there were statistically significant differences in the MBL2 polymorphism distributions between treatment-responsive SCZ or BD patients and treatment-resistant patients diagnosed with SCZ or BD. The heterozygous genotype percentages were also significantly higher in the treatment-responsive group than in the treatment-resistant group in SCZ or BD patients (OR: 7.857; 95% Cl: 1.006-61.363; p=0.023; OR: 8.782; 95% Cl: 1.114-69.197; p=0.016, respectively).

CONCLUSION

The presence of a heterozygous MBL2 genotype seems to be favorable both in terms of the absence of SCZ and BD in the healthy population and treatment response for Turkish patients.

Family Genetic Risk Scores and the Genetic Architecture of Major Affective and Psychotic Disorders in a Swedish National Sample

Importance

Family and genetic approaches have traditionally been used to evaluate our diagnostic concepts. Using a novel method, the family genetic risk score (FGRS), can we validate the genetic architecture of major affective and psychotic disorders in a national Swedish sample?

Objective

To determine whether FGRSs, calculated for the entire Swedish population, can elucidate the genetic relationship between major affective and psychotic disorders and clarify the association of genetic risk with important clinical features of disease.

Design, Setting, and Participants

This cohort study included the native Swedish population born from January 1, 1950, through December 31, 1995, and followed up through December 31, 2017. Data were collected from Swedish population-based primary care, specialist, and hospital registers, including age at first registration for a psychiatric diagnosis and number of registrations for major depression, bipolar disorder, and schizophrenia. Data were analyzed from October 15, 2020, to February 2, 2021.

Exposures

FGRSs for major depression, bipolar disorder, and schizophrenia calculated from morbidity risks for disorders in first- through fifth-degree relatives, controlling for cohabitation.

Main Outcomes and Measures

Diagnoses of major depression, bipolar disorder, schizophrenia, schizoaffective disorder, and other nonaffective psychoses (ONAPs), age at registration, and number of registrations for major depression, bipolar disorder, and schizophrenia. Diagnostic conversion of major depression to bipolar disorder and ONAPs to schizophrenia was assessed by Cox proportional hazards regression models.

Results

The cohort included 4 129 002 individuals (51.4% male) with a mean (SD) age at follow-up of 45.5 (13.4) years. Mean FGRSs for major depression, bipolar disorder, and schizophrenia produced distinct patterns for major depression, bipolar disorder, schizophrenia, schizoaffective disorder, and ONAPs with large separations between disorders. In major depression, bipolar disorder, and schizophrenia, high FGRSs were associated with early age at onset and high rates of recurrence: a high mean FGRS for bipolar disorder was associated with early age at onset (younger than 25 years, 0.11; 95% CI, 0.11-0.12) and higher recurrence (8 or more registrations, 0.11; 95% CI, 0.11-0.12) in major depression. The schizophrenia FGRS was separately associated with psychotic and nonpsychotic forms of major depression (0.10; 95% CI, 0.06-0.14 vs 0.03; 95% CI, 0.02-0.03) and bipolar disorder (0.22; 95% CI, 0.16-0.28 vs 0.11; 95% CI, 0.09-0.12). The bipolar disorder and schizophrenia FGRSs were associated with conversion from major depression to bipolar disorder (eg, hazard ratio, 1.70 [95% CI, 1.63-1.78] for high vs low bipolar FGRS) and ONAP to schizophrenia (eg, hazard ratio, 1.38 [95% CI, 1.27-1.51] for high vs low schizophrenia FGRS).

Conclusions and Relevance

In this Swedish cohort study, the FGRSs for major depression, bipolar disorder, and schizophrenia for the Swedish population clearly separated major affective and psychotic disorders from each other in a larger and more representative patient sample than previously possible. These findings provide possible validation, from a genetic perspective, for these major diagnostic categories. These results replicated and extended prior observations on more limited samples of the association of FGRS with age at onset, recurrence, psychotic subtypes, and diagnostic conversions.

Dissecting clinical heterogeneity of bipolar disorder using multiple polygenic risk scores

Bipolar disorder (BD) has high clinical heterogeneity, frequent psychiatric comorbidities, and elevated suicide risk. To determine genetic differences between common clinical sub-phenotypes of BD, we performed a systematic polygenic risk score (PRS) analysis using multiple PRSs from a range of psychiatric, personality, and lifestyle traits to dissect differences in BD sub-phenotypes in two BD cohorts: the Mayo Clinic BD Biobank (N = 968) and Genetic Association Information Network (N = 1001). Participants were assessed for history of psychosis, early-onset BD, rapid cycling (defined as four or more episodes in a year), and suicide attempts using questionnaires and the Structured Clinical Interview for DSM-IV. In a combined sample of 1969 bipolar cases (45.5% male), those with psychosis had higher PRS for SCZ (OR = 1.3 per S.D.; p = 3e-5) but lower PRSs for anhedonia (OR = 0.87; p = 0.003) and BMI (OR = 0.87; p = 0.003). Rapid cycling cases had higher PRS for ADHD (OR = 1.23; p = 7e-5) and MDD (OR = 1.23; p = 4e-5) and lower BD PRS (OR = 0.8; p = 0.004). Cases with a suicide attempt had higher PRS for MDD (OR = 1.26; p = 1e-6) and anhedonia (OR = 1.22; p = 2e-5) as well as lower PRS for educational attainment (OR = 0.87; p = 0.003). The observed novel PRS associations with sub-phenotypes align with clinical observations such as rapid cycling BD patients having a greater lifetime prevalence of ADHD. Our findings confirm that genetic heterogeneity contributes to clinical heterogeneity of BD and consideration of genetic contribution to psychopathologic components of psychiatric disorders may improve genetic prediction of complex psychiatric disorders.

Psychiatric comorbidities in Asperger syndrome are related with polygenic overlap and differ from other Autism subtypes

There is great phenotypic heterogeneity within autism spectrum disorders (ASD), which has led to question their classification into a single diagnostic category. The study of the common genetic variation in ASD has suggested a greater contribution of other psychiatric conditions in Asperger syndrome (AS) than in the rest of the DSM-IV ASD subtypes (Non_AS). Here, using available genetic data from previously performed genome-wide association studies (GWAS), we aimed to study the genetic overlap between five of the most related disorders (schizophrenia (SCZ), major depression disorder (MDD), attention deficit hyperactivity disorder (ADHD), obsessive-compulsive disorders (OCD) and anxiety (ANX)), and AS, comparing it with the overlap in Non_AS subtypes. A Spanish cohort of autism trios (N = 371) was exome sequenced as part of the Autism Sequencing Consortium (ASC) and 241 trios were extensively characterized to be diagnosed with AS following DSM-IV and Gillberg's criteria (N = 39) or not (N = 202). Following exome imputation, polygenic risk scores (PRS) were calculated for ASD, SCZ, ADHD, MDD, ANX, and OCD (from available summary data from Psychiatric Genomic Consortium (PGC) repository) in the Spanish trios' cohort. By using polygenic transmission disequilibrium test (pTDT), we reported that risk for SCZ (P_scz= 0.008, corrected-P_SCZ = 0.0409), ADHD (P_ADHD = 0.021, corrected-P_ADHD = 0.0301), and MDD (P_MDD = 0.039, corrected-P_MDD = 0.0501) is over-transmitted to children with AS but not to Non_AS. Indeed, agnostic clustering procedure with deviation values from pTDT tests suggested two differentiated clusters of subjects, one of which is significantly enriched in AS (P = 0.025). Subsequent analysis with S-Predixcan, a recently developed software to predict gene expression from genotype data, revealed a clear pattern of correlation between cortical gene expression in ADHD and AS (P < 0.001) and a similar strong correlation pattern between MDD and AS, but also extendable to another non-brain tissue such as lung (P < 0.001). Altogether, these results support the idea of AS being qualitatively distinct from Non_AS autism and consistently evidence the genetic overlap between AS and ADHD, MDD, or SCZ.

Evaluating the effect of birth weight on brain volumes and depression: An observational and genetic study using UK Biobank cohort

Background.

Birth weight influences not only brain development, but also mental health outcomes, including depression, but the underlying mechanism is unclear.

Methods.

The phenotypic data of 12,872–91,009 participants (59.18–63.38% women) from UK Biobank were included to test the associations between the birth weight, depression, and brain volumes through the linear and logistic regression models. As birth weight is highly heritable, the polygenic risk scores (PRSs) of birth weight were calculated from the UK Biobank cohort (154,539 participants, 56.90% women) to estimate the effect of birth weight-related genetic variation on the development of depression and brain volumes. Finally, the mediation analyses of step approach and mediation analysis were used to estimate the role of brain volumes in the association between birth weight and depression. All analyses were conducted sex stratified to assess sex-specific role in the associations.

Result.

We observed associations between birth weight and depression (odds ratio [OR] = 0.968, 95% confidence interval [CI] = 0.957–0.979, p = 2.29 × 10⁻⁶). Positive associations were observed between birth weight and brain volumes, such as gray matter (B = 0.131, p = 3.51 × 10⁻⁷⁴) and white matter (B = 0.129, p = 1.67 × 10⁻⁷⁴). Depression was also associated with brain volume, such as left thalamus (OR = 0.891, 95% CI = 0.850–0.933, p = 4.46 × 10⁻⁵) and right thalamus (OR = 0.884, 95% CI = 0.841–0.928, p = 2.67 × 10⁻⁵). Additionally, significant mediation effects of brain volume were found for the associations between birth weight and depression through steps approach and mediation analysis, such as gray matter (B = –0.220, p = 0.020) and right thalamus (B = –0.207, p = 0.014).

Conclusions.

Our results showed the associations among birth weight, depression, and brain volumes, and the mediation effect of brain volumes also provide evidence for the sex-specific of associations.

A principal component approach to improve association testing with polygenic risk scores

Polygenic risk scores (PRSs) have become an increasingly popular approach for demonstrating polygenic influences on complex traits and for establishing common polygenic signals between different traits. PRSs are typically constructed using pruning and thresholding (P+T), but the best choice of parameters is uncertain; thus multiple settings are used and the best is chosen. Optimization can lead to inflated Type I error. Permutation procedures can correct this, but they can be computationally intensive. Alternatively, a single parameter setting can be chosen a priori for the PRS, but choosing suboptimal settings results in loss of power. We propose computing PRSs under a range of parameter settings, performing principal component analysis (PCA) on the resulting set of PRSs, and using the first PRS-PC in association tests. The first PC reweights the variants included in the PRS to achieve maximum variation over all PRS settings used. Using simulations and a real data application to study PRS association with bipolar disorder and psychosis in bipolar disorder, we compare the performance of the proposed PRS-PCA approach with a permutation test and an a priori selected p-value threshold. The PRS-PCA approach is simple to implement, outperforms the other strategies in most scenarios, and provides an unbiased estimate of prediction performance.

Prefrontal cortex eQTLs/mQTLs enriched in genetic variants associated with alcohol use disorder and other diseases

Aim: This study aimed to investigate the function of genome-wide association study (GWAS)-identified variants associated with alcohol use disorder (AUD)/comorbid psychiatric disorders. Materials & methods: Genome-wide genotype, transcriptome and DNA methylome data were obtained from postmortem prefrontal cortex (PFC) of 48 Caucasians (24 AUD cases/24 controls). Expression/methylation quantitative trait loci (eQTL/mQTL) were identified and their enrichment in GWAS signals for the above disorders were analyzed. Results: PFC cis-eQTLs (923 from cases+controls, 27 from cases and 98 from controls) and cis-mQTLs (9,932 from cases+controls, 264 from cases and 695 from controls) were enriched in GWAS-identified genetic variants for the above disorders. Cis-eQTLs from AUD cases were mapped to morphine addiction-related genes. Conclusion: PFC cis-eQTLs/cis-mQTLs influence gene expression/DNA methylation patterns, thus increasing the disease risk.

Label-free proteomics differences in the dorsolateral prefrontal cortex between bipolar disorder patients with and without psychosis

BACKGROUND

Psychosis is common in bipolar disorder (BD) and is related to more severe cognitive impairments. Since the molecular mechanism of BD psychosis is elusive, we conducted this study to explore the proteomic differences associated with BD psychosis in the dorsolateral prefrontal cortex (DLPFC; BA9).

METHODS

Postmortem DLPFC gray matter tissues from five pairs of age-matched male BD subjects with and without psychosis history were used. Tissue proteomes were identified and quantified by label-free liquid chromatography tandem mass spectrometry and then compared between groups. Statistical significance was set at q < 0.40 and Log₂ fold change (Log₂FC) ≥ |1|. Protein groups with differential expression between groups at p < 0.05 were subjected to pathway analysis.

RESULTS

Eleven protein groups differed significantly between groups, including the reduction of tenascin C (q = 0.005, Log₂FC = -1.78), the elevations of synaptoporin (q = 0.235, Log₂FC = 1.17) and brain-specific angiogenesis inhibitor 1-associated protein 3 (q = 0.241, Log₂FC = 2.10) in BD with psychosis. The between-group differences of these proteins were confirmed by Western blots. The top enriched pathways (p < 0.05 with ≥ 3 hits) were the outgrowth of neurons, neuronal cell proliferation, growth of neurites, and outgrowth of neurites, which were all predicted to be upregulated in BD with psychosis.

LIMITATIONS

Small sample size and uncertain relationships of the observed proteomic differences with illness stage and acute psychosis.

CONCLUSIONS

These results suggested BD with psychosis history may be associated with abnormalities in neurodevelopment, neuroplasticity, neurotransmission, and neuromodulation in the DLPFC.

Heterogeneity and Polygenicity in Psychiatric Disorders: A Genome-Wide Perspective

Genome-wide association studies (GWAS) have been performed for many psychiatric disorders and revealed a complex polygenic architecture linking mental and physical health phenotypes. Psychiatric diagnoses are often heterogeneous, and several layers of trait heterogeneity may contribute to detection of genetic risks per disorder or across multiple disorders. In this review, we discuss these heterogeneities and their consequences on the discovery of risk loci using large-scale genetic data. We primarily highlight the ways in which sex and diagnostic complexity contribute to risk locus discovery in schizophrenia, bipolar disorder, attention deficit hyperactivity disorder, autism spectrum disorder, posttraumatic stress disorder, major depressive disorder, obsessive-compulsive disorder, Tourette’s syndrome and chronic tic disorder, anxiety disorders, suicidality, feeding and eating disorders, and substance use disorders. Genetic data also have facilitated discovery of clinically relevant subphenotypes also described here. Collectively, GWAS of psychiatric disorders revealed that the understanding of heterogeneity, polygenicity, and pleiotropy is critical to translate genetic findings into treatment strategies.

On the diagnostic and neurobiological origins of bipolar disorder

Psychiatry is constructed around a taxonomy of several hundred diagnoses differentiated by nuances in the timing, co-occurrence, and severity of symptoms. Bipolar disorder (BD) is notable among these diagnoses for manic, depressive, and psychotic symptoms all being core features. Here, we trace current understanding of the neurobiological origins of BD and related diagnoses. To provide context, we begin by exploring the historical origins of psychiatric taxonomy. We then illustrate how key discoveries in pharmacology and neuroscience gave rise to a generation of neurobiological hypotheses about the origins of these disorders that facilitated therapeutic innovation but failed to explain disease pathogenesis. Lastly, we examine the extent to which genetics has succeeded in filling this void and contributing to the construction of an objective classification of psychiatric disturbance.

Schizophrenia research in the era of Team Science and big data

The last decade has provided new insights into the genetic architecture of schizophrenia. For the first time researchers have identified genetic factors conferring risk that can be mapped to tissue and cell specific perturbations of the molecular machinery underlying disease processes. However, it has also become clear that attempts to gain mechanistic insights into disease processes that span multiple levels of biological complexity, from genes to cells to circuits to behaviors, are inherently difficult and will require interdisciplinary efforts. Here we discuss the opportunities and pitfalls of developing causal models of SCZ that will lead to novel treatments and prevention strategies. We make the case that integrated large-scale Team Science efforts will be necessary to achieve this goal and that a systems level approach that includes genetics and integrative modelling is needed.

A trans-ethnic two-stage polygenetic scoring analysis detects genetic correlation between osteoporosis and schizophrenia

BACKGROUNDS

To explore the genetic correlation between schizophrenia (SCZ) and osteoporosis (OP).

DESIGN, SETTING, PARTICIPANTS, MEASUREMENTS

We conducted a trans-ethnic two-stage genetic correlation analysis of OP and SCZ, totally invoking 2286 Caucasia subjects in discovery stage and 4124 Chinese subjects in replication stage. The bone mineral density (BMD) and bone area values of ulna & radius, hip and spine were measured using Hologic 4500W dual energy X-ray absorptiometry machine. SCZ was diagnosed according to DSM-IV criteria. For the genome-wide association study (GWAS) of Caucasian OP, Chinese OP and Chinese SCZ, SNP genotyping was performed using Affymetrix SNP 6.0 array. For the GWAS of Caucasian SCZ, SNP genotyping was conducted using the Affymetrix 5.0 array, Affymetrix 6.0 array and Illumina 550 K array. Polygenetic risk scoring (PRS) analysis was conducted by PRSice software. Also, Linkage disequilibrium score regression (LD Score regression) analysis was performed to evaluate the genetic correlation between OP and SCZ. Multi-trait analysis of GWAS (MTAG) was performed to detect novel candidate genes for osteoporosis and SCZ.

RESULTS

In the Caucasia discovery samples, significant genetic correlations were observed for ulna & radius BMD vs. SCZ (P value = 0.010), ulna & radius area vs. SCZ (P value = 0.031). In the Chinese replication samples, we observed significant correlation for ulna & radius area vs. SCZ (P value = 0.019). In addition, LD Score regression also identified significant genetic correlations between SCZ and bone phenotypes in Caucasian and Chinese sample respectively. MTAG analysis identified several novel candidate genes, such as CTNNA2 (MTAG P value = 2.24 × 10-6) for SCZ and FADS2 (MTAG P value = 2.66 × 10-7) for osteoporosis.

CONCLUSIONS

Our study results support the overlapped genetic basis for osteoporosis and SCZ, and provide novel clues for elucidating the biological mechanism of increased osteoporosis risk in SCZ patients.

Neurodevelopmental pathways in bipolar disorder

Aberrations in neurodevelopmental trajectories have been implicated in the neurobiology of several mental disorders and evidence indicates a pathophysiological and genetic overlap of schizophrenia and bipolar disorder (BD). In this narrative review, we summarize findings related to developmental and perinatal factors as well as epidemiological, clinical, neuropsychological, brain imaging, postmortem brain and genomic studies that provide evidence for a putative neurodevelopmental pathogenesis and etiology of BD. Overall, aberrations in neurodevelopmental pathways have been more consistently implicated in the pathophysiology of schizophrenia compared to BD. Nevertheless, an accumulating body of evidence indicates that dysfunctional neurodevelopmental pathways may be implicated in the underlying pathophysiology of at least a subset of individuals with BD particularly those with an early age of illness onset and those exhibiting psychotic symptoms. A heuristic neurodevelopmental model for the pathophysiology of BD based on the findings of this review is proposed. Furthermore, we critically discuss clinical and research implications of this model. Finally, further research directions for this emerging field are provided.

Exploring the genetic overlap between psychiatric illness and epilepsy: A review

There is a long-documented epidemiological link between epilepsy and psychiatric disorders. People with epilepsy are at an increased risk for a variety of psychiatric illnesses, as are their family members, and people with epilepsy may experience psychiatric side effects because of their antiepileptic drugs (AEDs). In recent years, large-scale, collaborative international studies have begun to shed light on the role of genetic variation in both epilepsy and psychiatric illnesses, such as schizophrenia, depression, and anxiety. But so far, finding shared genetic links between epilepsy and psychiatric illness has proven surprisingly difficult. This review will discuss the prevalence of psychiatric comorbidities in epilepsy, recent advances in genetic research into both epilepsy and psychiatric illness, and the extent of our current knowledge of the genetic overlap between these two important neurobiological conditions.

Investigating associations between genetic risk for bipolar disorder and cognitive functioning in childhood

INTRODUCTION

Identifying phenotypic manifestations of genetic risk for bipolar disorder (BD) in childhood could increase our understanding of aetiological mechanisms.

AIMS

To examine whether BD genetic risk is associated with childhood (age 8 years) cognitive function.

METHODS

Using data from the Avon Longitudinal Study of Parents and Children, we examined associations between polygenic risk scores for BD (BD-PRS) derived using Psychiatric Genomics Consortium summary data at p-thresholds (P_T) ≤0.01 (primary) and ≤0.5 (secondary) and several cognitive domains (sample sizes 5,613 to 5,936). We also examined whether associations were due to SNPs that have shared risk effects on schizophrenia (SZ).

RESULTS

At P_T≤0.01, the BD-PRS was associated with poorer executive functioning (ß= -0.03, 95%CI -0.06, -0.01; p = 0.013), and, more weakly with poorer processing speed (ß = -0.02, 95%CI -0.05, 0.02; p = 0.075). Evidence of association with both poorer processing speed (p = 0.016) and performance IQ (p = 0.018) was stronger at P_T≤0.5. Associations with performance IQ and processing speed were primarily driven by genetic effects that are shared with SZ risk, but there was some evidence of bipolar-specific genetic effects on childhood executive functioning.

LIMITATIONS

The BD-PRS still explains only a small proportion of the variance for BD which will have reduced power to detect associations.

CONCLUSIONS

Genetic risk for BD manifests as impaired cognition in childhood, and this is driven by risk SNPs that are also shared with SZ genetic risk. Further elucidation of which cognitive domains are most affected by genetic risk for BD could help understanding of aetiology and improve prediction of BD.

Association of Cytomegalovirus and Toxoplasma gondii Antibody Titers With Bipolar Disorder

IMPORTANCE

Infection-associated immune activation and inflammation are increasingly recognized in the pathophysiology of bipolar disorder.

OBJECTIVE

To determine whether antibodies to common infectious agents, including cytomegalovirus (CMV), Toxoplasma gondii, and measles, as well as the inflammatory marker C-reactive protein, in serum samples differ between patients with bipolar disorder and control individuals without bipolar disorder.

DESIGN, SETTING, AND PARTICIPANTS

In this case-control study, antibody titers were measured in serum samples from 1207 patients with bipolar disorder and 745 controls that were obtained from biobanks with participating sites in Rochester and Minneapolis, Minnesota (n = 1537), and Cincinnati, Ohio (n = 415), from January 5, 2009, through May 12, 2014. A subset of case patients and controls from Minnesota were matched by age, sex, and educational level. Bipolar type, age at onset, and history of psychosis were assessed for case patients as well as current drug treatment at the time of blood sample obtainment from the biobank. Data were analyzed from February 5, 2018, to January 4, 2019.

EXPOSURES

The CMV and T gondii antibodies with IgM titers were expressed as z scores and IgG titers dichotomized into seropositive and seronegative based on expected prevalence in the US population and further classified based on the joint CMV-positive/T gondii-negative IgG status, C-reactive protein z score, and drug treatments with antitoxoplasma activity.

MAIN OUTCOMES AND MEASURES

Patients were stratified by bipolar disorder type I or type II, nonearly (>19 years of age) and early (≤19 years of age) onset, and history of psychosis during mania or no psychosis.

RESULTS

Of 1207 patients with bipolar disorder (mean [SD] age, 43.2 [15.1] years; 742 [61.5%] female), the CMV-positive/T gondii-negative IgG status was significantly higher (odds ratio [OR], 1.33; 95% CI, 1.09-1.62; P = .004) compared with that in the 745 controls (mean [SD] age, 44.5 [15.5] years; 444 [59.6%] female). The CMV-positive/T gondii-negative IgG status was associated with bipolar cases type I (OR, 1.41; 95% CI, 1.14-1.75; P = .001), nonearly age at onset (OR, 1.41; 95% CI, 1.16-1.72; P = .001), and history of manic psychosis (OR, 1.46; 95% CI, 1.13-1.88; P = .004). Patients with bipolar disorder who received drug treatment with antitoxoplasma activity (n = 272) had significantly lower T gondii IgM titers (median, 1.59; interquartile range, 1.30-2.07) compared with those (n = 900) who did not receive this treatment (median, 1.69; interquartile range, 1.35-2.25) (P = .03).

CONCLUSIONS AND RELEVANCE

In this sample, increased long-term antibody response to CMV and decreased long-term antibody response to T gondii were associated with bipolar disorder and the subphenotypes of bipolar type I, nonearly disease onset, and manic psychosis. Further work appears to be needed to better understand genetic vs environmental disease risk and infection or immune activation contribution to overall disease pathogenesis with particular reference to disease onset.

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.

Imaging Genetics Towards a Refined Diagnosis of Schizophrenia

Current diagnoses of schizophrenia and related psychiatric disorders are classified by phenomenological principles and clinical descriptions while ruling out other symptoms and conditions. Specific biomarkers are needed to assist the current diagnostic system. However, complicated gene and environment interactions induce great disease heterogeneity. This unclear etiology and heterogeneity raise difficulties in distinguishing schizophrenia-related effects. Simultaneously, the overlap in symptoms, genetic variations, and brain alterations in schizophrenia and related psychiatric disorders raises similar difficulties in determining disease-specific effects. Imaging genetics is a unique methodology to assess the impact of genetic factors on both brain structure and function. More importantly, imaging genetics builds a bridge to understand the behavioral and clinical implications of genetics and neuroimaging. By characterizing and quantifying the brain measures affected in psychiatric disorders, imaging genetics is contributing to identifying potential biomarkers for schizophrenia and related disorders. To date, candidate gene analysis, genome-wide association studies, polygenetic risk score analysis, and large-scale collaborative studies have made contributions to the understanding of schizophrenia with the potential to serve as biomarkers. Despite limitations, imaging genetics remains promising as more aggregative, clustering methods and imaging genetics-compatible clinical assessments are employed in future studies. We review imaging genetics' contribution to our understanding of the heterogeneity within schizophrenia and the commonalities across schizophrenia and other diagnostic borders, and we will discuss whether imaging genetics is ready to form its own diagnostic system.