Characterizing the polygenic overlaps of bipolar disorder subtypes with schizophrenia and major depressive disorder

Characterizing pleiotropy among bipolar disorder, schizophrenia, and major depression: a genome-wide cross-disorder meta-analysis

BACKGROUND

To understand the pathogenetic mechanisms shared among schizophrenia (SCZ), bipolar disorder (BP), and major depression (MDD), we investigated the pleiotropic mechanisms using large-scale genome-wide and brain transcriptomic data.

METHODS

We analyzed SCZ, BP, and MDD genome-wide association datasets available from the Psychiatric Genomics Consortium using the PLEIO framework and characterized the pleiotropic loci identified using pathway and tissue enrichment analyses. Pleiotropic and disorder-specific loci were also assessed.

RESULTS

Our pleiotropy-informed genome-wide analysis identified 553 variants that included 192 loci not reaching genome-wide significance in input datasets. These were enriched for five molecular pathways: cadherin signaling (p = 2.18 × 10-8), Alzheimer's disease-amyloid secretase (p = 4 × 10-4), oxytocin receptor-mediated signaling (p = 1.47 × 10-3), metabotropic glutamate receptor group III (p = 5.82 × 10-4) and Wnt signaling (p = 1.61 × 10-11). Pleiotropic loci demonstrated the strongest enrichment in the brain cortex (p = 5.8 × 10-28), frontal cortex (p = 3 × 10-31), and cerebellar hemisphere (p = 9.8 × 10-28). SCZ-BP-MDD pleiotropic variants were also enriched for neurodevelopmental brain transcriptomic profiles related to the second-trimester post-conception (week 21, p = 7.35 × 10-5; week 17, p = 6.36 × 10-4) and first year of life (p = 3.25 × 10-5).

CONCLUSIONS

Genetic mechanisms shared among SCZ, BP, and MDD appear to be related to early neuronal development. Because the genetic architecture of psychopathology transcends diagnostic boundaries, pleiotropy-focused analyses can lead to increased gene discovery and novel insights into relevant pathogenic mechanisms.

Effects of parental characteristics on the risk of psychopathology in offspring: a 4-year follow-up study

Offspring of patients diagnosed with schizophrenia (SZoff) or bipolar disorder (BDoff) have double the risk of developing a psychiatric disorder. Here we report the effects of some parental characteristics on the offspring risk of psychopathology at 4-year follow-up. At baseline, 90 BDoff, 41 SZoff and 107 Community Control offspring (CCoff) aged 6 to 17 were included. At 4-year follow-up, 71% of the sample was assessed. Parents' and offspring's psychiatric diagnoses as well as socio-economic status (SES) and global functioning were assessed in addition to parents' ages at childbirth and offspring subclinical psychotic/bipolar symptoms. Kaplan-Meier method and Cox regression analysis were used to assess between-group differences in the cumulative incidence of psychiatric disorders and subclinical psychotic/bipolar symptoms and the association of some offspring and parents' variables with risk of psychopathology and subclinical psychotic/bipolar symptoms. SZoff and BDoff had a higher risk of psychopathology than CCoff at 4-year follow-up. SZoff showed a higher risk for attention deficit hyperactivity disorder (ADHD), disruptive disorders and subclinical psychotic symptoms, whereas BDoff displayed a heightened risk for mood disorders, ADHD and subclinical bipolar symptoms when compared to CCoff. Higher parental psychosocial functioning and SES were associated with a lower prevalence of psychopathology. Both SZoff and BDoff samples have a higher risk for psychopathology but the pattern of this psychopathology seems to be group specific. Longer follow-up studies and larger sample sizes are needed to assess the capacity of psychopathological disorder and subclinical psychotic or bipolar symptoms to predict progression to fully-fledged disorders.

Multigene overlap analysis of bipolar disorder subtypes and educational attainment

OBJECTIVE

Bipolar disorder subtypes (BIP-I and BIP-II) differ in clinical presentation and genetic basis, yet their patterns of genetic association with educational attainment (EA) remain poorly understood. This study investigated the genetic overlap between BIP subtypes and EA, along with their underlying molecular mechanisms.

METHODS

Using genome-wide association study (GWAS) data for BIP-I (n = 25,060), BIP-II (n = 6781), and EA (n = 765,283), we estimated genetic overlap using bivariate causal mixed models (MiXeR) and identified shared gene loci through the joint false discovery rate (conjFDR) method.

RESULTS

MiXeR analysis revealed approximately 7.4 K single nucleotide polymorphisms (SNPs) shared between BIP-I and EA, accounting for 97.4 % of SNPs influencing BIP-I and 56.5 % of those affecting EA. ConjFDR identified 264 loci commonly associated with BIP-I and EA, including 168 novel loci for both traits. Among the 312 lead SNPs at these loci, 219 exhibited consistent effects, while 93 demonstrated opposing effects. In contrast, only two loci were co-associated between BIP-II and EA. Functional annotation and enrichment analyses showed that most loci shared by BIP-I and EA were located in intronic and intergenic regions, with associated genes enriched in processes such as protein binding and nervous system development.

CONCLUSIONS

This study highlights the distinct degrees and patterns of genetic association between BIP subtypes and EA, offering insights into the heterogeneity of BIP and a potential genetic basis for clinical subtyping and personalized treatment strategies.

Seven loci associated with schizophrenia and bipolar I disorder in selected southern African population groups

Two major psychiatric disorders, schizophrenia and bipolar I disorder, are regarded as distinct disorder entities; however, they share intricate connections through characteristic overlap and underlying genetic aetiology, challenging the traditional dichotomy. This convergence emerged as an essential area of investigation in understanding the genetic determinants of schizophrenia and bipolar I disorder. Moreover, psychiatric genetic research has revealed demographic disparities, with South African population groups notably underrepresented. Therefore, this preliminary targeted candidate gene association study of 20 single nucleotide polymorphisms implicated in schizophrenia and bipolar I disorder aimed to investigate association and overlap. Candidate loci for schizophrenia and bipolar I disorder were selected through an exploratory Illumina® Infinium PsychArray-24 analysis combined with literature and database searches. Genotyping of the selected loci was performed with the Agena Bioscience MassARRAY® platform on 96 cases (58 schizophrenia and 38 bipolar I disorder patients) and 44 controls of Afrikaner, Sotho, and Tswana descent. Association analysis was performed by comparing and combining population and phenotype groups. Significant (p < 0.05) loci in the ADAMTSL1, CACNA1B, CACNA1C, CDH13, CTNNA2, RBFOX1, and TRIO genes were identified as possible susceptibility factors, and differences were observed with the association between population and phenotype groups. Through further pathway analysis, the calcium and cadherin-catenin pathways were identified as possible role players in the aetiology of schizophrenia and bipolar I disorder. The study represented an essential step towards understanding the genetic contribution towards schizophrenia and bipolar I disorder in distinct population groups and has the potential to contribute towards the knowledge base and inform future research efforts.

A cross-section study of the comparison of plasma inflammatory cytokines and short-chain fatty acid in patients with depression and schizophrenia

BACKGROUND

Major depressive disorder (MDD) and schizophrenia (SCH) are common and severe mental disorders that are mainly diagnosed depending on the subjective identification by psychiatrists. Finding potential objective biomarkers that can distinguish these two diseases is still meaningful.

METHODS

In the present study, we investigate the differences in plasma inflammatory cytokines and short-chain fatty acids (SCFAs) among patients with MDD (n = 24) and SCH (n = 24), and gender- and age-matched healthy controls (HC, n = 27) and identify potential plasma biomarkers.

RESULTS

We found that the concentrations of pro-inflammatory cytokines were increased, whereas the anti-inflammatory cytokines were decreased in both MDD and SCH. Meanwhile, except for an increase in 4-Methylvaleric acid, other SCFAs with statistical differences were reduced in both MDD and SCH. Moreover, potential biomarker panels were developed that can effectively discriminate MDD from HC (AUC = 0.997), SCH from HC (AUC = 0.999), and from each other (MDD from SCH, AUC = 0.983).

CONCLUSIONS

These data suggest that alterations in plasma cytokines and SCFAs might be one of the potential features for distinguishing MDD and SCH.

TRIAL REGISTRATION

Chinese Clinical Trial Registry: ChiCTR2100051243, registration date: 2021/09/16.

Investigating the shared genetic architecture between depression and subcortical volumes

Depression, a widespread and highly heritable mental health condition, profoundly affects millions of individuals worldwide. Neuroimaging studies have consistently revealed volumetric abnormalities in subcortical structures associated with depression. However, the genetic underpinnings shared between depression and subcortical volumes remain inadequately understood. Here, we investigate the extent of polygenic overlap using the bivariate causal mixture model (MiXeR), leveraging summary statistics from the largest genome-wide association studies for depression (N = 674,452) and 14 subcortical volumetric phenotypes (N = 33,224). Additionally, we identify shared genomic loci through conditional/conjunctional FDR analyses. MiXeR shows that subcortical volumetric traits share a substantial proportion of genetic variants with depression, with 44 distinct shared loci identified by subsequent conjunctional FDR analysis. These shared loci are predominantly located in intronic regions (58.7%) and non-coding RNA intronic regions (25.4%). The 269 protein-coding genes mapped by these shared loci exhibit specific developmental trajectories, with the expression level of 55 genes linked to both depression and subcortical volumes, and 30 genes linked to cognitive abilities and behavioral symptoms. These findings highlight a shared genetic architecture between depression and subcortical volumetric phenotypes, enriching our understanding of the neurobiological underpinnings of depression.

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.

Genetic causal association between varicella-zoster virus infection and psychiatric disorders: A 2-sample Mendelian randomization study

BACKGROUND

Psychiatric disorders, such as schizophrenia (SCZ), major depressive (MDD), and bipolar disorder (BD) have a profound impact on millions of individuals worldwide. The critical step toward developing effective preventive and treatment strategies lies in comprehending the causal mechanisms behind these diseases and identifying modifiable risk factors associated with them.

METHODS

In this study, we conducted a 2-sample Mendelian randomization analysis to explore the potential links between chickenpox(varicella-zoster virus infection) and three major psychiatric disorders(SCZ, MDD, BD).

RESULTS

In our MR study, among the three major psychiatric disorders, chickenpox was shown to be causally related to BD, indicating that infection with chickenpox may increase the risk of developing BD (IVW: OR = 1.064, 95% CI =1.025-1.104, P=0.001; RAPS: OR=1.066, 95% CI=1.024-1.110, P=0.002), while there was no causal relationship between SCZ and MDD. Similar estimated causal effects were observed consistently across the various MR models. The robustness of the identified causal relationship between chickenpox and BD holds true regardless of the statistical methods employed, as confirmed by extensive sensitivity analyses that address violations in model assumptions. The MR-Egger regression test failed to reveal any signs of directional pleiotropy (intercept = -0.042, standard error (SE) = 0.029, p = 0.236). Similarly, the MR-PRESSO analysis revealed no evidence of directional pleiotropy or outliers among the chickenpox-related instrumental variables (global test p = 0.653). Furthermore, a leave-one-out sensitivity analysis yielded consistent results, further underscoring the credibility and stability of the causal relationship.

CONCLUSIONS

Our findings provide compelling evidence of a causal effect of chickenpox on the risk of BD. To gain a more comprehensive understanding of this association and its underlying mechanisms, additional research is needed. Such investigations are pivotal in identifying effective interventions for promoting BD prevention.

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.

A Preliminary Comparison of Plasma Tryptophan Metabolites and Medium- and Long-Chain Fatty Acids in Adult Patients with Major Depressive Disorder and Schizophrenia

Background and Objectives: Disturbance of tryptophan (Trp) and fatty acid (FA) metabolism plays a role in the pathogenesis of psychiatric disorders. However, quantitative analysis and comparison of plasma Trp metabolites and medium- and long-chain fatty acids (MCFAs and LCFAs) in adult patients with major depressive disorder (MDD) and schizophrenia (SCH) are limited. Materials and Methods: Clinical symptoms were assessed and the level of Trp metabolites and MCFAs and LCFAs for plasma samples from patients with MDD (n = 24) or SCH (n = 22) and healthy controls (HC, n = 23) were obtained and analyzed. Results: We observed changes in Trp metabolites and MCFAs and LCFAs with MDD and SCH and found that Trp and its metabolites, such as N-formyl-kynurenine (NKY), 5-hydroxyindole-3-acetic acid (5-HIAA), and indole, as well as omega-3 polyunsaturated fatty acids (N3) and the ratio of N3 to omega-6 polyunsaturated fatty acids (N3: N6), decreased in both MDD and SCH patients. Meanwhile, levels of saturated fatty acids (SFA) and monounsaturated fatty acids (MUFA) decreased in SCH patients, and there was a significant difference in the composition of MCFAs and LCFAs between MDD and SCH patients. Moreover, the top 10 differential molecules could distinguish the two groups of diseases from HC and each other with high reliability. Conclusions: This study provides a further understanding of dysfunctional Trp and FA metabolism in adult patients with SCH or MDD and might develop combinatorial classifiers to distinguish between these disorders.