Immunogenetics of lithium response and psychiatric phenotypes in patients with bipolar disorder.

The link between bipolar disorder (BP) and immune dysfunction remains controversial. While epidemiological studies have long suggested an association, recent research has found only limited evidence of such a relationship. To clarify this, we performed an exploratory study of the contributions of immune-relevant genetic factors to the response to lithium (Li) treatment and the clinical presentation of BP. First, we assessed the association of a large collection of immune-related genes (4925) with Li response, defined by the Retrospective Assessment of the Lithium Response Phenotype Scale (Alda scale), and clinical characteristics in patients with BP from the International Consortium on Lithium Genetics (ConLi+Gen, N = 2374). Second, we calculated here previously published polygenic scores (PGSs) for immune-related traits and evaluated their associations with Li response and clinical features. Overall, we observed relatively weak associations (p < 1 × 10-4) with BP phenotypes within immune-related genes. Network and functional enrichment analyses of the top findings from the association analyses of Li response variables showed an overrepresentation of pathways participating in cell adhesion and intercellular communication. These appeared to converge on the well-known Li-induced inhibition of GSK-3ß. Association analyses of age-at-onset, number of mood episodes, and presence of psychosis, substance abuse and/or suicidal ideation suggested modest contributions of genes such as RTN4, XKR4, NRXN1, NRG1/3 and GRK5 to disease characteristics. PGS analyses returned weak associations (p < 0.05) between inflammation markers and the studied BP phenotypes. Our results suggest a modest relationship between immunity and clinical features in BP. More research is needed to assess the potential therapeutic relevance.

Association of major depression, schizophrenia and bipolar disorder with thyroid cancer: a bidirectional two-sample mendelian randomized study.

BACKGROUND: Major depressive disease (MDD), schizophrenia (SCZ), and bipolar disorder (BD) are common psychiatric disorders, and their relationship with thyroid cancer has been of great interest. This study aimed to investigate the potential causal effects of MDD, SCZ, BD, and thyroid cancer. METHODS: We used publicly available summary statistics from large-scale genome-wide association studies to select genetic variant loci associated with MDD, SCZ, BD, and thyroid cancer as instrumental variables (IVs), which were quality controlled and clustered. Additionally, we used three Mendelian randomization (MR) methods, inverse variance weighted (IVW), MR-Egger regression and weighted median estimator (WME) methods, to estimate the bidirectional causal relationship between psychiatric disorders and thyroid cancer. In addition, we performed heterogeneity and multivariate tests to verify the validity of the IVs. RESULTS: We used two-sample bidirectional MR analysis to determine whether there was a positive causal association between MDD and thyroid cancer risk. The results of the IVW analysis (OR = 3.956 95% CI = 1.177-13.299; P = 0.026) and the WME method (OR = 5.563 95% CI = 0.998-31.008; P = 0.050) confirmed that MDD may increase the risk of thyroid cancer. Additionally, our study revealed a correlation between genetic susceptibility to SCZ and thyroid cancer (OR = 1.532 95% CI = 1.123-2.088; P = 0.007). The results of the WME method analysis based on the median estimate (OR = 1.599 95% CI = 1.014-2.521; P = 0.043) also suggested that SCZ may increase the risk of thyroid cancer. Furthermore, our study did not find a causal relationship between BD and thyroid cancer incidence. In addition, the results of reverse MR analysis showed no significant causal relationships between thyroid cancer and MDD, SCZ, or BD (P > 0.05), ruling out the possibility of reverse causality. CONCLUSIONS: This MR method analysis provides new evidence that MDD and SCZ may be positively associated with thyroid cancer risk while also revealing a correlation between BD and thyroid cancer. These results may have important implications for public health policy and clinical practice. Future studies will help elucidate the biological mechanisms of these associations and potential confounders.

Decreased telomere length in a subgroup of young individuals with bipolar disorders: replication in the FACE-BD cohort and association with the shelterin component POT1.

Bipolar disorder (BD) has been associated with premature cellular aging with shortened telomere length (TL) as compared to the general population. We recently identified a subgroup of young individuals with prematurely shortened TL. The aims of the present study were to replicate this observation in a larger sample and analyze the expression levels of genes associated with age or TL in a subsample of these individuals. TL was measured on peripheral blood DNA using quantitative polymerase chain reaction in a sample of 542 individuals with BD and clustering analyses were performed. Gene expression level of 29 genes, associated with aging or with telomere maintenance, was analyzed in RNA samples from a subsample of 129 individuals. Clustering analyses identified a group of young individuals (mean age 29.64 years), with shorter TL. None of the tested clinical variables were significantly associated with this subgroup. Gene expression level analyses showed significant downregulation of MYC, POT1, and CD27 in the prematurely aged young individuals compared to the young individuals with longer TL. After adjustment only POT1 remained significantly differentially expressed between the two groups of young individuals. This study confirms the existence of a subgroup of young individuals with BD with shortened TL. The observed decrease of POT1 expression level suggests a newly described cellular mechanism in individuals with BD, that may contribute to telomere shortening.

Pathogenesis or a response to lithium? A novel perspective for mitochondrial mass fluctuation of naïve T cells in patients with bipolar disorder.

BACKGROUND: Immune imbalances are associated with the pathogenesis and pharmacological efficacy of bipolar disorder (BD). The underlying mechanisms remain largely obscure but may involve immunometabolic dysfunctions of T-lymphocytes. METHODS: We investigated if inflammatory cytokines and the immunometabolic function of T-lymphocytes, including frequencies of subsets, mitochondrial mass (MM), and low mitochondrial membrane potential (MMPLow) differed between BD patients (n = 47) and healthy controls (HC, n = 43). During lithium treatment of hospitalized patients (n = 33), the association between weekly T-lymphocyte immune metabolism and clinical symptoms was analyzed, and preliminary explorations on possible mechanisms were conducted. RESULTS: In comparison to HC, BD patients predominantly showed a trend toward CD4+ naïve T (Tn) activation and exhibited mitochondrial metabolic disturbances such as decreased MM and increased MMPLow. Lower CD4+ Tn-MM correlated with elevated IL-6, IL-8, and decreased IL-17 A in BD patients. With lithium treatment effective, MM of CD4+ T/Tn was negatively correlated with depression score HAMD. When lithium intolerance was present, MM of CD4+ T/Tn was positively correlated with depression score HAMD and mania score BRMS. Lithium does not mediate through the inositol depletion hypothesis, but the mRNA level of IMPA2 in peripheral blood is associated with mitochondrial function in CD8+ T cells. LIMITATIONS: The cross-sectional design and short-term follow-up meant that we could not directly examine the causality of BD and immune dysregulation. CONCLUSION: The altered metabolism of CD4+ Tn was strongly associated with remodeling of the inflammatory landscape in BD patients and can also be used to reflect the short-term therapeutic effects of lithium.

Increased circulating cell-free mitochondrial DNA in plasma of first-diagnosed drug-naïve bipolar disorder patients: A case-control and 4-week follow-up study.

BACKGROUND: The study of clinical biological indicators in bipolar disorder (BD) is important. In recent years, basic experiments have associated the pathophysiological mechanism of BD is related to mitochondrial dysfunction, but few clinical studies have confirmed this finding. OBJECT: The present study aimed to evaluate whether plasma circulating cell-free mitochondrial DNA (ccf-mtDNA) levels, which can represent the degree of mitochondrial damage in vivo, are altered in patients with BD in early onset and during treatment compared with controls. METHOD: A total of 75 first-diagnosed drug-naive patients with BD and 60 HCs were recruited and followed up for 1 month. The clinical symptoms were assessed using HAMD, HAMA, and YMRS, and ccf-mtDNA levels were measured by qPCR before and after drug treatment in BD. RESULT: (1) The plasma ccf-mtDNA levels in first-diagnosed drug-naive patients with BD increased compared with those in HCs (p = 0.001). (2) Drug treatment for 1 month can decrease the expression of ccf-mtDNA in BD (p < 0.001). (3) No significant correlation was observed between the changes in ccf-mtDNA levels and the improvement of clinical symptoms in BD after drug treatment. CONCLUSION: The plasma ccf-mtDNA level was increased in BD, and decreased after pharmacological treatment. These outcomes suggested that plasma ccf-mtDNA level is likely to be sensitive to the drug response in BD, and mitochondrial pathway is a potential target for further therapy.

Genetic and phenotypic similarity across major psychiatric disorders: a systematic review and quantitative assessment.

There is widespread overlap across major psychiatric disorders, and this is the case at different levels of observations, from genetic variants to brain structures and function and to symptoms. However, it remains unknown to what extent these commonalities at different levels of observation map onto each other. Here, we systematically review and compare the degree of similarity between psychiatric disorders at all available levels of observation. We searched PubMed and EMBASE between January 1, 2009 and September 8, 2022. We included original studies comparing at least four of the following five diagnostic groups: Schizophrenia, Bipolar Disorder, Major Depressive Disorder, Autism Spectrum Disorder, and Attention Deficit Hyperactivity Disorder, with measures of similarities between all disorder pairs. Data extraction and synthesis were performed by two independent researchers, following the PRISMA guidelines. As main outcome measure, we assessed the Pearson correlation measuring the degree of similarity across disorders pairs between studies and biological levels of observation. We identified 2975 studies, of which 28 were eligible for analysis, featuring similarity measures based on single-nucleotide polymorphisms, gene-based analyses, gene expression, structural and functional connectivity neuroimaging measures. The majority of correlations (88.6%) across disorders between studies, within and between levels of observation, were positive. To identify a consensus ranking of similarities between disorders, we performed a principal component analysis. Its first dimension explained 51.4% (95% CI: 43.2, 65.4) of the variance in disorder similarities across studies and levels of observation. Based on levels of genetic correlation, we estimated the probability of another psychiatric diagnosis in first-degree relatives and showed that they were systematically lower than those observed in population studies. Our findings highlight that genetic and brain factors may underlie a large proportion, but not all of the diagnostic overlaps observed in the clinic.

Similar imaging changes and their relations to genetic profiles in bipolar disorder across different clinical stages.

Bipolar disorder (BD) across different clinical stages may present shared and distinct changes in brain activity. We aimed to reveal the neuroimaging homogeneity and heterogeneity of BD and its relationship with clinical variables and genetic variations. In present study, we conducted fractional amplitude of low-frequency fluctuations (fALFF), functional connectivity (FC) and genetic neuroimaging association analyses with 32 depressed, 26 manic, 35 euthymic BD patients and 87 healthy controls (HCs). Significant differences were found in the bilateral pre/subgenual anterior cingulate cortex (ACC) across the four groups, and all bipolar patients exhibited decreased fALFF values in the ACC when compared to HCs. Furthermore, positive associations were significantly observed between fALFF values in the pre/subgenual ACC and participants' cognitive functioning. No significant changes were found in ACC-based FC. We identified fALFF-alteration-related genes in BD, with enrichment in biological progress including synaptic and ion transmission. Taken together, abnormal activity in ACC is a characteristic change associated with BD, regardless of specific mood stages, serving as a potential neuroimaging feature in BD patients. Our genetic neuroimaging association analysis highlights possible heterogeneity in biological processes that could be responsible for different clinical stages in BD.

Hemorrhoidal disease and its genetic association with depression, bipolar disorder, anxiety disorders, and schizophrenia: a bidirectional mendelian randomization study.

BACKGROUND: Hemorrhoids and psychiatric disorders exhibit high prevalence rates and a tendency for relapse in epidemiological studies. Despite this, limited research has explored their correlation, and these studies are often subject to reverse causality and residual confounding. We conducted a Mendelian randomization (MR) analysis to comprehensively investigate the association between several mental illnesses and hemorrhoidal disease. METHODS: Genetic associations for four psychiatric disorders and hemorrhoidal disease were obtained from large consortia, the FinnGen study, and the UK Biobank. Genetic variants associated with depression, bipolar disorder, anxiety disorders, schizophrenia, and hemorrhoidal disease at the genome-wide significance level were selected as instrumental variables. Screening for potential confounders in genetic instrumental variables using PhenoScanner V2. Bidirectional MR estimates were employed to assess the effects of four psychiatric disorders on hemorrhoidal disease. RESULTS: Our analysis revealed a significant association between genetically predicted depression and the risk of hemorrhoidal disease (IVW, OR=1.20,95% CI=1.09 to 1.33, P <0.001). We found no evidence of associations between bipolar disorder, anxiety disorders, schizophrenia, and hemorrhoidal disease. Inverse MR analysis provided evidence for a significant association between genetically predicted hemorrhoidal disease and depression (IVW, OR=1.07,95% CI=1.04 to 1.11, P <0.001). CONCLUSIONS: This study offers MR evidence supporting a bidirectional causal relationship between depression and hemorrhoidal disease.

Advances in the understanding of the pathophysiology of schizophrenia and bipolar disorder through induced pluripotent stem cell models.

The pathophysiology of schizophrenia and bipolar disorder involves a complex interaction between genetic and environmental factors that begins in the early stages of neurodevelopment. Recent advancements in the field of induced pluripotent stem cells (iPSCs) offer a promising tool for understanding the neurobiological alterations involved in these disorders and, potentially, for developing new treatment options. In this review, we summarize the results of iPSC-based research on schizophrenia and bipolar disorder, showing disturbances in neurodevelopmental processes, imbalance in glutamatergic-GABAergic transmission and neuromorphological alterations. The limitations of the reviewed literature are also highlighted, particularly the methodological heterogeneity of the studies, the limited number of studies developing iPSC models of both diseases simultaneously, and the lack of in-depth clinical characterization of the included samples. Further studies are needed to advance knowledge on the common and disease-specific pathophysiological features of schizophrenia and bipolar disorder and to promote the development of new treatment options.

Coexpression network analysis of the adult brain sheds light on the pathogenic mechanism of DDR1 in schizophrenia and bipolar disorder.

DDR1 has been linked to schizophrenia (SCZ) and bipolar disorder (BD) in association studies. DDR1 encodes 58 distinct transcripts, which can be translated into five isoforms (DDR1a-e) and are expressed in the brain. However, the transcripts expressed in each brain cell type, their functions and their involvement in SCZ and BD remain unknown. Here, to infer the processes in which DDR1 transcripts are involved, we used transcriptomic data from the human brain dorsolateral prefrontal cortex of healthy controls (N = 936) and performed weighted gene coexpression network analysis followed by enrichment analyses. Then, to explore the involvement of DDR1 transcripts in SCZ (N = 563) and BD (N = 222), we studied the association of coexpression modules with disease and performed differential expression and transcript significance analyses. Some DDR1 transcripts were distributed across five coexpression modules identified in healthy controls (MHC). MHC1 and MHC2 were enriched in the cell cycle and proliferation of astrocytes and OPCs; MHC3 and MHC4 were enriched in oligodendrocyte differentiation and myelination; and MHC5 was enriched in neurons and synaptic transmission. Most of the DDR1 transcripts associated with SCZ and BD pertained to MHC1 and MHC2. Altogether, our results suggest that DDR1 expression might be altered in SCZ and BD via the proliferation of astrocytes and OPCs, suggesting that these processes are relevant in psychiatric disorders.

Dissecting the genetic overlap between severe mental disorders and markers of cellular aging: Identification of pleiotropic genes and druggable targets.

Patients with severe mental disorders such as bipolar disorder (BD), schizophrenia (SCZ) and major depressive disorder (MDD) show a substantial reduction in life expectancy, increased incidence of comorbid medical conditions commonly observed with advanced age and alterations of aging hallmarks. While severe mental disorders are heritable, the extent to which genetic predisposition might contribute to accelerated cellular aging is not known. We used bivariate causal mixture models to quantify the trait-specific and shared architecture of mental disorders and 2 aging hallmarks (leukocyte telomere length [LTL] and mitochondrial DNA copy number), and the conjunctional false discovery rate method to detect shared genetic loci. We integrated gene expression data from brain regions from GTEx and used different tools to functionally annotate identified loci and investigate their druggability. Aging hallmarks showed low polygenicity compared with severe mental disorders. We observed a significant negative global genetic correlation between MDD and LTL (rg = -0.14, p = 6.5E-10), and no significant results for other severe mental disorders or for mtDNA-cn. However, conditional QQ plots and bivariate causal mixture models pointed to significant pleiotropy among all severe mental disorders and aging hallmarks. We identified genetic variants significantly shared between LTL and BD (n = 17), SCZ (n = 55) or MDD (n = 19), or mtDNA-cn and BD (n = 4), SCZ (n = 12) or MDD (n = 1), with mixed direction of effects. The exonic rs7909129 variant in the SORCS3 gene, encoding a member of the retromer complex involved in protein trafficking and intracellular/intercellular signaling, was associated with shorter LTL and increased predisposition to all severe mental disorders. Genetic variants underlying risk of SCZ or MDD and shorter LTL modulate expression of several druggable genes in different brain regions. Genistein, a phytoestrogen with anti-inflammatory and antioxidant effects, was an upstream regulator of 2 genes modulated by variants associated with risk of MDD and shorter LTL. While our results suggest that shared heritability might play a limited role in contributing to accelerated cellular aging in severe mental disorders, we identified shared genetic determinants and prioritized different druggable targets and compounds.

Oxidation of DNA and RNA in young patients with newly diagnosed bipolar disorder and relatives.

Excessive oxidative stress-generated nucleoside damage seems to play a key role in bipolar disorder (BD) and may present a trait phenomenon associated with familial risk and is one of the putative mechanisms explaining accelerated atherosclerosis and premature cardiovascular diseases (CVD) in younger patients with BD. However, oxidative stress-generated nucleoside damage has not been studied in young BD patients and their unaffected relatives (UR). Therefore, we compared oxidative stress-generated damage to DNA and RNA in young patients newly diagnosed with BD, UR, and healthy control individuals (HC). Systemic oxidative stress-generated DNA and RNA damage levels were compared by analyzing urinary levels of 8-oxo-7,8-dihydro-2'-deoxyguanosine and 8-oxo-7,8-dihydroguanosine in participants aged 15-25 years, including 133 patients newly diagnosed with BD, 57 UR, and 83 HC. Compared with HC, damage to DNA was 21.8% higher in BD patients (B = 1.218, 95% CI = 1.111-1.335, p = <0.001) and 22.5% higher in UR (B = 1.225, 95% CI = 1.090-1.377, p = <0.002), while damage to RNA was 14.8% higher in BD patients (B = 1.148, 95% CI = 1.082-1.219, p = <0.001) and 14.0% higher in UR (B = 1.140, 95% CI = 1.055-1.230, p = < 0.001) in models adjusted for sex and age after correction for multiple comparison. Levels did not differ between patients with BD and UR. Our findings support higher oxidative stress-generated nucleoside damage being a trait phenomenon in BD associated with familial risk and highlight the importance of early diagnosis and treatment to prevent illness progression and development of premature CVD.

Multimodal integration of neuroimaging and genetic data for the diagnosis of mood disorders based on computer vision models.

Mood disorders, particularly major depressive disorder (MDD) and bipolar disorder (BD), are often underdiagnosed, leading to substantial morbidity. Harnessing the potential of emerging methodologies, we propose a novel multimodal fusion approach that integrates patient-oriented brain structural magnetic resonance imaging (sMRI) scans with DNA whole-exome sequencing (WES) data. Multimodal data fusion aims to improve the detection of mood disorders by employing established deep-learning architectures for computer vision and machine-learning strategies. We analyzed brain imaging genetic data of 321 East Asian individuals, including 147 patients with MDD, 78 patients with BD, and 96 healthy controls. We developed and evaluated six fusion models by leveraging common computer vision models in image classification: Vision Transformer (ViT), Inception-V3, and ResNet50, in conjunction with advanced machine-learning techniques (XGBoost and LightGBM) known for high-dimensional data analysis. Model validation was performed using a 10-fold cross-validation. Our ViT ⊕ XGBoost fusion model with MRI scans, genomic Single Nucleotide polymorphism (SNP) data, and unweighted polygenic risk score (PRS) outperformed baseline models, achieving an incremental area under the curve (AUC) of 0.2162 (32.03% increase) and 0.0675 (+8.19%) and incremental accuracy of 0.1455 (+25.14%) and 0.0849 (+13.28%) compared to SNP-only and image-only baseline models, respectively. Our findings highlight the opportunity to refine mood disorder diagnostics by demonstrating the transformative potential of integrating diverse, yet complementary, data modalities and methodologies.

Correlation of potential diagnostic biomarkers (circulating miRNA and protein) of bipolar II disorder.

OBJECTIVES: We previously identified certain peripheral biomarkers of bipolar II disorder (BD-II) including circulating miRNAs (miR-7-5p, miR-142-3p, miR-221-5p, and miR-370-3p) and proteins (Matrix metallopeptidase 9 (MMP9), phenylalanyl-tRNA synthetase subunit beta (FARSB), peroxiredoxin 2 (PRDX2), carbonic anhydrase 1 (CA-1), and proprotein convertase subtilisin/kexin type 9 (PCSK9)). We try to explore the connection between these biomarkers. METHODS: We explored correlations between the peripheral levels of above circulating miRNAs and proteins in our previously collected BD-II (N = 96) patients and control (N = 115) groups. We further searched TargetScan and BioGrid websites to identify direct and indirect interactions between these protein-coding genes and circulating miRNAs. RESULTS: In the BD-II group, we identified significant correlations between the miR-221-5p and CA-1 (rho = -0.323, P = 0.001), FARSB (rho = 0.251, P = 0.014), MMP-9 (rho = 0.313, P = 0.002) and PCSK9 (rho = 0.252, P = 0.014). The miR-370-3p also significantly correlated with FARSB expression (rho = 0.330, P = 0.001) and PCSK9 expression (rho = 0.221, P = 0.031) in the BD-II group. Our findings were in line with the modulating axis identified from TargetScan and BioGrid, miR-221-5p/CA-1/MMP9 and miR-370-3p/FARSB/PCSK9, suggesting their association with BD-II. CONCLUSION: Our result supported that peripheral candidate miRNA and protein biomarkers may interact in BD-II. We concluded that miR-221-5p/CA-1/MMP9 and miR-370-3p/FARSB/PCSK9 axes might act a critical role in the pathomechanism of BD-II.

Impact of genetic, sociodemographic, and clinical features on antidepressant treatment trajectories in the perinatal period.

Pregnant women on antidepressants must balance potential fetal harm with the relapse risk. While various clinical and sociodemographic factors are known to influence treatment decisions, the impact of genetic factors remains unexplored. We conducted a cohort study among 2,316 women with diagnosed affective disorders who had redeemed antidepressant prescriptions six months before pregnancy, identified from the Danish Integrated Psychiatric Research study. We calculated polygenic risk scores (PGSs) for major depression (MDD), bipolar disorder (BD), and schizophrenia (SCZ) using individual-level genetic data and summary statistics from genome-wide association studies. We retrieved data on sociodemographic and clinical features from national registers. Applying group-based trajectory modeling, we identified four treatment trajectories across pregnancy and postpartum: Continuers (38.2 %), early discontinuers (22.7 %), late discontinuers (23.8 %), and interrupters (15.3 %). All three PGSs were not associated with treatment trajectories; for instance, the relative risk ratio for continuers versus early discontinuers was 0.93 (95 % CI: 0.81-1.06), 0.98 (0.84-1.13), 1.09 (0.95-1.27) for per 1-SD increase in PGS for MDD, BD, and SCZ, respectively. Sociodemographic factors were generally not associated with treatment trajectories, except for the association between primiparity and continuing antidepressant use. Women who received ≥2 classes or a higher dose of antidepressants had a higher probability of being late discontinuers, interrupters, and continuers. The likelihood of continuing antidepressants or restarting antidepressants postpartum increased with the previous antidepressant treatment duration. Our findings indicate that continued antidepressant use during pregnancy is influenced by the severity of the disease rather than genetic predisposition as measured by PGSs.

White and gray matter alterations in bipolar I and bipolar II disorder subtypes compared with healthy controls - exploring associations with disease course and polygenic risk.

Patients with bipolar disorder (BD) show alterations in both gray matter volume (GMV) and white matter (WM) integrity compared with healthy controls (HC). However, it remains unclear whether the phenotypically distinct BD subtypes (BD-I and BD-II) also exhibit brain structural differences. This study investigated GMV and WM differences between HC, BD-I, and BD-II, along with clinical and genetic associations. N = 73 BD-I, n = 63 BD-II patients and n = 136 matched HC were included. Using voxel-based morphometry and tract-based spatial statistics, main effects of group in GMV and fractional anisotropy (FA) were analyzed. Associations between clinical and genetic features and GMV or FA were calculated using regression models. For FA but not GMV, we found significant differences between groups. BD-I patients showed lower FA compared with BD-II patients (ptfce-FWE = 0.006), primarily in the anterior corpus callosum. Compared with HC, BD-I patients exhibited lower FA in widespread clusters (ptfce-FWE < 0.001), including almost all major projection, association, and commissural fiber tracts. BD-II patients also demonstrated lower FA compared with HC, although less pronounced (ptfce-FWE = 0.049). The results remained unchanged after controlling for clinical and genetic features, for which no independent associations with FA or GMV emerged. Our findings suggest that, at a neurobiological level, BD subtypes may reflect distinct degrees of disease expression, with increasing WM microstructure disruption from BD-II to BD-I. This differential magnitude of microstructural alterations was not clearly linked to clinical and genetic variables. These findings should be considered when discussing the classification of BD subtypes within the spectrum of affective disorders.

Lithium response in bipolar disorder is associated with focal adhesion and PI3K-Akt networks: a multi-omics replication study.

Lithium is the gold standard treatment for bipolar disorder (BD). However, its mechanism of action is incompletely understood, and prediction of treatment outcomes is limited. In our previous multi-omics study of the Pharmacogenomics of Bipolar Disorder (PGBD) sample combining transcriptomic and genomic data, we found that focal adhesion, the extracellular matrix (ECM), and PI3K-Akt signaling networks were associated with response to lithium. In this study, we replicated the results of our previous study using network propagation methods in a genome-wide association study of an independent sample of 2039 patients from the International Consortium on Lithium Genetics (ConLiGen) study. We identified functional enrichment in focal adhesion and PI3K-Akt pathways, but we did not find an association with the ECM pathway. Our results suggest that deficits in the neuronal growth cone and PI3K-Akt signaling, but not in ECM proteins, may influence response to lithium in BD.

Pharmacogenomic overlap between antidepressant treatment response in major depression & antidepressant associated treatment emergent mania in bipolar disorder.

There is increasing interest in individualizing treatment selection for more than 25 regulatory approved treatments for major depressive disorder (MDD). Despite an inconclusive efficacy evidence base, antidepressants (ADs) are prescribed for the depressive phase of bipolar disorder (BD) with oftentimes, an inadequate treatment response and or clinical concern for mood destabilization. This study explored the relationship between antidepressant response in MDD and antidepressant-associated treatment emergent mania (TEM) in BD. We conducted a genome-wide association study (GWAS) and polygenic score analysis of TEM and tested its association in a subset of BD-type I patients treated with SSRIs or SNRIs. Our results did not identify any genome-wide significant variants although, we found that a higher polygenic score (PGS) for antidepressant response in MDD was associated with higher odds of TEM in BD. Future studies with larger transdiagnostic depressed cohorts treated with antidepressants are encouraged to identify a neurobiological mechanism associated with a spectrum of depression improvement from response to emergent mania.

Gene expression insights: Chronic stress and bipolar disorder: A bioinformatics investigation.

Bipolar disorder (BD) is a psychiatric disorder that affects an increasing number of people worldwide. The mechanisms of BD are unclear, but some studies have suggested that it may be related to genetic factors with high heritability. Moreover, research has shown that chronic stress can contribute to the development of major illnesses. In this paper, we used bioinformatics methods to analyze the possible mechanisms of chronic stress affecting BD through various aspects. We obtained gene expression data from postmortem brains of BD patients and healthy controls in datasets GSE12649 and GSE53987, and we identified 11 chronic stress-related genes (CSRGs) that were differentially expressed in BD. Then, we screened five biomarkers (IGFBP6, ALOX5AP, MAOA, AIF1 and TRPM3) using machine learning models. We further validated the expression and diagnostic value of the biomarkers in other datasets (GSE5388 and GSE78936) and performed functional enrichment analysis, regulatory network analysis and drug prediction based on the biomarkers. Our bioinformatics analysis revealed that chronic stress can affect the occurrence and development of BD through many aspects, including monoamine oxidase production and decomposition, neuroinflammation, ion permeability, pain perception and others. In this paper, we confirm the importance of studying the genetic influences of chronic stress on BD and other psychiatric disorders and suggested that biomarkers related to chronic stress may be potential diagnostic tools and therapeutic targets for BD.