Lithium is a first-line treatment for bipolar disorder (BD), but weight gain is a common side effect, leading to physical comorbidities and reduced average life expectancy. Some individuals are predisposed to weight gain due to lithium therapy, indicating the need to explore metabolic differences to prevent health complications. This descriptive feasibility study aimed to explore metabolic parameters in lithium-naïve BD individuals who later gained weight during lithium therapy versus those who did not. Data from BD individuals (N = 10) were included, five of whom gained weight (≥ 5 kg) during lithium treatment and five who did not. Nuclear Magnetic Resonance spectroscopy was used to measure blood serum lipoprotein and inflammation parameters, as well as molecular metabolites before lithium treatment. Univariate t-tests and multivariate orthogonal partial least-squares discriminant analysis (oPLS-DA) were performed to observe metabolomic between-group differences. The multivariate oPLS-DA did not show significant differences between the groups, but data visualization suggested distinct metabolic profiles. Univariate analyses revealed significantly elevated lipoprotein parameters in the weight gain group, which did not remain significant after correction for multiple testing. Phenylalanine levels showed an observable but non-significant downward trend in the weight gain group (fold change = 0.40, p = .057). The findings suggest a link between weight gain during lithium therapy and altered lipoprotein metabolism, aligning with previous research. However, larger studies are needed to further explore the underlying mechanisms. These preliminary findings represent a stepping stone for personalized lithium treatment strategies, which could help mitigate adverse metabolic side effects and improve treatment adherence.

This scoping review synthesized evidence on vitamin D, parathyroid hormone (PTH), and serum calcium in bipolar disorder (BD) to evaluate their potential clinical utility. A systematic PubMed search identified original studies examining calcium metabolism biomarkers (vitamin D, PTH, serum calcium) exclusively in BD populations. Findings were synthesized narratively due to substantial methodological heterogeneity. Fourteen studies met inclusion criteria, with small sample sizes (median n = 55) and predominantly cross-sectional designs. Vitamin D comparisons between BD patients and controls yielded contradictory results: three studies reported significantly lower levels in BD patients, two found significantly higher levels, and three found no differences. Vitamin D deficiency definitions varied widely (< 25 to < 50 nmol/L), precluding meaningful comparisons. Four cognition studies showed inconsistent associations with vitamin D, with negative correlations, age-dependent effects, or no associations reported. Two small vitamin D supplementation studies in bipolar spectrum disorders yielded contradictory results in distinct populations, with one in youth and the other in adults. Data on PTH and calcium were sparse and inconsistent. Study limitations included a single database search, substantial study heterogeneity, and inadequate control for confounders, including seasonal variation. Evidence on calcium metabolism biomarkers in BD is contradictory and methodologically limited. Fundamental inconsistencies in vitamin D status between BD patients and controls, combined with conflicting supplementation data, preclude clinical recommendations. Routine vitamin D screening specifically for BD management cannot be supported. Large-scale, standardized studies are needed before clinical application.

BACKGROUND:The gut microbiome plays a central role in human health and is strongly influenced by diet. Probiotics can beneficially modulate the microbiome and, through the gut-brain axis, may affect mood, appetite, and food preferences. This randomized controlled trial examined whether three months of probiotic supplementation could alter dietary intake in individuals with major depression (MD) and healthy controls (HC). METHODS:In this double-blind, placebo-controlled trial, 53 participants (23 with MD, 30 HC) received either a multi-strain probiotic or placebo twice daily for three months. Dietary intake was assessed at baseline and three follow-ups using the Vienna Food Record (VFR). Nutritional data were analyzed with nut.s® software and evaluated using mixed ANOVAs for repeated measures. These analyses represent additional data collected within the framework of the ProBioHRV study. RESULTS:Changes across dietary measures were generally small, with only a limited number reaching statistical significance. Significant three-way interactions (time × intervention × diagnosis) emerged for vitamin D intake, dietary variety, folic acid, and diversity. In HC, probiotic supplementation was associated with higher vitamin D intake after one week, while in MD, a similar increase was observed after three months (trend level, p = .058). Conversely, participants receiving probiotics showed lower dietary variety and diversity scores at several time points. Across all time points, folic acid intake was lower in MD compared to HC, independent of intervention. CONCLUSION:Probiotic supplementation did not produce consistent changes in nutrient intake but showed exploratory, time- and group-dependent patterns for selected measures, including vitamin D intake and dietary variety and diversity. Given the pilot nature of the study, these findings are descriptive and hypothesis- generating. Larger, well-powered studies with objective nutritional and microbiome measures are required.

This study performs patient-to-mouse fecal microbiota transplantation (FMT) as an experimental platform to investigate gut-brain axis alterations with potential relevance to psychiatric disorders, integrating metabolic modeling with measured metabolites and multi-layer molecular profiling. Microbial communities of a stool sample associated with bipolar disorder (BD) displayed a reduced ecological diversity and diminished metabolic potential, particularly within glutamate, aspartate, and GABA biosynthetic pathways. Upon transplantation with BD patient microbiota, recipient mice displayed a markedly altered microbiome characterized by loss of Akkermansia and expansion of Alloprevotella, alongside disruptions in amino acid and carbohydrate metabolism not evident in mice colonized by a healthy donor microbiota. Metabolic microbiome alterations in BD-recipient mice were also correlated to reduced glutathione levels in gut tissue, likely indicating increased oxidative stress, and decreased mRNA expression of key enteroendocrine hormones, including peptide YY and glucagon. Brain metabolomic profiling of BD-recipient mice revealed significant depletion of glycine, choline, and methionine levels connected to anxiety-like phenotypes in elevated plus-maze and light-dark box behavioral tests. Akkermansia abundance positively correlated with physical activity and exploratory behavior, highlighting an important role of this taxon in gut-brain signaling. Collectively, these findings identify distinct microbial, metabolic, and neurobehavioral signatures transmittable from humans to mice via FMT and demonstrate that differences in donor microbiome diversity and metabolic capacity shape engraftment dynamics in recipient mice, which contribute to differences in gut-brain signaling.

Bipolar disorder is a heritable mental illness with complex etiology. While the largest published genome-wide association study identified 64 bipolar disorder risk loci, the causal SNPs and genes within these loci remain unknown. We applied a suite of statistical and functional fine-mapping methods to these loci and prioritized 17 likely causal SNPs for bipolar disorder. We mapped these SNPs to genes and investigated their likely functional consequences by integrating variant annotations, brain cell-type epigenomic annotations, brain quantitative trait loci and results from rare variant exome sequencing in bipolar disorder. Convergent lines of evidence supported the roles of genes involved in neurotransmission and neurodevelopment, including SCN2A, TRANK1, DCLK3, INSYN2B, SYNE1, THSD7A, CACNA1B, TUBBP5, FKBP2, RASGRP1, FURIN, FES, MED24 and THRA among others in bipolar disorder. These represent promising candidates for functional experiments to understand biological mechanisms and therapeutic potential. Additionally, we demonstrated that fine-mapping effect sizes can improve performance of bipolar disorder polygenic risk scores across diverse populations and present a high-throughput fine-mapping pipeline.

Background: Polygenic scores (PGSs) hold the potential to identify patients who respond favorably to specific psychiatric treatments. However, their biological interpretation remains unclear. In this study, we developed pathway-specific PGSs (PSPGSs) for lithium response and assessed their association with clinical lithium response in patients with bipolar disorder. Methods: Using sets of genes involved in pathways affected by lithium, we developed 9 PSPGSs and evaluated their associations with lithium response in the International Consortium on Lithium Genetics (ConLi+Gen) (N = 2367), with validation in combined PsyCourse (Pathomechanisms and Signatures in the Longitudinal Course of Psychosis) (N = 105) and BipoLife (N = 102) cohorts. The association between each PSPGS and lithium response—defined both as a continuous ALDA score and a categorical outcome (good vs. poor responses)—was evaluated using regression models, with adjustment for confounders. The cutoff for a significant association was p < .05 after multiple testing correction. Results: The PGSs for acetylcholine, GABA (gamma-aminobutyric acid), and mitochondria were associated with response to lithium in both categorical and continuous outcomes. However, the PGSs for calcium channel, circadian rhythm, and GSK (glycogen synthase kinase) were associated only with the continuous outcome. Each score explained 0.29% to 1.91% of the variance in the categorical and 0.30% to 1.54% of the variance in the continuous outcomes. A multivariate model combining PSPGSs that showed significant associations in the univariate analysis (combined PSPGS) increased the percentage of variance explained (R2) to 3.71% and 3.18% for the categorical and continuous outcomes, respectively. Associations for PGSs for GABA and circadian rhythm were replicated. Patients with the highest genetic loading (10th decile) for acetylcholine variants were 3.03 times more likely (95% CI, 1.95 to 4.69) to show a good lithium response (categorical outcome) than patients with the lowest genetic loading (1st decile). Conclusions: PSPGSs achieved predictive performance comparable to the conventional genome-wide PGSs, with the added advantage of biological interpretability using a smaller list of genetic variants.

Background Anorexia nervosa (AN) is characterized by high mortality, limited treatment options, altered gut microbiome composition, and impaired feedback (FB) learning. This pilot study explores the relationship between gut microbiome composition and reduced implicit FB learning in AN. Methods Sixteen female patients with AN and fourteen healthy controls (HC) completed the Weather Prediction Task to assess implicit learning (feedback and paired-associate formats). Gut microbiome composition was analyzed via Illumina sequencing, with species differences identified using linear discriminant effect size (LEfSe) analysis. Results Patients with AN had lower FB learning scores compared to HC (p = .012), while no significant difference in the paired-associate task was found (p = .905). Better feedback learning was associated with greater gut microbiome diversity, indicated by a larger number of observed species (r = 0.45, p = .013), and a higher Shannon index (r = 0.39, p = .035). LEfSe analysis revealed an increased abundance of Akkermansia muciniphila in AN, while short-chain fatty acid-producing species (such as phylum Firmicutes, including Roseburia, Agathobacter and Faecalibacterium) were more prevalent in HC. Participants with higher FB learning exhibited an increase in Actinobacteria, particularly Bifidobacteria, while those with low FB learning had an increase in the Lachnospirales of the phylum Firmicutes. Conclusions These findings highlight the gut microbiome's potential role in implicit learning in AN, which could play an important role in the success of treatments. Future research should focus on microbiome-targeted interventions, such as probiotics, particularly Bifidobacteria, to improve gut health and implicit learning in patients with AN.

Bipolar disorder is a leading contributor to the global burden of disease1. Despite high heritability (60-80%), the majority of the underlying genetic determinants remain unknown2. We analysed data from participants of European, East Asian, African American and Latino ancestries (n = 158,036 cases with bipolar disorder, 2.8 million controls), combining clinical, community and self-reported samples. We identified 298 genome-wide significant loci in the multi-ancestry meta-analysis, a fourfold increase over previous findings3, and identified an ancestry-specific association in the East Asian cohort. Integrating results from fine-mapping and other variant-to-gene mapping approaches identified 36 credible genes in the aetiology of bipolar disorder. Genes prioritized through fine-mapping were enriched for ultra-rare damaging missense and protein-truncating variations in cases with bipolar disorder4, highlighting convergence of common and rare variant signals. We report differences in the genetic architecture of bipolar disorder depending on the source of patient ascertainment and on bipolar disorder subtype (type I or type II). Several analyses implicate specific cell types in the pathophysiology of bipolar disorder, including GABAergic interneurons and medium spiny neurons. Together, these analyses provide additional insights into the genetic architecture and biological underpinnings of bipolar disorder.

BackgroundBipolar disorder is associated with impairments in cognition and psychosocial functioning. Although these impairments occur frequently, often persist during euthymic times, and worsen quality of life, the impact of cognitive abilities on functioning has not yet been fully elucidated.MethodsThe current study investigated the effects of cognitive domains (attention/psychomotor speed, verbal learning/memory, executive function) on psychosocial functioning cross-sectionally. Data from 210 euthymic individuals with bipolar disorder [101 female, 109 male; M(age) = 44.47; SD(age) = 14.25] were included into the analysis. A neurocognitive test battery was administered and the Global Assessment of Functioning was used to depict psychosocial functioning. Correlation analyses were conducted to observe the associations between functioning and the cognitive domains. Moreover, three hierarchical regression analyses were applied to predict functioning by each of the cognitive domains, while considering age, sex, and education as control variables.ResultsCorrelation analyses revealed that functioning was positively associated with attention/psychomotor speed and verbal learning/memory. However, the consecutive hierarchical regression analyses found that none of the cognitive domains were able predict functioning beyond the control variables age, sex, and education.ConclusionOur findings indicate that greater abilities in the domains of attention/psychomotor speed and verbal learning/memory are associated with better functioning. However, this association can be explained by other relevant variables such as age or education, indicating that cognitive abilities are not the sole contributor of psychosocial functioning. Investigating other measurements of functioning or cognitive abilities could lead to different results. Nevertheless, promoting cognitive abilities and autonomy in daily life remains an important aspect of therapy in bipolar disorder.

Importance:The clinical heterogeneity of bipolar disorder (BD) is a major obstacle to improving diagnosis, predicting patient outcomes, and developing personalized treatments. A genetic approach is needed to deconstruct the disorder and uncover its fundamental biology. Previous genetic studies focusing on broad diagnostic categories have been limited in their ability to parse this complexity. Objective:To test the hypothesis that clinically distinct subphenotypes of BD are associated with different underlying common variant genetic architectures. Design Setting and Participants:This multicenter study included a primary genome-wide association study (GWAS) of up to 23,819 bipolar disorder (BD) cases and 163,839 controls. These results were integrated via multi-trait analysis of GWAS (MTAG) with external summary statistics for BD (59,287 cases; 781,022 controls) and schizophrenia (SCZ; 53,386 cases; 77,258 controls). Sample overlap was statistically accounted for. Main Outcomes and Measures:The primary outcomes were the genetic dimensions underlying BD heterogeneity, differentiated by single nucleotide polymorphism (SNP)-heritability (h 2 SNP ), genetic correlations, genomic loci ( P ≤5×10 -8 ), and functional, cell-type, and gene-expression pathway analyses. Results:We identified four genetically-informed dimensions of BD: Severe Illness, Core Mania, Externalizing/Impulsive Comorbidity, and Internalizing/Affective Comorbidity. The analyses yielded up to 181 subphenotype-associated loci, 53 of which are novel. The Severe Illness Dimension was characterized by a unique neuro-immune signature (a protective association with HLA-DMB , P =2.50×10 -273 ) evident only when leveraging SCZ genetic data. The Internalizing/Affective dimension was associated with neurodevelopmental genes (e.g., DCC ). Notably, the rapid-cycling subphenotype showed a unique signature of strong negative selection, a finding not observed in other subphenotypes. Conclusions and Relevance:The clinical heterogeneity of bipolar disorder appears to be defined by a complex and multi-layered genetic architecture. The presented findings provide an empirical framework that may advance psychiatric nosology beyond its current diagnostic boundaries. These results may also inform future research to identify targets for personalized interventions. The delineation of these genetically-informed dimensions offers specific, biologically-grounded hypotheses for subsequent therapeutic discovery. Establishing such a framework is an essential step toward refining diagnostic criteria and developing more effective, personalized treatments. This work lays the foundation for a transition from a uniform treatment model to the paradigm of precision psychiatry. Key Points:Question: What are the distinct genetic architectures underlying the clinical heterogeneity of bipolar disorder?Findings: In this genetic study of 23,819 bipolar disorder (BD) cases and 163,839 controls, clinical heterogeneity mapped onto four genetically-informed dimensions. A severe illness dimension was defined by a neuro-immune signature ( HLA-DMB ) shared with schizophrenia. An affective comorbidity dimension was distinguished by neurodevelopmental pathways involving axonal guidance ( DCC ). Notably, the rapid-cycling phenotype showed evidence of purifying selection, suggesting influence by rare, highly penetrant alleles. Meaning: These findings provide a data-driven biological framework for bipolar disorder, guiding future research toward patient stratification and targeted therapeutics.

IntroductionC-reactive protein (CRP) is a systemic inflammatory marker, which indicates systemic inflammatory processes It is involved in different inflammatory processes of the body and is a reliable marker for the general inflammatory state of the body. High sensitive CRP seems to play a key role as a state and trait marker of bipolar disorder (BD). In the current study, we tried to determine the long-term effect of CRP levels on clinical symptoms and illness course of bipolar disorder.MethodsFor the current study, we examined 106 patients with BD for a period of four years. Participants underwent a clinical screening for depressive and manic episodes with the Hamilton Depression Scale (HAMD) and the Young Mania Rating Score (YMRS) and a serological diagnostic for inflammatory parameters every six months, thus leading to 8 measurement times in total. Patients with the presence of severe medical or neurological comorbidities such as active cancer, chronic obstructive lung disease, rheumatoid arthritis, systemic lupus erythematosus, Alzheimer’s disease, Parkinson’s disease, Huntington’s disease or multiple sclerosis and acute infections were not included in the study.ResultsIn our sample, 26% showed a mean hsCRP above 5 mg/dl. Those patients showed a significantly higher mean YMRS score than those with a mean hsCRP under 5 mg/dl during our observation period. Regarding HAMD there was no significant difference in hsCRP values. The existence of lithium treatment showed no significant influence on mean hsCRP levels between the start and endpoint.ConclusionIndividuals who were exposed to a higher level of inflammation over time suffered from more manic symptoms in this period. These findings underline the hypothesis that inflammatory processes have an accumulative influence on the illness course of BD, especially concerning manic symptoms and episodes.

Background:Lithium (Li) remains the treatment of choice for bipolar disorders (BP). Its mood-stabilizing effects help reduce the long-term burden of mania, depression and suicide risk in patients with BP. It also has been shown to have beneficial effects on disease-associated conditions, including sleep and cardiovascular disorders. However, the individual responses to Li treatment vary within and between diagnostic subtypes of BP (e.g. BP-I and BP-II) according to the clinical presentation. Moreover, long-term Li treatment has been linked to adverse side-effects that are a cause of concern and non-adherence, including the risk of developing chronic medical conditions such as thyroid and renal disease. In recent years, studies by the Consortium on Lithium Genetics (ConLiGen) have uncovered a number of genetic factors that contribute to the variability in Li treatment response in patients with BP. Here, we leveraged the ConLiGen cohort (N=2,064) to investigate the genetic basis of Li effects in BP. For this, we studied how Li response and linked genes associate with the psychiatric symptoms and polygenic load for medical comorbidities, placing particular emphasis on identifying differences between BP-I and BP-II. Results:We found that clinical response to Li treatment, measured with the Alda scale, was associated with a diminished burden of mania, depression, substance and alcohol abuse, psychosis and suicidal ideation in patients with BP-I and, in patients with BP-II, of depression only. Our genetic analyses showed that a stronger clinical response to Li was modestly related to lower polygenic load for diabetes and hypertension in BP-I but not BP-II. Moreover, our results suggested that a number of genes that have been previously linked to Li response variability in BP differentially relate to the psychiatric symptomatology, particularly to the numbers of manic and depressive episodes, and to the polygenic load for comorbid conditions, including diabetes, hypertension and hypothyroidism. Conclusions:Taken together, our findings suggest that the effects of Li on symptomatology and comorbidity in BP are partially modulated by common genetic factors, with differential effects between BP-I and BP-II.

Background: Culinary medicine integrates healthy eating with positive food experiences, offering a holistic approach to treating mental health disorders, such as depression and eating disorders, where disruptions in eating habits and mood are common. While traditional psychiatric treatments focus on medication and psychotherapy, culinary workshops provide a novel intervention for inpatient care. This study evaluated the effectiveness of culinary medicine cooking workshops as a supplementary treatment for psychiatric inpatients with depression and eating disorders. Methods: We assessed the feasibility of five cooking workshops led by a professional chef and nutritional therapist in 39 psychiatric inpatients (depression, n = 29; eating disorders, n = 10). Participants completed questionnaires on dietary habits, mood, and workshop feedback before and after the intervention. Results: The workshops were highly accepted, with 90% of participants reporting they would recommend them for recovery. Significant improvements were observed in mood (p < 0.001), sadness (p < 0.001), hopelessness (p = 0.002), and tiredness (p = 0.003) across the overall group. Patients with depression showed improvements in nearly all mood subscales, while those with eating disorders improved in sadness (p = 0.029). Conclusions: Culinary medicine workshops are a promising tool for enhancing mood and reducing hopelessness and tiredness in inpatients with depression. They also promote sustainable lifestyle changes that may benefit long-term physical and mental health. Future studies should explore the long-term impact of these interventions on psychiatric disorders.

INTRODUCTION:An increasing body of evidence suggests a strong relationship between gut health and mental state. Lately, a connection between butyrate-producing bacteria and sleep quality has been discussed. The PROVIT study, as a randomized, double-blind, 4-week, multispecies probiotic intervention study, aims at elucidating the potential interconnection between the gut's metabolome and the molecular clock in individuals with major depressive disorder (MDD). METHODS:The aim of the PROVIT-CLOCK study was to analyze changes in core clock gene expression during treatment with probiotic intervention versus placebo in fasting blood and the connection with the serum- and stool-metabolome in patients with MDD (n = 53). In addition to clinical assessments in the PROVIT study, metabolomics analyses with 1H nuclear magnetic resonance spectroscopy (stool and serum) and gene expression (RT-qPCR) analysis of the core clock genes ARNTL, PER3, CLOCK, TIMELESS, NR1D1 in peripheral blood mononuclear cells of fasting blood were performed. RESULTS:The gene expression levels of the clock gene CLOCK were significantly altered only in individuals receiving probiotic add-on treatment. TIMELESS and ARNTL gene expression changed significantly over the 4-week intervention period in both groups. Various positive and negative correlations between metabolites in serum/stool and core clock gene expression levels were observed. CONCLUSION:Changing the gut microbiome by probiotic treatment potentially influences CLOCK gene expression. The preliminary results of the PROVIT-CLOCK study indicate a possible interconnection between the gut microbiome and circadian rhythm potentially orchestrated by metabolites.