Association of polygenic score and the involvement of cholinergic and glutamatergic pathways with lithium treatment response in patients with bipolar disorder.

Lithium is regarded as the first-line treatment for bipolar disorder (BD), a severe and disabling mental health disorder that affects about 1% of the population worldwide. Nevertheless, lithium is not consistently effective, with only 30% of patients showing a favorable response to treatment. To provide personalized treatment options for bipolar patients, it is essential to identify prediction biomarkers such as polygenic scores. In this study, we developed a polygenic score for lithium treatment response (Li+PGS) in patients with BD. To gain further insights into lithium's possible molecular mechanism of action, we performed a genome-wide gene-based analysis. Using polygenic score modeling, via methods incorporating Bayesian regression and continuous shrinkage priors, Li+PGS was developed in the International Consortium of Lithium Genetics cohort (ConLi+Gen: N = 2367) and replicated in the combined PsyCourse (N = 89) and BipoLife (N = 102) studies. The associations of Li+PGS and lithium treatment response - defined in a continuous ALDA scale and a categorical outcome (good response vs. poor response) were tested using regression models, each adjusted for the covariates: age, sex, and the first four genetic principal components. Statistical significance was determined at P < 0.05. Li+PGS was positively associated with lithium treatment response in the ConLi+Gen cohort, in both the categorical (P = 9.8 × 10-12, R2 = 1.9%) and continuous (P = 6.4 × 10-9, R2 = 2.6%) outcomes. Compared to bipolar patients in the 1st decile of the risk distribution, individuals in the 10th decile had 3.47-fold (95%CI: 2.22-5.47) higher odds of responding favorably to lithium. The results were replicated in the independent cohorts for the categorical treatment outcome (P = 3.9 × 10-4, R2 = 0.9%), but not for the continuous outcome (P = 0.13). Gene-based analyses revealed 36 candidate genes that are enriched in biological pathways controlled by glutamate and acetylcholine. Li+PGS may be useful in the development of pharmacogenomic testing strategies by enabling a classification of bipolar patients according to their response to treatment.

Machine-based learning of multidimensional data in bipolar disorder - pilot results.

INTRODUCTION: Owing to the heterogenic picture of bipolar disorder, it takes approximately 8.8 years to reach a correct diagnosis. Early recognition and early intervention might not only increase quality of life, but also increase life expectancy as a whole in individuals with bipolar disorder. Therefore, we hypothesize that implementing machine learning techniques can be used to support the diagnostic process of bipolar disorder and minimize misdiagnosis rates. MATERIALS AND METHODS: To test this hypothesis, a de-identified data set of only demographic information and the results of cognitive tests of 196 patients with bipolar disorder and 145 healthy controls was used to train and compare five different machine learning algorithms. RESULTS: The best performing algorithm was logistic regression, with a macro-average F1-score of 0.69 [95% CI 0.66-0.73]. After further optimization, a model with an improved macro-average F1-score of 0.75, a micro-average F1-score of 0.77, and an AUROC of 0.84 was built. Furthermore, the individual amount of contribution per variable on the classification was assessed, which revealed that body mass index, results of the Stroop test, and the d2-R test alone allow for a classification of bipolar disorder with equal performance. CONCLUSION: Using these data for clinical application results in an acceptable performance, but has not yet reached a state where it can sufficiently augment a diagnosis made by an experienced clinician. Therefore, further research should focus on identifying variables with the highest amount of contribution to a model's classification.

PROVIT-CLOCK: A Potential Influence of Probiotics and Vitamin B7 Add-On Treatment and Metabolites on Clock Gene Expression in Major Depression.

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.

Impaired implicit learning in adults with anorexia nervosa.

OBJECTIVE: Cognitive alterations play an important role in the pathophysiology and treatment of anorexia nervosa (AN). Previous studies suggest that some implicit learning processes may be inhibited in AN. However, this has not yet been fully explored. The purpose of this study is to analyze implicit learning in patients with AN in comparison to healthy controls. METHODS: In this pilot-study, a total of 21 patients diagnosed with AN and 21 matched controls were administered the weather prediction task (WPT), a probabilistic implicit category learning task that consists of two sub-variants. During the feedback (FB) version of the task, participants learn associations between tarot cards and weather outcomes via an operant learning model through which they receive immediate FB on their answers, whereas during the paired associate (PA) variant, participants are directly asked to memorize given associations. RESULTS: AN patients showed selective impairment on the FB task where they scored significantly lower both in comparison to controls (p = .001) who completed the same task and when compared to their own performance on the PA variant (p = .006). Clinical measures showed no significant correlations with test scores. DISCUSSION: Our results demonstrate implicit FB learning deficiencies in adult patients with AN. These impairments may have an impact on the effect of psychotherapeutic interventions and could partially explain the lack of treatment response in AN. Further studies are necessary to derive when and through which mechanisms these alterations originate, and to what extent they should be considered during treatment of the disorder. PUBLIC SIGNIFICANCE: Cognitive impairments pose a challenge in the management of anorexia nervosa. Improved comprehension of cognitive alterations could lead to a greater understanding of the disease and adaptation of psychotherapeutic treatments. In this study, we found that implicit feedback learning in anorexia nervosa is impaired compared to healthy controls. This could indicate the necessity of treatment adaptations in the form of therapy tools without feedback and a larger focus on psychoeducation.

Gut Microbiome Composition and Its Association with Sleep in Major Psychiatric Disorders.

INTRODUCTION: Sleep disturbances are highly prevalent across most major psychiatric disorders. Alterations in the hypothalamic-pituitary-adrenal axis, neuroimmune mechanisms, and circadian rhythm disturbances partially explain this connection. The gut microbiome is also suspected to play a role in sleep regulation, and recent studies suggest that certain probiotics, prebiotics, synbiotics, and fecal microbiome transplantation can improve sleep quality. METHODS: We aimed to assess the relationship between gut-microbiota composition, psychiatric disorders, and sleep quality in this cross-sectional, cross-disorder study. We recruited 103 participants, 63 patients with psychiatric disorders (major depressive disorder [n = 31], bipolar disorder [n = 13], psychotic disorder [n = 19]) along with 40 healthy controls. Sleep quality was assessed with the Pittsburgh Sleep Quality Index (PSQI). The fecal microbiome was analyzed using 16S rRNA sequencing, and groups were compared based on alpha and beta diversity metrics, as well as differentially abundant species and genera. RESULTS: A transdiagnostic decrease in alpha diversity and differences in beta diversity indices were observed in psychiatric patients, compared to controls. Correlation analysis of diversity metrics and PSQI score showed no significance in the patient and control groups. However, three species, Ellagibacter isourolithinifaciens, Senegalimassilia faecalis, and uncultured Blautia sp., and two genera, Senegalimassilia and uncultured Muribaculaceae genus, were differentially abundant in psychiatric patients with good sleep quality (PSQI >8), compared to poor-sleep quality patients (PSQI ≤8). CONCLUSION: In conclusion, this study raises important questions about the interconnection of the gut microbiome and sleep disturbances.

The Association of Tube Weaning and Oral Skill Development in Infants With Tube Dependency: A Prospective Study.

OBJECTIVE: This study was the first of its kind by assessing oral skills development during and after applying the "Graz Model" of tube weaning. METHODS: This prospective case series study included data of 67 (35 females, 32 males, treated from March 2018 to April 2019) tube dependent children, who participated in the effective "Graz Model" of tube weaning. Parents filled out the standardized Pediatric Assessment Scale for Severe Feeding Problems (PASSFP) prior to and immediately after completion of the program. Paired sample t tests were conducted to examine pre-to-post changes in the children's oral skills. RESULTS: The study showed that oral skills increased significantly during tube weaning PASSFP score of 24.76 (standard deviation, SD = 12.38) prior to versus 47.97 (SD = 6.98) after completion of the program. Furthermore, significant changes in their sensory and tactile perception and in their general eating behavior were observed. Children also showed reduced oral aversion symptoms and food pocketing, could enjoy their meals, and increased their food repertoire. Mealtime duration could be decreased, and parents were less anxious about their infants' intake and less frustrated because of their children's eating behavior. CONCLUSION: The results of this study demonstrated for the first time that tube dependent children can improve their oral skills significantly during and after their participation in the child-led approach of the "Graz model" of tube weaning.

[COVID-19 and Bipolar Affective Disorder: Subjective Changes in Lifestyle Variables During the First Lockdown During the COVID-19 Pandemic in Austria]. / COVID-19 und bipolare affektive Störung: Subjektive Veränderung der Lebensstilvariablen während des ersten Lockdowns in der COVID-19-Pandemie in Österreich.

INTRODUCTION: The COVID-19 pandemic with its protective measures (e. g. lockdown) had far-reaching effects on everyone's well-being. The aim of this study was to examine lifestyle variables during the first Austrian lockdown in patients with bipolar disorder in comparison to a healthy control group and to assess subjective changes caused by the pandemic. METHOD: At the beginning of April 2020, an online survey of n=75 participants (35 people with bipolar disorder and 40 healthy controls) with standardized questionnaires (Beck Depression Inventory-2, Food Craving Inventory, Altman Self Rating Mania Scale) as well as non-standardized COVID-19-specific questions on the subject of "Psychological stress and effects of the COVID-19 pandemic in bipolar disorder" was created and distributed via LimeSurvey. RESULTS: Both groups reported a negative impact on their mental health. The participants with bipolar disorder showed significantly higher values in the Beck Depression Inventory-2 score (p<0,001), in emotional distress due to social distancing (p=0,003) and significantly lower values in muscle-strengthening exercise (p=0,039) and in sport units (p=0,003) compared to the control group. In addition, patients with bipolar disorder smoked more often than individuals of the control group. People with bipolar disorder were 42,9% more likely to report they were less efficient during the pandemic, and 22,9% experienced weight gain compared to before the pandemic. The control group, on the other hand, was less efficient at 17,5% and 5,0% reported weight gain. However, a comparison with pre-pandemic data showed a decrease in food craving in both groups. CONCLUSION: This study provided first evidence of self-reported adverse effects on mental stress and lifestyle in people with bipolar disorder at the beginning of the COVID-19 pandemic. Psychiatric care and early interventions for patients with bipolar disorder would be particularly important in times of crisis in order to help maintain a healthy lifestyle and thus counteract unfavourable developments.

Using polygenic scores and clinical data for bipolar disorder patient stratification and lithium response prediction: machine learning approach.

BACKGROUND: Response to lithium in patients with bipolar disorder is associated with clinical and transdiagnostic genetic factors. The predictive combination of these variables might help clinicians better predict which patients will respond to lithium treatment. AIMS: To use a combination of transdiagnostic genetic and clinical factors to predict lithium response in patients with bipolar disorder. METHOD: This study utilised genetic and clinical data (n = 1034) collected as part of the International Consortium on Lithium Genetics (ConLi+Gen) project. Polygenic risk scores (PRS) were computed for schizophrenia and major depressive disorder, and then combined with clinical variables using a cross-validated machine-learning regression approach. Unimodal, multimodal and genetically stratified models were trained and validated using ridge, elastic net and random forest regression on 692 patients with bipolar disorder from ten study sites using leave-site-out cross-validation. All models were then tested on an independent test set of 342 patients. The best performing models were then tested in a classification framework. RESULTS: The best performing linear model explained 5.1% (P = 0.0001) of variance in lithium response and was composed of clinical variables, PRS variables and interaction terms between them. The best performing non-linear model used only clinical variables and explained 8.1% (P = 0.0001) of variance in lithium response. A priori genomic stratification improved non-linear model performance to 13.7% (P = 0.0001) and improved the binary classification of lithium response. This model stratified patients based on their meta-polygenic loadings for major depressive disorder and schizophrenia and was then trained using clinical data. CONCLUSIONS: Using PRS to first stratify patients genetically and then train machine-learning models with clinical predictors led to large improvements in lithium response prediction. When used with other PRS and biological markers in the future this approach may help inform which patients are most likely to respond to lithium treatment.

Association of polygenic score for major depression with response to lithium in patients with bipolar disorder.

Lithium is a first-line medication for bipolar disorder (BD), but only one in three patients respond optimally to the drug. Since evidence shows a strong clinical and genetic overlap between depression and bipolar disorder, we investigated whether a polygenic susceptibility to major depression is associated with response to lithium treatment in patients with BD. Weighted polygenic scores (PGSs) were computed for major depression (MD) at different GWAS p value thresholds using genetic data obtained from 2586 bipolar patients who received lithium treatment and took part in the Consortium on Lithium Genetics (ConLi+Gen) study. Summary statistics from genome-wide association studies in MD (135,458 cases and 344,901 controls) from the Psychiatric Genomics Consortium (PGC) were used for PGS weighting. Response to lithium treatment was defined by continuous scores and categorical outcome (responders versus non-responders) using measurements on the Alda scale. Associations between PGSs of MD and lithium treatment response were assessed using a linear and binary logistic regression modeling for the continuous and categorical outcomes, respectively. The analysis was performed for the entire cohort, and for European and Asian sub-samples. The PGSs for MD were significantly associated with lithium treatment response in multi-ethnic, European or Asian populations, at various p value thresholds. Bipolar patients with a low polygenic load for MD were more likely to respond well to lithium, compared to those patients with high polygenic load [lowest vs highest PGS quartiles, multi-ethnic sample: OR = 1.54 (95% CI: 1.18-2.01) and European sample: OR = 1.75 (95% CI: 1.30-2.36)]. While our analysis in the Asian sample found equivalent effect size in the same direction: OR = 1.71 (95% CI: 0.61-4.90), this was not statistically significant. Using PGS decile comparison, we found a similar trend of association between a high genetic loading for MD and lower response to lithium. Our findings underscore the genetic contribution to lithium response in BD and support the emerging concept of a lithium-responsive biotype in BD.

Eating Habits and Eating Disorder Associated Behavior in Bipolar Disorder.

ABSTRACT: A relevant comorbidity of bipolar disorder (BD) is eating disorders (EDs). Crossed vulnerability factors as eating disorder-specific symptoms (EDSSs) may trigger the onset of both disorders in either direction. The Structured Inventory for Anorexic and Bulimic Eating Disorders for Self-Report was used to examine the occurrence of EDs in euthymic/subsyndromal individuals with BD ( n = 86) and healthy controls ( n = 86) matched for age and sex. Furthermore, we explored EDSSs with the subscales "general psychopathology and social integration," "bulimic symptoms," "body image and slimness ideal," "sexuality and body weight," "counteract," and "atypical binge." Higher rates of all EDSSs were reported in BD. Younger individuals with BD showed higher expression in "bulimic symptoms," "body image and slimness ideal," and "atypical binge" subscales. No participants fulfilled ED diagnosis. The findings show a link between EDSS and BD. Clinicians should pay attention to a multimodal intervention, considering risk factors, investigating eating habits and ED associated behaviors.

[Symptom Monitoring and Detection of Early Warning Signs in Bipolar Episodes Via App - Views of Patients and Relatives on e-Health Need]. / Notwendigkeit für Symptom-Monitoring und Frühwarnzeichenerkennung bipolarer Episoden durch eine App? ­ Ansichten von PatientInnen und Angehörigen zu e-health Bedarf.

BACKGROUND: The onset and early warning signs of episodes of bipolar disorder are often realized late by those affected. The earlier an incipient episode is treated, the more prognostically favorable the course will be. Symptom monitoring via smartphone application (app) could be an innovative way to recognize and react to early warning signs more swiftly. The aim of this study was to find out whether patients and their relatives consider technical support through an app to be useful and practical in the early warning sign detection and treatment. METHODS: In the present study, 51 patients with bipolar disorder and 28 relatives were interviewed. We gathered information on whether participants were able to perceive early warning signs in form of behavioral changes sufficiently and in a timely fashion and also whether they would use an app as treatment support tool. RESULTS: Although 94.1% of the surveyed patients and 78.6% of their relatives felt that they were well informed about the disease, 13.7% and 35.7%, respectively were not fully satisfied with the current treatment options. Early warning signs of every depressive development were noticed by 25.5% of the patients (relatives 10.7%). Every (hypo)manic development was only noticed by 11.8% of the patients (relatives 7.1%); 88.2% of the patients and 85.7% of the relatives noticed the same symptoms recurrently at the beginning of a depression and 70.6% and 67.9%, respectively, at the beginning of a (hypo)manic episode (in particular changes in physical activity, communication behavior and the sleep-wake rhythm). 84.3% of the patients and 89.3% of the relatives stated that they considered technical support that draws attention to mood and activity changes as useful and that they would use such an app for the treatment. DISCUSSION: The current options for perceiving early warning signs of a depressive or (hypo)manic episode in bipolar disorder are clinically inadequate. Those affected and their relatives desire innovative, technical support. Early detection of symptoms, which often manifest themselves in changes in behavior or activity patterns, is essentiell for managing the course of bipolar disorder. In the future, smartphone apps could be used for clinical treatment and research through objective, continuous and.

The Outcome of Psychiatric Rehabilitation Treatment Depends on Affective State at the Time of Admission.

BACKGROUND: In Austria, new approaches of rehabilitation programs focus on the prevention of mental illness and offer treatment not only for acute psychiatric patients, but also for those who are at risk of developing a mental disorder or have recovered from one.The aim of this study was to determine the effects of a psychiatric rehabilitation program on individuals with different mood states. SUBJECTS AND METHODS: 600 patients with a history of affective disorder were tested at the time of admission to an Austrian inpatient psychiatric rehabilitation center. Data of extreme groups - patients who were depressed (n=59; BDI-II<9 and HAMD<8) or euthymic (n=59; BDI<18 and HAMD>19) at the time of therapy start - were analyzed. The participants completed the Maslach Burnout Inventory - General Survey, the Symptom Checklist - Revised and the Stress Coping Questionnaire at the beginning and the end of the 6-weeks rehabilitation program. RESULTS: After 6 weeks, both groups showed significantly less psychiatric symptoms (BDI-II, HAMD, SCL-90, and negative coping strategies (SVF). Importantly, work-related stress symptoms ("burnout" symptoms) improved significantly in the euthymic group. CONCLUSIONS: Euthymic patients seem to be able to focus on work-related stress symptoms including reduced emotional exhaustion through treatment, while currently depressed patients primarily benefit by an improvement in general psychiatric symptomatology. The results indicate the crucial role of mood state validated with standardized psychological questionnaires BDI-II and HAMD at time of admission to such programs. These findings could have implications on treatment decisions for psychiatric patients and assist in making a forecast concerning ability to recover and treatment prognosis.

Characterisation of age and polarity at onset in bipolar disorder.

BACKGROUND: Studying phenotypic and genetic characteristics of age at onset (AAO) and polarity at onset (PAO) in bipolar disorder can provide new insights into disease pathology and facilitate the development of screening tools. AIMS: To examine the genetic architecture of AAO and PAO and their association with bipolar disorder disease characteristics. METHOD: Genome-wide association studies (GWASs) and polygenic score (PGS) analyses of AAO (n = 12 977) and PAO (n = 6773) were conducted in patients with bipolar disorder from 34 cohorts and a replication sample (n = 2237). The association of onset with disease characteristics was investigated in two of these cohorts. RESULTS: Earlier AAO was associated with a higher probability of psychotic symptoms, suicidality, lower educational attainment, not living together and fewer episodes. Depressive onset correlated with suicidality and manic onset correlated with delusions and manic episodes. Systematic differences in AAO between cohorts and continents of origin were observed. This was also reflected in single-nucleotide variant-based heritability estimates, with higher heritabilities for stricter onset definitions. Increased PGS for autism spectrum disorder (ß = -0.34 years, s.e. = 0.08), major depression (ß = -0.34 years, s.e. = 0.08), schizophrenia (ß = -0.39 years, s.e. = 0.08), and educational attainment (ß = -0.31 years, s.e. = 0.08) were associated with an earlier AAO. The AAO GWAS identified one significant locus, but this finding did not replicate. Neither GWAS nor PGS analyses yielded significant associations with PAO. CONCLUSIONS: AAO and PAO are associated with indicators of bipolar disorder severity. Individuals with an earlier onset show an increased polygenic liability for a broad spectrum of psychiatric traits. Systematic differences in AAO across cohorts, continents and phenotype definitions introduce significant heterogeneity, affecting analyses.

Body Mass Index Predicts Decline in Executive Function in Bipolar Disorder: Preliminary Data of a 12-Month Follow-up Study.

INTRODUCTION: Obesity and associated risk factors have been linked to cognitive decline before. OBJECTIVES: In the present study, we evaluated potential cumulative negative effects of overweight and obesity on cognitive performance in euthymic patients with bipolar disorder (BD) in a longitudinal design. METHODS: Neurocognitive measures (California Verbal Learning Test, Trail Making Test [TMT] A/B, Digit-Symbol-Test, Digit-Span, d2 Test), anthropometrics (e.g., body mass index [BMI]), and clinical ratings (Hamilton Depression Scale, Young Mania Rating Scale) were collected over a 12-month observation period. Follow-up data of 38 patients with BD (mean age 40 years; 15 males, 23 females) were available. RESULTS: High baseline BMI predicted a decrease in the patient's performance in the Digit-Span backwards task measuring working memory performance. In contrast, cognitive performance was not predicted by increases in BMI at follow-up. Normal weight bipolar patients (n = 19) improved their performance on the TMT B, measuring cognitive flexibility and executive functioning, within 1 year, while overweight bipolar patients (n = 19) showed no change in this task. CONCLUSIONS: The results suggest that overweight can predict cognitive performance changes over 12 months.

Review and Consensus on Pharmacogenomic Testing in Psychiatry.

The implementation of pharmacogenomic (PGx) testing in psychiatry remains modest, in part due to divergent perceptions of the quality and completeness of the evidence base and diverse perspectives on the clinical utility of PGx testing among psychiatrists and other healthcare providers. Recognizing the current lack of consensus within the field, the International Society of Psychiatric Genetics assembled a group of experts to conduct a narrative synthesis of the PGx literature, prescribing guidelines, and product labels related to psychotropic medications as well as the key considerations and limitations related to the use of PGx testing in psychiatry. The group concluded that to inform medication selection and dosing of several commonly-used antidepressant and antipsychotic medications, current published evidence, prescribing guidelines, and product labels support the use of PGx testing for 2 cytochrome P450 genes (CYP2D6, CYP2C19). In addition, the evidence supports testing for human leukocyte antigen genes when using the mood stabilizers carbamazepine (HLA-A and HLA-B), oxcarbazepine (HLA-B), and phenytoin (CYP2C9, HLA-B). For valproate, screening for variants in certain genes (POLG, OTC, CSP1) is recommended when a mitochondrial disorder or a urea cycle disorder is suspected. Although barriers to implementing PGx testing remain to be fully resolved, the current trajectory of discovery and innovation in the field suggests these barriers will be overcome and testing will become an important tool in psychiatry.

A step ahead: Exploring the gut microbiota in inpatients with bipolar disorder during a depressive episode.

OBJECTIVES: There is evidence that the gut microbiota plays a major role in the pathogenesis of diseases of the central nervous system through the gut-brain axis. The aim of the present study was to analyze gut microbiota composition in bipolar disorder (BD) and its relation to inflammation, serum lipids, oxidative stress, tryptophan (TRP)/kynurenine (KYN) levels, anthropometric measurements and parameters of metabolic syndrome. Further, microbial community differences of individuals with BD compared with healthy controls (HC) were explored. METHODS: In this cross-sectional study, we performed 16S rRNA gene sequencing of stool samples from 32 BD individuals and 10 HC. Laboratory parameters included inflammatory markers, serum lipids, KYN, oxidative stress and anthropometric measures. Microbial community analysis and correlation to clinical parameters was performed with QIIME, differential abundance analysis of taxa encompassed linear discriminant analysis effect size (LEfSe). RESULTS: We found a negative correlation between microbial alpha-diversity and illness duration in BD (R = -0.408, P = 0.021). Furthermore, we identified bacterial clades associated with inflammatory status, serum lipids, TRP, depressive symptoms, oxidative stress, anthropometrics and metabolic syndrome in individuals with BD. LEfSe identified the phylum Actinobacteria (LDA= 4.82, P = 0.007) and the class Coriobacteria (LDA= 4.75, P = 0.010) as significantly more abundant in BD when compared with HC, and Ruminococcaceae (LDA= 4.59, P = 0.018) and Faecalibacterium (LDA= 4.09, P = 0.039) as more abundant in HC when compared with BD. CONCLUSIONS: The present findings suggest that causes and/or consequences of BD may also lie outside the brain. Exploratory research of the gut microbiota in affective disorders like BD may identify previously unknown underlying causes, and offer new research and therapeutic approaches to mood disorders.

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

OBJECTIVES: Bipolar disorder (BD) with early disease onset is associated with an unfavorable clinical outcome and constitutes a clinically and biologically homogenous subgroup within the heterogeneous BD spectrum. Previous studies have found an accumulation of early age at onset (AAO) in BD families and have therefore hypothesized that there is a larger genetic contribution to the early-onset cases than to late onset BD. To investigate the genetic background of this subphenotype, we evaluated whether an increased polygenic burden of BD- and schizophrenia (SCZ)-associated risk variants is associated with an earlier AAO in BD patients. METHODS: A total of 1995 BD type 1 patients from the Consortium of Lithium Genetics (ConLiGen), PsyCourse and Bonn-Mannheim samples were genotyped and their BD and SCZ polygenic risk scores (PRSs) were calculated using the summary statistics of the Psychiatric Genomics Consortium as a training data set. AAO was either separated into onset groups of clinical interest (childhood and adolescence [≤18 years] vs adulthood [>18 years]) or considered as a continuous measure. The associations between BD- and SCZ-PRSs and AAO were evaluated with regression models. RESULTS: BD- and SCZ-PRSs were not significantly associated with age at disease onset. Results remained the same when analyses were stratified by site of recruitment. CONCLUSIONS: The current study is the largest conducted so far to investigate the association between the cumulative BD and SCZ polygenic risk and AAO in BD patients. The reported negative results suggest that such a polygenic influence, if there is any, is not large, and highlight the importance of conducting further, larger scale studies to obtain more information on the genetic architecture of this clinically relevant phenotype.

[The relationship between intake of lithium and neuroradiological alterations in bipolar disorder. Are there predictors of clinical remission?] / Zusammenhang zwischen der Einnahme von Lithium und neuroradiologischen Veränderungen bei der bipolar affektiven Störung: Gibt es Hinweise auf ein klinisches Ansprechen?

For avoiding affective episodes, patients with bipolar disorders are treated with mood stabilizers. Under that term, the substances lithium, valproic acid, lamotrigine and carbamazepine are included. In the light of upcoming new psychiatric concepts, the use of second generation antipsychotics is also taken into consideration in pharmacological treatment. In this review, the relation between brain structure and the use of lithium in bipolar disorders is examined. Therefore, results from MRI-, DTI-, SPECT-studies assessing this relation, were included.Most of the studies are cross-sectional and examined the effects of lithium. The latter is associated with increased cortical and sub-cortical gray matter volume and ameliorative white matter microstructure. 7-lithium spectroscopy showed a significant difference in brain-lithium concentrations between remitted and non-remitted patients.There are preclinical studies reporting induction of promitotic and antiapoptotic effects by lithium. This literature underpins the hypothesis of lithium-induced neurogenesis. However, osmotic and physical effects of lithium could also explain the demonstrated volume gain in bipolar human brain.Cross-sectional design and small patient groups are typical limitations of numerous studies included in this review.Notably, with the 7-lithium spectroscopy of the central nervous system, new perspectives in clinical research to clarify pharmacokinetic differences between remitted and non-remitted bipolar patients can be established in future.

Genome-wide association study of 40,000 individuals identifies two novel loci associated with bipolar disorder.

Bipolar disorder (BD) is a genetically complex mental illness characterized by severe oscillations of mood and behaviour. Genome-wide association studies (GWAS) have identified several risk loci that together account for a small portion of the heritability. To identify additional risk loci, we performed a two-stage meta-analysis of >9 million genetic variants in 9,784 bipolar disorder patients and 30,471 controls, the largest GWAS of BD to date. In this study, to increase power we used ∼2,000 lithium-treated cases with a long-term diagnosis of BD from the Consortium on Lithium Genetics, excess controls, and analytic methods optimized for markers on the X-chromosome. In addition to four known loci, results revealed genome-wide significant associations at two novel loci: an intergenic region on 9p21.3 (rs12553324, P = 5.87 × 10 - 9; odds ratio (OR) = 1.12) and markers within ERBB2 (rs2517959, P = 4.53 × 10 - 9; OR = 1.13). No significant X-chromosome associations were detected and X-linked markers explained very little BD heritability. The results add to a growing list of common autosomal variants involved in BD and illustrate the power of comparing well-characterized cases to an excess of controls in GWAS.

The Role of Nutrition and the Gut-Brain Axis in Psychiatry: A Review of the Literature.

INTRODUCTION: Individuals suffering from psychiatric disorders experience high levels of illness burden and a significantly reduced quality of life. Despite targeted psychopharmacological strategies and complementary psychotherapeutic procedures only moderate effects are obtained, and the risk of relapse is high in many patients. Worldwide, psychiatric diseases such as depression are continuously increasing, challenging the personal life of the affected as well as their families, but also whole societies by increasing disability, early retirement and hospitalization. According to current scientific knowledge psychiatric disorders are caused by a multifactorial pathogenesis, including genetics, inflammation and neurotransmitter imbalance; furthermore, also lifestyle-associated factors gain rising importance. In line with this, there is growing evidence that the gut microbiota and nutrition have an impact on the onset and course of psychiatric disorders. AIM: This narrative review highlights the important role of nutrition in psychiatric care and underlines the significance of nutritional advice in the multifactorial, biopsychosocial treatment of patients. It focuses on current dietary interventions such as the Mediterranean diet, dietary supplements and modifications of the gut microbiota with pre-, pro- and postbiotics. RESULTS: Recent studies support the connection between the quality of diet, gut microbiota and mental health through regulation of metabolic functions, anti-inflammatory and antiapoptotic properties and the support of neurogenesis. Dietary coaching to improve mental health seems to be an additional, cost-effective, practical, nonpharmacological intervention for individuals with psychiatric disorders. CONCLUSION: The use of nutritional interventions in psychiatry equips therapists with a promising tool for both the prevention and treatment of psychiatric disorders. Besides pharmacological therapy, psychotherapy and physical activity, nutritional interventions are an important pillar in the multifactorial, biopsychosocial treatment of psychiatric disease and could be used as a potential therapeutic target.