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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.
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Trastorno Bipolar , Aprendizaje Automático , Humanos , Trastorno Bipolar/diagnóstico , Femenino , Masculino , Adulto , Proyectos Piloto , Persona de Mediana Edad , Pruebas NeuropsicológicasRESUMEN
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.
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Proteínas CLOCK , Trastorno Depresivo Mayor , Probióticos , Humanos , Probióticos/farmacología , Probióticos/administración & dosificación , Trastorno Depresivo Mayor/terapia , Trastorno Depresivo Mayor/metabolismo , Trastorno Depresivo Mayor/sangre , Trastorno Depresivo Mayor/tratamiento farmacológico , Método Doble Ciego , Adulto , Masculino , Femenino , Persona de Mediana Edad , Proteínas CLOCK/genética , Microbioma Gastrointestinal/fisiología , Microbioma Gastrointestinal/efectos de los fármacos , Expresión Génica/efectos de los fármacos , Metaboloma/efectos de los fármacos , Heces/microbiología , Heces/químicaRESUMEN
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.
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Trastorno Depresivo Mayor , Microbioma Gastrointestinal , Trastornos Mentales , Trastornos del Sueño-Vigilia , Humanos , Microbioma Gastrointestinal/genética , ARN Ribosómico 16S/genética , Estudios Transversales , Sistema Hipotálamo-Hipofisario , Sistema Hipófiso-Suprarrenal , Trastornos Mentales/diagnóstico , SueñoRESUMEN
Introduction: Although adherence to immunosuppressive medication is the key factor for long-term graft survival today, 20-70% of transplant recipients are non-adherent to their immunosuppressive medication. Objective: A prospective, randomized, controlled single-center feasibility study was designed to evaluate the impact of a step guided multicomponent interprofessional intervention program for patients after kidney or liver transplantation on adherence to their immunosuppressive medication in daily clinical practice. Materials and methods: The intervention consisted of group therapy and daily training as well as individual sessions in a step guided approach. The primary endpoint of the study was adherence to immunosuppression as assessed with the "Basel Assessment of Adherence to Immunosuppressive Medications Scale" (BAASIS). The coefficient of variation (CV%) of Tacrolimus (TAC) through levels and the level of personality functioning was a secondary endpoint. We conducted six monthly follow-up visits. Results: Forty-one age- and sex-matched patients [19 females, 58.5 (SD = 10.56) years old, 22 kidney- and 19 liver transplantation] were randomized to the intervention- (N = 21) or control-group (N = 20). No differences between intervention- and control groups were found in the primary endpoint adherence and CV% of TAC. However, in further exploratory analyses, we observed that individuals with higher impairments in personality functioning showed higher CV% of TAC in the controls. The intervention might compensate personality-related susceptibility to poor adherence as evident in CV% of TAC. Discussion: The results of the feasibility study showed that this intervention program was highly accepted in the clinical setting. The Intervention group could compensate higher CV% of TAC after liver or kidney transplantation in individuals with lower levels of personality functioning and non-adherence. Clinical trial registration: ClinicalTrials.gov, identifier NCT04207125.
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Cognition, emotion, emotional regulation, and believing play a special role in psychosocial functioning, especially in times of crisis. So far, little is known about the process of believing during the COVID-19 pandemic. The aim of this study was to examine the process of believing (using the Model of Credition) and the associated psychosocial strain/stress during the first lockdown in the COVID-19 pandemic. An online survey via LimeSurvey was conducted using the Brief Symptom Inventory-18 (BSI-18), the Pittsburgh Sleep Quality Index (PSQI), and a dedicated Believing Questionnaire, which assesses four parameters of credition (propositions, certainty, emotion, mightiness) between April and June, 2020, in Austria. In total, n = 156 mentally healthy participants completed all questionnaires. Negative credition parameters were associated with higher global symptom load (from BSI-18): narratives: r = 0.29, p < 0.001; emotions r = 0.39, p < 0.001. These findings underline the importance of credition as a link between cognition and emotion and their impact on psychosocial functioning and stress regulation in implementing novel strategies to promote mental health.
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COVID-19 , COVID-19/epidemiología , Cognición , Control de Enfermedades Transmisibles , Emociones , Humanos , PandemiasRESUMEN
The gut-brain axis plays a role in major depressive disorder (MDD). Gut-bacterial metabolites are suspected to reduce low-grade inflammation and influence brain function. Nevertheless, randomized, placebo-controlled probiotic intervention studies investigating metabolomic changes in patients with MDD are scarce. The PROVIT study (registered at clinicaltrials.com NCT03300440) aims to close this scientific gap. PROVIT was conducted as a randomized, single-center, double-blind, placebo-controlled multispecies probiotic intervention study in individuals with MDD (n = 57). In addition to clinical assessments, metabolomics analyses (1H Nuclear Magnetic Resonance Spectroscopy) of stool and serum, and microbiome analyses (16S rRNA sequencing) were performed. After 4 weeks of probiotic add-on therapy, no significant changes in serum samples were observed, whereas the probiotic groups' (n = 28) stool metabolome shifted towards significantly higher concentrations of butyrate, alanine, valine, isoleucine, sarcosine, methylamine, and lysine. Gallic acid was significantly decreased in the probiotic group. In contrast, and as expected, no significant changes resulted in the stool metabolome of the placebo group. Strong correlations between bacterial species and significantly altered stool metabolites were obtained. In summary, the treatment with multispecies probiotics affects the stool metabolomic profile in patients with MDD, which sets the foundation for further elucidation of the mechanistic impact of probiotics on depression.