International Journal of Bipolar Disorders最新文献

Background: Detecting prodromal symptoms of bipolar disorder (BD) has garnered significant attention in recent research, as early intervention could potentially improve therapeutic efficacy and improve patient outcomes. The heterogeneous nature of the prodromal phase in BD, however, poses considerable challenges for investigators. Our study aimed to identify distinct prodromal phenotypes or "fingerprints" in patients diagnosed with BD and subsequently examine correlations between these fingerprints and relevant clinical outcomes.

Methods: 20,000 veterans diagnosed with BD were randomly selected for this study. K-means clustering analysis was performed on temporal graphs of the clinical features of each patient. We applied what we call "temporal blurring" to each patient image in order to allow clustering to focus on the clinical features, and not cluster patients based upon their varying temporal patterns in diagnosis, which lead to the desired types of clusters. We evaluated several outcomes including mortality rate, hospitalization rate, mean number of hospitalizations, mean length of stay, and the occurrence of a psychosis diagnosis within one year following the initial BD diagnosis. To determine the statistical significance of the observed differences for each outcome, we conducted appropriate tests, such as ANOVA or Chi-square.

Results: Our analysis yielded 8 clusters which appear to represent distinct phenotypes with differing clinical attributes. Each of these clusters also has statistically significant differences across all outcomes (p < 0.0001). The clinical features in many of the clusters were consistent with findings in the literature concerning prodromal symptoms in patients with BD. One cluster, notably characterized by patients lacking discernible prodromal symptoms, exhibited the most favorable results across all measured outcomes.

Conclusion: Our study successfully identified distinct prodromal phenotypes in patients diagnosed with BD. We also found that these distinct prodromal phenotypes are associated with different clinical outcomes.

Background: Several studies have reported on the feasibility of electronic (e-)monitoring using computers or smartphones in patients with mental disorders, including bipolar disorder (BD). While studies on e-monitoring have examined the role of demographic factors, such as age, gender, or socioeconomic status and use of health apps, to our knowledge, no study has examined clinical characteristics that might impact adherence with e-monitoring in patients with BD. We analyzed adherence to e-monitoring in patients with BD who participated in an ongoing e-monitoring study and evaluated whether demographic and clinical factors would predict adherence.

Methods: Eighty-seven participants with BD in different phases of the illness were included. Patterns of adherence for wearable use, daily and weekly self-rating scales over 15 months were analyzed to identify adherence trajectories using growth mixture models (GMM). Multinomial logistic regression models were fitted to compute the effects of predictors on GMM classes.

Results: Overall adherence rates were 79.5% for the wearable; 78.5% for weekly self-ratings; and 74.6% for daily self-ratings. GMM identified three latent class subgroups: participants with (i) perfect; (ii) good; and (iii) poor adherence. On average, 34.4% of participants showed "perfect" adherence; 37.1% showed "good" adherence; and 28.2% showed poor adherence to all three measures. Women, participants with a history of suicide attempt, and those with a history of inpatient admission were more likely to belong to the group with perfect adherence.

Conclusions: Participants with higher illness burden (e.g., history of admission to hospital, history of suicide attempts) have higher adherence rates to e-monitoring. They might see e-monitoring as a tool for better documenting symptom change and better managing their illness, thus motivating their engagement.

Background: Across clinical settings, black individuals are disproportionately less likely to be diagnosed with bipolar disorder compared to schizophrenia, a traditionally more severe and chronic disorder with lower expectations for remission. The causes of this disparity are likely multifactorial, ranging from the effects of implicit bias, to developmental and lifelong effects of structural racism, to differing cultural manifestations of psychiatric symptoms and distress. While prior studies examining differences have found a greater preponderance of specific psychotic symptoms (such as persecutory delusions and hallucinations) and a more dysphoric/mixed mania presentation in Black individuals, these studies have been limited by a lack of systematic phenotypic assessment and small sample sizes. In the current report, we have combined data from two large multi-ethnic studies of bipolar disorder with comparable semi-structured interviews to investigate differences in symptoms presentation across the major clinical symptom domains of bipolar disorder.

Results: In the combined meta-analysis, there were 4423 patients diagnosed with bipolar disorder type I, including 775 of self-reported as Black race. When symptom presentations were compared in Black versus White individuals, differences were found across all the major clinical symptom domains of bipolar disorder. Psychotic symptoms, particularly persecutory hallucinations and both persecutory and mood-incongruent delusions, were more prevalent in Black individuals with bipolar disorder type I (ORs = 1.26 to 2.45). In contrast, Black individuals endorsed fewer prototypical manic symptoms, with a notably decreased likelihood of endorsing abnormally elevated mood (OR = 0.44). Within depression associated symptoms, we found similar rates of mood or cognitive related mood symptoms but higher rates of decreased appetite (OR = 1.32) and weight loss (OR = 1.40), as well as increased endorsement of initial, middle, and early-morning insomnia (ORs = 1.73 to 1.82). Concurrently, we found that black individuals with BP-1 were much less likely to be treated with mood stabilizers, such as lithium (OR = 0.45), carbamazepine (OR = 0.37) and lamotrigine (OR = 0.34), and moderately more likely to be on antipsychotic medications (OR = 1.25).

Conclusions: In two large studies spanning over a decade, we found highly consistent and enduring differences in symptoms across the major clinical symptom domains of bipolar disorder. These differences were marked by a greater burden of mood-incongruent psychotic symptoms, insomnia and irritability, and fewer prototypical symptoms of mania. While such symptoms warrant better recognition to reduce diagnostic disparities, they may also represent potential targets of treatment that can be addressed to mitigate persistent disparities in outcome.

Background: Response to lithium (Li) is highly variable in bipolar disorders (BD). Despite decades of research, no clinical predictor(s) of response to Li prophylaxis have been consistently identified. Recently, we developed epigenetic Methylation Specific High-Resolution Melting (MS-HRM) assays able to discriminate good responders (GR) from non-responders (NR) to Li in individuals with BD type 1 (BD-I). This study examined whether a combination of clinical and epigenetic markers can distinguish NR from other types of Li responders.

Methods: We recorded clinical variables that are potentially associated with Li response in 64 individuals with BD-I. MS-HRM assays were performed on DNA isolated from peripheral blood. We used backward stepwise logistic regression analyses, followed by receiver operating characteristic (ROC) curve analysis to estimate the performance of the clinical variables, alone then in combination with the epigenetic biomarkers, to identify GR and partial responders (PaR) vs NR.

Results: Polarity at onset, psychotic symptoms at onset and family history of BD classified correctly 70% of individuals according to their Li response (PaR + GR = 86%; NR = 35%). When combined with the epigenetic biomarkers, these three clinical variables plus alcohol misuse (and one DMR: Differentially Methylated Region) correctly classified 86% of individuals, improving the prediction of PaR + GR (93%) and of NR (70%). The ROC analysis demonstrated an improvement in the area under the curve from 0.75 (clinical variables alone) to 0.87 (combination of clinical and epigenetic markers).

Conclusions: Combining clinical predictors and DNA methylation markers of Li response may have greater utility in clinical practice than relying on clinical characteristics alone.

Background: Physical exercise (PE) is a recommended lifestyle intervention for different mental disorders and has shown specific positive therapeutic effects in unipolar depressive disorder. Considering the similar symptomatology of the depressive phase in patients with bipolar disorder (BD) and unipolar depressive disorder, it is reasonable to suggest that PE may also be beneficial for bipolar depression. However, there is an absence of studies evaluating the antidepressant effect of a structured PE intervention in BD.

Methods: This is an open-label, single-arm study trial. Fifteen patients with a diagnosis of BD Type I or Type II, presenting a depressive episode were included in the study. After physical and functional evaluation, patients participated in supervised training sessions with aerobics followed by strength exercises, three times per week, for 12 weeks (36 training sessions). Depressive and manic symptoms were assessed at baseline and 2, 4, 8, and 12 weeks. Additionally, quality of Life and functioning were assessed at baseline and 4, 8, and 12 weeks). Finally, we tested cardiorespiratory fitness, muscle strength and body composition at baseline and week-12.

Results: The mean (± SD) Montgomery Asberg Depression Rating Scale (MADRS) score at baseline was 23.6 ± 8.3 points and after 12 weeks of PE the mean score was 10.2 ± 4.8 points. Nine patients (82%) presented an antidepressant response defined as a reduction of more than 50% of depressive symptoms at week 12 with five of those patients (45%) presenting criteria for full remission. A large and significant Cohen's D Effect Size (pre-post) was verified for MADRS reduction [1.98 (95% Confidence interval = 0.88 to 3.08)]. We did not detect a significant change in manic symptoms, functioning, and quality of life during the 12-week follow-up. At week-12, all patients increased their muscular strength (one repetition maximal test - 1RM) and reduced the percentage of body fat (spectral bioelectrical impedance analysis).

Conclusions: This study, using rigorous criteria and a structured intervention, provides valid pilot data, showing the feasibility of a structured PE intervention for the treatment of depressive symptoms in BD, and suggesting a potential adjunctive antidepressant effect. Moreover, PE showed a positive impact on muscle strength and body composition. This should be further verified by randomized controlled studies.

Background: When assessing the value of an intervention in bipolar disorder, researchers and clinicians often focus on metrics that quantify improvements to core diagnostic symptoms (e.g., mania). Providers often overlook or misunderstand the impact of treatment on life quality and function. We wanted to better characterize the shared experiences and obstacles of bipolar disorder within the United States from the patient's perspective.

Methods: We recruited 24 individuals diagnosed with bipolar disorder and six caretakers supporting someone with the condition. Participants were involved in treatment or support services for bipolar disorder in central Texas. As part of this qualitative study, participants discussed their everyday successes and obstacles related to living with bipolar disorder during personalized, open-ended interviews. Audio files were transcribed, and Nvivo software processed an initial thematic analysis. We then categorized themes into bipolar disorder-related obstacles that limit the patient's capability (i.e., function), comfort (i.e., relief from suffering) and calm (i.e., life disruption) (Liu et al., FebClin Orthop 475:315-317, 2017; Teisberg et al., MayAcad Med 95:682-685, 2020). We then discuss themes and suggest practical strategies that might improve the value of care for patients and their families.

Results: Issues regarding capability included the struggle to maintain identity, disruptions to meaningful employment, relationship loss and the unpredictable nature of bipolar disorder. Comfort related themes included the personal perception of diagnosis, social stigma and medication issues. Calm themes included managing dismissive doctors, finding the right psychotherapist and navigating financial burdens.

Conclusions: Qualitative data from patients with bipolar disorder helps identify gaps in care or practical limitations to treatment. When we listen to these individuals, it is clear that treatments must also address the unmet psychosocial impacts of the condition to improve patient care, capability and calm.

Background: Bipolar disorder type-I (BD-I) patients are known to show emotion regulation abnormalities. In a previous fMRI study using an explicit emotion regulation paradigm, we compared responses from 19 BD-I patients and 17 matched healthy controls (HC). A standard general linear model-based univariate analysis revealed that BD patients showed increased activations in inferior frontal gyrus when instructed to decrease their emotional response as elicited by neutral images. We implemented multivariate pattern recognition analyses on the same data to examine if we could classify conditions within-group as well as HC versus BD.

Methods: We reanalyzed explicit emotion regulation data using a multivariate pattern recognition approach, as implemented in PRONTO software. The original experimental paradigm consisted of a full 2 × 2 factorial design, with valence (Negative/Neutral) and instruction (Look/Decrease) as within subject factors.

Results: The multivariate models were able to accurately classify different task conditions when HC and BD were analyzed separately (63.24%-75.00%, p = 0.001-0.012). In addition, the models were able to correctly classify HC versus BD with significant accuracy in conditions where subjects were instructed to downregulate their felt emotion (59.60%-60.84%, p = 0.014-0.018). The results for HC versus BD classification demonstrated contributions from the salience network, several occipital and frontal regions, inferior parietal lobes, as well as other cortical regions, to achieve above-chance classifications.

Conclusions: Our multivariate analysis successfully reproduced some of the main results obtained in the previous univariate analysis, confirming that these findings are not dependent on the analysis approach. In particular, both types of analyses suggest that there is a significant difference of neural patterns between conditions within each subject group. The multivariate approach also revealed that reappraisal conditions provide the most informative activity for differentiating HC versus BD, irrespective of emotional valence (negative or neutral). The current results illustrate the importance of investigating the cognitive control of emotion in BD. We also propose a set of candidate regions for further study of emotional control in BD.

Background: Patients should get actively involved in the management of their illness. The aim of this study was to assess the influence of lifestyle factors, including sleep, diet, and physical activity, on lithium levels in patients with bipolar disorder.

Methods: A multicenter study was performed. In total, 157 lithium measurements were done biweekly in a sample of 65 patients (35 women) over 6 weeks. Lifestyle, based on total sleep hours and physical activity, was assessed by actigraphy. Diet was evaluated using the Mediterranean Lifestyle Index (Medlife).

Results: 35.4% of patients had a normal weight. The mean Medlife score was 14.5 (± 2.5) (moderate-good adherence to Mediterranean diet). BMI, daily dose of lithium and intensity of physical activity had a combined effect on lithium levels, after adjustment for other variables. Patients who practiced intense physical exercise, who took lower doses and had a higher BMI exhibited lower levels of lithium.

Conclusions: Higher physical activity and BMI contribute to lower lithium levels. Patients should be made aware of these relationships to improve their perception of control and self-management. Lifestyle-based interventions contribute to establishing a more personalized medicine.

Background: Offspring of parents with bipolar disorder (OBD) are at risk for developing mental disorders, and the literature suggests that parenting stress may represent an important risk factor linking parental psychopathology to offspring psychopathology. We aimed to investigate whether improvements in parenting stress mediated the relationship between participation in a prevention program and offspring internalizing and externalizing symptoms at follow-up.

Methods: Families having a parent with BD (N = 25) underwent a 12-week prevention program. Assessments were conducted at pre-intervention, post-intervention, and at 3- and 6-month follow-ups. Families of parents with no affective disorders (i.e., control families) served as a comparison sample (N = 28). The Reducing Unwanted Stress in the Home (RUSH) program aimed to teach communication, problem-solving, and organization skills to improve the rearing environment. Measures included the Parenting Stress Index-4th Edition, the Behaviour Assessment Scales for Children-2nd Edition, and the UCLA Life Stress Interview.

Results: Families having a parent with BD reported more parenting stress at pre-intervention, and more change across time, than control families. Improvements in parenting stress mediated the relationship between participation in the intervention and reduced offspring internalizing and externalizing symptoms. While families having a parent with BD reported more chronic interpersonal stress at pre-intervention, no intervention effects were found.

Conclusions: The findings demonstrate that a preventative intervention targeting parenting stress in families may serve to prevent the development of mental disorders in at-risk children.