Eating disorders, bipolar disorders and other mood disorders: complex and under-researched relationships

Serum Vitamin D, Mania and Depression-Related Scores: A Comparison among Mixed Bipolar, Mania, and Healthy Subjects

Objective: Manic and mixed episodes of bipolar disorder are important episodes of this disorder. The aim of the current study was to assess serum vitamin D (SVD) levels in patients with mania and mixed bipolar disorder, compared to healthy subjects. Method : The current cross-sectional study was conducted on 75 subjects, including healthy subjects (n = 25), patients with acute-phase mania (n = 25), and patients with mixed bipolar disorder (n = 25). The SVD levels were measured in all of the enrolled subjects. The Hamilton Depression Rating Scale (HDRS), Young Mania Rating Scale (YMRS), and Clinical Global Impression- Severity (CGI-S) were used to assess disease activity in patient groups. Data analysis was performed using SPSS version 18. For statistical analysis, analysis of variance (ANOVA), independent-sample t test, Pearson correlation, and Chi-square tests were utilized. P-values < 0.05 were considered statistically significant. Results: The results showed that the mean of SVD was significantly lower in mania and mixed bipolar patients compared to healthy subjects (P < 0.05). In addition, the number of subjects with SVD ≥ 20 ng/ml was higher in the healthy group compared to the patient groups (P < 0.05). Also, SVD was negatively correlated with the CGI-S (r = -0.311; P = 0.028), YMRS (r = -0.464; P = 0.001), and HDRS (r = -0.393; P = 0.005) in the total patient subjects. Conclusion: Prevalence of low SVD was considerably high in mania and mixed bipolar patients compared to healthy subjects. Additionally, meaningful negative correlations were found between SVD and disease activity-related variables including the HDRS, YMRS, and CGI-S.

iPSC-derived models for anorexia nervosa research

Anorexia nervosa (AN) is a complex neuropsychiatric disorder with genetic and epigenetic components that results in reduced food intake combined with alterations in the reward-processing network. While studies of patient cohorts and mouse models have uncovered genes and epigenetic changes associated with the disease, neuronal networks and brain areas preferentially activated and metabolic changes associated with reduced food intake, the underlying molecular and cellular mechanisms remain unknown. The use of both 2D in vitro cultures and 3D models, namely organoids and spheroids, derived from either human embryonic stem cells (ESCs) or induced pluripotent stem cells (iPSCs), would allow identification of cell type-specific changes associated with AN and comorbid diseases, to study preferential connections between brain areas and organs, and the development of therapeutic strategies.

Prevalence of eating disorders in patients with bipolar disorder: a scoping review of the literature

BACKGROUND

Eating disorder (ED) and bipolar disorder (BD) exhibit certain phenomenological similarities rooted in eating behavior and emotional regulation. However, despite the growing body of research on the comorbidity of ED and BD, scientific data on the concurrent course of these disorders has remained poorly systematized.

AIM

To conduct a scoping review of published data on the prevalence of various types of ED among patients with BD types I and II in the context of the sex and clinical features of the concurrent course of these disorders.

METHODS

The analysis was reported following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for scoping reviews. The search was conducted in the MEDLINE electronic database. Studies were included if they were focused samples of patients diagnosed with BD and ED, and the Diagnostic and Statistical Manual of Mental Disorders, fourth and fifth editions (DSM-IV, DSM-5), or International Statistical Classification of Diseases and Related Health Problems, tenth Revision (ICD-10), were used for the verification of the ED and BD diagnoses. The descriptive analysis method was used to summarize the review findings.

RESULTS

A total of 41 studies were selected for the review. Lifetime ED in patients with BD ranged from 2.2% to 31.1%, and the prevalence rates of BD among patients with ED varied from 11.3% to 68.1%. ED nominally had a higher prevalence among individuals with BD type II and females. Additionally, the presence of ED in patients with BD was associated with earlier onset of mood disorder, a higher number of depressive episodes, higher levels of atypical depressive symptoms, suicide attempts, as well as a higher frequency of comorbid obsessive-compulsive and anxiety disorders, addictions, and various metabolic disorders.

CONCLUSION

Despite the high degree of volatility in the results, the prevalence rates of a concurrent course of ED and BD are rather high. For this reason, screening for ED in patients with BD and vice versa holds significant value in the accurate diagnosis and selection of the most effective therapy. The patterns of comorbidity among different types of ED and BD, depending on gender, need further exploration in future research.

Characterizing eating behavioral phenotypes in mood disorders: a narrative review

Mood disorders, including depressive and bipolar disorders, represent a multidimensional and prevalent group of psychiatric illnesses characterized by disturbances in emotion, cognition and metabolism. Maladaptive eating behaviors in mood disorders are diverse and warrant characterization in order to increase the precision of diagnostic criteria, identify subtypes and improve treatment strategies. The current narrative review synthesizes evidence for Eating Behavioral Phenotypes (EBP) in mood disorders as well as advancements in pathophysiological conceptual frameworks relevant to each phenotype. Phenotypes include maladaptive eating behaviors related to appetite, emotion, reward, impulsivity, diet style and circadian rhythm disruption. Potential treatment strategies for each phenotype are also discussed, including psychotherapeutic, pharmacological and nutritional interventions. Maladaptive eating behaviors related to mood disorders are relevant from both clinical and research perspectives, yet have been somewhat overlooked thus far. A better understanding of this aspect of mood disorders holds promise to improve clinical care in this patient group and contribute to the subtyping of these currently subjectively diagnosed and treated disorders.

Quantification of diet quality utilizing the rapid eating assessment for participants-shortened version in bipolar disorder: Implications for prospective depression and cardiometabolic studies

OBJECTIVES

Recognizing bipolar disorder as a multi-system metabolic condition driven, in part, by binge eating behavior and atypical depressive symptoms, this study aimed to quantify diet quality and evaluate clinical correlates in a bipolar disorder cohort.

METHODS

Participants from the Mayo Clinic Bipolar Disorder Biobank (n = 734) completed the Rapid Eating Assessment for Participants - Shortened version (REAP-S) to determine diet quality. The average REAP-S score for a U.S. omnivorous diet is 32 (range 13 to 39) with higher scores indicating healthier diet. Demographic variables were collected in a standardized clinical questionnaire. Depressive symptoms were assessed by the Bipolar Inventory of Symptoms Scale. Cardiometabolic variables were retrieved from the electronic health record. Associations between continuous variables and REAP-S scores (total, 'healthy foods' and 'avoidance of unhealthy foods') were assessed using linear regression.

RESULTS

Overall, our sample had a mean REAP-S score of 27.6 (4.9), suggestive of a lower diet quality than the average general population in the US. There was a significant inverse relationship between mean REAP-S lower scores with increased BMI, waist circumference, disordered eating and depression. All these associations were significantly stronger in female participants.

LIMITATIONS

EHR cross-sectional data.

CONCLUSIONS

Our data suggest unhealthy diet quality in bipolar disorder is associated with depression, obesity and cardiometabolic abnormalities. Additional work is encouraged to prospectively track mood and diet quality to further understand the bidirectional relationship and clarify if dietary interventions can positively impact mood. Further delineating potential sex differences in diet quality and depression may provide greater appreciation of modifiable risk factors for future cardiometabolic burden.

What can we learn about the psychiatric diagnostic categories by analysing patients' lived experiences with Machine-Learning?

BACKGROUND

To deliver appropriate mental healthcare interventions and support, it is imperative to be able to distinguish one person from the other. The current classification of mental illness (e.g., DSM) is unable to do that well, indicating the problem of diagnostic heterogeneity between disorders (i.e., the disorder categories have many common symptoms). As a result, the same person might be diagnosed with two different disorders by two independent clinicians. We argue that this problem might have resulted because these disorders were created by a group of humans (APA taskforce members) who relied on more intuition and consensus than data. Literature suggests that human-led decisions are prone to biases, group-thinking, and other factors (such as financial conflict of interest) that can enormously influence creating diagnostic and treatment guidelines. Therefore, in this study, we inquire that if we prevent such human intervention (and thereby their associated biases) and use Artificial Intelligence (A.I.) to form those disorder structures from the data (patient-reported symptoms) directly, then can we come up with homogenous clusters or categories (representing disorders/syndromes: a group of co-occurring symptoms) that are adequately distinguishable from each other for them to be clinically useful. Additionally, we inquired how these A.I.-created categories differ (or are similar) from human-created categories. Finally, to the best of our knowledge, this is the first study, that demonstrated how to use narrative qualitative data from patients with psychopathology and group their experiences using an A.I. Therefore, the current study also attempts to serve as a proof-of-concept.

METHOD

We used secondary data scraped from online communities and consisting of 10,933 patients' narratives about their lived experiences. These patients were diagnosed with one or more DSM diagnoses for mental illness. Using Natural Language Processing techniques, we converted the text data into a numeric form. We then used an Unsupervised Machine Learning algorithm called K-Means Clustering to group/cluster the symptoms.  RESULTS: Using the data mining approach, the A.I. found four categories/clusters formed from the data. We presented ten symptoms or experiences under each cluster to demonstrate the practicality of application and understanding. We also identified the transdiagnostic factors and symptoms that were unique to each of these four clusters. We explored the extent of similarities between these clusters and studied the difference in data density in them. Finally, we reported the silhouette score of + 0.046, indicating that the clusters are poorly distinguishable from each other (i.e., they have high overlapping symptoms).

DISCUSSION

We infer that whether humans attempt to categorise mental illnesses or an A.I., the result is that the categories of mental disorders will not be unique enough to be able to distinguish one service seeker from another. Therefore, the categorical approach of diagnosing mental disorders can be argued to fall short of its purpose. We need to search for a classification system beyond the categorical approaches even if there are secondary merits (such as ease of communication and black-and-white (binary) decision making). However, using our A.I. based data mining approach had several meritorious findings. For example, we found that some symptoms are more exclusive or unique to one cluster. In contrast, others are shared by most other clusters (i.e., identification of transdiagnostic experiences). Such differences are interesting objects of inquiry for future studies. For example, in clear contrast to the traditional diagnostic systems, while some experiences, such as auditory hallucinations, are present in all four clusters, others, such as trouble with eating, are exclusive to one cluster (representing a syndrome: a group of co-occurring symptoms). We argue that trans-diagnostic conditions (e.g., auditory hallucinations) might be prime targets for symptom-level interventions. For syndrome-level grouping and intervention, however, we argue that exclusive symptoms are the main targets.

CONCLUSION

Categorical approach to mental disorders is not a way forward because the categories are not unique enough and have several shared symptoms. We argue that the same symptoms can be present in more than one syndrome, although dimensionally different. However, we need additional studies to test this hypothesis. Future directions and implications were discussed.

Using shape and weight overvaluation to empirically differentiate severity of other specified feeding or eating disorder

BACKGROUND

Although no severity specifiers are noted in the Diagnostic and Statistical Manual of Mental Disorders - 5 for other specified feeding or eating disorder (OSFED), shape/weight overvaluation is a proposed eating disorder (ED) severity specifier. We used structural equation modeling (SEM) Trees to empirically determine values of shape/weight overvaluation that differentiate OSFED severity. We additionally tested whether the SEM Tree-defined thresholds or a clinical cutoff for shape/weight overvaluation differentiated severity more meaningfully.

METHODS

Participants were 690 females with OSFED presenting to residential ED treatment. SEM Tree analyses specified an outcome model of OSFED severity and then recursively partitioning the outcome model into severity groups. The SEM Tree-defined and clinical cutoff severity groups were compared on clinical characteristics.

RESULTS

SEM Trees identified one split that occurred at value 5.12 on our shape/weight overvaluation items from the Eating Disorder Examination Questionnaire. The subgroup with higher overvaluation had significantly greater intensity of ED and depressive symptoms and longer lengths of stay. The subgroups created from the shape/weight overvaluation clinical-cut off value of 4 differed on the same clinical characteristics as the SEM Tree-derived groups, with the exception of laxative use frequency. Effect sizes were larger for the clinical cutoff as compared to the SEM Tree severity specification scheme.

LIMITATIONS

These cross-sectional data were used from a predominately white and female residential treatment sample; this likely skewed the subgroups and may limit generalizability.

CONCLUSIONS

Shape/weight overvaluation can meaningfully differentiate OSFED severity. The clinical cutoff slightly outperformed the empirically determined thresholds for shape/weight overvaluation.

Biological mechanisms underlying widowhood's health consequences: Does diet play a role?

The loss of a spouse is a highly stressful event that puts older adults at increased risk for morbidity and mortality. The risk is highest in the first year to 18 months post-loss; nevertheless, widow(er)s, in general, are at heightened risk of cardiovascular disease (CVD) related morbidity and mortality, and to a lesser extent, non-CVD related morbidity and mortality. The primary goal of this article is to argue for a perspective that considers diet and emotion-induced autonomic, neuroendocrine, and immune dysregulation, in unison, to understand the mechanisms underlying morbidity and mortality in early widowhood. Toward this end, we first summarize our previously published work, as well as work from other investigatory teams, showing that compared with those who were not bereaved, widow(er)s have higher levels of pro-inflammatory cytokine production and more dysregulated autonomic and neuroendocrine activity than non-widow(er)s, independent of health behaviors such as diet. We highlight that a major gap in our current understanding of the biobehavioral mechanisms that underlie the widowhood effect is the role of diet and hypothesize that the adverse health impact of grief and associated negative emotions and diet may be more than additive. Therefore, we propose that diet may be a pathway by which widow(er)s are at higher CVD risk requiring further investigation.

The prevalence, odds and predictors of lifespan comorbid eating disorder among people with a primary diagnosis of bipolar disorders, and vice-versa: Systematic review and meta-analysis

BACKGROUND

There are scarce and discrepant data about the prevalence and correlates of co-occurring eating disorders (EDs) among people with a primary diagnosis of bipolar disorder (BD), and vice-versa, compelling a systematic review and meta-analysis on the matter.

METHODS

MEDLINE/PsycINFO databases were systematically searched for original studies documenting BD⇌ED comorbidity across the lifespan, from inception up until April 20^th, 2020. Random-effects meta-analysis and meta-regression analyses were conducted, accounting for multiple moderators.

RESULTS

Thirty-six studies involved 15,084 primary BD patients. Eleven studies encompassed 15,146 people with primary EDs. Binge eating disorder (BED) occurred in 12.5% (95%C.I.=9.4-16.6%, I²=93.48%) of BDs, while 9.1% (95%C.I.=3.3-22.6%) of BEDs endorsed BD. Bulimia Nervosa (BN) occurred in 7.4% (95%C.I.=6-10%) of people with BD, whereas 6.7% (95%C.I.=12-29.2%) of subjects with BN had a diagnosis of BD. Anorexia Nervosa (AN) occurred in 3.8% (95%C.I.=2-6%) of people with BDs; 2% (95%C.I.=1-2%) of BD patients had a diagnosis of AN. Overall, BD patients with EDs had higher odds of being female vs. non-ED controls. Several moderators yielded statistically significant differences both within- and between different types of BDs and EDs.

LIMITATIONS

Scant longitudinal studies, especially across different EDs and pediatric samples. High heterogeneity despite subgroup comparisons. Limited discrimination of the quality of the evidence.

CONCLUSIONS

The rates of BD⇌ED comorbidity vary across different diagnostic groups, more than they do according to the "direction" of BD⇌ED. Further primary studies should focus on the risks, chronology, clinical impact, and management of the onset of intertwined BD⇌ED across different ages, promoting a continuum approach.

Are eating disorders associated with bipolar disorder type I? Results of a Lebanese case-control study

OBJECTIVES

To assess the association between disordered eating and bipolar disorder (BD).

METHODS/DESIGN

A case-control study, conducted between April and September 2018, enrolled 50 patients and 50 controls.

RESULTS

Higher eating attitude test scores were significantly associated with the presence of BD. This association remained after the introduction of other factors (marital status, family history of BD, shopping and gambling addictions, sleep quality, and insomnia severity) that were also associated with the presence of BD.

PRACTICAL IMPLICATIONS

This study suggested that eating disorders are associated with BD type I, independent of mediating factors. Health care providers should consider pharmacological or psychotherapeutic interventions that could treat both syndromes sparingly.

Pharmacological treatment of eating disorders, comorbid mental health problems, malnutrition and physical health consequences

The pharmacological treatment of patients with an eating disorder (ED) often includes medications to treat their ED, comorbid mental health problems, malnutrition and the physical health problems resulting from it. The currently approved pharmacological treatment options for EDs are limited to fluoxetine for bulimia nervosa (BN) and - in some countries - lisdexamfetamine for binge eating disorder (BED). Thus, there are no approved pharmacological options for anorexia nervosa (AN), even though study results for olanzapine and dronabinol are promising. Topiramate might be an additional future option for the treatment of BN and BED. Selective serotonin reuptake inhibitors (SSRI), mirtazapine and bupropion could be considered for the treatment of comorbid unipolar depression. However, AN and BN are contraindications for bupropion. For ED patients with a manic episode, we recommend olanzapine in AN and risperidone in BN and BED; whereas for bipolar depression, olanzapine (plus fluoxetine) seems appropriate in AN and lamotrigine in BN and BED. Acute anxiety or suicidality may warrant benzodiazepine treatment with lorazepam. Proton-pump inhibitors, gastroprokinetic drugs, laxatives and hormones can alleviate certain physical health problems caused by EDs. Therapeutic drug monitoring, pharmacogenomic testing, a more restrictive use of "pro re nata" (PRN) medication, an interdisciplinary treatment approach, shared decision making (SDM) and the formulation of common treatment goals by the patients, their family or carers and clinicians could improve treatment success and safety. Novel genetic, immunological, microbiome and brain imaging research as well as new pharmacological developments like the use of psychedelics, stimulants, novel monoaminergic drugs, hormone analogues and drugs which enhance the effects of psychotherapy may extend our therapeutic options in the near future.