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INTRODUCTION: Individuals with bipolar disorder (BD) have higher rates of unhealthy lifestyles and risk for medical comorbidities Research currently suggests that dietary factors may play a role in the development of depression and anxiety. Therefore, nutritional approaches are potential strategies for the treatment of BD. The aim of this review is to summarize the available evidence on nutrition and BD. MATERIALS AND METHODS: The paper was developed based on PRISMA 2020 guidelines. The search was conducted in Sep-2021 using PubMed and Cochrane Library, augmented by manually checked references lists. The search found 986 studies, of which 47 were included, combined with 13 from reference lists, totaling 60 studies. RESULTS: There were 33 observational trials, of which 15 focused on fatty acids, 9 on micronutrients, 5 on specific foods, 4 on macro and micronutrients. The 27 interventional studies mainly focused on fatty acids, micronutrients and N-acetylcysteine (NAC). DISCUSSION: Dietary intake or supplementation of unsaturated fatty acids, mainly Omega-3 seems to be associated with improved BD symptoms, along with seafood, folic acid and zinc. Studies found variable, mainly non-significant impacts of creatine, carnitine, vitamin D, inositol or NAC supplementation on BD. There are promising results associated with Coenzyme Q10 (Coq10) and probiotics. Taken together, these preliminary findings suggest that dietetic approaches might be included as part of BD treatment. Also considering the high risk of metabolic disorders in individuals with BD, they should be encouraged to choose healthy dietary lifestyles, including daily intake of fruits, vegetables, seafood and whole grains.

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OBJECTIVES: This study examined cognition-immune interactions, specifically executive function, working memory, peripheral levels of tumour necrosis factor-alpha (TNF-α), and soluble tumour necrosis factor receptors-1 and -2 (sTNFR1 and 2) levels in bipolar disorder (BD) patients in comparison with controls. METHODS: Thirty-one BD participants and twenty-seven controls participated in the study. The neurocognitive assessment was performed through three of CogState Research BatteryTM tasks for executive function and working memory. Plasma levels of TNF-α, sTNFR1, and sTNFR2 were measured after overnight fasting. Sociodemographic data and symptom severity of depression and mania were assessed. RESULTS: BD presented a significantly worse performance in the working memory task (p = .005) and higher levels of TNF-α (p = .043) in comparison to controls. A trend level of significance was found for sTNFR1 between groups (p = .082). Among BD participants, there were significant correlations between sTNFR2 and neurocognitive tasks (Groton Maze Learning Task: ρ = .54, p = .002; Set-Shifting Task: ρ = .37, p = .042; and the Two-Back Task: ρ = -.49, p = .005), and between sTNFR1 and mania, depression and anxiety symptoms (respectively ρ = .37, p = .038; ρ = -.38, p = .037; and ρ = .42, p = .002). CONCLUSION: TNF-α and its receptors might be an important variable in cognitive impairment in BD. Future studies might focus on the development of anti-inflammatory therapeutic targets for cognitive dysfunction in BD.

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BACKGROUND: Comparisons between healthy controls (HCs) and individuals with mood disorders have shown more cognitive dysfunction among the latter group, in particular in bipolar disorder (BD). This study aimed to characterize the pattern of cognitive function of BD and major depressive disorder (MDD) and compare them to HC using the (CogState Research Battery) CSRB™. METHOD: Participants were tested, comprising the following domains: processing speed, attention, working memory, visual memory, executive functions, and verbal memory. Quality of life and functionality were also assessed. Multiple linear regression models were performed to examine the effect of demographic characteristics and functionality on cognitive outcomes separately for BD and MDD. RESULTS: Ninety individuals participated in the study, of which 32 had BD, 30 had MDD, and 28 were HC. Differences were found between both BD and MDD and HC for the composite cognitive score, with significant differences between BD and HC (Diff = -5.5, 95% CI = [-9.5, -1.5], p = 0.005), and MDD and HC (Diff = -4.6, 95% CI = [-8.6, -0.5], p = 0.025). There were overall significant differences in five cognitive domains: processing speed (p = 0.001 and p = 0.004), attention (p = 0.002), working memory (p = 0.02), visual memory (p = 0.021), and verbal memory (p = 0.007). BD also presented worse performance than both MDD and HC, and MDD presented better performance than BD but worse than HC in quality of life and functionality. Multiple linear regression models were significative for education (p < 0.001) and age (p = 0.004) for BD and education (p < 0.001) for MDD. CONCLUSION: In general, cognition is more affected in BD than MDD, which could be associated with functional and quality of life impairment.

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Adherence to antidepressants is crucial for optimal treatment outcomes when treating depressive disorders. However, poor adherence is common among patients prescribed antidepressants. This targeted review summarizes the main factors associated with poor adherence, interventions that promote antidepressant adherence, pharmacological aspects related to antidepressant adherence, and formulates 10 clinical recommendations to optimize antidepressant adherence. Patient-related factors associated with antidepressant non-adherence include younger age, psychiatric and medical comorbidities, cognitive impairment, and substance use disorders. Prescriber behavior-related factors include neglecting medical and family histories, selecting poorly tolerated antidepressants, or complex antidepressant regimens. Multi-disciplinary interventions targeting both patient and prescriber, aimed at improving antidepressant adherence, include psychoeducation and providing the patient with clear behavioral interventions to prevent/minimize poor adherence. Regarding antidepressant choice, agents with individually tailored tolerability profile should be chosen. Ten clinical recommendations include four points focusing on the patient (therapeutic alliance, adequate history taking, measurement of depressive symptoms, and adverse effects improved access to clinical care), three focusing on prescribing practice (psychoeducation, individually tailored antidepressant choice, simplified regimen), two focusing on mental health services (improved access to mental health care, incentivized adherence promotion and monitoring), and one relating to adherence measurement (adherence measurement with scales and/or therapeutic drug monitoring).

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Adherence to antidepressants is crucial for optimal treatment outcomes when treating depressive disorders. However, poor adherence is common among patients prescribed antidepressants. This targeted review summarizes the main factors associated with poor adherence, interventions that promote antidepressant adherence, pharmacological aspects related to antidepressant adherence, and formulates 10 clinical recommendations to optimize antidepressant adherence. Patient-related factors associated with antidepressant non-adherence include younger age, psychiatric and medical comorbidities, cognitive impairment, and substance use disorders. Prescriber behavior-related factors include neglecting medical and family histories, selecting poorly tolerated antidepressants, or complex antidepressant regimens. Multi-disciplinary interventions targeting both patient and prescriber, aimed at improving antidepressant adherence, include psychoeducation and providing the patient with clear behavioral interventions to prevent/minimize poor adherence. Regarding antidepressant choice, agents with individually tailored tolerability profile should be chosen. Ten clinical recommendations include four points focusing on the patient (therapeutic alliance, adequate history taking, measurement of depressive symptoms, and adverse effects improved access to clinical care), three focusing on prescribing practice (psychoeducation, individually tailored antidepressant choice, simplified regimen), two focusing on mental health services (improved access to mental health care, incentivized adherence promotion and monitoring), and one relating to adherence measurement (adherence measurement with scales and/or therapeutic drug monitoring).

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BACKGROUND: Randomized controlled clinical trials that have investigated minocycline as an adjunctive treatment for major depressive disorder have proved promising. Data from two studies were pooled to evaluate more definitively whether the addition of minocycline to standard treatment for major depressive disorder leads to an improvement of depressive symptoms when compared with placebo. METHODS: Both studies were multi-site, double-blinded, placebo-controlled trials of minocycline 200 mg/day added to treatment as usual during a 12-week period. The primary outcome measure was change in depressive symptoms (Montgomery-Asberg Depression Rating Scale in Dean et al. and Hamilton Depression Rating Scale in Husain et al.). Secondary outcomes were change in depression severity (Montgomery-Asberg Depression Rating Scale for Dean et al. and 9-item Patient Health Questionnaire in Husain et al.), anxiety severity (Hamilton Anxiety Rating Scale in Dean et al. and Generalized Anxiety Disorder 7-item scale in Husain et al.) and functional status, which were also evaluated as potential mediators on the primary outcome. RESULTS: A total of 112 participants were included in the pooled data (Dean et al., n = 71; Husain et al., n = 41). A significant change from baseline to week 12 was noted in depressive symptoms - differential change (Placebo vs Minocycline): 9.0, 95% confidence interval = [4.2, 13.9], Cohen's D (95% confidence interval): 0.71 [0.29, 1.14], p < 0.001 - anxiety severity - differential change (Placebo vs Minocycline): 0.38, confidence interval = [0.00, 0.75], Cohen's D (95% confidence interval): 0.41 [0.00, 0.82], p = 0.050) and functional status - differential change (Placebo vs Minocycline): 1.0, 95% confidence interval = [0.4, 1.5], Cohen's D (95% confidence interval): 0.76 [0.34, 1.19], p = 0.001). Duration of illness, current use of benzodiazepine and pain medication were identified as moderators, whereas functional status as a mediator/predictor. CONCLUSION: The improvement of depressive symptoms, anxiety severity and functional status is promising and suggests that minocycline has potential as an adjunctive treatment for major depressive disorder. However, further studies are warranted to confirm therapeutic effects of minocycline in major depressive disorder. TRIAL REGISTRATIONS: NCT02263872, registered October 2014, and ACTRN12612000283875, registered March 2012.

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OBJECTIVE: The role of mood disorders in cancer onset is unclear. The aim of this study was to investigate the association between mood disorder and incident cancer in a population-based sample of women. METHODS: Data were derived from women aged 28-94 years participating in the Geelong Osteoporosis Study. Mood disorder was identified via Clinical Interview (SCID-I/NP). Cancer data was obtained following linkage with the Victorian Cancer Registry. Demographic and lifestyle factors were self-reported. Nested case-control and retrospective study designs were utilized. RESULTS: In the case-control study (n=807), mood disorder was documented for 18 of the 75 (9.3%) cancer cases and among 288 controls (24.0% vs. 39.3%, p = 0.009). Prior exposure to mood disorder was associated with reduced cancer incidence (OR 0.49, 95%CI 0.28-0.84); this was sustained following adjustment for confounders (ORadj 0.52, 95%CI 0.30-0.90). In the retrospective cohort study (n=655), among 154 women with a history of mood disorder at baseline, 13 (8.5%) developed incident cancer during follow-up, whereas among 501 women with no history of mood disorder, 54 (10.8%) developed incident cancer. Exposure to mood disorder was not associated with incident cancer over the follow-up period (HR 0.58, 95%CI 0.31-1.08, p = 0.09). CONCLUSION: Mood disorder was associated with reduced odds of cancer onset. However, this finding was not supported in the retrospective cohort study. Larger studies able to investigate specific cancers and mood disorders as well as underlying mechanisms in both men and women are warranted.

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Objective: This study aimed to determine if personality disorder (PD) predicted functional outcomes in patients with major depressive disorder (MDD). Methods: Data (n=71) from a double-blind, randomized, placebo-controlled 12-week trial assessing the efficacy of 200 mg/day adjunctive minocycline for MDD were examined. PD was measured using the Standardized Assessment of Personality Abbreviated Scale. Outcome measures included Clinical Global Impression - Improvement (CGI-I), Quality of Life Enjoyment and Satisfaction Questionnaire (Q-LES-Q), Social and Occupational Functioning Scale (SOFAS), and Range of Impaired Functioning (RIFT). Analysis of covariance was used to examine the impact of PD (dichotomized factor [≥ 3] or continuous measure) on the outcome measures-treatment group correlation. Results: PD was identified in 69% of the sample. After adjusting for age, sex, and baseline scores for each of the outcome measures, there was no significant difference between participants with and without PD on week 12 scores for any of the outcome measures (all p > 0.14). Conclusion: In this secondary analysis of a primary efficacy study, PD was a common comorbidity among those with MDD, but was not a significant predictor of functional outcomes. This study adds to the limited literature on PD in randomized controlled trials for MDD. Clinical trial registration: ACTRN12612000283875.

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