Gender Differences in the Prevalence and Clinical Correlates of Metabolic Syndrome in First-Episode and Drug-Naïve Patients With Major Depressive Disorder.

OBJECTIVE: Major depressive disorder (MDD) is a severe psychiatric symptom worldwide, and the coexistence of MDD with metabolic syndrome (MetS) is common in clinical practice. However, gender differences in comorbid MetS in first-episode and drug-naïve (FEDN) MDD patients have not been reported. Here, we explored potential gender differences in the prevalence and clinical correlates of comorbid MetS in FEDN MDD patients. METHODS: A cross-sectional study of 1718 FEDN MDD patients was conducted. Demographic and clinical data were collected. The Hamilton Depression Scale (HAMD), Hamilton Anxiety Scale, and Positive and Negative Syndrome Scale positive subscale were used to evaluate depression, anxiety, and psychotic symptoms, respectively. RESULTS: The prevalence of MetS was 1.645-fold higher in female MDD patients (38.50%) than in male patients (26.53%). Patients with MetS had higher HAMD score, Hamilton Anxiety Scale score, and Positive and Negative Syndrome Scale positive subscale score than patients without MetS (p values < .001). Furthermore, suicide attempts (male: odds ratio [OR] = 1.706, p = .034; female: OR = 1.639, p = .004) and HAMD score (male: OR = 1.251, p < .001; female: OR = 1.148, p < .001) were independently associated with MetS in male and female patients, whereas age of onset was independently associated with MetS only in female patients (OR = 1.744, p = .047). CONCLUSIONS: Our findings suggest significant gender differences in the prevalence and clinical correlates of comorbid MetS in FEDN MDD patients. Clinical variables (suicide attempts and HAMD scores) may be independently associated with MetS in MDD patients.

Study on exosomes for identifying bipolar disorder in early stage: A cross-sectional and validation study protocol.

BACKGROUND: The difficulty is remained to accurately distinguish bipolar disorder (BD) from major depressive disorder (MDD) in early stage, with a delayed diagnosis for 5-10 years. BD patients are often treated with antidepressants systematically due to being diagnosed with MDD, affecting the disease course and clinical outcomes. The current study aims to explore the role of plasma exosomes as biomarker to distinguish BD from MDD in early stage. METHODS: Two stages are included. The first stage is a cross-sectional study, comparing the concentrations of plasma exosome microRNA and related proteins among BD group, MDD group, and healthy controls (HC) group (n = 40 respectively), to identify target biomarkers preliminarily. The "Latent Class Analysis" and "Receiver Operating Characteristic" analysis will be performed to determine the optimal concentration range for each biomarker. The second stage is to validate target markers in subjects, coming from an ongoing study focusing on patients with a first depressive episode. All target biomarkers will be test in plasma samples reserved at the initial stage to detect whether the diagnosis indicated by biomarker level is consistent with the diagnosis by DSM-5. Furthermore, the correlation between specific biomarkers and the manic episode, suicidal ideation, and adverse reactions will also be observed. DISCUSSION: Exosome-derived microRNA and related proteins have potential in serving as a good medium for exploring mental disorders because it can pass through the blood-brain barrier bidirectionally and convey a large amount of information stably. Improving the early diagnosis of BD would help implement appropriate intervention strategy as early as possible and significantly reduce the burden of disease.

Characterizing Major Depressive Disorder (MDD) using alpha-band activity in resting-state electroencephalogram (EEG) combined with MATRICS Consensus Cognitive Battery (MCCB).

BACKGROUND: The diagnosis of major depressive disorder (MDD) is commonly based on the subjective evaluation by experienced psychiatrists using clinical scales. Hence, it is particularly important to find more objective biomarkers to aid in diagnosis and further treatment. Alpha-band activity (7-13 Hz) is the most prominent component in resting electroencephalogram (EEG), which is also thought to be a potential biomarker. Recent studies have shown the existence of multiple sub-oscillations within the alpha band, with distinct neural underpinnings. However, the specific contribution of these alpha sub-oscillations to the diagnosis and treatment of MDD remains unclear. METHODS: In this study, we recorded the resting-state EEG from MDD and HC populations in both open and closed-eye state conditions. We also assessed cognitive processing using the MATRICS Consensus Cognitive Battery (MCCB). RESULTS: We found that the MDD group showed significantly higher power in the high alpha range (10.5-11.5 Hz) and lower power in the low alpha range (7-8.5 Hz) compared to the HC group. Notably, high alpha power in the MDD group is negatively correlated with working memory performance in MCCB, whereas no such correlation was found in the HC group. Furthermore, using five established classification algorithms, we discovered that combining alpha oscillations with MCCB scores as features yielded the highest classification accuracy compared to using EEG or MCCB scores alone. CONCLUSIONS: Our results demonstrate the potential of sub-oscillations within the alpha frequency band as a potential distinct biomarker. When combined with psychological scales, they may provide guidance relevant for the diagnosis and treatment of MDD.

The relationship between serum resolvin D1, NLRP3, cytokine levels, and adolescents with first-episode medication-naïve major depressive disorder.

BACKGROUND: Inflammation has become a critical pathological mechanism of Major Depressive Disorder (MDD). NLRP3 is a critical inflammatory pathway to maintain the immune balance. Recently, preclinical evidence showed that Resolvin D1 might potentially offer a new option for antidepressant treatment due to its protective effects through the inhibition of neuroinflammation. However, whether they have clinical value in the diagnosis and treatment evaluation of adolescent depression was unclear. METHODS: Forty-eight untreated first-episode adolescent patients with moderate to severe major depressive disorder, as well as 30 healthy adolescents (HCs, age and gender-matched), were enrolled for this study. Their ages ranged from 13 to 18 (15.75 ± 1.36) years. The patients were treated with fluoxetine for 6-8 weeks. HDRS-17 was used to evaluate the severity of depressive symptoms. Venous blood samples were collected at baseline for the two groups and at the time-point of post-antidepressant treatment for the patients. Serum concentrations of RvD1, NLRP3, IL-1ß, IL-18, and IL-4 were measured by enzyme-linked immunosorbent assays (ELISA) pre- and post-fluoxetine treatment. RESULTS: Serum levels of RvD1 and anti-inflammatory cytokine IL-4 were significantly elevated in adolescents with MDD compared to healthy adolescents, but no significant difference in NLRP3, IL-1ß, and IL-18 between the two groups. Meanwhile, RvD1 (positively) and IL-4 (negatively) were correlated with the severity of symptoms (HDRS-17 scores) after adjusting age, gender, and BMI. Interestingly, fluoxetine treatment significantly reduced the serum levels of RvD1, NLRP3, IL-1ß, and IL-18 in MDD adolescents but increased the levels of IL-4 relative to baseline. Furthermore, we observed that serum levels of RvD1 might be an excellent distinguishing indicator for depression and healthy adolescents. CONCLUSIONS: Our study is the first to compare RvD1 and NLRP3 between adolescent MDD and HCs. Our findings of reactive increase of RvD1 in adolescent MDD comprised a novel and critical contribution. Our results showed the presence of inflammation resolution unbalanced in adolescents with MDD and indicated that RvD1 might be an ideal biomarker for diagnosing and treating adolescent MDD.

Cluster analysis dissecting cognitive deficits in older adults with major depressive disorder and the association with neurofilament light chain.

BACKGROUND: Cognitive impairment is a growing problem with increasing burden in global aging. Older adults with major depressive disorder (MDD) have higher risk of dementia. Neurofilament light chain (NfL) has been proven as a potential biomarker in neurodegenerative disease, including dementia. We aimed to investigate the association between cognitive deficits and NfL levels in older adults with MDD. METHODS: In this cross-sectional study, we enrolled 39 MDD patients and 15 individuals with mild neurocognitive disorder or major neurocognitive disorder, Alzheimer's type, as controls, from a tertiary psychiatric hospital. Both groups were over age 65 and with matched Mini-Mental State Examination (MMSE) score. Demographic data, clinical variables, and plasma NfL levels were obtained. We used cluster analysis according to their cognitive profile and estimated the correlation between plasma NfL levels and each cognitive domain. RESULTS: In the MDD group, participants had higher rate of family psychiatry history and current alcohol use habit compared with controls. Control group of neurocognitive disorders showed significantly lower score in total MMSE and higher plasma NfL levels. Part of the MDD patients presented cognitive deficits clustered with that of neurocognitive disorders (cluster A). In cluster A, the total MMSE score (r=-0.58277, p=0.0287) and the comprehension domain (r=-0.71717, p=0.0039) were negatively correlated to NfL levels after adjusting for age, while the associations had not been observed in the other cluster. CONCLUSIONS: We noted the negative correlation between NfL levels and cognition in MDD patients clustered with neurodegenerative disorder, Alzheimer's type. NfL could be a promising candidate as a biomarker to predict subtype of patients in MDD to develop cognitive decline. Further longitudinal studies and within MDD cluster analysis are required to validate our findings for clinical implications.

Prevalence of major depressive disorder and its associated factors among adult patients with neurolathyrism in Dawunt District, Ethiopia; 2022: community-based cross-sectional study.

INTRODUCTION: Major Depressive Disorder (MDD) is one of the commonest mental disorders affecting more than 250 million people globally. Patients with chronic illnesses had higher risks for developing MDD than the general population. Neurolathyrism is a chronic illness characterized by lifelong incurable spastic paralysis of lower extremities; causing permanent disability. It is highly prevalent in Dawunt district, Ethiopia; with a point prevalence of 2.4%. Despite this, there were no previous studies assessing the prevalence of MDD among patients with neurolathyrism in Ethiopia. OBJECTIVE: To assess the prevalence of MDD and to identify its associated factors among patients with neurolathyrism in Dawunt district, Ethiopia. METHODS: A community based cross-sectional study was conducted on 260 samples in Dawunt district from February 01 to March 30/ 2021. Multistage sampling technique was used to select study participants. The patient Health Questionnaire-9 (PHQ-9) depression screening tool was used to diagnose MDD. PHQ-9 is a standardized depression screening tool and a PHQ-9 score of ≥ 10 has a sensitivity and specificity of 88.0% [95% CI (83.0-92.0%)] and 85.0% [95% CI (82.0-88.0%)] for screening MDD. Data were collected by interview; entered to EpiData version 4.2.0; exported to SPSS version 25.0 for analysis; descriptive statistics and binary logistic regression model were used; AOR with 95% CI was used to interpret the associations; and finally results were presented by texts, charts, graphs, and tables. RESULTS: A total of 256 adult patients with neurolathyrism were participated; and the prevalence of MDD was found to be 38.7%. Being female [AOR = 3.00; 95% CI (1.15, 7.84)], living alone [AOR = 2.77; 95% CI (1.02-7.53)], being on neurolathyrism stage-3 [AOR = 3.22; 95% CI (1.09, 9.54)] or stage-4 [AOR = 4.00; 95% CI (1.28, 12.48)], stigma [AOR = 2.69; 95% CI (1.34, 5.39)], and lack of social/ family support [AOR = 3.61; 95% CI (1.80, 7.24)] were found to have statistically significant association with an increased odds of MDD; while regular exercise and ever formal counselling were found to have statistically significant association with a decreased odds of MDD. CONCLUSION: The prevalence of MDD among neurolathyrism patients in Dawunt district was high. Lack of social support, stigma, not getting formal counselling, and not involving in regular exercise were modifiable risk factors. Therefore, social support, reducing stigma, formal counselling, and encouraging regular exercise might help to reduce the burden of MDD among neurolathyrism patients.

Validation of the predictive value of BDNF -87 methylation for antidepressant treatment success in severely depressed patients-a randomized rater-blinded trial.

BACKGROUND: Brain-derived neurotrophic factor (BDNF) is essential for antidepressant treatment of major depressive disorder (MDD). Our repeated studies suggest that DNA methylation of a specific CpG site in the promoter region of exon IV of the BDNF gene (CpG -87) might be predictive of the efficacy of monoaminergic antidepressants such as selective serotonin reuptake inhibitors (SSRIs), serotonin-norepinephrine reuptake inhibitors (SNRIs), and others. This trial aims to evaluate whether knowing the biomarker is non-inferior to treatment-as-usual (TAU) regarding remission rates while exhibiting significantly fewer adverse events (AE). METHODS: The BDNF trial is a prospective, randomized, rater-blinded diagnostic study conducted at five university hospitals in Germany. The study's main hypothesis is that {1} knowing the methylation status of CpG -87 is non-inferior to not knowing it with respect to the remission rate while it significantly reduces the AE rate in patients experiencing at least one AE. The baseline assessment will occur upon hospitalization and a follow-up assessment on day 49 (± 3). A telephone follow-up will be conducted on day 70 (± 3). A total of 256 patients will be recruited, and methylation will be evaluated in all participants. They will be randomly assigned to either the marker or the TAU group. In the marker group, the methylation results will be shared with both the patient and their treating physician. In the TAU group, neither the patients nor their treating physicians will receive the marker status. The primary endpoints include the rate of patients achieving remission on day 49 (± 3), defined as a score of ≤ 10 on the Hamilton Depression Rating Scale (HDRS-24), and the occurrence of AE. ETHICS AND DISSEMINATION: The trial protocol has received approval from the Institutional Review Boards at the five participating universities. This trial holds significance in generating valuable data on a predictive biomarker for antidepressant treatment in patients with MDD. The findings will be shared with study participants, disseminated through professional society meetings, and published in peer-reviewed journals. TRIAL REGISTRATION: German Clinical Trial Register DRKS00032503. Registered on 17 August 2023.

Towards precision in the diagnostic profiling of patients: leveraging symptom dynamics as a clinical characterisation dimension in the assessment of major depressive disorder.

BACKGROUND: International guidelines present overall symptom severity as the key dimension for clinical characterisation of major depressive disorder (MDD). However, differences may reside within severity levels related to how symptoms interact in an individual patient, called symptom dynamics. AIMS: To investigate these individual differences by estimating the proportion of patients that display differences in their symptom dynamics while sharing the same overall symptom severity. METHOD: Participants with MDD (n = 73; mean age 34.6 years, s.d. = 13.1; 56.2% female) rated their baseline symptom severity using the Inventory for Depressive Symptomatology Self-Report (IDS-SR). Momentary indicators for depressive symptoms were then collected through ecological momentary assessments five times per day for 28 days; 8395 observations were conducted (average per person: 115; s.d. = 16.8). Each participant's symptom dynamics were estimated using person-specific dynamic network models. Individual differences in these symptom relationship patterns in groups of participants sharing the same symptom severity levels were estimated using individual network invariance tests. Subsequently, the overall proportion of participants that displayed differential symptom dynamics while sharing the same symptom severity was calculated. A supplementary simulation study was conducted to investigate the accuracy of our methodology against false-positive results. RESULTS: Differential symptom dynamics were identified across 63.0% (95% bootstrapped CI 41.0-82.1) of participants within the same severity group. The average false detection of individual differences was 2.2%. CONCLUSIONS: The majority of participants within the same depressive symptom severity group displayed differential symptom dynamics. Examining symptom dynamics provides information about person-specific psychopathological expression beyond severity levels by revealing how symptoms aggravate each other over time. These results suggest that symptom dynamics may be a promising new dimension for clinical characterisation, warranting replication in independent samples. To inform personalised treatment planning, a next step concerns linking different symptom relationship patterns to treatment response and clinical course, including patterns related to spontaneous recovery and forms of disorder progression.

Developing a prediction model to identify people with severe mental illness without regular contact to their GP - a study based on data from the Danish national registers.

INTRODUCTION: People with severe mental illness (SMI) face a higher risk of premature mortality due to physical morbidity compared to the general population. Establishing regular contact with a general practitioner (GP) can mitigate this risk, yet barriers to healthcare access persist. Population initiatives to overcome these barriers require efficient identification of those persons in need. OBJECTIVE: To develop a predictive model to identify persons with SMI not attending a GP regularly. METHOD: For individuals with psychotic disorder, bipolar disorder, or severe depression between 2011 and 2016 (n = 48,804), GP contacts from 2016 to 2018 were retrieved. Two logistic regression models using demographic and clinical data from Danish national registers predicted severe mental illness without GP contact. Model 1 retained significant main effect variables, while Model 2 included significant bivariate interactions. Goodness-of-fit and discriminating ability were evaluated using Hosmer-Lemeshow (HL) test and area under the receiver operating characteristic curve (AUC), respectively, via cross-validation. RESULTS: The simple model retained 11 main effects, while the expanded model included 13 main effects and 10 bivariate interactions after backward elimination. HL tests were non-significant for both models (p = 0.50 for the simple model and p = 0.68 for the extended model). Their respective AUC values were 0.789 and 0.790. CONCLUSION: Leveraging Danish national register data, we developed two predictive models to identify SMI individuals without GP contact. The extended model had slightly better model performance than the simple model. Our study may help to identify persons with SMI not engaging with primary care which could enhance health and treatment outcomes in this group.

Depression and cognition are associated with lipid dysregulation in both a multigenerational study of depression and the National Health and Nutrition Examination Survey.

Chronic dysregulation of peripheral lipids has been found to be associated with depression and cognition, but their interaction has not been investigated. Growing evidence has highlighted the association between peripheral lipoprotein levels with depression and cognition with inconsistent results. We assessed the association between peripheral lipids, depression, and cognition while evaluating their potential interactions using robust clinically relevant predictors such as lipoprotein levels and chronic medical disorders that dysregulate lipoproteins. We report an association between peripheral lipids, depression, and cognition, suggesting a common underlying biological mechanism driven by lipid dysregulation in two independent studies. Analysis of a longitudinal study of a cohort at high or low familial risk for major depressive disorder (MDD) (n = 526) found metabolic diseases, including diabetes, hypertension, and other cardiovascular diseases, were associated with MDD and cognitive outcomes. Investigating a cross-sectional population survey of adults in the National Health and Nutrition Examination Survey 2011-2014 (NHANES) (n = 2377), depression was found to be associated with high density lipoprotein (HDL) and cognitive assessments. In the familial risk study, medical conditions were found to be associated with chronic lipid dysregulation and were significantly associated with MDD using the structural equation model. A positive association between chronic lipid dysregulation and cognitive scores was found in an exploratory analysis of the familial risk study. In a complementary study, analysis of NHANES revealed a positive association of HDL levels with cognition. Further analysis of the NHANES cohort indicated that depression status mediated the interaction between HDL levels and cognitive tests. Importantly, the protective effect of HDL on cognition was absent in those with depressive symptoms, which may ultimately result in worse outcomes leading to cognitive decline. These findings highlight the potential for the early predictive value of medical conditions with chronic lipid dyshomeostasis for the risk of depression and cognitive decline.

Is there a relationship between the severity of disease in major depressive disorder patients and dry eye disease?

PURPOSE: To investigate dry eye disease (DED) in newly diagnosed patients with depressive disorder (MDD). METHOD: This observational study included 48 MDD patients in Group 1 and 20 healthy controls in Group 2. Psychiatric and ophthalmic examinations, Beck Depression Inventory (BDI), Ocular Surface Disease Index (OSDI), Schirmer's test, tear breakup time (TBUT), Meibomian gland dysfunction (MGD), and ocular staining were conducted. The results were statistically compared. RESULTS: The participants, comprising 32 men and 36 women, had a mean age of 31.08 ± 11.7 years (18-64 years). Group 1 had a mean BDI score of 30.87 ± 8.56, while Group 2 had a score of 1.3 ± 1.3 (p < 0.001). In Group 1, 28 patients were diagnosed with DED, whereas in Group 2, six subjects were diagnosed with DED. The mean Schirmer's results in Group 1 and Group 2 were (mm/5 min) 10.87 ± 2.44 and 12.70 ± 2.3, respectively, and were significantly lower in Group 1 (p < 0.001). The mean OSDI scores in Group 1 (34.95 ± 15.8) were significantly higher compared to Group 2 (3.2 ± 3.1) (p < 0.001). There was no significant difference in mean TBUT between Group 1 (9.41 ± 2.6 s) and Group 2 (9.8 ± 0.61 s) (p > 0.05). Significant correlations were found between BDI scores and Schirmer's results as well as OSDI scores (p < 0.05, p = 0.02, respectively). No statistically significant correlations were found between BDI scores and TBUT or MGD (p > 0.05). CONCLUSION: DED was found to be more prevalent in the MDD group. The severity of MDD and DED, as indicated by BDI, OSDI, and Schirmer's results, was found to be correlated. It was observed that patients with higher depression scores had more severe dry eye. As a result, we recommend performing ophthalmic examinations in newly diagnosed MDD patients.

Omega-3 fatty acids for inflamed depression - A match/mismatch study.

Despite decades of research on the pathophysiology of depression, the development of new therapeutic interventions has been slow, and no biomarkers of treatment response have been clinically implemented. Several lines of evidence suggest that the clinical and biological heterogeneity among patients with major depressive disorder (MDD) has hampered progress in this field. MDD with low-grade inflammation - "inflamed depression" - is a subtype of depression that may be associated with a superior antidepressant treatment response to anti-inflammatory compounds. Omega-3 fatty acid eicosapentaenoic acid (EPA) has anti-inflammatory properties, and preliminary data suggest that it may be particularly efficacious in inflamed depression. In this study we tested the hypothesis that add-on EPA has greater antidepressant efficacy in MDD patients with high baseline high-sensitivity C-reactive protein (hs-CRP) compared to MDD patients with low hs-CRP. All subjects received 2.2 g EPA, 400 mg docosahexaenoic acid and 800 mg of other fatty acids daily for 8 weeks, added to stable ongoing antidepressant treatment. The primary outcome was change in the 17-item Hamilton Depression Rating Scale (HAMD-17). Patients and raters were blind to baseline hs-CRP status. In an intention-to-treat analysis including all subjects with at least one post baseline visit (n = 101), ahs-CRPcut-off of ≥1 mg/L, but not ≥3 mg/L, was associated with a greater improvement in HAMD-17 total score. In addition to a general antidepressant effect among patients with hs-CRP ≥ 1 mg/L, adjuvant EPA treatment improved symptoms putatively related to inflamed depression such as fatigue and sleep difficulties. This adds to the mounting evidence that delineation of MDD subgroups based on inflammation may be clinically relevant to predict treatment response to anti-inflammatory interventions.

Quality Indicators for Major Depressive Disorder in Adults: A Review of Performance Measures by the American College of Physicians.

Major depressive disorder (MDD) is a severe mood disorder that affects at least 8.4% of the adult population in the United States. Characteristics of MDD include persistent sadness, diminished interest in daily activities, and a state of hopelessness. The illness may progress quickly and have devastating consequences if left untreated. Eight performance measures are available to evaluate screening, diagnosis, and successful management of MDD. However, many performance measures do not meet the criteria for validity, reliability, evidence, and meaningfulness.The American College of Physicians (ACP) embraces performance measurement as a means to externally validate the quality of care of practices, medical groups, and health plans and to drive reimbursement processes. However, a plethora of performance measures that provide low or no value to patient care have inundated physicians, practices, and systems and burdened them with collecting and reporting of data. The ACP's Performance Measurement Committee (PMC) reviews performance measures using a validated process to inform regulatory and accreditation bodies in an effort to recognize high-quality performance measures, address gaps and areas for improvement in performance measures, and help reduce reporting burden. Out of 8 performance measures, the PMC found only 1 measure (suicide risk assessment) that was valid at all levels of attribution. This paper presents a review of MDD performance measures and highlights opportunities to improve performance measures addressing MDD management.

Postpartum blues: a predictor of postpartum depression, from the IGEDEPP Cohort.

BACKGROUND: To identify the different factors associated with postpartum blues and its association with postpartum depression, from a large French cohort. METHODS: We conducted an analysis of the Interaction Gene Environment in Postpartum Depression cohort, which is a prospective, multicenter cohort including 3310 women. Their personal (according to the Diagnostic and Statistical Manual, fifth edition [DSM-5]) and family psychiatric history, stressful life events during childhood, pregnancy, and delivery were collected. Likewise, the French version of the Maternity Blues Scale questionnaire was administered at the maternity department. Finally, these women were assessed at 8 weeks and 1 year postpartum by a clinician for postpartum depression according to DSM-5 criteria. RESULTS: The prevalence of postpartum blues in this population was 33%, and significant factors associated with postpartum blues were found as personal (aOR = 1.2) and family psychiatric history (aOR = 1.2), childhood trauma (aOR = 1.3), obstetrical factors, or events related to the newborn, as well as an experience of stressful life events during pregnancy (aOR = 1.5). These factors had a cumulative effect, with each additional factor increasing the risk of postpartum blues by 31%. Furthermore, adjustment for sociodemographic measures and history of major depressive episode revealed a significant association between postpartum blues and postpartum depression, mainly at early onset, within 8 weeks after delivery (aOR = 2.1; 95% CI = 1.6-2.7), but also at late onset (aOR = 1.4; 95% CI = 1.1-1.9), and mainly if the postpartum blues is severe. CONCLUSION: These results justify raising awareness among women with postpartum blues, including reassurance and information about postpartum depression, its symptomatology, and the need for management in case of worsening or prolongation of postpartum blues.

IV low dose ketamine infusions for treatment resistant depression: Results from a five-year study at a free public clinic in an academic hospital.

Individuals with major depressive disorder and treatment resistant depression (MDD-TRD) have limited and sometimes poorly tolerated therapeutic options. Low dose ketamine has presented promising and potent antidepressant effects in this population. To support the existent literature, we conducted a longitudinal study examining five years of real-world clinical data on the use of IV low-dose ketamine alongside standard care for MDD-TRD outpatients. For this study we collected demographic information, clinical scale scores, side effects and dropout data. The data was analyzed using descriptive statistics, effect size using Cohen's D analysis, and multivariate ANOVA (MANOVA) to determine the impact of sociodemographic variables. 71 outpatients (50.28 years old, SD: 14.26; female 74.65%) were included in the analysis. The results showed a significant reduction in depressive symptoms and suicide ideation (SI) by treatment endpoint. 54.93% of patients responded to the treatment, 78.26% experienced transient and mild side effects, and 11.27% of dropped out of the treatment. Multivariate analysis showed that the demographic variables did not impact treatment effect or tolerability. The results of this study suggest that IV low dose ketamine treatment is effective, fast-acting, and well tolerated for the management of depressive symptoms and SI in patients with MDD-TRD in naturalistic clinical practice.

Identifying predictive factors for mood recurrence in early-onset major mood disorders: A 4-year, multicenter, prospective cohort study.

We investigate the predictive factors of the mood recurrence in patients with early-onset major mood disorders from a prospective observational cohort study from July 2015 to December 2019. A total of 495 patients were classified into three groups according to recurrence during the cohort observation period: recurrence group with (hypo)manic or mixed features (MMR), recurrence group with only depressive features (ODR), and no recurrence group (NR). As a result, the baseline diagnosis of bipolar disorder type 1 (BDI) and bipolar disorder type 2 (BDII), along with a familial history of BD, are strong predictors of the MMR. The discrepancies in wake-up times between weekdays and weekends, along with disrupted circadian rhythms, are identified as a notable predictor of ODR. Our findings confirm that we need to be aware of different predictors for each form of mood recurrences in patients with early-onset mood disorders. In clinical practice, we expect that information obtained from the initial assessment of patients with mood disorders, such as mood disorder type, family history of BD, regularity of wake-up time, and disruption of circadian rhythms, can help predict the risk of recurrence for each patient, allowing for early detection and timely intervention.

Point of Care Testing (POCT) in Psychopathology Using Fractal Analysis and Hilbert Huang Transform of Electroencephalogram (EEG).

Research has shown that relying only on self-reports for diagnosing psychiatric disorders does not yield accurate results at all times. The advances of technology as well as artificial intelligence and other machine learning algorithms have allowed the introduction of point of care testing (POCT) including EEG characterization and correlations with possible psychopathology. Nonlinear methods of EEG analysis have significant advantages over linear methods. Empirical mode decomposition (EMD) is a reliable nonlinear method of EEG pre-processing. In this chapter, we compare two existing EEG complexity measures - Higuchi fractal dimension (HFD) and sample entropy (SE), with our newly proposed method using Higuchi fractal dimension from the Hilbert Huang transform (HFD-HHT). We present an example using the three complexity measures on a 2-minute EEG recorded from a healthy 20-year-old male after signal pre-processing. Furthermore, we showed the usefulness of these complexity measures in the classification of major depressive disorder (MDD) with healthy controls. Our study is in line with previous research and has shown an increase in HFD and SE values in the full, alpha and beta frequency bands suggestive of an increase in EEG irregularity. Moreover, the HFD-HHT values decreased in those three bands for majority of electrodes which is suggestive of a decrease in irregularity in the frequency-time domain. We conclude that all three complexity measures can be vital features useful for EEG analysis which could be incorporated in POCT systems.

Comparative study of sleep and circadian rhythms in patients presenting unipolar or bipolar major depressive episodes.

Currently, there is a major challenge in distinguishing between unipolar and bipolar major depressive episode. A significant body of research has been dedicated to identifying biomarkers that can aid in this differentiation due to its crucial implications, particularly for therapeutic and prognostic purposes. Among the biomarkers of interest, markers related to sleep and circadian rhythms show promise and could potentially aid in making this distinction. Nevertheless, no study has simultaneously examined sleep-wake disorders, circadian rhythms, and seasonal patterns using both subjective and objective measures. This study aims to characterize and compare the sleep-wake and rhythm disorders including patients with unipolar major depressive episode (n = 72) and with bipolar major depressive episode (n = 43) using both subjective markers (using self-report questionnaires and sleep complaints) and objective markers (using actigraphy). Patients with unipolar major depressive episode seem to experience significantly poorer quality of sleep, more symptoms of insomnia and lower sleep efficiency compared to patients with bipolar major depressive episode. On the other hand, patients with bipolar major depressive episode exhibit significantly more symptoms of motor retardation and hypersomnia compared to patients with unipolar disorder. These results hold significant implications for identifying individuals with unipolar major depressive episode or bipolar major depressive episode using sleep and circadian markers, and for developing recommended and personalized therapeutic strategies.

Cognitive function based on theta-gamma coupling vs. clinical diagnosis in older adults with mild cognitive impairment with or without major depressive disorder.

Whether individuals with mild cognitive impairment (MCI) and a history of major depressive disorder (MDD) are at a higher risk for cognitive decline than those with MCI alone is still not clear. Previous work suggests that a reduction in prefrontal cortical theta phase-gamma amplitude coupling (TGC) is an early marker of cognitive impairment. This study aimed to determine whether using a TGC cutoff is better at separating individuals with MCI or MCI with remitted MDD (MCI+rMDD) on cognitive performance than their clinical diagnosis. Our hypothesis was that global cognition would differ more between TGC-based groups than diagnostic groups. We analyzed data from 128 MCI (mean age: 71.8, SD: 7.3) and 85 MCI+rMDD (mean age: 70.9, SD: 4.7) participants. Participants completed a comprehensive neuropsychological battery; TGC was measured during the N-back task. An optimal TGC cutoff was determined during the performance of the 2-back. This TGC cutoff was used to classify participants into low vs. high-TGC groups. We then compared Cohen's d of the difference in global cognition between the high and low TGC groups to Cohen's d between the MCI and MCI+rMDD groups. We used bootstrapping to determine 95% confidence intervals for Cohen's d values using the whole sample. As hypothesized, Cohen's d for the difference in global cognition between the TGC groups was larger (0.64 [0.32, 0.88]) than between the diagnostic groups (0.10 [0.004, 0.37]) with a difference between these two Cohen's d's of 0.54 [0.10, 0.80]. Our findings suggest that TGC is a useful marker to identify individuals at high risk for cognitive decline, beyond clinical diagnosis. This could be due to TGC being a sensitive marker of prefrontal cortical dysfunction that would lead to an accelerated cognitive decline.

Gut microbial CAZymes markers for depression.

Major depressive disorder (MDD) is a serious mental illness, characterized by disturbances of gut microbiome, it is required to further explore how the carbohydrate-active enzymes (CAZymes) were changed in MDD. Here, using the metagenomic data from patients with MDD (n = 118) and heath controls (HC, n = 118), we found that the whole CAZymes signatures of MDD were significantly discriminated from that in HC. α-diversity indexes of the two groups were also significantly different. The patients with MDD were characterized by enriched Glycoside Hydrolases (GHs) and Polysaccharide Lyases (PLs) relative to HC. A panel of makers composed of 9 CAZymes mainly belonging to GHs enabled to discriminate the patients with MDD and HC with AUC of 0.824. In addition, this marker panel could classify blinded test samples from the two groups with an AUC of 0.736. Moreover, we found that baseline 4 CAZymes levels also could predict the antidepressant efficacy after adjusted confounding factors and times of depressive episode. Our findings showed that MDD was associated with disturbances of gut CAZymes, which may help to develop diagnostic and predictive tools for depression.