Perimenopause and First-Onset Mood Disorders: A Closer Look.

Perimenopause is often a time of social, emotional, and physical change. Various factors contribute to the development of mood disorders during this time. There is a known association among women with previous history of major depressive disorder or bipolar disorder and relapse during the menopausal transition. First-onset mood disorders during this time have been less studied. A literature review in PsycInfo Ovid of records pertaining to first-onset mood disorders during perimenopause showed that this multifactorial process involves hormonal fluctuations, with estrogen being a key player. In addition, vasomotor symptoms, previous negative life events, and socioeconomic status were found to contribute to first-onset mood disorders during perimenopause. Treatment options include established medication regimens for psychiatric conditions; however, hormone therapy also has proven beneficial for this patient population. Further research, particularly on bipolar disorder, is needed to develop a clear association between perimenopause and first-onset mood disorders.

Corrigendum to "Applications of machine learning algorithms to predict therapeutic outcomes in depression: A meta-analysis and systematic review." J Affect Disord. 241 (2018) 519-532.

The authors regret an error in one of the extracted data points in the meta-analysis. The classification accuracy for Serretti et al. (2007) was corrected to 64% (Table 3b). The overall results before and after this correction remain directionally consistent and are summarized below (Figures 2 and 3; Table 2; results subsection 3.6). The authors apologise for any inconvenience caused.

Parental characteristics and the risk of schizophrenia in a Chinese population: a case-control study.

BACKGROUND: Genetic studies have provided convergent results indicating that schizophrenia is a polygenic disorder with a heritability estimate of ∼60-80%. The propensity for schizophrenia is ∼10 times higher in individuals with first-degree relatives with schizophrenia when compared to the general population. AIM: To identify associations between parental characteristics and the risk of schizophrenia in a Chinese population. METHODS: Participants with a diagnosis of schizophrenia were recruited along with healthy controls (HCs) matched for age and gender from Weifang, China. Logistic regression models and generalized linear models were used to explore the associations between parental characteristics with the risk and age at onset of schizophrenia. In total, 414 cases and 639 HCs were recruited for the study. RESULTS: We observed an inverse association between levels of paternal and maternal education and risk of schizophrenia after controlling for potential confounders (Paternal: OR = 1.525, 95% CI: 1.080-2.153, p = .017; Maternal: OR = 1.984, 95% CI: 1.346-2.924, p = .001). Younger paternal and maternal childbearing age were associated with a higher risk of diagnosis of schizophrenia. We furtherly observed that individuals with earlier age at onset of schizophrenia had fewer siblings (p = .007) and had higher rates of parental marital disharmony (p = .033). CONCLUSION: Our results indicate that parental years of education and age of childbearing are associated with an increased risk of schizophrenia in a Chinese population. Age of onset of schizophrenia was positively associated with a greater number of siblings and negatively associated with parental marital disharmony.

Characterizing acyl-carnitine biosignatures for schizophrenia: a longitudinal pre- and post-treatment study.

Subjects with schizophrenia have high risks of metabolic abnormalities and bioenergetic dysfunction. Acyl-carnitines involved in bioenergetic pathways provide potential biomarker targets for identifying early changes and onset characteristics in subjects with schizophrenia. We measured 29 acyl-carnitine levels within well-characterized plasma samples of adults with schizophrenia and healthy controls using liquid chromatography-mass spectrometry (LC-MS). Subjects with schizophrenia were measured at baseline and after 8 weeks of treatment. A total of 225 subjects with schizophrenia and 175 age- and gender-matched healthy controls were enrolled and 156 subjects completed the 8-week follow-up. With respect to plasma acyl-carnitines, the individuals with schizophrenia at baseline showed significantly higher levels of C4-OH (C3-DC) and C16:1, but lower concentrations of C3, C8, C10, C10:1, C10:2, C12, C14:1-OH, C14:2, and C14:2-OH when compared with healthy controls after controlling for age, sex, body mass index (BMI), smoking, and drinking. For the comparison between pretreatment and posttreatment subjects, all detected acyl-carnitines were significantly different between the two groups. Only the concentration of C3 and C4 were increased after selection by variable importance in projection (VIP) value >1.0 and false discovery rate (FDR) q value <0.05. A panel of acyl-carnitines were selected for the ability to differentiate subjects of schizophrenia at baseline from controls, pre- from post-treatment, and posttreatment from controls. Our data implicated acyl-carnitines with abnormalities in cellular bioenergetics of schizophrenia. Therefore, acyl-carnitines can be potential targets for future investigations into their roles in the pathoetiology of schizophrenia.

Recognition and Treatment of Cognitive Dysfunction in Major Depressive Disorder.

Major Depressive Disorder (MDD) is a prevalent, chronic, disabling, and multidimensional mental disorder. Cognitive dysfunction represents a core diagnostic and symptomatic criterion of MDD, and is a principal determinant of functional non-recovery. Cognitive impairment has been observed to persist despite remission of mood symptoms, suggesting dissociability of mood and cognitive symptoms in MDD. Recurrent impairments in several domains including, but not limited to, executive function, learning and memory, processing speed, and attention and concentration, are associated with poor psychosocial and occupational outcomes. Attempts to restore premorbid functioning in individuals with MDD requires regular screenings and assessment of objective and subjective measures of cognition by clinicians. Easily accessible and cost-effective tools such as the THINC-integrated tool (THINC-it) are suitable for use in a busy clinical environment and appear to be promising for routine usage in clinical settings. However, antidepressant treatments targeting specific cognitive domains in MDD have been insufficiently studied. While select antidepressants, e.g., vortioxetine, have been demonstrated to have direct and independent pro-cognitive effects in adults with MDD, research on additional agents remains nascent. A comprehensive clinical approach to cognitive impairments in MDD is required. The current narrative review aims to delineate the importance and relevance of cognitive dysfunction as a symptomatic target for prevention and treatment in the phenomenology of MDD.

Association between Helicobacter pylori infection and tumor markers: an observational retrospective study.

OBJECTIVE: Helicobacter pylori infection is a major cause of several cancers such as gastric, pancreatic and lung. The relationship between H. pylori and tumour markers continues to remain unclear. The primary goal of this study is to clarify the associations between H. pylori infection and six tumour markers (ie, carcinoembryonic antigen (CEA), cancer antigen (CA) 153, CA199, CA724, CA125 and alpha-fetoprotein (AFP)). The secondary goal is to provide understanding for further research about H. pylori infection and gastrointestinal cancer. DESIGN: Observational retrospective study. SETTING: The study was performed in Beijing, China, where enrolled subjects had all passed health examinations during the period of 2012-2016. Subjects were categorised into H. pylori (+) and H. pylori (-) group according to their infection status and the measured six biomarkers. We used logistic regression models and generalised linear models to explore the associations between H. pylori infection and six tumour markers (ie, CEA, CA153, CA199, CA724, CA125 and AFP). PARTICIPANTS: A total of 14 689 subjects were included and 6493 (44.2%) subjects were infected by H. pylori. The subjects had a mean age (1SD) of 45 (18) years. There were 4530 (31.0%) female subjects. RESULTS: After adjusting for the confounding factors, infections with H. pylori were found to be significantly associated with abnormal ratios in CEA, AFP and CA724 of H. pylori (+) to H. pylori (-) groups. Significant positive correlation was found between H. pylori infection and CEA values (adjusted ß=0.056; 95% CI 0.005 to 0.107; p=0.033). CONCLUSIONS: In this observational retrospective study, we observed the H. pylori infections in a Chinese population and found higher CEA level in H. pylori-infected subjects and abnormal ratios in CEA, AFP and CA724 in infected subjects to uninfected subjects. These findings may provide a basis for future exploration with H. pylori and tumour markers.

Applications of machine learning algorithms to predict therapeutic outcomes in depression: A meta-analysis and systematic review.

BACKGROUND: No previous study has comprehensively reviewed the application of machine learning algorithms in mood disorders populations. Herein, we qualitatively and quantitatively evaluate previous studies of machine learning-devised models that predict therapeutic outcomes in mood disorders populations. METHODS: We searched Ovid MEDLINE/PubMed from inception to February 8, 2018 for relevant studies that included adults with bipolar or unipolar depression; assessed therapeutic outcomes with a pharmacological, neuromodulatory, or manual-based psychotherapeutic intervention for depression; applied a machine learning algorithm; and reported predictors of therapeutic response. A random-effects meta-analysis of proportions and meta-regression analyses were conducted. RESULTS: We identified 639 records: 75 full-text publications were assessed for eligibility; 26 studies (n=17,499) and 20 studies (n=6325) were included in qualitative and quantitative review, respectively. Classification algorithms were able to predict therapeutic outcomes with an overall accuracy of 0.82 (95% confidence interval [CI] of [0.77, 0.87]). Pooled estimates of classification accuracy were significantly greater (p < 0.01) in models informed by multiple data types (e.g., composite of phenomenological patient features and neuroimaging or peripheral gene expression data; pooled proportion [95% CI] = 0.93[0.86, 0.97]) when compared to models with lower-dimension data types (pooledproportion=0.68[0.62,0.74]to0.85[0.81,0.88]). LIMITATIONS: Most studies were retrospective; differences in machine learning algorithms and their implementation (e.g., cross-validation, hyperparameter tuning); cannot infer importance of individual variables fed into learning algorithm. CONCLUSIONS: Machine learning algorithms provide a powerful conceptual and analytic framework capable of integrating multiple data types and sources. An integrative approach may more effectively model neurobiological components as functional modules of pathophysiology embedded within the complex, social dynamics that influence the phenomenology of mental disorders.

Probiotics for the treatment of depressive symptoms: An anti-inflammatory mechanism?

During the past decade, there has been renewed interest in the relationship between brain-based disorders, the gut microbiota, and the possible beneficial effects of probiotics. Emerging evidence suggests that modifying the composition of the gut microbiota via probiotic supplementation may be a viable adjuvant treatment option for individuals with major depressive disorder (MDD). Convergent evidence indicates that persistent low-grade inflammatory activation is associated with the diagnosis of MDD as well as the severity of depressive symptoms and probability of treatment response. The objectives of this review are to (1) evaluate the evidence supporting an anti-inflammatory effect of probiotics and (2) describe immune system modulation as a potential mechanism for the therapeutic effects of probiotics in populations with MDD. A narrative review of studies investigating the effects of probiotics on systemic inflammation was conducted. Studies were identified using PubMed/Medline, Google Scholar, and clinicaltrials.gov (from inception to November 2017) using the following search terms (and/or variants): probiotic, inflammation, gut microbiota, and depression. The available evidence suggests that probiotics should be considered a promising adjuvant treatment to reduce the inflammatory activation commonly found in MDD. Several controversial points remain to be addressed including the role of leaky gut, the role of stress exposure, and the role of blood-brain-barrier permeability. Taken together, the results of this review suggest that probiotics may be a potentially beneficial, but insufficiently studied, antidepressant treatment intervention.

Comparative efficacy and acceptability of antidiabetic agents for Alzheimer's disease and mild cognitive impairment: A systematic review and network meta-analysis.

This study (registered with PROSPERO, CRD42018085967) compares the efficacy (i.e. pro-cognitive effects) and acceptability of antidiabetic agents for Alzheimer's disease (AD) and mild cognitive impairment (MCI). Cochrane Library (CENTRAL), PubMed/MEDLINE, EMBASE and PsycINFO were searched from inception to January 15, 2018 for randomized controlled trials comparing antidiabetic agents with placebo and/or another active antidiabetic agent for the treatment of AD or MCI. Nineteen eligible studies (n = 4855) evaluating the effects of 6 different antidiabetic drugs (i.e. intranasal insulin, pioglitazone, rosiglitazone, metformin, sitagliptin and liraglutide) were included. The results of 29 pairwise comparisons indicated that cognition was significantly improved in subjects treated with antidiabetic agents compared with placebo. Pioglitazone 15 to 30 mg demonstrated the greatest efficacy compared to placebo in network meta-analysis. No significant differences in acceptability were identified when comparing agents with each other and with placebo. The current findings indicate a pro-cognitive class effect of antidiabetic agents in AD/MCI. Other antidiabetic agents should also be investigated in future studies.