Lifetime Major Depressive Disorder Research Articles

Major depression recurrence is associated with differences in obesity-related traits in women, but not in men.

Obesity-related cardiometabolic comorbidity is common in major depressive disorder (MDD). However, sex differences and MDD recurrence may modify the MDD-obesity-link. Sex-specific associations of MDD recurrence (single [MDDS] or recurrent episodes [MDDR]) and obesity-related traits were analyzed in 4.100 adults (51.6% women) from a cross-sectional population-based cohort in Germany (SHIP-Trend-0). DSM-IV-based lifetime MDD diagnoses and MDD recurrence status were obtained through diagnostic interviews. Obesity-related outcomes included anthropometrics (weight, body mass index, waist- and hip-circumference, waist-to-hip ratio, waist-to-height ratio), bioelectrical impedance analysis of body fat mass and fat-free mass, and subcutaneous (SAT) and visceral adipose tissue (VAT) from abdominal magnetic resonance imaging. Sex-stratified linear regression models predicting obesity-related traits from MDD recurrence status were adjusted for age, education, and current depressive symptoms. 790 participants (19.3%) fulfilled lifetime MDD criteria (23.8% women vs. 14.5% men, p<0.001). In women, MDDS was inversely associated with anthropometric indicators of general and central obesity, while MDDR was positively associated with all obesity-related traits, except waist-to-hip ratio and fat-free mass. In women, MDDR versus MDDS was associated with higher levels of obesity across all outcomes except fat-free mass. In men, MDD was positively associated with SAT regardless of MDD recurrence. Additionally, lifetime MDD was positively associated with VAT in men. Results remained significant in sensitivity analyses after exclusion of participants with current use of antidepressants. The MDD-obesity association is modified by MDD recurrence and sex independent of current depressive symptoms. Accounting for sex and MDD recurrence may identify individuals with MDD at increased cardiometabolic risk.

The interaction between TMEM161B (rs768705) and paranoid personality traits in relation to the risk of major depressive disorder: Results form a longitudinal study of 7642 Chinese freshmen

BackgroundRs768705 (TMEM161B) is one of the identified single nucleotide polymorphisms related to major depressive disorder (MDD). Paranoid personality traits are independently associated with the risk of MDD. This study aimed to investigate the interaction effect between rs768705 (TMEM161B) and paranoid personality traits on the new-onset risk of MDD in Chinese freshmen. MethodsA longitudinal study was conducted among 7642 Chinese freshmen without lifetime MDD at baseline in 2018. 158 new-onset MDD cases were ascertained in 2019. DNA samples were extracted to detect the genotype of rs768705. The diagnostic and statistical manual of mental disorders-IV criteria were used to determine MDD and personality disorder traits. Multiplicative interaction was assessed by logistic regression models. Tomas Andersson's method for calculating biological interactions was used to estimate the additive interaction. ResultsRs768705(AG) (OR = 1.88, 95 % CI: 1.24–2.83) and paranoid personality traits (OR = 3.68, 95 % CI: 2.57–5.26) were significantly associated with the risk of MDD. The multiplicative interaction model with the product term of rs768705 and paranoid personality trait traits had a significant interaction effect (OR = 4.20, 95 % CI:1.62–10.91). There was also a significant additive interaction effect (RR = 7.08, 95 % CI:4.31–11.65) for the incidence of MDD. Seventy seven percent patients among new MDD cases were attributed to the additive interaction effect between rs768705 and paranoid personality traits. ConclusionsRs768705 (AG) may interact with paranoid personality traits to increase the incidence of MDD among Chinese college students. Schools and psychosocial health organizations should pay more attention to individuals with paranoid personality traits for MDD intervention and prevention.

Genetic architecture and socio-environmental risk factors for major depressive disorder in Nepal.

Major depressive disorder (MDD) is the leading cause of disability globally, with moderate heritability and well-established socio-environmental risk factors. Genetic studies have been mostly restricted to European settings, with polygenic scores (PGS) demonstrating low portability across diverse global populations. This study examines genetic architecture, polygenic prediction, and socio-environmental correlates of MDD in a family-based sample of 10 032 individuals from Nepal with array genotyping data. We used genome-based restricted maximum likelihood to estimate heritability, applied S-LDXR to estimate the cross-ancestry genetic correlation between Nepalese and European samples, and modeled PGS trained on a GWAS meta-analysis of European and East Asian ancestry samples. We estimated the narrow-sense heritability of lifetime MDD in Nepal to be 0.26 (95% CI 0.18-0.34, p = 8.5 × 10-6). Our analysis was underpowered to estimate the cross-ancestry genetic correlation (rg = 0.26, 95% CI -0.29 to 0.81). MDD risk was associated with higher age (beta = 0.071, 95% CI 0.06-0.08), female sex (beta = 0.160, 95% CI 0.15-0.17), and childhood exposure to potentially traumatic events (beta = 0.050, 95% CI 0.03-0.07), while neither the depression PGS (beta = 0.004, 95% CI -0.004 to 0.01) or its interaction with childhood trauma (beta = 0.007, 95% CI -0.01 to 0.03) were strongly associated with MDD. Estimates of lifetime MDD heritability in this Nepalese sample were similar to previous European ancestry samples, but PGS trained on European data did not predict MDD in this sample. This may be due to differences in ancestry-linked causal variants, differences in depression phenotyping between the training and target data, or setting-specific environmental factors that modulate genetic effects. Additional research among under-represented global populations will ensure equitable translation of genomic findings.

Causes of death in individuals with lifetime major depression: a comprehensive machine learning analysis from a community-based autopsy center

BackgroundDepression can be associated with increased mortality and morbidity, but no studies have investigated the specific causes of death based on autopsy reports. Autopsy studies can yield valuable and detailed information on pathological ailments or underreported conditions. This study aimed to compare autopsy-confirmed causes of death (CoD) between individuals diagnosed with major depressive disorder (MDD) and matched controls. We also analyzed subgroups within our MDD sample, including late-life depression and recurrent depression. We further investigated whether machine learning (ML) algorithms could distinguish MDD and each subgroup from controls based on their CoD.MethodsWe conducted a comprehensive analysis of CoD in individuals who died from nontraumatic causes. The diagnosis of lifetime MDD was ascertained based on the DSM-5 criteria using information from a structured interview with a knowledgeable informant. Eleven established ML algorithms were used to differentiate MDD individuals from controls by simultaneously analyzing different disease category groups to account for multiple tests. The McNemar test was further used to compare paired nominal data.ResultsThe initial dataset included records of 1,102 individuals, among whom 232 (21.1%) had a lifetime diagnosis of MDD. Each MDD individual was strictly paired with a control non-psychiatric counterpart. In the MDD group, the most common CoD were circulatory (67.2%), respiratory (13.4%), digestive (6.0%), and cancer (5.6%). Despite employing a range of ML models, we could not find distinctive CoD patterns that could reliably distinguish individuals with MDD from individuals in the control group (average accuracy: 50.6%; accuracy range: 39-59%). These findings were consistent even when considering factors within the MDD group, such as late-life or recurrent MDD. When comparing groups with paired nominal tests, no differences were found for circulatory (p=0.450), respiratory (p=0.790), digestive (p=1.000), or cancer (p=0.855) CoD.ConclusionsOur analysis revealed that autopsy-confirmed CoD exhibited remarkable similarity between individuals with depression and their matched controls, underscoring the existing heterogeneity in the literature. Future research should prioritize more severe manifestations of depression and larger sample sizes, particularly in the context of CoD related to cancer.

Prevalence and correlates of common mental disorders among participants of the Uganda Genome Resource: Opportunities for psychiatric genetics research.

Genetics research has potential to alleviate the burden of mental disorders in low- and middle-income-countries through identification of new mechanistic pathways which can lead to efficacious drugs or new drug targets. However, there is currently limited genetics data from Africa. The Uganda Genome Resource provides opportunity for psychiatric genetics research among underrepresented people from Africa. We aimed at determining the prevalence and correlates of major depressive disorder (MDD), suicidality, post-traumatic stress disorder (PTSD), alcohol abuse, generalised anxiety disorder (GAD) and probable attention-deficit hyperactivity disorder (ADHD) among participants of the Uganda Genome Resource. Standardised tools assessed for each mental disorder. Prevalence of each disorder was calculated with 95% confidence intervals. Multivariate logistic regression models evaluated the association between each mental disorder and associated demographic and clinical factors. Among 985 participants, prevalence of the disorders were: current MDD 19.3%, life-time MDD 23.3%, suicidality 10.6%, PTSD 3.1%, alcohol abuse 5.7%, GAD 12.9% and probable ADHD 9.2%. This is the first study to determine the prevalence of probable ADHD among adult Ugandans from a general population. We found significant association between sex and alcohol abuse (adjusted odds ratio [AOR] = 0.26 [0.14,0.45], p < 0.001) and GAD (AOR = 1.78 [1.09,2.49], p = 0.019) respectively. We also found significant association between body mass index and suicidality (AOR = 0.85 [0.73,0.99], p = 0.041), alcohol abuse (AOR = 0.86 [0.78,0.94], p = 0.003) and GAD (AOR = 0.93 [0.87,0.98], p = 0.008) respectively. We also found a significant association between high blood pressure and life-time MDD (AOR = 2.87 [1.08,7.66], p = 0.035) and probable ADHD (AOR = 1.99 [1.00,3.97], p = 0.050) respectively. We also found a statistically significant association between tobacco smoking and alcohol abuse (AOR = 3.2 [1.56,6.67], p = 0.002). We also found ever been married to be a risk factor for probable ADHD (AOR = 2.12 [0.88,5.14], p = 0.049). The Uganda Genome Resource presents opportunity for psychiatric genetics research among underrepresented people from Africa.

Association of Lower Rostral Anterior Cingulate GABA+ and Dysregulated Cortisol Stress Response With Altered Functional Connectivity in Young Adults With Lifetime Depression: A Multimodal Imaging Investigation of Trait and State Effects.

Preclinical work suggests that excess glucocorticoids and reduced cortical γ-aminobutyric acid (GABA) may affect sex-dependent differences in brain regions implicated in stress regulation and depressive phenotypes. The authors sought to address a critical gap in knowledge, namely, how stress circuitry is functionally affected by glucocorticoids and GABA in current or remitted major depressive disorder (MDD). Multimodal imaging data were collected from 130 young adults (ages 18-25), of whom 44 had current MDD, 42 had remitted MDD, and 44 were healthy comparison subjects. GABA+ (γ-aminobutyric acid and macromolecules) was assessed using magnetic resonance spectroscopy, and task-related functional MRI data were collected under acute stress and analyzed using data-driven network modeling. Across modalities, trait-related abnormalities emerged. Relative to healthy comparison subjects, both clinical groups were characterized by lower rostral anterior cingulate cortex (rACC) GABA+ and frontoparietal network amplitude but higher amplitude in salience and stress-related networks. For the remitted MDD group, differences from the healthy comparison group emerged in the context of elevated cortisol levels, whereas the MDD group had lower cortisol levels than the healthy comparison group. In the comparison group, frontoparietal and stress-related network connectivity was positively associated with cortisol level (highlighting putative top-down regulation of stress), but the opposite relationship emerged in the MDD and remitted MDD groups. Finally, rACC GABA+ was associated with stress-induced changes in connectivity between overlapping default mode and salience networks. Lifetime MDD was characterized by reduced rACC GABA+ as well as dysregulated cortisol-related interactions between top-down control (frontoparietal) and threat (task-related) networks. These findings warrant further investigation of the role of GABA in the vulnerability to and treatment of MDD.

462 Depression Moderates Independent Effects of Daily Natural Light Exposure and Activity on Daily Mood

OBJECTIVES/GOALS: Ambulatory methods are useful tools to study physical and mental health in everyday life. While many studies show daily activity improves mood, the effects of daily light exposure on mood remain unknown. This study evaluated the effects of daily natural light exposure and activity on daily mood and evaluate whether depression moderate effects. METHODS/STUDY POPULATION: 82 adults with lifetime major depression disorder (25 current) and 49 healthy controls were recruited from the greater Chicago community (N = 131, 62% female, age M = 30.15, SD = 9.94). At baseline, participants completed the Inventory of Depression and Anxiety Symptoms to measure depression symptoms of anhedonia, or loss of pleasure. Positive and negative affect were then measured 3x daily for 14-days via self-report using smartphones while light exposure and activity were continuously recorded from a wrist-worn actigraphy device. Following prior studies, daily natural light exposure was measured as the total number of white light samples greater than 1000 lux each day. Multilevel models were used to separate within-person (daily level) from between-person (subject level) effects. RESULTS/ANTICIPATED RESULTS: Results revealed daily within-person activity (p &lt; .001) and natural light exposure duration (p = .035) were independently associated with increased positive affect. Effects were significantly moderated by baseline anhedonia symptoms (3-way interaction: p = .004). Natural light exposure duration only increased positive affect on lower activity days for high anhedonia and higher activity days for low anhedonia (ps &lt; .018). Significant results remained controlling for between-person light and activity, time of year, age, sex, negative affect, and baseline general depression symptoms. Compared to one’s own daily averages, daily activity and natural light exposure may be independent pathways to boost positive affect, especially for individuals with high anhedonia symptoms. DISCUSSION/SIGNIFICANCE: Results suggest daily natural light exposure may be an accessible, low-cost alternative to independently increase positive affect in depression on days when activity is low. Translational applications are discussed focusing on transdiagnostic implications for physical and mental health conditions that disrupt mood and limit activity.

Genomics Research of Lifetime Depression in the Netherlands: The BIObanks Netherlands Internet Collaboration (BIONIC) Project.

In this cohort profile article we describe the lifetime major depressive disorder (MDD) database that has been established as part of the BIObanks Netherlands Internet Collaboration (BIONIC). Across the Netherlands we collected data on Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) lifetime MDD diagnosis in 132,850 Dutch individuals. Currently, N = 66,684 of these also have genomewide single nucleotide polymorphism (SNP) data. We initiated this project because the complex genetic basis of MDD requires large population-wide studies with uniform in-depth phenotyping. For standardized phenotyping we developed the LIDAS (LIfetime Depression Assessment Survey), which then was used to measure MDD in 11 Dutch cohorts. Data from these cohorts were combined with diagnostic interview depression data from 5 clinical cohorts to create a dataset of N = 29,650 lifetime MDD cases (22%) meeting DSM-5 criteria and 94,300 screened controls. In addition, genomewide genotype data from the cohorts were assembled into a genomewide association study (GWAS) dataset of N = 66,684 Dutch individuals (25.3% cases). Phenotype data include DSM-5-based MDD diagnoses, sociodemographic variables, information on lifestyle and BMI, characteristics of depressive symptoms and episodes, and psychiatric diagnosis and treatment history. We describe the establishment and harmonization of the BIONIC phenotype and GWAS datasets and provide an overview of the available information and sample characteristics. Our next step is the GWAS of lifetime MDD in the Netherlands, with future plans including fine-grained genetic analyses of depression characteristics, international collaborations and multi-omics studies.

Lifetime history of major depressive disorder is associated with decreased reward learning: Evidence from a novel online version of the probabilistic reward task

BackgroundThe Probabilistic Reward Task (PRT) is a signal detection task that assesses reward learning. In laboratory versions of the task, individuals with current or past major depressive disorder (MDD) were characterized by reduced response bias towards a more frequently rewarded stimuli, compared to controls. Our main goal was to develop and validate a novel online version of the PRT, and, in exploratory analyses, evaluate whether lifetime history of depression was associated with blunted reward learning. Methods429 participants recruited via CloudResearch completed questionnaires assessing psychiatric history and an online PRT featuring visually appealing stimuli. 108 participants reported either current or past diagnosis of MDD (lifetime MDD group), and were compared to 321 without lifetime MDD. ResultsParticipants showed overall increase in response bias, validating the online PRT. Females with lifetime MDD (N = 43), compared to females without prior history of MDD (N = 173), exhibited blunted response bias towards the more frequently rewarded stimulus (i.e., reduced reward learning). LimitationsParticipants did not undergo a structured clinical interview, thus we cannot confirm whether they met full diagnostic criteria for depression. ConclusionsThe online PRT yielded similar psychometric properties as laboratory versions of the task. In exploratory analyses, females with lifetime MDD showed a lower propensity to modulate behavior as a function of rewards, which might contribute to heightened vulnerability for developing MDD in females. Future studies should consider social, cultural, and neurobiological factors contributing to sex differences in reward responsiveness and how factors may relate to disease prognosis and treatment outcomes.

A Systematic Evaluation of Machine Learning–Based Biomarkers for Major Depressive Disorder

Biological psychiatry aims to understand mental disorders in terms of altered neurobiological pathways. However, for one of the most prevalent and disabling mental disorders, major depressive disorder (MDD), no informative biomarkers have been identified. To evaluate whether machine learning (ML) can identify a multivariate biomarker for MDD. This study used data from the Marburg-Münster Affective Disorders Cohort Study, a case-control clinical neuroimaging study. Patients with acute or lifetime MDD and healthy controls aged 18 to 65 years were recruited from primary care and the general population in Münster and Marburg, Germany, from September 11, 2014, to September 26, 2018. The Münster Neuroimaging Cohort (MNC) was used as an independent partial replication sample. Data were analyzed from April 2022 to June 2023. Patients with MDD and healthy controls. Diagnostic classification accuracy was quantified on an individual level using an extensive ML-based multivariate approach across a comprehensive range of neuroimaging modalities, including structural and functional magnetic resonance imaging and diffusion tensor imaging as well as a polygenic risk score for depression. Of 1801 included participants, 1162 (64.5%) were female, and the mean (SD) age was 36.1 (13.1) years. There were a total of 856 patients with MDD (47.5%) and 945 healthy controls (52.5%). The MNC replication sample included 1198 individuals (362 with MDD [30.1%] and 836 healthy controls [69.9%]). Training and testing a total of 4 million ML models, mean (SD) accuracies for diagnostic classification ranged between 48.1% (3.6%) and 62.0% (4.8%). Integrating neuroimaging modalities and stratifying individuals based on age, sex, treatment, or remission status does not enhance model performance. Findings were replicated within study sites and also observed in structural magnetic resonance imaging within MNC. Under simulated conditions of perfect reliability, performance did not significantly improve. Analyzing model errors suggests that symptom severity could be a potential focus for identifying MDD subgroups. Despite the improved predictive capability of multivariate compared with univariate neuroimaging markers, no informative individual-level MDD biomarker-even under extensive ML optimization in a large sample of diagnosed patients-could be identified.

Serum Levels of the Steroid Hormone Dehydroepiandrosterone Are Associated with Psychological Trauma and Lymphocyte Telomere Integrity in Women Suffering from Depression.

Emerging studies highlight the telomere system as an aging mechanism underlying the association between exposure to psychological trauma and the development of a wide range of physical and mental disorders, including major depressive disorder (MDD). Here, we investigated associations of circulating levels of the steroid hormone dehydroepiandrosterone (DHEA) with immune cell telomere length (TL) in the context of lifetime trauma exposure and MDD. Lifetime traumatic events (trauma load) were assessed using the Essener Trauma Inventory in n = 22 postmenopausal female inpatients with MDD and n = 22 non-depressed controls. All women completed the Beck's Depression Inventory II to assess the severity of current depressive symptoms. DHEA concentration in serum was measured by immunoassay, and TL was quantified in kilobase units using quantitative fluorescent in situ hybridization in total peripheral blood mononuclear cells (PBMC) and in selected T-cell subpopulations isolated by FACS separation. Higher trauma load was significantly associated with lower DHEA concentration, which in turn was linked to more depression-related fatigue. Furthermore, DHEA concentration was positively and significantly associated with TL in memory CD4+ T cells as well as in naïve and memory CD8+ T cells, but not in naïve CD4+ T cells and total PBMC. Mediational analysis suggested that DHEA concentration is a mediator in the relationship between trauma load and memory CD8+ T-cell TL. The current findings suggest a potential role of DHEA as a biological resilience factor that may exert beneficial effects on telomere integrity, especially in conditions related to distress.

Substance Use Disorder and Suicidal Ideation in Rural Maryland

Background Rural areas in the United States have been disproportionately burdened with high rates of substance use, mental health challenges, chronic stress, and suicide behaviors. Factors such as a lack of mental health services, decreased accessibility to public health resources, and social isolation contribute to these disparities. The current study explores risk factors to suicidal ideation, using emergency room discharge data from Maryland. Methods The current study used data from the Healthcare Cost and Utilization Project (HCUP) State Emergency Department Databases (SEDD) from the State of Maryland. Logistic regression was used to assess the association between ICD-10 coded opioid use disorder, alcohol use disorder, cannabis use disorder, major depressive disorder, and the outcome variable of suicidal ideation discharge. We controlled for income, race, age, and gender. Results Lifetime major depressive disorder diagnosis (odds ration [OR] = 79.30; 95% confidence interval [CI] 51.91-121.15), alcohol use disorder (OR = 6.87; 95% CI 4.97-9.51), opioid use disorder (OR = 5.39; 95% CI 3.63-7.99), and cannabis use disorder (OR = 2.67; 95% CI 1.37-5.18) were all positively associated with suicidal ideation. Conclusions The study highlights the strong link between prior substance use disorder, depression, and suicidal ideation visit to the emergency room, indicating the need for prevention and intervention, particularly among those in rural areas where the burden of suicidal ideation and chronic stress are high. As health disparities between rural and urban areas further widened during the COVID-19 pandemic, there is an urgent need to address these issues.

Preexisting depression and COVID-19: a cohort study on the risk of susceptibility and hospitalization

BackgroundDepression can have negative effects on a person’s physical health. However, the available evidence on the risk of susceptibility to COVID-19 and its adverse outcomes in people with mental disorders, including depression, is limited and inconsistent. Therefore, we investigated the relationship between major depressive disorder (MDD) and the risk of susceptibility to COVID-19 infection and hospitalization. The data used in the study were obtained from the Employees’ Health Cohort Study of Iran (EHCSIR).MethodsWe conducted a cohort study that included 3355 participants who had complete data on major depressive disorder at baseline assessment and two annual telephone follow-ups between January 2020 and March 2022. Trained psychologists used the Persian version of the Composite International Diagnostic Interview (CIDI-2.1) to identify major depressive disorders during the baseline assessment. We applied log binomial regression models to adjust for sociodemographic factors and background health conditions.ResultsWe found that 11.4% of participants had lifetime MDD and 7.3% had MDD in the past 12 months. During the pandemic, 26.1% of participants were infected with COVID-19, and 14.4% of those who were infected were hospitalized. The risk of susceptibility to COVID-19 infection was significantly higher among participants with lifetime MDD than among those without MDD (adjusted risk ratio (ARR) = 1.24, 95% CI: 1.06–1.47). However, lifetime MDD or 12-month MDD was not independently associated with hospitalization among COVID-19 cases.ConclusionsPreexisting major depressive disorder may increase the risk of susceptibility to COVID-19.

Sex-dependent association of DNA methylation of HPA axis-related gene FKBP5 with obsessive-compulsive disorder

AimsAlthough hypothalamic-pituitary-adrenal (HPA) axis dysregulation in obsessive-compulsive disorder (OCD) has been reported, epigenetic changes in HPA axis-related genes have not been well studied in OCD. The present study investigated whether the epigenetic regulation of FK506-binding protein 51 gene (FKBP5) intron 7 is associated with OCD status in each sex. In addition, relationships among the DNA methylation levels of FKBP5 intron 7, OCD status and early-life trauma were explored. MethodsA total of 267 patients with OCD and 201 controls aged between 18 and 40 years were recruited. Demographic and clinical assessment, FKBP5 rs1360780 genotyping, and pyrosequencing of FKBP5 intron 7 were conducted. DNA was extracted from peripheral blood leucocytes. First, multivariate analysis of covariance for differential DNA methylation levels between OCD patients and controls was conducted with adjustment for FKBP5 rs1360780 genotype, early-life trauma, depressive symptoms, and age as covariates in each sex. Next, path analysis was conducted to determine the mediation effects of DNA methylation levels of FKBP5 between early-life trauma and OCD status. In addition, sensitivity analyses for medication and lifetime major depression were also performed. ResultsDNA methylation at the FKBP5 intron 7 CpG site was significantly lower in men with OCD, compared to controls (mean difference −1.33%, 95% CI −2.11 to −0.55, p < 0.001). The results remained significant for drug naïve or free subjects (mean difference −1.27%, 95% CI −2.18 to −0.37, p = 0.006, in men) and for subjects without lifetime major depressive disorder (mean difference −1.60%, 95% CI −2.54 to −0.66, p < 0.001, in men). The mediation effect of DNA methylation levels was not significant between early-life trauma and OCD status. ConclusionThese findings suggest that epigenetic factors of HPA axis-related gene FKBP5 may play a role in the pathogenesis of OCD. Further studies are needed to determine how altered DNA methylation of FKBP5 intron 7 and HPA axis function are involved in OCD.

Supportive relationships in childhood: Does it have a long Reach into health and depression outcomes for immigrants from Latin America?

This study examines how social support during childhood and adolescence is associated with self-rated good health and the incidence of depression among Latin American immigrants in the U.S. We focus on those who immigrated under age 18 (childhood arrivals) to understand the interplay between early social support and adult health outcomes. Data are from the 2012–2013 iteration of the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC-III), which included a sample of 3441 immigrant respondents born in Latin America. Multivariable binomial logistic regression analyses indicated that childhood and interpersonal support in adulthood were negatively associated with lifetime major depressive disorder (LMDD) episodes. These associations differed between childhood arrival and adult arrival immigration samples. Findings from this study highlight the role that social support in critical developmental periods has on immigrant health and depression outcomes. Continued and more nuanced investigations are warranted to examine social resources across lifespans and their roles in mitigating adverse health outcomes among immigrants from Latin America.

Depression and Reciprocal Language Style Matching in Text Messages

This study investigates whether interpersonal coordination of language style in written text message communication relates to past-year depressive symptoms and lifetime major depressive disorder (MDD) in young adults. Consistent with application of Joiner's integrative interpersonal framework to interpersonal coordination, we hypothesized that students with more experiences of depression, and their conversation partners, would engage in less interpersonal coordination in text messages (indexed by reciprocal language style matching of function words; rLSM). College students at a large southeastern university ( N = 263) contributed two weeks of text messages in 2014−2015, alongside a mental health survey. Texts were filtered to dyads that used formal English (207,942 talk turns), accommodating limitations of LSM measurement. Structural equation models showed that students with more past-year depressive symptoms and lifetime MDD coordinated more (opposite the hypothesized direction of effect). Implications for interpersonal processes in depression and measurement of rLSM in text messages are discussed.

Change in cardiovascular health among adults with current or past major depressive disorder enrolled in intensive smoking cessation treatment

BackgroundElevated depressive symptoms and cigarette smoking are independently associated with poorer cardiovascular health (CVH), but it is unknown whether their treatment can synergistically improve CVH. We sought to characterize CVH of adults with comorbid depression and smoking and examine changes in CVH associated with changes in smoking and depression. MethodsParticipants (N = 300, 55 % women) were adult smokers (≥ 1 cigarette/day) with lifetime major depressive disorder enrolled in a 12-week intervention trial targeting depression and smoking. Multiple linear regression examined prospective associations between changes in depression (Beck Depression Inventory-II), smoking (past 24-hour cigarettes or smoking abstinence), and modified CVH score (per American Heart Association, excluding smoking: diet, physical activity, body mass index, blood glucose, cholesterol, blood pressure). ResultsBaseline mean CVH score was 5.87/12 points (SD = 2.13). No participants met “ideal” on all CVH components (blood glucose: 48 %, cholesterol: 46 %, physical activity: 38 %, body mass index: 24 %, blood pressure: 22 %, diet: 3 %). CVH scores did not change from baseline to end-of-treatment (M = 0.18 points, SD = 1.36, p = .177), nor did change in depression × smoking predict change in CVH (p = .978). However, greater reductions in depression were significantly associated with greater improvements in CVH (β = −0.04, SE = 0.01, p = .015). LimitationsThis study was limited by a short follow-up period, missing blood glucose and cholesterol data, and treatment-seeking smokers. ConclusionsAdults with comorbid depression and smoking had poor CVH. Although integrated treatment for depression and smoking improved both conditions, only reductions in depression were associated with improvements in CVH. These findings have implications for integrating psychosocial treatment into CVH promotion efforts. RegistrationNCT02378714 (clinicaltrials.gov).

Interplay of Metabolome and Gut Microbiome in Individuals With Major Depressive Disorder vs Control Individuals

Metabolomics reflect the net effect of genetic and environmental influences and thus provide a comprehensive approach to evaluating the pathogenesis of complex diseases, such as depression. To identify the metabolic signatures of major depressive disorder (MDD), elucidate the direction of associations using mendelian randomization, and evaluate the interplay of the human gut microbiome and metabolome in the development of MDD. This cohort study used data from participants in the UK Biobank cohort (n = 500 000; aged 37 to 73 years; recruited from 2006 to 2010) whose blood was profiled for metabolomics. Replication was sought in the PREDICT and BBMRI-NL studies. Publicly available summary statistics from a 2019 genome-wide association study of depression were used for the mendelian randomization (individuals with MDD = 59 851; control individuals = 113 154). Summary statistics for the metabolites were obtained from OpenGWAS in MRbase (n = 118 000). To evaluate the interplay of the metabolome and the gut microbiome in the pathogenesis of depression, metabolic signatures of the gut microbiome were obtained from a 2019 study performed in Dutch cohorts. Data were analyzed from March to December 2021. Outcomes were lifetime and recurrent MDD, with 249 metabolites profiled with nuclear magnetic resonance spectroscopy with the Nightingale platform. The study included 6811 individuals with lifetime MDD compared with 51 446 control individuals and 4370 individuals with recurrent MDD compared with 62 508 control individuals. Individuals with lifetime MDD were younger (median [IQR] age, 56 [49-62] years vs 58 [51-64] years) and more often female (4447 [65%] vs 2364 [35%]) than control individuals. Metabolic signatures of MDD consisted of 124 metabolites spanning the energy and lipid metabolism pathways. Novel findings included 49 metabolites, including those involved in the tricarboxylic acid cycle (ie, citrate and pyruvate). Citrate was significantly decreased (β [SE], -0.07 [0.02]; FDR = 4 × 10-04) and pyruvate was significantly increased (β [SE], 0.04 [0.02]; FDR = 0.02) in individuals with MDD. Changes observed in these metabolites, particularly lipoproteins, were consistent with the differential composition of gut microbiota belonging to the order Clostridiales and the phyla Proteobacteria/Pseudomonadota and Bacteroidetes/Bacteroidota. Mendelian randomization suggested that fatty acids and intermediate and very large density lipoproteins changed in association with the disease process but high-density lipoproteins and the metabolites in the tricarboxylic acid cycle did not. The study findings showed that energy metabolism was disturbed in individuals with MDD and that the interplay of the gut microbiome and blood metabolome may play a role in lipid metabolism in individuals with MDD.

Signatures of HIV and Major Depressive Disorder in the Plasma Microbiome.

Inter-individual differences in the gut microbiome are linked to alterations in inflammation and blood-brain barrier permeability, which may increase the risk of depression in people with HIV (PWH). The microbiome profile of blood, which is considered by many to be typically sterile, remains largely unexplored. We aimed to characterize the blood plasma microbiome composition and assess its association with major depressive disorder (MDD) in PWH and people without HIV (PWoH). In this cross-sectional, observational cohort, we used shallow-shotgun metagenomic sequencing to characterize the plasma microbiome of 151 participants (84 PWH and 67 PWoH), all of whom underwent a comprehensive neuropsychiatric assessment. The microbial composition did not differ between PWH and PWoH or between participants with MDD and those without it. Using the songbird model, we computed the log ratio of the highest and lowest 30% of the ranked classes associated with HIV and MDD. We found that HIV infection and lifetime MDD were enriched in a set of differentially abundant inflammatory classes, such as Flavobacteria and Nitrospira. Our results suggest that the circulating plasma microbiome may increase the risk of MDD related to dysbiosis-induced inflammation in PWH. If confirmed, these findings may indicate new biological mechanisms that could be targeted to improve treatment of MDD in PWH.

The association between child maltreatment and mental disorders in the Australian Child Maltreatment Study.

To examine the associations between experiences of child maltreatment and mental disorders in the Australian population. Population-representative survey conducted by computer-assisted telephone interviewing. Australian residents aged 16 years and older. Mental disorder diagnoses of lifetime major depressive disorder, current alcohol use disorder (mild, moderate and severe), current generalised anxiety disorder and current post-traumatic stress disorder. More than one in three Australians (3606/8503 surveyed participants; 38.0%; 95% CI, 36.7-39.3%) met the diagnostic criteria for a mental disorder. The prevalence of mental disorders in non-maltreated participants was 21.6% (95% CI, 19.9-23.3%; n=851). This increased to 36.2% (95% CI, 33.5-38.9%; n=764) for those who experienced a single type of maltreatment and 54.8% (95% CI, 52.6-56.9%; n=1991) for participants who experienced multi-type maltreatment. Compared with non-maltreated Australians, maltreated participants had about three times the odds of any mental disorder (odds ratio [OR], 2.82; 95% CI, 2.47-3.22), generalised anxiety disorder (OR, 3.14; 95% CI, 2.48-3.97), major depressive disorder (OR, 3.19; 95% CI, 2.68-3.80) and severe alcohol use disorder (OR, 2.62; 95% CI, 1.83-3.76), and almost five times the odds of post-traumatic stress disorder (OR, 4.60; 95% CI, 3.00-7.07). Associations between experiences of child maltreatment and mental disorders were strongest for sexual abuse, emotional abuse and multi-type maltreatment. The strength of the associations did not differ by gender. Adjustment for childhood and current financial hardship and for current socio-economic status did not significantly attenuate the associations. Mental disorders are significantly more likely to occur in individuals who experience child maltreatment, particularly multi-type maltreatment. Prevention of child maltreatment provides an opportunity to substantially reduce the prevalence of mental illness and improve the health of the Australian population.