Major Depressive Disorder Cases Research Articles

Global, regional, and national temporal trend in burden of major depressive disorder from 1990 to 2019: An analysis of the global burden of disease study

Major depressive disorder (MDD) is one of the leading causes of disability worldwide. Comprehensive description of the global burden of MDD and its attributable risk factors is essential for policymaking but currently lacking. In this study, we aim to estimate the burden of MDD in terms of incidence, prevalence, and years lived with disability (YLDs), along with its attributable risk factors at global, regional, and rational level between 1990 and 2019, using data from the Global Burden of Diseases, Injuries, and Risk Factors Study 2019. Data analysis was completed on July 1, 2023. In 2019, 274.80 million (95 % uncertainty interval [UI], 241.28 to 312.77) new cases of MDD were identified globally, with an increase of 59 % from 1990. A total of 37.20 million (25.65 to 51.22) YLDs were attributable to MDD, accounting for the largest proportion of mental disorder YLDs (29.7 %). Countries in the low sociodemographic index quantile exhibited the highest age-standardized incidence rate of MDD, with Uganda (7836.2, per 100,000 person-years, 6713.7 to 9181.1) and Palestine (7687.7, 6546.1 to 9023.9) reporting the highest rates among them. The United States had the highest increase in age-standardized rates, with an average annual percent change of 0.99. Females had 1.6 times higher age-standardised rates than males, ranging from 1.2 (Oceania) to 2.2 (tropical Latin America) times across 21 regions. Globally, the proportions of YLDs due to MDD attributable to bullying victimization, childhood sexual abuse, and intimate partner violence were 4.86 %, 5.46 %, and 8.43 % in 2019, respectively. The heavy burden of MDD serves as a stark reminder that a coordinated response from governments and health communities is urgently needed to scale up mental health services and implement effective interventions, particularly in low-income countries.

The prevalence of major depressive disorder in people with HIV: Results from the All of Us Research Program.

The All of Us (AoU) Research Program is a national-scale effort to build a dataset to help transform the future of health research by equipping researchers with comprehensive health data from diverse populations, especially those underrepresented in biomedical research. Our objectives were to evaluate the burden of HIV and major depressive disorder (MDD) in underrepresented groups and the frequency of the HIV/MDD comorbidity. We conducted a cross-sectional analysis combining collected survey and electronic health record (EHR) data. We ascertained HIV and MDD cases using Observational Medical Outcomes Partnership codes. We used multivariable logistic regression to obtain the odds ratio of HIV in AoU participants and MDD in AoU participants with HIV. The latest AoU data release includes 412 211 participants: 254 700 have at least one medical condition concept in their EHR, of whom 5193 (1.3%) had HIV, and 2238 (43%) of those with HIV had a diagnosis of MDD. Black AoU participants had approximately 4.58 times the odds of having an HIV diagnosis compared with the combined odds of all other racial groups. AoU participants with HIV were more likely to have MDD (p = 0.001) than were participants without HIV. Among AoU participants, Black individuals have a disproportionately high burden of HIV, pointing to underlying factors such as social determinants of health, limited access to healthcare or prevention resources, and potential systemic biases that contribute to these differences. In addition, HIV is a risk factor for mental health issues like MDD. Further data collection from people with HIV will elucidate contributing factors and the need for interventions.

Valuing the health benefits of nature-based recreational physical activity in England

Physical activity (PA) reduces the risk of several non-communicable diseases (NCDs). Natural environments support recreational PA. Using data including a representative cross-sectional survey of the English population, we estimated the annual value of nature-based PA conducted in England in 2019 in terms of avoided healthcare and societal costs of disease.Population-representative data from the Monitor of Engagement with the Natural Environment (MENE) survey (n = 47,580; representing 44,386,756) were used to estimate the weekly volume of nature-based recreational PA by adults in England in 2019. We used epidemiological dose–response data to calculate incident cases of six NCDs (ischaemic heart disease (IHD), ischaemic stroke (IS), type 2 diabetes (T2D), colon cancer (CC), breast cancer (BC) and major depressive disorder (MDD)) prevented through nature-based PA, and estimated associated savings using published costs of healthcare, informal care and productivity losses. We investigated additional savings resulting from hypothetical increases in: (a) visitor PA and (b) visitor numbers.In 2019, 22million adults > 16 years of age in England visited natural environments at least weekly. At reported volumes of nature-based PA, we estimated that 550 cases of IHD, 168 cases of IS, 1,410 cases of T2D, 41 cases of CC, 37 cases of BC and 10,552 cases of MDD were prevented, creating annual savings of £108.7million (95 % uncertainty interval: £70.3million; £150.3million).Nature-based recreational PA in England results in reduced burden of disease and considerable annual savings through prevention of priority NCDs. Strategies that increase nature-based PA could lead to further reductions in the societal burden of NCDs.

A comprehensive hierarchical comparison of structural connectomes in Major Depressive Disorder cases v. controls in two large population samples.

The brain can be represented as a network, with nodes as brain regions and edges as region-to-region connections. Nodes with the most connections (hubs) are central to efficient brain function. Current findings on structural differences in Major Depressive Disorder (MDD) identified using network approaches remain inconsistent, potentially due to small sample sizes. It is still uncertain at what level of the connectome hierarchy differences may exist, and whether they are concentrated in hubs, disrupting fundamental brain connectivity. We utilized two large cohorts, UK Biobank (UKB, N = 5104) and Generation Scotland (GS, N = 725), to investigate MDD case-control differences in brain network properties. Network analysis was done across four hierarchical levels: (1) global, (2) tier (nodes grouped into four tiers based on degree) and rich club (between-hub connections), (3) nodal, and (4) connection. In UKB, reductions in network efficiency were observed in MDD cases globally (d = -0.076, pFDR = 0.033), across all tiers (d = -0.069 to -0.079, pFDR = 0.020), and in hubs (d = -0.080 to -0.113, pFDR = 0.013-0.035). No differences in rich club organization and region-to-region connections were identified. The effect sizes and direction for these associations were generally consistent in GS, albeit not significant in our lower-N replication sample. Our results suggest that the brain's fundamental rich club structure is similar in MDD cases and controls, but subtle topological differences exist across the brain. Consistent with recent large-scale neuroimaging findings, our findings offer a connectomic perspective on a similar scale and support the idea that minimal differences exist between MDD cases and controls.

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.

Major depressive disorder and irritable bowel syndrome risk: A Mendelian randomization study.

Previous studies have revealed a connection between major depressive disorder (MDD) and irritable bowel syndrome (IBS), but it remains obscure if the two diseases are related causally. Mendelian randomization was utilized in this investigation to ascertain whether MDD contributed to the emergence of IBS. To examine possible connections between MDD and IBS, we used two-sample Mendelian randomization (MR) utilizing summary data from genome-wide association studies (GWAS). The Psychiatric Genomics Consortium (PGC) provided information on genetic associations with MDD (cases: 135,458; controls: 344,901). The Medical Research Council Integrative Epidemiology Unit (MRC-IEU) provided information on genetic associations with IBS (cases:10,939; controls:451,994). Inverse Variance Weighted (main analyses), MR-Egger regression, Weighted mode, and Weighted Median were the four MR methods used in this investigation. In addition, we also performed multiplicity and heterogeneity analyses to eliminate possible biases. In the standard Inverse Variance Weighting (IVW) method, an increased risk of IBS was linked to a genetic susceptibility to MDD (OR: 1.01; 95% CI: 1.006 to 1.014, p = 1.02E-07). In addition, neither significant heterogeneity (IVW Q = 24.80, p = 0.73) nor horizontal pleiotropy (MR Egger p = 0.17; MRPRESSO p = 0.54) were detected in this MR analysis. The bidirectional analysis, however, did not show a genetic link between IBD and MDD (p steiger <0.01). A direct causal relationship between MDD and IBS was revealed by Mendelian randomization study, which contributes to the effective clinical management of both diseases.

Interventionism and Intelligibility: Why Depression Is Not (Always) a Brain Disease.

Major depressive disorder (MDD) is a serious condition with a large disease burden. It is often claimed that MDD is a "brain disease." What would it mean for MDD to be a brain disease? I argue that the best interpretation of this claim is as offering a substantive empirical hypothesis about the causes of the syndrome of depression. This syndrome-causal conception of disease, combined with the idea that MDD is a disease of the brain, commits the brain disease conception of MDD to the claim that brain dysfunction causes the symptoms of MDD. I argue that this consequence of the brain disease conception of MDD is false. It incorrectly rules out genuine instances of content-sensitive causation between adverse conditions in the world and the characteristic symptoms of MDD. Empirical evidence shows that the major causes of depression are genuinely psychological causes of the symptoms of MDD. This rules out, in many cases, the "brute" causation required by the brain disease conception. The existence of cases of MDD with non-brute causes supports the reinstatement of the old nosological distinction between endogenous and exogenous depression.

Polygenic Analyses Show Important Differences Between Major Depressive Disorder Symptoms Measured Using Various Instruments

BackgroundSymptoms of major depressive disorder (MDD) are commonly assessed using self-rating instruments like the Patient Health Questionnaire-9 (PHQ-9) (current symptoms) and the Composite International Diagnostic Interview Short-Form (CIDI-SF) (worst-episode symptoms). We performed a systematic comparison between them for their genetic architecture and utility in investigating MDD heterogeneity. MethodsUsing data from the UK Biobank (n = 41,948–109,417), we assessed the single nucleotide polymorphism heritability and genetic correlation (rg) of both sets of MDD symptoms. We further compared their rg with non-MDD traits and used Mendelian randomization to assess whether either set of symptoms has more genetic sharing with non-MDD traits. We also assessed how specific each set of symptoms is to MDD using the metric polygenic risk score pleiotropy. Finally, we used genomic structural equation modeling to identify factors that explain the genetic covariance between each set of symptoms. ResultsCorresponding symptoms reported through the PHQ-9 and CIDI-SF have low to moderate genetic correlations (rg = 0.43–0.87), and this cannot be fully attributed to different severity thresholds or the use of a skip structure in the CIDI-SF. Both Mendelian randomization and polygenic risk score pleiotropy analyses showed that PHQ-9 symptoms are more associated with traits that reflect general dysphoria, whereas the skip structure in the CIDI-SF allows for the identification of heterogeneity among likely MDD cases. Finally, the 2 sets of symptoms showed different factor structures in genomic structural equation modeling, reflective of their genetic differences. ConclusionsMDD symptoms assessed using the PHQ-9 and CIDI-SF are not interchangeable; the former better indexes general dysphoria, while the latter is more informative about within-MDD heterogeneity.

The association of changes in leisure-time physical activity on depressive symptoms during Covid-19 in German adults: A longitudinal study

This longitudinal survey assessed preventive and curative antidepressant effects of at least 75 min/week of leisure-time physical activity (LTPA) at different timepoints of the Covid-19 pandemic. We further investigated if high self-regulation skills were associated with higher odds of initiating or maintaining LTPA during the pandemic. Data was collected online from 4253 participants (age: m = 33.65 years, SD = 0.79; 79 % female) during the first quarantine measures in Germany (T1), as well as 4 weeks (T2), and 8 months (T3) later. We performed linear mixed models with changes (T2-T1, T3-T1) in LTPA and baseline major depressive disorder (MDD) as predictors (main effects and interaction effect) and depressive symptoms (at T2, T3) as the primary outcome. We found significant interaction effects of baseline depression and change in LTPA on depressive symptoms at T2 and T3 (p < 0.001). For probable cases of MDD an increasing LTPA to ≥75 min/week (vs. no change, <75 min/week) was associated with less depressive symptoms at T2 and T3 (p = 0.003, d = 0.28). For absence of depression at baseline, remaining at ≥75 min/week of LTPA was associated with less depressive symptoms at T2 and T3 compared to remaining at <75 min/week (p = 0.006, d = 0.11) or decreasing LTPA to <75 min/week (p = 0.018, d = 0.11). Reporting high self-regulation at T1 was associated with higher odds of performing ≥75 min/week of LTPA at T2/T3 (OR = 1.74, p < 0.001). In general, studies report reduced LTPA during Covid-19. To benefit from the reported preventive and interventional effects, further interventions should focus on improving physical activity related self-regulation to identify and overcome barriers for LTPA.

Polygenic risk scores of lithium response and treatment resistance in major depressive disorder

Treatment response and resistance in major depressive disorder (MDD) are suggested to be heritable. Due to significant challenges in defining treatment-related phenotypes, our understanding of their genetic bases is limited. This study aimed to derive a stringent definition of treatment resistance and to investigate the genetic overlap between treatment response and resistance in MDD. Using electronic medical records on the use of antidepressants and electroconvulsive therapy (ECT) from Swedish registers, we derived the phenotype of treatment-resistant depression (TRD) and non-TRD within ~4500 individuals with MDD in three Swedish cohorts. Considering antidepressants and lithium are first-line treatment and augmentation used for MDD, respectively, we generated polygenic risk scores (PRS) of antidepressants and lithium response for individuals with MDD and evaluated their associations with treatment resistance by comparing TRD with non-TRD. Among 1778 ECT-treated MDD cases, nearly all (94%) used antidepressants before their first ECT and the vast majority had at least one (84%) or two (61%) antidepressants of adequate duration, suggesting these MDD cases receiving ECT were resistant to antidepressants. We did not observe a significant difference in the mean PRS of antidepressant response between TRD and non-TRD; however, we found that TRD cases had a significantly higher PRS of lithium response compared to non-TRD cases (OR = 1.10–1.12 under various definitions). The results support the evidence of heritable components in treatment-related phenotypes and highlight the overall genetic profile of lithium-sensitivity in TRD. This finding further provides a genetic explanation for lithium efficacy in treating TRD.

Individual and Combined Effect of MAO-A/MAO-B Gene Variants and Adverse Childhood Experiences on the Severity of Major Depressive Disorder.

Major depressive disorder (MDD) is a mood disorder with a high prevalence worldwide that causes disability and, in some cases, suicide. Although environmental factors play a crucial role in this disease, other biological factors may predispose individuals to MDD. Genetic and environmental factors influence mental disorders; therefore, a potential combined effect of MAO-A/MAO-B gene variants may be a target for the study of susceptibility to MDD. This study aimed to evaluate the effects of MAO-A and -B gene variants when combined with adverse childhood experiences (ACEs) on the susceptibility and severity of symptoms in MDD. A case-control study was performed, including 345 individuals, 175 MDD cases and 170 controls. Genotyping was performed using real-time PCR with hydrolysis probes. The analysis of the rs1465107 and rs1799836 gene variants of MAO-A and -B, respectively, was performed either alone or in combination with ACEs on the severity of depression, as determined through specific questionnaires, including DSM-IV diagnostic criteria for MDD. According to individual effects, the presence of ACEs, as well as the allele G of the rs1465107 of MAO-A, is associated with a higher severity of depression, more significantly in females. Furthermore, the allele rs1799836 G of MAO-B was associated with the severity of depression, even after being adjusted by gene variants and ACEs (IRR = 1.67, p = 0.01). In males, the allele rs1799836 G of MAO-B was shown to interact with SNP with ACEs (IRR = 1.70, p < 0.001). According to combined effect analyses, the severity of depression was associated with ACEs when combined with either allele rs1465107 of MAO-A or allele rs17993836 of MAO-B, whereas SNP risk association was influenced by gender. The severity of depression is related to either individual or combined effects of temperamental traits and genetic susceptibility of specific genes such as MAO-A and MAO-B.

Genetically predicted circulating levels of cytokines and the risk of depression: a bidirectional Mendelian-randomization study.

Objective: Inflammatory cytokines disturbance is the main result of immune dysregulation, which is widely described in major depressive disorder (MDD). However, the potential causal relationship between these two factors has not been discovered. Therefore, the purpose of this study was to investigate the causal relationship between inflammatory cytokines and MDD risk by using the two-sample Mendelian randomization (MR) analysis. Method: Two genetic instruments obtained from publicly available gene profile data were utilized for the analysis. We obtained the genetic variation data of 41 inflammatory cytokines from genome-wide association studies (GWAS) meta-analysis of 8293 individuals of Finnish descent. The MDD data, including 135,458 MDD cases and 344,901 controls, were obtained from the Psychiatric Genomics Consortium Database. For the Mendelian randomization (MR) estimation, several methods were employed, namely, MR-Egger regression, inverse-variance weighted (IVW), weighted median, and MR-Pleiotropy RESidual Sum and Outlier (MR-PRESSO) methods. Result: A causal relationship was identified between the genetically proxied levels of Interleukin (IL) -18, IL-1β, and Regulated upon activation normal T cell expressed and secreted (RANTES) and the risk of MDD (OR = 0.968, 95%CI = 0.938, 0.998, p = 0.036; OR = 0.875, 95%CI = 0.787, 0.971, p = 0.012; OR = 0.947, 95%CI = 0.902, 0.995, p = 0.03; respectively). However, our Mendelian randomization (MR) estimates provided no causality of MDD on inflammatory cytokines. Conclusion: Our study elucidates the connection between inflammatory cytokines and MDD by using MR analysis, thereby enhancing our comprehension of the potential mechanisms. By identifying these associations, our findings hold substantial implications for the development of more effective treatments aimed at improving patient outcomes. However, further investigation is required to fully comprehend the exact biological mechanisms involved.

Problematic internet use and sleep quality in adolescents with major depressive disorder

ABSTRACT This study aims to compare adolescents newly diagnosed with major depressive disorder (MDD) and healthy controls in terms of problematic internet use (PIU) and sleep quality. The study sample consisted of 50 newly diagnosed MDD patients aged 12–18 years and 50 healthy controls. Schedule for Affective Disorders and Schizophrenia for School-Age Children-Present and Lifetime Version (K-SADS-PL) was administered to all cases by a child psychiatrist and sociodemographic data were collected. Children’s Depression Inventory (CDI), Pittsburgh Sleep Quality Index (PSQI), and Internet Addiction Test (IAT) were administered to all participants. Data of the MDD and control groups were compared using Student’s t-test or Mann-Whitney U test and the total scores of the IAT (z = −6.23, p < 0.001) and PSQI (t =–11.42, p < 0.001) scales were found to be significantly higher in MDD cases compared to the control group. The results of analysis of covariance demonstrated that there was a significant positive correlation between CDI and IAT, as well as CDI and PSQI total scores in patients with MDD. While no correlation was observed between the total scores of the IAT and PSQI scales in the MDD group, a significant positive correlation was found between the total scores of the IAT and PSQI scales in the healthy control group. Furthermore, there was a significant difference between the PSQI habitual sleep efficiency subscale score and the IAT total score (r = 0.36, p = 0.009), and the IAT responsibility (r = 0.34, p = 0.015), relationship (r = 0.36, p = 0.01), and mood subscale scores (r = 0.30, p = 0.03). A significant positive correlation was also found between the IAT duration subscale score and PSQI sleep disorder subscale score (r = 0.35, p = 0.013). In addition, binary logistic regression analysis showed that PSQI total score (B = 0.79, p < 0.001) and IAT total scores (B = 0.08, p = 0.001) could be significant predictors of MDD. The findings of this study indicate that the prevalence of PIU and poor sleep quality is higher in adolescents with newly diagnosed MDD compared to healthy controls. The results of our study indicated that the severity of depression, PIU, and sleep quality were significantly correlated in adolescents with newly diagnosed MDD, while PIU and sleep quality were correlated in adolescents without any psychiatric disorders. In addition, this study suggests that poor sleep quality and PIU may be risk factors for MDD.

Circulating T-cell subsets discrepancy between bipolar disorderand major depressive disorder during mood episodes: A naturalistic, retrospective study of 1015 cases.

We aimed to investigate whether peripheral T-cell subsets could be a biomarker to distinguish major depressive disorder (MDD) and bipolar disorder (BD). Medical records of hospitalized patients in the Department of Psychiatry, the First Affiliated Hospital, Zhejiang University School of Medicine, from January 2015 to September 2020 with a discharge diagnosis of MDD or BD were reviewed. Patients who underwent peripheral blood examination of T-cell subtype proportions, including CD3+, CD4+, CD8+ T-cell, and natural killer (NK) cells, were enrolled. The Chi-square test, t-test, or one-way analysis of variance were used to analyze group differences. Demographic profiles and T-cell data were used to construct a random forest classifier-based diagnostic model. Totally, 98 cases of BD mania, 459 cases of BD depression (BD-D), and 458 cases of MDD were included. There were significant differences in the proportions of CD3+, CD4+, CD8+ T-cell, and NK cells among the three groups. Compared with MDD, the BD-D group showed higher CD8+ but lower CD4+ T-cell and a significantly lower ratio of CD4+ and CD8+ proportions. The random forest model achieved an area under the curve of 0.77 (95% confidence interval: 0.71-0.83) to distinguish BD-D from MDD patients. These findings imply that BD and MDD patients may harbor different T-cell inflammatory patterns, which could be a potential diagnostic biomarker for mood disorders.

Validation of the Strengths and Difficulties Questionnaire (SDQ) emotional subscale in assessing depression and anxiety across development.

Emotional disorders are common in childhood, and their prevalence sharply increases during adolescence. The Strengths and Difficulties Questionnaire (SDQ) is widely used for screening emotional and behavioural difficulties in children and young people, but little is known about the accuracy of the emotional subscale (SDQ-E) in detecting emotional disorders, and whether this changes over development. Such knowledge is important in determining whether symptom changes across age are due to developmental or measurement differences. This study assessed the validity of the SDQ-E and two individual items (low mood and general worry) in differentiating between cases and non-cases of Major Depressive Disorder (MDD), Generalised Anxiety Disorder (GAD), and other anxiety disorders across ages 7, 10, 13, 15, and 25 years in a UK population cohort. Analyses showed moderate accuracy of the subscale in discriminating cases of MDD (AUC = 0.67-0.85), and high accuracy for discriminating cases of GAD (AUC = 0.80-0.93) and any anxiety disorder (AUC = 0.74-0.83) compared to non-cases. The SDQ-E performed well across ages and sex, and generally performed better than the two individual items. Together our findings validate the SDQ-E as a screen for emotional disorders during childhood, adolescence, and early adulthood, and as a tool for longitudinal research on depression and anxiety disorders.

In vivo analyses reveal hippocampal subfield volume reductions in adolescents with schizophrenia, but not with major depressive disorder

BackgroundAdult studies have reported atypicalities in the hippocampus and subfields in patients with schizophrenia (SCZ) and major depressive disorder (MDD). Both affective and psychotic disorders typically onset in adolescence, when human brain develops rapidly and shows increased susceptibility to adverse environments. However, few in vivo studies have investigated whether hippocampus subfield abnormalities occur in adolescence and whether they differ between SCZ and MDD cases. MethodsWe recruited 150 adolescents (49 SCZ patients, 67 MDD patients, and 34 healthy controls) and obtained their structural images. We used FreeSurfer to automatically segment hippocampus into 12 subfields and analyzed subfield volumetric differences between groups by analysis of covariance, covarying for age, sex, and intracranial volume. Composite measures by summing subfield volumes were further compared across groups and analyzed in relation to clinical characteristic. ResultsSCZ adolescents showed significant volume reductions in subfields of CA1, molecular layer, subiculum, parasubiculum, dentate gyrus and CA4 than healthy controls, and almost significant reductions, as compared to the MDD group, in left molecular layer, dentate gyrus, CA2/3 and CA4. Composite analyses showed smaller volumes in SCZ group than in healthy controls in all bilateral composite measures, and reduced volumes in comparison to MDD group in all left composite measures only. ConclusionsSCZ adolescents exhibited both hippocampal subfield and composite volumes reduction, and also showed greater magnitude of deviance than those diagnosed with MDD, particularly in core CA regions. These results indicate a hippocampal disease process, suggesting a potential intervention marker of early psychotic patients and risk youths.

A multivariate blood metabolite algorithm stably predicts risk and resilience to major depressive disorder in the general population.

Socioeconomic pressures, sex, and physical health status strongly influence the development of major depressive disorder (MDD) and mask other contributing factors in small cohorts. Resilient individuals overcome adversity without the onset of psychological symptoms, but resilience, as for susceptibility, has a complex and multifaceted molecular basis. The scale and depth of the UK Biobank affords an opportunity to identify resilience biomarkers in rigorously matched, at-risk individuals. Here, we evaluated whether blood metabolites could prospectively classify and indicate a biological basis for susceptibility or resilience to MDD. Using the UK Biobank, we employed random forests, a supervised, interpretable machine learning statistical method to determine the relative importance of sociodemographic, psychosocial, anthropometric, and physiological factors that govern the risk of prospective MDD onset (total n=15,710). We then used propensity scores to rigorously match individuals with a history of MDD (n=491) against a resilient subset of individuals without an MDD diagnosis (retrospectively or during follow-up; n=491) using an array of key social, demographic, and disease-associated drivers of depression risk. 381 blood metabolites and clinical chemistry variables and 4 urine metabolites were integrated to generate a multivariate random forest-based algorithm using 10-fold cross-validation to predict prospective MDD risk and resilience. In unmatched individuals, a first case of MDD, with a median time-to-diagnosis of 72 years, can be predicted using random forest classification probabilities with an area under the receiver operator characteristic curve (ROC AUC) of 0.89. Prospective resilience/susceptibility to MDD was then predicted with a ROC AUC of 0.72 (x˜= 3.2 years follow-up) and 0.68 (x˜= 7.2 years follow-up). Increased pyruvate was identified as a key biomarker of resilience to MDD and was validated retrospectively in the TwinsUK cohort. Blood metabolites prospectively associate with substantially reduced MDD risk. Therapeutic targeting of these metabolites may provide a framework for MDD risk stratification and reduction. New York Academy of Sciences' Interstellar Programme Award; Novo Fonden; Lincoln Kingsgate award; Clarendon Fund; Newton-Abraham studentship (University of Oxford). The funders had no role in the development of the present study.

Major depressive disorder plays a vital role in the pathway from gastroesophageal reflux disease to chronic obstructive pulmonary disease: a Mendelian randomization study.

Background: Observational studies have shown a bidirectional association between chronic obstructive pulmonary disease (COPD) and gastroesophageal reflux disease (GERD), but it is not clear whether this association is causal. In our previous study, we found that depression was a hot topic of research in the association between COPD and GERD. Is major depressive disorder (MDD) a mediator of the association between COPD and GERD? Here, we evaluated the causal association between COPD, MDD, and GERD using Mendelian randomization (MR) study. Methods: Based on the FinnGen, United Kingdom Biobank, and Psychiatric Genomics Consortium (PGC) databases, we obtained genome-wide association study (GWAS) summary statistics for the three phenotypes from 315,123 European participants (22,867 GERD cases and 292,256 controls), 462,933 European participants (1,605 COPD cases and 461,328 controls), and 173,005 European participants (59,851 MDD cases and 113,154 controls), respectively. To obtain more instrumental variables to reduce bias, we extracted relevant single-nucleotide polymorphisms (SNPs) for the three phenotypes from published meta-analysis studies. Bidirectional MR and expression quantitative trait loci (eQTL)-MR were performed using the inverse variance weighting method to assess the causal association between GERD, MDD, and COPD. Results: There was no evidence of a causal effect between GERD and COPD in the bidirectional MR analysis [forward MR for GERD on COPD: odds ratios (OR) = 1.001, p = 0.270; reverse MR for COPD on GERD: OR = 1.021, p = 0.303]. The causal effect between GERD and MDD appeared to be bidirectional (forward MR for GERD on MDD: OR = 1.309, p = 0.006; reverse MR for MDD on GERD: OR = 1.530, p < 0.001), while the causal effect between MDD and COPD was unidirectional (forward MR for MDD on COPD: OR = 1.004, p < 0.001; reverse MR for COPD on MDD: OR = 1.002, p = 0.925). MDD mediated the effect of GERD on COPD in a unidirectional manner (OR = 1.001). The results of the eQTL-MR were consistent with those of the bidirectional MR. Conclusion: MDD appears to play a vital role in the effect of GERD on COPD. However, we have no evidence of a direct causal association between GERD and COPD. There is a bidirectional causal association between MDD and GERD, which may accelerate the progression from GERD to COPD.

Epidemiological overview of major depressive disorder in Scandinavia using nationwide registers.

Major depressive disorder (MDD) is a common psychiatric disorder associated with a high disease burden. This study gives a comprehensive overview of the prevalence, outcomes, treatment, and genetic epidemiology of MDD within and across the Scandinavian countries. This study has aimed to assess and compare across Norway, Denmark, and Sweden 1) the prevalence and trajectories of MDD and comorbidity, 2) outcomes and treatment, and 3) heritability (Denmark and Sweden only). The analyses leveraged data on 272,944 MDD cases (and 6.2 million non-cases) from Norway, Sweden, and Denmark in specialist care in national longitudinal health registers covering 1975-2013. Relying on harmonized public data global comparisons of socioeconomic and health metrics were performed to assess to what extent findings are generalizable. MDD ranked among the most prevalent psychiatric disorders. For many cases, the disorder trajectory was severe, with varying proportions experiencing recurrence, developing comorbid disorders, requiring inpatient treatment, or dying of suicide. Important country differences in specialist care prevalence and treatment were observed. Heritability estimates were moderate (35-48%). In terms of socioeconomic and health indices, the Scandinavian nations were comparable to one another and grouped with other Western nations. The Scandinavian countries were similar with regards to MDD epidemiological measures, but we show that differences in health care organization need to be taken into consideration when comparing countries. This study demonstrates the utility of using comprehensive population-wide registry data, outlining possibilities for other applications. The findings will be of use to policy makers for developing better prevention and intervention strategies. Swedish Research Council (Vetenskapsrådet, award D0886501 to PFS), US National Institutes of Mental HealthR01 MH123724 (to PFS), European Union's Horizon 2020 Research and Innovation Program (847776 and 964874, to OA) and European Research Council grant (grant agreement ID 101042183, to YL).

Higher immune-related gene expression in major depression is independent of CRP levels: results from the BIODEP study

Compelling evidence demonstrates that some individuals suffering from major depressive disorder (MDD) exhibit increased levels of inflammation. Most studies focus on inflammation-related proteins, such as serum or plasma C-reactive protein (CRP). However, the immune-related modifications associated with MDD may be not entirely captured by CRP alone. Analysing mRNA gene expression levels, we aimed to identify broader molecular immune-related phenotypes of MDD. We examined 168 individuals from the non-interventional, case–control, BIODEP study, 128 with a diagnosis of MDD and 40 healthy controls. Individuals with MDD were further divided according to serum high-sensitivity (hs)CRP levels (n = 59 with CRP <1, n = 33 with CRP 1–3 and n = 36 with CRP >3 mg/L). We isolated RNA from whole blood and performed gene expression analyses using RT-qPCR. We measured the expression of 16 immune-related candidate genes: A2M, AQP4, CCL2, CXCL12, CRP, FKBP5, IL-1-beta, IL-6, ISG15, MIF, GR, P2RX7, SGK1, STAT1, TNF-alpha and USP18. Nine of the 16 candidate genes were differentially expressed in MDD cases vs. controls, with no differences between CRP-based groups. Only CRP mRNA was clearly associated with serum CRP. In contrast, plasma (proteins) IL-6, IL-7, IL-8, IL-10, IL-12/IL-23p40, IL-16, IL-17A, IFN-gamma and TNF-alpha, and neutrophils counts, were all differentially regulated between CRP-based groups (higher in CRP >3 vs. CRP <1 and/or controls), reflecting the gradient of CRP values. Secondary analyses on MDD individuals and controls with CRP values <1 mg/L (usually interpreted as 'no inflammation') confirmed MDD cases still had significantly different mRNA expression of immune-related genes compared with controls. These findings corroborate an immune-related molecular activation in MDD, which appears to be independent of serum CRP levels. Additional biological mechanisms may then be required to translate this mRNA signature into inflammation at protein and cellular levels. Understanding these mechanisms will help to uncover the true immune abnormalities in depression, opening new paths for diagnosis and treatment.