Risk Of Major Depressive Disorder Research Articles

Exploring the mechanisms underlying increased risk of depressive disorder in ethnic minority populations in Europe: A causal loop diagram

BackgroundMultiple ethnic minority populations in Europe show high risk of major depressive disorder (MDD), with ethnic discrimination and low socioeconomic position (SEP) as established risk factors. How this risk is shaped by the interactions between these, and other social factors, remains to be elucidated. We aimed to develop a causal-loop diagram (CLD) to gain a better understanding of how factors at the intersection of ethnic discrimination and SEP dynamically interact to drive MDD risk. MethodsWe iteratively mapped the interactions and feedback loops between factors at the intersection of ethnic discrimination and SEP, drawing input from (i) a series of two interviews with a range of MDD domain experts, (ii) an existing CLD mapping the onset of MDD across psychological, biological, and social dimensions at the level of the individual, and (iii) other relevant literature. ResultsThrough tracing the feedback loops in the resulting CLD, we identified ten driving mechanisms for MDD onset in ethnic minorities (two related to ethnic discrimination, SEP, social network and support, and acculturation, as well as one relating to the living environment and self-stigma towards MDD); and four factors that modulate these mechanisms (recent migration, religious affiliation, neighborhood social environment, and public stigma towards MDD). The intersecting nature of ethnic discrimination and SEP, combined with the reinforcing dynamics of the identified driving mechanisms across time- and spatial scales, underscores the excess exposure to circumstances that increase MDD risk in ethnic minorities. ConclusionsWhile this CLD requires validation through future studies, the intersecting and reinforcing nature of the identified driving mechanisms highlights that tackling the high risk of MDD in ethnic minorities may require intervening at multiple targets, from the individual (e.g., psychological interventions targeting negative beliefs or reducing stress) to the societal level (e.g., addressing labor market discrimination).

The role of SKA2 on affective disorder, post-traumatic stress disorder and suicide behavior: systematic review and in silico analysis.

Genes involved in the hypothalamic-pituitary-adrenal axis may be a robust biomarker of psychiatric disorders. Genetic polymorphisms of the SKA2 gene are associated with several behavioral disorders. In this study, we embarked on a systematic search of all possible reports of genetic association with SKA2 and affective disorder, post-traumatic stress disorder, and suicide behavior; the functional consequences of nsSNPs were explored through computational tools with an in silico analysis. Eight eligible articles were included. Our study identified that SKA2 did not show association with risk of Major Depression Disorder. Epigenetic variation at SKA2 mediates vulnerability to Post-Traumatic Stress Disorder. Studies provide strong preliminary evidence that alterations at the SKA2 gene covary with types of suicide behavior, including suicidal ideation, attempts, and completions. Results from in silico analysis predicted that I22S, I22G, I78T, A15L, D18R, R25L, N42I, Y21S, K14I, K14L, and L60R were the most structurally and functionally significant nsSNPs in SKA2. Amino acid conservation analysis revealed that the amino acids were highly conserved and some dissimilarities of mutant type amino acids from wild-type amino acids such as charge, size, and hydrophobicity were observed. In the future, SKA2 gene have the potential to be evaluated as prognostic biomarkers for diagnosis and research.

Predictive Models for Suicide Attempts in Major Depressive Disorder and the Contribution of EPHX2: A Pilot Integrative Machine Learning Study

Suicide is a major public health problem caused by a complex interaction of various factors. Major depressive disorder (MDD) is the most prevalent psychiatric disorder associated with suicide; therefore, it is essential to prioritize suicide prediction and prevention within this population. Integrated information from different dimensions, including personality, cognitive function, and social and genetic factors, is necessary to improve the performance of predictive models. Besides, recent studies have indicated the critical roles for EPHX2/P2X2 in the pathophysiology of MDD. Our previous studies found an association of EPHX2 and P2X2 with suicide in MDD. This study is aimed at (1) establishing predictive models with integrated information to distinguish MDD from healthy volunteers, (2) estimating the suicide risk of MDD, and (3) determining the contribution of EPHX2/P2X2. This cross-sectional study was conducted on 472 prospectively collected participants. The machine learning (ML) technique using Extreme Gradient Boosting (XGBoost) classifier was employed to evaluate the performance and relative importance of the extracted characteristics in recognising patients with MDD and depressed suicide attempters (DSA). In independent validation set, the model with clinical and cognitive information could recognise MDD with an area under the receiver operating characteristic curve (AUC) of 0.938 (95% confidence interval (CI), 0.898–0.977), and genetic information did not improve classification performance. The model with clinical, cognitive, and genetic information resulted in a significantly higher AUC of 0.801 (95% CI, 0.719–0.884) for identifying DSA than the model with only clinical information, in which the three single nucleotide polymorphisms of EPHX2 showed important roles. This study successfully established step-by-step predictive ML models to estimate the risk of suicide attempts in MDD. We found that EPHX2 can help improve the performance of suicidal predictive models. This trial is registered with NCT05575713.

The relationship between event-related potential components and suicide risk in major depressive disorder

BackgroundSuicide is a serious global issue, with major depressive disorder (MDD) being a significant risk factor for suicidal thoughts and behaviors. There is an urgent need to determine whether event-related potential components (ERPs) could be used as an indicator to assess suicidal risk. MethodsFrom 2020 to 2023, 258 participants in total were recruited into the study. All participants were divided into four groups: MDD patients at high (n = 66), moderate (n = 66), and low risk (n = 56) of suicide, and healthy controls (HCs)(n = 70). Each participant provided socio-demographic information and underwent evaluations using clinical psychological scales such as 7-item Generalized Anxiety Disorder (GAD-7), Health Questionnaire-9 items (PHQ-9), and Nurses' Global Assessment of Suicide Risk (NGASR). The auditory brainstem response test and ERP examination were performed for all subjects. ResultsOur study found that the amplitude of P2–P3 and N2–P3 was significantly reduced in MDD patients at moderate and high risk of suicide, and these were negatively correlated with NGASR total score (all P < 0.05). Point B latency was positively correlated with NGASR total score (P < 0.05). Patients with MDD patients at low risk for suicide had a lower A-B amplitude compared to HCs (P < 0.05). No differences were found in MMN or P50 components between the four groups (all P > 0.05). ConclusionsMDD patients at higher risk of suicide exhibited severe impairment of cognitive function. ERP indices, such as the amplitude of P2–P3 and N2–P3, could be associated with the risk of suicide in MDD patients.

Shared genetic architecture highlights the bidirectional association between major depressive disorder and fracture risk

BackgroundThere is limited evidence suggesting that osteoporosis might exacerbate depressive symptoms, while more studies demonstrate that depression negatively affects bone density and increases fracture risk.AimsTo explore the relationship between major...

Molecular mechanisms underlying structural plasticity of electroconvulsive therapy in major depressive disorder.

Although previous studies reported structural changes associated with electroconvulsive therapy (ECT) in major depressive disorder (MDD), the underlying molecular basis of ECT remains largely unknown. Here, we combined two independent structural MRI datasets of MDD patients receiving ECT and transcriptomic gene expression data from Allen Human Brain Atlas to reveal the molecular basis of ECT for MDD. We performed partial least square regression to explore whether/how gray matter volume (GMV) alterations were associated with gene expression level. Functional enrichment analysis was conducted using Metascape to explore ontological pathways of the associated genes. Finally, these genes were further assigned to seven cell types to determine which cell types contribute most to the structural changes in MDD patients after ECT. We found significantly increased GMV in bilateral hippocampus in MDD patients after ECT. Transcriptome-neuroimaging association analyses showed that expression levels of 726 genes were positively correlated with the increased GMV in MDD after ECT. These genes were mainly involved in synaptic signaling, calcium ion binding and cell-cell signaling, and mostly belonged to excitatory and inhibitory neurons. Moreover, we found that the MDD risk genes of CNR1, HTR1A, MAOA, PDE1A, and SST as well as ECT related genes of BDNF, DRD2, APOE, P2RX7, and TBC1D14 showed significantly positive associations with increased GMV. Overall, our findings provide biological and molecular mechanisms underlying structural plasticity induced by ECT in MDD and the identified genes may facilitate future therapy for MDD.

Obstructive sleep apnea and mental disorders: a bidirectional mendelian randomization study

BackgroundPrevious studies have reported associations between obstructive sleep apnea (OSA) and several mental disorders. However, further research is required to determine whether these associations are causal. Therefore, we evaluated the bidirectional causality between the genetic liability for OSA and nine mental disorders by using Mendelian randomization (MR).MethodWe performed two-sample bidirectional MR of genetic variants for OSA and nine mental disorders. Summary statistics on OSA and the nine mental disorders were extracted from the FinnGen study and the Psychiatric Genomics Consortium. The primary analytical approach for estimating causal effects was the inverse-variance weighted (IVW), with the weighted median and MR Egger as complementary methods. The MR Egger intercept test, Cochran’s Q test, Rucker’s Q test, and the MR pleiotropy residual sum and outlier (MR-PRESSO) test were used for sensitivity analyses.ResultMR analyses showed that genetic liability for major depressive disorder (MDD) was associated with an increased risk of OSA (odds ratio [OR] per unit increase in the risk of MDD, 1.29; 95% CI, 1.11–1.49; P < 0.001). In addition, genetic liability for OSA may be associated with an increased risk of attention-deficit/hyperactivity disorder (ADHD) (OR = 1.26; 95% CI, 1.02–1.56; p = 0.032). There was no evidence that OSA is associated with other mental disorders.ConclusionOur study indicated that genetic liability for MDD is associated with an increased risk of OSA without a bidirectional relationship. Additionally, there was suggestive evidence that genetic liability for OSA may have a causal effect on ADHD. These findings have implications for prevention and intervention strategies targeting OSA and ADHD. Further research is needed to investigate the biological mechanisms underlying our findings and the relationship between OSA and other mental disorders.

Serum neuroactive metabolites of the tryptophan pathway in patients with acute phase of affective disorders.

Many studies showed disrupted tryptophan metabolism in patients with affective disorders. The aims of this study were to explore the differences in the metabolites of tryptophan pathway (TP) and the relationships between TP metabolites and clinical symptoms, therapeutic effect in patients with bipolar disorder with acute manic episode (BD-M), depressive episode (BD-D) and major depressive disorder (MDD). Patients with BD-M (n=52) and BD-D (n=39), MDD (n=48) and healthy controls (HCs, n=49) were enrolled. The serum neuroactive metabolites levels of the TP were measured by liquid chromatography-tandem mass spectrometry. Hamilton Depression Scale-17 item (HAMD-17) and Young Mania Rating Scale (YMRS) were used to evaluate depressive and manic symptoms at baseline and after 8 weeks of antidepressants, mood stabilizers, some also received antipsychotic medication. The levels of tryptophan (TRP) and kynurenic acid (KYNA) were significantly lower and the ratios of tryptophan/kynurenine (TRP/KYN), 5-hydroxytryptamine/tryptophan (5-HT/TRP), quinolinic acid/kynurenic acid (QUIN/KYNA) were higher in BD-M, BD-D, MDD vs. HC. The levels of QUIN and the ratios of QUIN/KYNA were higher in BD-M than in BD-D, MDD, and HCs. The 5-hydroxyindoleacetic acid (5-HIAA) levels of patients with MDD were significantly higher than those in BD-M and BD-D. Binary logistic regression analysis showed the lower peripheral KYNA, the higher the QUIN level, and the higher the risk of BD-M; the lower peripheral KYNA and the higher KYN/TRP and 5-HT/TRP, the higher the risk of BD-D; and the lower the peripheral KYNA level and the higher the KYN/TRP and 5-HT/TRP, the higher the risk of MDD. Correlation analysis, showing a significant association between tryptophan metabolites and improvement of clinical symptoms, especially depression symptoms. Patients with affective disorders had abnormal tryptophan metabolism, which involved in 5-HT and kynurenine pathway (KP) sub-pathway. Tryptophan metabolites might be potential biomarkers for affective disorders and some metabolites have been associated with remission of depressive symptoms.

Osteoporosis and depression in perimenopausal women: From clinical association to genetic causality

BackgroundOsteoporosis and major depressive disorder (MDD) represent two significant health challenges globally, particularly among perimenopausal women. This study utilizes NHANES data and Mendelian randomization (MR) analysis to explore the link between them, aiming to provide a basis for intervention strategies for this group. MethodsThe study analyzed NHANES 2007–2018 data using weighted logistic regression in R software to evaluate the link between MDD and osteoporosis risk. Then, a two-sample MR analysis with GWAS summary statistics was performed, mainly using the IVW method. Additional validation included MR Egger, Weighted Median, Mode, and MR-PRESSO methods. ResultsThe research analysis indicated a significant link between MDD and the risk of osteopenia/osteoporosis. Our analysis revealed a significant positive relationship between MDD and both femoral neck osteoporosis (OR = 6.942 [95 % CI, 1.692–28.485]) and trochanteric osteoporosis (OR = 4.140 [95 % CI, 1.699–10.089]). In analyses related to osteopenia, a significant positive correlation was observed between MDD and both total femoral osteopenia (OR = 3.309 [95 % CI, 1.577–6.942]) and trochanteric osteopenia (OR = 2.467 [95 % CI, 1.004–6.062]). Furthermore, in the MR analysis, genetically predicted MDD was causally associated with an increased risk of osteoporosis via the IVW method (P = 0.013). LimitationsOur study was limited by potential selection bias due to excluding subjects with missing data, and its applicability was primarily to European and American populations. ConclusionIntegrating NHANES and MR analyses, a robust correlation between MDD and osteoporosis was identified, emphasizing the significance of addressing this comorbidity within clinical practice and meriting further investigation.

Multiple coronary heart diseases are risk factors for mental health disorders: A mendelian randomization study

BackgroundPrevious observational studies have suggested associations between Coronary Heart Disease (CHD) and Mental Health Disorders (MHD). However, the causal nature of these relationships has remained elusive. ObjectiveThe purpose of this study is to elucidate the causal relationships between eight distinct types of CHD and six types of MHD using Mendelian randomization (MR) analysis. MethodsThe MR analysis employed a suite of methods including inverse variance-weighted (IVW), MR-Egger, weighted mode, weighted median, and simple mode techniques. To assess heterogeneity, IVW and MR-Egger tests were utilized. MR-Egger regression also served to investigate potential pleiotropy. The stability of IVW results was verified by leave-one-out sensitivity analysis. ResultsWe analyzed data from over 2,473,005 CHD and 803,801 MHD patients, informed by instrumental variables from large-scale genomic studies on European populations. The analysis revealed a causal increase in the risk of Major Depressive Disorder and Mania associated with Coronary Artery Disease and Myocardial Infarction. Heart Failure was found to causally increase the risk for Bipolar Disorder and Schizophrenia. Atrial Fibrillation and Ischemic Heart Diseases were positively linked to Generalized Anxiety Disorder and Mania, respectively. There was no significant evidence of an association between Hypertensive Heart Disease, Hypertrophic Cardiomyopathy, Pulmonary Heart Disease, and MHD. Reverse MR analysis indicated that MHD do not serve as risk factors for CHD. ConclusionsThe findings suggest that specific types of CHD may act as risk factors for certain MHDs. Consequently, incorporating psychological assessments into the management of patients with CHD could be advantageous.

Associations between breakfast skipping and outcomes in neuropsychiatric disorders, cognitive performance, and frailty: a Mendelian randomization study

BackgroundPrior studies have identified a correlation between breakfast skipping and a heightened risk of mental health issues. This investigation aimed to employ a Two-Sample Mendelian Randomization (MR) approach to explore the potential causal links between breakfast skipping and various psychiatric, neurological disorders, cognitive performance, and frailty.MethodsUtilizing data from genome-wide association studies within European demographics, this research scrutinized the association between breakfast habits and several neuropsychiatric conditions and physical health outcomes, including Alzheimer’s disease (AD), Attention Deficit Hyperactivity Disorder (ADHD), Bipolar Disorder (BD), Major Depressive Disorder (MDD), Narcolepsy, Insomnia, cognitive performance, and frailty. In this MR analysis, the Inverse Variance Weighted (IVW) method was primarily utilized for evaluation. Outcomes were reported as Odds Ratios (OR) and regression coefficients (β), and underwent validation through False Discovery Rate (FDR) corrections, thereby offering a rigorous evaluation of the effects of breakfast habits on both mental and physical health dimensions.ResultsFindings demonstrate a significant causal link between skipping breakfast and an increased risk of ADHD (OR = 2.74, 95%CI: 1.54–4.88, PFDR = 0.003) and MDD (OR = 1.7, 95%CI: 1.22–2.37, PFDR = 0.005). Conversely, no substantial causal associations were identified between breakfast skipping and AD, BD, narcolepsy, or insomnia (PFDR > 0.05). Moreover, a notable causal relationship was established between skipping breakfast and a reduction in cognitive performance (β = -0.16, 95%CI: -0.29–0.04, PFDR = 0.024) and an increase in frailty (β = 0.29, 95%CI: 0.12–0.45, PFDR = 0.003).ConclusionThe MR analysis reveals that skipping breakfast is associated with an increased risk of ADHD, MDD, decreased cognitive performance, and greater frailty, while showing no associations were found with AD, BD, narcolepsy, or insomnia. These findings warrant further investigation into the underlying mechanisms and emphasize the importance of regular breakfast consumption for mental and physical well-being.

The reciprocal associations between social deficits, social engagement, and inflammation: Longitudinal evidence comparing venous blood samples and dried blood spots and mapping the modifying role of phenotypic and genotypic depression

BackgroundSocial psychoneuroimmunology suggests an interplay between social deficits (loneliness and isolation) and chronic inflammation, but the direction of these relationships remains unclear. We estimated the reciprocal associations of social deficits and social engagement with levels of C-reactive protein (CRP), compared the consistency of the findings depending on the biological sampling method used, and examined the modifying role of phenotypic and genotypic depression. MethodsWe used longitudinal nationally representative data from the US (Health and Retirement Study, 3 waves, 2006–16) and England (English Longitudinal Study of Ageing, 4 waves, 2004–18). Loneliness, social isolation, and social engagement were self-reported. CRP was measured using dried blood spots (US) and venous blood samples (England). Cross-lagged panel models were fitted and tested interactions with phenotypic depression (above-threshold depressive symptom scores) and genotypic depression (polygenic score for major depressive disorder). ResultsWe included 15,066 participants (mean age = 66.1 years, SD = 9.8) in the US and 10,290 (66.9 years, SD = 10.5) in England. We found reciprocal associations between loneliness and CRP using dried blood spots and venous blood samples. Higher CRP predicted higher subsequent loneliness and higher loneliness predicted elevated CRP. Both phenotypic and genotypic depression modified this reciprocal association. There were also reciprocal associations for social engagement in venous blood samples: higher CRP predicted lower social engagement and greater social engagement predicted lower subsequent CRP. Associations between social isolation and CRP were inconsistent and unidirectional. ConclusionsLoneliness may increase chronic inflammation, whereas social engagement may reduce inflammation. As these relationships were reciprocal, there may be a loop between inflammation, loneliness, and social engagement. This loop was stronger in those with depression or at high genetic risk for major depressive disorder. This relationship for loneliness was present in both blood sampling methods despite contrasting methods of CRP measurement, indicating that the finding is not attributable to measurement bias in biomarkers.

The Association of Redox Regulatory Drug Target Genes with Psychiatric Disorders: A Mendelian Randomization Study.

Redox regulatory drug (RRD) targets may be considered potential novel drug targets of psychosis due to the fact that the brain is highly susceptible to oxidative stress imbalance. The aim of the present study is to identify potential associations between RRD targets' perturbation and the risk of psychoses; to achieve this, Mendelian randomization analyses were conducted. The expression quantitative trait loci (eQTL) and protein QTL data were used to derive the genetic instrumental variables. We obtained the latest summary data of genome-wide association studies on seven psychoses as outcomes, including schizophrenia (SCZ), bipolar disorder (BD), major depressive disorder (MDD), attention-deficit/hyperactivity disorder, autism, obsessive-compulsive disorder and anorexia nervosa. In total, 95 unique targets were included in the eQTL panel, and 48 targets in the pQTL one. Genetic variations in the vitamin C target (OGFOD2, OR = 0.784, p = 2.14 × 10-7) and melatonin target (RORB, OR = 1.263, p = 8.80 × 10-9) were significantly related to the risk of SCZ. Genetic variation in the vitamin E (PRKCB, OR = 0.248, p = 1.24 × 10-5) target was related to an increased risk of BD. Genetic variation in the vitamin C target (P4HTM: cerebellum, OR = 1.071, p = 4.64 × 10-7; cerebellar hemisphere, OR = 1.092, p = 1.98 × 10-6) was related to an increased risk of MDD. Cognitive function mediated the effects on causal associations. In conclusion, this study provides supportive evidence for a causal association between RRD targets and risk of SCZ, BD or MDD, which were partially mediated by cognition.

Childhood correlates and young adult outcomes of trajectories of emotional problems from childhood to adolescence.

Emotional problems, especially anxiety, have become increasingly common in recent generations. Few population-based studies have examined trajectories of emotional problems from early childhood to late adolescence or investigated differences in psychiatric and functional outcomes. Using the Avon Longitudinal Study of Parents and Children (ALSPAC, n = 8286, 50.4% male), we modeled latent class growth trajectories of emotional problems, using the parent-reported Strength and Difficulties Questionnaire emotional scale (SDQ-E) on seven occasions (4-17 years). Psychiatric outcomes in young adulthood (21-25 years) were major depressive disorder (MDD), generalized anxiety disorder (GAD), and self-harm. Functional outcomes were exam attainment, educational/occupational status, and social relationship quality. We identified four classes of emotional problems: low (67.0%), decreasing (18.4%), increasing (8.9%), and persistent (5.7%) problems. Compared to those in the low class, individuals with decreasing emotional problems were not at elevated risk of any poor adult outcome. Individuals in the increasing and persistent classes had a greater risk of adult MDD (RR: 1.59 95% CI 1.13-2.26 and RR: 2.25 95% CI 1.49-3.41) and self-harm (RR: 2.37 95% CI 1.91-2.94 and RR: 1.87 95% CI 1.41-2.48), and of impairment in functional domains. Childhood sleep difficulties, irritability, conduct and neurodevelopmental problems, and family adversity were associated with a persistent course of emotional problems. Childhood emotional problems were common, but those whose symptoms improved over time were not at increased risk for adverse adult outcomes. In contrast, individuals with persistent or adolescent-increasing emotional problems had a higher risk of mental ill-health and social impairment in young adulthood which was especially pronounced for those with persistent emotional problems.

Genetically predicted processed meat, red meat intake, and risk of mental disorders: A multivariable Mendelian randomization analysis

BackgroundPrevious observational studies have highlighted potential links between the consumption of processed meat and red meat (such as pork, mutton, and beef intake) and the occurrence of mental disorders. However, it is unclear whether a causal association exists. Therefore, we employed the Mendelian randomization (MR) study to investigate the causal effects of genetically predicted processed meat and red meat on mood disorders (MD), anxiety disorders (AD), and major depressive disorder (MDD). MethodsGenetic instruments for processed and red meat were selected from the Genome-Wide Association Study (GWAS) of the UK Biobank Study. Their associations with MD (42,746 cases 254,976), AD (35,385 cases and 254,976 controls), and MDD (38,225 cases and 299,886 controls) were obtained from the FinnGen Consortium. The inverse variance weighted (IVW) method was the primary method for two-sample MR analysis. Additionally, we employed complementary analysis to assess the robustness of our MR findings (eg, MR Egger and weighted median). We also conducted multiple sensitivity analyses to investigate horizontal pleiotropy and heterogeneity. Moreover, we performed a univariate and multivariable MR (MVMR) study to evaluate these associations. ResultsIn our univariate MR analysis, we observed that genetically predicted beef intake was associated with a reduced risk of MD [odds ratio (OR) = 0.403, 95 % confidence interval (CI) = 0.246–0.659; PIVW = 4.428 × 10−5], AD (OR = 0.443, 95 % CI = 0.267–0.734; PIVW = 1.563 × 10−3), and MDD (OR = 0.373, 95 % CI = 0.216–0.643; PIVW = 3.878 × 10−4). After adjusting for processed meat, pork, and mutton intake in the MVMR analysis, the protective association of beef intake against MD and MDD remained. However, there was no substantial evidence indicating a significant causal relationship between processed meat, pork, and mutton intake and the occurrence of mental disorders. Furthermore, our sensitivity analysis revealed no significant evidence of horizontal pleiotropy. ConclusionThese findings support a causal relationship between genetically predicted beef intake and reducing the risk of MD and MDD.

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

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

Social determinants of mental health in major depressive disorder: Umbrella review of 26 meta-analyses and systematic reviews

There is a growing recognition of the impact of social determinants of mental health (SDoMHs) on people with, or at risk of, developing serious mental illnesses. Yet it is not known how associations of individual SDoMHs with risk for major depressive disorder (MDD) vary and roughly compare with one another. Following PRISMA guidelines, this umbrella review included 26 meta-analyses and systematic reviews that reported odds ratios, effect sizes, and/or pooled prevalence rates of MDD in samples with versus without specified SDoMHs. Childhood emotional, physical, or sexual abuse and neglect; intimate partner violence in females; and food insecurity were significantly associated with increased risk of MDD, with medium effect sizes. Natural disasters, terrorist acts, and military combat during deployment had small-size adverse effects, and homelessness, incarceration, and migration were associated with significantly elevated prevalence of MDD. Conversely, higher levels of parental care were significantly associated with reduced risk of MDD with medium effect sizes. Evidence supports the use of certain interventions at the individual and community level that can reduce the impact of these factors and promote health, although much more research is warranted in this area along with meaningful healthcare and societal policies to accomplish this goal.

Polygenic risk for major depression, attention deficit hyperactivity disorder, neuroticism, and schizophrenia are correlated with experience of intimate partner violence

Research has suggested that mental illness may be a risk factor for, as well as a sequela of, experiencing intimate partner violence (IPV). The association between IPV and mental illness may also be due in part to gene-environment correlations. Using polygenic risk scores for six psychiatric disorders - attention-deficit hyperactivity disorder (ADHD), autism spectrum disorder (ASD), bipolar disorder (BPD), major depressive disorder (MDD), neuroticism, and schizophrenia—and a combined measure of overall genetic risk for mental illness, we tested whether women’s genetic risk for mental illness was associated with the experience of three types of intimate partner violence. In this cohort of women of European ancestry (N = 11,095), participants in the highest quintile of genetic risk for ADHD (OR range: 1.38–1.49), MDD (OR range: 1.28–1.43), neuroticism (OR range: (1.18–1.25), schizophrenia (OR range: 1.30–1.34), and overall genetic risk (OR range: 1.30–1.41) were at higher risk for experiencing more severe emotional and physical abuse, and, except schizophrenia, more severe sexual abuse, as well as more types of abuse and chronic abuse. In addition, participants in the highest quintile of genetic risk for neuroticism (OR = 1.43 95% CI: 1.18, 1.72), schizophrenia (OR = 1.33 95% CI: 1.10, 1.62), and the overall genetic risk (OR = 1.40 95% CI: 1.15, 1.71) were at higher risk for experiencing intimate partner intimidation and control. Participants in the highest quintile of genetic risk for ADHD, ASD, MDD, schizophrenia, and overall genetic risk, compared to the lowest quintile, were at increased risk for experiencing harassment from a partner (OR range: 1.22–1.92). No associations were found between genetic risk for BPD with IPV. A better understanding of the salience of the multiple possible pathways linking genetic risk for mental illness with risk for IPV may aid in preventing IPV victimization or re-victimization.

Dissecting the genetic overlap between severe mental disorders and markers of cellular aging: Identification of pleiotropic genes and druggable targets.

Patients with severe mental disorders such as bipolar disorder (BD), schizophrenia (SCZ) and major depressive disorder (MDD) show a substantial reduction in life expectancy, increased incidence of comorbid medical conditions commonly observed with advanced age and alterations of aging hallmarks. While severe mental disorders are heritable, the extent to which genetic predisposition might contribute to accelerated cellular aging is not known. We used bivariate causal mixture models to quantify the trait-specific and shared architecture of mental disorders and 2 aging hallmarks (leukocyte telomere length [LTL] and mitochondrial DNA copy number), and the conjunctional false discovery rate methodto detect shared genetic loci. We integrated gene expression data from brain regions from GTEx and used different tools to functionally annotate identified loci and investigate their druggability. Aging hallmarks showed low polygenicity compared with severe mental disorders. We observed a significant negative global genetic correlation between MDD and LTL (rg = -0.14, p = 6.5E-10), and no significant results for other severe mental disorders or for mtDNA-cn. However, conditional QQ plots and bivariate causal mixture models pointed to significant pleiotropy among all severe mental disorders and aging hallmarks. We identified genetic variants significantly shared between LTL and BD (n = 17), SCZ (n = 55) or MDD (n = 19), or mtDNA-cn and BD (n = 4), SCZ (n = 12) or MDD (n = 1), with mixed direction of effects. The exonic rs7909129 variant in the SORCS3 gene, encoding a member of the retromer complex involved in protein trafficking and intracellular/intercellular signaling, was associated with shorter LTL and increased predisposition to all severe mental disorders. Genetic variants underlying risk of SCZ or MDD and shorter LTL modulate expression of several druggable genes in different brain regions. Genistein, a phytoestrogen with anti-inflammatory and antioxidant effects, was an upstream regulator of 2 genes modulated by variants associated with risk of MDD and shorter LTL. While our results suggest that shared heritability might play a limited role in contributing to accelerated cellular aging in severe mental disorders, we identified shared genetic determinants and prioritized different druggable targets and compounds.

Influence of PCDH9 (rs9540720) and narcissistic personality traits on the incidence of major depressive disorder in Chinese first-year university students: findings from a 2-year cohort study.

Objective: The objective of this study was to explore the influence of the polymorphism of the protocadherin 9 (PCDH9) gene and the narcissistic personality trait (NPT) on the risk of major depressive disorder (MDD) in Chinese first-year university students. Methods: A 2-year cohort study was conducted among Chinese first-year university students who were enrolled in 2018 from two universities in Shandong Province, China. The snapshot technique was used to detect the genotypes of PCDH9 (rs9540720). The Chinese version of the Composite International Diagnostic Interview was used for the MDD assessment. The NPTs were measured by 11 items based on DSM-IV. Patient Health Questionnaire-9 and the Beck Anxiety Inventory were used to assess depressive and anxiety symptoms, respectively. Logistic regression modeling was carried out to examine the relationship between rs9540720, NPTs, and the incidence of MDD. Results: A total of 5,327 students participated in the baseline and follow-up studies and provided their blood samples. PCDH9 (rs9540720) (ORGG+GA = 2.33, 95% CI: 1.35-4.02) and NPTs (OR5-9 = 2.26, 95% CI: 1.40-3.64) increased the risk of MDD onset. There was no multiplicative interaction between NPTs and Rs9540720 (OR = 1.51, 95% CI: 0.30-7.63). Furthermore, there was no additive interaction between them (RERI = 2.40, 95% CI: -0.82-5.62; AP = 0.47, 95% CI: -0.04-0.97; and S = 2.37, 95% CI: 0.54-10.33). Conclusion: PCDH9 (rs9540720) and more NPTs are the risk factors for the incidence of MDD in Chinese first-year university students.