Polygenic dissection of major depression clinical heterogeneity

Deconstructing major depressive episodes across unipolar and bipolar depression by severity and duration: a cross-diagnostic cluster analysis on a large, international, observational study

A cross-diagnostic, post-hoc analysis of the BRIDGE-II-MIX study was performed to investigate how unipolar and bipolar patients suffering from an acute major depressive episode (MDE) cluster according to severity and duration. Duration of index episode, Clinical Global Impression-Bipolar Version-Depression (CGI-BP-D) and Global Assessment of Functioning (GAF) were used as clustering variables. MANOVA and post-hoc ANOVAs examined between-group differences in clustering variables. A stepwise backward regression model explored the relationship with the 56 clinical-demographic variables available. Agglomerative hierarchical clustering with two clusters was shown as the best fit and separated the study population (n = 2314) into 65.73% (Cluster 1 (C1)) and 34.26% (Cluster 2 (C2)). MANOVA showed a significant main effect for cluster group (p < 0.001) but ANOVA revealed that significant between-group differences were restricted to CGI-BP-D (p < 0.001) and GAF (p < 0.001), showing greater severity in C2. Psychotic features and a minimum of three DSM-5 criteria for mixed features (DSM-5-3C) had the strongest association with C2, that with greater disease burden, while non-mixed depression in bipolar disorder (BD) type II had negative association. Mixed affect defined as DSM-5-3C associates with greater acute severity and overall impairment, independently of the diagnosis of bipolar or unipolar depression. In this study a pure, non-mixed depression in BD type II significantly associates with lesser burden of clinical and functional severity. The lack of association for less restrictive, researched-based definitions of mixed features underlines DSM-5-3C specificity. If confirmed in further prospective studies, these findings would warrant major revisions of treatment algorithms for both unipolar and bipolar depression.

Approaches to Defining Common and Dissociable Neurobiological Deficits Associated With Psychopathology in Youth

Psychiatric disorders show high rates of comorbidity and nonspecificity of presenting clinical symptoms, while demonstrating substantial heterogeneity within diagnostic categories. Notably, many of these psychiatric disorders first manifest in youth. We review progress and next steps in efforts to parse heterogeneity in psychiatric symptoms in youths by identifying abnormalities within neural circuits. To address this fundamental challenge in psychiatry, a number of methods have been proposed. We provide an overview of these methods, broadly organized into dimensional versus categorical approaches and single-view versus multiview approaches. Dimensional approaches including factor analysis and canonical correlation analysis aim to capture dimensional associations between psychopathology and brain measures across a continuous spectrum from health to disease. In contrast, categorical approaches, such as clustering and community detection, aim to identify subtypes of individuals within a class of symptoms or brain features. We highlight several studies that apply these methods to samples of youths and discuss issues to consider when using these approaches. Finally, we end by highlighting avenues for future research.

Causes and Consequences of Diagnostic Heterogeneity in Depression: Paths to Discovering Novel Biological Depression Subtypes

Depression is a highly heterogeneous syndrome that bears only modest correlations with its biological substrates, motivating a renewed interest in rethinking our approach to diagnosing depression for research purposes and new efforts to discover subtypes of depression anchored in biology. Here, we review the major causes of diagnostic heterogeneity in depression, with consideration of both clinical symptoms and behaviors (symptomatology and trajectory of depressive episodes) and biology (genetics and sexually dimorphic factors). Next, we discuss the promise of using data-driven strategies to discover novel subtypes of depression based on functional neuroimaging measures, including dimensional, categorical, and hybrid approaches to parsing diagnostic heterogeneity and understanding its biological basis. The merits of using resting-state functional magnetic resonance imaging functional connectivity techniques for subtyping are considered along with a set of technical challenges and potential solutions. We conclude by identifying promising future directions for defining neurobiologically informed depression subtypes and leveraging them in the future for predicting treatment outcomes and informing clinical decision making.

Appetite changes reveal depression subgroups with distinct endocrine, metabolic, and immune states

There exists little human neuroscience research to explain why some individuals lose their appetite when they become depressed, while others eat more. Answering this question may reveal much about the various pathophysiologies underlying depression. The present study combined neuroimaging, salivary cortisol, and blood markers of inflammation and metabolism collected prior to scanning. We compared the relationships between peripheral endocrine, metabolic, and immune signaling and brain activity to food cues between depressed participants experiencing increased (N = 23) or decreased (N = 31) appetite and weight in their current depressive episode and healthy control participants (N = 42). The two depression subgroups were unmedicated and did not differ in depression severity, anxiety, anhedonia, or body mass index. Depressed participants experiencing decreased appetite had higher cortisol levels than subjects in the other two groups, and their cortisol values correlated inversely with the ventral striatal response to food cues. In contrast, depressed participants experiencing increased appetite exhibited marked immunometabolic dysregulation, with higher insulin, insulin resistance, leptin, CRP, IL-1RA, and IL-6, and lower ghrelin than subjects in other groups, and the magnitude of their insulin resistance correlated positively with the insula response to food cues. These findings provide novel evidence linking aberrations in homeostatic signaling pathways within depression subtypes to the activity of neural systems that respond to food cues and select when, what, and how much to eat. In conjunction with prior work, the present findings strongly support the existence of pathophysiologically distinct depression subtypes for which the direction of appetite change may be an easily measured behavioral marker.

Symptom networks in acute depression across bipolar and major depressive disorders: A network analysis on a large, international, observational study

Major Depressive Episode (MDE) is a transdiagnostic nosographic construct straddling Major Depressive (MDD) and Bipolar Disorder (BD). Prognostic and treatment implications warrant a differentiation between these two disorders. Network analysis is a novel approach that outlines symptoms interactions in psychopathological networks. We investigated the interplay among depressive and mixed symptoms in acutely depressed MDD/BD patients, using a data-driven approach. We analyzed 7 DSM-IV-TR criteria for MDE and 14 researched-based criteria for mixed features (RBDC) in 2758 acutely depressed MDD/BD patients from the BRIDGE-II-Mix study. The global network was described in terms of symptom thresholds and symptom centrality. Symptom endorsement rates were compared across diagnostic subgroups. Subsequently, MDD/BD differences in symptom-network structure were examined using permutation-based network comparison test. Mixed symptoms were the most central and highly interconnected nodes in the network, particularly agitation followed by irritability. Despite mixed symptoms, appetite gain and hypersomnia were significantly more endorsed in BD patients, associations between symptoms were highly correlated across MDD/BD (Spearman's r = 0.96, p<0.001). Network comparison tests showed no significant differences among MDD/BD in network strength, structure, or specific edges, with strong edges correlations (0.66-0.78). Upstream differences in MDD/BD may produce similar symptoms networks downstream during acute depression. Yet, mixed symptoms, appetite gain and hypersomnia are associated to BD rather than MDD. Symptoms during mixed-MDE might aggregate according to 2 different clusters, suggesting a possible stratification within mixed states. Future symptom-based studies should implement clinical, longitudinal, and biological factors, in order to establish tailored therapeutic strategies for acute depression.

Genetic stratification of depression in UK Biobank

Depression is a common and clinically heterogeneous mental health disorder that is frequently comorbid with other diseases and conditions. Stratification of depression may align sub-diagnoses more closely with their underling aetiology and provide more tractable targets for research and effective treatment. In the current study, we investigated whether genetic data could be used to identify subgroups within people with depression using the UK Biobank. Examination of cross-locus correlations were used to test for evidence of subgroups using genetic data from seven other complex traits and disorders that were genetically correlated with depression and had sufficient power (>0.6) for detection. We found no evidence for subgroups within depression for schizophrenia, bipolar disorder, attention deficit/hyperactivity disorder, autism spectrum disorder, anorexia nervosa, inflammatory bowel disease or obesity. This suggests that for these traits, genetic correlations with depression were driven by pleiotropic genetic variants carried by everyone rather than by a specific subgroup.

The biological classification of mental disorders (BeCOME) study: a protocol for an observational deep-phenotyping study for the identification of biological subtypes

BACKGROUND

A major research finding in the field of Biological Psychiatry is that symptom-based categories of mental disorders map poorly onto dysfunctions in brain circuits or neurobiological pathways. Many of the identified (neuro) biological dysfunctions are "transdiagnostic", meaning that they do not reflect diagnostic boundaries but are shared by different ICD/DSM diagnoses. The compromised biological validity of the current classification system for mental disorders impedes rather than supports the development of treatments that not only target symptoms but also the underlying pathophysiological mechanisms. The Biological Classification of Mental Disorders (BeCOME) study aims to identify biology-based classes of mental disorders that improve the translation of novel biomedical findings into tailored clinical applications.

METHODS

BeCOME intends to include at least 1000 individuals with a broad spectrum of affective, anxiety and stress-related mental disorders as well as 500 individuals unaffected by mental disorders. After a screening visit, all participants undergo in-depth phenotyping procedures and omics assessments on two consecutive days. Several validated paradigms (e.g., fear conditioning, reward anticipation, imaging stress test, social reward learning task) are applied to stimulate a response in a basic system of human functioning (e.g., acute threat response, reward processing, stress response or social reward learning) that plays a key role in the development of affective, anxiety and stress-related mental disorders. The response to this stimulation is then read out across multiple levels. Assessments comprise genetic, molecular, cellular, physiological, neuroimaging, neurocognitive, psychophysiological and psychometric measurements. The multilevel information collected in BeCOME will be used to identify data-driven biologically-informed categories of mental disorders using cluster analytical techniques.

DISCUSSION

The novelty of BeCOME lies in the dynamic in-depth phenotyping and omics characterization of individuals with mental disorders from the depression and anxiety spectrum of varying severity. We believe that such biology-based subclasses of mental disorders will serve as better treatment targets than purely symptom-based disease entities, and help in tailoring the right treatment to the individual patient suffering from a mental disorder. BeCOME has the potential to contribute to a novel taxonomy of mental disorders that integrates the underlying pathomechanisms into diagnoses.

TRIAL REGISTRATION

Retrospectively registered on June 12, 2019 on ClinicalTrials.gov (TRN: NCT03984084).

A phenome-wide association and Mendelian Randomisation study of polygenic risk for depression in UK Biobank

Depression is a leading cause of worldwide disability but there remains considerable uncertainty regarding its neural and behavioural associations. Here, using non-overlapping Psychiatric Genomics Consortium (PGC) datasets as a reference, we estimate polygenic risk scores for depression (depression-PRS) in a discovery (N = 10,674) and replication (N = 11,214) imaging sample from UK Biobank. We report 77 traits that are significantly associated with depression-PRS, in both discovery and replication analyses. Mendelian Randomisation analysis supports a potential causal effect of liability to depression on brain white matter microstructure (β: 0.125 to 0.868, p_FDR < 0.043). Several behavioural traits are also associated with depression-PRS (β: 0.014 to 0.180, p_FDR: 0.049 to 1.28 × 10⁻¹⁴) and we find a significant and positive interaction between depression-PRS and adverse environmental exposures on mental health outcomes. This study reveals replicable associations between depression-PRS and white matter microstructure. Our results indicate that white matter microstructure differences may be a causal consequence of liability to depression.

Depression is correlated with many brain-related traits. Here, Shen et al. perform phenome-wide association studies of a depression polygenic risk score (PRS) and find associations with 51 behavioural and 26 neuroimaging traits which are further followed up on using Mendelian randomization and mediation analyses.

Characteristics, comorbidities, and correlates of atypical depression: evidence from the UK Biobank Mental Health Survey

BACKGROUND

Depression is a heterogeneous disorder with multiple aetiological pathways and multiple therapeutic targets. This study aims to determine whether atypical depression (AD) characterized by reversed neurovegetative symptoms is associated with a more pernicious course and a different sociodemographic, lifestyle, and comorbidity profile than nonatypical depression (nonAD).

METHODS

Among 157 366 adults who completed the UK Biobank Mental Health Questionnaire (MHQ), N = 37 434 (24%) met the DSM-5 criteria for probable lifetime major depressive disorder (MDD) based on the Composite International Diagnostic Interview Short Form. Participants reporting both hypersomnia and weight gain were classified as AD cases (N = 2305), and the others as nonAD cases (N = 35 129). Logistic regression analyses were conducted to examine differences between AD and nonAD in depression features, sociodemographic and lifestyle factors, lifetime adversities, psychiatric and physical comorbidities.

RESULTS

Persons with AD experienced an earlier age of depression onset, longer, more severe and recurrent episodes, and higher help-seeking rates than nonAD persons. AD was associated with female gender, unhealthy behaviours (smoking, social isolation, low physical activity), more lifetime deprivation and adversity, higher rates of comorbid psychiatric disorders, obesity, cardiovascular disease (CVD), and metabolic syndrome. Sensitivity analyses comparing AD persons with those having typical neurovegetative symptoms (hyposomnia and weight loss) revealed similar results.

CONCLUSIONS

These findings highlight the clinical and public health significance of AD as a chronic form of depression, associated with high comorbidity and lifetime adversity. Our findings have implications for predicting depression course and comorbidities, guiding research on aetiological mechanisms, planning service use and informing therapeutic approaches.

Neurovegetative symptom subtypes in young people with major depressive disorder and their structural brain correlates

Depression is a leading cause of burden of disease among young people. Current treatments are not uniformly effective, in part due to the heterogeneous nature of major depressive disorder (MDD). Refining MDD into more homogeneous subtypes is an important step towards identifying underlying pathophysiological mechanisms and improving treatment of young people. In adults, symptom-based subtypes of depression identified using data-driven methods mainly differed in patterns of neurovegetative symptoms (sleep and appetite/weight). These subtypes have been associated with differential biological mechanisms, including immuno-metabolic markers, genetics and brain alterations (mainly in the ventral striatum, medial orbitofrontal cortex, insular cortex, anterior cingulate cortex amygdala and hippocampus). K-means clustering was applied to individual depressive symptoms from the Quick Inventory of Depressive Symptoms (QIDS) in 275 young people (15-25 years old) with MDD to identify symptom-based subtypes, and in 244 young people from an independent dataset (a subsample of the STAR*D dataset). Cortical surface area and thickness and subcortical volume were compared between the subtypes and 100 healthy controls using structural MRI. Three subtypes were identified in the discovery dataset and replicated in the independent dataset; severe depression with increased appetite, severe depression with decreased appetite and severe insomnia, and moderate depression. The severe increased appetite subtype showed lower surface area in the anterior insula compared to both healthy controls. Our findings in young people replicate the previously identified symptom-based depression subtypes in adults. The structural alterations of the anterior insular cortex add to the existing evidence of different pathophysiological mechanisms involved in this subtype.

Redefining phenotypes to advance psychiatric genetics: Implications from hierarchical taxonomy of psychopathology

Genetic discovery in psychiatry and clinical psychology is hindered by suboptimal phenotypic definitions. We argue that the hierarchical, dimensional, and data-driven classification system proposed by the Hierarchical Taxonomy of Psychopathology (HiTOP) consortium provides a more effective approach to identifying genes that underlie mental disorders, and to studying psychiatric etiology, than current diagnostic categories. Specifically, genes are expected to operate at different levels of the HiTOP hierarchy, with some highly pleiotropic genes influencing higher order psychopathology (e.g., the general factor), whereas other genes conferring more specific risk for individual spectra (e.g., internalizing), subfactors (e.g., fear disorders), or narrow symptoms (e.g., mood instability). We propose that the HiTOP model aligns well with the current understanding of the higher order genetic structure of psychopathology that has emerged from a large body of family and twin studies. We also discuss the convergence between the HiTOP model and findings from recent molecular studies of psychopathology indicating broad genetic pleiotropy, such as cross-disorder SNP-based shared genetic covariance and polygenic risk scores, and we highlight molecular genetic studies that have successfully redefined phenotypes to enhance precision and statistical power. Finally, we suggest how to integrate a HiTOP approach into future molecular genetic research, including quantitative and hierarchical assessment tools for future data-collection and recommendations concerning phenotypic analyses. (PsycINFO Database Record (c) 2020 APA, all rights reserved).

The association between overall and abdominal adiposity and depressive mood: A cross-sectional analysis in 6459 participants

OBJECTIVE

We aimed to evaluate the association between measures of adiposity with depressive mood and specific depressive symptoms.

METHODS

This study was performed in the Netherlands Epidemiology of Obesity (NEO) study, a population-based study that consists of 6671 middle-aged individuals. We examined the association between measures of overall adiposity (BMI and total body fat), and abdominal adiposity (waist circumference and visceral adipose tissue), with depressive mood severity subgroups and 30 depressive symptoms. Multinomial logistic regression was performed adjusting for potential confounding.

RESULTS

Measures of adiposity were associated with depressive mood in a graded fashion. Total body fat showed the strongest association with mild (Odds Ratio (OR): 1.59 per standard deviation, 95% Confidence Interval (95% CI): 1.41-1.80) and moderate to very severe (OR: 1.97, 95% CI: 1.59-2.44) depressive mood. Regarding individual symptoms of depressive mood, total body fat was associated with most depressive symptoms (strongest associations for hyperphagia and fatigability).

CONCLUSIONS

In the general population, overall and abdominal adiposity measures were associated with depressive mood. This association encompasses most of the depressive symptoms and appeared to be the strongest with specific ''atypical'' neurovegetative symptoms, which may be an indication of an alteration in the energy homeostasis.

Mental health is biological health: Why tackling "diseases of the mind" is an imperative for biological anthropology in the 21st century

The germ theory of disease and the attendant public health initiatives, including sanitation, vaccination, and antibiotic treatment, led to dramatic increases in global life expectancy. As the prevalence of infectious disease declines, mental disorders are emerging as major contributors to the global burden of disease. Scientists understand little about the etiology of mental disorders, however, and many of the most popular psychopharmacological treatments, such as antidepressants and antipsychotics, have only moderate-to-weak efficacy in treating symptoms and fail to target biological systems that correspond to discrete psychiatric syndromes. Consequently, despite dramatic increases in the treatment of some mental disorders, there has been no decrease in the prevalence of most mental disorders since accurate record keeping began. Many researchers and theorists are therefore endeavoring to rethink psychiatry from the ground-up. Anthropology, especially biological anthropology, can offer critical theoretical and empirical insights to combat mental illness globally. Biological anthropologists are unique in that we take a panhuman approach to human health and behavior and are trained to address each of Tinbergen's four levels of analysis as well as culture. The field is thus exceptionally well-situated to help resolve the mysteries of mental illness by integrating biological, evolutionary, and sociocultural perspectives.

Shared pathways for neuroprogression and somatoprogression in neuropsychiatric disorders

Activated immune-inflammatory, oxidative and nitrosative stress (IO&NS) pathways and consequent mitochondrial aberrations are involved in the pathophysiology of psychiatric disorders including major depression, bipolar disorder and schizophrenia. They offer independent and shared contributions to pathways underpinning medical comorbidities including insulin resistance, metabolic syndrome, obesity and cardiovascular disease - herein conceptualized as somatoprogression. This narrative review of human studies aims to summarize relationships between IO&NS pathways, neuroprogression and somatoprogression. Activated IO&NS pathways, implicated in the neuroprogression of psychiatric disorders, affect the pathogenesis of comorbidities including insulin resistance, dyslipidaemia, obesity and hypertension, and by inference, metabolic syndrome. These conditions activate IO&NS pathways, exacerbating neuroprogression in psychiatric disorders. The processes whereby proinflammatory cytokines, nitrosative and endoplasmic reticulum stress, NADPH oxidase isoforms, PPARγ inactivation, SIRT1 deficiency and intracellular signalling pathways impact lipid metabolism and storage are considered. Through associations between body mass index, chronic neuroinflammation and FTO expression, activation of IO&NS pathways arising from somatoprogression may contribute to neuroprogression. Early evidence highlights the potential of adjuvants targeting IO&NS pathways for treating somatoprogression and neuroprogression.

A role for vitamin D and omega-3 fatty acids in major depression? An exploration using genomics

Trials testing the effect of vitamin D or omega-3 polyunsaturated fatty acid (n3-PUFA) supplementation on major depressive disorder (MDD) reported conflicting findings. These trials were inspired by epidemiological evidence suggesting an inverse association of circulating 25-hydroxyvitamin D (25-OH-D) and n3-PUFA levels with MDD. Observational associations may emerge from unresolved confounding, shared genetic risk, or direct causal relationships. We explored the nature of these associations exploiting data and statistical tools from genomics. Results from genome-wide association studies on 25-OH-D (N = 79 366), n3-PUFA (N = 24 925), and MDD (135 458 cases, 344 901 controls) were applied to individual-level data (>2000 subjects with measures of genotype, DSM-IV (Diagnostic and Statistical Manual of Mental Disorders, 4th edition) lifetime MDD diagnoses and circulating 25-OH-D and n3-PUFA) and summary-level data analyses. Shared genetic risk between traits was tested by polygenic risk scores (PRS). Two-sample Mendelian Randomization (2SMR) analyses tested the potential bidirectional causality between traits. In individual-level data analyses, PRS were associated with the phenotype of the same trait (PRS 25-OH-D p = 1.4e - 20, PRS n3-PUFA p = 9.3e - 6, PRS MDD p = 1.4e - 4), but not with the other phenotypes, suggesting a lack of shared genetic effects. In summary-level data analyses, 2SMR analyses provided no evidence of a causal role on MDD of 25-OH-D (p = 0.50) or n3-PUFA (p = 0.16), or for a causal role of MDD on 25-OH-D (p = 0.25) or n3-PUFA (p = 0.66). Applying genomics tools indicated that shared genetic risk or direct causality between 25-OH-D, n3-PUFA, and MDD is unlikely: unresolved confounding may explain the associations reported in observational studies. These findings represent a cautionary tale for testing supplementation of these compounds in preventing or treating MDD.

Progress in psychoradiology, the clinical application of psychiatric neuroimaging

Psychoradiology is an emerging field that applies radiological imaging technologies to psychiatric conditions. In the past three decades, brain imaging techniques have rapidly advanced understanding of illness and treatment effects in psychiatry. Based on these advances, radiologists have become increasingly interested in applying these advances for differential diagnosis and individualized patient care selection for common psychiatric illnesses. This shift from research to clinical practice represents the beginning evolution of psychoradiology. In this review, we provide a summary of recent progress relevant to this field based on their clinical functions, namely the (1) classification and subtyping; (2) prediction and monitoring of treatment outcomes; and (3) treatment selection. In addition, we provide guidelines for the practice of psychoradiology in clinical settings and suggestions for future research to validate broader clinical applications. Given the high prevalence of psychiatric disorders and the importance of increased participation of radiologists in this field, a guide regarding advances in this field and a description of relevant clinical work flow patterns help radiologists contribute to this fast-evolving field.

Involvement of inflammatory gene expression pathways in depressed patients with hyperphagia

The pathophysiology of major depressive disorder (MDD) is highly heterogeneous. Previous evidence at the DNA level as well as on the serum protein level suggests that the role of inflammation in MDD pathology is stronger in patients with hyperphagia during an active episode. Which inflammatory pathways differ in MDD patients with hyperphagia inflammatory pathways in terms of gene expression is unknown. We analyzed whole-blood gene expression profiles of 881 current MDD cases and 331 controls from the Netherlands Study of Depression and Anxiety (NESDA). The MDD patients were stratified according to patients with hyperphagia (characterized by increased appetite and/or weight, N = 246) or hypophagia (characterized by decreased appetite and/or weight, N = 342). Using results of differential gene expression analysis between controls and the MDD subgroups, enrichment of curated inflammatory pathways was estimated. The majority of the pathways were significantly (FDR < 0.1) enriched in the expression profiles of MDD cases with hyperphagia, including top pathways related to factors responsible for the onset of inflammatory response ('caspase', 'GATA3', 'NFAT', and 'inflammasomes' pathways). Only two pathways ('adaptive immune system' and 'IL-8- and CXCR2-mediated signaling') were enriched in the MDD with hypophagia subgroup, these were also enriched in the total current MDD group and the group with hyperphagia. This confirms the importance of inflammation in MDD pathology of patients with hyperphagia, and suggests that distinguishing more uniform MDD phenotypes can help in finding their pathophysiological basis.

Neurobiological substrates underlying the effect of genomic risk for depression on the conversion of amnestic mild cognitive impairment

Depression increases the conversion risk from amnestic mild cognitive impairment to Alzheimer's disease with unknown mechanisms. We hypothesize that the cumulative genomic risk for major depressive disorder may be a candidate cause for the increased conversion risk. Here, we aimed to investigate the predictive effect of the polygenic risk scores of major depressive disorder-specific genetic variants (PRSsMDD) on the conversion from non-depressed amnestic mild cognitive impairment to Alzheimer's disease, and its underlying neurobiological mechanisms. The PRSsMDD could predict the conversion from amnestic mild cognitive impairment to Alzheimer's disease, and amnestic mild cognitive impairment patients with high risk scores showed 16.25% higher conversion rate than those with low risk. The PRSsMDD was correlated with the left hippocampal volume, which was found to mediate the predictive effect of the PRSsMDD on the conversion of amnestic mild cognitive impairment. The major depressive disorder-specific genetic variants were mapped into genes using different strategies, and then enrichment analyses and protein-protein interaction network analysis revealed that these genes were involved in developmental process and amyloid-beta binding. They showed temporal-specific expression in the hippocampus in middle and late foetal developmental periods. Cell type-specific expression analysis of these genes demonstrated significant over-representation in the pyramidal neurons and interneurons in the hippocampus. These cross-scale neurobiological analyses and functional annotations indicate that major depressive disorder-specific genetic variants may increase the conversion from amnestic mild cognitive impairment to Alzheimer's disease by modulating the early hippocampal development and amyloid-beta binding. The PRSsMDD could be used as a complementary measure to select patients with amnestic mild cognitive impairment with high conversion risk to Alzheimer's disease.

Increased serum levels of leptin and insulin in both schizophrenia and major depressive disorder: A cross-disorder proteomics analysis

We investigated whether there are similar serum alterations in schizophrenia and major depressive disorder (MDD). We investigated serum analytes in two epidemiological studies on schizophrenia (N = 121) and MDD (N = 1172) versus controls. Serum analytes (N = 109) were measured with a multi-analyte profiling platform and analysed using linear regression models, adjusted for site, age, gender, ethnicity, anti-inflammatory agents, smoking, cardiovascular disease and diabetes, and adjusted for multiple comparisons. An increase in leptin and insulin levels was observed for both schizophrenia patients (Cohen's d (d): 0.26 and 0.65, respectively) and MDD patients (d: 0.29 and 0.12, respectively) compared to their respective controls. Lower angiopoietin-2 levels were seen in both schizophrenia (d: -0.22) and MDD (d: -0.13). Four analytes differed in only schizophrenia patients (increased levels of C-peptide and prolactin, and decreased levels of CD5 antigen-like and sex hormone binding globulin) and one analyte differed in only MDD patients (increased angiotensinogen levels) compared to their respective controls. Restricting analyses to patients with a current episode of disease showed even more marked elevations of insulin and leptin. Our results suggest the presence of insulin and leptin resistance as cross-disorder mechanisms that could contribute to the higher somatic comorbidity and decreased life-span seen in both disorders.

Data-driven biological subtypes of depression: systematic review of biological approaches to depression subtyping

Research into major depressive disorder (MDD) is complicated by population heterogeneity, which has motivated the search for more homogeneous subtypes through data-driven computational methods to identify patterns in data. In addition, data on biological differences could play an important role in identifying clinically useful subtypes. This systematic review aimed to summarize evidence for biological subtypes of MDD from data-driven studies. We undertook a systematic literature search of PubMed, PsycINFO, and Embase (December 2018). We included studies that identified (1) data-driven subtypes of MDD based on biological variables, or (2) data-driven subtypes based on clinical features (e.g., symptom patterns) and validated these with biological variables post-hoc. Twenty-nine publications including 24 separate analyses in 20 unique samples were identified, including a total of ~ 4000 subjects. Five out of six biochemical studies indicated that there might be depression subtypes with and without disturbed neurotransmitter levels, and one indicated there might be an inflammatory subtype. Seven symptom-based studies identified subtypes, which were mainly determined by severity and by weight gain vs. loss. Two studies compared subtypes based on medication response. These symptom-based subtypes were associated with differences in biomarker profiles and functional connectivity, but results have not sufficiently been replicated. Four out of five neuroimaging studies found evidence for groups with structural and connectivity differences, but results were inconsistent. The single genetic study found a subtype with a distinct pattern of SNPs, but this subtype has not been replicated in an independent test sample. One study combining all aforementioned types of data discovered a subtypes with different levels of functional connectivity, childhood abuse, and treatment response, but the sample size was small. Although the reviewed work provides many leads for future research, the methodological differences across studies and lack of replication preclude definitive conclusions about the existence of clinically useful and generalizable biological subtypes.

Cholinergic regulation of mood: from basic and clinical studies to emerging therapeutics

Mood disorders are highly prevalent and are the leading cause of disability worldwide. The neurobiological mechanisms underlying depression remain poorly understood, although theories regarding dysfunction within various neurotransmitter systems have been postulated. Over 50 years ago, clinical studies suggested that increases in central acetylcholine could lead to depressed mood. Evidence has continued to accumulate suggesting that the cholinergic system has a important role in mood regulation. In particular, the finding that the antimuscarinic agent, scopolamine, exerts fast-onset and sustained antidepressant effects in depressed humans has led to a renewal of interest in the cholinergic system as an important player in the neurochemistry of major depression and bipolar disorder. Here, we synthesize current knowledge regarding the modulation of mood by the central cholinergic system, drawing upon studies from human postmortem brain, neuroimaging, and drug challenge investigations, as well as animal model studies. First, we describe an illustrative series of early discoveries which suggest a role for acetylcholine in the pathophysiology of mood disorders. Then, we discuss more recent studies conducted in humans and/or animals which have identified roles for both acetylcholinergic muscarinic and nicotinic receptors in different mood states, and as targets for novel therapies.

The effect of genetic vulnerability and military deployment on the development of post-traumatic stress disorder and depressive symptoms

Exposure to trauma strongly increases the risk to develop stress-related psychopathology, such as post-traumatic stress disorder (PTSD) or major depressive disorder (MDD). In addition, liability to develop these moderately heritable disorders is partly determined by common genetic variance, which is starting to be uncovered by genome-wide association studies (GWASs). However, it is currently unknown to what extent genetic vulnerability and trauma interact. We investigated whether genetic risk based on summary statistics of large GWASs for PTSD and MDD predisposed individuals to report an increase in MDD and PTSD symptoms in a prospective military cohort (N = 516) at five time points after deployment to Afghanistan: one month, six months and one, two and five years. Linear regression was used to analyze the contribution of polygenic risk scores (PRSs, at multiple p-value thresholds) and their interaction with deployment-related trauma to the development of PTSD- and depression-related symptoms. We found no main effects of PRSs nor evidence for interactions with trauma on the development of PTSD or depressive symptoms at any of the time points in the five years after military deployment. Our results based on a unique long-term follow-up of a deployed military cohort suggest limited validity of current PTSD and MDD polygenic risk scores, albeit in the presence of minimal severe psychopathology in the target cohort. Even though the predictive value of PRSs will likely benefit from larger sample sizes in discovery and target datasets, progress will probably also depend on (endo)phenotype refinement that in turn will reduce etiological heterogeneity.

GWAS and Beyond: Using Omics Approaches to Interpret SNP Associations

PURPOSE OF REVIEW

Neurodegenerative diseases, neuropsychiatric disorders, and related traits have highly complex etiologies but are also highly heritable and identifying the causal genes and biological pathways underlying these traits may advance the development of treatments and preventive strategies. While many genome-wide association studies (GWAS) have successfully identified variants contributing to polygenic neurodegenerative and neuropsychiatric phenotypes including Alzheimer's disease (AD), schizophrenia (SCZ), and bipolar disorder (BPD) amongst others, interpreting the biological roles of significantly-associated variants in the genetic architecture of these traits remains a significant challenge. Here we review several 'omics' approaches which attempt to bridge the gap from associated genetic variants to phenotype by helping define the functional roles of GWAS loci in the development of neuropsychiatric disorders and traits.

RECENT FINDINGS

Several common 'omics' approaches have been applied to examine neuropsychiatric traits, such as nearest-gene mapping, trans-ethnic fine mapping, annotation enrichment analysis, transcriptomic analysis, and pathway analysis, and each of these approaches has strengths and limitations in providing insight into biological mechanisms. One popular emerging method is the examination of tissue-specific genetically-regulated gene expression (GReX), which aggregates the genetic variants' effects at the gene-level. Furthermore, proteomic, metabolomic, and microbiomic studies and phenome-wide association studies will further enhance our understanding of neuropsychiatric traits.

SUMMARY

GWAS has been applied to neuropsychiatric traits for a decade, but our understanding about the biological function of identified variants remains limited. Today, technological advancements have created analytical approaches for integrating transcriptomics, metabolomics, proteomics, pharmacology and toxicology as tools for understanding the functional roles of genetics variants. These data, as well as the broader clinical information provided by electronic health records, can provide additional insight and complement genomic analyses.

[Genetic comorbidity of depression and somatic disorders]

The aim of our review was to evaluate the perspectives of new therapeutic approaches in comorbid depressive and somatic disorders based on common pathological mechanisms and their genetic risk factors. Literature analysis showed that depression was a complex heterogeneous condition associated with significant prevalence of metabolic, cardiovascular and immune disturbances. The understanding of common molecular mechanisms of risks and course of abovementioned disorders could provide a new strategy for early diagnosis and therapeutic optimization and give the opportunity of 'targeted' approach to different pathological elements.

Depression and obesity: evidence of shared biological mechanisms

Depression and obesity are common conditions with major public health implications that tend to co-occur within individuals. The relationship between these conditions is bidirectional: the presence of one increases the risk for developing the other. It has thus become crucial to gain a better understanding of the mechanisms responsible for the intertwined downward physiological spirals associated with both conditions. The present review focuses specifically on shared biological pathways that may mechanistically explain the depression-obesity link, including genetics, alterations in systems involved in homeostatic adjustments (HPA axis, immuno-inflammatory activation, neuroendocrine regulators of energy metabolism including leptin and insulin, and microbiome) and brain circuitries integrating homeostatic and mood regulatory responses. Furthermore, the review addresses interventional opportunities and questions to be answered by future research that will enable a comprehensive characterization and targeting of the biological links between depression and obesity.

The Association Between the Sedative Loads and Clinical Severity Indicators in the First-Onset Major Depressive Disorder

Background: High sedative use in a major depressive episode may imply specific clinical features. This study aims to examine the correlation between sedative use and clinical severity indicators in the initial treatment phase of first-onset major depressive disorder. Methods: A study cohort in the first episode of major depressive disorder was used to conduct pharmacological dissection. All participants had at least a 2-year follow-up period with a complete treatment record. The defined daily dose of antidepressants and augmentation agents were calculated as the antidepressant load and augmentation load, respectively. Sedative use, which was calculated as the equivalent dosage of lorazepam, were defined as the sedative load. These psychotropic loads were measured monthly and the averaged psychotropic loads for each day were obtained. Results: A total of 106 individuals (75.5% female) were included. The mean duration of disease course in participants was 5.5 ± 3.5 years. In the multiple regression analysis, after controlling for other classes of psychotropics and comorbid anxiety disorders, the sedative load independently correlated with higher number of antidepressants used, higher number of antidepressant used with an adequate dose and duration, more psychiatric emergency and outpatient visits within 2 years of disease onset. Conclusion: High loading of sedatives correlated with several indicators of clinical severity in major depressive disorder. The sedative load may be used as a specifier to identify subgroups in patients with major depressive disorder.

Depression and eating styles are independently associated with dietary intake

Depression and eating styles are two important, interrelated factors associated with dietary intake. However, it remains unclear whether depression and eating styles are independently associated with dietary intake, and whether associations between depression and dietary intake are mediated by eating styles. Therefore, the aim of the current study was to investigate the associations of, and interplay between depression and eating styles in relation to different aspects of dietary intake. Cross-sectional data from 1442 participants (healthy controls (22.7%), remitted (61.0%) and current patients (16.3%)) from the Netherlands Study of Depression and Anxiety were used. Linear regression analyses were used to determine associations of depressive disorders (DSM-IV based psychiatric interview), self-reported depressive symptoms (Inventory of Depressive Symptomatology), emotional, external and restrained eating (Dutch Eating Behavior Questionnaire) with 4 measures of dietary intake (total energy intake (kcal/d), Mediterranean diet score (MDS), intake of sweets foods (g/d), and snack/fast-food (g/d)) measured with a 238-item food frequency questionnaire. Statistical mediation analyses were used to study whether associations between depression and dietary intake were mediated by eating styles. Current depression diagnosis and severity were associated with lower MDS and higher intake of sweet foods and snack/fast-food. Emotional and external eating were associated with higher intakes of snack/fast-food; external eating was also associated with higher total energy intake. Restrained eating was associated with lower total energy and intake of sweet foods, and higher MDS. Associations between current depression or severity and intake of snack/fast-food were mediated by external eating. In general, depression and eating styles contributed independently to poorer diet quality and higher intake of sweet and snack/fast-food. The association between depression and higher intake of snack/fast-food was mediated by external eating.

The prognostic role of depression as a predictor of chronic somatic diseases manifestation

The negative impact of depression on the course and outcome of somatic disorders is well-known and has a solid theoretical basis. The analyses of prospective studies confirm the role of depression as an independent and significant risk factor for widespread chronic somatic disorders including such severe and life-threatening conditions as cardiovascular diseases, diabetes and oncological pathology. The majority of somatic disorders and depression are the part of the big class of hereditary diseases with multifactorial character and polygenic nature. It is likely, that the genetic risk diversity of these diseases in population is close. There is also a high probability of genetic risks levels overlap (or of common «cluster») of two or more diseases in one individual, with one disorder being major depression. In that case such diseases could be considered «genetically comorbid» and manifestation of one disease could alter the risks of other. Precise and informative diagnostic tools could detect subsyndromal depression that could be the prognostic sign of the high risk and rapid manifestation of somatic diseases. Thus, patients with depressive disorder could be considered as a group with high risks of diverse range of somatic pathology. The coalescence of fundamental biomedical scientists and internists (psychiatrists and other physicians) could lead to the elaboration of specific complex preventative measures including social ones.

[The current state and future prospects of depression research (clinical and classification problems)]

Despite decades of research, neurobiological studies of depression haven't achieved significant results. Many experts propose that one of the main reasons for this failure is current diagnostic standards not considering the heterogeneity and polymorphism of depression. Research is unable to identify specific neurobiological changes due to formal diagnosis 'major depressive disorder' and new diagnostic criteria are needed. RDoC (Research Domain Criteria) has intensified the confrontation between biological and clinical researchers and changes in approach to depressive psychopathology are discussed. A review presents the recent approaches used in studies of depressive disorders, the methodology they use, the scientific paradigms they rely on.

Metabolic syndrome in psychiatric patients: overview, mechanisms, and implications

Psychiatric patients have a greater risk of premature mortality, predominantly due to cardiovascular diseases (CVDs). Convincing evidence shows that psychiatric conditions are characterized by an increased risk of metabolic syndrome (MetS), a clustering of cardiovascular risk factors including dyslipidemia, abdominal obesity, hypertension, and hyperglycemia. This increased risk is present for a range of psychiatric conditions, including major depressive disorder (MDD), bipolar disorder (BD), schizophrenia, anxiety disorder, attention-deficit/hyperactivity disorder (ADHD), and posttraumatic stress disorder (PTSD). There is some evidence for a dose-response association with the severity and duration of symptoms and for a bidirectional longitudinal impact between psychiatric disorders and MetS. Associations generally seem stronger with abdominal obesity and dyslipidemia dysregulations than with hypertension. Contributing mechanisms are an unhealthy lifestyle and a poor adherence to medical regimen, which are prevalent among psychiatric patients. Specific psychotropic medications have also shown a profound impact in increasing MetS dysregulations. Finally, pleiotropy in genetic vulnerability and pathophysiological mechanisms, such as those leading to the increased central and peripheral activation of immunometabolic or endocrine systems, plays a role in both MetS and psychiatric disorder development. The excess risk of MetS and its unfavorable somatic health consequences justifies a high priority for future research, prevention, close monitoring, and treatment to reduce MetS in the vulnerable psychiatric patient.

Health, pre-disease and critical transition to disease in the psycho-immune-neuroendocrine network: Are there distinct states in the progression from health to major depressive disorder?

The psycho-immune-neuroendocrine (PINE) network is a regulatory network of interrelated physiological pathways that have been implicated in major depressive disorder (MDD). A model of disease progression for MDD is presented where the stable, healthy state of the PINE network (PINE physiome) undergoes progressive pathophysiological changes to an unstable but reversible pre-disease state (PINE pre-diseasome) with chronic stress. The PINE network may then undergo critical transition to a stable, possibly irreversible disease state of MDD (PINE pathome). Critical transition to disease is heralded by early warning signs which are detectible by biomarkers specific to the PINE network and may be used as a screening test for MDD. Critical transition to MDD may be different for each individual, as it is reliant on diathesis, which comprises genetic predisposition, intrauterine and developmental factors. Finally, we propose the PINE pre-disease state may form a "universal pre-disease state" for several non-communicable diseases (NCDs), and critical transition of the PINE network may lead to one of several frequently associated disease states (influenced by diathesis), supporting the existence of a common Chronic Illness Risk Network (CIRN). This may provide insight into both the puzzle of multifinality and the growing clinical challenge of multimorbidity.

Blood and urinary metabolomic evidence validating traditional Chinese medicine diagnostic classification of major depressive disorder

Background

Major depressive disorder (MDD) is a highly heterogeneous disease. Further classification may characterize its heterogeneity. The purpose of this study was to examine whether metabolomic variables could differentiate traditional Chinese medicine (TCM) diagnostic subtypes of MDD.

Methods

Fifty medication-free patients who were experiencing a recurrent depressive episode were classified into Liver Qi Stagnation (LQS, n = 30) and Heart and Spleen Deficiency (HSD, n = 20) subtypes according to TCM diagnosis. Healthy volunteers (n = 28) were included as controls. Gas chromatography-mass spectrometry (GC–MS) was used to examine serum and urinary metabolomic profiles.

Results

Twenty-eight metabolites were identified for good separations between TCM subtypes and healthy controls in serum samples. Both TCM subtypes had similar profiles in proteinogenic branched-chain amino acids (BCAAs) (valine, leucine, and isoleucine) and energy metabolism-related metabolites that were differentiated from healthy controls. The LQS subtype additionally differed from healthy controls in multiple amino acid metabolites that are involved in biosynthesis of monoamine and amino acid neurotransmitters, including phenylalanine, 3-hydroxybutric acid, o-tyrosine, glycine, l-tryptophan, and N-acetyl-l-aspartic acid. Threonic acid, methionine, stearic acid, and isobutyric acid are differentially associated with the two subtypes.

Conclusions

While both TCM subtypes are associated with aberrant BCAA and energy metabolism, the LQS subtype may represent an MDD subpopulation characterized by abnormalities in the biosynthesis of monoamine and amino acid neurotransmitters and closer associations with stress-related pathophysiology. The metabolites differentially associated with the two subtypes are promising biomarkers for predicting TCM subtype-specific antidepressant response [registered at http://www.clinicaltrials.gov (NCT02346682) on January 27, 2015].

Electronic supplementary material

The online version of this article (10.1186/s13020-018-0211-z) contains supplementary material, which is available to authorized users.

Effects of genetic deletion versus pharmacological blockade of the LPA1 receptor on depression-like behaviour and related brain functional activity

Animal models of psychopathology are particularly useful for studying the neurobiology of depression and characterising the subtypes. Recently, our group was the first to identify a possible relationship between the LPA₁ receptor and a mixed anxiety-depression phenotype. Specifically, maLPA₁-null mice exhibited a phenotype characterised by depressive and anxious features. However, the constitutive lack of the gene encoding the LPA₁ receptor (Lpar1) can induce compensatory mechanisms that might have resulted in the observed deficits. Therefore, in the present study, we have compared the impact of permanent loss and acute pharmacological inhibition of the LPA₁ receptor on despair-like behaviours and on the functional brain map associated with these behaviours, as well as on the degree of functional connectivity among structures. Although the antagonist (intracerebroventricularly administered Ki16425) mimicked some, but not all, effects of genetic deletion of the LPA₁ receptor on the results of behavioural tests and engaged different brain circuits, both treatments induced depression-like behaviours with an agitation component that was linked to functional changes in key brain regions involved in the stress response and emotional regulation. In addition, both Ki16425 treatment and LPA₁ receptor deletion modified the functional brain maps in a way similar to the changes observed in depressed patients. In summary, the pharmacological and genetic approaches could ultimately assist in dissecting the function of the LPA₁ receptor in emotional regulation and brain responses, and a combination of those approaches might provide researchers with an opportunity to develop useful drugs that target the LPA₁ receptor as treatments for depression, mainly the anxious subtype.

This article has an associated First Person interview with the first author of the paper.

Summary: Animal models of psychopathology are useful for studying the neurobiology of depression. Here, we have assessed by pharmacological approach and knockout models the contribution of the LPA-LPA₁ signalling pathway to anxious depression.

PRS-on-Spark (PRSoS): a novel, efficient and flexible approach for generating polygenic risk scores

BACKGROUND

Polygenic risk scores (PRS) describe the genomic contribution to complex phenotypes and consistently account for a larger proportion of variance in outcome than single nucleotide polymorphisms (SNPs) alone. However, there is little consensus on the optimal data input for generating PRS, and existing approaches largely preclude the use of imputed posterior probabilities and strand-ambiguous SNPs i.e., A/T or C/G polymorphisms. Our ability to predict complex traits that arise from the additive effects of a large number of SNPs would likely benefit from a more inclusive approach.

RESULTS

We developed PRS-on-Spark (PRSoS), a software implemented in Apache Spark and Python that accommodates different data inputs and strand-ambiguous SNPs to calculate PRS. We compared performance between PRSoS and an existing software (PRSice v1.25) for generating PRS for major depressive disorder using a community cohort (N = 264). We found PRSoS to perform faster than PRSice v1.25 when PRS were generated for a large number of SNPs (~ 17 million SNPs; t = 42.865, p = 5.43E-04). We also show that the use of imputed posterior probabilities and the inclusion of strand-ambiguous SNPs increase the proportion of variance explained by a PRS for major depressive disorder (from 4.3% to 4.8%).

CONCLUSIONS

PRSoS provides the user with the ability to generate PRS using an inclusive and efficient approach that considers a larger number of SNPs than conventional approaches. We show that a PRS for major depressive disorder that includes strand-ambiguous SNPs, calculated using PRSoS, accounts for the largest proportion of variance in symptoms of depression in a community cohort, demonstrating the utility of this approach. The availability of this software will help users develop more informative PRS for a variety of complex phenotypes.

Examining neural correlates of psychopathology using a lesion-based approach

Studies of individuals with focal brain damage have long been used to expand understanding of the neural basis of psychopathology. However, most previous studies were conducted using small sample sizes and relatively coarse methods for measuring psychopathology or mapping brain-behavior relationships. Here, we examined the factor structure and neural correlates of psychopathology in 232 individuals with focal brain damage, using their responses to the Minnesota Multiphasic Personality Inventory-2-Restructured Form (MMPI-2-RF). Factor analysis and voxel-based lesion symptom mapping were used to examine the structure and neural correlates of psychopathology in this sample. Consistent with existing MMPI-2-RF literature, separate internalizing, externalizing, and psychotic symptom dimensions were found. In addition, a somatic dimension likely reflecting neurological symptoms was identified. Damage to the medial temporal lobe, including the hippocampus, was associated with scales related to both internalizing problems and psychoticism. Damage to the medial temporal lobe and orbitofrontal cortex was associated with both a general distrust of others and beliefs that one is being personally targeted by others. These findings provide evidence for the critical role of dysfunction in specific frontal and temporal regions in the development of psychopathology.

The use of latent class analysis for identifying subtypes of depression: A systematic review

Depression is a significant public health problem but symptom remission is difficult to predict. This may be due to substantial heterogeneity underlying the disorder. Latent class analysis (LCA) is often used to elucidate clinically relevant depression subtypes but whether or not consistent subtypes emerge is unclear. We sought to critically examine the implementation and reporting of LCA in this context by performing a systematic review to identify articles detailing the use of LCA to explore subtypes of depression among samples of adults endorsing depression symptoms. PubMed, PsycINFO, CINAHL, Scopus, and Google Scholar were searched to identify eligible articles indexed prior to January 2016. Twenty-four articles reporting 28 LCA models were eligible for inclusion. Sample characteristics varied widely. The majority of articles used depression symptoms as the observed indicators of the latent depression subtypes. Details regarding model fit and selection were often lacking. No consistent set of depression subtypes was identified across studies. Differences in how models were constructed might partially explain the conflicting results. Standards for using, interpreting, and reporting LCA models could improve our understanding of the LCA results. Incorporating dimensions of depression other than symptoms, such as functioning, may be helpful in determining depression subtypes.

Does Childhood Trauma Moderate Polygenic Risk for Depression? A Meta-analysis of 5765 Subjects From the Psychiatric Genomics Consortium

BACKGROUND

The heterogeneity of genetic effects on major depressive disorder (MDD) may be partly attributable to moderation of genetic effects by environment, such as exposure to childhood trauma (CT). Indeed, previous findings in two independent cohorts showed evidence for interaction between polygenic risk scores (PRSs) and CT, albeit in opposing directions. This study aims to meta-analyze MDD-PRS × CT interaction results across these two and other cohorts, while applying more accurate PRSs based on a larger discovery sample.

METHODS

Data were combined from 3024 MDD cases and 2741 control subjects from nine cohorts contributing to the MDD Working Group of the Psychiatric Genomics Consortium. MDD-PRS were based on a discovery sample of ∼110,000 independent individuals. CT was assessed as exposure to sexual or physical abuse during childhood. In a subset of 1957 cases and 2002 control subjects, a more detailed five-domain measure additionally included emotional abuse, physical neglect, and emotional neglect.

RESULTS

MDD was associated with the MDD-PRS (odds ratio [OR] = 1.24, p = 3.6 × 10-5, R2 = 1.18%) and with CT (OR = 2.63, p = 3.5 × 10-18 and OR = 2.62, p = 1.4 ×10-5 for the two- and five-domain measures, respectively). No interaction was found between MDD-PRS and the two-domain and five-domain CT measure (OR = 1.00, p = .89 and OR = 1.05, p = .66).

CONCLUSIONS

No meta-analytic evidence for interaction between MDD-PRS and CT was found. This suggests that the previously reported interaction effects, although both statistically significant, can best be interpreted as chance findings. Further research is required, but this study suggests that the genetic heterogeneity of MDD is not attributable to genome-wide moderation of genetic effects by CT.

Diagnosis of major depressive disorder based on changes in multiple plasma neurotransmitters: a targeted metabolomics study

Major depressive disorder (MDD) is a debilitating psychiatric illness. However, there is currently no objective laboratory-based diagnostic tests for this disorder. Although, perturbations in multiple neurotransmitter systems have been implicated in MDD, the biochemical changes underlying the disorder remain unclear, and a comprehensive global evaluation of neurotransmitters in MDD has not yet been performed. Here, using a GC-MS coupled with LC-MS/MS-based targeted metabolomics approach, we simultaneously quantified the levels of 19 plasma metabolites involved in GABAergic, catecholaminergic, and serotonergic neurotransmitter systems in 50 first-episode, antidepressant drug-naïve MDD subjects and 50 healthy controls to identify potential metabolite biomarkers for MDD (training set). Moreover, an independent sample cohort comprising 49 MDD patients, 30 bipolar disorder (BD) patients and 40 healthy controls (testing set) was further used to validate diagnostic generalizability and specificity of these candidate biomarkers. Among the 19 plasma neurotransmitter metabolites examined, nine were significantly changed in MDD subjects. These metabolites were mainly involved in GABAergic, catecholaminergic and serotonergic systems. The GABAergic and catecholaminergic had better diagnostic value than serotonergic pathway. A panel of four candidate plasma metabolite biomarkers (GABA, dopamine, tyramine, kynurenine) could distinguish MDD subjects from health controls with an AUC of 0.968 and 0.953 in the training and testing set, respectively. Furthermore, this panel distinguished MDD subjects from BD subjects with high accuracy. This study is the first to globally evaluate multiple neurotransmitters in MDD plasma. The altered plasma neurotransmitter metabolite profile has potential differential diagnostic value for MDD.

Inflammatory markers and cortisol parameters across depressive subtypes in an older cohort

BACKGROUND

There is growing evidence that inflammatory and cortisol dysregulation are underlying pathophysiological mechanisms in the aetiology of major depressive disorder, particularly in younger adults. However, findings of biological disturbances in late-life depression have been divergent, probably due to the even greater heterogeneity of depression in older adults with aging processes influencing biological factors. Using empirically derived subtypes may enable the identification of biological disturbances underlying depression in older adults.

METHODS

Data were used from the Netherlands Study of Depression in Older Persons (NESDO) of 359 persons aged 60 years or older, with a current diagnosis of major depressive disorder (MDD). Depressive subtypes (severe atypical, severe melancholic, and moderate severe subtype) that were previously identified through latent class analysis (LCA), were examined on differences in inflammatory markers including C-reactive protein (CRP), interleukin-6 (IL-6), and neutrophil gelatinase-associated lipocalin (NGAL), as well as cortisol parameters.

RESULTS

No differences in measures for inflammation and cortisol across subtypes were observed in uncorrected or for putative confounders corrected models.

LIMITATIONS

Several subjects had missing cortisol and inflammatory data, decreasing the power. However, results did not change after imputation analysis.

DISCUSSION

In this cohort of depressed older adults, no differences in inflammation and cortisol measures between depression subtypes were observed. This is probably due to the many (patho)physiological processes that are involved in aging, thereby clouding the results.

The use of polygenic risk scores to identify phenotypes associated with genetic risk of bipolar disorder and depression: A systematic review

BACKGROUND

Identifying the phenotypic manifestations of increased genetic liability for depression (MDD) and bipolar disorder (BD) can enhance understanding of their aetiology. The polygenic risk score (PRS) derived using data from genome-wide-association-studies can be used to explore how genetic risk is manifest in different samples.

AIMS

In this systematic review, we review studies that examine associations between the MDD and BD polygenic risk scores and phenotypic outcomes.

METHODS

Following PRISMA guidelines, we searched EMBASE, Medline and PsycINFO (from August 2009 - 14th March 2016) and references of included studies. Study inclusion was based on predetermined criteria and data were extracted independently and in duplicate.

RESULTS

Twenty-five studies were included. Overall, both polygenic risk scores were associated with other psychiatric disorders (not the discovery sample disorder) such as depression, schizophrenia and bipolar disorder, greater symptom severity of depression, membership of a creative profession and greater educational attainment. Both depression and bipolar polygenic risk scores explained small amounts of variance in most phenotypes (< 2%).

LIMITATIONS

Many studies did not report standardised effect sizes. This prevented us from conducting a meta-analysis.

CONCLUSIONS

Polygenic risk scores for BD and MDD are associated with a range of phenotypes and outcomes. However, they only explain a small amount of the variation in these phenotypes. Larger discovery and adequately powered target samples are required to increase power of the PRS approach. This could elucidate how genetic risk for bipolar disorder and depression is manifest and contribute meaningfully to stratified medicine.

The use of polygenic risk scores to identify phenotypes associated with genetic risk of schizophrenia: Systematic review

Studying the phenotypic manifestations of increased genetic liability for schizophrenia can increase our understanding of this disorder. Specifically, information from alleles identified in genome-wide association studies can be collapsed into a polygenic risk score (PRS) to explore how genetic risk is manifest within different samples. In this systematic review, we provide a comprehensive assessment of studies examining associations between schizophrenia PRS (SZ-PRS) and several phenotypic measures. We searched EMBASE, Medline and PsycINFO (from August 2009-14th March 2016) plus references of included studies, following PRISMA guidelines. Study inclusion was based on predetermined criteria and data were extracted independently and in duplicate. Overall, SZ-PRS was associated with increased risk for psychiatric disorders such as depression and bipolar disorder, lower performance IQ and negative symptoms. SZ-PRS explained up to 6% of genetic variation in psychiatric phenotypes, compared to <0.7% in measures of cognition. Future gains from using the PRS approach may be greater if used for examining phenotypes that are more closely related to biological substrates, for scores based on gene-pathways, and where PRSs are used to stratify individuals for study of treatment response. As it was difficult to interpret findings across studies due to insufficient information provided by many studies, we propose a framework to guide robust reporting of PRS associations in the future.

Latent class cluster analysis of symptom ratings identifies distinct subgroups within the clinical high risk for psychosis syndrome

The clinical-high-risk for psychosis (CHR-P) syndrome is heterogeneous in terms of clinical presentation and outcomes. Identifying more homogenous subtypes of the syndrome may help clarify its etiology and improve the prediction of psychotic illness. This study applied latent class cluster analysis (LCCA) to symptom ratings from the North American Prodrome Longitudinal Studies 1 and 2 (NAPLS 1 and 2). These analyses produced evidence for three to five subgroups within the CHR-P syndrome. Differences in negative and disorganized symptoms distinguished among the subgroups. Subgroup membership was found to predict conversion to psychosis. The authors contrast the methods employed within this study with previous attempts to identify more homogenous subgroups of CHR-P individuals and discuss how these results could be tested in future samples of CHR-P individuals.

The association between depression and eating styles in four European countries: The MooDFOOD prevention study

OBJECTIVE

Depression, one of the most prevalent and disabling disorders in Europe, is thought to be associated with unhealthy eating styles. As prevalence of depression and eating styles potentially differ across Europe, the current study aimed to investigate in a large, European sample, the associations of history of major depressive disorder and depression severity with unhealthy eating styles.

METHODS

Baseline data of the MooDFOOD prevention study was used. The current analysis included 990 participants of four European countries (The Netherlands, United Kingdom, Germany, Spain). Analyses of Covariance and linear regression analyses were performed with depression history or depression severity as determinants, and emotional, uncontrolled, and cognitive restrained eating (Three Factor Eating Questionnaire Revised, 18 item) as outcomes.

RESULTS

Depression history and severity were associated with more emotional and uncontrolled eating and with less cognitive restrained eating. Mood, somatic, and cognitive symptom clusters were also associated with more emotional and uncontrolled eating, and with less cognitive restrained eating. The somatic depressive symptoms "increased appetite" and "increased weight" were more strongly associated to unhealthy eating styles compared to other symptoms. No differences in associations between depression and unhealthy eating were found between European countries.

CONCLUSION

Our results suggest that depression is related to more unhealthy eating styles. Diminishing unhealthy eating styles in subthreshold depressed persons could potentially reduce adverse health consequences like weight gain, unhealthy dietary patterns and weight-related diseases. It is also possible that interventions that decrease depressive symptoms can lead to a decrease in unhealthy eating styles.

Metabolic and inflammatory markers: associations with individual depressive symptoms

BACKGROUND

Literature has shown that obesity, metabolic syndrome and inflammation are associated with depression, however, evidence suggests that these associations are specific to atypical depression. Which of the atypical symptoms are driving associations with obesity-related outcomes and inflammation is unknown. We evaluated associations between individual symptoms of depression (both atypical and non-atypical) and body mass index (BMI), metabolic syndrome components and inflammatory markers.

METHODS

We included 808 persons with a current diagnosis of depression participating in the Netherlands Study of Depression and Anxiety (67% female, mean age 41.6 years). Depressive symptoms were derived from the Composite International Diagnostic Interview and the Inventory of Depressive Symptomatology. Univariable and multivariable regression analyses adjusting for sex, age, educational level, depression severity, current smoking, physical activity, anti-inflammatory medication use, and statin use were performed.

RESULTS

Increased appetite was positively associated with BMI, number of metabolic syndrome components, waist circumference, C-reactive protein and tumor necrosis factor-α. Decreased appetite was negatively associated with BMI and waist circumference. Psychomotor retardation was positively associated with BMI, high-density lipoprotein cholesterol and triglycerides, and insomnia with number of metabolic syndrome components.

CONCLUSION

Increased appetite - in the context of a depressive episode - was the only symptom that was associated with both metabolic as well as inflammatory markers, and could be a key feature of an immuno-metabolic form of depression. This immuno-metabolic depression should be considered in clinical trials evaluating effectiveness of compounds targeting metabolic and inflammatory pathways or lifestyle interventions.

The Genetics of Treatment-Resistant Depression: A Critical Review and Future Perspectives

BACKGROUND

One-third of depressed patients develop treatment-resistant depression with the related sequelae in terms of poor functionality and worse prognosis. Solid evidence suggests that genetic variants are potentially valid predictors of antidepressant efficacy and could be used to provide personalized treatments.

METHODS

The present review summarizes genetic findings of treatment-resistant depression including results from candidate gene studies and genome-wide association studies. The limitations of these approaches are discussed, and suggestions to improve the design of future studies are provided.

RESULTS

Most studies used the candidate gene approach, and few genes showed replicated associations with treatment-resistant depression and/or evidence obtained through complementary approaches (e.g., gene expression studies). These genes included GRIK4, BDNF, SLC6A4, and KCNK2, but confirmatory evidence in large cohorts was often lacking. Genome-wide association studies did not identify any genome-wide significant association at variant level, but pathways including genes modulating actin cytoskeleton, neural plasticity, and neurogenesis may be associated with treatment-resistant depression, in line with results obtained by genome-wide association studies of antidepressant response. The improvement of aggregated tests (e.g., polygenic risk scores), possibly using variant/gene prioritization criteria, the increase in the covering of genetic variants, and the incorporation of clinical-demographic predictors of treatment-resistant depression are proposed as possible strategies to improve future pharmacogenomic studies.

CONCLUSIONS

Genetic biomarkers to identify patients with higher risk of treatment-resistant depression or to guide treatment in these patients are not available yet. Methodological improvements of future studies could lead to the identification of genetic biomarkers with clinical validity.

Novel functional variants at the GWAS-implicated loci might confer risk to major depressive disorder, bipolar affective disorder and schizophrenia

BACKGROUND

A challenge of understanding the mechanisms underlying cognition including neurodevelopmental and neuropsychiatric disorders is mainly given by the potential severity of cognitive disorders for the quality of life and their prevalence. However, the field has been focused predominantly on protein coding variation until recently. Given the importance of tightly controlled gene expression for normal brain function, the goal of the study was to assess the functional variation including non-coding variation in human genome that is likely to play an important role in cognitive functions. To this end, we organized and utilized available genome-wide datasets from genomic, transcriptomic and association studies into a comprehensive data corpus. We focused on genomic regions that are enriched in regulatory activity-overlapping transcriptional factor binding regions and repurpose our data collection especially for identification of the regulatory SNPs (rSNPs) that showed associations both with allele-specific binding and allele-specific expression. We matched these rSNPs to the nearby and distant targeted genes and then selected the variants that could implicate the etiology of cognitive disorders according to Genome-Wide Association Studies (GWAS). Next, we use DeSeq 2.0 package to test the differences in the expression of the certain targeted genes between the controls and the patients that were diagnosed bipolar affective disorder and schizophrenia. Finally, we assess the potential biological role for identified drivers of cognition using DAVID and GeneMANIA.

RESULTS

As a result, we selected fourteen regulatory SNPs locating within the loci, implicated from GWAS for cognitive disorders with six of the variants unreported previously. Grouping of the targeted genes according to biological functions revealed the involvement of processes such as 'posttranscriptional regulation of gene expression', 'neuron differentiation', 'neuron projection development', 'regulation of cell cycle process' and 'protein catabolic processes'. We identified four rSNP-targeted genes that showed differential expression between patient and control groups depending on brain region: NRAS-in schizophrenia cohort, CDC25B, DDX21 and NUCKS1-in bipolar disorder cohort.

CONCLUSIONS

Overall, our findings are likely to provide the keys for unraveling the mechanisms that underlie cognitive functions including major depressive disorder, bipolar disorder and schizophrenia etiopathogenesis.

Genome-wide association study of depression phenotypes in UK Biobank identifies variants in excitatory synaptic pathways

Depression is a polygenic trait that causes extensive periods of disability. Previous genetic studies have identified common risk variants which have progressively increased in number with increasing sample sizes of the respective studies. Here, we conduct a genome-wide association study in 322,580 UK Biobank participants for three depression-related phenotypes: broad depression, probable major depressive disorder (MDD), and International Classification of Diseases (ICD, version 9 or 10)-coded MDD. We identify 17 independent loci that are significantly associated (P < 5 × 10-8) across the three phenotypes. The direction of effect of these loci is consistently replicated in an independent sample, with 14 loci likely representing novel findings. Gene sets are enriched in excitatory neurotransmission, mechanosensory behaviour, post synapse, neuron spine and dendrite functions. Our findings suggest that broad depression is the most tractable UK Biobank phenotype for discovering genes and gene sets that further our understanding of the biological pathways underlying depression.

Regulatory T Cells As Supporters of Psychoimmune Resilience: Toward Immunotherapy of Major Depressive Disorder

There is growing evidence that inflammation plays a role in major depressive disorder (MDD). As the main role of regulatory T cells (Tregs) is to control inflammation, this might denote a Treg insufficiency in MDD. However, neither a qualitative nor a quantitative defect of Tregs has been ascertained and no causality direction between inflammation and depression has been established. Here, after reviewing the evidence supporting a relation between Treg insufficiency and MDD, we conclude that a novel therapeutic approach based on Treg stimulation could be valuable in at least the subset of patients with inflammatory MDD. Low-dose interleukin-2 appears to be a good candidate as it is not only a safe stimulator of Tregs in humans but also an inhibitor of pro-inflammatory Th17 lymphocytes. Here, we discuss that a thorough immune investigation as well as immunotherapy will be heuristic for deciphering the pathophysiology of MDD.