Metabolomics signatures of depression: the role of symptom profiles.

Depression shows a metabolomic signature overlapping with that of cardiometabolic conditions. Whether this signature is linked to specific depression profiles remains undetermined. Previous research suggested that metabolic alterations cluster more consistently with depressive symptoms of the atypical spectrum related to energy alterations, such as hyperphagia, weight gain, hypersomnia, fatigue and leaden paralysis. We characterized the metabolomic signature of an "atypical/energy-related" symptom (AES) profile and evaluated its specificity and consistency. Fifty-one metabolites measured using the Nightingale platform in 2876 participants from the Netherlands Study of Depression and Anxiety were analyzed. An 'AES profile' score was based on five items of the Inventory of Depressive Symptomatology (IDS) questionnaire. The AES profile was significantly associated with 31 metabolites including higher glycoprotein acetyls (ß = 0.13, p = 1.35*10-12), isoleucine (ß = 0.13, p = 1.45*10-10), very-low-density lipoproteins cholesterol (ß = 0.11, p = 6.19*10-9) and saturated fatty acid levels (ß = 0.09, p = 3.68*10-10), and lower high-density lipoproteins cholesterol (ß = -0.07, p = 1.14*10-4). The metabolites were not significantly associated with a summary score of all other IDS items not included in the AES profile. Twenty-five AES-metabolites associations were internally replicated using data from the same subjects (N = 2015) collected at 6-year follow-up. We identified a specific metabolomic signature-commonly linked to cardiometabolic disorders-associated with a depression profile characterized by atypical, energy-related symptoms. The specific clustering of a metabolomic signature with a clinical profile identifies a more homogenous subgroup of depressed patients at higher cardiometabolic risk, and may represent a valuable target for interventions aiming at reducing depression's detrimental impact on health.

Genetic underpinnings of sociability in the general population.

Levels of sociability are continuously distributed in the general population, and decreased sociability represents an early manifestation of several brain disorders. Here, we investigated the genetic underpinnings of sociability in the population. We performed a genome-wide association study (GWAS) of a sociability score based on four social functioning-related self-report questions from 342,461 adults in the UK Biobank. Subsequently we performed gene-wide and functional follow-up analyses. Robustness analyses were performed in the form of GWAS split-half validation analyses, as well as analyses excluding neuropsychiatric cases. Using genetic correlation analyses as well as polygenic risk score analyses we investigated genetic links of our sociability score to brain disorders and social behavior outcomes. Individuals with autism spectrum disorders, bipolar disorder, depression, and schizophrenia had a lower sociability score. The score was significantly heritable (SNP h2 of 6%). We identified 18 independent loci and 56 gene-wide significant genes, including genes like ARNTL, DRD2, and ELAVL2. Many associated variants are thought to have deleterious effects on gene products and our results were robust. The sociability score showed negative genetic correlations with autism spectrum, disorders, depression, schizophrenia, and two sociability-related traits-loneliness and social anxiety-but not with bipolar disorder or Alzheimer's disease. Polygenic risk scores of our sociability GWAS were associated with social behavior outcomes within individuals with bipolar disorder and with major depressive disorder. Variation in population sociability scores has a genetic component, which is relevant to several psychiatric disorders. Our findings provide clues towards biological pathways underlying sociability.

Metabolomic profiles discriminating anxiety from depression.

OBJECTIVE: Depression has been associated with metabolomic alterations. Depressive and anxiety disorders are often comorbid diagnoses and are suggested to share etiology. We investigated whether differential metabolomic alterations are present between anxiety and depressive disorders and which clinical characteristics of these disorders are related to metabolomic alterations. METHODS: Data were from the Netherlands Study of Depression and Anxiety (NESDA), including individuals with current comorbid anxiety and depressive disorders (N = 531), only a current depression (N = 304), only a current anxiety disorder (N = 548), remitted depressive and/or anxiety disorders (N = 897), and healthy controls (N = 634). Forty metabolites from a proton nuclear magnetic resonance lipid-based metabolomics panel were analyzed. First, we examined differences in metabolites between disorder groups and healthy controls. Next, we assessed whether depression or anxiety clinical characteristics (severity and symptom duration) were associated with metabolites. RESULTS: As compared to healthy controls, seven metabolomic alterations were found in the group with only depression, reflecting an inflammatory (glycoprotein acetyls; Cohen's d = 0.12, p = 0.002) and atherogenic-lipoprotein-related (e.g., apolipoprotein B: Cohen's d = 0.08, p = 0.03, and VLDL cholesterol: Cohen's d = 0.08, p = 0.04) profile. The comorbid group showed an attenuated but similar pattern of deviations. No metabolomic alterations were found in the group with only anxiety disorders. The majority of metabolites associated with depression diagnosis were also associated with depression severity; no associations were found with anxiety severity or disease duration. CONCLUSION: While substantial clinical overlap exists between depressive and anxiety disorders, this study suggests that altered inflammatory and atherogenic-lipoprotein-related metabolomic profiles are uniquely associated with depression rather than anxiety disorders.

Associations between depressive symptom profiles and immunometabolic characteristics in individuals with depression and their siblings.

OBJECTIVES: The present study examined associations between immunometabolic characteristics (IMCs) and depressive symptom profiles (DSPs) in probands with lifetime diagnoses of depression and/or anxiety disorders and their siblings. METHODS: Data were from the Netherlands Study of Depression and Anxiety, comprising 256 probands with lifetime diagnoses of depression and/or anxiety and their 380 siblings. Measured IMCs included blood pressure, waist circumference, and levels of glucose, triglycerides, HDL cholesterol, CRP, TNF-α and IL-6. DSPs included mood, cognitive, somatic and atypical-like profiles. We cross-sectionally examined whether DSPs were associated with IMCs within probands and within siblings, and whether DSPs were associated with IMCs between probands and siblings. RESULTS: Within probands and within siblings, higher BMI and waist circumference were associated with higher somatic and atypical-like profiles. Other IMCs (IL-6, glucose and HDL cholesterol) were significantly related to DSPs either within probands or within siblings. DSPs and IMCs were not associated between probands and siblings. CONCLUSIONS: The results suggest that there is a familial component for each trait, but no common familial factors for the association between DSPs and IMCs. Alternative mechanisms, such as direct causal effects or non-shared environmental risk factors, may better fit these results.

Working memory moderates the relation between the brain-derived neurotropic factor (BDNF) and psychotherapy outcome for depression.

BACKGROUND: Insight into patient characteristics that predict response to treatment for major depressive disorder (MDD) may help to personalize treatment and improve outcomes. One mechanism that has been linked to the success of treatment for MDD is brain-derived neurotropic factor (BDNF). BDNF is implicated in learning and memory and may play a role in the effects of psychotherapy that involves changing cognitions and behaviors. In addition, only in individuals with low BDNF, low working memory capacity has been associated with increased symptoms of depression. However, the role of BDNF and working memory capacity in psychotherapy outcome is unclear. The aim of this study was to investigate the role of BDNF and its interaction with working memory capacity in psychotherapy outcomes for MDD. METHOD: Adult patients with MDD were randomized to weekly or twice weekly sessions of cognitive behavioral therapy or interpersonal psychotherapy. BDNF Val66Met polymorphism (rs6265) (n = 138) was defined and serum BDNF was quantified before (n = 138) and after psychotherapy (n = 82). RESULTS: Baseline serum BDNF and the Val66Met polymorphism were not associated with outcome and associations did not differ between treatment conditions. Working memory capacity significantly moderated the relation between baseline serum BDNF and outcome: high serum BDNF at baseline was related to less depressive symptoms following psychotherapy in the presence of high working memory capacity, but not low working memory capacity. DISCUSSION: These findings, if replicated, might indicate that while BDNF may not be related to psychotherapy outcomes in general, they may play a role in the presence of specific learning processes such as working memory capacity.

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.

Exploring the role of low-frequency and rare exonic variants in alcohol and tobacco use.

BACKGROUND: Alcohol and tobacco use are heritable phenotypes. However, only a small number of common genetic variants have been identified, and common variants account for a modest proportion of the heritability. Therefore, this study aims to investigate the role of low-frequency and rare variants in alcohol and tobacco use. METHODS: We meta-analyzed ExomeChip association results from eight discovery cohorts and included 12,466 subjects and 7432 smokers in the analysis of alcohol consumption and tobacco use, respectively. The ExomeChip interrogates low-frequency and rare exonic variants, and in addition a small pool of common variants. We investigated top variants in an independent sample in which ICD-9 diagnoses of "alcoholism" (N = 25,508) and "tobacco use disorder" (N = 27,068) had been assessed. In addition to the single variant analysis, we performed gene-based, polygenic risk score (PRS), and pathway analyses. RESULTS: The meta-analysis did not yield exome-wide significant results. When we jointly analyzed our top results with the independent sample, no low-frequency or rare variants reached significance for alcohol consumption or tobacco use. However, two common variants that were present on the ExomeChip, rs16969968 (p = 2.39 × 10-7) and rs8034191 (p = 6.31 × 10-7) located in CHRNA5 and AGPHD1 at 15q25.1, showed evidence for association with tobacco use. DISCUSSION: Low-frequency and rare exonic variants with large effects do not play a major role in alcohol and tobacco use, nor does the aggregate effect of ExomeChip variants. However, our results confirmed the role of the CHRNA5-CHRNA3-CHRNB4 cluster of nicotinic acetylcholine receptor subunit genes in tobacco use.

A tutorial on conducting genome-wide association studies: Quality control and statistical analysis.

OBJECTIVES: Genome-wide association studies (GWAS) have become increasingly popular to identify associations between single nucleotide polymorphisms (SNPs) and phenotypic traits. The GWAS method is commonly applied within the social sciences. However, statistical analyses will need to be carefully conducted and the use of dedicated genetics software will be required. This tutorial aims to provide a guideline for conducting genetic analyses. METHODS: We discuss and explain key concepts and illustrate how to conduct GWAS using example scripts provided through GitHub (https://github.com/MareesAT/GWA_tutorial/). In addition to the illustration of standard GWAS, we will also show how to apply polygenic risk score (PRS) analysis. PRS does not aim to identify individual SNPs but aggregates information from SNPs across the genome in order to provide individual-level scores of genetic risk. RESULTS: The simulated data and scripts that will be illustrated in the current tutorial provide hands-on practice with genetic analyses. The scripts are based on PLINK, PRSice, and R, which are commonly used, freely available software tools that are accessible for novice users. CONCLUSIONS: By providing theoretical background and hands-on experience, we aim to make GWAS more accessible to researchers without formal training in the field.

Paternal age and psychiatric disorders: A review.

We review the hypotheses concerning the association between the paternal age at childbearing and childhood psychiatric disorders (autism spectrum- and attention deficit/hyperactive disorder) and adult disorders (schizophrenia, bipolar-, obsessive-compulsive-, and major depressive disorder) based on epidemiological studies. Several hypotheses have been proposed to explain the paternal age effect. We discuss the four main-not mutually exclusive-hypotheses. These are the de novo mutation hypothesis, the hypothesis concerning epigenetic alterations, the selection into late fatherhood hypothesis, and the environmental resource hypothesis. Advanced paternal age in relation to autism spectrum disorders and schizophrenia provided the most robust epidemiological evidence for an association, with some studies reporting a monotonic risk increase over age, and others reporting a marked increase at a given age threshold. Although there is evidence for the de novo mutation hypothesis and the selection into late fatherhood hypothesis, the mechanism(s) underlying the association between advanced paternal age and psychiatric illness in offspring remains to be further clarified. © 2016 The Authors. American Journal of Medical Genetics Part B: Neuropsychiatric Genetics Published by Wiley Periodicals, Inc.

The pupil response reveals increased listening effort when it is difficult to focus attention.

Recent studies have shown that prior knowledge about where, when, and who is going to talk improves speech intelligibility. How related attentional processes affect cognitive processing load has not been investigated yet. In the current study, three experiments investigated how the pupil dilation response is affected by prior knowledge of target speech location, target speech onset, and who is going to talk. A total of 56 young adults with normal hearing participated. They had to reproduce a target sentence presented to one ear while ignoring a distracting sentence simultaneously presented to the other ear. The two sentences were independently masked by fluctuating noise. Target location (left or right ear), speech onset, and talker variability were manipulated in separate experiments by keeping these features either fixed during an entire block or randomized over trials. Pupil responses were recorded during listening and performance was scored after recall. The results showed an improvement in performance when the location of the target speech was fixed instead of randomized. Additionally, location uncertainty increased the pupil dilation response, which suggests that prior knowledge of location reduces cognitive load. Interestingly, the observed pupil responses for each condition were consistent with subjective reports of listening effort. We conclude that communicating in a dynamic environment like a cocktail party (where participants in competing conversations move unpredictably) requires substantial listening effort because of the demands placed on attentional processes.