A wealth of clinical studies have identified objective biomarkers, which separate schizophrenia patients from healthy controls on a group level, but current diagnostic systems solely include clinical symptoms. In this study, we investigate if machine learning algorithms on multimodal data can serve as a framework for clinical translation.

Forty-six antipsychotic-naïve, first-episode schizophrenia patients and 58 controls underwent neurocognitive tests, electrophysiology, and magnetic resonance imaging (MRI). Patients underwent clinical assessments before and after 6 weeks of antipsychotic monotherapy with amisulpride. Nine configurations of different supervised machine learning algorithms were applied to first estimate the unimodal diagnostic accuracy, and next to estimate the multimodal diagnostic accuracy. Finally, we explored the predictability of symptom remission.

Cognitive data significantly classified patients from controls (accuracies = 60–69%; p values = 0.0001–0.009). Accuracies of electrophysiology, structural MRI, and diffusion tensor imaging did not exceed chance level. Multimodal analyses with cognition plus any combination of one or more of the remaining three modalities did not outperform cognition alone. None of the modalities predicted symptom remission.

In this multivariate and multimodal study in antipsychotic-naïve patients, only cognition significantly discriminated patients from controls, and no modality appeared to predict short-term symptom remission. Overall, these findings add to the increasing call for cognition to be included in the definition of schizophrenia. To bring about the full potential of machine learning algorithms in first-episode, antipsychotic-naïve schizophrenia patients, careful a priori variable selection based on independent data as well as inclusion of other modalities may be required.

We assessed whether the risk of various psychotic disorders and non-psychotic bipolar disorder (including mania) varied by migrant status, a region of origin, or age-at-migration, hypothesizing that risk would only be elevated for psychotic disorders.

We established a prospective cohort of 1 796 257 Swedish residents born between 1982 and 1996, followed from their 15th birthday, or immigration to Sweden after age 15, until diagnosis, emigration, death, or end of 2011. Cox proportional hazards models were used to model hazard ratios by migration-related factors, adjusted for covariates.

All psychotic disorders were elevated among migrants and their children compared with Swedish-born individuals, including schizophrenia and schizoaffective disorder (adjusted hazard ratio [aHR]migrants: 2.20, 95% CI 1.96–2.47; aHRchildren : 2.00, 95% CI 1.79–2.25), affective psychotic disorders (aHRmigrant1.42, 95% CI 1.25–1.63; aHRchildren: 1.22 95% CI 1.07–1.40), and other non-affective psychotic disorders (aHRmigrant: 1.97, 95% CI 1.81–2.14; aHRchildren: 1.68, 95% CI 1.54–1.83). For all psychotic disorders, risks were generally highest in migrants from Africa (i.e. aHRschizophrenia: 5.24, 95% CI 4.26–6.45) and elevated at most ages-of-migration. By contrast, risk of non-psychotic bipolar disorders was lower for migrants (aHR: 0.58, 95% CI 0.52–0.64) overall, and across all ages-of-migration except infancy (aHR: 1.20; 95% CI 1.01–1.42), while risk for their children was similar to the Swedish-born population (aHR: 1.00, 95% CI 0.93–1.08).

Increased risk of psychiatric disorders associated with migration and minority status may be specific to psychotic disorders, with exact risk dependent on the region of origin.

Non-motor features of Parkinson's disease (PD) and dementia with Lewy bodies (DLB), such as auditory hallucinations (AH), contribute to disease burden but are not well understood.

Systematic review and random-effects meta-analyses of studies reporting AH associated with PD or DLB. Prevalence of visual hallucinations (VH) in identified studies meeting eligibility criteria were included in meta-analyses, facilitating comparison with AH. Synthesis of qualitative descriptions of AH was performed. PubMed, Web of Science and Scopus databases were searched for primary journal articles, written in English, published from 1970 to 2017. Studies reporting AH prevalence in PD or DLB were screened using PRISMA methods.

Searches identified 4542 unique studies for consideration, of which, 26 met inclusion criteria. AH pooled prevalence in PD was estimated to be 8.9% [95% confidence interval (CI) 5.3–14.5], while in DLB was estimated to be 30.8% (±23.4 to 39.3). Verbal hallucinations, perceived as originating outside the head, were the most common form of AH. Non-verbal AH were also common while musical AH were rare. VH were more prevalent, with an estimated pooled prevalence in PD of 28.2% (±19.1 to 39.5), while in DLB they were estimated to be 61.8% (±49.1 to 73.0). Meta-regression determined that the use of validated methodologies to identify hallucinations produced higher prevalence estimates.

AH and VH present in a substantial proportion of PD and DLB cases, with VH reported more frequently in both conditions. Both AH and VH are more prevalent in DLB than PD. There is a need for standardised use of validated methods to detect and monitor hallucinations.

Individuals with autism spectrum disorder (ASD) appear to be at increased risk of non-affective psychotic disorder (NAPD) and bipolar disorder (BD). However, most previous studies examined the co-occurrence of ASD and NAPD or BD, ignoring possible diagnostic bias and selection bias. We used longitudinal data from Dutch psychiatric case registers to assess the risk of NAPD or BD among individuals with ASD, and compared the results to those obtained for the Dutch population in earlier studies.

Individuals with ASD (n = 17 234) were followed up between 16 and 35 years of age. Kaplan–Meier estimates were used to calculate the risk of NAPD or BD. We conducted separate analyses to reduce possible bias, including an analysis among individuals diagnosed with ASD before age 16 years (n = 8337).

Of the individuals with ASD, 23.50% (95% confidence interval 21.87–25.22) were diagnosed with NAPD and 3.79% (3.06–4.69) with BD before age 35 years. The corresponding figures for the general population were 0.91% (0.63–1.28) and 0.13% (0.08–0.20). Risk estimates were substantially lower, but still higher than general population estimates, when we restricted our analyses to individuals diagnosed with ASD before age 16, with 1.87% (1.33–2.61) being diagnosed with NAPD and 0.57% (0.21–1.53) with BD before age 25 years. The corresponding figures for the general population were 0.63% (0.44–0.86) and 0.08% (0.05–0.12).

Individuals with ASD are at increased risk of NAPD or BD. This is likely not the result of diagnostic or selection bias.

Mood disorders and adiposity are major public health challenges. Few studies have investigated the bidirectional association of weight and waist circumference (WC) change with psychological distress in middle age, while taking into account the potential U-shape of the association. The aim of this study was to examine the bidirectional association between psychological distress and categorical change in objectively measured weight and WC.

We analysed repeated measures (up to 17 522 person-observations in adjusted analyses) of psychological distress, weight and WC from the Whitehall II cohort. Participants were recruited at age 35–55 and 67% male. Psychological distress was assessed using the General Health Questionnaire. We used random-effects regressions to model the association between weight and WC changes and psychological distress, with and without a 5-year lag period.

Psychological distress was associated with weight and WC gain over the subsequent 5 years but not the second 5-year period. Weight gain and loss were associated with increased odds for incident psychological distress in models with and without time-lag [odds ratio (OR) for incident psychological distress after 5-year time-lag: loss 1.20, 95% confidence interval (CI) 1.00–1.43; gain>5% 1.20, 95% CI 1.02–1.40]. WC changes were only associated with psychological distress in models without time-lag (OR for incident psychological distress: loss 1.29, 95% CI 1.02–1.64; gain>5% 1.33, 95% CI 1.11–1.58).

Weight gain and loss increase the odds for psychological distress compared with stable weight over subsequent 10 years. In contrast, the association between psychological distress and subsequent weight and WC changes was limited to the first 5 years of follow-up.

An increasing importance is being placed on mental health and wellbeing at individual and population levels. While there are several interventions that have been proposed to improve wellbeing, more evidence is needed to understand which aspects of wellbeing are most influential. This study aimed to identify key items that signal improvement of mental health and wellbeing.

Using network analysis, we identified the most central items in the graph network estimated from the well-established Warwick-Edinburgh Mental Well-being Scale (WEMWBS). Results were compared across four major UK cohorts comprising a total of 47,578 individuals: the Neuroscience in Psychiatry Network, the Scottish Schools Adolescent Lifestyle and Substance Use Survey, the Northern Ireland Health Survey, and the National Child Development Study.

Regardless of gender, the three items most central in the network were related to positive self-perception and mood: ‘I have been feeling good about myself’; ‘I have been feeling confident’; and ‘I have been feeling cheerful’. Results were consistent across all four cohorts.

Positive self-perception and positive mood are central to psychological wellbeing. Psychotherapeutic and public mental health interventions might best promote psychological wellbeing by prioritising the improvement of self-esteem, self-confidence and cheerfulness. However, empirical testing of interventions using these key targets is needed.

Depression is increasingly recognized as a chronic and relapsing disorder. However, an important minority of patients who start treatment for their major depressive episode recover to euthymia. It is clinically important to be able to predict such individuals.

The study is a secondary analysis of a recently completed pragmatic megatrial examining first- and second-line treatments for hitherto untreated episodes of non-psychotic unipolar major depression (n = 2011). Using the first half of the cohort as the derivation set, we applied multiply-imputed stepwise logistic regression with backward selection to build a prediction model to predict remission, defined as scoring 4 or less on the Patient Health Quetionnaire-9 at week 9. We used three successively richer sets of predictors at baseline only, up to week 1, and up to week 3. We examined the external validity of the derived prediction models with the second half of the cohort.

In total, 37.0% (95% confidence interval 34.8–39.1%) were in remission at week 9. Only the models using data up to week 1 or 3 showed reasonable performance. Age, education, length of episode and depression severity remained in the multivariable prediction models. In the validation set, the discrimination of the prediction model was satisfactory with the area under the curve of 0.73 (0.70–0.77) and 0.82 (0.79–0.85), while the calibration was excellent with non-significant goodness-of-fit χ2 values (p = 0.41 and p = 0.29), respectively.

Patients and clinicians can use these prediction models to estimate their predicted probability of achieving remission after acute antidepressant therapy.

Some Internet interventions are regarded as effective treatments for adult depression, but less is known about who responds to this form of treatment.

An elastic net and random forest were trained to predict depression symptoms and related disability after an 8-week course of an Internet intervention, Deprexis, involving adults (N = 283) from across the USA. Candidate predictors included psychopathology, demographics, treatment expectancies, treatment usage, and environmental context obtained from population databases. Model performance was evaluated using predictive R2$\lpar R_{{\rm pred}}^2\rpar\comma $ the expected variance explained in a new sample, estimated by 10 repetitions of 10-fold cross-validation.

An ensemble model was created by averaging the predictions of the elastic net and random forest. Model performance was compared with a benchmark linear autoregressive model that predicted each outcome using only its baseline. The ensemble predicted more variance in post-treatment depression (8.0% gain, 95% CI 0.8–15; total $R_{{\rm pred}}^2 \; $= 0.25), disability (5.0% gain, 95% CI −0.3 to 10; total $R_{{\rm pred}}^2 \; $= 0.25), and well-being (11.6% gain, 95% CI 4.9–19; total $R_{{\rm pred}}^2 \; $= 0.29) than the benchmark model. Important predictors included comorbid psychopathology, particularly total psychopathology and dysthymia, low symptom-related disability, treatment credibility, lower access to therapists, and time spent using certain Deprexis modules.

A number of variables predict symptom improvement following an Internet intervention, but each of these variables makes relatively small contributions. Machine learning ensembles may be a promising statistical approach for identifying the cumulative contribution of many weak predictors to psychosocial depression treatment response.

Despite the well-documented association between smoking and personality traits such as neuroticism and extraversion, little is known about the potential causal nature of these findings. If it were possible to unpick the association between personality and smoking, it may be possible to develop tailored smoking interventions that could lead to both improved uptake and efficacy.

Recent genome-wide association studies (GWAS) have identified variants robustly associated with both smoking phenotypes and personality traits. Here we use publicly available GWAS summary statistics in addition to individual-level data from UK Biobank to investigate the link between smoking and personality. We first estimate genetic overlap between traits using LD score regression and then use bidirectional Mendelian randomisation methods to unpick the nature of this relationship.

We found clear evidence of a modest genetic correlation between smoking behaviours and both neuroticism and extraversion. We found some evidence that personality traits are causally linked to certain smoking phenotypes: among current smokers each additional neuroticism risk allele was associated with smoking an additional 0.07 cigarettes per day (95% CI 0.02–0.12, p = 0.009), and each additional extraversion effect allele was associated with an elevated odds of smoking initiation (OR 1.015, 95% CI 1.01–1.02, p = 9.6 × 10−7).

We found some evidence for specific causal pathways from personality to smoking phenotypes, and weaker evidence of an association from smoking initiation to personality. These findings could be used to inform future smoking interventions or to tailor existing schemes.

Converging lines of evidence implicate an important role for the immune system in schizophrenia. Microglia are the resident immune cells of the central nervous system and have many functions including neuroinflammation, axonal guidance and neurotrophic support. We aimed to provide a quantitative review of in vivo PET imaging studies of microglia activation in patients with schizophrenia compared with healthy controls.

Demographic, clinical and imaging measures were extracted from each study and meta-analysis was conducted using a random-effects model (Hedge's g). The difference in 18-kDa translocator protein (TSPO) binding between patients with schizophrenia and healthy controls, as quantified by either binding potential (BP) or volume of distribution (VT), was used as the main outcome. Sub-analysis and sensitivity analysis were carried out to investigate the effects of genotype, ligand and illness stage.

In total, 12 studies comprising 190 patients with schizophrenia and 200 healthy controls met inclusion criteria. There was a significant elevation in tracer binding in schizophrenia patients relative to controls when BP was used as an outcome measure, (Hedge's g = 0.31; p = 0.03) but no significant differences when VT was used (Hedge's g = −0.22; p = 0.29).

In conclusion, there is evidence for moderate elevations in TSPO tracer binding in grey matter relative to other brain tissue in schizophrenia when using BP as an outcome measure, but no difference when VT is the outcome measure. We discuss the relevance of these findings as well as the methodological issues that may underlie the contrasting difference between these outcomes.

Neuropsychological investigations can help untangle the aetiological and phenomenological heterogeneity of schizophrenia but have scarcely been employed in the context of treatment-resistant (TR) schizophrenia. No population-based study has examined neuropsychological function in the first-episode of TR psychosis.

We report baseline neuropsychological findings from a longitudinal, population-based study of first-episode psychosis, which followed up cases from index admission to 10 years. At the 10-year follow up patients were classified as treatment responsive or TR after reconstructing their entire case histories. Of 145 cases with neuropsychological data at baseline, 113 were classified as treatment responsive, and 32 as TR at the 10-year follow-up.

Compared with 257 community controls, both case groups showed baseline deficits in three composite neuropsychological scores, derived from principal component analysis: verbal intelligence and fluency, visuospatial ability and executive function, and verbal memory and learning (p values⩽0.001). Compared with treatment responders, TR cases showed deficits in verbal intelligence and fluency, both in the extended psychosis sample (t = −2.32; p = 0.022) and in the schizophrenia diagnostic subgroup (t = −2.49; p = 0.017). Similar relative deficits in the TR cases emerged in sub-/sensitivity analyses excluding patients with delayed-onset treatment resistance (p values<0.01–0.001) and those born outside the UK (p values<0.05).

Verbal intelligence and fluency are impaired in patients with TR psychosis compared with those who respond to treatment. This differential is already detectable – at a group level – at the first illness episode, supporting the conceptualisation of TR psychosis as a severe, pathogenically distinct variant, embedded in aberrant neurodevelopmental processes.

The value of the nosological distinction between non-affective and affective psychosis has frequently been challenged. We aimed to investigate the transdiagnostic dimensional structure and associated characteristics of psychopathology at First Episode Psychosis (FEP). Regardless of diagnostic categories, we expected that positive symptoms occurred more frequently in ethnic minority groups and in more densely populated environments, and that negative symptoms were associated with indices of neurodevelopmental impairment.

This study included 2182 FEP individuals recruited across six countries, as part of the EUropean network of national schizophrenia networks studying Gene–Environment Interactions (EU-GEI) study. Symptom ratings were analysed using multidimensional item response modelling in Mplus to estimate five theory-based models of psychosis. We used multiple regression models to examine demographic and context factors associated with symptom dimensions.

A bifactor model, composed of one general factor and five specific dimensions of positive, negative, disorganization, manic and depressive symptoms, best-represented associations among ratings of psychotic symptoms. Positive symptoms were more common in ethnic minority groups. Urbanicity was associated with a higher score on the general factor. Men presented with more negative and less depressive symptoms than women. Early age-at-first-contact with psychiatric services was associated with higher scores on negative, disorganized, and manic symptom dimensions.

Our results suggest that the bifactor model of psychopathology holds across diagnostic categories of non-affective and affective psychosis at FEP, and demographic and context determinants map onto general and specific symptom dimensions. These findings have implications for tailoring symptom-specific treatments and inform research into the mood-psychosis spectrum.

Previous studies on reporting bias generally examined whether trials were published in stand-alone publications. In this study, we investigated whether pooled-trials publications constitute a specific form of reporting bias. We assessed whether negative trials were more likely to be exclusively published in pooled-trials publications than positive trials and examined the research questions, individual trial results, and conclusions presented in these articles.

Data from a cohort of 105 randomized controlled trials of 16 antidepressants were extracted from earlier publications and the corresponding Food and Drug Administration (FDA) reviews. A systematic literature search was conducted to identify pooled-trials publications.

We found 107 pooled-trials publications that reported results of 23 (72%) of 32 trials not published in stand-alone publications. Only two (3.8%) of 54 positive trials were published exclusively in pooled-trials publications, compared with 21 (41.1%) of 51 negative trials (p < 0.001). Thirteen (12%) of 107 publications had as primary aim to present data on the trial's primary research question (drug efficacy compared with placebo). Only four of these publications, reporting on five (22%) trials, presented individual efficacy data for the primary research question. Additionally, only five (5%) of 107 pooled-trials publications had a negative conclusion.

Compared with positive trials, negative trials of antidepressants for depression were much more likely to be reported exclusively in pooled-trials publications. Pooled-trials publications flood the evidence base with often-redundant articles that, instead of addressing the original primary research question, present (positive) results on secondary questions. Therefore, pooled-trials publications distort the apparent risk–benefit profile of antidepressants.

Various childhood social experiences have been reported to predict adult outcomes. However, it is unclear how different social contexts may influence each other's effects in the long run. This study examined the joint contribution of adolescent family and peer experiences to young adult wellbeing and functioning.

Participants came from the TRacking Adolescents’ Individual Lives Survey (TRAILS) study (n = 2230). We measured family and peer relations at ages 11 and 16 (i.e. family functioning, perceived parenting, peer status, peer relationship quality), and functioning as the combination of subjective wellbeing, physical and mental health, and socio-academic functioning at age 22. Using structural equation modelling, overall functioning was indicated by two latent variables for positive and negative functioning. Positive, negative and overall functioning at young adulthood were regressed on adolescent family experiences, peer experiences and interactions between the two.

Family experiences during early and mid-adolescence were most predictive for later functioning; peer experiences did not independently predict functioning. Interactions between family and peer experiences showed that both protective and risk factors can have context-dependent effects, being exacerbated or overshadowed by negative experiences or buffered by positive experiences in other contexts. Overall the effect sizes were modest at best.

Adolescent family relations as well as the interplay with peer experiences predict young adult functioning. This emphasizes the importance of considering the relative effects of one context in relation to the other.

Electroconvulsive therapy (ECT), an effective antidepressive treatment, is frequently accompanied by cognitive impairment (predominantly memory), usually transient and self-limited. The hippocampus is a key region involved in memory and emotion processing, and in particular, the anterior-posterior hippocampal subregions has been shown to be associated with emotion and memory. However, less is known about the relationship between hippocampal-subregion alterations following ECT and antidepressant effects or cognitive impairments.

Resting-state functional connectivity (RSFC) based on the seeds of hippocampal subregions were investigated in 45 pre- and post-ECT depressed patients. Structural connectivity between hippocampal subregions and corresponding functionally abnormal regions was also conducted using probabilistic tractography. Antidepressant effects and cognitive impairments were measured by the Hamilton Depressive Rating Scale (HDRS) and the Category Verbal Fluency Test (CVFT), respectively. Their relationships with hippocampal-subregions alterations were examined.

After ECT, patients showed increased RSFC in the hippocampal emotional subregion (HIPe) with the left middle occipital gyrus (LMOG) and right medial temporal gyrus (RMTG). Decreased HDRS was associated with increased HIPe-RMTG RSFC (r = −0.316, p = 0.035) significantly and increased HIPe-LMOG RSFC at trend level (r = −0.283, p = 0.060). In contrast, the hippocampal cognitive subregion showed decreased RSFC with the bilateral angular gyrus, and was correlated with decreased CVFT (r = 0.418, p = 0.015 for left; r = 0.356, p = 0.042 for right). No significant changes were found in structural connectivity.

The hippocampal-subregions functional alterations may be specially associated with the antidepressant and cognitive effects of ECT.

Neurobiological models of stress and stress-related mental illness, including post-traumatic stress disorder, converge on the amygdala and the prefrontal cortex (PFC). While a surge of research has reported altered structural and functional connectivity between amygdala and the medial PFC following severe stress, few have addressed the underlying neurochemistry.

We combined resting-state functional magnetic resonance imaging measures of amygdala connectivity with in vivo MR-spectroscopy (1H-MRS) measurements of glutamate in 26 survivors from the 2011 Norwegian terror attack and 34 control subjects.

Traumatized youths showed altered amygdala–anterior midcingulate cortex (aMCC) and amygdala–ventromedial prefrontal cortex (vmPFC) connectivity. Moreover, the trauma survivors exhibited reduced levels of glutamate in the vmPFC which fits with the previous findings of reduced levels of Glx (glutamate + glutamine) in the aMCC (Ousdal et al., 2017) and together suggest long-term impact of a traumatic experience on glutamatergic pathways. Importantly, local glutamatergic metabolite levels predicted the individual amygdala–aMCC and amygdala–vmPFC functional connectivity, and also mediated the observed group difference in amygdala–aMCC connectivity.

Our findings suggest that traumatic stress may influence amygdala–prefrontal neuronal connectivity through an effect on prefrontal glutamate and its compounds. Understanding the neurochemical underpinning of altered amygdala connectivity after trauma may ultimately lead to the discovery of new pharmacological agents which can prevent or treat stress-related mental illness.

Most studies underline the contribution of heritable factors for psychiatric disorders. However, heritability estimates depend on the population under study, diagnostic instruments, and study designs that each has its inherent assumptions, strengths, and biases. We aim to test the homogeneity in heritability estimates between two powerful, and state of the art study designs for eight psychiatric disorders.

We assessed heritability based on data of Swedish siblings (N = 4 408 646 full and maternal half-siblings), and based on summary data of eight samples with measured genotypes (N = 125 533 cases and 208 215 controls). All data were based on standard diagnostic criteria. Eight psychiatric disorders were studied: (1) alcohol dependence (AD), (2) anorexia nervosa, (3) attention deficit/hyperactivity disorder (ADHD), (4) autism spectrum disorder, (5) bipolar disorder, (6) major depressive disorder, (7) obsessive-compulsive disorder (OCD), and (8) schizophrenia.

Heritability estimates from sibling data varied from 0.30 for Major Depression to 0.80 for ADHD. The estimates based on the measured genotypes were lower, ranging from 0.10 for AD to 0.28 for OCD, but were significant, and correlated positively (0.19) with national sibling-based estimates. When removing OCD from the data the correlation increased to 0.50.

Given the unique character of each study design, the convergent findings for these eight psychiatric conditions suggest that heritability estimates are robust across different methods. The findings also highlight large differences in genetic and environmental influences between psychiatric disorders, providing future directions for etiological psychiatric research.

Depressive symptoms and inflammation are risk factors for cardiovascular disease (CVD) and mortality. We investigated the combined association of these factors with the prediction of CVD and all-cause mortality in a representative cohort of older men and women.

We measured C-reactive protein (CRP) and depressive symptoms in 5328 men and women aged 52–89 years in the English Longitudinal Study of Ageing. Depressive symptoms were measured using the eight-item Centre for Epidemiological Studies Depression Scale. CRP was analysed from peripheral blood. Mortality was ascertained from national registers and associations with depressive symptoms and inflammation were estimated using Cox proportional hazard models.

We identified 112 CVD related deaths out of 420 all-cause deaths in men and 109 CVD related deaths out of 334 all-cause deaths in women over a mean follow-up of 7.7 years. Men with both depressive symptoms and high CRP (3–20 mg/L) had an increased risk of CVD mortality (hazard ratio; 95% confidence interval: 3.89; 2.04–7.44) and all-cause mortality (2.40; 1.65–3.48) after adjusting for age, socioeconomic variables and health behaviours. This considerably exceeds the risks associated with high CRP alone (CVD 2.43; 1.59–3.71, all-cause 1.49; 1.20–1.84). There was no significant increase in mortality risk associated with depressive symptoms alone in men. In women, neither depressive symptoms or inflammation alone or the combination of both significantly predicted CVD or all-cause mortality.

The combination of depressive symptoms and increased inflammation confers a considerable increase in CVD mortality risk for men. These effects appear to be independent, suggesting an additive role.