Despite statistical evidence of a general factor of psychopathology (i.e., p-factor), there is little agreement about what the p-factor represents. Researchers have proposed five theories: dispositional negative emotionality (neuroticism), impulsive responsivity to emotions (impulsivity), thought dysfunction, low cognitive functioning, and impairment. These theories have primarily been inferred from patterns of loadings of diagnoses on p-factors with different sets of diagnoses included in different studies. Researchers who have directly examined these theories of p have examined a subset of the theories in any single sample, limiting the ability to compare the size of their associations with a p-factor.

In a sample of adults (N = 1833, Mage = 34.20, 54.4% female, 53.3% white) who completed diagnostic assessments, self-report measures, and cognitive tests, we evaluated statistical p-factor structures across modeling approaches and compared the strength of associations among the p-factor and indicators of each of these five theories.

We found consistent evidence of the p-factor's unidimensionality across one-factor and bifactor models. The p-factor was most strongly and similarly associated with neuroticism (r = .88), impairment (r = .88), and impulsivity (r = .87), χ2(1)s < .15, ps > .70, and less strongly associated with thought dysfunction (r = .78), χ2(1)s > 3.92, ps < .05, and cognitive functioning (r = −.25), χ2(1)s > 189.56, ps < .01.

We discuss a tripartite definition of p that involves the transaction of impulsive responses to frequent negative emotions leading to impairment that extends and synthesizes previous theories of psychopathology.

Responses to the COVID-19 pandemic have included lockdowns and social distancing with considerable disruptions to people's lives. These changes may have particularly impacted on those with mental health problems, leading to a worsening of inequalities in the behaviours which influence health.

We used data from four national longitudinal British cohort studies (N = 10 666). Respondents reported mental health (psychological distress and anxiety/depression symptoms) and health behaviours (alcohol, diet, physical activity and sleep) before and during the pandemic. Associations between pre-pandemic mental ill-health and pandemic mental ill-health and health behaviours were examined using logistic regression; pooled effects were estimated using meta-analysis.

Worse mental health was related to adverse health behaviours; effect sizes were largest for sleep, exercise and diet, and weaker for alcohol. The associations between poor mental health and adverse health behaviours were larger during the May lockdown than pre-pandemic. In September, when restrictions had eased, inequalities had largely reverted to pre-pandemic levels. A notable exception was for sleep, where differences by mental health status remained high. Risk differences for adverse sleep for those with the highest level of prior mental ill-health compared to those with the lowest were 21.2% (95% CI 16.2–26.2) before lockdown, 25.5% (20.0–30.3) in May and 28.2% (21.2–35.2) in September.

Taken together, our findings suggest that mental health is an increasingly important factor in health behaviour inequality in the COVID era. The promotion of mental health may thus be an important component of improving post-COVID population health.

Contemporary views of emotion dysregulation in post-traumatic stress disorder (PTSD) highlight reduced ability to flexibly select regulatory strategies according to differing situational demands. However, empirical evidence of reduced regulatory selection flexibility in PTSD is lacking. Multiple studies show that healthy individuals demonstrate regulatory selection flexibility manifested in selecting attentional disengagement regulatory strategies (e.g. distraction) in high-intensity emotional contexts and selecting engagement meaning change strategies (e.g. reappraisal) in low-intensity contexts. Accordingly, we hypothesized that PTSD populations will show reduced regulatory selection flexibility manifested in diminished increase in distraction (over reappraisal) preference as intensity increases from low to high intensity.

Study 1 compared student participants with high (N = 22) post-traumatic symptoms (PTS, meeting the clinical cutoff for PTSD) and participants with low (N = 22) post-traumatic symptoms. Study 2 compared PTSD diagnosed women (N = 31) due to childhood sexual abuse and matched non-clinical women (N = 31). In both studies, participants completed a well-established regulatory selection flexibility performance-based paradigm that involves selecting between distraction and reappraisal to regulate negative emotional words of low and high intensity.

Beyond demonstrating adequate psychometric properties, Study 1 confirmed that relative to the low PTS group, the high PTS group presented reduced regulatory selection flexibility (p = 0.01, $\eta _{\rm p}^2$ = 0.14). Study 2 critically extended findings of Study 1, in showing similar reduced regulatory selection flexibility in a diagnosed PTSD population, relative to a non-clinical population (p = 0.002, $\eta _{\rm p}^2$ = 0.114).

Two studies provide converging evidence for reduced emotion regulatory selection flexibility in two PTSD populations.

Near-term risk factors for suicidal behavior, referred to as ‘warning signs’ (WS), distinguish periods of acute heightened risk from periods of lower risk within an individual. No prior published study has examined, using a controlled study design, a broad set of hypothesized WS for suicide attempt. This study addressed this gap through examination of hypothesized behavioral/experiential, cognitive, and affective WS among patients recently hospitalized following a suicide attempt.

Participants were recruited during hospitalization from five medical centers across the USA including two civilian hospitals and three Veterans Health Administration facilities (n = 349). A within-person case-crossover study design was used, where each patient served as her/his own control. WS were measured by the Timeline Follow-back for Suicide Attempts Interview and were operationalized as factors that were present (v. absent) or that increased in frequency/intensity within an individual during the 6 h preceding the suicide attempt (case period) compared to the corresponding 6 h on the day before (control period).

Select WS were associated with near-term risk for suicide attempt including suicide-related communications, preparing personal affairs, drinking alcohol, experiencing a negative interpersonal event, and increases in key affective (e.g. emptiness) and cognitive (e.g. burdensomeness) responses.

The identification of WS for suicidal behavior can enhance risk recognition efforts by medical providers, patients, their families, and other stakeholders that can serve to inform acute risk management decisions.

While effective treatments exist for binge-eating disorder (BED), prediction of treatment outcomes has proven difficult, and few reliable predictors have been identified. Machine learning is a promising method for improving the accuracy of difficult-to-predict outcomes. We compared the accuracy of traditional and machine-learning approaches for predicting BED treatment outcomes.

Participants were 191 adults with BED in a randomized controlled trial testing 6-month behavioral and stepped-care treatments. Outcomes, determined by independent assessors, were binge-eating (% reduction, abstinence), eating-disorder psychopathology, and weight loss (% loss, ⩾5% loss). Predictors included treatment condition, demographic information, and baseline clinical characteristics. Traditional models were logistic/linear regressions. Machine-learning models were elastic net regressions and random forests. Predictive accuracy was indicated by the area under receiver operator characteristic curve (AUC), root mean square error (RMSE), and R2. Confidence intervals were used to compare accuracy across models.

Across outcomes, AUC ranged from very poor to fair (0.49–0.73) for logistic regressions, elastic nets, and random forests, with few significant differences across model types. RMSE was significantly lower for elastic nets and random forests v. linear regressions but R2 values were low (0.01–0.23).

Different analytic approaches revealed some predictors of key treatment outcomes, but accuracy was limited. Machine-learning models with unbiased resampling methods provided a minimal advantage over traditional models in predictive accuracy for treatment outcomes.

Impulsivity may be a process underlying binge-eating disorder (BED) psychopathology and its treatment. This study examined change in impulsivity during cognitive-behavioral therapy (CBT) and/or pharmacological treatment for BED and associations with treatment outcomes.

In total, 108 patients with BED (NFEMALE = 84) in a randomized placebo-controlled clinical trial evaluating the efficacy of CBT and/or fluoxetine were assessed before treatment, monthly throughout treatment, at post-treatment (16 weeks), and at 12-month follow-up after completing treatment. Patients completed established measures of impulsivity, eating-disorder psychopathology, and depression, and were measured for height and weight [to calculate body mass index (BMI)] during repeated assessments by trained/monitored doctoral research-clinicians. Mixed-effects models using all available data examined changes in impulsivity and the association of rapid and overall changes in impulsivity on treatment outcomes. Exploratory analyses examined whether baseline impulsivity predicted/moderated outcomes.

Impulsivity declined significantly throughout treatment and follow-up across treatment groups. Rapid change in impulsivity and overall change in impulsivity during treatment were significantly associated with reductions in eating-disorder psychopathology, depression scores, and BMI during treatment and at post-treatment. Overall change in impulsivity during treatment was associated with subsequent reductions in depression scores at 12-month follow-up. Baseline impulsivity did not moderate/predict eating-disorder outcomes or BMI but did predict change in depression scores.

Rapid and overall reductions in impulsivity during treatment were associated with improvements in specific eating-disorder psychopathology and associated general outcomes. These effects were found for both CBT and pharmacological treatment for BED. Change in impulsivity may be an important process prospectively related to treatment outcome.

There is evidence for a polygenic contribution to psychosis. One targetable mechanism through which polygenic variation may impact on individuals and interact with the social environment is stress sensitization, characterized by elevated reactivity to minor stressors in daily life. The current study aimed to investigate whether stress reactivity is modified by polygenic risk score for schizophrenia (PRS) in cases with enduring non-affective psychotic disorder, first-degree relatives of cases, and controls.

We used the experience sampling method to assess minor stressors, negative affect, positive affect and psychotic experiences in 96 cases, 79 first-degree relatives, i.e. siblings, and 73 controls at wave 3 of the Dutch Genetic Risk and Outcome of Psychosis (GROUP) study. Genome-wide data were collected at baseline to calculate PRS.

We found that associations of momentary stress with psychotic experiences, but not with negative and positive affect, were modified by PRS and group (all pFWE<0.001). In contrast to our hypotheses, siblings with high PRS reported less intense psychotic experiences in response to momentary stress compared to siblings with low PRS. No differences in magnitude of these associations were observed in cases with high v. low level of PRS. By contrast, controls with high PRS showed more intense psychotic experiences in response to stress compared to those with low PRS.

This tentatively suggests that polygenic risk may operate in different ways than previously assumed and amplify reactivity to stress in unaffected individuals but operate as a resilience factor in relatives by attenuating their stress reactivity.

To determine: whether young adults (aged 18–24) not in education, employment or training (NEET) have different psychological treatment outcomes to other young adults; any socio-demographic or treatment-related moderators of differential outcomes; and whether service-level changes are associated with better outcomes for those who are NEET.

A cohort was formed of 20 293 young adults treated with psychological therapies in eight Improving Access to Psychological Therapies services. Pre-treatment characteristics, outcomes, and moderators of differential outcomes were compared for those who were and were not NEET. Associations between outcomes and the following were assessed for those that were NEET: missing fewer sessions, attending more sessions, having a recorded diagnosis, and waiting fewer days between referral and starting treatment.

Those who were NEET had worse outcomes: odds ratio (OR) [95% confidence interval (CI)] for reliable recovery = 0.68 (0.63–0.74), for deterioration = 1.41 (1.25–1.60), and for attrition = 1.31 (1.19–1.43). Ethnic minority participants that were NEET had better outcomes than those that were White and NEET. Living in deprived areas was associated with worse outcomes. The intensity of treatment (high or low) did not moderate outcomes, but having more sessions was associated with improved outcomes for those that were NEET: odds (per one-session increase) of reliable recovery = 1.10 (1.08–1.12), deterioration = 0.94 (0.91–0.98), and attrition = 0.68 (0.66–0.71).

Earlier treatment, supporting those that are NEET to attend sessions, and in particular, offering them more sessions before ending treatment might be effective in improving clinical outcomes. Additional support when working with White young adults that are NEET and those in more deprived areas may also be important.

Meta-analyses agree that depression is characterized by neurocognitive dysfunctions relative to nonclinical controls. These deficits allegedly stem from impairments in functionally corresponding brain areas. Increasingly, studies suggest that some performance deficits are in part caused by negative task-taking attitudes such as poor motivation or the presence of distracting symptoms. A pilot study confirmed that these factors mediate neurocognitive deficits in depression. The validity of these results is however questionable given they were based solely on self-report measures. The present study addresses this caveat by having examiners assess influences during a neurocognitive examination, which were concurrently tested for their predictive value on performance.

Thirty-three patients with depression and 36 healthy controls were assessed on a battery of neurocognitive tests. The examiner completed the Impact on Performance Scale, a questionnaire evaluating mediating influences that may impact performance.

On average, patients performed worse than controls at a large effect size. When the total score of the Impact on Performance Scale was accounted for by mediation analysis and analyses of covariance, group differences were reduced to a medium effect size. A total of 30% of patients showed impairments of at least one standard deviation below the mean.

This study confirms that neurocognitive impairment in depression is likely overestimated; future studies should consider fair test-taking conditions. We advise researchers to report percentages of patients showing performance deficits rather than relying solely on overall group differences. This prevents fostering the impression that the majority of patients exert deficits, when in fact deficits are only true for a subgroup.

Overgeneralised self-blame and worthlessness are key symptoms of major depressive disorder (MDD) and have previously been associated with self-blame-selective changes in connectivity between right superior anterior temporal lobe (rSATL) and subgenual frontal cortices. Another study showed that remitted MDD patients were able to modulate this neural signature using functional magnetic resonance imaging (fMRI) neurofeedback training, thereby increasing their self-esteem. The feasibility and potential of using this approach in symptomatic MDD were unknown.

This single-blind pre-registered randomised controlled pilot trial probed a novel self-guided psychological intervention with and without additional rSATL-posterior subgenual cortex (BA25) fMRI neurofeedback, targeting self-blaming emotions in people with insufficiently recovered MDD and early treatment-resistance (n = 43, n = 35 completers). Participants completed three weekly self-guided sessions to rebalance self-blaming biases.

As predicted, neurofeedback led to a training-induced reduction in rSATL-BA25 connectivity for self-blame v. other-blame. Both interventions were safe and resulted in a 46% reduction on the Beck Depression Inventory-II, our primary outcome, with no group differences. Secondary analyses, however, revealed that patients without DSM-5-defined anxious distress showed a superior response to neurofeedback compared with the psychological intervention, and the opposite pattern in anxious MDD. As predicted, symptom remission was associated with increases in self-esteem and this correlated with the frequency with which participants employed the psychological strategies in daily life.

These findings suggest that self-blame-rebalance neurofeedback may be superior over a solely psychological intervention in non-anxious MDD, although further confirmatory studies are needed. Simple self-guided strategies tackling self-blame were beneficial, but need to be compared against treatment-as-usual in further trials. https://doi.org/10.1186/ISRCTN10526888

Evidence suggests that cognitive subtypes exist in schizophrenia that may reflect different neurobiological trajectories. We aimed to identify whether IQ-derived cognitive subtypes are present in early-phase schizophrenia-spectrum disorder and examine their relationship with brain structure and markers of neuroinflammation.

161 patients with recent-onset schizophrenia spectrum disorder (<5 years) were recruited. Estimated premorbid and current IQ were calculated using the Wechsler Test of Adult Reading and a 4-subtest WAIS-III. Cognitive subtypes were identified with k-means clustering. Freesurfer was used to analyse 3.0 T MRI. Blood samples were analysed for hs-CRP, IL-1RA, IL-6 and TNF-α.

Three subtypes were identified indicating preserved (PIQ), deteriorated (DIQ) and compromised (CIQ) IQ. Absolute total brain volume was significantly smaller in CIQ compared to PIQ and DIQ, and intracranial volume was smaller in CIQ than PIQ (F(2, 124) = 6.407, p = 0.002) indicative of premorbid smaller brain size in the CIQ group. CIQ had higher levels of hs-CRP than PIQ (F(2, 131) = 5.01, p = 0.008). PIQ showed differentially impaired processing speed and verbal learning compared to IQ-matched healthy controls.

The findings add validity of a neurodevelopmental subtype of schizophrenia identified by comparing estimated premorbid and current IQ and characterised by smaller premorbid brain volume and higher measures of low-grade inflammation (CRP).

As an accelerated cognitive decline frequently heralds onset of severe neuropathological disorders, understanding the source of individual differences in withstanding the onslaught of cognitive ageing may highlight how best cognitive abilities may be retained into advanced age.

Using a population representative sample of 5088 adults aged •50 years from the English Longitudinal Study of Ageing, we investigated relationships of polygenic predisposition to general cognition with a rate of change in cognition during a 10-year follow-up period. Polygenic predisposition was measured with polygenic scores for general cognition (GC-PGS). Cognition was measured employing tests for verbal memory and semantic fluency.

The average baseline memory score was 11.1 (s.d. = 2.9) and executive function score was 21.5 (s.d. = 5.8). An increase in GC-PGS by one standard deviation (1-s.d.) was associated with a higher baseline verbal memory by an average 0.27 points (95% CI 0.19–0.34, p < 0.001). Similarly, 1-s.d. increase in GC-PGS was associated with a higher semantic fluency score at baseline in the entire sample (β = 0.45, 95% CI 0.27–0.64, p < 0.001). These associations were significant for women and men, and all age groups. Nonetheless, 1-s.d. increase in GC-PGS was not associated with decreases in verbal memory nor semantic fluency during follow-up in the entire sample, as well stratified models by sex and age.

Although common genetic variants associated with general cognition additively are associated with a stable surplus to cognition in adults, a polygenic predisposition to general cognition is not associated with age-related cognitive decline during a 10-year follow-up.

Previous studies have shown a negative impact of the COVID-19 pandemic and its associated sanitary measures on mental health, especially among adolescents and young adults. Such a context may raise many concerns about the COVID-19 pandemic long-term psychological effects. An analysis of administrative databases could be an alternative and complementary approach to medical interview-based epidemiological surveys to monitor the mental health of the population. We conducted a nationwide study to describe the consumption of anxiolytics, antidepressants and hypnotics during the first year of the COVID-19 pandemic, compared to the five previous years.

A historic cohort study was conducted by extracting and analysing data from the French health insurance database between 1 January 2015 and 28 February 2021. Individuals were classified into five age-based classes. Linear regression models were performed to assess the impact of the COVID-19 pandemic period on the number of drug consumers, in introducing an interaction term between time and COVID-19 period.

Since March 2020, in all five age groups and all three drug categories studied, the number of patients reimbursed weekly has increased compared to the period from January 2015 to February 2020. The youngest the patients, the more pronounced the magnitude.

Monitoring the consumption of psychiatric medications could be of great interest as reliable indicators are essential for planning public health strategies. A post-crisis policy including reliable monitoring of mental health must be anticipated.

Schizophrenia is a severely debilitating psychiatric disorder with high heritability and polygenic architecture. A higher polygenic risk score for schizophrenia (SzPRS) has been associated with smaller gray matter volume, lower activation, and decreased functional connectivity (FC). However, the effect of polygenic inheritance on the brain white matter microstructure has only been sparsely reported.

Eighty-four patients with first-episode schizophrenia (FES) patients and ninety-three healthy controls (HC) with genetics, diffusion tensor imaging (DTI), and resting-state functional magnetic resonance imaging (rs-fMRI) data were included in our study. We investigated impaired white matter integrity as measured by fractional anisotropy (FA) in the FES group, further examined the effect of SzPRS on white matter FA and FC in the regions connected by SzPRS-related white matter tracts.

Decreased FA was observed in FES in many commonly identified regions. Among these regions, we observed that in the FES group, but not the HC group, SzPRS was negatively associated with the mean FA in the genu and body of corpus callosum, right anterior corona radiata, and right superior corona radiata. Higher SzPRS was also associated with lower FCs between the left inferior frontal gyrus (IFG)–left inferior temporal gyrus (ITG), right IFG–left ITG, right IFG–left middle frontal gyrus (MFG), and right IFG–right MFG in the FES group.

Higher polygenic risks are linked with disrupted white matter integrity and FC in patients with schizophrenia. These correlations are strongly driven by the interhemispheric callosal fibers and the connections between frontotemporal regions.

Although the ICD and DSM differentiate between different psychiatric disorders, these often share symptoms, risk factors, and treatments. This was a population-based, case–control, sibling study examining familial clustering of all psychiatric disorders and low IQ, using data from the Israel Draft-Board Registry on all Jewish adolescents assessed between 1998 and 2014.

We identified all cases with autism spectrum disorder (ASD, N = 2128), severe intellectual disability (ID, N = 9572), attention-deficit hyperactive disorder (ADHD) (N = 3272), psychotic (N = 7902), mood (N = 9704), anxiety (N = 10 606), personality (N = 24 816), or substance/alcohol abuse (N = 791) disorders, and low IQ (⩾2 SDs below the population mean, N = 31 186). Non-CNS control disorders were adolescents with Type-1 diabetes (N = 2427), hernia (N = 29 558) or hematological malignancies (N = 931). Each case was matched with 10 age-matched controls selected at random from the Draft-Board Registry, with replacement, and for each case and matched controls, we ascertained all full siblings. The main outcome measure was the relative recurrence risk (RRR) of the sibling of a case having the same (within-disorder RRR) or a different (across-disorder RRR) disorder.

Within-disorder RRRs were increased for all diagnostic categories, ranging from 11.53 [95% confidence interval (CI): 9.23–14.40] for ASD to 2.93 (95% CI: 2.80–3.07) for personality disorders. The median across-disorder RRR between any pair of psychiatric disorders was 2.16 (95% CI: 1.45–2.43); the median RRR between low IQ and any psychiatric disorder was 1.37 (95% CI: 0.93–1.98). There was no consistent increase in across-disorder RRRs between the non-CNS disorders and psychiatric disorders and/or low IQ.

These large population-based study findings suggest shared etiologies among most psychiatric disorders, and low IQ.

This study examined the pattern of medical utilization and the distribution of comorbidities shortly before death among adolescents who died from suicide and compared these data with those of living controls.

From Taiwan's National Health Insurance Research Database, this study identified adolescents aged 10–19 years who died from suicide (n = 935) between 1 January 2000, and 31 December 2016, by linking each patient with the national mortality database. The researchers conducted a nested case–control study through risk set sampling, and for each case, 20 age- and sex-matched controls (n = 18 700) were selected from the general population. The researchers applied conditional logistic regression to investigate differences in medical utilization and physical and psychiatric comorbidities between cases and controls.

Cases had a higher proportion of contact with the psychiatric department but a similar proportion of contact with any non-psychiatric medical department within 1 year before suicide compared with controls. There were 18.6% of adolescent suicide victims who only had contacted with a psychiatric department 3 months before suicide. Moreover, cases had a higher proportion of contact with non-psychiatric services within 3 months before suicide, particularly with emergency, surgery, and internal medicine departments. Cases had higher risks of several psychiatric disorders and physical illnesses, including heart diseases, pneumonia, and ulcer disease, than did controls.

The findings of increased medical utilization and higher risks of physical and psychiatric comorbidities in adolescent suicide victims are crucial for developing specific interventions to prevent suicide in this population.

Self-harm in pregnancy or the year after birth (‘perinatal self-harm’) is clinically important, yet prevalence rates, temporal trends and risk factors are unclear.

A cohort study of 679 881 mothers (1 172 191 pregnancies) was conducted using Danish population register data-linkage. Hospital treatment for self-harm during pregnancy and the postnatal period (12 months after live delivery) were primary outcomes. Prevalence rates 1997–2015, in women with and without psychiatric history, were calculated. Cox regression was used to identify risk factors.

Prevalence rates of self-harm were, in pregnancy, 32.2 (95% CI 28.9–35.4)/100 000 deliveries and, postnatally, 63.3 (95% CI 58.8–67.9)/100 000 deliveries. Prevalence rates of perinatal self-harm in women without a psychiatric history remained stable but declined among women with a psychiatric history. Risk factors for perinatal self-harm: younger age, non-Danish birth, prior self-harm, psychiatric history and parental psychiatric history. Additional risk factors for postnatal self-harm: multiparity and preterm birth. Of psychiatric conditions, personality disorder was most strongly associated with pregnancy self-harm (aHR 3.15, 95% CI 1.68–5.89); psychosis was most strongly associated with postnatal self-harm (aHR 6.36, 95% CI 4.30–9.41). For psychiatric disorders, aHRs were higher postnatally, particularly for psychotic and mood disorders.

Perinatal self-harm is more common in women with pre-existing psychiatric history and declined between 1997 and 2015, although not among women without pre-existing history. Our results suggest it may be a consequence of adversity and psychopathology, so preventative intervention research should consider both social and psychological determinants among women with and without psychiatric history.

The search for relevant biomarkers of major depressive disorder (MDD) is challenged by heterogeneity; biological alterations may vary in patients expressing different symptom profiles. Moreover, most research considers a limited number of biomarkers, which may not be adequate for tagging complex network-level mechanisms. Here we studied clusters of proteins and examined their relation with MDD and individual depressive symptoms.

The sample consisted of 1621 subjects from the Netherlands Study of Depression and Anxiety (NESDA). MDD diagnoses were based on DSM-IV criteria and the Inventory of Depressive Symptomatology questionnaire measured endorsement of 30 symptoms. Serum protein levels were detected using a multi-analyte platform (171 analytes, immunoassay, Myriad RBM DiscoveryMAP 250+). Proteomic clusters were computed using weighted correlation network analysis (WGCNA).

Six proteomic clusters were identified, of which one was nominally significantly associated with current MDD (p = 9.62E-03, Bonferroni adj. p = 0.057). This cluster contained 21 analytes and was enriched with pathways involved in inflammation and metabolism [including C-reactive protein (CRP), leptin and insulin]. At the individual symptom level, this proteomic cluster was associated with ten symptoms, among which were five atypical, energy-related symptoms. After correcting for several health and lifestyle covariates, hypersomnia, increased appetite, panic and weight gain remained significantly associated with the cluster.

Our findings support the idea that alterations in a network of proteins involved in inflammatory and metabolic processes are present in MDD, but these alterations map predominantly to clinical symptoms reflecting an imbalance between energy intake and expenditure.