We aimed to analyse the evolving trends in macronutrient intake and dietary composition among Korean children and adolescents over a 10-year period.

We utilised cross-sectional data from the Korean National Health and Nutrition Examination Survey (KNHANES) spanning the years 2010–2020. Overall, the study included 11 861 participants aged 6–18 years who completed the 24-h dietary recall survey. Subsequently, we assessed trends in energy consumption and macronutrient intake across population subgroups, including age, sex and obesity status. Survey-weighted linear regression was employed to determine the β coefficient and P-value for trends in dietary nutrient consumption, treating the survey year as a continuous variable.

KNHANES from 2010 to 2020.

11 861 children and adolescents aged 6–18 years.

Total energy intake significantly decreased across the 10-year survey period, with a corresponding decline in the percentage of energy intake from carbohydrates. Conversely, the proportion of energy intake from fat increased during the same period. Subgroup analysis revealed changes in the composition of energy intake across age, sex and obesity status, with a consistent increase in total fat intake observed across all subgroups. Upon analysing data on dietary fibres, total sugars and fat subtypes intake, we found insufficient dietary fibre intake and increased intake of all fat subtypes.

This study underscores the gradually changing dietary intake patterns among Korean children and adolescents. Our findings revealed that these transitions in dietary nutrient consumption may pose potential risks of diet-related diseases in the future.

Although disconnectivity among brain regions has been one of the main hypotheses for schizophrenia, the superficial white matter (SWM) has received less attention in schizophrenia research than the deep white matter (DWM) owing to the challenge of consistent reconstruction across subjects.

We obtained the diffusion magnetic resonance imaging (dMRI) data of 223 healthy controls and 143 patients with schizophrenia. After harmonising the raw dMRIs from three different studies, we performed whole-brain two-tensor tractography and fibre clustering on the tractography data. We compared the fractional anisotropy (FA) of white matter tracts between healthy controls and patients with schizophrenia. Spearman’s rho was adopted for the associations with clinical symptoms measured by the Positive and Negative Syndrome Scale (PANSS). The Bonferroni correction was used to adjust multiple testing.

Among the 33 DWM and 8 SWM tracts, patients with schizophrenia had a lower FA in 14 DWM and 4 SWM tracts than healthy controls, with small effect sizes. In the patient group, the FA deviations of the corticospinal and superficial–occipital tracts were negatively correlated with the PANSS negative score; however, this correlation was not evident after adjusting for multiple testing.

We observed the structural impairments of both the DWM and SWM tracts in patients with schizophrenia. The SWM could be a potential target of interest in future research on neural biomarkers for schizophrenia.

Predicting the course of depression is necessary for personalized treatment. Impaired glucose metabolism (IGM) was introduced as a promising depression biomarker, but no consensus was made. This study aimed to predict IGM at the time of depression diagnosis and examine the relationship between long-term prognosis and predicted results.

Clinical data were extracted from four electronic health records in South Korea. The study population included patients with depression, and the outcome was IGM within 1 year. One database was used to develop the model using three algorithms. External validation was performed using the best algorithm across the three databases. The area under the curve (AUC) was calculated to determine the model’s performance. Kaplan–Meier and Cox survival analyses of the risk of hospitalization for depression as the long-term outcome were performed. A meta-analysis of the long-term outcome was performed across the four databases.

A prediction model was developed using the data of 3,668 people, with an AUC of 0.781 with least absolute shrinkage and selection operator (LASSO) logistic regression. In the external validation, the AUCs were 0.643, 0.610, and 0.515. Through the predicted results, survival analysis and meta-analysis were performed; the hazard ratios of risk of hospitalization for depression in patients predicted to have IGM was 1.20 (95% confidence interval [CI] 1.02–1.41, p = 0.027) at a 3-year follow-up.

We developed prediction models for IGM occurrence within a year. The predicted results were related to the long-term prognosis of depression, presenting as a promising IGM biomarker related to the prognosis of depression.

Predictive values of multiple serum biomarkers for suicidal behaviours (SBs) have rarely been tested. This study sought to evaluate and develop a panel of multiple serum biomarkers for predicting SBs in outpatients receiving a 12-month pharmacotherapy programme for depressive disorders.

At baseline, 14 serum biomarkers and socio-demographic/clinical characteristics including previous suicidal attempt and present suicidal severity were evaluated in 1094 patients with depressive disorders without a bipolar diagnosis. Of these, 884 were followed for increased suicidal severity and fatal/non-fatal suicide attempt outcomes over a 12-month treatment period. Individual and combined effects of serum biomarkers on these two prospective SBs were estimated using logistic regression analysis after adjustment for relevant covariates.

Increased suicidal severity and fatal/non-fatal suicide attempt during the 12-month pharmacotherapy were present in 155 (17.5%) and 38 (4.3%) participants, respectively. Combined cortisol, total cholesterol, and folate serum biomarkers predicted fatal/non-fatal suicide attempt, and these with interleukin-1 beta and homocysteine additionally predicted increased suicidal severity, with clear gradients robust to adjustment (p values < 0.001).

Application of multiple serum biomarkers could considerably improve the predictability of SBs during the outpatient treatment of depressive disorders, potentially highlighting the need for more frequent monitoring and risk appraisal.

Accumulating evidence suggests that alterations in inflammatory biomarkers are important in depression. However, previous meta-analyses disagree on these associations, and errors in data extraction may account for these discrepancies.

PubMed/MEDLINE, Embase, PsycINFO, and the Cochrane Library were searched from database inception to 14 January 2020. Meta-analyses of observational studies examining the association between depression and levels of tumor necrosis factor-α (TNF-α), interleukin 1-β (IL-1β), interleukin-6 (IL-6), and C-reactive protein (CRP) were eligible. Errors were classified as follows: incorrect sample sizes, incorrectly used standard deviation, incorrect participant inclusion, calculation error, or analysis with insufficient data. We determined their impact on the results after correction thereof.

Errors were noted in 14 of the 15 meta-analyses included. Across 521 primary studies, 118 (22.6%) showed the following errors: incorrect sample sizes (20 studies, 16.9%), incorrect use of standard deviation (35 studies, 29.7%), incorrect participant inclusion (7 studies, 5.9%), calculation errors (33 studies, 28.0%), and analysis with insufficient data (23 studies, 19.5%). After correcting these errors, 11 (29.7%) out of 37 pooled effect sizes changed by a magnitude of more than 0.1, ranging from 0.11 to 1.15. The updated meta-analyses showed that elevated levels of TNF- α, IL-6, CRP, but not IL-1β, are associated with depression.

These findings show that data extraction errors in meta-analyses can impact findings. Efforts to reduce such errors are important in studies of the association between depression and peripheral inflammatory biomarkers, for which high heterogeneity and conflicting results have been continuously reported.

The role of childhood abuse and serum brain-derived neurotrophic factor (BDNF) levels in suicidal behaviour is controversial.

We aimed to investigate the individual and interactive effects of the childhood abuse and serum BDNF on suicidal behaviour before and after pharmacologic treatment in patients with depressive disorders.

At baseline, reported childhood emotional, physical and sexual abuse were ascertained and serum BDNF levels were measured in 1094 patients with depressive disorder, 884 of whom were followed during a 1-year period of stepwise pharmacotherapy. Suicidal behaviours evaluated at baseline were previous suicide attempt and baseline suicide severity, and suicidal behaviours evaluated at follow-up were increased suicide severity and fatal/non-fatal suicide attempt. Individual and interactive associations of any childhood abuse and serum BDNF levels with four types of suicidal behaviours were analysed using logistic regression models, after adjusting relevant covariates.

Individual associations of childhood abuse were significant only with previous suicide attempt, and no significant individual associations were found for serum BDNF with any suicide outcome. However, the presence of both childhood abuse and lower serum BDNF levels was associated with the highest prevalence/incidence of all four suicidal behaviours, with significant interactions for baseline suicide severity and fatal/non-fatal suicide attempt during follow-up.

Synergistic interactive effects of child abuse and serum BDNF levels on suicidal behaviours were found before and after pharmacologic treatment in patients with depressive disorders. Information combining childhood abuse and serum BDNF levels could improve predictions of suicidal behaviour in patients with depressive disorders.

Current evidence on antipsychotic treatment and risk of psychiatric hospitalization in first-episode schizophrenia (FES) is largely based on the findings from randomized clinical trials (RCTs). However, the generalization of the findings to real-world patients is limited due to inherent caveats of the RCT. We aimed to investigate the treatment discontinuation and risk of psychiatric hospitalization using a nationwide population database.

The Health Insurance Review Agency database in South Korea was obtained, and the observation period started from 1 January 2009 to 31 December 2016. We defined the maintenance period as the period from 6-month after the diagnosis of schizophrenia, which is utilized for the main results. For a total of 44 396 patients with FES, a within-individual Cox regression model was used to compare the risk of the treatment discontinuation and psychiatric hospitalization.

In group comparison, a long-acting injectable (LAI) antipsychotic group was associated with the lowest risk of the treatment discontinuation (0.64, 0.55–0.75) and psychiatric hospitalization (0.29, 0.22–0.38) in comparison with a typical antipsychotic group and no use, respectively. Among individual antipsychotics, the lowest risk of the treatment discontinuation was observed in LAI paliperidone (0.46, 0.37–0.66) compared to olanzapine. Clozapine was found to be the most effective antipsychotic in lowering the risk of psychiatric hospitalization as monotherapy compared to no use (0.23, 0.18–0.31).

In real-world patients with FES, LAI paliperidone and clozapine were associated with low treatment discontinuation and better effectiveness in lowering the risk of psychiatric hospitalization.

To investigate the impacts of depression screening, diagnosis and treatment on major adverse cardiac events (MACEs) in acute coronary syndrome (ACS).

Prospective cohort study including a nested 24-week randomised clinical trial for treating depression was performed with 5–12 years after the index ACS. A total of 1152 patients recently hospitalised with ACS were recruited from 2006 to 2012, and were divided by depression screening and diagnosis at baseline and 24-week treatment allocation into five groups: 651 screening negative (N), 55 screening positive but no depressive disorder (S), 149 depressive disorder randomised to escitalopram (E), 151 depressive disorder randomised to placebo (P) and 146 depressive disorder receiving medical treatment only (M).

Cumulative MACE incidences over a median 8.4-year follow-up period were 29.6% in N, 43.6% in S, 40.9% in E, 53.6% in P and 59.6% in M. Compared to N, screening positive was associated with higher incidence of MACE [adjusted hazards ratio 2.15 (95% confidence interval 1.63–2.83)]. No differences were found between screening positive with and without a formal depressive disorder diagnosis. Of those screening positive, E was associated with a lower incidence of MACE than P and M. M had the worst outcomes even compared to P, despite significantly milder depressive symptoms at baseline.

Routine depression screening in patients with recent ACS and subsequent appropriate treatment of depression could improve long-term cardiac outcomes.

Given that only a subgroup of patients with schizophrenia responds to first-line antipsychotic drugs, a key clinical question is what underlies treatment response. Observations that prefrontal activity correlates with striatal dopaminergic function, have led to the hypothesis that disrupted frontostriatal functional connectivity (FC) could be associated with altered dopaminergic function. Thus, the aim of this study was to investigate the relationship between frontostriatal FC and striatal dopamine synthesis capacity in patients with schizophrenia who had responded to first-line antipsychotic drug compared with those who had failed but responded to clozapine.

Twenty-four symptomatically stable patients with schizophrenia were recruited from Seoul National University Hospital, 12 of which responded to first-line antipsychotic drugs (first-line AP group) and 12 under clozapine (clozapine group), along with 12 matched healthy controls. All participants underwent resting-state functional magnetic resonance imaging and [18F]DOPA PET scans.

No significant difference was found in the total PANSS score between the patient groups. Voxel-based analysis showed a significant correlation between frontal FC to the associative striatum and the influx rate constant of [18F]DOPA in the corresponding region in the first-line AP group. Region-of-interest analysis confirmed the result (control group: R2 = 0.019, p = 0.665; first-line AP group: R2 = 0.675, p < 0.001; clozapine group: R2 = 0.324, p = 0.054) and the correlation coefficients were significantly different between the groups.

The relationship between striatal dopamine synthesis capacity and frontostriatal FC is different between responders to first-line treatment and clozapine treatment in schizophrenia, indicating that a different pathophysiology could underlie schizophrenia in patients who respond to first-line treatments relative to those who do not.