Depression is a complex mental health disorder with highly heterogeneous symptoms that vary significantly across individuals, influenced by various factors, including sex and regional contexts. Network analysis is an analytical method that provides a robust framework for evaluating the heterogeneity of depressive symptoms and identifying their potential clinical implications.

To investigate sex-specific differences in the network structures of depressive symptoms in Asian patients diagnosed with depressive disorders, using data from the Research on Asian Psychotropic Prescription Patterns for Antidepressants, Phase 3, which was conducted in 2023.

A network analysis of 10 depressive symptoms defined according to the National Institute for Health and Care Excellence guidelines was performed. The sex-specific differences in the network structures of the depressive symptoms were examined using the Network Comparison Test. Subgroup analysis of the sex-specific differences in the network structures was performed according to geographical region classifications, including East Asia, Southeast Asia, and South or West Asia.

A total of 998 men and 1,915 women with depression were analysed in this study. The analyses showed that all 10 depressive symptoms were grouped into a single cluster. Low self-confidence and loss of interest emerged as the most central nodes for men and women, respectively. In addition, a significant difference in global strength invariance was observed between the networks. In the regional subgroup analysis, only East Asian men showed two distinct clustering patterns. In addition, significant differences in global strength and network structure were observed only between East Asian men and women.

The study highlights the sex-specific differences in depressive symptom networks across Asian countries. The results revealed that low self-confidence and loss of interest are the main symptoms of depression in Asian men and women, respectively. The network connections were more localised in men, whereas women showed a more diverse network. Among the Asian subgroups analysed, only East Asians exhibited significant differences in network structure. The considerable effects of neurovegetative symptoms in men may indicate potential neurobiological underpinnings of depression in the East Asian population.

Mood disorders require consistent management of symptoms to prevent recurrences of mood episodes. Circadian rhythm (CR) disruption is a key symptom of mood disorders to be proactively managed to prevent mood episode recurrences. This study aims to predict impending mood episodes recurrences using digital phenotypes related to CR obtained from wearable devices and smartphones.

The study is a multicenter, nationwide, prospective, observational study with major depressive disorder, bipolar disorder I, and bipolar II disorder. A total of 495 patients were recruited from eight hospitals in South Korea. Patients were followed up for an average of 279.7 days (a total sample of 75 506 days) with wearable devices and smartphones and with clinical interviews conducted every 3 months. Algorithms predicting impending mood episodes were developed with machine learning. Algorithm-predicted mood episodes were then compared to those identified through face-to-face clinical interviews incorporating ecological momentary assessments of daily mood and energy.

Two hundred seventy mood episodes recurred in 135 subjects during the follow-up period. The prediction accuracies for impending major depressive episodes, manic episodes, and hypomanic episodes for the next 3 days were 90.1, 92.6, and 93.0%, with the area under the curve values of 0.937, 0.957, and 0.963, respectively.

We predicted the onset of mood episode recurrences exclusively using digital phenotypes. Specifically, phenotypes indicating CR misalignment contributed the most to the prediction of episodes recurrences. Our findings suggest that monitoring of CR using digital devices can be useful in preventing and treating mood disorders.

There are growing concerns about the impact of the COVID-19 pandemic on the mental health of older adults. We examined the effect of the pandemic on the risk of depression in older adults.

We analyzed data from the prospective cohort study of Korean older adults, which has been followed every 2 years. Among the 2308 participants who completed both the third and the fourth follow-up assessments, 58.4% completed their fourth follow-up before the outbreak of COVID-19 and the rest completed it during the pandemic. We conducted face-to-face diagnostic interviews using Mini International Neuropsychiatric Interview and used Geriatric Depression Scale. We performed generalized estimating equations and logistic regression analyses.

The COVID-19 pandemic was associated with increased depressive symptoms in older adults [b (standard error) = 0.42 (0.20), p = 0.040] and a doubling of the risk for incident depressive disorder even in euthymic older adults without a history of depression (odds ratio = 2.44, 95% confidence interval 1.18–5.02, p = 0.016). Less social activities, which was associated with the risk of depressive disorder before the pandemic, was not associated with the risk of depressive disorder during the pandemic. However, less family gatherings, which was not associated with the risk of depressive disorder before the pandemic, was associated with the doubled risk of depressive disorder during the pandemic.

The COVID-19 pandemic significantly influences the risk of late-life depression in the community. Older adults with a lack of family gatherings may be particularly vulnerable.

Network approach has been applied to a wide variety of psychiatric disorders. The aim of the present study was to identify network structures of remitters and non-remitters in patients with first-episode psychosis (FEP) at baseline and the 6-month follow-up.

Participants (n = 252) from the Korean Early Psychosis Study (KEPS) were enrolled. They were classified as remitters or non-remitters using Andreasen's criteria. We estimated network structure with 10 symptoms (three symptoms from the Positive and Negative Syndrome Scale, one depressive symptom, and six symptoms related to schema and rumination) as nodes using a Gaussian graphical model. Global and local network metrics were compared within and between the networks over time.

Global network metrics did not differ between the remitters and non-remitters at baseline or 6 months. However, the network structure and nodal strengths associated with positive-self and positive-others scores changed significantly in the remitters over time. Unique central symptoms for remitters and non-remitters were cognitive brooding and negative-self, respectively. The correlation stability coefficients for nodal strength were within the acceptable range.

Our findings indicate that network structure and some nodal strengths were more flexible in remitters. Negative-self could be an important target for therapeutic intervention.

Some clinical studies have reported reduced peripheral glial cell line-derived neurotrophic factor (GDNF) level in elderly patients with major depressive disorder (MDD). We verified whether a reduction in plasma GDNF level was associated with MDD.

Plasma GDNF level was measured in 23 healthy control subjects and 23 MDD patients before and after 6 weeks of treatment.

Plasma GDNF level in MDD patients at baseline did not differ from that in healthy controls. Plasma GDNF in MDD patients did not differ significantly from baseline to the end of treatment. GDNF level was significantly lower in recurrent-episode MDD patients than in first-episode patients before and after treatment.

Our findings revealed significantly lower plasma GDNF level in recurrent-episode MDD patients, although plasma GDNF levels in MDD patients and healthy controls did not differ significantly. The discrepancy between our study and previous studies might arise from differences in the recurrence of depression or the ages of the MDD patients.

Decreased hemoglobin levels increase the risk of developing dementia among the elderly. However, the underlying mechanisms that link decreased hemoglobin levels to incident dementia still remain unclear, possibly due to the fact that few studies have reported on the relationship between low hemoglobin levels and neuroimaging markers. We, therefore, investigated the relationships between decreased hemoglobin levels, cerebral small-vessel disease (CSVD), and cortical atrophy in cognitively healthy women and men.

Cognitively normal women (n = 1,022) and men (n = 1,018) who underwent medical check-ups and magnetic resonance imaging (MRI) were enrolled at a health promotion center. We measured hemoglobin levels, white matter hyperintensities (WMH) scales, lacunes, and microbleeds. Cortical thickness was automatically measured using surface based methods. Multivariate regression analyses were performed after controlling for possible confounders.

Decreased hemoglobin levels were not associated with the presence of WMH, lacunes, or microbleeds in women and men. Among women, decreased hemoglobin levels were associated with decreased cortical thickness in the frontal (Estimates, 95% confidence interval, −0.007, (−0.013, −0.001)), temporal (−0.010, (−0.018, −0.002)), parietal (−0.009, (−0.015, −0.003)), and occipital regions (−0.011, (−0.019, −0.003)). Among men, however, no associations were observed between hemoglobin levels and cortical thickness.

Our findings suggested that decreased hemoglobin levels affected cortical atrophy, but not increased CSVD, among women, although the association is modest. Given the paucity of modifiable risk factors for age-related cognitive decline, our results have important public health implications.

Assessment of frontal lobe impairment in amyotrophic lateral sclerosis (ALS) is a matter of great importance, since it often causes ALS patients to decrease medication and nursing compliance, thus shortening their survival time.

The frontal assessment battery (FAB) is a short and rapid method for assessing frontal executive functions. We investigated the applicability of the FAB as a screening method for assessing cognitive impairments in 61 ALS patients. Depending on the results of the FAB, we classified patients into two subgroups: FAB-normal and FAB-abnormal. We then performed additional evaluations of cognitive function using the Korean version of the mini-mental state examination (K-MMSE), a verbal fluency test (COWAT), and a neuropsychiatric inventory (NPI). Results of these tests were compared between the two groups using Mann-Whitney U-tests, and Spearman correlation analyses were used to investigate the relationships between FAB score and disease duration and severity.

Of the 61 sporadic ALS patients included in this study, 14 were classified as FAB-abnormal and 47 were classified as FAB-normal. The FAB-normal and FAB-abnormal patients performed significantly differently in all domains of the COWAT. There was no difference in behavioral disturbance, as assessed by the NPI, between the two groups. The FAB scores were found to significantly correlate with both disease duration and severity.

The FAB shows promise as a method of screening for frontal lobe dysfunction in ALS, as it is not only quick and easy, but also reliable. Additional studies should examine how FAB performance changes as ALS progresses.

There is increasing evidence of a relationship between underweight or obesity and dementia risk. Several studies have investigated the relationship between body weight and brain atrophy, a pathological change preceding dementia, but their results are inconsistent. Therefore, we aimed to evaluate the relationship between body mass index (BMI) and cortical atrophy among cognitively normal participants.

We recruited cognitively normal participants (n = 1,111) who underwent medical checkups and detailed neurologic screening, including magnetic resonance imaging (MRI) in the health screening visits between September 2008 and December 2011. The main outcome was cortical thickness measured using MRI. The number of subjects with five BMI groups in men/women was 9/9, 148/258, 185/128, 149/111, and 64/50 in underweight, normal, overweight, mild obesity, and moderate to severe obesity, respectively. Linear and non-linear relationships between BMI and cortical thickness were examined using multiple linear regression analysis and generalized additive models after adjustment for potential confounders.

Among men, underweight participants showed significant cortical thinning in the frontal and temporal regions compared to normal weight participants, while overweight and mildly obese participants had greater cortical thicknesses in the frontal region and the frontal, temporal, and occipital regions, respectively. However, cortical thickness in each brain region was not significantly different in normal weight and moderate to severe obesity groups. Among women, the association between BMI and cortical thickness was not statistically significant.

Our findings suggested that underweight might be an important risk factor for pathological changes in the brain, while overweight or mild obesity may be inversely associated with cortical atrophy in cognitively normal elderly males.

Epidemiological studies have reported that higher education (HE) is associated with a reduced risk of incident Alzheimer's disease (AD). However, after the clinical onset of AD, patients with HE levels show more rapid cognitive decline than patients with lower education (LE) levels. Although education level and cognition have been linked, there have been few longitudinal studies investigating the relationship between education level and cortical decline in patients with AD. The aim of this study was to compare the topography of cortical atrophy longitudinally between AD patients with HE (HE-AD) and AD patients with LE (LE-AD).

We prospectively recruited 36 patients with early-stage AD and 14 normal controls. The patients were classified into two groups according to educational level, 23 HE-AD (>9 years) and 13 LE-AD (≤9 years).

As AD progressed over the 5-year longitudinal follow-ups, the HE-AD showed a significant group-by-time interaction in the right dorsolateral frontal and precuneus, and the left parahippocampal regions compared to the LE-AD.

Our study reveals that the preliminary longitudinal effect of HE accelerates cortical atrophy in AD patients over time, which underlines the importance of education level for predicting prognosis.

Social support programs for dementia caregivers were widely used in order to reduce care burden. We investigated which types of social supports can reduce psychological and non-psychological burdens of dementia caregivers, and explored the mechanism of those social supports.

We evaluated 731 community-dwelling dementia patients and their caregivers from the National Survey of Dementia Care in South Korea. We investigated the five types of social supports (emotional support, informational support, tangible support, positive social interaction, affectionate support) using the Medical Outcomes Study Social Support Survey in each caregiver. The mechanisms of specific types of social support on psychological/non-psychological burden were examined using path analysis.

Positive social interaction and affectionate support reduced psychological burden via direct and indirect paths. Tangible support reduced the non-psychological burden via direct and indirect paths. Informational support and emotional support were not helpful for reducing psychological or non-psychological burden. A maximum of 20% of psychological burden could be relieved by positive social interaction and 10.3% of that could be reduced by affectionate support. Tangible support was associated with a 15.1% maximal improvement in non-psychological burden.

In order to reduce caregiver burden in dementia effectively, psychosocial interventions should be tailored to target type of caregiver burden.