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.

Serotonergic dysfunction may play an important role in motor and nonmotor symptoms of Parkinson’s disease (PD). The loudness dependence of auditory evoked potentials (LDAEP) has been used to evaluate serotonergic activity. Therefore, this study aimed to determine central serotonergic activity using LDAEP in de novo PD according to the age at onset and changes in serotonergic activity after dopaminergic treatment.

A total of 30 patients with unmedicated PD, 16 in the early-onset and 14 in the late-onset groups, were enrolled. All subjects underwent comprehensive neurological examination, laboratory tests, the Unified Parkinson’s Disease Rating Scale, and LDAEP. The LDAEP was calculated as the slope of the two N1/P2 peaks measured at the Cz electrode, first at baseline conditions (pretreatment) and a second time after 12 weeks (post-treatment) following dopaminergic medications.

The absolute values of pretreatment N1/P2 LDAEP (early-onset: late-onset, 0.99 ± 0.68: 1.62 ± 0.88, p = 0.035) and post-treatment N1 LDAEP (early-onset: late-onset, −0.61 ± 0.61: −1.26 ± 0.91, p = 0.03) were significantly lower in the early-onset group compared with those of the late-onset group. In addition, a higher value of pretreatment N1/P2 LDAEP was significantly correlated with the late-onset group (coefficient = 1.204, p = 0.044). The absolute value of the N1 LDAEP decreased after 12 weeks of taking dopaminergic medication (pretreatment: post-treatment, −1.457 ± 1.078: −0.904 ± 0.812, p = 0.0018).

Based on the results of this study, LDAEP could be a marker for serotonergic neurotransmission in PD. Central serotonergic activity assessed by LDAEP may be more preserved in early-onset PD patients and can be altered with dopaminergic medication.

Polycyclic aromatic hydrocarbons (PAH) are common dietary exposures that cross the human placenta and are classified as a probable human carcinogen. The aim of the present study was to investigate the potential impact of exposure to PAH-containing meat consumed during pregnancy on birth outcomes.

Prospective birth cohort study. Only non-smoking women with singleton pregnancies, who were free from chronic disease such as diabetes and hypertension, were included in the study. Maternal consumption of PAH-rich meat was estimated through FFQ. Multiple linear regression was used to assess factors related to higher intake and the association between dietary PAH and birth outcomes.

Republic of Korea, 2006–2011.

Pregnant women (n 778) at 12–28 weeks of gestation enrolled in the Mothers and Children’s Environmental Health (MOCEH) study.

The multivariable regression model showed a significant reduction in birth weight associated with higher consumption level of foods rich in PAH, such as grilled or roasted meat, during pregnancy (β=−17·48 g, P<0·05 for every 1 point higher in meat score). Further adjusting for biomarkers of airborne PAH did not alter this association. There was no evidence that higher consumption level of PAH-rich meat shortens the duration of gestation (P=0·561). Regression models performed for birth length and head circumference produced negative effects that were not statistically significant.

Consumption of higher levels of barbecued, fried, roasted and smoked meats during pregnancy was associated with reduced birth weight. Dietary risk of PAH exposure in Korean women is of concern.

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.

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.