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.

The incidence of restless legs syndrome (RLS) is presumed to be higher among people with schizophrenia who take antipsychotic medication, most of which blocks the dopamine D2 receptor. The purpose of this study was to determine whether the G-protein β3 subunit (GNB3) C825T polymorphism is associated with antipsychotic-induced RLS in schizophrenia.

We examined 178 Korean patients with schizophrenia. All of the subjects were evaluated using the diagnostic criteria of the International Restless Legs Syndrome Study Group and the International Restless Legs Scale. Genotyping was performed for the C825T polymorphism in the GNB3 gene.

The genotype distribution did not differ significantly between antipsychotic-induced RLS patients and patients who had no-RLS symptoms (χ2 = 4.30, p = 0.116). The genotypes of the C825T single-nucleotide polymorphism (SNP) were classified into two groups: C+ (CC and CT genotypes) and C– (TT genotype). The presence of the C allele (C+) was associated with an increased likelihood of RLS (χ2 = 4.14, p = 0.042; odds ratio = 2.56, 95% confidence interval = 1.02–6.47).

These results suggest that the GNB3 C825T SNP is associated with RLS in schizophrenia. However, confirming this association requires future larger scale studies in which the effects of medication are strictly controlled.