Cohort profile: BioMD-Y (biopsychosocial factors of major depression in youth) - a biobank study on the molecular genetics and environmental factors of depression in children and adolescents in Munich.

Purpose: BioMD-Y is a comprehensive biobank study of children and adolescents with major depression (MD) and their healthy peers in Germany, collecting a host of both biological and psychosocial information from the participants and their parents with the aim of exploring genetic and environmental risk and protective factors for MD in children and adolescents.

Participants: Children and adolescents aged 8-18 years are recruited to either the clinical case group (MD, diagnosis of MD disorder) or the typically developing control group (absence of any psychiatric condition).

Findings To Date: To date, four publications on both genetic and environmental risk and resilience factors (including , glucocorticoid receptor activation, polygenic risk scores, psychosocial and sociodemographic risk and resilience factors) have been published based on the BioMD-Y sample.

[Overview of chronobiological and sleep medical aspects of depression in adolescents].

Changes in sleep are reported in adolescents with depression with a frequency of up to 71%. Aspects of chronobiology and sleep based on the current scientific literature are illustrated and summarized in this narrative review. The circadian clock synchronizes organisms to the light-dark structure of the environment.

Chronotype, Social Jetlag, and Nicotine Use.

Late chronotype, which often leads to higher social jetlag (SJL), is strongly associated with the prevalence of smoking. Any circadian disruption, strain, or misalignment, results in people not being able to live according to their biological time as is described by SJL, which we will therefore use as umbrella term. We hypothesized two scenarios potentially explaining the association between smoking and SJL: (A) If smoking delays the clock, circadian phase should advance upon quitting.

Validation of the Munich Actimetry Sleep Detection Algorithm for estimating sleep-wake patterns from activity recordings.

Periods of sleep and wakefulness can be estimated from wrist-locomotor activity recordings via algorithms that identify periods of relative activity and inactivity. Here, we evaluated the performance of our Munich Actimetry Sleep Detection Algorithm. The Munich Actimetry Sleep Detection Algorithm uses a moving 24-h threshold and correlation procedure estimating relatively consolidated periods of sleep and wake.

The µMCTQ: An Ultra-Short Version of the Munich ChronoType Questionnaire.

Individuals vary in how their circadian system synchronizes with the cyclic environment (zeitgeber). Assessing these differences in "phase of entrainment"-often referred to as chronotype-is an important procedure in laboratory experiments and epidemiological studies but is also increasingly applied in circadian medicine, both in diagnosis and therapy. While biochemical measurements (e.