Clinical trial NCT05866991: Cohort of Patients Suffering From Major Depressive Episode With Evaluation of Sleep, Circadian Rhythms and Psychiatric Disorders
Official title: Cohort of Patients Suffering From Major Depressive Episode With Evaluation of Sleep, Circadian Rhythms and Psychiatric Disorders
Study type: OBSERVATIONAL
Overall status: RECRUITING
Conditions: Major Depressive Episode
Keywords: Depression
Biomarkers
Depressive
Disorder
Sleep
circadian rhythms
seasonal affective disorder
Lead sponsor: Assistance Publique - Hôpitaux de Paris
Sponsor class: OTHER
First posted: 2023-05-19
Enrollment: 1000
Sex: ALL
Standard ages: CHILD
ADULT
OLDER_ADULT
Observational model: COHORT
Time perspective: PROSPECTIVE
Sampling method: NON_PROBABILITY_SAMPLE
Study population: The entry point for the cohort is any patient with a major depressive episode, in order to integrate the maximum variance in terms of manifestations, and thus to be able to contrast the different clinical pictures according to the biomarkers of sleep and biological rhythms.

The aim of this cohort is to pool the efforts of this network and to homogenise the assessments, in order to characterise more precisely and in a standardised manner the alterations in sleep and rhythms in depressive disorders, according to the different subtypes of disorder.

Brief summary: Despite international efforts to identify biomarkers of depression, none has been transferred to clinical practice, neither for diagnosis, evolution, nor therapeutic response. This led us to build a French national cohort (through the clinical and research network named SoPsy within the French biological psychiatry society (AFPBN) and sleep society (SFRMS)), to better identify markers of sleep and biological rhythms and validate more homogeneous subgroups of patients, but also to specify the manifestations and pathogeneses of depressive disorders.

Detailed description: Depressive disorders are a group of frequent and severe disorders that affect up to 20% of the general population. The WHO projects that depression will be the leading cause of disability by 2030. This growing public health problem is marked by a decrease in psychosocial functioning and quality of life, and is associated with a high rate of suicide. In addition, there is a significant economic impact including loss of productivity and a significant increase in the use of health care services. To date, the diagnosis of a depressive episode is based solely on clinical assessment and diagnostic criteria. Despite international efforts to identify biomarkers of depression, none of these identified biomarkers have been transferred to clinical practice, either for diagnosis, outcome or treatment prediction. Some of the difficulties and lack of replication of certain results are directly related to the nature of depressive disorders, which include a large number of very heterogeneous entities.

Among the markers of interest in patients with a major depressive episode (MDE), the scientific literature has shown close links between depression and disturbances in sleep and biological rhythms. Thus, more than 90% of patients suffering from MDE have sleep complaints (PMID:28972930). Moreover, it is now well demonstrated, via epidemiological and longitudinal follow-up studies, that sleep disorders, and in particular insomnia, are both risk factors and prodromes of MDE. These sleep and rhythm abnormalities seem to persist during remission phases and appear to be risk factors for depressive recurrence. Objective abnormalities, assessed by actigraphy and polysomnography, have also been demonstrated during episodes and in subjects at risk of depression, and thus appear to be both state and trait markers of the disorder. These sleep and circadian rhythm abnormalities, in addition to being associated with depressive relapse, are associated with poor global functioning, poor quality of life and risk of metabolic syndrome.

Moreover, depressive disorders encompass a very heterogeneous set of conditions, and these biomarkers seem to hold great promise for better characterising the different subtypes of disorders and for better characterising patient populations. Finally, these clinical observations make sleep and circadian rhythm abnormalities essential therapeutic targets, making it possible to propose a truly more personalised medicine in psychiatry

It is therefore urgent to better characterise the different subtypes of depressive disorders and to better understand the pathogenesis and evolution of these disorders in order to have predictive markers for conversion, recurrence or therapeutic responses. The objective of identifying such markers would also ultimately be to better screen patients and to propose adapted and personalised therapeutic strategies. The constitution of a national cohort, with a fine and homogeneous characterisation between the centres, is intended to meet these objectives by assessing psychiatry, addiction, sleep and chronobiology dimensions of depressive disorders.

Eligibility criteria: Inclusion Criteria:

* Individuals with depressive episode characterized according to the DSM-5 criteria regardless of the associated characteristics and comorbidities.
* Adult and child
* Affiliated to a social security

Exclusion Criteria:

* don't understand or read french
* Medical condition incompatible with administration of questionnaire
* impossibility to give informed decision (subject in an emergency condition, etc.)

Primary outcomes:
measure: amount of REM sleep
timeFrame: at inclusion
Secondary outcomes:
measure: duration of the first stage of REM sleep
timeFrame: at inclusion
measure: duration of the first episode of N3
timeFrame: at inclusion
measure: latency of the first episode of N3
timeFrame: at inclusion
measure: duration of N1 slow-wave sleep
timeFrame: at inclusion
measure: duration of N2 slow-wave sleep
timeFrame: at inclusion
measure: duration of N3 slow-wave sleep
timeFrame: at inclusion
measure: percentage of slow-wave sleep N1
timeFrame: at inclusion
measure: percentage of slow-wave sleep N2
timeFrame: at inclusion
measure: percentage of slow-wave sleep N3
timeFrame: at inclusion
measure: measurement of total sleep time
timeFrame: at inclusion
measure: sleep efficiency
timeFrame: at inclusion
measure: nocturnal awakenings
timeFrame: at inclusion
measure: latency of different sleep stages
timeFrame: at inclusion
measure: duration of different sleep stages
timeFrame: at inclusion
measure: density of different sleep stages
timeFrame: at inclusion
measure: movement during sleep
timeFrame: at inclusion
measure: percentage of time total sleep spent under 90% SaO2
timeFrame: at inclusion
measure: Mean for iterative latency tests falling asleep
timeFrame: at inclusion
measure: urinary dosage 6-sulfatoxymelatonin over 24 hours.
timeFrame: at inclusion
measure: urinary dosage cortisol over 24 hours.
timeFrame: at inclusion
measure: apnea-hypopnea index
timeFrame: at inclusion
measure: index of periodic leg movements
timeFrame: at inclusion
measure: characterization of the chronotype
timeFrame: at inclusion
measure: characterization of the patient's psychiatric state
timeFrame: at inclusion
measure: Sleep onset and offset
timeFrame: at inclusion
Other outcomes:
Locations:
city: Paris
country: France
facility: Hôpital Bichat Claude Bernard
Study officials:
References: