Sleep, Obesity and Mental Disease - Biological Markers for the Evaluation of Circadian Rhythmicity

NCT ID: NCT05413486

Last Updated: 2024-01-05

Basic Information

• Recruitment Status: RECRUITING
• Total Enrollment: 86 participants
• Study Classification: OBSERVATIONAL
• Study Start Date: 2022-04-04
• Study Completion Date: 2024-07-31

Brief Summary

Introduction

16.8% of the Danish adult population are obese (Body Mass Index> 30 kg / m2). Obesity increases the risk of lifestyle diseases such as type-2 diabetes and non-alcoholic fatty liver. People with mental illness have an increased risk of developing obesity. Both obesity and certain mental disorders (bipolar disorder and schizophrenia) are associated with circadian rhythm disorders. Clinically, this may manifest as reduced sleep quality, depressive symptoms and increased fatigue, but also deregulation of a wide range of bodily processes subject to the circadian rhythm.

In circadian rhythm disorders, the pattern of how mRNA of specific 'clock genes' is expressed in the cell may be affected. These clock genes are associated with obesity, bipolar disorder and schizophrenia. Despite the clear indications of an interplay between mental illness, obesity and circadian rhythm disorders, the relationship between these illnesses are largely unexplored.

Aim

The aim of this study is to investigate circadian disturbances in people with and without obesity, as well as people with obesity and a comorbid diagnosis of either schizophrenia or bipolar disorder.

Methods

The study population will consist of:

1. People with obesity and schizophrenia (N=22)

2. People with obesity and bipolar disorder (N=22)

3. People with obesity without psychiatric disease (N=22)

4. People with BMI 18.5 - 25kg/m2 and no psychiatric disease (N=20)

Study Procedure

Participants will visit the clinic 2 times. At each visit participants fill in questionnaires and perform physical tests. Between visit 1 and 2, participants will over a 2-day period (at-home), collect biological samples (Four hair- and six saliva samples per day). In addition, participants will wear accelerometers and continuous glucose monitors (CGMs) for a total of 8 days, including the 2-day sampling period.

Sampled hair follicles are analyzed for relative expression of clock gene mRNA. Saliva is analyzed for cortisol- and melatonin content. The four participants groups are analyzed and compared on daytime variation in mRNA expression, cortisol- and melatonin concentration, and body temperature.

Perspectives

A comparison of patient groups presenting with mental disease, obesity and circadian disturbances may provide new insight into the association between these diseases.

Detailed Description

Background

Obesity (30 ≥ kg/m2) is a major global health challenge. Worldwide obesity has nearly tripled since 1975 (WHO, 2021) and is projected to continue to rise throughout western society (OECD, 2017).

Obesity increases the risk of type-2 diabetes (T2D), obstructive sleep apnea (OSA), non-alcoholic fatty liver disease (NAFLD), hypertension, osteoarthritis, polycystic ovary syndrome and several other conditions (George et al., 2018; Luque-Ramirez et al., 2014; Mainous, Tanner, Jo, & Anton, 2016). Mortality is significantly increased, and a person with class III obesity (BMI > 40kg/m2) is predicted to live ten years shorter than a normal-weight person of same age (Finkelstein, Brown, Wrage, Allaire, & Hoerger, 2010). People with obesity have more days of sick leave, experience social disadvantages (Hernaes, Andersen, Norheim, & Vage, 2015) and report an overall poorer health-related quality of life compared to non-obese people (Kolotkin & Andersen, 2017).

Obesity and mental disease:

Mental disease is associated with increased risk of obesity. Obesity is approximately two and three times as prevalent in people with bipolar disorders and schizophrenia spectrum disorder compared to people without mental disease, respectively (Annamalai, Kosir, & Tek, 2017; Chao, Wadden, & Berkowitz, 2019; Sicras, Rejas, Navarro, Serrat, & Blanca, 2008). Many commonly used antipsychotic drugs induces weight gain with a magnitude ranging from neutral in some drugs to +5.3 kg in olanzapine (Vancampfort et al., 2015). Antipsychotic-induced weight changes depend of the underlying disease (Moteshafi, Zhornitsky, Brunelle, & Stip, 2012). Many mental diseases are associated with higher calorie intake, poorer food quality (Manu et al., 2015) and lower levels of physical activity (Schuch et al., 2017; Vancampfort et al., 2017).

Obesity, mental disease and circadian disturbances:

The human body adapts cellular, physiological, and behavioral rhythms to the 24-hour light cycle. Disturbing the normal circadian rhythms have dramatic consequences on many health issues ranging from cardiovascular disease to cancer (Morris, Purvis, Hu, & Scheer, 2016; Stevens, Brainard, Blask, Lockley, & Motta, 2014). A sleep pattern concordant with the diurnal rhythm is crucial for maintaining normal body weight. Sleeping incoherently with the circadian-defined sleep hours thus independently associates with overweight and obesity, increasing the relative risk by 31% and 96% respectively (McFadden, Jones, Schoemaker, Ashworth, & Swerdlow, 2014). In people with schizophrenia and bipolar disorders almost all measures of sleep quality and physiological sleep patterns are disturbed, even when their disease is considered well-treated (Meyer et al., 2020).

In human cells, circadian clocks are composed of a set of proteins that generate self-sustained circadian oscillation through positive and negative transcriptional/translational feedback loops. The human circadian clock entails a range of 'clock genes'. For example: The 'Period' genes (per1 and per2) are both parts of the circadian feedback loop. Mice models knocked out for per1/2 completely lacks a diurnal rhythm and gain more weight following a high-fat diet (Dallmann & Weaver, 2010). Dysregulation of per1, per2 and other clock genes have been linked to psychiatric disorders, including depression, schizophrenia and bipolar disorders (Charrier, Olliac, Roubertoux, & Tordjman, 2017).

Altogether disturbance in clock-gene and hormonal rhythmicity might be an important link between mental disease, sleep disturbance and obesity. Sleep disturbances are potentially treatable. Accordingly, restoration of sleep patterns might be a possible target to prevent weight gain and obesity in this group of patients.

Study aim:

To evaluate biological markers of disturbed circadian rhythm in people with obesity and schizophrenia or bipolar disorder.

Overall hypotheses:

People with obesity and schizophrenia or bipolar disorder has disturbed circadian rhythms compared to controls without mental disease.

Methods

Study design:

This will be a single-center case-control study with repeated measures.

Study Population:

The study population will consist of four groups:

1. People with BMI > 30 kg/m2 and schizophrenia spectrum disorder (N=22)

2. People with BMI > 30 kg/m2 and bipolar spectrum disorder (N=22)

3. People with BMI > 30 kg/m2 without psychiatric disease or sleep disorders (N=22)

4. People with BMI 18.5 - 25kg/m2 and no psychiatric disease or sleep disorders (N=20)

Exclusion criterion:

• Participants taking oral supplements of melatonin are excluded if pausing is deemed inappropriate.

Study Procedure:

Participants will visit the clinic two times. Between visits, participants will collect biological samples and data relevant to understanding circadian rhythms over a 2-day period. In addition participants will wear accelerometers and continuous glucose monitors (CGMs) for a total of 8 days.

Clinical visit 1:

During the first clinical visit, a short (<10 min) test battery will be administered. This includes tests of gait function, handgrip strength and balance. In addition weight, height, waist- and hip circumference and body composition (by bioimpedance) are measured. After tests, a short questionnaire is administered.

Finally, body worn sensors (accelerometers and CGMs) are mounted, and the participant is given thorough instruction on how to record dietary intake and perform biological sampling (hair and saliva samples). The two sampling days will, when possible, be placed immediately following clinical visit 1 and at least within 5 days.

At-home testing:

During test day 1 and 2, participants will collect saliva samples ~6 times (depended on bed time) per day and hair samples 4 times per day and record their body temperature and dietary food intake (see "data collection" below). Participants will each day receive home visits from the project manager. If possible, visits will be scheduled around noon in order to aid participants with mid-day sampling. Visits are scheduled to take <20 minutes. During visits, the project manager will administer a short questionnaire on media device usage and sleep environment light exposure.

Clinical visit 2:

Following the two sampling days, participants will again meet at the clinic. During this visit, remaining test equipment and samples are handed over. Afterwards, the patient fills in the Morningness-Eveningness Questionnaire (MEQ). In addition, the test leader will perform a short interview (~10 min) in which participants are asked to rate their experience. If the participant have not been screened for sleep apnea recently (<6months), a time for respiratory sleep monitoring will be scheduled.

Data handling and analyses:

Data will be hosted and handled in accordance with Danish law and regulation. All data Files will be kept for 5 years following study conclusion and subsequently anonymized or deleted.

Statistics:

Disturbances in circadian rhythm will be analyzed by multi-level longitudinal analyses comparing findings between study groups (BMI >30 kg/m2, ≤25 kg/m2, with and without mental disease) adjusted for gender and age. Associations between circadian regulated variables (hormones, temperature, glucose levels and gene expression) will be investigated by correlational analysis.

Power calculation:

Being explorative in nature, there is insufficient data to conduct a candid power-calculation. However recent studies detected significant differences in clock-gene expression between people with and without sleep disturbances with 14 to 20 people in each study group (Canales et al., 2019; Zhanfeng, Hechun, Zhijun, Hongyu, & Zhou, 2019).

Information from patient registries:

After consent is signed, patient journals will be reviewed for information on age, gender, socioeconomic status, medication status and the presence of psychiatric diagnoses (Bi-polar, schizophrenia and depression), medication history and obesity-related disease prevalence.

Financing and insurance:

This is an investigator initiated research project. The Project received 913.000 kr.- from Region Syddanmarks pulje for Fri og Strategisk Forskning 2021 to cover running expenses. Study funds are placed on a dedicated account and the account number has been disseminated to the Regional Committee on Health Research Ethics for Southern Denmark. The investigators or The Department of Medicine, University Hospital South West Jutland have no financial gain regarding the study and have no conflict of interest that could be perceived as prejudicing the impartiality of this study. The patients will not receive payment but reimbursement of travel expenses can be made.

Side effects, risks and complications:

The study is designed to minimize inconvenience by employing a relative short list of outcomes requiring active participant involvement. Moreover, participant work loads are minimized through the use of digital solutions. Participants are not required to record sleep or food diaries and do not need to weigh food items as these are recorded by digital camera.

There are no known risks associated with present study procedure. Participants are informed of potential discomfort when plucking hairs or when mounting the CGM and that some may experience poorer sleep quality when sleeping with the CRM instrument. Participants are encouraged to report any adverse events experienced during or following the study procedure. In case of injury participant are instructed to report their case to the Danish national patient compensation scheme (http://www.patientforsikringen.dk), also linked in the participant information.

Perspectives

Comparative data on patient groups presenting with mental disease, obesity and circadian disturbances may help elucidate the association between these diseases. If circadian disturbances are more pronounced in people with obesity and schizophrenia or bipolar disorder, compared to people with obesity and no mental disease, this highlights the need for treatment effective in normalizing sleep patterns in these patient groups.

Conditions

Bipolar Disorder; Schizophrenia; Obesity; Circadian Rhythm Disorders

Study Design

• Observational Model Type: CASE_CONTROL
• Study Time Perspective: PROSPECTIVE

Study Groups

SCH, OB

People with obesity (BMI \> 30 kg/m2) and a medical diagnosis of schizophrenia spectrum disorder.

Observational

Intervention Type: OTHER

Exposure is defined by group affiliation i.e., Bipolar disorder vs. schizophrenia vs. no disease. Likewise with obesity vs. normal weight.

Biological markers of daytime-circadian rhythmicity is compared across disease and weight groups.

BD, OB

People with obesity (BMI \> 30 kg/m2) and a medical diagnosis of bipolar spectrum disorder.

Observational

Intervention Type: OTHER

Exposure is defined by group affiliation i.e., Bipolar disorder vs. schizophrenia vs. no disease. Likewise with obesity vs. normal weight.

Biological markers of daytime-circadian rhythmicity is compared across disease and weight groups.

Control, OB

Control group with obesity. People with obesity (BMI \> 30 kg/m2) without psychiatric disease or sleep disorders.

Observational

Intervention Type: OTHER

Exposure is defined by group affiliation i.e., Bipolar disorder vs. schizophrenia vs. no disease. Likewise with obesity vs. normal weight.

Biological markers of daytime-circadian rhythmicity is compared across disease and weight groups.

Control, non-OB

Normal weight (BMI 18.5 - 25kg/m2) control group without psychiatric disease.

Observational

Intervention Type: OTHER

Exposure is defined by group affiliation i.e., Bipolar disorder vs. schizophrenia vs. no disease. Likewise with obesity vs. normal weight.

Biological markers of daytime-circadian rhythmicity is compared across disease and weight groups.

Interventions

Observational

Exposure is defined by group affiliation i.e., Bipolar disorder vs. schizophrenia vs. no disease. Likewise with obesity vs. normal weight.

Biological markers of daytime-circadian rhythmicity is compared across disease and weight groups.

Intervention Type: OTHER

Eligibility Criteria

Inclusion Criteria

Fulfilling the criteria for one of the four study groups:

• People with BMI > 30 kg/m2 and schizophrenia spectrum disorder (N=22)
• People with BMI > 30 kg/m2 and bipolar disorder spectrum disorder (N=22)
• People with BMI > 30 kg/m2 without psychiatric disease or sleep disorders (N=22)
• People with BMI 18.5 - 25kg/m2 and no psychiatric disease or sleep disorders (N=20)

Exclusion Criteria

• Participants taking oral supplements of melatonin are excluded if pausing is deemed inappropriate.

• Minimum Eligible Age: 18 Years
• Maximum Eligible Age: 60 Years
• Eligible Sex: ALL
• Accepts Healthy Volunteers: Yes

Sponsors

Steno Diabetes Center Odense

OTHER

Sponsor Role: collaborator

Region of Southern Denmark

OTHER

Sponsor Role: collaborator

Rigshospitalet, Denmark

OTHER

Sponsor Role: collaborator

University of Southern Denmark

OTHER

Sponsor Role: collaborator

Odense University Hospital

OTHER

Sponsor Role: collaborator

Odense Patient Data Explorative Network

OTHER

Sponsor Role: collaborator

Esbjerg Hospital - University Hospital of Southern Denmark

OTHER

Sponsor Role: lead

Responsible Party

Responsibility Role: SPONSOR

Principal Investigators

Claus B Juhl

Role: PRINCIPAL_INVESTIGATOR

University Hospital South West Jutland, Department of Endocrinology

Locations

Hospital South West Jutland

Esbjerg, , Denmark

Site Status: RECRUITING

Countries

Denmark

Central Contacts

Claus B Juhl, phD

Role: CONTACT

Claus.Bogh.Juhl@rsyd.dk

60867272 ext. +45

Mikkel EI Kolind, MSc

Role: CONTACT

mikkel.emil.iwanoff.kolind@rsyd.dk

31135292 ext. +45

Facility Contacts

Mikkel EI Kolind, MSc

Role: primary

mikkel.emil.iwanoff.kolind@rsyd.dk

31135292 ext. +45

Claus B Juhl, PhD

Role: backup

Claus.Bogh.Juhl@rsyd.dk

60867172 ext. +45

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Other Identifiers

21/61643

Identifier Type: -

Identifier Source: org_study_id