Chronotype of Patients With Type 2 Diabetes and Effect on Glycaemic Control

Study Overview
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Brief Summary
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The aim of this study is to explore the associations between chronotype and glycaemic control, cardiometabolic health and other lifestyle factors.

Detailed Description
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The incidence and prevalence of diabetes mellitus has now reached over 4 million in the UK. Type 2 diabetes mellitus (T2DM) accounts for approximately 90% of the UK population with diabetes and confers significant morbidity and mortality on patients and healthcare systems. Despite new therapies and management tools to improve quality of life and outcomes for patients with T2DM, diabetic complications with cardiovascular disease (CVD) remains the greatest cause of mortality. New paradigms for characterising and treating these patients could enhance current T2DM management. Recently, there has been considerable interest in the association between quantity and quality of sleep and circadian rhythms and the development of cardiometabolic disease especially metabolic syndrome, T2DM and CVD. A U-shaped relationship related to both short and long sleep duration exists between sleep duration and T2DM, obesity, CVD, hypertension and stroke. A meta-analysis of nearly 500,000 individuals ( 4% T2DM) identified a relative risk (RR) of 1.14 (95% CI 1.03-1.26) for every additional hour of sleep and RR 1.09 (95% CI 1.04-1.15) with each hour of shorter sleep compared to 7-hours sleep per day for the development of T2DM. Despite this many individuals do not consider sleep essential for good health but instead consider it to be rather more of an inconvenience. Subsequently, lifestyle choices, societal pressures and shift-work render the population chronically sleep deprived and thus at increased risk of metabolic dysfunction. Sleep is regulated, in part, by a homeostatic drive and is therefore unavoidable in humans (without sleep disorders). The circadian system, our internal clock, is also responsible for the regulation of sleep. Sleep is a multidimensional behaviour (and biological process) where the investigators need to not only consider duration and quality but timing also. A person's sleep pattern, in relation to the 24-hour clock, i.e. timing, is individual to them and referred to as their chronotype. The investigators can quantitatively characterize these individual differences in daily timing using a number of questionnaire based tools. Five different chronotypes have been identified using the 'Morningness-Eveningness' Questionnaire i.e. definite evening type, moderate evening type, intermediate, moderate morning type and definite morning type.The identification of these different chronotypes, which describes preferred circadian phases, into, at the two extremes, morning type and evening type has led to further research confirming that evening types are at greater risk of cardiometabolic disease. The underlying causes have not been clearly defined but appear to be related to circadian mal-alignment causing chronic sleep deprivation and leading to dysregulation of metabolic, immune and hormonal processes that govern energy regulation and glycaemic control. Several clock genes have been identified in the control of circadian rhythms including Clock (Circadian locomotor output cycles protein kaput), Npas2 (Neuronal PAS domain protein2), Bmal1 (Brain and muscle ARNT-like protein), Per1 (Period), Per2, Per3, Cry1 (Cryptochrome), Cry2, Rev-Erbs (Reverse erythroblastosis virus) and CkI (Casein kinase). However their role if any, in prevention and progression in T2DM remains to be elucidated. The concept of social jetlag has been developed to describe the deleterious effects of chronic sleep deprivation related to weekday occupational obligations on evening types and weekend social demands on morning types. For example, a large epidemiological study in Germany has shown that social jetlag is associated with obesity. Several public health questions are raised by these associations, not least whether chronotyping of all individuals should be considered and whether the individual chronotype can be adjusted by sleep hygiene and training (which requires discipline for maintenance) and/or exogenous treatment with melatonin. In this cross-sectional observational study, the investigators therefore propose to extensively chronotype a sample of patients with T2DM, and to determine the impact of chronotype on glycaemic control, insulin resistance, biochemical profile, and inflammatory, adipocytokine and genetic markers using a validated questionnaire and blood tests. In an optional sub-study we will explore the association between chronotype and objectively measured physical activity, energy intake and clock genes.

Official Title
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Chronotype of Patients With Type 2 Diabetes and Effect on Glycaemic Control: The CODEC Study

Conditions
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Type2 Diabetes

Participation Criteria
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Eligibility Criteria
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Inclusion Criteria: Participant is willing and able to give informed consent for participation in the study Established T2DM (>6months since diagnosis) Male or Female Aged 18-75 years inclusive BMI 23-45kg/m² inclusive No known sleep disorders except OSA HbA1c up to and below 10% (86mmol/mol) On any glucose-lowering therapy or lifestyle modification for management of T2DM Good command of the English language Exclusion Criteria: Participant is unwilling or unable to give informed consent Anyone without a good command of the English language Anyone <18 years of age and >75 years of age HbA1c above 10% (86mmol/mol) BMI>45 or <23 kg/m² A cannabis user Have a terminal illness A known sleep disorder that is not OSA Taking wakefulness promoting medication i.e. Modafinil as an adjunct to the management of OSA-related sleepiness

Ages Eligible for Study
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Minimum Age: 18 Years
Maximum Age: 75 Years

Sexes Eligible for Study
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All

Accepts Healthy Volunteers
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No

Study Plan
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How is the study designed?
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What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Choronotype (As defined by the MEQ chronotype categories and a HBA1C level (mmol/mnol) measured from a blood sample.) |  | Baseline (1 time point) | 

Secondary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Mid-Sleep Time (MSF) - on both free and work days |  | Baseline (1 time point) | 
| Glucose (mmol/L) |  | Baseline (1 time point) | 
| Insulin (mmol/L) |  | Baseline (1 time point) | 
| C-Peptide (ng/mL (conventional units), or nmol/L (SI)) |  | Baseline (1 time point) | 
| Total cholesterol levels (mmol/L) |  | Baseline (1 time point) | 
| HDL-cholesterol levels (mmol/L) |  | Baseline (1 time point) | 
| LDL-cholesterol levels (mmol/L) |  | Baseline (1 time point) | 
| Trigylceride levels(mmol/L) |  | Baseline (1 time point) | 
| Liver function test (including AST, ALT, ALP and albumin) |  | Baseline (1 time point) | 
| Weight (Kg) |  | Baseline (1 time point) | 
| Body composition via bioimpedance |  | Baseline (1 time point) | 
| Height (cm) |  | Baseline (1 time point) | 
| Blood pressure (mmHg) |  | Baseline (1 time point) | 
| hsCRP (mg/L) | Biomarker of inflammation | Baseline (1 time point) | 
| Levels of physical activity (Recall Physical Activity Questionnaire,RPAQ) |  | Baseline (1 time point) | 
| Duration of diabetes |  | Baseline (1 time point) | 
| Consumption of Pathogen Associated Molecular Patterns (PAMPs) |  | Baseline (1 time point) | 
| Sleep duration (self-report) |  | Baseline (1 time point) | 
| Physical function (self - report) |  | Baseline (1 time point) | 
| Physical performance (Short Physical Performance Battery (SPPB) plus hand grip) |  | Baseline (1 time point) | 
| Objective measures of physical activity and sleep duration (GENEActiv) |  | Baseline (1 time point) | 
| Energy intake (24-hour dietary recall (DR)) |  | Baseline (1 time point) | 
| Clock genes (whole blood sample) |  | Baseline (1 time point) | 
| Temporal distribution of calorie intake (determined by 24-hr food recall) |  | Baseline (1 time point) | 
| Prevalence of each chronotype category |  | Baseline (1 time point) | 
| IL-6 (pg/ml) | Biomarker of inflammation | Baseline (1 time point) | 
| Leptin (ng/L) | Biomarker of inflammation | Baseline (1 time point) | 
| Adiponectin (pg/ml) | Biomarker of inflammation | Baseline (1 time point) | 
| Age of onset | Age at which the participant was diagnosed with Type 2 Diabetes | Baseline (1 time point) |