Predicting Inter-individual Differences in Biochemical and Behavioral Response to Meals With Different Nutritional Compositions Using Metabolomic and Microbiome Profiling.
试验速览
- 阶段
- 不适用
- 入组人数
- 2,500
- 试验地点
- 1
- 主要终点
- Gut microbiome profile
研究概览
简要总结
The foods we eat - our diet - can affect whether we develop diseases during our lives, such as diabetes or heart disease. This is because the amount and types of foods we eat can affect our weight, and because different foods are metabolised (processed) by the body in different ways.
Scientists have also found that the bacteria in our guts (the gut microbiome) affects our metabolism, weight and health and that, together with a person's diet and metabolism, could be used to predict appetite and how meals affect levels of sugar (glucose) and fats (lipids) found in blood after eating. If blood sugar and fat are too high too often, there's a greater chance of developing diseases such as diabetes.
The gut microbiome is different in different people. Only 10-20% of the types of bacteria found in our guts are found in everyone. This might mean that the best diet to prevent disease needs matching to a person's gut microbiome and it might be possible to find personalised foods or diets that will help reduce the chance of developing chronic disease as well as metabolic syndrome.
The study investigators are recruiting volunteers aged 18 years or over from the TwinsUK cohort to take part in a study that aims to answer the questions above. The participants will need to come in for a clinical visit where they will give blood, stool, saliva and urine samples. The participants will also be given a standardised breakfast and lunch and fitted with a glucose monitor (Abbott Freestyle Libre-CE marked) to monitor their blood sugar levels. After the visit, the participants will be asked to eat standardised meals at home for breakfast for a further 12 days. Participants will also be required to prick their fingers at regular intervals to collect small amounts of blood, and to record constantly their appetite, food, physical activity and sleep using apps and wearable devices.
详细描述
Choice of design: The study is a single arm mechanistic intervention study.
Study population: Twin participants will be recruited from the TwinsUK database and non-twins will be recruited via social media platforms and advertising campaigns.
Screening Assessment: Prospective participants will be selected based on the defined inclusion and exclusion criteria by the study management team. Recruitment will be done over the phone and via the Internet and emails and prospective participants will be booked in for their initial appointment to acquire baseline measurements.
Study duration: Each participant will take part in the study for a period of up to 3 weeks.
The PREDICT study will be divided into 3 protocol cohorts, where all participants (n=2,500) complete a baseline clinical visit as described below. Of this total, Cohort 1 (n=1,150) will complete a home-based dietary intervention lasting up to 2 weeks (June 2018 - May 2019). Within this group, 100 participants will complete an additional home-based dietary intervention lasting up to 3 weeks (February 2019 - May 2019).
研究设计
- 研究类型
- Interventional
- 分配方式
- Na
- 干预模型
- Single Group
- 主要目的
- Basic Science
- 盲法
- None
入排标准
- 年龄范围
- 18 Years 至 —（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 是
入选标准
- •Participant eligibility includes those aged >18 years who have a body mass index (BMI) between 20 and 49.9 kg/m
- •Eligibility within a subgroup of participants undergoing the home-based intervention (n=1,100) will require participants to be 18-65 years of age.
- •Eligibility within a further subgroup of participants undergoing cardiometabolic phenotyping (n=50) will require participants to be >55 years of age.
排除标准
- •Refuse or are unable to give informed consent to participate in the study
- •Have ongoing inflammatory disease ie RA, SLE, polymyalgia and other connective tissue diseases.
- •Have had cancer in the last three years, excluding skin cancer.
- •Have had long term gastrointestinal disorders including inflammatory bowel disease (IBD) or Coeliac disease (gluten allergy), but not including IBS.
- •Are taking the following daily medications: immunosuppressants, antibiotics in the last three months.
- •Are long-term users of PPIs (such as omeprazole and pantoprazole), unless they are able to stop two weeks before the start of the study and remain off them during the two weeks of the study.
- •Have type I diabetes mellitus or are taking medications for type II diabetes mellitus. Those not on medications but having a capillary glucose level of >12mmol/l based on HemoCue will be excluded. Screening blood results will be shared with their GP after the study.
- •Are currently suffering from acute clinically diagnosed depression.
- •Have had a heart attack (myocardial infarction) or stroke in the last 6 months.
- •Are pregnant
- •Are vegan, suffering from an eating disorder or unwilling to take foods that are part of the study.
- •For participants continuing onto the home-based intervention (n=2,000), the additional following exclusions apply:
- •Do not have a mobile phone capable of running the digital app, or are unable to use it to operate the app.
- •Have an allergy to adhesives which would prevent proper attachment of the continuous glucose monitor.
- •For participants undergoing cardiometabolic phenotyping and XMRI (n=50), the additional following exclusions apply:
- •Are <55 years of age
- •Are not female
- •Have any kind of non-removable materials on their person that are not permitted under MR imaging.
研究组 & 干预措施
Dietary intervention
2 week dietary intervention using standardized test meals
干预措施: Dietary intervention (Other)
结局指标
主要结局
Gut microbiome profile
时间窗: 1-2 days
Assessment of participants' gut microbiome
Lipids
时间窗: 1 day to 2 weeks
Measurement of blood lipids
Hunger and appetite assessment
时间窗: 2 weeks
Record of hunger and appetite patterns using a digital app
Glucose
时间窗: 2 weeks
Measurement of blood Glucose
Sleep
时间窗: 2 weeks
Record of sleep pattern using a wearable device (i.e. fitness watch)
Physical activity
时间窗: 2 weeks
Record of physical activity using a wearable device (i.e. fitness watch)
次要结局
未报告次要终点