[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100659640":3},{"organization":4,"outcomesModule":7,"designInfo":156,"detailedDescription":159,"studyPopulation":160,"armGroups":161,"interventions":155,"overallOfficials":171,"centralContacts":179,"locations":188,"responsibleParty":209,"collaborators":212,"id":218,"slug":219,"hasResults":220,"nctId":221,"briefTitle":222,"officialTitle":223,"acronym":224,"eligibilityCriteria":225,"healthyVolunteers":226,"sex":227,"minAge":228,"maxAge":229,"enrollmentInfo":230,"targetDuration":155,"studyType":233,"phases":155,"briefSummary":234,"conditions":235,"keywords":239,"overallStatus":191,"whyStopped":155,"lastUpdateSubmitDate":244,"lastUpdatePostDateStruct":245,"startDateStruct":248,"completionDateStruct":250,"leadSponsor":252,"locationsCount":253},{"fullName":5,"class":6},"German Institute of Human Nutrition","OTHER",{"primaryOutcomes":8,"secondaryOutcomes":13,"otherOutcomes":155},[9],{"measure":10,"description":11,"timeFrame":12},"Glucose incremental Area Under the Curve (iAUC) after a morning test meal","Glucose iAUC \\[mg\u002FdL⋅min\\] measured using continuous glucose monitoring (CGM) after a standardized morning test meal as an average of two test days within the observation period","3 and 10 days",[14,18,21,24,27,30,33,36,39,42,45,48,51,54,57,60,63,66,69,72,75,78,81,84,87,90,93,97,100,103,106,109,112,115,118,121,124,127,130,133,137,140,143,146,149,152],{"measure":15,"description":16,"timeFrame":17},"Body height","Body height \\[m\\] measured using a stadiometer or calibrated wall-mounted measuring tape","2 weeks",{"measure":19,"description":20,"timeFrame":17},"Body weight","Body weight \\[kg\\] measured by scale weight",{"measure":22,"description":23,"timeFrame":17},"Waist and hip circumference","Waist and hip circumference \\[cm\\] measured using tape",{"measure":25,"description":26,"timeFrame":17},"Body Mass Index (BMI)","BMI \\[kg\u002Fm2\\], calculated as weight\u002Fsquare height",{"measure":28,"description":29,"timeFrame":17},"Body composition","Fat and muscle mass \\[kg\\] measured by bioelectrical impedance analysis (BIA)",{"measure":31,"description":32,"timeFrame":17},"Basal metabolic rate","Basal metabolic rate \\[kcal\u002Fday\\] assessed by indirect calorimetry",{"measure":34,"description":35,"timeFrame":17},"Handgrip strength","Maximal isometric handgrip strength \\[kg\\] as measured by a hand-dynamometers",{"measure":37,"description":38,"timeFrame":17},"Blood pressure","Systolic and diastolic blood pressure \\[mm Hg\\], as measured by a blood pressure monitor",{"measure":40,"description":41,"timeFrame":17},"Fasting glucose","Glucose levels \\[mg\u002FdL\\] assessed in fasting blood samples",{"measure":43,"description":44,"timeFrame":17},"HbA1c","HbA1c levels \\[%\\] assessed in fasting blood samples",{"measure":46,"description":47,"timeFrame":17},"Concentration of metabolic hormones","Insulin, C-peptide, glucagon, leptin and adiponectin levels \\[ng\u002FmL\\] assessed in fasting blood samples",{"measure":49,"description":50,"timeFrame":17},"Concentration of blood lipids","Total cholesterol, low-density lipoprotein (LDL), high-density lipoprotein cholesterol (HDL), triglycerides \\[mg\u002FdL\\] and lipidomic-based lipid patterns assessed in fasting blood samples",{"measure":52,"description":53,"timeFrame":17},"Concentration of inflammatory markers","Interleukin-6 and hsCRP levels \\[mg\u002FL\\] measured in blood samples",{"measure":55,"description":56,"timeFrame":17},"Concentration of liver enzymes","γ-glutamyltransferase (GGT), aspartate aminotransferase (AST), and alanine aminotransferase (ALT) levels \\[U\u002FL\\] determined in fasting blood samples",{"measure":58,"description":59,"timeFrame":17},"Concentration of kidney parameters","Creatinine, urea, uric acid levels \\[mg\u002FdL\\] determined in fasting blood samples",{"measure":61,"description":62,"timeFrame":17},"Concentration of blood metabolites","Metabolite levels measured by metabolomic analysis in blood samples",{"measure":64,"description":65,"timeFrame":17},"Gene expression in blood mononuclear cells (PBMC)","Gene expression assessed by RNA-Seq or qPCR analysis in PBMC",{"measure":67,"description":68,"timeFrame":17},"Gene expression in subcutaneous adipose tissue (SAT)","Gene expression assessed by RNA-Seq or qPCR analysis in SAT",{"measure":70,"description":71,"timeFrame":17},"Immune cell composition in PBMC and SAT","Immune cell composition measured using FACS analysis",{"measure":73,"description":74,"timeFrame":17},"Gut microbiome composition","Gut microbiome species as assessed by 16S rRNA gene sequencing of stool samples",{"measure":76,"description":77,"timeFrame":17},"Gut microbiome metabolites","Levels of microbiome-derived metabolites measured in stool samples",{"measure":79,"description":80,"timeFrame":17},"Mean glucose","Mean glucose level \\[mg\u002FdL\\] measured using CGM",{"measure":82,"description":83,"timeFrame":17},"Glycemic variability","Intra- and inter-day glycemic fluctuation indices \\[AU\\] from CGM measurement",{"measure":85,"description":86,"timeFrame":17},"Time in range (TIR)","TIR \\[%\\] from CGM measurement",{"measure":88,"description":89,"timeFrame":17},"Glucose Management Indicator (GMI, estimated HbA1c)","GMI \\[%\\] from CGM measurement",{"measure":91,"description":92,"timeFrame":12},"Glucose Area Under the Curve (AUC) after a morning test meal","Glucose AUC \\[mg\u002FdL⋅min\\] measured using CGM after a standardized morning test meal as an average of two test days within the observation period",{"measure":94,"description":95,"timeFrame":96},"Glucose AUC and iAUC after an evening test meal","Glucose AUC and iAUC \\[mg\u002FdL⋅min\\] is measured using CGM after a standardized evening test meal as an average of two test days within the observation period","5 and 12 days",{"measure":98,"description":99,"timeFrame":17},"Eating timing and composition","Food type, quality, meal times and nutrient composition assessed by digital or paper-based food records",{"measure":101,"description":102,"timeFrame":17},"Physical activity","24-hour physical activity monitored by actigraphy",{"measure":104,"description":105,"timeFrame":17},"Sleep timing","Sleep timing (sleep onset and offset \\[hh:mm\\]) and sleep duration as monitored using a sleep diary and actigraphy",{"measure":107,"description":108,"timeFrame":17},"Objective sleep quality","Sleep quality as assessed by actigraphy",{"measure":110,"description":111,"timeFrame":17},"Light exposure","24-hour light exposure \\[lux\\] as monitored by actigraphy",{"measure":113,"description":114,"timeFrame":17},"Body temperature","24-hour body temperature \\[°C\\] will be monitored by actigraphy",{"measure":116,"description":117,"timeFrame":17},"Subjective sleep quality","Sleep quality as assessed by the Pittsburgh Sleep Quality Index (PSQI score, which ranges from 0-21, where higher values correspond to worse sleep quality)",{"measure":119,"description":120,"timeFrame":17},"Chronotype","Chronotype assessed by the Munich Chronotype Questionnaire (MSFsc time, where later values correspond to later chronotype) and Morning-Eveningness Questionnaire (D-MEQ score, which ranges 19-76, where higher values correspond to later chronotype)",{"measure":122,"description":123,"timeFrame":17},"Body awareness","Body awareness assessed by the Multidimensional Assessment of Interoceptive Awareness (MAIA-2) and list of subjective hypoglycemia symptoms. The MAIA-2 provides subscale scores (across 8 dimensions) ranging from 1 to 5, where higher values correspond to greater interoceptive awareness and sensitivity to internal body signals",{"measure":125,"description":126,"timeFrame":17},"Eating Behavior","Eating behavior as assessed by the Dutch Eating Behavior Questionnaire (DEBQ). The DEBQ provides three distinct subscale scores-Emotional, External, and Controlled eating-each ranging from 1 to 4, where higher values correspond to greater prevalence of that specific eating behavior.",{"measure":128,"description":129,"timeFrame":17},"Emotional eating","Emotional eating behavior as assessed using the Salzburg Emotional Eating Scale (SEES). The SEES provides a score ranging from 1 to 5, where higher values correspond to greater frequency of emotional eating.",{"measure":131,"description":132,"timeFrame":17},"Food Timing","Food timing assessed using the Food Timing Screener (FTS) questionnaire, which provides timing of main meals and snacks \\[hh:mm\\]",{"measure":134,"description":135,"timeFrame":136},"Subjective feelings of hunger and satiety","Satiety and hunger scores assessed using Visual Analog Scales (VAS) before and after standardized test meals. VAS scores range from 0 to 100 mm, where higher values correspond to increased levels of hunger or fullness, respectively.","3, 5, 10 and 12 days",{"measure":138,"description":139,"timeFrame":17},"Health-related quality of life","Health-related quality-of-life, as assessed by the 36-Item Short Form Health Survey (SF-36), which provides standardized scores ranging from 0 to 100, where higher values correspond to better health-related quality of life",{"measure":141,"description":142,"timeFrame":17},"Affective states","Affective states as assessed with the Positive and Negative Affect Schedule (PANAS). The PANAS provides two subscale scores (Positive Affect and Negative Affect) ranging from 1 to 5, where higher values correspond to increased levels of positive or negative affect, respectively",{"measure":144,"description":145,"timeFrame":17},"Perceived stress","Perceived stress as assessed using the Perceived Stress Questionnaire (PSQ), which provides a score ranging from 0 to 40, where higher values correspond to greater levels of perceived stress",{"measure":147,"description":148,"timeFrame":17},"Anxiety","Anxiety levels as assessed using State-Trait Anxiety Inventory (STAI), which provides two subscale scores (State and Trait) ranging from 20 to 80, where higher values correspond to greater levels of state or trait anxiety, respectively",{"measure":150,"description":151,"timeFrame":17},"Depression","Depression levels as assessed using the Beck Depression Inventory (BDI) and the Health Questionnaire for Patients (PHQ-D). The BDI provides a score ranging from 0 to 63, where higher values correspond to greater severity of depressive symptoms. The PHQ-9 provides a score ranging from 0 to 27, where higher values correspond to greater severity of depressive symptoms.",{"measure":153,"description":154,"timeFrame":17},"Motivation","Motivation levels as assessed using the Behavioral Inhibition and Activation (BISBAS). The BIS\u002FBAS provides three subscale scores (BIS, BAS-Reward Responsiveness, and BAS-Impulsivity) ranging from 8 to 32, where higher values correspond to greater sensitivity to threat or reward, respectively",null,{"allocation":155,"interventionModel":155,"interventionModelDescription":155,"primaryPurpose":155,"observationalModel":157,"timePerspective":158,"maskingInfo":155},"COHORT","PROSPECTIVE","Studies show that glycemic responses vary significantly among individuals, even when consuming identical foods or meals. These varying glycemic responses are attributed to metabolic differences between individuals. Recently, machine learning models incorporating metabolic data (including microbiome composition) have been able to successfully predict individual blood glucose responses. Precision nutrition recommendations based on such predictions could facilitate better glycemic control and reduce the risk of diabetes. From this perspective, considering metabolic biomarkers, phenotype and genotype, as well as gut microbiome composition, could play a role in deriving dietary recommendations and thereby achieving the best possible health outcomes through nutrition. In addition to macronutrient composition, the timing, frequency and number of meals may also play a significant role in the glycemic response to diet. Finally, socioeconomic, cultural and personal lifestyle factors also have an influence on the glycemic response. Therefore, this study aims to characterize the personal lifestyle differences between individuals with prediabetes, T2D, and those without prediabetes or T2D.\n\nFurthermore, ketone bodies, specifically β-hydroxybutyrate (βHB), are gaining importance, as they serve as both metabolic biomarkers and alternative energy sources in periods of low carbohydrate availability. In individuals with insulin resistance or prediabetes, cerebral glucose utilization is often impaired; leading to the use of ketone bodies as a compensatory energy source for the brain. Findings indicate that the individual ketone response to dietary interventions varies significantly between individuals and could thus itself be relevant as a metabolic phenotype marker in the context of precision nutrition. Therefore, the study also aims to further investigate the extent to which exogenous βHB supplementation influences neurocognitive processes and decision-making behavior, and whether characteristic neurocognitive phenotypes can be derived from this in metabolic risk groups.\n\nThis study will achieve its aims by completing a comprehensive lifestyle characterization and metabolic, molecular and neurocognitive phenotyping of individuals with different glycemic status (prediabetes, type 2 diabetes \\[T2D\\], and absence of prediabetes or T2D) in a German cohort. The study consists of modules A and B.\n\nThis record represents a description of module A which includes a 14-days observational period at home and two visits (screening and phenotyping visits) of the study center at the German Institute for Human Nutrition Potsdam-Rehbrueke before and after the observational period, respectively. In the observation period, food intake, sleep, activity, and interstitial glucose will be monitored during 14 days, and test meals will be consumed at two days at specific times. Study visits of module A include the intensive characterization using questionaries, anthropometric and metabolic assessments as well as collection of biosamples.\n\nModule B has an interventional crossover design and is registered an a separate record. Module B takes place 1-12 weeks after module A and include two visits of the study center at the Free University of Berlin, separated by a two-week interval. Study visits of module B will focus on neurocognitive phenotyping including MRI of brain anatomy, function and complete computer-based decision-making behavior tests, and a consumption of the test drink containing ketone β-hydroxybutyrate (βHB) (test and placebo visits).\n\nThe aims of the study are as follows:\n\nPrimary aims:\n\n* Identification of metabolic biomarkers and omics-based scores that predict individual glycemic response to food\n* Identification of general lifestyle patterns that distinguish individuals with prediabetes or T2D from those without prediabetes or T2D\n* Identification of personal factors and differences in lifestyle patterns that predict individual glucose response to food\n\nSecondary aim:\n\n• Elucidation of neuronal, metabolic, and molecular mechanisms associated with specific lifestyle patterns","Adults (40-75 years) with overweight or obesity and with prediabetes or T2D or without prediabetes and T2D",[162,165,168],{"label":163,"type":155,"description":164,"interventionNames":155},"Group A (without Prediabetes or Type 2 Diabetes)","HbA1c \\\u003C5.7% and fasting plasma glucose \\\u003C 100 mg\u002Fdl",{"label":166,"type":155,"description":167,"interventionNames":155},"Group B (Prediabetes)","HbA1c 5.7-6.4%, or fasting plasma glucose 100-125 mg\u002FdL",{"label":169,"type":155,"description":170,"interventionNames":155},"Group C (Type 2 Diabetes)","HbA1c ≥6.5%, fasting plasma glucose ≥ 126 mg\u002Fdl, or existing T2D diagnosis by physician, or T2D diagnosis based on an available result from standardized 75 g oral glucose tolerance test",[172,176],{"name":173,"affiliation":174,"role":175},"Olga Ramich, Prof. Dr.","German Institute of Human Nutrition Potsdam-Rehbruecke and the Charité - Universitätsmedizin Berlin","PRINCIPAL_INVESTIGATOR",{"name":177,"affiliation":178,"role":175},"Soyoung Park, Prof. Dr.","German Institute of Human Nutrition Potsdam-Rehbrücke and the Charité - Universitätsmedizin Berlin",[180,184],{"name":173,"role":181,"phone":182,"phoneExt":155,"email":183},"CONTACT","+49 33200 882749","olga.ramich@dife.de",{"name":185,"role":181,"phone":186,"phoneExt":155,"email":187},"Beeke Peters, MSc","+49 33200 882690","beeke.peters@dife.de",[189],{"facility":190,"status":191,"city":192,"state":193,"zip":194,"country":195,"countryCode":196,"cosmosGeoPoint":197,"geoPoint":202,"contacts":203},"German Institute of Human Nutrition, Dept. Molecular Metabolism and Precision Nutrition and Decision Neuroscience and Nutrition","RECRUITING","Potsdam","Potsdam-Rehbrücke","14558","Germany","DE",{"type":198,"coordinates":199},"Point",[200,201],13.06566,52.39886,{"lat":201,"lon":200},[204,205],{"name":185,"role":181,"phone":186,"phoneExt":155,"email":187},{"name":206,"role":181,"phone":207,"phoneExt":155,"email":208},"Eva Fröhlich, Dr.","+49 33200 882511","eva.froehlich@dife.de",{"type":175,"investigatorFullName":210,"investigatorTitle":211,"investigatorAffiliation":5,"oldNameTitle":155,"oldOrganization":155},"Olga Ramich (formerly Pivovarova)","Prof. Dr.",[213,216],{"name":214,"class":215},"Freie Universität Berlin, Center for Cognitive Neuroscience Berlin (CCNB)","UNKNOWN",{"name":217,"class":215},"German Center of Diabetes Research (DZD)","100659640","lifestyle-metabotype-study-a-100659640",false,"NCT07868601","LIfestyle MEtabotype Study A","LIfestyle MEtabotype Study (Module A)","LIME-A","Inclusion Criteria:\n\n* Overweight or obesity (BMI 25-40 kg\u002Fm²)\n* Good knowledge of German\n\nExclusion Criteria:\n\n* Weight changes of more than 5% in the last 3 months\n* Night shift work\n* Travel across more than one time zone in the last month before and during study participation\n* Intensive regular physical activity of more than 2 hours per day\n* Current pregnancy or breastfeeding\n* Severe renal, liver or heart disease\n* Existing or past hematological malignancies, other malignant tumors, unless successfully treated more than 12 months before study start\n* Severe neurological or psychiatric disorders\n* Daily alcohol consumption of more than 20 grams or more than 150 grams per week\n* Use of illicit or legal drugs one week prior to study start and during study participation\n* Known systemic infections\n* Type 1 diabetes and rare forms of diabetes\n* Diabetes treatment with insulin or sulfonylureas or diabetes medication in the absence of manifest type 2 diabetes\n* Unstable thyroid dysfunction\n* Blood coagulation disorders or anticoagulation therapy that cannot be interrupted\n* Medications affecting nutrient absorption\n* Medications with immunosuppressants or steroids (oral or parenteral)\n* Current eating disorders, functional or structural digestive disorders or bariatric surgery\n* Food allergies or intolerances to ingredients of the test meals\n* Intermittent fasting or calorie-restricted diet four weeks prior to the start of the study or during the study\n* Ketogenic diet or ketogenic supplements four weeks prior to or during module B\n* Left-handedness\n* Severe claustrophobia\n* Electrical implants or non-removable metallic implants\n* Concurrent participation in another intervention study\n* Assessment by the study physician based on medical concerns precluding study participation",true,"ALL","40 Years","75 Years",{"count":231,"type":232},300,"ESTIMATED","OBSERVATIONAL","Glycemic responses vary significantly among individuals, even when consuming identical foods or meals, but the factors predicting individual glucose response to food intake remain poorly investigated.\n\nThe aim of the LIfestyle MEtabotype study (LIME) observational study is to identify lifestyle-related and mechanistic factors which predict individual postprandial glucose fluctuations in individuals with different glycemic status (prediabetes, type 2 diabetes \\[T2D\\], and absence of prediabetes or T2D). To address this aim, the study will conduct a comprehensive lifestyle characterization and metabolic, molecular and neurocognitive phenotyping during study center visits and a dietary, glucose, sleep and activity monitoring during the observational phase.",[236,237,238],"Nutritional and Metabolic Diseases","Prediabetes","Type 2 Diabetes",[237,238,240,241,242,243],"Metabolism","Lifestyle","Glycemic response","Eating timing","2026-10-06",{"date":246,"type":247},"2026-10-09","ACTUAL",{"date":249,"type":232},"2026-10-10",{"date":251,"type":232},"2031-12-31",{"name":5,"class":6},1]