Raw JSON
{'hasResults': False, 'derivedSection': {'miscInfoModule': {'versionHolder': '2025-12-24'}, 'conditionBrowseModule': {'meshes': [{'id': 'D000092862', 'term': 'Psychological Well-Being'}], 'ancestors': [{'id': 'D010549', 'term': 'Personal Satisfaction'}, {'id': 'D001519', 'term': 'Behavior'}]}, 'interventionBrowseModule': {'meshes': [{'id': 'D056692', 'term': 'Prebiotics'}, {'id': 'D007444', 'term': 'Inulin'}, {'id': 'D015636', 'term': 'Magnesium Chloride'}, {'id': 'C008315', 'term': 'maltodextrin'}], 'ancestors': [{'id': 'D004043', 'term': 'Dietary Fiber'}, {'id': 'D004040', 'term': 'Dietary Carbohydrates'}, {'id': 'D002241', 'term': 'Carbohydrates'}, {'id': 'D011135', 'term': 'Polysaccharides, Bacterial'}, {'id': 'D011134', 'term': 'Polysaccharides'}, {'id': 'D005502', 'term': 'Food'}, {'id': 'D000066888', 'term': 'Diet, Food, and Nutrition'}, {'id': 'D010829', 'term': 'Physiological Phenomena'}, {'id': 'D019587', 'term': 'Dietary Supplements'}, {'id': 'D019602', 'term': 'Food and Beverages'}, {'id': 'D013213', 'term': 'Starch'}, {'id': 'D005936', 'term': 'Glucans'}, {'id': 'D001704', 'term': 'Biopolymers'}, {'id': 'D011108', 'term': 'Polymers'}, {'id': 'D046911', 'term': 'Macromolecular Substances'}, {'id': 'D005630', 'term': 'Fructans'}, {'id': 'D002712', 'term': 'Chlorides'}, {'id': 'D006851', 'term': 'Hydrochloric Acid'}, {'id': 'D017606', 'term': 'Chlorine Compounds'}, {'id': 'D007287', 'term': 'Inorganic Chemicals'}, {'id': 'D017616', 'term': 'Magnesium Compounds'}]}}, 'protocolSection': {'designModule': {'phases': ['NA'], 'studyType': 'INTERVENTIONAL', 'designInfo': {'allocation': 'RANDOMIZED', 'maskingInfo': {'masking': 'TRIPLE', 'whoMasked': ['PARTICIPANT', 'INVESTIGATOR', 'OUTCOMES_ASSESSOR'], 'maskingDescription': 'Research nurses, Independent investigators'}, 'primaryPurpose': 'PREVENTION', 'interventionModel': 'PARALLEL', 'interventionModelDescription': 'Double blind, Placebo, Randomised'}, 'enrollmentInfo': {'type': 'ESTIMATED', 'count': 70}}, 'statusModule': {'overallStatus': 'NOT_YET_RECRUITING', 'startDateStruct': {'date': '2025-01-06', 'type': 'ESTIMATED'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2024-12', 'completionDateStruct': {'date': '2026-09-16', 'type': 'ESTIMATED'}, 'lastUpdateSubmitDate': '2024-12-04', 'studyFirstSubmitDate': '2024-08-07', 'studyFirstSubmitQcDate': '2024-08-20', 'lastUpdatePostDateStruct': {'date': '2024-12-09', 'type': 'ACTUAL'}, 'studyFirstPostDateStruct': {'date': '2024-08-22', 'type': 'ACTUAL'}, 'primaryCompletionDateStruct': {'date': '2025-09-16', 'type': 'ESTIMATED'}}, 'outcomesModule': {'otherOutcomes': [{'measure': 'Urine Metabolomics (Targeted)', 'timeFrame': "Participant home collection, 3 collections:24 hours before 'baseline visit' week 0, 24 hours before 'endpoint visit' week 6, 24 hours before follow-up visit (week 10).", 'description': "Targeted metabolomics using Gas Chromatography - Mass Spectrometry/ Liquid Chromatography - Mass Spectrometry (GC-MS/LC-MS) of urine samples following untargeted results. Biocrates Kits / neurobiological metabolites or their breakdown products i.e. 5-Hydroxyindoleacetic acid (serotonin), kynurenic acid (tryptophan).\n\nMetabolites are typically quantified in the in micrograms per millilitre concentration range (µg/mL).\n\nn= 315 samples in total across the three timepoints.\n\nExample outcome:\n\n'Using GC-MS we saw a significant change in the concentration of kynurenic acid \\[amount specified (µg/mL)\\] between the prebiotic and placebo groups.'"}, {'measure': 'Faeces Metabolomics (Targeted)', 'timeFrame': "Participant home collection, 3 collections:24 hours before 'baseline visit' week 0, 24 hours before 'endpoint visit' week 6, 24 hours before follow-up visit (week 10).", 'description': "Targeted metabolomics using Gas Chromatography - Mass Spectrometry/ Liquid Chromatography - Mass Spectrometry (GC-MS/LC-MS) of stool samples untargeted results. D-L amino acid assays - to determine microbial metabolites (D-glutamate, D-alanine, D-lysine)\n\nMetabolites are typically quantified in the nanomolar per gram concentration range (nmol/g).\n\nn= 315 samples in total across the three timepoints.\n\nExample outcome:\n\n'Using GC-MS we saw a significant change in the concentration of D-lysine \\[amount specified (nmol/g)\\] between the prebiotic and placebo groups'"}, {'measure': 'Plasma Metabolomics (Targeted)', 'timeFrame': "3 timepoints 'Baseline','Endpoint' and 'Follow-up' visits 0,6 and 10 weeks respectivley", 'description': "Targeted metabolomics using Gas Chromatography - Mass Spectrometry/ Liquid Chromatography - Mass Spectrometry (GC-MS/LC-MS) of plasma samples following untargeted results.\n\nD-L amino acid assay, neurobiological metabolites and short-chain fatty acids (typically produced from prebiotics - Acetate, Propionate and Butyrate).\n\nMetabolites are typically quantified in the in micrograms per millilitre concentration range (µg/mL).\n\nn= 315 samples in total across the three timepoints.\n\nExample outcome:\n\n'Using GC-MS we saw a significant change in the concentration of Acetate \\[amount specified (µg/mL)\\] between the prebiotic and placebo groups.'"}], 'primaryOutcomes': [{'measure': 'Salivary Cortisol Awakening Response - Biological salivary cortisol (µg/dL)', 'timeFrame': "6 collections across two working mornings per timepoint. (2 'baseline' - week 0 before supplementation; 2 'endpoint' - week 6 of supplementation ; 2 'follow-up' - within 3rd week (week 9) of supplement end)", 'description': "Salivary Cortisol Awakening Response (µg/dL) Measured on awakening and hereafter at 0, 15 , 30, 45 minutes Quantified by ELISA and presented as area under the curve, for each timepoint.\n\nExample outcome: 'Awakening salivary cortisol response was significantly lower in the prebiotic group compared to the placebo mean difference: -2.27( 95CI-3.68, -0.87) group after 6 weeks of supplementation.' \\[result sourced from clinicaltrials.gov NCT0521254\\]"}], 'secondaryOutcomes': [{'measure': 'Good Sleeper Scale -15 items (GSS -15) self-reported sleep.', 'timeFrame': "3 timepoints 'Baseline','Endpoint' and 'Follow-up' visits 0,6 and 10 weeks respectivley", 'description': "GSS-15 - Manners, J et al (2023) questionnaire A 15 item questionnaire validated in a population of Australian adults to give a self-reported indices of sleep on a scale of confidence of being a good sleeper.\n\n10.1111/jsr.13717\n\nGSS-15 ≥ 45: High confidence of being a Good Sleeper GSS-15 40 - 44: Moderate confidence of being a Good Sleeper GSS-15 \\< 40: Low confidence of being a Good Sleeper\n\nExample outcome: 'There was no difference in the mean reported good sleeper score (43.25 43.25 (95% CI: -40.1, 46.2) of the prebiotic and placebo groups after 6 weeks of supplementation.'"}, {'measure': 'Depression Anxiety and Stress Scales 42-items (DASS-42) questionnaire. Wellbeing and subjective mental health assessment.', 'timeFrame': "3 timepoints 'Baseline','Endpoint' and 'Follow-up' visits 0,6 and 10 weeks respectivley", 'description': "Depression, Anxiety and Stress Scales Lovibond, P. F., \\& Lovibond, S. H. (1995) 10.1016/0005-7967(94)00075-u\n\nScale Scores:\n\nDASS (42) Scores are calculated for each subset of the survey with the scale as follows where lower scores indicate a better outcome, while higher scores indicate worse results:\n\nDepression Anxiety Stress Normal 0-9 0-7 0-14 Mild 10-13 8-9 15-18 Moderate 14-20 10-14 19-25 Severe 21-27 15-19 26-33 Extremely Severe 28+ 20+ 34+\n\nExample outcome: 'There was a significant reduction in the stress score observed in the prebiotic group (mean: -3.25 (p=0.004) after 6 weeks of supplementation when compared to the placebo group.'"}, {'measure': 'Faceal microbial sequencing and interventional group microbiota compositional change', 'timeFrame': "Participant home collection, 3 collections:24 hours before 'baseline visit' week 0, 24 hours before 'endpoint visit' week 6, 24 hours before follow-up visit (week 10).", 'description': "16S ribosomal ribonucleic acid (rRNA) sequencing of stool samples measuring microbial composition change.\n\nUnits: Read counts, Operational Taxanomic Units (OTUs) and Relative abundance provide quantifications of the amount of bacterial genetic sequence present in a stool sample building an approximation of the faecal microbial composition to at least the genus level.\n\nResults are typical reported in compositional scores like alpha and beta diversity.\n\nBray-Curtis dissimilarity is a scale of similarity where values closer to 1 are more distinct, while values close to 0 represent similar compositions.\n\nExample outcome: 'The beta diversity (a measure of compositional change) of the prebiotic group using Bray-Curtis dissimilarity increased by 22.7%, suggesting a compositional change from the placebo group.'"}, {'measure': 'Short Food Frequency Questionnaire (SFFQ): Diet quality score', 'timeFrame': "3 timepoints 'Baseline','Endpoint' and 'Follow-up' visits 0,6 and 10 weeks respectivley", 'description': "Validated SFFQ for adults in the United Kingdom (UK) Cleghorn, CL. et al (2017) - University of Leeds\n\nScores per subgroup (Fruit, Vegetables, Oily Fish, Fat and Non-Milk Extrinsic Sugars (NMEs)) are converted to scores ranging from 1-3 based on consumption. Lower scores indicating less intake, while scores of 3 indicate high intake of particular food groups (except for fats and NMEs which is reverse scaled - lower score matching closer to nutritional guideline).\n\nA final dietary quality score score is calculated from all subgroups with higher scores indicating better dietary quality.\n\nExample outcome: 'Dietary quality scores did not significantly differ among the prebiotic and placebo groups after 6 weeks. This indicates that participants' dietary habits remained consistent throughout the intervention, thereby minimizing dietary intake as a confounding factor in the comparison of the interventional groups.'"}, {'measure': 'Activity monitoring using activewear devices', 'timeFrame': 'Continuous / 3 nights per 14 days (2 weeknights, 1 weekend night) depending on participants preference.', 'description': "Subsample analysis of biometric activity and sleep using FitBit Inspire 3.0. The Fitbit Inspire 2.0 can capture more objective measures of sleep including time spent in REM sleep phases, sleep duration, awakening and sleep latency.\n\nExample outcome: 'Sleep latency, defined as the time taken to fall asleep, was significantly reduced by 5.5 minutes (p \\< 0.05) after 6 weeks of prebiotic supplementation compared to the placebo group.'"}, {'measure': 'Urine Metabolomics (Untargeted)', 'timeFrame': "Participant home collection, 3 collections:24 hours before 'baseline visit' week 0, 24 hours before 'endpoint visit' week 6, 24 hours before follow-up visit (week 10).", 'description': "Untargeted Proton Nuclear Magnetic Resonance (1H NMR) metabolomic analysis of urine samples.\n\nNMR generates a spectrum of metabolites by detecting hydrogen atoms' response to an electromagnetic pulse. The resulting peaks correspond to specific chemical shift ranges (δ shifts), allowing for the identification of metabolite compositions. It is untargeted as identification is based on what is returned in spectral form, as opposed to targeted which preselects specific metabolites to measure.\n\nExample outcome: 'After 6 weeks of prebiotic supplementation, we observed significant increases in the urinary levels of dimethylglycine, indole-3-sulfate, and hippurate compared to the placebo group. These findings suggest that prebiotic supplementation may influence various metabolic pathways and gut microbiota activity.'"}, {'measure': 'Faeces Metabolomics (Untargeted)', 'timeFrame': "Participant home collection, 3 collections:24 hours before 'baseline visit' week 0, 24 hours before 'endpoint visit' week 6, 24 hours before follow-up visit (week 10).", 'description': "Untargeted Proton Nuclear Magnetic Resonance (1H NMR) metabolomic analysis of faeces.\n\nNMR generates a spectrum of metabolites by detecting hydrogen atoms' response to an electromagnetic pulse. The resulting peaks correspond to specific chemical shift ranges (δ shifts), allowing for the identification of metabolite compositions. It is untargeted as identification is based on what is returned in spectral form, as opposed to targeted which preselects specific metabolites to measure.\n\nExample outcome: 'After 6 weeks of prebiotic supplementation, we observed significant increases in the faecal levels of alanine and glutamate compared to the placebo group.\n\nMore targeted approaches would be needed to quantify and determine if these amino acids are from dietary, human or microbiome origins like Liquid Chromatography Mass Spectrometry LC-MS).'"}, {'measure': 'Plasma Metabolomics (Untargeted)', 'timeFrame': "3 timepoints 'Baseline','Endpoint' and 'Follow-up' visits 0,6 and 10 weeks respectivley", 'description': "Untargeted Proton Nuclear Magnetic Resonance (1H NMR) metabolomic analysis of plasma samples.\n\nNMR generates a spectrum of metabolites by detecting hydrogen atoms' response to an electromagnetic pulse. The resulting peaks correspond to specific chemical shift ranges (δ shifts), allowing for the identification of metabolite compositions. It is untargeted as identification is based on what is returned in spectral form, as opposed to targeted which preselects specific metabolites to measure.\n\nExample outcome: 'After 6 weeks, prebiotic supplementation significantly increased faecal levels of alanine and glutamate compared to placebo, while lysine levels remained unchanged. Further targeted analyses, such as LC-MS, are needed to determine the origins and concentrations of these amino acids'."}, {'measure': 'Anthropometrics - Body composition', 'timeFrame': "3 timepoints 'Baseline','Endpoint' and 'Follow-up' visits 0,6 and 10 weeks respectivley", 'description': "Height (cm), Weight (Kg), Waist Circumference (cm) and Body Mass Index (BMI (kg/m2)\n\nExample outcome: 'Mean waist circumference (cm) did not differ significantly (p \\> 0.05) between the prebiotic and placebo groups after 6 weeks, suggesting that the prebiotic had no effect on body composition in terms of waist circumference.'"}, {'measure': 'Adverse effects monitoring', 'timeFrame': 'Continuous monitoring from start to end of study for all participants', 'description': "Monitoring or reporting of any adverse or severe adverse effects experienced during intervention.\n\nReported and logged in active survey responses / contacting the study team directly\n\nExample outcome: 'There were two minor side effects reported early in the prebiotic supplementation, both instances self resolved within a few days and may be an effect of the initial introduction of a supplement to the individuals digestive system. No severe adverse effects were reported in either the prebiotic or the placebo control groups.'"}]}, 'oversightModule': {'isUsExport': False, 'oversightHasDmc': False, 'isFdaRegulatedDrug': False, 'isFdaRegulatedDevice': False}, 'conditionsModule': {'keywords': ['Prebiotics', 'Gut microbiome', 'Microbiome', 'Metabolomics', 'Sequencing', 'Stress', 'Wellbeing'], 'conditions': ['Wellbeing', 'Healthy', 'Mental Health']}, 'referencesModule': {'references': [{'pmid': '31525562', 'type': 'BACKGROUND', 'citation': 'Caspani G, Swann J. Small talk: microbial metabolites involved in the signaling from microbiota to brain. Curr Opin Pharmacol. 2019 Oct;48:99-106. doi: 10.1016/j.coph.2019.08.001. Epub 2019 Sep 14.'}, {'pmid': '29228000', 'type': 'BACKGROUND', 'citation': 'Costabile A, Buttarazzi I, Kolida S, Quercia S, Baldini J, Swann JR, Brigidi P, Gibson GR. An in vivo assessment of the cholesterol-lowering efficacy of Lactobacillus plantarum ECGC 13110402 in normal to mildly hypercholesterolaemic adults. PLoS One. 2017 Dec 11;12(12):e0187964. doi: 10.1371/journal.pone.0187964. eCollection 2017.'}]}, 'descriptionModule': {'briefSummary': 'The study will investigate whether taking a prebiotic for six weeks helps to reduce morning cortisol levels in healthy young adults with mild to moderate stress compared to a placebo. Individuals should continue with their usual lifestyle during the study. Other factors of wellbeing will also be assessed.', 'detailedDescription': 'PROMOTE is a double blinded parallel randomised controlled-trial investigating if prebiotic supplementation reduce awakening salivary cortisol response, reported as area under the curve compared to a maltodextrin placebo in healthy young adults with a mild-to-moderate self reported stress score. There will be a focus on biological secondary outcomes to better understand how supplementation may influence the microbiome using metabolomics and sequencing techniques. In addition to other measures of wellbeing captured by questionnaires and activity monitors.'}, 'eligibilityModule': {'sex': 'ALL', 'stdAges': ['ADULT'], 'maximumAge': '25 Years', 'minimumAge': '18 Years', 'healthyVolunteers': True, 'eligibilityCriteria': "Inclusion Criteria:\n\n* Aged 18-25 at time of recruitment\n* Body Mass Index (18.5 - 29.9 kg) : Healthy - Overweight\n* Stress score of 15≤ - ≥25 (DASS)\n* Willing and with capacity to give informed consent to participate at time of recruitment\n* Speak and comprehend English to a good standard\n* In good general health\n* Willing to provide stool, urine and blood (8mL) sample during intervention\n* Willing to attend 4 visits to Southampton General Hospital Clinical Research Facility over 10-11 weeks\n\nExclusion Criteria:\n\n* Consuming ≥ 14 units of alcohol/week (6 x 175 mL of wine, 6 pints of 4% beer)\n* Learning or behavioural difficulties (assessed on individual basis)\n* Planning a pregnancy in the next 6 months, pregnant, lactating or had a recent birth ≥6 months\n* Currently smoking or using e-cigarette, vape\n* Vulnerable adults (with self reported sever or very severe stress score (DASS)\n* Unwilling to suspend existing probiotic / prebiotic supplementation (with additional 4 weeks washout) before starting study.\n\nMedical exclusions:\n\n* Actively involved in therapy or psychiatric intervention of a diagnosed mental health condition\n* Prescribed psychotropic medication (Antidepressants, Monoamine Oxidase Inhibitors (MAOI's), Antipsychotics, sleeping pills, mood stabilisers etc)\n* Allergic to milk, soy, corn, penicillin or fermentable oligosaccharides, disaccharides, monosaccharides, and polyols (FODMAPS)\n* Currently prescribed laxatives, enemas, anti-coagulants or painkillers\n* Existing medical condition: cancer, hepatobiliary surgery, diabetes or diagnosed gastrointestinal diseases (irritable bowel disease, ulcerative colitis)\n* Involved in a recent pharmacology/psychological intervention, last 6 months\n* Recent antibiotic prescription, last 6 months"}, 'identificationModule': {'nctId': 'NCT06566157', 'acronym': 'PROMOTE', 'briefTitle': 'PROMOTE: The Effect of a Six Week Prebiotic Supplementation on Wellbeing of Young Adults.', 'organization': {'class': 'OTHER', 'fullName': 'University of Southampton'}, 'officialTitle': 'PROMOTE: The Effect of Prebiotic Supplementation on Salivary Cortisol Awakening Response in Young Adults With Mild-To-Moderate Self-Reported Stress: A Double Blinded Parallel Randomised Controlled-Trial.', 'orgStudyIdInfo': {'id': '340693'}, 'secondaryIdInfos': [{'id': '89554', 'type': 'OTHER', 'domain': 'University of Southampton Research Ethics Committee'}]}, 'armsInterventionsModule': {'armGroups': [{'type': 'EXPERIMENTAL', 'label': 'Prebiotic', 'description': 'WellBiome® prebiotic complex Inulin 67%, Xylooligosaccharides (XOS) 27%, Magnesium Chloride (MgCl2) 9.8 %', 'interventionNames': ['Dietary Supplement: Prebiotic']}, {'type': 'PLACEBO_COMPARATOR', 'label': 'Maltodextrin', 'description': 'Maltodextrin (Corn origin)', 'interventionNames': ['Dietary Supplement: Maltodextrin (Corn)']}], 'interventions': [{'name': 'Prebiotic', 'type': 'DIETARY_SUPPLEMENT', 'otherNames': ['WellBiome®', 'WellBiome® - Mineral Enriched Prebiotic Fibre Complex', 'Inulin', 'XOS', 'Magnesium Chloride'], 'description': 'WellBiome® prebiotic complex: Inulin 67%, XOS 27%, Magnesium Chloride (MgCl2) 9.8 %', 'armGroupLabels': ['Prebiotic']}, {'name': 'Maltodextrin (Corn)', 'type': 'DIETARY_SUPPLEMENT', 'otherNames': ['Maltodextrin Placebo'], 'description': 'Placebo', 'armGroupLabels': ['Maltodextrin']}]}, 'contactsLocationsModule': {'locations': [{'zip': 'SO16 6YD', 'city': 'Southampton', 'state': 'Hampshire', 'country': 'United Kingdom', 'contacts': [{'name': 'Michael L Harvey, PhD Student', 'role': 'CONTACT', 'email': 'm.l.harvey@soton.ac.uk', 'phone': '(+44) 0 7340 323183'}], 'facility': 'NIHR Southampton Clinical Research Facility', 'geoPoint': {'lat': 50.90395, 'lon': -1.40428}}], 'centralContacts': [{'name': 'Michael L Harvey', 'role': 'CONTACT', 'email': 'm.l.harvey@soton.ac.uk', 'phone': '(+44) 023 8120 8226'}, {'name': 'Jonathan R Swann, Professor', 'role': 'CONTACT', 'email': 'j.swann@soton.ac.uk'}], 'overallOfficials': [{'name': 'Jonathan R Swann, Professor', 'role': 'PRINCIPAL_INVESTIGATOR', 'affiliation': 'University of Southampton, Faculty of Medicine - Human Development and Health'}]}, 'ipdSharingStatementModule': {'ipdSharing': 'NO', 'description': 'Individual participant data will be anonymised and submitted to open access repositories upon the consent and permission of the participants. Biological data will not be available for secondary analysis but raw exports of biological data in anonymous form can be made available on conditional request provided ethics approval from a suitable institution is met.'}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'University of Southampton', 'class': 'OTHER'}, 'collaborators': [{'name': 'OptiBiotix Health Plc', 'class': 'UNKNOWN'}], 'responsibleParty': {'type': 'SPONSOR'}}}}