- ICH GCP
- US Clinical Trials Registry
- Clinical Trial NCT06513026
Milk for Diabetes Prevention
Study Overview
Status
Conditions
Intervention / Treatment
Detailed Description
The trial will feature a 2-week milk washout period, followed by 1:1 randomization to lactose-containing (1% or 2%) or lactose-free (1% or 2%) milk for 12 weeks (4 weeks each of ½ cup, 1 cup, and 2 cups milk). Before and after the 12 weeks, visits will entail lactose challenge hydrogen breath tests (HBT; i.e., lactose tolerance tests) and blood tests for fasting glucose, hemoglobin A1c, and metabolomics; while stool samples and continuous glucose monitoring (CGM) data will be collected at home using provided kits/devices.
Specific aims of the study are to: (1) establish feasibility and tolerability of a randomized trial of lactose-containing vs. lactose-free milk; (2) to examine the effect of lactose-containing milk on gut microbiome species, functions, and metabolites in LNP individuals with pre-diabetes; and (3) to examine the effect of lactose-containing milk on glycemic outcomes in LNP individuals with pre-diabetes.
Study Type
Enrollment (Estimated)
Phase
- Not Applicable
Contacts and Locations
Study Contact
- Name: Brandilyn Peters-Samuelson, PhD
- Phone Number: 718-430-3281
- Email: brandilyn.peterssamuelson@einsteinmed.edu
Study Contact Backup
- Name: Qibin Qi, PhD
- Phone Number: 718-430-4203
- Email: qibin.qi@einsteinmed.edu
Study Locations
-
-
New York
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The Bronx, New York, United States, 10458
- Recruiting
- HCHS/SOL Bronx Field Center
-
Contact:
- Phone Number: 718-584-1563
- Email: milkstudy@einsteinmed.edu
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-
Participation Criteria
Eligibility Criteria
Ages Eligible for Study
- Adult
- Older Adult
Accepts Healthy Volunteers
Description
Inclusion Criteria:
- LNP genotype (LCT gene rs4988235, GG genotype)
- History of pre-diabetes, defined as fasting blood glucose 100-125 mg/dL and/or hemoglobin A1c (HbA1c) 5.7-6.4% and have not been diagnosed with diabetes nor take diabetes medication (pre-diabetes determined at most recent study visit [for HCHS/SOL participant] or most recent medical chart or self-report [for other participant])
- Drink ≤1 cup milk/day
- Basic computer or smartphone skills
- Can speak and read English fluently
Exclusion Criteria:
- Diabetes diagnosis
- Taking anti-diabetes medication
- Cancer, cardiovascular disease (CVD), or life-threatening illness
- Known milk allergy
- Has severe GI symptoms after drinking milk
- History of GI surgery
- Had a double mastectomy
- Smoking
- More than 1 alcoholic beverage/day
- Pregnant or breastfeeding
- Colonoscopy in last 2 weeks
- Antibiotics in last 3 months
- Taking probiotics or fiber supplements (if taking, must be able to stop taking during study)
- Taking laxatives, stool softeners, anti-diarrheal (if taking, must be able to stop taking during study)
- Taking lactase pills (if taking, must be able to stop taking)
- Participating in extreme dieting program
- Planning extended travel that would prevent participation in study
- Taking medication that must be taken separate from calcium or dairy products
Study Plan
How is the study designed?
Design Details
- Primary Purpose: Prevention
- Allocation: Randomized
- Interventional Model: Parallel Assignment
- Masking: None (Open Label)
Arms and Interventions
Participant Group / Arm |
Intervention / Treatment |
|---|---|
|
Active Comparator: Lactose-Containing Milk
Participants will be randomized to lactose-containing milk in strata of age (<60, ≥60) and sex (female, male).
Within each age and sex stratum, 10 participants will be randomized into two intervention groups in a 1:1 ratio
|
Participants will be asked to drink regular milk (1% or 2%) for 12 weeks as follows:
Participants will continue drinking 2 cups milk/day for 2 weeks after the 12-week follow-up visit. |
|
Active Comparator: Lactose-Free Milk
Participants will be randomized to lactose-free milk in strata of age (<60, ≥60) and sex (female, male).
Within each age and sex stratum, 10 participants will be randomized into two intervention groups in a 1:1 ratio
|
Participants will be asked to drink 1% or 2% lactose-free milk for 12 weeks as follows:
Participants will continue drinking 2 cups milk/day for 2 weeks after the 12-week follow-up visit. |
What is the study measuring?
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Change in Expired Breath Hydrogen
Time Frame: From Baseline to Week 12
|
Expired breath hydrogen after lactose challenge will be measured during the baseline visit and after 12 weeks of milk intervention at the time of the follow-up visit using Hydrogen Breath Test (HBT) kits.
Breath tubes will be mailed to an external laboratory where stable isotope analysis for expired breath hydrogen will be conducted.
Expired breath hydrogen will be expressed as incremental Area Under the Curve (iAUC).
Change in iAUC from baseline to week 12 will be summarized using basic descriptive statistics (group means and standard deviations), and change in iAUC will be compared between treatment groups.
|
From Baseline to Week 12
|
|
Change in gut microbiome features - Relative Abundance of Species
Time Frame: From Baseline to Week 12
|
Stool samples will be collected using home stool microbiome kits at baseline, 4-, 8-, and 12-week timepoints.
Shotgun sequencing will be conducted.
Change in relative abundance of species (with >1% mean relative abundance) from baseline will summarized, using basic descriptive statistics (group means and standard deviations).
Change in relative abundance of species from baseline will be compared between the treatment groups.
|
From Baseline to Week 12
|
|
Change in gut microbiome features - Functional Pathway Relative Abundance
Time Frame: From Baseline to Week 12
|
Stool samples will be collected using home stool microbiome kits at baseline, 4-, 8-, and 12-week timepoints.
Shotgun sequencing will be conducted.
Change in relative abundance of functional pathways (with >1% mean relative abundance) from baseline will summarized, using basic descriptive statistics (group means and standard deviations).
Change in relative abundance of functional pathways from baseline will be compared between the treatment groups.
|
From Baseline to Week 12
|
|
Change in gut microbiome features - Metabolomics
Time Frame: From Baseline to Week 12
|
Targeted metabolic profiling will be performed on serum and stool samples (baseline and week 12) using LC-MS/MS methods for absolute quantitation of 70 metabolites associated with gut bacterial metabolism.
Change in stool and serum metabolites from baseline will be summarized using basic descriptive statistics (group means and standard deviations).
Change in stool and serum metabolites from baseline will be compared between the treatment groups.
|
From Baseline to Week 12
|
|
Change in glycemic outcomes - Fasting glucose
Time Frame: From Baseline to Week 12
|
Blood sera samples for fasting glucose will be collected at baseline and Week 12. Fasting glucose, i.e., blood sugar levels following an 8-hour fast, will be analyzed via standard analytical chemistry approaches and reported in mg/dL or mmol/L units.
Ranges vary but a fasting glucose level <99 mg/dL is considered 'normal', between 100-125 mg/dL is within the 'pre-diabetic' range, >126 mg/dL is within the 'diabetic' range.
Change in fasting glucose from baseline will be summarized using descriptive statistics (means and standard deviations) and compared between the treatment groups.
|
From Baseline to Week 12
|
|
Change in glycemic outcomes - Hemoglobin A1c (HbA1c)
Time Frame: From Baseline to Week 12
|
Whole blood samples for HbA1c will be collected at baseline and Week 12. HbA1c, used to measure the amount of hemoglobin with attached glucose and reflects average blood glucose levels over the past several months, will be analyzed via standard analytical chemistry approaches.
Ranges vary, however, a 'normal' HbA1c is generally <5.7%, 5.7-6.4% is in the 'pre-diabetic' range and a value of 6.5% or greater is in the 'diabetic' range.
Change in HbA1c from baseline will be summarized using descriptive statistics (means and standard deviations) and compared between the treatment groups.
|
From Baseline to Week 12
|
|
Change in glycemic outcomes - Continuous Glucose Monitoring (CGM) mean glucose
Time Frame: From Screening visit to Week 14 visit
|
During screening visit participants will have a 2-week continuous glucose monitor (CGM) applied to the skin on the upper arm in advance of the 2-week milk washout period.
The CGM will be returned during the baseline visit 2 weeks later.
After the 12 week visit, another 2-week CGM will be applied during which time participants will continue drinking milk concurrent with the 2-week CGM (i.e., until 14 weeks).
Change in mean glucose (mg/dL) from screening to week 14 will be summarized using descriptive statistics (means and standard deviations) and compared between the treatment groups.
|
From Screening visit to Week 14 visit
|
|
Change in glycemic outcomes - Continuous Glucose Monitoring (CGM) glycemic variability
Time Frame: From Screening visit to Week 14 visit
|
During screening visit participants will have a 2-week continuous glucose monitor (CGM) applied to the skin on the upper arm in advance of the 2-week milk washout period.
The CGM will be returned during the baseline visit 2 weeks later.
After the 12 week visit, another 2-week CGM will be applied during which time participants will continue drinking milk concurrent with the 2-week CGM (i.e., until 14 weeks).
Change in glycemic variability (%CV) from screening to week 14 will be summarized using descriptive statistics (means and standard deviations) and compared between the treatment groups.
|
From Screening visit to Week 14 visit
|
|
Change in glycemic outcomes - Continuous Glucose Monitoring (CGM) time above range
Time Frame: From Screening visit to Week 14 visit
|
During screening visit participants will have a 2-week continuous glucose monitor (CGM) applied to the skin on the upper arm in advance of the 2-week milk washout period.
The CGM will be returned during the baseline visit 2 weeks later.
After the 12 week visit, another 2-week CGM will be applied during which time participants will continue drinking milk concurrent with the 2-week CGM (i.e., until 14 weeks).
Change in time above range (%) from screening to week 14 will be summarized using descriptive statistics (means and standard deviations) and compared between the treatment groups.
|
From Screening visit to Week 14 visit
|
|
Change in glycemic outcomes - Continuous Glucose Monitoring (CGM) time in range
Time Frame: From Screening visit to Week 14 visit
|
During screening visit participants will have a 2-week continuous glucose monitor (CGM) applied to the skin on the upper arm in advance of the 2-week milk washout period.
The CGM will be returned during the baseline visit 2 weeks later.
After the 12 week visit, another 2-week CGM will be applied during which time participants will continue drinking milk concurrent with the 2-week CGM (i.e., until 14 weeks).
Change in time in range (%) from screening to week 14 will be summarized using descriptive statistics (means and standard deviations) and compared between the treatment groups.
|
From Screening visit to Week 14 visit
|
|
Change in glycemic outcomes - Continuous Glucose Monitoring (CGM) time below range
Time Frame: From Screening visit to Week 14 visit
|
During screening visit participants will have a 2-week continuous glucose monitor (CGM) applied to the skin on the upper arm in advance of the 2-week milk washout period.
The CGM will be returned during the baseline visit 2 weeks later.
After the 12 week visit, another 2-week CGM will be applied during which time participants will continue drinking milk concurrent with the 2-week CGM (i.e., until 14 weeks).
Change in time below range (%) from screening to week 14 will be summarized using descriptive statistics (means and standard deviations) and compared between the treatment groups.
|
From Screening visit to Week 14 visit
|
|
Gastrointestinal symptoms
Time Frame: Daily From Screening visit to Week 12
|
Gastrointestinal symptoms, specifically abdominal pain, bloating, flatulence, and diarrhea, will be recorded daily from screening visit through 12 weeks of milk intervention.
The occurrence and severity of these four adverse events will be summarized and reported by study arm.
Average frequencies of none-mild vs. moderate-severe symptoms will be compared between treatment groups by week of study, as well as for specific time intervals corresponding to milk doses (weeks 1-4, 5-8, 9-12).
|
Daily From Screening visit to Week 12
|
|
Change in Flatulence
Time Frame: From Screening to Week 1, from Week 1 to Week 10, and from Week 1 to Week 14
|
The Smart Underwear device will be worn externally on regular underwear near the rectum/perineum during specified daytime wear periods.
The device continuously detects hydrogen in expelled flatus and records supporting temperature and movement data.
These data will be used to derive the frequency of flatus events per wear period, which reflects intestinal gas production and gut microbial activity.
De-identified data will be transferred after each wear period through the Human Flatus Atlas mobile app and uploaded to servers.
Change in frequency of flatus events per wear period will be summarized using basic descriptive statistics (group means and standard deviations).
|
From Screening to Week 1, from Week 1 to Week 10, and from Week 1 to Week 14
|
Collaborators and Investigators
Collaborators
Investigators
- Principal Investigator: Brandilyn Peters-Samuelson, PhD, Albert Einstein College of Medicine
Publications and helpful links
General Publications
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- Zheng X, Chu H, Cong Y, Deng Y, Long Y, Zhu Y, Pohl D, Fried M, Dai N, Fox M. Self-reported lactose intolerance in clinic patients with functional gastrointestinal symptoms: prevalence, risk factors, and impact on food choices. Neurogastroenterol Motil. 2015 Aug;27(8):1138-46. doi: 10.1111/nmo.12602. Epub 2015 Jun 19.
- Qi Q, Li J, Yu B, Moon JY, Chai JC, Merino J, Hu J, Ruiz-Canela M, Rebholz C, Wang Z, Usyk M, Chen GC, Porneala BC, Wang W, Nguyen NQ, Feofanova EV, Grove ML, Wang TJ, Gerszten RE, Dupuis J, Salas-Salvado J, Bao W, Perkins DL, Daviglus ML, Thyagarajan B, Cai J, Wang T, Manson JE, Martinez-Gonzalez MA, Selvin E, Rexrode KM, Clish CB, Hu FB, Meigs JB, Knight R, Burk RD, Boerwinkle E, Kaplan RC. Host and gut microbial tryptophan metabolism and type 2 diabetes: an integrative analysis of host genetics, diet, gut microbiome and circulating metabolites in cohort studies. Gut. 2022 Jun;71(6):1095-1105. doi: 10.1136/gutjnl-2021-324053. Epub 2021 Jun 14.
- Gojda J, Cahova M. Gut Microbiota as the Link between Elevated BCAA Serum Levels and Insulin Resistance. Biomolecules. 2021 Sep 28;11(10):1414. doi: 10.3390/biom11101414.
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- Li X, Yin J, Zhu Y, Wang X, Hu X, Bao W, Huang Y, Chen L, Chen S, Yang W, Shan Z, Liu L. Effects of Whole Milk Supplementation on Gut Microbiota and Cardiometabolic Biomarkers in Subjects with and without Lactose Malabsorption. Nutrients. 2018 Oct 2;10(10):1403. doi: 10.3390/nu10101403.
- Ugidos-Rodriguez S , Matallana-Gonzalez MC , Sanchez-Mata MC . Lactose malabsorption and intolerance: a review. Food Funct. 2018 Aug 15;9(8):4056-4068. doi: 10.1039/c8fo00555a.
- Kaplan RC, Wang Z, Usyk M, Sotres-Alvarez D, Daviglus ML, Schneiderman N, Talavera GA, Gellman MD, Thyagarajan B, Moon JY, Vazquez-Baeza Y, McDonald D, Williams-Nguyen JS, Wu MC, North KE, Shaffer J, Sollecito CC, Qi Q, Isasi CR, Wang T, Knight R, Burk RD. Gut microbiome composition in the Hispanic Community Health Study/Study of Latinos is shaped by geographic relocation, environmental factors, and obesity. Genome Biol. 2019 Nov 1;20(1):219. doi: 10.1186/s13059-019-1831-z.
- Wang Z, Peters BA, Bryant M, Hanna DB, Schwartz T, Wang T, Sollecito CC, Usyk M, Grassi E, Wiek F, Peter LS, Post WS, Landay AL, Hodis HN, Weber KM, French A, Golub ET, Lazar J, Gustafson D, Sharma A, Anastos K, Clish CB, Burk RD, Kaplan RC, Knight R, Qi Q. Gut microbiota, circulating inflammatory markers and metabolites, and carotid artery atherosclerosis in HIV infection. Microbiome. 2023 May 27;11(1):119. doi: 10.1186/s40168-023-01566-2.
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- Kanehisa M, Sato Y, Kawashima M, Furumichi M, Tanabe M. KEGG as a reference resource for gene and protein annotation. Nucleic Acids Res. 2016 Jan 4;44(D1):D457-62. doi: 10.1093/nar/gkv1070. Epub 2015 Oct 17.
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- Oksanen J, Blanchet FG, Kindt R, et al. Multivariate analysis of ecological communities in R: vegan tutorial. R package version 1.7. 01/01 2013;
- Chen J, Bittinger K, Charlson ES, Hoffmann C, Lewis J, Wu GD, Collman RG, Bushman FD, Li H. Associating microbiome composition with environmental covariates using generalized UniFrac distances. Bioinformatics. 2012 Aug 15;28(16):2106-13. doi: 10.1093/bioinformatics/bts342. Epub 2012 Jun 17.
- Turner-McGrievy GM, Wirth MD, Shivappa N, Wingard EE, Fayad R, Wilcox S, Frongillo EA, Hebert JR. Randomization to plant-based dietary approaches leads to larger short-term improvements in Dietary Inflammatory Index scores and macronutrient intake compared with diets that contain meat. Nutr Res. 2015 Feb;35(2):97-106. doi: 10.1016/j.nutres.2014.11.007. Epub 2014 Dec 3.
- Lavange LM, Kalsbeek WD, Sorlie PD, Aviles-Santa LM, Kaplan RC, Barnhart J, Liu K, Giachello A, Lee DJ, Ryan J, Criqui MH, Elder JP. Sample design and cohort selection in the Hispanic Community Health Study/Study of Latinos. Ann Epidemiol. 2010 Aug;20(8):642-9. doi: 10.1016/j.annepidem.2010.05.006.
Study record dates
Study Major Dates
Study Start (Actual)
Primary Completion (Estimated)
Study Completion (Estimated)
Study Registration Dates
First Submitted
First Submitted That Met QC Criteria
First Posted (Actual)
Study Record Updates
Last Update Posted (Actual)
Last Update Submitted That Met QC Criteria
Last Verified
More Information
Terms related to this study
Keywords
Additional Relevant MeSH Terms
- Endocrine System Diseases
- Metabolism, Inborn Errors
- Genetic Diseases, Inborn
- Metabolic Diseases
- Intestinal Diseases
- Digestive System Diseases
- Gastrointestinal Diseases
- Glucose Metabolism Disorders
- Diabetes Mellitus
- Malabsorption Syndromes
- Carbohydrate Metabolism, Inborn Errors
- Hyperglycemia
- Congenital, Hereditary, and Neonatal Diseases and Abnormalities
- Nutritional and Metabolic Diseases
- Diabetes Mellitus, Type 2
- Glucose Intolerance
- Lactose Intolerance
Other Study ID Numbers
- 2024-16045
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.
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Services Hospital, LahoreCompletedAcute DiarrheaPakistan
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Danone ResearchCompletedHealthy | ConstipationIreland
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Coordinación de Investigación en Salud, MexicoTerminatedLiver Cirrhosis | Hepatic EncephalopathyMexico
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University of Illinois at Urbana-ChampaignCompletedPhysiological Stress | Cognition - OtherUnited States