Clinical Trial Details
— Status: Not yet recruiting
Administrative data
| NCT number |
NCT05000775 |
| Other study ID # |
20210615-001 |
| Secondary ID |
|
| Status |
Not yet recruiting |
| Phase |
N/A
|
| First received |
|
| Last updated |
|
| Start date |
September 1, 2021 |
| Est. completion date |
June 30, 2023 |
Study information
| Verified date |
August 2021 |
| Source |
Chinese University of Hong Kong |
| Contact |
Jamie Cheung |
| Phone |
61898616 |
| Email |
jamie.cheung[@]link.cuhk.edu.hk |
| Is FDA regulated |
No |
| Health authority |
|
| Study type |
Interventional
|
Clinical Trial Summary
Obesity is a global epidemic, and is an important cardio-metabolic risk factor associated
with many non-communicable diseases, such as coronary artery disease (CAD), diabetes and
non-alcoholic fatty liver diseases (NAFLD) (1-6). In 2010, our team recruited a cohort of
obese adolescents [mean age at baseline: 17.2 years, mean body mass index (BMI): 30.9 kg/m2]
from school surveys (7). Our group has examined the impact of dietary intervention using low
glycemic index (GI) diet to reduce body weight of adolescents. We have reported that
participants in the low GI group had a significantly greater reduction in obesity indices
namely waist circumference after 6 months of intervention compared to counterparts in usual
diet counselling group. We recently conducted a phone interview of the participants and most,
if not all, of them remained obese from self-reported body weight. Pharmacological treatment
options for obese individuals are limited (8-10). Amassing evidence showed that the gut
microbiota plays an important role in energy harvesting and lipid metabolism. Gut microbiota
dysbiosis was repeatedly reported in patients with obesity (11-13). Studies in humanized
mouse models suggest that the obese gut microbiota was more efficient in harvesting energy
from diet and may be a causative factor in the pathogenesis of metabolic disorders, including
obesity, type 2 diabetes and NAFLD (14). Therefore, modulation of microbiota might be a
potential strategy for prevention and treatment of metabolic disorders. Microbial-based
therapeutics such as probiotics, prebiotics, symbiotic or fecal microbiota transplantation
have shown promising effect in improving host metabolic health (15, 16). Prebiotics
consumption changes the composition of gut microbiota, alters levels of satietogenic gut
peptides, decreases systemic inflammation, and improves insulin sensitivity and glucose
tolerance (17). Supplementation of probiotics in overweight and obese individuals with
probiotics reduces body weight and obesity indices (16, 18, 19). The use of probiotics also
reduces intrahepatic triglyceride (IHTG) in patients with non-alcoholic steatohepatitis (20)
and improves post-prandial glucose control in subjects with type 2 diabetes (21). G-NiiB®, a
patent-protected microbiome immunity formula, composed of naturally occurring food-grade
bacteria approved by health authorities, has been developed by a group of CUHK
gastroenterology experts.
Description:
Study Design:
This will be a 24-week randomized double-blinded placebo-controlled study on the effect of
G-NiiB®, CU Medicine Immunity Microbiome Formula, on young obese individuals who exited from
a randomized controlled interventional trial with dietary intervention with low GI diet for
12-month that was conducted in 2010 (NCT no. 01278563). This study protocol complies with the
Declaration of Helsinki and ICH-GCP guideline.
Subjects and Methods:
Inclusion Criteria:
1. 281 obese adolescents who participated in the randomized controlled interventional trial
with low GI index diet
2. Willingness to give written consent
Exclusion Criteria:
1. Subjects who are allergic to any ingredients listed in G-NiiB®, microbiome immunity
formula.
2. Subjects with any condition that the investigator deems as a sound reason (e.g. active
gastrointestinal diseases and malignancies) for disqualification from enrollment into
the study.
Study Procedures:
At screening visit:
Anthropometric measurements, including body weight and height, waist and hip circumferences,
percentage body fat by bioimpedance (23).
Questionnaires to document 1) demographic data including past medical and history, birth
weight, 2) 3-day diet record using locally validated questionnaires (24) and 3) physical
activity level/log sheet (IPAQ) ; 4) change of eating behavior and quality of life by eating
disorders examinations (EDE) and 36-item short form survey (SF-36).
Pharmacist to record past and present medication history, including prescribed drugs,
over-the-counter drugs and supplements, especially, 1) Subjects who have received
antibiotics, antifungal, antiparasitic, or antiviral treatment within 12 weeks prior to study
entry; 2) Subjects who plan to use antibiotic, antifungal, antiparasitic, or antiviral
treatment during the study; 3) Subjects using proton pump inhibitor; 4) Present use of
probiotics/nutritional supplements e.g., the use of replacement doses of Vitamin D, calcium
supplements, and multi-vitamin tablet.
After an overnight fast of 8-10 hours, baseline blood tests will be sampled including plasma
glucose, insulin, complete blood picture, renal and liver function tests, thyroid function
test, lipid profiles, high sensitivity C-reactive protein (hs-CRP) (25). Additional 15ml of
blood will be collected for PBMC isolation (22). Spot urine for albumin-creatinine ratio will
be collected for detection of microalbuminuria (26). Various indexes of insulin resistance
(HOMA-IR) and pancreatic beta-cell function (HOMA-beta) will be calculated from the
homeostasis model assessment (27). Insulin secretion will be calculated from plasma glucose
and insulin during various time points of OGTT.
Liver assessment by transient elastography (Fibroscan®), in which controlled attenuation
parameter (CAP) will be used to detect liver steatosis while liver stiffness measurement
(LSM) will be used to assess liver fibrosis (28).
Ultrasound scan for mesenteric fat, fatty liver and carotid intimal medial thickness will be
performed (29, 30).
Stool for gut microbiota will be sampled. Blood for genetic studies (5ml), plasma (350 µL)
and urine (500 µL) for metabolomics investigations will also be stored.
At randomization visit:
Participants will be randomly assigned to either intervention or control arms in 1:1 ratio.
Allocation will be performed using block randomization with varying block sizes to maintain a
good balance of subjects between the two arms and optimize allocation concealment throughout
the subject recruitment period. A random sequence of grouping identifiers (I=intervention or
C=control), based on computer-generated random codes will be prepared in advance by a
statistician who is independent to arm allocation. The allocation sequence list will be
password-protected and stored in a computer, and only be accessible to staff who is for arm
allocation. The arm allocation of each participant will be assigned sequentially according to
his/her sequence of enrolment and the corresponding group identifier in the prior prepared
random sequence list. The research staff responsible for data collection will be blinded to
the arm allocation.
All participants will be dispensed a 12-week supply of double-blinded study intervention or
placebo products. Each participant will be given an administration log to record the daily
intake of G-NiiB® or its placebo-control. Patient will be counselled to take one packet of
the dispensed product once daily and record the time of ingestion and any adverse reactions
in the logbook daily for a total of 24 weeks. Patient will be advised to take photo of the
administration logbook within first week of enrollment into this study to ensure the log
entry has been filled accurately. Patient will receive monthly phone calls from a pharmacist
to ensure compliance of study product administration (31).
At interim study visit (at 12-week) All participants will be dispensed a 12-week supply of
double-blinded study intervention or placebo products. Administration logbook will be checked
by research staff. Adherence will be documented to compare the good adherence group and bad
adherence group for the efficacy of the product provided. Good adherence is defined as
missing not more than one daily dose of the product provided, while poor adherence is defined
as missing two or daily dose of the product provided.
Anthropometric measurements, including body weight and height, waist and hip circumferences,
percentage body fat by bioimpedance (23).
Questionnaires to document 1) demographic data including past medical and history, birth
weight, 2) 3-day diet record using locally validated questionnaires (24) and 3) physical
activity level/log sheet (IPAQ) ; 4) change of eating behavior and quality of life by eating
disorders examinations (EDE) and 36-item short form survey (SF-36).
Pharmacist to record past and present medication history, including prescribed drugs,
over-the-counter drugs and supplements, especially, 1) Subjects who have received
antibiotics, antifungal, antiparasitic, or antiviral treatment within 12 weeks prior to study
entry; 2) Subjects who plan to use antibiotic, antifungal, antiparasitic, or antiviral
treatment during the study; 3) Subjects using proton pump inhibitor; 4) Present use of
probiotics/nutritional supplements e.g., the use of replacement doses of Vitamin D, calcium
supplements, and multi-vitamin tablet.
After an overnight fast of 8-10 hours, baseline blood tests will be sampled including plasma
glucose, insulin, complete blood picture, renal and liver function tests, thyroid function
test, lipid profiles, high sensitivity C-reactive protein (hs-CRP) (25). Additional 15ml of
blood will be collected for PBMC isolation (22). Spot urine for albumin-creatinine ratio will
be collected for detection of microalbuminuria (26). Various indexes of insulin resistance
(HOMA-IR) and pancreatic beta-cell function (HOMA-beta) will be calculated from the
homeostasis model assessment (27). Insulin secretion will be calculated from plasma glucose
and insulin during various time points of OGTT.
Liver assessment by transient elastography (Fibroscan®), in which controlled attenuation
parameter (CAP) will be used to detect liver steatosis while liver stiffness measurement
(LSM) will be used to assess liver fibrosis (28).
Stool for gut microbiota will be sampled. Blood for genetic studies (5ml), plasma (350 µL)
and urine (500 µL) for metabolomics investigations will also be stored.
At follow-up visit (at 24-week) Repeat study procedures at baseline visit. All the unused
products must be returned to research team for examination.
