Fiber and metformin

Fiber and metformin DEFAULT

What should I eat while taking Metformin?

While there’s no official metformin diet, limiting your intake of certain types of foods will help manage your diabetes better

From being prescribed medications whose names you struggle to pronounce, to giving up the freedom to eat as you please, being diagnosed with diabetes means making changes to your lifestyle, all in the name of good health. And while these modifications are a must for maintaining optimum blood sugar levels, they’re not necessarily appealing – least of all to your appetite.

If you’re diabetic, you’ll likely be well-acquainted with metformin and even have it stockpiled in your medicine cabinet. Doctors typically use metformin as an initial treatment for diabetes.  Metformin effectively reduces the amount of glucose produced in the liver, decreases the amount of glucose absorbed from food and improves insulin sensitivity, all the while helping with weight loss – what a bonus!

Order safe and effective treatment for type 2 diabetes

View all treatments

While metformin may sound like a miracle pill that cures all your diabetes-related issues, we hate to burst your bubble, but it certainly is not. When taken as instructed by your doctor, along with diet and exercise, metformin can help improve your overall health and protect you from serious complications of diabetes such as heart disease, kidney failure, nerve damage and eye damage.  However, being careless about the food you consume can override the positive effects of metformin and cause your blood sugar levels to quickly spiral out of control.

So now that we’ve established that diet and drugs work in tandem to keep diabetes in check, what exactly should you (or shouldn’t you) be eating when taking metformin? 

Read on to find out.

 

What does a metformin diet look like?

While there’s no official metformin diet, per se, limiting your intake of certain types of foods will most definitely help you manage your diabetes.  As much as we don’t want to point any fingers, carbs, we’re talking about you!

When the body breaks down carbohydrates, glucose is the end result.  With the help of insulin, glucose then enters your cells and is stored or used for energy.  But when you consume more glucose than your body needs, much of it either gets stored in the liver and muscles for later use or is effectively converted to fat.

Here are some of the main carbohydrate-rich culprits that are likely to quickly raise your blood sugar levels:

  • Grains like bread, pasta, rice, and cereal
  • Starchy vegetables like potatoes and corn
  • Sugary sweets and drinks
  • Fruit juice

Cutting out carbohydrates completely isn’t a burden you should have to bear. Instead, learning ways you can control your carb consumption and, thereby, stabilize your glucose levels will bestow better diabetic management in the long-run.

 

How can I control my carb intake?

When it comes to achieving appropriate and sustainable carbohydrate intake, you’ll be glad to know that there is more than one way to get there. Here are just a few methods that have proved successful in steadying carbohydrate intake and therefore, blood sugar levels:

  • Counting your carbs: This involves allowing yourself to only eat and drink a set amount of carbohydrates throughout the day, measured in either grams or portions. It may take a while to come to grips with this method, but once you do, it can allow for greater flexibility with food choices while keeping your sugar levels under control.
  • Following a low-glycemic diet: Certain carbohydrates, known as high-glycemic foods, have a greater effect on blood sugar levels than others.  Recognizing what these foods are and avoiding them, can prevent rapid rises in blood sugar and excess release of insulin. Steer clear of white bread and pasta, and choose whole-grain alternatives instead.
  • Choosing your foods: If you prefer to have a little more structure to your meal plans, then this method may be just right for you. It involves having a set amount of carbohydrate, protein, and fat allowance each day and at each meal, and then choosing your desired foods accordingly – a great option for those who are counting calories and want to exercise portion control.
  • Creating your plate: This is probably the easiest and most fuss-free approach to controlling your carb consumption as it doesn’t involve any complicated counting, label-reading, or research. Simply divide your plate into clear sections, filling half of it with non-starchy vegetables like dark, leafy greens, bell peppers, tomatoes, asparagus, etc. then fill one quarter with healthy, low-glycemic carbs, and finally add a lean protein like chicken or beef to the final quarter of your plate. It’s as simple as that.

 

Are there any other changes I should make to my diet while taking metformin?

Having some general diet guidelines always helps when dealing with difficult conditions like diabetes.  Read through these top tips to stay in top form:

  • Consume fiber in moderation: According to one study by the University of Michigan, having a diet that is high in fiber when taking metformin can actually decrease the drug’s concentration, making it less effective. For this reason, it is recommended that you eat no more than 30mg of fiber per day.
  • Watch your alcohol intake: It’s worth noting that excessive consumption of alcohol while taking metformin can reduce your blood sugar levels and even induce a scary condition called lactic acidosis that can affect the liver, kidneys, and heart. So while a glass of wine can help you relax after a long and stressful day, just know that drinking large amounts of alcohol should be avoided.
  • Avoiding sodium and saturated or trans fats: As tempting as it may be to order takeout to save yourself the hassle of cooking, most fast foods are full of salt and saturated fats.  Instead, opt for foods containing healthy fats from fish, nuts, seeds, olive oil and avocado. Small amounts of sea salt or Himalayan pink salt are also preferred over the white variety that is typically kept on the dinner table.
  • Vitamin B12 supplements: Long-term use of metformin could potentially hinder the body’s ability to effectively absorb vitamin B12 from food, which can lead to anemia. Taking vitamin B12 supplements is therefore recommended when taking metformin for an extended period.

Hopefully, the above information has shed some light on what you can and cannot eat when taking metformin. Keeping your carb consumption in check is the first step to gaining control over your blood sugar, followed by other precautions such as minimizing alcohol, eating fiber in moderation, and trying to cut out fast food. If you’re still concerned about metformin and an optimal diet, speaking to your doctor may put your worries to rest.

 

References

  1. DiaTribe , Everything You’ve wanted to know about Metformin, but were Afraid to Ask, viewed 13th August ,https://diatribe.org/everything-you-always-wanted-know-about-metformin-were-afraid-ask

Buy Glucophage for type 2 diabetes from Medzino, your trusted online pharmacy

felix-star-rating

Complete a quick consultation, choose a FDA
approved treatment and get it shipped for free.

Free shipping on all orders

Featured treatments

Find out more about the treatments mentioned in this article below:

Prices from:

img

Quick medical consultation

Answer some simple questions about your health with our free 2 minute consultation

img

Reviewed by a real doctor

A U.S. licensed physician will review your answers and issue a prescription if suitable

img

Medicine delivered direct

Our pharmacy will pack your FDA approved medicine in anonymous packaging, and ship it for free

img

Quick consultation

img

Reviewed by a doctor

img

Medicine delivered

Order now for delivery on Wednesday

Prescription fees

Prescription fees are for our U.S. qualified doctors to evaluate your request and issue a prescription if that is the appropriate outcome for your case. We want to make healthcare pricing transparent and affordable that's why we set the doctor's fee at a flat rate of $20 for all services which is lower than most copays. The $20 medical fee does not include the cost of the medicine. We issue a % refund if we cannot help you including the doctor’s fee.

Register

Already have an account? Log in

img

Message Sent We will get back to you as soon as possible

img

Please choose your location

To get fast delivery and the best prices,
choose your location below:

Delivery to Germany only

Delivery to the US only

Delivery to UK only

img
img
img

You’ve successfully logged in.

img
img

Ask a doctor

If you’re not sure what to choose, our qualified GPs can help.

A doctor will review your consultation and message you with a suggestion within working days.

Thanks, a doctor will be in touch soon

Look out for the doctor’s response in your email inbox or patient account. View messages
img

Forgot your password?

Please check your email for password reset instructions. If you’re still having problems contact us .

Sours: https://www.medzino.com/us/health-center/what-should-i-eat-while-taking-metformin/

Efficacy of metformin and fermentable fiber combination therapy in adolescents with severe obesity and insulin resistance: study protocol for a double-blind randomized controlled trial

  • Study protocol
  • Open Access
  • Published:
  • Edward C. Deehan1na1,
  • Eloisa Colin-Ramirez2na1,
  • Lucila Triador2,
  • Karen L. Madsen3,
  • Carla M. Prado1,
  • Catherine J. Field1,
  • Geoff D. C. Ball2,
  • Qiming Tan2,
  • Camila Orsso1,
  • Irina Dinu4,
  • Mohammadreza Pakseresht1,
  • Daniela Rubin5,
  • Arya M. Sharma3,
  • Hein Tun6,
  • Jens Walter7,
  • Christopher B. Newgard8,
  • Michael Freemark8,
  • Eytan Wine9 &
  • Andrea M. Haqq2

Trialsvolume 22, Article number:  () Cite this article

  • Accesses

  • 1 Citations

  • 4 Altmetric

  • Metrics details

Abstract

Background

Accumulating evidence suggests that the metabolic effects of metformin and fermentable fibers are mediated, in part, through diverging or overlapping effects on the composition and metabolic functions of the gut microbiome. Pre-clinical animal models have established that the addition of fiber to metformin monotherapy improves glucose tolerance. However, possible synergistic effects of combination therapy (metformin plus fiber) have not been investigated in humans. Moreover, the underlying mechanisms of synergy have yet to be elucidated. The aim of this study is to compare in adolescents with obesity the metabolic effects of metformin and fermentable fibers in combination with those of metformin or fiber alone. We will also determine if therapeutic responses correlate with compositional and functional features of the gut microbiome.

Methods

This is a parallel three-armed, double-blinded, randomized controlled trial. Adolescents (aged 12–18 years) with obesity, insulin resistance (IR), and a family history of type 2 diabetes mellitus (T2DM) will receive either metformin ( mg p.o. twice/day), fermentable fibers (35 g/day), or a combination of metformin plus fiber for 12 months. Participants will be seen at baseline, 3, 6, and 12 months, with a phone follow-up at 1 and 9 months. Primary and secondary outcomes will be assessed at baseline, 6, and 12 months. The primary outcome is change in IR estimated by homeostatic model assessment of IR; key secondary outcomes include changes in the Matsuda index, oral disposition index, body mass index z-score, and fat mass to fat-free mass ratio. To gain mechanistic insight, endpoints that reflect host-microbiota interactions will also be assessed: obesity-related immune, metabolic, and satiety markers; humoral metabolites; and fecal microbiota composition, short-chain fatty acids, and bile acids.

Discussion

This study will compare the potential metabolic benefits of fiber with those of metformin in adolescents with obesity, determine if metformin and fiber act synergistically to improve IR, and elucidate whether the metabolic benefits of metformin and fiber associate with changes in fecal microbiota composition and the output of health-related metabolites. This study will provide insight into the potential role of the gut microbiome as a target for enhancing the therapeutic efficacy of emerging treatments for T2DM prevention.

Trial registration

ClinicalTrials.gov NCT Registered on 8 October

Peer Review reports

Administrative information

The order of the items has been modified to group similar items (see http://www.equator-network.org/reporting-guidelines/spiritstatement-defining-standard-protocol-items-for-clinical-trials/).

Title {1} Metformin and fermentable fiber combination therapy in adolescents with severe obesity and insulin resistance: Study protocol for a double-blind randomized controlled trial.
Trial registration {2a and 2b}. ClinicalTrials.gov Identifier: NCT
Protocol version {3} Protocol version dated 07 October
Funding {4} This work is funded by The W. Garfield Weston Foundation (without project number)
Author details {5a} University of Alberta, Edmonton, Canada
California State University, California, United States
University of Hong Kong, Sandy Bay, Hong Kong
University College Cork – National University of Ireland, Ireland
Duke University Medical Center, North Carolina, United Stated
Name and contact information for the trial sponsor {5b} University of Alberta
Quality Management in Clinical Research (QMCR) Department
Tel.: () –
Role of sponsor {5c} The University of Alberta and The W. Garfield Weston Foundation will not intervene in any aspect of the trial, including its design, data collection, analysis, or presentation.

Introduction

Background and rationale {6a}

Childhood obesity is a major risk factor for the development of insulin resistance (IR) and type 2 diabetes mellitus (T2DM) in youth. Importantly, youth-onset T2DM has been delineated as a more aggressive disorder, characterized by severe IR, insulin hypersecretion, rapid β-cell deterioration, and poor response to standard therapies [1,2,3,4]. Although limited or modest success has been reported for lifestyle interventions with behavioral modifications, such as diet and physical activity, they remain the most commonly applied therapies for IR and the underlying obesity in both adults and adolescents [1]. Pharmacotherapy with metformin (MET) has shown to induce modest reductions in body mass index (BMI) and reverse glucose intolerance in adult-onset T2DM [5]. However, for youth-onset T2DM, MET monotherapy has shown a 52% failure rate, while MET plus intensive lifestyle therapy also has shown a failure rate of 47%, as estimated by an uncontrolled intervention trial [1, 4]. Therefore, a clear need exists for the identification of efficacious therapies in adolescents which could be added to lifestyle modifications.

Adolescents with obesity typically present with systemic low-grade inflammation that has been implicated in the development of IR and cardiovascular dysfunction [6]. Obesity has also been associated with an imbalance in the composition and functionality of the gut microbiota [7,8,9]. However, it is unclear if changes in the gut microbial community contribute to the pathophysiology of adolescent obesity and associated comorbidities [10,11,12]. Gut microbiota might influence obesity and its dysregulated immunometabolism by facilitating caloric recovery [13], altering intestinal barrier and immune homeostasis [14], promoting the release of incretins and satiety hormones such as glucagon-like peptide 1 (GLP-1) [15], and regulating intestinal and hepatic gluconeogenesis [16]. Research further suggests that the composition of the gut microbiota can alter the risk of developing IR. For instance, the abundance of Akkermansia muciniphila has been inversely associated with obesity and IR [17,18,19]. On the other hand, Prevotella copri and Bacteroides vulgatus have been positively associated with the biosynthesis of branched chain amino acids (BCAAs), which are linked to the development of IR [20, 21]. Finally, the translocation of microbially derived lipopolysaccharides, termed endotoxemia, has been observed in patients with metabolic syndrome and T2DM [17, 22]. Despite the relationship described before, causal links between IR and the human gut microbiota remain to be established.

Effects of MET on glucose homeostasis are mediated through increases in hepatic insulin sensitivity, intestinal glucose utilization, anorexigenic GLP-1 levels, and reductions in hepatic glucose production [23]. At least some of the effects of MET are thought to be mediated by the gut microbiota. Recently, Wu and colleagues investigated the effect of MET on the composition and metabolic functions of the gut microbiota using a parallel-armed, randomized, placebo-controlled study in adults with newly diagnosed T2DM [24]. On an energy restricted diet, both groups reduced BMI significantly; however, only the MET group demonstrated reductions in fasting blood glucose and hemoglobin A1c (HbA1c) after 4 months. MET was found to increase the fecal abundances of Bifidobacterium adolescentis and A. muciniphila, with both species further shown to utilize MET for growth in vitro. However, HbA1c reductions were only associated with changes in B. adolescentis, suggesting a positive link between MET-improved glycemic control and the abundance of B. adolescentis [24]. More recently, administration of A. muciniphila has been shown to improve insulin sensitivity in adults with obesity and IR [25].

Dietary fibers have been long implicated in the protection from obesity and related comorbidities [26, 27]. As dietary fibers are not digested in the small intestine, they serve as growth substrates for the gut microbiota, producing putatively beneficial metabolites such as short-chain fatty acids (SCFAs) upon degradation [28, 29]. Microbially derived SCFAs have been proposed to enhance intestinal barrier function, downregulate pro-inflammatory immune responses, alter gastrointestinal transit time, reduce hepatic-associated gluconeogenesis, improve insulin sensitivity, and promote satiety independent of GLP-1 [29,30,31]. Administration of SCFAs in humans has also been shown to improve glucose metabolism, systemic inflammation, and energy homeostasis [30]. In addition, consumption of diets rich in dietary fiber can limit microbial fermentation of proteins and production of potentially detrimental metabolites, such as p-cresol, amines, and branched chain fatty acids [29, 32, 33]. Since MET and fermentable fibers have been shown to reduce weight and increase insulin sensitivity through divergent mechanisms of action, we postulate that combination therapy with MET plus fiber will act in concert to increase insulin sensitivity in adolescents with obesity through synergistic effects on the gut microbiome.

Pre-clinical studies in animal models of diabetes confirm that the addition of fermentable fibers, such as type-III resistant starch [34], PolyGlycopleX® (PGX) [35], and konjac mannan oligosaccharides [36], to MET monotherapy enhances glycemic control and delays T2DM progression. While evidence in humans remains limited, a short-term, uncontrolled study in adolescents showed that MET plus fiber (Policaptil Gel Retard®) promoted greater weight loss than MET alone; however, links to the gut microbiome were not elucidated [37]. In adults, the addition of inulin, oat β-glucan, and blueberry-derived polyphenolics to MET monotherapy has been shown to improve both glycemia and the gastrointestinal tolerance of MET after 2 weeks [38]. Furthermore, consumption of either supplemental fiber or a high-fiber diet promoted weight loss and improved HbA1c in adults with T2DM on MET monotherapy [39]. Overall, these findings suggest that separate pathways underlie the effects of MET and fermentable fibers, as fermentable fibers enhanced responses to MET. Thus, gut microbiome-targeted MET plus fiber combination therapies may have potential for enhanced reduction of IR in adolescents with obesity. The aim of this study protocol is to compare the effects of MET and fiber alone and in combination over 12 months on measures of insulin sensitivity and resistance in adolescents at high risk of T2DM.

Objectives {7}

The primary objective is to compare the efficacy of MET ( mg p.o. twice/day) versus FIBER (35 g/day supplemental fiber) alone versus combined MET plus FIBER on IR (as estimated by homeostatic model assessment of insulin resistance [HOMA-IR]) in adolescents with obesity, IR, and family history of T2DM.

The secondary objective is to compare the effects of the study therapies alone or in combination on:

  1. 1.

    Changes in the Matsuda, insulinogenic, and oral disposition indices as determined by OGTT

  2. 2.

    Changes in body weight, BMI percentile and z-score, and body composition (fat mass, fat-free mass, and fat mass to fat-free mass ratio)

  3. 3.

    Changes in quality of life (QoL) and perceived hunger and satiety

  4. 4.

    Changes in fasting metabolic (glucose, adiponectin, and lipids) and satiety markers (acylated ghrelin, peptide tyrosine tyrosine [PYY], GLP-1, and leptin)

  5. 5.

    Changes is measures of systemic inflammation (C-reactive protein, interleukin 6, and tumor necrosis factor-α [TNF-α]) and intestinal barrier function (lipopolysaccharide-binding protein (LPB) and fecal calprotectin)

  6. 6.

    Changes in gut microbiome composition and functions (fecal microbiota composition, fecal SCFAs and bile acids, and targeted plasma metabolomics [amino acids, branched chain ketoacids, acylcarnitines, ceramides, trimethylamine N-oxide, choline, and betaine])

Trial design {8}

A single-center, parallel three-armed, double-blinded, month randomized controlled trial with a allocation ratio. Ninety adolescents (n = 30 per arm) with obesity, IR, and family history of T2DM will be enrolled in the trial matched for sex and age (Figs. 1 and 2).

Study design. Participants meeting the eligibility criteria will be randomly allocated to one of three study groups: (1) metformin ( mg bid), (2) fiber (supplemental fiber 35 g/day) or metformin plus fiber. Participants will be followed up for 12 months with clinical visits every 3 months. Abbreviations: ADP, air displacement plethysmography; BMI, body mass index; HOMA-IR, homeostatic model assessment of insulin resistance; T2DM, type 2 diabetes mellitus

Full size image

Conceptual design. Changes expected in primary and secondary outcomes in the combination therapy compared to each monotherapy. Symbols: ↑ increase or improvement; ↓ decrease

Full size image

Methods: participants, interventions and outcomes

Study setting {9}

Participants will be recruited from both the Pediatric Endocrinology and General Pediatric Clinic at the Stollery Children’s Hospital at the University of Alberta (UofA), and the community based Pediatric Centre for Weight and Health in Edmonton, Canada.

Eligibility criteria {10}

Inclusion criteria:

  1. 1.

    Age 12–18 years old

  2. 2.

    BMI ≥ 95th percentile for age/sex

  3. 3.

    Total weight fluctuation over past 6 months < 10%

  4. 4.

    HOMA-IR > 

  5. 5.

    Family history of T2DM (first- or second-degree relative)

Exclusion criteria:

  1. 1.

    Current use of insulin or diagnosis of T2DM

  2. 2.

    Systolic or diastolic blood pressure > 99th percentile for age and sex

  3. 3.

    Acute infectious or inflammatory condition over the preceding 1 month; hospitalization > 48 h

  4. 4.

    History of chronic diseases, such as liver, kidney, or inflammatory bowel disease, or neurologic disorders

  5. 5.

    Active malignancy

  6. 6.

    Concomitant use of medication/investigational drug known to affect body weight in the past year

  7. 7.

    Antibiotic use in past 60 days; probiotic and/or prebiotic supplement use in the past 30 days; use of lipid-lowering and anti-inflammatory medication

Who will take informed consent? {26a}

Written informed consent (from parents/caregivers and participants aged 18 years) and assent (from participants aged 12–17 years) will be obtained from all participants before inclusion by the principal investigator or trained research staff.

Additional consent provisions for collection and use of participant data and biological specimens {26b}

Participants will be asked to provide Optional Specimen Consent to biobank blood and stool samples for future studies yet to be determined. Participants who do not consent for biobanking can still take part in the rest of the study.

Interventions

Explanation for the choice of comparators {6b}

We postulate that the therapeutic effects of both MET and fermentable fibers are mediated, in part, through diverging effects on the gut microbiome, and that MET plus fiber combination therapy will act synergistically to improve glucose tolerance in adolescents with obesity and IR. By combining MET with fiber, we anticipate that the improvement in IR and BMI will be significantly higher when compared to each monotherapy. A control group without treatment is not included, since a no treatment arm would be unethical for adolescents with obesity and IR.

Intervention description {11a}

Participants will be randomly assigned to one of three study arms:

  1. 1.

    MET arm: MET ( mg p.o. twice/day—standard of care) plus fiber placebo daily

  2. 2.

    FIBER arm: fiber supplementation (35 g/day fiber) plus MET placebo twice/day

  3. 3.

    MET + FIBER arm: MET ( mg p.o. twice/day) plus fiber supplementation (35 g/day fiber)

Metformin administration and rationale

Participants in the MET group will initially receive  mg daily, increasing to  mg twice/day if tolerated after 2 weeks (those who do not tolerate will be withdrawn from the study), and then increasing after an additional 2 weeks to  mg twice/day ( mg daily). The MET or placebo (microcrystalline cellulose [MCC] powder) capsules will be taken with meals along with a multivitamin containing B12, in order to prevent a potential MET-associated vitamin B12 deficiency [40]. A dose of  mg twice/day was chosen based on studies demonstrating decreases in BMI and IR at these doses [41, 42]. Although side-effects of MET are generally minor, the dosage will be titrated to avoid mild, self-limited side-effects (i.e., abdominal pain, flatulence, bloating, nausea, and diarrhea). Although lactic acidosis, hypoglycemia, and other serious side-effects are rare, side-effects will be routinely monitored throughout the trial by the principal investigator or a research coordinator.

Fiber administration and rationale

Our supplemental fiber mixture (35 g/day of total fiber) will be composed of fermentable non-viscous (6 g oligofructose + 12 g resistant maltodextrin + 12 g acacia gum) and viscous (5 g PGX) fibers. Dosages of individual fibers were determined based on clinical evidence for effective dose and known tolerability data (Additional file 1). In addition, we and others suggest that ~ 50 g/day of fiber (35 g/day supplemental + ~ 15 g/day from diet) may be required for attaining reliable physiological benefits linked to fiber [29, 43]. This conclusion is supported by recent findings that 35 g/day of fermentable fiber maximized the health-relevant shifts in both bacterial taxa and fecal SCFAs [33]. Previous pediatric dietary fiber interventions of similar dosage report no tolerance concerns [44, 45]. For instance, Zhang et al. provided children with obesity around 50 g/day of fiber without any concerns of tolerance [45]. While it is expected that 35 g/day of fermentable fiber will be tolerated, gastrointestinal symptoms will be monitored throughout the trial.

To allow time for gastrointestinal adaptation, participants will be instructed to use 1/3 of the total daily fiber dose (or placebo) during the first week of treatment; then 2/3 of the dose for the second and third weeks; and then the full dose thereafter. This dose escalation is suggested to improve tolerance as adaption over time has been previously described for such fiber supplements [46, 47]. The fiber treatment (or placebo) will be provided as a powder to be added by the participant to water or sugar-free beverages and consumed prior to meals. This method of consumption is easy to incorporate and ensures enough water intake is spread throughout the day to improve gastrointestinal tolerance. Alternatively, participants will be allowed to mix the fiber, or placebo, with foods (e.g., added to cereals, soups, and yogurt), if preferred, to allow flexibility and maximize compliance, which is important due to the duration of the intervention. The fiber placebo will consist of MCC, a non-fermentable fiber with no effect on the gut microbiota [48].

Criteria for discontinuing or modifying allocated interventions {11b}

Participants will be withdrawn from the study if the participant (1) withdraws consent, (2) becomes pregnant, (3) does not tolerate either MET or dietary fiber interventions, (4) requires antibiotic therapy within the first 6 months of the trial, (5) has an HbA1c > 8%, or (6) the participant, in the opinion of the investigator, is not clinically able to continue to follow the investigative intervention (e.g., need of initiating another specific medical intervention such as insulin). Participants will be free to withdraw consent at any time without prejudice to current or future medical care. When a participant expresses his/her wishes to withdraw from the study, he/she will receive instructions to complete an “end of study” visit, which will also be voluntary. Data collected up to the time of withdrawal will remain in the trial database and be included in data analysis.

Strategies to improve adherence to interventions {11c}

We will document and reinforce adherence during each study visit. Participants will complete a dosing journal (self-documentation) and return unused products; research staff will review the journal and number of remaining pills or sachets containing fiber or placebo to document adherence. Additionally, participants will be contacted regularly by email and text messages to reinforce adherence.

Relevant concomitant care permitted or prohibited during the trial {11d}

Hypoglycemic drugs, insulin, and medications known to affect body weight will not be allowed during the trial. If a participant must use any of these medications, he/she will be withdrawn from the study. The principal investigator will determine acceptability of any other concomitant medication. Adolescents in this study will continue to receive conventional lifestyle management advice as per routine clinical practice at their clinics.

Provisions for post-trial care {30}

There is no specified ancillary or post-trial care for participants in this trial. However, it is expected that the results of this study will guide clinical care of children at high risk of T2DM after completion of the trial. If a participant becomes ill or injured as a result of being in this study, he/she will receive necessary medical treatment, at no additional cost to the participant.

Outcomes {12}

The primary outcome of this study is a change in IR, as estimated by HOMA-IR, between baseline, 6, and 12 months. The secondary outcomes of this study include changes between baseline, 6, and 12 months in (1) the Matsuda, insulinogenic, and oral disposition indices as determined by OGTT; (2) weight, BMI percentile and z-score, and body composition (fat mass, fat-free mass, and ratio of fat mass to fat-free mass); (3) QoL and perceived hunger and satiety; (4) fasting metabolic (glucose, adiponectin, lipids, and OGTT) and satiety markers (acylated ghrelin, PYY, GLP-1, and leptin); (5) measures of systemic inflammation (C-reactive protein, interleukin 6, and TNF-α) and gut barrier integrity (lipopolysaccharide-binding protein [LPB] and fecal calprotectin); and (6) gut microbiome composition and functions (fecal microbiome composition, fecal SCFAs and bile acids, and targeted plasma metabolomics [amino acids, branched chain ketoacids, acylcarnitines, ceramides, trimethylamine N-oxide, choline, and betaine]).

Participant timeline {13}

Sample size {14}

Our primary outcome is IR as estimated by HOMA-IR. Based on a recent study where the effect size of MET on HOMA-IR among pubertal participants was [49], we estimated a sample size of 29 per arm, which will give us 90% power to find any significant post-intervention difference between arms at 5% significance level. Additionally, a percentage of change and 95% confidence interval for HOMA-IR after PGX from Pal et al. [50] resulted in an effect size of , rendering a sample size of 26 per arm. We expect a greater response in the combination therapy; for this reason and considering 26 per arm as feasible, and 15% attrition rate during follow-up, we estimated a total of 90 participants over the 3 arms.

Recruitment {15}

Participants will be recruited over 24 months. Potential participants will be identified by clinicians that are aware of the study, the principal investigator, or research staff who will review the clinical charts of patients attending the Pediatric Endocrinology Clinic, General Pediatric Clinic, and the Pediatric Centre for Weight and Health. Once a potential participant has been identified, a clinician or the principal investigator will approach the potential participant and their parents, provided information about the study, and ask the patient if his/her name can be passed onto a research team member to be contacted about the study. If the potential participant and their parents provide written consent to release contact information to researcher, the research team member will contact them to provide additional information about the study, answer questions or concerns, complete a screening process, and if applicable, arrange a potential study visit where written inform consent will be obtained. The informed consent process will be conducted in person by a qualified research team member.

In the case that a research staff member identifies a potential participant, the study coordinator will approach the attending physician and review this information. If the attending physician agrees, he/she will ask the patient if they might be interested in learning more about the research study. If the patient agrees, a member of the research team will be called to share the information and invite the patient to participate.

Assignment of interventions: allocation

Sequence generation {16a}

After having provided written informed consent/assent, participants will undergo a baseline assessment and be randomized to one of the three intervention groups A, B, and C (i.e. MET, FIBER, MET + FIBER) via computer-generated numbers and stratified by age and sex, using the adaptive (dynamic) randomization (Step 2, Fig. 3). Each group will be also randomly allocated to one of three intervention arms of MET, FIBER, and MET + FIBER (Step 3, Fig. 3). Staff who completed Steps 2 and 3 will be different and will be blinded to the other step. Stratification will be based on four sex/age categories of male 12–15 years old, female 12–15 years old, male 16–18 years old, and female 16–18 years old.

Study population recruitment and randomization strategy

Full size image

Concealment mechanism {16b}

The arm allocations will be concealed by keeping this information restricted by the statistician generating the randomizations codes.

Implementation {16c}

A statistician will generate the randomization codes and an unblinded research team member will package and label the investigational fibers and placebo. These research personnel will not be involved in any other study procedures/assessments. Different research staff will enroll and randomize participants.

Assignment of interventions: blinding

Who will be blinded {17a}

Both participants and research team will be blinded to the type of intervention allocated to each arm until the end of the study. The group not on MET (fiber alone) will receive a placebo pill (MCC). The group not on fiber will also receive a placebo (MCC) in identical sachets; this double-blind strategy will reduce risk of bias. Both fiber and MET have a similar side-effect profile, which will support the blinding procedures.

Procedure for unblinding if needed {17b}

In case of an emergency in which knowledge of the treatment assignment is deemed essential by the participant’s care, the code could be opened. The person in charge of keeping these codes secure will open the code for that specific participant and will inform only the treating physician, keeping the code concealed from research personnel. Any unblinding will be approved by the principal investigator.

Data collection and management

Plans for assessment and collection of outcomes {18a}

Study visits will be conducted at the Human Nutrition Research Unit, a state-of-the-art facility supporting leading nutrition intervention research at the UofA. Participants will be seen at baseline (visits 0 and 1), 3, 6, and 12 months, and a phone follow-up will be completed at 1 and 9 months (Table 1). The month duration of the intervention will assess both short- and longer-term effects of the combined FIBER plus MET intervention. At visit 0, and after obtaining informed consent/assent, baseline assessments will be conducted, including demographics, medical history, physical exam, sexual maturation (Tanner stage), anthropometrics, and body composition; in addition, participants will complete QoL, gastrointestinal tolerance, and 7-day physical activity questionnaires. During this visit, research staff will provide to the participants a 3-day food record (to assess dietary intake), Satiety Labeled Intensity Magnitude (SLIM) and bowel habit (Bristol stool chart) questionnaires, and stool sample collection kits to be completed at home and brought to visit 1 (day 0); this visit will occur within the following 10 days after visit 0. At visit 1, fasting blood samples will be withdrawn, and an OGTT will be completed. Once baseline assessments are completed, participants will be randomly assigned to one of the three study groups and the respective study intervention will be delivered.

Full size table

Initial assessments, including primary and secondary outcomes, will be repeated at 6- and month follow-up visits. At 1 month, participants will be contacted over the phone to monitor adverse events and compliance. During the 3-month visit, participants will undergo a physical exam and anthropometric assessments and will complete QoL, gastrointestinal tolerance, and SLIM questionnaires, as well as a 3-day food record. At 9 months (phone follow-up), only questionnaires and a 3-day food record will be completed; research staff will assist in completing these questionnaires over the phone when needed (Table 1).

Demographics and clinical assessment

Date of birth and ethnicity will be collected. A medical history (mode of delivery and infant nutrition practices [breastfeeding or formula], and current medications) will be completed, a physical exam (blood pressure and heart rate using an automated blood pressure monitor) will be conducted, and sexual maturation will be self-assessed (by children assisted by their parents) using the Tanner Stage scale [51].

Anthropometrics and body composition

After participants void their bladders, body weight and height will be measured and used to calculate BMI percentile and z-score (WHO Anthroplus software, Geneva, Switzerland). Waist circumference will be measured in narrowest site between the xiphoid process and iliac crest [52]. Waist circumference z-score will be calculated using the Anthropometric Calculator for normal children 5–19 years of age based on the World Health Organization Growth Charts for North America Children [53]. Body density using air displacement plethysmography (Bod Pod® 1SB M, Life Measurement Instruments, CA, USA) [54] will be assessed to estimate fat mass, fat-free mass, and the ratio of fat mass to fat-free mass, according to the manufacturer’s instructions [55].

Study questionnaires

A 3-day food record (2 weekdays/1 weekend day) will be completed every 3 months to monitor dietary intake and diet quality throughout the study. Self-reported physical activity levels will be assessed every 6 months using the physical activity questionnaire for older children (≤ 14 years) [56] and for adolescents (> 14 years) [57]. QoL will be measured every 3 months using the Peds QL instrument [58]. The validated SLIM scale will be used to assess perceived hunger and satiety (fasting, before dinner, and 1 and 2 h after dinner) every 3 months. This scale is a mm visual analog scale anchored by “greatest imaginable hunger” and “greatest imaginable fullness”, with “neither hungry nor full” in the center. Participants will place a mark on the scale corresponding to their sensation of hunger or fullness [59]. To evaluate the gastrointestinal tolerance of the interventions, a previously described gastrointestinal tolerance questionnaire will be used every 3 months [33]. This questionnaire assesses the presence and severity of six symptoms over the previous 7 days, including nausea, gastrointestinal rumblings, abdominal pain, bloating, flatulence, and diarrhea. Participants will rate each symptom as “did not experience,” “no more than usual,” “somewhat more than usual,” or “much more than usual” [33]. Bowel habits will also be recorded over 4 days every 6 months by using a bowel habits diary; in this diary, participants will record bowel movement frequency and fecal consistency rated on a scale of 1 (hard) to 5 (watery) using the Bristol Stool Scale for children [60].

Assessment of insulin resistance, metabolites, hormones, and intestinal barrier function

As the primary endpoint, HOMA-IR will be calculated as fasting glucose (mmol/L) × fasting insulin (μIU/mL)/22 [61, 62]. HOMA-IR has been shown to be reproducible and correlate with more invasive tests of insulin sensitivity [63, 64]. An OGTT will also be completed and the Matsuda (whole body insulin sensitivity index) [65], insulinogenic [66], and oral disposition [67] indices well be calculated. The OGTT has been validated in multiple clinical and research settings and reflects the efficiency of the body to dispose of glucose after an oral load; it is commonly used to diagnose glucose intolerance and diabetes [68,69,70]. The participants at risk for T2DM will already require regular screening using OGTT every ~ 6 months; thus, utilizing this gold standard for the study will not create extra patient burden. Participants will ingest  g/kg (75 g maximum) glucose; blood samples for glucose and insulin will be obtained at 0, 30, 60, and  min.

Fasting (12 h) plasma and serum samples will be collected and stored at − 80 °C until further analysis. These analyses include the measure of (1) general safety measures (CBC-D, electrolytes, blood urea nitrogen, creatine, thyroid-stimulating hormone, aspartate transaminase, and alanine aminotransferase), (2) satiety markers (acylated ghrelin, PYY, GLP-1, and leptin), (3) metabolic markers (glucose, insulin, HbA1c, total and high-molecular-weight adiponectin, total cholesterol, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, and triglycerides), (4) inflammatory markers (C-reactive protein, interleukin 6, TNF-α, and lipopolysaccharide-binding protein [LBP; a measure of intestinal barrier function]), and (5) targeted metabolites measured by liquid chromatography–tandem mass spectrometry (amino acids, branched chain ketoacids, acylcarnitines, ceramides, trimethylamine N-oxide, choline, and betaine). Protease inhibitors will be added when required for the quantification of hormones.

Fecal samples will also be used to measure calprotectin levels (as a measure of intestinal barrier function) using an enzyme-linked immunosorbent assay according to the manufacturer’s protocol.

Fecal microbiome analyses

Once collected from participants, stool samples will be immediately processed, aliquoted, and stored at − 80 °C until further analysis. DNA will be extracted from the fecal homogenates using the QIAamp DNA Stool Mini Kit (Qiagen, Valencia, CA, USA) with the addition of a mechanical lysis step, as recently described by Costea et al. [71]. Fecal microbiota composition will be characterized by 16S rRNA gene amplicon sequencing using MiSeq Illumina technology (pair-end) as previously described [33]. Quality-controlled reads will be analyzed using (1) taxonomic-based approaches (GAST and the Ribosomal Database Project Multi Classifier tool) and (2) non-taxonomic-based clustering algorithms for operational taxonomic unit (OTU) determination with the UPARSE pipeline. α-diversity (Shannon, Simpson, and observed OTUs) and β-diversity indices (Bray-Curtis and binary Jaccard) will be calculated in QIIME2 [72] and R (VEGAN package) [73]. To assess metabolic functions of the gut microbiota, fecal SCFAs will also be analyzed by gas chromatography (Varian, CA, USA) [74] and bile acids using liquid chromatography–mass spectrometry [75, 76].

Plans to promote participant retention and complete follow-up {18b}

When a participant expresses his/her wishes to withdraw from the study, he/she will be asked to complete an “end of study” visit. Data collected up to the time of withdrawal will remain in the trial database and be included in data analysis, unless otherwise indicated by the participant.

Data management {19}

Study charts will be stored within a secure cabinet at site. All research data will be captured and managed using Research Electronic Data Capture (REDCap) [77] hosted at the Faculty of Medicine and Dentistry at the UofA. To ensure data quality, the database will be designed with branching logic, data validation, and range checks for data values, where possible. Research data and study documentation will be retained for a period of 25 years.

Confidentiality {27}

No directly identifying information will be entered in the REDCap system, and participants will be identified by a unique participant study number (code) on the case report forms. Personnel entering research data into REDCap will have a personal username and password after access has been granted by the REDCap administrator. This password will be required to be changed periodically. Other study-related documents containing direct identifiers (e.g., signed consent form) will be stored in a locked filing cabinet in a secure office at site. All computer files related to this study (e.g., master list and data set) will be encrypted and password protected. Participants will be informed during the consent inform process that the coded research data and original medical records may be inspected by UofA auditors, members of the Research Ethics Board, and Health Canada, for regulatory and monitoring purposes.

Plans for collection, laboratory evaluation, and storage of biological specimens for genetic or molecular analysis in this trial/future use {33}

Stool and blood samples will be collected at site from the participant and processed. Then, aliquoted stool, serum, and plasma will be stored at − 80 °C in the freezer located at site until further analysis for the same purpose of the study objectives. Additional samples from participants who provided Optional Specimen Consent for biobanking and genetic testing will be kept up to 15 years, until they are used up for future studies, yet to be determined, or destroyed.

Statistical methods

Statistical methods for primary and secondary outcomes {20a}

Descriptive statistics will summarize all study variables. Prior to analysis, numerical variables with skewed distribution will be transformed (e.g., log2 or cubed root) or a comparable nonparametric test will be used. Between-group comparison of primary and secondary outcomes will be performed at baseline and two consecutive time points independently using unpaired t-tests (comparing two groups) or analysis of variance (three groups) and chi-square tests for numerical and categorical data, respectively. Impact of the three interventions on IR (HOMA-IR, primary endpoint) over time will be compared using linear mixed models, after adjusting for relevant confounders, including pubertal stage if any statistically significant difference is observed between treatment groups at baseline. OTU relative abundance will be compared between treatment groups. Statistical analyses for gut microbiota community composition will include principal coordinates analysis and canonical correlation. Linear discriminant analysis Effect Size [78] and multivariate association with linear models will be used to identify specific OTUs that differentiate the treatment groups. Mediation modeling will be employed to provide further insights on possible casual pathways to explore whether the gut microbiota may play a causal or mediation role in the physiological effects detected [79]. Treatment responders versus non-responders will also be evaluated. We will characterize the ecological differences prior to the intervention, and then the individualized response to the intervention in order to assess the role of the microbiome in the host’s metabolic response to the intervention. For this analysis, we will apply a machine learning approach called partition around medoids clustering [80]. Separate models will be estimated for secondary endpoints, which are exploratory, but nevertheless important. Intervention types and times will be included as fixed effects in linear mixed models. Pearson or Spearman correlation coefficients will be computed between changes in gut microbiome composition/function and insulin resistance, hormones, metabolites, and inflammatory markers.

Interim analyses {21b}

No interim analyses will be completed.

Methods for additional analyses (e.g., subgroup analyses) {20b}

We plan to do a subgroup analysis for age and sex differences within each arm.

Methods in analysis to handle protocol non-adherence and any statistical methods to handle missing data {20c}

We will undertake an intention-to-treat analysis to assess intervention effect.

Multiple imputation approach or a sensitivity analysis will be followed to address missing data.

Plans to give access to the full protocol, participant-level data, and statistical code {31c}

There are no plans for granting public access of the full protocol, participant-level dataset, or statistical code.

Oversight and monitoring

Composition of the coordinating center and trial steering committee {5d}

The study will be conducted under the leadership of a Steering Committee, which will be responsible for scientific and operational guidance to the overall protocol. The Steering Committee will meet monthly in the initial phases, then quarterly throughout the project remainder. A Data Safety Monitoring Board made of experts in pediatric obesity and T2DM will provide oversight and will be assembled on an ad hoc basis.

Composition of the data monitoring committee, its role and reporting structure {21a}

Site initiation, ongoing monitoring, and study close out will be performed by the Quality Management in Clinical Research Group within the UofA (www.qmcr.ualberta.ca/). Interim monitoring visits will be conducted to ensure compliance with Good Clinical Practices; the study is conducted according to site specific standard operating procedures, the protocol, and regulatory guidelines.

Adverse event reporting and harms {22}

All adverse events will be tracked in an adverse event log and classified following the Guidance Document for Clinical Trial Sponsors: Clinical Trial Applications [81], according to their severity (serious, non-serious), expectedness (expected, unexpected), and relatedness to the study intervention (related, possible related, unrelated). All serious adverse events will be collected in the participant case report forms. All serious, treatment-related adverse events will be reported to Health Canada and the UofA Human Research Ethics Board (HREB). All serious adverse events will be followed until resolution (for those that resolve before the end of the study), or for 1 month after the end of the study unless the investigator determines that additional follow-up is necessary.

Frequency and plans for auditing trial conduct {23}

There are no plans for auditing trial conduct beyond the interim monitoring visits conducted by the Quality Management in Clinical Research Group.

Plans for communicating important protocol amendments to relevant parties (e.g., trial participants, ethical committees) {25}

All protocol amendments will be submitted to the UofA-HREB for approval before implementation, unless the amendment is necessary to eliminate an immediate hazard to the trial participants. In this case, the necessary action will be taken first, with the relevant protocol amendment following shortly thereafter. Investigators will be notified once the amendment has been approved by the UofA-HREB.

Dissemination plans {31a}

Findings from this trial will be disseminated at local, national, and international academic and professional conferences. It is expected that the study results will be published in scientific peer-reviewed journals.

Discussion

This study will compare the metabolic benefits of fiber with those of metformin in adolescents with obesity, determine if metformin and fiber act synergistically to improve IR, and elucidate whether the metabolic benefits of metformin and fiber associate with changes in fecal microbiota composition and the output of health-relevant metabolites. The study will thereby assess the relationship between therapeutic intervention(s) and putative mechanisms that are hypothesized to underlie the clinical effects. Overall, we predict that the combination of MET and fiber will have a synergistic effect, being more effective than MET or fiber alone at 12 months in improving IR and BMI in the adolescents with obesity. We further predict that these metabolic benefits will be associated with changes in gut microbial composition and metabolic functions (assessed by 16S rRNA gene amplicon sequencing, fecal SCFAs and bile acids, and targeted plasma metabolomics) and measures of systemic inflammation and intestinal barrier function (assessed by plasma cytokine, LBP, and fecal calprotectin). If successful, our proposed combination therapy may help to interrupt the cycle of weight gain and IR, thereby reducing the risk for developing T2DM, a worldwide public health concern, in adolescence and adulthood.

To potentially maximize the number of responders to the dietary fiber intervention, a combination of fermentable non-viscous (oligofructose, resistant maltodextrin, acacia gum) and viscous (PGX) fibers will be used in this study, providing a complex and diverse array of substrates to the gut microbiota [29, 82]. The colonic microbiota exists as part of an ecosystem, where substantial cross-feeding occurs; metabolites produced by one bacterium are used as a substrate by another bacterium, and specific key-stone species or guilds are required to degrade a substrate [28, 29]. Therefore, a variety of substrates are likely needed to enhance and diversify microbial responses aimed at improving host metabolism. This concept is supported by in vitro evidence showing that a mixture of fibers is better than a single fiber at promoting bacterial diversity [83], which is generally lower in adolescents with obesity [7, 9]. In human trials involving fermentable fibers, a high degree of between-study heterogeneity has been reported in the clinical response to fiber [84, 85]. These inconsistencies might stem from the extensive interindividual differences in gut microbial configurations at baseline and in response to dietary fiber supplementation [48, 84, 86]. This concept is highlighted by the recent work of Hjorth and colleagues, where individuals with a higher Prevotella-to-Bacteroides ratio at baseline lost significantly more body weight and body fat on a fiber-rich diet than individuals with a lower ratio [87]. Thus, subjects with obesity and an imbalance in the composition and functionality of the gut microbiota may not possess the microbes necessary to utilize and benefit from a single-fiber supplement. Therefore, providing a mixture of fiber structures, as opposed to a single fiber, could potentially induce more reliable metabolic effects in individuals with obesity and IR.

By employing targeted fecal and plasma metabolomics with fecal microbiota sequencing, we can identify changes in metabolite production that correlate with modifications of the gut microbiota. This systematic analysis of the gut microbial community may result in the identification of baseline microbiota configurations or metabolites that predict effects of MET and/or fermentable fibers and could, therefore, be used to enhance clinical responses with personalized therapies. Such novel biomarkers might also be relevant for predicting the future risk of developing metabolic abnormalities associated with childhood obesity. Our novel approach will inform the development of future microbiome-targeted pharmaceutical and prebiotic therapies, including the possible implementation of long-term, multicenter microbiome-targeted intervention studies aimed at improving health outcomes in childhood obesity. Finally, the goal of the research team is to provide a basis for using the gut microbiome as a window to improve the assessment and treatment of metabolic abnormalities in children with obesity.

While the high dietary fiber dose and month intervention period are considered strengths of study, and potentially necessary for attaining reliable and sustained health benefits linked to fiber [85], both variables may impact protocol adherence and attrition throughout the intervention. To partially mitigate this, regular clinic visits, phone calls, emails, and text messages will occur to ensure the participants’ engagement and encourage protocol adherence. We will also monitor adherence through self-documentation (dosing journal) and collecting all unused study products. Another study limitation is that features of the participant’s lifestyle (i.e., diet and physical activity) remain uncontrolled. While this “real life” approach greatly improves the generalizability of study findings, as is often the case, intentional or unintentional lifestyle changes can occur that independently improve IR and BMI. To minimize these effects, participants will be encouraged to follow the study protocol without intentional lifestyle changes. Additionally, 3-day food records and physical activity questionnaires will be completed at baseline and throughout the dietary intervention to establish deviations from baseline, which will be incorporated and controlled through statistical analysis.

In summary, this study will determine the efficacy of MET and fermentable fibers alone or in combination on metabolic control, while also determining if the effects are related to individual differences in microbiome composition and functions. Thus, this study will demonstrate whether the gut microbiome represents a promising target for enhancing therapeutic efficacy and for further preventing T2DM in at risk adolescents. The results of this study may be integrated into clinical practice guidelines for the prevention of youth-onset T2DM and also aid in the development of novel microbiota-targeted therapies for adolescents with obesity and associated metabolic comorbidities.

Trial status

The protocol published herein is version dated 07 October The trial has not yet started recruitment. Estimated start date of recruitment is April 1, Estimated end date of recruitment is March 1,

Abbreviations

Body mass index

Glucagon-like peptide 1

Hemoglobin A1c

Homeostatic model assessment of insulin resistance

Insulin resistance

Lipopolysaccharide-binding protein

Metformin

Oral glucose tolerance test

Operational taxonomic unit

PolyGlycopleX

By mouth

Peptide tyrosine tyrosine

Short-chain fatty acid

Satiety Labeled Intensity Magnitude

Type 2 diabetes mellitus

Tumor necrosis factor-α

University of Alberta Human Research Ethics Board

References

  1. 1.

    Zeitler P. Progress in understanding youth-onset type 2 diabetes in the United States: recent lessons from clinical trials. World J Pediatr. ;15(4)–

    PubMedArticlePubMed Central Google Scholar

  2. 2.

    Jensen ET, Dabelea D. Type 2 diabetes in youth: new lessons from the SEARCH study. Curr Diab Rep. ;18(6)

    PubMedPubMed CentralArticle Google Scholar

  3. 3.

    Hamman RF, Bell RA, Dabelea D, D'Agostino RB Jr, Dolan L, Imperatore G, et al. The SEARCH for diabetes in youth study: rationale, findings, and future directions. Diabetes Care. ;37(12)–

    PubMedPubMed CentralArticle Google Scholar

  4. 4.

    Group TS, Zeitler P, Epstein L, Grey M, Hirst K, Kaufman F, et al. Treatment options for type 2 diabetes in adolescents and youth: a study of the comparative efficacy of metformin alone or in combination with rosiglitazone or lifestyle intervention in adolescents with type 2 diabetes. Pediatr Diabetes. ;8(2)–

    Article Google Scholar

  5. 5.

    Moin T, Schmittdiel JA, Flory JH, Yeh J, Karter AJ, Kruge LE, et al. Review of metformin use for type 2 diabetes prevention. Am J Prev Med. ;55(4)–

    PubMedPubMed CentralArticle Google Scholar

  6. 6.

    Koleva PT, Bridgman SL, Kozyrskyj AL. The infant gut microbiome: evidence for obesity risk and dietary intervention. Nutrients. ;7(4)–

    CASPubMedPubMed CentralArticle Google Scholar

  7. 7.

    Del Chierico F, Abbatini F, Russo A, Quagliariello A, Reddel S, Capoccia D, et al. Gut microbiota markers in obese adolescent and adult patients: age-dependent differential patterns. Front Microbiol. ;

    PubMedPubMed CentralArticle Google Scholar

  8. 8.

    Peng Y, Tan Q, Afhami S, Deehan EC, Liang S, Gantz M, et al. The gut microbiota profile in children with Prader-Willi syndrome. Genes (Basel). ;11(8)

    CASArticle Google Scholar

  9. 9.

    Rampelli S, Guenther K, Turroni S, Wolters M, Veidebaum T, Kourides Y, et al. Pre-obese children's dysbiotic gut microbiome and unhealthy diets may predict the development of obesity. Commun Biol. ;

    PubMedPubMed CentralArticle Google Scholar

  10. John GK, Mullin GE. The gut microbiome and obesity. Curr Oncol Rep. ;18(7)

    PubMedArticleCASPubMed Central Google Scholar

  11. Tun MH, Tun HM, Mahoney JJ, Konya TB, Guttman DS, Becker AB, et al. Postnatal exposure to household disinfectants, infant gut microbiota and subsequent risk of overweight in children. CMAJ. ;(37):E–E

    PubMedPubMed CentralArticle Google Scholar

  12. Sun L, Ma L, Ma Y, Zhang F, Zhao C, Nie Y. Insights into the role of gut microbiota in obesity: pathogenesis, mechanisms, and therapeutic perspectives. Protein Cell. ;9(5)–

    PubMedPubMed CentralArticle Google Scholar

  13. Tremaroli V, Kovatcheva-Datchary P, Bäckhed F. A role for the gut microbiota in energy harvesting? Gut. ;59(12)–

    PubMedArticlePubMed Central Google Scholar

  14. Zheng D, Liwinski T, Elinav E. Interaction between microbiota and immunity in health and disease. Cell Res. ;30(6)–

    PubMedPubMed CentralArticle Google Scholar

  15. Psichas A, Sleeth ML, Murphy KG, Brooks L, Bewick GA, Hanyaloglu AC, et al. The short chain fatty acid propionate stimulates GLP-1 and PYY secretion via free fatty acid receptor 2 in rodents. Int J Obes. ;39(3)–9.

    CASArticle Google Scholar

  16. De Vadder F, Kovatcheva-Datchary P, Goncalves D, Vinera J, Zitoun C, Duchampt A, et al. Microbiota-generated metabolites promote metabolic benefits via gut-brain neural circuits. Cell. ;(1–2)–

    PubMedArticleCASPubMed Central Google Scholar

  17. Allin KH, Tremaroli V, Caesar R, Jensen BAH, Damgaard MTF, Bahl MI, et al. Aberrant intestinal microbiota in individuals with prediabetes. Diabetologia. ;61(4)–

    PubMedPubMed CentralArticle Google Scholar

  18. Dao MC, Everard A, Aron-Wisnewsky J, Sokolovska N, Prifti E, Verger EO, et al. Akkermansia muciniphila and improved metabolic health during a dietary intervention in obesity: relationship with gut microbiome richness and ecology. Gut. ;65(3)–

    CASArticle Google Scholar

  19. Everard A, Belzer C, Geurts L, Ouwerkerk JP, Druart C, Bindels LB, et al. Cross-talk between Akkermansia muciniphila and intestinal epithelium controls diet-induced obesity. Proc Natl Acad Sci U S A. ;(22)–

    CASPubMed

Sours: https://trialsjournal.biomedcentral.com/articles//s
  1. Avengers cake pop ideas
  2. Portions master plate
  3. Destiny best class 2015
  4. Sullivan mo weather
  5. The raven mower

Prebiotics and Metformin Improve Gut and Hormones in Type 2 Diabetes in Youth (MIGHTY-fiber)

Detailed Description:

Metformin is the most widely prescribed anti-diabetes medication in the world and the first-line therapy for treating type 2 diabetes (T2D) in youth and adults. However, metformin s glucose-lowering ability is variable in clinical practice, and efficacy is further limited by poor medication adherence because of metformin-associated adverse effects. Gastrointestinal (GI) symptoms such as bloating, abdominal discomfort, cramping, and diarrhea are the most common side effects associated with metformin use occurring in up to 80% of individuals at drug initiation and up to 30% in individuals on chronic treatment. In youth with type 2 diabetes, the burden of metformin-associated side effects is high because metformin is the only oral FDA-approved for treatment and there are no other oral alternatives. Therefore, identifying ways to mitigate these GI side effects, especially in youth with type 2 diabetes, is of high clinical significance. New data suggest that metformin-induced changes in the gut and/ or the microbiome may be related to both its beneficial (glucose-lowering) and adverse effects. To address this clinical challenge, prebiotic fibers that are non-digestible food ingredients, may help to improve metformin tolerability by increasing beneficial bacteria and stool metabolites, such as short chain fatty acid (SCFA) stool concentrations. This pilot study will test the hypothesis that a prebiotic microbiome modulator (MM) - containing prebiotic fibers and polyphenols - will reduce GI side effects of metformin at time of initiation and change the stool metabolite profile in youth and young adults with T2D treated with metformin, age years who are not on insulin therapy. The 9-week study will have 2 phases and 6 outpatient visits at the NIH Clinical Center. Phase 1 is a 5-week randomized double blind cross-over trial with two 1-week intervention periods (metformin + prebiotic and metformin + placebo) during which subjects will eat a standardized diet. Phase 2 will occur immediately following phase 1 in which participants will start an open-label 4-week intervention with metformin and the prebiotic MM.

Sours: https://clinicaltrials.gov/ct2/show/NCT
How Do Drugs Work: Insulin and metformin

Additional Effect of Dietary Fiber in Patients with Type 2 Diabetes Mellitus Using Metformin and Sulfonylurea: An Open-Label, Pilot Trial

1. American Diabetes Association. Standards of medical care in diabetes: Diabetes Care. ;41(Suppl 1):S1–S [PubMed] [Google Scholar]

2. Abutair AS, Naser IA, Hamed AT. Soluble fibers from psyllium improve glycemic response and body weight among diabetes type 2 patients (randomized control trial) Nutr J. ;[PMC free article] [PubMed] [Google Scholar]

3. Bajorek SA, Morello CM. Effects of dietary fiber and low glycemic index diet on glucose control in subjects with type 2 diabetes mellitus. Ann Pharmacother. ;– [PubMed] [Google Scholar]

4. Gibb RD, McRorie JW, Jr, Russell DA, Hasselblad V, D'Alessio DA. Psyllium fiber improves glycemic control proportional to loss of glycemic control: a meta-analysis of data in euglycemic subjects, patients at risk of type 2 diabetes mellitus, and patients being treated for type 2 diabetes mellitus. Am J Clin Nutr. ;– [PubMed] [Google Scholar]

5. Hall M, Flinkman T. Do fiber and psyllium fiber improve diabetic metabolism? Consult Pharm. ;– [PubMed] [Google Scholar]

6. Pastors JG, Blaisdell PW, Balm TK, Asplin CM, Pohl SL. Psyllium fiber reduces rise in postprandial glucose and insulin concentrations in patients with non-insulin-dependent diabetes. Am J Clin Nutr. ;– [PubMed] [Google Scholar]

7. Weickert MO, Mohlig M, Koebnick C, Holst JJ, Namsolleck P, Ristow M, Osterhoff M, Rochlitz H, Rudovich N, Spranger J, Pfeiffer AF. Impact of cereal fibre on glucose-regulating factors. Diabetologia. ;– [PubMed] [Google Scholar]

8. Slavin JL. Position of the American Dietetic Association: health implications of dietary fiber. J Am Diet Assoc. ;– [PubMed] [Google Scholar]

9. Pluznick J. A novel SCFA receptor, the microbiota, and blood pressure regulation. Gut Microbes. ;–[PMC free article] [PubMed] [Google Scholar]

Esteve E, Ricart W, Fernandez-Real JM. Gut microbiota interactions with obesity, insulin resistance and type 2 diabetes: did gut microbiote co-evolve with insulin resistance? Curr Opin Clin Nutr Metab Care. ;– [PubMed] [Google Scholar]

Han JL, Lin HL. Intestinal microbiota and type 2 diabetes: from mechanism insights to therapeutic perspective. World J Gastroenterol. ;–[PMC free article] [PubMed] [Google Scholar]

Hur KY, Lee MS. Gut microbiota and metabolic disorders. Diabetes Metab J. ;–[PMC free article] [PubMed] [Google Scholar]

Kasubuchi M, Hasegawa S, Hiramatsu T, Ichimura A, Kimura I. Dietary gut microbial metabolites, short-chain fatty acids, and host metabolic regulation. Nutrients. ;–[PMC free article] [PubMed] [Google Scholar]

Forslund K, Hildebrand F, Nielsen T, Falony G, Le Chatelier E, Sunagawa S, Prifti E, Vieira-Silva S, Gudmundsdottir V, Pedersen HK, Arumugam M, Kristiansen K, Voigt AY, Vestergaard H, Hercog R, Costea PI, Kultima JR, Li J, Jorgensen T, Levenez F, Dore J, MetaHIT consortium. Nielsen HB, Brunak S, Raes J, Hansen T, Wang J, Ehrlich SD, Bork P, Pedersen O. Disentangling type 2 diabetes and metformin treatment signatures in the human gut microbiota. Nature. ;–[PMC free article] [PubMed] [Google Scholar]

Lee H, Ko G. Effect of metformin on metabolic improvement and gut microbiota. Appl Environ Microbiol. ;–[PMC free article] [PubMed] [Google Scholar]

Mardinoglu A, Boren J, Smith U. Confounding effects of metformin on the human gut microbiome in type 2 diabetes. Cell Metab. ;– [PubMed] [Google Scholar]

Napolitano A, Miller S, Nicholls AW, Baker D, Van Horn S, Thomas E, Rajpal D, Spivak A, Brown JR, Nunez DJ. Novel gut-based pharmacology of metformin in patients with type 2 diabetes mellitus. PLoS One. ;9:e [PMC free article] [PubMed] [Google Scholar]

Wu H, Esteve E, Tremaroli V, Khan MT, Caesar R, Manneras-Holm L, Stahlman M, Olsson LM, Serino M, Planas-Felix M, Xifra G, Mercader JM, Torrents D, Burcelin R, Ricart W, Perkins R, Fernandez-Real JM, Backhed F. Metformin alters the gut microbiome of individuals with treatment-naive type 2 diabetes, contributing to the therapeutic effects of the drug. Nat Med. ;– [PubMed] [Google Scholar]

Huo T, Xiong Z, Lu X, Cai S. Metabonomic study of biochemical changes in urinary of type 2 diabetes mellitus patients after the treatment of sulfonylurea antidiabetic drugs based on ultra-performance liquid chromatography/mass spectrometry. Biomed Chromatogr. ;– [PubMed] [Google Scholar]

Montandon SA, Jornayvaz FR. Effects of antidiabetic drugs on gut microbiota composition. Genes (Basel) ;8[PMC free article] [PubMed] [Google Scholar]

Korean Diabetes Association. Diabetes Fact Sheet in Korea Seoul: Korean Diabetes Association; [PMC free article] [PubMed] [Google Scholar]

Matsuda M, DeFronzo RA. Insulin sensitivity indices obtained from oral glucose tolerance testing: comparison with the euglycemic insulin clamp. Diabetes Care. ;– [PubMed] [Google Scholar]

Levy JC, Matthews DR, Hermans MP. Correct homeostasis model assessment (HOMA) evaluation uses the computer program. Diabetes Care. ;– [PubMed] [Google Scholar]

Katz A, Nambi SS, Mather K, Baron AD, Follmann DA, Sullivan G, Quon MJ. Quantitative insulin sensitivity check index: a simple, accurate method for assessing insulin sensitivity in humans. J Clin Endocrinol Metab. ;– [PubMed] [Google Scholar]

Hur M, Kim Y, Song HR, Kim JM, Choi YI, Yi H. Effect of genetically modified poplars on soil microbial communities during the phytoremediation of waste mine tailings. Appl Environ Microbiol. ;–[PMC free article] [PubMed] [Google Scholar]

Edgar RC, Haas BJ, Clemente JC, Quince C, Knight R. UCHIME improves sensitivity and speed of chimera detection. Bioinformatics. ;–[PMC free article] [PubMed] [Google Scholar]

Kim OS, Cho YJ, Lee K, Yoon SH, Kim M, Na H, Park SC, Jeon YS, Lee JH, Yi H, Won S, Chun J. Introducing EzTaxon-e: a prokaryotic 16S rRNA gene sequence database with phylotypes that represent uncultured species. Int J Syst Evol Microbiol. ;62(Pt 3)– [PubMed] [Google Scholar]

Segata N, Izard J, Waldron L, Gevers D, Miropolsky L, Garrett WS, Huttenhower C. Metagenomic biomarker discovery and explanation. Genome Biol. ;R [PMC free article] [PubMed] [Google Scholar]

Puddu A, Sanguineti R, Montecucco F, Viviani GL. Evidence for the gut microbiota short-chain fatty acids as key pathophysiological molecules improving diabetes. Mediators Inflamm. ;[PMC free article] [PubMed] [Google Scholar]

Woting A, Blaut M. The intestinal microbiota in metabolic disease. Nutrients. ;[PMC free article] [PubMed] [Google Scholar]

Brown AJ, Goldsworthy SM, Barnes AA, Eilert MM, Tcheang L, Daniels D, Muir AI, Wigglesworth MJ, Kinghorn I, Fraser NJ, Pike NB, Strum JC, Steplewski KM, Murdock PR, Holder JC, Marshall FH, Szekeres PG, Wilson S, Ignar DM, Foord SM, Wise A, Dowell SJ. The orphan G protein-coupled receptors GPR41 and GPR43 are activated by propionate and other short chain carboxylic acids. J Biol Chem. ;– [PubMed] [Google Scholar]

Mattace Raso G, Simeoli R, Russo R, Iacono A, Santoro A, Paciello O, Ferrante MC, Canani RB, Calignano A, Meli R. Effects of sodium butyrate and its synthetic amide derivative on liver inflammation and glucose tolerance in an animal model of steatosis induced by high fat diet. PLoS One. ;8:e [PMC free article] [PubMed] [Google Scholar]

Roelofsen H, Priebe MG, Vonk RJ. The interaction of short-chain fatty acids with adipose tissue: relevance for prevention of type 2 diabetes. Benef Microbes. ;– [PubMed] [Google Scholar]

Romeo GR, Lee J, Shoelson SE. Metabolic syndrome, insulin resistance, and roles of inflammation: mechanisms and therapeutic targets. Arterioscler Thromb Vasc Biol. ;–[PMC free article] [PubMed] [Google Scholar]

Qin J, Li Y, Cai Z, Li S, Zhu J, Zhang F, Liang S, Zhang W, Guan Y, Shen D, Peng Y, Zhang D, Jie Z, Wu W, Qin Y, Xue W, Li J, Han L, Lu D, Wu P, Dai Y, Sun X, Li Z, Tang A, Zhong S, Li X, Chen W, Xu R, Wang M, Feng Q, Gong M, Yu J, Zhang Y, Zhang M, Hansen T, Sanchez G, Raes J, Falony G, Okuda S, Almeida M, LeChatelier E, Renault P, Pons N, Batto JM, Zhang Z, Chen H, Yang R, Zheng W, Li S, Yang H, Wang J, Ehrlich SD, Nielsen R, Pedersen O, Kristiansen K, Wang J. A metagenome-wide association study of gut microbiota in type 2 diabetes. Nature. ;– [PubMed] [Google Scholar]

Vrieze A, Van Nood E, Holleman F, Salojarvi J, Kootte RS, Bartelsman JF, Dallinga-Thie GM, Ackermans MT, Serlie MJ, Oozeer R, Derrien M, Druesne A, Van Hylckama Vlieg JE, Bloks VW, Groen AK, Heilig HG, Zoetendal EG, Stroes ES, de Vos WM, Hoekstra JB, Nieuwdorp M. Transfer of intestinal microbiota from lean donors increases insulin sensitivity in individuals with metabolic syndrome. Gastroenterology. ;– [PubMed] [Google Scholar]

Neyrinck AM, Possemiers S, Verstraete W, De Backer F, Cani PD, Delzenne NM. Dietary modulation of clostridial cluster XIVa gut bacteria (Roseburia spp.) by chitin-glucan fiber improves host metabolic alterations induced by high-fat diet in mice. J Nutr Biochem. ;– [PubMed] [Google Scholar]

Kovatcheva-Datchary P, Nilsson A, Akrami R, Lee YS, De Vadder F, Arora T, Hallen A, Martens E, Bjorck I, Backhed F. Dietary fiber-induced improvement in glucose metabolism is associated with increased abundance of prevotella. Cell Metab. ;– [PubMed] [Google Scholar]

Post RE, Mainous AG, 3rd, King DE, Simpson KN. Dietary fiber for the treatment of type 2 diabetes mellitus: a meta-analysis. J Am Board Fam Med. ;– [PubMed] [Google Scholar]

Sours: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC/

And metformin fiber

Foods to Eat While Taking Metformin

Make sure that you watch how many carbs you eat.

Image Credit: fcafotodigital/E+/GettyImages

While medications like metformin can help you gain control over your blood sugar, it doesn't give you the freedom to eat whatever you want. While there's no metformin diet, you should be following the diet recommended to you by your doctor or dietitian to manage your blood sugar.

What Is Metformin?

Metformin is a medication prescribed as a treatment for Type 2 diabetes, prediabetes and insulin resistance. Of the more than 30 million people with diabetes, 90 to 95 percent of them have Type 2 diabetes, reports the Centers for Disease Control and Prevention.

This type of diabetes most often affects adults over age 45 and occurs when your cells no longer respond to insulin, which is a hormone that helps get glucose from your blood into your cells to supply energy. Over time, the excess glucose in your blood damages your blood vessels and organs, placing you at risk for other health issues, such as heart disease, kidney disease and neuropathy.

Metformin falls into a class of drugs referred to as biguanides, which are medications that prevent your liver from producing glucose. According to MedlinePlus, metformin also decreases the amount of glucose your body absorbs from the food you eat and improves your body's response to insulin.

While it may seem that metformin can help you gain control over your blood sugar in multiple ways, it's not a miracle drug or cure for your diabetes. In order to get the best outcomes from the medication, it should be used in addition to the healthy diet and exercise program designed by your doctor or dietitian.

Is There a Metformin Diet?

As mentioned previously, there's not really a specific diet for people taking metformin. But when it comes to managing diabetes, your diet plays as much of a role as your medication, if not more so.

During digestion and metabolism, certain types of food, namely carbohydrate-containing foods, get broken down into glucose, which your body then uses to supply your cells with energy. If you have more glucose than your cells need, your body stores it in your liver or muscles for later use or turns it into fat.

  • Breads, starches, grains and cereals
  • Fruit and fruit juice
  • Milk and yogurt
  • Starchy vegetables such as potatoes, peas and corn
  • Beans, peas and lentils

You don't need to omit carbohydrates from your diet if you have diabetes, but you do need to control the amount you eat at each meal. There are several different methods used to help control carbohydrate intake and blood sugar level. The best one for you depends on many factors and should be determined by you, your doctor and your dietitian.

Ways to Control Your Carbs

A breakdown of some of the methods you can use to control your carb intake to manage your diabetes includes:

&#;Carbohydrate Counting:&#; Also referred to as carb counting, it's a type of meal plan where you're given a set amount of carbohydrates to eat at each meal and snack, either in grams or portions. For example, you may be allowed 45 grams (three carbohydrate servings) at each meal and 15 grams (one carbohydrate serving) at your snack. This style of eating gives you more flexibility with choices, while still helping you control your blood sugar.

With carbohydrate counting, you round out your meals with carb-free or low-carb foods, such as lean proteins, healthy fats and nonstarchy vegetables.

&#;Low-Glycemic Diet:&#; The low-glycemic diet takes into consideration how certain types of carbohydrates affect blood sugar. Foods like white bread, which is a high-glycemic food, may cause a rapid rise in blood sugar, while whole-grain bread would only cause a small, but steady rise in blood sugar.

Keeping blood sugar levels even by including more low-glycemic foods may help prevent quick increases in blood sugar and excessive release of insulin, which may mean better control over your diabetes.

&#;Choose Your Foods:&#; If you need a little more structure for meal planning, then you may benefit from the "choose your foods" method. This method provides specifics on the amount of carbohydrates, protein and fat you can eat each day and at each meal. This not only helps with blood sugar control, but may be beneficial for weight loss by helping you control portions and calories.

&#;Create Your Plate:&#; For many, being diagnosed with diabetes can cause a range of feelings, which may make following a complicated diet that requires counting, label reading and research difficult. To keep things simple, the American Diabetes Association has created a diet plan they refer to as Create Your Plate.

With this method, you divide your plate into sections, filling half your plate with nonstarchy vegetables, one-quarter with healthy carbohydrates and one-quarter with a lean protein. Then, you may round out your meal with a serving of dairy and fruit.

Any of these methods include good food to eat while taking metformin.

Like many prescription medications, metformin may cause side effects you find uncomfortable. According to a December review published in &#;Diabetes, Obesity & Metabolis&#;m, the most common complaints affect the digestive system and include diarrhea, nausea, vomiting, abdominal pain and gas, with nausea and diarrhea topping the list.

According to the authors of the review in &#;Diabetes, Obesity & Metabolism&#;, it's not fully understood why metformin causes gastrointestinal distress. Given that the medication affects your body's ability to absorb glucose, it's been theorized that you may experience metformin diarrhea after carbs are consumed. However, according to Mayo Clinic, the gastrointestinal side effects are most often experienced when people take their medication without food.

If you're experiencing gastrointestinal issues, you should take your medication with food as directed. The authors of the review also suggested you may find it easier to tolerate a lower dose or the extended-release version of the medication.

Metformin, PCOS and Weight Loss

Polycystic ovary syndrome (PCOS) is a hormonal condition that affects women during their childbearing years. PCOS affects ovulation and may cause an increase in the production of androgens, which are male hormones (also found in women) responsible for facial hair growth and male-pattern baldness.

In addition to putting you at risk for developing infertility, depression and Type 2 diabetes, PCOS also increases your risk of obesity. Lifestyle changes that include a healthy diet and exercise program to lose weight are often recommended as a method of treatment for women with PCOS.

Metformin is sometimes prescribed to women with PCOS who are struggling with infertility to help improve ovulation and their chances of conception. It was also once theorized that metformin may have an added benefit of helping women with PCOS lose weight. However, according to a June review published in &#;Endocrinology and Metabolism&#;, there's no evidence to support the theory that metformin can help you lose weight if you have PCOS.

Grapefruit and Metformin

Grapefruit is a considered a healthy fruit. It's low in calories and rich in fiber and vitamin C. However, if you're taking any prescription medication, you may want to talk to your doctor or pharmacist to see if it's safe to take your medication with grapefruit or grapefruit juice.

According to the Food and Drug Administration, grapefruit and its juice affects drug metabolism by blocking an enzyme in your liver — CYP3A4 — that helps break down various medications. As a result, more of the medication enters your bloodstream than is needed, which can lead to health consequences.

While there are many medications that interact with grapefruit, metformin isn't one of them. If you have concerns, talk to your doctor or pharmacist.

Sours: https://www.livestrong.com/article/foods-eat-taking-metformin/
How Does Metformin Work? (Pharmacology for Nurses)

Fiber and Metformin Combination Therapy in Adolescents With Severe Obesity and Insulin Resistance

This is a month, single center, three-arm parallel design, double-blind, randomized clinical trial, to compare the effects of supplemental dietary fiber and metformin (MET) alone and in combination over 12 months on glucose metabolism (insulin resistance [IR]), inflammation and BMI in adolescents with obesity and IR, and to assess the relationship between therapeutic intervention(s) and changes in gut microbiome composition and function.

Since MET and FIBER have been shown to reduce weight and increase insulin sensitivity through distinct but overlapping mechanisms of action, our central hypothesis is that the combination of FIBER + MET will have a synergistic effect and be more effective than FIBER or MET alone in improving metabolic function (IR) and reducing BMI and inflammation in adolescents with obesity, IR and family history (FM) of T2DM.

.


Obesity, ChildhoodInsulin ResistanceDrug: Metformin mg oral tablet bidDietary Supplement: Supplemental fiber mixture (35 g total) composed of 6g of Oligofructose + 12g of resistant maltodextrin + 12g of acacia gum + 5g of PGX.Phase 3

Sours: https://clinicaltrials.gov/ct2/show/NCT

Now discussing:

Can I Have Grapefruit While Taking Metformin?

Recall of metformin extended release

In May , the recommended that some makers of metformin extended release remove some of their tablets from the U.S. market. This is because an unacceptable level of a probable carcinogen (cancer-causing agent) was found in some extended-release metformin tablets. If you currently take this drug, call your healthcare provider. They will advise whether you should continue to take your medication or if you need a new prescription.

Many medications, such as statins and some antihistamines, have a negative interaction with grapefruit. Metformin is used in treatment of type 2 diabetes.

Does having grapefruit while taking metformin lead to adverse side effects? There’s limited research, but here’s what you need to know.

What is metformin?

Metformin is a drug that’s prescribed to treat type 2 diabetes. People with type 2 diabetes can’t use insulin normally. This means they can’t control the amount of sugar in their blood. Metformin helps people with type 2 diabetes control the level of sugar in their blood in several ways, including:

  • decreasing the amount of sugar your body absorbs from food
  • decreasing the amount of sugar produced by your liver
  • increasing your body’s response to the insulin that it makes naturally

Metformin can rarely cause a very serious and life-threatening condition called lactic acidosis. People with liver, kidney, or heart problems should avoid taking metformin.

How drug interactions with grapefruit work

There are more than that are known to interact with grapefruit. Of these drugs, can lead to serious adverse effects. All forms of grapefruit — including freshly squeezed juice, frozen concentrate, and the whole fruit — can lead to drug interaction.

Some of the chemicals found in grapefruit can bind to and inactivate an enzyme in your body that’s found in your intestines and liver. This enzyme helps break down the medication you take.

Normally when you take a drug orally, it’s broken down slightly by enzymes before it reaches your bloodstream. This means that you receive a little less of the drug in your bloodstream than the amount you initially consumed.

But when the enzyme is inhibited — as it is when it interacts with the chemicals in grapefruit — there’s a dramatically larger amount of the drug that makes its way into your bloodstream. This leads to a higher risk of overdose. Take a more in-depth look at grapefruit-drug interactions.

What drugs interact with grapefruit?

According to the , the following types of drugs can have a negative interaction with grapefruit:

Grapefruit juice doesn’t have an effect on every drug in the categories above. Interaction with grapefruit juice is drug-specific, not drug category-specific.

When starting on a new medication, it’s very important that you ask your doctor or pharmacist if you’re able to consume grapefruit or grapefruit-related products.

How does grapefruit affect metformin?

It’s important to know that metformin isn’t broken down by the same enzyme as the drugs listed above. It’s unprocessed by your body and expelled in your urine.

There’s limited information available as to how having grapefruit while taking metformin affects people with type 2 diabetes.

A discussed the effects of grapefruit with metformin in nondiabetic rats. Some rats were exposed to grapefruit juice and metformin. Others were exposed to metformin alone. Researchers found that there was an increase in the amount of lactic acid production in the rats that were exposed to grapefruit juice and metformin.

Researchers guessed that grapefruit juice enhanced metformin accumulation in the liver. This, in turn, caused the increase in lactic acid production. Because of this, the researchers suggested that drinking grapefruit juice may lead to an increased risk of lactic acidosis in people taking metformin.

However, these results were observed in nondiabetic rats, not in humans with type 2 diabetes. To date, there hasn’t been a case study in humans that indicates that taking metformin with grapefruit juice leads to lactic acidosis.

Other things to avoid while on metformin

Taking some medications while taking metformin can increase the risk of developing lactic acidosis. You should let your doctor know if you’re taking any of the following medications:

  • diuretics, such as acetazolamide
  • corticosteroids, such as prednisone
  • blood pressure medication, such as amlodipine (Norvasc)
  • anticonvulsants, such as topiramate (Topamax) and zonisamide (Zonegran)
  • oral contraceptives
  • antipsychotic drugs, such as chlorpromazine

Avoid consuming large amounts of alcohol while on metformin. Drinking alcohol while taking metformin increases your risk of developing low blood sugar or even lactic acidosis.

According to the University of Michigan, you should avoid eating high-fiber foods after taking metformin. This is because fiber can bind to drugs and lower their concentration. Metformin levels decrease when taken with large amounts of fiber (greater than 30 grams per day).

Some general diet guidelines for people with diabetes are as follows:

  • Include carbohydrates that come from vegetables, fruits, and whole grains. Be sure to monitor your carbohydrate intake, as this will directly affect your blood sugar.
  • Avoid food that’s high in saturated and trans fats. Instead, consume fats from fish, nuts, and olive oil. Here are 10 ways to add healthy fats to your diet.
  • Eating 25 to 30 grams of fiber per day may help control blood glucose levels. See this list of 22 high-fiber foods to get started.
  • Avoid sodium. Try to consume less than 2, milligrams per day.

How grapefruit can help people with diabetes

Drinking grapefruit juice may actually be beneficial if you have diabetes.

An showed that drinking preparations of clarified grapefruit juice reduced both fasting glucose and weight gain. The effects observed were similar to the effects of metformin. There was no enhanced effect when grapefruit juice and metformin were tested together.

While promising, it’s important to note that these observations were made in a mouse model of diabetes.

A of the role of grapefruit in diet and drug interaction also suggests grapefruit is associated with weight loss and improved insulin resistance. What’s more, the review also reports a compound in grapefruit juice (naringin) has been found to improve hyperglycemia and high cholesterol in a type 2 diabetes animal model. Learn more about living with diabetes and high cholesterol.

Takeaway

Grapefruit does lead to negative interactions with some medications. However, there are no case studies in which consuming grapefruit juice while taking metformin led to adverse effects in humans.

There’s some promising experimental evidence that including grapefruit in your diet can help promote weight loss and reduce fasting glucose levels.

If you’re taking metformin and are concerned about drug-drug interactions or food-drug interactions, talk to your healthcare provider.

Sours: https://www.healthline.com/health/grapefruit-and-metformin


355 356 357 358 359