Dataset Information

The Muscle Carnosine Response to Beta-Alanine Supplementation: A Systematic Review With Bayesian Individual and Aggregate Data E-Max Model and Meta-Analysis.

ABSTRACT: Beta-alanine (BA) supplementation increases muscle carnosine content (MCarn), and has many proven, and purported, ergogenic, and therapeutic benefits. Currently, many questions on the nature of the MCarn response to supplementation are open, and the response to these has considerable potential to enhance the efficacy and application of this supplementation strategy. To address these questions, we conducted a systematic review with Bayesian-based meta-analysis of all published aggregate data using a dose response (Emax) model. Meta-regression was used to consider the influence of potential moderators (including dose, sex, age, baseline MCarn, and analysis method used) on the primary outcome. The protocol was designed according to PRISMA guidelines and a three-step screening strategy was undertaken to identify studies that measured the MCarn response to BA supplementation. Additionally, we conducted an original analysis of all available individual data on the MCarn response to BA supplementation from studies conducted within our lab (n = 99). The Emax model indicated that human skeletal muscle has large capacity for non-linear MCarn accumulation, and that commonly used BA supplementation protocols may not come close to saturating muscle carnosine content. Neither baseline values, nor sex, appeared to influence subsequent response to supplementation. Analysis of individual data indicated that MCarn is relatively stable in the absence of intervention, and effectually all participants respond to BA supplementation (99.3% response [95%CrI: 96.2-100]).

SUBMITTER: Rezende NS

PROVIDER: S-EPMC7456894 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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The Muscle Carnosine Response to Beta-Alanine Supplementation: A Systematic Review With Bayesian Individual and Aggregate Data E-Max Model and Meta-Analysis.

Rezende Nathália Saffioti NS Swinton Paul P de Oliveira Luana Farias LF da Silva Rafael Pires RP da Eira Silva Vinicius V Nemezio Kleiner K Yamaguchi Guilherme G Artioli Guilherme Giannini GG Gualano Bruno B Saunders Bryan B Dolan Eimear E

Frontiers in physiology 20200814

Beta-alanine (BA) supplementation increases muscle carnosine content (MCarn), and has many proven, and purported, ergogenic, and therapeutic benefits. Currently, many questions on the nature of the MCarn response to supplementation are open, and the response to these has considerable potential to enhance the efficacy and application of this supplementation strategy. To address these questions, we conducted a systematic review with Bayesian-based meta-analysis of all published aggregate data usin ...[more]

PMID: 32922303

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Project description:There is growing evidence that supplementation with carnosine, or its rate-limiting precursor β-alanine, can ameliorate aspects of metabolic dysregulation that occur in diabetes and its related conditions. The purpose of this systematic review and meta-analysis was to evaluate the effect of carnosine or β-alanine supplementation on markers of glycemic control and insulin resistance in humans and animals. We performed a systematic search of 6 electronic databases up to 31 December 2020. Primary outcomes were changes in 1) fasting glucose, 2) glycated hemoglobin (HbA1c), and 3) 2-h glucose following a glucose-tolerance test. A set of additional outcomes included fasting insulin and homeostatic model assessment of β-cell function (HOMA-β) and insulin resistance (HOMA-IR). We assessed risk of bias using the Cochrane risk of bias (RoB) 2.0 (human studies) and the Systematic Review Center for Laboratory Animal Experimentation (SYRCLE) RoB (animal studies) tools; and used the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) approach to assess certainty. We used Bayesian hierarchical random-effects models, with informative priors for human data and noninformative priors for animal data. Inferences were made on posterior samples generated by Hamiltonian Markov Chain Monte Carlo using 90% credible intervals (90% CrI) and calculated probabilities. Twenty studies (n = 4 human, n = 16 rodent) were included, providing data for 2 primary outcomes (fasting glucose and HbA1c) and 3 additional outcomes (fasting insulin, HOMA-β, and HOMA-IR). The model provides evidence that supplementation decreases fasting glucose [humans: mean difference (MD)0.5 = -0.95 mmol · L-1 (90% CrI: -2.1, 0.08); rodent: MD0.5 = -2.26 mmol · L-1 (90% CrI: -4.03, -0.44)], HbA1c [humans: MD0.5 = -0.91% (90% CrI: -1.46, -0.39); rodents: MD0.5 = -1.05% (90% CrI: -1.64, -0.52)], HOMA-IR [humans: standardized mean difference (SMD)0.5 = -0.41 (90% CrI: -0.82, -0.07); rodents: SMD0.5 = -0.63 (90% CrI: -1.98, 0.65)], and fasting insulin [humans: SMD0.5 = -0.41 (90% CrI: -0.77, -0.07)]. GRADE assessment showed our certainty in the effect estimate of each outcome to be moderate (human outcomes) or very low (rodent outcomes). Supplementation with carnosine or β-alanine may reduce fasting glucose, HbA1c, and HOMA-IR in humans and rodents, and fasting insulin in humans; both compounds show potential as therapeutics to improve glycemic control and insulin resistance. This review was registered at PROSPERO as CRD42020191588.

Project description:BackgroundDiabetes is a major public health issue and there is a need to develop low-cost, novel interventions to prevent or reduce disease progression. Growing evidence shows that supplementation with carnosine, or its rate-limiting precursor β-alanine, can ameliorate aspects of the metabolic dysregulation that occurs in diabetes. There is, however, a need to develop a better understanding of the magnitude of effect and the factors associated with positive outcomes. The purpose of this systematic review and meta-analysis is to evaluate the effect of carnosine or β-alanine supplementation on markers of glycaemic control and insulin resistance in humans and animals.MethodsWe will perform a systematic search for randomised and non-randomised controlled trials. Studies will be retrieved by searching electronic databases, clinical trial registers, author review, and cross-referencing. Primary outcomes include changes in (i) fasting glucose, (ii) glycated haemoglobin, and (iii) 2-h glucose following a glucose tolerance test. A set of additional outcomes includes other markers of glycaemic control and insulin resistance. Risk of bias (RoB) will be assessed using the Cochrane RoB 2.0 tool (human studies) and the Systematic Review Centre for Laboratory Animal Experimentation (SYRCLE) RoB tool (animal studies). Confidence in the cumulative evidence will be assessed using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach. All meta-analyses will be conducted within a Bayesian framework, providing a flexible modelling approach to account for uncertainty in model parameters and underlying structures within the data.DiscussionBy including all available human and animal data, we will provide the most comprehensive overview on the topic to date. The results will have implications for those working in prediabetes, diabetes, and metabolic health in general and may lead to the development of new treatment approaches.DisseminationStudy results will be presented at a professional conference and published in a peer-reviewed journal.Systematic review registrationCRD42020191588.

Project description:BackgroundIncreasingly in network meta-analysis (NMA), there is a need to incorporate non-randomised evidence to estimate relative treatment effects, and in particular in cases with limited randomised evidence, sometimes resulting in disconnected networks of treatments. When combining different sources of data, complex NMA methods are required to address issues associated with participant selection bias, incorporating single-arm trials (SATs), and synthesising a mixture of individual participant data (IPD) and aggregate data (AD). We develop NMA methods which synthesise data from SATs and randomised controlled trials (RCTs), using a mixture of IPD and AD, for a dichotomous outcome.MethodsWe propose methods under both contrast-based (CB) and arm-based (AB) parametrisations, and extend the methods to allow for both within- and across-trial adjustments for covariate effects. To illustrate the methods, we use an applied example investigating the effectiveness of biologic disease-modifying anti-rheumatic drugs for rheumatoid arthritis (RA). We applied the methods to a dataset obtained from a literature review consisting of 14 RCTs and an artificial dataset consisting of IPD from two SATs and AD from 12 RCTs, where the artificial dataset was created by removing the control arms from the only two trials assessing tocilizumab in the original dataset.ResultsWithout adjustment for covariates, the CB method with independent baseline response parameters (CBunadjInd) underestimated the effectiveness of tocilizumab when applied to the artificial dataset compared to the original dataset, albeit with significant overlap in posterior distributions for treatment effect parameters. The CB method with exchangeable baseline response parameters produced effectiveness estimates in agreement with CBunadjInd, when the predicted baseline response estimates were similar to the observed baseline response. After adjustment for RA duration, there was a reduction in across-trial heterogeneity in baseline response but little change in treatment effect estimates.ConclusionsOur findings suggest incorporating SATs in NMA may be useful in some situations where a treatment is disconnected from a network of comparator treatments, due to a lack of comparative evidence, to estimate relative treatment effects. The reliability of effect estimates based on data from SATs may depend on adjustment for covariate effects, although further research is required to understand this in more detail.

Dataset Information

The Muscle Carnosine Response to Beta-Alanine Supplementation: A Systematic Review With Bayesian Individual and Aggregate Data E-Max Model and Meta-Analysis.

Publications

The Muscle Carnosine Response to Beta-Alanine Supplementation: A Systematic Review With Bayesian Individual and Aggregate Data E-Max Model and Meta-Analysis.

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