Meta-Analyses of the Effect of Vegetable Protein for Animal Protein on Cardiometabolic Risk

Background: Vegetarian diets have been associated with a reduced risk of preventable cardiometabolic diseases such as type 2 diabetes and cardiovascular disease. It is unclear whether the replacement of animal protein with vegetable protein has cardiometabolic advantages.

Objectives: To improve evidence-based guidance for dietary guidelines and health claims development, we propose to conduct a series of systematic reviews and meta-analyses of the effects of plant-based protein in replacement for animal protein on cardiometabolic risk factors including: (1) blood lipids, (2) glycemic control, (3) blood pressure, (4) body weight, (5) uric acid, (6) markers of non-alcoholic fatty liver disease (NAFLD), and (7) kidney function and injury.

Design: The planning and conduct of the proposed meta-analyses will follow the Cochrane handbook for systematic reviews of interventions. The reporting will follow the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines.

Data sources: MEDLINE, EMBASE, and The Cochrane Central Register of Controlled Trials will be searched using appropriate search terms.

Study selection: Long term (≥ 3 weeks), randomized, controlled trials that investigate the effect of exchange of plant proteins for animal proteins on the outcomes previously mentioned in humans will be included. Studies that have an acute feeding design, are not randomized, or lack a suitable control will not be included. Both isocaloric and non-isocaloric studies will be included.

Data extraction: Independent investigators (≥2) will extract information about study design, sample size, subject characteristics, pulse form, dose, follow-up, and the composition of the background diets. Mean±SEM values will be extracted for all outcomes. Standard computations and imputations will be used to derive missing variance data. Risk of bias and study quality will be assessed using the Cochrane Risk of Bias Tool and the Heyland Methodological Quality Score (MQS), respectively.

Outcomes: The proposed syntheses will each assess a set of outcomes related to a different area of cardiometabolic risk: (1) blood lipids (established therapeutic targets for the prevention of cardiovascular disease - LDL-C, apo-B, non-HDL-C), (2) glycemic control (glycated blood proteins, fasting glucose and insulin, and Homeostasis model assessment of insulin resistance [HOMA-IR]), (3) body weight, (4) uric acid, (5) blood pressure (systolic BP and diastolic BP), (6) markers of NAFLD (imaging and spectroscopy endpoints of liver fat and biomarkers of hepatocellular injury [transaminases]), and (7) kidney injury and function (creatinine, urea, creatine clearance, estimated glomerular filtration rate [eGFR], albumin-to-creatine ratio [ACR], albuminuria, proteinuria).

Data synthesis: Separate pooled analyses will be conducted for each area of cardiometabolic control using the Generic Inverse Variance method. Random-effects models will be used even in the absence of statistically significant between-study heterogeneity, as they yield more conservative summary effect estimates in the presence of residual heterogeneity. Exceptions will be made for the use of fixed-effects models where there is <5 included trials irrespective of heterogeneity or small trials are being pooled with larger more precise trials in the absence of statistically significant heterogeneity. Paired analyses will be applied to all crossover trials. Heterogeneity will be tested by Cochran's Q statistic and quantified by the I2 statistic. Sources of heterogeneity will be explored by sensitivity and subgroup analyses. A priori subgroup analyses will include study design, dose, vegetable protein type, animal protein comparator, follow-up, baseline values, and study quality. Significant unexplained heterogeneity will be investigated by additional post hoc subgroup analyses (e.g. age, sex, level of feeding control [metabolic, supplemented, dietary advice], washout in crossover trials, energy balance of the background diet, composition of the background diet [total % energy from fat, carbohydrate, protein], change in cholesterol intake, change in glycemic index, etc.). Meta-regression analyses will assess the significance of subgroups analyses. Publication bias will be investigated by the inspection of funnel plots and application of Egger's and Begg's tests.

Knowledge translation plan: Results will be disseminated through traditional means such as interactive presentations at local, national, and international scientific meetings and publication in high impact factor journals. Innovative means such as webcasts with e-mail feedback mechanisms will also be used. Knowledge Users will act as knowledge brokers networking among opinion leaders and different adopter groups to increase awareness at each stage. Four Knowledge Users will also participate directly as members of nutrition guidelines committees. Target adopters will include the clinical practice, public health, industry, research communities, and patient groups. Feedback will be incorporated and used to guide analyses and improve key messages at each stage.

Significance: The proposed project will demonstrate that the improvement in longterm health measures. This demonstration will aid in knowledge translation related to the effects of plant proteins on cardiometabolic risk, kidney disease management, and metabolic syndrome, strengthening the evidence-base for dietary recommendations and health claims and improving health outcomes through informing healthcare providers and patients, stimulating industry innovation, and guiding future research.