Effect of a High-Protein Diet on the Renal Function in Healthy Individuals Without Chronic Kidney Disease: A Meta-Analysis of Randomized Controlled Trials

High-protein (HP) diets have been recommended for weight loss including obese persons. However, the potential effects of HP regimens on kidney health for persons without chronic kidney disease (CKD) are still controversial. Methods To investigate the effects of HP diets versus standard protein/low protein (SP/LP) ones on renal function in individuals without CKD, we conducted this meta-analysis. Thirty-nine RCTs including 3400 participants were considered in this meta-analysis. HP diets resulted in an increased GFR (standardized mean difference [SMD] = 0.64, 95% condence interval [CI]: 0.03, 1.26) and concentrations of serum urea (MD = 1.05, 95% CI: 0.66, 1.44), creatinine (MD = 2.94, 95% CI: 1.30, 4.58), and uric acid (MD = 19.89, 95% CI: 12.35, 27.43) in obese subjects when compared with SP/LP diets. The results in T2D and health participants did not show a notable detrimental effect on renal outcomes. Subgroup analysis showed that an increase in GFR was presented in obese subjects following an intervention shorter than 6 months. No signicant differences were found in the urinary albumin excretion between the HP and SP/LP diets in obese and T2D populations, except for the healthy participants which was reported by only one study. This meta-analysis showed that HP diets were associated with increased GFR, serum urea, creatinine, and uric acid in obese adults. Future studies are warranted to examine whether resulted glomerular hyperltration from HP diet can cause kidney damage in obese individuals. year, study design, duration period, baseline characteristics of the participants (i.e., age, sex, number, BMI, and race), sample size, protein intake between two groups (% of total energy content), and outcomes. If no signicant difference was found between the two groups about the baseline data or the change from baseline values were not available, post-intervention mean values were used. in healthy young adults in a randomized crossover study. Urinary albumin measured in 24-h urine samples Subgroup analyses showed that the effect of HP diets in obese T2D the independent of the


Introduction
Since a growing population can be classi ed as overweight or obese, a low-carbohydrate, high-protein (HP) diet has recently emerged to be popular for weight loss [1]. Even in patients with Type 2 diabetics (T2D), HP diets have been demonstrated to induce reduction in appetite and improvement in outcomes and have been recommended as a medical nutrition therapy in some guidelines [2]. The International Society of Sports Nutrition states that the daily intake of 1.4-2.0g/kg protein for physical activity may improve the adaptability of training to exercise training, and provides new evidence that higher protein intake (>3.0g/kg/d) may promote the loss of fat mass and the building of muscle mass in resistance-trained individuals [3]. Therefore, such diets have recently gained increasing attention. However, the potential effects of HP regimes on the parameters of kidney health for individuals without chronic kidney disease (CKD; glomerular ltration rate [GFR] < 60mL/min) are still controversial.
The recommended daily amount of protein for the general population is 0.83g/kg, which is su cient to avoid negative nitrogen balance and meet 97% − 98% of the population's requirements. Although the consensus de nition of an HP diet remains unclear, most de nitions had set thresholds of 1.2 g/kg to 2.0 g/kg per day [1]. High intake of dietary protein, including animal and plant protein, may accelerate the loss of kidney function for patients with CKD or at risk of CKD (e.g., patients with diabetes or obese patients with microalbuminuria). A body of evidence has suggested that an HP regime leads to an increase in GFR and triggers renal glomerular hyper ltration, which results in renal damage [4]. In animal studies, HP diets have been associated with increased blood ow to the kidneys, a deterioration of renal injury, increased albuminuria, and histopathological changes in the kidneys [5].
Human data have also revealed hyper ltration with HP consumption. The largest short-term (< 6 months) randomized controlled trial (RCT) conducted by Juraschek et al. [6] reported that a diet rich in protein (25% of kilocalories from protein) signi cantly increased the eGFR by 4 mL/min/1.73 m 2 after six weeks in contrast to a lower protein diet (LP, 15% of kilocalories from protein). A community-based prospective study enrolling a total of 9,226 subjects showed that long-term HP consumption increased the risk of renal hyper ltration and reduced the renal function in the general population compared with a stand-protein diet (SP) after a 4-year follow-up [7]. By contrast, several RCTs have reported no detrimental effects of HP diets on renal outcomes, including GFR, albuminuria, or serum laboratory values [8-10].
With the increased interest for HP diets in obese, T2D, and healthy population, as well as given aforementioned controversies, concerns about the renal effects of an HP protocol have been raised. Therefore, this meta-analysis was focused on the comparison of HP diet and SP/low-protein (LP) diet patterns on the renal function parameters in adult individuals.

Search strategy
Literature search was performed using PubMed, Cochrane Central, and Embase database to identify RCTs that evaluated the effects of HP diet on the renal function in individuals without CKD until 29th December 2020. The following search terms were used: ("high protein diet" OR "protein overconsumption" OR "protein overuse" OR "high meat diet") and ("kidney" OR "renal"). Moreover, references from previous reviews and retrieved original articles were scanned to further nd relevant studies. Only English and Chinese languages were imposed in the study selection.

Inclusion and exclusion criteria
Inclusion criteria were as follows: (1) a RCTs or crossover design; (2) intervention period was more than 1 week; (3) study population was ≥ 18 years old; (4) comparison of HP diet and SP / low protein diet on renal function (According to a previous review conducted by Santesso et al. in 2012 [11], the authors considered an increase of 5% difference in the total energy intake to distinguish between HP and SP/LP diets); (5) trial participants were obese, overweight, T2D, and healthy adults; (6) the study assessed one or more outcomes (i.e., GFR, serum urea, serum creatinine, serum uric acid, urinary albumin, and kidney volume) from baseline to the end of the intervention. Participants with CKD (GFR < 60 mL/min/1.73 m 2 ), albuminuria beyond normal range, and type 1 diabetes were excluded.

Study selection and data extraction
Two reviewers (Y Zhu and ZJ Xie) conducted the study selection by screening the title and abstract of all articles independently. The nal recruited literatures were determined by reading the full text of the articles. Inconsistencies were resolved by consensus with a third reviewer. The following information was extracted from each study: the rst author's last name, publication year, study design, duration period, baseline characteristics of the participants (i.e., age, sex, number, BMI, and race), sample size, protein intake between two groups (% of total energy content), and outcomes. If no signi cant difference was found between the two groups about the baseline data or the change from baseline values were not available, post-intervention mean values were used.

Quality assessment
The Cochrane Risk of Bias tool was applied to evaluate the quality of included RCTs. Risk of bias consisted of the following bias domains: random sequence generation, allocation concealment, blinding of participants and personnel, blinding of outcome assessment, incomplete data outcome, selective reporting, and other biases. The studies were assessed as having high, low, or unclear risk for each domain. Two authors independently reviewed and judged the assessment.

Statistical analysis
In this meta-analysis, mean difference (MD) with 95% con dence interval (CI) was analyzed for continuous data. If the unit was different across various studies, standardized mean difference (SMD) with 95% CI was used. When the mean or standard deviation (SD) values were not available, the values were estimated on the basis of other relevant measurements. The heterogeneity was assessed across included studies by I 2 statistics and Cochran's Q-test. The study with an I 2 > 50% or a P < 0.1 in the Cochran's Q-test was considered to have substantial heterogeneity. The results were pooled using a random effect model in the presence of considerable heterogeneity across all studies. Otherwise, a xed effect model was selected. In addition, subgroup analyses (based on the duration of intervention) and sensitivity analysis were performed to explore the substantial causes of heterogeneity.
Publication bias was evaluated using Egger's test, and a funnel plot was constructed for the GFR values. All analyses were conducted using RevMan Manager software (version 5.3), and P < 0.05 was considered to be statistically signi cant.

Study selection
A total of 1398 relevant articles were screened in the initial search. Among these reports, 1359 were excluded and 39 eligible RCTs with 3216 participants were nally included for this meta-analysis [6, 8-10, 12-46]. The PRISMA owchart is shown in Fig. 1.
Twenty-six studies were parallel RCTs, and thirteen had a crossover study design. Among the included studies, participants were either obese, overweight, T2D, or healthy adults. The main characteristics of the participants and the protein diet protocols were summarized in Table 1. The mean age was between 24.1 years and 75.4 years, the median BMI was 33.0 (range: 22.3 to 43.6), and the sample size of the included studies ranged from 6 to 419. The protein content ranged from 20-40% of the total energy intake in the HP diets and from 10-24% in the SP/LP diets. The duration of HP diet intervention was < 6 months in 23 trials, and ≥ 6 months in 16 trials. In addition, protein intakes in two groups were mostly of animal origin, except for one trial, in which vegetable protein (speci cally, wheat gluten protein) was used. Quality assessment and publication bias Figure 2 showed the quality assessment of the included studies. Overall, all of the studies described a random sequence generation. Only 10 trials (25.6%) reported appropriate allocation concealment methods. Double-blind design was conducted in two studies, and whereas single-blind were used in four studies. Since all results in the present study were laboratory parameters, which were less likely to be affected by an open-label design. Thirty-ve trials were considered to have low risk of bias on the domain of incomplete outcome data. The GFR levels were used to assess the publication bias, and according to the result of Egger's test (p = 0.142, t = 1.51), no evidence of publication bias was found in the included studies.

Glomerular ltration rate
Page 9/20 Twenty-seven studies provided the effect of HP diets on the GFR level and were pooled in our analysis (Fig. 3). HP diets were associated with signi cantly increased GFR in comparison to the SP/LP diets in obese subjects (SMD = 0.64, 95% CI 0.03 to 1.26, P = 0.04) with signi cant heterogeneity among studies (I 2 = 93%). In T2D and healthy subjects, HP diets did not show any change in the GFR level compared with SP/LP diets (T2D: SMD = − 0.54, 95% CI = − 1.36 to 0.28; P = 0.20, I 2 = 92%; Healthy: SMD = 0.78; 95% CI = − 0.43 to 1.94; P = 0.21, I 2 = 99%). The results from the subgroup analyses showed that the HP diets increased the GFR in a longterm duration (< 6 months) in obese subjects, but no signi cant difference was observed after a short-term intervention (> 6 months). Detailed results of subgroup analyses were shown in Table 2.

Urinary albumin excretion
Twelve studies with 732 participants reported the effects of HP diets on the urinary albumin excretion (UAE, Fig. 4). No signi cant difference was found in the UAE between HP diets and SP/LP diets in obese participants (SMD = − 0.16, 95% CI = − 0.61 to 0.28; P = 0.47, I 2 = 70%) and T2D (SMD = − 0.03, 95% CI = − 0.38 to 0.31; P = 0.85, I 2 = 57%). Only one study with 48 participants compared HP diets with SP/LP diets in healthy young adults in a randomized crossover study. Urinary albumin measured in 24-h urine samples was signi cantly elevated in the HP diets compared with the SP diets (SMD = 1.35, 95% CI = 0.72 to 1.98; P < 0.0001). Subgroup analyses showed that the effect of HP diets in obese and T2D individuals on the UAE was independent of the duration (Table 2).

Biochemical indicators
The pooled results in the meta-analysis showed that HP diets were associated with a signi cant increase in serum urea (MD = 1.  Figure S1, S2, and S3. But subgroup analyses revealed that long-term HP diet intervention had no effect on the serum urea (Table 2).

Discussion
In this meta-analysis of 39 RCTs, which is an update on this topic, the effects of HP and SP/LP diets on the renal function parameters in general population without CKD were compared. The evidences suggested that HP diets probably led to a signi cantly increased GFR and an increased concentration of serum urea, uric acid, and creatinine in obese subjects. However, the results in T2D patients and healthy participants did not show a notable detrimental effect on the renal outcomes. When the participants were sub grouped according to the duration of intervention, an increase in GRF was only presented in the obese subjects following a long-term intervention. As for albuminuria, no signi cant difference was observed in those individuals after an HP diet, except for healthy participants which was reported by only one study.
Increased protein consumption has been considered as a potential regulator of renal function as a result of increasing renal plasma ow and GFR [1]. In a mouse model, a 4-week HP diet led to a signi cant increase in the GFR by 33.6%, renal blood ow by 38.0%, and kidney weight by 25.7% compared with an LP diet [47]. A randomized study had demonstrated that a high dietary protein intake over six months in overweight subjects induced an increase in GFR by approximately 10%, and similar changes were observed in renal size [31]. In this study, a signi cant difference in GFR was found in obese adults between the HP diet and SP/LP diet groups after a follow-up over six months, but no elevated GRF was detected following a short-term HP intervention. Increased glomerular pressure and hyper ltration occurs as a rise in GFR, which may result in the loss of kidney function over a long term. In addition, a meta-analysis including 17 studies showed that HP diets were associated with increased all-cause mortality [48]. However, some researchers recognize that a rise in GFR may probably be a normal adaptation for kidney due to an elevated urea ltration following an ingestion of HP diets [49].
In healthy individuals, an increase in protein intake up to a maximum of 3.32 g/kg/d over 4 months had no adverse effects on the marks of kidney function [34]. The present study resulted in the same nding in healthy and T2D subjects independent of the intervention duration, which was also consistent with ndings from several RCTs among T2D individuals [8,17]. In a 2-year investigation of 115 adults with T2D, comparison of the HP (28% total energy) diet with LP (17% total energy) diets showed that both diets achieved no adverse renal effects, including estimated GFR or albuminuria [8]. Similarly, a short-term trial by Luger et al.
showed that a 5-week HP diet did not increase creatinine clearance among T2D subjects [17].
UAE is another marker for kidney damage and a predictor of end-stage renal disease in the general population and in individuals with diabetes mellitus [50]. Increased UAE has recently been reported to be associated with increased mortality and morbidity of cardiovascular risk in healthy adults and patients with diabetes [50,51]. Although HP diet has been demonstrated to increase urinary albumin creatinine ratio in animal models [5] and short-term clinical trials [52], this meta-analysis showed that HP diet did not alter UAE in subjects without CKD. Additionally, a clinical intervention study reported no difference between plant and animal protein meals on the urine albumin in T2D subjects without microalbuminuria [53].
Protein-enriched meals can also result in the proportional elevation in urea and the generation of other nitrogenous waste products which due to increased protein metabolism. An experimental study has shown that high serum urea concentration, namely azotemia, is a common indicator for uremia, which may lead to oxidative stress, in ammation, endothelial dysfunction, and cardiovascular disease by increasing protein carbamylation and generating reactive oxygen species [54]. In the present metaanalysis, a rise in serum urea concentration was found in obese and healthy adults following an HP diet. Other nitrogenous waste product, such as creatinine, also increased in T2D and obesity subjects after an HP diet intervention. Of note, no difference was found between two groups when the T2D subjects were divided into subgroups according to the HP intervention duration. Increased serum urea and GFR among subjects without CKD was only an adaptation to a high protein load, because nitrogenous waste products may result in osmotic diuresis, and no indication of kidney damage was found [9].
A recent meta-analysis conducted by Schwingshackl et al. in 2014 [55] showed that HP diets were associated with increased GFR, serum urea, serum uric acid, and urinary calcium excretion in healthy individuals or individuals with T2D and obesity. Moreover, the study enrolled participants with normal and microalbuminuria, and subgroup analysis was not performed. Considering that most of the RCTs included in the previous meta-analysis recruited obese individuals, the authors infer that HP diets will increase the risk of kidney dysfunction for this population and this inference was consistent with this update study.
Several study limitations exist in this meta-analysis. First, the main outcome parameter GFR was evaluated by creatinine-based method. Clearance of endogenous creatinine, a previously widely used method to measure GFR, overestimates GFR by probably 10% because of the reabsorption and secretion of creatinine in renal tubules. In addition, HP intake, body size, and muscle mass are important sources of error in creatinine-based GFR [56], especially in those undergoing remarkable weight loss. Thus, a conservative attitude should be considered toward the GFR results reported in this meta-analysis. A randomized crossover trial by Juraschek et al. showed that the GFR changes during the HP diet measured using a cystatin C-based method differed from that using a creatinine-based method [6]. Second, compliance with HP diet intervention reported poor and higher dropout rates in most long-term trials, and enough protein are di cult to take to maintain the inclusion criteria for participants, especially to those with HP diet intervention. Third, several outcomes presented high heterogeneity even if subgroup analysis based on the intervention duration and participants have been performed. Some reasons for the signi cant heterogeneity may include different study designs (RCTs and crossover studies), study populations (age, sex, and race), and de nition of HP and SP/LP diets. Fortunately, the outcomes were all laboratory test results, that is, the data were quantitative, not qualitative.

Conclusions
Although the renal-related contraindications to an HP diet were not clear in populations without CKD, and the elevation of GFR and serum nitrogenous waste products may be a normal adaptation of the kidney. The potential risk demonstrated in the experimental study should be carefully considered, especially to obese adults. Furthermore, HP diets may accelerate the progression of CKD and should be avoided in the dietary behaviors of these individuals. Based on a clinical trial in apparently healthy young US adults, only half of the participants presented an optimal range of UAE [51]. Considering the latent feature of CKD, all individuals should measure their serum creatinine concentration and urine specimen test for proteinuria before they take a protein-enriched meal.
Consent for publication: Each author meets the criteria for authorship and assumes the corresponding responsibility.
Availability of data and materials: Not applicable.
Competing interests: The authors declared that they had no con ict of interest.  Risk of bias graph Figure 3 Forest plot of GRF level between HP diet and SP/LP diet; Figure 4 Forest plot of urinary albumin excretion between HP diet and SP/LP diet;

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