Serum metabolites associated with dietary protein intake: results from the Modification of Diet in Renal Disease (MDRD) randomized clinical trial

Diet-Induced Proteomic and Metabolomic Signatures in Chronic Kidney Disease: A Precision Nutrition Approach

Background: Diet is a key modifiable factor that can either support renal health or accelerate the onset and progression of chronic kidney disease (CKD). Recent advances in multiomics, particularly proteomics and metabolomics, significantly enhanced our understanding of the molecular mechanisms linking diet to CKD risk. Proteomics offers a comprehensive analysis of protein expression, structure, and interactions, revealing how dietary components regulate cellular processes and signaling pathways. Meanwhile, metabolomics provides a detailed profile of low-molecular-weight compounds, including endogenous metabolites and diet-derived molecules, offering insights into the metabolic states that influence kidney function. Methods: We have conducted a narrative review of key papers from databases such as PubMed, Scopus, and Web of Science to explore the potential of proteomic and metabolomic analysis in identifying molecular signatures associated with diet in human and animal biological samples, such as blood plasma, urine, and in kidney tissues. These signatures help elucidate how specific foods, food groups, and overall dietary patterns may either contribute to or mitigate CKD risk. Results: Recent studies the impact of high-fat diets on protein expression involved in energy metabolism, inflammation, and fibrosis, identifying early biomarkers of kidney injury. Metabolic, including disruptions in in fatty acid metabolism, glucose regulation, and amino acid pathways, have been recognized as key indicators of CKD risk. Additionally, several studies explore specific metabolites found in biological fluids and renal tissue in response to protein-rich foods, assessing their potential roles in a progressive loss of kidney function. Emerging evidence also suggests that dietary interventions targeting the gut microbiota may help alleviate inflammation, oxidative stress, and toxin accumulation in chronic kidney disease. Notably, recent findings highlight metabolomic signatures linked to beneficial shifts in gut microbial metabolism, particularly in the context of prebiotic supplementation. Conclusions: By integrating proteomics and metabolomics, future research can refine precision nutrition strategies, helping mitigate CKD progression. Expanding large-scale studies and clinical trials will be essential in translating these molecular insights into actionable dietary guidelines.

Causality of blood metabolites and metabolic pathways on peripheral arteriosclerosis: a Mendelian randomization study

Background

Peripheral arteriosclerosis is caused by any atherosclerosis outside the heart and brain. However, the underlying biological mechanisms are not fully understood. This study aims to explore the causal relationship between blood metabolites and peripheral arteriosclerosis.

Methods

A Mendelian randomization (MR) analysis was implemented to estimate the causality of blood metabolites on peripheral arteriosclerosis. A genome-wide association study (GWAS) of 1,400 metabolites was used as the exposure, whereas two different GWAS datasets of peripheral arteriosclerosis were the outcomes. Inverse-variance weighted (IVW) was the main analysis of causal analysis. MR-Egger, the simple mode, weighted median and weighted mode were used to increase the stability and robustness of the results. Cochran Q test, MR-Egger intercept test, the funnel plot, and MR-Pleiotropy RESidual Sum and Outlier were used for sensitivity analyses. Furthermore, metabolic pathway enrichment analysis was performed using MetaboAnalyst5.0.

Results

In this MR study, eight blood metabolites have a strong causal relationship with peripheral arteriosclerosis, including 1-myristoyl-2-arachidonoyl-GPC (14:0/20:4), 1-palmitoyl-2-arachidonoyl-gpc (16:0/20:4n6), 1-(1-enyl-stearoyl)-2-arachidonoyl-GPE, 1-palmitoyl-2-dihomo-linolenoyl-GPC, Gamma-glutamylleucine, Deoxycholic acid glucuronide and two named X- (X-24546, X-26111). In addition, five important metabolic pathways in peripheral arteriosclerosis were identified through metabolic pathway analysis.

Conclusion

This study provides evidence for the causal relationship between blood metabolites and peripheral arteriosclerosis, and these eight blood metabolites provide new perspectives for screening and prevention of peripheral arteriosclerosis in the future.

Validity of dietary intake methods in cancer cachexia

PURPOSE OF REVIEW

Accurate assessment of dietary intake, especially energy and protein intake, is crucial for optimizing nutritional care and outcomes in patients with cancer. Validation of dietary assessment methods is necessary to ensure accuracy, but the validity of these methods in patients with cancer, and especially in those with cancer cachexia, is uncertain. Validating nutritional intake is complex because of the variety of dietary methods, lack of a gold standard method, and diverse validation measures. Here, we review the literature on validations of dietary intake methods in patients with cancer, including those with cachexia, and highlight the gap between current validation efforts and the need for accurate dietary assessment methods in this population.

RECENT FINDINGS

We analyzed eight studies involving 1479 patients with cancer to evaluate the accuracy and reliability of 24-hour recalls, food records, and food frequency questionnaires in estimating energy and protein intake. We discuss validation methods, including comparison with biomarkers, indirect calorimetry, and relative validation of dietary intake methods.

SUMMARY

Few have validated dietary intake methods against objective markers in patients with cancer. While food records and 24-hour recalls show potential accuracy for energy and protein intake, this may be compromised in hypermetabolic patients. Additionally, under- and overreporting of intake may be less frequent, and the reliability of urinary nitrogen as a protein intake marker in patients with cachexia needs further investigation. Accurate dietary assessment is important for enhancing nutritional care outcomes in cachexia trials, requiring validation at multiple time points throughout the cancer trajectory.

A longitudinal study of the blood and urine metabolome of Vipera berus envenomated dogs

Envenomation of dogs by the common European adder (Vipera berus) is associated with high morbidity. The cytotoxic venom of Vipera berus contains enzymes with the potential to cause acute kidney injury, among other insults, however robust biomarkers for such effects are lacking. A prospective observational follow-up study of naturally envenomated dogs and controls was conducted to fill knowledge gaps regarding canine Vipera berus envenomation, attempt to identify novel biomarkers of envenomation and related kidney injury, and elucidate potential long-term effects. Blood and urine samples were analyzed with a global metabolomics approach using liquid chromatography-mass spectrometry, uncovering numerous features significantly different between cases and controls. After data processing and feature annotation, eight features in blood and 24 features in urine were investigated in order to elucidate their biological relevance. Several of these are associated with AKI, while some may also originate from disturbed fatty acid β-oxidation and soft tissue damage. A metabolite found in both blood and a venom reference sample may represent identification of a venom component in case dogs. Our findings suggest that envenomated dogs treated according to current best practice are unlikely to suffer permanent injury.

Serum Metabolomic Markers of Protein-Rich Foods and Incident CKD: Results From the Atherosclerosis Risk in Communities Study

Rationale & Objective

While urine excretion of nitrogen estimates the total protein intake, biomarkers of specific dietary protein sources have been sparsely studied. Using untargeted metabolomics, this study aimed to identify serum metabolomic markers of 6 protein-rich foods and to examine whether dietary protein-related metabolites are associated with incident chronic kidney disease (CKD).

Study Design

Prospective cohort study.

Setting & Participants

A total of 3,726 participants from the Atherosclerosis Risk in Communities study without CKD at baseline.

Exposures

Dietary intake of 6 protein-rich foods (fish, nuts, legumes, red and processed meat, eggs, and poultry), serum metabolites.

Outcomes

Incident CKD (estimated glomerular filtration rate < 60 mL/min/1.73 m2 with ≥25% estimated glomerular filtration rate decline relative to visit 1, hospitalization or death related to CKD, or end-stage kidney disease).

Analytical Approach

Multivariable linear regression models estimated cross-sectional associations between protein-rich foods and serum metabolites. C statistics assessed the ability of the metabolites to improve the discrimination of highest versus lower 3 quartiles of intake of protein-rich foods beyond covariates (demographics, clinical factors, health behaviors, and the intake of nonprotein food groups). Cox regression models identified prospective associations between protein-related metabolites and incident CKD.

Results

Thirty significant associations were identified between protein-rich foods and serum metabolites (fish, n = 8; nuts, n = 5; legumes, n = 0; red and processed meat, n = 5; eggs, n = 3; and poultry, n = 9). Metabolites collectively and significantly improved the discrimination of high intake of protein-rich foods compared with covariates alone (difference in C statistics = 0.033, 0.051, 0.003, 0.024, and 0.025 for fish, nuts, red and processed meat, eggs, and poultry-related metabolites, respectively; P < 1.00 × 10-16 for all). Dietary intake of fish was positively associated with 1-docosahexaenoylglycerophosphocholine (22:6n3), which was inversely associated with incident CKD (HR, 0.82; 95% CI, 0.75-0.89; P = 7.81 × 10-6).

Limitations

Residual confounding and sample-storage duration.

Conclusions

We identified candidate biomarkers of fish, nuts, red and processed meat, eggs, and poultry. A fish-related metabolite, 1-docosahexaenoylglycerophosphocholine (22:6n3), was associated with a lower risk of CKD.

Precision Medicine in Diabetic Kidney Disease: A Narrative Review Framed by Lived Experience

Purpose of review

Diabetic kidney disease (DKD) is a leading cause of chronic kidney disease (CKD) for which many treatments exist that have been shown to prevent CKD progression and kidney failure. However, DKD is a complex and heterogeneous etiology of CKD with a spectrum of phenotypes and disease trajectories. In this narrative review, we discuss precision medicine approaches to DKD, including genomics, metabolomics, proteomics, and their potential role in the management of diabetes mellitus and DKD. A patient and caregivers of patients with lived experience with CKD were involved in this review.

Sources of information

Original research articles were identified from MEDLINE and Google Scholar using the search terms "diabetes," "diabetic kidney disease," "diabetic nephropathy," "chronic kidney disease," "kidney failure," "dialysis," "nephrology," "genomics," "metabolomics," and "proteomics."

Methods

A focused review and critical appraisal of existing literature regarding the precision medicine approaches to the diagnosis, prognosis, and treatment of diabetes and DKD framed by a patient partner's/caregiver's lived experience.

Key findings

Distinguishing diabetic nephropathy from CKD due to other types of DKD and non-DKD is challenging and typically requires a kidney biopsy for a diagnosis. Biomarkers have been identified to assist with the prediction of the onset and progression of DKD, but they have yet to be incorporated and evaluated relative to clinical standard of care CKD and kidney failure risk prediction tools. Genomics has identified multiple causal genetic variants for neonatal diabetes mellitus and monogenic diabetes of the young that can be used for diagnostic purposes and to specify antiglycemic therapy. Genome-wide-associated studies have identified genes implicated in DKD pathophysiology in the setting of type 1 and 2 diabetes but their translational benefits are lagging beyond polygenetic risk scores. Metabolomics and proteomics have been shown to improve diagnostic accuracy in DKD, have been used to identify novel pathways involved in DKD pathogenesis, and can be used to improve the prediction of CKD progression and kidney failure as well as predict response to DKD therapy.

Limitations

There are a limited number of large, high-quality prospective observational studies and no randomized controlled trials that support the use of precision medicine based approaches to improve clinical outcomes in adults with or at risk of diabetes and DKD. It is unclear which patients may benefit from the clinical use of genomics, metabolomics and proteomics along the spectrum of DKD trajectory.

Implications

Additional research is needed to evaluate the role of the use of precision medicine for DKD management, including diagnosis, differentiation of diabetic nephropathy from other etiologies of DKD and CKD, short-term and long-term risk prognostication kidney outcomes, and the prediction of response to and safety of disease-modifying therapies.

Metabolomic Profiling of an Ultraprocessed Dietary Pattern in a Domiciled Randomized Controlled Crossover Feeding Trial

BACKGROUND

Objective markers of ultraprocessed foods (UPF) may improve the assessment of UPF intake and provide insight into how UPF influences health.

OBJECTIVES

To identify metabolites that differed between dietary patterns (DPs) high in or void of UPF according to Nova classification.

METHODS

In a randomized, crossover, controlled-feeding trial (clinicaltrials.govNCT03407053), 20 domiciled healthy participants (mean ± standard deviation: age 31 ± 7 y, body mass index [kg/m2] 22 ± 11.6) consumed ad libitum a UPF-DP (80% UPF) and an unprocessed DP (UN-DP; 0% UPF) for 2 wk each. Metabolites were measured using liquid chromatography with tandem mass spectrometry in ethylenediaminetetraacetic acid plasma, collected at week 2 and 24-h, and spot urine, collected at weeks 1 and 2, of each DP. Linear mixed models, adjusted for energy intake, were used to identify metabolites that differed between DPs.

RESULTS

After multiple comparisons correction, 257 out of 993 plasma and 606 out of 1279 24-h urine metabolites differed between UPF-DP and UN-DP. Overall, 21 known and 9 unknown metabolites differed between DPs across all time points and biospecimen types. Six metabolites were higher (4-hydroxy-L-glutamic acid, N-acetylaminooctanoic acid, 2-methoxyhydroquinone sulfate, 4-ethylphenylsulfate, 4-vinylphenol sulfate, and acesulfame) and 14 were lower following the UPF-DP; pimelic acid, was lower in plasma but higher in urine following the UPF-DP.

CONCLUSIONS

Consuming a DP high in, compared with 1 void of, UPF has a measurable impact on the short-term human metabolome. Observed differential metabolites could serve as candidate biomarkers of UPF intake or metabolic response in larger samples with varying UPF-DPs. This trial was registered at clinicaltrials.gov as NCT03407053 and NCT03878108.

Healthful eating patterns, serum metabolite profile and risk of diabetes in a population-based prospective study of US Hispanics/Latinos

AIMS/HYPOTHESIS

We aimed to evaluate associations of multiple recommended dietary patterns (i.e. the alternate Mediterranean diet [aMED], the Healthy Eating Index [HEI]-2015 and the healthful Plant-based Diet Index [hPDI]) with serum metabolite profile, and to examine dietary-pattern-associated metabolites in relation to incident diabetes.

METHODS

We included 2842 adult participants free from diabetes, CVD and cancer during baseline recruitment of the Hispanic Community Health Study/Study of Latinos. Metabolomics profiling of fasting serum was performed using an untargeted approach. Dietary pattern scores were derived using information collected by two 24 h dietary recalls. Dietary-pattern-associated metabolites were identified using multivariable survey linear regressions and their associations with incident diabetes were assessed using multivariable survey Poisson regressions with adjustment for traditional risk factors.

RESULTS

We identified eight metabolites (mannose, γ/β-tocopherol, N1-methylinosine, pyrraline and four amino acids) that were inversely associated with all dietary scores. These metabolites were detrimentally associated with various cardiometabolic risk traits, especially insulin resistance. A score comprised of these metabolites was associated with elevated risk of diabetes (RRper SD 1.54 [95% CI 1.29, 1.83]), and this detrimental association appeared to be attenuated or eliminated by having a higher score for aMED (pinteraction = 0.0001), HEI-2015 (pinteraction = 0.020) or hPDI (pinteraction = 0.023). For example, RR (95% CI) of diabetes for each SD increment in the metabolite score was 1.99 (1.44, 2.37), 1.67 (1.17, 2.38) and 1.08 (0.86, 1.34) across the lowest to the highest tertile of aMED score, respectively.

CONCLUSIONS/INTERPRETATION

Various recommended dietary patterns were inversely related to a group of metabolites that were associated with elevated risk of diabetes. Adhering to a healthful eating pattern may attenuate or eliminate the detrimental association between metabolically unhealthy serum metabolites and risk of diabetes.

Metabolomics of Dietary Acid Load and Incident Chronic Kidney Disease

OBJECTIVE

Blood biomarkers of dietary intake are more objective than self-reported dietary intake. Metabolites associated with dietary acid load were previously identified in 2 chronic kidney disease (CKD) populations. We aimed to extend these findings to a general population, replicating their association with dietary acid load, and investigating whether the individual biomarkers were prospectively associated with incident CKD.

METHODS

Among 15,792 participants in the Atherosclerosis Risk in Communities cohort followed up from 1987 to 1989 (baseline) to 2019, we evaluated 3,844 black and white men and women with dietary and metabolomic data in cross-sectional and prospective analyses. We hypothesized that a higher dietary acid load (using equations for potential renal acid load and net endogenous acid production) was associated with lower serum levels of 12 previously identified metabolites: indolepropionylglycine, indolepropionate, N-methylproline, N-δ-acetylornithine, threonate, oxalate, chiro-inositol, methyl glucopyranoside, stachydrine, catechol sulfate, hippurate, and tartronate. In addition, we hypothesized that lower serum levels of these 12 metabolites were associated with higher risk of incident CKD.

RESULTS

Eleven out of 12 metabolites were significantly inversely associated with dietary acid load, after adjusting for demographics, socioeconomic status, health behaviors, health status, and estimated glomerular filtration rate: indolepropionylglycine, indolepropionate, N-methylproline, threonate, oxalate, chiro-inositol, catechol sulfate, hippurate, methyl glucopyranoside (α + β), stachydrine, and tartronate. N-methylproline was inversely associated with incident CKD (hazard ratio: 0.95, 95% confidence interval: 0.91, 0.99, P = .01). The metabolomic biomarkers of dietary acid load significantly improved prediction of elevated dietary acid load estimated using dietary data, beyond covariates (difference in C statistics: 0.021-0.077, P ≤ 1.08 × 10-3).

CONCLUSION

Inverse associations between candidate biomarkers of dietary acid load were replicated in a general population. N-methylproline, representative of citrus fruit consumption, is a promising marker of dietary acid load and could represent an important pathway between dietary acid load and CKD.

Serum and Fecal Amino Acid Profiles in Cats with Chronic Kidney Disease

The purpose of the study was to quantify serum and fecal amino acids (AA) in cats with chronic kidney disease (CKD) and compare to healthy cats. Thirty-five cats with International Renal Interest Society Stage 1–4 CKD and 16 healthy mature adult and senior client-owned cats were included in this prospective cross-sectional study. Sera were analyzed for 25 AA concentrations using an ion exchange chromatography AA analyzer with post column ninhydrin derivatization. Voided fecal samples were analyzed for 22 AA concentrations using liquid chromatography with tandem mass spectrometry. CKD cats had lower serum concentrations of phenylalanine (mean difference ± standard error of the mean: 12.7 ± 4.3 µM; p = 0.03), threonine (29.6 ± 9.2 µM; p = 0.03), tryptophan (18.4 ± 5.4 µM; p = 0.005), serine (29.8 ± 12.6 µM; p = 0.03), and tyrosine (11.6 ± 3.8 µM; p = 0.01) and higher serum concentrations of aspartic acid (4.7 ± 2.0 µM; p = 0.01), β-alanine (3.4 ± 1.2 µM; p = 0.01), citrulline (5.7 ± 1.6 µM; p = 0.01), and taurine (109.9 ± 29.6 µM; p = 0.01) when compared to healthy cats. Fecal AA concentrations did not differ between healthy cats and CKD cats. 3-Methylhistidine-to-creatinine did not differ between healthy cats with and without muscle loss. Cats with CKD IRIS Stages 1–4 have a deranged serum amino acid profile compared to healthy cats.

Acylcarnitines: Can They Be Biomarkers of Diabetic Nephropathy?

Diabetic nephropathy (DN), one of the most serious microvascular complications of diabetes mellitus (DM), may progress to end-stage renal disease (ESRD). Current biochemical biomarkers, such as urinary albumin excretion rate (UAER), have limitations for early screening and monitoring of DN. Recent studies have identified some metabolites as candidate biomarkers for early detection of DN. In this review, we summarize the role of dysregulated acylcarnitines (AcylCNs) in DN pathophysiology. Lower abundance of short- and medium-chain AcylCNs and higher long-chain AcylCNs often occurred in DM with normal albuminuria and microalbuminuria, compared with advanced stages of DN. The increase of long-chain AcylCNs was supposed to be an adaptive compensation in fat acids (FAs) oxidation in the early stage of DN. Conversely, the decrease of long-chain AcylCNs was due to incomplete oxidation of FAs in advanced stage of DN. Thus, AcylCNs may serve as sensitive biomarkers in predicting the risk of DN.

Plasma Metabolites Associated with a Protein-Rich Dietary Pattern: Results from the OmniHeart Trial

Scope

Lack of biomarkers is a challenge for the accurate assessment of protein intake and interpretation of observational study data. The study aims to identify biomarkers of a protein‐rich dietary pattern.

Methods and Results

The Optimal Macronutrient Intake Trial to Prevent Heart Disease (OmniHeart) trial is a randomized cross‐over feeding study which tested three dietary patterns with varied macronutrient content (carbohydrate‐rich; protein‐rich with about half from plant sources; and unsaturated fat‐rich). In 156 adults, differences in log‐transformed plasma metabolite levels at the end of the protein‐ and carbohydrate‐rich diet periods using paired t‐tests is examined. Partial least‐squares discriminant analysis is used to identify a set of metabolites which are influential in discriminating between the protein‐rich versus carbohydrate‐rich dietary patterns. Of 839 known metabolites, 102 metabolites differ significantly between the protein‐rich and the carbohydrate‐rich dietary patterns after Bonferroni correction, the majority of which are lipids (n = 35), amino acids (n = 27), and xenobiotics (n = 24). Metabolites which are the most influential in discriminating between the protein‐rich and the carbohydrate‐rich dietary patterns represent plant protein intake, food or beverage intake, and preparation methods.

Conclusions

The study identifies many plasma metabolites associated with the protein‐rich dietary pattern. If replicated, these metabolites may be used to assess level of adherence to a similar dietary pattern.

Healthy and Chronic Kidney Disease (CKD) Dogs Have Differences in Serum Metabolomics and Renal Diet May Have Slowed Disease Progression

Chronic kidney disease (CKD) is highly prevalent in dogs, and metabolomics investigation has been recently introduced for a better understanding of the role of diet in CKD. This study aimed to compare the serum metabolomic profile of healthy dogs (CG) and dogs with CKD (CKD-T0 and CKD-T6) to evaluate whether the diet would affect metabolites. Six dogs (5 females; 1 male; 7.47 ± 2.31 years old) with CKD stage 3 or 4 (IRIS) were included. CG consisted of 10 healthy female dogs (5.89 ± 2.57 years old) fed a maintenance diet. Serum metabolites were analyzed by ¹H nuclear magnetic resonance (¹H NMR) spectra. Principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) were performed to assess differences in metabolomic profiles between groups and before (CKD-T0) and after renal diet (CKD-T6). Data analysis was performed on SIMCA-P software. Dogs with CKD showed an altered metabolic profile with increased urea, creatinine, creatine, citrate, and lipids. Lactate, branched-chain amino acids (BCAAs), and glutamine were decreased in the CKD group. However, after 6 months of diet, the metabolite profiles of CKD-T0 and CKD-T6 were similar. Metabolomics profile may be useful to evaluate and recognize metabolic dysfunction and progression of CKD, and the diet may have helped maintain and retard the progression of CKD.

Associations between dietary amino acid intakes and blood concentration levels

BACKGROUND AND AIMS

Emerging evidence suggests a role of amino acids (AAs) in the development of various diseases including renal failure, liver cirrhosis, diabetes and cancer. However, mechanistic pathways and the effects of dietary AA intakes on circulating levels and disease outcomes are unclear. We aimed to compare protein and AA intakes, with their respective blood concentrations in the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort.

METHODS

Dietary protein and AA intakes were assessed via the EPIC dietary questionnaires (DQ) and 24-h dietary recalls (24-HDR). A subsample of 3768 EPIC participants who were free of cancer had blood AA concentrations measured. To investigate how circulating levels relate to their respective intakes, dietary AA intake was examined in quintiles and ANOVA tests were run. Pearson correlations were examined for continous associations between intakes and blood concentrations.

RESULTS

Dietary AA intakes (assessed with the DQ) and blood AA concentrations were not strongly correlated (-0.15 ≤ r ≤ 0.17) and the direction of the correlations depended on AA class: weak positive correlations were found for most essential AAs (isoleucine, leucine, lysine, methionine, threonine, tryptophan, and valine) and conditionally essential AAs (arginine and tyrosine), while negative associations were found for non-essential AAs. Similar results were found when using the 24-HDR. When conducting ANOVA tests for essential AAs, higher intake quintiles were linked to higher blood AA concentrations, except for histidine and phenylalanine. For non-essential AAs and glycine, an inverse relationship was observed. Conditionally-essential AAs showed mixed results.

CONCLUSIONS

Weak positive correlations and dose responses were found between most essential and conditionally essential AA intakes, and blood concentrations, but not for the non-essential AAs. These results suggest that intake of dietary AA might be related to physiological AA status, particularly for the essential AAs. However, these results should be further evaluated and confirmed in large-scale prospective studies.

Effects of Low Protein Diet on Modulating Gut Microbiota in Patients with Chronic Kidney Disease: A Systematic Review and Meta-analysis of International Studies

Background: Although associations between low protein diet (LPD) and changes of gut microbiota have been reported; however, systematic discernment of the effects of LPD on diet-microbiome-host interaction in patients with chronic kidney disease (CKD) is lacking. Methods: We searched PUBMED and EMBASE for articles published on changes of gut microbiota associated with implementation of LPD in CKD patients until July 2021. Independent researchers extracted data and assessed risks of bias. We conducted meta-analyses of combine p-value, mean differences and random effects for gut microbiota and related metabolites. Study heterogeneity was measured by Tau² and I² statistic. This study followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Results: Five articles met inclusion criteria. The meta-analyses of gut microbiota exhibited enrichments of Lactobacillaceae (meta-p= 0.010), Bacteroidaceae (meta-p= 0.048) and Streptococcus anginosus (meta-p< 0.001), but revealed depletion of Bacteroides eggerthii (p=0.017) and Roseburia faecis (meta-p=0.019) in LPD patients compared to patients undergoing normal protein diet. The serum IS levels (mean difference: 0.68 ug/mL, 95% CI: -8.38-9.68, p= 0.89) and pCS levels (mean difference: -3.85 ug/mL, 95% CI: -15.49-7.78, p < 0.52) did not change between groups. We did not find significant differences on renal function associated with change of microbiota between groups (eGFR, mean difference: -7.21 mL/min/1.73 m², 95% CI: -33.2-18.79, p= 0.59; blood urea nitrogen, mean difference: -6.8 mg/dL, 95% CI: -46.42-32.82, p= 0.74). Other clinical (sodium, potassium, phosphate, albumin, fasting sugar, uric acid, total cholesterol, triglycerides, C-reactive protein and hemoglobin) and anthropometric estimates (body mass index, systolic blood pressure and diastolic blood pressure) did not differ between the two groups. Conclusions: This systematic review and meta-analysis suggested that the effects of LPD on the microbiota were observed predominantly at the families and species levels but minimal on microbial diversity or richness. In the absence of global compositional microbiota shifts, the species-level changes appear insufficient to alter metabolic or clinical outputs.

Low protein diets for non-diabetic adults with chronic kidney disease

BACKGROUND

Chronic kidney disease (CKD) is defined as reduced function of the kidneys present for 3 months or longer with adverse implications for health and survival. For several decades low protein diets have been proposed for participants with CKD with the aim of slowing the progression to end-stage kidney disease (ESKD) and delaying the onset of renal replacement therapy. However the relative benefits and harms of dietary protein restriction for preventing progression of CKD have not been resolved. This is an update of a systematic review first published in 2000 and updated in 2006, 2009 and 2018.

OBJECTIVES

To determine the efficacy of low protein diets in preventing the natural progression of CKD towards ESKD and in delaying the need for commencing dialysis treatment in non-diabetic adults.

SEARCH METHODS

We searched the Cochrane Kidney and Transplant Register of Studies up to 7 September 2020 through contact with the Information Specialist using search terms relevant to this review. Studies in the Register are identified through searches of CENTRAL, MEDLINE, and EMBASE, conference proceedings, the International Clinical Trials Register (ICTRP) Search Portal and ClinicalTrials.gov.

SELECTION CRITERIA

We included randomised controlled trials (RCTs) or quasi RCTs in which adults with non-diabetic CKD (stages 3 to 5) not on dialysis were randomised to receive a very low protein intake (0.3 to 0.4 g/kg/day) compared with a low protein intake (0.5 to 0.6 g/kg/day) or a low protein intake compared with a normal protein intake (≥ 0.8 g/kg/day) for 12 months or more.

DATA COLLECTION AND ANALYSIS

Two authors independently selected studies and extracted data. For dichotomous outcomes (death, all causes), requirement for dialysis, adverse effects) the risk ratios (RR) with 95% confidence intervals (CI) were calculated and summary statistics estimated using the random effects model. Where continuous scales of measurement were used (glomerular filtration rate (GFR), weight), these data were analysed as the mean difference (MD) or standardised mean difference (SMD) if different scales had been used. The certainty of the evidence was assessed using GRADE.

MAIN RESULTS

We identified 17 studies with 2996 analysed participants (range 19 to 840). Four larger multicentre studies were subdivided according to interventions so that the review included 21 separate data sets. Mean duration of participant follow-up ranged from 12 to 50 months. Random sequence generation and allocation concealment were considered at low risk of bias in eleven and nine studies respectively. All studies were considered at high risk for performance bias as they were open-label studies. We assessed detection bias for outcome assessment for GFR and ESKD separately. As GFR measurement was a laboratory outcome all studies were assessed at low risk of detection bias. For ESKD, nine studies were at low risk of detection bias as the need to commence dialysis was determined by personnel independent of the study investigators. Five studies were assessed at high risk of attrition bias with eleven studies at low risk. Ten studies were at high risk for reporting bias as they did not include data which could be included in a meta-analysis. Eight studies reported funding from government bodies while the remainder did not report on funding. Ten studies compared a low protein diet with a normal protein diet in participants with CKD categories 3a and b (9 studies) or 4 (one study). There was probably little or no difference in the numbers of participants who died (5 studies 1680 participants: RR 0.77, 95% CI 0.51 to 1.18; 13 fewer deaths per 1000; moderate certainty evidence). A low protein diet may make little or no difference in the number of participants who reached ESKD compared with a normal protein diet (6 studies, 1814 participants: RR 1.05, 95% CI 0.73 to 1.53; 7 more per 1000 reached ESKD; low certainty evidence). It remains uncertain whether a low protein diet compared with a normal protein intake impacts on the outcome of final or change in GFR (8 studies, 1680 participants: SMD -0.18, 95% CI -0.75 to 0.38; very low certainty evidence). Eight studies compared a very low protein diet with a low protein diet and two studies compared a very low protein diet with a normal protein diet. A very low protein intake compared with a low protein intake probably made little or no difference to death (6 studies, 681 participants: RR 1.26, 95% CI 0.62 to 2.54; 10 more deaths per 1000; moderate certainty evidence). However it probably reduces the number who reach ESKD (10 studies, 1010 participants: RR 0.65, 95% CI 0.49 to 0.85; 165 per 1000 fewer reached ESKD; moderate certainty evidence). It remains uncertain whether a very low protein diet compared with a low or normal protein intake influences the final or change in GFR (6 studies, 456 participants: SMD 0.12, 95% CI -0.27 to 0.52; very low certainty evidence). Final body weight was reported in only three studies. It is uncertain whether the intervention alters final body weight (3 studies, 89 participants: MD -0.40 kg, 95% CI -6.33 to 5.52; very low certainty evidence).Twelve studies reported no evidence of protein energy wasting (malnutrition) in their study participants while three studies reported small numbers of participants in each group with protein energy wasting. Most studies reported that adherence to diet was satisfactory. Quality of life was not formally assessed in any studies.

AUTHORS' CONCLUSIONS

This review found that very low protein diets probably reduce the number of people with CKD 4 or 5, who progress to ESKD. In contrast low protein diets may make little difference to the number of people who progress to ESKD. Low or very low protein diets probably do not influence death. However there are limited data on adverse effects such as weight differences and protein energy wasting. There are no data on whether quality of life is impacted by difficulties in adhering to protein restriction. Studies evaluating the adverse effects and the impact on quality of life of dietary protein restriction are required before these dietary approaches can be recommended for widespread use.

Effect of Added Dietary Betaine and Soluble Fiber on Metabolites and Fecal Microbiome in Dogs with Early Renal Disease

Renal diets are recommended for dogs with chronic kidney disease (CKD). This study examined the effects of foods with added betaine and fiber on the plasma and fecal metabolome and fecal microbiome in dogs with early stage CKD. At baseline, several metabolites differed between healthy dogs and those with CKD. Dogs with CKD (n = 28) received a control food, low soluble fiber plus betaine food (0.5% betaine, 0.39% oat beta-glucan, and 0.27% short-chain fructooligosaccharides (scFOS)), or high soluble fiber plus betaine food (0.5% betaine, 0.59% oat beta-glucan, and 0.41% scFOS) each for 10 weeks in different sequences. Consumption of test foods led to several favorable, significant changes in the plasma metabolome, including decreases of several uremic toxins and other deleterious metabolites, and increases in favorable metabolites compared with the control food. Only 7 fecal metabolites significantly changed with consumption of the test foods compared with the control food, largely increases in polyphenols and lignans. Few changes were seen in the fecal microbiome, though some taxa that significantly changed in response to the test foods have beneficial effects on health, with some negatively correlating with uremic toxins. Overall, foods with added betaine and soluble fiber showed positive effects on the plasma and fecal metabolomes.

Fecal Amino Acid Profiles Exceed Accuracy of Serum Amino Acids in Diagnosing Pediatric Inflammatory Bowel Disease

In this prospective intention-to-diagnose pilot study, we aimed to assess accuracy of serum and fecal amino-acids to discriminate de novo pediatric inflammatory bowel disease (IBD) and non-IBD children. Patients with suspected IBD were allocated the IBD (n = 11) or non-IBD group (n = 8) following laboratory testing or endoscopy according to the revised Porto-criteria. Fecal calprotectin levels were obtained, an additional blood and fecal sample were collected. Fecal and serum amino-acid profiles were analyzed using high performance-liquid chromatography. Nine fecal amino-acids (alanine [area under the curve 0.94], citrulline [0.94], glutamine [0.89], leucine [0.98], lysine [0.89], phenylalanine [0.99], serine [0.91], tyrosine [0.96], and valine [0.95]) differed significantly between IBD and non-IBD. In serum, no significant differences were observed. This study underlines the potential of fecal amino-acids as novel, adjuvant noninvasive, and low-cost biomarkers in the diagnostic work-up of pediatric IBD detection.

Accelerating the Search for Interventions Aimed at Expanding the Health Span in Humans: The Role of Epidemiology

BACKGROUND

Extensive work in basic and clinical science suggests that biological mechanisms of aging are causally related to the development of disease and disability in late life. Modulation of the biological mechanisms of aging can extend both life span and health span in animal models, but translation to humans has been slow.

METHODS

Summary of workshop proceedings from the 2018-2019 Epidemiology of Aging Workshop hosted by the Intramural Research Program at the National Institute on Aging.

RESULTS

Epidemiologic studies play a vital role to progress in this field, particularly in evaluating new risk factors and measures of biologic aging that may influence health span, as well as developing relevant outcome measures that are robust and relevant for older individuals.

CONCLUSIONS

Appropriately designed epidemiological studies are needed to identify targets for intervention and to inform study design and sample size estimates for future clinical trials designed to promote health span.

Caution in studying and interpreting the lupus metabolome

Several metabolomics studies have shed substantial light on the pathophysiological pathways underlying multiple diseases including systemic lupus erythematosus (SLE). This review takes stock of our current understanding of this field. We compare, collate, and investigate the metabolites in SLE patients and healthy volunteers, as gleaned from published metabolomics studies on SLE. In the surveyed primary reports, serum or plasma samples from SLE patients and healthy controls were assayed using mass spectrometry or nuclear magnetic resonance spectroscopy, and metabolites differentiating SLE from controls were identified. Collectively, the circulating metabolome in SLE is characterized by reduced energy substrates from glycolysis, Krebs cycle, fatty acid β oxidation, and glucogenic and ketogenic amino acid metabolism; enhanced activity of the urea cycle; decreased long-chain fatty acids; increased medium-chain and free fatty acids; and augmented peroxidation and inflammation. However, these findings should be interpreted with caution because several of the same metabolic pathways are also significantly influenced by the medications commonly used in SLE patients, common co-morbidities, and other factors including smoking and diet. In particular, whereas the metabolic alterations relating to inflammation, oxidative stress, lipid peroxidation, and glutathione generation do not appear to be steroid-dependent, the other metabolic changes may in part be influenced by steroids. To conclude, metabolomics studies of SLE and other rheumatic diseases ought to factor in the potential contributions of confounders such as medications, co-morbidities, smoking, and diet.

Plasma Metabolomics Profiles are Associated with the Amount and Source of Protein Intake: A Metabolomics Approach within the PREDIMED Study

SCOPE

The plasma metabolomics profiles of protein intake have been rarely investigated. The aim is to identify the distinct plasma metabolomics profiles associated with overall intakes of protein as well as with intakes from animal and plant protein sources.

METHODS AND RESULTS

A cross-sectional analysis using data from 1833 participants at high risk of cardiovascular disease is conducted. Associations between 385 identified metabolites and the intake of total, animal protein (AP), and plant protein (PP), and plant-to-animal ratio (PR) are assessed using elastic net continuous regression analyses. A double 10-cross-validation (CV) procedure is used and Pearson correlations coefficients between multi-metabolite weighted models and reported protein intake in each pair of training-validation datasets are calculated. A wide set of metabolites is consistently associated with each protein source evaluated. These metabolites mainly consisted of amino acids and their derivatives, acylcarnitines, different organic acids, and lipid species. Few metabolites overlapped among protein sources (i.e., C14:0 SM, C20:4 carnitine, GABA, and allantoin) but none of them toward the same direction. Regarding AP and PP approaches, C20:4 carnitine and dimethylglycine are positively associated with PP but negatively associated with AP. However, allantoin, C14:0 SM, C38:7 PE plasmalogen, GABA, metronidazole, and trigonelline (N-methylnicotinate) behave contrarily. Ten-CV Pearson correlation coefficients between self-reported protein intake and plasma metabolomics profiles range from 0.21 for PR to 0.32 for total protein.

CONCLUSIONS

Different sets of metabolites are associated with total, animal, and plant protein intake. Further studies are needed to assess the contribution of these metabolites in protein biomarkers' discovery and prediction of cardiometabolic alterations.

Proteomics and Metabolomics in Kidney Disease, including Insights into Etiology, Treatment, and Prevention

In this review of the application of proteomics and metabolomics to kidney disease research, we review key concepts, highlight illustrative examples, and outline future directions. The proteome and metabolome reflect the influence of environmental exposures in addition to genetic coding. Circulating levels of proteins and metabolites are dynamic and modifiable, and thus amenable to therapeutic targeting. Design and analytic considerations in proteomics and metabolomics studies should be tailored to the investigator's goals. For the identification of clinical biomarkers, adjustment for all potential confounding variables, particularly GFR, and strict significance thresholds are warranted. However, this approach has the potential to obscure biologic signals and can be overly conservative given the high degree of intercorrelation within the proteome and metabolome. Mass spectrometry, often coupled to up-front chromatographic separation techniques, is a major workhorse in both proteomics and metabolomics. High-throughput antibody- and aptamer-based proteomic platforms have emerged as additional, powerful approaches to assay the proteome. As the breadth of coverage for these methodologies continues to expand, machine learning tools and pathway analyses can help select the molecules of greatest interest and categorize them in distinct biologic themes. Studies to date have already made a substantial effect, for example elucidating target antigens in membranous nephropathy, identifying a signature of urinary peptides that adds prognostic information to urinary albumin in CKD, implicating circulating inflammatory proteins as potential mediators of diabetic nephropathy, demonstrating the key role of the microbiome in the uremic milieu, and highlighting kidney bioenergetics as a modifiable factor in AKI. Additional studies are required to replicate and expand on these findings in independent cohorts. Further, more work is needed to understand the longitudinal trajectory of select protein and metabolite markers, perform transomics analyses within merged datasets, and incorporate more kidney tissue-based investigation.

Protective Effects of Dietary MUFAs Mediating Metabolites against Hypertension Risk in the Korean Genome and Epidemiology Study

Background and Aims: Metabolites related to dietary factors can be used to identify biological markers to prevent metabolic disease. However, most studies have been conducted in the United States and Europe, and those in the Asian region are limited. We investigated the effects of dietary monounsaturated fatty acids (MUFAs) and metabolites on new-onset hypertension in the Korean Genome and Epidemiology Study. Method and Results: A total of 1529 subjects without hypertension were divided into tertiles of dietary MUFAs intake. After a 4-year follow-up, 135 serum metabolites were measured using the AbsoluteIDQ p180 kit. During the 4-year follow-up period, 193 new-onset hypertension incidences were observed. The highest MUFAs intake group was inversely associated with the risk of hypertension compared with the lowest MUFAs intake group (odds ratio (OR) = 0.49, (95% confidence interval (CI) = 0.29–0.82)). Of the 135 metabolites, eight were significantly associated with MUFAs intake. Phosphatidylcholine-diacyl (PC aa) C 38:1 and hydroxysphingomyelin (SM OH) C 16:1 were associated with a decrease in hypertension risk (PC aa C 38:1, OR = 0.60 (95% CI = 0.37–0.96); SM OH C 16:1, OR = 0.42 (95% CI = 0.20–0.90)). The highest MUFAs intake group had a significantly decreased risk of hypertension, even considering PC aa C 38:1 and SM (OH) C 16:1 as a mediator. Conclusion: We confirmed that dietary MUFAs intake, and PC aa C 38:1 and SM (OH) C 16:1 had protective effects against hypertension. Furthermore, high MUFAs intake combined with PC aa C 38:1 and SM (OH) C 16:1 has the most significant effect on reducing the risk hypertension.

The Serum Metabolome Identifies Biomarkers of Dietary Acid Load in 2 Studies of Adults with Chronic Kidney Disease

BACKGROUND

Dietary acid load is a clinically important aspect of the diet that reflects the balance between acid-producing foods, for example, meat and cheese, and base-producing foods, for example, fruits and vegetables.

METHODS

We used metabolomics to identify blood biomarkers of dietary acid load in 2 independent studies of chronic kidney disease patients: the African American Study of Kidney Disease and Hypertension (AASK, n = 689) and the Modification of Diet in Renal Disease (MDRD, n = 356) study. Multivariable linear regression was used to assess the cross-sectional association between serum metabolites whose identity was known (outcome) and dietary acid load (exposure), estimated with net endogenous acid production (NEAP) based on 24-h urine urea nitrogen and potassium, and adjusted for age, sex, race, randomization group, measured glomerular filtration rate, log-transformed urine protein-to-creatinine ratio, history of cardiovascular disease, BMI, and smoking status.

RESULTS

Out of the 757 known, nondrug metabolites identified in AASK, 26 were significantly associated with NEAP at the Bonferroni threshold for significance (P < 6.6 × 10-5). Twenty-three of the 26 metabolites were also identified in the MDRD study, and 13 of the 23 (57%) were significantly associated with NEAP (P < 2.2 × 10-3), including 5 amino acids (S-methylmethionine, indolepropionylglycine, indolepropionate, N-methylproline, N-δ-acetylornithine), 2 cofactors and vitamins (threonate, oxalate), 1 lipid (chiro-inositol), and 5 xenobiotics (methyl glucopyranoside, stachydrine, catechol sulfate, hippurate, and tartronate). Higher levels of all 13 replicated metabolites were associated with lower NEAP in both AASK and the MDRD study.

CONCLUSION

Metabolomic profiling of serum specimens from kidney disease patients in 2 study populations identified 13 replicated metabolites associated with dietary acid load. Additional studies are needed to validate these compounds in healthy populations. These 13 compounds may potentially be used as objective markers of dietary acid load in future nutrition research studies.