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Clinical Journal of the American Society of Nephrology : CJASN logoLink to Clinical Journal of the American Society of Nephrology : CJASN
. 2018 Jun 22;13(8):1244–1246. doi: 10.2215/CJN.01830218

Metabolic Changes with Base-Loading in CKD

Julia J Scialla 1,2,, Landon Brown 1, Susan Gurley 1, David L Corcoran 1,3, James R Bain 1,4, Michael J Muehlbauer 4, Sara K O’Neal 4, Thomas M O’Connell 1,4,5, Myles Wolf 1,2, Michal L Melamed 6, Thomas H Hostetter 7, Matthew K Abramowitz 6
PMCID: PMC6086694  PMID: 29934431

In small, randomized studies, treatment with sodium bicarbonate slowed kidney function decline in patients with CKD, possibly by lowering urine ammonium or inhibiting the renin-angiotensin-aldosterone or endothelin-1 pathways (1). Understanding the metabolic effects of alkali supplementation may reveal new candidate mechanisms. With this goal in mind, we profiled changes in systemic metabolites after treatment with sodium bicarbonate within a previously performed crossover trial of oral sodium bicarbonate (2).

The trial enrolled 20 adults with moderate CKD (mean±SD eGFR: 33±9 ml/min per 1.73 m2) and serum bicarbonate concentration of 20–24 mEq/L (2). Mean age was 63±11 years, 85% had diabetes mellitus, and the mean±SD body mass index was 31.2±6.4 kg/m2. Each participant was treated sequentially for 2 weeks with placebo, followed by sodium bicarbonate at escalating doses (0.3, 0.6, and 1.0 mEq/kg per day) under a protocol approved by the Institutional Review Board of the Albert Einstein College of Medicine (protocol #2008-376). We extracted a volume containing 2 µmol of creatinine into ethyl acetate from stored 24-hour urine samples collected after the placebo and 1.0 mEq/kg per day sodium bicarbonate period in all participants. From these, we generated nontargeted urine metabolite profiles using gas chromatography/electron-ionization mass spectrometry (GC/EI-MS). Blood samples were not fasting, therefore we performed plasma metabolomics among 11 out of 20 individuals, each of whom had similar fasting duration at their paired timepoints. Fasting duration ranged from 90 to 330 minutes, with a maximum difference in fasting time between paired samples of ±150 minutes. Plasma metabolomics included nontargeted GC/EI-MS from samples after methanol extraction, targeted panels using the AbsoluteIDQ p180 kit (Biocrates, Innsbruck, Austria), and conventional plasma metabolites (i.e., lactate, ketones, and pyruvate) measured on a Beckman Unicel DxC 600 autoanalyzer. Full details of GC/EI-MS protocols at the Duke Molecular Physiology Institute (DMPI) have been previously reported (3).

Nontargeted data were deconvoluted and annotated using the DMPI’s custom spectral libraries with entries from external libraries (Fiehn laboratory and Golm Metabolome Database), public libraries such as the National Institute of Standards and Technology database, and the DMPI’s own additions. Integrated peak areas were log2 transformed. Metabolites missing in >50% of samples were not analyzed further, and other missing values were imputed using k-nearest neighbor (k=6) for nontargeted platforms or set to the limit of detection for targeted results. We used mixed linear models to evaluate pre-post metabolite changes and express the exponentiated β coefficients (2β) as fold change.

No targeted plasma metabolites differed significantly pre- and postbicarbonate. Plasma lactate, ketones, and pyruvate (n=11) were each quantitatively higher after sodium bicarbonate, but also were not statistically significant. In nontargeted platforms, 234 unique plasma metabolites and 195 unique urine metabolites were analyzed. Identifiable plasma and urine metabolites that differed after bicarbonate therapy at a nominal P value ≤0.1 are presented in Table 1. Probable contaminants were removed. After correcting P values for a false discovery rate (FDR) of 20%, only urinary citrate/isocitrate remained significant (FDR-adjusted P value=0.03). Using each timepoint tested, log2 peak areas for citrate/isocitrate correlated moderately with serum bicarbonate concentrations (r=0.43; P<0.01) but within-person changes in these parameters were not correlated (P=0.9).

Table 1.

Change in selected metabolites in nontargeted analyses in plasma and urine

Metabolite Annotationa Fold Change Nominal P Value Metabolite Descriptionb
Plasma metabolites
 3-Indoleacetic acid 0.63 0.005 Tryptophan metabolite
β-Sitosterol 1.49 0.01 Dietary phytosterol
 Methyl stearateb 1.50 0.01 Fatty acid methyl ester
 Lauric acid 1.36 0.02 Medium-chain fatty acid
 Sucrose and similar disaccharides 2.07 0.02 Simple sugars
 Methyl palmitateb 1.38 0.02 Fatty acid methyl ester
 Methyl oleateb 1.67 0.02 Fatty acid methyl ester
 Methyl linolenateb 1.60 0.02 Fatty acid methyl ester
 Glycerol 1-phosphate 1.86 0.04 Glycolysis intermediate
 Decanoic acid 1.79 0.05 Median-chain fatty acid
 Malic acid 1.46 0.05 Intermediate of TCA cycle
 Nonanoic acid 1.46 0.06 Median-chain fatty acid
 Maltose or similar disaccharide 1.79 0.06 Simple sugar
 Citric acid/isocitric acid 1.40 0.07 Intermediate of TCA cycle
 Glycerol 1.33 0.08 Backbone of triglyceride
 Urea 1.40 0.08 End product of protein metabolism
α-Ketoglutaric acid 1.27 0.09 Intermediate of TCA cycle
p-Cresol 0.67 0.09 Phenol derived from bacterial metabolism
 Dehydroascorbic acid 1.25 0.09 Oxidized vitamin C
 2-Hydroxybutyric acid 1.35 0.09 α-Hydroxy fatty acid
Urine metabolites
 Citric acid/isocitric acid 2.71 <0.001 Intermediate of TCA cycle
 Succinic acid 2.01 0.002 Intermediate of TCA cycle
 3-Indoleacetic acid 2.01 0.005 Tryptophan metabolite
 2-Ethyl-3-hydroxypropionic acid 1.42 0.01 β-Hydroxy fatty acid; related to BCAA metabolism
 Methylmalonic acid 1.45 0.02 Dicarboxylic acid; anaplerotic substrate
 Pimelic acid 0.71 0.02 Dicarboxylic acid
 Glyoxylic acid 0.57 0.02 Carboxylic acid
α-Ketoglutaric acid 1.61 0.03 Intermediate of TCA cycle
 3-Methyl-3-Hydroxyisobutanoic acid 1.41 0.03 β-Hydroxy fatty acid; increased in ketoacidosis
 Fumaric acid 1.44 0.04 Intermediate of TCA cycle
 2-Isopropylmalic acid 1.69 0.05 α-Hydroxy dicarboxylic acid; elevated in ketoacidosis
 Hippuric acid 1.35 0.08 Acyl-glycine
 Lactic acid 1.69 0.1 α-Hydroxy acid

TCA, tricarboxylic acid; BCAA, branched chain amino acid.

a

Reported metabolites are identifiable metabolites from nontargeted analyses with a nominal P value ≤0.1.

b

Plasma C12 hydrocarbon and aminomalonic acid, and urine 4-hydroxycyclohexanecarboxylic acid were removed as likely contaminants. Methyl esters may be artificially derived during the extraction protocol with methanol but are listed because they may represent change in the underlying fatty acid ester. Alternatively they may represent increased methylation reactions in the setting of higher plasma pH.

Each of the nominally significant metabolites (Table 1) was entered in MetaboAnalyst 3.0 (http://www.metaboanalyst.ca/) to determine pathway effects. On the basis of urine metabolites, pathway analysis revealed a strong effect on the tricarboxylic acid (TCA) cycle (FDR-adjusted P value<0.001), with additional effects on propanoate metabolism (FDR-adjusted P value=0.01). There were marginally significant pathway effects on pyruvate (nominal P value=0.01; FDR-adjusted P value=0.14) and branched chain-amino acid metabolism (nominal P value=0.02; FDR-adjusted P value=0.19) on the basis of urine metabolites, and the TCA cycle on the basis of plasma metabolites (nominal P value=0.01; FDR-adjusted P value=0.66).

In this study, treatment with sodium bicarbonate resulted in increased urinary excretion of multiple organic anions, including citrate/isocitrate, fumarate, succinate, malate, and α-ketoglutarate. Citrate/isocitrate was the only individual metabolite significant at an FDR-adjusted level of significance; however, the more statistically powerful pathway analyses indicate a robust effect on the TCA cycle. In this context, higher levels of circulating TCA intermediates (e.g., citrate/isocitrate, α-ketoglutarate), as well as the directly measured organic anions lactate, ketones, and pyruvate, suggest broader systemic effects of bicarbonate administration despite these changes not being statistically significant. Anaplerotic pathways including branched chain-amino acid and propanoate and pyruvate metabolism, act to restore TCA cycle intermediates and were also affected by sodium bicarbonate in our patients. In light of published reports that implicate changes in the TCA cycle in diabetic and nondiabetic kidney disease (4,5), these results may suggest a mechanism of protection in CKD.

Disclosures

None.

Acknowledgments

We sincerely thank participants and staff who participated in this trial, as well as Dr. Christopher Newgard (Director, Duke Molecular Physiology Institute) and Dr. Arthur Moseley, Dr. Lisa St. John-Williams, and Dr. J. Will Thompson (Duke Proteomics and Metabolomics Shared Resource) for valuable consultations.

The Alkali in CKD Trial was supported by grants R21DK077326 and R01DK087783 to T.H.H. from the National Institute of Diabetes and Digestive and Kidney Diseases and Clinical and Translational Science Award grants UL1RR025750 and KL2RR025749 from the National Center for Research Resources, a component of the National Institutes of Health. Metabolite analyses were supported by the National Institute of Diabetes and Digestive and Kidney Diseases grant P30DK096493, as a pilot and feasibility award from the Duke O’Brien Center for Kidney Research to J.J.S. Additional support was provided by grants K23DK095949 (to J.J.S.) and K23DK099438 (to M.K.A.) also from the National Institute of Diabetes and Digestive and Kidney Diseases.

Footnotes

Published online ahead of print. Publication date available at www.cjasn.org.

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