The plot shows multivariable-adjusted hazard ratios (HRs) and 95% CIs (error bars) comparing quintiles 3 to 5 with quintiles 1 and 2. Cutoffs for continuous variables were chosen to represent medians or clinically relevant subgroups. Models are adjusted for age, sex, race/ethnicity, systolic blood pressure, diabetes, body mass index (BMI; calculated as weight in kilograms divided by height in meters squared), 24-hour urinary creatinine excretion, medications (phosphate binders, angiotensin II receptor blockers [ARBs], angiotensin-converting enzyme inhibitors [ACEIs], diuretics, β-blockers, statins, antiplatelet agents), hemoglobin, serum albumin, and baseline eGFR. To convert albumin to grams per liter, multiply by 10; to convert calcium to millimoles per liter, multiply by 0.25; and to convert phosphorus to millimoles per liter, multiply by 0.323.
The plot shows multivariable-adjusted hazard ratios (HRs) and 95% CIs (error bars) comparing quintiles 3 to 5 and quintiles 1 and 2. Cutoffs for continuous variables were chosen to represent medians or clinically relevant subgroups. Models are adjusted for age, sex, race/ethnicity, systolic blood pressure, diabetes, body mass index (BMI; calculated as weight in kilograms divided by height in meters squared), 24-hour urinary creatinine excretion, medications (phosphate binders, angiotensin II receptor blockers [ARBs], angiontensin-converting enzyme inhibitors [ACEIs], diuretics, β-blockers, statins, antiplatelet agents), hemoglobin, serum albumin, and baseline estimated glomerular filtration rate (eGFR). To convert albumin to grams per liter, multiply by 10; to convert calcium to millimoles per liter, multiply by 0.25; and to convert phosphorus to millimoles per liter, multiply by 0.323.
eTable. Risk of all-cause mortality according to ascending quintiles of 24h urinary oxalate excretion
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Waikar SS, Srivastava A, Palsson R, et al. Association of Urinary Oxalate Excretion With the Risk of Chronic Kidney Disease Progression. JAMA Intern Med. 2019;179(4):542–551. doi:10.1001/jamainternmed.2018.7980
Does higher urinary oxalate excretion predispose patients to kidney failure?
In this cohort study of 3123 individuals with chronic kidney disease, higher urinary excretion of oxalate was associated with a 37% greater adjusted risk of future end-stage kidney disease.
Urinary oxalate excretion appears to be an independent risk factor for chronic kidney disease progression.
Oxalate is a potentially toxic terminal metabolite that is eliminated primarily by the kidneys. Oxalate nephropathy is a well-known complication of rare genetic disorders and enteric hyperoxaluria, but oxalate has not been investigated as a potential contributor to more common forms of chronic kidney disease (CKD).
To assess whether urinary oxalate excretion is a risk factor for more rapid progression of CKD toward kidney failure.
Design, Setting, and Participants
This prospective cohort study assessed 3123 participants with stages 2 to 4 CKD who enrolled in the Chronic Renal Insufficiency Cohort study from June 1, 2003, to September 30, 2008. Data analysis was performed from October 24, 2017, to June 17, 2018.
Twenty-four–hour urinary oxalate excretion.
Main Outcomes and Measures
A 50% decline in estimated glomerular filtration rate (eGFR) and end-stage renal disease (ESRD).
This study included 3123 participants (mean [SD] age, 59.1 [10.6] years; 1414 [45.3%] female; 1423 [45.6%] white). Mean (SD) eGFR at the time of 24-hour urine collection was 42.9 (16.8) mL/min/1.73 m2. Median urinary excretion of oxalate was 18.6 mg/24 hours (interquartile range [IQR], 12.9-25.7 mg/24 hours) and was correlated inversely with eGFR (r = −0.13, P < .001) and positively with 24-hour proteinuria (r = 0.22, P < .001). During 22 318 person-years of follow-up, 752 individuals reached ESRD, and 940 individuals reached the composite end point of ESRD or 50% decline in eGFR (CKD progression). Higher oxalate excretion was independently associated with greater risks of both CKD progression and ESRD: compared with quintile 1 (oxalate excretion, <11.5 mg/24 hours) those in quintile 5 (oxalate excretion, ≥27.8 mg/24 hours) had a 33% higher risk of CKD progression (hazard ratio [HR], 1.33; 95% CI, 1.04-1.70) and a 45% higher risk of ESRD (HR, 1.45; 95% CI, 1.09-1.93). The association between oxalate excretion and CKD progression and ESRD was nonlinear and exhibited a threshold effect at quintiles 3 to 5 vs quintiles 1 and 2. Higher vs lower oxalate excretion (at the 40th percentile) was associated with a 32% higher risk of CKD progression (HR, 1.32; 95% CI, 1.13-1.53) and 37% higher risk of ESRD (HR, 1.37; 95% CI, 1.15-1.63). Results were similar when treating death as a competing event.
Conclusions and Relevance
Higher 24-hour urinary oxalate excretion may be a risk factor for CKD progression and ESRD in individuals with CKD stages 2 to 4.
Oxalate is a potentially toxic terminal metabolite that is eliminated primarily through the kidneys by glomerular filtration and tubular secretion.1 Kidney failure from oxalate nephropathy is a devastating complication of rare disorders of oxalate metabolism (primary hyperoxaluria),2 oxalate overabsorption (enteric hyperoxaluria),3-5 and ingestion of large amounts of oxalate6 or its precursors (eg, ethylene glycol poisoning7). In these disorders, high concentrations of oxalate in kidney tubular fluid leads to calcium oxalate crystal formation, obstruction, and direct injury to tubular epithelial cells, leading ultimately to kidney injury and decreased glomerular filtration rate (GFR).8 Calcium oxalate crystal deposition in tissue parenchyma can also cause tissue injury and inflammation by activating the intracellular nucleotide-binding domain, leucine-rich repeat–containing receptor, pyrin domain–containing-3 (NLRP3) inflammasome, which translates danger signals into secretion of interleukin 1β (IL-1β), a highly proinflammatory cytokine.9-11
The exposure of the kidney to oxalate is dependent on dietary intake, gut absorption and secretion, and endogenous generation of oxalate from metabolism of precursor molecules, including serine, glycine, hydroxyproline, and certain carbohydrates.12 After glomerular filtration, oxalate is reabsorbed and secreted along the nephron.13 In the steady state, net urinary excretion of oxalate is a measure of its intake, endogenous generation, gut metabolism, and fecal excretion.
On the basis of the known association of high urinary oxalate with acute kidney injury and chronic kidney disease (CKD) in specific disease settings, we hypothesized that higher urinary oxalate, even within the typical ranges of excretion, would be associated with higher risk for CKD progression. To test the hypothesis that oxalate may accelerate CKD progression in more commons forms of kidney disease, we measured 24-hour urinary oxalate excretion in participants with CKD enrolled in the Chronic Renal Insufficiency Cohort (CRIC) study.
The CRIC study is a multicenter, prospective, observational cohort study of risk factors for cardiovascular disease, progression of CKD, and mortality.14 From January 1, 2003, to September 30, 2008, a total of 3939 individuals aged 21 to 74 years with an age-stratified estimated GFR (eGFR) of 20 to 70 mL/min/1.73 m2 were enrolled across 7 clinical centers (University of Pennsylvania, Johns Hopkins University, Case Western Reserve University, University of Michigan, University of Illinois at Chicago, Tulane University Health Science Center, and Kaiser Permanente of Northern California) in the United States. Because CKD is more common among minorities, blacks were oversampled, and the ancillary Hispanic CRIC study enrolled 327 additional Hispanic participants. Exclusion criteria included inability to provide consent, institutionalization, enrollment in other research studies, pregnancy, New York Heart Association class III to IV congestive heart failure, HIV infection, cirrhosis, multiple myeloma, renal cancer, recent chemotherapy or immunosuppressive therapy, polycystic kidney disease, organ transplantation, or prior treatment with dialysis for at least 1 month. Data analysis was performed from October 24, 2017, to June 7, 2018. Samples for this study were from 24-hour urine samples collected in the year 1 (Y1) visit (1 year after baseline) from participants who were free of end-stage renal disease (ESRD) at the time of urine collection and had available eGFR measurements. After exclusions, 3123 participants were included in the analysis. The CRIC protocol was approved by the institutional review boards at each of the recruiting sites, and all participants provided written informed consent. All data were deidentified.
Participants were provided a 24-hour urine collection container without preservatives along with written instructions on 24-hour urine collection procedures. They were told to keep the urine specimen refrigerated and to begin the sample collection 24 hours before a study visit. Completed urine collections with total volume less than 500 mL or total collection time less than 22 hours or greater than 26 hours were discarded and collections were performed again. Aliquots from the thoroughly mixed 24-hour urine collection were then stored at −80°C in 9-mL tubes. For the purpose of this study, frozen 9-mL urine samples were thawed overnight at 4°C, inverted 4 times, vortexed for 10 seconds, inverted again 4 times, and then subaliquoted and frozen at −80°C in 1-mL daughter vials, 1 of which was shipped on dry ice to a laboratory for oxalate measurement.
Urinary oxalate was measured at the Mayo Clinic (Rochester, Minnesota) using an oxalate oxidase enzymatic assay. Frozen samples were received, thawed, and then measured for pH. Samples with pH 8 or higher were rejected and not processed (76 of >3000) because of concern for bacterial contamination. Before oxalate measurement, sample pH was adjusted to 2.5 to 3.0 with phosphate buffer (pH 2.5), and nitrite was added to remove interference from ascorbic acid. The interassay coefficients of variation, measured from 249 masked split replicate samples collected from an individual with CKD whose urine samples were aliquoted into tubes identical to CRIC study tubes, were less than 3%. The 24-hour urinary oxalate excretion was calculated by multiplying the oxalate concentration by the urinary volume and then adjusting for the number of hours collected.
Self-reported sociodemographic characteristics, medical history, lifestyle behaviors, current medications, blood pressure, and anthropometric measures were obtained at the Y1 visit at the time of the 24-hour urine collection for oxalate measurement. Laboratory measurements using standard assays were also performed on samples from the Y1 visit with the exception of urine albumin to creatinine ratio and urinary calcium, which was available only from the 24-hour urine collection at year 0 (baseline visit). Diabetes was defined as a fasting plasma glucose level of 126 mg/dL or higher, a nonfasting plasma glucose level of 200 mg/dL or higher (to convert glucose to millimoles per liter, multiply by 0.0555), or self-reported use of antidiabetes medication. The eGFR was calculated using the CRIC-derived estimating equation.15 Proteinuria was measured from the Y1 24-hour urine collection.
The CRIC study participants were followed up annually by clinic visits, with interim telephone contact at 6 months. The primary outcomes were incident ESRD and CKD progression, the latter defined as a composite of incident ESRD or 50% decline in eGFR. End-stage renal disease was defined as receipt of long-term dialysis or a kidney transplant. Information on initiation and maintenance of dialysis and kidney transplant was obtained annually during follow-up visits and interim telephone interviews and confirmed by the dialysis unit or hospital medical record review. Ascertainment of ESRD was also supplemented by information from the US Renal Data System.16 Time to 50% decline in eGFR was imputed, assuming a linear decrease in kidney function between in-person annual visit measurements.17 Patient follow-up was censored at the first occurrence of voluntary study withdrawal, loss to follow-up, end of the follow-up period, or death. All deaths were confirmed by death certificate review.
We expressed continuous variables as means (SDs) or medians (interquartile ranges [IQRs]) and compared them with parametric or nonparametric tests, as appropriate. We tested the associations of 24-hour urinary oxalate with variables using Spearman correlation coefficients and unadjusted and multivariable-adjusted linear regression models. We used Cox proportional hazards regression models to examine the multivariable-adjusted risks of outcomes according to 24-hour urinary oxalate as a categorical variable (with the reference group as quintile 1) and as a binary variable above or below the 40th percentile, based on our observation of a nonlinear association in this study. We confirmed no violation of the proportional hazards assumption using the Kolmogorov-type Supremum test. Our multivariable adjustment strategy for the proportional hazards models was hierarchical and based on biological and clinical plausibility of covariates as potential confounders of the association between a urinary metabolite and CKD progression.
We stratified by clinical site and adjusted for age, sex, race/ethnicity, systolic blood pressure, diabetes mellitus, body mass index (BMI; calculated as weight in kilograms divided by height in meters squared), and 24-hour urinary creatinine excretion. We then added medications (angiotensin-converting enzyme inhibitors or angiotensin II receptor blockers, diuretics, β-blockers, statins, and antiplatelet agents), hemoglobin, and serum albumin. We then added baseline eGFR for the final adjusted multivariable model. We performed exploratory subgroup analyses according to clinically relevant conditions and adjusted for proteinuria as a covariate in sensitivity analyses because of its potential role as a mediator of CKD progression.18 Less than 3% of data were missing. Complete case analysis was used for the main findings. Multiple imputation for missing covariate values was performed in a sensitivity analysis, and no substantial differences were observed. Competing risk regression for the ESRD end point was also performed as a sensitivity analysis. All statistical tests were 2-sided, and P < .05 was considered statistically significant. All analyses were performed with SAS statistical software, version 9.4 (SAS Institute Inc).
This study included 3123 participants (mean [SD] age, 59.1 [10.6] years; 1414 [45.3%] female; 1423 [45.6%] white). Baseline characteristics of participants are given in Table 1 for the overall population and according to 24-hour urinary oxalate quintiles. The median 24-hour urinary excretion of oxalate was 18.6 mg (IQR, 12.9-25.7 mg). Median urinary oxalate excretion was higher in men than women (20.4 vs 16.6 mg, P < .001), in those with vs without diabetes (20.0 vs 17.0 mg, P < .001), and in users vs nonusers of angiotensin-converting enzyme inhibitors or angiotensin II receptor blockers (19.2 vs 16.6 mg; P < .001), statins (19.3 vs 17.3 mg; P < .001), and thiazide diuretics (20.3 vs 17.9 mg, P < .001). Body mass index correlated positively with urinary oxalate excretion (r = 0.10, P < .001). Those with higher urinary oxalate excretion had lower eGFR (r = −0.13, P < .001) and greater proteinuria (r = 0.22, P < .001). Urinary oxalate excretion correlated positively with urinary creatinine excretion (r = 0.36, P < .001) and negatively with urinary calcium excretion (r = −0.27, P < .001) and serum calcium (r = −0.15, P < .001).
Factors associated with urinary oxalate excretion in unadjusted and adjusted linear regression models are given in Table 2. Adjusted oxalate excretion rate was 11% higher in individuals with vs without diabetes (95% CI, 7%-14%), 12% lower in black vs nonblack individuals (95% CI, 8%-15%), 11% higher in individuals taking vs not taking thiazide diuretics (95% CI, 7%-15%), 5% lower in individuals taking vs not taking loop diuretics (95% CI, 1%-9%), and not significantly different according to use of phosphate-binding medications (3%; 95% CI, −4% to 9%). The laboratory variables most strongly associated with adjusted oxalate excretion rate were higher urinary creatinine excretion (4% higher per 100 mg/24 hours; 95% CI, 3.5%-4.2%), lower urinary calcium excretion rate (2% lower for every 100 mg/24 hours; 95% CI, 1.7%-2.2%), and lower serum calcium (11% lower for every 1 mg/dL; 95% CI, 7%-15%).
During 22 318 person-years of follow-up, 752 individuals reached ESRD, and 940 individuals reached the composite end point of ESRD or 50% decline in eGFR (CKD progression). Median 24-hour urinary oxalate excretion at the Y1 visit was significantly higher in those who reached ESRD (20.5 mg; IQR, 14.8-27.5 mg) or the composite end point (20.1 mg; IQR, 14.7-27.4 mg) than those who reached neither end point and were censored at loss to follow-up or death (17.6 mg; IQR, 12.2-25.2 mg) (P < .001). Table 3 gives the results of multivariable-adjusted models according to quintiles of urinary oxalate excretion. After multivariable adjustment for demographics, diabetes, systolic blood pressure, BMI, medications, laboratory values, and baseline eGFR, individuals in the highest quintile vs lowest quintile of urinary oxalate excretion had a 33% higher risk of CKD progression (HR, 1.33; 95% CI, 1.04-1.70) and a 45% higher risk of ESRD (HR, 1.45; 95% CI, 1.09-1.93). Results were similar when death was treated as a competing risk for the ESRD end point (highest vs lowest quintile: HR, 1.40; 95% CI, 1.04-1.88). The association between urinary oxalate excretion and CKD progression and ESRD appeared nonlinear with a threshold effect in quintiles 3 to 5 compared with quintiles 1 and 2. Using a dichotomous definition of higher vs lower urinary oxalate excretion (at the 40th percentile), there was a 32% higher risk of CKD progression (HR, 1.32; 95% CI, 1.13-1.53) and 37% higher risk of ESRD (HR, 1.37; 95% CI, 1.15-1.63). Results were generally consistent across subgroups (Figure 1 and Figure 2) and were not substantially changed after additional adjustment for 24-hour proteinuria (CKD progression: HR, 1.27; 95% CI, 1.09-1.48; ESRD: HR, 1.31; 95% CI, 1.09-1.56). In sensitivity analyses, we found no association between urinary oxalate excretion and mortality (eTable in the Supplement).
Higher levels of urinary oxalate excretion appear to be independently associated with greater risk of CKD progression and ESRD. The nephrotoxicity of oxalate has been long recognized in rare genetic disorders of primary hyperoxaluria2 and in enteric hyperoxaluria3-5 but has not previously been extended to more common forms of CKD as our results now show. Our findings are consistent with mechanistic data from tissue culture studies and animal models of oxalate toxicity.19 Our findings are also consistent with epidemiologic findings that individuals with a history of kidney stone disease, of which calcium oxalate is the cause in 80%, have an increased risk of CKD and incident ESRD.20-22 Collectively, these data provide evidence in support of the hypothesis that oxalate is a causal mediator of progression in CKD.23
Calcium oxalate crystals can precipitate in the tubular lumen and cause obstruction and also deposit in the parenchyma and cause nephrocalcinosis. More recent evidence shows that calcium oxalate–induced kidney injury can arise through activation of the intrarenal NLRP3 inflammasome.24 Oxalate can activate the NLRP3 inflammasome in acute and chronic oxalate models.9,10 Using an acute oxalate nephropathy model, Mulay et al10 demonstrated that oxalate triggered IL-1β–dependent innate immunity via the NLRP3 inflammasome in renal dendritic cells. They found that oxalate also indirectly activated NLRP3 and IL-1β secretion by damaging tubular epithelial cells and releasing adenosine triphosphate, an NLRP3 agonist. Finally, they found protection against oxalate-induced kidney injury in vivo in NLRP3−/− null mice and with treatment of the IL-1β antagonist anakinra. Using a mouse model of long-term dietary oxalate loading, Knauf et al9 found a role for NLRP3-mediated inflammation in oxalate-induced CKD. Mice fed a diet high in soluble oxalate had kidney intratubular crystal deposition and tubulointerstitial damage and inflammation and died of progressive kidney failure within 30 days. Oxalate-rich dietary feeding has also been introduced as a mouse model of CKD that recapitulates many features of human CKD, including GFR loss with histologic features of CKD (tubular injury, atubular glomeruli, interstitial inflammation, and fibrosis), metabolic complications of CKD (normochromic anemia, metabolic acidosis, hyperkalemia, fibroblast growth factor 23 activation, and hyperphosphatemia), and extrarenal complications of CKD, including arterial hypertension and cardiac fibrosis.25
The 24-hour excretion of oxalate, as measured in the CRIC study participants, reflects dietary oxalate intake, net intestinal absorption (accounting for fecal excretion and gut degradation), and endogenous oxalate synthesis from the liver. A lower GFR itself should not affect urinary oxalate excretion at steady state: as GFR decreases and plasma oxalate concentration increases, the filtered load increases such that the excretion rate at steady state is unchanged, provided that the generation rate and extrarenal elimination are unchanged. Our cross-sectional observation of an inverse correlation between urinary oxalate excretion and eGFR cannot be explained, therefore, by increased plasma oxalate concentrations from CKD. Few published data exist on urinary oxalate excretion in CKD. In a study26 of 297 patients with primary hyperoxaluria types 1, 2, and 3 and a median eGFR of 73 mL/min/1.73 m2, urinary oxalate excretion had an inverse association with eGFR at diagnosis (r = −0.13, P = .12), which was similar in magnitude to the association reported here but was not statistically significant. In a study of 403 individuals with a mean eGFR of 77 mL/min/1.73 m2, Gershman et al27 reported lower oxalate excretion across increasing GFR quintiles, but the study included few participants with advanced CKD.
Urinary oxalate in our study was measured by a reference laboratory using the oxalate oxidase assay. We would caution that the absolute values of urinary oxalate reported here may not be comparable to measurements on nonfrozen urine samples or measurements performed in other laboratories. The median value of oxalate excretion in this study is lower than that reported by Taylor and Curhan28 in the Nurses’ Health Studies and Health Professionals Follow-up Study, which measured oxalate in nonfrozen samples and used a different laboratory for oxalate measurement. There is considerable interlaboratory variability in urinary oxalate measurements.29 Prolonged storage of our samples at −80°C could have led to calcium oxalate precipitation and underestimation of oxalate levels; alternatively, spontaneous oxalate generation over time could increase levels. However, the samples were vigorously shaken before aliquoting and then acidified before being assayed so oxalate that had been in crystals would have been measured. The values for urinary calcium excretion rate previously reported in the CRIC study are also substantially lower than reference ranges30 and could reflect true differences in calcium metabolism in CKD and/or some degree of artifact that results from measurements in frozen samples. Our results on the prospective associations of urinary oxalate excretion with CKD progression and ESRD should not be biased, however, if the relative rank ordering remained intact. The internal validity of our results is supported by consistency with the reported literature on the associations with oxalate excretion. We found that oxalate excretion was higher with higher BMI, in diabetes, and in men, which has been reported previously in non-CKD studies.28,31,32 Our cross-sectional findings of an association between higher urinary oxalate excretion with lower urinary calcium excretion and lower serum calcium concentration, even after adjustment for eGFR, has not, to our knowledge, been reported previously and could reflect the effect of dietary calcium on oxalate absorption.28,33,34
Higher urinary oxalate excretion is also associated with progressive kidney failure in primary hyperoxaluria, with an apparent threshold effect at 140 mg/24 hours.26 We also found an apparent threshold effect in adjusted proportional hazards models, albeit at a far lower level of oxalate excretion. Whether the findings of an oxalate threshold reflect an underlying biological phenomenon or a measurement error attributable to biological or assay variability is not clear. Within-person biological variability of urinary oxalate excretion could be attenuating the signal between oxalate excretion and CKD progression.
Several limitations should be considered in interpreting our findings. We measured urinary oxalate excretion at only one time point and did not measure urinary citrate or plasma oxalate concentration. We could not determine the dietary vs metabolic vs gut contributions to oxalate balance or whether CKD itself leads to metabolic or intestinal alterations that affect urinary oxalate excretion. The CRIC study did not ascertain self-reported history of nephrolithiasis or record or require kidney biopsies for assessment of oxalate nephropathy or renal ultrasonography for assessment of nephrocalcinosis or nephrolithiasis. Finally, unmeasured or residual confounding is also always a possibility in prospective observational cohort studies. Given the attenuation of the strength of the signal with multivariable adjustment, it would be premature to recommend, for example, low-oxalate diets to all individuals with CKD. The absence of a dose-response association between higher oxalate excretion quintiles and CKD progression could also argue against oxalate as a potential therapeutic target to prevent CKD progression.
Our results are the first, to our knowledge, to show urinary oxalate excretion as a potential risk factor for progression in common forms of CKD. Oxalate nephropathy is not always suspected in individuals with CKD, even among those with a history of nephrolithiasis: there are several case reports35-37 of primary (autosomal-recessive) hyperoxaluria being diagnosed after dialysis initiation or transplantation. Secondary oxalate nephropathy is occasionally identified in patients with unexplained acute kidney injury or CKD,6,38-41 but the true prevalence of oxalate nephropathy is unknown. In a retrospective report42 of native kidney biopsies, the prevalence of oxalate deposition was only 61 of 5160 (1.18%). However, the extent of underascertainment is unclear because polarized light microscopy is required for calcium oxalate crystal detection and is not always used routinely. Biopsy-based studies also are not representative of the overall population of individuals with CKD, most of whom do not typically undergo biopsy. In 1 autopsy-based study,42 the prevalence of oxalate deposition in kidneys from patients with non–dialysis-requiring CKD was more than 80%, but these individuals had advanced CKD and are also not representative of the overall population with CKD. Whether any CRIC study participants in this study have primary or secondary oxalate nephropathy is not clear from our data.
There is clinical plausibility to our findings of oxalate as a risk factor for CKD progression, considering the fact that rare genetic diseases of oxalate overproduction, enteric hyperoxaluria, and ethylene glycol ingestion are all well-recognized causes of kidney failure.2,6 There is also biological plausibility to our findings based on animal model data and tissue culture data showing multiple mechanisms for oxalate to cause kidney injury.9,10,19 In conclusion, we found that higher urinary oxalate excretion may be a novel risk factor for CKD progression. If our results are confirmed, future research on pharmacologic or dietary measures to limit oxalate absorption and/or generation would be required to evaluate whether lowering urinary oxalate excretion is beneficial in CKD.
Accepted for Publication: November 20, 2018.
Corresponding Author: Sushrut S. Waikar, MD, MPH, Division of Renal Medicine, Brigham and Women’s Hospital, Harvard Medical School, 75 Francis St, Medical Research Bldg, Fourth Floor, Boston, MA 02115 (email@example.com).
Published Online: March 4, 2019. doi:10.1001/jamainternmed.2018.7980
Author Contributions: Dr Waikar had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.
Concept and design: Waikar, Palsson, Hsu, He, Lieske, Curhan.
Acquisition, analysis, or interpretation of data: Srivastava, Palsson, Shafi, Hsu, Sharma, Lash, Chen, He, Lieske, Xie, Zhang, Feldman, Curhan.
Drafting of the manuscript: Waikar, Sharma, Lash.
Critical revision of the manuscript for important intellectual content: All authors.
Statistical analysis: Waikar, Srivastava, Palsson, Shafi, Chen, Xie, Zhang, Curhan.
Obtained funding: Waikar, Hsu, He, Feldman, Curhan.
Administrative, technical, or material support: Waikar, Palsson, Hsu, Lash, Lieske, Curhan.
Supervision: Waikar, Sharma, He.
Conflict of Interest Disclosures: Dr Waikar reported receiving grants from National Institutes of Health during the conduct of the study and grants and personal fees from Allena outside the submitted work. Dr Shafi reported receiving grants from the National Institutes of Health during the conduct of the study. Dr Hsu reported receiving grants from the National Institutes of Health during the conduct of the study. Dr Feldman reported receiving grants from the National Institutes of Health and personal fees from Kyowa Hakko Kirin Com and the National Kidney Foundation during the conduct of the study. Dr Curhan reported receiving grants, personal fees, and other from Allena Pharmaceuticals, personal fees from Shire, and other from UpToDate during the conduct of the study and personal fees from AstraZeneca and grants from Shoebox Audiometry outside the submitted work. No other disclosures were reported.
Funding/Support: This study was supported by grant R01DK103784 from National Institutes of Health (NIH)/National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) (Dr Waikar). Funding for the Chronic Renal Insufficiency Cohort study was obtained from grants U01DK060990, U01DK060984, U01DK061022, U01DK061021, U01DK061028, U01DK060980, U01DK060963, and U01DK060902 under a cooperative agreement from NIDDK. In addition, this work was supported in part by Clinical and Translational Science Award NIH/National Center for Advancing Translational Science UL1TR000003 from the Perelman School of Medicine at the University of Pennsylvania, grant UL1 TR-000424 from Johns Hopkins University, grant M01 RR-16500 from the General Clinical Research Center, University of Maryland, the Clinical and Translational Science Collaborative of Cleveland, grant UL1TR000439 from the National Center for Advancing Translational Sciences component of the NIH and the NIH roadmap for Medical Research, grant UL1TR00043 from the Michigan Institute for Clinical and Health Research Center, Clinical and Translational Science Award UL1RR029879 from University of Illinois at Chicago, grant P20 GM109036 from Tulane Center of Biomedical Research Excellence for Clinical and Translational Research in Cardiometabolic Diseases, and grant UL1 RR-024131 from Kaiser Permanente, NIH/National Center for Research Resources, University of California, San Francisco, Clinical & Translational Science Institute.
Role of the Funder/Sponsor: The funding sources had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.
Group Members: The Chronic Renal Insufficiency Cohort study investigators are Lawrence J. Appel, MD, MPH, Johns Hopkins Bloomberg School of Public Health, Alan S. Go, MD, Kaiser Permanente Northern California John W. Kusek, PhD, National Institutes of Diabetes Digestive and Kidney Diseases, Panduranga Rao, MBBS, University of Michigan Hospital and Health Systems, Mahboob Rahman, MD, Case Western Reserve University, School of Medicine, and Raymond R. Townsend, MD, University of Pennsylvania, Perelman School of Medicine.