Patent Application
20250076302
The present invention relates to systems, kits, and methods for identifying subjects with increased levels (e.g., in a urine sample, or sample derived from a urine sample) of at least two urine metabolites selected from: butanal, 2-Hydroxy-1,3-dimethoxy-8,9-methylenedioxycoumestan, 6-Methylmercaptopurine, Dimethyl-L-arginine, N-butanoyl-lhomoserine lactone, Hexanoylglycine, Methyl propenyl ketone, Ferulate, 2-Oxoarginine, and 2-Hydroxyestradiol-3-methyl ether, as well as methods of determining if a subject has or is at risk of urinary stone disease based on such urine metabolites. In certain embodiments, the urinary tract of a subject with elevated levels of at least two of the urine metabolites is imaged (e.g., to generate an image showing the size, location, or number of urinary stones present).
Urinary stone disease (USD) afflicts 1 in 11 Americans and incurs an annual expenditure of approximately $10 billion in healthcare costs1. USD is a chronic disease with long asymptomatic periods and high recurrence rate2. More than 90% of cases involve calcium-based stones (CBS)3, most of which are labeled as idiopathic4. While a few studies have examined the urinary metabolome in the context of USD5, 6, many questions remain about the interactions between urinary metabolites and lithogenesis.
Urine is a source of nearly 5000 metabolites, collectively called the metabolome, many of which have been associated with disease7. Urinary metabolites can come from the host, microbiome7, as well as from the diet or biochemical interactions, and can strongly influence biomineralization8. Similarities in urinary chemistry abnormalities exist among patients with different urinary stone compositions. For instance, low urinary citrate is associated with the development of uric acid or CBS9. Moreover, a prospective study of stone formers with and without radiographic stones demonstrated that USD patients with different stone compositions exhibited a lower urinary concentration of osteopontin10.
The present invention relates to systems, kits, and methods for identifying subjects with increased levels (e.g., in a urine sample, or sample derived from a urine sample) of at least two urine metabolites selected from: butanal, 2-Hydroxy-1,3-dimethoxy-8,9-methylenedioxycoumestan, 6-Methylmercaptopurine, Dimethyl-L-arginine, N-butanoyl-lhomoserine lactone, Hexanoylglycine, Methyl propenyl ketone, Ferulate, 2-Oxoarginine, and 2-Hydroxyestradiol-3-methyl ether (or at least two urine metabolites selected from those recited in Table 5, Appendix A), as well as methods of determining if a subject has or is at risk of urinary stone disease based on such urine metabolites. In certain embodiments, the urinary tract of a subject with elevated levels of at least two of the urine metabolites is imaged (e.g., to generate an image showing the size, location, or number of urinary stones present).
In some embodiments, provided herein are compositions, kits, and systems comprising: a) a sample from a subject (e.g., human subject) having: urinary stone disease, or who is suspected of having urinary stone disease, or who has a recurrent episode of urinary stone disease, and b) at least two stable isotope labeled urine metabolites selected from: butanal, 2-Hydroxy-1,3-dimethoxy-8,9-methylenedioxycoumestan, 6-Methylmercaptopurine, Dimethyl-L-arginine, N-butanoyl-lhomoserine lactone, Hexanoylglycine, Methyl propenyl ketone, Ferulate, 2-Oxoarginine, and 2-Hydroxyestradiol-3-methyl ether; and/or selected from at least two stable isotope labeled urine metabolites selected from Table 5 (Appendix A).
In particular embodiments, the stable isotope is selected from 2H, 13C, and 15N. In other embodiments, the sample comprises a urine sample. The compositions, kits, and systems further comprise: c) un-labelled versions of the at least two urine metabolites. In additional embodiments, the sample further comprises a stable isotope labeled third, fourth, fifth, sixth, seventh, eighth, ninth, or tenth stable isotope labeled urinary metabolite from the recited group.
In certain embodiments, provided herein are methods of performing an activity based on a level of at least two urine metabolites in a urine sample from a subject (e.g., human subject) comprising: a) determining, or receiving information regarding, the level of the at least two urine metabolites in, or from, a urine sample from a subject, wherein the at least two urine metabolites are selected from: butanal, 2-Hydroxy-1,3-dimethoxy-8,9-methylenedioxycoumestan, 6-Methylmercaptopurine, Dimethyl-L-arginine, N-butanoyl-lhomoserine lactone, Hexanoylglycine, Methyl propenyl ketone, Ferulate, 2-Oxoarginine, and 2-Hydroxyestradiol-3-methyl ether; and/or selected from Table 5 (Appendix A); and b) identifying an increased level of the at least two urine metabolites in the sample compared to corresponding control values, and performing at least one of the following activities: i) imaging the urinary tract of the subject and generating an image that shows the size and/or number and/or position of at least one urinary stone; ii) treating the subject with an agent or procedure that treats urinary stone disease; iii) generating and/or transmitting a report that: A) displays the level of the at least two urinary metabolites, and B) indicates that the subject is in need of: A) the imaging, and/or B) the agent or procedure that treat urinary stone disease; and iv) characterizing the subject as having urinary stones, recurrence of urinary stones, urinary stone disease, recurrence of urinary stone disease, having recurrent stone activity, or an elevated risk for urinary stones or urinary stone disease.
In further embodiments, the at least two urine metabolites is at least three, at least four, at least five, at least six, at least seven, at least eight, at least nine, or all ten, of the urine metabolites. In particular embodiments, the imaging is selected from: computed tomography (CT), ultrasound, x-ray, and KUB x-ray; and/or B) the urinary stone disease therapeutic is selected from: thiazide, a potassium supplement, a magnesium supplement, and a calcium supplement; and/or C) wherein the procedure comprises removal of at least one urinary stone from the subject. In additional embodiments, the subject has, or is suspected of having, urinary stone disease, or wherein the subject has, or is suspected of having, recurrent urinary stone disease. In further embodiments, determining the level comprises the use of mass spectrometry with chromatography. In additional embodiments, the urine sample comprises a spot urine sample.
In some embodiments, the report comprises a paper report or an electronic report; and/or wherein the receiving information comprises receiving the report, wherein the receiving the report is optionally via: 1) the mail system, 2) email, or 3) via a LAN of a hospital or clinic. In additional embodiments, the transmitting the report comprises: 1) mailing the reporting through the mail system, 2) emailing the report over the internet, or 3) sending the report through a local area network (LAN) or a hospital or clinic. In additional embodiments, the corresponding control values are derived from samples from the general public or from a group known to not have urinary stone disease or be at risk for urinary stone disease. In further embodiments, the determining comprises detecting the at least two urinary metabolites with an analytical device selected from: a mass spectrometer, NMR spectrometer, and a UV/Vis spectrometer.
In some embodiments, provided herein are methods of treatment and/or imaging comprising: a) identifying a subject as having increased levels of at least two urinary metabolites compared to corresponding reference values, wherein the at least two urinary metabolites are selected from: butanal, 2-Hydroxy-1,3-dimethoxy-8,9-methylenedioxycoumestan, 6-Methylmercaptopurine, Dimethyl-L-arginine, N-butanoyl-lhomoserine lactone, Hexanoylglycine, Methyl propenyl ketone, Ferulate, 2-Oxoarginine, and 2-Hydroxyestradiol-3-methyl ether; and/or selected from Table 5 (Appendix A); and b) performing at least one of the following activities: i) treating the subject with a therapeutic or procedure that treats urinary stone disease, and/or ii) imaging the urinary tract of the subject and generating an image that shows the size and/or number and/or position of at least one urinary stone, and optionally generating a written plan of care tailored to the size, number, and/or position of the at least one urinary stone.
In additional embodiments, the receiving information comprises receiving a report, wherein the receiving the report is optionally via: 1) the mail system, 2) email, or 3) via a LAN of a hospital or clinic. In other embodiments, the at least two urine metabolites is at least three, at least four, at least five, at least six, at least seven, at least eight, at least nine, or all ten, of the urine metabolites. In particular embodiments, wherein: i) the urinary stone disease therapeutic is selected from: thiazide, a potassium supplement, a magnesium supplement, and a calcium supplement, and ii) wherein the written plan comprises instructions for therapeutic treatment, expulsive therapy, and/or surgical intervention to remove the at least one urinary stone, and/or iii) the imaging is selected from: computed tomography (CT), ultrasound, x-ray, and KUB x-ray.
In additional embodiments, the subject (e.g., human subject): i) has, or is suspected of having, urinary stone disease, has recurrence of urinary stones, iii) has recurrence of urinary stone disease, iv) has recurrent stone activity, or v) has an elevated risk for urinary stones or urinary stone disease. In further embodiments, the corresponding control values are derived from samples from the general public or from a group known to not have urinary stone recurrence or active stone disease.
In some embodiments, provide herein are methods of detecting the level of at least two urinary metabolites in, or from a urine sample from a subject comprising: a) obtaining a urine sample, wherein the urine sample is from a human subject suspected of having urinary stone disease or recurrence of urinary stone disease; and b) treating the urine sample, or derivative thereof, under conditions such that the level of the at least two urinary metabolites is determined, wherein the at least two urinary metabolites are selected from: butanal, 2-Hydroxy-1,3-dimethoxy-8,9-methylenedioxycoumestan, 6-Methylmercaptopurine, Dimethyl-L-arginine, N-butanoyl-lhomoserine lactone, Hexanoylglycine, Methyl propenyl ketone, Ferulate, 2-Oxoarginine, and 2-Hydroxyestradiol-3-methyl ether; and/or selected from Table 5 (Appendix A), and c) optionally imaging the urinary tract of the subject, and further optionally generating an image that shows the size, location, or number of urinary stones. In additional embodiments, the treating comprises adding to the sample at least two stable isotope labeled urine metabolites selected from: butanal, 2-Hydroxy-1,3-dimethoxy-8,9-methylenedioxycoumestan, 6-Methylmercaptopurine, Dimethyl-L-arginine, N-butanoyl-lhomoserine lactone, Hexanoylglycine, Methyl propenyl ketone, Ferulate, 2-Oxoarginine, and 2-Hydroxyestradiol-3-methyl ether.
The patent or application file contains at least one drawing executed in color. Copies of this patent or patent application publication with color drawings will be provided by the Office upon request and payment of the necessary fee.
The present invention relates to systems, kits, and methods for identifying subjects with increased levels (e.g., in a urine sample) of at least two urine metabolites selected from: butanal, 2-Hydroxy-1,3-dimethoxy-8,9-methylenedioxycoumestan, 6-Methylmercaptopurine, Dimethyl-L-arginine, N-butanoyl-lhomoserine lactone, Hexanoylglycine, Methyl propenyl ketone, Ferulate, 2-Oxoarginine, and 2-Hydroxyestradiol-3-methyl ether (or at least two urine metabolites selected from Table 5, Appendix A), as well as methods of determining if a subject has or is at risk of urinary stone disease based on such urine metabolites. In certain embodiments, the urinary tract of a subject with elevated levels of at least two of the urine metabolites is imaged (e.g., to generate an image showing the size, location, or number of urinary stones present).
Urinary stone disease (USD) affects more than 11% of the population with half of those individuals exhibiting at least one recurrent episode. Work conducted during development of embodiments herein observed that threshold urinary concentrations of at least 10 known specific small molecules are useful in predicting an active stone burden. As such, provided herein, in some embodiments, is a chromatography-mass spectrometry based assay, using a spot urine collection, to determine if patients have a recurrent kidney stone assay. Such assays, in certain embodiments, may eliminate repeated imaging protocols based on loose guidelines11, which are burdensome, costly, and exposes patients to unnecessary radiation. Furthermore, spot urine samples could be mailed to the clinic so that patients do even need an appointment for follow-up surveillance.
Current follow-up surveillance for patients at risk of recurrent kidney stone formation often involves regular imaging-based studies or 24-hour urine collections. These measures are expensive, difficult to comply with, and can involve the risk of significant radiation exposure. The proposed solutions provide, in some embodiments, a novel diagnostic test, based on a spot urine sample (or other urine sample) that could be mailed in by the patient. Such a test is easy to comply with, does not require an appointment, and is a tiny fraction of the cost to implement than current measures.
In some embodiments, the control values herein (e.g., for each urine metabolites herein) are derived from samples from the general public or from a group known to not have urinary stone disease or be at risk for urinary stone disease. In certain embodiments, levels of the at least two urine metabolites in the sample obtained from the subject may compared to a control value (e.g., to know if a particular urine metabolite is the same, increased, or decreased compared to the control). A control value is, for example, a concentration of a urine metabolite that represents a known or representative amount of an analyte. For example, the control value can be based upon levels of the selected urine metabolites in comparable samples obtained from a reference cohort. In certain embodiments, the reference cohort is the general population. In certain embodiments, the reference cohort is a select population of human subjects. In certain embodiments, the reference cohort is comprised of individuals who have not previously had any signs or symptoms indicating the presence of urinary stone disease. In certain embodiments, the reference cohort includes individuals, who if examined by a medical professional would be characterized as free of symptoms of disease (e.g., urinary stone disease).
The control value is preferably measured using the same units used to characterize the level of the selected urine metabolite obtained from the subject. Thus, if the level of the selected urine metabolite is an absolute value such as the units of the urine metabolite per ml of blood or plasma, the control value is also based upon the units of the urine metabolite per ml of blood or plasma in individuals in the general population or a select population of human subjects.
The control value can take a variety of forms. The control value can be a single cut-off value, such as a median or mean. The control value can be established based upon comparative groups such as where the risk in one defined group is double the risk in another defined group. The control values can be divided equally (or unequally) into groups, such as a low risk group, a medium risk group and a high-risk group, or into quadrants, the lowest quadrant being individuals with the lowest risk the highest quadrant being individuals with the highest risk, and the test subject's risk of having urinary stone disease can be based upon which group his or her test value falls. Control values of the selected urine metabolite in biological samples obtained, such as mean levels, median levels, or “cut-off” levels, are established by assaying a large sample of individuals in the general population or the select population and using a statistical model such as the predictive value method for selecting a positivity criterion or receiver operator characteristic curve that defines optimum specificity (highest true negative rate) and sensitivity (highest true positive rate) as described, for example, in Knapp, R. G., and Miller, M. C. (1992). Clinical Epidemiology and Biostatistics. William and Wilkins, Harual Publishing Co. Malvern, Pa., which is specifically incorporated herein by reference. A “cutoff” value can be determined for each of the urine metabolites that are assayed.
Levels of at least two selected urine metabolites in a subject's biological sample may be compared to a single control value or to a range of control values. In certain embodiments, the at least two urine metabolites are selected from those in Table 5 (Appendix A) or from the following: butanal, 2-Hydroxy-1,3-dimethoxy-8,9-methylenedioxycoumestan, 6-Methylmercaptopurine, Dimethyl-L-arginine, N-butanoyl-lhomoserine lactone, Hexanoylglycine, Methyl propenyl ketone, Ferulate, 2-Oxoarginine, and 2-Hydroxyestradiol-3-methyl ether. If the level of the at least two urine metabolites are greater than the control value or exceeds or is in the upper range of control values, the test subject is at greater risk of developing or having urinary stone disease. In certain embodiments, the extent of the difference between the test subject's at least two urine metabolite levels and control values is also useful for characterizing the extent of the risk and thereby determining which individuals would most greatly benefit from certain therapies. In those cases, where the control value ranges are divided into a plurality of groups, such as the control value ranges for individuals at high risk, average risk, and low risk, the comparison involves determining into which group the test subject's level of the relevant risk predictor falls.
Another type of control value is an internal standard in the sample. An internal standard is a known amount of another compound that can be provided in a sample that can be measured along with the analyte to serve as a reference. The diagnostic methods described herein can also be carried out by determining the levels of at least two selected urine metabolites in a subject's biological sample and comparing them to the amount of an internal standard.
To address questions about the lithogenic potential of the urinary metabolome, we sought to: 1) Characterize the non-crystalline metabolome of CBS and urine of SF with or without radiographic stone appearance; and 2) Delineate hypotheses about the influence of urinary metabolites on lithogenesis. While not limiting the present invention, we hypothesize that specific metabolites within the urinary tract may facilitate stone formation through the direct interaction with mineralized components present in the stones.
Project workflow is presented in
Recruitment of participants
To identify stone metabolites, surgically-extracted stones were collected, washed and sent for composition analysis with infrared spectroscopy. Only CBS were considered for metabolomic analysis, which represent about 90% of all USD cases, to focus hypotheses while covering the most commonly manifested stone types3. Pure CaOx or pure CaPhos stones were used to ensure a clear demarcation in stone composition. No other clinical data was collected.
Population to Delineate Urinary Metabolome of Active Vs. Non-Active Stone Formers
Two independent cohorts were recruited for urine specimens to delineate hypotheses surrounding direct and passive metabolite-stone interactions by focusing on patients with a history of USD that visited the Kidney Stone Clinic at Cleveland Clinic to evaluate stone burden by radiographic imaging. These patients either did or did not exhibit radiographic stone activity with imaging. Recruitment of independent populations for the stone and urine analyses allowed for robust hypothesis testing while removing biases associated with individual variabilities in each cohort. The inclusion criteria were patients of both sexes, >18 years old, any ethnicity, history of ≥1 episodes of USD, any composition of previous calculi, stone free after their latest stone episode (no visible stones on imaging) and patients were to be radiologically evaluated to determine stone activity. Patients without imaging on the same day of urine collection and those with an active urinary tract infection were excluded. For imaging, either ultrasonography or non-contrast enhanced computer tomography (NCCT) was used as requested by the treating physician as part of standard operating procedures. Patients were classified as radiographically active, if stones ≥4 mm were observed on imaging, or non-active if no stone was observed. This stone size threshold was used to overcome the sensitivity limitation of ultrasonography12. Clinical data collected from USD patients were number of previous episodes, method of last episode stone clearance, and time since last USD episode. Given limitations in identifying stone composition based on radiographic imaging, our study is limited to identifying urinary metabolites associated with different types of stones, rather than metabolites specifically linked to CBS. Urine samples were collected and stored based on a established protocol for urine metabolomics research13. To minimize diurnal variation and effect of diet on the urinary metabolome, fasting patients were asked to give the first morning, midstream urine samples the same day of clinical follow-up imaging. Urine samples were stored at 4° C., less than 3 h before centrifuging at 14000 RPM for 5 minutes and saving 1 ml of supernatant at −80° C. until processing. All procedures were approved by the Institutional Review Board of Cleveland Clinic (IRB #18-586).
Urine supernatant and 125 mg of powder-stone samples were diluted 1:4 in a 50% acetonitrile solution containing two internal standards, using previously validated protocols14. Samples were vortexed to solubilize adherent metabolites and centrifuged at 14,000 g for 5 minutes to precipitate proteins and the supernatant recovered. Supernatant of the stone samples was filtered (0.2 micron) to exclude crystalline components. External standards were added to all samples to ensure run consistency. Negative controls including extraction solutions with added standards were run at the beginning, middle, and end of the run. Untargeted metabolomics was performed on an ultra-high performance liquid chromatography tandem mass spectrometry system coupled to a Q
Untargeted metabolomic data is semi-quantitative and requires normalization to a common factor14. As such, data from urine samples were normalized to total creatinine quantified through mass spectrometry and data from stones were normalized to total mass used for extraction. Normalized data were analyzed in Metabolyzer software15. Spectral features were defined by molecular mass and retention time and given putative identification by comparison to metabolites in the curated databases KEGG, HMDB, BioCyc, and LIPIDMAPS15 with validation of identification given by correctly identifying added internal and external standards from mass and retention time. Prior to comparative analyses, metabolites present in negative controls or in fewer than 25% of samples for any one population were removed. Additionally, samples that had concentrations of internal or external standards that deviated more than 1.5 fold from the inter-quartile range for all samples, were removed.
Power analysis to calculate the sample size for the cohort of active or non-active patients for urinary metabolome analysis was conducted in the PWR package in R statistical software using results from a previous urinary metabolome study in patients with or without USD5.
The CBS samples were stratified into CaOx and CaPhos groups based on composition analysis. Urine samples were stratified into radiographically active vs. non-active. Urine specimens collected for metabolomic analysis were collected, processed and assayed in two batches by the same individuals, one year apart. The urinary metabolomic data was corrected for batch effects with the BER package in R16, which uses a linear regression model that identifies the location and scale of batch effects in the metabolomic data.
To determine if the metabolomes differed by sample type, stone composition, or radiographic stone activity, the dissimilarity of whole metabolome was quantified through a binomial dissimilarity matrix analysis17. For stone-urine comparisons, an unweighted analysis, which considers the presence or absence of metabolites, was used given the differences in normalization procedures. For stone-stone or urine-urine comparisons, a weighted analysis, which considers presence or absence of metabolites combined with creatinine-normalized concentration. Dissimilarity between groups was compared by PERMANOVA with 999 permutations, using the Vegan package18 in R.
To determine the specific metabolites that differentiated each group, a permuted Welch's t-test was conducted. All p-values were corrected via the Benjamini-Hochberg18 step-up procedure for false discovery rate (FDR) correction. To delineate either the direct interaction of metabolites with the stone matrix vs. passive uptake, the metabolites significantly enriched in the urine of active or non-active SF were compared to metabolites that were highly prevalent in CaOx or CaPhos stones, defined as present in >80% of samples for each stone composition.
To further validate the relevance of metabolites, we defined threshold concentration values for the metabolites that were both enriched in either the radiographically active or non-active groups and were highly abundant in CaOx or CaPhos stones. Thresholds were quantified by taking the average concentration of the selected metabolites in each group±standard error, then finding the middle value between metabolite concentration in the active population minus standard error and the metabolite concentration in the non-active population plus standard error. Patients with a metabolite concentration above or below the threshold were classified as active or non-active for that metabolite, respectively (
A total of 10 CaOx stones and 13 CaPhos stones were assessed. Additionally, 60 patients were recruited for urinary metabolome analyses with 40 patients exhibiting an active stone burden and 20 non-active patients. Power analysis for the comparison of the urinary metabolome between active and non-active patients revealed an 86% probability of detecting a significant difference in these populations if one exists. Clinical data of the patients recruited for metabolomics of urine specimens are presented in Table 1.
last episode in months, median (IQR)
-59)
for actual diag
graphy
indicates data missing or illegible when filed
Groups did not differ by age, biological sex, method of last stone removal, and time since last active episode, minimizing any biases associated with life history or the natural history of the stones. However, there was a significant difference between groups in the diagnostic imaging modality between groups (Table 1).
Normalized values of raw metabolomic data are provided in Table 3.
The processed and filtered spectral features with number of metabolites in each population and putative identification are presented in Table 4.
The sample metabolomes differed significantly from negative controls and exhibited significantly greater levels of variance compared to duplicate control samples (
Metabolomic profiles stratified by stone type and radiographic stone activity status are presented in
The differences in the metabolomic composition of the stone types were driven by 722 metabolites enriched in either the CaOx or CaPhos stones (
Table 5. Metabolites that were significantly different between groups. Listed are the dataset compared (initial or validation), group the metabolite was enriched in (i.e. CaOx, CaPhos). Table 5 is at Appendix A.
To help delineate potential interactions between the urinary metabolome and stone burden, we cross-referenced metabolites significantly enriched in the urine of active and non-active SF to those that were highly prevalent in CaOx or CaPhos stones, defined as being present in >80% of stone samples. The 80% threshold was selected to focus only on metabolites strongly associated with the stone matrix. This approach revealed that of the 73 metabolites enriched in active SF, 27 were highly prevalent in CaOx stones and 14 in CaPhos stones. All 14 highly prevalent metabolites in CaPhos stones were also highly prevalent in CaOx stones (Table 2).
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4.33
.
7.37
7.28
.05
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0.67
0.64
0.64
72
.91
7
1.65
7
.
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0.48
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indicates data missing or illegible when filed
In contrast, none of the metabolites enriched in the non-active SF were found to be highly prevalent in either CaOx or CaPhos stones (Table 2). Ten of the 14 metabolites that were significantly enriched in the urine of active SF and highly prevalent in CBS were putatively identified (Table 2). To further validate that these specific metabolites could be drivers of stone activity, we developed a predictive radiographic activity assay after establishing threshold values for metabolite concentrations using data from the initial cohort (
Case-control studies have revealed significant differences in the whole metabolome between individuals with an active episode of USD and those with no history of the disease5, 6. The current study sought to delineate hypotheses about urinary metabolites present in the stone matrix, as potential promoters of lithogenesis or as passive components absorbed into organic matrix of the stone. Several metabolomic characteristics distinguish the alternative hypotheses. Under the direct promoter hypothesis, we would expect unique metabolomes between CaOx and CaPhos stones. In contrast, under the passive absorption hypothesis, we would expect no such metabolomic differences. Here we show clear differences in the metabolome of CaOx vs. CaPhos stones, which supports the direct promoter hypothesis (
The second characteristic that distinguishes the direct promoter and passive absorption hypotheses refers to differences in the urinary metabolome of individuals with a history of USD, with or without radiographic stone activity. We observed a significant difference in the urinary metabolome profile based on the radiographic presence of a stone (
To validate the passive uptake hypothesis, we compared the metabolites significantly enriched in the urine of active vs. non-active SF to those that were highly prevalent in the CBS. With this analysis, under the stone promoter hypothesis, we expect to see an overlap of metabolites enriched in the urine of patients with radiographic activity and those that are highly prevalent in the stones, with the assumption that higher levels of stone-promoting urinary metabolites would facilitate urinary stone development. In contrast, with passive absorption, we would expect that stones will become part of the stone matrix without promoting lithogenesis. This would produce the counter-intuitive result that there would be an overlap in metabolites enriched in non-active SF and those that are highly prevalent in stones. Comparison of metabolites differing between active and non-active SF clearly favored the stone-promoter hypothesis (Table 2), such that there was an overlap of several of the metabolites present in the group with stone activity and the metabolites highly prevalent in stones, but there was no overlap between the metabolites in the non-active group and the metabolites prevalent in stones. These results are in contrast to the interpretation achieved using the urine metabolome data alone, but consistent with the comparative stone metabolome data. Collectively, results suggest that the urine of active SF has a higher concentration of potentially lithogenic metabolites than non-active SF.
Among the potentially lithogenic metabolites identified, ten were given putative identification. Of these, butanal21, N-butanoyl-lhomoserine lactone22, and methyl-propenyl-ketone23 have been correlated with pathogenic bacteria activity, supporting a potential role of the urinary microbiome in stone formation7. Six metabolites were of apparent host origins. These include the metabolite 6-methylmercaptopurine, which has previously been associated with lithogenic activity24. Hexanolglycine has been closely linked with metabolic syndrome25. Two of the metabolites are involved in estrogen metabolism pathways, 2-hydroxyestradiol-3-methyl ether, and methylenedioxycoumestan26. Previous work has demonstrated that renal cells treated with estrogen exhibit reduced CaOx crystal binding which may contribute to stone prevention27, so weaker estrogenic activity represented by these metabolites could be associated with a diminished protective effect of estrogen. Two additional metabolites were derivatives of arginine, dimethyl-L-arginine and 2-oxoarginine. Dimethyl-L-arginine is a biomarker of proteolysis28 and high levels are associated with chronic kidney disease, end-stage renal disease, and coronary calcifications29. The metabolite 2-oxoarginine is formed during the catabolism of arginine and has been linked to sepsis in rodent models30. Ferulate is ubiquitously produced in plants and likely represents some residuals from the diet31. Future studies will need to address the causality of the metabolites identified here for stone formation.
The metabolome of CaOx vs. CaPhos stones differs significantly, as does the urinary metabolome of radiologically active and non-active SF. Collectively, our data suggest that stone activity may be driven by high levels of lithogenic metabolites in the urinary tract that can potentially promote lithogenesis.
Journal of clinical medicine, 9: 1843-1862, 2020
All publications and patents mentioned in the present application are herein incorporated by reference. Various modification and variations of the described methods and compositions of the invention will be apparent to those skilled in the art without departing from the scope and spirit of the invention. Although the invention has been described in connection with specific preferred embodiments, it should be understood that the invention as claimed should not be unduly limited to such specific embodiments. Indeed, various modifications of the described modes for carrying out the invention that are obvious to those skilled in the relevant fields are intended to be within the scope of the following claims.
The present application claims priority to U.S. Provisional application Ser. No. 63/507,665, filed Jun. 12, 2023, which is herein incorporated by reference in its entirety.
This invention was made with government support under DK136517 awarded by the National Institutes of Health. The government has certain rights in the invention.
| Number | Date | Country | |
|---|---|---|---|
| 63507665 | Jun 2023 | US |
