Glycolytic lactate in diabetic kidney disease.

Lactate elevation is a well-characterized biomarker of mitochondrial dysfunction, but its role in diabetic kidney disease (DKD) is not well defined. Urine lactate was measured in patients with type 2 diabetes (T2D) in 3 cohorts (HUNT3, SMART2D, CRIC). Urine and plasma lactate were measured during euglycemic and hyperglycemic clamps in participants with type 1 diabetes (T1D). Patients in the HUNT3 cohort with DKD had elevated urine lactate levels compared with age- and sex-matched controls. In patients in the SMART2D and CRIC cohorts, the third tertile of urine lactate/creatinine was associated with more rapid estimated glomerular filtration rate decline, relative to first tertile. Patients with T1D demonstrated a strong association between glucose and lactate in both plasma and urine. Glucose-stimulated lactate likely derives in part from proximal tubular cells, since lactate production was attenuated with sodium-glucose cotransporter-2 (SGLT2) inhibition in kidney sections and in SGLT2-deficient mice. Several glycolytic genes were elevated in human diabetic proximal tubules. Lactate levels above 2.5 mM potently inhibited mitochondrial oxidative phosphorylation in human proximal tubule (HK2) cells. We conclude that increased lactate production under diabetic conditions can contribute to mitochondrial dysfunction and become a feed-forward component to DKD pathogenesis.

Metabolic Analysis and Renal Protective Effects of Linagliptin and Empagliflozin in Alport Syndrome.

BACKGROUND: We previously demonstrated that Empagliflozin (Empa), a sodium-glucose cotransporter-2 (SGLT2) inhibitor, reduces intrarenal lipid accumulation and slows kidney function decline in experimental Alport syndrome (AS). In this study, we aimed to evaluate the renal protective benefits of Linagliptin (Lina), a dipeptidyl peptidase-4 (DPP4) inhibitor in AS and compare it to Empa. METHODS: Metabolite distribution in kidney cortices was assessed using mass spectrometry imaging. We examined albuminuria and histological changes in kidneys from AS mice treated with Lina and/or Empa or vehicle. RESULTS: Several metabolites, including adrenic acid (AdA) and glucose, were increased in renal cortices of AS mice when compared to wildtype (WT) mice, while eicosapentaenoic acid (EPA) levels were decreased. In addition, a redistribution of AdA from the glomerular compartment in WT mice to the tubulointerstitial compartment in AS mice was observed. Both Lina and Empa treatments were found to reduce albuminuria, to extend the survival of AS mice for about 10 days, and to decrease glomerulosclerosis and tubulointerstitial fibrosis compared to WT mice. There were no significant differences with regard to the renal phenotype observed between Empa and Lina treated AS mice, and the combination of Lina and Empa was not superior to individual treatments. In vitro experiments revealed that DPP4 is expressed in podocytes and tubular cells derived from both AS and WT mice. Differently from what we have reported for Empa, Lina treatment was found to reduce glucose-driven respiration in AS tubular cells, but not in AS podocytes. CONCLUSIONS: Renal expression patterns and spatial distribution of several metabolites differ in AS compared to WT mice. While Lina and Empa treatments similarly partially slow the progression of kidney disease in AS, the metabolic mechanisms conferring the protective effect may be different.

Quinolinic acid links kidney injury to brain toxicity.

Kidney dysfunction often leads to neurological impairment, yet the complex kidney-brain relationship remains elusive. We employed spatial and bulk metabolomics to investigate a mouse model of rapid kidney failure induced by mouse double minute 2 ( Mdm2) conditional deletion in the kidney tubules to interrogate kidney and brain metabolism. Pathway enrichment analysis of focused plasma metabolomics panel pinpointed tryptophan metabolism as the most altered pathway with kidney failure. Spatial metabolomics showed toxic tryptophan metabolites in the kidneys and brains, revealing a novel connection between advanced kidney disease and accelerated kynurenine degradation. In particular, the excitotoxic metabolite quinolinic acid was localized in ependymal cells adjacent to the ventricle in the setting of kidney failure. These findings were associated with brain inflammation and cell death. A separate mouse model of acute kidney injury also had an increase in circulating toxic tryptophan metabolites along with altered brain inflammation. Patients with advanced CKD similarly demonstrated elevated plasma kynurenine metabolites and quinolinic acid was uniquely correlated with fatigue and reduced quality of life in humans. Overall, our study identifies the kynurenine pathway as a bridge between kidney decline, systemic inflammation, and brain toxicity, offering potential avenues for diagnosis and treatment of neurological issues in kidney disease.

SUPPRESION OF MITOCHONDRIAL RESPIRATION IS A FEATURE OF CELLULAR GLUCOSE TOXICITY.

Glucose toxicity is central to the myriad complications of diabetes and is now believed to encompass neurodegenerative diseases and cancer as well as microvascular and macrovascular disease. Due to the widespread benefits of SGLT2 inhibitors, which affect glucose uptake in the kidney proximal tubular cell, a focus on cell metabolism in response to glucose has important implications for overall health. We previously found that a -Warburg-type effect underlies diabetic kidney disease and involves metabolic reprogramming. This is now supported by quantitative measurements of superoxide measurement in the diabetic kidney and systems biology analysis of urine metabolites in patients. Further exploration of mechanisms underlying mediators of mitochondrial suppression will be critical in understanding the chronology of glucose-induced toxicity and developing new therapeutics to arrest the systemic glucose toxicity of diabetes.

Endogenous adenine mediates kidney injury in diabetic models and predicts diabetic kidney disease in patients.

Diabetic kidney disease (DKD) can lead to end-stage kidney disease (ESKD) and mortality; however, few mechanistic biomarkers are available for high-risk patients, especially those without macroalbuminuria. Urine from participants with diabetes from the Chronic Renal Insufficiency Cohort (CRIC) study, the Singapore Study of Macro-angiopathy and Micro-vascular Reactivity in Type 2 Diabetes (SMART2D), and the American Indian Study determined whether urine adenine/creatinine ratio (UAdCR) could be a mechanistic biomarker for ESKD. ESKD and mortality were associated with the highest UAdCR tertile in the CRIC study and SMART2D. ESKD was associated with the highest UAdCR tertile in patients without macroalbuminuria in the CRIC study, SMART2D, and the American Indian study. Empagliflozin lowered UAdCR in nonmacroalbuminuric participants. Spatial metabolomics localized adenine to kidney pathology, and single-cell transcriptomics identified ribonucleoprotein biogenesis as a top pathway in proximal tubules of patients without macroalbuminuria, implicating mTOR. Adenine stimulated matrix in tubular cells via mTOR and stimulated mTOR in mouse kidneys. A specific inhibitor of adenine production was found to reduce kidney hypertrophy and kidney injury in diabetic mice. We propose that endogenous adenine may be a causative factor in DKD.

Role of endogenous adenine in kidney failure and mortality with diabetes.

Diabetic kidney disease (DKD) can lead to end-stage kidney disease (ESKD) and mortality, however, few mechanistic biomarkers are available for high risk patients, especially those without macroalbuminuria. Urine from participants with diabetes from Chronic Renal Insufficiency Cohort (CRIC), Singapore Study of Macro-Angiopathy and Reactivity in Type 2 Diabetes (SMART2D), and the Pima Indian Study determined if urine adenine/creatinine ratio (UAdCR) could be a mechanistic biomarker for ESKD. ESKD and mortality were associated with the highest UAdCR tertile in CRIC (HR 1.57, 1.18, 2.10) and SMART2D (HR 1.77, 1.00, 3.12). ESKD was associated with the highest UAdCR tertile in patients without macroalbuminuria in CRIC (HR 2.36, 1.26, 4.39), SMART2D (HR 2.39, 1.08, 5.29), and Pima Indian study (HR 4.57, CI 1.37-13.34). Empagliflozin lowered UAdCR in non-macroalbuminuric participants. Spatial metabolomics localized adenine to kidney pathology and transcriptomics identified ribonucleoprotein biogenesis as a top pathway in proximal tubules of patients without macroalbuminuria, implicating mammalian target of rapamycin (mTOR). Adenine stimulated matrix in tubular cells via mTOR and stimulated mTOR in mouse kidneys. A specific inhibitor of adenine production was found to reduce kidney hypertrophy and kidney injury in diabetic mice. We propose that endogenous adenine may be a causative factor in DKD.

A reference tissue atlas for the human kidney.

Kidney Precision Medicine Project (KPMP) is building a spatially specified human kidney tissue atlas in health and disease with single-cell resolution. Here, we describe the construction of an integrated reference map of cells, pathways, and genes using unaffected regions of nephrectomy tissues and undiseased human biopsies from 56 adult subjects. We use single-cell/nucleus transcriptomics, subsegmental laser microdissection transcriptomics and proteomics, near-single-cell proteomics, 3D and CODEX imaging, and spatial metabolomics to hierarchically identify genes, pathways, and cells. Integrated data from these different technologies coherently identify cell types/subtypes within different nephron segments and the interstitium. These profiles describe cell-level functional organization of the kidney following its physiological functions and link cell subtypes to genes, proteins, metabolites, and pathways. They further show that messenger RNA levels along the nephron are congruent with the subsegmental physiological activity. This reference atlas provides a framework for the classification of kidney disease when multiple molecular mechanisms underlie convergent clinical phenotypes.

A dataset of distribution of antibiotic occurrence in solid environmental matrices in China.

While there is growing global concern about the impact of antibiotic residues on emergence and enhancement bacteria's resistance, toxicity to natural organisms, and, ultimately, public health, a concise picture of measured environmental concentrations of antibiotic occurrence in multiple environmental matrices, particularly in solid matrices (e.g., sludge, soil, and sediments) is still elusive, especially for China. In this paper, we present an up-to-date dataset of the distribution of antibiotic occurrence in solid environmental matrices in China, derived from 210 peer-reviewed literature published between 2000 and 2020. We extracted geographical sampling locations and measured concentration associated with antibiotic occurrence reported in English and Chinese original publications, and applied quality-control procedures to remove duplicates and ensure accuracy. The dataset contains 6929 records of geo-referenced occurrences for 135 antibiotics distributed over 391 locations distinguished at four levels of scale i.e., provincial, prefectural, county, and township or finer. The geographical dataset provides an updated map of antibiotic occurrence in solid environmental matrices in China and can be used for further environmental health risk assessment.

Identification of Serum-Predictive Biomarkers for Subclinical Mastitis in Dairy Cows and New Insights into the Pathobiology of the Disease.

Targeted direct injection/liquid chromatography coupled to tandem mass spectrometry-based metabolomics was employed to identify metabolite alterations that could differentiate subclinical mastitis (SCM) from control (CON) dairy cows at -8, -4, disease diagnosis, +4 and +8 wks relative to parturition. We identified and measured 128 metabolites in the serum. Univariate analysis revealed significant alterations of serum metabolites at all five time points studied. By applying multivariate analyses including principle component analysis and partial least squares-discriminant analysis, some of the metabolites were found to have the strongest power for discriminating the SCM from CON cows. The top five metabolites with the greatest variable importance in projection values were selected as potential biomarkers for SCM. A set of five serum metabolites including lysine, ornithine, isoleucine, LysoPC a C17:0, and leucine at -8 wks and five other metabolites including lysine, leucine, isoleucine, kynurenine, and sphingomyelin (SM) C26:0 at -4 wks prepartum were determined as predictive biomarkers for SCM, which provided highly predictive capabilities with AUC (area under the curve) at 1.00. Five metabolites including lysine, leucine, isoleucine, kynurenine, and SM C26:1 in the serum were identified as diagnostic biomarkers for SCM with the AUC of 1.00. Moreover, we observed that distinct metabolic pathways were affected in SCM cows including lysine degradation, biotin, cysteine, methionine, and glutathione metabolism, valine, leucine, and isoleucine biosynthesis and degradation, and aminoacyl-tRNA biosynthesis prior to and during the occurrence of the disease. Results of this study showed that metabolomics analyses can be used to identify susceptible cows to SCM starting from -8 and -4 wks prepartum and that blood can be used to diagnose cows with SCM.

A Targeted Serum Metabolomics GC-MS Approach Identifies Predictive Blood Biomarkers for Retained Placenta in Holstein Dairy Cows.

The retained placenta is a common pathology of dairy cows. It is associated with a significant drop in the dry matter intake, milk yield, and increased susceptibility of dairy cows to metritis, mastitis, and displaced abomasum. The objective of this study was to identify metabolic alterations that precede and are associated with the disease occurrence. Blood samples were collected from 100 dairy cows at -8 and -4 weeks prior to parturition and on the day of retained placenta, and only 16 healthy cows and 6 cows affected by retained placenta were selected to measure serum polar metabolites by a targeted gas chromatography-mass spectroscopy (GC-MS) metabolomics approach. A total of 27 metabolites were identified and quantified in the serum. There were 10, 18, and 17 metabolites identified as being significantly altered during the three time periods studied. However, only nine metabolites were identified as being shared among the three time periods including five amino acids (Asp, Glu, Ser, Thr, and Tyr), one sugar (myo-inositol), phosphoric acid, and urea. The identified metabolites can be used as predictive biomarkers for the risk of retained placenta in dairy cows and might help explain the metabolic processes that occur prior to the incidence of the disease and throw light on the pathomechanisms of the disease.

A Multi-Platform Metabolomics Approach Identifies Urinary Metabolite Signatures That Differentiate Ketotic From Healthy Dairy Cows.

Ketosis and subclinical ketosis are widespread among dairy cows especially after calving. Etiopathology of ketosis has been related to negative energy balance. The objective of this study was to investigate metabolite fingerprints in the urine of pre-ketotic, ketotic, and post-ketotic cows to identify potential metabolite alterations that can be used in the future to identify susceptible cows for ketosis and metabolic pathways involved in the development of disease. In this study, NMR, DI/LC-MS/MS, and GC-MS-based metabolomics were used to analyze urine samples from 6 cows diagnosed with ketosis and 20 healthy control (CON) cows at -8 and -4 weeks prepartum, the week (+1 to +3) of ketosis diagnosis, and at +4 and +8 weeks after parturition. Univariate and multivariate analyses were used to screen metabolite panels that can identify cows at their pre-ketotic stage. A total of 54, 42, 48, 16, and 31 differential metabolites between the ketotic and CON cows were identified at -8 and -4 weeks prepartum, ketosis week, and at +4, and +8 weeks postpartum, respectively. Variable importance in projection (VIP) plots ranked the most significant differential metabolites, which differentiated ketotic cows from the CON ones. Additionally, several metabolic pathways that are related to ketosis were identified. Moreover, two promising metabolite panels were identified which clearly separated ketotic from CON cows with excellent level of sensitivity and specificity. Overall, multiple urinary metabolite alterations were identified in pre-ketotic, ketotic, and post-ketotic cows. The metabolite panels identified need to be validated in the future in a larger cohort of animals.

A multimodal and integrated approach to interrogate human kidney biopsies with rigor and reproducibility: guidelines from the Kidney Precision Medicine Project.

Comprehensive and spatially mapped molecular atlases of organs at a cellular level are a critical resource to gain insights into pathogenic mechanisms and personalized therapies for diseases. The Kidney Precision Medicine Project (KPMP) is an endeavor to generate three-dimensional (3-D) molecular atlases of healthy and diseased kidney biopsies by using multiple state-of-the-art omics and imaging technologies across several institutions. Obtaining rigorous and reproducible results from disparate methods and at different sites to interrogate biomolecules at a single-cell level or in 3-D space is a significant challenge that can be a futile exercise if not well controlled. We describe a "follow the tissue" pipeline for generating a reliable and authentic single-cell/region 3-D molecular atlas of human adult kidney. Our approach emphasizes quality assurance, quality control, validation, and harmonization across different omics and imaging technologies from sample procurement, processing, storage, shipping to data generation, analysis, and sharing. We established benchmarks for quality control, rigor, reproducibility, and feasibility across multiple technologies through a pilot experiment using common source tissue that was processed and analyzed at different institutions and different technologies. A peer review system was established to critically review quality control measures and the reproducibility of data generated by each technology before their being approved to interrogate clinical biopsy specimens. The process established economizes the use of valuable biopsy tissue for multiomics and imaging analysis with stringent quality control to ensure rigor and reproducibility of results and serves as a model for precision medicine projects across laboratories, institutions and consortia.

Storage Conditions of Human Kidney Tissue Sections Affect Spatial Lipidomics Analysis Reproducibility.

Lipids often are labile, unstable, and tend to degrade overtime, so it is of the upmost importance to study these molecules in their most native state. We sought to understand the optimal storage conditions for spatial lipidomic analysis of human kidney tissue sections. Specifically, we evaluated human kidney tissue sections on several different days throughout the span of a week using our established protocol for elucidating lipids using high mass resolution matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI). We studied kidney tissue sections stored under five different conditions: open stored at -80 °C, vacuumed sealed and stored at -80 °C, with matrix preapplied before storage at -80 °C, under a nitrogen atmosphere and stored at -80 °C, and at room temperature in a desiccator. Results were compared to data obtained from kidney tissue sections that were prepared and analyzed immediately after cryosectioning. Data was processed using METASPACE. After a week of storage, the sections stored at room temperature showed the largest amount of lipid degradation, while sections stored under nitrogen and at -80 °C retained the greatest number of overlapping annotations in relation to freshly cut tissue. Overall, we found that molecular degradation of the tissue sections was unavoidable over time, regardless of storage conditions, but storing tissue sections in an inert gas at low temperatures can curtail molecular degradation within tissue sections.

Serum metabolomics identifies metabolite panels that differentiate lame dairy cows from healthy ones.

INTRODUCTION: Although much is known about lameness application of metabolomics technologies to better understanding its etiology and pathogenesis is of utmost interest. OBJECTIVES: The objective of this study was to investigate serum metabolite alterations in pre-lame, lame and post-lame dairy cows in order to identify potential screening serum metabolite biomarkers for lameness and better understand its pathobiology. METHODS: A combination of direct injection and tandem mass spectrometry (DI-MS/MS) with a reverse-phase liquid chromatography and tandem mass spectrometry (LC-MS/MS) analysis was performed in the serum of six cases of lameness and 20 healthy control cows (CON) at - 8 and - 4 weeks prepartum, at lameness diagnosis week, and at + 4 and + 8 weeks postpartum. RESULTS: Data indicated that pre-lame, lame, and post-lame cows experienced altered concentrations of multiple metabolites. It is interesting to note that throughout the 16-weeks of the study, 7 serum metabolites [e.g., diacyl-phosphatidylcholine (PC aa) C30:0, phosphatidylcholine acyl-alkyl (PC ae) C40:2, sphingomyelin (SM) (OH) C14:1, SM C18:0, isoleucine (Ile), leucine (Leu), and lysine (Lys)] differentiated CON cows from the lame ones. Furthermore, 4 metabolic pathways (i.e., Lys degradation, biotin metabolism, tryptophan (Trp) metabolism, and valine [(Val)-Leu-Ile degradation) were altered in cows with lameness during the onset and progression of the disease. CONCLUSION: Multiple metabolite and pathway alterations were identified in the serum of pre-lame, lame, and post-lame cows that through light into the pathobiology of the disease and that can be used as potential biomarker sets that can predict the risk of lameness in dairy cows.

Formation and stability of biogenic tooeleite during Fe(II) oxidation by Acidithiobacillus ferrooxidans.

Tooeleite is the only known ferric arsenite sulfate mineral and has environmental significance for arsenic remediation. This study investigated the formation and stability of biogenic tooeleite in Fe(II)-As(III)-SO42- environment using Acidithiobacillus ferrooxidans under the ambient conditions. The results show that bacteria facilitated the formation and crystallization of tooeleite owing to the microbial oxidation of Fe(II) to Fe(III). Due to the better growth of bacteria, the higher removal of As(III) by tooeleite formation was achieved under 8.978-10.806 g/L initial Fe(II) concentration and 2.00-3.00 initial pH, and the highest efficiency was ~95%. Fe(III) and As(III) precipitated simultaneously into two types of tooeleite. The relatively stable tooeleite is featured by the developed (020) crystal face and the bulk-like structure with thick flakes. This study yields a better understanding of biogenic tooeleite, and the importance of tooeleite formation in As(III)-rich environment for arsenic remediation.

Restoring mitochondrial superoxide levels with elamipretide (MTP-131) protects db/db mice against progression of diabetic kidney disease.

Exposure to chronic hyperglycemia because of diabetes mellitus can lead to development and progression of diabetic kidney disease (DKD). We recently reported that reduced superoxide production is associated with mitochondrial dysfunction in the kidneys of mouse models of type 1 DKD. We also demonstrated that humans with DKD have significantly reduced levels of mitochondrion-derived metabolites in their urine. Here we examined renal superoxide production in a type 2 diabetes animal model, the db/db mouse, and the role of a mitochondrial protectant, MTP-131 (also called elamipretide, SS-31, or Bendavia) in restoring renal superoxide production and ameliorating DKD. We found that 18-week-old db/db mice have reduced renal and cardiac superoxide levels, as measured by dihydroethidium oxidation, and increased levels of albuminuria, mesangial matrix accumulation, and urinary H2O2 Administration of MTP-131 significantly inhibited increases in albuminuria, urinary H2O2, and mesangial matrix accumulation in db/db mice and fully preserved levels of renal superoxide production in these mice. MTP-131 also reduced total renal lysocardiolipin and major lysocardiolipin subspecies and preserved lysocardiolipin acyltransferase 1 expression in db/db mice. These results indicate that, in type 2 diabetes, DKD is associated with reduced renal and cardiac superoxide levels and that MTP-131 protects against DKD and preserves physiological superoxide levels, possibly by regulating cardiolipin remodeling.

Milk Metabotyping Identifies Metabolite Alterations in the Whole Raw Milk of Dairy Cows with Lameness.

The objective of this study was to evaluate whether whole raw milk originating from Holstein dairy cows affected by lameness alters its composition. A total of 20 healthy control cows and 6 cows diagnosed with lameness were selected out of 100 sampled cows in a nested case control study at 2 weeks postpartum, and whole raw milk samples were collected and analyzed with direct inject/liquid chromatography-tandem mass spectrometry and nuclear magnetic resonance. In total, 168 metabolites were identified and quantified using an in-house mass spectrometry library. A total of 35 of the identified metabolites decreased versus control cows. Only two metabolites (i.e., sn-glycero-3-phosphocholine and phosphatidylethanolamine ae C42:1) were increased in the milk of lame cows. In conclusion, milk metabotyping of lame cows revealed significant changes in multiple milk components, including amino acids, lipids, and biogenic amines. Most of the milk compounds identified as altered were lowered, suggesting deflection of nutrients from the mammary gland to the host needs for healing lameness-associated pathological processes.

Response Surface Methodology As a New Approach for Finding Optimal MALDI Matrix Spraying Parameters for Mass Spectrometry Imaging.

Automated spraying devices have become ubiquitous in laboratories employing matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI), in part because they permit control of a number of matrix application parameters that can easily be reproduced for intra- and interlaboratory studies. Determining the optimal parameters for MALDI matrix application, such as temperature, flow rate, spraying velocity, number of spraying cycles, and solvent composition for matrix application, is critical for obtaining high-quality MALDI-MSI data. However, there are no established approaches for optimizing these multiple parameters simultaneously. Instead optimization is performed iteratively (i.e., one parameter at a time), which is time-consuming and can lead to overall nonoptimal settings. In this report, we demonstrate the use a novel experimental design and the response surface methodology to optimize five parameters of MALDI matrix application using a robotic sprayer. Thirty-two combinations of MALDI matrix spraying conditions were tested, which allowed us to elucidate relationships between each of the application parameters as determined by MALDI-MS (specifically, using a 15 T Fourier transform ion cyclotron resonance mass spectrometer). As such, we were able to determine the optimal automated spraying parameters that minimized signal delocalization and enabled high MALDI sensitivity. We envision this optimization strategy can be utilized for other matrix application approaches and MALDI-MSI analyses of other molecular classes and tissue types.

Mass-spec-based urinary metabotyping around parturition identifies screening biomarkers for subclinical mastitis in dairy cows.

The objective of this study was to determine urinary metabotypes of dairy cows prior to, during, and after diagnosis of subclinical mastitis (SCM). Twenty controls (CON) and 6 cows with SCM were included in the study. DI/LC-MS/MS was used to measure 186 metabolites in the urine at -8 and - 4 wks prepartum, disease diagnosis, and at +4 and + 8 wks postpartum. Results showed a total of 24 and 27 metabolites that differentiated SCM and CON cows at -8 and - 4 wks, respectively, with 5 top metabolites having an accuracy to predict SCM of 1.0, for both time point. Altered metabolites included several acylcarnitines (ACs), phosphatidylcholines (PCs), amino acids (AAs), and biogenic amines (BAs). During SCM diagnosis week there were a total of 22 metabolites that differentiated the SCM and CON cows including 13 ACs, 5 AAs, hexose, and phosphatidylethanolamine ae C44:3. The top 5 metabolites Symmetric dimethylarginine (SDMA), methylglutarylcarnitine, dodecanoylcarnitine, phosphatidylethanolamine ae C42:1, and phosphatidylethanolamine ae C42:0 showed an AUC of 1.0. Metabolite alterations continued at +4 and + 8 wks postpartum with 13 (9 ACs, 3 glycerophospholipids, and 1 BA) and 28 metabolites (14 ACs, 2 glycerophospholipids, hexose, 8 AAs, and 2 BAs) that differentiated the two groups, respectively. The top 5 most important metabolites, for both time points, showed AUCs of 1.0. Results of this study showed that typical urinary metabotypes preceded SCM event starting from -8 and - 4 wks prepartum. Metabotypes typical of SCM continued to be present during the week of SCM and at +4 and + 8 wks postpartum. These data show that the urine of dairy cows can be used with very high accuracy for screening dairy cows for susceptibility to SCM prior to entering into the dry off period and a potential new pen-side test can help dairy producers and veterinarians to make selective treatments.