Metabolite Profiles Predict Acute Kidney Injury and Mortality in Patients Undergoing Transcatheter Aortic Valve Replacement

Gut microbiome-metabolome interactions predict host condition

BACKGROUND

The effect of microbes on their human host is often mediated through changes in metabolite concentrations. As such, multiple tools have been proposed to predict metabolite concentrations from microbial taxa frequencies. Such tools typically fail to capture the dependence of the microbiome-metabolite relation on the environment.

RESULTS

We propose to treat the microbiome-metabolome relation as the equilibrium of a complex interaction and to relate the host condition to a latent representation of the interaction between the log concentration of the metabolome and the log frequencies of the microbiome. We develop LOCATE (Latent variables Of miCrobiome And meTabolites rElations), a machine learning tool to predict the metabolite concentration from the microbiome composition and produce a latent representation of the interaction. This representation is then used to predict the host condition. LOCATE's accuracy in predicting the metabolome is higher than all current predictors. The metabolite concentration prediction accuracy significantly decreases cross datasets, and cross conditions, especially in 16S data. LOCATE's latent representation predicts the host condition better than either the microbiome or the metabolome. This representation is strongly correlated with host demographics. A significant improvement in accuracy (0.793 vs. 0.724 average accuracy) is obtained even with a small number of metabolite samples ([Formula: see text]).

CONCLUSION

These results suggest that a latent representation of the microbiome-metabolome interaction leads to a better association with the host condition than any of the two separated or the simple combination of the two. Video Abstract.

SAH and SAM/SAH ratio associate with acute kidney injury in critically ill patients: A case-control study

BACKGROUND

Acute kidney injury (AKI) is a serious clinical emergency with an acute onset, rapid progression and poor prognosis, which has high morbidity and mortality in hospitalized patients. DNA methylation plays an important role in the occurrence and progression of kidney disease, and aberrant methylation and certain altered methylation-related metabolites have been reported in AKI patients. However, the specific alterations of methylation-related metabolites in the AKI patients were not investigated clearly.

METHOD

In this study, 61 AKI and 61 matched non-AKI inpatients were recruited after propensity score matching the age and hypertension. And 11 methylation-related metabolites in the plasma and urine of the two groups were quantified by using UHPLC-MS/MS method.

RESULTS

Certain methylation-relate intermediates were up-regulated in the plasma (choline, trimethylamine N-oxide (TMAO), trimethyl lysine (TML), S-adenosylmethionine (SAM) and S-adenosylhomocysteine (SAH)) and down-regulated in the urine of AKI inpatients (choline, betaine, TMAO, dimethylglycine (DMG), SAM and taurine). The correlation analysis revealed a relatively strong correlation between plasma SAH, SAM/SAH ratio and renal function index (serum creatinine (SCr) and estimated glomerular filtration rate (eGFR), r = 0.523-0.616), and the correlation of urinary intermediates with renal function index was weaker than that in the plasma. Furthermore, receiver operating characteristic (ROC) analysis showed that plasma SAH and urinary SAM/SAH ratio represented the best distinguishing efficiency with AUC 0.844 and 0.794, respectively. Moreover, the findings of binary regression analysis demonstrated plasma choline, TMAO, TML, SAM and SAH were the risk markers of AKI (up-regulation in plasma, OR > 1), urinary choline, betaine, TMAO, DMG and SAM were protective markers of AKI (down-regulation in urine, OR < 1), and SAM/SAH ratio was a protective marker in plasma and urine (down-regulation in both two biofluids, OR = 0.510, 0.383-0.678 in plasma, OR = 0.904, 0.854-0.968 in urine), indicating the increased risk of AKI when combined with the alteration of plasma and urinary levels.

CONCLUSION

The comprehensive analysis of plasma and urine samples from AKI inpatients offers a more extensive assessment of methylated metabolic alterations, suggesting a close relationship between AKI stress and altered methylation ability. The plasma level of SAH and SAM/SAH ratio and urinary SAM/SAH ratio both showed a strong correlation with renal function (SCr and eGFR) and good accuracy for distinguishing AKI in the two biomatrices, which exhibited promising prospects in predicting renal function decline and providing further information for the pathogenesis of AKI.

A systematic review of metabolomic findings in adult and pediatric renal disease

Chronic kidney disease (CKD) affects over 0.5 billion people worldwide across their lifetimes. Despite a growingly ageing world population, an increase in all-age prevalence of kidney disease persists. Adult-onset forms of kidney disease often result from lifestyle-modifiable metabolic illnesses such as type 2 diabetes. Pediatric and adolescent forms of renal disease are primarily caused by morphological abnormalities of the kidney, as well as immunological, infectious and inherited metabolic disorders. Alterations in energy metabolism are observed in CKD of varying causes, albeit the molecular mechanisms underlying pathology are unclear. A systematic indexing of metabolites identified in plasma and urine of patients with kidney disease alongside disease enrichment analysis uncovered inborn errors of metabolism as a framework that links features of adult and pediatric kidney disease. The relationship of genetics and metabolism in kidney disease could be classified into three distinct landscapes: (i) Normal genotypes that develop renal damage because of lifestyle and / or comorbidities; (ii) Heterozygous genetic variants and polymorphisms that result in unique metabotypes that may predispose to the development of kidney disease via synergistic heterozygosity, and (iii) Homozygous genetic variants that cause renal impairment by perturbing metabolism, as found in children with monogenic inborn errors of metabolism. Interest in the identification of early biomarkers of onset and progression of CKD has grown steadily in the last years, though it has not translated into clinical routine yet. This systematic review indexes findings of differential concentration of metabolites and energy pathway dysregulation in kidney disease and appraises their potential use as biomarkers.

Factors Associated With Acute Kidney Injury in Patients Undergoing Transcatheter Aortic Valve Implantation: A Systematic Review and Meta-Analysis

The aim of this meta-analysis is to assess the effect of different independent predictors on acute kidney injury (AKI) after transcatheter aortic valve implantation (TAVI). This meta-analysis adhered to the guidelines of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). A comprehensive database search was conducted using PubMed, Web of Science, and Scopus for the period from January 1, 2015, to August 15, 2023. The following key terms were employed: "transcatheter aortic valve implantation" OR "transcatheter aortic valve replacement" AND "acute kidney injury" OR "acute renal failure." Our search was limited to studies published exclusively in the English language. The statistical analysis was conducted using RevMan version 5.4.1 (The Cochrane Collaboration). Estimates were presented as odds ratio (OR) with 95% confidence interval (CI) for categorical variables, while continuous variables were reported as mean difference (MD) with 95% CI. A total of 19 studies met the selection criteria and were included in the meta-analysis. The pooled incidence of AKI was reported as 20% (95% CI: 18-20%). Factors significantly associated with post-TAVI AKI encompass hypertension, chronic kidney disease (CKD), low estimated glomerular filtration rate (eGFR), high baseline creatinine levels, peripheral vascular disease (PVD), Society of Thoracic Surgeons (STS) score, European System for Cardiac Operative Risk Evaluation (EUROscore) II, and the transfemoral surgical approach.

Metabolomics in Acute Kidney Injury: The Clinical Perspective

BACKGROUND

Acute kidney injury (AKI) affects increasing numbers of hospitalized patients worldwide. The diagnosis of AKI is made too late in most individuals since it is still based on dynamic changes in serum creatinine. In recent years, new AKI biomarkers have been identified; however, none of these can reliably replace serum creatinine yet. Metabolomic profiling (metabolomics) allows the concomitant detection and quantification of large numbers of metabolites from biological specimens. The current article aims to summarize clinical studies on metabolomics in AKI diagnosis and risk prediction.

METHODS

The following databases were searched for references: PubMed, Web of Science, Cochrane Library, and Scopus, and the period lasted from 1940 until 2022. The following terms were utilized: 'AKI' OR 'Acute Kidney Injury' OR 'Acute Renal Failure' AND 'metabolomics' OR 'metabolic profiling' OR 'omics' AND 'risk' OR 'death' OR 'survival' OR 'dialysis' OR 'KRT' OR 'kidney replacement therapy' OR 'RRT' OR 'renal replacement therapy' OR 'recovery of kidney function' OR 'renal recovery' OR 'kidney recovery' OR 'outcome'. Studies on AKI risk prediction were only selected if metabolomic profiling allowed differentiation between subjects that fulfilled a risk category (death or KRT or recovery of kidney function) and those who did not. Experimental (animal-based) studies were not included.

RESULTS

In total, eight studies were identified. Six studies were related to the diagnosis of AKI; two studies were performed on metabolic analysis in AKI risk (death) prediction. Metabolomics studies in AKI already helped to identify new biomarkers for AKI diagnosis. The data on metabolomics for AKI risk prediction (death, KRT, recovery of kidney function), however, are very limited.

CONCLUSIONS

Both the heterogenous etiology and the high degree of pathogenetic complexity of AKI most likely require integrated approaches such as metabolomics and/or additional types of '-omics' studies to improve clinical outcomes in AKI.

Transcatheter Aortic Valve Replacement-Associated Acute Kidney Injury: An Update

BACKGROUND

Transcatheter aortic valve replacement (TAVR) is a relatively novel minimally invasive procedure for the treatment of symptomatic patients with severe aortic stenosis. Although it has been proven effective in improving mortality and quality of life, TAVR is associated with serious complications, such as acute kidney injury (AKI).

SUMMARY

TAVR-associated AKI is likely due to several factors such as sustained hypotension, transapical approach, volume of contrast use, and baseline low GFR. This narrative review aims to present an overview of the latest literature and evidence regarding the definition of TAVR-associated AKI, its risk factors, and its impact on morbidity and mortality. The review used a systematic search strategy with multiple health-focused databases (Medline, EMBASE) and identified 8 clinical trials and 27 observational studies concerning TAVR-associated AKI. Results showed that TAVR-associated AKI is linked to several modifiable and nonmodifiable risk factors and is associated with higher mortality. A variety of diagnostic imaging modalities have the potential to identify patients at high risk for development of TAVR-AKI; however, there are no existing consensus recommendations regarding their use as of this time. The implications of these findings highlight the importance of identifying high-risk patients for which preventive measures may play a crucial role, and should be maximized.

KEY MESSAGE

This study reviews the current understanding of TAVR-associated AKI including its pathophysiology, risk factors, diagnostic modalities, and preventative management for patients.

Relation of Subacute Kidney Injury to Mortality After Transcatheter Aortic Valve Implantation

Acute kidney injury after transcatheter aortic valve implantation (TAVI) has been associated with adverse outcomes; however, data are limited on the subacute changes in renal function that occur after discharge and their impact on clinical outcomes. This study investigates the relation between subacute changes in kidney function at 30 days after TAVI and survival. Patients from 2 centers who underwent TAVI and survived beyond 30 days with baseline, in-hospital, and 30-day measures of renal function were retrospectively analyzed. Patients were stratified based on change in estimated glomerular filtration rate (eGFR) from baseline to 30 days as follows: improved (≥15% higher than baseline), worsened (≤15% lower), or unchanged (values in between). Univariable and multivariable models were constructed to identify predictors of subacute changes in renal function and of 2-year mortality. Of the 492 patients who met inclusion criteria, eGFR worsened in 102 (22%), improved in 110 (22%), and was unchanged in 280 (56%). AKI occurred in 90 patients (18%) and in only 27% of patients with worsened eGFR at 30 days. After statistical adjustment, worsened eGFR at 30 days (hazard ratio vs unchanged eGFR 2.09, 95% CI 1.37 to 3.19, p <0.001) was associated with worse survival, whereas improvement in renal function was not associated with survival (hazard ratio vs unchanged eGFR 1.30, 95% CI 0.79 to 2.11, p = 0.30). Worsened renal function at 30 days after TAVI is associated with increased mortality after TAVI. In conclusion, monitoring renal function after discharge may identify patients at high risk of adverse outcomes.

Serum metabolite profiles predict outcomes in critically ill patients receiving renal replacement therapy

Acute kidney injury (AKI) requiring renal replacement therapy (RRT) is associated with increased incidence of dialysis dependence and portends high mortality in critically ill patients. At the early stage of RRT, serum metabolic biomarkers might differntiate patients with a high risk of mortality or permanent kidney injury from those who can recover. Serum samples from participants enrolled in the Veteran's Affairs/National Institutes of Health Acute Renal Failure Trial Network study were collected on day 1 (n = 97) and day 8 (n = 105) of randomized RRT. The samples were further evaluated using LC/MS-based metabolic profiling. A model predicting mortality by day 8 was built from samples collected on day 1 and based on four metabolites with an area under the curve (AUC) of 0.641. A model most predictive of mortality by day 28 was built from the levels of 11 serum metabolites from day 8 with an AUC of 0.789. Both day 1 and day 8 samples had lower serum levels of 1-arachidonoyl-lysoPC and 1-eicosatetraenoyl-lysoPC (involved in anti-inflammatory processes) in the critically ill patients who died by day 8 or day 28. Higher levels of amino acids and amino acid metabolites in the day 8 model predicting < day 28 mortality may be indicative of muscle wasting. A kidney recovery biomarker panel based on the serum levels of three metabolites from day 8 samples with an AUC of 0.70 was devised. Serum metabolic profiling of AKI critically ill patients requiring RRT revealed predictive models of mortality based on observed differences in four serum metabolites at day 1 and 11 metabolites at day 8 which were predictive of mortality. Significant changes in the levels of these metabolites suggest links to inflammatory processes and/or muscle wasting.

Plasma Metabolites-Based Prediction in Cardiac Surgery-Associated Acute Kidney Injury

Background

Cardiac surgery–associated acute kidney injury (CSA‐AKI) is a common postoperative complication following cardiac surgery. Currently, there are no reliable methods for the early prediction of CSA‐AKI in hospitalized patients. This study developed and evaluated the diagnostic use of metabolomics‐based biomarkers in patients with CSA‐AKI.

Methods and Results

A total of 214 individuals (122 patients with acute kidney injury [AKI], 92 patients without AKI as controls) were enrolled in this study. Plasma samples were analyzed by liquid chromatography tandem mass spectrometry using untargeted and targeted metabolomic approaches. Time‐dependent effects of selected metabolites were investigated in an AKI swine model. Multiple machine learning algorithms were used to identify plasma metabolites positively associated with CSA‐AKI. Metabolomic analyses from plasma samples taken within 24 hours following cardiac surgery were useful for distinguishing patients with AKI from controls without AKI. Gluconic acid, fumaric acid, and pseudouridine were significantly upregulated in patients with AKI. A random forest model constructed with selected clinical parameters and metabolites exhibited excellent discriminative ability (area under curve, 0.939; 95% CI, 0.879–0.998). In the AKI swine model, plasma levels of the 3 discriminating metabolites increased in a time‐dependent manner (R², 0.480–0.945). Use of this AKI predictive model was then confirmed in the validation cohort (area under curve, 0.972; 95% CI, 0.947–0.996). The predictive model remained robust when tested in a subset of patients with early‐stage AKI in the validation cohort (area under curve, 0.943; 95% CI, 0.883–1.000).

Conclusions

High‐resolution metabolomics is sufficiently powerful for developing novel biomarkers. Plasma levels of 3 metabolites were useful for the early identification of CSA‐AKI.

Urinary Metabolome Analyses of Patients with Acute Kidney Injury Using Capillary Electrophoresis-Mass Spectrometry

Acute kidney injury (AKI) is defined as a rapid decline in kidney function. The associated syndromes may lead to increased morbidity and mortality, but its early detection remains difficult. Using capillary electrophoresis time-of-flight mass spectrometry (CE-TOFMS), we analyzed the urinary metabolomic profile of patients admitted to the intensive care unit (ICU) after invasive surgery. Urine samples were collected at six time points: before surgery, at ICU admission and 6, 12, 24 and 48 h after. First, urine samples from 61 initial patients (non-AKI: 23, mild AKI: 24, severe AKI: 14) were measured, followed by the measurement of urine samples from 60 additional patients (non-AKI: 40, mild AKI: 20). Glycine and ethanolamine were decreased in patients with AKI compared with non-AKI patients at 6-24 h in the two groups. The linear statistical model constructed at each time point by machine learning achieved the best performance at 24 h (median AUC, area under the curve: 89%, cross-validated) for the 1st group. When cross-validated between the two groups, the AUC showed the best value of 70% at 12 h. These results identified metabolites and time points that show patterns specific to subjects who develop AKI, paving the way for the development of better biomarkers.

Serum 5-Hydroxyindoleacetic Acid and Ratio of 5-Hydroxyindoleacetic Acid to Serotonin as Metabolomics Indicators for Acute Oxidative Stress and Inflammation in Vancomycin-Associated Acute Kidney Injury

The incidence of vancomycin-associated acute kidney injury (VAKI) varies from 5–43%, and early detection of VAKI is important in deciding whether to discontinue nephrotoxic agents. Oxidative stress is the main mechanism of VAKI, and serotonin (5-HT) and its metabolite 5-hydroxyindoleacetic acid (5-HIAA) have been examined with respect to their involvement in ischemia/reperfusion damage in experimental animal models. In the current study, we assessed 5-HT and 5-HIAA as novel biomarkers for detecting VAKI in patients who have infections or compromised renal function, using a mass spectrometry–based metabolomics approach. We conducted amino acid profiling analysis and measurements of 5-HT and 5-HIAA using serum from subjects with VAKI (n = 28) and non-VAKI control subjects (n = 69), consisting of the infection subgroup (n = 23), CKD subgroup (n = 23), and healthy controls (HCs, n = 23). 5-HT was significantly lower in the VAKI group than in the non-VAKI groups, and the concentration of 5-HIAA and the ratio of 5-HIAA to 5-HT (5-HIAA/5-HT) showed higher values in the VAKI group. The infection subgroup presented a significantly greater 5-HIAA/5-HT ratio compared with the HC subgroup. Our study revealed that increased 5-HIAA/5-HT ratio has the potential to act as a VAKI surrogate marker, reflecting acute oxidative stress and inflammation.

Evaluation and Management of Aortic Stenosis in Chronic Kidney Disease: A Scientific Statement From the American Heart Association

Aortic stenosis with concomitant chronic kidney disease (CKD) represents a clinical challenge. Aortic stenosis is more prevalent and progresses more rapidly and unpredictably in CKD, and the presence of CKD is associated with worse short-term and long-term outcomes after aortic valve replacement. Because patients with advanced CKD and end-stage kidney disease have been excluded from randomized trials, clinicians need to make complex management decisions in this population that are based on retrospective and observational evidence. This statement summarizes the epidemiological and pathophysiological characteristics of aortic stenosis in the context of CKD, evaluates the nuances and prognostic information provided by noninvasive cardiovascular imaging with echocardiography and advanced imaging techniques, and outlines the special risks in this population. Furthermore, this statement provides a critical review of the existing literature pertaining to clinical outcomes of surgical versus transcatheter aortic valve replacement in this high-risk population to help guide clinical decision making in the choice of aortic valve replacement and specific prosthesis. Finally, this statement provides an approach to the perioperative management of these patients, with special attention to a multidisciplinary heart-kidney collaborative team-based approach.

Incidence, predictors, and outcomes associated with acute kidney injury in patients undergoing transcatheter aortic valve replacement: from the BRAVO-3 randomized trial

BACKGROUND

Acute kidney injury (AKI) is not uncommon in patients undergoing transcatheter aortic valve replacement (TAVR).

OBJECTIVE

We examined the incidence, predictors, and outcomes of AKI from the BRAVO 3 randomized trial.

METHODS

The BRAVO-3 trial included 802 patients undergoing transfemoral TAVR randomized to bivalirudin vs. unfractionated heparin (UFH). The primary endpoint of the trial was Bleeding Academic Research Consortium (BARC) type ≥ 3b bleeding at 48 h. Total follow-up was to 30 days. AKI was adjudicated using the modified RIFLE (Valve Academic Research Consortium, VARC 1) criteria through 30-day follow-up, and in a sensitivity analysis AKI was assessed at 7 days (modified VARC-2 criteria). We examined the incidence, predictors, and 30-day outcomes associated with diagnosis of AKI. We also examined the effect of procedural anticoagulant (bivalirudin or unfractionated heparin, UFH) on AKI within 48 h after TAVR.

RESULTS

The trial population had a mean age of 82.3 ± 6.5 years including 48.8% women with mean EuroScore I 17.05 ± 10.3%. AKI occurred in 17.0% during 30-day follow-up and was associated with greater adjusted risk of 30-day death (13.0% vs. 3.5%, OR 5.84, 95% CI 2.62-12.99) and a trend for more BARC ≥ 3b bleeding (15.1% vs. 8.6%, OR 1.80, 95% CI 0.99-3.25). Predictors of 30-day AKI were baseline hemoglobin, body weight, and pre-existing coronary disease. AKI occurred in 10.7% at 7 days and was associated with significantly greater risk of 30-day death (OR 6.99, 95% CI 2.85-17.15). Independent predictors of AKI within 7 days included pre-existing coronary or cerebrovascular disease, chronic kidney disease (CKD), and transfusion which increased risk, whereas post-dilation was protective. The incidence of 48-h AKI was higher with bivalirudin compared to UFH in the intention to treat cohort (10.9% vs. 6.5%, p = 0.03), but not in the per-protocol assessment (10.7% vs. 7.1%, p = 0.08).

CONCLUSION

In the BRAVO 3 trial, AKI occurred in 17% at 30 days and in 10.7% at 7 days. AKI was associated with a significantly greater adjusted risk for 30-day death. Multivariate predictors of AKI at 30 days included baseline hemoglobin, body weight, and prior coronary artery disease, and predictors at 7 days included pre-existing vascular disease, CKD, transfusion, and valve post-dilation. Bivalirudin was associated with greater AKI within 48 h in the intention to treat but not in the per-protocol analysis.

Metabolomic Profiling for Diagnosis and Prognostication in Surgery: A Scoping Review

OBJECTIVE

This review assimilates and critically evaluates available literature regarding the use of metabolomic profiling in surgical decision-making.

BACKGROUND

Metabolomic profiling is performed by nuclear magnetic resonance spectroscopy or mass spectrometry of biofluids and tissues to quantify biomarkers (ie, sugars, amino acids, and lipids), producing diagnostic and prognostic information that has been applied among patients with cardiovascular disease, inflammatory bowel disease, cancer, and solid organ transplants.

METHODS

PubMed was searched from 1995 to 2019 to identify studies investigating metabolomic profiling of surgical patients. Articles were included and assimilated into relevant categories per PRISMA-ScR guidelines. Results were summarized with descriptive analytical methods.

RESULTS

Forty-seven studies were included, most of which were retrospective studies with small sample sizes using various combinations of analytic techniques and types of biofluids and tissues. Results suggest that metabolomic profiling has the potential to effectively screen for surgical diseases, suggest diagnoses, and predict outcomes such as postoperative complications and disease recurrence. Major barriers to clinical adoption include a lack of high-level evidence from prospective studies, heterogeneity in study design regarding tissue and biofluid procurement and analytical methods, and the absence of large, multicenter metabolome databases to facilitate systematic investigation of the efficacy, reproducibility, and generalizability of metabolomic profiling diagnoses and prognoses.

CONCLUSIONS

Metabolomic profiling research would benefit from standardization of study design and analytic approaches. As technologies improve and knowledge garnered from research accumulates, metabolomic profiling has the potential to provide personalized diagnostic and prognostic information to support surgical decision-making from preoperative to postdischarge phases of care.

Application of Differential Network Enrichment Analysis for Deciphering Metabolic Alterations

Modern analytical methods allow for the simultaneous detection of hundreds of metabolites, generating increasingly large and complex data sets. The analysis of metabolomics data is a multi-step process that involves data processing and normalization, followed by statistical analysis. One of the biggest challenges in metabolomics is linking alterations in metabolite levels to specific biological processes that are disrupted, contributing to the development of disease or reflecting the disease state. A common approach to accomplishing this goal involves pathway mapping and enrichment analysis, which assesses the relative importance of predefined metabolic pathways or other biological categories. However, traditional knowledge-based enrichment analysis has limitations when it comes to the analysis of metabolomics and lipidomics data. We present a Java-based, user-friendly bioinformatics tool named Filigree that provides a primarily data-driven alternative to the existing knowledge-based enrichment analysis methods. Filigree is based on our previously published differential network enrichment analysis (DNEA) methodology. To demonstrate the utility of the tool, we applied it to previously published studies analyzing the metabolome in the context of metabolic disorders (type 1 and 2 diabetes) and the maternal and infant lipidome during pregnancy.

Metabolic Modulation and Potential Biomarkers of the Prognosis Identification for Severe Aortic Stenosis after TAVR by a Metabolomics Study

Objectives

To investigate the metabolic profile in patients with aortic stenosis (AS) after transcatheter aortic valve replacement (TAVR) and explore the potential biomarkers to predict prognosis after TAVR based on metabolomics.

Methods and Results

Fifty-nine consecutive AS patients were prospectively recruited. Blood samples from the ascending aorta, coronary sinus, and peripheral vein at before and after TAVR were collected, respectively. Liquid chromatography-mass spectrometry and gas chromatography-mass spectrometry were performed to analyze the metabolic profile before and after TAVR. Influential metabolites were identified by integrating the univariate test, multivariate analysis, and weighted gene coexpression network analysis (WGCNA) algorithm. PLS-DA analysis revealed a significant extremely early (within 30 minutes after TAVR) alterations of metabolites in the ascending aorta, coronary sinus, and peripheral vein. The early (within 7 days after TAVR) changed metabolites in the peripheral vein were involved in purine metabolism, primary bile acid biosynthesis, glycerolipid metabolism, amino sugar and nucleotide sugar metabolism, one carbon pool by folate and alanine, and the aspartate and glutamate metabolism pathway. We used volcano plots to find that the cardiac-specific changed metabolites were enriched to the sphingolipid metabolism pathway after TAVR. Besides, WGCNA algorithm was performed to reveal that arginine and proline metabolites could reflect left ventricle regression to some extent.

Conclusion

This is the first study to reveal systemic and cardiac metabolites changed significantly in patients with AS after TAVR. Some altered metabolites involved in the arginine and proline metabolism pathway in the peripheral vein could predict left ventricle regression, which merited further study.

Metabolomic profiling of patients with high gradient aortic stenosis undergoing transcatheter aortic valve replacement

Aim

Aim of our study was to evaluate metabolic changes in patients with aortic stenosis (AS) before and after transcatheter aortic valve replacement (TAVR) and to assess whether this procedure reverses metabolomic alterations.

Methods

188 plasma metabolites of 30 patients with severe high-gradient aortic valve stenosis (pre-TAVR and 6 weeks post-TAVR) as well as 20 healthy controls (HC) were quantified by liquid chromatography tandem mass spectrometry. Significantly altered metabolites were then correlated to an extensive patient database of clinical parameters at the time of measurement.

Results

Out of the determined metabolites, 26.6% (n = 50) were significantly altered in patients with AS pre-TAVR compared to HC. In detail, 5/40 acylcarnitines as well as 10/42 amino acids and biogenic amines were mainly increased in AS, whereas 29/90 glycerophospholipids and 6/15 sphingomyelins were mainly reduced. In the post-TAVR group, 10.1% (n = 19) of metabolites showed significant differences when compared to pre-TAVR. Moreover, we found nine metabolites revealing reversible concentration levels. Correlation with clinically important parameters revealed strong correlations between sphingomyelins and cholesterol (r = 0.847), acylcarnitines and brain natriuretic peptide (r = 0.664) and showed correlation of acylcarnitine with an improvement of left ventricular (LV) ejection fraction (r = − 0.513) and phosphatidylcholines with an improvement of LV mass (r = − 0.637).

Conclusion

Metabolic profiling identified significant and reversible changes in circulating metabolites of patients with AS. The correlation of circulating metabolites with clinical parameters supports the use of these data to identify novel diagnostic as well as prognostic markers for disease screening, pathophysiological studies as well as patient surveillance.

Electronic supplementary material

The online version of this article (10.1007/s00392-020-01754-2) contains supplementary material, which is available to authorized users.

Implications of Renal Disease in Patients Undergoing Structural Interventions

Chronic kidney disease patients have a high prevalence of severe valvular heart disease, which reduces life expectancy. Transcatheter valve interventions has revamped the way we manage severe valvular heart disease and are an attractive alternative to invasive surgery in patients with chronic kidney disease and severe valvular heart disease. This review summarizes the impact of transcatheter valve interventions in patients with severe valvular heart disease and chronic kidney disease.

Urinary NMR Profiling in Pediatric Acute Kidney Injury-A Pilot Study

Acute kidney injury (AKI) in critically ill children and adults is associated with significant short- and long-term morbidity and mortality. As serum creatinine- and urine output-based definitions of AKI have relevant limitations, there is a persistent need for better diagnostics of AKI. Nuclear magnetic resonance (NMR) spectroscopy allows for analysis of metabolic profiles without extensive sample manipulations. In the study reported here, we examined the diagnostic accuracy of NMR urine metabolite patterns for the diagnosis of neonatal and pediatric AKI according to the Kidney Disease: Improving Global Outcomes (KDIGO) definition. A cohort of 65 neonatal and pediatric patients (0–18 years) with established AKI of heterogeneous etiology was compared to both a group of apparently healthy children (n = 53) and a group of critically ill children without AKI (n = 31). Multivariate analysis identified a panel of four metabolites that allowed diagnosis of AKI with an area under the receiver operating characteristics curve (AUC-ROC) of 0.95 (95% confidence interval 0.86–1.00). Especially urinary citrate levels were significantly reduced whereas leucine and valine levels were elevated. Metabolomic differentiation of AKI causes appeared promising but these results need to be validated in larger studies. In conclusion, this study shows that NMR spectroscopy yields high diagnostic accuracy for AKI in pediatric patients.

Metabolomics technology and bioinformatics for precision medicine

Precision medicine is rapidly emerging as a strategy to tailor medical treatment to a small group or even individual patients based on their genetics, environment and lifestyle. Precision medicine relies heavily on developments in systems biology and omics disciplines, including metabolomics. Combination of metabolomics with sophisticated bioinformatics analysis and mathematical modeling has an extreme power to provide a metabolic snapshot of the patient over the course of disease and treatment or classifying patients into subpopulations and subgroups requiring individual medical treatment. Although a powerful approach, metabolomics have certain limitations in technology and bioinformatics. We will review various aspects of metabolomics technology and bioinformatics, from data generation, bioinformatics analysis, data fusion and mathematical modeling to data management, in the context of precision medicine.

Association of Acylcarnitines With Left Ventricular Remodeling in Patients With Severe Aortic Stenosis Undergoing Transcatheter Aortic Valve Replacement

Importance

Clinical practice guidelines currently endorse a reliance on clinical symptoms of overt left ventricular (LV) failure to time aortic valve replacement for severe aortic stenosis; however, delayed aortic valve replacement can result in irreversible LV injury and adverse outcomes. Blood metabolomic signatures possess prognostic value in heart failure; this study assesses whether they are informative in aortic stenosis.

Objective

To evaluate the value of metabolomic signatures in reflecting the extent of maladaptive LV remodeling in patients with end-stage aortic stenosis undergoing transcatheter aortic valve replacement, and to assess whether this procedure reverses metabolomic aberrations.

Design, Setting, and Participants

This study of 44 patients with symptomatic severe aortic stenosis who underwent transfemoral transcatheter aortic valve replacement at a single-center tertiary care hospital. Liquid chromatography-mass spectrometry-based metabolomic profiling was performed on blood samples collected before and 24 hours after the procedure, and analyses were conducted to identify metabolites related to the measures of LV remodeling.

Main Outcomes and Measures

We evaluated LV ejection fraction, LV mass index, and relative wall thickness, as well as levels of the acylcarnitines C16, C18:1, C18:2, C18, C26, choline, and kynurenine.

Results

We enrolled 44 patients with severe aortic stenosis with a mean (SD) age of 81.9 (8.5) years, of whom 23 (52%) were women. The mean (SD) LV ejection fraction was 56.7% (18.2%), mean (SD) LV mass index was 117.3 (41.4) g/m2, and relative wall thickness was 0.53 (0.14). The mean β values of acylcarnitines C16, C18:1, C18:2, C18, and C26 were independently associated with LV mass index (C16: mean, 19.24; 95% CI, 5.48-33.01; P = .008; C18:1: mean, 26.18; 95% CI, 14.04-38.32; P < 1.0 × 10-4; C18:2: mean, 17.42; 95% CI, 3.40-31.43; P = .02; C18: mean, 25.25; 95% CI, 10.91-39.58; P = .001; C26: mean, 19.93; 95% CI, 4.41-35.45; P = .01), even after adjustments for age, sex, diabetes status, renal function, and B-type natriuretic peptide (BNP). Circulating levels of C18:2 acylcarnitine were associated with LV ejection fraction before and after multivariable adjustment (mean, -6.11; 95% CI, -10.88 to 1.34; P = .01). Blood metabolite levels did not independently relate to relative wall thickness. Within 24 hours of transcatheter aortic valve replacement, circulating levels of C16 decreased by 30.2% (P = 7.3 × 10-6), C18:1 by 42.7% (P = 3.7 × 10-8), C18:2 by 37.3% (P = 5.1 × 10-6), and C18 by 38.3% (P = 3.4 × 10-5).

Conclusions and Relevance

In symptomatic patients with severe aortic stenosis undergoing transcatheter aortic valve replacement, circulating levels of long-chain acylcarnitines were independently associated with measures of maladaptive LV remodeling, and metabolic perturbations lessened after procedure completion. Further efforts are needed to determine the clinical applicability of these novel biomarkers.

Determination of S-adenosylmethionine and S-adenosylhomocysteine in blood plasma by UPLC with fluorescence detection

A validated approach to determine various methionine cycle metabolites (S-adenosylmethionine, S-adenosylhomocysteine, and methylthioadenosine) in human blood plasma is offered. The approach is based on solid-phase extraction (with grafted phenylboronic acid) and derivatization with chloroacetaldehyde followed by ultra-performance liquid chromatography with fluorescence detection. We used a 100 × 2.1 mm × 1.8 μm C18 column for the selective separation of analytes. Chromatographic separation was achieved with gradient elution of acetonitrile (flow rate 0.2 mL/min) from 2 to 20%. The eluent was initially composed of 10 mM KH₂PO₄ with 10 mM acetic acid and 25 μM heptafluorobutyric acid. The total analysis time was 11 min. Validation of the method included detection of the limit of detection (2 nM), limit of quantification (5 nM), accuracy (97.2-101%), and intra- and interday precision (2.2-9.0%). Analysis of plasma samples from healthy volunteers revealed that the average levels of S-adenosylmethionine, S-adenosylhomocysteine, and methylthioadenosine were 93.6, 20.9 and 14.8 nM, respectively.

Hyperhomocysteinemia Accelerates Acute Kidney Injury to Chronic Kidney Disease Progression by Downregulating Heme Oxygenase-1 Expression

AIMS

The risk factors promoting acute kidney injury (AKI) to chronic kidney disease (CKD) progression remain largely unknown. The aim of the present study was to investigate whether hyperhomocysteinemia (Hhcy) accelerates the development of renal fibrosis after AKI.

RESULTS

Hhcy aggravated ischemia-reperfusion-induced AKI and the subsequent development of renal fibrotic lesions characterized by excessive extracellular matrix deposition. Mechanistically, the RNA binding protein human antigen R (HuR) bound to the 3'-untranslated region (3'-UTR) of heme oxygenase-1 (HO-1) messenger RNA (mRNA). Homocysteine (Hcy) downregulated HuR expression, reduced the binding of HuR to the 3'-UTR of HO-1, and thereafter decreased HO-1 expression. Administration of the HO-1 inducer cobalt protoporphyrin-IX significantly hindered Hhcy-augmented reactive oxygen species production and renal fibrotic lesions. Innovation and Conclusion: These data indicate that Hhcy might be a novel risk factor that promotes AKI to CKD progression. Lowering Hcy level or HO-1 induction might be a potential therapeutic strategy to improve the outcome of AKI.

Urinary metabolites predict prolonged duration of delayed graft function in DCD kidney transplant recipients

Extending kidney donor criteria, including donation after circulatory death (DCD), has resulted in increased rates of delayed graft function (DGF) and primary nonfunction. Here, we used Nuclear Magnetic Resonance (NMR) spectroscopy to analyze the urinary metabolome of DCD transplant recipients at multiple time points (days 10, 42, 180, and 360 after transplantation). The aim was to identify markers that predict prolonged duration of functional DGF (fDGF). Forty-seven metabolites were quantified and their levels were evaluated in relation to fDGF. Samples obtained at day 10 had a different profile than samples obtained at the other time points. Furthermore, at day 10 there was a statistically significant increase in eight metabolites and a decrease in six metabolites in the group with fDGF (N = 53) vis-à-vis the group without fDGF (N = 22). In those with prolonged fDGF (≥21 days) (N = 17) urine lactate was significantly higher and pyroglutamate lower than in those with limited fDGF (<21 days) (N = 36). In order to further distinguish prolonged fDGF from limited fDGF, the ratios of all metabolites were analyzed. In a logistic regression analysis, the sum of branched-chain amino acids (BCAAs) over pyroglutamate and lactate over fumarate, predicted prolonged fDGF with an AUC of 0.85. In conclusion, kidney transplant recipients with fDGF can be identified based on their altered urinary metabolome. Furthermore, two ratios of urinary metabolites, lactate/fumarate and BCAAs/pyroglutamate, adequately predict prolonged duration of fDGF.

Clinical effects of acute kidney injury after transcatheter aortic valve implantation: a systematic review and meta-analysis

Several observational studies have shown that postoperative acute kidney injury (AKI) may significantly worsen the prognosis of a transcatheter aortic valve implantation (TAVI). The purpose of this systematic review and meta-analysis is to evaluate the recent evidence on the impact of AKI on clinical outcomes following TAVI. A comprehensive search in PubMed, Embase and the Cochrane Library was performed for relevant studies by two independent investigators. We pooled the odds ratio (OR) from individual studies, and performed heterogeneity, quality assessment and publication bias analysis. Forty-three eligible studies comprising 544,112 patients were included. Postoperative AKI not only significantly increased the risk for short-term and long-term all-cause mortality (OR 6.25, 95% CI 5.72-6.83, P < 0.00001; OR 3.49, 95% CI 2.78-4.40, P < 0.00001, respectively), but also increased the risk for early myocardial infarction (OR 3.98, 95% CI 1.90-8.31, P = 0.0002), major and life-threatening bleeding (OR 1.51, 95% CI 1.12-2.03, P = 0.007; OR 2.35, 95% CI 1.80-3.06, P < 0.00001, respectively), major vascular complications (OR 1.69, 95% CI 1.30-2.18, P < 0.0001), need for blood transfusion (OR 2.15, 95% CI 1.89-2.46, P < 0.00001) renal replacement therapy (OR 22.36, 95% CI 11.88-42.12, P = 0.0002) and cerebrovascular accidents (OR 1.92, 95% CI 1.23-2.98, P = 0.004). Acute kidney injury following TAVI is associated with increased postoperative mortality and morbidity. Future efforts are required to determine whether early prevention of post-procedural AKI after TAVI impacts upon clinical outcomes.

Identification of specific metabolic pathways as druggable targets regulating the sensitivity to cyanide poisoning

Cyanide is a potent toxic agent, and the few available antidotes are not amenable to rapid deployment in mass exposures. As a result, there are ongoing efforts to exploit different animal models to identify novel countermeasures. We have created a pipeline that combines high-throughput screening in zebrafish with subsequent validation in two mammalian small animal models as well as a porcine large animal model. We found that zebrafish embryos in the first 3 days post fertilization (dpf) are highly resistant to cyanide, becoming progressively more sensitive thereafter. Unbiased analysis of gene expression in response to several hours of ultimately lethal doses of cyanide in both 1 and 7 dpf zebrafish revealed modest changes in iron-related proteins associated with the age-dependent cyanide resistance. Metabolomics measurements demonstrated significant age-dependent differences in energy metabolism during cyanide exposure which prompted us to test modulators of the tricarboxylic acid cycle and related metabolic processes as potential antidotes. In cyanide-sensitive 7 dpf larvae, we identified several such compounds that offer significant protection against cyanide toxicity. Modulators of the pyruvate dehydrogenase complex, as well as the small molecule sodium glyoxylate, consistently protected against cyanide toxicity in 7 dpf zebrafish larvae. Together, our results indicate that the resistance of zebrafish embryos to cyanide toxicity during early development is related to an altered regulation of cellular metabolism, which we propose may be exploited as a potential target for the development of novel antidotes against cyanide poisoning.

Acute kidney injury post-transcatheter aortic valve replacement

Transcatheter aortic valve replacement (TAVR) is a treatment option in high-risk patients with severe aortic stenosis who are not surgical candidates. In light of emerging evidence, it is being increasingly performed even in intermediate-risk patients in recent years. Patients who develop acute kidney injury (AKI) following TAVR are known to have worse outcomes. The objective of this concise review was to identify the prevalence and the impact of AKI following TAVR on patient outcomes by including the most recent literature in our search. After a thorough search on MEDLINE, Google Scholar, and PubMed, we included all literature relevant to AKI following TAVR. We found that AKI was caused by a variety of reasons, such as hemodynamic instability during rapid pacing, blood transfusion, periprocedural embolization, and use of contrast medium, to name a few. In patients who developed AKI following TAVR, 30-day and 1-year mortality were increased. Further, in these patients, length and cost of hospital stay were increased as well. Preventive measures such as optimal periprocedural hydration, careful contrast use, and techniques to prevent embolization during device implantation have been tried with limited success. Given that TAVR is expected to be increasingly performed, this review aimed to summarize the rapidly expanding currently available literature in an effort to reduce procedural complications and thereby improve patient outcomes.

The Sulfur Metabolite Lanthionine: Evidence for a Role as a Novel Uremic Toxin

Lanthionine is a nonproteinogenic amino acid, composed of two alanine residues that are crosslinked on their β-carbon atoms by a thioether linkage. It is biosynthesized from the condensation of two cysteine molecules, while the related compound homolanthionine is formed from the condensation of two homocysteine molecules. The reactions can be carried out by either cystathionine-β-synthase (CBS) or cystathionine-γ-lyase (CSE) independently, in the alternate reactions of the transsulfuration pathway devoted to hydrogen sulfide biosynthesis. Low plasma total hydrogen sulfide levels, probably due to reduced CSE expression, are present in uremia, while homolanthionine and lanthionine accumulate in blood, the latter several fold. Uremic patients display a derangement of sulfur amino acid metabolism with a high prevalence of hyperhomocysteinemia. Uremia is associated with a high cardiovascular mortality, the causes of which are still not completely explained, but are related to uremic toxicity, due to the accumulation of retention products. Lanthionine inhibits hydrogen sulfide production in hepatoma cells, possibly through CBS inhibition, thus providing some basis for the biochemical mechanism, which may significantly contribute to alterations of metabolism sulfur compounds in these subjects (e.g., high homocysteine and low hydrogen sulfide). We therefore suggest that lanthionine is a novel uremic toxin.

Biomarkers for the Early Detection and Prognosis of Acute Kidney Injury

AKI is an increasingly common disorder that is strongly linked to short- and long-term morbidity and mortality. Despite a growing heterogeneity in its causes, providing a timely and certain diagnosis of AKI remains challenging. In this review, we summarize the evolution of AKI biomarker studies over the past few years, focusing on two major areas of investigation: the early detection and prognosis of AKI. We highlight some of the lessons learned in conducting AKI biomarker studies, including ongoing attempts to address the limitations of creatinine as a reference standard and the recent shift toward evaluating the prognostic potential of these markers. Lastly, we suggest current gaps in knowledge and barriers that may be hindering their incorporation into care and a full ascertainment of their value.

An overview of renal metabolomics

The high-throughput, high-resolution phenotyping enabled by metabolomics has been applied increasingly to a variety of questions in nephrology research. This article provides an overview of current metabolomics methodologies and nomenclature, citing specific considerations in sample preparation, metabolite measurement, and data analysis that investigators should understand when examining the literature or designing a study. Furthermore, we review several notable findings that have emerged in the literature that both highlight some of the limitations of current profiling approaches, as well as outline specific strengths unique to metabolomics. More specifically, we review data on the following: (i) tryptophan metabolites and chronic kidney disease onset, illustrating the interpretation of metabolite data in the context of established biochemical pathways; (ii) trimethylamine-N-oxide and cardiovascular disease in chronic kidney disease, illustrating the integration of exogenous and endogenous inputs to the blood metabolome; and (iii) renal mitochondrial function in diabetic kidney disease and acute kidney injury, illustrating the potential for rapid translation of metabolite data for diagnostic or therapeutic aims. Finally, we review future directions, including the need to better characterize interperson and intraperson variation in the metabolome, pool existing data sets to identify the most robust signals, and capitalize on the discovery potential of emerging nontargeted methods.

Independent Risk Factors Contributing to Acute Kidney Injury According to Updated Valve Academic Research Consortium-2 Criteria After Transcatheter Aortic Valve Implantation: A Meta-analysis and Meta-regression of 13 Studies

OBJECTIVES

This study aimed to examine the risk factors for transcatheter aortic valve implantation (TAVI)-associated acute kidney injury (AKI) according to the AKI definition from the Valve Academic Research Consortium-2 (VARC-2).

SETTING

A meta-analysis.

PARTICIPANTS

A total of 661 patients with post-TAVI AKI according to the VARC-2 definition and 2,012 controls were included in the meta-analysis.

INTERVENTIONS

Patients undergoing TAVI were included in this meta-analysis.

MEASUREMENTS AND MAIN RESULTS

Multiple electronic databases were searched using predefined criteria. The diagnosis of AKI was based on the VARC-2 classification. The authors found that preoperative New York Heart Association class IV (odds ratio [OR], 7.77; 95% confidence interval [CI], 3.81-15.85), previous chronic renal disease (CKD) (OR, 2.81; 95% CI, 1.96-4.03), and requirement for transfusion (OR, 2.03; 95% CI, 1.59-2.59) were associated significantly with an increased risk for post-TAVI AKI. Furthermore, previous peripheral vascular disease (PVD), hypertension, atrial fibrillation, congestive heart failure, diabetes mellitus, and stroke were also risk factors for TAVI-associated AKI. Additionally, transfemoral access significantly correlated with a reduced risk for post-TAVI AKI (OR, 0.43; 95% CI, 0.33-0.57). The potential confounders, including Society of Thoracic Surgeons Score, the logistic European System for Cardiac Operative Risk Evaluation, aortic valve area, mean pressure gradient, left ventricular ejection fraction, age, body mass index, contrast volume, and valve type, had no impact on the association between the risk factors and post-TAVI AKI. Subgroup analysis of the eligible studies presenting multivariate logistic regression analysis on the independent risk factors for post-TAVI AKI revealed that previous CKD, previous PVD, and transapical access were independent risk factors for TAVI-associated AKI.

CONCLUSIONS

The current meta-analysis suggested that previous CKD, previous PVD, and transapical access may be independent risk factors for TAVI-associated AKI.

Metabolite Profiles Predict Acute Kidney Injury and Mortality in Patients Undergoing Transcatheter Aortic Valve Replacement

Background

Acute kidney injury (AKI) occurs commonly after transcatheter aortic valve replacement (TAVR) and is associated with markedly increased postoperative mortality. We previously identified plasma metabolites predictive of incident chronic kidney disease, but whether metabolite profiles can identify those at risk of AKI is unknown.

Methods and Results

We performed liquid chromatography–mass spectrometry–based metabolite profiling on plasma from patients undergoing TAVR and subjects from the community‐based Framingham Heart Study (N=2164). AKI was defined by using the Valve Academic Research Consortium‐2 criteria. Of 44 patients (mean age 82±9 years, 52% female) undergoing TAVR, 22 (50%) had chronic kidney disease and 9 (20%) developed AKI. Of 85 metabolites profiled, we detected markedly concordant cross‐sectional metabolic changes associated with chronic kidney disease in the hospital‐based TAVR and Framingham Heart Study cohorts. Baseline levels of 5‐adenosylhomocysteine predicted AKI after TAVR, despite adjustment for baseline glomerular filtration rate (odds ratio per 1‐SD increase 5.97, 95% CI 1.62–22.0; P=0.007). Of the patients who had AKI, 6 (66.7%) subsequently died, compared with 3 (8.6%) deaths among those patients who did not develop AKI (P=0.0008) over a median follow‐up of 7.8 months. 5‐adenosylhomocysteine was predictive of all‐cause mortality after TAVR (hazard ratio per 1‐SD increase 2.96, 95% CI 1.33–6.58; P=0.008), independent of baseline glomerular filtration rate.

Conclusions

In an elderly population with severe aortic stenosis undergoing TAVR, metabolite profiling improves the prediction of AKI. Given the multifactorial nature of AKI after TAVR, metabolite profiles may identify those patients with reduced renal reserve.