1H NMR global metabolic phenotyping of acute pancreatitis in the emergency unit

Multi-dimensional metabolomic profiling reveals dysregulated ornithine metabolism hallmarks associated with a severe acute pancreatitis phenotype

To reveal dysregulated metabolism hallmark that was associated with a severe acute pancreatitis (SAP) phenotype. In this study, LC-MS/MS-based targeted metabolomics was used to analyze plasma samples from 106 acute pancreatitis (AP) patients (34 mild, 38 moderate, and 34 severe) admitted within 48 hours from abdominal pain onset and 41 healthy controls. Temporal metabolic profiling was performed on days 1, 3, and 7 after admission. A random forest (RF) was performed to significantly determine metabolite differences between SAP and non-SAP (NSAP) groups. Mass spectrometry imaging (MSI) and immunohistochemistry were conducted for the examination of pancreatic metabolite and metabolic enzyme alterations, respectively, on necrosis and paracancerous tissues. Simultaneously determination of serum and pancreatic tissue metabolic alterations using an L-ornithine-induced AP model to discover metabolic commonalities. Twenty-two significant differential metabolites screened by RF were selected to build an accurate model for the prediction of SAP from NSAP (AUC = 0.955). Six of 22 markers were found by MSI with significant alterations in pancreatic lesions, reduced ornithine-related metabolites were also identified. The abnormally expressed arginase2 and ornithine transcarboxylase were further discovered in combination with time-course metabolic profiling in the SAP animal models, the decreased ornithine catabolites were found at a late stage of inflammation, but ornithine-associated metabolic enzymes were activated during the inflammatory process. The plasma metabolome of AP patients is distinctive, which shows promise for early SAP diagnosis. AP aggravation is linked to the activated ornithine metabolic pathway and its inadequate levels of catabolites in in-situ lesion.

Unraveling the Metabolic Changes in Acute Pancreatitis: A Metabolomics-Based Approach for Etiological Differentiation and Acute Biomarker Discovery

Acute pancreatitis (AP) remains a challenging medical condition, where a deeper metabolic insight could pave the way for innovative treatments. This research harnessed serum metabolomics to discern potential diagnostic markers for AP and distinguish between its biliary (BAP) and alcohol-induced (AAP) forms. Leveraging high-performance liquid chromatography coupled with mass spectrometry, the metabolic signatures of 34 AP patients were contrasted against 26 healthy participants, and then between different etiologies of AP. The results identified metabolites primarily from glycerophospholipids, glycerolipids, fatty acyls, sterol lipids, and pteridines and derivative classes, with the Human Metabolome Database aiding in classification. Notably, these metabolites differentiated AP from healthy states with high AUROC values above 0.8. Another set of metabolites revealed differences between BAP and AAP, but these results were not as marked as the former. This lipidomic analysis provides an introduction to the metabolic landscape of acute pancreatitis, revealing changes in multiple lipid classes and metabolites and identifying these metabolites. Future research could add and discover new diagnostic biomarkers and therapeutic strategies enhancing the management of acute pancreatitis.

Temporal Proteomic and Lipidomic Profiles of Cerulein-Induced Acute Pancreatitis Reveal Novel Insights for Metabolic Alterations in the Disease Pathogenesis

The pathophysiological mechanisms of acute pancreatitis (AP) are complex and have remained a mystery to date, but metabolism is gradually recognized as an important driver of AP onset and development. We used a cerulein-induced AP mouse model to conduct liquid chromatography-mass spectrometry (LC-MS/MS)-based time-course proteomics and lipidomics in order to better understand the underlying metabolic alterations linked with AP. Results showed that a series of significant changes in proteins over time with a boost in expression were enriched in lipase activity, lipoprotein, and lipids absorption and transport regulation. Furthermore, 16 proteins associated with lipid metabolism and signaling pathways together with the whole lipid species changing profile led to the vital identification of changing law in glycerides, phosphoglycerides, and free fatty acids. In addition to lipid metabolism and regulation-associated proteins, several digestive enzymes and adaptive anti-trypsin, stress response, and energy metabolism-related proteins showed an increment in abundance. Notably, central carbon and branched chain amino acid metabolism were enhanced during 0-24 h from the first cerulein stimulation. Taken together, this integrated proteomics and lipidomics revealed a novel metabolic insight into metabolites transforming rules that might be relevant to their function and drug targets investigation. (Created with Biorender.com.).

Fighting Fire with Fire: Exosomes and Acute Pancreatitis-Associated Acute Lung Injury

Acute pancreatitis (AP) is a prevalent clinical condition of the digestive system, with a growing frequency each year. Approximately 20% of patients suffer from severe acute pancreatitis (SAP) with local consequences and multi-organ failure, putting a significant strain on patients' health insurance. According to reports, the lungs are particularly susceptible to SAP. Acute respiratory distress syndrome, a severe type of acute lung injury (ALI), is the primary cause of mortality among AP patients. Controlling the mortality associated with SAP requires an understanding of the etiology of AP-associated ALI, the discovery of biomarkers for the early detection of ALI, and the identification of potentially effective drug treatments. Exosomes are a class of extracellular vesicles with a diameter of 30-150 nm that are actively released into tissue fluids to mediate biological functions. Exosomes are laden with bioactive cargo, such as lipids, proteins, DNA, and RNA. During the initial stages of AP, acinar cell-derived exosomes suppress forkhead box protein O1 expression, resulting in M1 macrophage polarization. Similarly, macrophage-derived exosomes activate inflammatory pathways within endothelium or epithelial cells, promoting an inflammatory cascade response. On the other hand, a part of exosome cargo performs tissue repair and anti-inflammatory actions and inhibits the cytokine storm during AP. Other reviews have detailed the function of exosomes in the development of AP, chronic pancreatitis, and autoimmune pancreatitis. The discoveries involving exosomes at the intersection of AP and acute lung injury (ALI) are reviewed here. Furthermore, we discuss the therapeutic potential of exosomes in AP and associated ALI. With the continuous improvement of technological tools, the research on exosomes has gradually shifted from basic to clinical applications. Several exosome-specific non-coding RNAs and proteins can be used as novel molecular markers to assist in the diagnosis and prognosis of AP and associated ALI.

Temporal metabolic trajectory analyzed by LC-MS/MS based targeted metabolomics in acute pancreatitis pathogenesis and Chaiqin Chengqi decoction therapy

BACKGROUND

Acute pancreatitis (AP) is an inflammatory disorder of pancreas that lacks effective specific drugs as well as gold standard laboratory tests for diagnosis and severity assessment. Chaiqin chengqi decoction (CQCQD) has been proven to alleviate the severity and mortality of AP, but its underlying mechanisms remain incompletely understood.

PURPOSE

To investigate the correlation between metabolic trajectories of the serum and pancreas, the metabolic pathways with respect to the onset and progression of AP, and investigate the effect of CQCQD in modulating the dysregulated pancreatic metabolism of AP.

METHODS

Serum and pancreas samples from cerulein-induced AP mice were collected for pathology, biochemical index assessment, LC-MS/MS based metabolomics and functional validation over the course of 1 - 24 h. The temporal trends of pancreatic and serum metabolites in AP were analyzed using Mfuzz clustering algorithm, and their associations were revealed by Pearson correlation analysis. The metabolic trajectories and pathways across multi-timepoints were analyzed by univariate and multivariate statistical analyses, and the AP-related metabolic pathways were further screened by metabolite correlation and network interaction analyses. Finally, the changes in metabolite levels and metabolic trajectory after CQCQD therapy were identified, and the altered expression of related metabolic enzymes was verified by RT-qPCR, western blotting, and immunohistochemistry.

RESULTS

Amino acid metabolism was significantly altered in the pancreas and serum of AP, but with different trends. The unsynchronized "open" and "closed" metabolic trajectories in pancreas and serumrevealed that metabolic processes occur earlier in peripheral rather than local tissue, with the most obvious changes occuring at 12 h in the pancreas which were also consistent with the inflammation score results. Several amino acid intermediates showed strong positive correlation between serum and pancreas, and therein serum cystathionine was positively correlated to 33 pancreatic metabolites. In particular, the correlations between the levels of pancreatic cystathionine and methionine, serine, and glutathione (GSH) emphasized the importance of trans-sulfuration to GSH metabolism for AP progression. CQCQD treatment reversed the metabolic trajectory of the pancreas, and also restored the levels of cystathionine and glutathione synthase.

CONCLUSION

Our results have defined a unique time-course metabolic trajectory for AP progression in both the serum and pancreas; it has also revealed a key role of CQCQD in reversing AP-associated metabolic alterations, thus providing new metabolic targets for the treatment and prognosis of AP.

Quantitative metabolic analysis of plasma extracellular vesicles for the diagnosis of severe acute pancreatitis

BACKGROUND

Severe acute pancreatitis (SAP) is the most common gastrointestinal disease and is associated with unpredictable seizures and high mortality rates. Despite improvements in the treatment of acute pancreatitis, the timely and accurate diagnosis of SAP remains highly challenging. Previous research has shown that extracellular vesicles (EVs) in the plasma have significant potential for the diagnosis of SAP since the pancreas can release EVs that carry pathological information into the peripheral blood in the very early stages of the disease. However, we know very little about the metabolites of EVs that might play a role in the diagnosis of SAP.

METHODS

Here, we performed quantitative metabolomic analyses to investigate the metabolite profiles of EVs isolated from SAP plasma. We also determined the metabolic differences of EVs when compared between healthy controls, patients with SAP, and those with mild acute pancreatitis (MAP).

RESULTS

A total of 313 metabolites were detected, mainly including organic acids, amino acids, fatty acids, and bile acids. The results showed that the metabolic composition of EVs derived from SAP and MAP was significantly different from those derived from healthy controls and identified specific differences between EVs derived from patients with SAP and MAP. On this basis, we identified four biomarkers from plasma EVs for SAP detection, including eicosatrienoic acid (C20:3), thiamine triphosphate, 2-Acetylfuran, and cis-Citral. The area under the curve (AUC) was greater than 0.95 for both discovery (n = 30) and validation (n = 70) sets.

CONCLUSIONS

Our data indicate that metabolic profiling analysis of plasma EVs and the screening of potential biomarkers are of significant potential for improving the early diagnosis and severity differentiation of acute pancreatitis.

Correlation between metabolomic profile constituents and feline pancreatic lipase immunoreactivity

Background

Feline pancreatic lipase immunoreactivity (fPLI) is commonly used to diagnose pancreatitis in cats (FP). Untargeted metabolomics has been extensively applied in human and veterinary medicine, but no metabolomic studies regarding FP have been conducted.

Objectives

To identify metabolites significantly associated with increased fPLI.

Animals

Forty‐nine client‐owned cats: 11 clinically healthy and 38 with various clinical conditions.

Methods

Analytical cross‐sectional study with convenience sampling. A panel of 630 metabolites belonging to 26 biochemical classes was quantified in plasma using a commercial metabolomic assay. The correlation between plasma metabolite concentrations and serum fPLI was evaluated using Spearman's rank correlation coefficient (R_s) with Bonferroni correction. Multivariable analysis then was performed to control for glomerular filtration rate, liver damage, and blood glucose concentration. The accuracy of selected metabolites in discriminating between cats with normal (≤3.5 μg/L) and increased (>5.3 μg/L) fPLI was estimated using the area under the receiver operating characteristic curve (AUROC).

Results

Four hundred and seven of 630 metabolites (64.6%) were quantified in all cats. When controlled for potential confounders only 3 sphingolipids were significantly positively correlated with fPLI: 2 cerebrosides: HexCer(d18:1/24:0); (R_s = .56), and HexCer(d18:1/24:1); (R_s = .58) and 1 sphingomyelin: SM C18:0 (R_s = .55). Their AUROCs in identifying cats with increased fPLI were 82% (95% confidence interval [CI 95%], 70%‐94%), 84% (CI 95%, 72%‐96%), and 78% (CI 95%, 65%‐92%), respectively.

Conclusions and Clinical Importance

Selected sphingolipids are moderately positively correlated with fPLI and appear to have fair to moderate diagnostic accuracy in discriminating between cats with normal and increased fPLI.

Plasmatic Oxidative and Metabonomic Profile of Patients with Different Degrees of Biliary Acute Pancreatitis Severity

Acute pancreatitis (AP) is an inflammatory process of the pancreas with variable involvement of the pancreatic and peripancreatic tissues and remote organ systems. The main goal of this study was to evaluate the inflammatory biomarkers, oxidative stress (OS), and plasma metabolome of patients with different degrees of biliary AP severity to improve its prognosis. Twenty-nine patients with biliary AP and 11 healthy controls were enrolled in this study. We analyzed several inflammatory biomarkers, multifactorial scores, reactive oxygen species (ROS), antioxidants defenses, and the plasma metabolome of biliary AP and healthy controls. Hepcidin (1.00), CRP (0.94), and SIRI (0.87) were the most accurate serological biomarkers of AP severity. OS played a pivotal role in the initial phase of AP, with significant changes in ROS and antioxidant defenses relating to AP severity. Phenylalanine (p < 0.05), threonine (p < 0.05), and lipids (p < 0.01) showed significant changes in AP severity. The role of hepcidin and SIRI were confirmed as new prognostic biomarkers of biliary AP. OS appears to have a role in the onset and progression of the AP process. Overall, this study identified several metabolites that may predict the onset and progression of biliary AP severity, constituting the first metabonomic study in the field of biliary AP.

Metabolomic-based clinical studies and murine models for acute pancreatitis disease: A review

Acute pancreatitis (AP) is one of the most common gastroenterological disorders requiring hospitalization and is associated with substantial morbidity and mortality. Metabolomics nowadays not only help us to understand cellular metabolism to a degree that was not previously obtainable, but also to reveal the importance of the metabolites in physiological control, disease onset and development. An in-depth understanding of metabolic phenotyping would be therefore crucial for accurate diagnosis, prognosis and precise treatment of AP. In this review, we summarized and addressed the metabolomics design and workflow in AP studies, as well as the results and analysis of the in-depth of research. Based on the metabolic profiling work in both clinical populations and experimental AP models, we described the metabolites with potential utility as biomarkers and the correlation between the altered metabolites and AP status. Moreover, the disturbed metabolic pathways correlated with biological function were discussed in the end. A practical understanding of current and emerging metabolomic approaches applicable to AP and use of the metabolite information presented will aid in designing robust metabolomics and biological experiments that result in identification of unique biomarkers and mechanisms, and ultimately enhanced clinical decision-making.

Associations between ketone bodies and fasting plasma glucose in individuals with post-pancreatitis prediabetes

Context: Levels of ketone bodies are altered in both acute pancreatitis and type 1 and type 2 diabetes. However, the role of ketone bodies in the pathogenesis of abnormal glucose metabolism after pancreatitis is largely unknown.Objective: To investigate the associations between ketone bodies and glucose homeostasis in individuals with post-pancreatitis prediabetes (PPP) versus normoglycaemia after pancreatitis (NAP).Methods: Fasting blood samples were analysed for acetoacetate, β-hydroxybutyrate, and markers of glucose metabolism at a median of 26 months after acute pancreatitis. A series of linear regression analyses were conducted adjusting for patient- and pancreatitis-related characteristics.Results: The study included 27 individuals with PPP and 52 with NAP. β-hydroxybutyrate was significantly associated with fasting plasma glucose (p = .002) and explained 26.2% of its variance in PPP, but not in NAP (p = .814; 0%). Acetoacetate was not significantly associated with fasting plasma glucose in both PPP (p = .681) or NAP (p = .661).Conclusions: An inverse association between β-hydroxybutyrate and fasting plasma glucose characterises PPP and this may have translational implications.

Clinical Application of Metabolomics in Pancreatic Diseases: A Mini-Review

Metabolomics is a powerful new analytical method to describe the set of metabolites within cellular tissue and bodily fluids. Metabolomics can uncover detailed information about metabolic changes in organisms. The morphology of these metabolites represents the metabolic processes that occur in cells, such as anabolism, catabolism, inhomogeneous natural absorption and metabolism, detoxification, and metabolism of biomass energy. Because the metabolites of different diseases are different, the specificity of the changes can be found by metabolomics testing, which provides a new source of biomarkers for the early identification of diseases and the difference between benign and malignant states. Metabolomics has a wide application potential in pancreatic diseases, including early detection, diagnosis, and identification of pancreatic diseases. However, there are few studies on metabolomics in pancreatic diseases in the literature. This article reviews the application of metabolomics in the diagnosis, prognosis, treatment, and evaluation of pancreatic diseases.

Serum Concentrations of Citrate, Tyrosine, 2- and 3- Hydroxybutyrate are Associated with Increased 3-Month Mortality in Acute Heart Failure Patients

Considering the already established relationship between the extent of the metabolic dysfunction and the severity of heart failure (HF), it is conceivable that the metabolomic profile of the serum may have a prognostic capacity for 3-month mortality in acute heart failure (AHF). Out of 152 recruited patients, 130 serum samples were subjected to the metabolomic analyses. The 3-month mortality rate was 24.6% (32 patients). Metabolomic profiling by nuclear magnetic resonance spectroscopy found that the serum levels of 2-hydroxybutyrate (2-HB), 3-hydoxybutyrate (3-HB), lactate, citrate, and tyrosine, were higher in patients who died within 3 months compared to those who were alive 3 months after onset of AHF, which was confirmed by univariable logistic regression analyses (p = 0.009, p = 0.005, p = 0.008, p<0.001, and p<0.001, respectively). These associations still remained significant for all tested metabolites except for lactate after adjusting for established prognostic parameters in HF. In conclusion, serum levels of 2-HB, 3-HB, tyrosine, and citrate measured at admission are associated with an increased 3-month mortality rate in AHF patients and might thus be of prognostic value in AHF.

Nuclear magnetic resonance spectroscopy as a new approach for improvement of early diagnosis and risk stratification of prostate cancer

Prostate cancer (PCa) is the second most common male cancer worldwide and the fifth leading cause of death from cancer in men. Early detection and risk stratification is the most effective way to improve the survival of PCa patients. Current PCa biomarkers lack sufficient sensitivity and specificity to cancer. Metabolite biomarkers are evolving as a new diagnostic tool. This review is aimed to evaluate the potential of metabolite biomarkers for early detection, risk assessment, and monitoring of PCa. Of the 154 identified publications, 27 and 38 were original papers on urine and serum metabolomics, respectively. Nuclear magnetic resonance (NMR) is a promising method for measuring concentrations of metabolites in complex samples with good reproducibility, high sensitivity, and simple sample processing. Especially urine-based NMR metabolomics has the potential to be a cost-efficient method for the early detection of PCa, risk stratification, and monitoring treatment efficacy.

Identification of potential diagnostic biomarkers of acute pancreatitis by serum metabolomic profiles

Acute pancreatitis (AP) is defined as an acute inflammation of pancreas that may cause damage to other tissues and organs depending upon the severity of symptoms. The diagnosis of AP is usually made by detection of raised circulating pancreatic enzyme levels, but there are occasional false positive and false negative diagnoses and such tests are often normal in delayed presentations. More accurate biomarkers would help in such situations. In this study, the global metabolites' changes of AP patients (APP) were profiled by using gas chromatography-mass spectrometry (GC-MS). Multivariate pattern recognition techniques were used to establish the classification models to distinguish APP from healthy participants (HP). Some significant metabolites including 3-hydroxybutyric acid, phosphoric acid, glycerol, citric acid, d-galactose, d-mannose, d-glucose, hexadecanoic acid and serotonin were selected as potential biomarkers for helping clinical diagnosis of AP. Furthermore, the metabolite changes in APP with severe and mild symptoms were also analyzed. Based on the selected biomarkers, some relevant pathways were also identified. Our results suggested that GC-MS based serum metabolomics method can be used in the clinical diagnosis of AP by profiling potential biomarkers.

Gut Microbiota Profiling: Metabolomics Based Approach to Unravel Compounds Affecting Human Health

The gut microbiota is composed of a huge number of different bacteria, that produce a large amount of compounds playing a key role in microbe selection and in the construction of a metabolic signaling network. The microbial activities are affected by environmental stimuli leading to the generation of a wide number of compounds, that influence the host metabolome and human health. Indeed, metabolite profiles related to the gut microbiota can offer deep insights on the impact of lifestyle and dietary factors on chronic and acute diseases. Metagenomics, metaproteomics and metabolomics are some of the meta-omics approaches to study the modulation of the gut microbiota. Metabolomic research applied to biofluids allows to: define the metabolic profile; identify and quantify classes and compounds of interest; characterize small molecules produced by intestinal microbes; and define the biochemical pathways of metabolites. Mass spectrometry and nuclear magnetic resonance spectroscopy are the principal technologies applied to metabolomics in terms of coverage, sensitivity and quantification. Moreover, the use of biostatistics and mathematical approaches coupled with metabolomics play a key role in the extraction of biologically meaningful information from wide datasets. Metabolomic studies in gut microbiota-related research have increased, focusing on the generation of novel biomarkers, which could lead to the development of mechanistic hypotheses potentially applicable to the development of nutritional and personalized therapies.

Gut Microbiota Profiling: Metabolomics Based Approach to Unravel Compounds Affecting Human Health

The gut microbiota is composed of a huge number of different bacteria, that produce a large amount of compounds playing a key role in microbe selection and in the construction of a metabolic signaling network. The microbial activities are affected by environmental stimuli leading to the generation of a wide number of compounds, that influence the host metabolome and human health. Indeed, metabolite profiles related to the gut microbiota can offer deep insights on the impact of lifestyle and dietary factors on chronic and acute diseases. Metagenomics, metaproteomics and metabolomics are some of the meta-omics approaches to study the modulation of the gut microbiota. Metabolomic research applied to biofluids allows to: define the metabolic profile; identify and quantify classes and compounds of interest; characterize small molecules produced by intestinal microbes; and define the biochemical pathways of metabolites. Mass spectrometry and nuclear magnetic resonance spectroscopy are the principal technologies applied to metabolomics in terms of coverage, sensitivity and quantification. Moreover, the use of biostatistics and mathematical approaches coupled with metabolomics play a key role in the extraction of biologically meaningful information from wide datasets. Metabolomic studies in gut microbiota-related research have increased, focusing on the generation of novel biomarkers, which could lead to the development of mechanistic hypotheses potentially applicable to the development of nutritional and personalized therapies.

Gut Microbiota Profiling: Metabolomics Based Approach to Unravel Compounds Affecting Human Health

The gut microbiota is composed of a huge number of different bacteria, that produce a large amount of compounds playing a key role in microbe selection and in the construction of a metabolic signaling network. The microbial activities are affected by environmental stimuli leading to the generation of a wide number of compounds, that influence the host metabolome and human health. Indeed, metabolite profiles related to the gut microbiota can offer deep insights on the impact of lifestyle and dietary factors on chronic and acute diseases. Metagenomics, metaproteomics and metabolomics are some of the meta-omics approaches to study the modulation of the gut microbiota. Metabolomic research applied to biofluids allows to: define the metabolic profile; identify and quantify classes and compounds of interest; characterize small molecules produced by intestinal microbes; and define the biochemical pathways of metabolites. Mass spectrometry and nuclear magnetic resonance spectroscopy are the principal technologies applied to metabolomics in terms of coverage, sensitivity and quantification. Moreover, the use of biostatistics and mathematical approaches coupled with metabolomics play a key role in the extraction of biologically meaningful information from wide datasets. Metabolomic studies in gut microbiota-related research have increased, focusing on the generation of novel biomarkers, which could lead to the development of mechanistic hypotheses potentially applicable to the development of nutritional and personalized therapies.

Stereotypical Metabolic Response to Endoscopic Retrograde Cholangiopancreatography Show Alterations in Pancreatic Function Regardless of Post-Procedure Pancreatitis

OBJECTIVES:

Metabolomics-based diagnosis or prediction of risk may improve patient outcomes and improve understanding of the pathogenesis of acute pancreatitis (AP). Endoscopic retrograde cholangiopancreatography (ERCP) is a risk factor for developing AP. This pilot study examined metabolomes of patients before and after ERCP, hypothesizing that metabolomics could differentiate between patients who did and did not develop post-ERCP pancreatitis, and that biomarkers associated with development of AP could be identified.

METHODS:

Patients at high risk for developing post-ERCP pancreatitis were prospectively enrolled at the University of Minnesota from October 2012 to February 2014. Urine and serum samples were collected before ERCP, 2 h after ERCP, and daily thereafter if patients were admitted to the hospital with AP. Pancreatitis severity was calculated with Bedside Index for Severity in Acute Pancreatitis (BISAP) and Modified Glasgow scores. Patients who developed AP (n=9) were matched to patients who did not develop AP (n=18) by age and gender. Urine and serum metabolites were profiled with nuclear magnetic resonance spectroscopy. Partial least squares discriminant analysis (PLS-DA) was performed to detect changes in metabolic profiles associated with development of pancreatitis. Metabolic networks were constructed to probe functional relationships among metabolites.

RESULTS:

Of the 113 enrolled patients, 9 developed mild AP according to BISAP and modified Glasglow scores. PLS-DA showed common differences between pre- and post-ERCP metabolic profiles in urine and serum regardless of AP status, characterized by increases in serum and urine ketones and serum glucose. Pre-ERCP lipase levels were somewhat elevated in those who went on to develop AP, though this did not reach statistical significance. Metabolic networks differed between patients with AP and those without after ERCP; however, metabolomics did not identify specific prognostic or diagnostic markers of ERCP-induced AP. Aspartate and asparagine were identified as well-connected hubs in post-ERCP serum networks of cases and were correlated with aspartate transaminase (AST) and white blood cell count levels. These features were not evident in controls. Serum aspartate was elevated in AP patients relative to those without AP after ERCP (P=0.03).

CONCLUSIONS:

In this pilot study, ERCP was found to induce global changes in urine and serum metabolomes indicative of alterations in pancreatic function and insulin resistance. This should be taken into consideration in future research on this topic. Post-ERCP serum metabolic networks indicate functional differences surrounding aspartate metabolism between patients with AP and those without. Further study must be done in larger patient populations to test elevated lipase as a prognostic biomarker associated with risk of developing AP and to examine active metabolic mechanisms at work.

Beta-hydroxybutyrate Concentrations in Dogs with Acute Pancreatitis and Without Diabetes Mellitus

BACKGROUND

β-hydroxybutyrate (BOHB) concentrations have not been quantified in dogs with acute pancreatitis (AP).

OBJECTIVE

The aim of this study was to investigate BOHB concentrations in dogs with AP.

ANIMALS

A total of 154 client-owned dogs without DM.

METHODS

Prospective clinical study. Dogs were enrolled into 1 of 3 groups: AP, sick without an AP diagnosis, or fasted. Dogs were diagnosed with AP (44) if they had vomiting or anorexia, and either ultrasonographic findings consistent with AP or increased pancreatic lipase. Sick dogs without AP (68) had vomiting or anorexia but a diagnosis of AP was either not suspected or was excluded based on ultrasonographic findings or a normal pancreatic lipase. Dogs without anorexia or vomiting that were fasted for over 10 hours for a procedure were also enrolled (42). BOHB was measured on whole blood with a portable ketone meter. The Kruskal-Wallis test was performed to compare BOHB in the 3 groups. Pair-wise comparisons were performed using the Mann-Whitney test and Bonferroni corrected P-values are reported.

RESULTS

Median BOHB concentration was significantly higher in dogs with AP (0.3 mmol/L, range 0-2.9 mmol/L) compared to sick dogs without AP (0.20 mmol/L, range 0-0.9 mmol/L, P = .007) and fasted dogs (0.1 mmol/L, range 0-0.4 mmol/L, P = .0001). Median BOHB concentration was significantly higher in sick dogs without AP compared to fasted dogs (P = .0002).

CONCLUSIONS AND CLINICAL IMPORTANCE

In dogs without DM, BOHB is significantly higher in dogs with AP compared to other dogs. The diagnostic utility of this finding remains to be investigated.

Serum nuclear magnetic resonance-based metabolomics and outcome in diffuse large B-cell lymphoma patients - a pilot study

The prognosis for diffuse large B-cell lymphoma (DLBCL) patients with early relapse or refractory disease is dismal. To determine if clinical outcome correlated to diverse serum metabolomic profiles, we used (1)H nuclear magnetic resonance (NMR) spectroscopy and compared two groups of DLBCL patients treated with immunochemotherapy: i) refractory/early relapse (REF/REL; n=27) and ii) long-term progression-free (CURED; n = 60). A supervised multivariate analysis showed a separation between the groups. Among discriminating metabolites higher in the REF/REL group were the amino acids lysine and arginine, the degradation product cadaverine and a compound in oxidative stress (2-hydroxybutyrate). In contrast, the amino acids aspartate, valine and ornithine, and a metabolite in the glutathione cycle, pyroglutamate, were higher in CURED patients. Together, our data indicate that NMR-based serum metabolomics can identify a signature for DLBCL patients with high-risk of failing immunochemotherapy, prompting for larger validating studies which could lead to more individualized treatment of this disease.