scholarly journals Identification and validation of a multivariable prediction model based on blood plasma and serum metabolomics for the distinction of chronic pancreatitis subjects from non-pancreas disease control subjects

Gut ◽  
2021 ◽  
pp. gutjnl-2020-320723
Author(s):  
M Gordian Adam ◽  
Georg Beyer ◽  
Nicole Christiansen ◽  
Beate Kamlage ◽  
Christian Pilarsky ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Chronic Pancreatitis ◽  
Ethylenediaminetetraacetic Acid ◽  
External Validation ◽  
Gas Chromatography Mass Spectrometry ◽  
Imaging Features ◽  
Total N ◽  
Increased Risk ◽  
Edta Plasma ◽  
Bayes Algorithm

ObjectiveChronic pancreatitis (CP) is a fibroinflammatory syndrome leading to organ dysfunction, chronic pain, an increased risk for pancreatic cancer and considerable morbidity. Due to a lack of specific biomarkers, diagnosis is based on symptoms and specific but insensitive imaging features, preventing an early diagnosis and appropriate management.DesignWe conducted a type 3 study for multivariable prediction for individual prognosis according to the TRIPOD guidelines. A signature to distinguish CP from controls (n=160) was identified using gas chromatography-mass spectrometry and liquid chromatography‐tandem mass spectrometry on ethylenediaminetetraacetic acid (EDTA)-plasma and validated in independent cohorts.ResultsA Naive Bayes algorithm identified eight metabolites of six ontology classes. After algorithm training and computation of optimal cut-offs, classification according to the metabolic signature detected CP with an area under the curve (AUC) of 0.85 ((95% CI 0.79 to 0.91). External validation in two independent cohorts (total n=502) resulted in similar accuracy for detection of CP compared with non-pancreatic controls in EDTA-plasma (AUC 0.85 (95% CI 0.81 to 0.89)) and serum (AUC 0.87 (95% CI 0.81 to 0.95)).ConclusionsThis is the first study that identifies and independently validates a metabolomic signature in plasma and serum for the diagnosis of CP in large, prospective cohorts. The results could provide the basis for the development of the first routine laboratory test for CP.

scholarly journals Xylazine detected in unregulated opioids and drug administration equipment in Toronto, Canada: clinical and social implications

2021 ◽  
Vol 18 (1) ◽  
Author(s):  
Jeanette M. Bowles ◽  
Karen McDonald ◽  
Nazlee Maghsoudi ◽  
Hayley Thompson ◽  
Cristiana Stefan ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
High Resolution Mass Spectrometry ◽  
Gas Chromatography Mass Spectrometry ◽  
Opioid Overdose ◽  
Drug Markets ◽  
Dynamic Nature ◽  
The North ◽  
Rapid Responses ◽  
Increased Risk ◽  
Drug Checking

Abstract Background The North American opioid overdose crisis is driven in large part by the presence of unknown psychoactive adulterants in the dynamic, unregulated drug supply. We herein report the first detection of the psychoactive veterinary compound xylazine in Toronto, the largest urban center in Canada, by the city’s drug checking service. Methods Toronto’s Drug Checking Service launched in October 2019. Between then and February 2021, 2263 samples were submitted for analysis. The service is offered voluntarily at harm reduction agencies that include supervised consumption services. Samples were analyzed using gas chromatography–mass spectrometry or liquid chromatography-high resolution mass spectrometry. Targeted and/or untargeted screens for psychoactive substances were undertaken. Results In September 2020, xylazine was first detected by Toronto’s Drug Checking Service. Among samples analyzed from September 2020 to February 2021 expected to contain fentanyl in isolation (610) or in combination with methamphetamine (16), xylazine was detected in 46 samples (7.2% and 12.5% of samples, respectively). Samples were predominantly drawn from used drug equipment. Three of the samples containing xylazine (6.5%) were associated with an overdose. Conclusion We present the first detection of xylazine in Toronto, North America’s fourth-largest metropolitan area. The increased risk of overdose associated with use of xylazine and its detection within our setting highlights the importance of drug checking services in supporting rapid responses to the emergence of potentially harmful adulterants. These data also highlight the clinical challenges presented by the dynamic nature of unregulated drug markets and the concomitant need to establish regulatory structures to reduce their contribution to overdose morbidity and mortality.

scholarly journals Monitoring EDTA and endogenous metabolite biomarkers from serum with mass spectrometry

2005 ◽  
Vol 19 (3) ◽  
pp. 137-146 ◽  
Author(s):  
Rachel Lowe ◽  
Eden P. Go ◽  
Grace C. Tong ◽  
Nicolas H. Voelcker ◽  
Gary Siuzdak
Keyword(s):  
Mass Spectrometry ◽  
Ethylenediaminetetraacetic Acid ◽  
Limit Of Detection ◽  
Free Acid ◽  
Direct Analysis ◽  
Gas Chromatography Mass Spectrometry ◽  
Esi Ms ◽  
C Isotopes ◽  
Endogenous Metabolites

We describe a quantitative method for the determination of ethylenediaminetetraacetic acid (EDTA) in human serum by gas chromatography mass spectrometry (GC-MS), liquid chromatography electrospray ionisation tandem mass spectrometry (LC-ESI-MS/MS), and desorption ionisation on silicon mass spectrometry (DIOS-MS). In the initial stages of the analysis, endogenous metabolites (1-palmitoyl-sn-glycero-3-phosphocholine and 1-stearoyl-sn-glycero-3-phosphocholine) were readily observed in LC-ESI-MS and DIOS-MS however, direct analysis of the EDTA free acid had limited sensitivity. In order to improve EDTA detection we employed a straightforward esterification derivatization. The most successful derivatization procedure converted EDTA to its methyl ester and, since13C isotopes of these reagents are readily available, internal standards could be easily generated for quantitative analysis. This approach provided a limit of detection of 0.5 and 0.1 μM for GC-MS and LC-ESI-MS, and offers a viable method for the EDTA detection.

scholarly journals Biochemical and genetic approaches to the prenatal diagnosis of propionic acidemia in 78 pregnancies

2020 ◽  
Vol 15 (1) ◽  
Author(s):  
Mengyao Dai ◽  
Bing Xiao ◽  
Huiwen Zhang ◽  
Jun Ye ◽  
Wenjuan Qiu ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Prenatal Diagnosis ◽  
Reliability And Validity ◽  
Metabolite Profile ◽  
Propionic Acidemia ◽  
Gas Chromatography Mass Spectrometry ◽  
Prenatal Diagnostic ◽  
Increased Risk ◽  
Significant Difference ◽  
Hydroxypropionic Acid

Abstract Background Propionic acidemia (PA) is a serious metabolic disorder, and different approaches have been applied to its prenatal diagnosis. To evaluate the reliability and validity of a biochemical strategy in the prenatal diagnosis of PA, we conducted a retrospective study of our 11-year experiences at a single center. Methods We accumulated data from 78 pregnancies from 58 families referred to our center and provided prenatal diagnosis by directed genetic analysis and/or metabolite measurement using tandem mass spectrometry (MS/MS) and gas chromatography/mass spectrometry (GC/MS) of amniotic fluid (AF) samples. Results Sixty-five unaffected fetuses (83.33%) and 13 affected fetuses (16.67%) were confirmed in our study. The characteristic metabolites including propionylcarnitine (C3) level, C3/acetylcarnitine (C2) ratio and 2-methylcitric acid (2MCA) level in unaffected and affected groups showed significant differences (P < 0.0001), while the level of 3-hydroxypropionic acid (3HPA) showed no significant difference between the two groups (P > 0.05).Of the 78 pregnancies, 24 fetuses were found to have either one causative pathogenic variant or were without genetic information in the proband. Three of these fetuses had elevated AF levels of C3, C3/C2 ratio, and 2MCA and, thus, were determined to be affected, while the remaining fetuses were determined to be unaffected based on a normal AF metabolite profile. Our genetic and biochemical results were highly consistent with postnatal follow-up results on all unaffected fetuses. Conclusions We conclude that a biochemical approach can serve as a fast and convenient prenatal diagnostic method for pregnancies at an increased risk for PA, which could be used in conjunction with genetic testing for precise prenatal diagnosis of this disorder. In our analysis, the characteristic metabolites C3 level, C3/C2 ratio, and 2MCA level in AF supernatant were dependable biochemical markers for diagnosis, of which the C3/C2 ratio appears to be the most reliable biochemical marker for the prenatal diagnosis of PA.

scholarly journals Metabolic biomarker signature to differentiate pancreatic ductal adenocarcinoma from chronic pancreatitis

Gut ◽  
2017 ◽  
Vol 67 (1) ◽  
pp. 128-137 ◽  
Author(s):  
Julia Mayerle ◽  
Holger Kalthoff ◽  
Regina Reszka ◽  
Beate Kamlage ◽  
Erik Peter ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Pancreatic Cancer ◽  
Chronic Pancreatitis ◽  
Pancreatic Ductal Adenocarcinoma ◽  
Ductal Adenocarcinoma ◽  
Diagnostic Purpose ◽  
Training Set ◽  
Test Set ◽  
Increased Risk ◽  
Biomarker Signature

ObjectiveCurrent non-invasive diagnostic tests can distinguish between pancreatic cancer (pancreatic ductal adenocarcinoma (PDAC)) and chronic pancreatitis (CP) in only about two thirds of patients. We have searched for blood-derived metabolite biomarkers for this diagnostic purpose.DesignFor a case–control study in three tertiary referral centres, 914 subjects were prospectively recruited with PDAC (n=271), CP (n=282), liver cirrhosis (n=100) or healthy as well as non-pancreatic disease controls (n=261) in three consecutive studies. Metabolomic profiles of plasma and serum samples were generated from 477 metabolites identified by gas chromatography–mass spectrometry and liquid chromatography–tandem mass spectrometry.ResultsA biomarker signature (nine metabolites and additionally CA19-9) was identified for the differential diagnosis between PDAC and CP. The biomarker signature distinguished PDAC from CP in the training set with an area under the curve (AUC) of 0.96 (95% CI 0.93–0.98). The biomarker signature cut-off of 0.384 at 85% fixed specificity showed a sensitivity of 94.9% (95% CI 87.0%–97.0%). In the test set, an AUC of 0.94 (95% CI 0.91–0.97) and, using the same cut-off, a sensitivity of 89.9% (95% CI 81.0%–95.5%) and a specificity of 91.3% (95% CI 82.8%–96.4%) were achieved, successfully validating the biomarker signature.ConclusionsIn patients with CP with an increased risk for pancreatic cancer (cumulative incidence 1.95%), the performance of this biomarker signature results in a negative predictive value of 99.9% (95% CI 99.7%–99.9%) (training set) and 99.8% (95% CI 99.6%–99.9%) (test set). In one third of our patients, the clinical use of this biomarker signature would have improved diagnosis and treatment stratification in comparison to CA19-9.

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