Relationship between Excreted Uremic Toxins and Degree of Disorder of Children with ASD.

Autism spectrum disorder (ASD) is a complex developmental disorder in which communication and behavior are affected. A number of studies have investigated potential biomarkers, including uremic toxins. The aim of our study was to determine uremic toxins in the urine of children with ASD (143) and compare the results with healthy children (48). Uremic toxins were determined with a validated high-performance liquid chromatography coupled to mass spectrometry (LC-MS/MS) method. We observed higher levels of p-cresyl sulphate (pCS) and indoxyl sulphate (IS) in the ASD group compared to the controls. Moreover, the toxin levels of trimethylamine N-oxide (TMAO), symmetric dimethylarginine (SDMA), and asymmetric dimethylarginine (ADMA) were lower in ASD patients. Similarly, for pCS and IS in children classified, according to the intensity of their symptoms, into mild, moderate, and severe, elevated levels of these compounds were observed. For mild severity of the disorder, elevated levels of TMAO and comparable levels of SDMA and ADMA for ASD children as compared to the controls were observed in the urine. For moderate severity of ASD, significantly elevated levels of TMAO but reduced levels of SDMA and ADMA were observed in the urine of ASD children as compared to the controls. When the results obtained for severe ASD severity were considered, reduced levels of TMAO and comparable levels of SDMA and ADMA were observed in ASD children.

Comparison of ADVIA Centaur ultra-sensitive and high-sensitive assays for troponin I in serum.

Cardiac troponin I (cTnI) is a standard biomarker for the diagnosis of acute myocardial infarction (AMI). While older, ultra-sensitive cTnI (us-cTnI) assays use the 99th percentile as the reference threshold, newer high-sensitive cTnI (hs-cTnI) assays use the limit of detection or functional sensitivity instead. However, little has been done to systematically compare these two methods. The present study also served as a validation of hs-cTnI in our laboratory. Here, we compared the results obtained from the blood serum obtained from 8810 patients using the us-cTnI and the hs-cTnI assays run in tandem on the ADVIA Centaur XP analyser. We found that in 2279 samples the concentration of cTnI measured with the ultra-sensitive method was below the detection limit, while with the high-sensitive method, only 540 were below the detection limit. We also compared results from these assays with the ultimate diagnosis of a subset of individuals. The analysis of the results below cut-off with the ultra-sensitive method showed that this method would not detect 96 cases related to heart disorder. Overall, the main finding of our research is that hs-cTnI is the preferable option and is able to be deployed effectively in the laboratory setting.

Point-of-care high-sensitivity assay on PATHFAST as the backup in the emergency room.

Aim: Although the levels of cardiac troponin I (cTnI) have proved to be a useful diagnostic biomarker of acute myocardial infarction, there are a wide variety of point-of-care (POC) analysers, which provide measurements of cTnI. The aim of this study was to compare the results obtained by the ADVIA Centaur ultra-assay cTnI assay (us-cTnI), ADVIA Centaur high-sensitive cTnI assay (hs-cTnI) and a POC high-sensitivity assay using PATHFAST. We also aimed to explore total turnaround time (TAT) for laboratory results using the POC PATHFAST analyser. Methods: Samples from 161 patients were taken. Of these samples, 129 were tested with all three assays (us-cTnI, hs-cTnI and PATHFAST), and 32 samples were tested on PATHFAST for the comparison of whole blood, serum and plasma. Results: Comparison of the POC testing methods in this study demonstrated that there are strong linear relationships between all three cTnI assays (us-cTnI, hs-cTnI and POC on PATHFAST). Furthermore, we also show there are strong linear relationships between the two high-sensitive cTnI assays (hs-cTnI and PATHFAST) for blood serum samples, as determined by Passing-Bablok regression analyses. In our comparison of our new data with our older study, the TAT went down. Conclusion: The timeliness of laboratory results is, in addition to accuracy and precision, one of the key indicators of laboratory performance, and at the same time has a significant impact on the course of the patient's condition. It is therefore important that the laboratory strives to meet the expectations of clinicians regarding the time from the order to the result of the analysis.

Urinary Markers of Oxidative Stress in Children with Autism Spectrum Disorder (ASD).

Background: Autism spectrum disorder (ASD) is a developmental disorder characterized by deficits in social interaction, restricted interest and repetitive behavior. Oxidative stress in response to environmental exposure plays a role in virtually every human disease and represents a significant avenue of research into the etiology of ASD. The aim of this study was to explore the diagnostic utility of four urinary biomarkers of oxidative stress. Methods: One hundred and thirty-nine (139) children and adolescents with ASD (89% male, average age = 10.0 years, age range = 2.1 to 18.1 years) and 47 healthy children and adolescents (49% male, average age 9.2, age range = 2.5 to 20.8 years) were recruited for this study. Their urinary 8-OH-dG, 8-isoprostane, dityrosine and hexanoil-lisine were determined by using the ELISA method. Urinary creatinine was determined with the kinetic Jaffee reaction and was used to normalize all biochemical measurements. Non-parametric tests and support vector machines (SVM) with three different kernel functions (linear, radial, polynomial) were used to explore and optimize the multivariate prediction of an ASD diagnosis based on the collected biochemical measurements. The SVM models were first trained using data from a random subset of children and adolescents from the ASD group (n = 70, 90% male, average age = 9.7 years, age range = 2.1 to 17.8 years) and the control group (n = 24, 45.8% male, average age = 9.4 years, age range = 2.5 to 20.8 years) using bootstrapping, with additional synthetic minority over-sampling (SMOTE), which was utilized because of unbalanced data. The computed SVM models were then validated using the remaining data from children and adolescents from the ASD (n = 69, 88% male, average age = 10.2 years, age range = 4.3 to 18.1 years) and the control group (n = 23, 52.2% male, average age = 8.9 years, age range = 2.6 to 16.7 years). Results: Using a non-parametric test, we found a trend showing that the urinary 8-OH-dG concentration was lower in children with ASD compared to the control group (unadjusted p = 0.085). When all four biochemical measurements were combined using SVMs with a radial kernel function, we could predict an ASD diagnosis with a balanced accuracy of 73.4%, thereby accounting for an estimated 20.8% of variance (p < 0.001). The predictive accuracy expressed as the area under the curve (AUC) was solid (95% CI = 0.691-0.908). Using the validation data, we achieved significantly lower rates of classification accuracy as expressed by the balanced accuracy (60.1%), the AUC (95% CI = 0.502-0.781) and the percentage of explained variance (R2 = 3.8%). Although the radial SVMs showed less predictive power using the validation data, they do, together with ratings of standardized SVM variable importance, provide some indication that urinary levels of 8-OH-dG and 8-isoprostane are predictive of an ASD diagnosis. Conclusions: Our results indicate that the examined urinary biomarkers in combination may differentiate children with ASD from healthy peers to a significant extent. However, the etiological importance of these findings is difficult to assesses, due to the high-dimensional nature of SVMs and a radial kernel function. Nonetheless, our results show that machine learning methods may provide significant insight into ASD and other disorders that could be related to oxidative stress.