METHODS: Urine samples were collected from pesticide applicators in Malaysia, Uganda, and the UK during mixing/application days (and also during non-application days in Uganda). Samples were collected pre- and post-activity on the same day and analysed for biomarkers of active ingredients (AIs), including synthetic pyrethroids (via the metabolite 3-phenoxybenzoic acid [3-PBA]) and glyphosate, as well as creatinine. We performed multilevel Tobit regression models for each study to assess the relationship between exposure modifying factors (e.g., mixing/application of AI, duration of activity, personal protective equipment [PPE]) and urinary biomarkers of exposure.
RESULTS: From the Malaysia, Uganda, and UK studies, 81, 84, and 106 study participants provided 162, 384 and 212 urine samples, respectively. Pyrethroid use on the sampling day was most common in Malaysia (n = 38; 47%), and glyphosate use was most prevalent in the UK (n = 93; 88%). Median pre- and post-activity 3-PBA concentrations were similar, with higher median concentrations post-compared to pre-activity for glyphosate samples in the UK (1.7 to 0.5 μg/L) and Uganda (7.6 to 0.8 μg/L) (glyphosate was not used in the Malaysia study). There was evidence from individual studies that higher urinary biomarker concentrations were associated with mixing/application of the AI on the day of urine sampling, longer duration of mixing/application, lower PPE protection, and less education/literacy, but no factor was consistently associated with exposure across biomarkers in the three studies.
CONCLUSIONS: Our results suggest a need for AI-specific interpretation of exposure modifying factors as the relevance of exposure routes, levels of detection, and farming systems/practices may be very context and AI-specific.
METHODS: C. elegans was aliquoted onto the center of assay plates and allowed to migrate towards sepsis (T) or control (C) urine samples spotted on the same plate. The number of worms found in either (T) or (C) was scored at 10-minute intervals over a 60-minute period.
RESULTS: The worms were able to identify the urine (<48 hours) of sepsis patients rapidly within 20 minutes (AUROC=0.67, p=0.012) and infection within 40 minutes (AUROC=0.80, p=0.016).
CONCLUSIONS: CESDA could be further explored for sepsis diagnosis.
OBJECTIVE: The aim of this review is to examine studies that focused on the different types of samples which may serve as a good and promising biomarker for early diagnosis of CKD or to detect rapidly declining renal function among CKD patient.
METHOD: The review of international literature was made on paper and electronic databases Nature, PubMed, Springer Link and Science Direct. The Scopus index was used to verify the scientific relevance of the papers. Publications were selected based on the inclusion and exclusion criteria.
RESULT: 63 publications were found to be compatible with the study objectives. Several biomarkers of interest with different sample types were taken for comparison.
CONCLUSION: Biomarkers from urine samples yield more significant outcome as compare to biomarkers from blood samples. But, validation and confirmation with a different type of study designed on a larger population is needed. More comparison studies on different types of samples are needed to further illuminate which biomarker is the better tool for the diagnosis and prognosis of CKD.
STUDY DESIGN: Literature-based meta-analysis and individual-study-data meta-analysis of diagnostic studies following PRISMA-IPD guidelines.
SETTING & STUDY POPULATIONS: Studies of adults investigating AKI, severe AKI, and AKI-D in the setting of cardiac surgery, intensive care, or emergency department care using either urinary or plasma NGAL measured on clinical laboratory platforms.
SELECTION CRITERIA FOR STUDIES: PubMed, Web of Science, Cochrane Library, Scopus, and congress abstracts ever published through February 2020 reporting diagnostic test studies of NGAL measured on clinical laboratory platforms to predict AKI.
DATA EXTRACTION: Individual-study-data meta-analysis was accomplished by giving authors data specifications tailored to their studies and requesting standardized patient-level data analysis.
ANALYTICAL APPROACH: Individual-study-data meta-analysis used a bivariate time-to-event model for interval-censored data from which discriminative ability (AUC) was characterized. NGAL cutoff concentrations at 95% sensitivity, 95% specificity, and optimal sensitivity and specificity were also estimated. Models incorporated as confounders the clinical setting and use versus nonuse of urine output as a criterion for AKI. A literature-based meta-analysis was also performed for all published studies including those for which the authors were unable to provide individual-study data analyses.
RESULTS: We included 52 observational studies involving 13,040 patients. We analyzed 30 data sets for the individual-study-data meta-analysis. For AKI, severe AKI, and AKI-D, numbers of events were 837, 304, and 103 for analyses of urinary NGAL, respectively; these values were 705, 271, and 178 for analyses of plasma NGAL. Discriminative performance was similar in both meta-analyses. Individual-study-data meta-analysis AUCs for urinary NGAL were 0.75 (95% CI, 0.73-0.76) and 0.80 (95% CI, 0.79-0.81) for severe AKI and AKI-D, respectively; for plasma NGAL, the corresponding AUCs were 0.80 (95% CI, 0.79-0.81) and 0.86 (95% CI, 0.84-0.86). Cutoff concentrations at 95% specificity for urinary NGAL were>580ng/mL with 27% sensitivity for severe AKI and>589ng/mL with 24% sensitivity for AKI-D. Corresponding cutoffs for plasma NGAL were>364ng/mL with 44% sensitivity and>546ng/mL with 26% sensitivity, respectively.
LIMITATIONS: Practice variability in initiation of dialysis. Imperfect harmonization of data across studies.
CONCLUSIONS: Urinary and plasma NGAL concentrations may identify patients at high risk for AKI in clinical research and practice. The cutoff concentrations reported in this study require prospective evaluation.
SUBJECTS/METHODS: A taste database including 467 foods' sweet, sour, bitter, salt, umami and fat sensation values was combined with food intake data to assess dietary taste patterns: the contribution to energy intake of 6 taste clusters. The FFQ's reliability was assessed against 3-d 24hR and urinary biomarkers for sodium (Na) and protein intake (N) in Dutch men (n = 449) and women (n = 397) from the NQplus validation study (mean age 53 ± 11 y, BMI 26 ± 4 kg/m2).
RESULTS: Correlations of dietary taste patterns ranged from 0.39-0.68 between FFQ and 24hR (p
CONCLUSION: The diagnosis of LPI is usually not suspected by clinical findings alone, and specific laboratory investigations and molecular analysis are important to get a definitive diagnosis.
OBJECTIVE: The purpose of this study was to determine the organophosphorus pesticide urinary metabolite levels and its predictors among Orang Asli children of the Mah Meri tribe living in an agricultural island in Kuala Langat, Selangor.
METHODS: Data collection was carried out at an island in Kuala Langat, Selangor, where a total of 180 Orang Asli children of the Mah Meri tribe voluntarily participated in the study. Data were collected via a validated, modified questionnaire. Urinary organophosphate metabolites, namely dimethylphosphate, diethylphosphate, dimethylthiophosphate, dimethyldithiophosphate, diethylthiophosphate, and diethyldithiophosphate were measured to assess organophosphate pesticide exposure in children.
FINDINGS: Eighty-four (46.7%) of the respondents were positive for urine dialkyl phosphate metabolites. In multivariable analysis, children who frequently consumed apples had 4 times higher risk of pesticide detection than those who consumed apple less frequently. In addition, those who frequently ate cucumbers had 4 times higher risk for pesticide detection than those who ate cucumbers less frequently. Children with a father whose occupation involved high exposure to pesticides (agriculture) had 3 times higher risk of pesticide detection than those with a father in a low-risk occupation (nonagriculture).
CONCLUSIONS: Almost half of the children (46.7%) in the study area tested positive for urinary dialkyl phosphate metabolite levels. Most of the metabolite levels were equal to or higher than that reported in other previous studies. Major factors associated with pesticide detection in children in this study were frequent intake of apple and cucumber and fathers who are working in an agricultural area.
OBJECTIVES: To identify novel biomarkers able to discriminate between alcohol-dependent, non-AD alcohol drinkers and controls using metabolomics.
METHOD: Urine samples were collected from 30 alcohol-dependent persons who did not yet start AD treatment, 54 social drinkers and 60 controls, who were then analysed using NMR. Data analysis was done using multivariate analysis including principal component analysis (PCA) and orthogonal partial least square-discriminate analysis (OPLS-DA), followed by univariate and multivariate logistic regression to develop the discriminatory model. The reproducibility was done using intraclass correlation coefficient (ICC).
RESULTS: The OPLS-DA revealed significant discrimination between AD and other groups with sensitivity 86.21%, specificity 97.25% and accuracy 94.93%. Six biomarkers were significantly associated with AD in the multivariate logistic regression model. These biomarkers were cis-aconitic acid, citric acid, alanine, lactic acid, 1,2-propanediol and 2-hydroxyisovaleric acid. The reproducibility of all biomarkers was excellent (0.81-1.0).
CONCLUSION: This study revealed that metabolomics analysis of urine using NMR identified AD novel biomarkers which can discriminate AD from social drinkers and controls with high accuracy.
METHODS: A cross-sectional study was performed involving SLE patients (n = 120 patients) from Universiti Kebangsaan Malaysia Medical Centre (UKMMC). Serum and urinary IL-17A levels were determined by immunoassay while disease activity was assessed using Systemic Lupus Erythematosus Disease Activity Index-2000 (SLEDAI-2K) and British Isles Lupus Assessment Group's 2004 index (BILAG 2004) scores. The correlations between serum and urinary IL-17A levels with total SLEDAI-2K and BILAG 2004 scores were determined using bivariate correlation analyses. Receiver operating characteristic curves were calculated to determine their sensitivity and specificity as disease activity biomarkers.
RESULTS: Both serum and urinary IL-17A levels correlated with total scores of BILAG 2004, BILAG renal, BILAG mucocutaneous, and SLEDAI-2K (P
METHODS: Warfarin relies on regular monitoring of International Normalized Ratio which is a standardized test to measure prothrombin time and appropriate dose adjustment. Pharmacometabonomics is a novel scientific field which deals with identification and quantification of the metabolites present in the metabolome using spectroscopic techniques such as Nuclear Magnetic Resonance (NMR). Pharmacometabonomics helps to indicate perturbation in the levels of metabolites in the cells and tissues due to drug or ingestion of any substance. NMR is one of the most widely-used spectroscopic techniques in metabolomics because of its reproducibility and speed.
RESULTS: There are many factors that influence the metabolism of warfarin, making changes in drug dosage common, and clinical factors like drug-drug interactions, dietary interactions and age explain for the most part the variability in warfarin dosing. Some studies have showed that pharmacogenetic testing for warfarin dosing does not improve health outcomes, and around 26% of the variation in warfarin dose requirements remains unexplained yet.
CONCLUSION: Many recent pharmacometabonomics studies have been conducted to identify novel biomarkers of drug therapies such as paracetamol, aspirin and simvastatin. Thus, a technique such as NMR based pharmacometabonomics to find novel biomarkers in plasma and urine might be useful to predict warfarin outcome.