Quantitative determination of potential urine biomarkers of respiratory illnesses using new targeted metabolomic approach

Western Economic Diversification Canada, AllerGen NCE, Saskatchewan Health Research FoundationPeer ReviewedThe diagnosis of asthma and chronic obstructive pulmonary disease (COPD) can be challenging due to the overlap in their clinical presentations in some patients. There is a need for a more objective clinical test that can be routinely used in primary care settings. Through an untargeted 1H NMR urine metabolomic approach, we identified a set of endogenous metabolites as potential biomarkers for the differentiation of asthma and COPD. A subset of these potential biomarkers contains 7 highly polar metabolites of diverse physicochemical properties. To the best of our knowledge, there is no liquid chromatography-tandem mass spectrometry (LC-MS/MS) method that evaluated more than two of the target metabolites in a single analytical run. The target metabolites belong to the families of monosaccharides, organic acids, amino acids, quaternary ammonium compounds and nucleic acids, rendering hydrophilic interaction liquid chromatography (HILIC) an ideal technology for their quantification. Since a clinical decision is to be made from patients data, a fully validated analytical method is required for biomarker validation. Method validation for endogenous metabolites is a daunting task since current guidelines were designed for exogenous compounds. As such, innovative approaches were adopted to meet the validation requirements. Herein, we describe a sensitive HILIC-MS/MS method for the quantification of the 7 endogenous urinary metabolites. Detection was achieved in the multiple reaction monitoring (MRM) mode with polarity switching, using quadrupole-linear ion trap instrument (QTRAP 6500) as well as single ion monitoring in the negative-ion mode. The method was fully validated according to the regulatory guidelines. Linearity was established between 6 and 21000 ng/mL and quality control samples demonstrated acceptable intra- and inter-day accuracy (85.7%-112%), intra- and inter-day precision (CV% <11.5%) as well as stability under various storage and sample processing conditions. To illustrate the method's applicability, the validated method was applied to the analysis of a small set of urine samples collected from asthma and COPD patients. Preliminary modelling of separation was generated using partial least square discriminant analysis (R2 0.752 and Q2 0.57). The adequate separation between patient samples confirms the diagnostic potential of these target metabolites as a proof-of-concept for the differentiation between asthma and COPD. However, more patient urine samples are needed in order to increase the statistical power of the analytical model

Mass Spectrometric Based Approaches in Urine Metabolomics and Biomarker Discovery

Urine metabolomics has recently emerged as a prominent field for the discovery of non-invasive biomarkers that can detect subtle metabolic discrepancies in response to a specific disease or therapeutic intervention. Urine, compared to other biofluids, is characterized by its ease of collection, richness in metabolites and its ability to reflect imbalances of all biochemical pathways within the body. Following urine collection for metabolomic analysis, samples must be immediately frozen to quench any biogenic and/or non-biogenic chemical reactions. According to the aim of the experiment; sample preparation can vary from simple procedures such as filtration to more specific extraction protocols such as liquid-liquid extraction. Due to the lack of comprehensive studies on urine metabolome stability, higher storage temperatures (i.e. 4 °C) and repetitive freeze-thaw cycles should be avoided. To date, among all analytical techniques, mass spectrometry (MS) provides the best sensitivity, selectivity and identification capabilities to analyze the majority of the metabolite composition in the urine. Combined with the qualitative and quantitative capabilities of MS, and due to the continuous improvements in its related technologies (i.e. ultra high-performance liquid chromatography [UPLC] and hydrophilic interaction liquid chromatography [HILIC]), liquid chromatography (LC)-MS is unequivocally the most utilized and the most informative analytical tool employed in urine metabolomics. Furthermore, differential isotope tagging techniques has provided a solution to ion suppression from urine matrix thus allowing for quantitative analysis. In addition to LC-MS, other MS-based technologies have been utilized in urine metabolomics. These include direct injection (infusion)-MS, capillary electrophoresis-MS and gas chromatography-MS. In this article, the current progresses of different MS-based techniques in exploring the urine metabolome as well as the recent findings in providing potentially diagnostic urinary biomarkers are discussed

Development of a validated LC- MS/MS method for the quantification of 19 endogenous asthma/COPD potential urinary biomarkers

Saskatchewan Health Research Foundation; AllerGen NCE Inc; Canada Foundation for Innovation; College of Pharmacy and Nutrition, University of SaskatchewanPeer ReviewedObstructive airways inflammatory diseases sometimes show overlapping symptoms that hinder their early and correct diagnosis. Current clinical tests are tedious and are of inadequate specificity in special population such as the elderly and children. Therefore, we are developing tandem mass spectrometric (MS/MS) methods for targeted analysis of urine biomarkers. Recently, proton-nuclear magnetic resonance (1H-NMR) analysis proposed 50 urinary metabolites as potential diagnostic biomarkers among asthma and chronic obstructive pulmonary disease (COPD) patients. Metabolites are divided into 3 groups based on chemical nature. For group 1 (amines and phenols, 19 urinary metabolites), we developed and validated a high performance liquid chromatographic (HPLC)-MS/MS method using differential isotope labeling with dansyl chloride. Method development included the optimization of the derivatization reaction, the MS/MS conditions, and the chromatographic separation. Linearity varied from 2 to 4800 ng/mL and the use of 13C2-labeled derivatives allowed for the correction of matrix effects as well as the unambiguous confirmation of the identity of each metabolite in the presence of interfering isomers in urine. Despite the challenges associated with method validation, the method was fully validated as per the food and drug administration (FDA) and the European medicines agency (EMA) recommendations. Validation criteria included linearity, precision, accuracy, dilution integrity, selectivity, carryover, and stability. Challenges in selectivity experiments included the isotopic contributions of the analyte towards its internal standard (IS), that was addressed via the optimization of the IS concentration. In addition, incurred sample analysis was performed to ensure that results from patient samples are accurate and reliable. The method was robust and reproducible and is currently being applied in a cohort of asthma and COPD patient urine samples for biomarker discovery purposes

Comparison of accuracy and precision between multipoint calibration, single point calibration and relative quantification for targeted metabolomic analysis

Natural Sciences and Engineering Research Council of Canada (NSERC); Western Economic Diversification CanadaPeer ReviewedTargeted metabolomics requires accurate and precise quantification of candidate biomarkers, often through tandem mass spectrometric (MS/MS) analysis. Differential isotope labeling (DIL) improves mass spectrometric (MS) analysis in metabolomics by derivatizing metabolites with two isotopic forms of the same reagent. Despite its advantages, DIL-liquid chromatographic (LC)-MS/MS can result in substantial increase in workload when fully validated quantitative methods are required. To decrease the workload, we hypothesized that single point calibration or relative quantification could be used as alternative methods. Either approach will result in significant saving in resources and time. To test our hypothesis, six urinary metabolites were selected as model compounds. Urine samples were analyzed using a fully-validated multipoint dansyl chloride-DIL-LC-MS/MS method. Samples were reprocessed using single point calibration and relative quantification modes. Our results demonstrated that the performance of single point calibration or relative quantification was inferior, for some metabolites, to multipoint calibration. The lower limit of quantification failed in the quantification of ethanolamine in most of participant samples using single point calibration. In addition, its precision was not acceptable in one participant during serine and ethanolamine quantification. On the other hand, relative quantification resulted in the least accurate data. In fact, none of the data generated from relative quantification for serine was comparable to that obtained from multipoint calibration. Finally, while single point calibration showed an overall acceptable performance for the majority of the model compounds, we cannot extrapolate the findings to other metabolites within the same analytical run. Analysts are advised to assess accuracy and precision for each metabolite in which single point calibration is the intended quantification mean

Analysis of a Series of Chlorogenic Acid Isomers using Differential Ion Mobility and Tandem Mass Spectrometry

Canada Foundation for InnovationChlorogenic acids are among the most abundant phenolics found in the human diet. Of these, the mono-caffeoylquinic acids are the predominant phenolics found in fruits, such as apples and pears, and products derived from them. In this research, a comprehensive study of the electrospray ionization (ESI) tandem mass spectrometric (MS/MS) dissociation behavior of the three most common mono-caffeoylquinic acids, namely 5-O-caffeoylquinic acid (5-CQA), 3-O-caffeoylquinic acid (3-CQA) and 4-O-caffeoylquinic acid (4-CQA), were determined using both positive and negative ionization. All proposed structures of the observed product ions were confirmed with second-generation MS3 experiments. Similarities and differences between the dissociation pathways in the positive and negative ion modes are discussed, confirming the proposed structures and the established MS/MS fingerprints. MS/MS dissociation was primarily driven via the cleavage of the ester bond linking the quinic acid moiety to the caffeic acid moiety within tested molecules. Despite being structural isomers with the same m/z values and dissociation behaviors, the MS/MS data in the negative ion mode was able to differentiate the three isomers based on ion intensity for the major product ions, observed at m/z 191, 178 and 171. This differentiation was consistent among various MS instruments. In addition, ESI coupled with high-field asymmetric waveform ion mobility spectrometry-mass spectrometry (ESI-FAIMS-MS) was employed for the separation of these compounds for the first time. By combining MS/MS data and differential ion mobility, a method for the separation and identification of mono-caffeoylquinic in apple/pear juice samples was developed with a run time of less than one minute. It is envisaged that this methodology could be used to identify pure juices based on their chlorogenic acid profile (i.e., metabolomics), and could also be used to detect juice-to-juice adulteration (e.g., apple juice addition to pear juice)

Comparative analysis of creatinine and osmolality as urine normalization strategies in targeted metabolomics for the differential diagnosis of asthma and COPD

Peer ReviewedIntroduction Urine is an ideal matrix for metabolomics investigation due to its non-invasive nature of collection and its rich metabolite content. Despite the advancements in mass spectrometry and 1H-NMR platforms in urine metabolomics, the statistical analysis of the generated data is challenged with the need to adjust for the hydration status of the person. Normalization to creatinine or osmolality values are the most adopted strategies, however, each technique has its challenges that can hinder its wide application. Objective Assessment of whether the statistical model established using a targeted urine metabolomics dataset for the differential diagnosis of asthma and chronic obstructive pulmonary disease (COPD) would be improved by normalization to osmolality instead of creatinine. Methods A metabolomics dataset from 51 patient urine samples previously analyzed using two liquid chromatography-tandem mass spectrometry methods was used. The data was normalized to creatinine and osmolality. The statistical analysis was achieved using partial least square discriminant analysis and models of separation were generated and compared. Results Creatinine and osmolality values in asthma and COPD patients were strongly correlated. Using the same metabolites, we found that normalization to osmolality did not significantly change the results. The metabolites of importance in separation remained the same for both methods. The statistical strength of the creatinine model was somewhat better than the osmolality normalized model (R2Q2=0.919, 0.705 vs R2Q2 =0.929, 0.671). Conclusion Our findings suggest that targeted urine metabolomics data can be normalized to creatinine or osmolality with no significant impact on the diagnostic accuracy of the model

Virtual reality socialization groups on Facebook: A new frontier for children with social anxiety disorder

As a potential treatment intervention for youngsters with Social Anxiety Disorder (SAD) in UAE, this study aims to investigate the use of virtual reality socialization groups on the widely used social media platform Facebook. The purpose of this research is to examine how social anxiety, sadness, and anxiety symptoms change after receiving treatment. The quantitative approach used in the study yields very small impact sizes. No discernible differences emerged, however, between the test and control groups at the statistical level. It investigates how cultural factors, including the unique social norms and expectations in UAE, play a crucial role in determining the success of interventions. Specifically adapted virtual reality therapies for various cultural settings are emphasized. In addition, it highlights the importance of understanding the therapeutic implications of small effect sizes. Prospective research directions are explored in this article; special attention is paid to the development of ever-better technologically-driven treatments across a variety of cultural settings

Impact of opioid-free analgesia on pain severity and patient satisfaction after discharge from surgery: multispecialty, prospective cohort study in 25 countries

Background: Balancing opioid stewardship and the need for adequate analgesia following discharge after surgery is challenging. This study aimed to compare the outcomes for patients discharged with opioid versus opioid-free analgesia after common surgical procedures.Methods: This international, multicentre, prospective cohort study collected data from patients undergoing common acute and elective general surgical, urological, gynaecological, and orthopaedic procedures. The primary outcomes were patient-reported time in severe pain measured on a numerical analogue scale from 0 to 100% and patient-reported satisfaction with pain relief during the first week following discharge. Data were collected by in-hospital chart review and patient telephone interview 1 week after discharge.Results: The study recruited 4273 patients from 144 centres in 25 countries; 1311 patients (30.7%) were prescribed opioid analgesia at discharge. Patients reported being in severe pain for 10 (i.q.r. 1-30)% of the first week after discharge and rated satisfaction with analgesia as 90 (i.q.r. 80-100) of 100. After adjustment for confounders, opioid analgesia on discharge was independently associated with increased pain severity (risk ratio 1.52, 95% c.i. 1.31 to 1.76; P &lt; 0.001) and re-presentation to healthcare providers owing to side-effects of medication (OR 2.38, 95% c.i. 1.36 to 4.17; P = 0.004), but not with satisfaction with analgesia (beta coefficient 0.92, 95% c.i. -1.52 to 3.36; P = 0.468) compared with opioid-free analgesia. Although opioid prescribing varied greatly between high-income and low- and middle-income countries, patient-reported outcomes did not.Conclusion: Opioid analgesia prescription on surgical discharge is associated with a higher risk of re-presentation owing to side-effects of medication and increased patient-reported pain, but not with changes in patient-reported satisfaction. Opioid-free discharge analgesia should be adopted routinely

Metabolomic analysis of urine for improving the diagnosis of asthma and COPD

Asthma and chronic obstructive pulmonary disease (COPD) are chronic inflammatory respiratory illnesses with increasing mortality rates. Despite distinct pathophysiological differences, the differential diagnosis of these diseases can be challenging in some patients. Currently, physicians rely on patients’ history and therapy trials leading to misdiagnoses and disease management errors. Therefore, better diagnostic tests are needed. A recent untargeted proton nuclear magnetic resonance (1H-NMR) metabolomics study revealed 50 urine metabolites as candidate biomarkers for differentiating asthma from COPD. Since clinical validation of candidate biomarkers requires robust assays, we developed liquid chromatography-tandem mass spectrometric (LC-MS/MS) methods to meet this purpose. The metabolites were divided into four subgroups based on structure/concentration. Differential isotope labeling and hydrophilic interaction LC were utilized for method development. Methods were fully validated for clinical testing according to the FDA and European Medicines Agency guidelines. Two strategies of urine normalization were evaluated (creatinine vs. osmolality). Urine samples from asthma (n=51) and COPD (n=78) patients were analyzed for 41 metabolites and statistical analysis was performed using partial least square-discriminant analysis (PLS-DA). The endogenous nature of the metabolites sometimes hindered the direct application of the regulatory validation guidelines. Accordingly, novel approaches were adopted to address the unexpected challenges. For example, since metabolite-free urine is not available, blank surrogate matrix and pooled urine were used during validation. The isotopic interference from the metabolites on their internal standards dictated atypical optimization and validation experiments. PLS-DA successfully separated asthma from COPD using a validated model (R2Y= 0.851, Q2= 0.759). Nineteen metabolites were identified as the most significant biomarkers for disease differentiation. To test the model, 27 samples were run blindly resulting in 82% accuracy. The involved biochemical pathways were identified. To expedite sample analysis, we compared between absolute (fully validated), relative and single point quantification strategies, since the last two are widely used in metabolomics studies. In general, while the three methods were precise, the fully validated method provided the most accurate data. Finally, to test the ruggedness of the analytical platforms, 17 urine samples were reprocessed after 28-months storage. The PLS-DA classification of the reanalyzed samples was 100% identical to their initial results

DETERMINANTS OF CEREAL CONSUMPTION IN EGYPT AND SOME MIDDLE EASTERN COUNTRIES

This study depend on the results of the study prepared by the World Bank (WB), the United Nations Development Program (UNDP) and the Food and Agriculture Organization of the United Nations (FAO) in order to indicate and analyze the average individual cereal consumption in Egypt and some neighboring countries. The consumption of wheat is ranked first in all countries of the study sample. Consumption of maize comes in second place after consumption of wheat in the countries of the study sample in Africa continent. Consumption of rice is also comes second only to consumption of wheat in the sample countries in Asia continent.     The difference between the average cereal consumption in Egypt and the average cereal consumption in Algeria was about 35.2 kg. This difference is attributed to the total determinants studied as follows:  6.2% due to the percentage of average years of education, 87.3% 17.8% attributable to the percentage of average per capita consumption of maize, -27.5% attributable to the percentage of average per capita consumption of wheat, 11.2% attributed to the percentage of corn / rice import price. In general, it is found that the percentage of rural / urban population is primarily responsible for the difference between the average cereal consumption in Egypt and the average cereal consumption in Egypt's neighboring countries,  followed by average per capita consumption of wheat and average per capita consumption of maize