Baharudin Ibrahim

Non-invasive phenotyping using exhaled volatile organic compounds in asthma

Background Breath volatile organic compounds (VOCs) may be useful for asthma diagnosis and phenotyping, identifying patients who could benefit from personalised therapeutic strategies. The authors aimed to identify specific patterns of breath VOCs in patients with asthma and in clinically relevant disease phenotypes. Methods Breath samples were analysed by gas chromatography–mass spectrometry. The Asthma Control Questionnaire was completed, together with lung function and induced sputum cell counts. Breath data were reduced to principal components, and these principal components were used in multiple logistic regression to identify discriminatory models for diagnosis, sputum inflammatory cell profile and asthma control. Results The authors recruited 35 patients with asthma and 23 matched controls. A model derived from 15 VOCs classified patients with asthma with an accuracy of 86%, and positive and negative predictive values of 0.85 and 0.89, respectively. Models also classified patients with asthma based on the following phenotypes: sputum (obtained in 18 patients with asthma) eosinophilia ≥2% area under the receiver operating characteristics (AUROC) curve 0.98, neutrophilia ≥40% AUROC 0.90 and uncontrolled asthma (Asthma Control Questionnaire ≥1) AUROC 0.96. Conclusions Detection of characteristic breath VOC profiles could classify patients with asthma versus controls, and clinically relevant disease phenotypes based on sputum inflammatory profile and asthma control. Prospective validation of these models may lead to clinical application of non-invasive breath profiling in asthma.

Exhaled volatile organic compounds for phenotyping chronic obstructive pulmonary disease: a cross-sectional study

BackgroundNon-invasive phenotyping of chronic respiratory diseases would be highly beneficial in the personalised medicine of the future. Volatile organic compounds can be measured in the exhaled breath and may be produced or altered by disease processes. We investigated whether distinct patterns of these compounds were present in chronic obstructive pulmonary disease (COPD) and clinically relevant disease phenotypes.MethodsBreath samples from 39 COPD subjects and 32 healthy controls were collected and analysed using gas chromatography time-of-flight mass spectrometry. Subjects with COPD also underwent sputum induction. Discriminatory compounds were identified by univariate logistic regression followed by multivariate analysis: 1. principal component analysis; 2. multivariate logistic regression; 3. receiver operating characteristic (ROC) analysis.ResultsComparing COPD versus healthy controls, principal component analysis clustered the 20 best-discriminating compounds into four components explaining 71% of the variance. Multivariate logistic regression constructed an optimised model using two components with an accuracy of 69%. The model had 85% sensitivity, 50% specificity and ROC area under the curve of 0.74. Analysis of COPD subgroups showed the method could classify COPD subjects with far greater accuracy. Models were constructed which classified subjects with ≥2% sputum eosinophilia with ROC area under the curve of 0.94 and those having frequent exacerbations 0.95. Potential biomarkers correlated to clinical variables were identified in each subgroup.ConclusionThe exhaled breath volatile organic compound profile discriminated between COPD and healthy controls and identified clinically relevant COPD subgroups. If these findings are validated in prospective cohorts, they may have diagnostic and management value in this disease.

Breath metabolomic profiling by nuclear magnetic resonance spectroscopy in asthma.

Metabolomic profiling of exhaled breath condensate offers opportunities for the development of noninvasive diagnostics in asthma. We aimed to determine and validate discriminatory metabolomic profiles in adult asthma and to explore profiles in clinically relevant disease phenotypes.

The Personalization of Clopidogrel Antiplatelet Therapy: The Role of Integrative Pharmacogenetics and Pharmacometabolomics

Dual antiplatelet therapy of aspirin and clopidogrel is pivotal for patients undergoing percutaneous coronary intervention. However, the variable platelets reactivity response to clopidogrel may lead to outcome failure and recurrence of cardiovascular events. Although many genetic and nongenetic factors are known, great portion of clopidogrel variable platelets reactivity remain unexplained which challenges the personalization of clopidogrel therapy. Current methods for clopidogrel personalization include CYP2C19 genotyping, pharmacokinetics, and platelets function testing. However, these methods lack precise prediction of clopidogrel outcome, often leading to insufficient prediction. Pharmacometabolomics which is an approach to identify novel biomarkers of drug response or toxicity in biofluids has been investigated to predict drug response. The advantage of pharmacometabolomics is that it does not only predict the response but also provide extensive information on the metabolic pathways implicated with the response. Integrating pharmacogenetics with pharmacometabolomics can give insight on unknown genetic and nongenetic factors associated with the response. This review aimed to review the literature on factors associated with the variable platelets reactivity response to clopidogrel, as well as appraising current methods for the personalization of clopidogrel therapy. We also aimed to review the literature on using pharmacometabolomics approach to predict drug response, as well as discussing the plausibility of using it to predict clopidogrel outcome.

Metabolic phenotyping of urine for discriminating alcohol-dependent from social drinkers and alcohol-naive subjects.

BACKGROUND Alcohol-dependence (AD) is a ravaging public health and social problem. AD diagnosis depends on questionnaires and some biomarkers, which lack specificity and sensitivity, however, often leading to less precise diagnosis, as well as delaying treatment. This represents a great burden, not only on AD individuals but also on their families. Metabolomics using nuclear magnetic resonance spectroscopy (NMR) can provide novel techniques for the identification of novel biomarkers of AD. These putative biomarkers can facilitate early diagnosis of AD. 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.

The effect of CYP2C19 genetic polymorphism and non-genetic factors on clopidogrel platelets inhibition in East Asian coronary artery disease patients

Clopidogrel has essential role in dual antiplatelet therapy (DAPT). However, some patients suffer high on treatment platelets reactivity (HTPR) which may lead to recurrence of cardiac events. Among several genetic variabilities, the CYP2C19*2 and CYP2C19*3 alleles were significantly associated with clopidogrel HTPR [1]. Both alleles are more prevalent in East Asians compared to Caucasian and African Americas. In Malaysia, an East Asian population, clopidogrel HTPR and CYP2C19*2 are frequent [2,3]. However, CYP2C19*2 had modest role in clopidogrel HTPR, suggesting the interference of other clinical variables. In these reports, platelets function testing (PFT) were measured after standard clopidogrel loading dose (LD) (300 mg) or after at least 4 days of maintenance dose (MD) (75 mg). It has been suggested that high LD of clopidogrel (600 mg) can reduce clopidogrel HTPR [4]. The use of clopidogrel 600 mg LD is uncommon in Malaysian clinical practice [5]. To date, clopidogrel HTPR for LD 600 mg has not been reported in Malaysia. To that end, we investigated clopidogrel HTPR frequency post LD 600 mg and evaluated the effect of CYP2C19*2 and CYP2C19*3, as well as other clinical variables on platelets reactivity.

NMR-based plasma metabolomic discrimination for male fertility assessment of rats treated with Eurycoma longifolia extracts

ABSTRACT Male infertility is one of the leading causes of infertility which affects many couples worldwide. Semen analysis is a routine examination of male fertility status which is usually performed on semen samples obtained through masturbation that may be inconvenient to patients. Eurycoma longifolia (Tongkat Ali, TA), native to Malaysia, has been traditionally used as a remedy to boost male fertility. In our recent studies in rats, upon the administration of high-quassinoid content extracts of TA including TA water (TAW), quassinoid-rich TA (TAQR) extracts, and a low-quassinoid content extract including quassinoid-poor TA (TAQP) extract, sperm count (SC) increased in TAW- and TAQR-treated rats when compared to the TAQP-treated and control groups. Consequently, the rats were divided into normal- (control and TAQP-treated) and high- (TAW- and TAQR-treated) SC groups [Ebrahimi et al. 2016]. Post-treatment rat plasma was collected. An optimized plasma sample preparation method was developed with respect to the internal standards sodium 3- (trimethylsilyl) propionate- 2,2,3,3- d4 (TSP) and deuterated 4-dimethyl-4-silapentane-1-ammonium trifluoroacetate (DSA). Carr-Purcell-Meibum-Gill (CPMG) experiments combined with orthogonal partial least squares discriminant analysis (OPLS-DA) was employed to evaluate plasma metabolomic changes in normal- and high-SC rats. The potential biomarkers associated with SC increase were investigated to assess fertility by capturing the metabolomic profile of plasma. DSA was selected as the optimized internal standard for plasma analysis due to its significantly smaller half-height line width (W h/2) compared to that of TSP. The validated OPLS-DA model clearly discriminated the CPMG profiles in regard to the SC level. Plasma profiles of the high-SC group contained higher levels of alanine, lactate, and histidine, while ethanol concentration was significantly higher in the normal-SC group. This approach might be a new alternative applicable to the fertility assessment in humans through the quantitative metabolomic analysis of plasma without requiring semen. Abbreviations: TA: Tongkat Ali; LOD: limit of detection; LOQ: limit of quantification; HPLC-UV: high performance liquid chromatography-ultrviolet; PDA: photodiode array; NMR: nuclear magnetic resonance; FID: free induction decay; LC-MS: liquid chromatography-mass spectrometry; GC-MS: gas chromatography-mass spectrometry; HSQC: heteronuclear single quantum coherence; CPMG: Carr-Purcell-Meibum-Gill; VLDL: very low density lipoprotein; HDL: high density lipoprotein; EDTA: ethylenediaminetetraacetic acid; ANOVA: analysis of variance; AMIX: analysis of mixtures; SIMCA: soft independent modeling of class analogy; PCA: principal components analysis; OPLS-DA: orthogonal partial least-squares discriminant analysis; VIP: variable importance plot; AUROC: area under the receiver operating characteristic; TSP: sodium 3-(trimethylsilyl) propionate- 2,2,3,3- d4; DSA: deuterated 4-dimethyl-4-silapentane-1-ammonium trifluoroacetate; ESI: electrospray ionization; TCA: trichloroacetic acid; ACN: acetonitrile; dd H2O: distilled deionized water; FSH: follicle-stimulating hormone; LH: luteinizing hormone; OECD: Organisation for Economic Co-operation and Development

Pharmacometabolomics analysis of plasma to phenotype clopidogrel high on treatment platelets reactivity in coronary artery disease patients

&NA; Dual antiplatelet therapy (DAPT) of clopidogrel and aspirin is crucial for coronary artery disease (CAD) patients undergoing percutaneous coronary intervention (PCI). However, some patients may endure clopidogrel high on treatment platelets reactivity (HTPR) which may cause thromboembolic events. Clopidogrel HTPR is multifactorial with some genetic and non‐genetic factors contributing to it. We aimed to use nuclear magnetic resonance (1H NMR) pharmacometabolomics analysis of plasma to investigate this multifactorial and identify metabolic phenotypes and pathways associated with clopidogrel HTPR. Blood samples were collected from 71 CAD patients planned for interventional angiographic procedure (IAP) before the administration of clopidogrel 600 mg loading dose (LD) and 6 h after the LD. Platelets function testing was done 6 h post‐LD using VerifyNow® P2Y12 assay. Pre‐dose and post‐dose plasma samples were analysed using 1H NMR. Multivariate statistical analysis was used to indicate the discriminating metabolites. Two metabotypes, each with 34 metabolites (pre‐dose and post‐dose) were associated with clopidogrel HTPR. Pathway analysis of these metabotypes revealed that aminoacyl‐tRNA biosynthesis, nitrogen metabolism and glycine‐serine‐threonine metabolism are the most perturbed metabolic pathways associated with clopidogrel HTPR. Furthermore, the identified biomarkers indicated that clopidogrel HTPR is multifactorial where the metabolic phenotypes of insulin resistance, type two diabetes mellitus, obesity, gut‐microbiota and heart failure are associated with it. Pharmacometabolomics analysis of plasma revealed new insights on the implicated metabolic pathways and the predisposing factors of clopidogrel HTPR. Graphical abstract Figure. No caption available.

Plasma metabolic biomarkers for discriminating individuals with alcohol use disorders from social drinkers and alcohol-naive subjects

BACKGROUND Alcohol use disorders (AUD) is a phase of alcohol misuse in which the drinker consumes excessive amount of alcohol and have a continuous urge to consume alcohol which may lead to various health complications. The current methods of alcohol use disorders diagnosis such as questionnaires and some biomarkers lack specificity and sensitivity. Metabolomics is a novel scientific field which may provide a novel method for the diagnosis of AUD by using a sensitive and specific technique such as nuclear magnetic resonance (NMR). METHODS A cross sectional study was conducted on three groups: individuals with alcohol use disorders (n=30), social drinkers (n=54) and alcohol-naive controls (n=60). 1H NMR-based metabolomics was used to obtain the metabolic profiles of plasma samples. Data were processed by multivariate principal component analysis (PCA) and orthogonal partial least squares-discriminant analysis (OPLS-DA) followed by univariate and multivariate logistic regressions to produce the best fit-model for discrimination between groups. RESULTS The OPLS-DA model was able to distinguish between the AUD group and the other groups with high sensitivity, specificity and accuracy of 64.29%, 98.17% and 91.24% respectively. The logistic regression model identified two biomarkers in plasma (propionic acid and acetic acid) as being significantly associated with alcohol use disorders. The reproducibility of all biomarkers was excellent (0.81-1.0). CONCLUSIONS The applied plasma metabolomics technique was able to differentiate the metabolites between AUD and the other groups. These metabolites are potential novel biomarkers for diagnosis of alcohol use disorders.

Urinary NMR-based metabolomic analysis of rats possessing variable sperm count following orally administered Eurycoma longifolia extracts of different quassinoid levels

ETHNOPHARMACOLOGICAL RELEVANCE Eurycoma longifolia (Tongkat Ali, TA) roots have been ethnically used as a remedy to boost male sexual desire, libido, energy and fertility. AIM OF THE STUDY The study evaluated the effect of TA extracts with different quassinoid levels on rats sperm count and examined corresponding post-treatment urinary metabolic changes. MATERIALS AND METHODS Twenty-four male Sprague-Dawley rats, categorized into 4 groups of 6 rats each, were orally administered for 48 days with water for the control (group 1), 125mg/kg of TA water extract (TAW, group 2), 125mg/kg of TA quassinoid-poor extract (TAQP, group 3) and 21mg/kg of TA quassinoid-rich extract (TAQR, group 4). Upon completion of the 48-day treatment, the urine samples were analyzed by NMR and the animals were subsequently sacrificed for sperm count analysis. The urine profiles were categorized according to sperm count level. RESULTS The results showed that the sperm count in TAW- and TAQR-treated groups was significantly higher compared to the TAQP-administered and control groups. The orthogonal partial least squares discriminant analysis (OPLS-DA) model indicated a clear separation among the urine profiles with respect to sperm count level. Urine (1)H-NMR profiles of the high-sperm count group contained higher concentrations of trigonelline, alanine, benzoic acid and higher intensity of a signal at 3.42ppm, while ethanol was at higher concentration in the normal-sperm count group. CONCLUSIONS The results proved the efficacy of quassinoids on sperm count increase in rats and provided quantitative markers in urine suitable for analysis of sperm profile and male fertility status.