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Profiles of Volatile Biomarkers Detect Tuberculosis from Skin.

ABSTRACT: Tuberculosis (TB) is an infectious disease that threatens >10 million people annually. Despite advances in TB diagnostics, patients continue to receive an insufficient diagnosis as TB symptoms are not specific. Many existing biodiagnostic tests are slow, have low clinical performance, and can be unsuitable for resource-limited settings. According to the World Health Organization (WHO), a rapid, sputum-free, and cost-effective triage test for real-time detection of TB is urgently needed. This article reports on a new diagnostic pathway enabling a noninvasive, fast, and highly accurate way of detecting TB. The approach relies on TB-specific volatile organic compounds (VOCs) that are detected and quantified from the skin headspace. A specifically designed nanomaterial-based sensors array translates these findings into a point-of-care diagnosis by discriminating between active pulmonary TB patients and controls with sensitivity above 90%. This fulfills the WHO's triage test requirements and poses the potential to become a TB triage test.

SUBMITTER: Vishinkin R

PROVIDER: S-EPMC8336503 | biostudies-literature | 2021 Aug

REPOSITORIES: biostudies-literature

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Profiles of Volatile Biomarkers Detect Tuberculosis from Skin.

Vishinkin Rotem R Busool Rami R Mansour Elias E Fish Falk F Esmail Ali A Kumar Parveen P Gharaa Alaa A Cancilla John C JC Torrecilla Jose S JS Skenders Girts G Leja Marcis M Dheda Keertan K Singh Sarman S Haick Hossam H

Advanced science (Weinheim, Baden-Wurttemberg, Germany) 20210602 15

Tuberculosis (TB) is an infectious disease that threatens >10 million people annually. Despite advances in TB diagnostics, patients continue to receive an insufficient diagnosis as TB symptoms are not specific. Many existing biodiagnostic tests are slow, have low clinical performance, and can be unsuitable for resource-limited settings. According to the World Health Organization (WHO), a rapid, sputum-free, and cost-effective triage test for real-time detection of TB is urgently needed. This art ...[more]

PMID: 34075714

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Project description:BackgroundThe risk of individuals infected with human immunodeficiency virus (HIV)-1 developing tuberculosis (TB) is high, while both prognostic and diagnostic tools remain insensitive. The potential for plasma biomarkers to predict which HIV-1-infected individuals are likely to progress to active disease is unknown.MethodsThirteen analytes were measured from QuantiFERON Gold in-tube (QFT) plasma samples in 421 HIV-1-infected persons recruited within the screening and enrollment phases of a randomized, controlled trial of isoniazid preventive therapy. Blood for QFT was obtained pre-randomization. Individuals were classified into prevalent TB, incident TB, and control groups. Comparisons between groups, supervised learning methods, and weighted correlation network analyses were applied utilizing the unstimulated and background-corrected plasma analyte concentrations.ResultsUnstimulated samples showed higher analyte concentrations in the prevalent and incident TB groups compared to the control group. The largest differences were seen for C-X-C motif chemokine 10 (CXCL10), interleukin-2 (IL-2), IL-1α, transforming growth factor-α (TGF-α). A predictive model analysis using unstimulated analytes discriminated best between the control and prevalent TB groups (area under the curve [AUC] = 0.9), reasonably well between the incident and prevalent TB groups (AUC > 0.8), and poorly between the control and incident TB groups. Unstimulated IL-2 and IFN-γ were ranked at or near the top for all comparisons, except the comparison between the control vs incident TB groups. Models using background-adjusted values performed poorly.ConclusionsSingle plasma biomarkers are unlikely to distinguish between disease states in HIV-1 co-infected individuals, and combinations of biomarkers are required. The ability to detect prevalent TB is potentially important, as no blood test hitherto has been suggested as having the utility to detect prevalent TB amongst HIV-1 co-infected persons.

Project description:Background and aimNumerous women of reproductive age experience physical or mental discomfort during their natural menstrual cycle due to paramenstrual symptoms, such as premenstrual syndrome (PMS). To date, there is no established biomarker for the diagnosis of PMS. This study investigated the relationship between skin gas composition and menstruation cycles, and evaluated the possibility of skin gas composition as a biomarker of paramenstrual symptoms.MethodsWe conducted an exploratory pilot study. Healthy Japanese women (aged 20-29 years) underwent blood and skin gas analyses on 1 day corresponding to menstruation, preovulatory, middle luteal, and late luteal phases. Skin gas was collected from the cubital fossa and armpit using a Passive Flux Sampler; samples were analyzed for 65 volatile organic compounds (VOCs) by gas chromatography-mass spectrometry (GC-MS). Non-parametric statistical analysis was performed to identify VOCs related to the menstrual cycle, levels of female hormones, and severity of PMS.ResultsFourteen women participated; of those, 12 completed the study. Regarding the relationship with the menstrual cycles, seven and four VOCs were significantly and marginally changed, respectively, at the cubital fossa during menstruation. Of those 11 compounds, 10 were also correlated with the levels of serum female hormones. At the armpit, five and three compounds were significantly and marginally changed, respectively, during menstruation. Of those eight compounds, five were also correlated with the levels of serum female hormones. In the study of PMS severity, analysis of the changes in VOCs suggested that ketones and fatty acids are increased during menstruation in the severe PMS group versus the mild PMS group.ConclusionsThe results of this study suggest that certain VOCs emitted in skin gas related to the menstrual cycle, levels of female hormones, and severity of PMS. These findings may advance the metabolic understanding and development of diagnostic biomarkers for menstruation-related symptoms.

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Profiles of Volatile Biomarkers Detect Tuberculosis from Skin.

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Profiles of Volatile Biomarkers Detect Tuberculosis from Skin.

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