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Capuano R, Ciotti M, Catini A, Bernardini S, Di Natale C. Clinical applications of volatilomic assays. Crit Rev Clin Lab Sci 2024:1-20. [PMID: 39129534 DOI: 10.1080/10408363.2024.2387038] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2024] [Revised: 04/23/2024] [Accepted: 07/29/2024] [Indexed: 08/13/2024]
Abstract
The study of metabolomics is revealing immense potential for diagnosis, therapy monitoring, and understanding of pathogenesis processes. Volatilomics is a subcategory of metabolomics interested in the detection of molecules that are small enough to be released in the gas phase. Volatile compounds produced by cellular processes are released into the blood and lymph, and can reach the external environment through different pathways, such as the blood-air interface in the lung that are detected in breath, or the blood-water interface in the kidney that leads to volatile compounds detected in urine. Besides breath and urine, additional sources of volatile compounds such as saliva, blood, feces, and skin are available. Volatilomics traces its roots back over fifty years to the pioneering investigations in the 1970s. Despite extensive research, the field remains in its infancy, hindered by a lack of standardization despite ample experimental evidence. The proliferation of analytical instrumentations, sample preparations and methods of volatilome sampling still make it difficult to compare results from different studies and to establish a common standard approach to volatilomics. This review aims to provide an overview of volatilomics' diagnostic potential, focusing on two key technical aspects: sampling and analysis. Sampling poses a challenge due to the susceptibility of human samples to contamination and confounding factors from various sources like the environment and lifestyle. The discussion then delves into targeted and untargeted approaches in volatilomics. Some case studies are presented to exemplify the results obtained so far. Finally, the review concludes with a discussion on the necessary steps to fully integrate volatilomics into clinical practice.
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Affiliation(s)
- Rosamaria Capuano
- Department of Electronic Engineering, University of Rome Tor Vergata, Roma, Italy
- Interdepartmental Center for Volatilomics, "A. D'Amico", University of Rome Tor Vergata, Rome, Italy
| | - Marco Ciotti
- Department of Laboratory Medicine, University Hospital Tor Vergata, Rome, Italy
| | - Alexandro Catini
- Department of Electronic Engineering, University of Rome Tor Vergata, Roma, Italy
- Interdepartmental Center for Volatilomics, "A. D'Amico", University of Rome Tor Vergata, Rome, Italy
| | - Sergio Bernardini
- Interdepartmental Center for Volatilomics, "A. D'Amico", University of Rome Tor Vergata, Rome, Italy
- Department of Laboratory Medicine, University Hospital Tor Vergata, Rome, Italy
- Department of Experimental Medicine, University of Rome Tor Vergata, Rome, Italy
| | - Corrado Di Natale
- Department of Electronic Engineering, University of Rome Tor Vergata, Roma, Italy
- Interdepartmental Center for Volatilomics, "A. D'Amico", University of Rome Tor Vergata, Rome, Italy
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Heers H, Gut JM, Hofmann R, Flegar L, Derigs M, Huber J, Baumbach JI, Koczulla AR, Boeselt T. Pilot study for bladder cancer detection with volatile organic compounds using ion mobility spectrometry: a novel urine-based approach. World J Urol 2024; 42:353. [PMID: 38795133 PMCID: PMC11127872 DOI: 10.1007/s00345-024-05047-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2024] [Accepted: 05/06/2024] [Indexed: 05/27/2024] Open
Abstract
PURPOSE Despite many efforts, no reliable urinary marker system has so far shown the potential to substitute cystoscopy. Measuring volatile organic compounds (VOCs) from urine is a promising alternative. VOCs are metabolic products which can be measured from the headspace of urine samples. Previous studies confirmed that the urine of bladder tumor patients has a different VOC profile than healthy controls. In this pilot study, the feasibility of discriminating VOCs from urine of bladder cancer patients from that of healthy control subjects was investigated. Aim of this study was to investigate whether VOC-based diagnosis of bladder cancer from urine samples is feasible using multicapillary column ion mobility spectrometry (MCC/IMS) and to identify potential molecular correlates to the relevant analytes. METHODS Headspace measurements of urine samples of 30 patients with confirmed transitional cell carcinoma (TCC) and 30 healthy controls were performed using MCC/IMS. In the results of the measurements, peaks showing significant differences between both groups were identified and implemented into a decision tree with respect to achieve group separation. Molecular correlates were predicted using a pre-defined dataset. RESULTS Eight peaks with significantly differing intensity were identified, 5 of which were highly significant. Using a six-step decision tree, MCC/IMS showed a sensitivity of 90% and specificity of 100% in group separation. CONCLUSION VOC-based detection of bladder cancer is feasible. MCC/IMS is a suitable method for urine-based diagnosis and should be further validated. The molecular characteristics and metabolic background of the analytes require further workup.
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Affiliation(s)
- Hendrik Heers
- Department of Urology, Philipps-Universität Marburg, Baldingerstraße, 35033, Marburg, Germany.
| | - Josef Maximilian Gut
- Department of Urology, Philipps-Universität Marburg, Baldingerstraße, 35033, Marburg, Germany
- Department of General and Visceral Surgery, München Klinik Neuperlach, Oskar-Maria-Graf-Ring 51, 81737, Munich, Germany
| | - Rainer Hofmann
- Department of Urology, Philipps-Universität Marburg, Baldingerstraße, 35033, Marburg, Germany
| | - Luka Flegar
- Department of Urology, Philipps-Universität Marburg, Baldingerstraße, 35033, Marburg, Germany
| | - Marcus Derigs
- Department of Urology, Philipps-Universität Marburg, Baldingerstraße, 35033, Marburg, Germany
| | - Johannes Huber
- Department of Urology, Philipps-Universität Marburg, Baldingerstraße, 35033, Marburg, Germany
| | - Joerg Ingo Baumbach
- Department Bio- and Chemical Engineering, Technical University Dortmund, Emil-Figge-Straße 66, 44227, Dortmund, Germany
| | - Andreas Rembert Koczulla
- Department of Pulmonology, Philipps-Universität Marburg, Baldingerstraße, 35033, Marburg, Germany
- Department of Pulmonology, Schön-Klinik Berchtesgadener Land, Malterhöh 1, 83471, Schönau, Germany
| | - Tobias Boeselt
- Department of Pulmonology, Philipps-Universität Marburg, Baldingerstraße, 35033, Marburg, Germany
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Boeselt T, Terhorst P, Kroenig J, Nell C, Spielmanns M, Boas U, Veith M, Vogelmeier C, Greulich T, Koczulla AR, Beutel B, Huber J, Heers H. Specific molecular peak analysis by ion mobility spectrometry of volatile organic compounds in urine of COVID-19 patients: A novel diagnostic approach. J Virol Methods 2024; 326:114910. [PMID: 38452823 DOI: 10.1016/j.jviromet.2024.114910] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2023] [Revised: 01/08/2024] [Accepted: 03/02/2024] [Indexed: 03/09/2024]
Abstract
INTRODUCTION SARS-CoV-2 is usually diagnosed from naso-/oropharyngeal swabs which are uncomfortable and prone to false results. This study investigated a novel diagnostic approach to Covid-19 measuring volatile organic compounds (VOC) from patients' urine. METHODS Between June 2020 and February 2021, 84 patients with positive RT-PCR for SARS-CoV-2 were recruited as well as 54 symptomatic individuals with negative RT-PCR. Midstream urine samples were obtained for VOC analysis using ion mobility spectrometry (IMS) which detects individual molecular components of a gas sample based on their size, configuration, and charge after ionization. RESULTS Peak analysis of the 84 Covid and 54 control samples showed good group separation. In total, 37 individual specific peaks were identified, 5 of which (P134, 198, 135, 75, 136) accounted for significant differences between groups, resulting in sensitivities of 89-94% and specificities of 82-94%. A decision tree was generated from the relevant peaks, leading to a combined sensitivity and specificity of 98% each. DISCUSSION VOC-based diagnosis can establish a reliable separation between urine samples of Covid-19 patients and negative controls. Molecular peaks which apparently are disease-specific were identified. IMS is an additional non-invasive and cheap device for the diagnosis of this ongoing endemic infection. Further studies are needed to validate sensitivity and specificity.
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Affiliation(s)
- T Boeselt
- Department of Medicine, Pulmonary and Critical Care Medicine, University Medical Center Giessen and Marburg, Philipps-University Marburg, German Center for Lung Research (DZL), Germany
| | - P Terhorst
- Department of Medicine, Pulmonary and Critical Care Medicine, University Medical Center Giessen and Marburg, Philipps-University Marburg, German Center for Lung Research (DZL), Germany
| | - J Kroenig
- Department of Medicine, Pulmonary and Critical Care Medicine, University Medical Center Giessen and Marburg, Philipps-University Marburg, German Center for Lung Research (DZL), Germany
| | - C Nell
- Department of Medicine, Pulmonary and Critical Care Medicine, University Medical Center Giessen and Marburg, Philipps-University Marburg, German Center for Lung Research (DZL), Germany
| | - M Spielmanns
- Pulmonary Rehabilitation, Zuercher Reha Zentren Klinik Wald, Switzerland; Faculty of Health, Department of Pneumology, University of Witten, Herdecke, Germany
| | - U Boas
- Department of Medicine, Pulmonary and Critical Care Medicine, University Medical Center Giessen and Marburg, Philipps-University Marburg, German Center for Lung Research (DZL), Germany
| | - M Veith
- Department of Medicine, Pulmonary and Critical Care Medicine, University Medical Center Giessen and Marburg, Philipps-University Marburg, German Center for Lung Research (DZL), Germany
| | - C Vogelmeier
- Department of Medicine, Pulmonary and Critical Care Medicine, University Medical Center Giessen and Marburg, Philipps-University Marburg, German Center for Lung Research (DZL), Germany
| | - T Greulich
- Department of Medicine, Pulmonary and Critical Care Medicine, University Medical Center Giessen and Marburg, Philipps-University Marburg, German Center for Lung Research (DZL), Germany
| | - A R Koczulla
- Department of Medicine, Pulmonary and Critical Care Medicine, University Medical Center Giessen and Marburg, Philipps-University Marburg, German Center for Lung Research (DZL), Germany; Department of Pulmonology, Schoen-Kliniken Berchtesgaden, Philipps-University Marburg, Germany
| | - B Beutel
- Department of Medicine, Pulmonary and Critical Care Medicine, University Medical Center Giessen and Marburg, Philipps-University Marburg, German Center for Lung Research (DZL), Germany
| | - J Huber
- Department of Urology, University Medical Center Giessen and Marburg, Philipps-University Marburg, Germany
| | - H Heers
- Department of Urology, University Medical Center Giessen and Marburg, Philipps-University Marburg, Germany.
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Heers H, Chwilka O, Huber J, Vogelmeier C, Koczulla AR, Baumbach JI, Boeselt T. VOC-based detection of prostate cancer using an electronic nose and ion mobility spectrometry: A novel urine-based approach. Prostate 2024. [PMID: 38497426 DOI: 10.1002/pros.24692] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/24/2024] [Accepted: 03/07/2024] [Indexed: 03/19/2024]
Abstract
BACKGROUND Many diseases leave behind specific metabolites which can be detected from breath and urine as volatile organic compounds (VOC). Our group previously described VOC-based methods for the detection of bladder cancer and urinary tract infections. This study investigated whether prostate cancer can be diagnosed from VOCs in urine headspace. METHODS For this pilot study, mid-stream urine samples were collected from 56 patients with histologically confirmed prostate cancer. A control group was formed with 53 healthy male volunteers matched for age who had recently undergone a negative screening by prostate-specific antigen (PSA) and digital rectal exam. Headspace measurements were performed with the electronic nose Cyranose 320TM . Statistical comparison was performed using principal component analysis, calculating Mahalanobis distance, and linear discriminant analysis. Further measurements were carried out with ion mobility spectrometry (IMS) to compare detection accuracy and to identify potential individual analytes. Bonferroni correction was applied for multiple testing. RESULTS The electronic nose yielded a sensitivity of 77% and specificity of 62%. Mahalanobis distance was 0.964, which is indicative of limited group separation. IMS identified a total of 38 individual analytical peaks, two of which showed significant differences between groups (p < 0.05). To discriminate between tumor and controls, a decision tree with nine steps was generated. This model led to a sensitivity of 98% and specificity of 100%. CONCLUSIONS VOC-based detection of prostate cancer seems feasible in principle. While the first results with an electronic nose show some limitations, the approach can compete with other urine-based marker systems. However, it seems less reliable than PSA testing. IMS is more accurate than the electronic nose with promising sensitivity and specificity, which warrants further research. The individual relevant metabolites identified by IMS should further be characterized using gas chromatography/mass spectrometry to facilitate potential targeted rapid testing.
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Affiliation(s)
- Hendrik Heers
- Department of Urology, Philipps-Universität Marburg, Marburg, Germany
| | - Oliver Chwilka
- Department of Urology, Philipps-Universität Marburg, Marburg, Germany
| | - Johannes Huber
- Department of Urology, Philipps-Universität Marburg, Marburg, Germany
| | - Claus Vogelmeier
- Department of Medicine, Pulmonary and Critical Care Medicine, Philipps-Universität Marburg, Marburg, Germany
| | - Andreas Rembert Koczulla
- Department of Medicine, Pulmonary and Critical Care Medicine, Philipps-Universität Marburg, Marburg, Germany
- Department of Pulmonology, Schoen-Kliniken, Berchtesgaden, Germany
| | - Jörg Ingo Baumbach
- Department of Biochemical and Chemical Engineering, Technical University of Dortmund, Dortmund, Germany
| | - Tobias Boeselt
- Department of Medicine, Pulmonary and Critical Care Medicine, Philipps-Universität Marburg, Marburg, Germany
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Cao Y, Jiang L, Zhang J, Fu Y, Li Q, Fu W, Zhu J, Xiang X, Zhao G, Kong D, Chen X, Fang J. A fast and non-invasive artificial intelligence olfactory-like system that aids diagnosis of Parkinson's disease. Eur J Neurol 2024; 31:e16167. [PMID: 38009830 PMCID: PMC11235760 DOI: 10.1111/ene.16167] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2023] [Revised: 10/31/2023] [Accepted: 11/09/2023] [Indexed: 11/29/2023]
Abstract
BACKGROUND AND PURPOSE Several previous studies have shown that skin sebum analysis can be used to diagnose Parkinson's disease (PD). The aim of this study was to develop a portable artificial intelligence olfactory-like (AIO) system based on gas chromatographic analysis of the volatile organic compounds (VOCs) in patient sebum and explore its application value in the diagnosis of PD. METHODS The skin VOCs from 121 PD patients and 129 healthy controls were analyzed using the AIO system and three classic machine learning models were established, including the gradient boosting decision tree (GBDT), random forest and extreme gradient boosting, to assist the diagnosis of PD and predict its severity. RESULTS A 20-s time series of AIO system data were collected from each participant. The VOC peaks at a large number of time points roughly concentrated around 5-12 s were significantly higher in PD subjects. The gradient boosting decision tree model showed the best ability to differentiate PD from healthy controls, yielding a sensitivity of 83.33% and a specificity of 84.00%. However, the system failed to predict PD progression scored by Hoehn-Yahr stage. CONCLUSIONS This study provides a fast, low-cost and non-invasive method to distinguish PD patients from healthy controls. Furthermore, our study also indicates abnormal sebaceous gland secretion in PD patients, providing new evidence for exploring the pathogenesis of PD.
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Affiliation(s)
- Yina Cao
- Department of NeurologyThe Fourth Affiliated Hospital of Zhejiang University Medical CollegeZhejiangChina
| | - Lina Jiang
- Department of RadiologyFourth Affiliated Hospital of Zhejiang University Medical CollegeZhejiangChina
| | - Jingxin Zhang
- Department of NeurologyThe Fourth Affiliated Hospital of Zhejiang University Medical CollegeZhejiangChina
| | - Yanlu Fu
- Department of NeurologyThe Fourth Affiliated Hospital of Zhejiang University Medical CollegeZhejiangChina
| | - Qiwei Li
- Department of NeurologyThe Fourth Affiliated Hospital of Zhejiang University Medical CollegeZhejiangChina
| | - Wei Fu
- Department of Biomedical Engineering, Key Laboratory of Biomedical Engineering of Ministry of Education of ChinaZhejiang UniversityZhejiangChina
| | - Junjiang Zhu
- College of Mechanical and Electrical EngineeringChina Jiliang UniversityZhejiangChina
| | - Xiaohui Xiang
- Department of NeurologyThe Fourth Affiliated Hospital of Zhejiang University Medical CollegeZhejiangChina
| | - Guohua Zhao
- Department of NeurologyThe Fourth Affiliated Hospital of Zhejiang University Medical CollegeZhejiangChina
| | - Dongdong Kong
- School of Mechatronic Engineering and AutomationShanghai UniversityShanghaiChina
| | - Xing Chen
- Department of Biomedical Engineering, Key Laboratory of Biomedical Engineering of Ministry of Education of ChinaZhejiang UniversityZhejiangChina
| | - Jiajia Fang
- Department of NeurologyThe Fourth Affiliated Hospital of Zhejiang University Medical CollegeZhejiangChina
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Moura PC, Raposo M, Vassilenko V. Breath biomarkers in Non-Carcinogenic diseases. Clin Chim Acta 2024; 552:117692. [PMID: 38065379 DOI: 10.1016/j.cca.2023.117692] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2023] [Revised: 12/02/2023] [Accepted: 12/03/2023] [Indexed: 12/19/2023]
Abstract
The analysis of volatile organic compounds (VOCs) from human matrices like breath, perspiration, and urine has received increasing attention from academic and medical researchers worldwide. These biological-borne VOCs molecules have characteristics that can be directly related to physiologic and pathophysiologic metabolic processes. In this work, gathers a total of 292 analytes that have been identified as potential biomarkers for the diagnosis of various non-carcinogenic diseases. Herein we review the advances in VOCs with a focus on breath biomarkers and their potential role as minimally invasive tools to improve diagnosis prognosis and therapeutic monitoring.
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Affiliation(s)
- Pedro Catalão Moura
- Laboratory for Instrumentation, Biomedical Engineering and Radiation Physics (LIBPhys-UNL), Department of Physics, NOVA School of Science and Technology, NOVA University of Lisbon, Campus FCT-UNL, 2829-516, Caparica, Portugal.
| | - Maria Raposo
- Laboratory for Instrumentation, Biomedical Engineering and Radiation Physics (LIBPhys-UNL), Department of Physics, NOVA School of Science and Technology, NOVA University of Lisbon, Campus FCT-UNL, 2829-516, Caparica, Portugal.
| | - Valentina Vassilenko
- Laboratory for Instrumentation, Biomedical Engineering and Radiation Physics (LIBPhys-UNL), Department of Physics, NOVA School of Science and Technology, NOVA University of Lisbon, Campus FCT-UNL, 2829-516, Caparica, Portugal.
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Habibzadeh A, Ostovan VR, Keshavarzian O, Kardeh S, Mahmoudi SS, Zakeri MR, Tabrizi R. Volatile organic compounds analysis as promising biomarkers for Parkinson's disease diagnosis: A systematic review and meta-analysis. Clin Neurol Neurosurg 2023; 235:108022. [PMID: 37939618 DOI: 10.1016/j.clineuro.2023.108022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2023] [Revised: 09/26/2023] [Accepted: 10/24/2023] [Indexed: 11/10/2023]
Abstract
OBJECTIVE Researchers are investigating the potential of volatile organic compounds (VOCs) obtained from exhaled breath and sebum as non-invasive tools for early Parkinson's disease (PD) diagnosis. The present study aims to assess the feasibility of using VOC analysis for PD diagnosis and determine the overall diagnostic accuracy of the proposed tests. METHODS We performed systematic searches based on the PRISMA guidelines to identify relevant studies on VOCs in PD diagnosis using exhaled breath or sebum samples. The selected articles were described, and meta-analysis was conducted on those that provided the sensitivity and specificity data. RESULTS Out of 1268 articles initially identified, 8 met the inclusion criteria and provided specific sensitivity and specificity data for PD, which were included in the current meta-analysis. The pooled analysis of these findings showed a mean area under the receiver operating characteristic curve of 0.85, a sensitivity of 0.81 (95% confidence interval (CI): 0.72, 0.88), and a specificity of 0.76 (95% CI: 0.66, 0.84). CONCLUSION The analysis of VOCs in exhaled breath and sebum has shown promise as a new avenue for non-invasive diagnosis of PD. VOCs' ability to distinguish PD from healthy controls suggests their potential clinical application in screening for the disease. Consequently, VOCs hold significant potential as biomarkers for PD diagnosis and offer a promising novel approach to identifying and diagnosing the condition.
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Affiliation(s)
- Adrina Habibzadeh
- Student Research Committee, Fasa University of Medical Sciences, Fasa, Iran; USERN Office, Fasa University of Medical Sciences, Fasa, Iran
| | - Vahid Reza Ostovan
- Clinical Neurology Research Center, Shiraz University of Medical Sciences, Shiraz, Iran
| | - Omid Keshavarzian
- School of Medicine, Shiraz University of Medical Sciences, Shiraz, Iran
| | - Sina Kardeh
- Central Clinical School, Monash University, Melbourne, Australia
| | - Seyed Sasan Mahmoudi
- Student Research Committee, Department of Neurosurgery, School of Medicine, Shiraz University of Medical Sciences, Shiraz, Iran
| | - Mohamad-Reza Zakeri
- Health Policy Research Center, Institute of Health, Shiraz University of Medical Sciences, Shiraz, Iran
| | - Reza Tabrizi
- USERN Office, Fasa University of Medical Sciences, Fasa, Iran; Noncommunicable Diseases Research Center, Fasa University of Medical Sciences, Fasa, Iran; Clinical Research Development Unit, Valiasr Hospital, Fasa University of Medical Sciences, Fasa, Iran.
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Gade IL, Riddersholm SJ, Stilling-Vinther T, Brøndum RF, Bennike TB, Honoré B. A clinical proteomics study of exhaled breath condensate and biomarkers for pulmonary embolism. J Breath Res 2023; 18:016007. [PMID: 37939397 DOI: 10.1088/1752-7163/ad0aaa] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2023] [Accepted: 11/07/2023] [Indexed: 11/10/2023]
Abstract
Pulmonary embolism (PE) can be a diagnostic challenge. Current diagnostic markers for PE are unspecific and new diagnostic tools are needed. The air we exhale is a possible new source for biomarkers which can be tapped into by analysing the exhaled breath condensate (EBC). We analysed the EBC from patients with PE and controls to investigate if the EBC is a useful source for new diagnostic biomarkers of PE. We collected and analysed EBC samples from patients with suspected PE and controls matched on age and sex. Patients in whom PE was ruled out after diagnostic work-up were included in the control group to increase the sensitivity and generalizability of the identified markers. EBC samples were collected using an RTube™. The protein composition of the EBCs were analysed using data dependent label-free quantitative nano liquid chromatography-tandem mass spectrometry. EBC samples from 28 patients with confirmed PE, and 49 controls were analysed. A total of 928 EBC proteins were identified in the 77 EBC samples. As expected, a low protein concentration was determined which resulted in many proteins with unmeasurable levels in several samples. The levels of HSPA5, PEBP1 and SFTPA2 were higher and levels of POF1B, EPPK1, PSMA4, ALDOA, and CFL1 were lower in PE compared with controls. In conclusion, the human EBC contained a variety of endogenous proteins and may be a source for new diagnostic markers of PE and other diseases.
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Affiliation(s)
- Inger Lise Gade
- Department of Hematology and Clinical Cancer Research Center, Aalborg University Hospital, 9000 Aalborg, Denmark
| | | | | | - Rasmus Froberg Brøndum
- Center for Clinical Data Science, Aalborg University and Aalborg University Hospital, 9260 Gistrup, Denmark
| | - Tue Bjerg Bennike
- Department of Health Science and Technology, Aalborg University, Aalborg, Denmark
| | - Bent Honoré
- Department of Clinical Medicine, Aalborg University, 9000 Aalborg, Denmark
- Department of Biomedicine, Aarhus University, 8000 Aarhus, Denmark
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Jiao B, Zhang S, Bei Y, Bu G, Yuan L, Zhu Y, Yang Q, Xu T, Zhou L, Liu Q, Ouyang Z, Yang X, Feng Y, Tang B, Chen H, Shen L. A detection model for cognitive dysfunction based on volatile organic compounds from a large Chinese community cohort. Alzheimers Dement 2023; 19:4852-4862. [PMID: 37032600 DOI: 10.1002/alz.13053] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2022] [Revised: 02/17/2023] [Accepted: 02/21/2023] [Indexed: 04/11/2023]
Abstract
INTRODUCTION We explored whether volatile organic compound (VOC) detection can serve as a screening tool to distinguish cognitive dysfunction (CD) from cognitively normal (CN) individuals. METHODS The cognitive function of 1467 participants was assessed and their VOCs were detected. Six machine learning algorithms were conducted and the performance was determined. The plasma neurofilament light chain (NfL) was measured. RESULTS Distinguished VOC patterns existed between CD and CN groups. The CD detection model showed good accuracy with an area under the receiver-operating characteristic curve (AUC) of 0.876. In addition, we found that 10 VOC ions showed significant differences between CD and CN individuals (p < 0.05); three VOCs were significantly related to plasma NfL (p < 0.005). Moreover, a combination of VOCs with NfL showed the best discriminating power (AUC = 0.877). DISCUSSION Detection of VOCs from exhaled breath samples has the potential to provide a novel solution for the dilemma of CD screening.
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Affiliation(s)
- Bin Jiao
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China
- Engineering Research Center of Hunan Province in Cognitive Impairment Disorders, Central South University, Changsha, China
- Hunan International Scientific and Technological Cooperation Base of Neurodegenerative and Neurogenetic Diseases, Changsha, China
- Key Laboratory of Hunan Province in Neurodegenerative Disorders, Central South University, Changsha, China
| | - Sizhe Zhang
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
| | - Yuzhang Bei
- Department of Neurology, Liuyang Jili Hospital, Changsha, China
| | - Guiwen Bu
- Department of Neurology, Liuyang Jili Hospital, Changsha, China
| | - Li Yuan
- Department of Neurology, Liuyang Jili Hospital, Changsha, China
| | - Yuan Zhu
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
| | - Qijie Yang
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
| | - Tianyan Xu
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
| | - Lu Zhou
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
| | - Qianqian Liu
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
| | - Ziyu Ouyang
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
| | - Xuan Yang
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
| | - Yong Feng
- Breax Laboratory, PCAB Research Center of Breath and Metabolism, Beijing, China
| | - Beisha Tang
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China
- Engineering Research Center of Hunan Province in Cognitive Impairment Disorders, Central South University, Changsha, China
- Hunan International Scientific and Technological Cooperation Base of Neurodegenerative and Neurogenetic Diseases, Changsha, China
- Key Laboratory of Hunan Province in Neurodegenerative Disorders, Central South University, Changsha, China
| | - Haibin Chen
- Breax Laboratory, PCAB Research Center of Breath and Metabolism, Beijing, China
| | - Lu Shen
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China
- Engineering Research Center of Hunan Province in Cognitive Impairment Disorders, Central South University, Changsha, China
- Hunan International Scientific and Technological Cooperation Base of Neurodegenerative and Neurogenetic Diseases, Changsha, China
- Key Laboratory of Hunan Province in Neurodegenerative Disorders, Central South University, Changsha, China
- Key Laboratory of Organ Injury, Aging and Regenerative Medicine of Hunan Province, Changsha, China
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10
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Baudrexler T, Boeselt T, Li L, Bohlscheid S, Boas U, Schmid C, Rank A, Schmohl J, Koczulla R, Schmetzer HM. Volatile Phases Derived from Serum, DC, or MLC Culture Supernatants to Deduce a VOC-Based Diagnostic Profiling Strategy for Leukemic Diseases. Biomolecules 2023; 13:989. [PMID: 37371569 DOI: 10.3390/biom13060989] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2022] [Revised: 05/29/2023] [Accepted: 05/31/2023] [Indexed: 06/29/2023] Open
Abstract
Volatile organic compounds (VOCs) reflect the metabolism in healthy and pathological conditions, and can be collected easily in a noninvasive manner. They are directly measured using electronical nose (eNose), and may qualify as a systemic tool to monitor biomarkers related to disease. Myeloid leukemic blasts can be transformed into leukemia-derived dendritic cells (DCleu) able to improve (anti-leukemic) immune responses. To profile immunological changes in healthy and acute myeloid leukemic (AML) patients' ex vivo cell cultures, we correlated the cell biological data with the profiles of cell culture supernatant-derived VOCs. DC/DCleu from leukemic or healthy whole blood (WB) were generated without (Control) or with immunomodulatory Kit M (Granulocyte macrophage-colony-stimulating-factor (GM-CSF) + prostaglandin E1 (PGE1)) in dendritic cell cultures (DC culture). Kit-pretreated/not pretreated WB was used to stimulate T cell-enriched immunoreactive cells in mixed lymphocyte cultures (MLC culture). Leukemia-specific adaptive and innate immune cells were detected with a degranulation assay (Deg) and an intracellular cytokine assay (InCyt). Anti-leukemic cytotoxicity was explored with a cytotoxicity fluorolysis assay (CTX). VOCs collected from serum or DC- and MLC culture supernatants (with vs. without Kit M pretreatment and before vs. after culture) were measured using eNose. Compared to the Control (without treatment), Kit M-pretreated leukemic and healthy WB gave rise to higher frequencies of mature (leukemia-derived) DC subtypes of activated and (memory) T cells after MLC. Moreover, antigen (leukemia)-specific cells of several lines (innate and adaptive immunity cells) were induced, giving rise to blast-lysing cells. The eNose could significantly distinguish between healthy and leukemic patients' serum, DC and MLC culture supernatant-derived volatile phases and could significantly separate several supernatant (with vs. without Kit M treatment, cultured vs. uncultured)-derived VOCs within subgroups (healthy DC or leukemic DC, or healthy MLC or leukemic MLC supernatants). Interestingly, the eNose could indicate a Kit M- and culture-associated effect. The eNose may be a prospective option for the deduction of a VOC-based profiling strategy using serum or cell culture supernatants and could be a useful diagnostic tool to recognize or qualify AML disease.
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Affiliation(s)
- Tobias Baudrexler
- Medical Department III, Hospital Großhadern, Ludwig-Maximilians-University, 81377 Munich, Germany
| | - Tobias Boeselt
- Department of Pulmonary Rehabilitation, German Center for Lung Research (DZL), Phillipps-University of Marburg, 35043 Marburg, Germany
| | - Lin Li
- Medical Department III, Hospital Großhadern, Ludwig-Maximilians-University, 81377 Munich, Germany
| | - Sophia Bohlscheid
- Medical Department III, Hospital Großhadern, Ludwig-Maximilians-University, 81377 Munich, Germany
| | - Ursel Boas
- Department of Pulmonary Rehabilitation, German Center for Lung Research (DZL), Phillipps-University of Marburg, 35043 Marburg, Germany
| | - Christoph Schmid
- Department of Hematology and Oncology, University Hospital of Augsburg, 86156 Augsburg, Germany
| | - Andreas Rank
- Department of Hematology and Oncology, University Hospital of Augsburg, 86156 Augsburg, Germany
| | - Jörg Schmohl
- Department of Hematology and Oncology, Diaconia Hospital Stuttgart, 70176 Stuttgart, Germany
| | - Rembert Koczulla
- Department of Pulmonary Rehabilitation, German Center for Lung Research (DZL), Phillipps-University of Marburg, 35043 Marburg, Germany
| | - Helga Maria Schmetzer
- Medical Department III, Hospital Großhadern, Ludwig-Maximilians-University, 81377 Munich, Germany
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11
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Lagopati N, Valamvanos TF, Proutsou V, Karachalios K, Pippa N, Gatou MA, Vagena IA, Cela S, Pavlatou EA, Gazouli M, Efstathopoulos E. The Role of Nano-Sensors in Breath Analysis for Early and Non-Invasive Disease Diagnosis. CHEMOSENSORS 2023; 11:317. [DOI: 10.3390/chemosensors11060317] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/11/2023]
Abstract
Early-stage, precise disease diagnosis and treatment has been a crucial topic of scientific discussion since time immemorial. When these factors are combined with experience and scientific knowledge, they can benefit not only the patient, but also, by extension, the entire health system. The development of rapidly growing novel technologies allows for accurate diagnosis and treatment of disease. Nanomedicine can contribute to exhaled breath analysis (EBA) for disease diagnosis, providing nanomaterials and improving sensing performance and detection sensitivity. Through EBA, gas-based nano-sensors might be applied for the detection of various essential diseases, since some of their metabolic products are detectable and measurable in the exhaled breath. The design and development of innovative nanomaterial-based sensor devices for the detection of specific biomarkers in breath samples has emerged as a promising research field for the non-invasive accurate diagnosis of several diseases. EBA would be an inexpensive and widely available commercial tool that could also be used as a disease self-test kit. Thus, it could guide patients to the proper specialty, bypassing those expensive tests, resulting, hence, in earlier diagnosis, treatment, and thus a better quality of life. In this review, some of the most prevalent types of sensors used in breath-sample analysis are presented in parallel with the common diseases that might be diagnosed through EBA, highlighting the impact of incorporating new technological achievements in the clinical routine.
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Affiliation(s)
- Nefeli Lagopati
- Laboratory of Biology, Department of Basic Medical Sciences, Medical School, National and Kapodistrian University of Athens, 11527 Athens, Greece
- Biomedical Research Foundation, Academy of Athens, 11527 Athens, Greece
| | - Theodoros-Filippos Valamvanos
- Laboratory of Biology, Department of Basic Medical Sciences, Medical School, National and Kapodistrian University of Athens, 11527 Athens, Greece
- Medical Physics Unit, 2nd Department of Radiology, Medical School, National and Kapodistrian University of Athens, Attikon University Hospital, 12462 Athens, Greece
| | - Vaia Proutsou
- Laboratory of Biology, Department of Basic Medical Sciences, Medical School, National and Kapodistrian University of Athens, 11527 Athens, Greece
- Medical Physics Unit, 2nd Department of Radiology, Medical School, National and Kapodistrian University of Athens, Attikon University Hospital, 12462 Athens, Greece
| | - Konstantinos Karachalios
- Laboratory of Biology, Department of Basic Medical Sciences, Medical School, National and Kapodistrian University of Athens, 11527 Athens, Greece
- Medical Physics Unit, 2nd Department of Radiology, Medical School, National and Kapodistrian University of Athens, Attikon University Hospital, 12462 Athens, Greece
| | - Natassa Pippa
- Section of Pharmaceutical Technology, Department of Pharmacy, School of Health Sciences, National and Kapodistrian University of Athens, 15771 Athens, Greece
| | - Maria-Anna Gatou
- Laboratory of General Chemistry, School of Chemical Engineering, National Technical University of Athens, Zografou Campus, 15772 Athens, Greece
| | - Ioanna-Aglaia Vagena
- Laboratory of Biology, Department of Basic Medical Sciences, Medical School, National and Kapodistrian University of Athens, 11527 Athens, Greece
| | - Smaragda Cela
- Laboratory of Biology, Department of Basic Medical Sciences, Medical School, National and Kapodistrian University of Athens, 11527 Athens, Greece
- Medical Physics Unit, 2nd Department of Radiology, Medical School, National and Kapodistrian University of Athens, Attikon University Hospital, 12462 Athens, Greece
| | - Evangelia A. Pavlatou
- Laboratory of General Chemistry, School of Chemical Engineering, National Technical University of Athens, Zografou Campus, 15772 Athens, Greece
| | - Maria Gazouli
- Laboratory of Biology, Department of Basic Medical Sciences, Medical School, National and Kapodistrian University of Athens, 11527 Athens, Greece
- School of Science and Technology, Hellenic Open University, 26335 Patra, Greece
| | - Efstathios Efstathopoulos
- Biomedical Research Foundation, Academy of Athens, 11527 Athens, Greece
- School of Science and Technology, Hellenic Open University, 26335 Patra, Greece
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12
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Wilson AD, Forse LB. Potential for Early Noninvasive COVID-19 Detection Using Electronic-Nose Technologies and Disease-Specific VOC Metabolic Biomarkers. SENSORS (BASEL, SWITZERLAND) 2023; 23:2887. [PMID: 36991597 PMCID: PMC10054641 DOI: 10.3390/s23062887] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/29/2023] [Revised: 02/19/2023] [Accepted: 03/03/2023] [Indexed: 06/12/2023]
Abstract
The established efficacy of electronic volatile organic compound (VOC) detection technologies as diagnostic tools for noninvasive early detection of COVID-19 and related coronaviruses has been demonstrated from multiple studies using a variety of experimental and commercial electronic devices capable of detecting precise mixtures of VOC emissions in human breath. The activities of numerous global research teams, developing novel electronic-nose (e-nose) devices and diagnostic methods, have generated empirical laboratory and clinical trial test results based on the detection of different types of host VOC-biomarker metabolites from specific chemical classes. COVID-19-specific volatile biomarkers are derived from disease-induced changes in host metabolic pathways by SARS-CoV-2 viral pathogenesis. The unique mechanisms proposed from recent researchers to explain how COVID-19 causes damage to multiple organ systems throughout the body are associated with unique symptom combinations, cytokine storms and physiological cascades that disrupt normal biochemical processes through gene dysregulation to generate disease-specific VOC metabolites targeted for e-nose detection. This paper reviewed recent methods and applications of e-nose and related VOC-detection devices for early, noninvasive diagnosis of SARS-CoV-2 infections. In addition, metabolomic (quantitative) COVID-19 disease-specific chemical biomarkers, consisting of host-derived VOCs identified from exhaled breath of patients, were summarized as possible sources of volatile metabolic biomarkers useful for confirming and supporting e-nose diagnoses.
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Affiliation(s)
- Alphus Dan Wilson
- Pathology Department, Center for Forest Health & Disturbance, Forest Genetics and Ecosystems Biology, Southern Research Station, USDA Forest Service, Stoneville, MS 38776, USA
| | - Lisa Beth Forse
- Southern Hardwoods Laboratory, Southern Research Station, USDA Forest Service, Stoneville, MS 38776, USA
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13
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Oxner M, Trang A, Mehta J, Forsyth C, Swanson B, Keshavarzian A, Bhushan A. The Versatility and Diagnostic Potential of VOC Profiling for Noninfectious Diseases. BME FRONTIERS 2023; 4:0002. [PMID: 37849665 PMCID: PMC10521665 DOI: 10.34133/bmef.0002] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2022] [Accepted: 11/11/2022] [Indexed: 10/19/2023] Open
Abstract
A variety of volatile organic compounds (VOCs) are produced and emitted by the human body every day. The identity and concentration of these VOCs reflect an individual's metabolic condition. Information regarding the production and origin of VOCs, however, has yet to be congruent among the scientific community. This review article focuses on the recent investigations of the source and detection of biological VOCs as a potential for noninvasive discrimination between healthy and diseased individuals. Analyzing the changes in the components of VOC profiles could provide information regarding the molecular mechanisms behind disease as well as presenting new approaches for personalized screening and diagnosis. VOC research has prioritized the study of cancer, resulting in many research articles and reviews being written on the topic. This review summarizes the information gained about VOC cancer studies over the past 10 years and looks at how this knowledge correlates with and can be expanded to new and upcoming fields of VOC research, including neurodegenerative and other noninfectious diseases. Recent advances in analytical techniques have allowed for the analysis of VOCs measured in breath, urine, blood, feces, and skin. New diagnostic approaches founded on sensor-based techniques allow for cheaper and quicker results, and we compare their diagnostic dependability with gas chromatography- and mass spectrometry-based techniques. The future of VOC analysis as a clinical practice and the challenges associated with this transition are also discussed and future research priorities are summarized.
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Affiliation(s)
- Micah Oxner
- Department of Biomedical Engineering, Illinois Institute of Technology, Chicago, IL 60616, USA
| | - Allyson Trang
- Department of Biomedical Engineering, Illinois Institute of Technology, Chicago, IL 60616, USA
| | - Jhalak Mehta
- Department of Biomedical Engineering, Illinois Institute of Technology, Chicago, IL 60616, USA
| | - Christopher Forsyth
- Department of Internal Medicine, Division of Digestive Diseases and Nutrition, Section of Gastroenterology, Rush Medical College, Chicago, IL 60612, USA
| | - Barbara Swanson
- Department of Adult Health and Gerontological Nursing, Rush University College of Nursing, Chicago, IL 60612, USA
| | - Ali Keshavarzian
- Department of Internal Medicine, Division of Digestive Diseases and Nutrition, Section of Gastroenterology, Rush Medical College, Chicago, IL 60612, USA
| | - Abhinav Bhushan
- Department of Biomedical Engineering, Illinois Institute of Technology, Chicago, IL 60616, USA
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14
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Ubeda C, Vázquez-Carretero MD, Luque-Tirado A, Ríos-Reina R, Rubio-Sánchez R, Franco-Macías E, García-Miranda P, Calonge ML, Peral MJ. Fecal Volatile Organic Compounds and Microbiota Associated with the Progression of Cognitive Impairment in Alzheimer's Disease. Int J Mol Sci 2022; 24:ijms24010707. [PMID: 36614151 PMCID: PMC9821163 DOI: 10.3390/ijms24010707] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2022] [Revised: 12/22/2022] [Accepted: 12/27/2022] [Indexed: 01/04/2023] Open
Abstract
Metabolites produced by an altered gut microbiota might mediate the effects in the brain. Among metabolites, the fecal volatile organic compounds (VOCs) are considered to be potential biomarkers. In this study, we examined both the VOCs and bacterial taxa in the feces from healthy subjects and Alzheimer's disease (AD) patients at early and middle stages. Remarkably, 29 fecal VOCs and 13 bacterial genera were differentiated from the healthy subjects and the AD patients. In general, higher amounts of acids and esters were found in in the feces of the AD patients and terpenes, sulfur compounds and aldehydes in the healthy subjects. At the early stage of AD, the most relevant VOCs with a higher abundance were short-chain fatty acids and their producing bacteria, Faecalibacterium and Lachnoclostridium. Coinciding with the development of dementia in the AD patients, parallel rises of heptanoic acid and Peptococcus were observed. At a more advanced stage of AD, the microbiota and volatiles shifted towards a profile in the feces with increases in hexanoic acid, Ruminococcus and Blautia. The most remarkable VOCs that were associated with the healthy subjects were 4-ethyl-phenol and dodecanol, together with their possible producers Clostridium and Coprococcus. Our results revealed a VOCs and microbiota crosstalk in AD development and their profiles in the feces were specific depending on the stage of AD. Additionally, some of the most significant fecal VOCs identified in our study could be used as potential biomarkers for the initiation and progression of AD.
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Affiliation(s)
- Cristina Ubeda
- Departamento de Nutrición y Bromatología, Facultad de Farmacia, Universidad de Sevilla, 41012 Sevilla, Spain
| | - María D. Vázquez-Carretero
- Departamento de Fisiología, Facultad de Farmacia, Universidad de Sevilla, 41012 Sevilla, Spain
- Correspondence: (M.D.V.-C.); (P.G.-M.); Tel.: +34-954556777 (M.D.V.-C.); +34-954556777 (P.G.-M.)
| | - Andrea Luque-Tirado
- Unidad de Memoria, Servicio de Neurología, Hospital Universitario Virgen del Rocío, 41013 Sevilla, Spain
| | - Rocío Ríos-Reina
- Departamento de Nutrición y Bromatología, Facultad de Farmacia, Universidad de Sevilla, 41012 Sevilla, Spain
| | - Ricardo Rubio-Sánchez
- Laboratorio de Análisis Clínicos, Hospital Universitario Valme, 41014 Sevilla, Spain
| | - Emilio Franco-Macías
- Unidad de Memoria, Servicio de Neurología, Hospital Universitario Virgen del Rocío, 41013 Sevilla, Spain
| | - Pablo García-Miranda
- Departamento de Fisiología, Facultad de Farmacia, Universidad de Sevilla, 41012 Sevilla, Spain
- Correspondence: (M.D.V.-C.); (P.G.-M.); Tel.: +34-954556777 (M.D.V.-C.); +34-954556777 (P.G.-M.)
| | - María L. Calonge
- Departamento de Fisiología, Facultad de Farmacia, Universidad de Sevilla, 41012 Sevilla, Spain
| | - María J. Peral
- Departamento de Fisiología, Facultad de Farmacia, Universidad de Sevilla, 41012 Sevilla, Spain
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15
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Abstract
The technological developments of recent times have allowed the use of innovative approaches to support the diagnosis of various diseases. Many of such clinical conditions are often associated with metabolic unbalance, in turn producing an alteration of the gut microbiota even during asymptomatic stages. As such, studies regarding the microbiota composition in biological fluids obtained by humans are continuously growing, and the methodologies for their investigation are rapidly changing, making it less invasive and more affordable. To this extent, Electronic Nose and Electronic Tongue tools are gaining importance in the relevant field, making them a useful alternative—or support—to traditional analytical methods. In light of this, the present manuscript seeks to investigate the development and use of such tools in the gut microbiota assessment according to the current literature. Significant gaps are still present, particularly concerning the Electronic Tongue systems, however the current evidence highlights the strong potential such tools own to enter the daily clinical practice, with significant advancement concerning the patients’ acceptability and cost saving for healthcare providers.
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16
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Kaloumenou M, Skotadis E, Lagopati N, Efstathopoulos E, Tsoukalas D. Breath Analysis: A Promising Tool for Disease Diagnosis-The Role of Sensors. SENSORS (BASEL, SWITZERLAND) 2022; 22:1238. [PMID: 35161984 PMCID: PMC8840008 DOI: 10.3390/s22031238] [Citation(s) in RCA: 25] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/31/2021] [Revised: 01/30/2022] [Accepted: 02/01/2022] [Indexed: 05/07/2023]
Abstract
Early-stage disease diagnosis is of particular importance for effective patient identification as well as their treatment. Lack of patient compliance for the existing diagnostic methods, however, limits prompt diagnosis, rendering the development of non-invasive diagnostic tools mandatory. One of the most promising non-invasive diagnostic methods that has also attracted great research interest during the last years is breath analysis; the method detects gas-analytes such as exhaled volatile organic compounds (VOCs) and inorganic gases that are considered to be important biomarkers for various disease-types. The diagnostic ability of gas-pattern detection using analytical techniques and especially sensors has been widely discussed in the literature; however, the incorporation of novel nanomaterials in sensor-development has also proved to enhance sensor performance, for both selective and cross-reactive applications. The aim of the first part of this review is to provide an up-to-date overview of the main categories of sensors studied for disease diagnosis applications via the detection of exhaled gas-analytes and to highlight the role of nanomaterials. The second and most novel part of this review concentrates on the remarkable applicability of breath analysis in differential diagnosis, phenotyping, and the staging of several disease-types, which are currently amongst the most pressing challenges in the field.
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Affiliation(s)
- Maria Kaloumenou
- Department of Applied Physics, National Technical University of Athens, 15780 Athens, Greece; (M.K.); (D.T.)
| | - Evangelos Skotadis
- Department of Applied Physics, National Technical University of Athens, 15780 Athens, Greece; (M.K.); (D.T.)
| | - Nefeli Lagopati
- Medical School, National and Kapodistrian University of Athens, 75, Mikras Asias Str., Goudi, 11527 Athens, Greece; (N.L.); (E.E.)
| | - Efstathios Efstathopoulos
- Medical School, National and Kapodistrian University of Athens, 75, Mikras Asias Str., Goudi, 11527 Athens, Greece; (N.L.); (E.E.)
| | - Dimitris Tsoukalas
- Department of Applied Physics, National Technical University of Athens, 15780 Athens, Greece; (M.K.); (D.T.)
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17
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Identification of volatile compounds from bacteria by spectrometric methods in medicine diagnostic and other areas: current state and perspectives. Appl Microbiol Biotechnol 2021; 105:6245-6255. [PMID: 34415392 PMCID: PMC8377328 DOI: 10.1007/s00253-021-11469-7] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2021] [Revised: 07/20/2021] [Accepted: 07/22/2021] [Indexed: 10/25/2022]
Abstract
Diagnosis of bacterial infections until today mostly relies on conventional microbiological methods. The resulting long turnaround times can lead to delayed initiation of adequate antibiotic therapy and prolonged periods of empiric antibiotic therapy (e.g., in intensive care medicine). Therewith, they contribute to the mortality of bacterial infections and the induction of multidrug resistances. The detection of species specific volatile organic compounds (VOCs) emitted by bacteria has been proposed as a possible diagnostic approach with the potential to serve as an innovative point-of-care diagnostic tool with very short turnaround times. A range of spectrometric methods are available which allow the detection and quantification of bacterial VOCs down to a range of part per trillion. This narrative review introduces the application of spectrometric analytical methods for the purpose of detecting VOCs of bacterial origin and their clinical use for diagnosing different infectious conditions over the last decade. KEY POINTS: • Detection of VOCs enables bacterial differentiation in various medical conditions. • Spectrometric methods may function as point-of-care diagnostics in near future.
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18
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Snitz K, Andelman-Gur M, Pinchover L, Weissgross R, Weissbrod A, Mishor E, Zoller R, Linetsky V, Medhanie A, Shushan S, Jaffe E, Sobel N. Proof of concept for real-time detection of SARS CoV-2 infection with an electronic nose. PLoS One 2021; 16:e0252121. [PMID: 34077435 PMCID: PMC8172018 DOI: 10.1371/journal.pone.0252121] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2020] [Accepted: 05/10/2021] [Indexed: 01/12/2023] Open
Abstract
Rapid diagnosis is key to curtailing the Covid-19 pandemic. One path to such rapid diagnosis may rely on identifying volatile organic compounds (VOCs) emitted by the infected body, or in other words, identifying the smell of the infection. Consistent with this rationale, dogs can use their nose to identify Covid-19 patients. Given the scale of the pandemic, however, animal deployment is a challenging solution. In contrast, electronic noses (eNoses) are machines aimed at mimicking animal olfaction, and these can be deployed at scale. To test the hypothesis that SARS CoV-2 infection is associated with a body-odor detectable by an eNose, we placed a generic eNose in-line at a drive-through testing station. We applied a deep learning classifier to the eNose measurements, and achieved real-time detection of SARS CoV-2 infection at a level significantly better than chance, for both symptomatic and non-symptomatic participants. This proof of concept with a generic eNose implies that an optimized eNose may allow effective real-time diagnosis, which would provide for extensive relief in the Covid-19 pandemic.
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Affiliation(s)
- Kobi Snitz
- Department of Neurobiology and Azrieli Center for Human Brain Imaging and Research, Weizmann Institute of Science, Rehovot, Israel
- * E-mail: (NS); (KS)
| | - Michal Andelman-Gur
- Department of Neurobiology and Azrieli Center for Human Brain Imaging and Research, Weizmann Institute of Science, Rehovot, Israel
| | - Liron Pinchover
- Department of Neurobiology and Azrieli Center for Human Brain Imaging and Research, Weizmann Institute of Science, Rehovot, Israel
| | - Reut Weissgross
- Department of Neurobiology and Azrieli Center for Human Brain Imaging and Research, Weizmann Institute of Science, Rehovot, Israel
| | - Aharon Weissbrod
- Department of Neurobiology and Azrieli Center for Human Brain Imaging and Research, Weizmann Institute of Science, Rehovot, Israel
| | - Eva Mishor
- Department of Neurobiology and Azrieli Center for Human Brain Imaging and Research, Weizmann Institute of Science, Rehovot, Israel
| | - Roni Zoller
- Department of Neurobiology and Azrieli Center for Human Brain Imaging and Research, Weizmann Institute of Science, Rehovot, Israel
| | - Vera Linetsky
- Department of Neurobiology and Azrieli Center for Human Brain Imaging and Research, Weizmann Institute of Science, Rehovot, Israel
| | - Abebe Medhanie
- Department of Neurobiology and Azrieli Center for Human Brain Imaging and Research, Weizmann Institute of Science, Rehovot, Israel
| | - Sagit Shushan
- Department of Neurobiology and Azrieli Center for Human Brain Imaging and Research, Weizmann Institute of Science, Rehovot, Israel
- Department of Otolaryngology & Head and Neck Surgery, Edith Wolfson Medical Center, Holon, Israel
| | - Eli Jaffe
- Magen David Adom in Israel and Department of Emergency Medicine, Ben-Gurion University of the Negev, Beer Sheva, Israel
| | - Noam Sobel
- Department of Neurobiology and Azrieli Center for Human Brain Imaging and Research, Weizmann Institute of Science, Rehovot, Israel
- * E-mail: (NS); (KS)
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19
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Sinclair E, Walton-Doyle C, Sarkar D, Hollywood KA, Milne J, Lim SH, Kunath T, Rijs AM, de Bie RMA, Silverdale M, Trivedi DK, Barran P. Validating Differential Volatilome Profiles in Parkinson's Disease. ACS CENTRAL SCIENCE 2021; 7:300-306. [PMID: 33655068 PMCID: PMC7908024 DOI: 10.1021/acscentsci.0c01028] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/04/2020] [Indexed: 05/10/2023]
Abstract
Parkinson's disease (PD) is a progressive neurodegenerative disorder that does not currently have a robust clinical diagnostic test. Nonmotor symptoms such as skin disorders have long since been associated with the disease, and more recently a characteristic odor emanating from the skin of people with Parkinson's has been identified. Here, dynamic head space (DHS) thermal desorption (TD) gas chromatography-mass spectrometry (GC-MS) is implemented to directly measure the volatile components of sebum on swabs sampled from people with Parkinson's-both drug naïve and those on PD medications (n = 100) and control subjects (n = 29). Supervised multivariate analyses of data showed 84.4% correct classification of PD cases using all detected volatile compounds. Variable importance in projection (VIP) scores were generated from these data, which revealed eight features with VIP > 1 and p < 0.05 which all presented a downregulation within the control cohorts. Purified standards based on previously annotated analytes of interest eicosane and octadecanal did not match to patient sample data, although multiple metabolite features are annotated with these compounds all with high spectral matches indicating the presence of a series of similar structured species. DHS-TD-GC-MS analysis of a range of lipid standards has revealed the presence of common hydrocarbon species rather than differentiated intact compounds which are hypothesized to be breakdown products of lipids. This replication study validates that a differential volatile profile between control and PD cohorts can be measured using an analytical method that measures volatile compounds directly from skin swabs.
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Affiliation(s)
- Eleanor Sinclair
- Manchester
Institute of Biotechnology, School of Chemistry, The University of Manchester, Princess Street, Manchester M1 7DN, United Kingdom
| | - Caitlin Walton-Doyle
- Manchester
Institute of Biotechnology, School of Chemistry, The University of Manchester, Princess Street, Manchester M1 7DN, United Kingdom
| | - Depanjan Sarkar
- Manchester
Institute of Biotechnology, School of Chemistry, The University of Manchester, Princess Street, Manchester M1 7DN, United Kingdom
| | - Katherine A. Hollywood
- Manchester
Institute of Biotechnology, School of Chemistry, The University of Manchester, Princess Street, Manchester M1 7DN, United Kingdom
- Manchester
Centre for Synthetic Biology of Fine and Speciality Chemicals (SYNBIOCHEM),
Manchester Institute of Biotechnology, School of Chemistry, The University of Manchester, Princess Street, Manchester M1 7DN, United Kingdom
| | - Joy Milne
- Manchester
Institute of Biotechnology, School of Chemistry, The University of Manchester, Princess Street, Manchester M1 7DN, United Kingdom
| | - Sze Hway Lim
- Department
of Neurology, Salford Royal Foundation Trust, Manchester Academic
Health Science Centre, The University of
Manchester, Manchester M13 9PL, United Kingdom
| | - Tilo Kunath
- Institute
for Stem Cell Research, School of Biological Sciences, The University of Edinburgh, Edinburgh EH16 4UU, United Kingdom
| | - Anouk M. Rijs
- Division
of BioAnalytical Chemistry, AIMMS Amsterdam Institute of Molecular
and Life Sciences, Vrije Universiteit Amsterdam, De Boelelaan 1108, 1081 HZ Amsterdam, The Netherlands
| | - Rob M. A. de Bie
- Department
of Neurology, Amsterdam Neuroscience, Amsterdam
University Medical Centers, University of Amsterdam, Meibergdreef 9, 1105
AZ Amsterdam, The Netherlands
| | - Monty Silverdale
- Department
of Neurology, Salford Royal Foundation Trust, Manchester Academic
Health Science Centre, The University of
Manchester, Manchester M13 9PL, United Kingdom
| | - Drupad K. Trivedi
- Manchester
Institute of Biotechnology, School of Chemistry, The University of Manchester, Princess Street, Manchester M1 7DN, United Kingdom
| | - Perdita Barran
- Manchester
Institute of Biotechnology, School of Chemistry, The University of Manchester, Princess Street, Manchester M1 7DN, United Kingdom
- E-mail:
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20
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Kenn K, Gloeckl R, Leitl D, Schneeberger T, Jarosch I, Hitzl W, Alter P, Sczepanski B, Winterkamp S, Boensch M, Schade-Brittinger C, Skevaki C, Holz O, Jones PW, Vogelmeier CF, Koczulla AR. Protocol for an observational study to identify potential predictors of an acute exacerbation in patients with chronic obstructive pulmonary disease (the PACE Study). BMJ Open 2021; 11:e043014. [PMID: 33558356 PMCID: PMC7871687 DOI: 10.1136/bmjopen-2020-043014] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/03/2022] Open
Abstract
INTRODUCTION Acute exacerbations of chronic obstructive pulmonary disease (AECOPD) are the most critical events for patients with COPD that have a negative impact on patients' quality of life, accelerate disease progression, and can result in hospital admissions and death. Although there is no distinct definition or detailed knowledge about AECOPD, it is commonly used as primary outcome in clinical studies. Furthermore, it may be difficult in clinical practice to differentiate the worsening of symptoms due to an AECOPD or to the development of heart failure. Therefore, it is of major clinical importance to investigate the underlying pathophysiology, and if possible, predictors of an AECOPD and thus to identify patients who are at high risk for developing an acute exacerbation. METHODS AND ANALYSIS In total, 355 patients with COPD will be included prospectively to this study during a 3-week inpatient pulmonary rehabilitation programme at the Schoen Klinik Berchtesgadener Land, Schoenau am Koenigssee (Germany). All patients will be closely monitored from admission to discharge. Lung function, exercise tests, clinical parameters, quality of life, physical activity and symptoms will be recorded, and blood samples and exhaled air will be collected. If a patient develops an AECOPD, there will be additional comprehensive diagnostic assessments to differentiate between cardiac, pulmonary or cardiopulmonary causes of worsening. Follow-up measures will be performed at 6, 12 and 24 months.Exploratory data analyses methods will be used for the primary research question (screening and identification of possible factors to predict an AECOPD). Regression analyses and a generalised linear model with a binomial outcome (AECOPD) will be applied to test if predictors are significant. ETHICS AND DISSEMINATION This study has been approved by the Ethical Committee of the Philipps University Marburg, Germany (No. 61/19). The results will be presented in conferences and published in a peer-reviewed journal. TRIAL REGISTRATION NUMBER NCT04140097.
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Affiliation(s)
- Klaus Kenn
- Department of Pulmonary Rehabilitation, Member of the German Center for Lung Research (DZL), Philipps University Marburg, Marburg, Germany
- Institute for Pulmonary Rehabilitation Research, Schoen Klinik Berchtesgadener Land, Schoenau am Koenigssee, Germany
| | - Rainer Gloeckl
- Department of Pulmonary Rehabilitation, Member of the German Center for Lung Research (DZL), Philipps University Marburg, Marburg, Germany
- Institute for Pulmonary Rehabilitation Research, Schoen Klinik Berchtesgadener Land, Schoenau am Koenigssee, Germany
| | - Daniela Leitl
- Department of Pulmonary Rehabilitation, Member of the German Center for Lung Research (DZL), Philipps University Marburg, Marburg, Germany
- Institute for Pulmonary Rehabilitation Research, Schoen Klinik Berchtesgadener Land, Schoenau am Koenigssee, Germany
| | - Tessa Schneeberger
- Department of Pulmonary Rehabilitation, Member of the German Center for Lung Research (DZL), Philipps University Marburg, Marburg, Germany
- Institute for Pulmonary Rehabilitation Research, Schoen Klinik Berchtesgadener Land, Schoenau am Koenigssee, Germany
| | - Inga Jarosch
- Department of Pulmonary Rehabilitation, Member of the German Center for Lung Research (DZL), Philipps University Marburg, Marburg, Germany
- Institute for Pulmonary Rehabilitation Research, Schoen Klinik Berchtesgadener Land, Schoenau am Koenigssee, Germany
| | - Wolfgang Hitzl
- Research Office (Biostatistics), Paracelsus Medical University Salzburg, Salzburg, Austria
- Department of Ophthalmology and Optometry, Paracelsus Medical University Salzburg, Salzburg, Austria
- Research Program Experimental Ophtalmology and Glaucoma Reserach, Paracelsus Medical University, Salzburg, Austria
| | - Peter Alter
- Department of Medicine, Pulmonary and Critical Care Medicine, Member of the German Center for Lung Research (DZL), Philipps University Marburg, Marburg, Germany
| | - Bernd Sczepanski
- Institute for Pulmonary Rehabilitation Research, Schoen Klinik Berchtesgadener Land, Schoenau am Koenigssee, Germany
| | - Sandra Winterkamp
- Institute for Pulmonary Rehabilitation Research, Schoen Klinik Berchtesgadener Land, Schoenau am Koenigssee, Germany
| | - Martina Boensch
- Institute for Pulmonary Rehabilitation Research, Schoen Klinik Berchtesgadener Land, Schoenau am Koenigssee, Germany
| | - Carmen Schade-Brittinger
- Coordinating Centre for Clinical Trials, Member of the German Center for Lung Research (DZL), Philipps University Marburg, Marburg, Germany
| | - Chrysanthi Skevaki
- Institute of Laboratory Medicine, Universities of Giessen and Marburg Lung Center (UGMLC), Member of the German Center for Lung Research (DZL), Marburg, Germany
| | - Olaf Holz
- Biomedical Research in Endstage and Obstructive Lung Disease Hannover (BREATH), Fraunhofer Institute for Toxicology and Experimental Medicine (ITEM), Member of the German Center for Lung Research (DZL), Hannover, Germany
| | - Paul W Jones
- Institute of Infection and Immunity, St George's University of London, London, UK
| | - Claus F Vogelmeier
- Department of Medicine, Pulmonary and Critical Care Medicine, Member of the German Center for Lung Research (DZL), Philipps University Marburg, Marburg, Germany
| | - Andreas R Koczulla
- Department of Pulmonary Rehabilitation, Member of the German Center for Lung Research (DZL), Philipps University Marburg, Marburg, Germany
- Institute for Pulmonary Rehabilitation Research, Schoen Klinik Berchtesgadener Land, Schoenau am Koenigssee, Germany
- Department of Medicine, Paracelsus Medical University, Salzburg, Austria
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21
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Kuo TC, Tan CE, Wang SY, Lin OA, Su BH, Hsu MT, Lin J, Cheng YY, Chen CS, Yang YC, Chen KH, Lin SW, Ho CC, Kuo CH, Tseng YJ. Human Breathomics Database. DATABASE-THE JOURNAL OF BIOLOGICAL DATABASES AND CURATION 2020; 2020:5682403. [PMID: 31976536 PMCID: PMC6978997 DOI: 10.1093/database/baz139] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/19/2019] [Revised: 09/12/2019] [Accepted: 11/13/2019] [Indexed: 12/11/2022]
Abstract
Breathomics is a special branch of metabolomics that quantifies volatile organic compounds (VOCs) from collected exhaled breath samples. Understanding how breath molecules are related to diseases, mechanisms and pathways identified from experimental analytical measurements is challenging due to the lack of an organized resource describing breath molecules, related references and biomedical information embedded in the literature. To provide breath VOCs, related references and biomedical information, we aim to organize a database composed of manually curated information and automatically extracted biomedical information. First, VOCs-related disease information was manually organized from 207 literature linked to 99 VOCs and known Medical Subject Headings (MeSH) terms. Then an automated text mining algorithm was used to extract biomedical information from this literature. In the end, the manually curated information and auto-extracted biomedical information was combined to form a breath molecule database—the Human Breathomics Database (HBDB). We first manually curated and organized disease information including MeSH term from 207 literatures associated with 99 VOCs. Then, an automatic pipeline of text mining approach was used to collect 2766 literatures and extract biomedical information from breath researches. We combined curated information with automatically extracted biomedical information to assemble a breath molecule database, the HBDB. The HBDB is a database that includes references, VOCs and diseases associated with human breathomics. Most of these VOCs were detected in human breath samples or exhaled breath condensate samples. So far, the database contains a total of 913 VOCs in relation to human exhaled breath researches reported in 2766 publications. The HBDB is the most comprehensive HBDB of VOCs in human exhaled breath to date. It is a useful and organized resource for researchers and clinicians to identify and further investigate potential biomarkers from the breath of patients. Database URL: https://hbdb.cmdm.tw
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Affiliation(s)
- Tien-Chueh Kuo
- Graduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University, No. 1, Sec. 4, Roosevelt Road, Taipei 10617, Taiwan.,The Metabolomics Core Laboratory, Centers of Genomic Medicine and Precision Medicine, National Taiwan University, No. 2, Syu-Jhou Road, Taipei 10055, Taiwan.,Drug Research Center, College of Pharmacy, College of Medicine, National Taiwan University, No. 33, Linsen S. Road, Taipei 10055, Taiwan
| | - Cheng-En Tan
- The Metabolomics Core Laboratory, Centers of Genomic Medicine and Precision Medicine, National Taiwan University, No. 2, Syu-Jhou Road, Taipei 10055, Taiwan.,Drug Research Center, College of Pharmacy, College of Medicine, National Taiwan University, No. 33, Linsen S. Road, Taipei 10055, Taiwan.,Department of Computer Science and Information Engineering, National Taiwan University, No. 1, Sec. 4, Roosevelt Road, Taipei 10617, Taiwan
| | - San-Yuan Wang
- The Metabolomics Core Laboratory, Centers of Genomic Medicine and Precision Medicine, National Taiwan University, No. 2, Syu-Jhou Road, Taipei 10055, Taiwan.,Department of Computer Science and Information Engineering, National Taiwan University, No. 1, Sec. 4, Roosevelt Road, Taipei 10617, Taiwan.,Master Program in Clinical Pharmacogenomics and Pharmacoproteomics, College of Pharmacy, Taipei Medical University, No. 250, Wu-Hsing St., Taipei 11031, Taiwan
| | - Olivia A Lin
- Graduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University, No. 1, Sec. 4, Roosevelt Road, Taipei 10617, Taiwan
| | - Bo-Han Su
- Department of Computer Science and Information Engineering, National Taiwan University, No. 1, Sec. 4, Roosevelt Road, Taipei 10617, Taiwan
| | - Ming-Tsung Hsu
- Genome and Systems Biology Degree Program, National Taiwan University and Academia Sinica, No. 1, Sec. 4, Roosevelt Road, Taipei 10617, Taiwan
| | - Jessica Lin
- Graduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University, No. 1, Sec. 4, Roosevelt Road, Taipei 10617, Taiwan
| | - Yu-Yen Cheng
- Graduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University, No. 1, Sec. 4, Roosevelt Road, Taipei 10617, Taiwan.,The Metabolomics Core Laboratory, Centers of Genomic Medicine and Precision Medicine, National Taiwan University, No. 2, Syu-Jhou Road, Taipei 10055, Taiwan
| | - Ciao-Sin Chen
- Department of Pharmacy, School of Pharmacy, College of Medicine, National Taiwan University, No. 33, Linsen S. Road, Taipei 10055, Taiwan
| | - Yu-Chieh Yang
- Department of Obstetrics and Gynecology, National Taiwan University Hospital-Yunlin Branch, No. 579, Sec. 2, Yunlin Road, Douliu, Yunlin County 640, Taiwan
| | - Kuo-Hsing Chen
- Department of Oncology, National Taiwan University Hospital, National Taiwan University Cancer Center, No. 1, Sec. 4, Roosevelt Road, Taipei 10048, Taiwan
| | - Shu-Wen Lin
- Graduate Institute of Clinical Pharmacy, College of Medicine, National Taiwan University, No. 33, Linsen S. Road, Taipei 10055, Taiwan
| | - Chao-Chi Ho
- Department of Internal Medicine, National Taiwan University Hospital, No. 7, Chung-Shan South Road, Taipei 10002, Taiwan
| | - Ching-Hua Kuo
- The Metabolomics Core Laboratory, Centers of Genomic Medicine and Precision Medicine, National Taiwan University, No. 2, Syu-Jhou Road, Taipei 10055, Taiwan.,Drug Research Center, College of Pharmacy, College of Medicine, National Taiwan University, No. 33, Linsen S. Road, Taipei 10055, Taiwan.,Department of Pharmacy, School of Pharmacy, College of Medicine, National Taiwan University, No. 33, Linsen S. Road, Taipei 10055, Taiwan
| | - Yufeng Jane Tseng
- Graduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University, No. 1, Sec. 4, Roosevelt Road, Taipei 10617, Taiwan.,The Metabolomics Core Laboratory, Centers of Genomic Medicine and Precision Medicine, National Taiwan University, No. 2, Syu-Jhou Road, Taipei 10055, Taiwan.,Drug Research Center, College of Pharmacy, College of Medicine, National Taiwan University, No. 33, Linsen S. Road, Taipei 10055, Taiwan.,Department of Computer Science and Information Engineering, National Taiwan University, No. 1, Sec. 4, Roosevelt Road, Taipei 10617, Taiwan
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22
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Serafín V, Gamella M, Pedrero M, Montero-Calle A, Razzino CA, Yáñez-Sedeño P, Barderas R, Campuzano S, Pingarrón JM. Enlightening the advancements in electrochemical bioanalysis for the diagnosis of Alzheimer's disease and other neurodegenerative disorders. J Pharm Biomed Anal 2020; 189:113437. [PMID: 32629192 DOI: 10.1016/j.jpba.2020.113437] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2020] [Revised: 06/10/2020] [Accepted: 06/17/2020] [Indexed: 12/13/2022]
Abstract
Neurodegenerative disorders (NDD), and particularly Alzheimer's disease (AD), are one of the greatest challenges facing our current medicine and society because of its increasing incidence and the high burden imposed both on patients' families and health systems. Despite this, their accurate diagnosis, mostly conducted by cerebrospinal fluid (CSF) analysis or neuroimaging techniques, costly, time-consuming, and unaffordable for most of the population, remains a complex task. In this situation, electrochemical biosensors are flourishing as promising alternative tools for the simple, fast, and low-cost diagnosis of NDD/AD. This review article provides the relevant clinical details of NDD/AD along with the closely related genetic (genetic mutations, polymorphisms of ApoE and specific miRNAs) and proteomic (amyloid-β peptides, total and phosphorylated tau protein) biomarkers circulating mostly in CSF. In addition, the article systematically enlightens a general view of the electrochemical affinity biosensors (mostly aptasensors and immunosensors) reported in the past two years for the determination of such biomarkers. The different developed strategies, analytical performances and applications are comprehensively discussed. Recent advancements in signal amplification methodologies involving smart designs and the use of nanomaterials and rational surface chemistries, as well as the challenges that must be struggled and the prospects in electrochemical affinity biosensing to bring more accessibility to NDD/AD diagnosis, prognosis, and follow-up, are also pointed out.
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Affiliation(s)
- V Serafín
- Department of Analytical Chemistry, Faculty of Chemical Sciences, Complutense University of Madrid, Madrid, 28040, Spain
| | - M Gamella
- Department of Analytical Chemistry, Faculty of Chemical Sciences, Complutense University of Madrid, Madrid, 28040, Spain
| | - M Pedrero
- Department of Analytical Chemistry, Faculty of Chemical Sciences, Complutense University of Madrid, Madrid, 28040, Spain
| | - A Montero-Calle
- Chronic Disease Programme, UFIEC, Carlos III Health Institute, Majadahonda, Madrid, 28220, Spain
| | - C A Razzino
- Department of Analytical Chemistry, Faculty of Chemical Sciences, Complutense University of Madrid, Madrid, 28040, Spain
| | - P Yáñez-Sedeño
- Department of Analytical Chemistry, Faculty of Chemical Sciences, Complutense University of Madrid, Madrid, 28040, Spain
| | - R Barderas
- Chronic Disease Programme, UFIEC, Carlos III Health Institute, Majadahonda, Madrid, 28220, Spain.
| | - S Campuzano
- Department of Analytical Chemistry, Faculty of Chemical Sciences, Complutense University of Madrid, Madrid, 28040, Spain.
| | - J M Pingarrón
- Department of Analytical Chemistry, Faculty of Chemical Sciences, Complutense University of Madrid, Madrid, 28040, Spain.
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23
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Tiele A, Wicaksono A, Daulton E, Ifeachor E, Eyre V, Clarke S, Timings L, Pearson S, Covington JA, Li X. Breath-based non-invasive diagnosis of Alzheimer's disease: a pilot study. J Breath Res 2020; 14:026003. [PMID: 31816609 DOI: 10.1088/1752-7163/ab6016] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
Early detection of Alzheimer's disease (AD) will help researchers to better understand the disease and develop improved treatments. Recent developments have thus focused on identifying biomarkers for mild cognitive impairment due to AD (MCI) and AD during the preclinical phase. The aim of this pilot study is to determine whether exhaled volatile organic compounds (VOCs) can be used as a non-invasive method to distinguish controls from MCI, controls from AD and to determine whether there are differences between MCI and AD. The study used gas chromatography-ion mobility spectrometry (GC-IMS) techniques. Confounding factors, such as age, smoking habits, gender and alcohol consumption are investigated to demonstrate the efficacy of results. One hundred subjects were recruited including 50 controls, 25 AD and 25 MCI patients. The subject cohort was age- and gender-matched to minimise bias. Breath samples were analysed using a commercial GC-IMS instrument (G.A.S. BreathSpec, Dortmund, Germany). Data analysis indicates that the GC-IMS signal was consistently able to separate between diagnostic groups [AUC ± 95%, sensitivity, specificity], controls versus MCI: [0.77 (0.64-0.90), 0.68, 0.80], controls versus AD: [0.83 (0.72-0.94), 0.60, 0.96], and MCI versus AD: [0.70 (0.55-0.85), 0.60, 0.84]. VOC analysis indicates that six compounds play a crucial role in distinguishing between diagnostic groups. Analysis of possible confounding factors indicate that gender, age, smoking habits and alcohol consumption have insignificant influence on breath content. This pilot study confirms the utility of exhaled breath analysis to distinguish between AD, MCI and control subjects. Thus, GC-IMS offers great potential as a non-invasive, high-throughput, diagnostic technique for diagnosing and potentially monitoring AD in a clinical setting.
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Affiliation(s)
- Akira Tiele
- School of Engineering, University of Warwick, Coventry CV4 7AL, United Kingdom
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24
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Xu B, Moradi M, Kuplicki R, Stewart JL, McKinney B, Sen S, Paulus MP. Machine Learning Analysis of Electronic Nose in a Transdiagnostic Community Sample With a Streamlined Data Collection Approach: No Links Between Volatile Organic Compounds and Psychiatric Symptoms. Front Psychiatry 2020; 11:503248. [PMID: 33192639 PMCID: PMC7524957 DOI: 10.3389/fpsyt.2020.503248] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/07/2019] [Accepted: 08/24/2020] [Indexed: 11/25/2022] Open
Abstract
Non-intrusive, easy-to-use and pragmatic collection of biological processes is warranted to evaluate potential biomarkers of psychiatric symptoms. Prior work with relatively modest sample sizes suggests that under highly-controlled sampling conditions, volatile organic compounds extracted from the human breath (exhalome), often measured by an electronic nose ("e-nose"), may be related to physical and mental health. The present study utilized a streamlined data collection approach and attempted to replicate and extend prior e-nose links to mental health in a standard research setting within large transdiagnostic community dataset (N = 1207; 746 females; 18-61 years) who completed a screening visit at the Laureate Institute for Brain Research between 07/2016 and 05/2018. Factor analysis was used to obtain latent exhalome variables, and machine learning approaches were employed using these latent variables to predict three types of symptoms independent of each other (depression, anxiety, and substance use disorder) within separate training and a test sets. After adjusting for age, gender, body mass index, and smoking status, the best fitting algorithm produced by the training set accounted for nearly 0% of the test set's variance. In each case the standard error included the zero line, indicating that models were not predictive of clinical symptoms. Although some sample variance was predicted, findings did not generalize to out-of-sample data. Based on these findings, we conclude that the exhalome, as measured by the e-nose within a less-controlled environment than previously reported, is not able to provide clinically useful assessments of current depression, anxiety or substance use severity.
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Affiliation(s)
- Bohan Xu
- Laureate Institute for Brain Research, Tulsa, OK, United States.,Department of Computer Science, Tandy School of Computer Science, University of Tulsa, Tulsa, OK, United States
| | - Mahdi Moradi
- Laureate Institute for Brain Research, Tulsa, OK, United States.,Department of Computer Science, Tandy School of Computer Science, University of Tulsa, Tulsa, OK, United States
| | - Rayus Kuplicki
- Laureate Institute for Brain Research, Tulsa, OK, United States
| | - Jennifer L Stewart
- Laureate Institute for Brain Research, Tulsa, OK, United States.,Department of Community Medicine, Oxley College of Health Sciences, University of Tulsa, Tulsa, OK, United States
| | - Brett McKinney
- Department of Computer Science, Tandy School of Computer Science, University of Tulsa, Tulsa, OK, United States.,Department of Mathematics, College of Engineering & Natural Sciences, University of Tulsa, Tulsa, OK, United States
| | - Sandip Sen
- Department of Computer Science, Tandy School of Computer Science, University of Tulsa, Tulsa, OK, United States
| | - Martin P Paulus
- Laureate Institute for Brain Research, Tulsa, OK, United States.,Department of Community Medicine, Oxley College of Health Sciences, University of Tulsa, Tulsa, OK, United States.,Department of Psychiatry, School of Medicine, University of California San Diego, San Diego, CA, United States
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25
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Orzechowska S, Mazurek A, Świsłocka R, Lewandowski W. Electronic Nose: Recent Developments in Gas Sensing and Molecular Mechanisms of Graphene Detection and Other Materials. MATERIALS 2019; 13:ma13010080. [PMID: 31877901 PMCID: PMC6981730 DOI: 10.3390/ma13010080] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/20/2019] [Revised: 12/17/2019] [Accepted: 12/19/2019] [Indexed: 12/18/2022]
Abstract
Keywords: graphene; electronic nose; carbon nanotubes; porphyrins; conductive polymers.
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Affiliation(s)
- Sylwia Orzechowska
- M. Smoluchowski Institute of Physics, Jagiellonian University, 30-348 Krakow, Poland
- Correspondence: ; Tel.: +48-12-664-4637
| | - Andrzej Mazurek
- Faculty of Pharmacy, Medical University of Warsaw, 02-097 Warszawa, Poland;
| | - Renata Świsłocka
- Department of Chemistry, Biology and Biotechnology, Bialystok University of Technology, 15-351 Bialystok, Poland; (R.Ś.); (W.L.)
| | - Włodzimierz Lewandowski
- Department of Chemistry, Biology and Biotechnology, Bialystok University of Technology, 15-351 Bialystok, Poland; (R.Ś.); (W.L.)
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26
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Iitani K, Toma K, Arakawa T, Mitsubayashi K. Ultrasensitive Sniff-Cam for Biofluorometric-Imaging of Breath Ethanol Caused by Metabolism of Intestinal Flora. Anal Chem 2019; 91:9458-9465. [PMID: 31287286 DOI: 10.1021/acs.analchem.8b05840] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
We developed a gas-imaging system (sniff-cam) for gaseous ethanol (EtOH) with improved sensitivity. The sniff-cam was applied to measure the extremely low concentration distribution of breath EtOH without the consumption of alcohol, which is related to the activity of the oral or gut bacterial flora. A ring-type ultraviolet-light-emitting diode was mounted around a camera lens as an excitation light source, which enabled simultaneous excitation and imaging of the fluorescence. In the EtOH sniff-cam, a nicotinamide adenine dinucleotide (NAD)-dependent alcohol dehydrogenase (ADH) was used to catalyze the redox reaction between EtOH and the oxidized form of NAD (NAD+). Upon application of gaseous EtOH to the ADH-immobilized mesh that was soaked in an NAD+ solution and placed in front of the camera, NADH was produced through an ADH-mediated reaction. NADH expresses fluorescence at an emission wavelength of 490 nm and excitation wavelength of 340 nm. Thus, the concentration distribution of EtOH was visualized by measuring the distribution of the fluorescence light intensity from NADH on the ADH-immobilized mesh surface. First, a comparison of image analysis methods based on the red-green-blue color (RGB) images and the optimization of the buffer pH and NAD+ solution concentration was performed. The new sniff-cam showed a 25-fold greater sensitivity and broader dynamic range (20.6-300000 ppb) in comparison to those of the previously fabricated sniff-cam. Finally, we measured the concentration distribution of breath EtOH without alcohol consumption using the improved sniff-cam and obtained a value of 116.2 ± 35.7 ppb (n = 10).
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Affiliation(s)
- Kenta Iitani
- Postdoctoral Research Fellow PD , Japan Society for the Promotion of Science , 5-3-1 Kojimatchi , Chiyoda-ku, Tokyo 102-0083 , Japan.,Department of Life Science and Medical Bioscience, Graduate School of Advanced Science and Engineering , Waseda University (TWIns) , 2-2 Wakamatsu-cho , Shinjuku-ku, Tokyo 162-8480 , Japan.,Graduate School of Medical and Dental Sciences , Tokyo Medical and Dental University , 1-5-45 Yushima , Bunkyo-ku, Tokyo 113-8510 , Japan
| | - Koji Toma
- Department of Biomedical Devices and Instrumentation, Institute of Biomaterials and Bioengineering , Tokyo Medical and Dental University , 2-3-10 Kanda-Surugadai , Chiyoda-ku, Tokyo 101-0062 , Japan
| | - Takahiro Arakawa
- Department of Biomedical Devices and Instrumentation, Institute of Biomaterials and Bioengineering , Tokyo Medical and Dental University , 2-3-10 Kanda-Surugadai , Chiyoda-ku, Tokyo 101-0062 , Japan
| | - Kohji Mitsubayashi
- Graduate School of Medical and Dental Sciences , Tokyo Medical and Dental University , 1-5-45 Yushima , Bunkyo-ku, Tokyo 113-8510 , Japan.,Department of Biomedical Devices and Instrumentation, Institute of Biomaterials and Bioengineering , Tokyo Medical and Dental University , 2-3-10 Kanda-Surugadai , Chiyoda-ku, Tokyo 101-0062 , Japan
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27
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Switchable sniff-cam (gas-imaging system) based on redox reactions of alcohol dehydrogenase for ethanol and acetaldehyde in exhaled breath. Talanta 2019; 197:249-256. [DOI: 10.1016/j.talanta.2018.12.070] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2018] [Revised: 12/21/2018] [Accepted: 12/21/2018] [Indexed: 11/18/2022]
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28
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Mitropoulos K, Katsila T, Patrinos GP, Pampalakis G. Multi-Omics for Biomarker Discovery and Target Validation in Biofluids for Amyotrophic Lateral Sclerosis Diagnosis. OMICS-A JOURNAL OF INTEGRATIVE BIOLOGY 2019; 22:52-64. [PMID: 29356625 DOI: 10.1089/omi.2017.0183] [Citation(s) in RCA: 25] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Amyotrophic lateral sclerosis (ALS) is a rare but usually fatal neurodegenerative disease characterized by motor neuron degeneration in the brain and the spinal cord. Two forms are recognized, the familial that accounts for 5-10% and the sporadic that accounts for the rest. New studies suggest that ALS is a highly heterogeneous disease, and this diversity is a major reason for the lack of successful therapeutic treatments. Indeed, only two drugs (riluzole and edaravone) have been approved that provide a limited improvement in the quality of life. Presently, the diagnosis of ALS is based on clinical examination and lag period from the onset of symptoms to the final diagnosis is ∼12 months. Therefore, the discovery of robust molecular biomarkers that can assist in the diagnosis is of major importance. DNA sequencing to identify pathogenic gene variants can be applied in the cases of familial ALS. However, it is not a routinely used diagnostic procedure and most importantly, it cannot be applied in the diagnosis of sporadic ALS. In this expert review, the current approaches in identification of new ALS biomarkers are discussed. The advent of various multi-omics biotechnology platforms, including miRNomics, proteomics, metabolomics, metallomics, volatolomics, and viromics, has assisted in the identification of new biomarkers. The biofluids are the most preferable material for the analysis of potential biomarkers (such as proteins and cell-free miRNAs), since they are easily obtained. In the near future, the biofluid-based biomarkers will be indispensable to classify different ALS subtypes and understand the molecular heterogeneity of the disease.
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Affiliation(s)
- Konstantinos Mitropoulos
- 1 Department of Histology and Embryology, University of Athens School of Medicine , Athens, Greece
| | - Theodora Katsila
- 2 Department of Pharmacy, University of Patras School of Health Sciences , Patras, Greece
| | - George P Patrinos
- 2 Department of Pharmacy, University of Patras School of Health Sciences , Patras, Greece .,3 Department of Pharmacy, College of Medicine and Health Sciences, United Arab Emirates University , Al Ain, UAE
| | - Georgios Pampalakis
- 2 Department of Pharmacy, University of Patras School of Health Sciences , Patras, Greece
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29
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Abstract
An odor sensor is a device for detecting target odors within a mixture, used in many fields including medical diagnosis. Electronic noses are networks of olfactory sensors, consisting of a surface whose properties are modified in the presence of odors, coupled with a measurement system. Their olfactory signature is analyzed in comparison with databases. Such portable devices can monitor body odors, e.g. in the breath, so as to reliably diagnose various pathologies at an early stage and non-invasively. It is tempting to use the naturally optimized molecular recognition of odorants and intrinsic sensitivity of the animal olfactory system to detect and discriminate minute amounts of odorants. New bioelectronic hybrid devices or "bioelectronic noses" can be designed by replacing the artificial sensory elements of e-noses by proteins naturally binding odorants, particularly olfactory receptors. As in the animal olfactory system, the detection and discrimination of odorants require a network of olfactory receptors. Prototypes of such miniaturized bioelectronic noses yield promising results.
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Affiliation(s)
- Édith Pajot-Augy
- NeuroBiologie de l'Olfaction, INRA, université Paris-Saclay, 78350 Jouy-en-Josas, France
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Finberg JPM, Schwartz M, Jeries R, Badarny S, Nakhleh MK, Abu Daoud E, Ayubkhanov Y, Aboud-Hawa M, Broza YY, Haick H. Sensor Array for Detection of Early Stage Parkinson's Disease before Medication. ACS Chem Neurosci 2018; 9:2548-2553. [PMID: 29989795 DOI: 10.1021/acschemneuro.8b00245] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023] Open
Abstract
Early diagnosis of Parkinson's disease (PD) is important because it affects the choice of therapy and is subject to a relatively high degree of error. In addition, early detection of PD can potentially enable the start of neuroprotective therapy before extensive loss of dopaminergic neurons of the substantia nigra occurs. However, until now, studies for early detection of PD using volatile biomarkers sampled only treated and medicated patients. Therefore, there is a great need to evaluate untreated patients for establishing a real world screening and diagnostic technology. Here we describe for the first time a clinical trial to distinguish between de novo PD and control subjects using an electronic system for detection of volatile molecules in exhaled breath (sensor array). We further determine for the first time the association to other common tests for PD diagnostics as smell, ultrasound, and nonmotor symptoms. The test group consisted of 29 PD patients after initial diagnosis by an experienced neurologist, compared with 19 control subjects of similar age. The sensitivity, specificity, and accuracy values of the sensor array to detect PD from controls were 79%, 84%, and 81% respectively, in comparison with midbrain ultrasonography (93%, 90%, 92%) and smell detection (62%, 89%, 73%). The results confirm previous data showing the potential of sensor arrays to detect PD.
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Affiliation(s)
- John P. M. Finberg
- Neuroscience Department, Bruce Rappaport Faculty of Medicine, Technion - Israel Institute of Technology, Haifa 3200003, Israel
| | - Miguel Schwartz
- Bruce Rappaport Faculty of Medicine, Technion - Israel Institute of Technology, Haifa 3200003, Israel
| | - Raneen Jeries
- Department of Chemical Engineering, Technion - Israel Institute of Technology, Haifa 3200003, Israel
| | - Samih Badarny
- Bruce Rappaport Faculty of Medicine, Technion - Israel Institute of Technology, Haifa 3200003, Israel
| | - Morad K. Nakhleh
- Department of Chemical Engineering, Technion - Israel Institute of Technology, Haifa 3200003, Israel
| | - Enas Abu Daoud
- Bruce Rappaport Faculty of Medicine, Technion - Israel Institute of Technology, Haifa 3200003, Israel
| | - Yelena Ayubkhanov
- Bruce Rappaport Faculty of Medicine, Technion - Israel Institute of Technology, Haifa 3200003, Israel
| | - Manal Aboud-Hawa
- Department of Chemical Engineering, Technion - Israel Institute of Technology, Haifa 3200003, Israel
| | - Yoav Y Broza
- Department of Chemical Engineering, Technion - Israel Institute of Technology, Haifa 3200003, Israel
| | - Hossam Haick
- Department of Chemical Engineering, Technion - Israel Institute of Technology, Haifa 3200003, Israel
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31
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Wallace MAG, Pleil JD. Evolution of clinical and environmental health applications of exhaled breath research: Review of methods and instrumentation for gas-phase, condensate, and aerosols. Anal Chim Acta 2018; 1024:18-38. [PMID: 29776545 PMCID: PMC6082128 DOI: 10.1016/j.aca.2018.01.069] [Citation(s) in RCA: 60] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2017] [Revised: 01/29/2018] [Accepted: 01/31/2018] [Indexed: 12/20/2022]
Abstract
Human breath, along with urine and blood, has long been one of the three major biological media for assessing human health and environmental exposure. In fact, the detection of odor on human breath, as described by Hippocrates in 400 BC, is considered the first analytical health assessment tool. Although less common in comparison to contemporary bio-fluids analyses, breath has become an attractive diagnostic medium as sampling is non-invasive, unlimited in timing and volume, and does not require clinical personnel. Exhaled breath, exhaled breath condensate (EBC), and exhaled breath aerosol (EBA) are different types of breath matrices used to assess human health and disease state. Over the past 20 years, breath research has made many advances in assessing health state, overcoming many of its initial challenges related to sampling and analysis. The wide variety of sampling techniques and collection devices that have been developed for these media are discussed herein. The different types of sensors and mass spectrometry instruments currently available for breath analysis are evaluated as well as emerging breath research topics, such as cytokines, security and airport surveillance, cellular respiration, and canine olfaction.
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Affiliation(s)
- M Ariel Geer Wallace
- U.S. Environmental Protection Agency, Office of Research and Development, National Exposure Research Laboratory, 109 T.W. Alexander Drive, Research Triangle Park, NC, 27711, USA.
| | - Joachim D Pleil
- U.S. Environmental Protection Agency, Office of Research and Development, National Exposure Research Laboratory, 109 T.W. Alexander Drive, Research Triangle Park, NC, 27711, USA.
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Broza YY, Vishinkin R, Barash O, Nakhleh MK, Haick H. Synergy between nanomaterials and volatile organic compounds for non-invasive medical evaluation. Chem Soc Rev 2018; 47:4781-4859. [PMID: 29888356 DOI: 10.1039/c8cs00317c] [Citation(s) in RCA: 112] [Impact Index Per Article: 18.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
This article is an overview of the present and ongoing developments in the field of nanomaterial-based sensors for enabling fast, relatively inexpensive and minimally (or non-) invasive diagnostics of health conditions with follow-up by detecting volatile organic compounds (VOCs) excreted from one or combination of human body fluids and tissues (e.g., blood, urine, breath, skin). Part of the review provides a didactic examination of the concepts and approaches related to emerging sensing materials and transduction techniques linked with the VOC-based non-invasive medical evaluations. We also present and discuss diverse characteristics of these innovative sensors, such as their mode of operation, sensitivity, selectivity and response time, as well as the major approaches proposed for enhancing their ability as hybrid sensors to afford multidimensional sensing and information-based sensing. The other parts of the review give an updated compilation of the past and currently available VOC-based sensors for disease diagnostics. This compilation summarizes all VOCs identified in relation to sickness and sampling origin that links these data with advanced nanomaterial-based sensing technologies. Both strength and pitfalls are discussed and criticized, particularly from the perspective of the information and communication era. Further ideas regarding improvement of sensors, sensor arrays, sensing devices and the proposed workflow are also included.
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Affiliation(s)
- Yoav Y Broza
- Department of Chemical Engineering and Russell Berrie Nanotechnology Institute, Technion - Israel Institute of Technology, Haifa 3200003, Israel.
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Emergence of breath testing as a new non-invasive diagnostic modality for neurodegenerative diseases. Brain Res 2018; 1691:75-86. [DOI: 10.1016/j.brainres.2018.04.017] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2017] [Revised: 04/13/2018] [Accepted: 04/17/2018] [Indexed: 12/11/2022]
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Tebani A, Afonso C, Bekri S. Advances in metabolome information retrieval: turning chemistry into biology. Part I: analytical chemistry of the metabolome. J Inherit Metab Dis 2018; 41:379-391. [PMID: 28840392 PMCID: PMC5959978 DOI: 10.1007/s10545-017-0074-y] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/13/2017] [Revised: 06/28/2017] [Accepted: 07/14/2017] [Indexed: 12/20/2022]
Abstract
Metabolites are small molecules produced by enzymatic reactions in a given organism. Metabolomics or metabolic phenotyping is a well-established omics aimed at comprehensively assessing metabolites in biological systems. These comprehensive analyses use analytical platforms, mainly nuclear magnetic resonance spectroscopy and mass spectrometry, along with associated separation methods to gather qualitative and quantitative data. Metabolomics holistically evaluates biological systems in an unbiased, data-driven approach that may ultimately support generation of hypotheses. The approach inherently allows the molecular characterization of a biological sample with regard to both internal (genetics) and environmental (exosome, microbiome) influences. Metabolomics workflows are based on whether the investigator knows a priori what kind of metabolites to assess. Thus, a targeted metabolomics approach is defined as a quantitative analysis (absolute concentrations are determined) or a semiquantitative analysis (relative intensities are determined) of a set of metabolites that are possibly linked to common chemical classes or a selected metabolic pathway. An untargeted metabolomics approach is a semiquantitative analysis of the largest possible number of metabolites contained in a biological sample. This is part I of a review intending to give an overview of the state of the art of major metabolic phenotyping technologies. Furthermore, their inherent analytical advantages and limits regarding experimental design, sample handling, standardization and workflow challenges are discussed.
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Affiliation(s)
- Abdellah Tebani
- Department of Metabolic Biochemistry, Rouen University Hospital, 76000, Rouen, France
- Normandie Université, UNIROUEN, CHU Rouen, IRIB, INSERM U1245, 76000, Rouen, France
- Normandie Université, UNIROUEN, INSA Rouen, CNRS, COBRA, 76000, Rouen, France
| | - Carlos Afonso
- Normandie Université, UNIROUEN, INSA Rouen, CNRS, COBRA, 76000, Rouen, France
| | - Soumeya Bekri
- Department of Metabolic Biochemistry, Rouen University Hospital, 76000, Rouen, France.
- Normandie Université, UNIROUEN, CHU Rouen, IRIB, INSERM U1245, 76000, Rouen, France.
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Abstract
The electronic nose (e-nose) is a promising technology as a useful addition to the currently available modalities to achieve lung cancer diagnosis. The e-nose can assess the volatile organic compounds detected in the breath and derived from the cellular metabolism. Volatile organic compounds can be analyzed to identify the individual chemical elements as well as their pattern of expression to reproduce a sensorial combination similar to a fingerprint (breathprint). The e-nose can be used alone, mimicking the combinatorial selectivity of the human olfactory system, or as part of a multisensorial platform. This review analyzes the progress made by investigators interested in this technology as well as the perspectives for its future utilization.
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Greulich T, Fischer H, Lubbe D, Nell C, Ingo Baumbach J, Koehler U, Boeselt T, Vogelmeier C, Koczulla AR. Obstructive sleep apnea patients can be identified by ion mobility spectrometry-derived smell prints of different biological materials. J Breath Res 2018; 12:026006. [PMID: 29083318 DOI: 10.1088/1752-7163/aa96e2] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
BACKGROUND The analysis of obstructive sleep apnoea syndrome (OSAS) is time- and cost-intensive. A number of studies demonstrated that the non-invasive analysis of exhaled breath (EB) may be suitable to distinguish between OSAS patients and healthy subjects (HS). Methods/Population: We included OSAS patients (n = 15) and HS (n = 15) in this diagnostic proof-of-concept-study. All participants underwent polygraphy to verify or exclude OSAS and performed spirometry to exclude pulmonary ventilatory diseases. The volatile organic compound profile of EB and of the headspaces over EB condensate, pharyngeal washing fluid, and serum was measured using ion mobility spectrometry (IMS) (BioScout®) and an e-nose (Cyranose® 320). For the statistical analysis, we fitted classification tree models using recursive partitioning, followed by a leave-one-out cross-validation. For the cross-validated predictions we calculated descriptive classification statistics, p-values from a [Formula: see text]-test with continuity correction, as well as ROC curves. RESULTS Using IMS, OSAS patients and HS could be distinguished with high accuracy (values ranged from 79% to 97%). The results of the e-nose-derived analyses (with the exception of EB) were less accurate. However, the cross-validated accuracy for EB was very good (0.9), reflecting a positive predictive value of 100% and a negative predictive value of 83%. For each material, we identified the best five substances that may be used for diagnostic purposes. 2-Methylfluran was found in three different biological materials to be discriminative between OSAS and HS. CONCLUSION The results strengthen the hypothesis that substances detectable in headspace measurements of different airway and blood materials may undergo a transition from blood into the alveoli (and EB) or vice versa. This means that substances from different compartments could be used to distinguish patients with airway diseases (in this case OSAS) from healthy controls.
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Affiliation(s)
- Timm Greulich
- Department of Medicine, Pulmonary and Critical Care Medicine, University Medical Centre Giessen and Marburg, Philipps-University, Member of the German Centre for Lung Research (DZL), D-35043 Marburg, Germany
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Gill EL, Koelmel JP, Yost RA, Okun MS, Vedam-Mai V, Garrett TJ. Mass Spectrometric Methodologies for Investigating the Metabolic Signatures of Parkinson’s Disease: Current Progress and Future Perspectives. Anal Chem 2018; 90:2979-2986. [DOI: 10.1021/acs.analchem.7b04084] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Affiliation(s)
- Emily L. Gill
- Department of Chemistry, University of Florida, Gainesville, Florida 32611, United States
| | - Jeremy P. Koelmel
- Department of Chemistry, University of Florida, Gainesville, Florida 32611, United States
| | - Richard A. Yost
- Department of Chemistry, University of Florida, Gainesville, Florida 32611, United States
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Beale DJ, Jones OAH, Karpe AV, Dayalan S, Oh DY, Kouremenos KA, Ahmed W, Palombo EA. A Review of Analytical Techniques and Their Application in Disease Diagnosis in Breathomics and Salivaomics Research. Int J Mol Sci 2016; 18:E24. [PMID: 28025547 PMCID: PMC5297659 DOI: 10.3390/ijms18010024] [Citation(s) in RCA: 48] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2016] [Revised: 12/12/2016] [Accepted: 12/16/2016] [Indexed: 12/14/2022] Open
Abstract
The application of metabolomics to biological samples has been a key focus in systems biology research, which is aimed at the development of rapid diagnostic methods and the creation of personalized medicine. More recently, there has been a strong focus towards this approach applied to non-invasively acquired samples, such as saliva and exhaled breath. The analysis of these biological samples, in conjunction with other sample types and traditional diagnostic tests, has resulted in faster and more reliable characterization of a range of health disorders and diseases. As the sampling process involved in collecting exhaled breath and saliva is non-intrusive as well as comparatively low-cost and uses a series of widely accepted methods, it provides researchers with easy access to the metabolites secreted by the human body. Owing to its accuracy and rapid nature, metabolomic analysis of saliva and breath (known as salivaomics and breathomics, respectively) is a rapidly growing field and has shown potential to be effective in detecting and diagnosing the early stages of numerous diseases and infections in preclinical studies. This review discusses the various collection and analyses methods currently applied in two of the least used non-invasive sample types in metabolomics, specifically their application in salivaomics and breathomics research. Some of the salient research completed in this field to date is also assessed and discussed in order to provide a basis to advocate their use and possible future scientific directions.
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Affiliation(s)
- David J Beale
- Commonwealth Scientific & Industrial Research Organization (CSIRO), Land & Water, P.O. Box 2583, Brisbane, QLD 4001, Australia.
| | - Oliver A H Jones
- Australian Centre for Research on Separation Science, School of Science, RMIT University, P.O. Box 2547, Melbourne, VIC 3001, Australia.
| | - Avinash V Karpe
- Commonwealth Scientific & Industrial Research Organization (CSIRO), Land & Water, P.O. Box 2583, Brisbane, QLD 4001, Australia.
- Department of Chemistry and Biotechnology, Swinburne University of Technology, P.O. Box 218, Hawthorn, VIC 3122, Australia.
| | - Saravanan Dayalan
- Metabolomics Australia, Bio21 Molecular Science and Biotechnology Institute, University of Melbourne, 30 Flemington Road, Parkville, VIC 3010, Australia.
| | - Ding Yuan Oh
- WHO Collaborating Centre for Reference and Research on Influenza (VIDRL), Peter Doherty Institute for Infection and Immunity, 792 Elizabeth Street, Melbourne, VIC 3000, Australia.
- School of Applied and Biomedical Sciences, Federation University, Churchill, VIC 3350, Australia.
| | - Konstantinos A Kouremenos
- Metabolomics Australia, Bio21 Molecular Science and Biotechnology Institute, University of Melbourne, 30 Flemington Road, Parkville, VIC 3010, Australia.
| | - Warish Ahmed
- Commonwealth Scientific & Industrial Research Organization (CSIRO), Land & Water, P.O. Box 2583, Brisbane, QLD 4001, Australia.
| | - Enzo A Palombo
- Department of Chemistry and Biotechnology, Swinburne University of Technology, P.O. Box 218, Hawthorn, VIC 3122, Australia.
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Zamuruyev KO, Aksenov AA, Baird M, Pasamontes A, Parry C, Foutouhi S, Venn-Watson S, Weimer BC, Delplanque JP, Davis CE. Enhanced non-invasive respiratory sampling from bottlenose dolphins for breath metabolomics measurements. J Breath Res 2016; 10:046005. [PMID: 27689905 DOI: 10.1088/1752-7155/10/4/046005] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/02/2023]
Abstract
Chemical analysis of exhaled breath metabolites is an emerging alternative to traditional clinical testing for many physiological conditions. The main advantage of breath analysis is its inherent non-invasive nature and ease of sample collection. Therefore, there exists a great interest in further development of this method for both humans and animals. The physiology of cetaceans is exceptionally well suited for breath analysis due to their explosive breathing behavior and respiratory tract morphology. At the present time, breath analysis in cetaceans has very limited practical applications, in large part due to lack of widely adopted sampling device(s) and methodologies that are well-standardized. Here, we present an optimized design and the operating principles of a portable apparatus for reproducible collection of exhaled breath condensate from small cetaceans, such as bottlenose dolphins (Tursiops truncatus). The device design is optimized to meet two criteria: standardized collection and preservation of information-rich metabolomic content of the biological sample, and animal comfort and ease of breath sample collection. The intent is to furnish a fully-benchmarked technology that can be widely adopted by researchers and conservationists to spur further developments of breath analysis applications for marine mammal health assessments.
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Affiliation(s)
- Konstantin O Zamuruyev
- Department of Mechanical and Aerospace Engineering, One Shields Avenue, University of California, Davis, Davis, CA 95616, USA
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Tebani A, Abily-Donval L, Afonso C, Marret S, Bekri S. Clinical Metabolomics: The New Metabolic Window for Inborn Errors of Metabolism Investigations in the Post-Genomic Era. Int J Mol Sci 2016; 17:ijms17071167. [PMID: 27447622 PMCID: PMC4964538 DOI: 10.3390/ijms17071167] [Citation(s) in RCA: 77] [Impact Index Per Article: 9.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2016] [Revised: 07/12/2016] [Accepted: 07/15/2016] [Indexed: 12/29/2022] Open
Abstract
Inborn errors of metabolism (IEM) represent a group of about 500 rare genetic diseases with an overall estimated incidence of 1/2500. The diversity of metabolic pathways involved explains the difficulties in establishing their diagnosis. However, early diagnosis is usually mandatory for successful treatment. Given the considerable clinical overlap between some inborn errors, biochemical and molecular tests are crucial in making a diagnosis. Conventional biological diagnosis procedures are based on a time-consuming series of sequential and segmented biochemical tests. The rise of “omic” technologies offers holistic views of the basic molecules that build a biological system at different levels. Metabolomics is the most recent “omic” technology based on biochemical characterization of metabolites and their changes related to genetic and environmental factors. This review addresses the principles underlying metabolomics technologies that allow them to comprehensively assess an individual biochemical profile and their reported applications for IEM investigations in the precision medicine era.
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Affiliation(s)
- Abdellah Tebani
- Department of Metabolic Biochemistry, Rouen University Hospital, Rouen 76031, France.
- Normandie Univ, UNIROUEN, INSERM, CHU Rouen, IRIB, Laboratoire NeoVasc ERI28, Rouen 76000, France.
- Normandie Univ, UNIROUEN, INSA Rouen, CNRS, COBRA, Rouen 76000, France.
| | - Lenaig Abily-Donval
- Normandie Univ, UNIROUEN, INSERM, CHU Rouen, IRIB, Laboratoire NeoVasc ERI28, Rouen 76000, France.
- Department of Neonatal Pediatrics and Intensive Care, Rouen University Hospital, Rouen 76031, France.
| | - Carlos Afonso
- Normandie Univ, UNIROUEN, INSA Rouen, CNRS, COBRA, Rouen 76000, France.
| | - Stéphane Marret
- Normandie Univ, UNIROUEN, INSERM, CHU Rouen, IRIB, Laboratoire NeoVasc ERI28, Rouen 76000, France.
- Department of Neonatal Pediatrics and Intensive Care, Rouen University Hospital, Rouen 76031, France.
| | - Soumeya Bekri
- Department of Metabolic Biochemistry, Rouen University Hospital, Rouen 76031, France.
- Normandie Univ, UNIROUEN, INSERM, CHU Rouen, IRIB, Laboratoire NeoVasc ERI28, Rouen 76000, France.
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Chouinard CD, Wei MS, Beekman CR, Kemperman RHJ, Yost RA. Ion Mobility in Clinical Analysis: Current Progress and Future Perspectives. Clin Chem 2016; 62:124-33. [DOI: 10.1373/clinchem.2015.238840] [Citation(s) in RCA: 75] [Impact Index Per Article: 9.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2015] [Accepted: 10/29/2015] [Indexed: 11/06/2022]
Abstract
Abstract
BACKGROUND
Ion mobility spectrometry (IMS) is a rapid separation tool that can be coupled with several sampling/ionization methods, other separation techniques (e.g., chromatography), and various detectors (e.g., mass spectrometry). This technique has become increasingly used in the last 2 decades for applications ranging from illicit drug and chemical warfare agent detection to structural characterization of biological macromolecules such as proteins. Because of its rapid speed of analysis, IMS has recently been investigated for its potential use in clinical laboratories.
CONTENT
This review article first provides a brief introduction to ion mobility operating principles and instrumentation. Several current applications will then be detailed, including investigation of rapid ambient sampling from exhaled breath and other volatile compounds and mass spectrometric imaging for localization of target compounds. Additionally, current ion mobility research in relevant fields (i.e., metabolomics) will be discussed as it pertains to potential future application in clinical settings.
SUMMARY
This review article provides the authors' perspective on the future of ion mobility implementation in the clinical setting, with a focus on ambient sampling methods that allow IMS to be used as a “bedside” standalone technique for rapid disease screening and methods for improving the analysis of complex biological samples such as blood plasma and urine.
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Affiliation(s)
| | - Michael S Wei
- Department of Chemistry, University of Florida, Gainesville, FL
| | | | | | - Richard A Yost
- Department of Chemistry, University of Florida, Gainesville, FL
- Southeast Center for Integrated Metabolomics (SECIM), University of Florida, Gainesville, FL
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