Breathomics to diagnose systemic sclerosis using thermal desorption and comprehensive two-dimensional gas chromatography high-resolution time-of-flight mass spectrometry
Systemic sclerosis is a rare autoimmune disease associated with rapidly evolving interstitial lung disease, responsible for the disease severity and mortality. Specific biomarkers enabling the early diagnosis and prognosis associated with the disease progression are highly needed. Volatile organic c...
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| Published in | Analytical and bioanalytical chemistry Vol. 413; no. 14; pp. 3813 - 3822 |
|---|---|
| Main Authors | , , , , , , , , , , , |
| Format | Journal Article Web Resource |
| Language | English |
| Published |
Berlin/Heidelberg
Springer Berlin Heidelberg
01.06.2021
Springer Springer Nature B.V |
| Subjects | |
| Online Access | Get full text |
| ISSN | 1618-2642 1618-2650 1618-2650 |
| DOI | 10.1007/s00216-021-03333-4 |
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| Abstract | Systemic sclerosis is a rare autoimmune disease associated with rapidly evolving interstitial lung disease, responsible for the disease severity and mortality. Specific biomarkers enabling the early diagnosis and prognosis associated with the disease progression are highly needed. Volatile organic compounds in exhaled breath are widely available and non-invasive and have the potential to reflect metabolic processes occurring within the body. Comprehensive two-dimensional gas chromatography coupled to high-resolution mass spectrometry was used to investigate the potential of exhaled breath to diagnose systemic sclerosis. The exhaled breath of 32 patients and 30 healthy subjects was analyzed. The high resolving power of this approach enabled the detection of 356 compounds in the breath of systemic sclerosis patients, which was characterized by an increase of mainly terpenoids and hydrocarbons. In addition, the use of 4 complementary statistical approaches (two-tailed equal variance
t
-test, fold change, partial least squares discriminant analysis, and random forest) resulted in the identification of 16 compounds that can be used to discriminate systemic sclerosis patients from healthy subjects. Receiver operating curves were generated that provided an accuracy of 90%, a sensitivity of 92%, and a specificity of 89%. The chemical identification of eight compounds predictive of systemic sclerosis was validated using commercially available standards. The analytical variations together with the volatile composition of room air were carefully monitored during the timeframe of the study to ensure the robustness of the technique. This study represents the first reported evaluation of exhaled breath analysis for systemic sclerosis diagnosis and provides surrogate markers for such disease.
Graphical abstract |
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| AbstractList | Systemic sclerosis is a rare autoimmune disease associated with rapidly evolving interstitial lung disease, responsible for the disease severity and mortality. Specific biomarkers enabling the early diagnosis and prognosis associated with the disease progression are highly needed. Volatile organic compounds in exhaled breath are widely available and non-invasive and have the potential to reflect metabolic processes occurring within the body. Comprehensive two-dimensional gas chromatography coupled to high-resolution mass spectrometry was used to investigate the potential of exhaled breath to diagnose systemic sclerosis. The exhaled breath of 32 patients and 30 healthy subjects was analyzed. The high resolving power of this approach enabled the detection of 356 compounds in the breath of systemic sclerosis patients, which was characterized by an increase of mainly terpenoids and hydrocarbons. In addition, the use of 4 complementary statistical approaches (two-tailed equal variance
t
-test, fold change, partial least squares discriminant analysis, and random forest) resulted in the identification of 16 compounds that can be used to discriminate systemic sclerosis patients from healthy subjects. Receiver operating curves were generated that provided an accuracy of 90%, a sensitivity of 92%, and a specificity of 89%. The chemical identification of eight compounds predictive of systemic sclerosis was validated using commercially available standards. The analytical variations together with the volatile composition of room air were carefully monitored during the timeframe of the study to ensure the robustness of the technique. This study represents the first reported evaluation of exhaled breath analysis for systemic sclerosis diagnosis and provides surrogate markers for such disease.
Graphical abstract Systemic sclerosis is a rare autoimmune disease associated with rapidly evolving interstitial lung disease, responsible for the disease severity and mortality. Specific biomarkers enabling the early diagnosis and prognosis associated with the disease progression are highly needed. Volatile organic compounds in exhaled breath are widely available and non-invasive and have the potential to reflect metabolic processes occurring within the body. Comprehensive two-dimensional gas chromatography coupled to high-resolution mass spectrometry was used to investigate the potential of exhaled breath to diagnose systemic sclerosis. The exhaled breath of 32 patients and 30 healthy subjects was analyzed. The high resolving power of this approach enabled the detection of 356 compounds in the breath of systemic sclerosis patients, which was characterized by an increase of mainly terpenoids and hydrocarbons. In addition, the use of 4 complementary statistical approaches (two-tailed equal variance t-test, fold change, partial least squares discriminant analysis, and random forest) resulted in the identification of 16 compounds that can be used to discriminate systemic sclerosis patients from healthy subjects. Receiver operating curves were generated that provided an accuracy of 90%, a sensitivity of 92%, and a specificity of 89%. The chemical identification of eight compounds predictive of systemic sclerosis was validated using commercially available standards. The analytical variations together with the volatile composition of room air were carefully monitored during the timeframe of the study to ensure the robustness of the technique. This study represents the first reported evaluation of exhaled breath analysis for systemic sclerosis diagnosis and provides surrogate markers for such disease. Systemic sclerosis is a rare autoimmune disease associated with rapidly evolving interstitial lung disease, responsible for the disease severity and mortality. Specific biomarkers enabling the early diagnosis and prognosis associated with the disease progression are highly needed. Volatile organic compounds in exhaled breath are widely available and non-invasive and have the potential to reflect metabolic processes occurring within the body. Comprehensive two-dimensional gas chromatography coupled to high-resolution mass spectrometry was used to investigate the potential of exhaled breath to diagnose systemic sclerosis. The exhaled breath of 32 patients and 30 healthy subjects was analyzed. The high resolving power of this approach enabled the detection of 356 compounds in the breath of systemic sclerosis patients, which was characterized by an increase of mainly terpenoids and hydrocarbons. In addition, the use of 4 complementary statistical approaches (two-tailed equal variance ttest, fold change, partial least squares discriminant analysis, and random forest) resulted in the identification of 16 compounds that can be used to discriminate systemic sclerosis patients from healthy subjects. Receiver operating curves were generated that provided an accuracy of 90%, a sensitivity of 92%, and a specificity of 89%. The chemical identification of eight compounds predictive of systemic sclerosis was validated using commercially available standards. The analytical variations together with the volatile composition of room air were carefully monitored during the timeframe of the study to ensure the robustness of the technique. This study represents the first reported evaluation of exhaled breath analysis for systemic sclerosis diagnosis and provides surrogate markers for such disease. Systemic sclerosis is a rare autoimmune disease associated with rapidly evolving interstitial lung disease, responsible for the disease severity and mortality. Specific biomarkers enabling the early diagnosis and prognosis associated with the disease progression are highly needed. Volatile organic compounds in exhaled breath are widely available and non-invasive and have the potential to reflect metabolic processes occurring within the body. Comprehensive two-dimensional gas chromatography coupled to high-resolution mass spectrometry was used to investigate the potential of exhaled breath to diagnose systemic sclerosis. The exhaled breath of 32 patients and 30 healthy subjects was analyzed. The high resolving power of this approach enabled the detection of 356 compounds in the breath of systemic sclerosis patients, which was characterized by an increase of mainly terpenoids and hydrocarbons. In addition, the use of 4 complementary statistical approaches (two-tailed equal variance t-test, fold change, partial least squares discriminant analysis, and random forest) resulted in the identification of 16 compounds that can be used to discriminate systemic sclerosis patients from healthy subjects. Receiver operating curves were generated that provided an accuracy of 90%, a sensitivity of 92%, and a specificity of 89%. The chemical identification of eight compounds predictive of systemic sclerosis was validated using commercially available standards. The analytical variations together with the volatile composition of room air were carefully monitored during the timeframe of the study to ensure the robustness of the technique. This study represents the first reported evaluation of exhaled breath analysis for systemic sclerosis diagnosis and provides surrogate markers for such disease. Graphical abstract Systemic sclerosis is a rare autoimmune disease associated with rapidly evolving interstitial lung disease, responsible for the disease severity and mortality. Specific biomarkers enabling the early diagnosis and prognosis associated with the disease progression are highly needed. Volatile organic compounds in exhaled breath are widely available and non-invasive and have the potential to reflect metabolic processes occurring within the body. Comprehensive two-dimensional gas chromatography coupled to high-resolution mass spectrometry was used to investigate the potential of exhaled breath to diagnose systemic sclerosis. The exhaled breath of 32 patients and 30 healthy subjects was analyzed. The high resolving power of this approach enabled the detection of 356 compounds in the breath of systemic sclerosis patients, which was characterized by an increase of mainly terpenoids and hydrocarbons. In addition, the use of 4 complementary statistical approaches (two-tailed equal variance t-test, fold change, partial least squares discriminant analysis, and random forest) resulted in the identification of 16 compounds that can be used to discriminate systemic sclerosis patients from healthy subjects. Receiver operating curves were generated that provided an accuracy of 90%, a sensitivity of 92%, and a specificity of 89%. The chemical identification of eight compounds predictive of systemic sclerosis was validated using commercially available standards. The analytical variations together with the volatile composition of room air were carefully monitored during the timeframe of the study to ensure the robustness of the technique. This study represents the first reported evaluation of exhaled breath analysis for systemic sclerosis diagnosis and provides surrogate markers for such disease.Systemic sclerosis is a rare autoimmune disease associated with rapidly evolving interstitial lung disease, responsible for the disease severity and mortality. Specific biomarkers enabling the early diagnosis and prognosis associated with the disease progression are highly needed. Volatile organic compounds in exhaled breath are widely available and non-invasive and have the potential to reflect metabolic processes occurring within the body. Comprehensive two-dimensional gas chromatography coupled to high-resolution mass spectrometry was used to investigate the potential of exhaled breath to diagnose systemic sclerosis. The exhaled breath of 32 patients and 30 healthy subjects was analyzed. The high resolving power of this approach enabled the detection of 356 compounds in the breath of systemic sclerosis patients, which was characterized by an increase of mainly terpenoids and hydrocarbons. In addition, the use of 4 complementary statistical approaches (two-tailed equal variance t-test, fold change, partial least squares discriminant analysis, and random forest) resulted in the identification of 16 compounds that can be used to discriminate systemic sclerosis patients from healthy subjects. Receiver operating curves were generated that provided an accuracy of 90%, a sensitivity of 92%, and a specificity of 89%. The chemical identification of eight compounds predictive of systemic sclerosis was validated using commercially available standards. The analytical variations together with the volatile composition of room air were carefully monitored during the timeframe of the study to ensure the robustness of the technique. This study represents the first reported evaluation of exhaled breath analysis for systemic sclerosis diagnosis and provides surrogate markers for such disease. |
| Audience | Academic |
| Author | Henket, Monique Guiot, Julien Guissard, Françoise Focant, Jean-François Stefanuto, Pierre-Hugues Zanella, Delphine Potjewijd, Judith Giltay, Laurie André, Béatrice Malaise, Michel Schleich, Florence Louis, Renaud |
| Author_xml | – sequence: 1 givenname: Delphine orcidid: 0000-0002-0131-2837 surname: Zanella fullname: Zanella, Delphine email: d.zanella@uliege.be organization: Molecular System, Organic & Biological Analytical Chemistry Group, University of Liege – sequence: 2 givenname: Julien surname: Guiot fullname: Guiot, Julien organization: Respiratory Medicine, GIGA I3, CHU Liege – sequence: 3 givenname: Pierre-Hugues surname: Stefanuto fullname: Stefanuto, Pierre-Hugues organization: Molecular System, Organic & Biological Analytical Chemistry Group, University of Liege – sequence: 4 givenname: Laurie surname: Giltay fullname: Giltay, Laurie organization: Respiratory Medicine, GIGA I3, CHU Liege – sequence: 5 givenname: Monique surname: Henket fullname: Henket, Monique organization: Respiratory Medicine, GIGA I3, CHU Liege – sequence: 6 givenname: Françoise surname: Guissard fullname: Guissard, Françoise organization: Respiratory Medicine, GIGA I3, CHU Liege – sequence: 7 givenname: Béatrice surname: André fullname: André, Béatrice organization: Rheumatology Department, CHU Liege – sequence: 8 givenname: Michel surname: Malaise fullname: Malaise, Michel organization: Rheumatology Department, CHU Liege – sequence: 9 givenname: Judith surname: Potjewijd fullname: Potjewijd, Judith organization: Department of Internal Medicine, Division of Clinical and Experimental Immunology, Maastricht University Medical Center – sequence: 10 givenname: Florence surname: Schleich fullname: Schleich, Florence organization: Respiratory Medicine, GIGA I3, CHU Liege – sequence: 11 givenname: Renaud surname: Louis fullname: Louis, Renaud organization: Respiratory Medicine, GIGA I3, CHU Liege – sequence: 12 givenname: Jean-François surname: Focant fullname: Focant, Jean-François organization: Molecular System, Organic & Biological Analytical Chemistry Group, University of Liege |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/33903944$$D View this record in MEDLINE/PubMed |
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| CitedBy_id | crossref_primary_10_1039_D2AN00584K crossref_primary_10_1021_acs_analchem_2c04235 crossref_primary_10_1183_23120541_00175_2024 crossref_primary_10_3390_ijms24119614 crossref_primary_10_1016_j_microc_2025_113073 |
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| Snippet | Systemic sclerosis is a rare autoimmune disease associated with rapidly evolving interstitial lung disease, responsible for the disease severity and mortality.... |
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| Title | Breathomics to diagnose systemic sclerosis using thermal desorption and comprehensive two-dimensional gas chromatography high-resolution time-of-flight mass spectrometry |
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