Mass Spectrometry-Based Proteomic and Metabolomic Profiling of Serum Samples for Discovery and Validation of Tuberculosis Diagnostic Biomarker Signature
Tuberculosis (TB) is a transmissible disease listed as one of the 10 leading causes of death worldwide (10 million infected in 2019). A swift and precise diagnosis is essential to forestall its transmission, for which the discovery of effective diagnostic biomarkers is crucial. In this study, we aim...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-11-01
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| Series: | International Journal of Molecular Sciences |
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| Online Access: | https://www.mdpi.com/1422-0067/23/22/13733 |
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| author | Ana Filipa Fernandes Luís Gafeira Gonçalves Maria Bento Sandra I. Anjo Bruno Manadas Clara Barroso Miguel Villar Rita Macedo Maria João Simões Ana Varela Coelho |
| author_facet | Ana Filipa Fernandes Luís Gafeira Gonçalves Maria Bento Sandra I. Anjo Bruno Manadas Clara Barroso Miguel Villar Rita Macedo Maria João Simões Ana Varela Coelho |
| author_sort | Ana Filipa Fernandes |
| collection | DOAJ |
| description | Tuberculosis (TB) is a transmissible disease listed as one of the 10 leading causes of death worldwide (10 million infected in 2019). A swift and precise diagnosis is essential to forestall its transmission, for which the discovery of effective diagnostic biomarkers is crucial. In this study, we aimed to discover molecular biomarkers for the early diagnosis of tuberculosis. Two independent cohorts comprising 29 and 34 subjects were assayed by proteomics, and 49 were included for metabolomic analysis. All subjects were arranged into three experimental groups—healthy controls (controls), latent TB infection (LTBI), and TB patients. LC-MS/MS blood serum protein and metabolite levels were submitted to univariate, multivariate, and ROC analysis. From the 149 proteins quantified in the discovery set, 25 were found to be differentially abundant between controls and TB patients. The AUC, specificity, and sensitivity, determined by ROC statistical analysis of the model composed of four of these proteins considering both proteomic sets, were 0.96, 93%, and 91%, respectively. The five metabolites (9-methyluric acid, indole-3-lactic acid, trans-3-indoleacrylic acid, hexanoylglycine, and N-acetyl-L-leucine) that better discriminate the control and TB patient groups (VIP > 1.75) from a total of 92 metabolites quantified in both ionization modes were submitted to ROC analysis. An AUC = 1 was determined, with all samples being correctly assigned to the respective experimental group. An integrated ROC analysis enrolling one protein and four metabolites was also performed for the common control and TB patients in the proteomic and metabolomic groups. This combined signature correctly assigned the 12 controls and 12 patients used only for prediction (AUC = 1, specificity = 100%, and sensitivity = 100%). This multiomics approach revealed a biomarker signature for tuberculosis diagnosis that could be potentially used for developing a point-of-care diagnosis clinical test. |
| first_indexed | 2024-03-09T18:18:57Z |
| format | Article |
| id | doaj.art-bbd2adc5f39347c6955452be4390bcde |
| institution | Directory Open Access Journal |
| issn | 1661-6596 1422-0067 |
| language | English |
| last_indexed | 2024-03-09T18:18:57Z |
| publishDate | 2022-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | International Journal of Molecular Sciences |
| spelling | doaj.art-bbd2adc5f39347c6955452be4390bcde2023-11-24T08:32:31ZengMDPI AGInternational Journal of Molecular Sciences1661-65961422-00672022-11-0123221373310.3390/ijms232213733Mass Spectrometry-Based Proteomic and Metabolomic Profiling of Serum Samples for Discovery and Validation of Tuberculosis Diagnostic Biomarker SignatureAna Filipa Fernandes0Luís Gafeira Gonçalves1Maria Bento2Sandra I. Anjo3Bruno Manadas4Clara Barroso5Miguel Villar6Rita Macedo7Maria João Simões8Ana Varela Coelho9Instituto de Tecnologia Química e Biológica António Xavier, Universidade Nova de Lisboa, 2780-157 Oeiras, PortugalInstituto de Tecnologia Química e Biológica António Xavier, Universidade Nova de Lisboa, 2780-157 Oeiras, PortugalInstituto de Tecnologia Química e Biológica António Xavier, Universidade Nova de Lisboa, 2780-157 Oeiras, PortugalCNC-Center for Neuroscience and Cell Biology, University of Coimbra, 3004-504 Coimbra, PortugalCNC-Center for Neuroscience and Cell Biology, University of Coimbra, 3004-504 Coimbra, PortugalCDP Almada-Seixal, ARSLVT, 2805-021 Almada, PortugalCDP Venda Nova, ARSLVT, 2700-220 Amadora, PortugalInstituto Nacional de Saúde Dr. Ricardo Jorge, 1649-016 Lisboa, PortugalInstituto Nacional de Saúde Dr. Ricardo Jorge, 1649-016 Lisboa, PortugalInstituto de Tecnologia Química e Biológica António Xavier, Universidade Nova de Lisboa, 2780-157 Oeiras, PortugalTuberculosis (TB) is a transmissible disease listed as one of the 10 leading causes of death worldwide (10 million infected in 2019). A swift and precise diagnosis is essential to forestall its transmission, for which the discovery of effective diagnostic biomarkers is crucial. In this study, we aimed to discover molecular biomarkers for the early diagnosis of tuberculosis. Two independent cohorts comprising 29 and 34 subjects were assayed by proteomics, and 49 were included for metabolomic analysis. All subjects were arranged into three experimental groups—healthy controls (controls), latent TB infection (LTBI), and TB patients. LC-MS/MS blood serum protein and metabolite levels were submitted to univariate, multivariate, and ROC analysis. From the 149 proteins quantified in the discovery set, 25 were found to be differentially abundant between controls and TB patients. The AUC, specificity, and sensitivity, determined by ROC statistical analysis of the model composed of four of these proteins considering both proteomic sets, were 0.96, 93%, and 91%, respectively. The five metabolites (9-methyluric acid, indole-3-lactic acid, trans-3-indoleacrylic acid, hexanoylglycine, and N-acetyl-L-leucine) that better discriminate the control and TB patient groups (VIP > 1.75) from a total of 92 metabolites quantified in both ionization modes were submitted to ROC analysis. An AUC = 1 was determined, with all samples being correctly assigned to the respective experimental group. An integrated ROC analysis enrolling one protein and four metabolites was also performed for the common control and TB patients in the proteomic and metabolomic groups. This combined signature correctly assigned the 12 controls and 12 patients used only for prediction (AUC = 1, specificity = 100%, and sensitivity = 100%). This multiomics approach revealed a biomarker signature for tuberculosis diagnosis that could be potentially used for developing a point-of-care diagnosis clinical test.https://www.mdpi.com/1422-0067/23/22/13733tuberculosisdiagnosisbiomarkersmultiomicsmass spectrometryblood serum |
| spellingShingle | Ana Filipa Fernandes Luís Gafeira Gonçalves Maria Bento Sandra I. Anjo Bruno Manadas Clara Barroso Miguel Villar Rita Macedo Maria João Simões Ana Varela Coelho Mass Spectrometry-Based Proteomic and Metabolomic Profiling of Serum Samples for Discovery and Validation of Tuberculosis Diagnostic Biomarker Signature International Journal of Molecular Sciences tuberculosis diagnosis biomarkers multiomics mass spectrometry blood serum |
| title | Mass Spectrometry-Based Proteomic and Metabolomic Profiling of Serum Samples for Discovery and Validation of Tuberculosis Diagnostic Biomarker Signature |
| title_full | Mass Spectrometry-Based Proteomic and Metabolomic Profiling of Serum Samples for Discovery and Validation of Tuberculosis Diagnostic Biomarker Signature |
| title_fullStr | Mass Spectrometry-Based Proteomic and Metabolomic Profiling of Serum Samples for Discovery and Validation of Tuberculosis Diagnostic Biomarker Signature |
| title_full_unstemmed | Mass Spectrometry-Based Proteomic and Metabolomic Profiling of Serum Samples for Discovery and Validation of Tuberculosis Diagnostic Biomarker Signature |
| title_short | Mass Spectrometry-Based Proteomic and Metabolomic Profiling of Serum Samples for Discovery and Validation of Tuberculosis Diagnostic Biomarker Signature |
| title_sort | mass spectrometry based proteomic and metabolomic profiling of serum samples for discovery and validation of tuberculosis diagnostic biomarker signature |
| topic | tuberculosis diagnosis biomarkers multiomics mass spectrometry blood serum |
| url | https://www.mdpi.com/1422-0067/23/22/13733 |
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