Machine Learning-Empowered FTIR Spectroscopy Serum Analysis Stratifies Healthy, Allergic, and SIT-Treated Mice and Humans
The unabated global increase of allergic patients leads to an unmet need for rapid and inexpensive tools for the diagnosis of allergies and for monitoring the outcome of allergen-specific immunotherapy (SIT). In this proof-of-concept study, we investigated the potential of Fourier-Transform Infrared...
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MDPI AG
2020-07-01
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| Series: | Biomolecules |
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| Online Access: | https://www.mdpi.com/2218-273X/10/7/1058 |
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| author | Elke Korb Murat Bağcıoğlu Erika Garner-Spitzer Ursula Wiedermann Monika Ehling-Schulz Irma Schabussova |
| author_facet | Elke Korb Murat Bağcıoğlu Erika Garner-Spitzer Ursula Wiedermann Monika Ehling-Schulz Irma Schabussova |
| author_sort | Elke Korb |
| collection | DOAJ |
| description | The unabated global increase of allergic patients leads to an unmet need for rapid and inexpensive tools for the diagnosis of allergies and for monitoring the outcome of allergen-specific immunotherapy (SIT). In this proof-of-concept study, we investigated the potential of Fourier-Transform Infrared (FTIR) spectroscopy, a high-resolution and cost-efficient biophotonic method with high throughput capacities, to detect characteristic alterations in serum samples of healthy, allergic, and SIT-treated mice and humans. To this end, we used experimental models of ovalbumin (OVA)-induced allergic airway inflammation and allergen-specific tolerance induction in BALB/c mice. Serum collected before and at the end of the experiment was subjected to FTIR spectroscopy. As shown by our study, FTIR spectroscopy, combined with deep learning, can discriminate serum from healthy, allergic, and tolerized mice, which correlated with immunological data. Furthermore, to test the suitability of this biophotonic method for clinical diagnostics, serum samples from human patients were analyzed by FTIR spectroscopy. In line with the results from the mouse models, machine learning-assisted FTIR spectroscopy allowed to discriminate sera obtained from healthy, allergic, and SIT-treated humans, thereby demonstrating its potential for rapid diagnosis of allergy and clinical therapeutic monitoring of allergic patients. |
| first_indexed | 2024-03-10T18:26:28Z |
| format | Article |
| id | doaj.art-2dc3c1937ac84d29aa79b0f66802d5ae |
| institution | Directory Open Access Journal |
| issn | 2218-273X |
| language | English |
| last_indexed | 2024-03-10T18:26:28Z |
| publishDate | 2020-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Biomolecules |
| spelling | doaj.art-2dc3c1937ac84d29aa79b0f66802d5ae2023-11-20T06:55:48ZengMDPI AGBiomolecules2218-273X2020-07-01107105810.3390/biom10071058Machine Learning-Empowered FTIR Spectroscopy Serum Analysis Stratifies Healthy, Allergic, and SIT-Treated Mice and HumansElke Korb0Murat Bağcıoğlu1Erika Garner-Spitzer2Ursula Wiedermann3Monika Ehling-Schulz4Irma Schabussova5Institute of Specific Prophylaxis and Tropical Medicine, Medical University of Vienna, 1090 Vienna, AustriaInstitute of Microbiology, Department of Pathobiology, University of Veterinary Medicine, 1210 Vienna, AustriaInstitute of Specific Prophylaxis and Tropical Medicine, Medical University of Vienna, 1090 Vienna, AustriaInstitute of Specific Prophylaxis and Tropical Medicine, Medical University of Vienna, 1090 Vienna, AustriaInstitute of Microbiology, Department of Pathobiology, University of Veterinary Medicine, 1210 Vienna, AustriaInstitute of Specific Prophylaxis and Tropical Medicine, Medical University of Vienna, 1090 Vienna, AustriaThe unabated global increase of allergic patients leads to an unmet need for rapid and inexpensive tools for the diagnosis of allergies and for monitoring the outcome of allergen-specific immunotherapy (SIT). In this proof-of-concept study, we investigated the potential of Fourier-Transform Infrared (FTIR) spectroscopy, a high-resolution and cost-efficient biophotonic method with high throughput capacities, to detect characteristic alterations in serum samples of healthy, allergic, and SIT-treated mice and humans. To this end, we used experimental models of ovalbumin (OVA)-induced allergic airway inflammation and allergen-specific tolerance induction in BALB/c mice. Serum collected before and at the end of the experiment was subjected to FTIR spectroscopy. As shown by our study, FTIR spectroscopy, combined with deep learning, can discriminate serum from healthy, allergic, and tolerized mice, which correlated with immunological data. Furthermore, to test the suitability of this biophotonic method for clinical diagnostics, serum samples from human patients were analyzed by FTIR spectroscopy. In line with the results from the mouse models, machine learning-assisted FTIR spectroscopy allowed to discriminate sera obtained from healthy, allergic, and SIT-treated humans, thereby demonstrating its potential for rapid diagnosis of allergy and clinical therapeutic monitoring of allergic patients.https://www.mdpi.com/2218-273X/10/7/1058FTIR spectroscopyallergyspecific immunotherapyallergic airway inflammationserumclinical diagnostics |
| spellingShingle | Elke Korb Murat Bağcıoğlu Erika Garner-Spitzer Ursula Wiedermann Monika Ehling-Schulz Irma Schabussova Machine Learning-Empowered FTIR Spectroscopy Serum Analysis Stratifies Healthy, Allergic, and SIT-Treated Mice and Humans Biomolecules FTIR spectroscopy allergy specific immunotherapy allergic airway inflammation serum clinical diagnostics |
| title | Machine Learning-Empowered FTIR Spectroscopy Serum Analysis Stratifies Healthy, Allergic, and SIT-Treated Mice and Humans |
| title_full | Machine Learning-Empowered FTIR Spectroscopy Serum Analysis Stratifies Healthy, Allergic, and SIT-Treated Mice and Humans |
| title_fullStr | Machine Learning-Empowered FTIR Spectroscopy Serum Analysis Stratifies Healthy, Allergic, and SIT-Treated Mice and Humans |
| title_full_unstemmed | Machine Learning-Empowered FTIR Spectroscopy Serum Analysis Stratifies Healthy, Allergic, and SIT-Treated Mice and Humans |
| title_short | Machine Learning-Empowered FTIR Spectroscopy Serum Analysis Stratifies Healthy, Allergic, and SIT-Treated Mice and Humans |
| title_sort | machine learning empowered ftir spectroscopy serum analysis stratifies healthy allergic and sit treated mice and humans |
| topic | FTIR spectroscopy allergy specific immunotherapy allergic airway inflammation serum clinical diagnostics |
| url | https://www.mdpi.com/2218-273X/10/7/1058 |
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