Extraction of Reduced Infrared Biomarker Signatures for the Stratification of Patients Affected by Parkinson’s Disease: An Untargeted Metabolomic Approach
An untargeted Fourier transform infrared (FTIR) metabolomic approach was employed to study metabolic changes and disarrangements, recorded as infrared signatures, in Parkinson’s disease (PD). Herein, the principal aim was to propose an efficient sequential classification strategy based on SELECT-LDA...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-06-01
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| Series: | Chemosensors |
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| Online Access: | https://www.mdpi.com/2227-9040/10/6/229 |
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| author | Kateryna Tkachenko María Espinosa Isabel Esteban-Díez José M. González-Sáiz Consuelo Pizarro |
| author_facet | Kateryna Tkachenko María Espinosa Isabel Esteban-Díez José M. González-Sáiz Consuelo Pizarro |
| author_sort | Kateryna Tkachenko |
| collection | DOAJ |
| description | An untargeted Fourier transform infrared (FTIR) metabolomic approach was employed to study metabolic changes and disarrangements, recorded as infrared signatures, in Parkinson’s disease (PD). Herein, the principal aim was to propose an efficient sequential classification strategy based on SELECT-LDA, which enabled optimal stratification of three main categories: PD patients from subjects with Alzheimer’s disease (AD) and healthy controls (HC). Moreover, sub-categories, such as PD at the early stage (PDI) from PD in the advanced stage (PDD), and PDD vs. AD, were stratified. Every classification step with selected wavenumbers achieved 90.11% to 100% correct assignment rates in classification and internal validation. Therefore, selected metabolic signatures from new patients could be used as input features for screening and diagnostic purposes. |
| first_indexed | 2024-03-10T00:08:10Z |
| format | Article |
| id | doaj.art-71c5a2173023470e833767da79ae90d1 |
| institution | Directory Open Access Journal |
| issn | 2227-9040 |
| language | English |
| last_indexed | 2024-03-10T00:08:10Z |
| publishDate | 2022-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Chemosensors |
| spelling | doaj.art-71c5a2173023470e833767da79ae90d12023-11-23T16:04:20ZengMDPI AGChemosensors2227-90402022-06-0110622910.3390/chemosensors10060229Extraction of Reduced Infrared Biomarker Signatures for the Stratification of Patients Affected by Parkinson’s Disease: An Untargeted Metabolomic ApproachKateryna Tkachenko0María Espinosa1Isabel Esteban-Díez2José M. González-Sáiz3Consuelo Pizarro4Department of Chemistry, University of La Rioja, 26006 Logroño, SpainDepartment of Chemistry, University of La Rioja, 26006 Logroño, SpainDepartment of Chemistry, University of La Rioja, 26006 Logroño, SpainDepartment of Chemistry, University of La Rioja, 26006 Logroño, SpainDepartment of Chemistry, University of La Rioja, 26006 Logroño, SpainAn untargeted Fourier transform infrared (FTIR) metabolomic approach was employed to study metabolic changes and disarrangements, recorded as infrared signatures, in Parkinson’s disease (PD). Herein, the principal aim was to propose an efficient sequential classification strategy based on SELECT-LDA, which enabled optimal stratification of three main categories: PD patients from subjects with Alzheimer’s disease (AD) and healthy controls (HC). Moreover, sub-categories, such as PD at the early stage (PDI) from PD in the advanced stage (PDD), and PDD vs. AD, were stratified. Every classification step with selected wavenumbers achieved 90.11% to 100% correct assignment rates in classification and internal validation. Therefore, selected metabolic signatures from new patients could be used as input features for screening and diagnostic purposes.https://www.mdpi.com/2227-9040/10/6/229untargeted metabolomicsParkinson’s diseasepatient stratificationhealth and wellbeing monitoringmetabolic signaturesFTIR |
| spellingShingle | Kateryna Tkachenko María Espinosa Isabel Esteban-Díez José M. González-Sáiz Consuelo Pizarro Extraction of Reduced Infrared Biomarker Signatures for the Stratification of Patients Affected by Parkinson’s Disease: An Untargeted Metabolomic Approach Chemosensors untargeted metabolomics Parkinson’s disease patient stratification health and wellbeing monitoring metabolic signatures FTIR |
| title | Extraction of Reduced Infrared Biomarker Signatures for the Stratification of Patients Affected by Parkinson’s Disease: An Untargeted Metabolomic Approach |
| title_full | Extraction of Reduced Infrared Biomarker Signatures for the Stratification of Patients Affected by Parkinson’s Disease: An Untargeted Metabolomic Approach |
| title_fullStr | Extraction of Reduced Infrared Biomarker Signatures for the Stratification of Patients Affected by Parkinson’s Disease: An Untargeted Metabolomic Approach |
| title_full_unstemmed | Extraction of Reduced Infrared Biomarker Signatures for the Stratification of Patients Affected by Parkinson’s Disease: An Untargeted Metabolomic Approach |
| title_short | Extraction of Reduced Infrared Biomarker Signatures for the Stratification of Patients Affected by Parkinson’s Disease: An Untargeted Metabolomic Approach |
| title_sort | extraction of reduced infrared biomarker signatures for the stratification of patients affected by parkinson s disease an untargeted metabolomic approach |
| topic | untargeted metabolomics Parkinson’s disease patient stratification health and wellbeing monitoring metabolic signatures FTIR |
| url | https://www.mdpi.com/2227-9040/10/6/229 |
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