Exploring extra dimensions to capture saliva metabolite fingerprints from metabolically healthy and unhealthy obese patients by comprehensive two-dimensional gas chromatography featuring Tandem Ionization mass spectrometry Article Swipe
Marta Cialiè Rosso
,
Federico Stilo
,
Simone Squara
,
Erica Liberto
,
Stefania Mai
,
Chiara Mele
,
Paolo Marzullo
,
Gianluca Aimaretti
,
Stephen E. Reichenbach
,
Massimo Collino
,
Carlo Bicchi
,
Chiara Cordero
·
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.1007/s00216-020-03008-6
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.1007/s00216-020-03008-6
This study examines the information potential of comprehensive two-dimensional gas chromatography combined with time-of-flight mass spectrometry (GC×GC-TOF MS) and variable ionization energy (i.e., Tandem Ionization™) to study changes in saliva metabolic signatures from a small group of obese individuals. The study presents a proof of concept for an effective exploitation of the complementary nature of tandem ionization data. Samples are taken from two sub-populations of severely obese (BMI > 40 kg/m 2 ) patients, named metabolically healthy obese (MHO) and metabolically unhealthy obese (MUO). Untargeted fingerprinting, based on pattern recognition by template matching, is applied on single data streams and on fused data, obtained by combining raw signals from the two ionization energies (12 and 70 eV). Results indicate that at lower energy (i.e., 12 eV), the total signal intensity is one order of magnitude lower compared to the reference signal at 70 eV, but the ranges of variations for 2D peak responses is larger, extending the dynamic range. Fused data combine benefits from 70 eV and 12 eV resulting in more comprehensive coverage by sample fingerprints. Multivariate statistics, principal component analysis (PCA), and partial least squares discriminant analysis (PLS-DA) show quite good patient clustering, with total explained variance by the first two principal components (PCs) that increases from 54% at 70 eV to 59% at 12 eV and up to 71% for fused data. With PLS-DA, discriminant components are highlighted and putatively identified by comparing retention data and 70 eV spectral signatures. Within the most informative analytes, lactose is present in higher relative amount in saliva from MHO patients, whereas N-acetyl-D-glucosamine, urea, glucuronic acid γ-lactone, 2-deoxyribose, N-acetylneuraminic acid methyl ester, and 5-aminovaleric acid are more abundant in MUO patients. Visual feature fingerprinting is combined with pattern recognition algorithms to highlight metabolite variations between composite per-class images obtained by combining raw data from individuals belonging to different classes, i.e., MUO vs. MHO. Graphical abstract
Related Topics
Concepts
Chemistry
Principal component analysis
Mass spectrometry
Ionization
Chromatography
Metabolomics
Linear discriminant analysis
Analytical Chemistry (journal)
Multivariate statistics
Discriminant
Gas chromatography–mass spectrometry
Gas chromatography
Statistics
Artificial intelligence
Mathematics
Ion
Computer science
Organic chemistry
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1007/s00216-020-03008-6
- https://link.springer.com/content/pdf/10.1007/s00216-020-03008-6.pdf
- OA Status
- hybrid
- Cited By
- 20
- References
- 55
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W3096094441
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W3096094441Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1007/s00216-020-03008-6Digital Object Identifier
- Title
-
Exploring extra dimensions to capture saliva metabolite fingerprints from metabolically healthy and unhealthy obese patients by comprehensive two-dimensional gas chromatography featuring Tandem Ionization mass spectrometryWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2020Year of publication
- Publication date
-
2020-11-03Full publication date if available
- Authors
-
Marta Cialiè Rosso, Federico Stilo, Simone Squara, Erica Liberto, Stefania Mai, Chiara Mele, Paolo Marzullo, Gianluca Aimaretti, Stephen E. Reichenbach, Massimo Collino, Carlo Bicchi, Chiara CorderoList of authors in order
- Landing page
-
https://doi.org/10.1007/s00216-020-03008-6Publisher landing page
- PDF URL
-
https://link.springer.com/content/pdf/10.1007/s00216-020-03008-6.pdfDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
hybridOpen access status per OpenAlex
- OA URL
-
https://link.springer.com/content/pdf/10.1007/s00216-020-03008-6.pdfDirect OA link when available
- Concepts
-
Chemistry, Principal component analysis, Mass spectrometry, Ionization, Chromatography, Metabolomics, Linear discriminant analysis, Analytical Chemistry (journal), Multivariate statistics, Discriminant, Gas chromatography–mass spectrometry, Gas chromatography, Statistics, Artificial intelligence, Mathematics, Ion, Computer science, Organic chemistryTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
20Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 1, 2024: 4, 2023: 5, 2022: 7, 2021: 2Per-year citation counts (last 5 years)
- References (count)
-
55Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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