A multi-omics integration approach relying on circulating factors does not discern endotypes in childhood type 1 diabetes. Article Swipe
Alessandra Petrelli
,
Valentina Codazzi
,
Nicola Baldoni
,
Giulia Maria Scotti
,
Anna Giovenzana
,
Andrea Rigamonti
,
Giulio Frontino
,
Eugenia Bezzecchi
,
Camillo Bechi Genzano
,
Alessandra Mandelli
,
Debora Carnovale
,
Ilaria Marzinotto
,
Vito Lampasona
,
Paolo Fiorina
,
Andrea Giustina
,
Lorenzo Piemonti
,
Manuela Battaglia
,
Marco J. Morelli
,
Riccardo Bonfanti
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.21203/rs.3.rs-4213232/v1
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.21203/rs.3.rs-4213232/v1
Type 1 Diabetes (T1D) exhibits considerable heterogeneity, impacting prediction, prevention, diagnosis, and treatment. Precision medicine aims to tailor treatments using 'endotypes'—subtypes of disease with distinct pathophysiological mechanisms. However, proposed endotypes often lack mechanistic associations with clinical outcomes, remaining elusive in T1D. This study introduces a new approach leveraging the multi-omics factor analysis (MOFA) strategy to explore endotypes through data integration. Analyzing data from 146 new-onset pediatric T1D patients, including circulating immunome, transcriptome, and serum metabolic hormones, we identify 12 factors explaining variability across the three data sets. Notably, no clustering or direct association of these factors with clinical parameters, genetic predisposition and disease outcome are found, suggesting that a combination of clinical phenotypes is responsible for the differences across patients. These findings challenge the assumption that T1D heterogeneity reflects diverse developmental mechanisms, contributing significantly to the endotype discussion and impacting clinical trial design.
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- Type
- preprint
- Language
- en
- Landing Page
- https://doi.org/10.21203/rs.3.rs-4213232/v1
- https://www.researchsquare.com/article/rs-4213232/latest.pdf
- OA Status
- gold
- References
- 19
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4394930166
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4394930166Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.21203/rs.3.rs-4213232/v1Digital Object Identifier
- Title
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A multi-omics integration approach relying on circulating factors does not discern endotypes in childhood type 1 diabetes.Work title
- Type
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preprintOpenAlex work type
- Language
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enPrimary language
- Publication year
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2024Year of publication
- Publication date
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2024-04-18Full publication date if available
- Authors
-
Alessandra Petrelli, Valentina Codazzi, Nicola Baldoni, Giulia Maria Scotti, Anna Giovenzana, Andrea Rigamonti, Giulio Frontino, Eugenia Bezzecchi, Camillo Bechi Genzano, Alessandra Mandelli, Debora Carnovale, Ilaria Marzinotto, Vito Lampasona, Paolo Fiorina, Andrea Giustina, Lorenzo Piemonti, Manuela Battaglia, Marco J. Morelli, Riccardo BonfantiList of authors in order
- Landing page
-
https://doi.org/10.21203/rs.3.rs-4213232/v1Publisher landing page
- PDF URL
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https://www.researchsquare.com/article/rs-4213232/latest.pdfDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://www.researchsquare.com/article/rs-4213232/latest.pdfDirect OA link when available
- Concepts
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Omics, Computational biology, Type 2 diabetes, Computer science, Medicine, Diabetes mellitus, Bioinformatics, Data science, Biology, EndocrinologyTop concepts (fields/topics) attached by OpenAlex
- Cited by
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0Total citation count in OpenAlex
- References (count)
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19Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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