Combined unsupervised and semi-automated supervised analysis of flow cytometry data reveals cellular fingerprint associated with newly diagnosed pediatric type 1 diabetes
An unbiased and replicable profiling of type 1 diabetes (T1D)-specific circulating immunome at disease onset has yet to be identified due to experimental and patient selection limitations. Multicolor flow cytometry was performed on whole blood from a pediatric cohort of 107 patients with new-onset T...
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Frontiers Media S.A.
2022-10-01
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| Series: | Frontiers in Immunology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fimmu.2022.1026416/full |
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| author | Camillo Bechi Genzano Eugenia Bezzecchi Eugenia Bezzecchi Debora Carnovale Alessandra Mandelli Elisa Morotti Elisa Morotti Valeria Castorani Valeria Favalli Valeria Favalli Angela Stabilini Vittoria Insalaco Francesca Ragogna Valentina Codazzi Giulia Maria Scotti Stefania Del Rosso Benedetta Allegra Mazzi Maurizio De Pellegrin Andrea Giustina Andrea Giustina Lorenzo Piemonti Lorenzo Piemonti Emanuele Bosi Emanuele Bosi Emanuele Bosi Manuela Battaglia Marco J. Morelli Riccardo Bonfanti Riccardo Bonfanti Riccardo Bonfanti Alessandra Petrelli |
| author_facet | Camillo Bechi Genzano Eugenia Bezzecchi Eugenia Bezzecchi Debora Carnovale Alessandra Mandelli Elisa Morotti Elisa Morotti Valeria Castorani Valeria Favalli Valeria Favalli Angela Stabilini Vittoria Insalaco Francesca Ragogna Valentina Codazzi Giulia Maria Scotti Stefania Del Rosso Benedetta Allegra Mazzi Maurizio De Pellegrin Andrea Giustina Andrea Giustina Lorenzo Piemonti Lorenzo Piemonti Emanuele Bosi Emanuele Bosi Emanuele Bosi Manuela Battaglia Marco J. Morelli Riccardo Bonfanti Riccardo Bonfanti Riccardo Bonfanti Alessandra Petrelli |
| author_sort | Camillo Bechi Genzano |
| collection | DOAJ |
| description | An unbiased and replicable profiling of type 1 diabetes (T1D)-specific circulating immunome at disease onset has yet to be identified due to experimental and patient selection limitations. Multicolor flow cytometry was performed on whole blood from a pediatric cohort of 107 patients with new-onset T1D, 85 relatives of T1D patients with 0-1 islet autoantibodies (pre-T1D_LR), 58 patients with celiac disease or autoimmune thyroiditis (CD_THY) and 76 healthy controls (HC). Unsupervised clustering of flow cytometry data, validated by a semi-automated gating strategy, confirmed previous findings showing selective increase of naïve CD4 T cells and plasmacytoid DCs, and revealed a decrease in CD56brightNK cells in T1D. Furthermore, a non-selective decrease of CD3+CD56+ regulatory T cells was observed in T1D. The frequency of naïve CD4 T cells at disease onset was associated with partial remission, while it was found unaltered in the pre-symptomatic stages of the disease. Thanks to a broad cohort of pediatric individuals and the implementation of unbiased approaches for the analysis of flow cytometry data, here we determined the circulating immune fingerprint of newly diagnosed pediatric T1D and provide a reference dataset to be exploited for validation or discovery purposes to unravel the pathogenesis of T1D. |
| first_indexed | 2024-04-12T18:01:48Z |
| format | Article |
| id | doaj.art-d4d43b89ac9d42a1ad9479ca7e312d01 |
| institution | Directory Open Access Journal |
| issn | 1664-3224 |
| language | English |
| last_indexed | 2024-04-12T18:01:48Z |
| publishDate | 2022-10-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Immunology |
| spelling | doaj.art-d4d43b89ac9d42a1ad9479ca7e312d012022-12-22T03:22:09ZengFrontiers Media S.A.Frontiers in Immunology1664-32242022-10-011310.3389/fimmu.2022.10264161026416Combined unsupervised and semi-automated supervised analysis of flow cytometry data reveals cellular fingerprint associated with newly diagnosed pediatric type 1 diabetesCamillo Bechi Genzano0Eugenia Bezzecchi1Eugenia Bezzecchi2Debora Carnovale3Alessandra Mandelli4Elisa Morotti5Elisa Morotti6Valeria Castorani7Valeria Favalli8Valeria Favalli9Angela Stabilini10Vittoria Insalaco11Francesca Ragogna12Valentina Codazzi13Giulia Maria Scotti14Stefania Del Rosso15Benedetta Allegra Mazzi16Maurizio De Pellegrin17Andrea Giustina18Andrea Giustina19Lorenzo Piemonti20Lorenzo Piemonti21Emanuele Bosi22Emanuele Bosi23Emanuele Bosi24Manuela Battaglia25Marco J. Morelli26Riccardo Bonfanti27Riccardo Bonfanti28Riccardo Bonfanti29Alessandra Petrelli30Diabetes Research Institute, IRCCS Ospedale San Raffaele, Milan, ItalyDiabetes Research Institute, IRCCS Ospedale San Raffaele, Milan, ItalyCenter for Omics Sciences, IRCCS Ospedale San Raffaele, Milan, ItalyDiabetes Research Institute, IRCCS Ospedale San Raffaele, Milan, ItalyDiabetes Research Institute, IRCCS Ospedale San Raffaele, Milan, ItalyDiabetes Research Institute, IRCCS Ospedale San Raffaele, Milan, ItalyDepartment of Pediatrics, IRCCS Ospedale San Raffaele, Milan, ItalyDiabetes Research Institute, IRCCS Ospedale San Raffaele, Milan, ItalyDiabetes Research Institute, IRCCS Ospedale San Raffaele, Milan, ItalyDepartment of Pediatrics, IRCCS Ospedale San Raffaele, Milan, ItalyDiabetes Research Institute, IRCCS Ospedale San Raffaele, Milan, ItalyDiabetes Research Institute, IRCCS Ospedale San Raffaele, Milan, ItalyDiabetes Research Institute, IRCCS Ospedale San Raffaele, Milan, ItalyDiabetes Research Institute, IRCCS Ospedale San Raffaele, Milan, ItalyDiabetes Research Institute, IRCCS Ospedale San Raffaele, Milan, ItalyLaboratory Medicine, Autoimmunity Section, IRCCS Ospedale San Raffaele, Milan, ItalyImmuno-Hematology and Transfusion Medicine (ITMS), IRCCS Ospedale San Raffaele, Milan, ItalyPediatric Orthopedic and Traumatology Unit, IRCCS Ospedale San Raffaele, Milan, ItalyInstitute of Endocrine and Metabolic Sciences, IRCCS Ospedale San Raffaele, Milan, ItalyUniversità Vita-Salute San Raffaele, Milan, ItalyDiabetes Research Institute, IRCCS Ospedale San Raffaele, Milan, ItalyUniversità Vita-Salute San Raffaele, Milan, ItalyDiabetes Research Institute, IRCCS Ospedale San Raffaele, Milan, ItalyDepartment of General Medicine, Diabetes and Endocrinology, IRCCS Ospedale San Raffaele, Milan, ItalyUniversità Vita-Salute San Raffaele, Milan, ItalyDiabetes Research Institute, IRCCS Ospedale San Raffaele, Milan, ItalyCenter for Omics Sciences, IRCCS Ospedale San Raffaele, Milan, ItalyDiabetes Research Institute, IRCCS Ospedale San Raffaele, Milan, ItalyDepartment of Pediatrics, IRCCS Ospedale San Raffaele, Milan, ItalyUniversità Vita-Salute San Raffaele, Milan, ItalyDiabetes Research Institute, IRCCS Ospedale San Raffaele, Milan, ItalyAn unbiased and replicable profiling of type 1 diabetes (T1D)-specific circulating immunome at disease onset has yet to be identified due to experimental and patient selection limitations. Multicolor flow cytometry was performed on whole blood from a pediatric cohort of 107 patients with new-onset T1D, 85 relatives of T1D patients with 0-1 islet autoantibodies (pre-T1D_LR), 58 patients with celiac disease or autoimmune thyroiditis (CD_THY) and 76 healthy controls (HC). Unsupervised clustering of flow cytometry data, validated by a semi-automated gating strategy, confirmed previous findings showing selective increase of naïve CD4 T cells and plasmacytoid DCs, and revealed a decrease in CD56brightNK cells in T1D. Furthermore, a non-selective decrease of CD3+CD56+ regulatory T cells was observed in T1D. The frequency of naïve CD4 T cells at disease onset was associated with partial remission, while it was found unaltered in the pre-symptomatic stages of the disease. Thanks to a broad cohort of pediatric individuals and the implementation of unbiased approaches for the analysis of flow cytometry data, here we determined the circulating immune fingerprint of newly diagnosed pediatric T1D and provide a reference dataset to be exploited for validation or discovery purposes to unravel the pathogenesis of T1D.https://www.frontiersin.org/articles/10.3389/fimmu.2022.1026416/fulltype 1 diabetesfingerprintsimmune markerspediatric diabetesflow cytometrycomputational biology |
| spellingShingle | Camillo Bechi Genzano Eugenia Bezzecchi Eugenia Bezzecchi Debora Carnovale Alessandra Mandelli Elisa Morotti Elisa Morotti Valeria Castorani Valeria Favalli Valeria Favalli Angela Stabilini Vittoria Insalaco Francesca Ragogna Valentina Codazzi Giulia Maria Scotti Stefania Del Rosso Benedetta Allegra Mazzi Maurizio De Pellegrin Andrea Giustina Andrea Giustina Lorenzo Piemonti Lorenzo Piemonti Emanuele Bosi Emanuele Bosi Emanuele Bosi Manuela Battaglia Marco J. Morelli Riccardo Bonfanti Riccardo Bonfanti Riccardo Bonfanti Alessandra Petrelli Combined unsupervised and semi-automated supervised analysis of flow cytometry data reveals cellular fingerprint associated with newly diagnosed pediatric type 1 diabetes Frontiers in Immunology type 1 diabetes fingerprints immune markers pediatric diabetes flow cytometry computational biology |
| title | Combined unsupervised and semi-automated supervised analysis of flow cytometry data reveals cellular fingerprint associated with newly diagnosed pediatric type 1 diabetes |
| title_full | Combined unsupervised and semi-automated supervised analysis of flow cytometry data reveals cellular fingerprint associated with newly diagnosed pediatric type 1 diabetes |
| title_fullStr | Combined unsupervised and semi-automated supervised analysis of flow cytometry data reveals cellular fingerprint associated with newly diagnosed pediatric type 1 diabetes |
| title_full_unstemmed | Combined unsupervised and semi-automated supervised analysis of flow cytometry data reveals cellular fingerprint associated with newly diagnosed pediatric type 1 diabetes |
| title_short | Combined unsupervised and semi-automated supervised analysis of flow cytometry data reveals cellular fingerprint associated with newly diagnosed pediatric type 1 diabetes |
| title_sort | combined unsupervised and semi automated supervised analysis of flow cytometry data reveals cellular fingerprint associated with newly diagnosed pediatric type 1 diabetes |
| topic | type 1 diabetes fingerprints immune markers pediatric diabetes flow cytometry computational biology |
| url | https://www.frontiersin.org/articles/10.3389/fimmu.2022.1026416/full |
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