Cargando…
Meta-Immunological Profiling of Children With Type 1 Diabetes Identifies New Biomarkers to Monitor Disease Progression
Type 1 diabetes is characterized by autoimmune destruction of pancreatic β-cells in genetically susceptible individuals. Triggers of islet autoimmunity, time course, and the precise mechanisms responsible for the progressive β-cell failure are not completely understood. The recent escalation of obes...
Autores principales: | , , , , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Diabetes Association
2013
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3712055/ https://www.ncbi.nlm.nih.gov/pubmed/23396400 http://dx.doi.org/10.2337/db12-1273 |
_version_ | 1782277010938134528 |
---|---|
author | Galgani, Mario Nugnes, Rosa Bruzzese, Dario Perna, Francesco De Rosa, Veronica Procaccini, Claudio Mozzillo, Enza Cilio, Corrado M. Elding Larsson, Helena Lernmark, Åke La Cava, Antonio Franzese, Adriana Matarese, Giuseppe |
author_facet | Galgani, Mario Nugnes, Rosa Bruzzese, Dario Perna, Francesco De Rosa, Veronica Procaccini, Claudio Mozzillo, Enza Cilio, Corrado M. Elding Larsson, Helena Lernmark, Åke La Cava, Antonio Franzese, Adriana Matarese, Giuseppe |
author_sort | Galgani, Mario |
collection | PubMed |
description | Type 1 diabetes is characterized by autoimmune destruction of pancreatic β-cells in genetically susceptible individuals. Triggers of islet autoimmunity, time course, and the precise mechanisms responsible for the progressive β-cell failure are not completely understood. The recent escalation of obesity in affluent countries has been suggested to contribute to the increased incidence of type 1 diabetes. Understanding the link between metabolism and immune tolerance could lead to the identification of new markers for the monitoring of disease onset and progression. We studied several immune cell subsets and factors with high metabolic impact as markers associated with disease progression in high-risk subjects and type 1 diabetic patients at onset and at 12 and 24 months after diagnosis. A multiple correlation matrix among different parameters was evaluated statistically and assessed visually on two-dimensional graphs. Markers to predict residual β-cell function up to 1 year after diagnosis were identified in multivariate logistic regression models. The meta-immunological profile changed significantly over time in patients, and a specific signature that was associated with worsening disease was identified. A multivariate logistic regression model measuring age, BMI, fasting C-peptide, number of circulating CD3(+)CD16(+)CD56(+) cells, and the percentage of CD1c(+)CD19(−)CD14(−)CD303(−) type 1 myeloid dendritic cells at disease onset had a significant predictive value. The identification of a specific meta-immunological profile associated with disease status may contribute to our understanding of the basis of diabetes progression. |
format | Online Article Text |
id | pubmed-3712055 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | American Diabetes Association |
record_format | MEDLINE/PubMed |
spelling | pubmed-37120552014-07-01 Meta-Immunological Profiling of Children With Type 1 Diabetes Identifies New Biomarkers to Monitor Disease Progression Galgani, Mario Nugnes, Rosa Bruzzese, Dario Perna, Francesco De Rosa, Veronica Procaccini, Claudio Mozzillo, Enza Cilio, Corrado M. Elding Larsson, Helena Lernmark, Åke La Cava, Antonio Franzese, Adriana Matarese, Giuseppe Diabetes Original Research Type 1 diabetes is characterized by autoimmune destruction of pancreatic β-cells in genetically susceptible individuals. Triggers of islet autoimmunity, time course, and the precise mechanisms responsible for the progressive β-cell failure are not completely understood. The recent escalation of obesity in affluent countries has been suggested to contribute to the increased incidence of type 1 diabetes. Understanding the link between metabolism and immune tolerance could lead to the identification of new markers for the monitoring of disease onset and progression. We studied several immune cell subsets and factors with high metabolic impact as markers associated with disease progression in high-risk subjects and type 1 diabetic patients at onset and at 12 and 24 months after diagnosis. A multiple correlation matrix among different parameters was evaluated statistically and assessed visually on two-dimensional graphs. Markers to predict residual β-cell function up to 1 year after diagnosis were identified in multivariate logistic regression models. The meta-immunological profile changed significantly over time in patients, and a specific signature that was associated with worsening disease was identified. A multivariate logistic regression model measuring age, BMI, fasting C-peptide, number of circulating CD3(+)CD16(+)CD56(+) cells, and the percentage of CD1c(+)CD19(−)CD14(−)CD303(−) type 1 myeloid dendritic cells at disease onset had a significant predictive value. The identification of a specific meta-immunological profile associated with disease status may contribute to our understanding of the basis of diabetes progression. American Diabetes Association 2013-07 2013-06-14 /pmc/articles/PMC3712055/ /pubmed/23396400 http://dx.doi.org/10.2337/db12-1273 Text en © 2013 by the American Diabetes Association. Readers may use this article as long as the work is properly cited, the use is educational and not for profit, and the work is not altered. See http://creativecommons.org/licenses/by-nc-nd/3.0/ for details. |
spellingShingle | Original Research Galgani, Mario Nugnes, Rosa Bruzzese, Dario Perna, Francesco De Rosa, Veronica Procaccini, Claudio Mozzillo, Enza Cilio, Corrado M. Elding Larsson, Helena Lernmark, Åke La Cava, Antonio Franzese, Adriana Matarese, Giuseppe Meta-Immunological Profiling of Children With Type 1 Diabetes Identifies New Biomarkers to Monitor Disease Progression |
title | Meta-Immunological Profiling of Children With Type 1 Diabetes Identifies New Biomarkers to Monitor Disease Progression |
title_full | Meta-Immunological Profiling of Children With Type 1 Diabetes Identifies New Biomarkers to Monitor Disease Progression |
title_fullStr | Meta-Immunological Profiling of Children With Type 1 Diabetes Identifies New Biomarkers to Monitor Disease Progression |
title_full_unstemmed | Meta-Immunological Profiling of Children With Type 1 Diabetes Identifies New Biomarkers to Monitor Disease Progression |
title_short | Meta-Immunological Profiling of Children With Type 1 Diabetes Identifies New Biomarkers to Monitor Disease Progression |
title_sort | meta-immunological profiling of children with type 1 diabetes identifies new biomarkers to monitor disease progression |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3712055/ https://www.ncbi.nlm.nih.gov/pubmed/23396400 http://dx.doi.org/10.2337/db12-1273 |
work_keys_str_mv | AT galganimario metaimmunologicalprofilingofchildrenwithtype1diabetesidentifiesnewbiomarkerstomonitordiseaseprogression AT nugnesrosa metaimmunologicalprofilingofchildrenwithtype1diabetesidentifiesnewbiomarkerstomonitordiseaseprogression AT bruzzesedario metaimmunologicalprofilingofchildrenwithtype1diabetesidentifiesnewbiomarkerstomonitordiseaseprogression AT pernafrancesco metaimmunologicalprofilingofchildrenwithtype1diabetesidentifiesnewbiomarkerstomonitordiseaseprogression AT derosaveronica metaimmunologicalprofilingofchildrenwithtype1diabetesidentifiesnewbiomarkerstomonitordiseaseprogression AT procacciniclaudio metaimmunologicalprofilingofchildrenwithtype1diabetesidentifiesnewbiomarkerstomonitordiseaseprogression AT mozzilloenza metaimmunologicalprofilingofchildrenwithtype1diabetesidentifiesnewbiomarkerstomonitordiseaseprogression AT ciliocorradom metaimmunologicalprofilingofchildrenwithtype1diabetesidentifiesnewbiomarkerstomonitordiseaseprogression AT eldinglarssonhelena metaimmunologicalprofilingofchildrenwithtype1diabetesidentifiesnewbiomarkerstomonitordiseaseprogression AT lernmarkake metaimmunologicalprofilingofchildrenwithtype1diabetesidentifiesnewbiomarkerstomonitordiseaseprogression AT lacavaantonio metaimmunologicalprofilingofchildrenwithtype1diabetesidentifiesnewbiomarkerstomonitordiseaseprogression AT franzeseadriana metaimmunologicalprofilingofchildrenwithtype1diabetesidentifiesnewbiomarkerstomonitordiseaseprogression AT mataresegiuseppe metaimmunologicalprofilingofchildrenwithtype1diabetesidentifiesnewbiomarkerstomonitordiseaseprogression |