A composite immune signature parallels disease progression across T1D subjects. JCI Insight 2019 Dec 05;4(23)
Date
11/02/2019Pubmed ID
31671072Pubmed Central ID
PMC6962023DOI
10.1172/jci.insight.126917Scopus ID
2-s2.0-85077748478 (requires institutional sign-in at Scopus site) 12 CitationsAbstract
At diagnosis, most people with type 1 diabetes (T1D) produce measurable levels of endogenous insulin, but the rate at which insulin secretion declines is heterogeneous. To explain this heterogeneity, we sought to identify a composite signature predictive of insulin secretion, using a collaborative assay evaluation and analysis pipeline that incorporated multiple cellular and serum measures reflecting β cell health and immune system activity. The ability to predict decline in insulin secretion would be useful for patient stratification for clinical trial enrollment or therapeutic selection. Analytes from 12 qualified assays were measured in shared samples from subjects newly diagnosed with T1D. We developed a computational tool (DIFAcTO, Data Integration Flexible to Account for different Types of data and Outcomes) to identify a composite panel associated with decline in insulin secretion over 2 years following diagnosis. DIFAcTO uses multiple filtering steps to reduce data dimensionality, incorporates error estimation techniques including cross-validation and sensitivity analysis, and is flexible to assay type, clinical outcome, and disease setting. Using this novel analytical tool, we identified a panel of immune markers that, in combination, are highly associated with loss of insulin secretion. The methods used here represent a potentially novel process for identifying combined immune signatures that predict outcomes relevant for complex and heterogeneous diseases like T1D.
Author List
Speake C, Skinner SO, Berel D, Whalen E, Dufort MJ, Young WC, Odegard JM, Pesenacker AM, Gorus FK, James EA, Levings MK, Linsley PS, Akirav EM, Pugliese A, Hessner MJ, Nepom GT, Gottardo R, Long SAAuthor
Martin J. Hessner PhD Professor in the Pediatrics department at Medical College of WisconsinMESH terms used to index this publication - Major topics in bold
AdolescentAdult
Child
Computational Biology
Diabetes Mellitus, Type 1
Disease Progression
Female
Humans
Hypoglycemic Agents
Immunotherapy
Insulin-Secreting Cells
Male
Young Adult
