Andersen, Marie Louise Max2; Rasmussen, Morten Arendt8; Pörksen, Sven2; Svensson, Jannet2; Vikre-Jørgensen, Jennifer3; Thomsen, Jane4; Hertel, Niels Thomas5; Johannesen, Jesper2; Pociot, Flemming6; Petersen, Jacob Sten7; Hansen, Lars2; Mortensen, Henrik Bindesbøl2; Nielsen, Lotte Brøndum2
1 Spectroscopy and Chemometrics, Department of Food Science, Faculty of Science, Københavns Universitet2 Herlev Hospital3 Skejby University Hospital4 Kolding Hospital5 Odense University Hospital6 Glostrup University Hospital7 Novo Nordisk A/S8 Spectroscopy and Chemometrics, Department of Food Science, Faculty of Science, Københavns Universitet
The purpose of the present study is to explore the progression of type 1 diabetes (T1D) in Danish children 12 months after diagnosis using Latent Factor Modelling. We include three data blocks of dynamic paraclinical biomarkers, baseline clinical characteristics and genetic profiles of diabetes related SNPs in the analyses. This method identified a model explaining 21.6% of the total variation in the data set. The model consists of two components: (1) A pattern of declining residual β-cell function positively associated with young age, presence of diabetic ketoacidosis and long duration of disease symptoms (P = 0.0004), and with risk alleles of WFS1, CDKN2A/2B and RNLS (P = 0.006). (2) A second pattern of high ZnT8 autoantibody levels and low postprandial glucagon levels associated with risk alleles of IFIH1, TCF2, TAF5L, IL2RA and PTPN2 and protective alleles of ERBB3 gene (P = 0.0005). These results demonstrate that Latent Factor Modelling can identify associating patterns in clinical prospective data--future functional studies will be needed to clarify the relevance of these patterns.
P L O S One, 2013, Vol 8, Issue 6
Adolescent; Age of Onset; Alleles; Autoantibodies; C-Peptide; Cation Transport Proteins; Child; Diabetes Mellitus, Type 1; Disease Progression; Female; Genetic Predisposition to Disease; Hemoglobin A, Glycosylated; Humans; Insulin-Secreting Cells; Male; Models, Biological; Polymorphism, Single Nucleotide; Prospective Studies; Risk