Complex Multi-Block Analysis Identifies New Immunologic and Genetic Disease Progression Patterns Associated with the Residual β-Cell Function 1 Year after Diagnosis of Type 1 Diabetes

被引：17

作者：

Andersen, Marie Louise Max ^{[1
]}

Rasmussen, Morten Arendt ^{[2
]}

Porksen, Sven ^{[1
]}

Svensson, Jannet ^{[1
]}

Vikre-Jorgensen, Jennifer ^{[3
]}

Thomsen, Jane ^{[4
]}

Hertel, Niels Thomas ^{[5
]}

Johannesen, Jesper ^{[1
]}

Pociot, Flemming ^{[6
]}

Petersen, Jacob Sten ^{[7
]}

Hansen, Lars ^{[1
]}

Mortensen, Henrik Bindesbol ^{[1
]}

Nielsen, Lotte Brondum ^{[1
]}

机构：

[1] Univ Copenhagen, Herlev Hosp, Dept Pediat, Fac Hlth Sci, Copenhagen, Denmark

[2] Dept Food Sci Qual & Technol, Copenhagen, Denmark

[3] Skejby Univ Hosp, Dept Pediat, Aarhus, Denmark

[4] Kolding Cty Hosp, Dept Pediat, Kolding, Denmark

[5] Odense Univ Hosp, HC Andersen Childrens Hosp, DK-5000 Odense, Denmark

[6] Glostrup Univ Hosp, Diagnost Unit, Dept Biochem, Glostrup, Denmark

[7] Novo Nordisk AS, Diabet Pharmacol & Bioanal, Malov, Denmark

来源：

PLOS ONE | 2013年 / 8卷 / 06期

关键词：

GENOME-WIDE ASSOCIATION; PARTIAL REMISSION; GLYCEMIC CONTROL; CHILDREN; ADOLESCENTS; GLUCAGON; AUTOANTIBODIES; GLUCOSE; ZINC; SUSCEPTIBILITY;

D O I：

10.1371/journal.pone.0064632

中图分类号：

O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

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 beta-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.

引用

页数：8

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