Essi Laajala

Innate immune activity is detected prior to seroconversion in children with HLA-conferred type 1 diabetes susceptibility.

The insult leading to autoantibody development in children who will progress to develop type 1 diabetes (T1D) has remained elusive. To investigate the genes and molecular pathways in the pathogenesis of this disease, we performed genome-wide transcriptomics analysis on a unique series of prospective whole-blood RNA samples from at-risk children collected in the Finnish Type 1 Diabetes Prediction and Prevention study. We studied 28 autoantibody-positive children, out of which 22 progressed to clinical disease. Collectively, the samples covered the time span from before the development of autoantibodies (seroconversion) through the diagnosis of diabetes. Healthy control subjects matched for date and place of birth, sex, and HLA-DQB1 susceptibility were selected for each case. Additionally, we genotyped the study subjects with Immunochip to identify potential genetic variants associated with the observed transcriptional signatures. Genes and pathways related to innate immunity functions, such as the type 1 interferon (IFN) response, were active, and IFN response factors were identified as central mediators of the IFN-related transcriptional changes. Importantly, this signature was detected already before the T1D-associated autoantibodies were detected. Together, these data provide a unique resource for new hypotheses explaining T1D biology.

Th1/Th17 Plasticity Is a Marker of Advanced β Cell Autoimmunity and Impaired Glucose Tolerance in Humans

Upregulation of IL-17 immunity and detrimental effects of IL-17 on human islets have been implicated in human type 1 diabetes. In animal models, the plasticity of Th1/Th17 cells contributes to the development of autoimmune diabetes. In this study, we demonstrate that the upregulation of the IL-17 pathway and Th1/Th17 plasticity in peripheral blood are markers of advanced β cell autoimmunity and impaired β cell function in human type 1 diabetes. Activated Th17 immunity was observed in the late stage of preclinical diabetes in children with β cell autoimmunity and impaired glucose tolerance, but not in children with early β cell autoimmunity. We found an increased ratio of IFN-γ/IL-17 expression in Th17 cells in children with advanced β cell autoimmunity, which correlated with HbA1c and plasma glucose concentrations in an oral glucose tolerance test, and thus impaired β cell function. Low expression of Helios was seen in Th17 cells, suggesting that Th1/Th17 cells are not converted thymus-derived regulatory T cells. Our results suggest that the development of Th1/Th17 plasticity may serve as a biomarker of disease progression from β cell autoantibody positivity to type 1 diabetes. These data in human type 1 diabetes emphasize the role of Th1/Th17 plasticity as a potential contributor to tissue destruction in autoimmune conditions.

Probe-level estimation improves the detection of differential splicing in Affymetrix exon array studies

The recent advent of exon microarrays has made it possible to reveal differences in alternative splicing events on a global scale. We introduce a novel statistical procedure that takes full advantage of the probe-level information on Affymetrix exon arrays when detecting differential splicing between sample groups. In comparison to existing ranking methods, the procedure shows superior reproducibility and accuracy in distinguishing true biological findings from background noise in high agreement with experimental validations.

Serum Proteomes Distinguish Children Developing Type 1 Diabetes in a Cohort With HLA-Conferred Susceptibility

We determined longitudinal serum proteomics profiles from children with HLA-conferred diabetes susceptibility to identify changes that could be detected before seroconversion and positivity for disease-associated autoantibodies. Comparisons were made between children who seroconverted and progressed to type 1 diabetes (progressors) and those who remained autoantibody negative, matched by age, sex, sample periodicity, and risk group. The samples represented the prediabetic period and ranged from the age of 3 months to 12 years. After immunoaffinity depletion of the most abundant serum proteins, isobaric tags for relative and absolute quantification were used for sample labeling. Quantitative proteomic profiles were then measured for 13 case-control pairs by high-performance liquid chromatography-tandem mass spectrometry (LC-MS/MS). Additionally, a label-free LC-MS/MS approach was used to analyze depleted sera from six case-control pairs. Importantly, differences in abundance of a set of proteins were consistently detected before the appearance of autoantibodies in the progressors. Based on top-scoring pairs analysis, classification of such progressors was observed with a high success rate. Overall, the data provide a reference of temporal changes in the serum proteome in healthy children and children progressing to type 1 diabetes, including new protein candidates, the levels of which change before clinical diagnosis.

Genome-wide Analysis of STAT3-Mediated Transcription during Early Human Th17 Cell Differentiation

The development of therapeutic strategies to combat immune-associated diseases requires the molecular mechanisms of human Th17 cell differentiation to be fully identified and understood. To investigate transcriptional control of Th17 cell differentiation, we used primary human CD4+ Txa0cells in small interfering RNA (siRNA)-mediated gene silencing and chromatin immunoprecipitation followed by massive parallel sequencing (ChIP-seq) to identify both the early direct and indirect targets of STAT3. The integrated dataset presented in this study confirms that STAT3 is critical for transcriptional regulation of early human Th17 cell differentiation. Additionally, we found that a number of SNPs from loci associated with immune-mediated disorders were located at sites where STAT3 binds to induce Th17 cell specification. Importantly, introduction of such SNPs alters STAT3 binding in DNA affinity precipitation assays. Overall, our study provides important insights for modulating Th17-mediated pathogenic immune responses in humans.

Exploring the risk factors for differences in the cumulative incidence of coeliac disease in two neighboring countries: the prospective DIABIMMUNE study

BACKGROUNDnDuring the last several decades the prevalence of coeliac disease (CD) has increased worldwide.nnnAIMnTo compare the cumulative incidence of CD between Estonian and Finnish children and to identify the risk factors.nnnMATERIALS AND METHODSnChildren were recruited as part of the DIABIMMUNE Study. In the birth cohort (BC) 258 children from Estonia and 305 from Finland, and in the young childrens cohort (YCC) 1363 and 1384 children were followed up, respectively. The diagnosis of CD was made in accordance with the ESPGHAN guidelines-the presence of IgA-tTG antibodies and small bowel villous atrophy.nnnRESULTSnDuring the study period 29 children developed CD. The cumulative incidence of CD was significantly higher in Finland (0.77% vs 0.27%; P=0.01). No difference was seen between the children with CD and the controls in the duration of breastfeeding or the age at cereal introduction. The BC children with CD had had significantly more episodes of infections with fever by the age of 12 months compared to the controls (3.4 vs 1.4; P=0.04).nnnCONCLUSIONnThe 5-year cumulative incidence of childhood CD is significantly higher in Finland than in Estonia. Sequential infections early in life may increase the risk for developing CD.

Characterization and non-parametric modeling of the developing serum proteome during infancy and early childhood

Children develop rapidly during the first years of life, and understanding the sources and associated levels of variation in the serum proteome is important when using serum proteins as markers for childhood diseases. The aim of this study was to establish a reference model for the evolution of a healthy serum proteome during early childhood. Label-free quantitative proteomics analyses were performed for 103 longitudinal serum samples collected from 15 children at birth and between the ages of 3–36 months. A flexible Gaussian process-based probabilistic modelling framework was developed to evaluate the effects of different variables, including age, living environment and individual variation, on the longitudinal expression profiles of 266 reliably identified and quantified serum proteins. Age was the most dominant factor influencing approximately half of the studied proteins, and the most prominent age-associated changes were observed already during the first year of life. High inter-individual variability was also observed for multiple proteins. These data provide important details on the maturing serum proteome during early life, and evaluate how patterns detected in cord blood are conserved in the first years of life. Additionally, our novel modelling approach provides a statistical framework to detect associations between covariates and non-linear time series data.