Improving coeliac disease risk prediction by testing non-HLA variants additional to HLA variants

Background: The majority of coeliac disease (CD) patients are not being properly diagnosed and therefore remain untreated, leading to a greater risk of developing CD-associated complications. The major genetic risk heterodimer, HLA-DQ2 and DQ8, is already used clinically to help exclude disease. However, approximately 40% of the population carry these alleles and the majority never develop CD. Objective: We explored whether CD risk prediction can be improved by adding non-HLA-susceptible variants to common HLA testing. Design: We developed an average weighted genetic risk score with 10, 26 and 57 single nucleotide polymorphisms (SNP) in 2675 cases and 2815 controls and assessed the improvement in risk prediction provided by the non-HLA SNP. Moreover, we assessed the transferability of the genetic risk model with 26 non-HLA variants to a nested case–control population (n=1709) and a prospective cohort (n=1245) and then tested how well this model predicted CD outcome for 985 independent individuals. Results: Adding 57 non-HLA variants to HLA testing showed a statistically significant improvement compared to scores from models based on HLA only, HLA plus 10 SNP and HLA plus 26 SNP. With 57 non-HLA variants, the area under the receiver operator characteristic curve reached 0.854 compared to 0.823 for HLA only, and 11.1% of individuals were reclassified to a more accurate risk group. We show that the risk model with HLA plus 26 SNP is useful in independent populations. Conclusions: Predicting risk with 57 additional non-HLA variants improved the identification of potential CD patients. This demonstrates a possible role for combined HLA and non-HLA genetic testing in diagnostic work for CD

Two Single Nucleotide Polymorphisms Identify the Highest-Risk Diabetes HLA Genotype: Potential for Rapid Screening

OBJECTIVE—People with the HLA genotype DRB1*0301-DQA1*0501-DQB1*0201/DRB1*04-DQA1*0301-DQB1*0302 (DR3/4-DQ8) are at the highest risk of developing type 1 diabetes. We sought to find an inexpensive, rapid test to identify DR3/4-DQ8 subjects using two single nucleotide polymorphisms (SNPs)

Data-Driven Phenotyping of Presymptomatic Type 1 Diabetes Using Longitudinal Autoantibody Profiles

Abstract Objective: To characterize distinct islet autoantibody profiles preceding stage 3 type 1 diabetes Research Design and Methods: The T1DI (Type 1 Diabetes Intelligence) study combined data from 1,845 genetically susceptible prospectively observed children who were positive for at least one islet autoantibody: insulin autoantibody (IAA), GAD antibody (GADA), or islet antigen 2 antibody (IA-2A). Using a novel similarity algorithm that considers an individual’s temporal autoantibody profile, age at autoantibody appearance, and variation in the positivity of autoantibody types, we performed an unsupervised hierarchical clustering analysis. Progression rates to diabetes were analyzed via survival analysis. Results: We identified five main clusters of individuals with distinct autoantibody profiles characterized by seroconversion age and sequence of appearance of the three autoantibodies. The highest 5-year risk from first positive autoantibody to type 1 diabetes (69.9%; 95% CI 60.0–79.2) was observed in children who first developed IAA in early life (median age 1.6 years) followed by GADA (1.9 years) and then IA-2A (2.1 years). Their 10-year risk was 89.9% (95% CI 81.9–95.4). A high 5-year risk was also found in children with persistent IAA and GADA (39.1%) and children with persistent GADA and IA-2A (30.9%). A lower 5-year risk (10.5%) was observed in children with a late appearance of persistent GADA (6.1 years). The lowest 5-year diabetes risk (1.6%) was associated with positivity for a single, often reverting, autoantibody. Conclusions: The novel clustering algorithm identified children with distinct islet autoantibody profiles and progression rates to diabetes. These results are useful for prediction, selection of individuals for prevention trials, and studies investigating various pathways to type 1 diabetes.Abstract Objective: To characterize distinct islet autoantibody profiles preceding stage 3 type 1 diabetes Research Design and Methods: The T1DI (Type 1 Diabetes Intelligence) study combined data from 1,845 genetically susceptible prospectively observed children who were positive for at least one islet autoantibody: insulin autoantibody (IAA), GAD antibody (GADA), or islet antigen 2 antibody (IA-2A). Using a novel similarity algorithm that considers an individual’s temporal autoantibody profile, age at autoantibody appearance, and variation in the positivity of autoantibody types, we performed an unsupervised hierarchical clustering analysis. Progression rates to diabetes were analyzed via survival analysis. Results: We identified five main clusters of individuals with distinct autoantibody profiles characterized by seroconversion age and sequence of appearance of the three autoantibodies. The highest 5-year risk from first positive autoantibody to type 1 diabetes (69.9%; 95% CI 60.0–79.2) was observed in children who first developed IAA in early life (median age 1.6 years) followed by GADA (1.9 years) and then IA-2A (2.1 years). Their 10-year risk was 89.9% (95% CI 81.9–95.4). A high 5-year risk was also found in children with persistent IAA and GADA (39.1%) and children with persistent GADA and IA-2A (30.9%). A lower 5-year risk (10.5%) was observed in children with a late appearance of persistent GADA (6.1 years). The lowest 5-year diabetes risk (1.6%) was associated with positivity for a single, often reverting, autoantibody. Conclusions: The novel clustering algorithm identified children with distinct islet autoantibody profiles and progression rates to diabetes. These results are useful for prediction, selection of individuals for prevention trials, and studies investigating various pathways to type 1 diabetes

Age-Related Patterns in Clinical Presentations and Gluten-Related Issues Among Children and Adolescents With Celiac Disease

OBJECTIVES: Celiac disease (CD) is common and often cited as an “iceberg” phenomenon (i.e., an assumed large number of undiagnosed cases). Recently, atypical or asymptomatic manifestations are becoming more commonly described in older children and adolescents. Moreover, CD diagnosis in children can be complicated by several factors, including its diverse clinical presentations, delay in recognizing CD signs and symptoms, and premature dietary gluten avoidance before the formal diagnosis of CD. To date, few studies have directly examined age-related differences in clinical characteristics and gluten-related issues among children with CD. The aim of this study was to determine age-related patterns in clinical characteristics and gluten-related issues among children with confirmed CD. METHODS: We performed a structured medical record review of biopsy-proven CD patients, aged 0–19 years, between 2000 and 2010 at a large Boston teaching hospital. Data collection included demographics, medical history, gluten-related issues, and diagnostic investigations (CD-specific serology, upper gastrointestinal endoscopy, and small intestinal biopsy). The first positive duodenal biopsy with Marsh III classification defined age of diagnosis. Patients were divided into three age groups for comparisons of the aforementioned characteristics: infant-preschool group (0–5 years), school-aged group (6–11 years), and adolescence group (12–19 years). RESULTS: Among 411 children with biopsy-proven CD, the mean age was 9.5 (s.d. 5.1) years. Most were female (63%) and white (96%). All children had positive CD-specific serology. Most children presented with either abdominal complaints or bowel movement changes. Overall, boys were more common among infant-preschool group compared with the other age groups. More distinct clinical manifestations (vomiting, bowel movement changes, and weight issues) were apparent in the youngest group, whereas school-aged children had more subjective abdominal complaints at the initial presentation. Conversely, the adolescents were most likely to present without any gastrointestinal (GI) symptoms, but not when this was combined with absence of weight issues. Age of diagnosis was not associated with atypical extraintestinal CD presentations. Regarding the gluten-related issues, 10% of school-aged children avoided dietary gluten before the formal CD diagnosis, and 27% of the adolescents reported dietary gluten transgression within the first 12 months of diagnosis, significantly higher than the other age groups. Age differences in histopathology were also found. Whereas the infant-preschool group had a higher proportion of total villous atrophy, the older children were more likely to have gross duodenal abnormalities and chronic duodenitis suggestive of CD at the time of diagnosis. CONCLUSIONS: Children and adolescents with CD have age-related patterns in both the clinical presentations and gluten-related issues. More pronounced clinical and histological features were determined in younger children, whereas older children more commonly presented with solely subjective abdominal complaints or even without any GI symptoms. However, silent and atypical extraintestinal CD presentations were comparable between age groups. In addition to the aforementioned presentations, the higher rates of dietary gluten avoidance and transgression in older children make CD diagnosis and management particularly challenging. These age-related patterns may further increase awareness, facilitate early diagnosis, and improve patient care of pediatric CD