Celiac Disease and Anorexia Nervosa: A Nationwide Study

BACKGROUND AND OBJECTIVE: Previous research suggests an association of celiac disease (CD) with anorexia nervosa (AN), but data are mostly limited to case reports. We aimed to determine whether CD is associated with the diagnosis of AN. METHODS: Register-based cohort and case-control study including women with CD (n = 17 959) and sex- and age-matched population-based controls (n = 89 379). CD (villous atrophy) was identified through the histopathology records of Sweden's 28 pathology departments. Inpatient and hospital-based outpatient records were used to identify AN. Hazard ratios for incident AN diagnosis were estimated by using stratified Cox regression with CD diagnosis as a time-dependent exposure variable. In the secondary analyses, we used conditional logistic regression to estimate odds ratios for being diagnosed with AN before CD. RESULTS: Median age of CD diagnosis was 28 years. During 1 174 401 person-years of follow-up, 54 patients with CD were diagnosed with AN (27/100 000 person-years) compared with 180 matched controls (18/100 000 person-years). The hazard ratio for later AN was 1.46 (95% confidence interval [CI], 1.08-1.98) and 1.31 beyond the first year after CD diagnosis (95% CI, 0.95-1.81). A previous AN diagnosis was also associated with CD (odds ratio, 2.18; 95% CI, 1.45-3.29). Estimates remained largely unchanged when adjusted for socioeconomic characteristics and type 1 diabetes. CONCLUSIONS: The bidirectional association between AN diagnosis and CD warrants attention in the initial assessment and follow-up of these conditions because underdiagnosis and misdiagnosis of these disorders likely cause protracted and unnecessary morbidity

Haptoglobin genotype predicts development of coronary artery calcification in a prospective cohort of patients with type 1 diabetes

<p>Abstract</p> <p>Background</p> <p>Coronary artery disease has been linked with genotypes for haptoglobin (Hp) which modulates extracorpuscular hemoglobin. We hypothesized that the Hp genotype would predict progression of coronary artery calcification (CAC), a marker of subclinical atherosclerosis.</p> <p>Methods</p> <p>CAC was measured three times in six years among 436 subjects with type 1 diabetes and 526 control subjects participating in the Coronary Artery Calcification in Type 1 Diabetes (CACTI) study. Hp typing was performed on plasma samples by polyacrylamide gel electrophoresis.</p> <p>Results</p> <p>The Hp 2-2 genotype predicted development of significant CAC only in subjects with diabetes who were free of CAC at baseline (OR: 1.95, 95% CI: 1.07-3.56, p = 0.03), compared to those without the Hp 2-2 genotype, controlling for age, sex, blood pressure and HDL-cholesterol. Hp 2 appeared to have an allele-dose effect on development of CAC. Hp genotype did not predict CAC progression in individuals without diabetes.</p> <p>Conclusions</p> <p>Hp genotype may aid prediction of accelerated coronary atherosclerosis in subjects with type 1 diabetes.</p

Components of Metabolic Syndrome and 5-Year Chance in Insulin Clearance - The Resistance Atherosclerosis Study (IRAS)

Aims Cross-sectional evidence indicates that abdominal adiposity, hypertension, dyslipidaemia and glycaemia are associated with reduced metabolic clearance rate of insulin (MCRI). Little is known about the progression of MCRI and whether components of metabolic syndrome are associated with the change in MCRI. In this study, we examined the association between components of metabolic syndrome and the 5-year change of MCRI. Methods At baseline and 5-year follow-up, we measured fasting plasma triglycerides (TG), high-density lipoprotein (HDL) cholesterol, blood pressure (BP), waist circumference (WC) and fasting blood glucose (FBG) in 784 non-diabetic participants in the Insulin Resistance Atherosclerosis Study. MCRI, insulin sensitivity (SI) and acute insulin response (AIR) were determined from frequently sampled intravenous glucose tolerance tests. Results We observed a 29% decline of MCRI at follow-up. TG, systolic BP and WC at baseline were inversely associated with a decline of MCRI regression models adjusted for age, sex, ethnicity, smoking, alcohol consumption, energy expenditure, family history of diabetes, BMI, SI and AIR [β = −0.057 (95% confidence interval, CI: −0.11, −0.0084) for TG, β = −0.0019 (95% CI: −0.0035, −0.00023) for systolic BP and β  = −0.0084 (95% CI: −0.013, −0.0039) for WC; all p \u3c 0.05]. Higher HDL cholesterol at baseline was associated with an increase in MCRI [multivariable-adjusted β = 0.0029 (95% CI: 0.0010, 0.0048), p = 0.002]. FBG at baseline was not associated with MCRI at follow-up [multivariable-adjusted β = 0.0014 (95% CI: −0.0026, 0.0029)]. Conclusions MCRI declined progressively over 5 years in a non-diabetic cohort. Components of metabolic syndrome at baseline were associated with a significant change in MCRI

Clinical Study Evidence of Stage-and Age-Related Heterogeneity of Non-HLA SNPs and Risk of Islet Autoimmunity and Type 1 Diabetes: The Diabetes Autoimmunity Study in the Young

Previously, we examined 20 non-HLA SNPs for association with islet autoimmunity (IA) and/or progression to type 1 diabetes (T1D). Our objective was to investigate fourteen additional non-HLA T1D candidate SNPs for stage-and age-related heterogeneity in the etiology of T1D. Of 1634 non-Hispanic white DAISY children genotyped, 132 developed IA (positive for GAD, insulin, or IA-2 autoantibodies at two or more consecutive visits); 50 IA positive children progressed to T1D. Cox regression was used to analyze risk of IA and progression to T1D in IA positive children. Restricted cubic splines were used to model SNPs when there was evidence that risk was not constant with age. C1QTNF6 (rs229541) predicted increased IA risk (HR: 1.57, CI: 1.20-2.05) but not progression to T1D (HR: 1.13, CI: 0.75-1.71). SNP (rs10517086) appears to exhibit an age-related effect on risk of IA, with increased risk before age 2 years (age 2 HR: 1.67, CI: 1.08-2.56) but not older ages (age 4 HR: 0.84, CI: 0.43-1.62). C1QTNF6 (rs229541), SNP (rs10517086), and UBASH3A (rs3788013) were associated with development of T1D. This prospective investigation of non-HLA T1D candidate loci shows that some SNPs may exhibit stage-and age-related heterogeneity in the etiology of T1D

Transcriptional networks in at-risk individuals identify signatures of type 1 diabetes progression.

Type 1 diabetes (T1D) is a disease of insulin deficiency that results from autoimmune destruction of pancreatic islet β cells. The exact cause of T1D remains unknown, although asymptomatic islet autoimmunity lasting from weeks to years before diagnosis raises the possibility of intervention before the onset of clinical disease. The number, type, and titer of islet autoantibodies are associated with long-term disease risk but do not cause disease, and robust early predictors of individual progression to T1D onset remain elusive. The Environmental Determinants of Diabetes in the Young (TEDDY) consortium is a prospective cohort study aiming to determine genetic and environmental interactions causing T1D. Here, we analyzed longitudinal blood transcriptomes of 2013 samples from 400 individuals in the TEDDY study before both T1D and islet autoimmunity. We identified and interpreted age-associated gene expression changes in healthy infancy and age-independent changes tracking with progression to both T1D and islet autoimmunity, beginning before other evidence of islet autoimmunity was present. We combined multivariate longitudinal data in a Bayesian joint model to predict individual risk of T1D onset and validated the association of a natural killer cell signature with progression and the model's predictive performance on an additional 356 samples from 56 individuals in the independent Type 1 Diabetes Prediction and Prevention study. Together, our results indicate that T1D is characterized by early and longitudinal changes in gene expression, informing the immunopathology of disease progression and facilitating prediction of its course.The TEDDY Study is funded by U01 DK63829, U01 DK63861, U01 DK63821, U01 DK63865, U01 DK63863, U01 DK63836, U01 DK63790, UC4 DK63829, UC4 DK63861, UC4 DK63821, UC4 DK63865, UC4 DK63863, UC4 DK63836, UC4 DK95300, UC4 DK100238, UC4 DK106955, UC4 DK112243, UC4 DK117483, and Contract No. HHSN267200700014C from the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), National Institute of Allergy and Infectious Diseases (NIAID), Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD), National Institute of Environmental Health Sciences (NIEHS), Centers for Disease Control and Prevention (CDC), and JDRF. This work supported in part by the NIH/NCATS Clinical and Translational Science Awards to the University of Florida (UL1 TR000064) and the University of Colorado (UL1 TR001082). KGCS is a Lister Prize fellow and is supported by a Wellcome Trust Senior Investigator award (200871/Z/16/Z). EFM is a Wellcome-Beit prize fellow (10406/Z/14/A) supported by the Wellcome Trust and Beit Foundation (10406/Z/14/Z) and by the National Institutes for Health Research Biomedical Research Centre (Cambridge). LPX’s affiliation changed after completion of the manuscript and is now Département d'informatique et de recherche opérationnelle, Université de Montréal, Montréal, Canada and Mila, Quebec Institute for Learning Algorithms, Montréal, Canada