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OBJECTIVE To distinguish among predictors of seroconversion, progression to multiple autoantibodies and from multiple autoantibodies to type 1 diabetes in young children. RESEARCH DESIGN AND METHODS Genetically high-risk newborns (n = 8,502) were followed for a median of 11.2 years (interquartile range 9.3–12.6); 835 (9.8%) developed islet autoantibodies and 283 (3.3%) were diagnosed with type 1 diabetes. Predictors were examined using Cox proportional hazards models. RESULTS Predictors of seroconversion and progression differed, depending on the type of first appearing autoantibody. Male sex, Finnish residence, having a sibling with type 1 diabetes, the HLA DR4 allele, probiotic use before age 28 days, and single nucleotide polymorphism (SNP) rs689_A (INS) predicted seroconversion to IAA-first (having islet autoantibody to insulin as the first appearing autoantibody). Increased weight at 12 months and SNPs rs12708716_G (CLEC16A) and rs2292239_T (ERBB3) predicted GADA-first (autoantibody to GAD as the first appearing). For those having a father with type 1 diabetes, the SNPs rs2476601_A (PTPN22) and rs3184504_T (SH2B3) predicted both. Younger age at seroconversion predicted progression from single to multiple autoantibodies as well as progression to diabetes, except for those presenting with GADA-first. Family history of type 1 diabetes and the HLA DR4 allele predicted progression to multiple autoantibodies but not diabetes. Sex did not predict progression to multiple autoantibodies, but males progressed more slowly than females from multiple autoantibodies to diabetes. SKAP2 and MIR3681HG SNPs are newly reported to be significantly associated with progression from multiple autoantibodies to type 1 diabetes. CONCLUSIONS Predictors of IAA-first versus GADA-first autoimmunity differ from each other and from the predictors of progression to diabetes.

AIMS/HYPOTHESIS: Prognostic factors and characteristics of children diagnosed with type 1 diabetes before 6years of age were compared with those diagnosed at 6-13years of age in the TEDDY study. METHODS: Genetically high-risk children (n = 8502) were followed from birth for a median of 9.9years; 328 (3.9%) were diagnosed with type 1 diabetes. Cox proportional hazard model was used to assess the association of prognostic factors with the risk of type 1 diabetes in the two age groups. RESULTS: Children in the younger group tended to develop autoantibodies earlier than those in the older group did (mean age 1.5 vs 3.5years), especially insulin autoantibodies (IAA), which developed earlier than GAD autoantibodies (GADA). Children in the younger group also progressed to diabetes more rapidly than the children in the older group did (mean duration 1.9 vs 5.4 years). Children with autoantibodies first appearing against insulinoma antigen-2 (IA-2A) were found only in the older group. The significant diabetes risk associated with the country of origin in the younger group was no longer significant in the older group. Conversely, the diabetes risk associated with HLA genotypes was statistically significant also in the older group. Initial seroconversion after and before 2years of age was associated with decreased risk for diabetes diagnosis in children positive for multiple autoantibodies, but the diabetes risk did not decrease further with increasing age if initial seroconversion occurred after age 2. Diabetes risk associated with the minor alleles of rs1004446 (INS) was decreased in both the younger and older groups compared with other genotypes (HR 0.67). Diabetes risk was significantly increased with the minor alleles of rs2476601 (PTPN22) (HR 2.04 and 1.72), rs428595 (PPIL2) (HR 2.13 and 2.10), rs113306148 (PLEKHA1) (HR 2.34 and 2.21) and rs73043122 (RNASET2) (HR 2.31 and 2.54) (HR values represent the younger and older groups, respectively). CONCLUSIONS/INTERPRETATIONS: Diabetes at an early age is likely to be preceded by IAA autoantibodies and is a more aggressive form of the disease. Among older children, once multiple autoantibodies have been observed there does not seem to be any association between progression to diabetes and the age of the child or family history. TRIAL REGISTRATION: ClinicalTrials.gov identifier: NCT00279318.

BACKGROUND: Breastfeeding has beneficial effects on numerous health outcomes. OBJECTIVES: We investigated whether breastfeeding duration is associated with the development of early childhood autoimmunity, allergies, or obesity in a multinational prospective birth cohort. METHODS: Infants with genetic susceptibility for type 1 diabetes (n=8676) were followed for the development of autoantibodies to islet autoantigens or transglutaminase, allergies, and for anthropometric measurements to a median age of 8.3 y (IQR: 2.8-10.2y). Information on breastfeeding was collected at 3 mo of age and prospectively thereafter. A propensity score for longer breastfeeding was calculated from the variables that were likely to influence any or exclusive breastfeeding. The risks of developing autoimmunity or allergy were assessed using Cox proportional hazards models, and the risk of obesity at 5.5 y of age was assessed using logistic regression with adjustment by the propensity score. RESULTS: Breastfeeding duration was not associated with a lower risk of either islet or transglutaminase autoimmunity (any breastfeeding>6 mo, adjusted HR: 1.07; 95% CI: 0.96, 1.19; exclusive breastfeeding>3 mo, adjusted HR: 1.03; 95% CI: 0.92, 1.15). Exclusive breastfeeding>3 mo was associated with a decreased risk of seasonal allergic rhinitis (adjusted HR: 0.70; 95% CI: 0.53, 0.92; P6 mo and exclusive breastfeeding>3mo were associated with decreased risk of obesity (adjusted OR: 0.62; 95% CI: 0.47, 0.81; P&nbsp

To determine the long-term potential benefit of adjuvant chemotherapy in subgroups of high-risk stage I mucinous ovarian cancer patients using a predictive scoring algorithm.Data were collected from the National Cancer Database from 2004 to 2014. Based on demographic and surgical characteristics, a novel 10-year survival prognostic scoring system was developed using Cox regression.There were 2041 eligible patients with stage I mucinous ovarian cancer including 1362 (67%) with stage IA/IB disease, 598 (29%) with stage IC disease, and 81 (4%) with stage I disease not otherwise specified. Median age was 52 with a range of 13-90 years old. 737 (36%) patients were treated with adjuvant chemotherapy. Adjuvant chemotherapy was more common in patients with stage IC relative to stage IA/IB disease (69% vs. 21%, P 0.001) or with poorly-differentiated relative to well-differentiated tumors (69% vs. 23%, P 0.001). Unadjusted 10-year survival was 81% relative to 79% for patients treated with vs. without chemotherapy, respectively (P = 0.46). Patients were predicted to exhibit a low- or a high-risk of death using a multivariate Cox regression model with age, stage, grade, lymphovascular space invasion and ascites. Risk of death without vs. with adjuvant chemotherapy was similar in low-risk patients (88% vs. 84%; HR = 0.80, 95%CI = 0.56-1.15, P = 0.23) and worse in high-risk patients (51% vs. 74%; HR = 1.58, 95%CI: 1.05-2.38, P = 0.03) with stage I mucinous ovarian cancer.A predictive scoring algorithm may provide prognostic information on long-term survival and identify high-risk stage I mucinous ovarian cancer patients who might achieve a survival benefit from adjuvant chemotherapy.

Type 1 diabetes (T1D)—an autoimmune disease that destroys the pancreatic islets, resulting in insulin deficiency—often begins early in life when islet autoantibody appearance signals high risk1. However, clinical diabetes can follow in weeks or only after decades, and is very difficult to predict. Ketoacidosis at onset remains common2,3 and is most severe in the very young4,5, in whom it can be life threatening and difficult to treat6–9. Autoantibody surveillance programs effectively prevent most ketoacidosis10–12 but require frequent evaluations whose expense limits public health adoption13. Prevention therapies applied before onset, when greater islet mass remains, have rarely been feasible14 because individuals at greatest risk of impending T1D are difficult to identify. To remedy this, we sought accurate, cost-effective estimation of future T1D risk by developing a combined risk score incorporating both fixed and variable factors (genetic, clinical and immunological) in 7,798 high-risk children followed closely from birth for 9.3 years. Compared with autoantibodies alone, the combined model dramatically improves T1D prediction at ≥2 years of age over horizons up to 8 years of age (area under the receiver operating characteristic curve ≥ 0.9), doubles the estimated efficiency of population-based newborn screening to prevent ketoacidosis, and enables individualized risk estimates for better prevention trial selection. In a study of children with high genetic risk aged 2 years or older, a risk score integrating pancreatic islet autoantibodies, genetic factors and family history is highly predictive of type 1 diabetes in the subsequent 8 years.

OBJECTIVE: To measure anti-glycan antibodies (AGA) in cervical cancer (CC) patient sera and assess their effect on therapeutic outcome. PATIENTS AND METHODS: Serum AGA was measured in 276 stage II and 292 stage III Peruvian CC patients using a high content and throughput Luminex multiplex glycan array (LMGA) containing 177 glycans. Association with disease-specific survival (DSS) and progression free survival (PFS) were analyzed using Cox regression. RESULTS: AGAs were detected against 50 (28.3%) of the 177 glycans assayed. Of the 568 patients, 84.5% received external beam radiation therapy (EBRT) plus brachytherapy (BT), while 15.5% only received EBRT. For stage-matched patients (Stage III), receiving EBRT alone was significantly associated with worse survival (HR 6.4, p < 0.001). Stage III patients have significantly worse survival than Stage II patients after matching for treatment (HR = 2.8 in EBRT+BT treatment group). Furthermore, better PFS and DSS were observed in patients positive for AGA against multiple glycans belonging to the blood group H, Lewis, Ganglio, Isoglobo, lacto and sialylated tetrarose antigens (best HR = 0.49, best p = 0.0008). CONCLUSIONS: Better PFS and DSS are observed in cervical cancer patients that are positive for specific antiglycan antibodies and received brachytherapy.

Determine the utility of a clinical calculator to predict the benefit of chemotherapy in stage IA uterine papillary serous cancer (UPSC).Data were collected from NCDB from years 2010-2014. Based on demographic and surgical characteristics, a clinical score was developed using the random survival forest machine learning algorithm.Of 1,751 patients with stage IA UPSC, 1,012 (58%) received chemotherapy and 739 (42%) did not. Older age (HR 1.06), comorbidities (HR 1.31), larger tumor size (HR 1.27), lymphovascular invasion (HR 1.86), positive peritoneal cytology (HR 2.62), no pelvic lymph node dissection (HR 1.51), and no chemotherapy (HR 2.16) were associated with poorer prognosis. Compared to no chemotherapy, patients who underwent chemotherapy had a 5-year overall survival of 80% vs. 67%. To better delineate those who may derive more benefit from chemotherapy, we designed a clinical calculator capable of dividing patients into low, moderate, and high-risk groups with associated 5-year OS of 86%, 73%, and 53%, respectively. Using the calculator to assess the relative benefit of chemotherapy in each risk group, chemotherapy improved the 5-year OS in the high (42% to 64%; p 0.001) and moderate risk group (66% to 79%; p 0.001) but did not benefit the low risk group (84% to 87%; p = 0.29).Our results suggest a clinical calculator is useful for counseling and personalizing chemotherapy for stage IA UPSC.

Type 1 diabetes (T1D) is an autoimmune disease, characterized by the presence of autoantibodies to protein and non-protein antigens. Here we report the identification of specific anti-carbohydrate antibodies (ACAs) that are associated with pathogenesis and progression to T1D. We compare circulatory levels of ACAs against 202 glycans in a cross-sectional cohort of T1D patients (n = 278) and healthy controls (n = 298), as well as in a longitudinal cohort (n = 112). We identify 11 clusters of ACAs associated with glycan function class. Clusters enriched for aminoglycosides, blood group A and B antigens, glycolipids, ganglio-series, and O-linked glycans are associated with progression to T1D. ACAs against gentamicin and its related structures, G418 and sisomicin, are also associated with islet autoimmunity. ACAs improve discrimination of T1D status of individuals over a model with only clinical variables and are potential biomarkers for T1D.

We present here detailed protocols for the newly developed multiplex glycan bead array (MGBA) for the high throughput and high content analyses of various glycan binding proteins including anti-glycan antibodies. This platform takes advantage of the commercially available Luminex beads to construct glycan arrays that are easily customizable at will and anytime by researchers. The platform allows the simultaneous analyses of up to 500 glycans and 384 samples at a time. By using multiple arrays, a researcher can analyze thousands of glycans and tens of thousands of samples within a short period. The assay is highly sensitive, specific, reproducible, economic, and fast. Furthermore, the bead array platform is approved for use in clinical settings, speeding up the translation of laboratory discoveries into patient care.

Fungal infections are a major health problem that often begin in the gastrointestinal tract. Gut microbe interactions in early childhood are critical for proper immune responses, yet there is little known about the development of the fungal population from infancy into childhood. Here, as part of the TEDDY (The Environmental Determinants of Diabetes in the Young) study, we examine stool samples of 888 children from 3 to 48 months and find considerable differences between fungi and bacteria. The metagenomic relative abundance of fungi was extremely low but increased while weaning from milk and formula. Overall fungal diversity remained constant over time, in contrast with the increase in bacterial diversity. Fungal profiles had high temporal variation, but there was less variation from month-to-month in an individual than among different children of the same age. Fungal composition varied with geography, diet, and the use of probiotics. Multiple Candida spp. were at higher relative abundance in children than adults, while Malassezia and certain food-associated fungi were lower in children. There were only subtle fungal differences associated with the subset of children that developed islet autoimmunity or type 1 diabetes. Having proper fungal exposures may be crucial for children to establish appropriate responses to fungi and limit the risk of infection: the data here suggests those gastrointestinal exposures are limited and variable.

Development of complications in type 1 diabetes patients can be reduced by modifying risk factors. We used a cross-sectional cohort of 1646 patients diagnosed with type 1 diabetes (T1D) to develop a clinical risk score for diabetic peripheral neuropathy (DPN), autonomic neuropathy (AN), retinopathy (DR), and nephropathy (DN). Of these patients, 199 (12.1%) had DPN, 63 (3.8%) had AN, 244 (14.9%) had DR, and 88 (5.4%) had DN. We selected five variables to include in each of the four microvascular complications risk models: age, age of T1D diagnosis, duration of T1D, and average systolic blood pressure and HbA1C over the last three clinic visits. These variables were selected for their strong evidence of association with diabetic complications in the literature and because they are modifiable risk factors. We found the optimism-corrected R2 and Harrell’s C statistic were 0.39 and 0.87 for DPN, 0.24 and 0.86 for AN, 0.49 and 0.91 for DR, and 0.22 and 0.83 for DN, respectively. This tool was built to help inform patients of their current risk of microvascular complications and to motivate patients to control their HbA1c and systolic blood pressure in order to reduce their risk of these complications.

Viruses are implicated in autoimmune destruction of pancreatic islet beta cells, which results in insulin deficiency and type 1 diabetes (T1D)(1-4). Certain enteroviruses can infect beta cells in vitro(5), have been detected in the pancreatic islets of patients with T1D(6) and have shown an association with T1D in meta-analyses(4). However, establishing consistency in findings across studies has proven difficult. Obstacles to convincingly linking RNA viruses to islet autoimmunity may be attributed to rapid viral mutation rates, the cyclical periodicity of viruses(7) and the selection of variants with altered pathogenicity and ability to spread in populations. beta cells strongly express cell-surface coxsackie and adenovirus receptor (CXADR) genes, which can facilitate enterovirus infection(8). Studies of human pancreata and cultured islets have shown significant variation in enteroviral virulence to beta cells between serotypes and within the same serotype(9,10). In this large-scale study of known eukaryotic DNA and RNA viruses in stools from children, we evaluated fecally shed viruses in relation to islet autoimmunity and T1D. This study showed that prolonged enterovirus B rather than independent, short-duration enterovirus B infections may be involved in the development of islet autoimmunity, but not T1D, in some young children. Furthermore, we found that fewer early-life human mastadenovirus C infections, as well as CXADR rs6517774, independently correlated with islet autoimmunity.

OBJECTIVE Type 1 diabetes (T1D) is a highly heritable disease with much lower incidence but more adult-onset cases in the Chinese population. Although genome-wide association studies (GWAS) have identified >60 T1D loci in Caucasians, less is known in Asians. RESEARCH DESIGN AND METHODS We performed the first two-stage GWAS of T1D using 2,596 autoantibody-positive T1D case subjects and 5,082 control subjects in a Chinese Han population and evaluated the associations between the identified T1D risk loci and age and fasting C-peptide levels at T1D diagnosis. RESULTS We observed a high genetic correlation between children/adolescents and adult T1D case subjects (rg = 0.87), as well as subgroups of autoantibody status (rg ≥ 0.90). We identified four T1D risk loci reaching genome-wide significance in the Chinese Han population, including two novel loci, rs4320356 near BTN3A1 (odds ratio [OR] 1.26, P = 2.70 × 10−8) and rs3802604 in GATA3 (OR 1.24, P = 2.06 × 10−8), and two previously reported loci, rs1770 in MHC (OR 4.28, P = 2.25 × 10−232) and rs705699 in SUOX (OR 1.46, P = 7.48 × 10−20). Further fine mapping in the MHC region revealed five independent variants, including another novel locus, HLA-C position 275 (omnibus P = 9.78 × 10−12), specific to the Chinese population. Based on the identified eight variants, we achieved an area under the curve value of 0.86 (95% CI 0.85–0.88). By building a genetic risk score (GRS) with these variants, we observed that the higher GRS were associated with an earlier age of T1D diagnosis (P = 9.08 × 10−11) and lower fasting C-peptide levels (P = 7.19 × 10−3) in individuals newly diagnosed with T1D. CONCLUSIONS Our results extend current knowledge on genetic contributions to T1D risk. Further investigations in different populations are needed for genetic heterogeneity and subsequent precision medicine.

INTRODUCTION: Ovarian cancer is one of the most lethal neoplasms with 22,000 new cases and 14,000 deaths per year. Aggressive cytoreduction and chemotherapy have response rates as high as 80%. Most women are diagnosed with stage 3 disease or later and over 70% of women recur within 18 months. There is need for a test to determine prognosis of remission patients to allow for intervention and prolonged survival. METHODS AND MATERIALS: Women at Augusta University with ovarian cancer were enrolled between 2005 and 2015 (n=71). Blood was drawn at enrollment and follow-up visits. Patient serum collected at remission was analyzed using the SOMAscan array (n=35) to measure concentrations of 1129 proteins. The best 26 proteins were confirmed using Luminex assays in the same 35 patients and an additional 36 patients (n(total)=71) as orthogonal validation. The data from these proteins was combined with clinical factors using an elastic net multivariate model to find an optimized combination predictive of progression-free survival (PFS). RESULTS: Brain Derived Neurotrophic Factor and Platelet Derived Growth Factor molecules were significant for predicting PFS on univariate and multivariate analyses. The 26 proteins were combined with clinical factors using the elastic net algorithm. Ten components were determined to predict PFS (HR of 6.55, p-value 1.12 × 10(−6), CI 2.57 – 16.71). This model was named the Serous High Grade Ovarian Cancer (SHOC) Score. CONCLUSION: The SHOC score can predict patient prognosis in remission and will hopefully lead to early intervention and consolidation therapy strategies in remission patients destined to recur.

The risk for autoimmunity and subsequently type 1 diabetes is 10-fold higher in children with a first-degree family history of type 1 diabetes (FDR children) than in children in the general population (GP children). We analyzed children with high-risk HLA genotypes (n = 4,573) in the longitudinal TEDDY birth cohort to determine how much of the divergent risk is attributable to genetic enrichment in affected families. Enrichment for susceptible genotypes of multiple type 1 diabetes–associated genes and a novel risk gene, BTNL2, was identified in FDR children compared with GP children. After correction for genetic enrichment, the risks in the FDR and GP children converged but were not identical for multiple islet autoantibodies (hazard ratio [HR] 2.26 [95% CI 1.6–3.02]) and for diabetes (HR 2.92 [95% CI 2.05–4.16]). Convergence varied depending upon the degree of genetic susceptibility. Risks were similar in the highest genetic susceptibility group for multiple islet autoantibodies (14.3% vs .12.7%) and diabetes (4.8% vs. 4.1%) and were up to 5.8-fold divergent for children in the lowest genetic susceptibility group, decreasing incrementally in GP children but not in FDR children. These findings suggest that additional factors enriched within affected families preferentially increase the risk of autoimmunity and type 1 diabetes in lower genetic susceptibility strata.

Aims/hypothesis: Psychological stress has long been considered a possible trigger of type 1 diabetes, although prospective studies examining the link between psychological stress or life events during pregnancy and the child’s type 1 diabetes risk are rare. The objective of this study was to examine the association between life events during pregnancy and first-appearing islet autoantibodies (IA) in young children, conditioned by the child’s type 1 diabetes-related genetic risk. Methods: The IA status of 7317 genetically at-risk The Environmental Determinants of Diabetes in the Young (TEDDY) participants was assessed every 3months from 3months to 4years, and bi-annually thereafter. Reports of major life events during pregnancy were collected at study inception when the child was 3months of age and placed into one of six categories. Life events during pregnancy were examined for association with first-appearing insulin (IAA) (N = 222) or GAD (GADA) (N = 209) autoantibodies in the child until 6years of age using proportional hazard models. Relative excess risk due to interaction (RERI) by the child’s HLA-DR and SNP profile was estimated. Results: Overall, 65% of mothers reported a life event during pregnancy; disease/injury (25%), serious interpersonal (28%) and job-related (25%) life events were most common. The association of life events during pregnancy differed between IAA and GADA as the first-appearing autoantibody. Serious interpersonal life events correlated with increased risk of GADA-first only in HLA-DR3 children with the BACH2-T allele (HR 2.28, p < 0.0001), an additive interaction (RERI 1.87, p = 0.0004). Job-related life events were also associated with increased risk of GADA-first among HLA-DR3/4 children (HR 1.53, p = 0.04) independent of serious interpersonal life events (HR 1.90, p = 0.002), an additive interaction (RERI 1.19, p = 0.004). Job-related life events correlated with reduced risk of IAA-first (HR 0.55, p = 0.004), particularly in children with the BTNL2-GG allele (HR 0.48; 95% CI 0.31, 0.76). Conclusions/interpretation: Specific life events during pregnancy are differentially related to IAA vs GADA as first-appearing IA and interact with different HLA and non-HLA genetic factors, supporting the concept of different endotypes underlying type 1 diabetes. However, the mechanisms underlying these associations remain to be discovered. Life events may be markers for other yet-to-be-identified factors important to the development of first-appearing IA. Graphical abstract: [Figure not available: see fulltext.]

Gliomas are currently classified through integration of histology and mutation information, with new developments in DNA methylation classification. However, discrepancies exist amongst the major classification methods. This study sought to compare transcriptome-based classification to the established methods. RNAseq and microarray data were obtained for 1032 gliomas from the TCGA and 395 gliomas from REMBRANDT. Data were analyzed using unsupervised and supervised learning and other statistical methods. Global transcriptomic profiles defined four transcriptomic glioma subgroups with 91.4% concordance with the WHO-defined mutation subtypes. Using these subgroups, 168 genes were selected for the development of 1000 linear support vector classifiers (LSVC). Based on plurality voting of 1000 LSVC, the final ensemble classifier confidently classified all but 17 TCGA gliomas to one of the four transcriptomic profile (TP) groups. The classifier was validated using a gene expression microarray dataset. TP1 cases include IDHwt, glioblastoma high immune infiltration and cellular proliferation and poor survival prognosis. TP2a is characterized as IDHmut-codel, oligodendrogliomas with high tumor purity. TP2b tissue is mostly composed of neurons and few infiltrating malignant cells. TP3 exhibit increased NOTCH signaling, are astrocytoma and IDHmut-non-codel. TP groups are highly concordant with both WHO integrated histology and mutation classification as well as methylation-based classification of gliomas. Transcriptomic profiling provides a robust and objective method to classify gliomas with high agreement to the current WHO guidelines and may provide additional survival prediction to the current methods.

OBJECTIVE The first-appearing β-cell autoantibody has been shown to influence risk of type 1 diabetes (T1D). Here, we assessed the risk of autoantibody spreading to the second-appearing autoantibody and further progression to clinical disease in The Environmental Determinants of Diabetes in the Young (TEDDY) study. RESEARCH DESIGN AND METHODS Eligible children with increased HLA-DR-DQ genetic risk for T1D were followed quarterly from age 3 months up to 15 years for development of a single first-appearing autoantibody (GAD antibody [GADA], insulin autoantibody [IAA], or insulinoma antigen-2 autoantibody [IA-2A]) and subsequent development of a single second-appearing autoantibody and progression to T1D. Autoantibody positivity was defined as positivity for a specific autoantibody at two consecutive visits confirmed in two laboratories. Zinc transporter 8 autoantibody (ZnT8A) was measured in children who developed another autoantibody. RESULTS There were 608 children who developed a single first-appearing autoantibody (IAA, n = 282, or GADA, n = 326) with a median follow-up of 12.5 years from birth. The risk of a second-appearing autoantibody was independent of GADA versus IAA as a first-appearing autoantibody (adjusted hazard ratio [HR] 1.12; 95% CI 0.88–1.42; P = 0.36). Second-appearing GADA, IAA, IA-2A, or ZnT8A conferred an increased risk of T1D compared with children who remained positive for a single autoantibody, e.g., IAA or GADA second (adjusted HR 6.44; 95% CI 3.78–10.98), IA-2A second (adjusted HR 16.33; 95% CI 9.10–29.29; P < 0.0001), or ZnT8A second (adjusted HR 5.35; 95% CI 2.61–10.95; P < 0.0001). In children who developed a distinct second autoantibody, IA-2A (adjusted HR 3.08; 95% CI 2.04–4.65; P < 0.0001) conferred a greater risk of progression to T1D as compared with GADA or IAA. Additionally, both a younger initial age at seroconversion and shorter time to the development of the second-appearing autoantibody increased the risk for T1D. CONCLUSIONS The hierarchical order of distinct autoantibody spreading was independent of the first-appearing autoantibody type and was age-dependent and augmented the risk of progression to T1D.

Children’s plasma metabolome, especially lipidome, reflects gene regulation and dietary exposures, heralding the development of islet autoantibodies (IA) and type 1 diabetes (T1D). The Environmental Determinants of Diabetes in the Young (TEDDY) study enrolled 8,676 newborns by screening of HLA-DR-DQ genotypes at six clinical centers in four countries, profiled metabolome, and measured concentrations of ascorbic acid, 25-hydroxyvitamin D [25(OH)D], and erythrocyte membrane fatty acids following birth until IA seroconversion under a nested case-control design. We grouped children having an initial autoantibody only against insulin (IAA-first) or GAD (GADA-first) by unsupervised clustering of temporal lipidome, identifying a subgroup of children having early onset of each initial autoantibody, i.e., IAA-first by 12 months and GADA-first by 21 months, consistent with population-wide early seroconversion age. Differential analysis showed that infants having reduced plasma ascorbic acid and cholesterol experienced IAA-first earlier, while early onset of GADA-first was preceded by reduced sphingomyelins at infancy. Plasma 25(OH)D prior to either autoantibody was lower in T1D progressors compared with nonprogressors, with simultaneous lower diglycerides, lysophosphatidylcholines, triglycerides, and alanine before GADA-first. Plasma ascorbic acid and 25(OH)D at infancy were lower in HLA-DR3/DR4 children among IA case subjects but not in matched control subjects, implying gene expression dysregulation of circulating vitamins as latent signals for IA or T1D 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 aim of this study was to investigate survival differences between equivalent residual disease [complete gross resection (CGR), minimal residual disease (MRD), suboptimal] at the time of primary debulking surgery (PDS) and interval debulking surgery (IDS).The National Cancer Database was used to identify patients from 2010 to 2015 with stage IIIC/IV primary peritoneal or ovarian cancer who had residual disease recorded. Propensity score matching (PSM) was used to correct for differences in characteristics between the PDS and IDS groups.Of 8683 patients with advanced ovarian cancer, 4493 (52%), 2546 (29%), and 1644 (19%) had CGR, MRD, or suboptimal resection, respectively. From 2010 to 2015, the number of patients undergoing IDS increased 27% (pThe use of IDS continues to rise in the US, and is associated with improved surgical outcomes but not necessarily similar oncologic outcomes. There should be continued efforts to improve cytoreductive outcomes in women with advanced ovarian and peritoneal malignancies.

Children at increased genetic risk for type 1 diabetes (T1D) after environmental exposures may develop pancreatic islet autoantibodies (IA) at a very young age. Metabolic profile changes over time may imply responses to exposures and signal development of the first IA. Our present research in The Environmental Determinants of Diabetes in the Young (TEDDY) study aimed to identify metabolome-wide signals preceding the first IA against GAD (GADA-first) or against insulin (IAA-first). We profiled metabolomes by mass spectrometry from children’s plasma at 3-month intervals after birth until appearance of the first IA. A trajectory analysis discovered each first IA preceded by reduced amino acid proline and branched-chain amino acids (BCAAs), respectively. With independent time point analysis following birth, we discovered dehydroascorbic acid (DHAA) contributing to the risk of each first IA, and γ-aminobutyric acid (GABAs) associated with the first autoantibody against insulin (IAA-first). Methionine and alanine, compounds produced in BCAA metabolism and fatty acids, also preceded IA at different time points. Unsaturated triglycerides and phosphatidylethanolamines decreased in abundance before appearance of either autoantibody. Our findings suggest that IAA-first and GADA-first are heralded by different patterns of DHAA, GABA, multiple amino acids, and fatty acids, which may be important to primary prevention of T1D.

The development of the microbiome from infancy to childhood is dependent on a range of factors, with microbial-immune crosstalk during this time thought to be involved in the pathobiology of later life diseases(1-9) such as persistent islet autoimmunity and type 1 diabetes(10-12). However, to our knowledge, no studies have performed extensive characterization of the microbiome in early life in a large, multi-centre population. Here we analyse longitudinal stool samples from 903 children between 3 and 46 months of age by 16S rRNA gene sequencing (n = 12,005) and metagenomic sequencing (n = 10,867), as part of the The Environmental Determinants of Diabetes in the Young (TEDDY) study. We show that the developing gut microbiome undergoes three distinct phases of microbiome progression: a developmental phase (months 3-14), a transitional phase (months 15-30), and a stable phase (months 31-46). Receipt of breast milk, either exclusive or partial, was the most significant factor associated with the microbiome structure. Breastfeeding was associated with higher levels of Bifidobacterium species (B. breve and B. bifidum), and the cessation of breast milk resulted in faster maturation of the gut microbiome, as marked by the phylum Firmicutes. Birth mode was also significantly associated with the microbiome during the developmental phase, driven by higher levels of Bacteroides species (particularly B. fragilis) in infants delivered vaginally. Bacteroides was also associated with increased gut diversity and faster maturation, regardless of the birth mode. Environmental factors including geographical location and household exposures (such as siblings and furry pets) also represented important covariates. A nested case-control analysis revealed subtle associations between microbial taxonomy and the development of islet autoimmunity or type 1 diabetes. These data determine the structural and functional assembly of the microbiome in early life and provide a foundation for targeted mechanistic investigation into the consequences of microbial-immune crosstalk for long-term health.

OBJECTIVE: Cesarean section (C-section) is associated with various immune-mediated diseases in the offspring. We investigated the relationship between mode of delivery and celiac disease (CD) and CD autoimmunity (CDA) in a multinational birth cohort. METHODS: From 2004 to 2010, infants from the general population who tested positive for HLA DR3-DQ2 or DR4-DQ8 were enrolled in The Environmental Determinants for Diabetes in the Young (TEDDY) study. Children were annually screened for transglutaminase autoantibodies, if positive, they are retested after 3 to 6 months and those persistently positive defined as CDA. Associations of C-section with maternal (age, education level, parity, pre-pregnancy weight, diabetes, smoking, weight gain during pregnancy) and child characteristics (gestational age, birth weight) were examined by Fisher exact test or Wilcoxon rank-sum test. Hazard ratios (HRs) for CDA or CD were calculated by Cox proportional hazard regression models. RESULTS: Of 6087 analyzed singletons, 1600 (26%) were born by C-section (Germany 38%, United States 37%, Finland 18%, Sweden 16%), and the remaining were born vaginally without instrumental support; 979 (16%) had developed CDA and 343 (6%) developed CD. C-section was associated with lower risk for CDA (hazard ratio [HR] = 0.85; 95% confidence interval [CI] 0.73, 0.99 P = 0.032) and CD (HR = 0.75; 95% CI 0.58, 0.98; P = 0.034). After adjusting for country, sex, HLA-genotype, CD in family, maternal education, and breast-feeding duration, significance was lost for CDA (HR = 0.91; 95% CI 0.78, 1.06; P = 0.20) and CD (HR = 0.85; 95% CI 0.65, 1.11; P = 0.24). Presurgical ruptured membranes had no influence on CDA or CD development. CONCLUSION: C-section is not associated with increased risk for CDA or CD in the offspring.

OBJECTIVE To examine duration of breastfeeding and timing of complementary foods and risk of islet autoimmunity (IA). RESEARCH DESIGN AND METHODS The Environmental Determinants of Diabetes in the Young (TEDDY) study prospectively follows 8,676 children with increased genetic risk of type 1 diabetes (T1D) in the U.S., Finland, Germany, and Sweden. This study included 7,563 children with at least 9 months of follow-up. Blood samples were collected every 3 months from birth to evaluate IA, defined as persistent, confirmed positive antibodies to insulin (IAAs), GAD, or insulinoma antigen-2. We examined the associations between diet and the risk of IA using Cox regression models adjusted for country, T1D family history, HLA genotype, sex, and early probiotic exposure. Additionally, we investigated martingale residuals and log-rank statistics to determine cut points for ages of dietary exposures. RESULTS Later introduction of gluten was associated with increased risk of any IA and IAA. The hazard ratios (HRs) for every 1-month delay in gluten introduction were 1.05 (95% CI 1.01, 1.10; P = 0.02) and 1.08 (95% CI 1.00, 1.16; P = 0.04), respectively. Martingale residual analysis suggested that the age at gluten introduction could be grouped as 9 months. The risk of IA associated with introducing gluten before 4 months of age was lower (HR 0.68; 95% CI 0.47, 0.99), and the risk of IA associated with introducing it later than the age of 9 months was higher (HR 1.57; 95% CI 1.07, 2.31) than introduction between 4 and 9 months of age. CONCLUSIONS The timing of gluten-containing cereals and IA should be studied further.

β-cell autoantibodies against insulin (IAA), GAD65 (GADA) and IA-2 (IA-2A) precede onset of childhood type 1 diabetes (T1D). Incidence of the first appearing β-cell autoantibodies peaks at a young age and is patterned by T1D-associated genes, suggesting an early environmental influence. Here, we tested if gestational infections and interactions with child's human leukocyte antigen (HLA) and non-HLA genes affected the appearance of the first β-cell autoantibody. Singletons of mothers without diabetes (n = 7472) with T1D-associated HLA-DR-DQ genotypes were prospectively followed quarterly through the first 4 years of life, then semiannually until age 6 years, using standardized autoantibody analyses. Maternal infections during pregnancy were assessed via questionnaire 3–4.5 months post-delivery. Polymorphisms in twelve non-HLA genes associated with the first appearing β-cell autoantibodies were included in a Cox regression analysis. IAA predominated as the first appearing β-cell autoantibody in younger children (n = 226, median age at seroconversion 1.8 years) and GADA (n = 212; 3.2 years) in children aged ≥2 years. Gestational infections were not associated with the first appearing β-cell autoantibodies overall. However, gestational respiratory infections (G-RI) showed a consistent protective influence on IAA (HR 0.64, 95% CI 0.45–0.91) among CTLA4-(AG, GG) children (G-RI*CTLA4 interaction, p = 0.002). The predominant associations of HLA-DR-DQ 4-8/8-4 with IAA and HLA-DR-DQ 3-2/3-2 with GADA were not observed if a G-RI was reported (G-RI*HLA-DR-DQ interaction, p = 0.03). The role of G-RI may depend on offspring HLA and CTLA-4 alleles and supports a bidirectional trigger for IAA or GADA as a first appearing β-cell autoantibody in early life.

Aims/hypothesis: During the A/H1N1 2009 (A/California/04/2009) pandemic, mass vaccination with a squalene-containing vaccine, Pandemrix®, was performed in Sweden and Finland. The vaccination was found to cause narcolepsy in children and young adults with the HLA-DQ 6.2 haplotype. The aim of this study was to investigate if exposure to Pandemrix® similarly increased the risk of islet autoimmunity or type 1 diabetes. Methods: In The Environmental Determinants of Diabetes in the Young (TEDDY) study, children are followed prospectively for the development of islet autoimmunity and type 1 diabetes. In October 2009, when the mass vaccination began, 3401 children at risk for islet autoimmunity and type 1 diabetes were followed in Sweden and Finland. Vaccinations were recorded and autoantibodies against insulin, GAD65 and insulinoma-associated protein 2 were ascertained quarterly before the age of 4 years and semi-annually thereafter. Results: By 5 August 2010, 2413 of the 3401 (71%) children observed as at risk for an islet autoantibody or type 1 diabetes on 1 October 2009 had been vaccinated with Pandemrix®. By 31 July 2016, 232 children had at least one islet autoantibody before 10 years of age, 148 had multiple islet autoantibodies and 96 had developed type 1 diabetes. The risk of islet autoimmunity was not increased among vaccinated children. The HR (95% CI) for the appearance of at least one islet autoantibody was 0.75 (0.55, 1.03), at least two autoantibodies was 0.85 (0.57, 1.26) and type 1 diabetes was 0.67 (0.42, 1.07). In Finland, but not in Sweden, vaccinated children had a lower risk of islet autoimmunity (0.47 [0.29, 0.75]), multiple autoantibodies (0.50 [0.28, 0.90] ) and type 1 diabetes (0.38 [0.20, 0.72]) compared with those who did not receive Pandemrix®. The analyses were adjusted for confounding factors. Conclusions/interpretation: Children with an increased genetic risk for type 1 diabetes who received the Pandemrix® vaccine during the A/H1N1 2009 pandemic had no increased risk of islet autoimmunity, multiple islet autoantibodies or type 1 diabetes. In Finland, the vaccine was associated with a reduced risk of islet autoimmunity and type 1 diabetes.

We examined the association between plasma 25-hydroxyvitamin D [25(OH)D] concentration and islet autoimmunity (IA) and whether vitamin D gene polymorphisms modify the effect of 25(OH)D on IA risk. We followed 8,676 children at increased genetic risk of type 1 diabetes at six sites in the U.S. and Europe. We defined IA as positivity for at least one autoantibody (GADA, IAA, or IA-2A) on two or more visits. We conducted a risk set sampled nested case-control study of 376 IA case subjects and up to 3 control subjects per case subject. 25(OH)D concentration was measured on all samples prior to, and including, the first IA positive visit. Nine polymorphisms in VDR, CYP24A, CYP27B1, GC, and RXRA were analyzed as effect modifiers of 25(OH)D. Adjusting for HLA-DR-DQ and ancestry, higher childhood 25(OH)D was associated with lower IA risk (odds ratio = 0.93 for a 5 nmol/L difference; 95% CI 0.89, 0.97). Moreover, this association was modified by VDR rs7975232 (interaction P = 0.0072), where increased childhood 25(OH)D was associated with a decreasing IA risk based upon number of minor alleles: 0 (1.00; 0.93, 1.07), 1 (0.92; 0.89, 0.96), and 2 (0.86; 0.80, 0.92). Vitamin D and VDR may have a combined role in IA development in children at increased genetic risk for type 1 diabetes.

OBJECTIVE We tested the associations between genetic background and selected environmental exposures with respect to islet autoantibodies and type 1 diabetes. RESEARCH DESIGN AND METHODS Infants with HLA-DR high-risk genotypes were prospectively followed for diabetes-related autoantibodies. Single nucleotide polymorphisms (SNPs) came from the Illumina ImmunoChip and environmental exposure data were by parental report. Children were followed to age 6 years. RESULTS Insulin autoantibodies occurred earlier than GAD antibody (GADA) and then declined, while GADA incidence rose and remained constant (significant in HLA-DR4 but not in the DR3/3 children). The presence of SNPs rs2476601 (PTPN22) and rs2292239 (ERBB3) demonstrated increased risk of both autoantibodies to insulin (IAA) only and GADA only. SNP rs689 (INS) was protective of IAA only, but not of GADA only. The rs3757247 (BACH2) SNP demonstrated increased risk of GADA only. Male sex, father or sibling as the diabetic proband, introduction of probiotics under 28 days of age, and weight at age 12 months were associated with IAA only, but only father as the diabetic proband and weight at age 12 months were associated with GADA only. Mother as the diabetic proband was not a significant risk factor. CONCLUSIONS These results show clear differences in the initiation of autoimmunity according to genetic factors and environmental exposures that give rise to IAA or GADA as the first appearing indication of autoimmunity.

Lung cancer is one of the most prevalent cancers and has very poor treatment outcome. Biomarkers useful for screening and assessing early therapeutic response may significantly improve the therapeutic outcome but are still lacking. In this study, serum samples from 218 non-small cell lung cancer (NSCLC) patients, 34 small cell lung cancer (SCLC) patients and 171 matched healthy controls from China were analyzed for 11 proteins using the Luminex multiplex assay. Eight of the 11 proteins (OPN, SAA, CRP, CYFRA21.1, CEA, NSE, AGP and HGF) are significantly elevated in NSCLC and SCLC (p = 10-5-10-59). At the individual protein level, OPN has the best diagnostic value for NSCLC (AUC = 0.92), two acute phase proteins (SAA and CRP) have AUC near 0.83, while CEA and CYFRA21.1 also possess good AUC (0.81 and 0.77, respectively). More importantly, several three-protein combinations that contain OPN and CEA plus one of four proteins (CRP, SAA, CYFRA21.1 or NSE) have excellent diagnostic potential for NSCLC (AUC = 0.96). Four proteins (CYFRA21.1, CRP, SAA and NSE) are severely reduced and three proteins (OPN, MIF and NSE) are moderately decreased after platinum-based chemotherapy. Therapeutic response index (TRI) computed with 3-5 proteins suggests that approximately 25% of the NSCLC patients respond well to the therapy and TRI is significantly correlated with pre-treatment protein levels. Our data suggest that therapeutic response in NSCLC patients can be effectively measured but personalized biomarkers may be needed to monitor different subsets of patients.

Objectives To develop a transcriptomic signature capable of predicting overall survival (OS) for uterine serous carcinoma (USC). Methods RNAseq data for 58 USC patients were obtained from TCGA. Expression of 73 candidate genes was measured for 67 Augusta University (AU) samples using NanoString technology. Results Analysis of the TCGA RNAseq data identified 73 genes that individually predict prognosis for USC patients and an elastic net model with all 73 genes (USC73) distinguishes a good OS group with low USC73 score from a poor OS group with high USC73 score (5-year OS = 83.3% and 13.3% respectively, HR = 40.1; p = 3 × 10−8). This finding was validated in the independent AU cohort (HR = 4.3; p = 0.0004). The poor prognosis group with high USC73 score consists of 37.9% and 32.8% of patients in the TCGA and AU cohort respectively. USC73 score and pathologic stage independently contribute to OS and together provide the best prognostic value. Early stage, low USC73 patients have the best prognosis (5-year OS = 85.1% in the combined dataset), while advanced stage, high USC73 patients have the worst prognosis (5-year OS = 6.4%, HR = 30.5, p = 1.2 × 10−12). Consistent with the observed poor survival, primary cell cultures from high USC73 patients had higher proliferation rate and cell cycle progression; and high USC73 patients had lower rates of complete response to standard therapy. Conclusions The USC73 transcriptomic signature and stage independently predict OS of USC patients and the best prediction is achieved using USC73 and stage. USC73 may also serve as a therapeutic biomarker to guide patient care.

OBJECTIVE This study investigates two-phase growth patterns in early life and their association with development of islet autoimmunity (IA) and type 1 diabetes (T1D). RESEARCH DESIGN AND METHODS The Environmental Determinants of Diabetes in the Young (TEDDY) study followed 7,522 genetically high-risk children in Sweden, Finland, Germany, and the U.S. from birth for a median of 9.0 years (interquartile range 5.7–10.6) with available growth data. Of these, 761 (10.1%) children developed IA and 290 (3.9%) children were diagnosed with T1D. Bayesian two-phase piecewise linear mixed models with a random change point were used to estimate children’s individual growth trajectories. Cox proportional hazards models were used to assess the effects of associated growth parameters on the risks of IA and progression to T1D. RESULTS A higher rate of weight gain in infancy was associated with increased IA risk (hazard ratio [HR] 1.09 [95% CI 1.02, 1.17] per 1 kg/year). A height growth pattern with a lower rate in infancy (HR 0.79 [95% CI 0.70, 0.90] per 1 cm/year), higher rate in early childhood (HR 1.48 [95% CI 1.22, 1.79] per 1 cm/year), and younger age at the phase transition (HR 0.76 [95% CI 0.58, 0.99] per 1 month) was associated with increased risk of progression from IA to T1D. A higher rate of weight gain in early childhood was associated with increased risk of progression from IA to T1D (HR 2.57 [95% CI 1.34, 4.91] per 1 kg/year) in children with first-appearing GAD autoantibody only. CONCLUSIONS Growth patterns in early life better clarify how specific growth phases are associated with the development of T1D.

Implication By understanding Matrix Metalloprotease (MMP) dysregulation from a pan-cancer perspective, this study sheds light on the diagnostic potentials of MMPs across multiple neoplasms. Background MMPs are intriguing genes related to cancer disease progression, functional promotion of angiogenesis, invasion, metastasis, and avoidance of immune surveillance. Many studies have noted these genes are frequently upregulated in cancer. However, expression patterns of all MMPs and their diagnostic and prognostic potential have not been investigated in a pan-cancer perspective. Methods The Cancer Genome Atlas (TCGA) data were used to evaluate diagnostic and prognostic potential of 24 MMPs in fifteen different cancer types. Gene expression measured by RNA-seq was analyzed by differential expression, hierarchical clustering, and ROC analysis for individual genes and in combination. Results MMP1, MMP9, MMP10, MMP11, and MMP13 were almost universally upregulated across all cancers, with significant (p 2) in ten of fifteen cancers. MMP3, MMP7, MMP12 and MMP14) are significantly up-regulated in at least 10 cancer types. Interestingly, MMP2, MMP7, MMP23B, MMP27 and MMP28) are significantly down-regulated in seven to nine cancer types. Multiple MMPs possess AUC’s > 0.9 in more than one cancer. However, survival analyses suggest that the prognostic value of MMPs is limited to clear cell renal carcinoma. Conclusions Most MMPs have consistently increased gene expression across cancers, while several MMPs have consistently decreased expression in several cancer types. Many MMPs have diagnostic value individually or in combination, while the prognostic value of MMPs is restricted to one subtype of kidney cancer. Electronic supplementary material The online version of this article (10.1186/s12885-019-5768-0) contains supplementary material, which is available to authorized users.

OBJECTIVE Assessment of the predictive power of The Environmental Determinants of Diabetes in the Young (TEDDY)-identified risk factors for islet autoimmunity (IA), the type of autoantibody appearing first, and type 1 diabetes (T1D). RESEARCH DESIGN AND METHODS A total of 7,777 children were followed from birth to a median of 9.1 years of age for the development of islet autoantibodies and progression to T1D. Time-dependent sensitivity, specificity, and receiver operating characteristic (ROC) curves were calculated to provide estimates of their individual and collective ability to predict IA and T1D. RESULTS HLA genotype (DR3/4 vs. others) was the best predictor for IA (Youden’s index J = 0.117) and single nucleotide polymorphism rs2476601, in PTPN22, was the best predictor for insulin autoantibodies (IAA) appearing first (IAA-first) (J = 0.123). For GAD autoantibodies (GADA)-first, weight at 1 year was the best predictor (J = 0.114). In a multivariate model, the area under the ROC curve (AUC) was 0.678 (95% CI 0.655, 0.701), 0.707 (95% CI 0.676, 0.739), and 0.686 (95% CI 0.651, 0.722) for IA, IAA-first, and GADA-first, respectively, at 6 years. The AUC of the prediction model for T1D at 3 years after the appearance of multiple autoantibodies reached 0.706 (95% CI 0.649, 0.762). CONCLUSIONS Prediction modeling statistics are valuable tools, when applied in a time-until-event setting, to evaluate the ability of risk factors to discriminate between those who will and those who will not get disease. Although significantly associated with IA and T1D, the TEDDY risk factors individually contribute little to prediction. However, in combination, these factors increased IA and T1D prediction substantially.

Objective: The capacity to precisely predict progression to type 1 diabetes (T1D) in young children over a short time span is an unmet need. We sought to develop a risk algorithm to predict progression in children with high‐risk human leukocyte antigen (HLA) genes followed in The Environmental Determinants of Diabetes in the Young (TEDDY) study. Methods: Logistic regression and 4‐fold cross‐validation examined 38 candidate predictors of risk from clinical, immunologic, metabolic, and genetic data. TEDDY subjects with at least one persistent, confirmed autoantibody at age 3 were analyzed with progression to T1D by age 6 serving as the primary endpoint. The logistic regression prediction model was compared to two non‐statistical predictors, multiple autoantibody status, and presence of insulinoma‐associated‐2 autoantibodies (IA‐2A). Results: A total of 363 subjects had at least one autoantibody at age 3. Twenty‐one percent of subjects developed T1D by age 6. Logistic regression modeling identified 5 significant predictors ‐ IA‐2A status, hemoglobin A1c, body mass index Z‐score, single‐nucleotide polymorphism rs12708716_G, and a combination marker of autoantibody number plus fasting insulin level. The logistic model yielded a receiver operating characteristic area under the curve (AUC) of 0.80, higher than the two other predictors; however, the differences in AUC, sensitivity, and specificity were small across models. Conclusions: This study highlights the application of precision medicine techniques to predict progression to diabetes over a 3‐year window in TEDDY subjects. This multifaceted model provides preliminary improvement in prediction over simpler prediction tools. Additional tools are needed to maximize the predictive value of these approaches.

Progression to clinical type 1 diabetes varies among children who develop β-cell autoantibodies. Differences in autoantibody patterns could relate to disease progression and etiology. Here we modeled complex longitudinal autoantibody profiles by using a novel wavelet-based algorithm. We identified clusters of similar profiles associated with various types of progression among 600 children from The Environmental Determinants of Diabetes in the Young (TEDDY) birth cohort study; these children developed persistent insulin autoantibodies (IAA), GAD autoantibodies (GADA), insulinoma-associated antigen 2 autoantibodies (IA-2A), or a combination of these, and they were followed up prospectively at 3- to 6-month intervals (median follow-up 6.5 years). Children who developed multiple autoantibody types (n = 370) were clustered, and progression from seroconversion to clinical diabetes within 5 years ranged between clusters from 6% (95% CI 0, 17.4) to 84% (59.2, 93.6). Children who seroconverted early in life (median age

Objective ZnT8-specific CD8+ T cells in human type 1 diabetes (T1D) have been reported recently, although the results from different laboratories are inconsistent. We aimed to characterize these ZnT8 specific CD8+ T cells and validate assays to screen peptide libraries. Methods We screened HLA-A2-restricted T cell candidate peptides of ZnT8 with different methods including computer algorithms, MHC-peptide binding and dissociation assays in T2 cell line, identification in HLA-A2 transgenic (Tg) mice and in vivo CTL assays. Then ELISpot assay was used to measure peptide-reactive T cell responses in 49 HLA-A2-restricted T1D patients. Results We demonstrated that ZnT8 107–116(115) , ZnT8 110–118 , and ZnT8 177–186 were novel HLA-A*0201-restricted CTL epitopes in T1D patients. ZnT8 107–116(115) , ZnT8 115–123 , ZnT8 153–161 , ZnT8 177–186 and ZnT8 291–300 represent potentially major biomarkers for T1D. T cell responses against these epitopes showed different distributions between recently diagnosed and long-standing patients. Furthermore, they displayed discriminating performance among different ethnicities. We also compared the performance of the epitope identification strategies used herein. The epitopes which exhibited strong immunogenicity in HLA-A2 Tg mice were also well recognized by T1D patients. Conclusions The differences in autoimmune T cell responses among T1D individuals may open new avenues toward T1D prediction and prevention. It also provides efficient strategies for immune intervention.

Background Around 0.3% of newborns will develop autoimmunity to pancreatic beta cells in childhood and subsequently develop type 1 diabetes before adulthood. Primary prevention of type 1 diabetes will require early intervention in genetically at-risk infants. The objective of this study was to determine to what extent genetic scores (two previous genetic scores and a merged genetic score) can improve the prediction of type 1 diabetes. Methods and findings The Environmental Determinants of Diabetes in the Young (TEDDY) study followed genetically at-risk children at 3- to 6-monthly intervals from birth for the development of islet autoantibodies and type 1 diabetes. Infants were enrolled between 1 September 2004 and 28 February 2010 and monitored until 31 May 2016. The risk (positive predictive value) for developing multiple islet autoantibodies (pre-symptomatic type 1 diabetes) and type 1 diabetes was determined in 4,543 children who had no first-degree relatives with type 1 diabetes and either a heterozygous HLA DR3 and DR4-DQ8 risk genotype or a homozygous DR4-DQ8 genotype, and in 3,498 of these children in whom genetic scores were calculated from 41 single nucleotide polymorphisms. In the children with the HLA risk genotypes, risk for developing multiple islet autoantibodies was 5.8% (95% CI 5.0%–6.6%) by age 6 years, and risk for diabetes by age 10 years was 3.7% (95% CI 3.0%–4.4%). Risk for developing multiple islet autoantibodies was 11.0% (95% CI 8.7%–13.3%) in children with a merged genetic score of >14.4 (upper quartile; n = 907) compared to 4.1% (95% CI 3.3%–4.9%, P < 0.001) in children with a genetic score of ≤14.4 (n = 2,591). Risk for developing diabetes by age 10 years was 7.6% (95% CI 5.3%–9.9%) in children with a merged score of >14.4 compared with 2.7% (95% CI 1.9%–3.6%) in children with a score of ≤14.4 (P < 0.001). Of 173 children with multiple islet autoantibodies by age 6 years and 107 children with diabetes by age 10 years, 82 (sensitivity, 47.4%; 95% CI 40.1%–54.8%) and 52 (sensitivity, 48.6%, 95% CI 39.3%–60.0%), respectively, had a score >14.4. Scores were higher in European versus US children (P = 0.003). In children with a merged score of >14.4, risk for multiple islet autoantibodies was similar and consistently >10% in Europe and in the US; risk was greater in males than in females (P = 0.01). Limitations of the study include that the genetic scores were originally developed from case–control studies of clinical diabetes in individuals of mainly European decent. It is, therefore, possible that it may not be suitable to all populations. Conclusions A type 1 diabetes genetic score identified infants without family history of type 1 diabetes who had a greater than 10% risk for pre-symptomatic type 1 diabetes, and a nearly 2-fold higher risk than children identified by high-risk HLA genotypes alone. This finding extends the possibilities for enrolling children into type 1 diabetes primary prevention trials., Anette-Gabriele Ziegler and colleagues report their novel genetic risk score for identifying infants with a high risk of developing type 1 diabetes., Author summary Why was this study done? Prevention of childhood diseases such as type 1 diabetes is of medical importance. Prevention of type 1 diabetes might be best achieved by intervention prior to the development of islet autoantibodies, which define a pre-symptomatic disease stage. Early intervention requires tools such as measures of genetic risk that identify future cases. Risk for type 1 diabetes in the absence of a family history is currently identified by HLA genotyping, with maximum identified risk reaching around 5%. Genetic scores derived from multiple risk loci may improve risk stratification for pre-symptomatic type 1 diabetes. What did the researchers do and find? Two previously proposed genetic scores for type 1 diabetes risk were calculated for over 3,000 children without a family history of type 1 diabetes but with 1 of the 2 highest-risk HLA genotypes (heterozygous DR3 and DR4-DQ8 or homozygous DR4-DQ8) participating in the TEDDY cohort study, which prospectively follows children from birth for the development of islet autoantibodies and diabetes. We found that both of the genetic scores, and a merged genetic score that combined the features of both, stratified the risk for islet autoantibodies and diabetes in the children. The upper quartile of the merged genetic score was associated with a >10% risk for the pre-symptomatic stage of multiple islet autoantibodies, and almost half the children who developed pre-symptomatic or symptomatic diabetes were identified by this score. What do these findings mean? Combining genetic information from multiple risk loci can improve the prediction of diseases such as type 1 diabetes. A genetic risk score model is proposed that could be used to recruit infants into early type 1 diabetes primary prevention trials. The model provides a new paradigm for genetic screening and selection of at-risk infants that, together with family history and HLA genotyping, could identify up to 25% of future childhood cases of type 1 diabetes from less than 1% of newborns.

Glycan-binding proteins (GBPs) play critical roles in diverse cellular functions such as cell adhesion, signal transduction and immune response. Studies of the interaction between GBPs and glycans have been hampered by the availability of high throughput and high-content technologies. Here we report multiplex glycan bead array (MGBA) that allows simultaneous analyses of 384 samples and up to 500 glycans in a single assay. The specificity, sensitivity and reproducibility of MGBA are evaluated using 39 plant lectins, 13 recombinant anti-glycan antibodies, and mammalian GBPs. We demonstrate the utility of this platform by the analyses of natural anti-glycan IgM and IgG antibodies in 961 human serum samples and the discovery of anti-glycan antibody biomarkers for ovarian cancer. Our data indicate that the MGBA platform is particularly suited for large population-based studies that require the analyses of large numbers of samples and glycans., The low throughput or content of current methods for the analysis of glycans-glycan binding proteins (GBPs) interactions hampers their clinical applications. Here, the authors conjugate synthesized glycans to Luminex beads to detect GBPs and apply it for the discovery of ovarian cancer biomarkers.

BackgroundProgression time from islet autoimmunity to clinical type 1 diabetes is highly variable and the extent that genetic factors contribute is unknown.MethodsIn 341 islet autoantibody-positive children with the human leucocyte antigen (HLA) DR3/DR4-DQ8 or the HLA DR4-DQ8/DR4-DQ8 genotype from the prospective TEDDY (The Environmental Determinants of Diabetes in the Young) study, we investigated whether a genetic risk score that had previously been shown to predict islet autoimmunity is also associated with disease progression.ResultsIslet autoantibody-positive children with a genetic risk score in the lowest quartile had a slower progression from single to multiple autoantibodies (p=0.018), from single autoantibodies to diabetes (p=0.004), and by trend from multiple islet autoantibodies to diabetes (p=0.06). In a Cox proportional hazards analysis, faster progression was associated with an increased genetic risk score independently of HLA genotype (HR for progression from multiple autoantibodies to type 1 diabetes, 1.27, 95% CI 1.02 to 1.58 per unit increase), an earlier age of islet autoantibody development (HR, 0.68, 95% CI 0.58 to 0.81 per year increase in age) and female sex (HR, 1.94, 95% CI 1.28 to 2.93).ConclusionsGenetic risk scores may be used to identify islet autoantibody-positive children with high-risk HLA genotypes who have a slow rate of progression to subsequent stages of autoimmunity and type 1 diabetes.

Soluble cytokine receptors may play an important role in development of microalbuminuria (MA) in type-1 diabetes (T1D). In this study, we measured 12 soluble receptors and ligands from TNF-α/IL6/IL2 pathways in T1D patients with MA (n = 89) and T1D patients without MA (n = 483) participating in the PAGODA study. Twelve proteins in the sera from T1D patients with and without MA were measured using multiplex Luminex assays. Ten serum proteins (sTNFR1, sTNFR2, sIL2Rα, MMP2, sgp130, sVCAM1, sIL6R, SAA, CRP, and sICAM1) were significantly elevated in T1D patients with MA. After adjusting for age, duration of diabetes, and sex in logistic regression, association remained significant for seven proteins. MA is associated with increasing concentrations of all 10 proteins, with the strongest associations observed for sTNFR1 (OR = 108.3, P

Islet autoantibodies, in addition to elevated blood glucose, define type 1 diabetes. These autoantibodies are detectable for a variable period of time before diabetes onset. Thus, the occurrence of islet autoantibodies is associated with the beginning of the disease process. The age at, and order in, which autoantibodies appear may be associated with different genetic backgrounds or environmental exposures, or both.Infants with HLA-DR high-risk genotypes (DR3/4, DR4/4, DR4/8 and DR3/3) were enrolled and prospectively followed with standardised autoantibody assessments quarterly throughout the first 4 years of life and then semi-annually thereafter.Autoantibodies appeared in 549/8,503 (6.5%) children during 34,091 person-years of follow-up. Autoantibodies at 3 (0.1%) and 6 (0.2%) months of age were rare. Of the 549, 43.7% had islet autoantibodies to insulin (IAA) only, 37.7% had glutamic acid decarboxylase autoantibodies (GADA) only, 13.8% had both GADA and IAA only, 1.6% had insulinoma antigen-2 only and 3.1% had other combinations. The incidence of IAA only peaked within the first year of life and declined over the following 5 years, but GADA only increased until the second year and remained relatively constant. GADA only were more common than IAA only in HLA-DR3/3 children but less common in HLA-DR4/8 children.Islet autoantibodies can occur very early in life and the order of appearance was related to HLA-DR-DQ genotype.

Importance Evidence is lacking regarding the consequences of antibiotic use in early life and the risk of certain autoimmune diseases. Objective To test the association between early-life antibiotic use and islet or celiac disease (CD) autoimmunity in genetically at-risk children prospectively followed up for type 1 diabetes (T1D) or CD. Design, Setting, and Participants HLA-genotyped newborns from Finland, Germany, Sweden, and the United States were enrolled in the prospective birth cohort of The Environmental Determinants of Diabetes in the Young (TEDDY) study between November 20, 2004, and July 8, 2010. The dates of analysis were November 20, 2004, to August 31, 2014. Individuals from the general population and those having a first-degree relative with T1D were enrolled if they had 1 of 9 HLA genotypes associated with a risk for T1D. Exposures Parental reports of the most common antibiotics (cephalosporins, penicillins, and macrolides) used between age 3 months and age 4 years were recorded prospectively. Main Outcomes and Measures Islet autoimmunity and CD autoimmunity were defined as being positive for islet or tissue transglutaminase autoantibodies at 2 consecutive clinic visits at least 3 months apart. Hazard ratios and 95% CIs calculated from Cox proportional hazards regression models were used to assess the relationship between antibiotic use in early life before seroconversion and the development of autoimmunity. Results Participants were 8495 children (49.0% female) and 6558 children (48.7% female) enrolled in the TEDDY study who were tested for islet and tissue transglutaminase autoantibodies, respectively. Exposure to and frequency of use of any antibiotic assessed in this study in early life or before seroconversion did not influence the risk of developing islet autoimmunity or CD autoimmunity. Cumulative use of any antibiotic during the first 4 years of life was not associated with the appearance of any autoantibody (hazard ratio [HR], 0.98; 95% CI, 0.95-1.01), multiple islet autoantibodies (HR, 0.99; 95% CI, 0.95-1.03), or the transglutaminase autoantibody (HR, 1.00; 95% CI, 0.98-1.02). Conclusions and Relevance The use of the most prescribed antibiotics during the first 4 years of life, regardless of geographic region, was not associated with the development of autoimmunity for T1D or CD. These results suggest that a risk of islet or tissue transglutaminase autoimmunity need not influence the recommendations for clinical use of antibiotics in young children at risk for T1D or CD.

Type 1 diabetes (T1D) is an autoimmune disease that targets pancreatic islet beta cells and incorporates genetic and environmental factors(1), including complex genetic elements(2), patient exposures(3) and the gut microbiome(4). Viral infections(5) and broader gut dysbioses(6) have been identified as potential causes or contributing factors; however, human studies have not yet identified microbial compositional or functional triggers that are predictive of islet autoimmunity or T1D. Here we analyse 10,913 metagenomes in stool samples from 783 mostly white, non-Hispanic children. The samples were collected monthly from three months of age until the clinical end point (islet autoimmunity or T1D) in the The Environmental Determinants of Diabetes in the Young (TEDDY) study, to characterize the natural history of the early gut microbiome in connection to islet autoimmunity, T1D diagnosis, and other common early life events such as antibiotic treatments and probiotics. The microbiomes of control children contained more genes that were related to fermentation and the biosynthesis of short-chain fatty acids, but these were not consistently associated with particular taxa across geographically diverse clinical centres, suggesting that microbial factors associated with T1D are taxonomically diffuse but functionally more coherent. When we investigated the broader establishment and development of the infant microbiome, both taxonomic and functional profiles were dynamic and highly individualized, and dominated in the first year of life by one of three largely exclusive Bifidobacterium species (B. bifidum, B. breve or B. longum) or by the phylum Proteobacteria. In particular, the strain-specific carriage of genes for the utilization of human milk oligosaccharide within a subset of B. longum was present specifically in breast-fed infants. These analyses of TEDDY gut metagenomes provide, to our knowledge, the largest and most detailed longitudinal functional profile of the developing gut microbiome in relation to islet autoimmunity, T1D and other early childhood events. Together with existing evidence from human cohorts(7,8) and a T1D mouse model(9), these data support the protective effects of short-chain fatty acids in early-onset human T1D.

BACKGROUND AND OBJECTIVES: Few birth cohorts have prospectively followed development of type 1 diabetes (T1D) and celiac disease (CD) autoimmunities to determine timing, extent of co-occurrence, and associated genetic and demographic factors. METHODS: In this prospective birth cohort study, 8676 children at high genetic risk of both diseases were enrolled and 5891 analyzed in median follow-up of 66 months. Along with demographic factors and HLA-DR-DQ, genotypes for HLA-DPB1 and 5 non-HLA loci conferring risk of both T1D and CD were analyzed. RESULTS: Development of persistent islet autoantibodies (IAs) and tissue transglutaminase autoantibodies (tTGAs), as well as each clinical disease, was evaluated quarterly from 3 to 48 months of age and semiannually thereafter. IAs alone appeared in 367, tTGAs alone in 808, and both in 90 children. Co-occurrence significantly exceeded the expected rate. IAs usually, but not always, appeared earlier than tTGAs. IAs preceding tTGAs was associated with increasing risk of tTGAs (hazard ratio [HR]: 1.48; 95% confidence interval [CI]: 1.15–1.91). After adjusting for country, sex, family history, and all other genetic loci, significantly greater co-occurrence was observed in children with a T1D family history (HR: 2.80), HLA-DR3/4 (HR: 1.94) and single-nucleotide polymorphism rs3184504 at SH2B3 (HR: 1.53). However, observed co-occurrence was not fully accounted for by all analyzed factors. CONCLUSIONS: In early childhood, T1D autoimmunity usually precedes CD autoimmunity. Preceding IAs significantly increases the risk of subsequent tTGAs. Co-occurrence is greater than explained by demographic factors and extensive genetic risk loci, indicating that shared environmental or pathophysiological mechanisms may contribute to the increased risk.

Aims: The onset of clinical type 1 diabetes (T1D) is preceded by the occurrence of disease-specific autoantibodies. The level of autoantibody titers is known to be associated with progression time from the first emergence of autoantibodies to the onset of clinical symptoms, but detailed analyses of this complex relationship are lacking. We aimed to fill this gap by applying advanced statistical models. Methods: We investigated data of 613 children from the prospective TEDDY study who were persistent positive for IAA, GADA and/or IA2A autoantibodies. We used a novel approach of Bayesian joint modeling of longitudinal and survival data to assess the potentially time- and covariate-dependent association between the longitudinal autoantibody titers and progression time to T1D. Results: For all autoantibodies we observed a positive association between the titers and the T1D progression risk. This association was estimated as time-constant for IA2A, but decreased over time for IAA and GADA. For example the hazard ratio [95% credibility interval] for IAA (per transformed unit) was 3.38 [2.66, 4.38] at 6 months after seroconversion, and 2.02 [1.55, 2.68] at 36 months after seroconversion. Conclusions: These findings indicate that T1D progression risk stratification based on autoantibody titers should focus on time points early after seroconversion. Joint modeling techniques allow for new insights into these associations.

Respiratory infections and onset of islet autoimmunity are reported to correlate positively in two small prospective studies. The Environmental Determinants of Diabetes in the Young (TEDDY) study is the largest prospective international cohort study on the environmental determinants of type 1 diabetes that regularly monitors both clinical infections and islet autoantibodies. The aim was to confirm the influence of reported respiratory infections and to further characterise the temporal relationship with autoantibody seroconversion. During the years 2004–2009, 8676 newborn babies with HLA genotypes conferring an increased risk of type 1 diabetes were enrolled at 3 months of age to participate in a 15 year follow-up. In the present study, the association between parent-reported respiratory infections and islet autoantibodies at 3 month intervals up to 4 years of age was evaluated in 7869 children. Time-dependent proportional hazard models were used to assess how the timing of respiratory infections related to persistent confirmed islet autoimmunity, defined as autoantibody positivity against insulin, GAD and/or insulinoma antigen-2, concordant at two reference laboratories on two or more consecutive visits. In total, 87,327 parent-reported respiratory infectious episodes were recorded while the children were under study surveillance for islet autoimmunity, and 454 children seroconverted. The number of respiratory infections occurring in a 9 month period was associated with the subsequent risk of autoimmunity (p

BACKGROUND & AIMS: Little is known about the pathogenic mechanisms of gluten immunogenicity in patients with celiac disease. We studied temporal associations between infections and the development of celiac disease autoimmunity, and examined effects of HLA alleles, rotavirus vaccination status, and infant feeding. METHODS: We monitored 6327 children in the United States and Europe carrying HLA risk genotypes for celiac disease from 1 to 4 years of age for presence of tissue transglutaminase autoantibodies (the definition of celiac disease autoimmunity), until March 31, 2015. Parental reports of gastrointestinal and respiratory infections were collected every third month from birth. We analyzed time-varying relationships among reported infections, rotavirus vaccination status, time to first introduction of gluten, breastfeeding, and risk of celiac disease autoimmunity using proportional hazard models. RESULTS: We identified 13,881 gastrointestinal infectious episodes (GIE) and 79,816 respiratory infectious episodes. During the follow-up period, 732 of 6327 (11.6%) children developed celiac disease autoimmunity. A GIE increased the risk of celiac disease autoimmunity within the following 3 months by 33% (hazard ratio [HR], 1.33; 95% confidence interval [CI], 1.11-1.59). This risk increased 2-fold among children born in winter and introduced to gluten before age 6 months (HR, 2.08; 95% CI, 1.46-2.98), and increased 10-fold among children without HLA-DQ2 alleles and breastfed for fewer than 4 months (HR, 9.76; 95% CI, 3.87-24.8). Risk of celiac disease autoimmunity was reduced in children vaccinated against rotavirus and introduced to gluten before age 6 months (HR, 0.57; 95% CI, 0.36-0.88). CONCLUSIONS: Gastrointestinal infections increase the risk of celiac disease autoimmunity in children with genetic susceptibility to this autoimmune disorder. The risk is modified by HLA genotype, infant gluten consumption, breastfeeding, and rotavirus vaccination, indicating complex interactions among infections, genetic factors, and diet in the etiology of celiac disease in early childhood.

OBJECTIVE Studies on the introduction of infant formulas and its effect on the risk of islet autoimmunity and type 1 diabetes (T1D) have yielded inconsistent results. We investigated whether the introduction of formula based on hydrolyzed cow’s milk as the first formula is associated with reduced islet autoimmunity risk in a large prospective cohort. RESEARCH DESIGN AND METHODS The Environmental Determinants of Diabetes in the Young (TEDDY) study prospectively monitors 8,676 children at increased genetic risk for T1D. Autoantibodies to insulin, GAD65, and IA2 were measured regularly to define islet autoimmunity. Information on formula feeding was collected by questionnaires at 3 months of age. RESULTS In survival analyses, after adjustment for family history with T1D, HLA genotype, sex, country, delivery mode, breast-feeding ≥3 months, and seasonality of birth, we observed no significant association with islet autoimmunity in infants who received extensively hydrolyzed compared with nonhydrolyzed cow’s milk–based formula as the first formula during the first 3 months (adjusted hazard ratio 1.38 [95% CI 0.95; 2.01]), and a significantly increased risk for extensively hydrolyzed formula introduced during the first 7 days (adjusted hazard ratio 1.57 [1.04; 2.38]). Using a partially hydrolyzed or other formula as the first formula, or no formula, was not associated with islet autoimmunity risk. CONCLUSIONS These results add to the existing evidence that islet autoimmunity risk is not reduced, and may be increased, by using hydrolyzed compared with nonhydrolyzed cow’s milk–based infant formula as the first formula in infants at increased genetic risk for T1D.

Perinatal exposure to nutrients and dietary components may affect the risk for coeliac disease (CD). We investigated the association between maternal use of vitamin D, n-3 fatty acids (FA) and Fe supplements during pregnancy and risk for CD autoimmunity (CDA) and CD in the offspring. Children at increased genetic risk were prospectively followed from birth in The Environmental Determinants of Diabetes in the Young (TEDDY) study. CDA was defined as having persistently positive tissue transglutaminase autoantibodies (tTGA). Diagnosis of CD was either biopsy-confirmed or considered likely if having persistently elevated levels of tTGA>100 AU. Of 6627 enrolled children, 1136 developed CDA at a median 3·1 years of age (range 0·9–10) and 409 developed CD at a median 3·9 years of age (range 1·2–11). Use of supplements containing vitamin D, n-3 FA and Fe was recalled by 66, 17 and 94 % of mothers, respectively, at 3–4 months postpartum. The mean cumulative intake over the entire pregnancy was 2014 μg vitamin D (sd 2045 μg), 111 g n-3 FA (sd 303 g) and 8806 mg Fe (sd 7017 mg). After adjusting for country, child’s human leucocyte antigen genotype, sex, family history of CD, any breast-feeding duration and household crowding, Cox’s proportional hazard ratios did not suggest a statistically significant association between the intake of vitamin D, n-3 FA or Fe, and risk for CDA or CD. Dietary supplementation during pregnancy may help boost nutrient intake, but it is not likely to modify the risk for the disease in the offspring.