TEDDY study
TEDDY is a prospective cohort study with the primary objective of identifying environmental factors associated with increased risk of islet autoimmunity and type 1 diabetes; it includes three centres in the USA (Colorado, Georgia/Florida and Washington) and three in Europe (Finland, Germany and Sweden). Infants younger than 4.5 months and carrying type-1-diabetes-associated HLA alleles (HLA-DR, DQ) were eligible to participate. From 2004 to 2010, TEDDY screened >420,000 newborns and identified 21,589 children with high-risk HLA-DR/DQ genotypes. Of these, 8,677 (932 with first-degree family history of type 1 diabetes and 7,745 without such history) were enrolled in the prospective follow-up. Participants were seen and blood collected every 3 months up to 4 years of age, and every 6 months thereafter. Written informed consent was obtained from the parents. The study was approved by the ethical committees of the participating sites [13].
Study outcome
The study outcome is the appearance of confirmed persistent islet autoimmunity, defined as positive for at least one autoantibody (GAD65A, islet antigen-2 [IA-2A] or insulin autoantibody [IAA]) in both TEDDY core laboratories (Barbara Davis Center, Aurora, CO, USA and the University of Bristol, Bristol, UK) in two consecutive samples or in one sample in children who developed diabetes before a follow-up sample was available for autoantibody testing [14]. Families were notified of the child’s autoantibody results at their next study visit. The study endpoint is the development of type 1 diabetes as defined by American Diabetes Association criteria [15].
Study participants and design
Of the TEDDY participants, 355 had islet autoimmunity, and 86 of these had progressed to type 1 diabetes by July 2011 when the current study was designed. Twenty-four of the children developed type 1 diabetes within 6 months from the appearance of islet autoimmunity and were selected for our study (Fig. 1a). Two nested case–control studies were designed.
Sequencing study
This study investigated whether viral sequences were present in plasma samples at two time points: (1) the ‘last islet-autoantibody-negative sample’; and (2) the first islet-autoantibody-positive ‘seroconversion sample’ (Fig. 1b). Fourteen of the 24 rapid-onset patients had samples with sufficient volume available at both time points. For each of these 14 patients one control child was selected. Controls were children who participated in the TEDDY study but remained negative for all three diabetes-associated islet autoantibodies and for type 1 diabetes for at least 12 months after the respective event in patients. Controls were matched by clinical site and the family history of type 1 diabetes (yes/no) if they had plasma samples at the respective time points (ESM Table 1). Controls were randomly selected from the pool of potential controls after being matched and conditioned. Control samples used in the study were age-matched to the last islet-autoantibody-negative sample and seroconversion sample of rapid-onset patients.
Table 1 Infection and fever reported in the infection history study
Infection history study
This study investigated whether infections or fever episodes were associated with rapid progression to type 1 diabetes. All 24 rapid-onset patients, with three controls for each, were examined. Controls were selected by the same procedure as for the sequencing study. Three time periods were examined in the 96 children (Fig. 1b): (1) the autoantibody-negative period, from birth to the last islet-autoantibody-negative sample; (2) the seroconversion period, from the last islet-autoantibody-negative sample to the first islet-autoantibody-positive sample; and (3) the progression period, from the first islet-autoantibody-positive sample to the date of type 1 diabetes diagnosis.
Nucleic acid sequencing
Total nucleic acids were extracted from 250 μl plasma (NucliSENS easyMag; Biomerieux, Marcy l’Etoile, France) and nucleic acid quantity and quality assessed (2100 Bioanalyzer; Agilent Technologies, Santa Clara, CA, USA). Samples were subjected to reverse transcription using random octamer primers linked to an arbitrary 17-mer primer sequence and products were randomly amplified by PCR, applying the same octamer-linked 17-mer primer in conjunction with the 17-mer primer sequence without the octamer tail in a 1:9 ratio [16]. Products of >70 bp were selected by column purification (MinElute; Qiagen, Hilden, Germany) and ligated to bar-coded linkers for sequencing on the 454 Genome Sequencer FLX (454 Life Sciences, Branford, CT, USA) without fragmentation [17]. Raw sequence reads were trimmed to remove sequences derived from amplification primers and linkers, filtered to eliminate highly repetitive sequences, and assembled into contiguous sequences, which were, together with the remaining non-assembled singleton reads, compared with the non-redundant GenBank database at the nucleotide and translated amino acid levels.
Infection history data
Acute infections or illnesses experienced between study visits were collected with the corresponding dates by parents and provided to study personnel every 3 months, starting from age 6 months. Acute infections or illnesses were recorded using ICD-10 codes (www.who.int/classifications/icd/en/) and categorised as respiratory tract, gastrointestinal or other infection. Fever was documented using one of the relevant ICD-10 codes, R50, R50.9, R50.8, or R56, and was assessed when reported with or without infection.
Statistical analysis
All infections and fever reports before type 1 diabetes onset were analysed and then assessed according to the three periods of disease progression defined in the study design (Fig. 1b). Infections and fever were either counted as present/absent in each period and child irrespective of the actual number of episodes (Table 1), or the number of episodes in each period was scored and reported as the mean per child with SD (Table 2).
Table 2 Number of infections and fever reports per case or control in infection history study
Conditional logistic regression adjusted for maternal age at delivery was used to obtain the estimate of OR for the factor of interest. A p value <0.05 was considered significant. All reported p values are two-sided without adjustment for multiple testing. All statistical analyses were performed using SAS 9.2 (SAS Institute, Cary, NC, USA).