Type 1 diabetes (T1D) associated genetic factors affect risk of islet autoantibodies (IA), but non-genetic factors show conflicting associations. Mechanistic interactions may play a role. Under a sufficient-component causal framework, we used a rule-based discovery method to investigate if genetic factors, early environment and first appearing IA (IAA or GADA) act synergistically to mark different disease mechanisms.
TEDDY children (n=7512) were followed until age 6 years for IA development (n=518). Rules differentiating IAA-first (n=258) from GADA-first (n=243) were identified by a rule discovery algorithm (RuleFit) and examined in logistic regression models. Rule components were assessed for additive interaction on IAA-first and GADA-first separately using Relative Excess Risk due to Interaction (RERI) calculated from Cox regression models.
Here we show 2 of the 5 top rules, the first involving the child having CTLA4-AA (rs231775) and mother with a gestational respiratory but no skin infection (rule1, OR=5.6, 95% CI=2.6-12.0, p<0.0001); the second involving child having BACH2-T (rs3757247) and sufficient weight gain by age 3 months (rule2, OR=0.47, 95% CI=0.30-0.72, p<0.0001). Each differentiated IAA from GADA, and rule components showed interaction on absolute risk of IAA-first or GADA-first.
K.F. Lynch: None. T. Feng: None. X. Qian: None. W. Hagopian: Research Support; Self; Novo Nordisk A/S. Å. Lernmark: None. A. Ziegler: None. J. Toppari: None. M. Rewers: None. J. She: None. D. Schatz: None. B. Akolkar: None. J. Krischer: None. S. Huang: None. K. Vehik: None.
National Institute of Diabetes and Digestive and Kidney Diseases; National Institute of Allergy and Infectious Diseases; Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute of Environmental Health Sciences; Centers for Disease Control and Prevention; JDRF; University of Florida (UL1TR000064); University of Colorado (UL1TR001082)