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Redondo, Maria J.; Geyer, Susan; Steck, Andrea K.; Sharp, Seth; Wentworth, John M.; Weedon, Michael N.; Antinozzi, Peter; Sosenko, Jay; Atkinson, Mark; Pugliese, Alberto; Oram, Richard A.; Antinozzi, P.; Atkinson, M.; Battaglia, M.; Becker, D.; Bingley, P.; Bosi, E.; Buckner, J.; Colman, P.; Gottlieb, P.; Herold, K.; Insel, R.; Kay, T.; Knip, M.; [...]

A Type 1 Diabetes Genetic Risk Score Predicts Progression of Islet Autoimmunity and Development of Type 1 Diabetes in Individuals at Risk

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  • Media type: E-Article
  • Title: A Type 1 Diabetes Genetic Risk Score Predicts Progression of Islet Autoimmunity and Development of Type 1 Diabetes in Individuals at Risk
  • Contributor: Redondo, Maria J.; Geyer, Susan; Steck, Andrea K.; Sharp, Seth; Wentworth, John M.; Weedon, Michael N.; Antinozzi, Peter; Sosenko, Jay; Atkinson, Mark; Pugliese, Alberto; Oram, Richard A.; Antinozzi, P.; Atkinson, M.; Battaglia, M.; Becker, D.; Bingley, P.; Bosi, E.; Buckner, J.; Colman, P.; Gottlieb, P.; Herold, K.; Insel, R.; Kay, T.; Knip, M.; [...]
  • imprint: American Diabetes Association, 2018
  • Published in: Diabetes Care
  • Language: English
  • DOI: 10.2337/dc18-0087
  • ISSN: 0149-5992; 1935-5548
  • Keywords: Advanced and Specialized Nursing ; Endocrinology, Diabetes and Metabolism ; Internal Medicine
  • Origination:
  • Footnote:
  • Description: <jats:sec> <jats:title>OBJECTIVE</jats:title> <jats:p>We tested the ability of a type 1 diabetes (T1D) genetic risk score (GRS) to predict progression of islet autoimmunity and T1D in at-risk individuals.</jats:p> </jats:sec> <jats:sec> <jats:title>RESEARCH DESIGN AND METHODS</jats:title> <jats:p>We studied the 1,244 TrialNet Pathway to Prevention study participants (T1D patients’ relatives without diabetes and with one or more positive autoantibodies) who were genotyped with Illumina ImmunoChip (median [range] age at initial autoantibody determination 11.1 years [1.2–51.8], 48% male, 80.5% non-Hispanic white, median follow-up 5.4 years). Of 291 participants with a single positive autoantibody at screening, 157 converted to multiple autoantibody positivity and 55 developed diabetes. Of 953 participants with multiple positive autoantibodies at screening, 419 developed diabetes. We calculated the T1D GRS from 30 T1D-associated single nucleotide polymorphisms. We used multivariable Cox regression models, time-dependent receiver operating characteristic curves, and area under the curve (AUC) measures to evaluate prognostic utility of T1D GRS, age, sex, Diabetes Prevention Trial–Type 1 (DPT-1) Risk Score, positive autoantibody number or type, HLA DR3/DR4-DQ8 status, and race/ethnicity. We used recursive partitioning analyses to identify cut points in continuous variables.</jats:p> </jats:sec> <jats:sec> <jats:title>RESULTS</jats:title> <jats:p>Higher T1D GRS significantly increased the rate of progression to T1D adjusting for DPT-1 Risk Score, age, number of positive autoantibodies, sex, and ethnicity (hazard ratio [HR] 1.29 for a 0.05 increase, 95% CI 1.06–1.6; P = 0.011). Progression to T1D was best predicted by a combined model with GRS, number of positive autoantibodies, DPT-1 Risk Score, and age (7-year time-integrated AUC = 0.79, 5-year AUC = 0.73). Higher GRS was significantly associated with increased progression rate from single to multiple positive autoantibodies after adjusting for age, autoantibody type, ethnicity, and sex (HR 2.27 for GRS &amp;gt;0.295, 95% CI 1.47–3.51; P = 0.0002).</jats:p> </jats:sec> <jats:sec> <jats:title>CONCLUSIONS</jats:title> <jats:p>The T1D GRS independently predicts progression to T1D and improves prediction along T1D stages in autoantibody-positive relatives.</jats:p> </jats:sec>
  • Access State: Open Access