ISSN 1662-4009 (online)

ey0018.10-4 | (1) | ESPEYB18

10.4. Extended family history of type 1 diabetes in HLA-predisposed children with and without islet autoantibodies

S Kuusela , P Keskinen , T Pokka , M Knip , J Ilonen , P Vahasalo , R Veijola

Pediatr Diabetes. 2020;21(8):1447–1456. doi: 10.1111/pedi.13122Family histories suggest strong degrees of inheritance of T1D in some children, especially in populations with an overall high risk of autoimmunity.This paper from the Finnish T1D Prediction and Prevention (DIPP) study looked at subjects carrying high HLA-conferred risk for T1D. A family history of T1D in...

ey0018.10-7 | (1) | ESPEYB18

10.7. Circulating metabolites in progression to islet autoimmunity and type 1 diabetes

S Lamichhane , E Kemppainen , K Trošt , H Siljander , H Hyoty , J Ilonen , J Toppari , R Veijola , T Hyotylainen , M Knip , M Orešič

Diabetologia. 2019;62(12):2287–2297. doi: 10.1007/s00125-019-04980-0This study identified different circulatory metabolite profiles in children who subsequently progress to T1D compared to children who progress to islet autoimmunity but not T1D, and antibody-negative control children.In addition to altered T cell immunity and autoantibody appearance, metaboli...

ey0019.10-6 | New paradigms | ESPEYB19

10.6. Progression of type 1 diabetes from latency to symptomatic disease is predicted by distinct autoimmune trajectories

BC Kwon , V Anand , P Achenbach , JL Dunne , W Hagopian , J Hu , E Koski , AE Lernmark , M Lundgren , K Ng , J Toppari , R Veijola , BI Frohnert

T1DI Study Group. Nat Commun. 2022 Mar 21;13(1):1514. https://pubmed.ncbi.nlm.nih.gov/35314671/Brief Summary: This study of 5 birth cohorts of individuals at high risk for type 1 diabetes (T1D) used machine learning methods to explore trajectories from autoantibodies appearance to T1D progression. They identified 11 distinct latent health states and individuals progressed according to one o...

ey0017.10-5 | (1) | ESPEYB17

10.5. Association of cereal, gluten, and dietary fiber intake with islet autoimmunity and type 1 diabetes

L Hakola , ME Miettinen , E Syrjala , M Akerlund , M-H Takkinen , TE Korhonen , S Ahonen , J Ilonen , J Toppari , R Veijola , J Nevelainen , M Knip , SM Virtanen

To read the full abstract: JAMA Pediatr 2019; 173:953–960.Dietary proteins, such as gluten, have been suggested to serve as triggers of the autoimmune process that leads to type 1 diabetes (T1DM). These authors studied the potential associations of cereal, gluten, and dietary fiber intake with the development of islet autoimmunity (IA) and T1DM.The prospective birth cohort Finnish Type 1 Diabetes Prediction and Preven...

ey0020.2-15 | New Perspectives | ESPEYB20

2.15. Childhood height growth rate association with the risk of islet autoimmunity and development of type 1 diabetes

Z Li , R Veijola , E Koski , V Anand , F Martin , K Waugh , H Hyoty , C Winkler , MB Killian , M Lundgren , K Ng , M Maziarz , J Toppari

Brief summary: In this study, 10 145 children of 1–8 years of age, selected from a prospective systematic cohort study and stratified according to HLA-risk categories for type-1-diabetes (T1D), underwent a combined evaluation of pancreatic autoimmunity, glucose metabolism and anthropometry at different timeframes. Diagnosis of T1D occurred in 131/10,145 children (1.3%). Faster height growth, both before and after age 3 years, was significantly associated with the appearan...

ey0020.8-4 | Important for Clinical Practice | ESPEYB20

8.4. Two-age islet-autoantibody screening for childhood type 1 diabetes: a prospective cohort study

M Ghalwash , JL Dunne , M Lundgren , M Rewers , AG Ziegler , V Anand , J Toppari , R Veijola , W Hagopian , Type 1 Diabetes Intelligence Study Group

Brief summary: Using data from the Type 1 Diabetes Intelligence (T1DI) cohort (n=24 662), this prospective study aimed to identify optimal ages for initial islet autoantibody (IAb) screening to predict the development of clinical type 1 diabetes (T1D). The identified optimal screening ages were 2 years and 6 years, with sensitivity of 82% and positive predictive value of 79% for T1D by age 15 years.Screening for T1D is a growing research topic a...