A combined risk score enhances prediction of type 1 diabetes among susceptible children

This is the author accepted manuscript. The final version is available from Nature Research via the DOI in this recordType 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.National Institutes of Health/National Center for Advancing Translational Sciences Clinical and Translational ScienceDiabetes Research CenterDiabetes UKWellcome TrustJDR

A combined risk score enhances prediction of type 1 diabetes among susceptible children.

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 risk(1). However, clinical diabetes can follow in weeks or only after decades, and is very difficult to predict. Ketoacidosis at onset remains common(2,3)and is most severe in the very young(4,5), in whom it can be life threatening and difficult to treat(6-9). Autoantibody surveillance programs effectively prevent most ketoacidosis(10-12)but require frequent evaluations whose expense limits public health adoption(13). Prevention therapies applied before onset, when greater islet mass remains, have rarely been feasible(14)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

Clinical, Biomarker, and Molecular Delineations and Genotype-Phenotype Correlations of Ataxia With Oculomotor Apraxia Type 1.

Ataxia with oculomotor apraxia type 1 (AOA1) is an autosomal recessive cerebellar ataxia due to mutations in the aprataxin gene (APTX) that is characterized by early-onset cerebellar ataxia, oculomotor apraxia, axonal motor neuropathy, and eventual decrease of albumin serum levels. To improve the clinical, biomarker, and molecular delineation of AOA1 and provide genotype-phenotype correlations. This retrospective analysis included the clinical, biological (especially regarding biomarkers of the disease), electrophysiologic, imaging, and molecular data of all patients consecutively diagnosed with AOA1 in a single genetics laboratory from January 1, 2002, through December 31, 2014. Data were analyzed from January 1, 2015, through January 31, 2016. The clinical, biological, and molecular spectrum of AOA1 and genotype-phenotype correlations. The diagnosis of AOA1 was confirmed in 80 patients (46 men [58%] and 34 women [42%]; mean [SD] age at onset, 7.7 [7.4] years) from 51 families, including 57 new (with 8 new mutations) and 23 previously described patients. Elevated levels of α-fetoprotein (AFP) were found in 33 patients (41%); hypoalbuminemia, in 50 (63%). Median AFP level was higher in patients with AOA1 (6.0 ng/mL; range, 1.1-17.0 ng/mL) than in patients without ataxia (3.4 ng/mL; range, 0.8-17.2 ng/mL; P < .01). Decreased albumin levels (ρ = -0.532) and elevated AFP levels (ρ = 0.637) were correlated with disease duration. The p.Trp279* mutation, initially reported as restricted to the Portuguese founder haplotype, was discovered in 53 patients with AOA1 (66%) with broad white racial origins. Oculomotor apraxia was found in 49 patients (61%); polyneuropathy, in 74 (93%); and cerebellar atrophy, in 78 (98%). Oculomotor apraxia correlated with the severity of ataxia and mutation type, being more frequent with deletion or truncating mutations (83%) than with presence of at least 1 missense variant (17%; P < .01). Mean (SD) age at onset was higher for patients with at least 1 missense mutation (17.7 [11.4] vs 5.2 [2.6] years; P < .001). The AFP level, slightly elevated in a substantial fraction of patients, may constitute a new biomarker for AOA1. Oculomotor apraxia may be an optional finding in AOA1 and correlates with more severe disease. The p.Trp279* mutation is the most frequent APTX mutation in the white population. APTX missense mutations may be associated with a milder phenotype