Development of a newborn screening tool based on bivariate normal limits: using psychosine and galactocerebrosidase determination on dried blood spots to predict Krabbe disease

Purpose Newborn screening for Krabbe disease (KD) originated in New York State in 2006 but has proven to have a high false positive rate and low positive predictive value. To improve accuracy of presymptomatic prediction, we propose a screening tool based on two biomarkers, psychosine and galactocerebrosidase enzyme activity (GalC). Methods We developed the tool using measures from dried blood spots of 166 normal newborns and tested it on dried blood spot measures from 15 newborns who later developed KD, 8 newborns identified as "high risk" by the New York screening protocol but were disease-free at follow-up, and 3 symptomatic children with onset before 4 years of age. The tool was developed from the (1–10−6)100% prediction region of the natural logarithms of psychosine and GalC measures, assuming bivariate normality, and their univariate normal limits. Results Krabbe disease was predicted correctly for every patient who developed symptoms in infancy or early childhood. None of the high-risk patients were incorrectly identified as having early KD. Conclusion Bivariate analysis of psychosine and GalC in newborn blood spots can accurately predict early Krabbe symptoms, control false positive rates, and permit presymptomatic treatment.