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.