Using bivariate analysis of Galc and PSY, we will develop a new paradigm aimed at early and accurate prediction of EIKD.
Principal Investigator: Randy Carter, PhD and Thomas Langan (Joint PIs)
Funding Agency: New York State Department of Health (NIH), Eunice Kennedy Shriver National Institute of Child Health and Human Development
Abstract: Krabbe leukodystrophy (KD) (purported incidence 1:250,000) is an autosomal recessive disease due to loss of function mutations in the lysosomal enzyme Galactosylceramidase (GalC). One consequence of GalC loss of function is accumulation of the metabolic byproduct and toxin, psychosine (PSY) in the nervous system. The most common form of KD is the devastating early infantile type (EIKD), with onset of symptoms of disease in the first six months of life and death within 2-3 years of symptom onset.
Newborn screening (NBS) for KD has been available for 9 years in New York State (NYS), 3 years in Missouri and will soon be available in New Jersey, Kentucky and Illinois. NBS and early diagnosis are critical for efficacious treatment of KD because the sole treatment available, pooled cord blood transplantation (CBT), is more effective when started pre-symptomatically and as early in life as possible.Accurate identification of imminent EIKD is also particularly important because the preparatory ablative regimen for CBT is associated with 20% mortality in the first year of life.
Unfortunately, the current NYSNBS diagnostic paradigm for EIKD is imperfect, despite comprising DNA diagnosis, GALC enzyme levels, neurological exam, MRI scan of brain and electrophysiological exams. We hypothesize that two tests that can be determined rapidly on NBS blood spots, psychosine levels and GalC enzyme activities, will better predict KD. To test this hypothesis, we will measure PSY levels on bloodspots of patients in the Worldwide Registry of KD (WWR) at the Hunter James Kelly Research Institute HJKRI, and on bloodspots from new NYS-NBS positive babies (GalC levels known), as well as on controls. Using bivariate analysis of Galc and PSY, we will develop a new paradigm aimed at early and accurate prediction of EIKD. If this hypothesis is proven correct, the resulting change in the NYS-NBS algorithm will improve the speed, the sensitivity and the specificity of diagnosis and prognosis of KD, and thereby the efficacy of CBT. It will also provide a better template for a diagnostic algorithm useful for other NBS diseases where early diagnosis renders treatment more efficacious.