Newborn screening for lysosomal storage diseases: Methodologies, screen positive rates, normalization of datasets, second-tier tests, and post-analysis tools

Abstract

All of the worldwide newborn screening (NBS) for lysosomal storage diseases (LSDs) is done by measurement of lysosomal enzymatic activities in dried blood spots (DBS). Substrates used for these assays are discussed. While the positive predictive value (PPV) is the gold standard for evaluating medical tests, current PPVs for NBS of LSDs cannot be used as a performance metric due to statistical sampling errors and uncertainty in the onset of disease symptoms. Instead, we consider the rate of screen positives as the only currently reliable way to compare LSD NBS results across labs worldwide. It has been suggested that the expression of enzymatic activity data as multiple-of-the-mean is a way to normalize datasets obtained using different assay platforms, so that results can be compared, and universal cutoffs can be developed. We show that this is often not the case, and normalization is currently not feasible. We summarize the recent use of pattern matching statistical analysis together with measurement of an expanded group of enzymatic activities and biomarkers to greatly reduce the number of false positives for NBS of LSDs. We provide data to show that these post-enzymatic activity assay methods are more powerful than genotype analysis for the stratification of NBS for LSDs.