Dihydropyrimidinase deficiency: Phenotype, genotype and structural consequences in 17 patients

AbstractDihydropyrimidinase (DHP) is the second enzyme of the pyrimidine degradation pathway and catalyses the ring opening of 5,6-dihydrouracil and 5,6-dihydrothymine. To date, only 11 individuals have been reported suffering from a complete DHP deficiency. Here, we report on the clinical, biochemical and molecular findings of 17 newly identified DHP deficient patients as well as the analysis of the mutations in a three-dimensional framework. Patients presented mainly with neurological and gastrointestinal abnormalities and markedly elevated levels of 5,6-dihydrouracil and 5,6-dihydrothymine in plasma, cerebrospinal fluid and urine. Analysis of DPYS, encoding DHP, showed nine missense mutations, two nonsense mutations, two deletions and one splice-site mutation. Seventy-one percent of the mutations were located at exons 5–8, representing 41% of the coding sequence. Heterologous expression of 11 mutant enzymes in Escherichia coli showed that all but two missense mutations yielded mutant DHP proteins without significant activity. Only DHP enzymes containing the mutations p.R302Q and p.T343A possessed a residual activity of 3.9% and 49%, respectively. The crystal structure of human DHP indicated that the point mutations p.R490C, p.R302Q and p.V364M affect the oligomerization of the enzyme. In contrast, p.M70T, p.D81G, p.L337P and p.T343A affect regions near the di-zinc centre and the substrate binding site. The p.S379R and p.L7V mutations were likely to cause structural destabilization and protein misfolding. Four mutations were identified in multiple unrelated DHP patients, indicating that DHP deficiency may be more common than anticipated

Clinical validation of cutoff target ranges in newborn screening of metabolic disorders by tandem mass spectrometry: A worldwide collaborative project

PURPOSE:: To achieve clinical validation of cutoff values for newborn screening by tandem mass spectrometry through a worldwide collaborative effort. METHODS:: Cumulative percentiles of amino acids and acylcarnitines in dried blood spots of approximately 25-30 million normal newborns and 10,742 deidentified true positive cases are compared to assign clinical significance, which is achieved when the median of a disorder range is, and usually markedly outside, either the 99th or the 1st percentile of the normal population. The cutoff target ranges of analytes and ratios are then defined as the interval between selected percentiles of the two populations. When overlaps occur, adjustments are made to maximize sensitivity and specificity taking all available factors into consideration. RESULTS:: As of December 1, 2010, 130 sites in 45 countries have uploaded a total of 25,114 percentile data points, 565,232 analyte results of true positive cases with 64 conditions, and 5,341 cutoff values. The average rate of submission of true positive cases between December 1, 2008, and December 1, 2010, was 5.1 cases/day. This cumulative evidence generated 91 high and 23 low cutoff target ranges. The overall proportion of cutoff values within the respective target range was 42% (2,269/5,341). CONCLUSION:: An unprecedented level of cooperation and collaboration has allowed the objective definition of cutoff target ranges for 114 markers to be applied to newborn screening of rare metabolic disorders. © 2011 Lippincott Williams & Wilkins

Enhanced interpretation of newborn screening results without analyte cutoff values

A collaboration among 157 newborn screening programs in 47 countries has lead to the creation of a database of 705,333 discrete analyte concentrations from 11,462 cases affected with 57 metabolic disorders, and from 631 heterozygotes for 12 conditions. This evidence was first applied to establish disease ranges for amino acids and acylcarnitines, and clinically validate 114 cutoff target ranges. Objective: To improve quality and performance with an evidence-based approach, multivariate pattern recognition software has been developed to aid in the interpretation of complex analyte profiles. The software generates tools that convert multiple clinically significant results into a single numerical score based on overlap between normal and disease ranges, penetration within the disease range, differences between specific conditions, and weighted correction factors. Design: Eighty-five on-line tools target either a single condition or the differential diagnosis between two or more conditions. Scores are expressed as a numerical value and as the percentile rank among all cases with the condition chosen as primary target, and are compared to interpretation guidelines. Tools are updated automatically after any new data submission (2009- 2011: 5.2 new cases added per day on average). Main outcome measures: Retrospective evaluation of past cases suggest that these tools could have avoided at least half of 277 false positive outcomes caused by carrier status for fatty acid oxidation disorders, and could have prevented 88% of false negative events caused by cutoff 7 values set inappropriately. In Minnesota, their prospective application has been a major contributing factor to the sustained achievement of a false positive rate below 0.1% and a positive predictive value above 60%. Conclusions: Application of this computational approach to raw data could make cutoff values for single analytes effectively obsolete. This paradigm is not limited to newborn screening and is applicable to the interpretation of diverse multi-analyte profiles utilized in laboratory medicine. Abstract wor