Heptadecanoylcarnitine (C17) a novel candidate biomarker for newborn screening of propionic and methylmalonic acidemias

BACKGROUND: 3-Hydroxypalmitoleoyl-carnitine (C16:1-OH) has recently been reported to be elevated in acylcarnitine profiles of patients with propionic acidemia (PA) or methylmalonic acidemia (MMA) during expanded newborn screening (NBS). High levels of C16:1-OH, combined with other hydroxylated long chain acylcarnitines are related to long-chain 3-hydroxyacyl-CoA dehydrogenase deficiency (LCHADD) and trifunctional protein (TFP) deficiency. METHODS: The acylcarnitine profile of two LCHADD patients was evaluated using liquid chromatography-tandem mass spectrometric method. A specific retention time was determined for each hydroxylated long chain acylcarnitine. The same method was applied to some neonatal dried blood spots (DBSs) from PA and MMA patients presenting abnormal C16:1-OH concentrations. RESULTS: The retention time of the peak corresponding to C16:1-OH in LCHADD patients differed from those in MMA and PA patients. Heptadecanoylcarnitine (C17) has been identified as the novel biomarker specific for PA and MMA patients through high resolution mass spectrometry (Orbitrap) experiments. We found that 21 out of 23 neonates (22 MMA, and 1PA) diagnosed through the Tuscany region NBS program exhibited significantly higher levels of C17 compared to controls. Twenty-three maternal deficiency (21 vitamin B12 deficiency, 1 homocystinuria and 1 gastrin deficiency) samples and 82 false positive for elevated propionylcarnitine (C3) were also analyzed. CONCLUSIONS: We have characterized a novel biomarker able to detect propionate disorders during expanded newborn screening (NBS). The use of this new biomarker may improve the analytical performances of NBS programs especially in laboratories where second tier tests are not performed

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