ABSTRACT
BACKGROUND: Newborn screening (NBS) is an effective public health intervention that reduces death and disability from treatable genetic diseases, but many conditions are not screened due to a lack of a suitable assay. Whole genome and whole exome sequencing can potentially expand NBS but there remain many technical challenges preventing their use in population NBS. We investigated if targeted gene sequencing (TGS) is a feasible methodology for expanding NBS. METHODS: We constructed a TGS panel of 164 genes which screens for a broad range of inherited conditions. We designed a high-volume, low-turnaround laboratory and bioinformatics workflow that avoids the technical and data interpretation challenges associated with whole genome and whole exome sequencing. A methods-based analytical validation of the assay was completed and test performance in 2552 newborns examined. We calculated annual birth estimates for each condition to assess cost-effectiveness. RESULTS: Assay analytical sensitivity was >99% and specificity was 100%. Of the newborns screened, 1.3% tested positive for a condition. On average, each individual had 225 variants to interpret and 1.8% were variants of uncertain significance (VUS). The turnaround time was 7 to 10 days. Maximum batch size was 1536 samples. CONCLUSIONS: We demonstrate that a TGS assay could be incorporated into an NBS program soon to increase the number of conditions screened. Additionally, we conclude that NBS using TGS may be cost-effective.
Subject(s)
Computational Biology , Neonatal Screening , Infant, Newborn , Humans , Neonatal Screening/methods , Feasibility Studies , DNA , Sequence Analysis, DNASubject(s)
Chemistry, Clinical/methods , Chemistry, Clinical/standards , Research Design , Algorithms , Calibration , Humans , Medical ErrorsABSTRACT
BACKGROUND: We compared the 99th percentile reference intervals with 3 modern cardiac troponin assays in a single cohort and tested the hypothesis that the same individuals will be identified as above the cutoff and that differences will be explained by analytical imprecision. METHODS: Blood was collected from 2005 apparently healthy blood donors. Cardiac troponin was measured with Abbott Architect STAT high sensitive troponin I, Beckman Coulter Access AccuTnI+3, and Roche Elecsys troponin T highly sensitive assays. RESULTS: The 99th percentile cutoff limits were as follows: Abbott cardiac troponin I (cTnI) 28.9 ng/L; Beckman Coulter cTnI 31.3 ng/L; and Roche cardiac troponin T (cTnT) 15.9 ng/L. Correlation among the assays was poor: Abbott cTnI vs Beckman Coulter cTnI, R(2) = 0.18; Abbott cTnI vs Roche cTnT, R(2) = 0.04; and Beckman Coulter cTnI vs Roche cTnT R(2) = 0.01. Of the results above the cutoff 50% to 70% were unique to individual assays, with only 4 out of 20 individuals above the cutoff for all 3 assays. The observed differences among assays were larger than predicted from analytical imprecision. CONCLUSIONS: The 99th percentile cutoff values were in agreement with those reported elsewhere. The poor correlation and concordance amongst the assays were notable. The differences found could not be explained by analytical imprecision and indicate the presence of inaccuracy (bias) that is unique to sample and assay combinations. Based on these findings we recommend less emphasis on the cutoff value and greater emphasis on δ values in the diagnosis of myocardial infarction.
