Abstract
Newborn screening (NBS) for Cystic Fibrosis (CF) is associated with improved outcomes. All US states screen for CF; however, CF NBS algorithms have high false positive (FP) rates. In New York State (NYS), the positive predictive value of CF NBS improved from 3.7% to 25.2% following the implementation of a three-tier IRT-DNA-SEQ approach using commercially available tests. Here we describe a modification of the NYS CF NBS algorithm via transition to a new custom next-generation sequencing (NGS) platform for more comprehensive cystic fibrosis transmembrane conductance regulator (CFTR) gene analysis. After full gene sequencing, a tiered strategy is used to first analyze only a specific panel of 338 clinically relevant CFTR variants (second-tier), followed by unblinding of all sequence variants and bioinformatic assessment of deletions/duplications in a subset of samples requiring third-tier analysis. We demonstrate the analytical and clinical validity of the assay and the feasibility of use in the NBS setting. The custom assay has streamlined our molecular workflow, increased throughput, and allows for bioinformatic customization of second-tier variant panel content. NBS aims to identify those infants with the highest disease risk. Technological molecular improvements can be applied to NBS algorithms to reduce the burden of FP referrals without loss of sensitivity.
Highlights
Cystic Fibrosis (CF; OMIM # 219700) is an autosomal recessive condition characterized by abnormal secretion of electrolytes and fluid across epithelial membranes of most exocrine organs
Second-tier analysis is bioinformatically limited to a defined set of clinically relevant CFTR variants
CF newborn screening (NBS) algorithms have had high false positive (FP) rates in the US and worldwide, leading to the unnecessary referral of unaffected infants, which can lead to anxiety and place a burden on families [24,25]
Summary
Cystic Fibrosis (CF; OMIM # 219700) is an autosomal recessive condition characterized by abnormal secretion of electrolytes and fluid across epithelial membranes of most exocrine organs. Identification of infants with CF via newborn screening (NBS) is cost-effective and associated with improved outcomes [1]. Homozygous or compound heterozygous variants in the cystic fibrosis transmembrane conductance regulator (CFTR) gene cause CF. NYS started screening for CF in October 2002 using a two-tier IRT-DNA algorithm consisting of first-tier immunoreactive trypsinogen (IRT) screening, followed by targeted screening using a CFTR variant panel for infants with IRT values in the daily top 5%. Targeted variant panels improve the specificity of CF NBS algorithms. The CF false positive rate was still high in NYS because carriers and infants with VHIRT were referred for diagnostic evaluation since only a limited genotyping panel was utilized and rare CF-causing variants could not be tested [3]
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