Population-based newborn screening for genetic disorders when multiple mutation DNA testing is incorporated: a cystic fibrosis newborn screening model demonstrating increased sensitivity but more carrier detections

UMMS Affiliation

Department of Pediatrics; New England Newborn Screening Program

Publication Date


Document Type



Algorithms; Cystic Fibrosis; Cystic Fibrosis Transmembrane Conductance Regulator; *DNA Mutational Analysis; Feasibility Studies; Female; Genetic Testing; Heterozygote Detection; Humans; Infant, Newborn; Male; Mutation; Neonatal Screening; Sensitivity and Specificity; Trypsinogen


Allergy and Immunology | Pediatrics | Respiratory Tract Diseases


OBJECTIVES: Newborn screening for cystic fibrosis (CF) provides a model to investigate the implications of applying multiple-mutation DNA testing in screening for any disorder in a pediatric population-based setting, where detection of affected infants is desired and identification of unaffected carriers is not. Widely applied 2-tiered CF newborn screening strategies first test for elevated immunoreactive trypsinogen (IRT) with subsequent analysis for a single CFTR mutation (DeltaF508), systematically missing CF-affected infants with any of the >1000 less common or population-specific mutations. Comparison of CF newborn screening algorithms that incorporate single- and multiple-mutation testing may offer insights into strategies that maximize the public health value of screening for CF and other genetic disorders. The objective of this study was to evaluate technical feasibility and practical implications of 2-tiered CF newborn screening that uses testing for multiple mutations (multiple-CFTR-mutation testing).

METHODS: We implemented statewide CF newborn screening using a 2-tiered algorithm: all specimens were assayed for IRT; those with elevated IRT then had multiple-CFTR-mutation testing. Infants who screened positive by detection of 1 or 2 mutations or extremely elevated IRT (>99.8%; failsafe protocol) were then referred for definitive diagnosis by sweat testing. We compared the number of sweat-test referrals using single- with multiple-CFTR-mutation testing. Initial physician assessments and diagnostic outcomes of these screened-positive infants and any affected infants missed by the screen were analyzed. We evaluated compliance with our screening and follow-up protocols. All Massachusetts delivery units, the Newborn Screening Program, pediatric health care providers who evaluate and refer screened-positive infants, and the 5 Massachusetts CF Centers and their affiliated genetic services participated. A 4-year cohort of 323 506 infants who were born in Massachusetts between February 1, 1999, and February 1, 2003, and screened for CF at approximately 2 days of age was studied.

RESULTS: A total of 110 of 112 CF-affected infants screened (negative predictive value: 99.99%) were detected with IRT/multiple-CFTR-mutation screening; 2 false-negative screens did not show elevated IRT. A total of 107 (97%) of the 110 had 1 or 2 mutations detected by the multiple- CFTR-mutation screen, and 3 had positive screens on the basis of the failsafe protocol. In contrast, had we used single-mutation testing, only 96 (87%) of the 110 would have had 1 or 2 mutations detectable by single-mutation screen, 8 would have had positive screens on the basis of the failsafe protocol, and an additional 6 infants would have had false-negative screens. Among 110 CF-affected screened-positive infants, a likely "genetic diagnosis" was made by the multiple-CFTR-mutation screen in 82 (75%) versus 55 (50%) with DeltaF508 alone. Increased sensitivity from multiple-CFTR-mutation testing yielded 274 (26%) more referrals for sweat testing and carrier identifications than testing with DeltaF508 alone.

CONCLUSIONS: Use of multiple-CFTR-mutation testing improved sensitivity and postscreening prediction of CF at the cost of increased referrals and carrier identification.


Pediatrics. 2004 Jun;113(6):1573-81.

Journal/Book/Conference Title


Related Resources

Link to Article in PubMed

PubMed ID