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Updated: Jun 3, 2026
Detection of Rare Mutations in CtDNA Using Next Generation Sequencing
Published on: August 24, 2017
Optimal DNA tier for the IRT/DNA algorithm determined by CFTR mutation results over 14 years of newborn screening
Mei W Baker1, Molly Groose, Gary Hoffman
1School of Medicine and Public Health, Newborn Screening Laboratory, Wisconsin State Laboratory of Hygiene, University of Wisconsin-Madison, Madison, WI 53706, USA.
Insights
A 23-mutation panel optimizes cystic fibrosis (CF) newborn screening sensitivity. The immunoreactive trypsinogen (IRT) cutoff is more critical than DNA for detecting CF in newborns.
Area of Science:
- Genetics
- Newborn Screening
- Public Health
Background:
- Significant variation exists in cystic fibrosis (CF) newborn screening algorithms regarding the number and type of CFTR mutations included.
- Limited research has addressed optimal CFTR mutation panel selection using large newborn populations.
Purpose of the Study:
- To determine the optimal panel of CFTR mutations for cystic fibrosis newborn screening.
- To evaluate the impact of different CFTR mutation panels and IRT cutoffs on screening sensitivity.
Main Methods:
- Analysis of approximately 1 million Wisconsin newborn screening results from 1994-2008.
- Evaluation of an immunoreactive trypsinogen (IRT)/DNA algorithm for CF screening.
- Comparison of a 23-mutation CFTR panel versus a single-mutation (F508del) panel.
Main Results:
- A 23-mutation CFTR panel, combined with a 96th percentile IRT cutoff, achieved 97.3% sensitivity for CF screening.
- Restricting the DNA tier to only the F508del mutation reduced sensitivity to 90%.
- The IRT cutoff value was found to be more critical than the DNA panel in determining screening sensitivity.
Conclusions:
- A 23-mutation CFTR panel is advantageous for optimizing CF newborn screening sensitivity.
- While CFTR panel selection is complex, the IRT cutoff plays a more pivotal role in newborn screening sensitivity than the specific DNA mutations analyzed.
Background:
There has been great variation and uncertainty about how many and what CFTR mutations to include in cystic fibrosis (CF) newborn screening algorithms, and very little research on this topic using large populations of newborns.
Methods:
We reviewed Wisconsin screening results for 1994-2008 to identify an ideal panel.
Results:
Upon analyzing approximately 1 million screening results, we found it optimal to use a 23 CFTR mutation panel as a second tier when an immunoreactive trypsinogen (IRT)/DNA algorithm was applied for CF screening. This panel in association with a 96th percentile IRT cutoff gave a sensitivity of 97.3%, but restricting the DNA tier to F508del was associated with 90% (P<.0001).
Conclusions:
Although CFTR panel selection has been challenging, our data show that a 23 mutation method optimizes sensitivity and is advantageous. The IRT cutoff value, however, is actually more critical than DNA in determining CF newborn screening sensitivity.
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