BackgroundCystic Fibrosis (CF) is caused by ∼1,900 mutations in the CF transmembrane conductance regulator (CFTR) gene encoding for a cAMP-regulated chloride (Cl−) channel expressed in several epithelia. Clinical features are dominated by respiratory symptoms, but there is variable organ involvement thus causing diagnostic dilemmas, especially for non-classic cases.Methodology/Principal FindingsTo further establish measurement of CFTR function as a sensitive and robust biomarker for diagnosis and prognosis of CF, we herein assessed cholinergic and cAMP-CFTR-mediated Cl− secretion in 524 freshly excised rectal biopsies from 118 individuals, including patients with confirmed CF clinical diagnosis (n = 51), individuals with clinical CF suspicion (n = 49) and age-matched non-CF controls (n = 18). Conclusive measurements were obtained for 96% of cases. Patients with “Classic CF”, presenting earlier onset of symptoms, pancreatic insufficiency, severe lung disease and low Shwachman-Kulczycki scores were found to lack CFTR-mediated Cl− secretion (<5%). Individuals with milder CF disease presented residual CFTR-mediated Cl− secretion (10–57%) and non-CF controls show CFTR-mediated Cl− secretion ≥30–35% and data evidenced good correlations with various clinical parameters. Finally, comparison of these values with those in “CF suspicion” individuals allowed to confirm CF in 16/49 individuals (33%) and exclude it in 28/49 (57%). Statistical discriminant analyses showed that colonic measurements of CFTR-mediated Cl− secretion are the best discriminator among Classic/Non-Classic CF and non-CF groups.Conclusions/SignificanceDetermination of CFTR-mediated Cl− secretion in rectal biopsies is demonstrated here to be a sensitive, reproducible and robust predictive biomarker for the diagnosis and prognosis of CF. The method also has very high potential for (pre-)clinical trials of CFTR-modulator therapies.

Altogether, these results indicate that R560S is a class II mutation. However, unlike F508del, it cannot be rescued by any of the CFTR modulators tested.

A major challenge in cystic fibrosis (CF) research is applying mutation‐specific therapy to individual patients with diverse and rare CF transmembrane conductance regulator (CFTR) genotypes. Read‐through agents are currently the most promising approach for Class I mutations that introduce premature termination codons (PTCs) into CFTR mRNA. However, variations in degradation of PTC containing transcripts by nonsense mediated decay (NMD) might lower read‐through efficacy. Allele specific quantitative real time (qRT)‐PCR was used to measure variations in CFTR mRNA abundance for several PTC mutations in respiratory cells and intestinal organoids. The majority of PTC mutations were associated with reduced levels of relative mRNA transcript abundance (∼33% and 26% of total CFTR mRNA in respiratory cells and intestinal organoids, respectively, compared to >50% for non‐PTC causing mutations). These levels were generally not affected by PTC mutation type or position, but there could be twofold variations between individuals bearing the same genotype. Most PTC mutations in CFTR are subject to similar levels of NMD, which reduce but do not abolish PTC bearing mRNAs. Measurement of individual NMD levels in intestinal organoids and HNE cells might, therefore, be useful in predicting efficacy of PTC read‐through in the context of personalized CFTR modulator therapy.

Newborn screening (NBS) for cystic fibrosis (CF) has been shown to be advantageous for children with CF, and has thus been included in most NBS programs using various algorithms. With this study, we intend to establish the most appropriate algorithm for CF-NBS in the Portuguese population, to determine the incidence, and to contribute to elucidating the genetic epidemiology of CF in Portugal. This was a nationwide three-year pilot study including 255,000 newborns (NB) that were also screened for congenital hypothyroidism (CH) and 24 other metabolic disorders included in the Portuguese screening program. Most samples were collected in local health centers spread all over the country, between the 3rd and 6th days of life. The algorithm tested includes immunoreactive trypsinogen (IRT) determination, pancreatitis associated protein (PAP) as a second tier, and genetic study for cases referred to specialized clinical centers. Thirty-four CF cases were confirmed positive, thus indicating an incidence of 1:7500 NB. The p.F508del mutation was found in 79% of the alleles. According to the results presented here, CF-NBS is recommended to be included in the Portuguese NBS panel with a small adjustment regarding the PAP cutoff , which we expect to contribute to the improvement of the CF-NBS performance. According to our results, this algorithm is a valuable alternative for CF-NBS in populations with stringent rules for genetic studies.

The Cystic Fibrosis p.Ile1234Val missense mutation actually creates a new dual splicing site possibly used either as a new acceptor or donor. Here, we aimed to test the accuracy of in silico predictions by comparing them with in vitro and ex vivo functional analyses of this mutation for an accurate CF diagnosis/prognosis. To this end, we applied a new in vitro strategy using a CFTR mini-gene which includes the complete CFTR coding sequence plus intron 22 (short version) which allows the assessment of alternatively spliced mRNA levels as well as the properties of the resulting abnormal CFTR protein regarding processing, intracellular localization and function. Our data demonstrate that p.Ile1234Val leads to usage of the alternative splicing donor (but not acceptor) resulting in alternative CFTR transcripts lacking 18 nts of exon 22 which produce a truncated CFTR protein with residual Cl- channel function. These results recapitulate data from native tissues of a CF patient. In conclusion, the existing in silico prediction models have limited application and ex vivo functional assessment of mutation effects should be made. Alternatively the in vitro strategy adopted here can be applied to assess the disease liability of mutations for an accurate CF diagnosis/prognosis.