Cystic Fibrosis Newborn Screening in Portugal: PAP Value in Populations with Stringent Rules for Genetic Studies

• Autor(a) principal: Marcão, Ana
• Data de Publicação: 2018
• Outros Autores: Barreto, Celeste, Pereira, Luísa, Vaz, Luísa, Cavaco, José, Casimiro, Ana, Félix, Miguel, Silva, Teresa, Barbosa, Telma, Freitas, Cristina, Nunes, Sidónia, Felício, Verónica, Lopes, Lurdes, Amaral, Margarida, Vilarinho, Laura
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: http://hdl.handle.net/10400.18/5898
• topic: Newborn Screening; Cystic Fibrosis; Genetic Epidemiology; Portugal; IRT; PAP; Doenças Genéticas

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 cut-off, 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.