Use of Next-Generation Sequencing to Support the Diagnosis of Familial Interstitial Pneumonia.
Ana Rita GiganteEduarda Milheiro TinocoAna FonsecaInês MarquesAgostinho SanchesNatália SalgueiroCarla NogueiraSérgio CampainhaSofia NevesPublished in: Genes (2023)
Familial interstitial pneumonia (FIP) is defined as idiopathic interstitial lung disease (ILD) in two or more relatives. Genetic studies on familial ILD discovered variants in several genes or associations with genetic polymorphisms. The aim of this study was to describe the clinical features of patients with suspected FIP and to analyze the genetic variants detected through next-generation sequencing (NGS) genetic testing. A retrospective analysis was conducted in patients followed in an ILD outpatient clinic who had ILD and a family history of ILD in at least one first- or second-degree relative and who underwent NGS between 2017 and 2021. Only patients with at least one genetic variant were included. Genetic testing was performed on 20 patients; of these, 13 patients had a variant in at least one gene with a known association with familial ILD. Variants in genes implicated in telomere and surfactant homeostasis and MUC5B variants were detected. Most variants were classified with uncertain clinical significance. Probable usual interstitial pneumonia radiological and histological patterns were the most frequently identified. The most prevalent phenotype was idiopathic pulmonary fibrosis. Pulmonologists should be aware of familial forms of ILD and genetic diagnosis.
Keyphrases
- interstitial lung disease
- idiopathic pulmonary fibrosis
- systemic sclerosis
- copy number
- end stage renal disease
- genome wide
- rheumatoid arthritis
- newly diagnosed
- ejection fraction
- chronic kidney disease
- early onset
- primary care
- peritoneal dialysis
- prognostic factors
- intensive care unit
- patient reported outcomes
- dna methylation
- genome wide identification
- extracorporeal membrane oxygenation
- acute respiratory distress syndrome
- circulating tumor cells
- bioinformatics analysis