NGS analysis in Marfan syndrome spectrum: Combination of rare and common genetic variants to improve genotype-phenotype correlation analysis
Autoři:
Davide Gentilini aff001; Antonino Oliveri aff001; Teresa Fazia aff001; Alessandro Pini aff004; Susan Marelli aff004; Luisa Bernardinelli aff001; Anna Maria Di Blasio aff003
Působiště autorů:
Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy
aff001; Istituto Auxologico Italiano IRCCS, Bioinformatics and Statistical Genomics Unit, Cusano Milanino, Milano, Italy
aff002; Istituto Auxologico Italiano IRCCS, Molecular Biology Laboratory, Cusano Milanino, Milano, Italy
aff003; Rare Disease Center, Marfan Clinic, Cardiology department, ASST-FBF-Sacco, Milano, Italy
aff004; Centro di Cardiogenetica Vascolare IRCCS Policlinico San Donato, San Donato Milanese, Milano, Italy
aff005
Vyšlo v časopise:
PLoS ONE 14(9)
Kategorie:
Research Article
doi:
https://doi.org/10.1371/journal.pone.0222506
Souhrn
The diagnosis of Marfan spectrum includes a large number of clinical criteria. Although the identification of pathogenic variants contributes to the diagnostic process, its value to the prediction of clinical outcomes is still limited. An important novelty of the present study is represented by the statistical approach adopted to investigate genotype-phenotype correlation. The analysis has been improved considering the extended genetic information obtained by Next Generation Sequencing (NGS) and combining the effects of both rare and common genetic variants in an inclusive model. To this aim a cohort of 181 patients were analyzed with a NGS panel including 11 genes associated with Marfan spectrum. The genotype-phenotype correlation was also investigated considering the possibility to predict presence of a pathological mutation in Marfan syndrome (MFS) main genes based only on the analysis of phenotypic traits. Results obtained indicate that information about clinical traits can be summarized in a new variable that resulted significantly associated with the probability to find a pathological mutation in MFS main genes. This is important since the choice of the genetic test is often influenced by the phenotypic characterization of patients. Moreover, both rare and common variants were found to significantly contribute to clinical spectrum and their combination allowed to increase the percentage of phenotype variability that could be explained based on genetic factors. Results highlight the opportunity to take advantage of the overall genetic information obtained by NGS data to have a better clinical classification of patients.
Klíčová slova:
Biology and life sciences – Genetics – Phenotypes – Population genetics – Human genetics – Heredity – Genetic mapping – Variant genotypes – Genomics – Genome analysis – Transcriptome analysis – Evolutionary biology – Genetic polymorphism – Population biology – Biochemistry – Proteins – Collagens – Molecular biology – Molecular biology techniques – Computational biology – Research and analysis methods – Sequencing techniques – DNA sequencing – Next-generation sequencing – Medicine and health sciences – Clinical genetics – Genetic diseases – Autosomal dominant diseases – Marfan syndrome – Rheumatology – Connective tissue diseases – Collagen diseases – Ehlers-Danlos syndrome
Zdroje
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