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      Novel Mutations in BMPR2, ACVRL1 and KCNA5 Genes and Hemodynamic Parameters in Patients with Pulmonary Arterial Hypertension

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          Pulmonary arterial hypertension (PAH) is a rare and progressive vascular disorder characterized by increased pulmonary vascular resistance and right heart failure. The aim of this study was to analyze the Bone Morphogenetic Protein Receptor 2 ( BMPR2), Activin A type II receptor like kinase 1 ( ALK1/ACVRL1) and potassium voltage-gated channel, shakerrelated subfamily, member 5 ( KCNA5) genes in patients with idiopathic and associated PAH. Correlation among pathogenic mutations and clinical and functional parameters was further analyzed.

          Methods and Results

          Forty one patients and fifty controls were included in this study. Analysis of BMPR2, ACVRL1 and KCNA5 genes was performed by polymerase chain reaction (PCR) and direct sequencing. Fifty one nucleotide changes were detected in these genes in 40 of the 41 patients; only 22 of these changes, which were classified as pathogenic, have been detected in 21 patients (51.2%). Ten patients (62.5%) with idiopathic PAH and 10 (40%) with associated PAH showed pathogenic mutations in some of the three genes. Several clinical and hemodynamics parameters showed significant differences between carriers and non-carriers of mutations, being more severe in carriers: mean pulmonary artery pressure (p = 0.043), pulmonary vascular resistence (p = 0.043), cardiac index (p = 0.04) and 6 minute walking test (p = 0.02). This differences remained unchanged after adjusting for PAH type (idiopathic vs non idiopathic).


          Pathogenic mutations in BMPR2 gene are frequent in patients with idiopathic and associated PAH group I. Mutations in ACVRL1 and KCNA5 are less frequent. The presence of these mutations seems to increase the severity of the disease.

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          Most cited references 40

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          Predicting the effects of coding non-synonymous variants on protein function using the SIFT algorithm.

          The effect of genetic mutation on phenotype is of significant interest in genetics. The type of genetic mutation that causes a single amino acid substitution (AAS) in a protein sequence is called a non-synonymous single nucleotide polymorphism (nsSNP). An nsSNP could potentially affect the function of the protein, subsequently altering the carrier's phenotype. This protocol describes the use of the 'Sorting Tolerant From Intolerant' (SIFT) algorithm in predicting whether an AAS affects protein function. To assess the effect of a substitution, SIFT assumes that important positions in a protein sequence have been conserved throughout evolution and therefore substitutions at these positions may affect protein function. Thus, by using sequence homology, SIFT predicts the effects of all possible substitutions at each position in the protein sequence. The protocol typically takes 5-20 min, depending on the input. SIFT is available as an online tool (
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            Guidelines for the diagnosis and treatment of pulmonary hypertension: the Task Force for the Diagnosis and Treatment of Pulmonary Hypertension of the European Society of Cardiology (ESC) and the European Respiratory Society (ERS), endorsed by the International Society of Heart and Lung Transplantation (ISHLT).

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              Predicting functional effect of human missense mutations using PolyPhen-2.

              PolyPhen-2 (Polymorphism Phenotyping v2), available as software and via a Web server, predicts the possible impact of amino acid substitutions on the stability and function of human proteins using structural and comparative evolutionary considerations. It performs functional annotation of single-nucleotide polymorphisms (SNPs), maps coding SNPs to gene transcripts, extracts protein sequence annotations and structural attributes, and builds conservation profiles. It then estimates the probability of the missense mutation being damaging based on a combination of all these properties. PolyPhen-2 features include a high-quality multiple protein sequence alignment pipeline and a prediction method employing machine-learning classification. The software also integrates the UCSC Genome Browser's human genome annotations and MultiZ multiple alignments of vertebrate genomes with the human genome. PolyPhen-2 is capable of analyzing large volumes of data produced by next-generation sequencing projects, thanks to built-in support for high-performance computing environments like Grid Engine and Platform LSF.

                Author and article information

                Role: Editor
                PLoS One
                PLoS ONE
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                17 June 2014
                : 9
                : 6
                [1 ]Department of Biochemistry, Genetics and Immunology, Faculty of Biology, University of Vigo, Instituto de Investigación Biomédica de Vigo (IBIV), Vigo, Spain
                [2 ]Respiratory Division, Complejo Hospitalario Universitario de Pontevedra, Pontevedra, Spain
                [3 ]Respiratory Division, Complejo Hospitalario Universitario de Vigo, Vigo, Spain
                [4 ]Respiratory Division, Hospital Universitario Marqués de Valdecilla, Santander, Spain
                University of Colorado, Denver, United States of America
                Author notes

                Competing Interests: The authors confirm that they received funding from a commercial source: “Actelion Pharmaceuticals”. But, this does not alter their adherence to PLOS ONE policies on sharing data and materials.

                Conceived and designed the experiments: GP AB DV. Performed the experiments: GP DV. Analyzed the data: GP AB CV DV. Contributed reagents/materials/analysis tools: GP AB CV JMC DV. Wrote the paper: GP AB DV. Clinical data: AB CV JMC.


                This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                Pages: 10
                This study was supported by the grants IN-202-05 from SOGAPAR, CO-0085-10 from Actelion Pharmaceuticals and INBIOMED 2009-063 Xunta de Galicia. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Research Article
                Biology and Life Sciences
                Genetic Engineering
                Genetic Dominance
                Autosomal Dominant Traits
                Genomic Medicine
                Genetic Testing
                Human Genetics
                Genetic Association Studies
                Mutational Hypotheses
                Genetics of Disease
                Molecular Biology
                Molecular Biology Techniques
                Sequencing Techniques
                Genome Sequencing



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