RESUMO
Standard analyses applied to genome-wide association data are well designed to detect additive effects of moderate strength. However, the power for standard genome-wide association study (GWAS) analyses to identify effects from recessive diplotypes is not typically high. We proposed and conducted a gene-based compound heterozygosity test to reveal additional genes underlying complex diseases. With this approach applied to iron overload, a strong association signal was identified between the fibroblast growth factor-encoding gene, FGF6, and hemochromatosis in the central Wisconsin population. Functional validation showed that fibroblast growth factor 6 protein (FGF-6) regulates iron homeostasis and induces transcriptional regulation of hepcidin. Moreover, specific identified FGF6 variants differentially impact iron metabolism. In addition, FGF6 downregulation correlated with iron-metabolism dysfunction in systemic sclerosis and cancer cells. Using the recessive diplotype approach revealed a novel susceptibility hemochromatosis gene and has extended our understanding of the mechanisms involved in iron metabolism.
Assuntos
Exoma/genética , Fator 6 de Crescimento de Fibroblastos/genética , Regulação da Expressão Gênica , Predisposição Genética para Doença , Hemocromatose/patologia , Hepcidinas/metabolismo , Sobrecarga de Ferro/patologia , Ferro/metabolismo , Sequência de Aminoácidos , Estudos de Casos e Controles , Diploide , Feminino , Fator 6 de Crescimento de Fibroblastos/metabolismo , Seguimentos , Genes Recessivos , Estudo de Associação Genômica Ampla , Hemocromatose/genética , Hepcidinas/genética , Humanos , Sobrecarga de Ferro/genética , Masculino , Pessoa de Meia-Idade , Neoplasias/genética , Neoplasias/patologia , Mapas de Interação de Proteínas , Escleroderma Sistêmico/genética , Escleroderma Sistêmico/patologia , Homologia de SequênciaRESUMO
BACKGROUND: Identification and evaluation of incidental findings in patients following whole exome (WGS) or whole genome sequencing (WGS) is challenging for both practicing physicians and researchers. The American College of Medical Genetics and Genomics (ACMG) recently recommended a list of reportable incidental genetic findings. However, no informatics tools are currently available to support evaluation of incidental findings in next-generation sequencing data. METHODS: The Wisconsin Hierarchical Analysis Tool for Incidental Findings (WHATIF), was developed as a stand-alone Windows-based desktop executable, to support the interactive analysis of incidental findings in the context of the ACMG recommendations. WHATIF integrates the European Bioinformatics Institute Variant Effect Predictor (VEP) tool for biological interpretation and the National Center for Biotechnology Information ClinVar tool for clinical interpretation. RESULTS: An open-source desktop program was created to annotate incidental findings and present the results with a user-friendly interface. Further, a meaningful index (WHATIF Index) was devised for each gene to facilitate ranking of the relative importance of the variants and estimate the potential workload associated with further evaluation of the variants. Our WHATIF application is available at: http://tinyurl.com/WHATIF-SOFTWARE CONCLUSIONS: The WHATIF application offers a user-friendly interface and allows users to investigate the extracted variant information efficiently and intuitively while always accessing the up to date information on variants via application programming interfaces (API) connections. WHATIF׳s highly flexible design and straightforward implementation aids users in customizing the source code to meet their own special needs.
