Fig 1.
Schematic representation of the pipeline for identification of pathogenic mutations.
Pathogenic mutations were identified on the basis of seven annotated databases: PKDB, dbSNP, SnpEff, UCSC (for conservation probability), PubMed (article searches), Pseudogene.org, and a database of polymorphic variants in 140 healthy Japanese individuals. Novel missense mutations and potential splicing mutations were evaluated for pathogenicity using public cloud-based computing (SIFT, PolyPhen-2, Align-GVGD, MutationTaster, and NNSplice). PKDB; PKD mutation database, NCBI; National Center for Biotechnology Information, dbSNP; Single Nucleotide Polymorphism database, UCSC; University of California, Santa Cruz, SIFT; Sorting Intolerant from Tolerant, GVGD; Grantham Variation Grantham Deviation.
Fig 2.
Schematic diagram of workflow in healthy volunteers.
140 healthy Japanese volunteers were recruited and they were age 35 or older and were confirmed as having no renal cysts by ultrasonography. Four nonsynonymous variants predicted to be likely pathogenic mutations in six subjects and other 134 subjects were predicted in likely neutral variants by the scoring protocol using cloud-based computing [31]. The specificity of the system was estimated to be 95.7%.
Fig 3.
Schematic diagram of workflow in the patients with ADPKD.
52 definitely pathogenic mutations, 22 highly likely pathogenic mutations and 20 likely pathogenic mutations were identified in 101 Japanese patients with ADPKD. The sensitivity of the system was estimated to be 93.1% in combined with multiplex ligation-dependent probe amplification analysis (MLPA).
Table 1.
Summary of the pathogenic mutations in Japanese patients with ADPKD.
Table 2.
Summary of novel and known pathogenic mutations identified in this study.