4.7 Article

A complete mutation screen of the ADPKD genes by DHPLC

Journal

KIDNEY INTERNATIONAL
Volume 61, Issue 5, Pages 1588-1599

Publisher

ELSEVIER SCIENCE INC
DOI: 10.1046/j.1523-1755.2002.00326.x

Keywords

autosomal dominant polycystic kidney disease; PKD1; PKD2; mutations; denaturing high-performance liquid chromatography

Funding

  1. NIDDK NIH HHS [R01 DK58816] Funding Source: Medline

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Background. Genetic analysis is a useful diagnostic tool in autosomal dominant polycystic kidney disease (ADPKD), especially when imaging results are equivocal. However, molecular diagnostics by direct mutation screening has proved difficult in this disorder due to genetic and allelic heterogeneity and complexity of the major locus, PKD1. Methods. A protocol was developed to specifically amplify the exons of PKD1 and PKD2 from genomic DNA as 150 to 450 bp amplicons. These fragments were analyzed by the technique of denaturing high-performance liquid chromatography (DHPLC) using a Wave Fragment Analysis System (Transgenomics) to detect base-pair changes throughout both genes, DHPI-C-detected changes were characterized by sequencing, Results. Cost effective and sensitive mutation screening of the entire coding regions of PKD1 and PKD2 by DHPLC was optimized. All base-pair mutations to these genes that we previously characterized were detected as an altered DHPLC profile. To assess this method for routine diagnostic use, samples from a cohort of 45 genetically uncharacterized ADPKD patients were analyzed. Twenty-nine definite mutations were detected, 26 PKD1, 3 PKD2 and a further five possible missense mutations were characterized leading to a maximal detection rate of 76%. A high level of polymorphism of PKD1 also was detected, with 71 different changes defined. The reproducibility of the DHPLC profile enabled the recognition of many common polymorphisms without the necessity for re-sequencing. Conclusions. DHPLC has been demonstrated to be an efficient and effective means for gene-based molecular diagnosis of ADPKD. Differentiating missense mutations and polymorphisms remains a challenge, but family-based segregation analysis is helpful.

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