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Variability in pathogenicity prediction programs: impact on clinical diagnostics.

ABSTRACT: Current practice by clinical diagnostic laboratories is to utilize online prediction programs to help determine the significance of novel variants in a given gene sequence. However, these programs vary widely in their methods and ability to correctly predict the pathogenicity of a given sequence change. The performance of 17 publicly available pathogenicity prediction programs was assayed using a dataset consisting of 122 credibly pathogenic and benign variants in genes associated with the RASopathy family of disorders and limb-girdle muscular dystrophy. Performance metrics were compared between the programs to determine the most accurate program for loss-of-function and gain-of-function mechanisms. No one program correctly predicted the pathogenicity of all variants analyzed. A major hindrance to the analysis was the lack of output from a significant portion of the programs. The best performer was MutPred, which had a weighted accuracy of 82.6% in the full dataset. Surprisingly, combining the results of the top three programs did not increase the ability to predict pathogenicity over the top performer alone. As the increasing number of sequence changes in larger datasets will require interpretation, the current study demonstrates that extreme caution must be taken when reporting pathogenicity based on statistical online protein prediction programs in the absence of functional studies.

SUBMITTER: Walters-Sen LC

PROVIDER: S-EPMC4367082 | biostudies-literature | 2015 Mar

REPOSITORIES: biostudies-literature

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Variability in pathogenicity prediction programs: impact on clinical diagnostics.

Walters-Sen Lauren C LC Hashimoto Sayaka S Thrush Devon Lamb DL Reshmi Shalini S Gastier-Foster Julie M JM Astbury Caroline C Pyatt Robert E RE

Molecular genetics & genomic medicine 20141203 2

Current practice by clinical diagnostic laboratories is to utilize online prediction programs to help determine the significance of novel variants in a given gene sequence. However, these programs vary widely in their methods and ability to correctly predict the pathogenicity of a given sequence change. The performance of 17 publicly available pathogenicity prediction programs was assayed using a dataset consisting of 122 credibly pathogenic and benign variants in genes associated with the RASop ...[more]

PMID: 25802880

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Project description:A database of apparently benign copy number variants (bCNVs) detected by a Spectral Genomics Inc./PerkinElmer BAC array platform has been maintained through the University of Utah Comparative Genomic Hybridization laboratory since 2005. The target population for this database represents 1275 patients with abnormal phenotypes, primarily children referred for developmental delay and mental retardation. These bCNVs are independent of any identified copy number abnormality detected. The most common 35 bCNVs observed and their frequencies are reported here, and a subset of ten of the patients studied was evaluated on a new oligonucleotide CNV array set designed by Agilent Technologies. There was a 76% concordance of calls detected by both array platforms in the same patients; the discordant regions may be due to differences in reference DNAs, or false positive/negative results on either array. The higher resolution of the Agilent oligonucleotide array compared to the BAC array allowed for further characterization to determine precise breakpoints of the observed CNVs, in addition to documenting additional CNVs of smaller sizes. As expected, observed CNVs and their frequencies were generally consistent with those of other previously published and available databases, including the Database of Genomic Variants (http://projects.tcag.ca/variation/). The availability of these data should assist other clinical laboratories in the evaluation of CNVs of unknown clinical significance. The Cytogenetics Laboratory at the University of Utah has been using aCGH to evaluate DNA derived from blood of patients with developmental delay, mental retardation and “syndromic” or dysmorphic phenotypes since 2005. From this database, we were able to determine which clones represented sequences which were frequently deleted or duplicated in our patient population. We identified our most common CNV regions and then selected DNAs from ten patients who exhibited copy number changes of those common regions for further study with the Agilent CNV microarray set. Normal male or female DNA from Promega was used as a sex-mismatched control. In addition to the ten clinical specimens, two self-self experiments for two patient samples were analyzed to estimate a false positive rate and to fine tune the parameters used for data analysis. A replicate hybridization was performed on one patient to determine reproducibility.

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Variability in pathogenicity prediction programs: impact on clinical diagnostics.

Publications

Variability in pathogenicity prediction programs: impact on clinical diagnostics.

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