Clinical proteome informatics workbench detects pathogenic mutations in hereditary amyloidoses

Surendra Dasari, Jason D. Theis, Julie A. Vrana, Roman M. Zenka, Michael T. Zimmermann, Jean-Pierre Kocher, W Edward Jr. Highsmith, Paul J. Kurtin, Ahmet Dogan

Research output: Contribution to journalArticle

22 Citations (Scopus)

Abstract

Shotgun proteomics of hereditary amyloid deposits generates all the information necessary to identify pathogenic mutant peptides and proteins. However, these mutant peptides are invisible to traditional database search strategies. We developed a two-pronged informatics workflow for detecting both known and novel amyloidogenic mutations from clinical proteomics data sets. We implemented the workflow in a CAP/CLIA certified clinical laboratory dedicated for proteomic subtyping of amyloid deposits extracted from formalin-fixed paraffin-embedded specimens. Performance of the workflow was characterized on a validation cohort of 49 hereditary amyloid samples, with confirmed mutations, and 85 controls. The sensitivity, specificity, positive predictive value, and negative predictive value of the known mutation detection workflow were determined to be 92%, 100%, 100%, and 96%, respectively. For novel mutation detection workflow, these performance parameters were 82%, 99%, 99%, and 90%, respectively. Validated workflow was applied to detect amyloidogenic mutations from a clinical cohort of 150 amyloid samples. The known mutation detection workflow detected rare frame shift mutations in apolipoprotein A1 and fibrinogen alpha amyloid deposits. The novel mutation detection workflow uncovered unanticipated mutations (W22G and C71Y) of the serum amyloid A4 protein present in patient amyloid deposits. In summary, clinical amyloid proteomics data sets contain mutant peptides of clinical significance that are recoverable with improved bioinformatics.

Original languageEnglish (US)
Pages (from-to)2352-2358
Number of pages7
JournalJournal of Proteome Research
Volume13
Issue number5
DOIs
StatePublished - May 2 2014

Fingerprint

Familial Amyloidosis
Medical Informatics
Workflow
Proteome
Amyloid
Mutation
Amyloid Plaques
Proteomics
Deposits
Peptides
Clinical laboratories
Amyloid beta-Peptides
Apolipoprotein A-I
Frameshift Mutation
Informatics
Bioinformatics
Firearms
Paraffin
Fibrinogen
Mutant Proteins

Keywords

  • amyloidosis
  • bioinformatics
  • clinical specimens
  • mutations
  • proteomics

ASJC Scopus subject areas

  • Biochemistry
  • Chemistry(all)

Cite this

Clinical proteome informatics workbench detects pathogenic mutations in hereditary amyloidoses. / Dasari, Surendra; Theis, Jason D.; Vrana, Julie A.; Zenka, Roman M.; Zimmermann, Michael T.; Kocher, Jean-Pierre; Highsmith, W Edward Jr.; Kurtin, Paul J.; Dogan, Ahmet.

In: Journal of Proteome Research, Vol. 13, No. 5, 02.05.2014, p. 2352-2358.

Research output: Contribution to journalArticle

Dasari, S, Theis, JD, Vrana, JA, Zenka, RM, Zimmermann, MT, Kocher, J-P, Highsmith, WEJ, Kurtin, PJ & Dogan, A 2014, 'Clinical proteome informatics workbench detects pathogenic mutations in hereditary amyloidoses', Journal of Proteome Research, vol. 13, no. 5, pp. 2352-2358. https://doi.org/10.1021/pr4011475
Dasari, Surendra ; Theis, Jason D. ; Vrana, Julie A. ; Zenka, Roman M. ; Zimmermann, Michael T. ; Kocher, Jean-Pierre ; Highsmith, W Edward Jr. ; Kurtin, Paul J. ; Dogan, Ahmet. / Clinical proteome informatics workbench detects pathogenic mutations in hereditary amyloidoses. In: Journal of Proteome Research. 2014 ; Vol. 13, No. 5. pp. 2352-2358.
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