Clinical proteome informatics workbench detects pathogenic mutations in hereditary amyloidoses

Area of Science:

• Proteomics
• Genetics
• Clinical Diagnostics

Background:

• Shotgun proteomics can identify pathogenic mutant peptides in hereditary amyloid deposits.
• Traditional database search strategies fail to detect these mutant peptides.

Purpose of the Study:

• To develop and validate a bioinformatics workflow for detecting known and novel amyloidogenic mutations from clinical proteomics data.
• To improve the identification of clinically significant mutant peptides in amyloid deposits.

Main Methods:

• A two-pronged informatics workflow was developed for mutation detection.
• The workflow was implemented in a CAP/CLIA certified clinical laboratory.
• Performance was validated on hereditary amyloid samples and controls.

Main Results:

• The workflow demonstrated high sensitivity and specificity for known (92% sensitivity, 100% specificity) and novel (82% sensitivity, 99% specificity) mutation detection.
• Rare frame shift mutations in apolipoprotein A1 and fibrinogen alpha were identified.
• Novel mutations (W22G, C71Y) in serum amyloid A4 protein were discovered.

Conclusions:

• Clinical proteomics data contains clinically significant mutant peptides that are recoverable with improved bioinformatics.
• The developed workflow enhances the proteomic subtyping of amyloid deposits.
• This approach advances the diagnosis and understanding of hereditary amyloidosis.