Conclusion
AFib amyloid can be identified reliably in glomerular amyloid by proteomics using a score-based algorithm. Proteomics data should be used as a guide to AFib diagnosis, with the results considered together with all available clinical and laboratory information.
Methods
Proteomics data from 1001 Congo red-positive patient samples were examined using the Mascot search engine to interrogate the Swiss-Prot database and generate protein identity scores. An algorithm was applied to identify FibA as the amyloid protein based on Mascot scores. FibA variants were identified by appending the known amyloidogenic variant sequences to the Swiss-Prot database.
Results
AFib amyloid was identified by proteomics in 64 renal samples based on the Mascot scores relative to other amyloid proteins, the presence of a pathogenic variant, and coverage of the p.449-621 sequence. Contamination by blood could be excluded from a comparison of the FibA score with that of the fibrinogen β and γ chains. The proteomics results were consistent with the clinical diagnosis. Four additional renal samples did not fulfill all the criteria using the algorithm but were adjudged as AFib amyloid based on a full assessment of the clinical and biochemical results.