Matrix-Assisted Laser Desorption Ionization Mass Spectrometry Imaging: a novel Tool for the Identification and Classification of Amyloidosis

Amyloidosis is a group of diseases caused by extracellular accumulation of fibrillar polypeptide aggregates. So far, diagnosis is performed by Congo red staining of tissue sections in combination with polarization microscopy. Subsequent identification of the causative protein by immunohistochemistry harbors some difficulties regarding sensitivity and specificity. Mass spectrometry-based approaches have been demonstrated to constitute a reliable method to supplement typing of amyloidosis, but still depend on Congo red staining. In the present study matrix-assisted laser desorption/ionization mass spectrometry imaging coupled with ion mobility separation (MALDI-IMS MSI) was used to investigate amyloid deposits in formalin-fixed and paraffin-embedded tissue samples. We designed a peptide filter method enabling the identification of tryptic peptides derived from amyloidogenic and amyloid-associated proteins without additional tandem mass spectrometry. Utilizing the filter we found a universal peptide signature for amyloidoses independent from amyloid type and histoanatomical localization. Examining a validation cohort of cardiac biopsies including 66 amyloid and 31 non-amyloid cases, amyloidosis was diagnosed with high sensitivity and specificity. Furthermore, differences in the peptide composition of AL-lambda and ATTR amyloid were revealed and used to build a reliable classification model. Integrating the peptide filter in MALDI-IMS MSI analysis we developed a bioinformatics workflow facilitating the identification and classification of amyloidosis in a less time and sample consuming experimental setup. Our findings demonstrate also the feasibility to investigate the amyloid's composition, thus paving the way to establish classification models for the diverse types of amyloidoses and to shed further light on the complex process of amyloidogenesis.