In recent years, a group of diseases has become the topic of advanced training for clinicians, i.e., amyloidoses. These are caused by misfolding of proteins into amyloid fibrils that deposit at different tissue- and organ-sites causing various diseases. Once considered a rare disease, it has become almost endemic.

We have not yet fully understood the pathomechanisms responsible for the different clinical manifestations of amyloidoses. In search for key players in disease progression, recent research uncovered that the fibril conformation is likely not the sole reason for differential clinical manifestations. Hence, the analysis of the overall amyloid proteome and specifically co-deposition of amyloid-associated compounds may shed light upon the underlying disease mechanisms. Understanding these mechanisms will provide earlier diagnosis and advanced therapy for patients suffering from an often lately detected, and potentially fatal disease.

For our studies, we selected formalin-fixed and paraffin-embedded (FFPE) heart explants diagnosed with the most common cardiac amyloid types, i.e., immunoglobulin light chain- (AL) and transthyretin-derived amyloid (ATTR). We coupled two methods to liquid chromatography tandem mass spectrometry (LC-MS/MS). At first, Congo red staining visualized the distribution of amyloid histologically and guided tissue sampling with varying amyloid load for the generation of tissue microarrays (TMAs). Selected samples of the TMAs were then processed for bottom-up LC-MS/MS followed by label-free intensity (LFI) profiling. This method correlates protein abundance to a target LFI profile such as the amyloid load, amyloid-associated or amyloidogenic proteins. One case each of AL and ATTR amyloidosis with comprehensive LFI profiling, were further investigated by mounting FFPE tissue sections directly on Bruker IntelliSlides. Tryptic digestion was followed by matrix-assisted laser desorption/ionization trapped ion mobility spectrometry (MALDI TIMS) imaging (timsTOF fleX, Bruker). After data acquisition, a list of peptides previously related to proteins associated with amyloid supervised a segmentation analysis of the imaging data and identified two clusters in each amyloidosis case (Fig.). Laser microdissection (LMD) sampled these selected clusters, which were then forwarded to LC-MS/MS for a more in-depth proteomic composition analysis.

Both workflows were able to allocate tissue regions with variable amounts of amyloid and differences in the abundance of amyloidogenic- and amyloid-associated proteins. This enables us to discuss potentially disease-related mechanisms and amyloid-related compounds, and to compare AL- to ATTR deposition.

In summary, both methods have proven their potential to characterize the cardiac amyloid proteome. Hence, these workflows will produce a comprehensive knowledge gain with each sample analyzed, which in turn will ideally help to reduce numbers of lately diagnosed amyloidosis in the near future.