Dataset Information

Quantification of amyloid protein enrichment by mass spectrometry improves typing of amyloidosis

ABSTRACT: Amyloidosis typing is crucial to determine the best therapeutic strategy for patients. Since conventional histological techniques often fail, the identification of amyloid precursors by mass spectrometry became the new standard. However, without quantification, selecting the amyloid precursor from proteins that may be ubiquitous under non-pathological conditions may be equivocal. Therefore, we quantified protein enrichment in amyloid deposits to improve typing. Protein enrichment was measured by extracted ion chromatogram based label-free (LFX) quantification by comparing a microdissected amyloid area with a non-amyloid area. We assessed the discrimination ability of candidate precursors with this approach compared to the two practiced identification methods. As proof of concept, we selected seven cases, 5 typical of the most common amyloidosis subtypes and typed by immunostainings (IHC), 2 unconclusive after immunohistochemistry. Proteins associated with amyloid deposits were identified in all samples confirming the pathology. When the routine clinical mass spectrometric identification techniques allowed unambiguous conclusions for 2/3 of 7 cases, quantification of the enrichment ratio in the amyloid deposit allowed unambiguous precursor selection in all cases. Quantification of precursor enrichment in amyloid deposits is a promising optimization for amyloidosis typing. Incorporated into routine clinical processes, it will improve patient care in difficult diagnostic situations.

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ORGANISM(S): Homo Sapiens (human)

SUBMITTER: Dupuy Jean-William

LAB HEAD: Anne-Aurelie Raymond

PROVIDER: PXD039814 | Pride | 2026-05-25

REPOSITORIES: Pride

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Publications

Quantitative enrichment of amyloid precursors refines mass spectrometry-based amyloidosis diagnosis.

Di Tommaso Sylvaine S Chauveau Bertrand B Dourthe Cyril C Dupuy Jean-William JW Saltel Frédéric F Bail Brigitte Le BL Raymond Anne-Aurélie AA

Clinical proteomics 20260317 1

<h4>Introduction</h4>Amyloidosis typing is crucial to determine the best therapeutic strategy for patients. Since conventional histological techniques often fail, the identification of amyloid precursors by mass spectrometry has become the new standard. However, without quantification, selecting the amyloid precursor from proteins that may be ubiquitous under non-pathological conditions can be equivocal. Therefore, we quantified protein enrichment in amyloid deposits to improve amyloidosis typin ...[more]

PMID: 41845213

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Project description:Cardiac amyloidosis is a severe clinical condition leading to restrictive cardiomyopathy and heart failure. With increasing options for specific treatment of different cardiac amyloid diseases, correct amyloid subtyping is essential for clinical outcome. Mass spectrometry-based methods for cardiac amyloid subtyping have become important diagnostic tools but are currently used only in a few reference laboratories. Such methods typically include laser-capture microdissection to ensure the specific analysis of amyloid deposits. While this strategy effectively reduces background signals, it is a labor-intensive and costly procedure hampering the implementation of these methods into a wider group of laboratories. Here we introduce a more direct proteomics-based method for subtyping of cardiac amyloids. Endomyocardial biopsies were retrospectively analyzed from fresh frozen material of 78 patients with cardiac amyloidosis and from 12 biopsies of unused donor heart explants. Cryostat sections were directly digested with trypsin and analyzed with the nano-liquid chromatography (nLC-MS/MS), and the data were evaluated by a proteomic software. With a diagnostic threshold set to 70% for each of the four most common amyloid proteins affecting the heart (LC k, LC l, TTR and SAA), 65 of the cases (87%) could be diagnosed, and of these, 61 cases (94%) were in concordance with the original diagnoses. The specimens were also analyzed for the summed intensities of the amyloid signature proteins (ApoE, ApoA-IV and SAP). The summed intensities were significantly higher (p<0.001) for all assigned amyloid cases, whereas unassigned cases were not significantly different from controls and had lower signals than the assigned cases (p<0.001), suggesting that signature proteins can serve as in situ quality markers of cardiac amyloid deposits. We argue that this efficient workflow can be useful for disseminating proteomics for cardiac amyloid subtyping into accredited clinical laboratories.

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