Literature DB >> 31752543

Immunoelectron microscopy and mass spectrometry for classification of amyloid deposits.

Niels Abildgaard1,2,3,4, Aleksandra M Rojek1,5, Hanne Eh Møller1,5, Nicolai Bjødstrup Palstrøm1,6, Charlotte Guldborg Nyvold1,3,7, Lars Melholt Rasmussen1,6, Charlotte Toftmann Hansen1,2, Hans Christian Beck1,6, Niels Marcussen1,5.   

Abstract

Amyloidosis is a shared name for several rare, complex and serious diseases caused by extra-cellular deposits of different misfolded proteins. Accurate characterization of the amyloid protein is essential for patient care. Immunoelectron microscopy (IEM) and laser microdissection followed by tandem mass spectrometry (LMD-MS) are new gold standards for molecular subtyping. Both methods perform superiorly to immunohistochemistry, but their complementarities, strengths and weaknesses across amyloid subtypes and organ biopsy origin remain undefined. Therefore, we performed a retrospective study of 106 Congo Red positive biopsies from different involved organs; heart, kidney, lung, gut mucosa, skin and bone marrow. IEM, performed with gold-labelled antibodies against kappa light chains, lambda light chains, transthyretin and amyloid A, identified specific staining of amyloid fibrils in 91.6%; in six biopsies amyloid fibrils were not identified, and in two, the fibril subtype could not be established. LMD-MS identified amyloid protein signature in 98.1%, but in nine the amyloid protein could not be clearly identified. MS identified protein subtype in 89.6%. Corresponding specificities ranged at organ level from 94-100%. Concordance was 89.6-100% for different amyloid subtypes. Importantly, combined use of both methods increased the diagnostic classification to 100%. Some variety in performances at organ level was observed.

Entities:  

Keywords:  Amyloidosis; immune electron microscopy; laser microdissection; mass spectrometry; proteomics

Year:  2019        PMID: 31752543     DOI: 10.1080/13506129.2019.1688289

Source DB:  PubMed          Journal:  Amyloid        ISSN: 1350-6129            Impact factor:   7.141


  7 in total

1.  Disrupting the DREAM transcriptional repressor complex induces apolipoprotein overexpression and systemic amyloidosis in mice.

Authors:  Pirunthan Perampalam; Haider M Hassan; Grace E Lilly; Daniel T Passos; Joseph Torchia; Patti K Kiser; Andrea Bozovic; Vathany Kulasingam; Frederick A Dick
Journal:  J Clin Invest       Date:  2021-02-15       Impact factor: 14.808

2.  The Clinical Impact of Proteomics in Amyloid Typing.

Authors:  Michelle M Hill; Surendra Dasari; Peter Mollee; Giampaolo Merlini; Catherine E Costello; Bouke P C Hazenberg; Martha Grogan; Angela Dispenzieri; Morie A Gertz; Taxiarchis Kourelis; Ellen D McPhail
Journal:  Mayo Clin Proc       Date:  2021-04-09       Impact factor: 11.104

3.  Classification of Amyloidosis by Model-Assisted Mass Spectrometry-Based Proteomics.

Authors:  Nicolai Bjødstrup Palstrøm; Aleksandra M Rojek; Hanne E H Møller; Charlotte Toftmann Hansen; Rune Matthiesen; Lars Melholt Rasmussen; Niels Abildgaard; Hans Christian Beck
Journal:  Int J Mol Sci       Date:  2021-12-28       Impact factor: 5.923

4.  Basement membrane proteins in various arterial beds from individuals with and without type 2 diabetes mellitus: a proteome study.

Authors:  Lasse Bach Steffensen; Xenia Emilie Sinding Iversen; Rasmus Søgaard Hansen; Pia Søndergaard Jensen; Anne-Sofie Faarvang Thorsen; Jes Sanddal Lindholt; Lars Peter Schødt Riber; Hans Christian Beck; Lars Melholt Rasmussen
Journal:  Cardiovasc Diabetol       Date:  2021-09-08       Impact factor: 9.951

5.  A Pilot Study of Rare Renal Amyloidosis Based on FFPE Proteomics.

Authors:  Shuang Meng; Wenwen Xia; Li Xia; Li Zhou; Jing Xu; Xiaoxia Pan; Liyuan Meng
Journal:  Molecules       Date:  2021-11-29       Impact factor: 4.411

6.  FAST-IT: Find A Simple Test - In TIA (transient ischaemic attack): a prospective cohort study to develop a multivariable prediction model for diagnosis of TIA through proteomic discovery and candidate lipid mass spectrometry, neuroimaging and machine learning-study protocol.

Authors:  Austin G Milton; Stephan Lau; Karlea L Kremer; Sushma R Rao; Emilie Mas; Marten F Snel; Paul J Trim; Deeksha Sharma; Suzanne Edwards; Mark Jenkinson; Timothy Kleinig; Erik Noschka; Monica Anne Hamilton-Bruce; Simon A Koblar
Journal:  BMJ Open       Date:  2022-04-01       Impact factor: 2.692

7.  Combined Subcutaneous Fat Aspirate and Skin Tru-Cut Biopsy for Amyloid Screening in Patients with Suspected Systemic Amyloidosis.

Authors:  Charlotte Toftmann Hansen; Hanne E H Møller; Aleksandra Maria Rojek; Niels Marcussen; Hans Christian Beck; Niels Abildgaard
Journal:  Molecules       Date:  2021-06-15       Impact factor: 4.411

  7 in total

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