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Personalized Proteomics for Precision Diagnostics in Hearing Loss: Disease-Specific Analysis of Human Perilymph by Mass Spectrometry

Authors: Heike A. Schmitt; Andreas Pich; Nils K. Prenzler; Thomas Lenarz; Jennifer Harre; Hinrich Staecker; Martin Durisin; +1 Authors

Personalized Proteomics for Precision Diagnostics in Hearing Loss: Disease-Specific Analysis of Human Perilymph by Mass Spectrometry

Abstract

Despite a vast amount of data generated by proteomic analysis on cochlear fluid, novel clinically applicable biomarkers of inner ear diseases have not been identified hitherto. The aim of the present study was to analyze the proteome of human perilymph from cochlear implant patients, thereby identifying putative changes of the composition of the cochlear fluid perilymph due to specific diseases. Sampling of human perilymph was performed during cochlear implantation from patients with clinically or radiologically defined inner ear diseases like enlarged vestibular aqueduct (EVA; n = 14), otosclerosis (n = 10), and Ménière's disease (n = 12). Individual proteins were identified by a shotgun proteomics approach and data-dependent acquisition, thereby revealing 895 different proteins in all samples. Based on quantification values, a disease-specific protein distribution in the perilymph was demonstrated. The proteins short-chain dehydrogenase/reductase family 9C member 7 and esterase D were detected in nearly all samples of Ménière's disease patients, but not in samples of patients suffering from EVA and otosclerosis. The presence of both proteins in the inner ear tissue of adult mice and neonatal rats was validated by immunohistochemistry. Whether these proteins have the potential for a biomarker in the perilymph of Ménière's disease patients remains to be elucidated.

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Keywords

Chemistry, QD1-999

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
18
Top 10%
Average
Top 10%
Green
gold