Akil Kaderbay1, François Berger2, Ali Bouamrani3, Marie Bidart4, Graciane Petre5, Ashley Baguant6, Ludovic Giraud6, Sébastien Schmerber6. 1. Department of oto-rhino-laryngology, Grenoble Alpes University Hospital, Avenue Maquis du Grésivaudan, 38700 La Tronche, France; Braintech Lab, INSERM unit 1205, Grenoble Alpes University, 38400 Saint Martin D'heres, France; Grenoble Alpes University, 38000 Grenoble, France. Electronic address: akil.kaderbay@gmail.com. 2. Braintech Lab, INSERM unit 1205, Grenoble Alpes University, 38400 Saint Martin D'heres, France; Grenoble Alpes University, 38000 Grenoble, France. 3. Medimprint, 38700 La Tronche, France. 4. Grenoble Alpes University, 38000 Grenoble, France; Medical molecular and genetic unit, Biology and pathology Institute, Grenoble Alpes University Hospital, 38700 La Tronche, France. 5. Braintech Lab, INSERM unit 1205, Grenoble Alpes University, 38400 Saint Martin D'heres, France. 6. Department of oto-rhino-laryngology, Grenoble Alpes University Hospital, Avenue Maquis du Grésivaudan, 38700 La Tronche, France; Braintech Lab, INSERM unit 1205, Grenoble Alpes University, 38400 Saint Martin D'heres, France; Grenoble Alpes University, 38000 Grenoble, France.
Abstract
INTRODUCTION: Sensorineural hearing losses (SNHLs) are a significant public health issue, and the hearing loss field is desperately in need of effective therapy. Pathophysiological mechanisms are not yet clearly understood in the absence of validated methods to assess the inner ear content. Proteomic and metabolomic analysis of perilymph is opening new research perspectives for SNHLs. We aimed to demonstrate the feasibility of an innovative mass spectrometry (MS) strategy using porous silicon chips (PSCs) to investigate the low molecular weight (LMW) protein and metabolite content of human perilymph. Our second objective was to stratify perilymph samples according to their MS profiles and compare these results with clinical data. MATERIAL AND METHODS: Perilymph samples obtained during cochlear implant surgery from patients with SNHLs were retrieved from a validated biobank. To focus on LMW entities, we used a PSC enrichment protocol before MALDI-ToF MS analysis. PSCs were used as a LMW molecular preanalytical stabilizer and amplifier. Patients' clinical data and SNHL characteristics were retrieved retrospectively from medical charts. RESULTS: We successfully acquired and compared 59 exploitable MS profiles out of 71 perilymph samples. There was a good correlation between duplicates. Comparing both ears from the same patient, we found good reproducibility even when there was a one-year interval between samplings. We identified three distinct groups when comparing the samples' metabolomic profiles and four homogeneous groups comparing their LMW proteome profiles. Clinical data analysis suggested that some groups shared clinical or preanalytical characteristics. CONCLUSION: This proof-of-concept study confirms that LMW proteome and metabolome content of perilymph can be analyzed with PSCs. Based on protein profiles, we managed to stratify perilymp samples according to their molecular composition. These results must be confirmed with a larger population, and sampling methods require improvement, but this approach seems promising. In the future, this approach may pave the way for companion test strategies to precisely diagnose and define potential molecular targets for audioprotective therapies.
INTRODUCTION: Sensorineural hearing losses (SNHLs) are a significant public health issue, and the hearing loss field is desperately in need of effective therapy. Pathophysiological mechanisms are not yet clearly understood in the absence of validated methods to assess the inner ear content. Proteomic and metabolomic analysis of perilymph is opening new research perspectives for SNHLs. We aimed to demonstrate the feasibility of an innovative mass spectrometry (MS) strategy using porous silicon chips (PSCs) to investigate the low molecular weight (LMW) protein and metabolite content of human perilymph. Our second objective was to stratify perilymph samples according to their MS profiles and compare these results with clinical data. MATERIAL AND METHODS: Perilymph samples obtained during cochlear implant surgery from patients with SNHLs were retrieved from a validated biobank. To focus on LMW entities, we used a PSC enrichment protocol before MALDI-ToF MS analysis. PSCs were used as a LMW molecular preanalytical stabilizer and amplifier. Patients' clinical data and SNHL characteristics were retrieved retrospectively from medical charts. RESULTS: We successfully acquired and compared 59 exploitable MS profiles out of 71 perilymph samples. There was a good correlation between duplicates. Comparing both ears from the same patient, we found good reproducibility even when there was a one-year interval between samplings. We identified three distinct groups when comparing the samples' metabolomic profiles and four homogeneous groups comparing their LMW proteome profiles. Clinical data analysis suggested that some groups shared clinical or preanalytical characteristics. CONCLUSION: This proof-of-concept study confirms that LMW proteome and metabolome content of perilymph can be analyzed with PSCs. Based on protein profiles, we managed to stratify perilymp samples according to their molecular composition. These results must be confirmed with a larger population, and sampling methods require improvement, but this approach seems promising. In the future, this approach may pave the way for companion test strategies to precisely diagnose and define potential molecular targets for audioprotective therapies.