Expression of serum proteins in noise induced hearing loss workers of mining based industry.

Noise Induced Hearing Loss (NIHL) is caused by excessive noise exposure due to occupational activities thus affects communication and quality of life. Prolonged occupational and environmental exposure to loud noise damages key molecules present in the micro-machinery of the ear which are required for the mechano-electrical transduction of sound waves in cochlea. Specific proteins are known to be associated with hearing loss and related structural and functional disabilities in the human inner, outer hair cells and cochlea. Rationale of this study was to identify the cochlear proteins associated with the pathophysiology of NIHL using proteomic approaches in mining based industrial workers. Total (n = 210) samples were collected from mining based industrial workers of central India. Subjects were categorized based on audiometric analysis. Proteome changes of the host serum were investigated using one and two-dimensional electrophoresis in combination with LC-MS/MS and MALDI-TOF-MS. Up-regulated 46 cochlear proteins among confirmed NIHL cases were identified by MASCOT. Shrinkage discriminant analysis provided top 25 discriminating feature proteins namely myosin, transthyretin, SERPIN, CCDC50, enkurin, transferin etc. The identified potential proteins may be used as biomarkers for early detection and to understand the pathogenic mechanism of NIHL. Evaluation of these biomarkers in follow-up cases may further aid in improving NIHL diagnosis. SIGNIFICANCE: Human proteome study in Noise Induced Hearing Loss (NIHL) cases has not been published till date. This study represents most comprehensive proteomic analysis in NIHL cases taken from Indian mine workers. The identified key twenty-five discriminating feature proteins which are upregulated when an individual develops (or is in stage of development of) NIHL, provides insights into the potential roles of these varied proteins in disease progression. The proteins thus identified by proteomic approach may be used as early diagnostic biomarker to predict the occurrence of disease at very early stage.