Mutations of TMC1 cause deafness by disrupting mechanoelectrical transduction

Abstract

Objective: Mutations of transmembrane channel-like 1 gene (TMC1) can cause dominant (DFNA36) or recessive (DFNB7/B11) deafness. In this article, we describe the characteristics of DFNA36 and DFNB7/B11 deafness, the features of the Tmc1 mutant mouse strains, and recent advances in our understanding of TMC1 function.

Methods: Publications related to TMC1, DFNA36, or DFNB7/B11 were identified through PubMed.

Results: All affected DFNA36 subjects showed post-lingual, progressive, sensorineural hearing loss (HL), initially affecting high frequencies. In contrast, almost all affected DFNB7/B11 subjects demonstrated congenital or prelingual severe to profound sensorineural HL. The mouse Tmc1 gene also has dominant and recessive mutant alleles that cause HL in mutant strains, including Beethoven, deafness, and Tmc1 knockout mice. These mutant mice have been instrumental for revealing that Tmc1 and its closely related paralog Tmc2 are expressed in cochlear and vestibular hair cells, and are required for hair cell mechanoelectrical transduction (MET). Recent studies suggest that TMC1 and TMC2 may be components of the long-sought hair cell MET channel.

Conclusion: TMC1 mutations disrupt hair cell MET.

Keywords: DFNA36; DFNB7/B11; Hearing loss; Mechanoelectrical transduction; TMC1; TMC2.

Fig. 1

Age-related typical audiograms for three families, LMG128, LMG248 and W06-792. (a) In LMG128, hearing loss was evident in the first decade of life and rapidly progressed to severe to profound deafness by the second decade of life. (b) In LMG248, hearing loss was reported in the second decade of life and progressed to profound levels by the fourth or fifth decade. (c) In family W06-792, hearing loss was noticed in the first to second decade, starting at high frequencies and rapidly progressing to severe to profound levels in the third or fourth decade. Numbers near the lines in the graph indicate ages in decade steps. We estimated age-matched hearing thresholds by plotting audiogram data of all the affected subjects in each frequency and depicting a polynomial trendline using the Mac version of Microsoft Excel.