INNOVATIONS IN RESEARCH OF HEREDITARY DEAFNESS
2020
INTRODUCTION: Deafness is the most common sensory disability in humans affecting all aspects of life. Approximately 50% of congenital deafness is hereditary and about half of genetic deafness is still unsolved. To date, more than 150 genes are known to cause hearing loss worldwide, with specific genes contributing to deafness in distinct populations. Of these, more than 20 genes are involved in deafness among the Jewish Israeli hearing-impaired population. The most common gene in many worldwide populations, including Israel, is GJB2, which encodes the connexin 26 protein. The second most common gene among Jews is TMC1, with most pathogenic variants found only among Jews of Moroccan origin. Most other pathogenic variants found in the Jewish population are origin-specific and not found in other Jewish ethnic groups or in other worldwide populations. In patients where hereditary deafness is suspected, known variants in the specific ethnicity are routinely examined. In Israel, the GJB2 gene is screened in all cases of hereditary deafness and the TMC1 gene is screened in deaf persons of Jewish Moroccan origin. In cases where no variant is found in a known gene, more comprehensive diagnostic tests should be used. Since the beginning of the deep sequencing era, less than a decade ago, the number of deafness-related genes in the Jewish population has increased by threefold. Identifying the pathogenic variant makes it possible to study molecular pathogenesis, to anticipate and understand the prognosis, to calculate probability of concomitant morbidity, to offer prenatal diagnosis, prevent recurrence of deafness in the family and early rehabilitation. Currently, cochlear implant offers the greatest chance for rehabilitation. The hope is that understanding the molecular pathogenesis will in the future lead to personalized medical treatment. We review the genetics of deafness, with an emphasis on the Jewish population in Israel, new diagnostic methods and suggest a diagnostic algorithm and future treatment methods.
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