Tinnitus is the most frequent phantom sensation, affecting 70 million individuals in Europe. It dramatically increases with age, with near 40% of the elderlies experiencing tinnitus. It can be severely debilitating, increasing the risk for sick leave, disability pension and even suicide. While prevalence is higher in men, women, shows greater psychological burden and loss of life quality, suggesting that different coping mechanisms operate in the two genders. From a genetic perspective, we recently found that specific forms of tinnitus displayed significant heritability in men, albeit when segregated according to age, young women showed such high genetic influences. On this basis, TIGER aims to provide three major insights needed for long-lasting prevention and therapy for tinnitus through the principal goals: i) the identification of environmental risk factors to define non-genetic risks of developing severe tinnitus; ii) the identification of novel genetic and blood biomarkers. The insights from the two first aims will be used to iii) stratify disease risk and elaborate preventive medical recommendations for high-risk subgroups of tinnitus patients and to define molecular drivers/biological pathways relevant for the development of severe tinnitus that will be used to identify and validate new therapeutic targets. Here, we will use epidemiological lifestyle, nutritional, and medical analytical data from large Swedish longitudinal and Italian retrospective studies, and molecular genetics, coupled to in-depth tinnitus phenotyping beyond current clinical practice.
The project consists in 5 major objectives:
Aim 1 - To identify novel environmental risk factors for developing tinnitus in each gender.
Aim 2 - To identify potential genetic determinants for tinnitus in each sex
Aim 3 - To identify Genetic and Environmental interactions that synergistically increase risk for tinnitus for each sex and gender.
Aim 4 - To identify potential blood biomarkers for tinnitus for each gender.
Aim 5 - To generate predictive algorithms based on the collected data.
