Familial aggregation of tinnitus: a European multicentre study.

INTRODUCTION AND AIM: Tinnitus is a common condition affecting approximately 20% of the older population. There is increasing evidence that changes in the central auditory system following cochlear malfunctioning are responsible for tinnitus. To date, few investigators have studied the influence of genetic factors on tinnitus. The present report investigates the presence of a familial effect in tinnitus subjects. METHODS: In a European multicentre study, 198 families were recruited in seven European countries. Each family had at least 3 siblings. Subjects were screened for causes of hearing loss other than presbyacusis by clinical examination and a questionnaire. The presence of tinnitus was evaluated with the question "Nowadays, do you ever get noises in your head or ear (tinnitus) which usually last longer than five minutes". Familial aggregation was tested using three methods: a mixed model approach, calculating familial correlations, and estimating the risk of a subject having tinnitus if the disorder is present in another family member. RESULTS: All methods demonstrated a significant familial effect for tinnitus. The effect persisted after correction for the effect of other risk factors such as hearing loss, gender and age. The size of the familial effect is smaller than that for age-related hearing impairment, with a familial correlation of 0.15. CONCLUSION: The presence of a familial effect for tinnitus opens the door to specific studies that can determine whether this effect is due to a shared familial environment or the involvement of genetic factors. Subsequent association studies may result in the identification of the factors responsible. In addition, more emphasis should be placed on the effect of role models in the treatment of tinnitus.

Genetic Geostatistical Framework for Spatial Analysis of Fine-Scale Genetic Heterogeneity in Modern Populations: Results from the KORA Study.

Aiming to investigate fine-scale patterns of genetic heterogeneity in modern humans from a geographic perspective, a genetic geostatistical approach framed within a geographic information system is presented. A sample collected for prospective studies in a small area of southern Germany was analyzed. None indication of genetic heterogeneity was detected in previous analysis. Socio-demographic and genotypic data of German citizens were analyzed (212 SNPs; n = 728). Genetic heterogeneity was evaluated with observed heterozygosity (H O ). Best-fitting spatial autoregressive models were identified, using socio-demographic variables as covariates. Spatial analysis included surface interpolation and geostatistics of observed and predicted patterns. Prediction accuracy was quantified. Spatial autocorrelation was detected for both socio-demographic and genetic variables. Augsburg City and eastern suburban areas showed higher H O values. The selected model gave best predictions in suburban areas. Fine-scale patterns of genetic heterogeneity were observed. In accordance to literature, more urbanized areas showed higher levels of admixture. This approach showed efficacy for detecting and analyzing subtle patterns of genetic heterogeneity within small areas. It is scalable in number of loci, even up to whole-genome analysis. It may be suggested that this approach may be applicable to investigate the underlying genetic history that is, at least partially, embedded in geographic data.