OBJECTIVE: Approximately half of the variance of Age-Related Hearing Impairment (ARHI) is attributable to environmental risk factors, and the other half to genetic factors. None of these genes has ever been identified, but the genes involved in monogenic nonsyndromic hearing impairment are good candidates. Here we define and validate a quantitative trait value for ARHI, correcting for age and gender, to allow the genetic study of ARHI as a quantitative trait. DESIGN: Based on the ISO 7029 standard, we convert audiometric data into a Z-score, an age- and gender-independent value expressing to what extent a person is affected by ARHI. The validity of this approach is checked using a test population of randomly collected subjects. The power to evaluate the contribution of a candidate gene to ARHI is assessed using simulated populations. As an example, one ARHI candidate gene is analyzed. RESULTS: In our test population, Z-scores were normally distributed although the mean did not equal zero. Z-scores were independent of age, and there was no difference between men and women. Power studies using simulated populations indicated that to detect moderate genetic effects, sample sizes of at least 500 random subjects are necessary. CONCLUSION: The Z-score conversion appears to be a valid method to describe to what extent a subject is affected by ARHI, allowing to compare persons from different age and gender. This method can be the basis of future, powerful studies to identify ARHI genes.
OBJECTIVE: Approximately half of the variance of Age-Related Hearing Impairment (ARHI) is attributable to environmental risk factors, and the other half to genetic factors. None of these genes has ever been identified, but the genes involved in monogenic nonsyndromic hearing impairment are good candidates. Here we define and validate a quantitative trait value for ARHI, correcting for age and gender, to allow the genetic study of ARHI as a quantitative trait. DESIGN: Based on the ISO 7029 standard, we convert audiometric data into a Z-score, an age- and gender-independent value expressing to what extent a person is affected by ARHI. The validity of this approach is checked using a test population of randomly collected subjects. The power to evaluate the contribution of a candidate gene to ARHI is assessed using simulated populations. As an example, one ARHI candidate gene is analyzed. RESULTS: In our test population, Z-scores were normally distributed although the mean did not equal zero. Z-scores were independent of age, and there was no difference between men and women. Power studies using simulated populations indicated that to detect moderate genetic effects, sample sizes of at least 500 random subjects are necessary. CONCLUSION: The Z-score conversion appears to be a valid method to describe to what extent a subject is affected by ARHI, allowing to compare persons from different age and gender. This method can be the basis of future, powerful studies to identify ARHI genes.
Authors: Zubair M Ahmed; Rizwan Yousaf; Byung Cheon Lee; Shaheen N Khan; Sue Lee; Kwanghyuk Lee; Tayyab Husnain; Atteeq Ur Rehman; Sarah Bonneux; Muhammad Ansar; Wasim Ahmad; Suzanne M Leal; Vadim N Gladyshev; Inna A Belyantseva; Guy Van Camp; Sheikh Riazuddin; Thomas B Friedman; Saima Riazuddin Journal: Am J Hum Genet Date: 2010-12-23 Impact factor: 11.025
Authors: Rick A Friedman; Lut Van Laer; Matthew J Huentelman; Sonal S Sheth; Els Van Eyken; Jason J Corneveaux; Waibhav D Tembe; Rebecca F Halperin; Ashley Q Thorburn; Sofie Thys; Sarah Bonneux; Erik Fransen; Jeroen Huyghe; Ilmari Pyykkö; Cor W R J Cremers; Hannie Kremer; Ingeborg Dhooge; Dafydd Stephens; Eva Orzan; Markus Pfister; Michael Bille; Agnete Parving; Martti Sorri; Paul H Van de Heyning; Linna Makmura; Jeffrey D Ohmen; Frederick H Linthicum; Jose N Fayad; John V Pearson; David W Craig; Dietrich A Stephan; Guy Van Camp Journal: Hum Mol Genet Date: 2008-12-01 Impact factor: 6.150
Authors: Dina L Newman; Laurel M Fisher; Jeffrey Ohmen; Robert Parody; Chin-To Fong; Susan T Frisina; Frances Mapes; David A Eddins; D Robert Frisina; Robert D Frisina; Rick A Friedman Journal: Hear Res Date: 2012-10-25 Impact factor: 3.208
Authors: E Van Eyken; G Van Camp; E Fransen; V Topsakal; J J Hendrickx; K Demeester; P Van de Heyning; E Mäki-Torkko; S Hannula; M Sorri; M Jensen; A Parving; M Bille; M Baur; M Pfister; A Bonaconsa; M Mazzoli; E Orzan; A Espeso; D Stephens; K Verbruggen; J Huyghe; I Dhooge; P Huygen; H Kremer; C W R J Cremers; S Kunst; M Manninen; I Pyykkö; A Lacava; M Steffens; T F Wienker; L Van Laer Journal: J Med Genet Date: 2007-05-18 Impact factor: 6.318
Authors: Erik Fransen; Vedat Topsakal; Jan-Jaap Hendrickx; Lut Van Laer; Jeroen R Huyghe; Els Van Eyken; Nele Lemkens; Samuli Hannula; Elina Mäki-Torkko; Mona Jensen; Kelly Demeester; Anke Tropitzsch; Amanda Bonaconsa; Manuela Mazzoli; Angeles Espeso; Katia Verbruggen; Joke Huyghe; Patrick L M Huygen; Sylvia Kunst; Minna Manninen; Amalia Diaz-Lacava; Michael Steffens; Thomas F Wienker; Ilmari Pyykkö; Cor W R J Cremers; Hannie Kremer; Ingeborg Dhooge; Dafydd Stephens; Eva Orzan; Markus Pfister; Michael Bille; Agnete Parving; Martti Sorri; Paul Van de Heyning; Guy Van Camp Journal: J Assoc Res Otolaryngol Date: 2008-06-10