Segregation analysis of hypospadias: a reanalysis of published pedigree data.
Little is known about the cause of hypospadias, one of the most common urogenital anomalies in males. Familial clustering of hypospadias is well recognized, with heritability estimated to be about 70% under a simple multifactorial threshold model. Neither alternative genetic mechanisms nor shared environmental factors within families have been explored fully. To learn more about possible genetic mechanisms, we used 2 methods of segregation analysis to analyze a set of published family data. These analyses are based on the families of 103 probands with hypospadias, who were ascertained through surgery departments in Denmark [Sørensen, 1953]. Urogenital examinations were performed on 95% (n = 1,510) of available male relatives, and 2.2% were found to have hypospadias. Within the probands' nuclear families, 12% of nonproband sons of normal fathers were affected. Using the mixed model of inheritance, both the autosomal dominant (AD) and codominant models fit these data better than either autosomal recessive (AR) or multifactorial models. Using the regressive logistic models, both AD and AR models were equally likely, and a model of nonMendelian sibship clustering gave a better fit to these data. These inconsistent findings illustrate the difficulties commonly encountered in segregation analysis. Using 2 different statistical approaches, we found 2 different explanations, both of which differ from the autosomal recessive model originally suggested by Sørensen [1953]. Hypospadias in these families is almost certainly heterogeneous. Determining the cause of familial clustering of hypospadias will require careful delineation of persons with recognized syndromes from uncomplicated cases and detailed information on potential prenatal risk factors.
Harris
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Department of Epidemiology, School of Hygiene and Public Health, Johns Hopkins University, Baltimore, Maryland 21205.
Beaty
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D005260:Female; D006801:Humans; D007021:Hypospadias / Q000235:genetics*; D008297:Male; D008957:Models, Genetic; D010375:Pedigree; D012044:Regression Analysis