Genetic and epidemiological studies of non-insulin dependent diabetes mellitus (NIDDM) are complicated by several factors; these include: 1) diagnostic criteria based on truncation of continuous distribituion (i.e., diagnosis based on elevated fasting blood glucose on more than one occasion), 2) ascertainment of families based on diabetic probands, 3) etiological heterogeneity, and 4) association with other traits such as obesity. In response to these so called """"""""pitfalls"""""""", the aims of this proposal are to develop statistical methodologies which explicitly incorporate these issues and then to apply the results to pedigree data on NIDDM obtained from Starr County, Texas; a population which is 97% Mexican-American and characterized by age and sex specific prevalences of NIDDM which are three- to five-fold higher than the U.S. population at large. Accomplishement of the aims of this proposal will required extension of statistical theory, implementation of computing algorithms and programs, evaluation of the theory numerically, and application to real data. This research will permit evaluation of the sources of familial aggregation of NIDDM, coaggregation of NIDDM and obesity, and heterogeneity. Failure to explicitly account for the statistical issues posed by diagnostic criteria based on cutpoints of a continuous distribution and ascertainment of families when such is the case can lead to inferences of genetic and/or environmental etiology which are artifacts of inadequate correction and do not reflect underlying biological processes. For example, ascertainment of nuclear families having one child whose phenotypic value is above some cutpoint will lead to significant spouse pair correlations when in fact none may exist. This can result in inferences of common environmental effects or assortative mating which are functions of sampling and not biology. Furthermore, these issues are significant in that they also characterize studies of most common complex diseases of man which aggregate in families; indeed, the Lipid Research Clinic and several Specialized Centers of Research employ truncated sampling. Also, diseases besides diabetes are defined by arbitrary cutpoints including obesity and hypertension.
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