The genetic epidemiology of patterns of change in growth will be investigated in order to achieve a more complete understanding of genetic and familial factors influencing long-term growth patterns in human beings. Highly reliable, extensive serial data for growth-related variables that have well-known health significance will be used to study genetic influences on the patterns of change in these variables. In the Fels Longitudinal Growth Study, growth data have been measured semi-annually from birth into adulthood for more than 600 participants in numerous large kindreds (extended families). Growth patterns will be described for these data using mathematical models that will allow the derivation of biologically interpretable growth-pattern variables. Known genes associated with growth regulation (i.e., candidate genes) have been selected and will be studied to determine their role in the observed growth patterns. This will be accomplished by performing genetic linkage studies between growth pattern traits and restriction fragment length polymorphisms (RFLPS) near the candidate genes (i.e., markers for these genes). The RFLPS, within known distances of the candidate genes, will be recognized using restriction nuclease analysis of DNA from nucleated blood cells in which they are isolated by electrophoresis, then hybridized and autoradiographed. The selected candidate genes include those for somatostatin, growth hormone, chorionic somatomammotropin, insulin-like growth factors I and II, insulin and the receptors for insulin and growth hormone. Their selection for this study is based on the occurrence of polymorphisms near these genes, know chromosomal location, and the availability of DNA probes for restriction fragment length polymorphism studies. As a result of this study, information will be obtained concerning patterns of human growth, the prevalence of polymorphisms for growth-related genes, and associations between growth patterns and growth genes within and among families. A primary aim of the study is to establish the extent to which major genes explain the variance in human growth patterns and adult status. The analyses will encompass many statistical and modem genetic epidemiological methodologies including examination of the distributions of derived growth-pattern variables, sex adjustments, identification of associations, segregation analyses, and genetic linkage analyses. Possible linkage of growth pattern variables with the RFLPs will be analyzed using sib-pair methods for initial studies and maximum likelihood procedures to obtain conventional log odds ratio (lod) scores.
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