Genetic analysis of the Stanford LRC family study data. I. Structured exploratory data analysis of height and weight measurements

A new methodology for determining mode for inheritance of continuously distributed traits in nuclear families, structured exploratory data analysis (SEDA), is described and applied to height and weight measurements. The family data were collected as part of the Lipid Research Clinic's collaborative study (LRC) and consists of first degree relatives of Stanford University employees who were selected either as a 2% random sample or were identified through a high lipid value. The variables are all standardized using three methods of age and sex adjustment based on two reference populations. The analysis and interpretations are based on the following statistics and indices: 1) the major gene index (MGI (alpha); 2) two measures of correlations between the midparental value and offspring (MPCC); and 3) the offspring between parent functions (OBP (beta). Consistent with a number of other studies, the results support that height shows multifactorial inheritance while height is principally under the influence of non-genetic environmental factors. In contrast to the random families, the male children of the probands who were selected due to their high lipid values exhibit height measurements which appear to involve environmental components or some major gene concomitants. The difference between the random and high lipid families is supported by all three statistical methods.