Emil Ginsburg

Evidence of major gene control of cortical bone loss in humans.

Cortical index (CI) is the ratio of the combined cortical thickness to the total diameter of the bone. It serves for the assessment of the geometric properties of bone and for indirect evaluation of bone mass. CI is a useful predictor of osteoporosis. The aim of the present study was to test the hypothesis of major gene control of CI variation in a large sample of pedigrees from Chuvashia, Russia. Complex segregation analysis revealed that the major gene model of CI inheritance is the best fitting and most parsimonious for the present data. Parameters of the genotype‐gender specific dependence of CI variation on age were estimated simultaneously with other parameters in the segregation analysis. The results of analysis showed that not only the baseline level of CI but also the age at onset of the involutive bone changes (inflection point) and the rate of the CI decrease with age (slope coefficient) are under control of the same major gene. Non‐major gene effects shared by pedigree members (residual familial correlations) were found to be statistically insignificant. Approximately 73% of inter‐individual variation in CI was attributable to the effects explicitly included in the model. Genet. Epidemiol. 19:410–421, 2000.

Genetics of human body size and shape: pleiotropic and independent genetic determinants of adiposity

The present study utilized pedigree data from three ethnically different populations of Kirghizstan, Turkmenia and Chuvasha. Principal component analysis was performed on a matrix of genetic correlations between 22 measures of adiposity, including skinfolds, circumferences and indices. Findings are summarized as follows: (1) All three genetic matrices were not positive definite and the first four factors retained even after exclusion RG > or = 1.0, explained from 88% to 97% of the total additive genetic variation in the 22 trials studied. This clearly emphasizes the massive involvement of pleiotropic gene effects in the variability of adiposity traits. (2) Despite the quite natural differences in pairwise correlations between the adiposity traits in the three ethnically different samples under study, factor analysis revealed a common basic pattern of covariability for the adiposity traits. In each of the three samples, four genetic factors were retained, namely, the amount of subcutaneous fat, the total body obesity, the pattern of distribution of subcutaneous fat and the central adiposity distribution. (3) Genetic correlations between the retained four factors were virtually non-existent, suggesting that several independent genetic sources may be governing the variation of adiposity traits. (4) Variance decomposition analysis on the obtained genetic factors leaves no doubt regarding the substantial familial and (most probably genetic) effects on variation of each factor in each studied population. The similarity of results in the three different samples indicates that the findings may be deemed valid and reliable descriptions of the genetic variation and covariation pattern of adiposity traits in the human species.

Sampling Correction in Pedigree Analysis

Usually, a pedigree is sampled and included in the sample that is analyzed after following a predefined non-random sampling design comprising several specific procedures. To obtain a pedigree analysis result free from the bias caused by the sampling procedures, a correction is applied to the pedigree likelihood. The sampling procedures usually considered are: the pedigree ascertainment, determining whether a population unit is to be sampled; the intrafamilial pedigree extension, determining what part of the pedigree is to be sampled; and selective censoring of the sampled pedigree, determining whether it should be included in the sample to be analyzed.The probability of pedigree ascertainment is determined by the total set of potential probands in the true pedigree from which the sampled pedigree is obtained and we indicate how the necessary information on this set can be collected. If insufficient information on this set is observed, it is impossible to correct the pedigree likelihood adequately. Here we show that, if only the structure of this set is known, then an ascertainment-model-based pedigree likelihood can be obtained by conditioning on this structure. An ascertainment-model-free (AMF) pedigree likelihood can be correctly constructed by conditioning on all the data in this set, i.e. on both its structure and its phenotypic content. However, if this set has missing data, the AMF likelihood becomes undefined, which limits the utility of this AMF approach originally proposed by Ewens and Shute (1986). We also consider the sampling correction necessary when the pedigrees included in the sample analyzed have been subjected to censoring. The forms of likelihood correction developed here provide asymptotically unbiased estimators of the genetic model only if the formulated model is correct, which means that it must correctly allow for the most important features of the true inheritance of the trait studied. Otherwise, if no special case of the formulated general model is close to the true inheritance model, then the forms of likelihood correction proposed here result in biases, the magnitude and direction of which depend on both the true model and the general analysis model that should subsume it.

Genetics of human body size and shape: evidence for an oligogenic control of adiposity.

In a previous study by the authors in each of the pedigree samples from Kirghizstan, Turkmenia and Chuvashia, four principal factors supposedly controlled by four non-overlapping gene subsets were found. About 90% of total variation of adiposity as assessed by 22 measurements of skinfolds, circumferences and indices were covered by these factors. This study provides results of segregation analysis of each of these four factors. By the usual transmission probability tests, major gene (MG) control was accepted in all 12 analyses--four traits in three populations. Some of the most parsimonious MG models included non-MG effects, such as correlation of residuals between spouses, between parent and offspring and between sibs. The Kirghizian samples showed a significant assortative mating effect as measured by the correlation between genotypic values at putative MG in spouses. The proportion of the trait variance attributable to the MG effect varied from 0.296 (factor F4 in the Chuvashia sample) to 0.596 (the same factor in the Kirghizian sample). It is assumed that four independent large-effect genes can be recognized in the genetic control of adiposity determining, respectively, individual predisposition to accumulate subcutaneous fat, its distribution between the body trunk and extremities, predisposition to accumulate inner fat and its distribution between the upper and lower body parts. In each population, unification of the four most parsimonious MG models forms oligogenic models explaining from 0.364 (Chuvashia) to 0.540 (Kirghizstan) of total adiposity.

Sample size required for predefined linkage decision quality

A method for estimating the sample size required to attain a predefined linkage decision quality (type I and type II errors) is proposed using the linkage test power estimate developed by Ginsburg et al. [(1996) Genet Epidemiol 13:355–366]. The method is applicable for samples of arbitrarily structured pedigrees collected via proband. Comparison of different ascertainment schemes and pedigree structures by their consequent minimal sample size was performed. For recessive and dominant inheritance with complete penetrance, the relative ranks of the ascertainment schemes are invariant regardless of the true recombination fraction value and the trait and marker gene frequencies, which enables one to point out the better scheme. The feasibility of evaluating a sampling strategy by the cost of pedigree collection is also considered, and comparison between these two methods of sample planning is performed. Genet. Epidemiol. 14:479–491,1997.