Pedigree samples were collected from five ethnically and geographically different populations : Kirghizians, Turkmenians, Chuvashians, Israelis and Mexicans. All studied individuals were assessed for body height, weight and BMI. The sample size in the studied pedigrees ranged from 381 to 1811 individuals. Segregation analysis of these traits preliminarily adjusted for sex and age was performed by means of program package  that provides parameter estimates for the major gene effects, for the residual within the genotype correlations between relatives and for the assortative mating. By the usual transmission probability tests, the ' environmental ' model was strongly rejected for all measured traits in all 5 populations. The major gene mode of inheritance, however, was accepted for all traits. The results of analysis in 5 populations were remarkably similar, and showed that except for Mexican sample, the proportion of variance attributable to major gene effect ranged between 37 and 53 % for body weight and height. In the Mexican sample it explained only about 14 % of the body weight variation. The proportion of inter-individual variation in BMI attributable to major gene effect was consistently lower in all populations in comparison with height and weight and ranged between 17 and 40 %. Strong assortive mating in body height, as estimated by correlation between putative major gene genotypes in spouses, was found in four populations, not including Mexican pedigrees. In spite of the fact that human body height, weight and other anthropometric characteristics became the subject of quantitative genetics almost from the beginning of the present century, very little is known regarding the involvement of large-effect genes in their mode of inheritance, except for body mass index (BMI) and various measures of obesity (e.g. Comuzzie et al. 1995 ; Lecomte et al. 1997).The heritability estimates obtained in standard genetic investigations, utilizing variance

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. © 2000 Wiley‐Liss, Inc.

A review of advanced methods of segregation analysis of quantitative traits on human pedigree data is presented. Special attention was paid to formulation of genetic models tested in the analysis, to the possibility of statistical distinguishing between these models, to the power of the used transmission probability tests, and to the possibility of unambiguous interpretation of the analysis results.

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.

In a linkage analysis that requires the estimation of parameters other than the recombination fraction, we can construct a pedigree likelihood that leads to consistent parameter estimators if the sampling procedures are known. In particular, it is necessary to identify the subset of pedigree members "relevant to sampling" (RS), where by sampling we mean both pedigree ascertainment through a proband combination and the selective inclusion of the sampled pedigrees in the data that are analyzed. If both these procedures are independent of the marker phenotypes and the model of trait inheritance is known, then no sampling or ascertainment correction is needed to obtain a consistent estimator of the recombination fraction. Otherwise, the correction can be of two types: sampling-model-based, in which the ascertainment and inclusion procedures are modeled and used in the likelihood expression, or sampling-model-free, in which the data RS are "conditioned out" without any modeling of the sampling procedures. In either case, the pedigree proband sampling frame must be identified.