Theory and Practice in Quantitative Genetics

With the rapid advances in molecular biology, the near completion of the human genome, the development of appropriate statistical genetic methods and the availability of the necessary computing power, the identification of quantitative trait loci has now become a realistic prospect for quantitative geneticists. We briefly describe the theoretical biometrical foundations underlying quantitative genetics. These theoretical underpinnings are translated into mathematical equations that allow the assessment of the contribution of observed (using DNA samples) and unobserved (using known genetic relationships) genetic variation to population variance in quantitative traits. Several statistical models for quantitative genetic analyses are described, such as models for the classical twin design, multivariate and longitudinal genetic analyses, extended twin analyses, and linkage and association analyses. For each, we show how the theoretical biometrical model can be translated into algebraic equations that may be used to generate scripts for statistical genetic software packages, such as Mx, Lisrel, SOLAR, or MERLIN. For using the former program a web-library (available from http://www.psy.vu.nl/mxbib) has been developed of freely available scripts that can be used to conduct all genetic analyses described in this paper

Dependent Hazards in Multivariate Survival Problems

A new class of bivariate survival distributions is constructed from a given family of survival distributions. The properties of these distributions are analyzed. It is shown that the same bivariate survival function can be derived using two radically different concepts: one involves transformation of the well-known bivariate survival function; the other involves correlated stochastic hazards. The new conditions that guarantee negative associations of life spans are derived. An exponential representation of the survival function for two related individuals is derived in terms of the conditional distribution of the stochastic hazards among survivors. Versions of the multivariate correlated gamma-frailty model are investigated.correlated hazards bivariate frailty, bivariate survival, mortality models

Multistate models of postpartum infecundity, fecundability and sterility by age and parity: Methodological issues

How do hidden physiological processes influence estimates of fecundability and sterility? Does unobserved heterogeneity play a role in these estimates? To address these questions mathematical models of the reproductive process are needed. It is not well known how to evaluate characteristics of reproductive models based on observed reproductive history data, and such models may not be identifiable without ancillary information. However, little is known about how to introduce ancillary information into reproductive models. Furthermore, even if such information was involved, the use of standard software packages for maximization of the likelihood function is often not feasible, because the function cannot be represented in an explicit parametric form. In this paper we propose an approach which represents the likelihood function in a form useful for further analysis. This approach is based on multistate models of the basic physiological processes that influence reproductive outcomes, and it is suitable in applications where ancillary information is given in the form of hazard rates. As an alternative, a competing risks model with incomplete information is discussed.Reproductive history models, Unobserved heterogeneity, Fertility Submitted by C.M. Suchindran,

Power of non-parametric linkage analysis in mapping genes contributing to human longevity in long-lived sib-pairs

This report investigates the power issue in applying the non-parametric linkage analysis of affected sib-pairs (ASP) [Kruglyak and Lander, 1995: Am J Hum Genet 57:439-454] to localize genes that contribute to human longevity using long-lived sib-pairs. Data were simulated by introducing a recently developed statistical model for measuring marker-longevity associations [Yashin et al., 1999: Am J Hum Genet 65:1178-1193], enabling direct power comparison between linkage and association approaches. The non-parametric linkage (NPL) scores estimated in the region harboring the causal allele are evaluated to assess the statistical power for different genetic (allele frequency and risk) and heterogeneity parameters under various sampling schemes (age-cut and sample size). Based on the genotype-specific survival function, we derived a heritability calculation as an overall measurement for the effect of causal genes with different parameter settings so that the power can be compared for different modes (dominant, recessive) of inheritance. Our results show that the ASP approach is a powerful tool in mapping very strong effect genes, both dominant and recessive. To map a rare dominant genetic variation that reduces hazard of death by half, a large sample (above 600 pairs) with at least one extremely long-lived (over age 99) sib in each pair is needed. Again, with large sample size and high age cut-off, the method is able to localize recessive genes with relatively small effects, but the power is very limited in case of a dominant effect. Although the power issue may depend heavily on the true genetic nature in maintaining survival, our study suggests that results from small-scale sib-pair investigations should be referred with caution, given the complexity of human longevity. © 2004 Wiley-Liss, Inc