The Genetic Epidemiology of Growth and Development

Bradford Towne, Ph.D., Ellen W. Demerath, Ph.D., and Stefan A. Czerwinski, Ph.D.

Lifespan Health Research Center, Wright State University School of Medicine, Kettering, Ohio introduction

In spite of the predominant role of genetic variation in causing the observed variability among children in their growth and development, studies of genetic influences on growth and development are few in comparison to the plethora of descriptive studies, population comparisons, and studies of the impact of specific environmental factors. There are two main reasons for this. First, the courses of study that many investigators of growth and development are trained under (e.g., physical anthropology or human biology) usually provide little formal training in human genetics and statistical genetic analysis. And second, to study genetic influences on growth and development, data from related children are needed. Preferably those data are longitudinal, and ideally they are longitudinal data from large numbers of related children reared under different household environments. Unfortunately, such data are very rare.

The purpose of this chapter is to provide an overview of the genetic epidemiology of normal human growth and development. Although a treatise on quantitative genetic approaches to the study of growth and development is beyond the scope of the chapter, as is a complete review of the existing literature on the genetics of growth and development, the references and suggested readings provide a good starting point for the interested student to pursue further study. This chapter is meant to serve as an introduction to how auxologists can most profitably approach the study of the genetics of growth and development today.

Almost half a century ago Neel and Schull1 proposed that the epidemiological approach can be extended to the study of nondiseased states and argued that, "genetic concepts must be an integral part of the armamentarium of the modern epidemiologist" (p. 302). The "epidemiological genetics" that Neel and Schull envisioned has become known as genetic epidemiology. On the establishment of the International Genetic Epidemiology Society (IGES) in 1992, its founding president, James V. Neel, succinctly defined genetic epidemiology as, "The study of genetic components in complex biological phenomena" (IGES website, IGES). From this perspective, the genetic epidemiology of growth and development may be considered as the study of the genetic underpinnings of the size, conformation, and maturity status of individuals over the course of childhood. This includes characterizing the magnitude of genetic influences on growth and development phenotypes, examining how those genetic influences operate over time, identifying and localizing specific genetic polymorphisms that contribute to variation in growth and development, and elucidating how genetic and environmental factors interact during growth and development. The advances made over the last two decades in both molecular and statistical genetics make possible the sophisticated analyses needed to elucidate the roles of genes and environment in the complex biological phenomena that constitute growth and development.

This chapter is divided as follows. We begin with an introduction to basic statistical genetic terminology. Next, different study designs used to examine genetic influences on quantitative traits are discussed. Then, we summarize published findings from various studies of the genetics of growth and development. After that, we present findings from current genetic epidemiological studies of the growth and development of U.S. children in the Fels Longitudinal Study and Nepali children in the newly established Jiri Growth Study. Throughout the chapter, important terms or concepts are in boldface the first time they are mentioned. Brief definitions of these terms and concepts can be found in the Glossary.

statistical genetic terms and concepts

Statistical genetics refers to a variety of methods for analyzing phenotypic variation among related individuals. These methods include those tailored for the study of both discrete and continuous traits. Most growth and development phe-notypes exhibit a continuous distribution over a delimited range, and because the growth and development status of a child can usually be measured in some way, most growth and development phenotypes are quantitative traits. Growth and development phenotypes also are referred to as being complex traits, meaning that genes at a few and perhaps several loci contribute to the variation observed in the trait, as do environmental factors, possibly through interaction with those genes. The field of quantitative genetics deals with the analysis of complex traits. As with any specialized field of study, it contains a number of specific terms and concepts. This section provides a brief discussion of those quantitative genetic terms and the concepts most important for an understanding of the genetic epidemiology of normal growth and development. Thorough discussion of quantitative genetic methods can be found in books listed in the Suggested Reading section.

To start with, because related individuals are not independent but share some of their genes by virtue of a common ancestry, it is necessary to consider their degree of relatedness in assessing their degree of resemblance for a trait. The kinship coefficient between two individuals is the probability that an allele taken at random from the two alleles at a locus in one individual is identical to an allele taken at random from the two alleles at the same locus in another individual. The kinship coefficient between first degree relatives is 0.25, meaning that, for example, between a pair of full siblings there is a 25% chance that at a locus each has the very same allele that they each inherited from a common ancestor.

Most of what we know about the genetic control of growth and development comes from family-based studies, in which the correlations between relatives and between unrelated individuals for a trait such as stature or weight are calculated. The basic premise underlying these investigations is straightforward: If the variation in a trait is largely under genetic control, then related individuals will be more similar for the trait than unrelated individuals (i.e., the intrafamily variance of the trait is low compared to the interfamily variance). Conversely, if the variation in a trait is only partly determined by genes, then related individuals may resemble each other only a little bit more than unrelated individuals (i.e., the intrafamily variance of the trait is a little smaller than the interfamily variance).

Through examination of correlations between different pairs of relatives, heri-tabilities can be calculated. The concept of heritability (h2) is central to understanding the nature of genetic control for any trait. The heritability of a trait is a measure of the degree of genetic control of a phenotype, ranging from 0% (no genetic effects) to 100% (complete genetic effects). Heritabilities are population level estimates, specific to a particular population in a given environment, and this can sometimes be an important consideration when comparing h2 estimates across populations.

According to classical quantitative genetics theory (e.g., Falconer and Mackay,2 Lynch and Walsh3) the observed phenotypic variation (op) in a trait can be expressed as the sum of both genetic (o|) and random environmental effects (oj). This is written as

Relatedness of Individuals


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