| HOME | HELP | FEEDBACK | SUBSCRIPTIONS | ARCHIVE | SEARCH | TABLE OF CONTENTS |
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
EDITORIAL COMMENT |
Social, Genetic and Developmental Psychiatry Research Centre Institute of Psychiatry King’s College London Denmark Hill London UK SE5 8AF Email: r.plomin@iop.kcl.ac.uk
The article by Raynor et al. (1) shows there is a lot of life left in the old workhorse of the twin method. In the excitement about the Human Genome Project and advances in molecular genetics, it is reasonable but wrong to think there is no longer any need for such quantitative genetic analyses that involve anonymous components of variance like heritability when we can work with the genes themselves that are responsible for heritability. Would that it were so: It has been much more difficult than expected to identify specific genes that contribute to the heritability of complex traits like personality, probably because there are many genes involved, which makes it difficult to pick up the signal of a single gene from the background noise. An important feature of the twin method and other quantitative genetic methods is that they are not limited to specific genes or to specific measures of the environment. They skip down to the bottom line of genetic and environmental influences. That is, regardless of how many genes affect a trait, these methods assess the overall effect of those genes on the phenotypic variance of a trait in the population.
In a postgenomic era in which the genome sequence, all genes, and all DNA variation are known, quantitative genetic methods will be more rather than less important because they can chart the course for molecular genetics. The most rudimentary information is heritability: You cannot find genes associated with a trait if the trait is not heritable. However, heritability estimates are not much help because everything seems to be heritable to some extent. No reader will be surprised to learn that in the Raynor et al. study, depressive symptoms show significant heritability because no area of psychopathology reliably shows zero heritability. Nonetheless, some traits may be more heritable than others, although very large samples are needed to prove differential heritability. For example, in the study by Raynor et al., hostility seems to show less heritability than the other traits, which confirms findings from other twin studies reviewed in their introduction.
The most interesting example of the usefulness of heritability estimates is the application of quantitative genetic techniques to ostensible measures of the environment, such as social support. The study by Raynor et al. shows the greatest heritability not for hostility or depression but for social support! This is amazing because social support has been used in hundreds of studies as a measure of the environment. The Raynor et al. result fits with the results of dozens of quantitative genetic studies that treat environmental measures as phenotypes and find evidence for significant genetic influence (2). This is a new direction for quantitative genetic research that has been called the nature of nurture. How can a measure of the environment show genetic influence? The answer is that measures such as social support are not measures of the environment independent of the individual like the weather. Psychosocial environments always involve the person. Genetically influenced characteristics of people, such as their personality, psychopathology, and cognitive abilities, can influence their perceptions and actual experiences of the quantity and quality of their social networks. The message from this body of research on the nature of nurture, confirmed by the Raynor et al. study, is that we need to shift from thinking about the organism as the passive recipient of environmental influences to a more active model that recognizes genetic contributions to how people select, modify, and construct their environments and how they construct and reconstruct their experiences in memory.
In addition to studying the nature-nurture interface, another example of using quantitative genetics to go beyond merely estimating heritability is multivariate genetic analysis, which is at the core of the study by Raynor et al. Multivariate genetic analysis focuses on the covariance between traits rather than the variance of each trait considered separately. Just as univariate genetic analysis decomposes the phenotypic variance of a trait into genetic and environmental components of variance, multivariate genetic analysis decomposes phenotypic covariance between traits into genetic and environmental components of covariance. Raynor et al. show that depression, hostility, and social support are correlated phenotypically. They use multivariate genetic analysis to show that these phenotypic correlations are largely mediated by genetic sources of covariance (see Table 2 in Raynor et al., Ref. 1). In other words, if you found a gene that contributed to the variance of depression, chances are that the same gene would also be associated with hostility and with social support. The way multivariate genetic analysis works is to compare the cross-trait cross-twin covariance for monozygotic and dizygotic twins. That is, instead of correlating one twin’s depression with the other twin’s depression, you correlate one twin’s depression with the other twin’s social support. If the cross-correlation for monozygotic twins exceeds the cross-correlation for dizygotic twins, this implies that genetic factors contribute to the phenotypic correlation between depression and social support.
As Raynor et al. point out, another important concept from multivariate genetic analysis is the genetic correlation. The genetic correlation is the correlation between genetic effects on two traits regardless of the heritabilities of the traits. (When Raynor et al. say that phenotypic correlations are mediated genetically, they are referring to the genetic correlation weighted by the heritabilities of the traits.) You can think about a genetic correlation as the likelihood that a gene found to be associated with one trait is also associated with the other trait. Genetic correlations are also substantial in the Raynor et al. study.
Multivariate genetic analysis is key for charting the course for molecular genetic analysis because it shows how to carve nature at its joints. As Raynor et al. indicate in the last sentence of their article, what is really needed is a multivariate genetic analysis between these psychosocial characteristics (depression, hostility, and social support) and cardiovascular disease itself. That is, although Raynor et al. show that depression, hostility, and social support overlap largely for genetic reasons, and although we know these psychosocial characteristics predict cardiovascular disease, it does not necessarily follow that the phenotypic association between these psychosocial characteristics and cardiovascular disease is mediated genetically.
REFERENCES
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| HOME | HELP | FEEDBACK | SUBSCRIPTIONS | ARCHIVE | SEARCH | TABLE OF CONTENTS |
