Genetics: Gene-Environment Interaction
GENETICS: GENE-ENVIRONMENT INTERACTION
Fundamentally, the science of genetics is concerned with the explanation of differences among organisms. Some theories and methods pertain to the differences among species; others concern the individual differences among members of the same species—the subject matter of this section.
Historically, Mendelian genetics was categorical, dealing with individual differences that could be characterized by assignment of individuals to one or another of two or three categories. Analytic logic compared the observed categorical status of individuals to expectations (hypotheses) derived from Mendel's theory. As long as category assignment was unambiguous, it was a matter of small concern that there might exist individual differences within categories, derived presumably from environmental sources or from genes other than the one under examination. Enormous advances in understanding the basics of inheritance were made from the comfortably simple logical stance of "all and only" causal analysis—all cases of a particular genotype (genetic constitution) were accompanied by the particular phenotype (a measured or observed attribute), and all cases of the phenotype occurred in the presence of that genotype. There were some puzzling exceptions, however. Sometimes, individuals who almost certainly had a particular genotype did not display the associated phenotype. Furthermore, it was observed that the actual manifestation of the phenotype could vary greatly among individuals with the same genotype (with respect to the relevant single locus). Explanations were sought for these cases of reduced penetrance or variable expressivity both in terms of the effects of "modifier" genes or of environmental influence on the phenotype.
The biometrical approach to inheritance concerned phenotypic domains that were not dior trichotomous but were instead continuously distributed. Individuality was measured as variance rather than as categorical membership and the logic underlying analysis concerned the degree of phenotypic similarity of individuals of differing degrees of biological relatedness. Initially thought to concern a fundamentally different type of inheritance from the Mendelian, it was shown early in the twentieth century that the basic difference was in the effect size of the relevant genetic factors. Quantitative or continuously distributed phenotypes were theorized to be due to the collective influence of many genes (polygenic inheritance), each of which acted according to Mendelian rules but with individually small effects. The statistical model of quantitative genetics identifies both genetic and environmental sources of individuality, and partitions the variability among individuals into components attributable to these domains. The model also necessarily acknowledges, by means of interaction and covariance terms, the possibilities of interrelationships of factors from these domains.
Thus, with respect both to classical genes of major categorical effect and the polygenes of quantitatively distributed phenotypes, the possibility that the influences of genes are importantly conditioned by environmental context must be considered. This section will provide examples of the interconnectedness of genetic and environmental effects with particular reference to age and aging, including both classical statistical interaction and reciprocal influence between the genetic and environmental domains. It is not intended to be an exhaustive review, but merely to be illustrative of the types of interaction and co-action that can be expected as research on genetic influence on aging processes advances.
Gene-environment interactions
Simply defined, gene-environment interaction refers to situations in which environmental influences have a different effect depending upon genotype, and genetic factors have a differential effect depending upon features of the environment. Such interactions have been found in a wide array of phenotypes in diverse organisms across the phyletic spectrum. Particularly persuasive are data from experimental settings, where different environmental circumstances can be imposed upon groups of differing genotypes. Numerous studies, for example, have shown that different inbred strains of animals respond differently to environmental variables (McClearn et al.). Inbreeding is simply the mating of relatives, which has the effect of reducing genetic heterogeneity in the offspring. Thus, after a number of consecutive generations of inbreeding, the animals within each inbred strain approach the condition of being genetically identical (technically, homozygous in like state at all loci). Because of the stochastic nature of the process through which the homozygosity is achieved, different strains inevitably have different genotypes. Thus, phenotypic differences between strains tested under the same conditions are evidence of genetic influence on the phenotype, even though specific genetic information concerning the number and chromosomal locations of the relevant polygenes is unknown. Similarly, strain differences in the impact of an administered environmental variable reveal a genetic basis for susceptibility to that environmental intervention.
Another genetic procedure available to the animal model researcher is selective breeding. Animals of a genetically heterogeneous population are measured for a particular phenotype; a subset of those with highest values and another subset with lowest values are selected. The "high" animals are mated together, as are the "low" animals. If there is any heritable influence on the phenotype, then offspring from the high-phenotype matings should have higher phenotypic values than that of the entire population from which their parents were selected, and similarly, the offspring from the matings of low-phenotype parents should have lower values. In subsequent generations, with similar continued selection, the increasing phenotypic separation of the high and low lines constitutes clear evidence of the existence of genetic factors affecting the phenotype. By contrast to inbred strains, in which the particular genotypes were simply made homogeneous without regard to any specific phenotype, bidirectionally selected lines represent contrasting groups in which (ideally) all of the genetic factors promoting a high level of phenotypic expression have been concentrated in one group and those promoting a low level in the other group. Such lines are powerful resources for testing hypotheses concerning the physiological mechanisms through which the genes are expressed. Both inbred strains and selected lines offer evidence on gene-environment interaction.
Several investigators have employed selective breeding for early and late onset of reproduction in Drosophila in order to generate long-lived and short-lived lines. Luckinbill and colleagues have described a clear example of gene-environment interaction in the course of these selection studies. When selection is attempted from an environment in which larval density is high, the results of selection have been positive; when larval density was thinned, however, no response to selection occurred. The first result gives unequivocal evidence of the existence of genetic variance of the selected trait under the crowded condition, and indicates absence of this genetic variance in the less crowded environment.
Some of the most pertinent mammalian examples concern rodent learning. A classic example is that of Cooper and Zubek, who assessed the influence of different rearing environments on the maze-learning performance of better learners and poorer learners produced by selective breeding. Samples of animals from each line were reared under controlled, environmentally enriched or environmentally impoverished conditions. Overall, the influence of environment was clear, with the number of errors in the test situation declining from the impoverished through the control to the enriched condition. However, the interaction with genotype was notable. The "bright" rats were adversely affected by the impoverished environment, but were not facilitated by the enriched one; the "dull" rats were not affected by impoverishment, but were improved substantially by enrichment. It is clear that the results can be stated equally as (1) the effect of the genotypic differences depending on the environment, or (2) the effect of the environment depending on the genotype.
With animals derived from a similar selective breeding program, McGaugh and Cole added the dimension of age. Samples of the "maze-bright" and "maze-dull" rats were measured at about one month and about five months of age. The environmental feature under examination was the degree of massing of practice during maze learning. When the intertrial interval was only thirty seconds, at the younger age, there were no differences between the lines in performance. When the intertrial interval was thirty minutes, young bright animals performed better than the dull animals. Interaction with sex was also observed: Although all older animals benefitted from distribution of practice, older females of the two lines did not differ under either degree of massing, but older bright males outperformed older dull males.
Sprott provided similar evidence from a study of passive avoidance learning in inbred mice. At a particular foot shock level, animals of one strain (C57BL/6) were superior to another (DBA/2) at five weeks of age, but were inferior at five months of age. These illustrative results collectively make it clear that the interaction of environments and genes may not be uniform temporally. The existence or nature of the interaction can change across age.
A final example of the use of inbred strains in detecting gene-environment interaction in phenomena of gerontological interest is the study of Fosmire and colleagues. Motivated by the inconsistent evidence that aluminum exposure may be a risk factor for the development of Alzheimer's disease, these investigators examined the effect of an elevated aluminum content in the diet of mice on brain aluminum levels. Five different inbred strains were studied, with a control group and a treatment group within each strain. There were different brain aluminum levels among the control animals who had the regular laboratory diet, showing a heritable basis for differential uptake of the metal under "ordinary" conditions. When exposed to the aluminum enriched diet, the treatment animals of three strains did not differ from the control animals of the same strain. One strain showed a slight effect, and one displayed a large response, with brain aluminum levels over three times that of their controls. These results indicate that there exist genetic factors that influence the physiological processes affecting uptake and distribution of dietary aluminum. Although this study does not address the possible pathophysiological consequences of aluminum, its heuristic value lies in showing a genetic basis of responsitivity to environment. By extension, we may presume that the principle applies generally, whether the environmental feature is a putative toxin or a putative therapeutic pharmaceutical.
It will be noted that the above examples have all concerned anonymous complexes of polygenes. The recent advances in characterizing the human genome and those of other model organisms have provided a potent research approach to the individuating of some of the polygenes in such systems, with greatly enhanced insights into the nature of the genetic influence on quantitative traits, and also of the interaction of the genes with environments. The large number of genotype markers now available make it possible to describe the approximate location on the chromosomes of genes of detectable influence on a particular phenotype. These genes, not described in molecular terms, are called quantitative trait loci (QTLs). A remarkable demonstration of the potential of QTL analysis in gerontology has been provided by Vieira and others, who identified QTLs affecting longevity in populations of Drosophila maintained under five environmental conditions: three different maintenance temperatures, a single heat shock exposure, or restricted nutrients. The results were a remarkable assortment of interactions. Seventeen QTLs were identified. One has an influence on life span only in the high temperature environment; another only in the starvation environment. Several are specific to one sex only, and in only some environments. One is specific to females and the same allele that has positive influence on life span in the control environment has a negative effect in the high temperature environment. Another has opposite effects in males and females in the heat-shock environment, and one similarly has opposite effects in males and females in the high temperature environment. An overall quantitative genetic analysis revealed that all of the genetic variance was to be found in the interactions of sex X genotype and environment X genotype!
Some loci may have an influence that is substantially additive across the usually encountered environments; others may be so sensitive as to be influencing the phenotype in some environments but not in others, and perhaps in different directions in different environments.
Reciprocal influence of genes and environments
In addition to the types of interaction cited above, there are other ways in which the effects of genes and environments are intertwined: environments can influence gene expression, and genes may affect the array of environments to which an organism is exposed (or exposes itself). These processes can lead to correlation between genotype and environment.
The influence of environment on the expression of genes was classically demonstrated in the operon model of Jacob and Monod, a landmark in the history of molecular genetics. Changes in the nutrient composition of the media of E. coli resulted in the "turning on" of the organism's gene that produces the appropriate enzyme for metabolism of lactose. Subsequent research on gene regulation has revealed that the particular genes of an organism that are being expressed may differ from time to time, both developmentally and in response to environmental factors. There has been, for example, a burgeoning of information about the effects of various stressors on gene expression. Described as "heat shock genes" because of the early experimental situations involving brief administration of a high-temperature environment to bacteria and Drosophila, this literature now includes examples of various environmental stresses both in vitro and in vivo, and in several species. As a general summary, these stressors have the effect of inhibiting the typical ongoing protein production of the cells, and promoting the translation of genes that produce a class of proteins that have a protective function in the cells. The rich detail of this research area complements the generalization that has emerged from quantitative genetic analyses in a variety of species, plant as well as animal, that the heritability of quantitatively distributed traits—the portion of the phenotypic variance attributable to genetic differences among the organisms—is often increased under conditions of environmental stress (Hoffman and Parsons).
It has long been appreciated that different loci are expressed in different tissues, and that different loci may be active at different developmental periods. The observations of Rogina and Helfand, who have described a typical life-span pattern of expression of a particular locus in the antennae of Drosophila, are particularly pertinent to the conceptualization of genetic and environmental influences on aging. Beginning at low levels, mRNA from this locus rises to a peak at midlife, with a subsequent decline to the initial low levels. In different temperature environments that influence Drosophila life span, the rising and falling of the mRNA level is altered, but the form of the function relative to the total life span under the particular environmental circumstances is remarkably preserved. This result can be interpreted as identifying an "intrinsic" pattern of gene expression over the life span, the temporal parameters of which are strongly influenced by environmental temperature. Another age-related illustration of environments affecting gene expression is that of Lee and colleagues, who used a gene array of the gastrocnemius muscle of mice to describe differences in the gene expression profile at five months and thirty months of age. Under conditions of caloric restriction, well established as a life-extending environmental intervention, most of the described gene expression changes were prevented or delayed.
There is also a growing literature concerning the role of genetics in determining the environment to which an organism is exposed. The field of microhabitat selection has provided plentiful illustration of organisms seeking environmental circumstances most suited to some aspect of their gene-influenced physiology. A case in point is that of selection of environments with or without the presence of alcohol by Drosophila larvae with different genotypes affecting alcohol dehydrogenase activity (Cavener). The scope for selecting from the array of environmental niches (or making them) is particularly pronounced in human beings (see Bergeman et al.).
Summary
The examples cited here make it clear that conclusions about the effect of a genetic locus must be interpreted cautiously. The detectability, effect size, or even direction of effect may be strongly contingent upon environmental circumstances. It is increasingly clear that the effective genotype—those loci actually being expressed at any given time—may change not only developmentally but also relatively quickly in response to an environmental alteration. It is equally the case that the effect of any environmental influence will depend upon the genotypes of the organisms exposed to that environment. Recognition of the scope for mutuality and reciprocity of genetic and environmental influences is important both for basic understanding of aging processes and for the design and application of interventions intended to extend life span and health span.
Gerald E. McClearn
See also Nutrition; Pathology of Aging, Human Factors; Stress.
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