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• W1972372815 abstract "THE EXPANDING USE of molecular techniques has had a highly positive effect on metabolic bone research, notably in the area of understanding the genetic influences that act to produce metabolic bone disease. However, examining the study designs and applications used in genetic studies of other chronic, multifactorial diseases, including heart disease, can motivate our use of a variety of genetic approaches in metabolic bone studies. We have an opportunity to see such application in the work by Klein et al.1 in this issue of the Journal, whose work can suggest potential candidate genes for encoding hormones, structural genes, and cell surface receptors. Typically, the first step into genetic studies is to inquire whether genetic factors play a role in determining the interindividual variability in phenotypic expression, typically a measure of bone mineral density (BMD) or fractures. There have now been almost two dozen clinical and epidemiological studies between 1973 and 1998 that suggest that BMD has a substantial familial or heritable component, some of which were reviewed by Pollitzer et al.2 With somewhat remarkable consistency, considering the diversity in population characteristics (age, ethnicity, gender, geographic location) and sample size, scientists have shown that ∼40–60% of the variation in BMD is attributable to a heritable component.3,4 Indeed, of the common chronic diseases occurring in developed countries, BMD has one of the higher heritability fractions (40–60%), comparable to that of coronary artery disease and greater than the 30% heritability observed in hypertension.5 Thus, heritability of BMD is not an issue. The open questions revolve around the nature of the genetic constituents of this highly heritable and quantitative phenotype (BMD) and whether this can be related to fractures. With the infusion of energy and excitement generated by the work of Morrison and his colleagues,6,7 many investigators sought “the osteoporosis gene.” Dozens of investigations, some published and probably many not published, explored the relationship of the markers of the vitamin D receptor (VDR).8 Subsequently, the studies of the relationship between the vitamin D genotypes and the BMD phenotype have been inconsistent, generating an environment of frustration. This frustration about the inconsistencies in VDR studies and BMD has several sources. It is fueled by a research culture that seeks to identify “the” cause of a disease. Some investigators have reported statistically significant associations between BMD and the VDR only within subsets, usually defined by lifestyle or age characteristics. The lively exchange that has ensued, however, should cause us to rethink our expectations about understanding the genetic basis of metabolic bone diseases.9,10 First, because osteoporosis is a multifactorial disease, it is relatively unlikely that a single gene or even a very limited number of dominant genes will be responsible for explaining substantial amounts of variation in the phenotypic presentation as assessed by either bone densitometry or by fractures. Osteoporosis, like coronary artery disease, has a complex etiology. Genes will be involved in wide-ranging and varied elements crucial to the bone formation and maintenance processes. These processes, minimally, include functional products for the appropriate composition of matrix, responsiveness to remodeling activities, hormonal influences, and the nature and type of local growth factors. Genes associated with these processes will be acting in combination to determine the individual's susceptibility (or resistance) to osteoporosis. While investigators focused on the VDR gene,6,7 there has been relatively less exploration of the genotypes associated with the other varied biochemical and physiological characteristics associated with bone mineralization, bone maintenance, and responsiveness to local or systemic regulators. It is increasingly recognized that there may be rare instances in which a single or small number of genes uniquely are associated with a disease (i.e., BRCA1 and subtypes of breast cancer); however, it is estimated that such a single gene explains <5% of all breast cancer cases. The experience to date suggests that the likelihood is small that a single gene will be “the osteoporosis gene” and explain an overwhelmingly large proportion of the osteoporosis observed in general populations. Indeed, one expects there to be very few genes with rare alleles that have a singularly large effect on osteoporosis. While it will be useful to explore for unique subpopulations with low BMD that assort very early to a high incidence of fractures in families, including the genotypes associated with osteogenesis imperfecta,11 the current state of investigation suggests that there is likely to be less success in finding “the osteoporosis gene(s)” with Mendelian transmission to explain a condition that presents in such a large proportion of the population. As we increase our understanding of the breadth of fundamental etiologic factors that contribute to osteoporosis or other metabolic bone diseases, the more we can appreciate the likelihood that there are likely to be many osteoporosis genes, each of which is contributing a small amount to the overall effect rather than a single gene or two with a large effect. The work by Klein and colleagues in this month's Journal reflects this broadening of approaches to define and evaluate genetic markers for the various bone-related functions likely to contribute to susceptibility to osteoporosis. The investigators have employed statistical methodology to identify chromosomal loci on inbred mouse strains where marker alleles and the trait of interest (BMD) covary. Identification of these areas on the chromosomes can then, in turn, be mapped to human chromosome regions because of the high degree of synteny between mouse and human genomes. These areas can then be explored for genes that may have functional roles in the BMD phenotype. Second, if multiple genes acting in concert with each other form the basis for presentation of the osteoporosis phenotype, the effect at any one allele of these genes may depend on the influence of alleles at other loci, potentially not being studied. Thus, current investigations centered only around the VDR genotype (as a major gene) may be inconsistent because of the presence or absence of other important genes at other loci that were not considered in the initial investigation.12 The particular approach selected by Klein et al.1 is suitable to identifying both major and minor gene loci as they might be associated with a continuously distributed trait, such as peak BMD. As future investigations map these other loci to the human chromosome, these can also explore their relevance as gene-by-gene interactions. With grounding in our understanding of those biologic processes that lead to bone maintenance, it is an exciting avenue of exploration to inquire whether selected alleles that mark several important functions related to BMD can be cumulatively linked to identify subpopulations with notably higher or lower BMD. An equally important contribution would be the identification of how genes at certain loci might serve to neutralize or exacerbate the influence of a specified allele. Thus, the exploration of a potential role for calcium intake (via the VDR genotypes), the role for estrogen (via the estrogen receptor genotypes), the role for bone matrix (via the type 1 collagen genotypes), and the role for growth factors could, in the aggregate, represent the combination of “small effects” genes whose cumulative contributions are not trivial. Of course, there are limitations to successful implementation of this approach in human studies. Studies should define the interindividual characteristics of these genotypes as well as the relative importance of environmental associations. Such studies should require collaborations between geneticists, molecular biologists, epidemiologists, and statistical geneticists. Furthermore, considering the interactions of possible genes and their disparate frequencies in populations, one must anticipate studies in which thousands are genotyped as well as phenotyped. The explorations of the VDR genotypes indicate the importance of evaluating the genotype within the context of its environment. To date, investigators have reported associations of the VDR genotype and BMD considering a variety of environmental influences, including dietary intake, estrogen level, and age.13 As summarized by Sing et al., “The genome is not an isolated source of fixed, one-way information but is constantly being shaped, changed, and transposed, and is generally responsive to epigenetic networks of cellular dimensions. These networks influence DNA methylation and repair, and they serve to organize co-ordinated response to heat shock, oxygen deprivation and other environmental changes.”14 Increasingly, genetic studies of metabolic bone disease in humans need to address the interrelationships among gene expression, phenotypic expression, and the common environmental influences. While studies have shown a substantial heritable component (40–60%), there is still a large component of BMD variation that is less likely to be explained by the genetic processes we associate with osteoporosis. The expanded list of influences for metabolic bone disease might include physical activity, body composition, sunlight exposure, smoking behavior and alcohol use, medication or therapy use, and the frequently unmeasured attributes of aging, such as renal status. For example, it is well recognized that measures of body size explain important amounts of variation in measures of BMD (explaining 10–20% of the variation, depending on the specific study).15 Even accounting for genetic contribution associated with the body size measure of height, fat mass, and lean mass, there is still substantial unexplained variation that is associated with “environment.” It can be intimidating to attempt to measure with precision or even accuracy these genetic and environmental attributes. It can be even more intimidating to measure them in appropriate time frames relevant to the biological processes associated with the actions of a gene or group of genes. Thus, the use of animal models to identify appropriate gene candidates may be one format that allows us to deal with the greater heterogeneity introduced by gene-by-environment interactions. With animal models, certain environmental factors can be held more constant so that genetic variation is the prime parameter being evaluated. Klein et al.1 used recombinant inbred mouse strains (in this instance 60 brother × sister matings) to establish genotypic variance and then held the dietary and physical activity environment constant. Likewise, in mouse knockout models, the environmental contribution could be measured or manipulated across the lifespan to assess its relative importance. This suggests that many more experiments and more complex experiments will be required to explore fully the value of knockout systems. Furthermore, the systems will be notably more complex when multiple gene knockout systems are in place to capture the multiple gene effect. It is reasonable to try to find genes affecting osteoporosis risk whose effects are sufficiently large to be distinguishable regardless of individual or family differences in other genetic factors or exposure to environmental influences. However, it is equally important that we not limit our genetic exploration to considering only the role of a major gene or to defining identification of major genes as the only marker of success in genetic studies." @default.
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• W1972372815 title "Expanding the Repertoire: The Future of Genetic Studies" @default.
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