Toward an Epigenetic Biology and Medicine

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Developments in the life sciences make it clear that the current genetic paradigm is too limited by mechanistic and deterministic models to accommodate new perceptions of the organism! Despite the successes of the currently accepted genetic paradigm in biomedical science, and the continuing pursuit of applied research using its models, basic research has revealed conflicts and inadequacies inherent in the assumptions supporting the paradigm[ 1]. What emerges from these challenges to concepts of genetic causality is the beginning of a new biological paradigm, an epigenetic view that embraces creative characteristics, fusion of genetic with environmental signals[ 2], and other aspects beyond currently accepted biomedical theory.
Epigenetic biology defined

The term epigenetic has been used in the past to describe organismal development as a non-linear, complex process. Usually it was used to distinguish developmental complexity from the theory of “preformation” which claimed that the becoming of complex organisms was simply a matter of growth of tiny preformed bodies. In modern form preformation is recreated in terms of DNA and genetic programs within which developmental instructions reside. Of course, this version of preformation based on DNA as the transcendent aspect of information is also wrong. The new biological paradigm has an epigenetic basis. Characterized by enormous complexity and by phenotypic (behavior) possibility of great variability, biological systems actually occupy many fewer phenotypic states than are possible. Choice is then a scientific rather than a metaphysical concept observable at all levels of biological organization[ 3]. Because functional states evolved by biological entities (cells, organisms) are adaptive, creative choice also comes into a scientific focus. “Choice” is no longer an anthropomorphic artifact, but an observable phenomenon. Organisms display enormous fidelity in their developmental and growth patterns. Memory, therefore, is an important characteristic of living things. Biological memory, however, differs from memory in physical systems (computers, other machines) because it does not reside in fixed predictable locations. Instead, it is distributed throughout dynamical systems, which themselves show enormous informational redundancy. Holistic memory must, therefore, be a primary characteristic of living systems.

Four major features of living systems, down to the cellular level, are (a) creative choice, (b) dynamical information storage or holistic memory, (c) non-linear or determinative chaos, and (d) informational redundancy. These features are not currently addressed by the prevailing biomedical paradigm and consequently offer an opportunity to develop a new paradigm.

The epigenetic features of life described here were formulated by the physicist, Walter Elsasser[ 3]. These features do not presently move beyond axioms or simple observables present in all life forms. They do not represent mechanisms but rather new starting points for thinking about relations between form and function. Since these features are not approached by the present governing paradigm of biology, they also provide a new opportunity at the level of biological epistemology and make insistent the need for biological theory that goes beyond reductionism.

What is helpful in developing new approaches to biological systems is to make clear where our present thinking is, or might be inadequate; this analysis follows below.
Points of departure between biomedical reductionism and emerging epigenetic biology

Currently, biomedical sciences focus on what is predicted to be useful. Much work is in concert with ongoing basic research into fundamental aspects of cellular and molecular biology For example, analysis of simple diseases with single gene causality is expected to produce new drugs based on molecular biology of cellular structures, receptors, and other molecules that mediate cellular function. However, this research bound by the reductionist model will not address the major human diseases. Because of the enormous complexity found in the simplest biological system and the inability of reductionism in general and determinism in particular to lead to new insights into these complex systems, the current paradigm fails in the areas shown in Table 1. These areas are discussed in the following paragraphs.
Population biology conflicts with genetic determinism

Genetic determinism in current biomedical technology is based on the general equation of uniqueness between genes and phenotype:

Unique Genes?Unique Effects (unique phenotypes)

Under this equation we may assemble the major assumptions of biomedicine as follows:

* Genes determine diseases.
* Genes determine aging.
* Genetic analysis provides diagnosis and therapy for disease and aging.

These assumptions underlie the human genome project, the multi-billion dollar national project to sequence, clone, and map the 100,000 genes in the 23 pairs of human chromosomes.

But fundamental rules governing population genetics stand in at least partial opposition to the uniqueness equation and to the assumptions. Essentially, the unique relationship between genes and phenotypes is flawed because most complex phenotypes (including diseases) have no unique genetic basis. Rather the relationship between genome and phenome is characterized by great complexity involving interaction between many genes, gene products, and environmental signaling. This interaction may involve 10, 100, 1000 or more genes for any common disease like cancer or the heart diseases[ 4]. In addition, the interaction will be a function of personal natural history and present environmental setting, so that even in simplified cases where genetic connections may be traced the genes will have different effects in different environments. Population genetics shows that a precipitating environment is required to produce disease manifestation across the entire range of genetic variation[ 4],[ 5]. For cardiovascular disease, most cancers, non-insulin-dependent diabetes, and most mental diseases, there is no evidence for single-gene causality—and certainly none that would support the uniqueness equation.
Disease natural history conflicts with genetic determinism

Diseases determined at fertilization, as Thomas McKeown[ 5] has made clear, are based in genetic abnormalities of one kind or another. Examples are sickle cell anemia, cystic fibrosis, and Duchenne muscular dystrophy. There are literally thousands of these diseases, but they occur within the human population at extremely low frequency and account for less than 2% of our total disease load. So, only 2% of the time does the “bad gene causes disease” mechanism operate, while 98% of the time humans are born with genetic constitutions capable of supporting a life span of over 100 years, an average life expectancy of about 85 years, and an old age relatively free of morbidity[ 5]. The human genome needs to find itself in an environment for which it has adequate representation—proper nutrition, housing, and sanitation, to name the obvious requirements—but the deterministic/mechanistic model of sabotage from within is not adequate to explain most human diseases.
Evolutionary biology conflicts with genetic determinism

Most people, scientists included, are not aware of problems within evolutionary biology having to do with genetic mechanisms. These problems do not provide any weakening of the foundations supporting evolution; they do provide concern that we may have oversimplified the idea that evolution is to be explained by genetic mechanisms alone. Again, this is a complex area but we can state the following. In the area of evolution, genetic change is seen as one end point of evolution, and change in genes (mutations) is seen as one element providing a basis for phenotypic variance that may be acted upon by natural selection. But gene changes alone will not and cannot explain evolution. The mechanistic genetic model does not explain how individual organisms generate their phenotypes in the presence (or absence) of gene changes in a variety of environmental settings[ 6]. Individual development is one missing link in our current theory of evolution, a link that is recognized, and one that the biological community is now struggling to mend and incorporate into a more complete picture of natural selection. As an illustration, there is the absence of relationship between genetic and morphological complexity of species. Some closely related species cannot be seen by expert examination to be different (have different morphology), yet they show great variation in complexity at both genetic and protein sequence levels. Somehow organisms are able to take vastly different genomes and construct nearly identical phenomes. This cannot be explained by a simple linear genetic paradigm. Equally puzzling, humans and chimps have a very different morphology, yet humans do not differ genetically from chimps by more than I to 2%. Somehow we are able to construct very different organisms from very similar genomes; this is currently not explained by genetic theory.
Developmental cell and molecular biology conflict with genetic determinism

First, genetic determinism for complex traits has assumed the notion of “gene programs” to help explain the causal linkage between genes and phenotype. But this assumption has been found to be without experimental verification. There are no genetic programs[ 7]. There are only genes that encode for proteins. Some of these genes, and their protein products, are extremely important. When they are mutated or missing, the effects on a complex trait are profound. We have assumed that these genes control this or that trait, but now we see that these genes only supply an important protein used by the cell or organism in constructing a complex trait. Genes, for example, do not control developmental traits; they only contain information necessary for the synthesis of proteins used in development…in the assembly of the organism. The control for this assembly is not found in the DNA; it is elsewhere within the cell and it depends on a vast array of information coming from many sectors of the organism. This control corresponds to epigenetic regulation. Far from being controlled by simple, linear genetic causality, development is seen to rely on a complex, non-linear determinism closer perhaps to chaos theory than it is to genetic theory. It is, of course, an amalgam of both. Creativity is evident, a creativity at the cellular level that uses genetic and other information to construct the organism. This creativity is hidden in the epigenetic regulatory processes of living cells; a creativity that may be illuminated by a new biological paradigm capable of going beyond and encompassing the genetic paradigm.

Second, informational redundancy in organisms, and especially within cells, confounds the uniqueness equation because more than one gene can bring about the same. The uniqueness equation completely fails, as there is informational redundancy not only at the gene level, but at the epigenetic level as well. There are many examples in the current literature of experimental biology testifying to the ability of the organism to get along without what were thought to be crucial genes[ 1]. The organism, when a gene is missing, finds other genes or finds new ways (epigenetic controls) to use vast numbers of remaining genes to produce the same or highly similar phenotypes[ 1].
Conclusion

The new biology is discovering important areas of conflict with the prevailing paradigm of genetic determinism. These discoveries lead us into new realms of complexity, and we see that obvious characteristics of life such as purpose, and creative (as distinct from Vital) forces need to be accommodated. Art epigenetic paradigm holds possibilities for recapturing these characteristics within a scientific framework. Through epigenetic controls or vast networks of genes, gene products, and environmental signals found in living ceils there is an opportunity for a new understanding. This understanding may augment the idea of body wisdom. Rather than the need to orient ourselves to a technology devoted to engineering genes so we call fit imperfectly into a persistently degraded world, we may come to understand how to re-engineer the world to reflect the ancient and highly adapted genome that we humans bring with us as our evolved informational capacity. The genome is well, changes only slowly and with difficulty; the environment is not well and can be changed to reflect human needs inseparable from the diverse needs of the planet itself. An epigenetic paradigm, then, is a goal worthy of our highest priority and one toward which we have taken the first steps.
References

1. Strohman, R.C. Ancient Genes, Wise Bodies, Unhealthy People: Limits of Genetic Thinking in Biology and Medicine. (1993). Perspectives in Biology and Medicine, 37(1), pp. 112–144.

2. Wolf, S. & Bruhn, J. G. (1992) The Power of Clan. New Jersey: Transactional Publishers.

3. Elsasser, W. (1987) Reflections on the Theory of Organisms. Quebec: Orbis Publishing.

4. Wahlsten, D. (1990) Insensitivity of the analysis of variance to heredity-environment interaction. Behav. and Brain Sci. 13:109–61.

5. McKeown, T. (1988). The Origins of Human Disease. New York: Basil Blackwell, Inc.

6. Gottlieb, G. (1992). Individual Development and Evolution: The Genesis of Novel Behavior. Oxford: Oxford University Press.

7. Nijhout, H. F. (1990) Metaphors and the Role of Genes in Development. BioEssays 12:441–6.

8. Neel, J.V. (1961) A geneticist looks at modern medicine. Harvey Lecture Series. pp. 127–150. New York: Academic Press.

“Instead of trying to tailor man to developments only dimly visualized, is not the more immediate and pressing task that of developing the culture best fitted to man's needs?”

J. V. Neel

Harvey Lecture, 1961

Table 1. Areas confounding genetic determinism in
biomedicine
AREA CONFOUNDING ELEMENTS
POPULATION BIOLOGY Complex traits not accessible to linear
genetic analysis.
DISEASE NATURAL HISTORY Most common diseases are not genetic.
EVOLUTIONARY BIOLOGY No relationship between genetic and
morphological complexity.
DEVELOPMENTAL BIOLOGY There are no genetic programs.
MOLECULAR AND CELL Informational redundancy confounds linear
BIOLOGY genetics.

PHOTO (BLACK & WHITE): Richard C. Strohman

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By Richard C. Strohman, Professor Emeritus, Molecular and Cell Biology University of California, Berkeley

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