BACKGROUND

The Medical-Epidemiological Background

Substantial evidence from diverse studies now points to the possibility that most human diseases in the Western world are manageable and that

---

we are reaching a limiting plateau in our attempts to extend life. In addition, there is mounting evidence that disease management and longer life expectancy are more related to the presence of an environment appropriate to the conserved human genome than they are to the total medical intervention effort. Life span is a species constant,16,17 and in the United States we appear now to be rapidly approaching a maximum life expectancy of age 85.18 Even the elimination of the most serious premature killers—cancer and cardiovascular diseases—is predicted to provide a mere two to three years of additional life for the population at large.19,20 Increases in life expectancy coming from molecular genetic approaches are not expected since monogenic diseases remain stable at only 2% of total diseases and since the afflictions of older people are seen to be multifactorial, polygenic, and therefore ultimately beyond the reach of applied molecular genetics. That is to say, progeroid syndromes have a genetic basis fundamentally different from the simple monogenic diseases afflicting mostly younger people. In younger people, but not in the older, the power of modern molecular biology is seen as sufficient to provide, in theory, a successful genetic analysis and even therapy based on a linear (single gene → single disease) format. Attempts by gene cloners, armed with advanced statistical devices, to redefine common polygenic diseases in terms of genetic tendency 21 and attempts by behavioral scholars of various backgrounds to apply monogenic “software” to the reality of polygenic human traits 22 all appear to discount the warnings coming from cell and molecular embryological studies 23,24 that genetic approaches alone are not sufficient to yield a satisfactory picture of complex phenotypes. These, as well as other studies discussed later in more detail, include examples of nongenetic but nevertheless cellular responses to developmental environments in which the genotype is constrained by local circumstances.

The Biomedical Paradigm
and the Problem of Informational Redundancy

The major assumption of modern biomedical research is that unique genes have unique effects. This assumption is essential in the following areas:

Medical genetics, which seeks isomorphic mapping of human diseases to Mendelian genes 25

Molecular biology, which seeks to identify unique, genetically based mechanisms driving cellular processes 26

---

Developmental biology, which presupposes (1) the presence of genetic programs, (2) additivity of gene effects, and (3) the ability to map complex developmental stages to additive programmatic sequences in DNA 27

These assumptions and presuppositions, now experiencing major problems, are also the major features of the HGP. The HGP has become the centerpiece of the biomedical paradigm and has distilled a simplistic guide for future research and application. This guide is summarized as follows:

1. All major noninfectious diseases are caused by defective genes.
2. Diagnosis and therapy are available through genetic analysis alone.
3. Aging and other complex human behavior is genetic, and all may be mapped to Mendelian factors.

As Brenner 28 and Wilkins 27 have pointed out, however, the uniqueness assumption of genetic determinism,

Unique Genes → Unique Effects,

is undermined by an emerging body of evidence showing functional informational redundancy in cell regulation. Here the focus is on redundant genes that more than one gene may specify any given function.29 In this case the reductionistic plan to associate genetic causality with complex phenotype is brought into question since the major research approach, saturation mutagenesis, depends completely on the uniqueness equation. This approach to understanding disease will generate a map or network of factors that interact to provide a useful background for a complex phenotype. However, as argued here, ultimate behavior is encoded not in DNA but rather in the environmentally interactive cellular epigenetic network, which includes the genome.

Levels of Biological Regulation

It is important here to distinguish three modes of gene activity that are operative in determining complex phenotype in organisms. The first is monogenic, which specifies a one gene → one trait pathway. This path

---

way is often influenced by environment or by other genes, but in some cases, when mutation involves a specific DNA sequence, environment is seen to be irrelevant. Diseases like sickle cell anemia and Duchenne muscular dystrophy come to mind as prime examples of monogenic diseases. The second pathway is polygenic, which refers to the fact that phenotype is determined by many genes acting together.

The third path is epigenetic, which may involve both single-gene and multigene interaction. Epigenesis implies a level of complexity beyond gene-gene interaction and extends to interaction between genes, between genes and gene products (proteins), and between all of these and environmental signals, including, of course, the individual organismal experience. But in addition, epigenetic pathways are usually thought by developmental biologists to involve progressive states of organization, each succeeding state depending on the prior state. Epigenetic pathway therefore implies great complexity of interaction as well as the production of entire states of organization arising from that interaction (see Figure 5.1). Finally, an epigenetic change in a cell, in a strict sense, is heritable; initial cellular responses not restricted to genomic alterations, usually called phenotypic or physiological adaptations, may persist over time and become stable so that change is transmitted to daughter cells during mitosis.

The heritable aspect of epigenetic change is an obvious aspect of differentiation where many different cell types, all with identical genomic sequences, maintain their differences over many generations. Of course, secondary changes in DNA may also contribute to the stabilization of cellular change, but these changes are not programmed by genes; they are rather programmed into DNA by regulatory events about which we now know quite a bit. Changes in methylation pattern, in DNA-binding proteins, or chromatin structure are examples of inherited secondary changes in DNA. These epigenetic changes result in altered transcriptional patterns and therefore in altered patterns of behavior at all levels

---

of the organism, from cellular to integrated psychophysiological action.30 Epigenesis has been given a modern definition as follows:

Classical genetics has revealed the mechanisms for the transmission of genes from generation to generation, but the strategy of the genes in unfolding the developmental programme remains obscure. Epigenetics comprises the study of the mechanisms that impart temporal and spatial control on the activity of all those genes required for the development of a complex organism from the zygote to the adult.31

As such, the definition establishes the basis for a level of organizational control above the genome, a level that is now well established in fact, but it is a level of complexity that continues to evade decisive theoretical insight. That is, epigenetic regulation is already extending and stretching the limits of our ability to draw the limits of interactional networks that are at work in governing a major phenotype like a complex disease. For example, the mechanisms of DNA marking (e.g., methylation) may be elucidated, but what is missing is any understanding of the question, “Where and how are these mechanisms deployed in cells … what are the rules, the boundary conditions for such deployment?” These questions are being addressed,10 but currently we have no consensus in biology that is necessary for a major new direction to be implemented. Courage and vision may be required on the part of our research leadership if we are to progress. Meanwhile we expect that a full description of a genetic network will come complete with a set of rules for its operation as an open system. But the rules do not come with the network diagram; they have to be discovered by human ingenuity. The differences between a genetic and an epigenetic informational system are depicted in Figure 5.1.

We have wrongly extended the theory of the gene to another area altogether; we have been lulled into reasoning that if the gene theory works at one level, from DNA to protein, it must work at all higher levels as well. We have thus extended the theory of the gene to the realm of gene management. But gene management is an entirely different process involving interactive cellular processes that display a complexity that may be described only as transcalculational, a mathematical term for “mind-boggling.” This interactive complexity is epigenetic in nature; it involves open networks of genes, proteins, and environmental signals that may turn out to be coextensive with the cell itself. It is as if the cell has interposed between its genome and its behavior a second informational

---

system able to integrate environmental and genetic information into its dynamical process and able to generate from this integration responses that are functional, or adaptive.

Genetic pathways specify organismal function only in rare cases, as in monogenic diseases like sickle cell anemia or muscular dystrophy, where mutation produces dysfunction in a protein of crucial importance. In these cases the cell (mostly but not always) has no compensatory mechanism, and environmental influences are nil; redundant information at either the genetic or the epigenetic level appears to be absent, and the mutant gene becomes the disease. But this rare event has such a powerful effect in making real the critical issues of disease and health that it has commanded our attention in other areas of our lives. Common diseases like cancer and cardiovascular problems that account for over 70% of premature morbidity and mortality are not the effects of single genes.

Epigenetic networks have been described as cellular neural networks and, given their great complexity and openness to environmental signals, most probably utilize a (nonlinear) logic and set of rules quite different from the comparatively linear rules needed for completing the genetic sequence of events. This comparison also emphasizes feedback from epigenetic networks to the genome, feedback that includes changing the patterns of gene expression. This change in pattern of gene expression is accomplished by enzymatic changes in chromosome structure and by “marking” sections of DNA chemically without changing the genetic code in any way. What is changed is the accessibility of genes to expression pathways. But the decisions to mark or not to mark are in the epigenetic and not the genetic pathway. These details of epigenetic biology, as defined by Jablonka and Holliday,30,31 are well known and are thoroughly covered in the literature. We can see at once that failure to include epigenetic processes and their rules in predicting outcomes and basing outcome analysis only on information in DNA will lead to the anomalies that are now being seen. Thus, information for cellular integration and response is encoded not only in DNA, and there are no genetic programs for this process; rather integration and response come out of the dynamics of the interactive system itself. The system response includes the genome but is not reducible to it. The cell is starting to look more like a complex adaptive system rather than a factory floor of robotic gene machines, and that is well and good.

In what follows, whenever I refer to polygenic traits or diseases, I assume,

---

along with mainstream biology, strong environmental interaction.

For my purposes, therefore, polygenic and epigenetic are synonymous. The basic assumption is that complex disease states, at a cellular level, involve heritable changes that may include gene mutation but that also include persistent cytoplasmic changes. In addition, it must be clear what classical developmental biologists mean when they discuss complex phenotypes in terms of genotypes. What is usually meant is that all complex traits (e.g., intelligence, aggressiveness, and cancer) have some genetic basis. But this basis is so polygenic (interactive and epigenetic)—it may extend to the entire genome—that there is little in the way of practical meaning given to “genetic basis.” For example, there is a genetic basis for speaking French, but the meaning of this does not go beyond the idea that there is a genetic basis for being human. In order to speak any language, we need to have something called a human genome (of which there are as many different kinds as there are humans) consisting of about 100,000 genes. But while these genes are necessary for speaking French, they are not sufficient. We also need the appropriate environment, the appropriate body, and the appropriate experience, all of which provide information not contained in the genome. Unfortunately, most behavioral and medical geneticists continue to believe that even the most complex human behavior can be reduced to genetic circuits. We now turn to examples where predictions and diagnoses based on genetic analysis alone have generated conflict and anomalous results.