Every day more data are published substantiating the fact that while animals and humans are superficially similar, small differences invalidate inter-species extrapolation in terms of disease and drug response. As I have pointed out, these differences include the way genes are expressed, mutations in genes, the networks the genes act in, and environmental factors among others. Put succinctly, animals and humans are examples of evolved complex systems that are differently complex. Reductionism does not account for all the relevant differences between complex systems. But reductionism can be used to explain some of the reasons inter-species extrapolation at higher levels of organization is problematic.
Zeng et al. studied brain slices obtained from humans at autopsy and compared gene expression profiles of ~1,000 genes from brain slices obtained from mice. They discovered that 21% of the profiles differed. The genes were involved in processing visual and sensory information. Zeng et al. state: “The data suggest that gene expression profile changes may contribute to differential cortical function across species, and in particular, a shift from corticosubcortical to more predominant corticocortical communications in the human brain.” (1)
That 21% difference in gene expression profiles invalidates the use of mice as predictive models for humans for disease and drug response because at that level of organization such differences between complex systems have far reaching effects. Granted, a cell in the human brain is more or less the same as a cell in the mouse brain, compared to, say a cell from a plant. But because different levels of organization require different degrees of similarity in order for inter-species extrapolation to be viable, these small differences in gene expression are significant for drug and disease response. To suggest that mice and humans both have eyes and brains and cells and that therefore we can study mice in order to predict the pathophysiology of neurological diseases is not consistent with current science.
Koch describes the complexity of the human brain:
Such systems [like the human brain] are characterized by large numbers of highly heterogeneous components, be they genes, proteins, or cells. These components interact causally in myriad ways across a very large spectrum of space-time, from nanometers to meters and from microseconds to years. A complete understanding of these systems demands that a large fraction of these interactions be experimentally or computationally probed. This is very difficult. . . . fields as diverse as neuroscience and cancer biology have proven resistant to facile predictions about imminent practical applications. Improved technologies for observing and probing biological systems has only led to discoveries of further levels of complexity that need to be dealt with. This process has not yet run its course. We are far away from understanding cell biology, genomes, or brains, and turning this understanding into practical knowledge. (2)
If we are this far away from understanding one complex system, the notion of extrapolating between complex systems, at higher levels of organization, is nonsensical. Moreover, even the brain of an individual differs across time. The brain of an individual at birth or during adolescence is not the same as that brain affected by Alzheimer’s disease (AD) or even in later life without AD. Responses to drugs also differ during a lifetime. Moreover, since genes are expressed secondary to environmental exposures, a person may be healthy one year but ill the next. Intra- and inter-individual differences exist in response to drugs and disease: monozygotic twins being a good example.
In an excellent article, available free online, Czyz et al (3) discuss why monozygotic (MZ) twins differ in their phenotype. They note that such discordance can occur secondary to differences in the “in utero environment, genetic mosaicism, and stochastic factors, [including] epigenetic discordance.” Numerous genetic differences have been discovered in MZ twins including chromosomal rearrangements, point mutations, mosaicism, copy number variants, and duplications.(3) Stochastic factors, such as errors in transcription and translation, may also account for differences between MZ twins. Differences between MZ twins have been noted for various traits including birth weight, height, eye and hair color, head circumference, language and motor skills, balance and coordination, congenital anomalies, and intelligence.(4-7) MZ twins also differ in response to perturbations such as disease. Czyz et al conclude: “The plausible assumption made by Galton that twin discordance can be explained by differential environmental exposures after birth is no longer tenable.”
If the vivisection activist wants to make a case for using animals to study fundamental processes of life, he has a point. But as soon as the research being conducted reaches the level of organization relevant to drug and disease response, it is impossible to make a case for studying animal in order to predict human response. Inter-human variability exists that translates to differences in response to drugs and disease between sexes and ethnicities. Even between MZ twins. (For more, see Animal models in an age of personalized medicine.) That should settle the argument. But since money and ego are involved, vivisection activists will continue to use fallacious reasoning and outright deceit in their attempt to confuse society. They will avoid real discussion of the issue and focus on sound bites instead. In the long run, a thorough examination of their position, based on the best science currently available, will expose them. In the meantime, patients will continue to die.
1. H. Zeng et al., Large-Scale Cellular-Resolution Gene Profiling in Human Neocortex Reveals Species-Specific Molecular Signatures. Cell149, 483 (2012).
2. C. Koch, Systems biology. Modular biological complexity. Science337, 531 (Aug 3, 2012).
3. W. Czyz, J. Morahan, G. Ebers, S. Ramagopalan, Genetic, environmental and stochastic factors in monozygotic twin discordance with a focus on epigenetic differences. BMC Medicine10, 93 (2012).
4. E. Ballestar, Epigenetics lessons from twins: prospects for autoimmune disease. Clin Rev Allergy Immunol39, 30 (Aug, 2010).
5. S. M. Singh, B. Murphy, R. O'Reilly, Epigenetic contributors to the discordance of monozygotic twins. Clin Genet62, 97 (Aug, 2002).
6. Z. Russell, R. A. Quintero, E. V. Kontopoulos, Intrauterine growth restriction in monochorionic twins. Semin Fetal Neonatal Med12, 439 (Dec, 2007).
7. A. Victoria, G. Mora, F. Arias, Perinatal outcome, placental pathology, and severity of discordance in monochorionic and dichorionic twins. Obstetrics and gynecology97, 310 (Feb, 2001).