TheNew York Times headline summed up a recent PNAS article quite well: “Mice Fall Short as Test Subjects for Humans’ Deadly Ills.” Gina Kolata begins the NYT article by saying:
For decades, mice have been the species of choice in the study of human diseases. But now, researchers report evidence that the mouse model has been totally misleading for at least three major killers — sepsis, burns and trauma. As a result, years and billions of dollars have been wasted following false leads, they say.
The article in question is titled: “Genomic responses in mouse models poorly mimic human inflammatory diseases,” and is authored by more than 20 scientists. The abstract reads:
A cornerstone of modern biomedical research is the use of mouse models to explore basic pathophysiological mechanisms, evaluate new therapeutic approaches, and make go or no-go decisions to carry new drug candidates forward into clinical trials. Systematic studies evaluating how well murine models mimic human inflammatory diseases are nonexistent. Here, we show that, although acute inflammatory stresses from different etiologies result in highly similar genomic responses in humans, the responses in corresponding mouse models correlate poorly with the human conditions and also, one another. Among genes changed significantly in humans, the murine orthologs are close to random in matching their human counterparts (e.g., R2 between 0.0 and 0.1). In addition to improvements in the current animal model systems, our study supports higher priority for translational medical research to focus on the more complex human conditions rather than relying on mouse models to study human inflammatory diseases.
This is essentially what Niall Shanks and I have been saying for over a decade.
The paper, published Monday in Proceedings of the National Academy of Sciences, helps explain why every one of nearly 150 drugs tested at a huge expense in patients with sepsis has failed. The drug tests all were based on studies in mice. And mice, it turns out, can have something that looks like sepsis in humans, but is very different from the condition in humans. . . . “This is a game changer,” said Dr. Mitchell Fink, a sepsis expert at the University of California, Los Angeles, of the new study.
I assure you, this will not be a game changer. Why? Kolata:
The study’s investigators tried for more than a year to publish their paper, which showed that there was no relationship between the genetic responses of mice and those of humans. They submitted it to the publications Science and Nature, hoping to reach a wide audience. It was rejected from both.
More on why in a moment.
This is not the first study to conclude that animal models of human disease fail to mimic human response to drugs and disease. (See [1-4] to mention but a few. See this blog and Animal Models in Light of Evolution for more.) Nor will it be the last. What science is good at, or I should say, among the many things that science is good at, is looking at diverse examples and coming up with an explanation for why all the data exists. In the physical sciences, scientists can look at regularities in the material universe and discover laws. Newton’s laws of motion, the laws of thermodynamics and so forth are examples. But in biology, laws are difficult because of things like chaos and complexity, among other reasons. Because the biological sciences are more statistics-based, they rely on theories. But a theory in biology is more than just a hypothesis. The National Academy of Sciences (USA), explains theory as follows:
In everyday usage, “theory” often refers to a hunch or a speculation. When people say, “I have a theory about why that happened,” they are often drawing a conclusion based on fragmentary or inconclusive evidence. The formal scientific definition of theory is quite different from the everyday meaning of the word. It refers to a comprehensive explanation of some aspect of nature that is supported by a vast body of evidence. Many scientific theories are so well established that no new evidence is likely to alter them substantially. . . . One of the most useful properties of scientific theories is that they can be used to make predictions about natural events or phenomena that have not yet been observed [p11]. (Emphasis added.)
The Germ Theory of Disease is a case in point. Many humans were dying from seemingly very different things. But the 19th century scientists figured out that all of the deaths were related. They were all caused by germs. Scarlet fever, hepatitis, whooping cough, sepsis, tetanus, and rabies, although causing symptoms that varied, were all caused by a group of organisms referred to as germs.
What Shanks and I have tried to do is find an explanation that accounts for all the failings of animal models as well as the successes (see Animal models and conserved processes for how to predict what will and what will not work in terms of animal models.) This would be the vast body of evidence referred to by the National Academy of Sciences. We have sought, and proposed, a theory. Put succinctly, our theory states that animals and humans are examples of evolved complex systems that are differently complex. If you understand complex systems and you understand evolutionary biology, that one sentence is all that is needed to explain why the PNAS paper on mouse models is a fact of the material universe as well as the other papers that come to similar conclusions. It also explains why some animal models function well for things other than predicting human response to drugs and disease. (For a broader and deeper examination of the issue, see our published works.)
But it takes time for even non-threatening theories to be accepted by the scientific community. This is why the PNAS paper will not be game changer. Kolata on the rejection of the article by top journals:
Still, Dr. Davis said, reviewers did not point out scientific errors. Instead, he said, “the most common response was, ‘It has to be wrong. I don’t know why it is wrong, but it has to be wrong.’ ” . . . “When I read the paper, I was stunned by just how bad the mouse data are,” Dr. Fink said. “It’s really amazing — no correlation at all. These data are so persuasive and so robust that I think funding agencies are going to take note.” Until now, he said, “to get funding, you had to propose experiments using the mouse model.”
Research in biomedical science is not a sacred thing. It revolves around money and ego, and facts rarely affect the status quo very quickly. Scientific research, especially biomedical research where so much money is involved, is no different from selling widgets. It is all about the bottom line. Universities keep roughly 50% of every biomedical research grant dollar that animal-based research brings in. Considering the fact that some universities see hundred of millions of dollars in animal model-related grants each year, their cut is in the hundred million dollar range. That's motivation! [6-11]
Science and medicine are no different from any other human enterprise in that both are conducted by humans that have human nature. Graduating from medical school or a PhD program does not change basic human nature. Money is as important to doctors, scientists, and researchers as it is to plumbers, engineers, and day laborers. Honesty and altruism operate under the confines of human nature in all humans regardless of education and profession. It is naïve to think a white coat makes a person undefiled by normal human passions.
The strength of a scientific position or piece of information can be judged by consilience; how well it fits into the web of other knowledge. If you think of the sum total of scientific information as a network and with each factoid, law, and or theory as a node then the probability that any individual item is true can be judged by how many connections it has. For example the node representing the Theory of Evolution has millions of connections to other nodes while string theory node has far fewer and homeopathy has essentially none. The PNAS article points out the fact that mice are poor models for sepsis, trauma, and burns while other article have shown that animal models in general are not predictive for carcinogenesis or Alzheimer’s or heart disease. This raises the question: “Is there something that connects all this?” The answer is: evolved complex systems theory. An appreciation for the fact that animals and humans are differently complex systems secondary to evolution allows us to predict success and failure of animal models. One will most certainly find examples of humans and animals responding the same way to drugs and disease but such instances will be unpredictable and, even with the same symptoms, the mechanisms may differ. Animal models per se will never be predictive modalities for human response to drugs and disease.
A comment by James Watson is appropriate at this time:
“Oh sure, I knew it would cause trouble," says [James] Watson, eyes widening with unabashed glee. "I said most scientists are stupid.” He pauses, furrowing his brow in an effort to quote himself accurately. “The fact is most scientists act as though they are stupid because they are wedded to some approach they can't change, meaning they are moving sideways or backwards.” 
That is pretty much our position regarding the use of animal models to predict human response to drugs and disease. The researchers and universities that use animals will never support our position. Not because our position is false but because their bottom line depends on using animals. Scientists who do support our position will not actively campaign on the issue as they have friends, family, and maybe even members of their own department who use animals. Even if these conditions are not present, it takes quite a bit of courage to rock a multibillion-dollar boat. The repercussion will be great and most scientists, or most people for that matter, do not seek out controversy for themselves.
Kolata concludes her article wit theme we have also articulated:
“This is a very important paper,” said Dr. Richard Hotchkiss, a sepsis researcher at Washington University who was not involved in the study. “It argues strongly — go to the patients. Get their cells. Get their tissues whenever you can. Get cells from airways.” “To understand sepsis, you have to go to the patients,” he said.
If you want to understand human response to drugs and disease, you must study humans. Who’d have thunk it?
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