Are four postulated disease spectra due to evolutionary trade-offs?

I recently read Crespi et al.’s interesting paper on this subject. They describe eight diseases as due to four underlying diametric sets that can be explained by evolutionary/genetic trade-offs:

  1. Autism spectrum vs psychotic-affective conditions
  2. Osteoarthritis vs osteoporosis
  3. Cancer vs neurodegenerative disorders
  4. Autoimmunity vs infectious disease

Of these, #2 and #4 seem obviously correct to me based on my fairly limited med school exposure, and they describe the evidence in a systematic way. I don’t know enough about the subject matter to speculate on #1, but I would like to see more genetic evidence.

Finally, I found their postulated explanations for #3 somewhat weak and I personally think that it is a selection bias trade-off, i.e. a case of Berkson’s bias as applied to trade-off. That is, since both cancer and neurodegeneration are age-related conditions, you could think of aging as the “agent” that selects either neurodegeneration or cancer as the ultimate cause of age-related death. I could be persuaded to change my mind on the basis of genetic predisposition evidence or some other mechanism, but I found the mechanism of apoptosis to be weak since apoptosis occurs (or doesn’t occur when it should) in many, many diseases, and moreover it is far from clear that neurodegeneration is mostly due to apoptosis as opposed to some other mechanism of cell death. A mechanism that might be most persuasive to me is one related to immune cells, since they clearly play a large role in regulating cancer growth, and also have high expression for the most GWAS risk factors for Alzheimer’s disease. But I still suspect that the selection bias is primary.

New page on biomedical trade-offs

Throughout my first two years of med school, I was surprised by how many of the most tricky — and to me, most interesting — topics in medicine involved some sort of underlying trade-off. For example, I couldn’t understand dynamic compression of the airways pretty much at all until I realized that it was a prototypical trade-off, in that higher expiration rates help push out CO2-enriched air faster, but also lead to a higher risk of airway collapse. Today I added a new page with a lot of these biomedical trade-offs, which is currently at 16 trade-offs, but I’m planning on adding more as I learn more. Hopefully somebody will find them useful, even if it’s just my future self.

Immanentizing the common trade-offs canon

Attention conservation notice: Meta-commentary on a 3,600 word essay that almost by definition is not directly relevant to your interests.


About five years ago I became obsessed with the idea that nobody had collected an authoritative list of all the trade-offs that cuts across broad domains, encompassing all of the sciences. So, I started to collect such a list, and eventually started blogging about it on my old site, some of which you can find in the archives.

Originally I had 25 trade-offs, then I realized that they could be combined until I had only 20, which were published in the first iteration of the list. As I noted above, at this point I wanted to describe all possible trade-offs, from the space vs memory trade-off in computer science, to the trade-offs underlying the periodic table, to deciding what type of tuna fish you should buy at the grocery store.

Eventually, I decided that this would not only be a) practically impossible for me, unless life extension research becomes way more promising, b) not particularly interesting or useful, because most of the trade-offs that come up over and over again occur because of the context-dependent structure of the world that we live in. In particular, most trade-offs are interesting mostly because of how our current situations have been selected for by evolutionary processes.

Upon deciding this, I trimmed the trade-offs list from 20 down to 11, and that is the number of trade-offs that you can find in the essay today. This new goal of indexing the common trade-offs that decision makers face is, I think, still ambitious, and still almost certainly more than I will be able to accomplish in my lifetime. But this way the interim results, at least, are more likely to be interesting.

Ultimately, I think that using these sort of frameworks can be a helpful way for people to learn from the decisions that others have made when they are making their own decisions. It certainly has been for me. I’m actively seeking feedback, for which you can either email me or leave me anonymous feedback here.