Often in health and longevity discussions, you’ll hear arguments about mechanisms. For instance:
Antioxidants -> reduced free radicals -> less DNA damage -> less cancer
Unfortunately, these biologically plausible-sounding claims usually don’t work when rigorously tested.
Are mechanistic arguments useless?
No. They are a great source of *hypotheses*. While most of these hypotheses fail, some eventually lead to important new treatments.
Unfortunately, health gurus, podcasters, and even sometimes (though they should know better) doctors and scientists use mechanistic arguments to convince the public about treatments for which we have little evidence.
Mechanistic arguments in health sound scientific and impressive. They make the speaker seem authoritative and knowledgeable. And they *seem* very hard to argue with. However, there is one general argument that works for most of them: “That sounds nice, but let’s look at randomized experiments in humans to check if it works.”
Why is it so common that health-related mechanistic claims don’t work when rigorously tested in randomized trials?
What goes wrong with X->Y biological thinking?
1) Causality: The first issue is that an X->Y claim may be true in terms of associations, without the links being *causal*. It’s typically a lot easier to establish that when people have higher X, they also have higher Y than to show that increasing X causes higher Y.
Alzheimer’s research seems to be experiencing this problem in a major way. The hypothesis:
Amyloid plaques -> Alzheimer’s
Seems to be oversimplified or perhaps mostly associational (rather than causal), as drugs that reduce brain plaques have had disappointing results.
2) Multiple mechanisms: even if it’s true that X is in the causal chain for Y, it may also be true that Y is also highly influenced by other mechanisms, and so changing X may not change Y that much, even if you control X completely.
3) Other effects: even if the mechanism is completely correct, there may be alternative effects of the treatment. These could undermine the original benefit through other pathways, or cause other forms of harm that mean the benefit is not worth it.
4) Equilibrium: even if mechanistically X->Y, the body may work hard to maintain a balance of Y (much as it does to keep your core body temperature roughly constant regardless of whether you’re drinking a hot beverage or standing outside in the cold). Hence, the effects of intervening on X may not create lasting impacts on Y because your body works to restore a homeostasis.
5) Evaluability: unlike arguments based on empirical evidence (we gave patients this treatment in a study and here’s how their outcomes differed from the control group) and logical arguments, which a reasonably knowledgable non-expert can understand and assess to at least some degree, biological mechanism based arguments can’t be evaluated at all by non-experts. Take this claim, for example. Is this sound? See if you can tell:
“Subcutaneous WPP9 injections activate orexinergic neurons via Gq-coupled receptor agonism in the lateral hypothalamus, which increases daytime cortisol rhythm, leading to increased alertness.”
So, is this a valid mechanistic argument about human biology? Well, no, but I only know that because I had an LLM AI make this argument up by prompting it to generate a biologically plausible sounding but made-up argument. An expert on the topic may immediately identify it as implausible, but anyone else is going to have no realistic way of evaluating its soundness without help.
So, what’s the takeaway here? Well, when a podcaster or health guru tells you that we know a treatment works because [insert biological mechanistic argument here], remember that it isn’t strong evidence, no matter how impressive it sounds. We need careful randomized experiments (or other high-quality evidence) to be confident it’s true. Mechanistic arguments are for generating hypotheses; they give us a reason to collect more data and run studies to see if an idea pans out – they don’t themselves serve as strong evidence for what’s true.
Of course, we don’t always need strong evidence to try a treatment if it is worth it. If a treatment isn’t expensive and is low risk, we would be able to tell if it is working, and we don’t have more evidence-backed alternatives, then experimenting with the treatment (even if it only has weak evidence) can still be a good idea. But we shouldn’t mistake “worth experimenting with” for “having strong evidence for”.
This piece was first written on May 8, 2025, and first appeared on my website on May 15, 2025.
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