Weightlifting as Anti-Aging Strategy

Weightlifting is a superior form of exercise

Weightlifting  is superior to other forms of exercise, an idea that is thoroughly at odds with mainstream and popular ideas about exercise.

Weightlifting enhances brain function, reverses sarcopenia, and lowers the death rate in cancer survivors. Garden-variety aerobic exercise had no effect on survival from cancer, while resistance training lowered death rates by one third; so in this one example, weight training is shown to be a vastly superior form of exercise.

Weightlifting is also superior in fighting aging.

Resistance training lowers levels of myostatin, one of the main ways muscle strength and mass are increased, since myostatin negatively regulates muscle strength and mass.

Myostatin increases with age, which partially accounts for loss of muscle mass and sarcopenia with aging. Mice that have been genetically engineered to have lower levels of myostatin live about 15% longer than wild-type mice. (See previous link.)

Therefore it follows that lowering myostatin through weightlifting should increase lifespan. (Branched chain amino acids, creatine, and polyphenols from chocolate and tea also lower myostatin.)

Parabiosis

However, one thing has bothered me – and presumably a few others – about all this is the results of the now well-known parabiosis experiments on mice, in which young blood from young mice rejuvenated the brains and muscles of old mice. (See here and here.) The reason for the bit of bother is that the rejuvenating component of these experiments was said to be a protein, growth differentiation factor 11, or GDF11, which is “homologous”, that is, very similar, to myostatin.

We have, if not quite a paradox, then a confusion. GDF11, very similar to myostatin, allegedly rejuvenates young animals, while myostatin increases with aging.

Resolving the paradox of GDF11

What if there’s some kind of mistake here? It appears that there has been, since a new paper finds that GDF11 increases with age and is not the rejuvenating factor hitherto thought: GDF11 Increases with Age and Inhibits Skeletal Muscle Regeneration.

Age-related frailty may be due to decreased skeletal muscle regeneration. The role of TGF-β molecules myostatin and GDF11 in regeneration is unclear. Recent studies showed an age-related decrease in GDF11 and that GDF11 treatment improves muscle regeneration, which were contrary to prior studies. We now show that these recent claims are not reproducible and the reagents previously used to detect GDF11 are not GDF11 specific. We develop a GDF11-specific immunoassay and show a trend toward increased GDF11 levels in sera of aged rats and humans. GDF11 mRNA increases in rat muscle with age. Mechanistically, GDF11 and myostatin both induce SMAD2/3 phosphorylation, inhibit myoblast differentiation, and regulate identical downstream signaling. GDF11 significantly inhibited muscle regeneration and decreased satellite cell expansion in mice. Given early data in humans showing a trend for an age-related increase, GDF11 could be a target for pharmacologic blockade to treat age-related sarcopenia.

The case for weightlifting as anti-aging just got stronger

So, we get two important facts from this new study:

1. The previous study which implicated GDF11 in anti-aging processes was incorrect; GDF11 is a pro-aging molecule.
2. GDF11 and myostatin are indeed very similar and have similar effects, inhibiting muscle regeneration, decreasing satellite cell expansion, and increasing with age.

And we know that weightlifting decreases myostatin. Now someone should see whether weightlifting decreases GDF11. I would say it almost surely does.

Other forms of exercise can also decrease myostatin, but to my knowledge there are no direct comparisons of the efficacy of weightlifting versus aerobic or endurance exercise in doing so. However, we know that only weightlifting increases muscle mass, and therefore it follows that weightlifting must decrease myostatin levels more so than endurance training.

The case for weightlifting as an anti-aging intervention just got a lot stronger, in my opinion. The iron pill is good for what ails you, and if you are serious about lifespan extension or just your health in general, you should head over to your local gym and start lifting.

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Leave a Comment:

17 comments
Shartiste says May 26, 2015

I wonder if sprinting or HIIT carries many of these same benefits.

Reply
    P. D. Mangan says May 26, 2015

    Yes, it likely does, however I don’t know specifically of studies relating myostatin and HIT.

    Reply
    Famiii says September 21, 2016

    Probably not, one of the clear signs of aging is loss of muscle mass, this starts in the 30s and continues through life. Aerobic exercise (such as sprinting) actually accelerates muscle loss as the body optimises itself for the type of work being demanded of it (i.e. if it does not need strength it loses muscle).

    My two pennies (without the backing of research) is that body weight exercises will be the most effective at reducing the signs of aging as these are generally compound exercises that target a whole muscle group, as opposed to weight training that targets specific muscles (normally the big ones) and leaves lots of smaller muscles untrained. Resulting in reduced mobility and increased risk of injury over time.

    In addition body weight exercises also strengthen joints and tendons

    Reply
      Famiii says September 21, 2016

      HIIT would carry similar benefits if the exercises done in the high intensity regime are body weight AND are progressively more difficult (i.e. increasing muscle mass and strengthening).

      Reply
John Sterling says May 27, 2015

Can you give a practical definition of weightlifting or some decision rules on what sort of routine would capture these anti-aging benefits? For example, could I achieve the benefits by doing 50 push-ups? Or perhaps 100 burpees or 100 kettlebell snatches (with a 24 kg bell). Did the studies that you cited only come from good, old-fashioned barbell training? I’m living overseas with restricted access to a proper gym but don’t want to forgo the “fountain of youth.”

Reply
    P. D. Mangan says May 28, 2015

    John, all exercise including endurance training appears to lower myostatin. Since myostatin negatively regulates muscle, and since weightlifting causes more muscle growth than other forms of exercise, I’m making the leap of inference that weightlifting decreases myostatin more than other forms of exercise. I believe that’s a good inference, but I’m not aware of any direct head to head comparisons. From what I know of high intensity training, which is basically the type of exercise you describe, it ought to be effective at lowering myostatin.

    Reply
    Famiii says September 21, 2016

    Get yourself a copy of You Are Your Own Gym my Mark Lauren (you can get it on Kindle if you live overseas). Or someother body weight manual (though I think Mark Lauren who is ex special forces and contributed significantly to the post 9/11 changes in special forces and US Marines training programs) is one of the best. Also the military programs have been used by thousands of people, some of whom are the fittest in the world and who’s lives depend on having effective training programs. ‘Convict Training’ also contains the basic principles.

    The point is not how many reps you do. The point is to move to doing variations of the exercises with progressive levels of difficulty . It is putting your muscles under overload that causes the increase in strength and mass. No challenge no gain. Appendix 2 and 3 (which are very short) explains the science behind all modern training regimes from HIIT to ladders to Tabata. Such that you could easily start designing your own effective programs (though my guess is that there is not much new that the thousands of trainers have not discovered.)

    Reply
      Famiii says September 21, 2016

      PS: These exercises have also been used effectively since antiquity and are the exercises that Hercules, Samson, ancient Spartans and thousand of Roman Legionaires have usedto become combat fit. There is no need looking for a ‘modern’ gym.

      Gyms go back to ancient Persia and the word gym originates from the greek gymnasium where young men used to go to get fit. There were no machines and the equipment that has survived intact remain the dip bars (or parrallel bars), the rings (from which I suspect the Olympic symbol originates), and the pull up bars. All of which you can rig in your home (except perhaps the rings)

      Reply
gwern says May 28, 2015

> For example, weightlifting enhances brain function, reverses sarcopenia, and lowers the death rate in cancer survivors. Take this last item, lowering death rate in cancer survivors: garden-variety aerobic exercise had no effect on survival, while resistance training lowered death rates by one third

[“The Effect of Resistance Exercise on All-Cause Mortality in Cancer Survivors”, Hardee et al 2014; fulltext: https://www.dropbox.com/s/vkuvrpyfftm4onm/2014-hardee.pdf / http://libgen.org/scimag/get.php?doi=10.1016%2Fj.mayocp.2014.03.018 ]

This is a bad study, but sadly the problems are common to the field. Claiming that this study shows ‘weight lifting lowered death rates and aerobic exercise did not change survival’ is making at least 4 errors:

1. correlation!=causation; this is simply your usual correlation study (you know, of the sort which is always wrong in diet studies?), where you look at some health records and crank out some p-values. There should be no expectation that this will prove to be causally valid; in particular, reverse confounding is pretty obvious here and should remind people of the debate about weight and mortality. (Ah, but you say that the difference they found between aerobic and resistance shows that it’s *not* confounding because health bias should operate equally? Well, read on…)
2. power: with only 121 total deaths ( p=0.12`; to compute a survival curve I would need more data, I think.) The study itself does not anywhere seem to directly compare aerobic with resistance but always works in a stratified setting; I don’t know if they don’t realize this point about the null hypotheses they’re testing, or if they did do the logrank test and it came out non-significant and they quietly dropped it from the paper.
5. the fallacy of controlling for intermediate variables: in the models they fit, they include as covariates “body mass index, current smoking (yes or no), heavy drinking (yes or no), hypertension (present or not), diabetes (present or not), hypercholesterolemia (yes or no), and parental history of cancer (yes or no).” This makes no sense. Both resistance exercise and aerobic exercise will themselves influence BMI, smoking status, hypertension, diabetes, and hypercholesterolemia. What does it mean to estimate the correlation of exercise with health which excludes all impact it has on your health through BMI, blood pressure, etc? You might as well say, ‘controlling for muscle percentage and body fat, we find weight lifting has no estimated benefits’, or ‘controlling for education, we find no benefits to IQ’ or ‘controlling for local infection rates, we find no mortality benefits to public vaccination’. This makes the results particularly nonsensical for the aerobic estimates if you want to interpret them as direct causal estimates – at most, the HR estimates here are an estimate of weird indirect effects (‘the remaining effect of exercise after removing all effects mediated by the covariates’). Unfortunately, structural equation models and Bayesian networks are a lot harder to use and justify than just dumping a list of covariates into your survival analysis package, so expect to see a lot more controlling for intermediate variables in the future.

Any of these is sufficient. This sort of problem is why one should put more weight on meta-analyses of RCTs – for example, “Progressive resistance strength training for improving physical function in older adults” http://onlinelibrary.wiley.com/enhanced/doi/10.1002/14651858.CD002759.pub2

Reply
gwern says May 28, 2015

> For example, weightlifting enhances brain function, reverses sarcopenia, and lowers the death rate in cancer survivors. Take this last item, lowering death rate in cancer survivors: garden-variety aerobic exercise had no effect on survival, while resistance training lowered death rates by one third

[“The Effect of Resistance Exercise on All-Cause Mortality in Cancer Survivors”, Hardee et al 2014; fulltext: https://www.dropbox.com/s/vkuvrpyfftm4onm/2014-hardee.pdf / http://libgen.org/scimag/get.php?doi=10.1016%2Fj.mayocp.2014.03.018 ]

This is a bad study, but sadly the problems are common to the field. Claiming that this study shows ‘weight lifting lowered death rates and aerobic exercise did not change survival’ is making at least 4 errors:

1. correlation!=causation; this is simply your usual correlation study (you know, of the sort which is always wrong in diet studies?), where you look at some health records and crank out some p-values. There should be no expectation that this will prove to be causally valid; in particular, reverse confounding is pretty obvious here and should remind people of the debate about weight and mortality. (Ah, but you say that the difference they found between aerobic and resistance shows that it’s *not* confounding because health bias should operate equally? Well, read on…)
2. power: with only 121 total deaths (~4% of the sample), this is inadequate to detect any differences but comically large correlates of health, as the estimate of predicting a third less mortality indicates
3. p-hacking/multiplicity, type S errors, exaggeration factor: take a look at that 95% confidence interval for resistance exercise (which is the only result they report in the abstract), which is an HR of 0.45-0.99. In other words, if the correlate were even the tiniest bit bigger, it would no longer have the magical ‘statistical significance at p<0.05’. There’s at least 16 covariates and 3 full models tested. By the statistical significance filter, a HR of 0.67 will be a serious exaggeration (because only exaggerated estimates would – just barely – reach p=0.05 on this small dataset with only 121 deaths).
4. “The Difference Between ‘Significant’ and ‘Not Significant’ is Not Itself Statistically Significant” (http://www.stat.columbia.edu/~gelman/research/published/signif4.pdf): the difference between aerobic exercise and resistance exercise is *not* statistically-significant in this study. The HR in model 1 for aerobic exercise is (0.63-1.32), and for aerobic exercise, (0.46-0.99). That is, the confidence intervals overlap. (Specifically, comparing the proportion of aerobic exercisers who died with the resistance exercisers who died, I get `prop.test(c(39,75), c(1251,1746))` = p=0.12; to compute a survival curve I would need more data, I think.) The study itself does not anywhere seem to directly compare aerobic with resistance but always works in a stratified setting; I don’t know if they don’t realize this point about the null hypotheses they’re testing, or if they did do the logrank test and it came out non-significant and they quietly dropped it from the paper.
5. the fallacy of controlling for intermediate variables: in the models they fit, they include as covariates “body mass index, current smoking (yes or no), heavy drinking (yes or no), hypertension (present or not), diabetes (present or not), hypercholesterolemia (yes or no), and parental history of cancer (yes or no).” This makes no sense. Both resistance exercise and aerobic exercise will themselves influence BMI, smoking status, hypertension, diabetes, and hypercholesterolemia. What does it mean to estimate the correlation of exercise with health which excludes all impact it has on your health through BMI, blood pressure, etc? You might as well say, ‘controlling for muscle percentage and body fat, we find weight lifting has no estimated benefits’, or ‘controlling for education, we find no benefits to IQ’ or ‘controlling for local infection rates, we find no mortality benefits to public vaccination’. This makes the results particularly nonsensical for the aerobic estimates if you want to interpret them as direct causal estimates – at most, the HR estimates here are an estimate of weird indirect effects (‘the remaining effect of exercise after removing all effects mediated by the covariates’). Unfortunately, structural equation models and Bayesian networks are a lot harder to use and justify than just dumping a list of covariates into your survival analysis package, so expect to see a lot more controlling for intermediate variables in the future.

Any of these is sufficient. This sort of problem is why one should put more weight on meta-analyses of RCTs – for example, “Progressive resistance strength training for improving physical function in older adults” http://onlinelibrary.wiley.com/enhanced/doi/10.1002/14651858.CD002759.pub2

[Reposting because a less-than sign meant most of my comment was eaten.]

Reply
Lurking_Gorilla says May 31, 2015

Hey Mangan, I’ve been going through the archives but can’t find a paper that I’m almost certain you mentioned, or maybe you linked to it on Twitter: the gist was that doing compound exercises like squats doesn’t have any significant result on, say, building your upper body muscles, contra to the claim thrown around that “if you want big biceps you gotta train legs!” The idea used to be that the excess of testosterone from the big lifts would carry through to other muscles, but in reality this isn’t the case.

Does that ring any bells or am I hallucinating that I read it here?

Many thanks

Reply
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