Fight Aging!

Metabolism, which might be broadly defined as the biochemical process of living, is absurdly complex. The way in which metabolism varies between individuals, and then changes over time with aging? Even more complex. This is one of the reasons why slowing aging by changing metabolic machinery - in effect creating a new human metabolism - looks very much like an inferior, harder path in comparison to attempts to restore the metabolism we have to the way it operates in youthful bodies.

Complexity is interesting to look at, however. I recently noticed a paper that investigates the details of a known trend in metabolism that takes places as people age:

This study investigates age-dependent changes in resting metabolic rate (RMR) considering changes in body composition and fat distribution within the longitudinal study on nutrition and health status in an aging population in Giessen (GISELA), Germany

...

Approach 1: RMR correlates significantly negatively with age in women and men. Considering fat free mass, fat mass, and [weight and height], age proved to be a significant predictor of RMR in both sexes in multiple regression analysis; RMR falls by 11.2 kJ/d and 34.1 kJ/d per year in females and males, respectively.

Approach 2: In males but not in females RMR decreases significantly in the course of the follow up. After ten years measured RMR is significantly lower than expected RMR predicted on the basis of body composition and fat distribution in females and males. Deviations correspond to a decline in RMR by 11.4 and 27.5 kJ/d per year independently of changes in body composition and fat distribution.

Approach 3: Results of the mixed linear model show that RMR decreases in the course of aging in both women and men; after considering changes in body composition and fat distribution respective decreases were 8.7 and 30.7 kJ/d per year.

...

These results indicate that the decline in RMR with advancing age cannot be totally due to changes in body composition.

Which is interesting. It has been known for a great many years that metabolic rate declines with age in a fairly predictable way, when averaged across populations. It would not be unreasonable to attribute this change to the way in which the gross details of the body change with age, on average - less muscle, more fat, for example. But not so, apparently. Other, more subtle processes are at work.

One might think of calorie restriction in this context. It is known that metabolic rate declines with calorie restriction in a variety of species, which includes primates. It is also generally the case that older humans eat less than they did when younger.

One might also consider this slowing down of metabolic rate with age as one a part of the evolved cancer suppression processes that take place in the body. Less biological activity, all other things being equal, should lead to a lower risk over time of generating cancerous mutations.

Interestingly, a combination of resting metabolic rate and a measure of the composition of mitochondria have been shown to correlate extremely well with the maximum life span recorded in varied species of mammal. These two items, the pace of your biology and the degree to which your mitochondria resist damage, appear to be the most important intrinsic determinants of the outer limits of natural life span.

Natural life span is something we'd all like to do away with, of course; researchers have been working on that task in one way or another since the dawn of humanity. Our ancestors focused on extrinsic determinants of life span - the food, the things with claws and large teeth, the diseases. What sets our era apart is not just that we are equipping ourselves to see the true complexity and operation of our biology, but that we are equipping ourselves to change it and even repair it. The days of degenerative aging and intrinsic outer bounds to human life span are numbered.

Luhrmann PM, Edelmann Schafer B, & Neuhauser Berthold M (2010). Changes in resting metabolic rate in an elderly german population: cross-sectional and longitudinal data. The journal of nutrition, health & aging, 14 (3), 232-6 PMID: 20191259