Cold Temperature and Life Span: It’s not about the rate of living

When cold-blooded animals are exposed to a cold environment, their metabolisms slow and they live longer. When warm-blooded animals are exposed to a cold environment, their metabolisms speed up (to maintain body temperature) and they live longer. In a new study from University of Michigan, both responses are traced to a common genetic mechanism that senses the temperature and signals a slower rate of aging. This adds to a mountain of evidence that animals life spans are fixed by genetic choice, and not by any kind of passive physical deterioration.

 

In 1986, John Holloszy of Washington University immersed his lab rats in shallow, cool water for four hours each day. They burned so many extra calories that they ate half again as much as control rats, but weighed less. The cold rats lived 10% longer, on average. Holloszy framed his report on this experiment not as a hormetic effect of cold exposure, but as a refutation of the “rate of living” hypothesis.

In 2006, Gordon Lithgow of the Buck Institute for Aging Research exposed lab worms to repeated heat shocks, and they lived 10-20% longer. Lithgow’s group noted that in response to the treatments the worms generated a surge of a protective hormone dubbed heat shock protein, and that heat shock protein also increases life span. They matter-of-factly reported their results as an example of hormesis, demonstrating that between 1986 and 2006, the concept of hormesis had worked its way into the field and become commonly integrated into gerontologists’ thought process.

Hormesis is the name for the paradoxical adaptation that makes animals live longer when they are exposed to challenges and hardships. Starvation, various toxins in low doses, infections, heat and cold can all lead to a longer life . These are not merely quirks of the physiology, but deep and ancient adaptations for the purpose of stabilizing population. The population death rate, like everything else about life, is homeostatic. That means that when something in the environment – perhaps a famine or an epidemic – is killing off part of the population, the rest of the population responds by toughening up and living longer. At the individual level, this is manifested as a slow-down of the aging process when starvation or other hardship is sensed. The response is managed by a logic system that works very much like a computer, but it is based on a web of hormones and chemical signals, in addition to neural circuits.

 

“Rate of living” theory – more lives than a cat

The new study, announced last week at the high-profile annual meeting of AAAS, also claimed to discredit the “rate of living” theory. In fact, a quick literature search reveals that this theory was discredited in 1956, in 1986, in 1989, again in 2002, in 2004, in 2007, and in 2009. In fact, August Weismann clearly saw through it in the 19th Century, thirty years before the eponymous book by Raymond Pearl proposed that faster metabolism leads to faster aging. In my most frequently cited academic publication, I, too, have railed against “rate of living”.

You don’t even have to know that bats burn 3 times as many calories as mice and live 10 times as long; the simple fact that sedentary people die early while athletes enjoy enhanced longevity would banish the idea that our bodies become damaged from use and simply wear out over time.

What is the power of this idea, that it continues to haunt the theory of aging, generation after generation? The appeal is its familiarity and common sense. Everything that we make, our tools and articles of clothing wear out over time. We imagine that biological aging must be related to the reason that knives get dull and auto bodies rust. (Nassim Taleb would say we are confusing the cat with the washing machine.)

This serial error comes from misunderstanding the Second Law of Thermodynamics. The Second Law says that entropy must increase in any closed system. This is indeed related to the reason that washing machine bearings wear out after a few years. But living things are not closed systems. They take in free energy from food or sunlight and dump their waste entropy back into the environment. The ability to do this is not a technicality; it is a fair definition of what life is, what distinguishes living from non-living things. All of life is an end run around the Second Law, and this is what enables us to grow and to learn, to increase in complexity. There is no physical requirement that living things should deteriorate over time – else how could we ever grow up?

 

Genetic mechanism for response of aging to temperature

The UMich study, published in Cell last week just as it was announced at AAAS, starts with an examination of genetics and cold treatment in the lab worm, C elegans.  Worms that are kept at lower temperatures live longer than worms kept at higher temperatures. No surprise there – here is a reference from 1908. Temperature modifications in both directions have been observed to increase life span of cold-blooded animals, and, to a lesser extent, mammals as well. The news is about discovery of the means by which worms adjust to colder temperature in order to lengthen life span.

“The extended lifespan observed at a low temperature cannot be simply explained by a reduced rate of chemical reactions,” reported Dr Shawn Xu of University of Michigan. “It’s in fact an active process that is regulated by genes.” (ref)

In particular, Xu’s lab discovered that the gene called TRPA-1 is necessary for the life-extending signals to find their mark. When TRPA-1 is knocked out of the worm’s genome, life spans is actually shortened in response to cold. Another gene necessary for life extension from cold temperature is the famous DAF-16, which was identified a dozen years back as the Grand Central Terminal of anti-aging signals in worms.

The Xu study goes on to relate the mammalian response to cold (Holloszy’s experiment above) to life extension in worms. That same TRPA-1 gene has a homolog in mammals that serves a similar function. Exposed to cold, mammals do a good job of keeping their core body temperatures steady in a cold environment by burning more fat, by shivering and by increased activity. That they live longer nonetheless demonstrates that their life extension is not a consequence of physiology but a choice made through hormonal signaling.  He notes that the same gene, TRPA-1 that is activated by cold in worms and mammals can also be triggered by eating Japanese horseradish (wasabi).

 

Human Longevity and Temperature: an informal analysis

Just for fun, I looked for demographic evidence that human longevity responds to cold. I found in Wikipedia tables of longevity and of record high and low temperatures for each of the fifty U.S. States. Record temperatures weren’t very representative, and state average temperatures are hard to define, so I used as a surrogate the average January temperature in the largest city of each state. Here is a scatter plot of Life Expectancy vs Avg January Temperature, for the contiguous 48 states:

Unadj-State-Life-Exp-vs-Temp

Visually, you can see a downward trend. Regression analysis gives R2=0.21, significant at p<0.001. The outliers in the upper right are Arizona and California, which have high incomes and warm Januaries.

I suspected that these results were too good to be true, because there’s a powerful relationship between income and longevity. Some of the poorest states happen to be in the American Southeast, where temperatures are warm. To correct for this, I found (also in Wikipedia) figures for median family income by state, and sure enough life expectancy had a much stronger relationship to income than to temperature (R2=0.49, p<2*10-8).

State-Life-Exp-vs-Income

After removing the effect of income, I plotted the residual variation in life expectancy against January temperature, and lo and behold, results were a bit more significant than the relationship for raw life expectancy (R2=0.16, p<1*10-5).

Residual-Life-exp-vs-Temp

Despite the direct simplicity of the comparison and the impressive statistical significance, I would not claim that this proves anything about a response to cold in human longevity. It may be that this is an artifact of the way life span is reported, or a reflection of the fact that Americans like to retire to warmer climates. These and other hypotheses need to be explored. This is what makes science complicated (and epidemiology fraught with contradiction). We might begin our skepticism by comparing Northern and Southern Europe. Scandinavia has much higher incomes but slightly shorter life spans than the Mediterranean.

IncomeLife Exp
( $ USD) (years)
Sweden

57,638

82.9

Norway

97,607

82.7

Denmark

59,709

80.5

Finland

48,783

82.7

Scandinavia, average:

65,934

82.2

 
Spain

32,077

83.7

Portugal

22,359

81.7

Italy

36,267

83.9

Greece

26,735

82.1

Mediterranean, average

29,360

82.8

So my longevity advice for the day is to enjoy a walk in the bracing air while we’ve still got some winter left, and come back in to plateful of sushi with extra horseradish.

DNA Methylation: an Epigenetic Aging Clock?

How does the body know how old it is? Our metabolisms change as we get older, even though our DNA doesn’t change. Different genes are activated at different times of life, and the timing of gene expression is what controls growth, development, sexual maturity, and perhaps aging as well. The body keeps accurate track of how old it is, though there has been no scientific agreement about where the clocks are, or how they work. Recently, some biologists have suggested that one such biological clock might reside in the epigenetic state of the DNA. If this is true, epigenetics will become an attractive, though challenging, target for anti-aging research.

An aging clock is the holy grail of anti-aging medicine. The body must have some way of knowing how old it is, a master reference that controls many aspects of the metabolism that can make us grow pubic hair at some time of life and grey hair at another time. (Aging is an active process, and not merely a matter of the body becoming damaged, or wearing out, as I have written previously.)

If we knew where the body kept its “clock”, then perhaps we could target the clock itself with biochemical interventions. We would not just be able to slow the progress of aging, but reset the clock to an earlier age.

I have written about telomeres as an aging clock. Telomeres are chromosome tails that are truncated with each cell division, so that they become shorter with age. Telomeres have all the characteristics of an aging clock in humans, and already therapies are being targeted toward promoting the enzyme telomerase and elongating our telomeres.

But there are other animals that have plenty of telomerase, and don’t lose telomere length over their lifetimes, and still they get old and die on a reliable schedule. So we know that telomeres are not the only aging clock. There are evolutionary reasons as well for believing that probably there is more than one aging clock at work in most higher organisms, including humans, (otherwise, it would be too easy to evolve away from aging, toward unlimited life span).

I have recently read about another candidate for an aging clock based on epigenetics. Genes are in control of every aspect of the body’s biochemistry, but different genes get turned on and off in different times and places in the body. In fact, 80-90% of the body’s genes are turned off in the average cell, at any given time. The choice of which genes to express is made from moment to moment by specialized promoter and inhibitor molecules.  These are responding to complex networks of chemical reactions and nervous signals as well that serve as a kind of neuro-chemical computer.

But there is also a more persistent aspect to the control of gene expression, and this is methylation. DNA is decorated with methyl groups, small molecular add-ons that act like “Do Not Disturb” signs for the underlying gene. A gene that is decorated with methyl groups is passed over, and not expressed. Patterns of methylation are programmed into the genome at birth, and they are known to change over a lifetime. The new idea is that these changes can constitute a reference, like a clock face that informs the cell about the body’s stage of life, so that it can appropriately adjust its gene expression, and thence its entire metabolism.

Methylation is controlled in turn by a set of enzymes called, appropriately enough, methyl transferases. There are “de novo” transferases that program the embryonic genome before birth, and then there are “maintenance” transferases that are active through the lifetime, assuring that the methylome decoration pattern is age- and tissue-appropriate.

 

Why does methylation make a plausible clock for aging and development?

Methylation patterns are important – they control gene expression. Mutations in the methyl transferase genes cause serious, usually lethal, defects.  Several of the diseases of old age, including diabetes and Alzheimer’s, are known to be associated with aberrant patterns of methylation.

Methylation patterns are persistent. They can last for years.  In fact, methylation patterns are copied when DNA is copied, which is to say whenever a cell is replicated.  Epigenetic patterns can persist for several generations, and epigenetic inheritance is thought to be mediated through patterns of methylation.

Gene expression changes during development and maturation, and it is plausible that this is accomplished through changing methylation patterns. And gene expression is known to change at advanced ages. The new hypothesis is that perhaps altered patterns of methylation are a deep cause of the disabilities and altered metabolism that come with age.

It is likely that some of the change in methylation patterns over time are random and haphazard, and can cause trouble; and other changes are programmed and determined, and these definitely cause trouble.

 

Three key experimental facts

  1. In general, we lose more methylation than we gain over time.  DNA from older animals is less methylated than from young animals, though there are also some regions of the DNA where there is more methylation with age. Ref  In a recent study, it was shown that people with less total methylation were more frail and sickly at the same age. Ref
  1. Gene methylation patterns were compared in identical twins when they were very young, and when they were older. Methylation patterns were very similar in young twins, but diverged markedly over time. Ref  Could it be that some of the body’s loss of function with age has to do with a haphazardness in the way that methylation changes over time?
  2. Fruit flies with an extra dose of methyl transferase in their genome lived up to 58% longer than control flies. Conversely, when one copy of the methyl transferase gene was deleted, flies lived only 3/4 as long. Ref.

How difficult will it be to learn to reset the clock?

The idea that methylation patterns could be an aging clock presents an opportunity and a challenge for anti-aging medicine. If the clock hypothesis pans out, we will have to learn two things: First, to read off a strand of DNA, which places are methylated and which are not. There is already good technology for acquiring this information, but it will have to be automated and far more efficient in order to create a detailed map.  Second, we will have to learn how to impose a pattern of methylation on a strand of DNA in vivo, without otherwise disrupting the function of the cell or its nucleus. This will mean acquiring a new language, the language of methyl transferases that accurately locate a place on the genome to do their decoration. This may be a decade-sized challenge for the current biochemical state of the art.

But if we’re really lucky, it will turn out that humans, like flies, respond well to a dumb, across-the-board increase in methylation.  Flies have just a single methyl transferase that is active in their adult lives, and extra copies of the gene for that molecule was enough to create a whopping boost in life span.  The methyl transferase system in humans is more complicated, but it will still be far easier to engineer a general increase in methylation than to copy youthful methylation patterns in detail.  This question could be posed in research project that we know how to do now.

Much of the technical information for this blog post came from this paper in Rejuvenation Research last fall.

China Study: A Voice for Veganism

The China Study used a broad comparison of different diets and living styles across diverse regions of China to answer questions about diet and disease. The authors’ bottom line is that eating animal protein leads to the high rates of cancer and heart disease, and many other afflictions of the Western world as well. They cite evidence that dairy is as bad as meat – worse in some respects, and they counsel a vegan diet. They have written an engaging book and make a compelling case, but why have so many studies before and since missed the connections that loom so large in the China Study?

A lot of legwork

Colin and Thomas Campbell are a father-son team from Cornell who have used epidemiology to answer the question, what diet is best for human health and longevity? There are a lot of things they get right.

First, epidemiology is far more compelling than animal studies or lab results or biochemical theory. Epidemiology looks at humans long-term, in settings that reflect the way people actually live. Epidemiological studies are based on correlations between behaviors and disease or behaviors and mortality, relating the choices we make to what happens to us. But in a science experiment, you like to have controls: two experiments that are run identically in all respects, except that one thing is changed. With people in their natural habitat, you have to give that up. No two people are alike, and no two groups of people differ in one respect only. Epidemiologists know this well, and they seek to bridge the gap (1) by constructing groups that are as much alike as possible, (2) by collecting data for large numbers of subjects, and (3) by using sophisticated mathematics to tease apart the possible causes for different outcomes.

The Campbells do all this well. They chose 65 counties in China because the population tended to stay put and maintain similar habits over decades, and because the Han people are genetically similar. They sent teams out to collect blood and vital stats from 6500 volunteers, and they visited each family to observe first-hand what they were eating, rather than rely upon questionnaires.

One thing in their design about which I’m more skeptical: they started with 367 factors that we wished to study, and a large number of health outcomes. People who do multi-factorial statistics often don’t realize that the number of possible causes rises rapidly with the number of variables. Even five variables cannot cannot be meaningfully separated, and 367 is ridiculous. But in the end, they limit their conclusion to broad-stroke conclusions about animal- vs plant-based diets.

A more essential limitation is that they have bet the farm by including dairy along with meat in their conclusions. The problem here is that only three of the 65 counties had any dairy at all in their diets, and zero relied primarily on dairy for protein. The Campbells supplement the China Study with lab rat studies and cross-country comparisons to fill this gap, but the result is much less convincing just because countries vary in so many cultural and genetic and environmental ways that different parts of China do not. Even meat consumption in rural China is nothing like meat consumption in the West. There is no part of China that consumes beef in quantities typical of Texas or Argentina.

The core methodology of the book is so strong, but then the principal conclusion is derived from a methodology that is more circumstantial. This is a kind of bait-and-switch, which does not invalidate the Campbells’ thesis, but certainly opens doors for doubt.

Here’s a plot from Chapter 5, showing that countries with higher consumption of animal protein tend to have higher rates of death from cardiovascular disease.

Animal-protein_Heart-disease

One problem with this evidence is that the same countries with high animal protein consumption also eat more saturated fats, and more fat in general. You could draw a nearly identical plot averring that it was fat intake and not animal protein that causes heart disease.

Principal study results

The core of the book is in statistical excerpts from the Study, in Chapter 4.

  • Rats are fed protein from casein, a dairy source. Some of the rats are on a 5% protein diet, others on a 20% protein diet. Both groups are challenged with aflatoxin, a potent carcinogen. None of the low-protein rats got cancer; but all the high protein rats contracted cancers.
  • In America, the (age-adjusted) death rate from coronary heart disease is 17 higher than the corresponding rate in rural China. Szichuan and Guizhou had extraordinarily low levels of CHD in middle-aged men, (even for China). What are they doing right? These areas had some of the lowest meat consumption levels. Compared to Western diets, the China study was comparing low animal protein with lower animal protein. Still, a robust association of animal protein with blood cholesterol and cancer were found, even at very low intake levels.
  • Chinese fiber intake is three times as high as in America (33 vs 11 g/day). Fiber decreases residence time of food in the GI track, and also absorbs and eliminates toxins as well as nutrients. The Campbells propose that this is part of the explanation for lower cancer rates in China.
  • Chinese women have half the estrogen levels of US and British women, and their reproductive lives are shorter at both ends. Lifetime exposure to estrogens is less than 40% that of American women. The Campbells propose that this is a factor in the lower breast cancer rate in China – less than 1/5 the American rate.
  • “Average calorie intake per kilogram of body weight was 30% higher among the least active Chinese than among average Americans. Yet, body weight was 20% lower. How can it be that even the least active Chinese consume more calories yet have no overweight problems?”
  • The Campbells propose that (1) even the least active Chinese are more active than the average American, and (2) higher proportion of complex carbs compared to protein and fat in the diet signals the body to store fewer calories as fat.
  • A whole section of the book is devoted to the association between cow’s milk and auto-immune diseases. Childhood diabetes is much more prevalent in children who are weaned early from breast milk to cow’s milk.

Conclusions
Much of the research for this book took place more than twenty years in the past. It is an intriguing thesis that the Campbells raise, and the notion of a vegan advantage seems intuitively attractive. But there is a lot of direct evidence that the Campbells fail to address. Some of it involves epidemiological comparisons that are able to address more directly the difference between high-dairy and low-dairy diets. Some of it does not support the Campbells’ powerful thesis. I was left feeling that they have opened a useful window, but they have not fairly summarized the diversity of evidence on vegan diets.

The Declining Force of Natural Selection

The “declining force of natural selection” is the foundation of two classical theories of aging. The phrase means that what happens when an individual is young contributes more to its fitness than what happens later in life. A new study seeks to test whether aging tends to evolve in the direction predicted by this theory, and the results have raised some eyebrows.

Setting the stage

For more than a century, it has been recognized that aging presents a conundrum for the theory of evolution. Aging reduces individual competitiveness and cuts off reproduction via senescence or death. Aging decreases fitness. How could aging have evolved?

There have been two sorts of answers, one based in the fitness of the individual, the other in the fitness of the community. Since aging is irredeemably bad for the individual, the community-fitness idea might seem to be a natural candidate. But most evolutionary biologists today are skeptical of the concept of community fitness; they believe that everything in evolution should be explainable in terms of the selfish gene. The classical hypothesis (from individual fitness alone) is based on the declining force of natural selection. This idea was first articulated by the British Nobel laureate Peter Medawar in a seminal book in 1952. Medawar started from the idea that death rates in nature tend to be high, just because it’s a rough-and-tumble world out there. For reasons that have nothing to do with aging, very few individuals actually live long enough to die of old age. So natural selection has rewarded animals that fight hard and reproduce fast. Even if that causes them to age more rapidly, it won’t matter much in the end because almost everyone will die of something else before they ever get to the age where aging could affect them.

An alternative answer which I and others have promoted is that aging isn’t about individual fitness at all, but rather the fitness of communities and populations. In nature, death rates tend to be clumpy – meaning that either everyone is dying or hardly anyone. If there is a famine or an epidemic, then the death rate is very high and everyone is at risk. But in conditions of plenty, when no new diseases threaten, the death rate can be very low. This clumpiness leads to boom-or-bust population cycles, in which population can grow to unsustainable conditions of crowding, until, too late, the population comes crashing down and extinction is a real risk. The population-based theory is called the Demographic Theory of Aging, and it states that the evolutionary significance of aging is to help level the population death rate in good times and in bad, avoiding population overshoot and reducing the risk of extinction.

Two theories face off

How can we tell which is correct? There is one area where the two ideas clearly make opposite predictions: How ought life span to evolve in response to the “background” death rate? When many animals are dying young, for whatever reason, the individual-based theory says that life span should evolve to be shorter, because the declining force of natural selection is declining so much the faster. But the theory from community fitness predicts the opposite effect: Aging responds as a complement to the background death rate. When the background death rate is low, then life span evolves shorter so that the death rate from aging can take up the slack; when the background death rate is high, then longer life span evolves as aging takes a vacation because there is no need for death from old age when other natural forces are already trimming the population.

(The Caloric Restriction effect is an easy prediction from the Demographic Theory. When there is a famine and everyone is starving, aging slows way down because the community needs to save every individual life. But when food is plentiful, that is the time when the risk of overpopulation looms, so aging occurs more rapidly, in order to thin the population.)

The individual-based theory and the communal-fitness theory make different predictions. Where does nature weigh in?

Two studies, two answers

The canonical experiment was done by Steven Austad as his dissertation project in 1993.  He compared two populations of opossums, one on the mainland that was ravaged by predators, and the other on an island where the opossums had lived without predators for thousands of years. The island opossums lived twice as long as the mainland opossums, supporting the classical idea of Medawar and the individual model.

But a decade later, David Reznick published a study of guppies in the river pools of Trinidad that reached the opposite conclusion. He identified adjacent pools, one with big fish that ate most of the guppies before they could grow up, and one with no larger fish at all, where the guppies grew unmolested. He captured guppies from the pool with low background death rate and from the pool with high background death rate, and brought them all back to his lab in Riverside, California where they could live out their lives in the safety of a fish tank. He found that the guppies from the site with the higher background death rate lived much longer than those from the lower death rate. Those fish that had the shorter life spans in the wild had longer life spans in the aquarium. This is the prediction of the community-fitness theory.

Reznick’s study got lots of attention, but wasn’t enough to overturn the strong presumption in favor of the individual-based theory.

New study from Sweden

Just last year, two researchers from Sweden threw their particular gasoline on this controversy with a lab study of roundworms. In one branch of their experiment, 85% of the worms were selected at random and killed. In the other branch, the temperature was raised gradually until 85% of the worms died of overheating. Hwei-yen Chen and Alexei Maklakov found that the first procedure led to agreement with the classical, individual theory. Life span evolved to be shorter. But under the second regimen, the worms evolved a longer life span.

Interpreting the results, David Dowling remarks that nature is more likely to emulate the second procedure. Individuals don’t tend to die at random, but rather because some environmental challenge takes out those individuals that can’t hack it. He notes that given the positive correlation between heat resistance and longevity, it is inevitable that the second procedure should lead to longer life spans.

But this is a genetic argument, not an evolutionary argument. From an evolutionary perspective, we must never expect that heat resistance is positively associated with longevity. Quite the opposite: the individual theory predicts that it should not be possible to extend life span without paying a price. If some worms live longer than others, they should be paying for it with a greater vulnerability to heat, or with some other weakness.

George Williams (whose name is associated with the classical theory for evolution of aging even more than Peter Medawar) predicted in 1957 that “Low adult death rates should be associated with low rates of senescence, and high adult death rates with high rates of senescence.” He was confident this must be true because he believed that individual fitness trumps group fitness every time, and so every gene that evolves must make a positive contribution to individual fitness. The only way a gene that shortens life span could evolve (in the Williams theory) would be if the primary function of the gene is to increase early survival or fertility. Every aging gene must entail a tradeoff, strong enough so that the net result is to benefit the individual.

Dowling, typically, doesn’t mention the alternative Demographic Theory. But he does duly remark that the genetic correlation is unexpeced and difficult to understand in terms of the classical theory. (Sometimes the cost is found as lower fertility, but Chen and Maklakov were careful to look for incidental effects on fertility, and found that fertility of the long-lived worms was not significantly different from the short-lived worms.)

The bottom line

The key question is whether there is a longevity cost to surviving and reproducing. Selfish gene theory demands absolutely that there must be a cost, but Chen and Maklakov suggest that sometimes there is none. The worms that were more robust to heat shock also lived longer. The more realistic branch of their experiment showed the result predicted by the theory of communal-fitness.

Score one for the Demographic Theory of Aging.

 For basic information about healthy living for a long life,
see the author’s permanent page at AgingAdvice.org.
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