AgingAdvice page is back online

Thanks to some of my readers who noticed that had disappeared.  It is now back online. is also back online.

(The site had been hosted by GoogleDrive, and I missed Google’s announcement that they would no longer be supporting public web pages.  The page now has a permanent home at  The web address remains the same.)

Putting the “system” back in Systems Biology

Cold Spring Harbor labs on Long Island has a diverse offering of conferences that attract experts from all areas of biology. For the last six years, there has been a sister group organizing conferences in Suzhou, China. I spent last week at the 2016 CSH Asia conference on Systems Biology.

While I have been to many conferences on aging and a few on evolution, this was my first Systems Biology conference. I looked forward to learning how biologists think about whole-body issues of homeostasis, organization, and (maybe if I was lucky) blood signals that regulate aging.

What I found instead was that researchers in systems biology are doing what other biologists are doing: they are babes in toyland, exploring the potential of a seductive array of new biomolecular tools. They are compiling catalogs and making maps and correlating every chemical they can find with every other chemical, and collaborating with statisticians to look for patterns in the data. If “systems thinking” is from the top down, what I found at this meeting was just the opposite.

A hundred years ago, Lord Rutherford said that “All science is either physics or stamp collecting.” He was mocking the biologists’ program of collecting specimens, classifying and cataloging them. Twentieth century biology turned this around; it was neither physics nor stamp collecting, but model-building. Systems biologists in particular have analyzed living organisms in terms of signals and networks and energy flows, and have generated a great deal of understanding. At its best, biology has forged a new mode of science.

So why is it that 21st Century systems biology is looking once more like stamp collecting? It’s a question I asked one of the conference organizers (in more polite terms), and he responded that “we are working from a reductionist framework. We are trying to build understanding from the bottom up.”

There’s a deeper answer

Why, after the revolutionary successes of late 20th century biology, should bioscience find itself back at square one, trying to build a foundation? The short answer: genetics is simple; epigenetics is complicated.

The heyday of genetics started from Crick’s decoding of the genetic code in 1961. DNA was revealed to be a blueprint for producing proteins that would do the body’s work. The code was just as simple and elegant as it could be, and the machinery to do the translation was segregated in ribosomes, which could be isolated and picked apart. The era of genetics ended in 2003 with the completion of the human genome project. Results were a surprise to everyone, and the message took awhile to filter into conceptual thinking: The genome is 3% genes and 97% gene regulation. All the impressive tasks of development, homeostasis, and metabolism are performed by an exquisitely adapted system that turns genes on and off in the right place at the right time.

2003 ended the era of genetics and began the era of epigenetics. How is gene expression regulated and contolled? DNA methylation was the first mechanism discovered. But as clues appeared and mechanisms were partially elucidated, it has become apparent that epigenetics is as complicated and intractable as it can possibly be. Besides methylation, there are more than 100 modifications of the DNA and its associated proteins (histones) that affect gene expression. There is also the way in which DNA folds around itself, leaving some regions open where they can be transcribed and keeping other regions under tight wraps. Finally, there is a variety of post-translational modifications; even after a stretch of DNA has been transcribed into RNA and translated into a protein, the protein can be turned on or off by adding a phosphate group or a methyl or acetate at any number of receptor sites.

Metabolism is now seen as a dense web of interacting processes, intertwined causes and effects. Gene network maps draw lines between genes that are co-expressed, and can divide the territory into subsets (modules) that are more closely related to each other than to other modules.


But this is a picture that only a computer could love; it contains intricacies on a scale that human consciousness cannot grasp with conceptual understanding.

Contrast this to the naive simplicity of Crick’s Central Dogma of Molecular Biology: Information flows in one direction, from DNA to RNA to proteins. Crick lived to see his insight de-dogmatized by exceptions, but it has been since his death (2004) that the essential, bewildering complexity of biochemical networks has been revealed.

No wonder the community of systems biologists feels that they are starting over again, collecting, classifying and cataloging stamps.

New Tools

Biochemical science this last few years seems to be driven by newly available technologies. These are so powerful and coming so fast that just exploring what they can tell us is occupying the lion’s share of available funding and lab space. I knew about some of these, and several more were new to me last week.

  • CRISPR-Cas9. This is a tool adapted from bacterial defenses against viruses. It has made it easy to delete a particular gene within a living cell culture, and perhaps within a living, breathing animal. It has been adapted to insert an exogenous gene at a particular location on a particular chromosome, and even to modify a particular section of DNA to turn a gene on or off. Cas9 has been limited to small “payloads”, adding short sequences of DNA, but just last year, techniques were reported for splitting a larger payload among multiple Cas9 vectors [Ref1, Ref2] in such a way that they piggyback.
  • Hi-C is a modern, computer-intensive version of a 20-year-old procedure for mapping a coiled and folded chromosome in 3-space. First, the chromosome is frozen by introducing random bonds between nearby strands. Then it is fragmented with a DNA slicing enzyme. Then the pieces are sequenced (this is the new part) with high throughput sequencing that can tell you which genes are physically closer to which other genes in the folded, 3-D configuration.  Finally, the computer can be used to reconstruct a picture of the 3-D configuration.
  • ATAC-Seq. This is a tool for finding the genes that, at any given time, are in open stretches of DNA (euchromatin), available to be transcribed. Chromosomes are peppered with an enzyme that slices up DNA. The fragments are then collected and sequenced, and a computer program matches the fragments to map where they came from. The DNA that was tightly-packed (heterochromatin) contributes few fragments because the enzyme can’t reach it. Thus the genes that are seen are representative of what is available for transcription.
  • Methylation mapping. Methylation of C’s in stretches of C-G-C-G-C-G-C-G-C-G within a chromosome is the best-studied mechanism of epigenetic regulation. Just in the last few years, it is possible to map the methylation state of an entire genome. A chemical transformation transforms only unmethylated C’s to uracil in a strand of DNA (with bisulfite), leaving the methylated C’s unconverted. By sequencing the strand before and after this transformation, and using a computer to map the differences, the places where C’s were methylated can be identified.
  • ChIP-Seq. If you know of a particular transcription factor—a protein that binds to DNA and turns certain genes on or off—then this technique can tell you where on the DNA the protein attaches itself. The technique combines two older technologies: immunoprecipitation, where an antibody is introduced that picks out one particular protein, and high-throughput sequencing, which identifies and locates the patch of DNA that is stuck to the CHIPped protein.

Gene expression maps have been around for a few years. They provide an enormous amount of information about what genes are being expressed where and when, but they are notoriously difficult to make sense of.  More recent are correlation maps, in which every gene is correlated with every other gene in a huge matrix that shows how likely they are to be expressed at the same time. I am intrigued by principal component analysis. You can start with a set of genes and measure all the cross correlations, and the math comes up with a combination of the genes most likely to be expressed together (Principal Component #1).

Sometimes a single gene sticks out, and the authors conclude that this particular cancer can be treated by targeting this particular gene.

More often, the results show a combination of hundreds of genes that tend to be expressed together in a particular proportion, say 1.2% gene #1, 0.04% gene #2, 0.15% gene #3…and so on, with coefficients for hundreds of genes. This is the output of a principal component analysis. If such a profile is identified with a healthy state, or a young state, we do not yet have the capability to shape this profile of gene expression in a cell culture, let alone in a living animal. But it is not inconceivable that we will acquire this ability with advancing biotechnology of the coming decade(s).


The Harvard laboratory of Brenda Andrews is fully automated, with robotic handling of yeast culture plates, robotic data collection, computerized data analysis. All that’s left for the human to do is to write the historical introduction and submit the manuscript. I am a fan of artificial intelligence and computer learning for some applications. Computers have their own ideas of what constitutes a pattern or a trend. They often come up with unexpected solutions to problems, even simple solutions on rare occasions. But AI never produces elegant theories or new ways to look at the big picture. We give that up when we rely on computers to do science for us.

Growth, Development and Aging

Growth and development are programmed, to be sure, but (so far as we know at present) there appears to be no central coordinator of the process. Rather, the tangled web of chemical signals adapts and responds to changes in the body and in itself. The intelligence is not in a central brain, but is distributed through the system itself. There is no one calling the shots. The metabolism behaves intelligently the way a beehive behaves intelligently, though no single bee has a a clue concerning the hive’s plans and strategies.

I have bet my career on the thesis that aging is a metabolic program, a continuation of the process of development into a phase of self-destruction. I used to think that this meant there were genes for aging. I was the most optimistic speaker at the anti-aging meetings. “All we have to do is find the aging genes and turn them off.”

Then I accepted the new picture centered on epigenetics. I thought that chemical signals were arranged in hierarchies, with a few hox genes and transcription factors controlling a much larger number of workhorse proteins that actually get the job done. The job of the anti-aging scientist is to re-balance the transcription factors to create a more youthful profile, and the workhorse proteins would dutifully take care of the rest.

But more recently, I learned that there are thousands of transcription factors, comparable to the number of genes they regulate.  And the lines between promoters, enhancers, transcription factors, and metabolites has been blurred.  A less optimistic scenario is beginning to come into focus for me. I believe that aging is a continuation of the developmental program, but development is inscrutably complex, and it seems to be controlled by a web of interacting molecules that play multiple roles. Each one is a cause and an effect. Many have roles both a regulatory agents and also as workhorses. There’s no one in charge of the factory. The factory is designed so ingeniously that it runs itself.

Study of Development may be a Key to Aging

Much is known about details of development, but there is no systemic understanding of how the process is put together

    • How much is predetermined in cell lineage?
    • How much is self-organization?
    • How much is centrally organized, through internal secretions?
    • How do these three interact?

Of course, the same questions may be asked about aging. It may be more feasible to approach these questions through development than through aging, (1) because development happens on a faster time scale, (2) because aging contains a stochastic element not present in development, and (3) because the phenotypes of development can be observed clearly and locally. I recognize that this suggestion means going back to basic science to make a long-term investment in understanding of aging, but maybe that’s what we need.

Energizer lab worms keep on keeping on long after they have stopped laying eggs

C. elegans worms live up to 3 weeks, and for the last 2½ weeks, they are post-reproductive, unable to lay fertile eggs because they have run out of sperm to fertilize them.  Why do they stop fertilizing their eggs, when sperm is metabolically ‘cheap’? Why has evolution endowed these nematodes with such an extended period of non-productive life?  In mammals, it is common to speak of the “grandmother hypothesis”—that human females live on past menopause in order to have time to take care of their grandchildren.  But worms haven’t been observed to care for their grandchildren.  

My hypothesis is that, nevertheless, maybe they do.  The service they provide to their grandchildren is in the form of pheromones.

Pheromones are powerful chemical signals.  Incredibly small amounts can affect behavior.  Hormones are chemical signals within the body, and pheromones are like external hormones, directed toward the behavior of other individuals.  (When the individuals are of a different species, they are called kairomones.)

C. elegans is the lab worm that has been so useful in lifespan experiments.  In the wild, it is thought that these millimeter-long worms live in the ground on rotting fruit or mushroom.  What is clear is that their life history is exquisitely adapted to boom-and-bust cycles of food availability.  Like many animals, they live a long time when they are waiting for food to appear, and a short time when they are eating and reproducing.  And unique to C. elegans, the worm’s best trick is to go into a state of semi-dormancy, something like a spore, that can live for months at a time without food or water, and which resists heat, cold, chemical toxins and other insults.  The spore-like state is called a dauer.

Young worm — Old worm

Young worm — Old worm

About 18-24 hours after a worm egg hatches, the stage-3 larva makes a decision whether to go for it, grow and eat and lay lots of eggs, or to become a dauer, to wait and bet on a better opportunity later on.  My hypothesis starts with the idea that the dauer state represents the only way that a worm can hope to spread its progeny from one food site to another, which is essential if the lineage is to have a long-term future.  “A chicken is an egg’s idea for making more eggs.” A colony of worms on one food source is a dauer’s way of making more dauers.

Come with me, and explore the dauer’s-eye perspective for a moment.  You are a fraction of a millimeter long, and you weigh a few billionths of a gram.  Imagine that you are carried by a bird or animal or by the wind, and you land on a piece of fruit.  Your lucky day!  Sensing food and moisture, you morph from the dauer state, turn yourself back into a larva, and you eat and eat, you grow and grow, and you lay several hundred eggs, all endowed for life with a copious food supply.

But if you’re thinking for the long term (all right, worms don’t have brains; but your genes can still be thinking) — if you’re thinking for the long term, your strategy will be to produce as many dauers as possible from this one piece of fruit.  Each dauer is a lottery ticket for your future legacy.  Remember that this piece of fruit is finite, and that when it’s gone, life beyond this one oasis is a very chancy proposition.

In the end, a good measure of your success in the evolutionary game—your fitness—is the number of dauers that come out of this piece of fruit.

With dauer number in mind as a goal, what’s your best strategy?  Well, for the first generation, it’s to produce several hundred eggs.  For the second generation, it’s to produce tens of thousands of eggs.  For the third generation, several million eggs.  But at that point (or possibly the fourth generation, depending on survival of your grandchildren) it will be important not to keep going with egg-laying, but to start generating dauers.  The decision that every larva must make should, for optimal fitness, be NOW for the first generation, NOW for the second, NOW, for the third, and LATER for the fourth generation.

But how are you to know that it’s the fourth generation?  Remember that you haven’t got eyes or ears or a brain.  You might just keep choosing NOW while there’s food, and wait until there’s no more food to say LATER.  This would be something you can sense for yourself, but (crucially) this is a flawed strategy.  The problem is that your population is growing exponentially.  Exponential population shoots up so quickly that there is no warning at the end.  There might be a billion larvae all competing for the food that was perfectly adequate for the last generation, when the population was a hundred times smaller, but now there are so many mouths to feed that NONE of them will make it to Stage 3 Larvahood, when the worm is mature enough to become a dauer.  

The population that can sense crowding and decide LATER before there is a food shortage has a big advantage in the number of dauers that will eventually be produced.  This is where your grandmother can be of great assistance.  She has stuck around, though she’s all done laying eggs, and has no prospects for herself, but she and her children can send pheromone signals to their grandchildren, warning them, “Don’t do it!  Don’t grow up!  Take refuge in dauerhood while there’s still time.  If you wait until we run out of food, it will certainly be too late!”

My theory is that the reason that C. elegans goes on living so many days beyond its fertility is that she is sticking around to send pheromone signals to her great grandchildren.  The 2-3 week lifespan is just sufficient to last through 4 generations.  The theory makes predictions that are being tested in the Beijing lab of Meng-qiu Dong, where I am a visiting scholar this fall.  Predictions are

  1. Life span should be extended in the presence of many old worms.
  2. The presence of just a few very old worms should be sufficient to bias a young larva’s decision toward becoming a dauer.
  3. Dauers should be hardy enough to survive the digestive tract of a mouse or bird, so that they can hitch a ride out into the wide world, looking for a new food source.

Nictation movie

Here’s a 6-second movie of nictating behavior in a dauer of C japonica, a cousin of C. elegans.  Does the dauer look like she’s hiding from predators, or does it look like she’s begging to be eaten?  My guess is that worms depend on larger animals to reach new food sources that they could never find in a lifetime at their usual squirming pace in the ground.

Prediction (1) has already been tested in the Dong lab, with encouraging results.  But the other two are stronger consequences of the theory, and I’ll be eager to see how the experiments fare.

Note on evolutionary theory and the state of the science

George Williams laid the foundation for the evolutionary theory of aging that is widely accepted and applied today.  In his seminal paper of 1957, he was bold and astute enough to make 8 predictions that could be used to validate (or falsify) his theory.  In the intervening years, only 2 of the 8 have been borne out, and 4 have been flat-out falsified.  One of the predictions that turned out to be false was that death ought to ensue promptly when the capacity for reproduction is lost.  Reproductive lifespan and actuarial lifespan should coincide closely, but they don’t.

Williams was, of course, aware that human females are an exception, handily explained by the “grandmother hypothesis” — older women are motivated to stick around because rearing young humans takes such a long time that a woman really needs to outlive her fertility.  But he would be surprised to learn that chickens and whales, partridge and elephants, guppies and yeast cells all have substantial post-reproductive lifespans.

It is to Williams’s credit that he put out a well-reasoned theory and volunteered ways it could be put to the test.  On the other hand, it reflects badly on the evolutionary scientists who came after him that as the theory was falsified time and again, they clung to the theory, patched it, made excuses for it, but never put it aside to look for a theory that aligns better with experimental reality.

With a lifespan eight times as long as their fertile life, C. elegans worms are in a class by themselves.  Their post-reproductive life has been recognized as a scientific puzzle, and I look forward to finding out if my own theory will stand up to experimental tests.

Nutritional Geometry 3: Ketosis— benefits & risks of oil-rich diets

The advantage of a low-carb diet is that it minimizes insulin spikes that can contribute to loss of insulin sensitivity=metabolic syndrome. The advantage of a low-protein diet is that it offers some of the anti-aging benefits of calorie restriction, and is associated with lower all-cause mortality. Can the two be combined? The low-protein, low-carb diet is by definition a high-fat diet. High fat diets are terrible for mice, but maybe they’re good for people. For more than a century, many people have found a high-fat diet is a path toward weight loss. Just in the last few years, there is a lot of salesmanship based on a little science that suggests a ketogenic diet can be healthy for the brain.

Does a high-fat diet induce ketosis? Is it practical? Is there a price to pay for too much oil?

This blog edition also features a description of my personal eating habits, as a curious example rather than a universal prescription.

There are but three macronutrient classes, so the only way to have a low-protein, low-carb diet is to eat a lot of fats. The low-carb diet has at least a 150-year history.

One of the first registries on low-carbohydrate diets was in 1860 when English casket maker William Banting was prompted to lose weight and decided to write “Letter on Corpulence, Addressed to the Public”, which aimed to completely avoid starch and sugar. Banting lost 45 pounds in a few weeks (with additional weight loss over several months) on a diet composed by meat (generally mutton or beef – plus poultry and fish), two very small (1 ounce) portions a day of rusk or dry toast, tea (with no sugar or milk), and a 2-4 drinks of dry wine or port a day as spelled out in his own writings. Thus, the Banting diet became a very well known method during that period of the 19th century, promoted also for weight loss and diabetes control [Wikipedia].

Diets comprising 80-90% fat have a remarkable benefit for people who suffer epileptic seizures. Known generically as ketogenic diets, they have been recommended by extension for other neurological disorders, and, of course, for diabetes (types 1 and 2). There is some evidence that low-carb diets protect against Alzheimer’s Disease. When sugar is not available, the body turns to fat as a fuel, and converts fat to three related biochemical forms (called ketone bodies) as a circulating intermediary. Cancer cells, however, can’t use ketones, so cancer also responds to a ketogenic diet (and even better to fasting). But if you don’t have a life-threatening disease and you don’t happen to be an Inuit, a diet that is 80% fat may feel extreme. It takes a lot of motivation to stick to a ketogenic diet, and for people who are basically well, the promised benefits are not commensurate with the discipline. All of the evidence for benefit in healthy individuals is theoretical, based on biochemistry.

Studies of lab mice consistently show that a high fat diet leads to shorter life span, compared to carb- or protein-based diets. The reason for this seems to be that fat nurtures a kind of intestinal flora that excite an immune response called endotoxicity. It’s the elevated inflammation that shortens lifespan. Whether this response is essential to high-fat diets or whether it is exacerbated by refined carbohydrates in the mouse chow, whether endotoxicity is also induced in humans on a high-fat diet–all these subjects are vigorously debated. The one clear message is that fiber is an antidote, so that anyone considering a high-fat diet should be doubling up on dietary fiber.


A Tasty, Satisfying Fat-based Vegan Diet

Think avocado salads and fried green vegetables with a bit of tofu. Think coconut and walnuts and greens and more greens. Here are some recipes from the incomparable Enid Kassner. All are guaranteed delicious, and all have 70-75% of calories from fat, with the residual comprising various mixtures of carb and protein.

1. Saag Tofu

8 oz spinach (washed and roughly chopped)
5 oz fresh tomato, chopped
6 oz extra firm tofu
1.5 oz coconut oil (3T)
Grated fresh ginger, chopped garlic, garam masala
(Indian spice mixture)
Press extra liquid from tofu using a towel. Cut into cubes, sprinkle with salt, and microwave about 3-4 minutes. Set aside. Heat oil and add ginger, garlic, and spinach. Stir frequently as spinach cooks and reduces in volume. Add chopped tomato and cook lightly, adding tofu, salt and garam masala to taste.


2. Fried Cauliflower with Tofu and Cashews

9 oz cauliflower florets
2.5 oz sweet red pepper, sliced
2T + 1t peanut oil
Scant oz chopped roasted cashews
4 oz extra firm tofu

Press extra liquid from tofu using a towel. Cut into cubes, sprinkle with salt, and microwave about 3-4 minutes. Set aside.

Heat oil and cook vegetables, stirring frequently, adding garlilc, if desired. Add tofu and nuts, salting to taste.


3. Marinated Vegetables

5.5 oz mushrooms, cleaned and sliced
3 oz chopped cucumber
4 oz green beans, chopped and lightly boiled (about 3-4 minutes)
.5 oz finely chopped sweet onion
2 oz sliced black olives
1.25 oz toasted almonds, sliced or chopped
1.5 oz olive oil (3T)
1 oz vinegar (2T)

Combine olives and vegetables and marinate in oil and vinegar, adding salt and pepper to taste. Can also add dried herbs, such as oregano, basil, or thyme. Let sit several hours at room temperature or overnight in refrigerator. Sprinkle with nuts when ready to eat.

A Bit of Biochem

Ketones are carbon chain molecules with an oxygen double-bonded to a carbon (C=O) somewhere in the middle. Beta hydroxybutyrate (BHB) is best-known of three “ketone bodies” that circulate in the blood. It is burned as fuel, but it is also a signal molecule “BHB has been found to act as a histone deacetylase (HDAC) inhibitor and to increase brain-derived neurotrophic factor (BNDF) levels and TrkB signaling in the hippocampus.” [ref] (BHB signals growth of new neurons and affects gene expression in unknown, complex but probably good ways, since BHB is associated with fasting and exercise.)

When the body burns ketones instead of glucose, less oxygen is needed. Theoretically, in intense aerobic exercise, when the body is limited by how fast oxygen can be pumped through the lungs and into the blood, there ought to be a slight benefit in power when the body is in ketosis mode. One wonky self-experimenter working with the lab of Dominic D’Agostino at U of S Florida claims to have measured and confirmed this effect in himself.


Eat Ketones?

If much of the benefit of a low-carb diet comes from the body’s adaptation via ketosis, why not cut out the middleman and just eat ketones? Once again, the miracle of capitalism has advanced ahead of the plodding pace of epidemiological science. There are several products to choose from. Raspberry ketones seem to be worthless. Ketones are cheap to manufacture, but you need a large quantity because it’s a food, not a supplement, and ketones taste awful. (Why should sugar taste so good when it’s so bad for us, and why should ketones taste so bad? Maybe because evolution is keenly concerned with our short-term survival, but is ambivalent about prolonging our lives.) Medium-chain triglycerides as found in coconut oil and butter seem to be a platable way to boost the benefits of a ketogenic diet, including weigh loss.

D’Agostino is researching and developing palatable ketone supplements.

This summer, Andrew Murray and colleagues at Oxford University reported an experiment in which mice had a ketone supplement (not BHB) added to their chow, and they showed both faster learning and greater aerobic capacity [pre-pub ref].


Modified Atkins Diet

Dom D’Agostino is the king of ketogenic research, and for himself he has chosen a Modified Atkins Diet accompanied by ketogenic substitutes, which offers much of the same benefit as a ketogenic diet. The original Atkins diet was heavy on meat and fish. The Modified Atkins Diet developed at Johns Hopkins for epilepsy has less protein, 65% fat and ultra-low carbohydrates (~5%) but more flexible than the ketogenic diet.

There are a range of generic Atkins diet spinoffs, including some that have less or zero meat. (I keep coming back to vegetarian options not just because my inclination is in this direction, but because there is good evidence for a longevity benefit. I also respect that other bodies make other choices.) All the “modified” versions introduce a lot more green vegetables, because their fiber and nutrients add a lot of value, and because the diet is much more varied and platable with vegetables. Some Atkins versions allow limited fruit. Atkins-spinoff diets tends to have less protein than the original and 50-60% fat, with limited carbohydrates, but more than the strict 5% prescribed for epilepsy by the Hopkins docs.


My diet

People ask how I eat, and I’m happy to tell them, but I make clear this is not a recommendation. Diets are personalized. At one level, there’s what you can live with and feels good to you; at a deeper level, you can experiment with different diets, see how your weight and your energy level and your emotional and intellectual life respond; at a deeper level yet, sensitize yourself to your body’s signals with yoga or biofeedback or meditation techniques, and perhaps your body will let you know what it wants.

Fresh vegetables, fruits, nuts, soy and other beans are the mainstay of what I live on. In addition to fat from nuts, I dress salads generously and stir-fry my vegetables in oil. I have been vegetarian since 1973. Lately, my diet is close to vegan, ultra-high fiber, low carb, relatively high in protein. (No vegetarian diet can be high-protein by Atkins standards.) Fish oil capsules are my one departure from strict vegetarianism. I start the day with a big bowl of raw wheat bran (the only wheat that I eat), made palatable with fruit and soymilk, sometimes blended in a smoothie.

(I’m 67 and exercise frequently and in diverse ways. If I were younger or less active, I would eat less protein.)

I eat no grains or potatoes: no rice, wheat, pastries, pasta, or cereals. Other starches occasionally: carrots, winter squash, beets, parsnips. I eat fruit liberally. I will also occasionally savor a square of chocolate or a spoonful of ice cream as a special treat. I’ll stop what I’m doing and roll it around in my mouth, extending and savoring the experience. An absolute proscription of grains helps me say no to cookies and cakes.

I confine eating to 12 hours each day. I fast one day a week, about 32 hours from Wed evening to Friday morning. I do longer fasts 2 or 3 times a year, and Longo semi-fasts another 4 or 5 times a year.

While I’m in personal mode, I’ll add a note on flatulence. What about all that fiber and beans? The truth is that I’ve had a gassy metabolism my entire life, especially so when I was growing up on a typical American diet of meat-and-potatoes, milk and cookies. In the last 10 years, my body has made a transition to a less prodigious level of flatulence, and I don’t know why–but this has been despite the beans and the wheat bran. (I still can’t eat black turtle beans, though I’d like to.)


The Bototm Line (concluding three long blogs on nutrition)

If we are what we eat, maybe the surprising thing is that what we eat makes so little difference that it requires human studies with tens of thousands of participants to be able to detect an effect of diet on lifespan. Monarch caterpillars eat only milkweed. Pandas won’t eat anything but bamboo. There are hundreds of species of wasp, each co-evolved to drink nectar from only a single species of fig flower. But we humans are omnivores, and our bodies are geniuses of homeostasis, able to stay pretty well on track no matter what we put into them. The differences in epidemiological studies amount to a few percent of lifespan, even as test diets are varied all over the map. Native Americans of the Paiute tribe eat grasshoppers, and Inuits eat blubber; on the Trobriand Islands they eat yams, Amazon tribes eat fruit, while the Masai eat a mixture of ox blood and milk. Yet the similarities in their life trajectories overwhelm the differences.