I’ve recently taken a large interest in the human microbiome and parasites and their relationship with how we behave. There are certain parasites that can and do have an effect on human behavior, and they also reduce or increase certain microbes, some of which are important for normal functioning. What I’m going to write may seem weird and counter-intuitive to the CI/CO (calories in/calories out) model, but once you understand how the diversity in the human mirobiome matters for energy acquisiton, then you’ll begin to understand how the microbiome contributes to the exploding obesity rate in the first world.
One of the books I’ve been reading about the human microbiome is 10% Human: How Your Body’s Microbes Hold the Key to Health and Happiness. P.h.D. in evolutionary biology Alanna Collen outlines how the microbiome has an effect on our health and how we behave. Though one of the most intriquing things I’ve read in the book so far is how there is a relationship with microbiome diversity, obesity and a virus.
Collen (2014: 69) writes:
But before we get too excited about the potential for a cure for obesity, we need to know how it all works. What are these microbes doing that make us fat? Just as before, the microbiotas in Turnbaugh’s obese mice contained more Firmicutes and fewer Bacteroidetes, and they somehow seemed to enable the mice to extract more energy from their food. This detail undermines one of the core tenets of the obesity equation. Counting ‘calories-in’ is not as simple as keeping track of what a person eats. More accurately, it is the energy content of what a person absorbs. Turnbaugh calculated that the mice with the obese microbiota were collecting 2 per cent more calories from their food. For every 100 calories the lean mice extracted, the obese mice squeezed out 102.
Not much, perhaps, but over the course of a year or more, it adds up. Let’s take a woman of average height. 5 foot 4 inches, who weights 62 kg (9st 11 lb) and a healthy Body Mass Index (BMI: weight (kg) /(height (m)^2) of 23.5. She consumes 2000 calories per day, but with an ‘obese’ microbiota, her extra 2 per cent calorie extraction adds 40 more calories each day. Without expending extra energy, those further 40 calories per day should translate, in theory at least, to a 1.9 kg weight gain over a year. In ten years, that’s 19 kg, taking her weight to 81 kg (12 st 11 lb) and her BMI to an obese 30.7. All because of just 2 percent extra calories extracted from her food by her gut bacteria.
Turnbaugh et al (2006) showed that differing microbiota contributes to differing amounts of weight gain. The obese microbiome does have a greater capacity to extract more energy out of the same amount of food in comparison to the lean microbiome. This implies that obese people would extract more energy eating the same food as a lean person—even if the so-called true caloric value on the package from a caloriometer says otherwise. How much energy we absorb from the food we consume comes down to genes, but not the genes you get from your parents; it matters which genes are turned on or off. Our microbes also control some of our genes to suit their own needs—driving us to do things that would benefit them.
Gut microbiota does influence gene expression (Krautkramer et al, 2016). This is something that behavioral geneticists and psychologists need to look into when attempting to explain human behavior, but that’s for another day. Fact of the matter is, where the energy that’s broken down from the food by the microbiome goes is dictated by genes; the expression of which is controlled by the microbiome. Certain microbiota have the ability to turn up production in certain genes that encourage more energy to be stored inside of the adipocite (Collen, 2014: 72). So the ‘obese’ microbiota, mentioned previously, has the ability to upregulate genes that control fat storage, forcing the body to extract more energy out of what is eaten.
Indian doctor Nikhil Dhurandhar set out to find out why he couldn’t cure his patients of obesity, they kept coming back to him again and again uncured. At the time, an infectious virus was wiping out chickens in India. Dhurandhar had family and friends who were veteraniarians who told him that the infected chickens were fat—with enlarged livers, shrunken thymus glands and a lot of fat. Dhurandhar then took chickens and injected them with the virus that supposedly induced the weight gain in the infected chickens, and discovered that the chickens injected with the virus were fatter than the chickens who were not injected with it (Collen, 2014: 56).
Dhurandhar, though, couldn’t continue his research into other causes for obesity in India, so he decided to relocate his family to America, as well as studing the underlying science behinnd obesity. He couldn’t find work in any labs in order to test his hypothesis that a virus was responsible for obesity, but right before he was about to give up and go back home, nutrional scientist Richard Atkinson offered him a job in his lab. Though, of course, they were not allowed to ship the chicken virus to America “since it might cause obesity after all” (Collen, 2014: 75), so they had to experiment with another virus, and that virus was called adenovirus 36—Ad-36 (Dhurandhar et al, 1997; Atkinson et al, 2005; Pasarica et al, 2006; Gabbert et al, 2010; Vander Wal et al, 2013; Berger et al, 2014; Pontiero and Gnessi, 2015; Zamrazilova et al. 2015).
Atkinson and Dhurandhar injected one group of chickens with the virus and had one control group. The infected chickens did indeed grow fatter than the ones who were not infected. However, there was a problem. Atkinson and Dhurandhar could not outright infect humans with Ad-36 and test them, so they did the next best thing: they tested their blood for Ad-36 antibodies. 30 percent of obese testees ended up having Ad-36 antibodies whereas only 11 percent of the lean testees had it (Collen, 2014: 77).
So, clearly, Ad-36 meddles with the body’s energy storage system. But we currently don’t know how much this virus contributes to the epidemic. This throws the CI/CO theory of obesity into dissarray, proving that stating that obesity is a ‘lifestyle disease’ is extremely reductionist and that other factors strongly influence the disease.
On the mechanisms of exactly how Ad-36 influences obesity:
The mechanism in which Ad-36 induces obesity is understood to be due to the viral gene, E4orf1, which infects the nucleus of host cells. E4orf1 turns on lipogenic (fat producing) enzymes and differentiation factors that cause increased triglyceride storage and differentiation of new adipocytes (fat cells) from pre-existing stem cells in fat tissue.
We can see that there is a large variation in how much energy is absorbed by looking at one overfeeding study. Bouchard et al (1990) fed 12 pairs of identical twins 1000 kcal a day over their TDEE, 6 days per week for 100 days. Each man ate about 84,000 kcal more than their bodies needed to maintain their previous weight. This should have translated over to exactly 24 pounds for each individual man in the study, but this did not turn out to be the case. Quoting Collen (2014: 78):
For starters, even the average amount the men gained was far less than maths dictates that it should have been, at 18 lb. But the individual gains betray the real failings of applying a mathematical rule to weight loss. The man who gained the least managed only 9 lb — just over a third of the predicted amount. And the twin who gained the most put on 29 lb — even more than expected. These values aren’t ’24 lb, more or less’, they are so far wide of the mark that using it even as a guide is purposeless.
This shows that, obviously, the composition of the individual microbiome contributes to how much energy is broken down in the food after it is consumed.
One of the most prominent microbes that shows a lean/obese difference is one called Akkermansia micinphilia. The less Akkermensia one has, the more likely they are to be obese. Akkermansia comprise about 4 percent of the whole microbiome in lean people, but they’re almost no where to be found in obese people. Akkermansia lives on the mucus lining of the stomach, which prevents the Akkermansia from crossing over into the blood. Further, people with a low amount of this bacterium are also more likely to have a thinner mucus layer in the gut and more lipopolysaccharides in the blood (Schneeberger et al, 2015). This one species of microbiota is responsible for dialing up gene activity which prevents LPS from crossing into the blood along with more mucus to live on. This is one example of the trillions of the bacteria in our microbiome’s ability to upregulate the expression of genes for their own benefit.
Everard et al (2013) showed that by supplementing the diets of a group of mice with Akkermensia, LPS levels dropped, their fat cells began creating new cells and their weight dropped. They conclude that the cause of the weight gain in the mice was due to increased LPS production which forced the fat cell to intake more energy and not use it.
There is evidence that obesity spreads in the same way that an epidemic does. Christakis and Fowler (2007) followed over 12000 people from 1971 to 2003. Their main conclusion was that the main predictor of weight gain for an individual was whether or not their closest loved one had become obese. One’s chance of becoming obese increased by a staggering 171 percent if they had a close friend who had become obese in the 32 year time period, whereas among twins, if one twin became obese there was a 40 percent chance that the co-twin would become obese and if one spouse became obese, the chance the other would become obese was 37 percent. This effect also did not hold for neighbors, so something else must be going in (i.e., it’s not the quality of the food in the neighborhood). Of course when obesogenic environments are spoken of, the main culprits are the spread of fast food restaurants and the like. But in regards to this study, that doesn’t seem to explain the shockingly high chance that people have to become obese if their closest loved ones did. What does?
There are, of course, the same old explanations such as sharing food, but by looking at it from a microbiome point of view, it can be seen that the microbiome can and does contribute to adult obesity—due in part to the effect on different viruses’ effects on our energy storage system, as described above. But I believe that introducing the hypothesis that we share microbes with eachother, which also drive obesity, should be an alternate or complimentary explanation.
As you can see, the closer one is with another person who becomes obese, the higher chance they have of also becoming obese. Close friends (and obviously couples) spend a lot of time around each other, in the same house, eating the same foods, using the same bathrooms, etc. Is it really an ‘out there’ to suggest that something like this may also contribute to the obesity epidemic? When taking into account some of the evidence reviewed here, I don’t think that such a hypothesis should be so easily discarded.
In sum, reducing obesity just to CI/CO is clearly erroneous, as it leaves out a whole slew of other explanatory theories/factors. Clearly, our microbiome has an effect on how much energy we extract from our food after we consume it. Certain viruses—such as Ad-36, an avian virus—influence the body’s energy storage, forcing the body to create no new fat cells as well as overcrowding the fat cells currently in the body with fat. That viruses and our diet can influence our microbiome—along with our microbiome influencing our diet—definitely needs to be studied more.
One good correlate of the microbiomes’/virsuses’ role in human obesity is that the closer one is to one who becomes obese, the more likely it is that the other person in the relationship will become obese. And since the chance increases the closer one is to who became obese, the explanation of gut microbes and how they break down our food and store energy becomes even more relevant. The trillions of bacteria in our guts may control our appetites (Norris, Molina, and Gewirtz, 2013; Alcock, Maley, and Atkipis, 2014), and do control our social behaviors (Foster, 2013; Galland, 2014).
So, clearly, to understand human behavior we must understand the gut microbiome and how it interacts with the brain and out behaviors and how and why it leads to obesity. Ad-36 is a great start with quite a bit of research into it; I await more research into how our microbiome and parasites/viruses control our behavior because the study of human behavior should now include the microbiome and parasites/viruses, since they have such a huge effect on eachother and us—their hosts—as a whole.
“if one spouse became obese, the chance the other would become obese was 37 percent.”
Is 37% the correct number here? Because that’s a little lower than the twin-percent.
Yea it’s right. Quote from the abstract:
A person’s chances of becoming obese increased by 57% (95% confidence interval [CI], 6 to 123) if he or she had a friend who became obese in a given interval. Among pairs of adult siblings, if one sibling became obese, the chance that the other would become obese increased by 40% (95% CI, 21 to 60). If one spouse became obese, the likelihood that the other spouse would become obese increased by 37% (95% CI, 7 to 73). These effects were not seen among neighbors.
Typo on my part. It’s siblings, not twins, that had a 40 percent chance of becoming obese if the other sibling did. Page 376 in the document has more information on the chance of becoming obese if person who one has close contact with becomes obese.
The Spread of Obesity in a Large Social Network Over 32 Years
Interesting that the effect wasn’t seen among neighbors. That, in my opinion, lends credence to the parasite/virus claim. I wouldn’t doubt that our microbiome is similar to those that we spend the most time around. I also don’t find it out of the ordinary that ‘microbiome switching’ is possible, which in my opinion is a part of the cause of obesity transmission.
It’s interesting to consider that a virus that depletes certain microbes in our bodies and screws with our body’s energy storage system is responsible for a part of the obesity epidemic. This is the case with a certain virus that chickens get, and being deficient in a certain microbiota due to a virus would mean that the body’s fat cells would intake more energy and get bigger, stopping production of other fat cells.
This take on obesity is pretty interesting, I’d like to see the microbiota/virus/social network hypothesis studied more because I think there is great promise there in identifying something that would work long term. There seems to be a gold mine of information there.
Gut flora … Whether these differences are the direct cause or the result of obesity has yet to be determined unequivocally.
some gross stuff:
do these transplants cure obesity?
One of the best cures we currently know of for obesity is bariatric surgery—and this changes the composition of the microbiome (Clement, 2011)
This is also seen in individuals who undergo gastric bypass surgery (Matuchansky, 2014; Palleja et al, 2016).
This is also a good review on fecal microbiota transplant (FMT) on animals and humans:
Treating Obesity and Metabolic Syndrome with Fecal Microbiota Transplantation
A woman also became obese after a fecal transplant from an overweight donor; so there is some anecdotal evidence there. There are a few stories like that around. And it makes sense too. The microbiome digests and breaks down a lot of food particles, and, if they have a microbiome as described in this article in the quote from Alanna Collen, they will, over time, become obese.
The fecal transplants cure obesity in ob/ob mice (the mice with the obese microbiome), and if I recall correctly, it’s been tried on humans and some reductions in weight were seen but I need to check one of my books for the specifics.
I think behavioral geneticists, psychologists et al really need to look into the microbiome if they want to explain human behavior. The microbiome influences gene expression, so the fact that they don’t integrate the microbiome and its influences on our genes to up or down regulate certain genes troubles me.
The microbiome opens up exciting avenues of research into mental diseases, obesity, metabolic syndromes and even autism. There is a growing body of research on the microbiome and autism as well.
The Gut Microbiome: A New Frontier in Autism Research
Microbiota Transfer Therapy alters gut ecosystem and improves gastrointestinal and autism symptoms: an open-label study
Emerging Roles for the Gut Microbiome in Autism Spectrum Disorder
New evidences on the altered gut microbiota in autism spectrum disorders
Emerging Roles for the Gut Microbiome in Autism Spectrum Disorder
There is a good amount of evidence for the microbiome and its role in autism. I know of the story of this one kid who was fine until he started getting antibiotics for a clogged ear and then he started acting weird. The doctors said he had autism and the mother didn’t believe it. So she jumped into the scientific literature and taught herself about autism and hypothesized that it may be caused by having fewer microbiota of a certain species. She took her idea to over 30 doctors who wouldn’t try it. One decided to try it and her son returned to normal. They tried it on 11 more kids and they too lost the symptoms. But they reverted back to the spectrum after they were taken off the antibiotics, which proves the causal role of the microbiota.
all i’ve read is that schizophrenia is related to celiac disease.
There is a relationship there between the microbiome, celiac disease and schizophrenia.
Review paper. Gluten-related disorders and schizophrenia – potential linking mechanisms, diagnostic and therapeutic challenge
Schizophrenia and the Gut Microbiome
A review on the relationship between gluten and schizophrenia: Is gluten the cause?
There is good evidence for the gluten/microbiome link with schizophrenia. The microbiome opens up a ton of new exciting possibilities for numerous causes of disease.
If only behavioral geneticists and psychologists integrated this research into their models, since as I’ve shown previously, the microbiome influences gene expression and behavior. Though this field is extremely new, they should still use some of these models to explain human behavior. The microbiome, clearly, influences our behavior—and by extent mental disorders etc—and so people who study behavior must become aware and knowledgeable on the microbiome and human behavior if they wish to fully explain it