Understanding Obesity? Fat Chance!

Obesity is one of our more widespread and serious health-threatening traits.  Many large-scale mapping as well as extensive environmental/behavioral epidemiological studies of obesity have been done over recent decades.  But if anything, the obesity epidemic seems to be getting worse.

There's deep meaning in that last sentence: the prevalence of obesity is changing rapidly.  This is being documented globally, and happening rapidly before our eyes.  Perhaps the most obvious implication is that this serious problem is not due to genetics!  That is, it is not due to genotypes that in themselves make you obese.  Although everyone's genotype is different, the changes are happening during lifetimes, so we can't attribute it to the different details of each generation's genotypes or their evolution over time. Instead, the trend is clearly due to lifestyle changes during lifetimes.

Of course, if you see everything through gene-colored lenses, you might argue (as people have) that sure, it's lifestyles, but only some key nutrient-responding genes are responsible for the surge in obesity.  These are the 'druggable' targets that we ought to be finding, and it should be rather easy since the change is so rapid that the genes must be few, so that even if we can't rein in McD and KFC toxicity, or passive TV-addiction, we can at least medicate the result.  That was always, at best, wishful thinking, and at worst, rationalization for funding Big Data studies.  Such a simple explanation would be good for KFC, and an income flood for BigPharma, the GWAS industry, DNA sequencer makers, and more.....except not so good for  those paying the medical price, and those who are trying to think about the problem in a disinterested scientific way.  Unfortunately, even when it is entirely sincere, that convenient hope for a simple genetic cause is being shown to be false.

A serious parody?
Year by year, more factors are identified that, by statistical association at least and sometimes by experimental testing, contribute to obesity.  A very fine review of this subject has appeared in the mid-October 201 Nature Reviews Genetics, by Ghosh and Bouchard, which takes seriously not just genetics but all the plausible causes of obesity, including behavior and environment, and their relationships as best we know them, and outlines the current state of knowledge.

Ghosh and Bouchard provide a well-caveated assessment of these various threads of evidence now in hand, and though they do end up with the pro forma plea for yet more funding to identify yet more details, they provide a clear picture that a serious reader can take seriously on its own merits.  However, we think that the proper message is not the usual one.  It is that we need to rethink what we've been investing so heavily on.

To their great credit, the authors melded behavioral, environmental, and genetic causation in their analysis. This is shown in this figure, from their summary; it is probably the best current causal map of obesity based on the studies the authors included in their analysis:

If this diagram were being discussed by John Cleese on Monty Python, we'd roar with laughter at what was an obvious parody of science.  But nobody's laughing and this isn't a parody!   And it is by no means of unusual shape and complexity.  Diagrams like this (but with little if any environmental component) have been produced by analyzing gene expression patterns even just of the early development of the simple sea urchin.  But we seem not to be laughing, which is understandable because they're serious diagrams.  On the other hand, we don't seem to be reacting other than by saying we need more of the same.  I think that is rather weird, for scientists, whose job it is to understand, not just list, the nature of Nature.

We said at the outset of this post that 'the obesity epidemic seems to be getting worse'.  There's a deep message there, but one essentially missing even from this careful obesity paper: it is that many of the causal factors, including genetic variants, are changing before our eyes. The frequency of genetic variants changes from population to population and generation to generation, so that all samples will look different.  And, mutations happen in every meiosis, adding new variants to a population every time a baby is born.   The results of many studies, as reflected in the current summary by Ghosh and Bouchard, show the many gene regions that contribute to obesity, their total net contribution is still minor.  It is possible, though perhaps very difficult to demonstrate, that an individual site might account more than minimally for some individual carriers in ways GWAS results can't really identify.  And the authors do cite published opinions that claim a higher efficacy of GWAS relative to obesity than we think is seriously defensible; but even if we're wrong, causation is very complex as the figure shows.

The individual genomic variants will vary in their presence or absence or frequency or average effect among studies, not to mention populations.  In addition, most contributing genetic variants are too rare or weak to be detected by the methods used in mapping studies, because of the constraints on statistical significance criteria, which is why so much of the trait's heritability in GWAS is typically unaccounted for by mapping.  These aspects and their details will differ greatly among samples and studies.

Relevant risk factors will come or go or change in exposure levels in the future--but these cannot be predicted, not even in principle.  Their interactions and contributions are also manifestly context-specific, as secular trends clearly show.  Even with the set of known genetic variants and other contributing factors, there are essentially an unmanageable number of possible combinations, so that each person is genetically and environmentally unique, and the complex combinations of future individuals are not predictable.

Risk assessment is essentially based on replicability, which in a sense is why statistical testing can be used (on which these sorts of results heavily rely).  However, because these risk factor combinations are each unique they're not replicable.  At best, as some advocate, the individual effects are additive so that if we just measure each in some individual add up each factor's effect, and predict the person's obesity (if the effects are not additive, this won't work).  We can probably predict, if perhaps not control, at least some of the major risk factors (people will still down pizzas or fried chicken while sitting in front of a TV). But even the known genetic factors in total only account for a small percentage of the trait's variance (the authors' Table 2), though the paper cites more optimistic authors.

The result of these indisputable facts is that as long as our eyes are focused, for research strategic reasons or lack of better ideas, on the litter of countless minor factors, even those we can identify, we have a fat chance of really addressing the problem this way.

If you pick any of the arrows (links) in this diagram, you can ask how strong or necessary that link is, how much it may vary among samples or depend on the European nature of the data used here, or to what extent even its identification could be a sampling or statistical artifact.  Links like 'smoking' or 'medication', not to mention specific genes, even if they're wholly correct, surely have quantitative effects that vary among people even within the sample, and the effect sizes probably often have very large variance. Many exposures are notoriously inaccurately reported or measured, or change in unmeasured ways.   Some are quite vague, like 'lifestyle', 'eating behavior', and many others--both hard to define and hard to assess with knowable precision, much less predictability.  Whether their various many effects are additive or have more complex interaction is another issue, and the connectivity diagram may be tentative in many places.  Maybe--probably?--in such traits simple behavioral changes would over-ride most of these behavioral factors, leaving those persons for whom obesity really is due to their genotype, which would then be amenable to gene-focused approaches.

If this is a friable diagram, that is, if the items, strengths, connections and so on are highly changeable, even if through no fault of the authors whatever, we can ask when and where and how this complex map is actually useful, no matter how carefully it was assembled.  Indeed, even if this is a rigidly accurate diagram for the samples used, how applicable is it to other samples or to the future?Or how useful is it in predicting not just group patterns, but individual risk?

Our personal view is that the rather ritual plea for more and more and bigger and bigger statistical association studies is misplaced, and, in truth, a way of maintaining funding and the status quo, something we've written much about--the sociopolitical economics of science today.  With obesity rising at a continuing rate and about a third of the US population recently reported as obese, we know that the future health care costs for the consequences will dwarf even the mega-scale genome mapping on which so much is currently being spent, if not largely wasted.  We know how to prevent much or most obesity in behavioral terms, and we think it is entirely fair to ask why we still pour resources into genetic mapping of this particular problem.

There are many papers on other complex traits that might seem to be simple like stature and blood pressure, not to mention more mysterious ones like schizophrenia or intelligence, in which hundreds of genomewide sites are implicated, strewn across the genome.  Different studies find different sites, and in most cases most of the heritability is not accounted for, meaning that many more sites are at work (and this doesn't include environmental effects).  In many instances, even the trait's definition itself may be comparably vague, or may change over time.  This is a landscape 'shape' in which every detail is different, within and between traits, but is found in common with complex traits.  That in itself is a tipoff that there is something consistent about these landscapes but we've not yet really awakened to it or learned how to approach it.

Rather than being skeptical about these Ghosh and Bouchard's' careful analysis or their underlying findings, I think we should accept their general nature, even if the details in any given study or analysis may not individually be so rigid and replicable, and ask: OK, this is the landscape--what do we do now?

Is there a different way to think about biological causation?  If not, what is the use or point of this kind of complexity enumeration, in which every person is different and the risks for the future may not be those estimated from past data to produce figures like the one above?  The rapid change in prevalence shows how unreliable these factors must be, at prediction--they are retrospective of the particular patterns of the study subjects.  Since we cannot predict the strengths or even presence of these or other new factors, what should we do?  How can we rethink the problem?

These are the harder question, much harder than analyzing the data; but they are in our view the real scientific questions that need to be asked.

On shouting, "SEED MY BABY WITH MY VAGINAL MICROBES!"

Co-authored by Emily Pereira, Anthropology major, University of Rhode Island

When I was pregnant, the human microbiome was hot. And news about the microbiomes of newborns was even hotter, at least to my eyes and ears because I was on the verge of having one.

This was in 2014. Studies were starting to find that babies born via c-section have different microbiomes than babies born vaginally. These findings were being interpretively linked to health problems down the road. 

Here’s a write-up of one study of a few 4-month-olds that I came across while pregnant: “Infant gut microbiota influenced by cesarean section and breastfeeding practices; may impact long-term health”

And today studies continue to pop-up that find differences in baby microbial composition and then suggest those differences may be linked to future health problems. For example, here’s a recent one from 2016 in JAMA Pediatrics: 

“CONCLUSIONS AND RELEVANCE The infant intestinal microbiome at approximately 6 weeks of age is significantly associated with both delivery mode and feeding method, and the supplementation of breast milk feeding with formula is associated with a microbiome composition that resembles that of infants who are exclusively formula fed. These results may inform feeding choices and shed light on the mechanisms behind the lifelong health consequences of delivery and infant feeding modalities.”

These discoveries about c-sections seem important because microbes are now famous for being linked to all kinds of health troubles. 

According to the American Microbiome Institute... 

“studies are finding that our bacteria (or lack thereof) can be linked to or associated with: obesity, malnutrition, heart disease, diabetes, celiac disease, eczema, asthma, multiple sclerosis, colitis, some cancers, and even autism.”

And of course many of those same things have been epidemiologically traced back to birth by c-section. Here’sa report on one study, “published in the British Medical Journal, [that] found that newborns delivered by C-section are more likely to develop obesity, asthma, and type 1 diabetes when they get older.”

Anotherfound that, “people born by C-section, more often suffer from chronic disorders such as asthma, rheumatism, allergies, bowel disorders, and leukaemia than people born naturally."

One can’t help but assume it’s all connected. If microbes are to blame for this list of problems and if c-sections are too and if c-sections are causing babies to have different microbiomes, then the following conclusion seems like a no-brainer: we need to be wiping c-sected babies with their mother’s vaginal juices.

So although I did basically nothing to prepare for a c-section (d’oh!), I imagined that if my childbirth came to surgery, that it would be really easy to avoid the risks to my baby's health by simply wiping him down with something soaked in my lady fluids.

I had even caught wind of a trial of this procedure, written-up somewhere, and so I mentioned it to my OB at a prenatal visit. She said she’d heard of it and that there was a term for it but the term escaped her. The idea excited her, but it wasn’t even remotely close to being part of regular clinical practice yet. Remember, this was summer 2014. Sensing it was too soon and out of reach, I changed the subject of conversation. Yet, I continued to believe that someone would just help me out with the whole vaginal swabbing thing if need be. It seemed simple enough. No biggie.

At the time, I didn’t Google around for tips or instructions so I don’t know what the Internet was offering up to would-be mothers/vaginal-microbe believers like me. But today it’s quite easy to find encouragement to D-I-Y transform your kid’s c-sected microbiome into a naturally-born one.

Here, let Mama Seeds explain:

“In the event of a c-section, be proactive. Mamas, we know this recommendation is not without its “icky-factor," but WOW it makes perfect sense when you think about it, and some believe it will be a standard recommendation in the future. Here goes: if your baby is born via c-section, consider taking a swab of your vaginal secretions and rubbing it on your baby’s skin and in her/his mouth. I know, ick. But when babies traverse the birth canal, they are coated in and swallowing those secretions/bacteria in a health-promoting way, so all you’re doing is mimicking that exposure. Don’t be afraid to ask your midwife or OB to help you collect the vaginal swabs—or do it yourself, if you’re comfortable. You have all the available evidence on your side.” - Michelle Bennett, MD is a full-time pediatrician, a Fellow of the American Academy of Pediatrics, a mother of two, and a founder of Mama Seeds.

Like I said, I didn’t have Mama Seeds. But I didn’t need Mama Seeds. While I was being wheeled into emergency cesarean surgery, I still shouted “SEED MY BABY WITH MY VAGINAL MICROBES!”

The reaction from the hospital staff? There was no reaction and, surprise surprise, there was no artificial seeding of my baby’s microbiome.

And that’s good. That’s how it should have gone down because my request was not based on scientific thinking. I hope you'll forgive me. I was pregnant. I wasn’t myself.

Slowly I’m becoming myself again, though, and thanks to a keen student, Emma Pereira, this post’s co-author, I’ve learned quite a bit about the science behind whether I should have seeded my newborn with my vaginal microbes. And the answer to anyone who’s wondering is a resounding NO. At least for now.

Here’s why.

1.   We don’t know if it’s necessary. Despite the increasing numbers of studies, no one to our knowledge has looked longitudinally at the microbiomes of humans born via c-section to find out if the changes detected (in very small samples) early on in these studies actually last, let alone if they can be causally linked to differences in health. It seems like the money and the technology is there to identify (via genetic sequencing) myriad microbial species, but the time and energy just isn’t there to do much else. So, although there is a growing literature, the dots aren’t connected yet. A graphic may help explain what we've learned: 

2.  You could actually harm your baby. Because there is currently no known good to come of seeding one’s c-sected baby with one’s vaginal microbes, there can only be bad. Yes, authors of this studypublished recently in Nature Medicine took a bunch of gauze that had been sitting in the mother’s vagina for an hour and swabbed 4 babies for a duration of about 15 seconds right after their birth by c-section and then found a significant difference in their microbiome at 30 days-old compared to babies who weren’t treated.  The microbiome wasn’t identical to vaginally born babies, but at least it wasn’t identical to those poor c-sected controls who didn’t get swabbed, right? Well, maybe wrong. First, please revisit number 1. And, second, maybe causing a baby to have a c-sected microbiome is not worse than seeding a baby with genital herpes, which is a very real possibility in practice, outside of these early, highly controlled pilot studies. As reported in Should C-section babies get wiped down with vagina microbes?, “the procedure could unknowingly expose newborns to dangerous bugs, pathogens that babies born by C-section usually avoid. Group B streptococcus, which is carried by about 30 percent of women, can trigger meningitis and fatal septicemia... Herpes simplex virus can lead to death and disability in newborns. And chlamydia and gonorrhea can cause severe eye infections.”

So, again, as of right now, there is no reason to seed one's c-sected baby with one's vaginal microbes. And there are very good reasons not to! 

We think that the temptation to blame the rise of numerous complex health problems to something as simple (and easily knowable) as the way we’re born is similar to the temptation to reduce these very same complexities to what’s coded in the genome. For some people, maybe even many, it may turn out to be this simple! But we’re far from knowing whether that’s true. 

Spare your baby from meddling with his microbes until the evidence is there. 

Obesity and diabetes: Actual epigenetics or just IVF?

This press release that appeared in my newsfeed titled "You are what your parents ate!" caught my eye because I'm a new mom of a new human and also because I study and teach human evolution.

So I clicked on it.

And after that title primed me to think about me!, the photo further encouraged my assumption that this is really all about humans.

"You are what your parents ate!"

But it's about mice. Yes, evolution, I know, I know. We share common ancestry with mice which is why they can be good experimental models for understanding our own biology. But we have been evolving separately from mice for a combined total of over 100 million years. Evolution means we're similar, yes, but evolution also means we're different.

Bah. It's still fascinating, mice or men, womice or women! So I kept reading and learned how new mice made with IVF--that is, made of eggs and sperm from lab-induced obese and diabetic mouse parents, but born of healthy moms--inherited the metabolic troubles of their biological parents. And by inherited, we're not talking genetically, because these phenotypes are lab-induced. We're talking epigenetically. So the eggs and sperm did it, but not the genomes they carry!

This isn't so surprising if you've been following the burgeoning field of epigenetics, but it's hard to look away. This fits with how we see secular increases in human obesity and adult-onset diabetes--it can't be genomic evolution, it must be epigenetic evolution, whatever that means!

As the press release says...

"From the perspective of basic research, this study is so important because it proves for the first time that an acquired metabolic disorder can be passed on epigenetically to the offspring via oocytes and sperm- similar to the ideas of Lamarck and Darwin," said Professor ...

Whole new ways of thinking are so exciting.

Except when you remember a two-year-old piece by Bethany Brookshire (because you use it to teach a course on sex and reproduction) which explained something that suggests we may have a major experimental problem with the study above.

In IVF, the sperm gets isolated (or "washed") from the semen.

You know what happens, to mice in particular, when there's no semen? Obesity and other symptoms of metabolic syndrome! There are placental differences too. This was published in PNAS.

"Offspring of male mice without seminal fluid had bigger placentas (top right) and increased body fat (bottom right) compared with offspring of normal male mice (left images)" from The fluid part of semen plays a seminal role by Bethany Brookshire.

So I went back to look at the original paper that the press release with the donut lady was about. I wanted to see if they are aware of this potential problem with IVF and whether it explains their findings, rather than the trendy concept of epigenetics...

So even though they titled it "Epigenetic germline inheritance of diet-induced obesity and insulin resistance," I wanted to see if they at least accounted for this trouble with semen, like how it's probably important, how its absence may bring about the same phenotypes they're tracking, and how IVF doesn't use semen.

But I don't have access to Nature Genetics.

Who has access to Nature Genetics, can check out the paper, and wants to write the ending of this blog post?

Step right up! Post your work in the comments (or email me holly_dunsworth@uri.edu, and please include a pdf of the paper so I can see too) and I'll paste it right here.

Update 12:19 pm
Two very good comments below are helpful. Please read those.

I'll add that I now have the pdf of the paper (but not the Supplemental portion where all the methods live and other important information resides). This quote from the second paragraph implies they do not agree with the finding of (or have forgotten about) the phenotypic variation apparently caused by sperm washed of their seminal fluid:

"The use of IVF enabled us to ensure that any inherited phenotype was exclusively transmitted via gametes."

As the second commenter (Anonymous) pointed out below, there does not appear to be a comparison of development or behavior between any of the IVF mice and mice made by mouse sex. So there is no way to tell whether their IVF mice exhibit the same metabolic changes that the semen/semenless study found. Therefore, it is neither possible to work the semen issue into the explanation nor to rule out its effects. Seems like a missed opportunity.

Completely unrelated and inescapable... I'm a little curious about how the authors decided to visualize their data like this: