Obesity is defined completely arbitrarily as a body mass index of 30 or higher (175 pounds for an average height woman). Now body mass follows more or less a normal distribution, whiich means if the the mean body weight is in the mid to high 20s, which it has been for many decades now, then tens of millions of people will have BMIs just below and just above the magic 30 line. So if the average weight of the population goes up by ten pounds, tens of millions of people who were just under the line will now be just over it.

This might be meaningful if there was any evidence that people who have BMIs in the low 30s have different average health than people with BMIs in the high 20s, but they don’t. At all. So the “obesity epidemic” is 100% a product of tens of millions of people having their BMIs creep over an arbitrary line. It’s exactly as sensible as declaring that people who are 5’11 are healthy but people who are 6’1″ are sick.

Adding to the absurdity of all this, people with BMIs in the mid to high 20s actually have the best overall health and longest life expectancy — ,more so than those in the so-called “normal” BMI range.

The notion that the 30 BMI line is arbitrary is just nonsense.

In fact, huge prospective studies have demonstrated that individuals with greater than 30 BMI do have greater all-cause mortality than individuals who are simply overweight (BMI 25-29). Here is the money-figure. The Prospective Studies Collaboration compiled 57 studies with nearly 900,000 participants (a mammoth study!) to look at the relationship between different BMIs and overall mortality. The study confirmed the inverted U effect long argued for by scientists and physicians that having a BMI either below or above the normal range confers greater risk of death. Here is Figure 2 of that paper:

You can see that above BMI 30, mortality increases above an average mortality maintained for BMI 20-29 — a range that includes both individuals defined as of “normal” weight and overweight.

What specifically are the causes of the observed all-cause increase in mortality? The PCS identified several. HR stands for hazard ratio which is a measure of the risk relative to the general population.

• Heart attack (HR 1.39)
• Stroke (HR 1.39)
• Diabetes (HR 2.16)
• Kidney disease (HR 1.59)
• Cancer (HR 1.10) including liver, kidney, breast, endometrial, prostate, and colon
• Lung disease (HR 1.20)

Now, it is possible that Campos is not aware of this data. The study was published in 2009, and his book was released in 2004. It is possible that he has been living in a cave or refuses to acknowledge this evidence. But this data is as definitive as you can possibly get: becoming obese as defined by having a BMI >30 is bad for your health.

it has been a source of considerable controversy in the medical community whether BMI is the best indicator of how we should measure whether someone is at risk or not.

The point is that when neurologists study the abnormal, it is typically on the non-functional end of the spectrum rather than the highly functional. This is why I found a paper in the journal Neurocase quite interesting. The authors, Raz et al., placed a superior mnemonist — an individual who can memorize long lists of arbitrary items — into an fMRI scanner to try and get an idea how they did it.

Raz et al. imaged a single participant known throughout the study as “PI.” PI is remarkable in his ability to recite the constant pi to around 2^16 decimal places with very few errors. (I have no idea whether the selection of the pseudonym is because P and I are actually this guy’s initials or it is some sort of pun.) The authors subjected participant to a psychological battery and two scanning experiments in the fMRI to try and see how this individual was so gifted at memory.

PI claims to be able to remember so many digits using a variant of a memory strategy called the Method of Loci (MOL). MOL is a very old method of memorizing material — known even to the ancient Greeks and Romans — where the user attempts to associate each item in memory with a spatial location or a visual scene. The user then mentally “walks” between each location and visual scene and uses this to help recall the associated items in memory. Basically, if you were trying to memorize all the phone numbers of all the people in your building, you might associate each phone number with a different turn on your drive to work. By visualizing the turn, you could help retrieve each phone number more easily. This MOL technique is demonstrably effective at improving memory performance, and many superior mnemonists claim to use this technique.

In interviews with PI, the subject claims to use a variation on the classical MOL technique. Rather than visualizing a mental journey, PI claims to try and associate each item in memory with an emotionally-laden image — sometimes funny, sometimes horrible. In this way, the subject can “co-opt” the emotional salience of the visual image to make the memory item more memorable. (More on the reliable of the subject’s reports and the relevance of MOL on the findings in a second.)

When the authors tested PI on a variety of memory tests — testing memory for different types of material — they found that PI’s abilities were around average with one exception. This finding is consistent with what we know about how memory is organized in the brain. Memory is not monolithic. Rather, it is organized into several parallel memory systems that sometimes act cooperatively and sometimes act antagonistically with one another. Each system is responsible for different classes of information. (For more information, I would read this.) Thus, it is reasonable that PI would be particularly good — probably through training — at certain types of memory, but not at memory as a global concept.

What was the type of memory that PI was good at? Neuroscientists refer to working memory as the type of memory that is necessary to keep information online over short intervals. This is the type of memory you use when you are trying to remember a phone number written on a piece of paper away from the phone before dialing. Measurements of PI’s working memory were off the chart (99th percentile). This is consistent with other superior mnemonists, and we think that some element of rehearsal — saying the item over and over again to yourself — within working memory may have to do with their excellent performance.

The authors then placed PI into a scanner and asked him to perform two tasks. In the first, they asked him to recite pi. This experiment asked: what areas of his brain are activated when he is retrieving this long number string? In the second, they asked him to memorize a list of 100 arbitrary (and novel for him) numbers. This experiment asked: what areas of his brain are activated when he is encoding new information of this type? Note that both of these two experiments are necessary. Memory is a multi-part process. For something to be remembered, it must first be encoded in the brain — analogous to writing something down. Then, after an interval, this encoded information must be successfully recalled — or retrieved.

When the authors asked PI to recite pi, they found increased activation in areas of the frontal cortex including the medial frontal gyrus and dorsolateral prefrontal cortex. This is interesting in relation to PI’s gifts at working memory. According to some current theories of how working memory and intelligence work (most notably P-FIT), frontal regions participate with regions in the back of the brain in the parietal cortex to form what is called a fronto-parietal loop. Information circulates between these two regions allowing it to stay online in the brain and continue to occupy working memory. We also believe that activity in the fronto-parietal loop may have a function in allocating attention.

What is interesting about this finding that this activation differs from structures that we traditionally associate with memory — structures like the hippocampus. Superior mnemonists appear to co-opt other memory systems — such as working memory — to increase performance.

Similarly, when the authors asked PI to encode a new random string of 100 numbers (which he later recited flawlessly to confirm that he had retained them), he activated parts of his frontal cortex as well as various association cortices (parts of the brain involved in associating different classes of stimuli). Activation in assocation cortices are consistent with PI’s reports of using the variant MOL technique of associating emotionally-laden images with the numbers. Again, the activity in frontal regions may be the result of co-opting working memory to assist in encoding.

All of these findings provide an interesting look into how a superior mnemonist’s brain works, but there are a couple of caveats.

First, this is a study with only a single subject, and we should be at least mildly skeptical of it on that basis. While the findings presented here conform broadly with those of other superior mnemonists, we are not dealing with a large enough data set to make definitive conclusions. Further, the authors acknowledge that we may not even be imaging this subject at the correct time. Clearly, PI has a lot of training applying the variant MOL technique. What would be really interesting is to follow a naive individual applying this technique to see how activation changes over time as the new technique is applied. Studies of this nature have been performed, but it would be interesting to watch subjects reach even higher levels of performance.

Further, we must always be skeptical of first person reports in science. I have no doubt that PI is a honorable person and provided accurate information about his thought processes to the best of his ability. But our insight into our own mental processes is always limited. One aspect of this that I found interesting is PI’s claim about the variant MOL procedure. PI claims that the variant MOL includes associating the digits with emotionally-laden imagery. Emotionally-laden stimuli in the brain is processed in part by a brain region called the amygdala, and individuals exposed to these stimuli often show activation in this region. This type of activation was not observed in either retrieval or encoding in this case. Whether this is because self-generated emotional imagery is processed differently or whether PI’s insight into the nature of his strategy is imperfect, it is very difficult to tell. I am just pointing out that we need to be skeptical of how people describe their memory experiences.

It may be that one reason that such little research goes on about superior human functioning is because exemplars are so rare. It is difficult to corral enough superior subjects together, and each subject may be unique in their superior function, such that it makes comparisons difficult to make.

Still I think this is a very interesting paper that offers some insight in how the human brain can be co-opt to perform amazing feats of memory.

The authors asked: how do a particular genotype of the serotonin gene and stressful life events interact to influence depression risk? Does having a certain genotype PLUS several stressful life events increase your risk?

Their results were stunning primarily because they so clearly illustrated the concept of a gene-environment interaction: the idea that neither your genes nor the environment is sufficient to cause depression; rather, depression results from a confluence of both factors.

Here is an example of their data (from Figure 2 of the paper):

The results show risk of depression (in percent, from ages 18 to 26) as related to whether the participant was mistreated as a child (from the ages of 3 to 11). The participants are broken up according to whether they have two of the short forms of the serotonin transporter gene (s/s), are heterozygotes for the long form for serotonin transporter (s/l), or have two copies of the long form (l/l).

In the absence of childhood mistreatment, there is no difference between the three genetic groups with respect to depression risk. Likewise, if you possess two copies of the long form (l/l) childhood mistreatment does not increase your risk. However, if you possess two copies of the short form (s/s) AND you were subjected to childhood mistreatment, your risk of depression doubles.

This and other data was used to argue that what determines whether an individual will get depression is a gene-environment interaction. Genes confer risk for depression, but only in the presence of stressful life events does a particular genetic makeup manifest.

I want to make something clear through all of this: Caspi et al. is an extremely well done paper. Up until reading this meta-analysis, I considered it the benchmark for these kinds of studies. Even realizing that the findings may have been a false positive, I still respect it. So I don’t want to suggest that I am trashing this work.

After Caspi et al., there emerged many other papers that attempted to find gene-environment interactions in the similar way. Primarily this was because Caspi et al. addressed a problem that had been quite prevalent in behavioral genetics: small and non-reproducible effects.

A common problem in studies attempting to relate genetics with a particular behavior is that a particular genotype might only confer a very small risk. Also, behavioral genetics studies are notoriously difficult to replicate. Say you find a significant relationship between gene A and depression. Then you go and try and replicate that finding in another population. A lot of the time, you will find that it is no longer significant in the new population. Sometimes that is because it was a weak correlation, and you don’t have enough people in the study. Sometimes it is because in the new population, the genetic background for their other genes masks the effect of gene A on depression. (This is called an epistatic interaction.)

The point is that behavioral genetics studies were dealing with a problem of reproducibility and small effect sizes. Caspi et al. demonstrated a way to identify more significant effects. If you can show that a subset of your population with a particular environmental history, there is an even greater association between the disease and their genotype, you can argue that the interaction between the two potentiated the effect of the gene. It also explains why there was so much trouble finding a significant gene-disease correlations: there were aspects of the population that you were missing.

If you think about it, the concept of a gene-environment also makes a great deal of sense. Let’s set aside the fact that biological systems show these all the time for physical traits. (It is a core principle to our understanding of evolution.) An individuals behavior is the consequence of many, many genes and many, many environmental interactions. To say that a single gene could result in a behavior, we would have to assume that it was relatively robust to a variety of environments that the individual might experience — that regardless of environment, the person would still show the behavior. But this argument belies the extreme variability that is present in human behavior. Even among identical twins there is a great deal of variation in personal preference, environment, and hence the risk for disease.

My point is that you can’t take too much of an issue with Caspi et al. for arguing for the existence of gene-environment interactions in producing behavioral outcomes because they make too much sense in light of what we already know about biology.

The problem, unfortunately, came in trying to verify the results of their work.

Risch and colleagues performed a meta-analysis using the original data from 14 studies that had attempted to replicate the findings of Caspi et al. These studies also looked at the roles of stressful life events, genotype at the serotonin transporter gene, and the resulting depression risk. In contrast to the earlier work, the authors found no relationship between serotonin transporter genotypes or the interaction and depression risk. The only significant predictor they found was the number of stressful life events:

In the meta-analysis of published data, the number of stressful life events was significantly associated with depression (OR, 1.41; 95% CI,1.25-1.57). No association was found between 5-HTTLPR genotype and depression in any of the individual studies nor in the weighted average (OR, 1.05; 95% CI, 0.98-1.13) and no interaction effect between genotype and stressful life events on depression was observed (OR, 1.01; 95% CI, 0.94-1.10). Comparable results were found in the sex-specific meta-analysis of individual-level data.

Note that this meta-analysis was performed on about 14 thousand participants from other studies. Hence it has a much greater statistical power than the previous study.

What do we make of this conclusion? How is it possible that such a well-constructed study — that had become a model for a variety of other studies — ended up being wrong?

Well, first of all, I should note that the lead author from the original study does not necessarily agree with the findings of this meta-analysis. From the NYTimes coverage:

Others said the new analysis was unjustifiably dismissive. “What is needed is not less research into gene-environment interaction,” Avshalom Caspi, a neuroscientist at Duke University and lead author of the original paper, wrote in an e-mail message, “but more research of better quality.”

I would say a couple of things:

1. 1) No one in the coverage I have read of this story — including the authors of the meta-analysis — is disputing that gene-environment interactions exist for behavioral phenotypes or that these studies NEED to continue being done. In fact, most of the coverage of this study has shown an very interesting doublethink, denying the accuracy of the original Caspi study findings while singing the praises of its theoretical basis.
2. 2) This is exactly the type of back and forth that we should expect from behavioral genetics studies. We should have a great deal of reticence when we read about studies like this in the news.

Behavior is affected by many, many genes. No one ever believed that just one gene was going to explain all of depression or any other mental illness. This is primarily why the effect sizes in these studies are so small: because behavior is so polygenic. Furthermore, when you are dealing with small effect sizes in complex systems, you have to prepare yourself for the possibility of sampling error. Caspi et al. was not a small study, but it also should surprise us that an analysis of a larger population yielded different results.

The point, I guess, is that we can simultaneously dispute the relevance of this particular gene, the serotonin transporter, in affecting depression risk while still believing in the concept of a gene-environment interaction.

We just have to be very, very careful when we assert with certainly the association of a particular gene. Results that look too good to be true often are.

Hat-tip: NYTimes

The four types of cells that compose brain tissue exclusively are neurons and three types of glia: astrocytes, oligodendrocytes or Schwann cells (depending on whether you are in the peripheral or central nervous system), and microglia. The word glia comes from the Greek word for glue, which tells you something about how important the people who named these things though they were.

Now if I might engage in a brief rant here, most textbooks I read when I was in college viewed the neurons as the first among equals from the group of four. Neurons were the Jaggers and the rest were just roadies. The assumption among much neuroscience research coming to the turn of the last century was that glial cells functioned primarily to provide physical or metabolic support, to respond to injury, and to direct development of the otherwise more important neurons. The assumption was that they were definitely not involved in information processing in the brain. However, while the generalization that neurons are the primary information processors in the brain is probably a fair one, more and more recent evidence points to a function for glia in information processing. In my summary, I am going to try to give you a taste of that evidence, so that you won’t wander through life thinking that glia are pathetic losers like I did for the first decade or so.

Neurons: The defining characteristic of

(Side note: the above clip is from Dr. Horrible’s Sing-a-long blog which is both SWEET and now available in its entirety on Hulu.)

Seriously, I would build my own death robot, but I doubt the New York authorities would be as understanding.

“But that is only if you really want to trip balls.” Priceless.

Anyway, South Park is correct that the active ingredient intrepid trippers would like to take is called dextramethorphan (DXM).

Different cough medicines have different types of formulations. Robitussin, for instance, contains a cough-suppressant compound called guaifenesin. This is mixed with other drugs such as phenylephrine/pseudoephedrine (both of which lower mucus production via action on alpha 1 adrenergic receptors), acetaminophen (Tylenol, which lowers fevers and treats pain), and DXM.

At high doses (about 200-400 mg for an average adult), DXM causes euphoria and hallucinations. Inappropriate laughing, agitation, and a zombie-like gait are also common. To quote MC Chris from “The Tussin” describing the high:

Frankly, the feeling’s f$%&ing fantastic
I’m tripping like Jesus in the desert when he fasted
Like it’s the night before we all get drafted
Like we’re rowin through some rapids with Kevin Bacon, whitewater raftin
(“Like you’re at Epcot Center on acid?”) Exactly

At even higher doses (300 mg to 600 mg in an adult), DXM can cause a dissociative “out of body” experience. You feel like you are watching yourself from outside your body. Higher doses than that…well…that is when bad things start to happen, but we’ll get to that.

The reason for the high is DXM’s action on a variety of receptors in the brain. The action for which the drug was intended — preventing coughing — derives from it binding to opioid receptors in the brainstem. (The molecule itself, shown to the right, is similar to codeine.)

However, this is kind of a messy drug — meaning that at higher doses it can bind to all sorts of different receptors. One important one for the high is the NMDA glutamate receptor — a receptor that is very important for learning and memory. DXM blocks this receptor, and it is that action that causes the “out of body” experience. Interestingly, two other drugs that block the NMDA receptor are ketamine and phencyclidine (PCP) both of which have pronounced dissociative effects.

I was curious about this. I probed the literature, and I couldn’t find any really good reasons why NMDA antagonists have this effect, but all of them do. Actually the whole effect puzzles me. I mean there are plenty of drugs out there that would inhibit various mechanisms of memory. Alcohol is one — as anyone who has woken up dressed as Santa in their bathtub would know. (Certainly has never, ever happened to me, though…) But alcohol acts on different receptors in the brain. Actually I am curious to hear people speculate as to why this perceptual change is only associated with these drugs. Any ideas?

Getting back to DXM, that is why people take it in large doses usually with other drugs: for the hallucinogenic effect. This effect is created by action on NMDA receptors.

However, I would not be being a good future doctor if I did not add a substantial note of caution about DXM abuse. It is not that I believe you will listen to me. (Current evidence indicates about a million adolescents abuse DXM every year.) It is just that it isn’t a great idea.

Here’s why:

1. 1) It’s a messy drug. I told you about the opioid and NMDA effects, but the drug also has some other effects. It can inhibit norepinephrine reuptake which can result in a racing heart, high blood pressure and excessive sweating. And that is assuming your heart doesn’t stop. Take enough of it, and you are running into similar toxic side-effects to ecstacy.
2. 2) It is nearly always mixed with something you shouldn’t be taking a lot of either. Most DXM preparations are mixed with things like acetaminophen. At high doses Tylenol causes liver failure (by creating a toxic by-product in the liver). This is why a patients with suspected DXM overdose will there acetaminophen level checked in the ER. So if you would like to continue using your liver — and trust me you do — taking gobs of tylenol because you want to get high on DXM is not a great plan.
3. 3) Going all out and mixing this drug with other drugs can be disastrous. While it is commonly mixed with alcohol, which causes respiratory suppression (not good when you are passed out), it is bad to mix it with anything. One thing DXM does is suppress reuptake of serotonin, so if it is mixed with some types of antidepressants it can result in a life-threatening complication called serotonin syndrome. Visualize it raising your temperature until your brain boils. Always a fun way to spend the evening.

So just a suggestion: leave the Tussin to pop culture. It may inspired some funny stuff, but unless you enjoy trips to the ER I would stay away from the stuff.

In either case, I am looking forward to talking about some fun neuroscience with all of you. Posting will be kind of sporadic because work is rough, but hopefully we will have a chance to really delve into neuroscience and medicine.

For those of you who don’t know, LTP stands for long-term potentiation. It is an important molecular process of memory formation that I will hopefully have a lot to say about in the next few weeks. In the meantime, I will put up my first post in a second.

Yours,
NotoriousLTP