In response to a couple of questions about the implications of long-term caffeine intake, I’d thought I’d throw out a couple of findings.
I recently wrote about a study that localized the receptors underlying the arousing effects of caffeine. (A2a receptors, in cells located in the shell of the nucleus accumbens). It’s only natural then to wonder what effect chronic caffeine intake might have on these receptors (and elsehwere in the brain).
That study didn’t look at chronic effects. But back in 1996, Glass et al. found that chronic caffeine consumption increased the global expression of adenosine receptors in the brain , suggesting that this increase was to compensate for caffeine’s antagonistic effects. Withdrawal from caffeine is, at least in part, likley related to a hypersensitivity to adenosine due to this increased number of adenosine receptors. The headaches that accompany caffeine withdrawal are thought to be related to the fact that adenosine is a known vasodilator and the increased receptor density + withdrawal of caffeine from the system leads to a significant drop in blood pressure.
A couple other interesting notes in regards to long-term effects of caffeine:
The Good News
Some case control studies have shown lower incidents of Parkinson’s disease in coffee drinkers vs. non-coffee drinkers, although this finding has not always been replicated. The correlation, when it has been found, was strongest in heavy consumers. (This is certainly a finding I would love to be true!) More evidence in support of these findings come from mouse studies showing that physiological doses of caffeine were able to reduce one of the major toxic factors associated with Parkinsons (MPTP-induced dopaminergic toxicity). It’s been suggested that caffeine may offer neuroprotective effects in the brain via action occurring at A2a receptors, which are the same receptors responsible for the arousing effect of caffeine (and which are also co-localized with dopamine D2 receptors). Additional support for this idea comes from studies in which mice who had their A2a receptors knocked out showed reduced MPTP-induced injury compared to wild types. How this all might be happening on a mechanistic level, however, is not well known.
The less good (but not totally bad) news:
Unfortunately, it seems that acute doses of caffeine often cause a rise in systolic and diastolic blood pressure, increase in catecholamine release and vasodilation (wideneing of blood vessels). However, some studies have shown this effect occurs primarily in non-regular consumers of caffeine. Many studies have shown either slight increases or no difference in blood pressure for regular users of caffeine. In fact, several large scale studies have found that heavy, regular use is protective against heart disease. (yes!) The findings are quite contradictory.
So what to make of all this? Is heavy coffee drinking bad or good for you?
There’s no simple answer to that question. But the paradoxical findings suggest that different individuals have varying levels of risk. And it’s likely that genetics play a significant role.
If one thinks of coffee as a drug, then the notion that the benefits of heavy coffee consumption might outweigh the risks seems very counterintuitive. That is, due to the brain’s propensity to maintain homeostasis, drug taking, either legal or illegal, usually involves some significant cost/benefit analysis, a trade off between the good (the high, buzz, relief from psychic or physical pain) and the bad (side effects, withdrawal, expense, long-term effects on health). Yet, the evidence on long-term caffeine intake seems to put it in a distinctive class of its own.
I once chatted with an extremely energetic and sprightly 93-year old Italian man from the old country, curious to know the the secret to his longevity and good health. “Five espressos a day,” he said. Anecdotes aren’t very informative in an empirical sense, of course, but, nonetheless, the old codger may have been on to something.*
* In addition to the espressos, he’d also claimed that he smoked a pack a day of American Winstons and was convinced that brand loyalty was one of the other secrets to his good health.
Have you ever wondered why, and exactly where in the brain, coffee (or any caffeinated product, for that matter) is able to exert its arousing effects? Well, wonder no longer, because an international team of researchers from Japan, China and the US, have located the primary neurons upon which caffeine works its magic (Lazarus 2011).
It was previously known that caffeine wakes you up through inhibiting activity at adenosine A2a receptors (adenosine is an inhibitory neuromodulator involved in regulating the sleep-wake cycle). However, it was not known exactly where in the brain the receptors that exerted this effect are located.
How did they do it?
The researchers utilized a method whereby the gene that codes for A2a receptors (A2aRs) is marked such that they can be deleted, but only in a specific regions of the brain. Using a rat model, the team utilized these gene deletion strategies and found that when they knocked out A2aRs in the shell of the nucleus accumbens, rats no longer experienced the arousing effects of caffeine.
How does this work?
Adenosine activates A2a receptors in the nucleus accumbens shell, activation of which receptors inhibit the arousal system. That is, the more adenosine activation there is, the sleepier an organism becomes. Caffeine, which binds to these same receptors and blocks adenosine from exerting its activity there, essentially disinhibits the arousal system, promoting wakefulness. (Amazingly, based on similarities between the brains of mice and men, the area of the human brain in which caffeine acts to counteract fatigue is approximately the size of a pea.)
What does this mean in practical terms? (or, in other words, why should we find this so cool?)
Well, for one, it gives us a more specific mechanistic explanation for the arousing effects of caffeine. It says that in order for caffeine to work, it not only has to be effective as an A2aR antagonist, but that excitatory A2aRs on nucleus accumbens shell neurons must be tonically activated by endogenous adenosine. This is especially important in consideration of individual differences in the subjective effects of caffeine.
What if A2aRs are more densely packed in the shell of your nucleus accumbens than in mine? Might you be more sensitive to the effects of caffeine than me? That certainly seems likely. And the reason that one person might over or underexpress these receptors vs. another seems to be related to variation in the gene that produces those receptors (the gene knocked out in the rat study described above). In fact, we’ve already have evidence that this is the case. Past studies have shown genetic variations in genes coding for A2aRs were associated with greater sensitivity to caffeine and sleep impairment (Retey 2007), and greater anxiety after caffeine (Childs 2008). This study refines the existing model and should inspire, and lead to more accurate interpretation of, future genetics studies.*
*Other significant genes that underly individual differences in the subjective effects of caffeine include CYP1A2, or cytochrome enzyme P-450 1A2, which is associated with caffeine metabolism, and those coding for dopamine D2 receptors.
Lazarus M, Shen HY, Cherasse Y, Qu WM, Huang ZL, Bass CE, Winsky-Sommerer R, Semba K, Fredholm BB, Boison D, Hayaishi O, Urade Y, & Chen JF (2011). Arousal Effect of Caffeine Depends on Adenosine A2A Receptors in the Shell of the Nucleus Accumbens. The Journal of neuroscience : the official journal of the Society for Neuroscience, 31 (27), 10067-10075 PMID: 21734299
Childs E, Hohoff C, Deckert J, Xu K, Badner J, de Wit H (2008) Association between ADORA2A and DRD2 polymorphisms and caffeine-induced anxiety. Neuropsychopharmacology. 33:2791– 2800
Retey JV, Adam M, Khatami R, Luhmann UF, Jung HH, Berger W, Landolt HP (2007) A genetic variation in the adenosine A2A receptor gene (ADORA2A) contributes to individual sensitivity
to caffeine effects on sleep. Clin Pharmacol Ther. 81:692–698
Google, are you reading my mind?
One interesting aspect of having a blog is checking out the search terms that people used to land at one’s site. It’s often difficult to figure out why a particular and seemingly unrelated term might bring someone this way.
But one recent search seems to have transcended the blog and gone straight into my brain-o-sphere, into the existential recess where some of my darker thoughts about grad school are stored:
Google, you know me so well. Now stop it, you’re freaking me out.
Research has shown that people’s names influence what professions they choose to enter; for example, men named Dennis are overrepresented among dentists and men named Raymond are overrepresented among doctors who specialize in radiology.
I wonder if guilt about his name is what drove the third author below to study the ill effects of cigarette smoking …
I’m working on a slew of new posts but wanted to just throw this out there. Reading through a paper this morning, I was struck by the fact that for the 4th time this week, I’ve come across a study that reports on or mentions some non-signifiant statistical trend in the data (the latest I’ve come across touts a p value of .07). Why are these trends reported at all? They’re very misleading and most certainly only reported when they suggest support for a given hypothesis (I haven’t noticed too many papers reporting trends that would go against the central hypothesis). Why set a threshold at all if you’re going to report stats that exceed it? Am I off base here?
People love pictures of brains. And, as a result, companies have been trying hard to find ways to incorporate MRI data into their sales pitches and business plans. One such company, Johnson O’Connor Research Foundation, has jumped on the bandwagon in a big way, having recently added a brain scan to the standard occupational aptitude test they offer to job seekers (they charge around $700 for the assessment):
The Johnson O’Connor Research Foundation is a nonprofit scientific research and educational organization with two primary commitments: to study human abilities and to provide people with a knowledge of their aptitudes that will help them in making decisions about school and work. Since 1922, hundreds of thousands of people have used our aptitude testing service to learn more about themselves and to derive more satisfaction from their lives.
See the Neurocritic for a spot-on criticism of the “study” upon which their new marketing pitch is based.
Bad neuroscience seems to be appearing increasingly frequently in the public media space. From misleading articles in the mainstream press to the poorly conducted studies that often form the basis for one or another misconceived business plan, fMRI research runs the danger of being victimized by its own success. Part of the problem stems from the general public’s inability to properly interpret neuroscientific data in the context of human psychology studies. Not that they should be blamed. Neuropsychology is a somewhat complicated discipline, and there isn’t any reason to believe that someone lacking in understanding of the basic principles of neural science, or psychology, or both, should be able to parse such data out correctly. The problem, however, is that the average public citizen isn’t neutral toward such data, but tends to be more satisfied by psychological explanations that include neuroscientific data, regardless of whether that data adds value to the explanation or not. The mere mention of something vaguely neuroscientific seems to increase the average reader’s satisfaction with a psychological finding, legitimizing it. Even worse, its the bad studies that benefit the most from this so-called “neurophlia”, the love of brain pictures. That’s according to a study from a research team led by Jeremy Grey at Yale University.
Participants read a series of summaries of psychological findings from one of four categories: Either a good or bad explanation, with or without a meaningless reference to neuroscience. After reading each explanation, participants rated how satisfying they found the explanation. The experiment was run on three different groups of participants: random undergraduates, undergrads who had taken intermediate-level cognitive neuroscience course and a slightly older group who had either already earned PhDs in neuroscience, or were in or about to enter graduate neuroscience programs.
The first group of regular undergrads were able to distinguish between good and bad explanations without neuroscience, but were much more satisfied by bad explanations that included reference to neural data ( The y-axis on the following figures stands for self-rated satisfaction):
Nor were the cognitive neuroscience students any more discerning. If anything, they were a bit worse than the non-cognitive neuroscience undergrads, in that they found good explanations with meaningless neuroscience more satisfying than good ones without :
But the PhD neural science people showed the benefits of their training. Not only did they not find bad explanations to be more satisfying by the addition of meaningless neuroscience, they found good explanations with meaningless neuroscience to be less satisfying.
As to why non-experts might have been fooled? The authors suggest that non-experts could be falling pray to the “the seductive details effect,” whereby “related but logically irrelevant details presented as part of an argument, tend to make it more difficult for subjects to encode and later recall the main argument of a text.” In other words, it might not be the neuroscience per se that leads to the increased satisfaction, but some more general property of the neuroscience information. As to what that property might be, it could be that people are biased towards arguments that possess a reductionist structure. That is, in science, “higher level” arguments that refer to macroscopic phenomena often refer to “lower level” explanations that invoke microscopic explanation. Neuroscientific explanations fit the bill in this case, by seeming to provide hard, low level data in support of higher level behavioral phenomenon. The mere mention of lower level data – albeit meaningless data – might have made it seem as if the “bad” higher level explanation was connected to some “larger explanatory system” and therefore more valid or meaningful. It could be simply that bad explanations – those involving neuroscience or otherwise – are buffered by the allure of complex, multilevel explanatory structures. Or it could be that people are easily seduced by fancy jargon like “ventral medial prefrontal connectivity” and “NMDA-type glutamate receptor regions.”
Whatever the proximal mechanisms of the “neurophilia” effect, the public infatuation with all things neural probably won’t be fading any time soon and, as such, its imperative that scientists, journalists and others who communicate with the public about brain science be on the lookout for bad, and incorrectly presented good, neuroscience, and be quick to issue correctives when it appears.
Go here for the Yale study.