With immune privilege comes immune responsibility

I am not a neuroscientist. Having poked a few cockroaches with electrodes as an undergraduate, I left the brain behind for the glamorous world of immunology. But immunologists and neuroscientists alike are challenging the long-held belief that the brain is separated from the immune system, and are exploring the idea that good immunological health and good mental health are linked. The immunology community considers some organs “immune privileged” – that is to say that immune cells stay away from certain delicate organs because they tend to do more harm than good. When faced with a foreign particle, white blood cells (leukocytes) trigger an immune response typically involving heat, swelling, redness and pain, all of which together comprise inflammation. This is great for dealing with infection, but causes significant collateral damage to tissues, which may have important functions. For example, our eyes are so sensitive that any amount of inflammation would impair vision. Evolutionarily, vision was so important for survival that our ancestors were more likely to survive if their eyes were left alone by the immune system and so avoided any inflammation-induced damage. But with immune privilege comes immune responsibility; reduced surveillance by leukocytes allows bacteria, viruses and other pathogens easier access to the host so organs must maintain a balance between keeping infection out and preserving tissue function.

In the brain, we used to think that this balance erred on the side of caution – that blood vessels in the brain excluded leukocytes almost completely to prevent inflammation and preserve delicate brain tissue. Indeed, when the brain does experience inflammation, the outcomes are usually bad – diseases such as Parkinson’s and Multiple Sclerosis (MS) are associated with inflammation in the brain. However, it turns out that an immune presence in the brain is not all bad. Clinical trials in the early 2000s aimed to use immunosuppressive drugs to reduce the infiltration of T cells (a type of white blood cell) into the brains of MS patients, thus reducing inflammation and alleviating disease. While symptoms did improve in treated patients, a small number of people died of overwhelming viral replication [1]. The infection was caused by JC virus, a common polyomavirus, which we now know is normally kept in check by T cells continuously patrolling the brain and central nervous system (CNS). So even when inflammation is harmful to the brain, leukocytes still have an important role to play. They are keeping the CNS under active surveillance to suppress infection and keep the brain healthy.

Since the emergence of HIV/AIDS in the 1970s and 80s, we have become aware of many other brain and CNS diseases that rely on robust immunity to stay quiet. Many herpesviruses, for example, live in the CNS and are reactivated following the immunosuppression associated with HIV infection. These viruses are present in the vast majority of people, most of whom will never know they’re infected. It’s only when we lose the protection afforded by patrolling leukocytes that these infections get out of control and cause disease.

So it seems that the brain and CNS are not separated from the immune system altogether. Though migration into these tissues is limited, we rely on sentinel T cells and other leukocytes to keep latent neuronal infections in check. But does it work both ways? Do events in the brain affect the immune system? We all recognise the utility of neural connections with body systems – muscles, gut, skin, eyes. But the immune system? How can cells that move freely and continuously around the body establish connections with the brain? And why would they? There are likely to be many answers to this, but one reason for neural/immune crosstalk is surprisingly intuitive: stress.

Dr Firdaus Dhabhar, Associate Professor at the Stanford Center on Stress and Health, studies the interactions between psychological stress and immune function and has described his work in a recent TED talk. He and others have found that leukocytes respond to short-term psychological stress by changing their migration behaviour. In response to the stress-related hormones epinephrine, norepinephrine and corticosterone, leukocytes leave their usual hangouts (organs like the spleen and lymph nodes) and travel in the blood to sites of potential damage, like the skin. This makes sense when one considers that acute stress can often be followed by injury. The immune system is simply preparing for action. Just as our muscles tense and heart rate increases in case we have to run, immune cells head to the skin in case the source of stress has big teeth and a penchant for human sashimi. Should we survive the attack, we may need to repair the skin and fight infection. In the modern world, this translates to bulk relocation of leukocytes in anticipation of trauma such as surgery. Worrying about surgery the night before going under the knife gives patients a short period of psychological stress, which causes leukocytes to migrate to the skin. This means that they are in the right place to repair damage, so patients whose leukocytes relocate in this way experience a more rapid recovery than those who don’t show any change [2]. Having experienced short-term stress gives immunity a boost and this extends to other immune functions. Mice given a psychological stressor or made to do exercise before vaccination have increased responses to the vaccine [3]. By getting the mediators of vaccine responses (leukocytes) to the site of action before or soon after a shot, we allow these cells increased and/or prolonged contact with the vaccine, thus enhancing the response. This suggests a surprising approach to boosting immunity: a short, sharp shock before a shot may be just the thing to maximise vaccine efficacy.

Just as too much immune activity can harm the brain, excessive triggering of leaukocytes by the brain can harm immunity. In the short-term, once the source of stress is removed, stress hormone levels drop and the immune system returns to normal within a few days. However, long-term stress leads to more lasting changes and can have detrimental effects on immunity. Long-term stress has the combined effect of reducing effective immune responses, while at the same time exposing tissues to inflammation-induced damage. People subject to prolonged periods of stress, including people with depression, PTSD and those caring for family members with dementia, have fewer leukocytes in the blood but increased levels of inflammation-associated factors [4-6]. This seems counter-intuitive since immune cells are a source of inflammation. However, in places like the skin, contact with the outside world leads to constant bombardment with foreign particles. By leaving organs like the lymph nodes, which tightly control exposure to foreign particles, and moving into immunologically noisier tissues, leukocytes become more active but less mobile. These activated cells can still pump inflammatory molecules into the circulation but are no longer able to move around the body, thus making them less likely to find infection when it occurs. Immunologists now think that long-term stress has the paradoxical effect of increasing inflammation while reducing effective immunity because of its tendency to trap crucial immune cells in the periphery.

One path to good immunological health then, is to minimise long-term psychological stress and to sharpen acute stress just before an immune insult. So listen to your mother: relax, eat well and sleep well. And maybe get a friend to terrify you before your next tetanus shot.

References:

[1]        Clifford et al. (2010). Natalizumab-associated progressive multifocal leukoencephalopathy in patients with multiple sclerosis: lessons from 28 cases. Lancet Neurol. 9: 438–446.

[2]        Rosenberger et al. (2009). Surgical stress-induced immune cell redistribution profiles predict short-term and long-term postsurgical recovery. A prospective study. J Bone Joint Surg Am. 91 (12): 2783-94.

[3]        Dhabhar and Viswanathan (2005). Short-term stress experienced at time of immunization induces a long-lasting increase in immunologic memory. Am J Physiol Regul Integr Comp Physiol. 289 (3): R738-44.

[4]        Dhabhar et al. (2009). Low serum IL-10 concentrations and loss of regulatory association between IL-6 and IL-10 in adults with major depression. J Psychiatr Res. 43 (11): 962-9.

[5]        Rawdin et al. (2012). Dysregulated relationship of inflammation and oxidative stress in major depression. Brain Behav Immun. pii: S0889-1591(12)00497-7.

[6]        Aschbacher et al. (2013). Good stress, bad stress and oxidative stress: Insights from anticipatory cortisol reactivity. Psychoneuroendocrinology. pii: S0306-4530(13)00042-5.

Linky and the Brain: May 20, 2013

The past week has been all about maths for me. Well, not all about maths. There was quite a bit of coding (PHP is not my friend) and some experiments (I blocked ALL the acetylcholine receptors).

But special tribute must be paid to all the maths.

First, for those who didn't catch it, Neuro PhD Candidate Kelly Zalocusky posted a fabulous discussion on statistical reliability in neuroscience, reviewing recent work by Stanford Professor Dr. John Ioannidis that highlights the lack of statistical power in many published neuroscience articles. I highly recommend you read Kelly's article (found here). And, if once you're done reading Kelly's post, you have the irresitable urge to calculate the size of n your data needs to be statistically reliable, I recommend the book Power Analysis for Experimental Research: A Pratical Guide for the Biological, Medical and Social Sciences by R. Barker Bauesell and Yu-Fang Li. If you are a Stanford University affiliate, Lane Library has a digital copy (catalogue record here). Last Tuesday, I used the power charts in the t-test section to calculate the correct n I need to have full statistical power, given my pilot data.

From using math to study brains, to studying brains that are doing math. Just in, by a group of researchers at Oxford University - Shocks to the Brain Improve Mathmatical Abilities. This article initialy crossed my internet browser in the form of coverage in Scientific America, as reprinted from Nature. The "shock" in question: transcranial direct current stimulation. The "brain" - the prefrontal cortex. The "math" - arithmetic - "rote memorization of mathematical facts (such as 2 x 17 = 34) and more complicated calculations (for example, 32 – 17 + 5)". The "improvement" - increased response speed - both immediately after stimulation, and, 6 months later, when Oxford students who had received the stimulation were 28% faster than control compatriots. An in depth analysis of the findings/protocols/interpretations of this study would require me to write a longer post, so for the present I'll just link you all to the original article, published in Current Biology. 

And, to round out our maths trilogy, this morning Gizmodo posted two video's featuring a mathematician explaining math jokes. It's funny. Very funny. Cora Ames, I expect you to integrate this concept into an improv segment. (Maths jokes, Explained)

A few other (non-math related) links:

Science Seeker Awards - With special call out both Part 1 and Part II of The Crayolafication of the Brain (Part II won best psych/neuro post)

SfN Careers Youtube Channel highlights alternative career choices - video interviews with Society members whose career paths are not of the traditional academic flavor.

A meta-analysis of the use of literary puns in science article titles. Yeah, we scientists took English Lit in college, too.

Highlight on Neural Prosthetic Systems: NSF IGERT Video Competition

The talented graduate students of Krishna Shenoy's Neural Prosthetic Systems Lab (Dan, Cora, Eric, Niru and Sergey) have made a video for the NSF IGERT Video and Poster Competition. Here is a link to their video: http://posterhall.org/igert2013/posters/432

I think it's fantastic. If you enjoy it as much as I did, consider "voting" for it under the Public Choice tab (and if you're part of IGERT / MBC, you can also log in and vote under the "Community Choice" tab). The Shenoy Lab team would really appreciate it.

The NSF IGERT 2013 Video & Poster Competition

The competition features over 100 presentations each made by a student or a team of students nominated from different IGERT Ph.D. programs. The work presented often transcends traditional disciplinary boundaries and addresses complex research problems of significant scientific and societal importance. While the presenters have been asked to make their posters for a technical/scientific audience, their videos are to be geared toward a more general, non-technical/non-scientific audience. Source: NSF IGERT Competition Website

Competing Gustatory Interests: the author of this post was promised brownies in exchange for blogging the link.

Linguistic Disconnect between the Brain and Emotions

How many love songs have you heard that mention the brain? Heartache and heartbreak are the shorthand for romantic unhappiness, a racing heart indicates excitement, but no English expression I am aware of links the emotions to the brain. On the contrary, language assigns emotions to almost any organ except the one that is actually responsible for them. The heart gets assigned this responsibility most frequently, but common usage also credits the intestines for producing a person’s courage. After all, we say that a courageous person has guts, not that he or she has a powerful prefrontal cortex, which would be the physiologically correct statement. It’s not just English either. Spanish proverbs on courage center on the person’s kidneys, and a Russian, when annoyed, is likely to say, “You have touched my liver.” Why is our language so out of touch with a basic scientific fact? One reason is history. In his treatise “On the Sacred Disease” dated to 400 B.C., Hippocrates (1), the father of modern medicine, states “Men ought to know that from nothing else but the brain come joys, delights, laughter and sports, and sorrows, griefs, despondency, and lamentations.” And the excellent website for the PBS documentary titled The Secret History of the Brain (2) states that Galen, an eminent Roman physician, wrote of the brain as the source of temperament and emotion in 170 B.C. The ancient Greeks and Romans already knew about the role of the brain in causing emotions, but, like so much of the knowledge of antiquity, this was forgotten in the Middle Ages, especially because the Christian Church banned anatomical studies. And, by the way, until real-time imaging of the brain with fMRI came along, anatomical comparisons of the brain across different species provided some of the best evidence for the functions of the different organs. As Paul D. MacLean wrote in his 1967 article “The Brain in Relation to Empathy and Medical Education” in the Journal of Nervous and Mental Disease (3), the similarity of the limbic lobe across all mammals and its absence in reptiles led to the hypothesis that it is involved in emotion. This similarity also permitted anatomical experiments on animals that in conjunction with clinical data on human psychiatric patients provide the bulk of the evidence for the contemporary scientific understanding of emotion. However, all this occurred within the past two centuries, too recently to affect our language. Therefore, the modern European languages came into existence at a time when their speakers were ignorant of the true cause of emotions.

Also, our language reflects our intuition whereas many scientific findings, even basic ones, are counterintuitive. Your heart does race when you’re excited. It is easy to assume that this correlation is causation and much harder to understand the real neurobiology involved. Perhaps, there will one day be a time when there will be as many sayings about the limbic system as there are about the heart now. But for that to happen, the limbic system would need to be thoroughly investigated and explained to all people, so that it is as concrete and tangible as a heartbeat.

Footnotes

1. On the Sacred Disease, Hippocrates - Source
2. The Secret History of the Brain, PBS - Source
3. Maclean (1967). The Brain in Relation to Empathy and Medical Education. Journal of Nervous and Mental Disease, 144 (5): 374-382. Source (warning: paywall)

Why most published neuroscience findings are false

Stanford Professor Dr. John Ioannidis has made some waves over the last few years. His best-known work is a 2005 paper titled "Why most published research findings are false."(1) It turns out that Ioannidis is not one to mince words.

In the May 2013 issue of Nature Reviews Neuroscience, Ioannidis and colleagues specifically tackle the validity of neuroscience studies (2). This recent paper was more graciously titled "Power failure: why small sample size undermines the reliability of neuroscience," but it very easily could have been called "Why most published neuroscience findings are false."

Since these papers outline a pretty damning analysis of statistical reliability in neuroscience (and biomedical research more generally) I thought they were worth a mention here on the Neuroblog.

Ioannidis and colleagues rely on a measure called Positive Predictive Value or PPV, a metric most commonly used to describe medical tests. PPV is the likelihood that, if a test comes back positive, the result in the real world is actually positive. Let's take the case of a throat swab for a strep infection. The doctors take a swipe from the patient's throat, culture it, and the next day come back with results. There are four possibilities.

1. The test comes back negative, and the patient is negative (does not have strep). This is known as a "correct rejection".
2. The test comes back negative, even though the patient is positive (a "miss" or a "false negative").
3. The test comes back positive, even when the patient is negative (a "false alarm" or a "false positive").
4. The test correctly detects that a patient has strep throat (a "hit").

In neuroscience research, we hope that every published "positive" finding reflects an actual relationship in the real world (there are no "false alarms"). We know that this is not completely the case. Not every single study ever published will turn out to be true. But Ioannidis makes the argument that these "false alarms" come up much more frequently than we would like to think.

To calculate PPV, you need three other values:

1. the threshold of significance, or α, usually set at 0.05.
2. the power of the statistical test. If β is the "false negative" rate of a statistical test, power is 1 - β. To give some intuition--if the power of a test is 0.7, and there are 10 studies done that all are testing non-null effects, the test will only uncover 7 of them. The main result in Ionnadis's paper is an analysis of neuroscience meta-analyses published in 2011. He finds the median statistical power of the papers in these studies to be 0.2. More on that later.
3. the pre-study odds, or R. R is the prior on any given relationship tested in the field being non-null. In other words, if you had a hat full of little slips of paper, one for every single experiment conducted in the field, and you drew one out, R is the odds that that experiment is looking for a relationship that exists in the real world.

For those who enjoy bar-napkin calculations--those values fit together like this:

$latex PPV = ([1 - \beta] * R) / ([1 - \beta] * R + \alpha) $

Let's get back to our medical test example for a moment. Say you're working in a population where 1 in 5 people actually has strep (R = 0.25). The power of your medical test (1- β) is 0.8, and you want your threshold for significance to be 0.05. Then the test's PPV is (0.8 * 0.25)/ (0.8 * 0.25 + 0.05) = 0.8. This means that 80% of the times that the test claims the patient has strep, this claim will actually be true. If, however, the power of the test were only 0.2, as Ioannidis claims it is broadly across neuroscience, then the PPV drops to 50%. Fully half of the time, the test's results indicate a false positive.

In a clinical setting, epidemiological results frequently give us a reasonable estimate for R. In neuroscience research, this quantity might be wholly unknowable. But, let's start with the intuition of most graduate students in the trenches (ahem...at the benches?)...which is that 90% of experiments we try don't work. And some days, even that feels optimistic. If this intuition is accurate, then only 10% of relationships tested in neuroscience are non-null in the real world.

Using that value, and Ioannidis's finding that the average power in neuroscience is only 20%, we learn that the PPV of neuroscience research, as a whole, is (drumroll........) 30%.

If our intuitions about our research are true, fellow graduate students, then fully 70% of published positive findings are "false positives". This result furthermore assumes no bias, perfect use of statistics, and a complete lack of "many groups" effect. (The "many groups" effect means that many groups might work on the same question. 19 out of 20 find nothing, and the 1 "lucky" group that finds something actually publishes). Meaning—this estimate is likely to be hugely optimistic.

If we keep 20% power in our studies, but want a 50/50 shot of published findings actually holding true, the pre-study odds (R) would have to be 1 in 5.

To move PPV up to 75%, fully 3 in 4 relationships tested in neuroscience would have to be non-null.

1 in 10 might be pervasive grad-student pessimism, but 3 out of 4 is absolutely not the case.

So—how can we, the researchers, make this better? Well, the power of our analyses depends on the test we use, the effect size we measure, and our sample size. Since the tests and the effect sizes are unlikely to change, the most direct answer is to increase our sample sizes. I did some coffee-shop-napkin calculations from Ioannidis’s data to find that the median effect size in the studies included in his analysis is 0.51 (Cohen’s d). For those unfamiliar with Cohen’s d—standard intuition is that 0.2 is a “small” effect, 0.5 is a “medium” effect, and 0.8 constitutes a “large” effect. For those who are familiar with Cohen’s d…I apologize for saying that.

Assuming that the average effect size in neuroscience studies remains unchanged at 0.51, let’s do some intuition building about sample sizes. For demonstration’s sake, we’ll use the power tables for a 2-tailed t-test.

To get a power of 0.2, with an effect size of 0.51, the sample size needs to be 12 per group. This fits well with my intuition of sample sizes in (behavioral) neuroscience, and might actually be a little generous.

To bump our power up to 0.5, we would need an n of 31 per group.

A power of 0.8 would require 60 per group.

My immediate reaction to these numbers is that they seem huge—especially when every additional data point means an additional animal utilized in research. Ioannidis makes the very clear argument, though, that continuing to conduct low-powered research with little positive predictive value is an even bigger waste. I am happy to take all comers in the comments section, at the Oasis, and/or in a later blog post, but I will not be solving this particular dilemma here.

For those actively in the game, you should know that Nature Publishing Group is working to improve this situation (3). Starting next month, all submitting authors will have to go through a checklist, stating how their sample size was chosen, whether power calculations were done given the estimated effect sizes, and whether the data fit the assumptions of the statistics that are used. On their end, in an effort to increase replicability, NPG will be removing all limits on the length of methods sections. Perhaps other prominent publications would do well to follow suit.

Footnotes

1.  Ioannidis JPA (2005) Why Most Published Research Findings Are False. PLoS Med 2(8): e124. doi:10.1371/journal.pmed.0020124

2. Button et al (2013). Power Failure: why small sample size undermines the reliability of neuroscience. Nature Reviews Neuroscience 14: 3665-376. doi:10.1038/nrn3475

3. The specific announcement detailing changes in submission guidelines, also the Nature Special on Challenges in Irreproducible Research

It's a Hen, not a Him: sex bias in neuroscience research

Tales from Lab Meeting

I’d like to conduct a survey.

Q1. How many times per lab meeting can I interrupt a discussion if someone refers to a female chicken as “he”?

This survey isn’t (solely) hyperbolic. I could actually use some advice over here. The comment section is open.

Do I interrupt my PI when he does it? The post-docs? Should I comment the first time it happens in each lab meeting, or the first time someone who isn’t the head of my lab does it.

As folks out there may well know, I work in a lab that studies behavior in chickens (amongst other things). After an infamous incident involving a newly sexually mature rooster, a surprisingly thin-walled animal facility, and the Shenoy lab monkeys*, my lab exclusively keeps female adult chickens.

And yet, despite knowing with absolute certainty that our birds are females, the vast majority of discussions during lab meeting refer to the hens using masculine pronouns:

“And then he pecks on the zeroing cross.”

“Does he prefer pecking at higher or lower targets?”

“Have you trained him on the cue-based task yet?”

A Literary Interlude

A seminal component of my childhood reading experience was the works of Tamora Pierce. Her books often feature a young female protagonist, taking on non-traditional gender roles in a medieval fantasy setting. One scene, in which the main character is the only female in a classroom full of males, seems particularly apropos.

Kel opened the book and pointed to the author’s name. “Sir, the writer is my father.”

The master of ceremonies snatched the book away and scowled at the title page. “What of that?” he demanded. “The child does not have all of his father’s knowledge.”

All of her father’s knowledge, thought Kel irritably.

“Excuse me, Master Oakbridge,” Neal said in his friendliest voice, “but Kel doesn’t have all of her father’s knowledge. Not his.”

Dropping her blank Yamani mask-face, Kel glared at him.

Oakbridge also glared at Neal. “The majority of you are lads. Proper usage calls for male pronouns when males are part of the group.”

“Except that you addressed Kel alone, which then demands the exact term.”

-- Tamora Piece, First Test

Bias in Science

At least on the second floor of the Fairchild Building, it is a truth universally acknowledged, that the pervasive STEM field gender gap, and the inherent biases against women in science that everyone, even female scientists, hold, are a problem. This blog post isn’t about these issues - I’ll merely comment that for those of you who haven’t yet read it, Stanford Professor Jennifer Raymond’s recent Nature article, Sexist Attitudes: Most of us are biased, is excellent.

Last week, at the Stanford Neurosciences PhD program retreat, held in a very swanky Pajaro Dunes Resort, Dr. Annaliese Beery (Smith College), gave an absolutely fantastic seminar.** By audience request, after she discussed her primary research on the neural basis of social bonds between rodent peers, Dr. Beery talked about a recent review she conducted with her post-doc advisor, Dr. Irving Zucker (UC Berkeley), on sexual biases in research on mammals. Their review was published in 2011, in the journal Neuroscience & Biobehavioral Reviews (Beery and Zucker, 2011).

Their basic claim? Female mammals are underrepresented in animal models, and for no good reason.

For 10 areas of biological research, e.g. neuroscience, Drs. Beery and Zucker conducted a literature review. The took four journals with high impact factors dedicated to publishing peer-reviewed articles on the chosen subject. In the case of neuroscience, the Journal of Neuroscience, Neuroscience, Journal of Comparative Neurology and Nature Neuroscience. For each journal, they surveyed the first 20 primary research articles published in 2009 that involved research on mammals. They determined whether the authors of those 20 articles listed research subjects as males, females, both or unspecified. Furthermore, if a study used both males and females, Drs. Beery and Zucker determined whether data were analyzed by sex.

(Some of) The Results

Across all 10 fields surveyed, 8 had biases towards using male animal subjects. These fields were: neuroscience, pharmacology, physiology, endocrinology, zoology, behavioral physiology and behavior. A skew towards using female subjects was found in the last 2 fields, immunology and reproduction.

Neuroscientists, meet me at camera three

Hi there, folks. Let’s ignore the other fields included in Annaliese’s study, and focus on the one that matters most to us (that’d be neuroscience). As of 2009, articles published in the aforementioned journals are rocking an impressive 5.5:1 bias towards reporting on only males versus only females. That’s the largest bias of all 10 biological fields.

But you know what’s worse that being called the most sexually biased field? Well, two things. 1) The fact that 22-42% of articles in neuroscience, physiology and interdisciplinary biology journals failed to specify the sex of the animal in question. 2) Of the ~10% of neuroscience articles that did report using both males and females, only 20% of those studies analyzed their data by sex.

Why a sex bias?

Apparently, the tradition of excluding females from research subjects is based on the assumption that for many animal behaviors, estrous or menstrual cycles result in higher variability amongst female subjects than seen in male subjects. This assumption has been directly challenged by several studies, but the common wisdom remains. Indeed, during my days as a rodent physiologist, I was trained that males were preferable for experiments because they would exhibit less response variability.

What should be done?

Drs. Beery and Zucker make a strong case that exclusion of females in non-human animal research is an issue whose correction will improve the quality of scientific research. I cannot think that many people will disagree with the authors that, "The genetic sex and hormone cycles of female animal models profoundly affect biological processes that remain urgently in need of investigation if we are to fulfill the mission of improving quality of life for women as well as men."

Beery and Zucker propose co-opting the NIH guidelines that have already successfully increased inclusion of females in clinical studies. Specifically, they suggest applying those guidelines to non-human animal research as follows:

1. If male and female animal models are thought to differ in response to an intervention then the study must be designed with adequate sample sizes to answer the question for each sex. 2. If prior research strongly indicates that there are no significant differences between male and female animals, then sex is not required in subject sex selection, but study of both males and females is both feasible and encouraged. 3. If information about the existence of sex differences is absent or equivocal then both sexes should be studied in numbers sufficient to permit valid analysis. 4. Study of mechanisms underlying sex differences should be a high priority. 5. Outreach training activities offering practical suggestions and additional sources of information should be made available by the NIH to help investigators design studies that fully incorporate female animals. 6. The review process for extramural funding should treat inclusion of female animals as a matter of scientific merit that affects funding.

All right, it’s time for a senior grad student moment.

Yes, carefully designed studies that seek to discover new sexually dimorphic traits should be done; such an effort can only advance biomedical research.

But, I am not naïve; I am under no illusions that the majority of neuroscientists will have either the inclination or the resources to expand their studies to include a full-fledged investigation of sexual-dimorphic features. I certainly cannot imagine attempting to include such a study in the last R01 my lab submitted to the NIH; neither do I think our reviewers would have been pleased with such an unfocused, likely unnecessary, series of proposed experiments. Yes, the proposed comparisons of responses in different sexes is ideal in theory, but in practice, hard to motivate.

But.

I think that there are at least a couple practical, implementable steps we (neuroscientists, graduate students, those in the trenches) can take.

 What should we demand of ourselves?

1. Think about your experimental design, and make a deliberate decision as to whether you will use only one gender or both. Be prepared to defend that decision.
2. When you do an experiment, include gender in your experimental notes. When you publish, report the gender of your research animals. The Nature publishing group has recently removed length restrictions on its methods sections. Where they lead, hopefully other journals will follow. Folks publishing in a NPG journal, you now have no limitations to hobble the detailed reporting of your experimental methodology. Use your power wisely.
3. If you have the data, either do the comparison between effect sizes in males and females, or mention your decision to not do the comparison. (Assuming you have sufficient sample sizes to make such a comparison statistically meaningful. More on that subject in an upcoming post by Kelly Zalocusky.) Let's avoid relegating this issue of sex bias to "out of sight, out of mind" status.

What’s next for me?

As I said, as convincing as I found Beery and Zucker’s discussion of the importance of research into sex differences, I will continue to study the neural mechanisms underlying attentional modulation of sensory information processing. On the less drastic scale, given the age and breed of chicken I employ, it is not feasible for me to identify the gender of my animal subjects. Birds are notoriously difficult to sex before they develop secondary sexual characteristics. But even though I will not be able to track the gender of each experimental subject, I can explicitly state in my methods sections that I did not select for any particular gender; that I assumed a 1:1 ratio of male and female chicks.

And as for the behavior hens, well, while writing this article, I checked the most recent draft of a soon-to-be-submitted R01, to see whether we had specified the gender of the bird. We hadn’t. Guess I know what the next edit I make will be. Maybe I’ll mention those male pronouns to my PI at the same time.

Footnotes

Beery and Zucker (2011). Sex bias in neuroscience and biomedical research. Neuroscience and biobehavioral research. Volume 35, Issue 3, January 2011, Pages 565–572

* Turns out, monkeys who can’t sleep at night because a rooster is constantly crowing, will fall asleep during the day. Which gets in the way of experiments.

** I cannot sing Dr. Beery’s praises enough.  If there are any readers searching for researchers to invite to their seminar series, I give a full-throated endorsement of inviting Dr. Beery. You won’t regret it. Again, here’s her lab website. I found her research on the role of neuropetides in regulating social behaviors to be particularly interesting. Not to mention adorable (see right). And her field research stories are great (permits for importing/exporting lab materials from South American countries can be … hilariously tricky).

And one last thing: Some non-sex-related findings findings that surprised me not at all:

Have you ever gotten the feeling that everyone and their post-doc advisor is using rodent models in neuroscience? Turns out “everyone” equals approximately 85% of published articles, at least as of 2009. The authors note that a separate analysis of historical trends in animal research shows that in the first 2 decades of the 20^th century, fewer than 10% of animal studies used rodents. Rates of rodent use started to skyrocket between 1969 and 2009; largely because of the growing popularity and genetic tractability of mice.

Ph.D's in Press: anxiety, presynaptic scaffolding, epigenetics and more!

Part 5 in an occasional feature, highlighting recently published articles featuring an author (or authors) who is a current member of the Stanford Neuroscience Ph.D program. (Part 1, Part 2, Part 3, Part 4)* First off, 4th year student Sung-Yon Kim (Deisseroth lab) published his study of distinct subregions of the bed nucelus of the stria terminalis, demonstrating, using optogenetics that BNST neurons that project to distinct brain regions each implement independent features of anxiety. Additional Neuro PhD authors include: Christina Kim, Caitlin Mallory and Joanna Mattis.

Behavioural states in mammals, such as the anxious state, are characterized by several features that are coordinately regulated by diverse nervous system outputs, ranging from behavioural choice patterns to changes in physiology (in anxiety, exemplified respectively by risk-avoidance and respiratory rate alterations). Here we investigate if and how defined neural projections arising from a single coordinating brain region in mice could mediate diverse features of anxiety. Integrating behavioural assays, in vivo and in vitro electrophysiology, respiratory physiology and optogenetics, we identify a surprising new role for the bed nucleus of the stria terminalis (BNST) in the coordinated modulation of diverse anxiety features. First, two BNST subregions were unexpectedly found to exert opposite effects on the anxious state: oval BNST activity promoted several independent anxious state features, whereas anterodorsal BNST-associated activity exerted anxiolytic influence for the same features. Notably, we found that three distinct anterodorsal BNST efferent projections-to the lateral hypothalamus, parabrachial nucleus and ventral tegmental area-each implemented an independent feature of anxiolysis: reduced risk-avoidance, reduced respiratory rate, and increased positive valence, respectively. Furthermore, selective inhibition of corresponding circuit elements in freely moving mice showed opposing behavioural effects compared with excitation, and in vivo recordings during free behaviour showed native spiking patterns in anterodorsal BNST neurons that differentiated safe and anxiogenic environments. These results demonstrate that distinct BNST subregions exert opposite effects in modulating anxiety, establish separable anxiolytic roles for different anterodorsal BNST projections, and illustrate circuit mechanisms underlying selection of features for the assembly of the anxious state.

Kim et al (2013). Diverging neural pathways assemble a behavioural state from separable features in anxiety. Nature, 496(7444): 219-23.

Poh Hui Chia (Shen lab), who recently defended her thesis research, published her work on intramolecular regulation of presynaptic scaffold protein SYD-2/liprin-a.

SYD-2/liprin-α is a multi-domain protein that associates with and recruits multiple active zone molecules to form presynaptic specializations. Given SYD-2's critical role in synapse formation, its synaptogenic ability is likely tightly regulated. However, mechanisms that regulate SYD-2 function are poorly understood. In this study, we provide evidence that SYD-2's function may be regulated by interactions between its coiled-coil (CC) domains and sterile α-motif (SAM) domains. We show that the N-terminal CC domains are necessary and sufficient to assemble functional synapses while C-terminal SAM domains are not, suggesting that the CC domains are responsible for the synaptogenic activity of SYD-2. Surprisingly, syd-2 alleles with single amino acid mutations in the SAM domain show strong loss of function phenotypes, suggesting that SAM domains also play an important role in SYD-2's function. A previously characterized syd-2 gain-of-function mutation within the CC domains is epistatic to the loss-of-function mutations in the SAM domain. In addition, yeast two-hybrid analysis showed interactions between the CC and SAM domains. Thus, the data is consistent with a model where the SAM domains regulate the CC domain-dependent synaptogenic activity of SYD-2. Taken together, our study provides new mechanistic insights into how SYD-2's activity may be modulated to regulate synapse formation during development.

Chia et al (2013). Intramolecular regulation of presynaptic scaffold portein SYD-2/liprin-a. Molecular and Cellular Neuroscience, 56: 76-84.

In the category of reviews and commentaries, Jana Lim (Brunet lab) co-authored a review on transgenerational epigenetic inheritance.

It is textbook knowledge that inheritance of traits is governed by genetics, and that the epigenetic modifications an organism acquires are largely reset between generations. Recently, however, transgenerational epigenetic inheritance has emerged as a rapidly growing field, providing evidence suggesting that some epigenetic changes result in persistent phenotypes across generations. Here, we survey some of the most recent examples of transgenerational epigenetic inheritance in animals, ranging from Caenorhabditis elegans to humans, and describe approaches and limitations to studying this phenomenon. We also review the current body of evidence implicating chromatin modifications and RNA molecules in mechanisms underlying this unconventional mode of inheritance and discuss its evolutionary implications.

Lim and Brunet (2013). Bridging the transgenerational gap with epigenetic memory. Trends in Genetics, 29(3): 176-186.

Several Neuro PhD students were also second through n-th authors on papers. From the prolific Deisseroth lab, students Aslihan Selimeyoglu and Sung-Yon Kim are coauthors on a paper describing "a prefrontal cortex-brainstem neural projection that controls response to behavioral challenge".

The prefrontal cortex (PFC) is thought to participate in high-level control of the generation of behaviours (including the decision to execute actions¹); indeed, imaging and lesion studies in human beings have revealed that PFC dysfunction can lead to either impulsive states with increased tendency to initiate action², or to amotivational states characterized by symptoms such as reduced activity, hopelessness and depressed mood³. Considering the opposite valence of these two phenotypes as well as the broad complexity of other tasks attributed to PFC, we sought to elucidate the PFC circuitry that favours effortful behavioural responses to challenging situations. Here we develop and use a quantitative method for the continuous assessment and control of active response to a behavioural challenge, synchronized with single-unit electrophysiology and optogenetics in freely moving rats. In recording from the medial PFC (mPFC), we observed that many neurons were not simply movement-related in their spike-firing patterns but instead were selectively modulated from moment to moment, according to the animal’s decision to act in a challenging situation. Surprisingly, we next found that direct activation of principal neurons in the mPFC had no detectable causal effect on this behaviour. We tested whether this behaviour could be causally mediated by only a subclass of mPFC cells defined by specific downstream wiring. Indeed, by leveraging optogenetic projection-targeting to control cells with specific efferent wiring patterns, we found that selective activation of those mPFC cells projecting to the brainstem dorsal raphe nucleus (DRN), a serotonergic nucleus implicated in major depressive disorder⁴, induced a profound, rapid and reversible effect on selection of the active behavioural state. These results may be of importance in understanding the neural circuitry underlying normal and pathological patterns of action selection and motivation in behaviour.

Warden et al (2013). A prefrontal cortex-brainstem neuronal projection that controls response to behavioural challenge. Nature, 492 (428-432).

Also from the Deisseroth lab, Sung-Yon Kim, Kelly Zalocusky, Joanna Mattis and Logan Grosenick are all authors of the recently published article describing CLARITY, a novel method developed by lead author Kwanghun Chung for producing optically transparent tissue for the purpose of  tissue-intact imaging.

Obtaining high-resolution information from a complex system, while maintaining the global perspective needed to understand system function, represents a key challenge in biology. Here we address this challenge with a method (termed CLARITY) for the transformation of intact tissue into a nanoporous hydrogel-hybridized form (crosslinked to a three-dimensional network of hydrophilic polymers) that is fully assembled but optically transparent and macromolecule-permeable. Using mouse brains, we show intact-tissue imaging of long-range projections, local circuit wiring, cellular relationships, subcellular structures, protein complexes, nucleic acids and neurotransmitters. CLARITY also enables intact-tissue in situ hybridization, immunohistochemistry with multiple rounds of staining and de-staining in non-sectioned tissue, and antibody labelling throughout the intact adult mouse brain. Finally, we show that CLARITY enables fine structural analysis of clinical samples, including non-sectioned human tissue from a neuropsychiatric-disease setting, establishing a path for the transmutation of human tissue into a stable, intact and accessible form suitable for probing structural and molecular underpinnings of physiological function and disease.

Chung (2013). Structural and molecular interrogation of intact biological systems. Nature. doi:10.1038/nature12107

Georgia Panagiotakos is the second author on a paper published in PLOS One, showing the mechanisms underlying the production of the calcium channel associated transcriptional regulator (CCAT), which is encoded by the C-terminus of the voltage-gated calcium channel Cav1.2.

The C-terminus of the voltage-gated calcium channel Ca_v1.2 encodes a transcription factor, the calcium channel associated transcriptional regulator (CCAT), that regulates neurite extension and inhibits Ca_v1.2 expression. The mechanisms by which CCAT is generated in neurons and myocytes are poorly understood. Here we show that CCAT is produced by activation of a cryptic promoter in exon 46 of CACNA1C, the gene that encodes Ca_V1.2. Expression of CCAT is independent of Ca_v1.2 expression in neuroblastoma cells, in mice, and in human neurons derived from induced pluripotent stem cells (iPSCs), providing strong evidence that CCAT is not generated by cleavage of Ca_V1.2. Analysis of the transcriptional start sites in CACNA1C and immune-blotting for channel proteins indicate that multiple proteins are generated from the 3′ end of the CACNA1C gene. This study provides new insights into the regulation of CACNA1C, and provides an example of how exonic promoters contribute to the complexity of mammalian genomes.

Gomez-Ospina N, Panagiotakos G, Portmann T, Pasca SP, Rabah D, et al. (2013) A Promoter in the Coding Region of the Calcium Channel Gene CACNA1C Generates the Transcription Factor CCAT. PLoS ONE 8(4): e60526. doi:10.1371/journal.pone.0060526

Matt Figley (Gitler lab) is the third author on a paper in Nature Genetics, discussing the suppression of TDP-43 toxicity in ALS disease models by the inhibition of RNA lariat debranching enzyme.

Amyotrophic lateral sclerosis (ALS) is a devastating neurodegenerative disease primarily affecting motor neurons. Mutations in the gene encoding TDP-43 cause some forms of the disease, and cytoplasmic TDP-43 aggregates accumulate in degenerating neurons of most individuals with ALS. Thus, strategies aimed at targeting the toxicity of cytoplasmic TDP-43 aggregates may be effective. Here, we report results from two genome-wide loss-of-function TDP-43 toxicity suppressor screens in yeast. The strongest suppressor of TDP-43 toxicity was deletion of DBR1, which encodes an RNA lariat debranching enzyme. We show that, in the absence of Dbr1 enzymatic activity, intronic lariats accumulate in the cytoplasm and likely act as decoys to sequester TDP-43, preventing it from interfering with essential cellular RNAs and RNA-binding proteins. Knockdown of Dbr1 in a human neuronal cell line or in primary rat neurons is also sufficient to rescue TDP-43 toxicity. Our findings provide insight into TDP-43–mediated cytotoxicity and suggest that decreasing Dbr1 activity could be a potential therapeutic approach for ALS.

Armakola et al (2013). Inhibition of RNA lariat debranching enzyme suppresses TDP-43 toxicity in ALS disease models. Nature Genetics, 44: 1302-1309.

And lastly, Daniel Kimmel, together with first-author Michael Greicius, co-authored a review on neuroimaging insights into network-based neurodegeneration.

Purpose of review: Convergent evidence from a number of neuroscience disciplines supports the hypothesis that Alzheimer's disease and other neurodegenerative disorders progress along brain networks. This review considers the role of neuroimaging in strengthening the case for network-based neurodegeneration and elucidating potential mechanisms.

Recent findings: Advances in functional and structural MRI have recently enabled the delineation of multiple large-scale distributed brain networks. The application of these network-imaging modalities to neurodegenerative disease has shown that specific disorders appear to progress along specific networks. Recent work applying theoretical measures of network efficiency to in-vivo network imaging has allowed for the development and evaluation of models of disease spread along networks. Novel MRI acquisition and analysis methods are paving the way for in-vivo assessment of the layer-specific microcircuits first targeted by neurodegenerative diseases. These methodological advances coupled with large, longitudinal studies of subjects progressing from healthy aging into dementia will enable a detailed understanding of the seeding and spread of these disorders.

Summary: Neuroimaging has provided ample evidence that neurodegenerative disorders progress along brain networks, and is now beginning to elucidate how they do so.

Greicius and Kimmel (2012). Neuroimaging insights into network-based neurodegeneration. Current Opinion in Neurology. 25(6): 727-734.

*Regarding the mechanics of this feature: This is purely through the magic of an ongoing My NCBI search for the names of Neuro PhD students. I wouldn’t be surprised if there were some false negatives in the data set. Neuro students – let me know if I’ve missed your paper, and I’ll gladly add it.