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Phil Wang:
Good afternoon, and welcome everyone to our innovation lecture. And it's a pleasure to -- well, I'm Phil Wang, the Deputy Director here at NIMH -- it's a pleasure to introduce our speaker for today's innovation talk, Dr. Alyce Adams. She received her Ph.D. in health policy from Harvard Medical School and then stayed on as faculty there for about a decade, I think. And in 2008 made the cross-country trek to Kaiser Permanente's Division of Research in Oakland where she's a research scientist and the Director of Health Care Delivery and Policy, did I get that right? Close enough? All right. But her research has really spanned a pretty impressive breadth, I think. From everything from -- I was looking at publications that you had published recently, looking at things from prior approvals and some prescription benefit designs that might be of help to disadvantaged populations, including populations of concern at least to the folks here at NIMH. People with schizophrenia, bipolar illness, depression. And also looking at modifiable factors that could be intervened upon, things like patient-doctor communication or churn rates in health plans, that are amenable potentially to intervention that could then benefit patients in terms of the treatments they use, the outcomes they experience, and also with a goal of also potentially mitigating disparities. So, all of importance and interest to us here. And her funding is equally broad and impressive. It comes in part from us, NIMH, NIA, AHRQ, PCORI foundations, so she's well-funded, and a lot of people are interested in having you do research. So with that, let me just say that her talk today is When Access Isn't Enough: Persistent Disparities Among Our Nation's Insured. Dr. Adams?
Alyce Adams:
Thank you so much. I want to thank everyone here at NIMH, particularly Drs. Insel and Armstrong and Dr. Schulte and everyone for inviting me here and for making me feel at home. Thank you so much. I've had a wonderful day, had great conversations with people about how people are thinking about, not just health care disparities, but in general health care delivery research, and how we move from the sort of, the research paradigm that we're used to one that's more interactive, which health care systems and policymakers and others, in a way that we actually get the impacts we're looking for, the outcomes that we're interested in, as opposed to sort of writing the papers and hoping someone reads it. So it's been a really exciting day for me here, thank you so much. I'm going to tell you a little bit about Kaiser Permanente's Division of Research, because many people say what? Where? And, so basically, the Division of Research is essentially a research arm of Kaiser, however we acted pretty much like a medical school department. So we're soft money for the most part, we primarily rely on funds from NIH, as well as AHRQ and PCORI and all the usual places as well as foundations, et cetera.
And we do a lot of -- a variety of work from epidemiology to, not so much bench research, but a lot of health services research, health policy research. And in the last couple of years when Joe Selby left the Division of Research to go head up PCORI, Dr. Tracy Lieu came on as our director. And one of the first things she said was we don't really have an organization that really defines who we are and where we're going as an organization. And she saw this vision of health care delivery science being something that we were uniquely positioned to do as researchers who were embedded within a health care system. So we reorganized everything, and I got lucky enough to be chief of the Health Care Delivery and Policy section, which is a group of about 10 investigators, overall about 50 people, including staff. And a lot of our work really is motivated by real-world clinical issues and real-world policy issues that we're hoping our research can influence.
And as part of that we've had to think really creatively about how do we get the right people in the room at the right time in order to generate those research questions that are most important, not only to Kaiser, but to other health care systems. And then how do we move from knowing there's a problem to actually doing something about it in a systematic way while retaining our scientific integrity? So, we don't have all the answers yet, but I feel like we're getting a little bit closer.
In addition to my role as Chief, as Dr. Wang kindly mentioned, I'm also a research scientist myself. We have a very similar trajectory as you would have in a medical school department, for example. So we have assistant associate in full in the associate level, so the two on the posters referring to associate level position with respect to research. And the poster also mentioned we have a number of different administrative roles, including outreach and collaborations core for the Cancer Research Network. We're also part of the MHRN, as it were, the Mental Health Research Network, the CBRN, and a lot of other types of network activities that a lot of you have been very supportive of over the years. So what I'm going to talk about today is this issue that even when patients have access to care, it's really not enough.
Now when I started this role as a researcher, it was back in 1999, and at that time, we were still having this conversation about well, if you just build the right health care system, if you just give people access to the right services, would you get better outcomes, so that all of these disparities that we're all worried about go away. Because at the time there was a lot of concern about this issue between health -- having health insurance and not, or having underinsured and what that meant for disparities. So, a lot of conversation about that. And over the years what we found is that access alone isn't enough. And it's pretty logical, I mean one, we know that there's a lot of big stuff besides health care that affects your health outcomes. But also, we also know that when patients are in the same system and have equal access to care, you can get some differential results.
So a lot of the stuff I'm going to talk about today is some of the work that we've done to sort of show sort of why does that happen. And when it does happen what can we do about it? And so I'm also going to talk specifically about modifiable determinants. These are things that affect how people experience the health care system and the outcomes of that health care system that are essentially intervenable by the health care system itself. Things that we can do today. And this really is driven by clinicians who've said to us you know, that paper you wrote is great, it's really great that you got it in JAMA or Health Affairs or wherever that is, what does it mean for me? What am I supposed to do tomorrow with my patients or tomorrow with my quality improvement program to help me move forward? They didn't care about co-variants, they didn't care about p-values, they didn't care about any of that. What they wanted to know was what can you tell me about what I can do to make a difference in terms of these disparities, as opposed to just telling me that they exist.
So, I've spent a lot of my last 15 years sort of focusing on this idea of what are those modifiable determinants? What are those things that we could do that if we turn them on they would have a chance of actually having an impact on the things that we care about? In particular I focus a lot on medication adherence, which I'll talk about. And finally I'm going to talk about what I'm really excited about, which is the job that I have now in addition to being a researcher, but really getting people engaged and involved in this idea of stakeholder-engaged research. How do we create an environment where we can generate new evidence, where we can test out innovative strategies for dealing with these disparities together as a group? It's us, it's the patients, it's the physicians, it's the people developing quality improvement programs, getting all of us together in the same places to hash out what do we need to be doing, where do we need to be going, and how could researchers help us get there? So, as you all know, you know, in the pre-ACA world at least, the fact that we had so many people that had lacked health insurance was a concern for disparities because it tended to affect disparities populations. We know that at that time at least 35 percent of Latinos and 30 percent of American Indians and Alaska Natives had no health insurance coverage at all, which made them vulnerable to all sorts of things in terms -- including chronic disease outcomes which were potentially avoidable if they had just had access to a usual source of care. A lot of that is because they did not necessarily have employer-based health insurance, which as you know in the United States is very heavily reliant on that.
We also have this additional factor of underinsurance. So, not all insurance is created equal, right? There's different generosity of coverage. And the fact is if you happen to have coverage that doesn't cover a whole lot, that leaves you sort of vulnerable and -- sorry, at important times, you're going to get worse outcomes than somebody who was better coverage. And certainly one of the things that came up over and over again was this issue of higher out-of-pocket cost burden. Patients saying I didn't get that service because quite frankly, it was too expensive. Or I cut my medications in half because I simply couldn't afford it. Or I started sharing, you know, my medications with my brother-in-law who also has hypertension, because quite frankly, we both couldn't afford that medication. Making those decisions, we've done a lot of interviews, for example, with patients who were saying: "When I'm faced with yet another medication to add to the regimen, I have to ask myself how important this this?" We've had patients tell us okay, this is going to help me from going blind, this is going to help me prevent maybe a stroke sometime in the future, I think I'm going to take the first one. So they're making these calculations regardless of how important we're saying the medications are for their health, regardless of all the evidence saying this is cost-effective, you should take these things. This is their reality. And so we're seeing these things even among patients who have some insurance, but also patients who have underinsurance or get insurance only part of the year.
So, over time there's been this push, as you know, to expand coverage. The idea if we expand coverage, we're going to do a lot to reduce disparities. And absolutely, that's certainly the case. We have Medicaid and CHIP and Medicare Part D and the Mental Health Parity Law and Affordable Care Act, and you can go on and on about all the ways in which we've tried to, you know, sort of fill the holes in this patchwork system that we have of health insurance in the United States so that those people who are most vulnerable don't fall through those cracks. And the impact that coverage, while undeniably has increased people's access to health care services, the impact on disparities has been more mixed. And in fact, we find that even when patients have insurance, for example, privately insured populations, we still see disparities, right? And again, when I started this work, that wasn't so clear. People were saying oh, well, if you're in a managed care situation, you shouldn't have disparities, right? Everyone has access to the same stuff, it's all good quality care, what are we worried about? But we do see that. And we also see that coverage expansion often improves access, but disparities often persist, and in some cases, disparities actually can get worse when we expand coverage because the very people that we're most concerned about giving the coverage to are often the last to sign up for it, right. So you get all of these bizarre sort of outcomes we didn't intend, but these policies were actually intended to help people, don't necessarily end up where we wanted to go. I just have a few examples of that.
This is some of our earlier work in diabetes, and this was in a health plan where patients had more or less equal access to a really great disease management program. Very progressive at the time, a lot of outreach, a lot of support, RN calls on a periodic basis to help them manage their diabetes, and yet when we looked overall at the population -- bottom is the year, so between 1994 and 2001, and the A1C control is on the left hand side. We saw that for both men and women, blacks had higher A1C than whites, and that kind of persisted over time. So even though here we were just getting the results of some of this, you know, sort of groundbreaking diabetes work and understanding what makes a difference and we started changing things in terms of quality improvement, all the way to 2001 where we felt like we know what we need to do to address diabetes control in terms of, you know, medications that people need, self-support, the chronic disease management program, et cetera, the disparity persists across all of that time. So we said well maybe it's because we just sort of randomly select these people with known diabetes. What about those people who are new to diabetes when they were in a system like this? We should see the disparity go away then, right? Because they're all new, none of them have been exposed to it. As soon as they get exposed, we'll see the disparity go away. Unfortunately, that's not what happened. We saw a couple of things.
One is when they were diagnosed with diabetes, blacks were still doing worse than whites with that first initial diagnosis. Which wasn't supposed to happen, again, in this wonderful managed care world where everyone gets the same care. Furthermore, the disparity persisted over time and for men, it actually got bigger. So this was not the answer I think people were looking for from managed care at the time. We really thought this was going to be it, if we could just get everything right so that patients had access to a usual source of care, primary care as well as disease management, we would get rid of these things, but they did persist. Furthermore -- this is not our work, it's the work of a former fellow who looked at the Massachusetts health reform. She asked the question well, what happens when you do health reform on a global scale? You say we're going to give people insurance coverage, we're going to do all these things, what happens? Well, she found that in the early years after the Massachusetts health care reform, certainly there was a decrease in the likelihood of not having insurance, right. Which is what you would expect. That's what it was designed to do, have everybody, it does that at the minimum. So it did that. But she also looked at cost as a barrier, as well as having no personal doctor, again, all very positive. So we saw a decrease in these bad things that we, like, don't want see when we actually offered people health insurance coverage.
The bad news is that black/white differences in these things persisted despite the fact that we'd launched this health care reform. Right? So we had black race and Hispanic race still being significant predictors of not having health insurance, of having cost as a barrier, and not having a personal doctor. So despite the fact that we have this policy that's designed to sort of raise all boats, we're still having this persistent issue. Similarly, we recently released some work that we've been doing on the Medicare Part D law, where we looked at patients who were living in states where there was a cap on the number of medications that they could actually -- that would actually be reimbursed by Medicaid in any given month. So say there might be four medications would be covered by Medicaid, after that you're on your own. So, what Medicare Part D was it lifted that cap. Because before that we had this variation by state in terms of whether or not you had a cap. Medicare Part D came in and said no caps. So all of a sudden this financial barrier was lifted. So we thought okay, when Part D goes in, we should see everyone going up, which we did. Everyone increased their utilization. In this case it was patients with diabetes with lipid-lowering drugs, we're seeing a similar pattern regardless of what we looked at. We're looking at schizophrenia, bipolar disorder, cancer, antidepressants. No matter what we sort of put on here, what we're seeing is when you lift that cap, you see an increase in use.
However -- and this is where the red line comes in -- we found a couple of things. For this condition in particular, for lipid-lowering drugs among diabetes patients, for this particular medication, what we found was that the response under those 65 and older, the response to the policy among whites was stronger than it was for blacks. So when you lifted the cap, whites and blacks both started using more, but whites used more at a higher rate, such that there became this difference, this statistically significant difference between whites and blacks in terms of who was using. So the disparities got broader as opposed to getting narrower.
Similarly, when you look at those age 65 or older, this was a non-statistically significant difference before Part D, even though it was trending upwards, in the difference between whites and blacks. So basically, the lines are on top of each other. Post-Part D, the whites are suddenly using more than blacks. And again, it had to do with this differential response to the policy, which was not what I anticipated, but ultimately what it meant was where before we were concerned about these differences, particularly in this group with respect to utilization, they seemed to be getting worse despite the fact that we're doing what we're supposed to do, which is to provide health care insurance.
So, why is it that despite all of these efforts, particularly at the federal and state level, to improve access to care would either one, have no impact on disparities, in other words, make everyone a little bit better off, but we saw this disparities gap, but then also two, in some cases exacerbate it? Well, we already know that there's lots of things that matter in terms of health care disparities and they go way beyond the health care system. There's a lot of stuff that we don't have a whole lot of control over within the context of the health care delivery system. And certainly those factors all come into play with respect to these findings. We also find, however, that there's variation within and across health care systems, even when you have coverage that matter, differences in quality and delivery care, true affordability, and true accessibility. So does it really mean you have access if your doctor doesn't speak your language? Those types of things. Further, there are issues in the patient/provider and patient-health system dynamic that may also play a part in terms of why it is that when we provide health insurance coverage, people don't necessarily just show up.
So, this next sort of part I'm going to talk to you about is really this issue of quality improvement. A big question that we were asked when we first started this work is that well, if you have this great disease management program, et cetera, and you implement it, by definition if we're treating everybody the same, everyone should get better and all the boats will rise at the same level and we'll have sort of this even playing field where everyone will have equitable access to care. And they kept, you know, likening it to the tide rising all boats. And so we started on this question well, what systematic -- can systematic improvements associated with integrated care delivery systems reduce or eliminate disparities just by their very nature of being systematic? One of the studies that we had done looked at changes over time pre-EHR, pre-concerted disease management programs in 1997 in a single HMO relative to 2001, which is after all this stuff got turned on, they got their EHR, their Electronic Health Record, they got their quality improvement, they got all of these things.
So the good news here is that yes, when you look at things like cholesterol testing and cholesterol control, we did see a huge bump up. You know, so this told us, well, there's something the health systems, especially these sort of integrated care systems can do that can improve control for chronic diseases for these patient populations, and that it seems to be true across racial and ethnic groups. Furthermore, there is -- a lot of variation that we saw before across race, ethnicity, and gender, didn't completely go away, but it certainly narrowed. A sort of narrowing of this variation in the later years versus the earlier years. So that was sort of the good news. However, when we looked a little closer and broke down various components, we sort of found this pattern where when we were looking at things that had to do with processes of care, whether or not someone gets tested, whether or not someone is initiated on a particular medication, whether or not someone is titrated in terms of a medication that they need to go up a dose, that's when we saw a lot of synergy and a lot of same delivery of care across different racial and ethnic groups. Where we saw the variation was actually sort of on the patient's side of things. The patient actually had to maintain that. It was a follow-up, it was adherence and persistence with things where we saw variation. And in particular when we looked at newly-diagnosed patients to say okay, what's going on with them, we found that they were just as likely to start self-monitoring, they were just as likely to have dose augmentation or clinical intensification of treatment when they needed it, unfortunately a lot of people weren't getting that, but in general, there weren't racial differences by it. But where we saw the racial and ethnic differences and people started spreading apart was when we looked at things like medication adherence.
Now, why is this important? It's important because we also found that medication adherence is a strong predictor, a good predictor of control. This is again, diabetes patients. And furthermore, we found that when we controlled for medication adherence, much of the black/white difference in A1C was attenuated. When we said okay, let's have everyone have the same medication adherence, now what do we see, we actually saw rates that were more comparable between the two groups. So that told us that maybe something about these areas where it's more self-management, self-support, those types of things where we're likely to see more variation within these health care systems where people have equal access, more than it is these processes of care and things that they do automatically and do well, and they're sort of taken out of the realm of individual-level decision-making and more at a systematic level. We sort of implement these things at a system-wide level, they get implemented and it works fine. Anything that seems to involve individual patient decisions or the dynamic between the physician and the provider is where we started to see people separating apart. And this is just sort of more of the same.
When we looked at initiation of medications for diabetes, we found that for men, whites and blacks looked very similar. However, when we looked at whites and blacks in terms of other oral medications, we found that blacks were actually more likely to be initiated on these medications. Again, something systematic that happens within the system that says okay, this is the result you get, here's a recommendation, put them on this number of milligrams, starting now, twice a day. It's a very automated process. And through that automated process, not only were we getting similar rates, but blacks were actually faring better. But after they initiated therapy, again, the lines start to separate. Blacks had higher rates of discontinuation than whites, and it happened very quickly. Right? I just showed you data showing they're no different here, right? But come three months out, five months, six months, we start to see the separation of the two lines. And so we started feeling there's something about this follow-up process, there's something about self-management, support, what have you, that's just not happening with these patients, at least not at a level that is allowing them to maintain that equitable health care outcome that we're so interested in.
Again, what we found in hypertension is similar to what we found in diabetes, and this is actually in the Kaiser system, where we looked at adherence to anti-hypertensive therapy. Where we said okay, what is the likelihood of you picking up a prescription if you're prescribed it? Almost 100 percent. Almost everybody picks up that first prescription, no problem. It's -- the Kaiser pharmacy's right downstairs. You know, there's no hassle, there's no logistic issue, you know, you just go downstairs, you pick it up, and you take it home. Are you taking it? Some are and some aren't. And in particular, we found -- and this is one of the first studies I think to find this for Asians as well as blacks and Hispanics, where this early-on persistence, what happens for the first refill that you're supposed to fill, how many people fall out, being black, being Asian, or being Hispanic was statistically significant predictor of not picking up that first refill. Similarly we looked at non-adherence which is over a longer period of time, six to 12 months of adherence following the initial diagnosis and initiation on medication.
Again, we found that for blacks and Hispanics there was this persistent non-adherence to these medications. Even though they started off, again, in the same place. We found the same thing with anti-depressants among patients with hypertension. We found the same thing among patients using anti-depressants for their -- regardless of whether or not they had some other comorbidity, where we found that consistently, there was this difference in non-persistence, higher rates of non-persistence among blacks, Asians, and Latinos in this period of time prior to their initial hypertension diagnosis, at six months and at 12 months. And that non-persistence with anti-hypertensive therapy, and this is true for everyone, was predictive of non-persistence with anti-hypertensives later on.
So if you were not adherent to your anti-hypertensive therapy, you were more likely to be not adherent to your anti-hypertensive therapy later on. And that was true of all racial and ethnic groups. So, I would say this led us to a lot of work focusing on medication adherence.
And I want to pause for a minute just to say that I don't think medication adherence is a panacea. I don't think if we fix medication adherence that all the other patient problems with disparities will go away. However, I like it. And the reason I think adherence as something to focus on is that it's a common potentially modifiable determinant across chronic conditions. So instead of saying okay, we're going to work on this disease silo and see what's affecting disparities here, and then we're going to go over there and do something else, it's something that's pervasive across the system. It doesn't matter which disease or problems you have, it seems to bother everybody. And so it gives us a nice starting place to say looking at the whole patient, and many of these patients do have chronic conditions, more than one, what are some of the things that we can focus on, and medication adherence might be one of those targets. It's also very easily monitored and targeted. We know how much they're taking. We can look, we can see, right? It's a very observable thing.
And finally, there's a strong evidence base for telling us whether or not these medications are likely to work for them and who should be on what and at what dose. Right? There's a lot of strong evidence around these issues. So we should be able to utilize that. Within that context, there are a lot of different factors that might influence why we're seeing these differences in medication adherence across racial and ethnic groups and across conditions, and we think they include patient as well as patient/provider dynamics and health systems factors. And these might be the opportunities for intervention here with respect to improving and moving us towards equitable health care outcomes. Some of the things I'm particularly excited about on the patient level that I think are interesting and that we're trying to test out in our own health care system is -- some of it is like motivational interviewing. And it may be most effective when it's in a clinic system by professional trained -- professionally trained and motivational interviewing.
However, one of the issues with motivational interviewing is that it's not clear who needs it and where it's going to have the most bang for the buck, right? When we talk with the health care system about motivation interviewing for medication adherence, they're like oh, gosh, hey now, who do we choose for this? Because this is a lot, you know, this is a lot for us to take on. So, to the extent that we as researchers could help them do a better job of segmenting the population and targeting who would be most appropriate for motivational interviewing we might be better off. Furthermore, we can look at things like values affirmation. So this is something that is coming from the educational literature and research where they found that a simple values affirmation exercise, then someone goes through that prior to a test for example, they tend to test better.
Similarly, the idea here is that before you go into your provider, if you have trouble communicating with your provider, do this values affirmation exercise with them beforehand, which is basically asking about what do you value, what do you care about, et cetera? It has nothing to do with your health necessarily, or your health care, but it has more to do with your own personal values. And then having them go see the physician may actually increase the lines of communication around medication adherence and around control. And so we're doing -- we're trying to do an intervention in this area but there's really strong evidence from the education literature about this.
One of the interesting things about motivational interviewing versus values affirmation is motivational interviewing is a patient-centric intervention, but that's not race or ethnicity specific. Okay it's not about cultural tailoring, necessarily. It really is about the individual patient, what's going to work best for them. Values affirmation speaks directly to racial and ethnic differences in experience that may result in differences in how they experience the world, how they experienced their conversations with their provider. And so I was trying to directly address those stereotypes and those issues that are underlying subconscious bias -- whatever you want to call it, that may be influencing the patient/provider dynamic. These are very different approaches but they both have some promise in terms of helping us to understand better what might be going on in terms of medication adherence.
Another thing that I'm particularly excited about is the idea of conjoint analysis, which really combines these two topics to say we want to find out from patients themselves what are their preferences with regard to treatments? How do they feel about side effects? How do they feel about their different medication choices? And asking these things overtly because we know patients are making choices. In the past I think we sort of keep giving them medication and sort of hoping that they'll take it. This really says you know what? Patients are making decisions with or without us. How about we try to find a way to solicit those preferences early on and then as much we can, tailor treatment, tailor regiments to those preferences? And we also have the opportunity to potentially uncover differences and beliefs across racial ethnic groups that would be underlying some of these adherence behaviors.
So for example, John Pate [phonetic sp] and others have done a lot of work showing that, for example, African-Americans tend to have more negative attitudes towards medicines. More likely they think that they might be addictive. More likely they think that they're not going to be helpful. And so to the extent that those things may be true, culturally there may be something going on. This is an effort to sort of drive -- to understand if it's one of those factors that are driving the behavior and then have a conversation about it and/or target therapies to more better fit what the patient needs. At the provider level, there's less evidence about things we could do at the provider level that are in disparities reduction per se. The cultural competency literature isn't as strong as we'd like to see in terms of providing that really strong evidence of what works. We do know that in general, feedback mechanisms are probably more effective than simple reminders. So having something just pop up on the EMR for them to remind them to do something is not only an annoyance, but often it doesn't really generate changes in behavior.
However, feeding back information to providers about what's going on with their individual patients and how that relates to the broader practice, does seem to be quite effective. So to the extent that we can actually leverage that to look at racial and ethnic disparities in how patients are experiencing their care, we may be able to get closer to behavior change that would lead us to more equitable care. One important thing, strategies that are aimed at only at the provider and only at the patient may be less effective than strategies that were aimed at both. So if we're interviewing at the patient level through motivational interviewing or values affirmation what have you, also interviewing at the provider level; providing the feedback about information about their patient panel, how they're doing and what's going on in sort of, this academic detailing cycle, doing both together may be more effective than doing either in isolation.
Finally, there are things at the health system level that may make a difference. Things like copayments. There's a lot of talk right now about co-pay reduction. If we just reduce co-pays will that do something? And so we think that there's hope that that co-pay reduction will likely improve or increase medication use, but that we might need to do something else to reduce disparities because of the data that I showed you earlier. Simply reducing the co-pay may not be enough. We may have to have concurrent strategies that are aimed at addressing the stigma or what have you that are associated with lower rates of usage among those populations for whom cost is not the primary barrier, right? It's like yes, okay, cost might be a convenient reason why I'm not taking this, but the truth is I don't want to be on this medication in the first place. So how do we combine strategies so that we reduce the costs but also talk with the patients about what their concerns are so that we can hopefully work with them together to get to where we need to be. Furthermore, opt-out strategies; when we know something works. With our setting we found that mail-order pharmacy is highly associated with medication adherence and it's partly because they often get a financial benefit of doing it instead of paying for three months of medication they only pay for two months of medication. But it also automates the process to an extent where you're getting multiple medications at once so you don't have to come back as frequently for refills. But African-Americans, for example, in our setting are less likely to sign up for it even when it's financially beneficial to them. And when you talk to them they start talking about their concerns about it. Well, I don't know. You have to pay up front. You have to use a credit card to pay up front. What if someone wants to drop something off at my house? How can I be sure that it's going to be secure on my porch? Those kinds of things [unintelligible] are talking about and they haven't quite found [unintelligible] even know about it.
So thinking about are there ways that we can have opt-out strategies where we automatically sign people up. Oh you have diabetes, here's your new medication. By the way, I've signed you up for mail-order pharmacy, rather than relying on the patient to find out about it and then sign up for it on their own. Those might be some strategies we should start looking into. Furthermore, workforce diversity may also be important. This is not my area of research, but certainly some others in our field have looked at race and language concordance, where they found that for African-Americans race concordance might be important. They've also found that language concordance, might be particularly important for Latinos in terms of improving adherence, in this case to cardiovascular medications.
So here's the rub. So I've talked about all of these things that we should be doing et cetera, and that health system should be doing based on the literature today, but in the reality, race and ethnicity are actually really poor predictors of future adherence behaviors. What do I mean by that?
So we know that there's a strong association between the two, but if you were to take your patient population and isolate all the patients of particular race ethnicity and say okay, they're going to be non-adherent, we need to focus on them, you won't be so successful. I mean, the reason is there's a lot more variation within than there is across these racial ethnic groups in terms of medication adherence, right? So I would vote that we should probably move away from a little bit of this idea of race/ethnicity focused approaches, and really think about patient-centric approaches. The patient is a whole person where race ethnicity is part of it, but certainly not the whole story and that I think has potential to address both individual and sub-cultural factors that are going on. We also need more sophisticated risk segmentation strategies. So how are health plans supposed to even identify these people? How are health systems supposed to be able to identify them? Again, identifying them based on race ethnicity is probably not a good idea. However, to the extent that we can tap into those things that are correlated with race ethnicity, health literacy, low English language proficiency, patient/provider communication as reported by patients; those types of things might be really good harbingers of poor adherence behavior into future and to the extent that we can target those things we might be able to find patients much quicker than if we just rely on race/ethnicity as our indicators for who needs help in terms of medication adherence.
So finally, I want to open this up for broader discussion, but just to close out: so we've been working on these issues since I started at Kaiser Permanente in 2008. We've been trying to figure out how do we get from knowing we have disparities to do something about them given all of this information that we've just shown you. And we've shown this to the health plan in the health care system and so they're also aware of all of these research findings. And we thought well, you know, we're in the perfect place to do this. We have data, we have scientists who are willing to do the work. We have these partnerships between patients and clinicians and researchers where we can really sort of kind of use our EMR and use the email and use kp.org and all of these different mechanisms for communicating with one another. We can mess with the incentives. So we can mess with the incentives providers. We can also reduce or increase co-pays for patients and then we also have leadership support, you know, so how could we possibly go wrong? We're at the prime to do this. We're at the perfect place to do this work, and this is what we saw in front of us know we started this process. We literally got into a room much like this one and we said here's the problem. This is what we're going to do and this is what we saw, right?
We saw sort of the summit here as equitable care outcomes. That's what we wanted to get to, but we didn't know where we were on this mountain. We didn't know what the best route was to get from point A to where we wanted to go and so it was a very intimidating initial process and people we're like -- the clinicians and the health plan leaders we're telling us we are overwhelmed. You're telling us to address something that is historical; something that has very even little even to do with us. How are we supposed to make an impact? And so, what we started was sort of with this sort of what I'm calling sort of, global positioning for equitable health care outcomes. We said that first of all we need to know where we are. Where are we on that edifice? Where do we start? And so the first thing is identify where we're at. And so we used the EHR to identify where there were these racial and ethnic differences in the metrics that we commonly use every day? Where are they? Where are the differences? Then we decided okay we need a common destination. We need to decide where on this mountain are we comfortable with landing and saying okay we'll be successful if we get where?
So we identified, you know, this is made up right now, but we're sort of for two areas for this colorectal cancer and hypertension control, we said we want to reduce the gap by X percent in a certain number of months and this is how we'll know we're making progress towards those goals. And all of this again, was based on the evidence that we'd gathered today. And then finally we created a map. We said okay, how do we get there? How do we make sure the way we started this process? And we literally just started meeting with one another with the idea that the first few meetings we're know that get anywhere, but eventually we will. We literally started meeting on a monthly basis, every couple of months, between physicians, quality leaders and researchers sitting in a room hashing out how do we get to where we want to be? And through this process, I think we're succeeding in terms of our general strategy, which is that researchers -- we have to eat, right? So we can't just stop doing research and all lead to quality improvement, right? So we're still doing our RO1 applications, but we're doing them starting with the clinical question, right? So instead of before we were sitting at our desks again, what I think is interesting? What's based on my last research grant? What should I write next? We went to the clinicians and we said okay here's all the stuff that we've done to date. What about this is useful to you? What is not useful and what's the next place that we should go together?
So they helped us define what they thought was interesting research -- a clinical question. We helped them turn that into a research question and then those things go to NIMH and NIDK an PCORI and all these other places to try to get our core funding base. Simultaneously, because the clinicians are telling us, look you guys have five years of funding that's great, I can't wait five years to find the answers to some of these problems. So we also started smaller RFAs internally; smaller research grants that are $50,000, $100,000, but they all have an end date. They're all usually no more than two years, but usually just one year. Some are even six months long, where we say in six months here are the deliverables. Here's what we want to be able to say and they're mostly about the feasibility. How is it that we can get some of these sort of, very innovative, very interesting interventions to work in practice? What are the barriers? What do the pharmacists need? What do the MAs need? What do the physicians need from us? Figuring out the strategies and figuring out sort of what's feasible to do in practice, and then testing them out in small places.
We have one right now in Richmond where we're basically saying here's data, here's what we think you should do; working with pharmacists to say okay, I'm willing to do that and then they're implementing it. And the idea is not to change the world with that, but to see is there an appetite for this? Is there something that's potentially sustainable so that if our grant on values affirmation in that same area hits, then they'll have more to buy in for; we'll have the tools ready for them to use to say okay, that went well, let's add this component of this values affirmation to get the patient side of things if you're going to focus on the physicians side, for example. So there's a lot of different things that we can do together that we could not do before when we were working on our own. And this is just basically some of the various strategies that we were playing with; these large pragmatic trials were new for us but they're very exciting.
Of course natural experiment is another way to get at this. If we know what's going on in the health care system we can evaluate it in real time and get the information back to them sooner. Mixed methods approaches, of course; and then of course validation studies to say okay how can we use some of these new data sources for research purposes in a way that feeds back into the health care system? So with all of that, sort of what I wanted to close with is again, that health care access is necessary but not sufficient for what we want to do and that we do need to focus on factors that are potentially modifiable health system intervention. There's promising strategies that are emerging and a very exciting and sometimes would get them from non-health-related like this educational values affirmation stuff that really does come from education has not been applied as much in the health care arena. And then finally, and I can't emphasize this enough, these collaborations between researchers and health care systems are desperately needed, and they do provide this opportunity for us to come together and say how can we facilitate the translation of these research findings into practice in a clinically-meaningful way but they still allow us as investigators from [unintelligible] our scientific integrity and survive in the world that we live in? And it's been really exciting and I think one of the best things about it is that I think, as researchers we have more accountability than we've ever had with the work that we're doing because it's very hard to not produce when a clinician is calling you and saying I'm meeting with the board tomorrow. They want to know how it's going, you know, where are we at? It's a very different level of intensity than I think you could have with our normal grant process. And so I think both are necessary, but it certainly does sort of elevate the bar for us, and it's just an exciting field to work in. So thank you so much for your time and I'd like to open it up for questions okay?
Male Speaker:
So we are very invested in how learning health care systems can completely change the paradigm around research where we go from research to practice and we have hand offs and this sort of thing, to what I think you traced. You start with the stakeholders questions, their problems you get those worked on by researchers; you're actually going to get their buy-in and hopefully they'll take up whatever it is. So you and I were talking about what does it concretely mean, you know, because we're in alignment on it, but does it mean we solicit ideas from your executives, your people who, you know, re-run your clinical operations, we limit their researcher's questions to only those that -- I mean, how do we concretely do this?
Alyce Adams:
[unintelligible] more successful than others. So when I talked about earlier when we tried to ask the health plan leaders, the CEOs, in other words and the chiefs, you know, the pie in the sky what would you want to know, it didn't work so well. In part because [unintelligible] they were [unintelligible] researchable. They might be important to them but they weren't really sort of in the form that was readily researchable. The other issue was it just wasn't on top of their priority. I think it felt a little bit too blue sky for them. And so we didn't get the participation that I think we would've liked. We also did these -- created these RFA mechanisms that I told you about. Internally we said here are some areas that are important to the clinician group and they came up with a list and they were very general areas and literally it might be improve depression care; so very generic. But it's a specific pot of money and in that description of the proposal you have to answer questions like at the end of this, what will we know that we can implement tomorrow? You know, how is this going to help the problems faced by the health system today? Who are your clinical partners? It's a very specifically oriented towards entering the clinical question. And so that's one way we've gotten it going.
The other way quite frankly, is just relationship-building. It's nothing new. It's literally just being in the room together trusting one another, getting to know each other so that the clinicians feel comfortable coming in and saying well, I had a really bad day yesterday, here's what happened. I'm frustrated because the evidence doesn't support what I want to do but I just don't know how to get there from here. We don't -- there is no obvious clinical answer to this question. And so from there we start flushing it out and saying okay is this a researchable question? Is this one patient? Is this all of your patients? What's the pattern? Then we take the data and we look at the data that say, you know, we were looking at your question and here's some of the patterns that were starting to see. Is this consistent with what you're feeling? And we literally work through it together, but it's a relationship and it's an ongoing one.
So it's not enough to for us to sit together in a room once every six months and talk to each other. We literally meet every other month and then we're on the phone with each other all the time and sometimes quite frankly, from the researcher's perspective, it does take a researcher who is okay with community service. And by that I mean sometimes the clinicians just need you to show up somewhere and give a talk, right? And I do it because it ultimately I'm reliant on them to help me find those important questions. So I show up when they ask me to show up and they're very respectful of my time, but I do it. But through that they became to trust me and say okay, I can tell her my woes, I can work through this with her and she's going to help me fix it or at least move us closer to where we want to be. So it's a combination of things. I don't think there's a single strategy, but I do think ultimately it comes down to relationship-building and then finding those clinicians that see the spark, right, of research and they appreciate it. You start talking about research and their eyes light up. Not because they want to be researchers, but because they see an opportunity. They see oh this is something that I'm missing, right? And that's what you want to see. That's sort of, the energy that you need to get from that collaborator in order to sense that this is worth investing in and this is worth us spending some time figuring out some real-life research questions that we can actually develop and answer over time.
Female Speaker:
Thank you. That was a great talk. So I want to follow on a little bit of what Phil was saying and just a practicality. So for example, what's really exciting is that you have the self-contained system, right? You can do the individual level; you can do the provider level. So let's say that you decided, you know, there is not as much evidence around the provider level interventions for example, and you decided, you know, this is where we need to try to do something. How does that work and then what happens afterwards? I mean, how do you make it happen? And does it happen in one section of the organization? Or does everyone then have to -- can you just talk a bit more about -
Alyce Adams:
Yes, we actually have tried to encourage our organization to think a little bit more in terms of pilots. You know often in the past whenever I've worked with health plans there seems to be this tendency to say okay we belong -- so the "New York Times" had an article on X, we're going to employ that right now, whether, it's, you know, [unintelligible] or whatever it is. Whatever it is sort of the thing of the moment is, and so we're just going to implement it system-wide, right? And I don't mean to sound so pejorative about it but that's part of it. And what we've said is you know what, you don't know yet whether or not this is going to work for you, so start small.
So for example, the one that we did, this project that we have right now which is about physician prescribing of diuretics is really physician-focused, to say on the on their right medication? Are they taking the right dose of it? It's very simplistic, right? But it's something that we haven't looked at before and it's not something that they've looked at before. So we said okay when you decide how you're going to intervene with these different patients and what they need, you have the screen, it's called a prompt, and it has in specific HEDA scores basically that you're looking for each patient, and it redlines those that they need to focus on. We said okay, what color are you not using? And they said yellow. I said okay, from now on you're going to have yellow is the color that means they need diuretics. They need to be on thiazide diuretics. We're going to create a new column in Prompt so that the data is there for -- we're going to give you the algorithm. We're going to show you how to run it. But from now on it's going to show up in yellow. So if they need to increase the dose, what have you, that's what's going to happen, and that's what they look at now and it's sort of part of it their own automated process and we did it in one place, Richmond, all right? We're not even done evaluating it yet but already again, they're implementing it potentially across the system. Why? Not because it's successful in terms of improving patient outcomes and reducing disparities, but because it was so easy to do, right?
It was easy for the clinicians to do and I think that's part of it, a lot, particularly if you're working in collaboration with the health care system that you're not really completely fully a part of, it's convincing them this is something that you already do, we're tweaking it a little bit. We're just adding to it. We're given you something that's when to help you make better decisions as opposed to we're going to disrupt your life and change everything you do and the way that you do it. So anything that you can do that doesn't mess with their workflow at all, but it really sort of uses existing strategies and existing workflow, and fit that in, you're going to have better success than if you're doing something outside. But yes, starting small; starting with one; getting one facility and they didn't want to do it at first, but we kept on them, and eventually they agreed and now they are talking about what a great thing it is and they feel like special because they have it, right? So a part of it is that just that working on small tests of change.
Female Speaker:
Thank you very much for your talk. I wanted to hear more about the vision that you had on reducing the gaps by 5 percent, and the question that I have is for whom and using what kinds of interventions? And I mean it's something that we think a lot about in our office where disparities in global mental health, and does identifying those people, especially, you know, since you mentioned that you're moving away from race/ethnicity to more patient-centered care, and that could be a combination of various things. So I wanted to hear your thoughts on that.
Alyce Adams:
Yes, I mean there's a lot in the question. So in terms of the way that we had done it is we started off with the literature and what we know and based on our own research as well as research of others with respect to where are the gaps, as well as what are people finding to be useful in terms of interventions? We then also had the clinical guidelines that we use to say okay, we know what sort of, the evidence stands, here's what the clinical guidelines says that sort of goes along with that and then we said where are the modifiable banks? What are the things that we can do something about? So with this issue with race/ethnicity, like I said, this was way too broad and it doesn't really tell you a lot about what's going on with any particular individual. So we said okay, what are those things that sort of explain those racial/ethnic differences? And things that we came up with were things like health literacy; [unintelligible] were a lot of that.
Often health literacy sometimes eliminates the disparity when you control for it. It's a huge component. Things like trouble paying for medication. People who say that they have really poor communication with their providers often have poor medication adherence. And those were all things that we measure all the time. We're constantly asking our patients whether communication was like. We ask it all the time, right? But we don't necessarily look at it in this systematic way and use it for segmentations, that was part of it, but it was a very long process. I don't mean to make it sound like it to one meeting and we were done. It took some of time that I there in 2008, it was 2010 before we would get all the regions in the same room and to agree to that goal. It took a good two years and it took a lot of dog and pony shows, and it took taking that they took around to different places to all of the different quality leaders around the different regions and saying here's what we're seeing.
This is why we think no the data aren't bad. You know, know that there's -- the data are really true. It's not just you, it's everybody, but we need to work together on this and yes, there's something we can do about it. So having that big meeting in 2010 and from there we didn't dictate specific interventions that they were supposed to do. We said really that's up to the local groups. That's at the physician office level. That's at a medical office level, the facility level. That's where that clinical question needs to happen. That's where they need to start designing sort of what is the question that we want to be able to answer. We gave them a lot of tools. We gave them a lot of information about what had been tested before. It was really up to them to figure out the context of their own situation and what best fit them and then they started again, these small tests of change.
Can I say that this is like a big success yet? No, it's still a work in progress. We're still working through it. But I have to tell you I was thrilled that we were able to sit in a meeting and have all of our quality leaders across the regions sit there and commit to doing something about this over the next however many years we said we would do it. I mean, that was -- just getting them together in a room was a huge step, and getting them to commit at that was equally exciting. So it takes time sometimes and sometimes there will be delays. There were some regions that said we're going to let you guys go ahead and then we'll catch up later, but they did. Eventually they caught up later, like our own region at first sort of, eschewed the whole process and said we're going to do our own thing, just last year came back to me and said, you know, could you do what you did with the whole program nationwide with us? Just with us? And then we did. We held another meeting. We had another symposium. We showed them the data again and then we had like an all-day meeting where they brought their -- they paid their clinicians to come to this meeting over lunch, over the rest of the afternoon to sort of hash out where we thought the rubber hit the road. And that's what started these frequent meetings. That's what started this -- sort of these ongoing communications with our clinicians and operation leader partners. But it's taken some time. It's not something that could be done overnight I don't think. Thank you so much for your time. I just -- obviously NIMH has been really helpful with us. These are just a smattering of some of the grants that myself and my colleagues have received that have supported this work.
So I just wanted to acknowledge that and the great support we received from NIMH and others in this work, as well as a number of investors -- see there's not everybody, but these are just some of the people I work with most closely on these issues. On the right-hand side you can see the long list of health systems leaders that have been in it with us from the very beginning and really leading the fight, and it's just been a joy to work with them as well as our scientific colleagues. So thank you so much.
Dr. Francis Collins: When I became director of the NIH five years ago I knew it would be an exciting ride, I knew there would be advances happening in many different areas of this wonderful landscape that I have the chance to watch over as NIH director that represents biomedical research. I frankly did not know that we would be at this point of announcing today the first launch of a most impressive series of projects aiming at understanding how the circuits of the human brain work. We are seriously tackling an understanding of the most complicated biological structure in the known universe. Because we are announcing today this first wave of NIH investments in support of the project called BRAIN, which of course is an acronym- we are the government. BRAIN stands for brain research through advancing innovative neurotechnologies. Stephen Colbert made fun of it. He says you're not supposed to have the word "brain" in the explanation of your acronym- BRAIN- but we're sticking with it because we think it says what this about. And notice the title, advancing innovative neurotechnologies, most of what you will see in this remarkable awards set today of these grant awards- 58 of them- are technological advances…the development of really exciting new tools to be able to understand how these circuits work. These awards will support more than 100 investigators who are going to develop transformative technologies that will accelerate fundamental understanding of the brain…and I think you will see that they are technologically really quite challenging and inspiring and they are across many different areas and many different organisms with some of them focuses on model organisms and some on the human brain itself. They focus on classifying on the myriad of cell types in the brain…we need to know those… producing tools and techniques for analyzing brain cells and circuits, creating next generation human brain imaging technology, developing methods for large scale recordings of brain activity and integrating experiments with theories and models to understand the functions of specific brain circuits. These are all pretty challenging but among them are the development, for instance, of a wearable PET scanner for measuring brain activity during daily activities. The investigator says he would like to have a PET scanner that could access what's happening in the brain during the proverbial walk in the park. And of course, these days, we are getting increasingly good at measuring brain activity but usually with people who are lying quite still in the midst of a major piece of equipment. The idea of making this ambulatory… and there's a similar kind of approach being proposed for MRI. Another one uses lasers to noninvasively turn hundreds of specific cells on or off anywhere in the brain. Another is developing next generation microelectrodes that can not only measure but deliver small doses of drugs and record activity from thousands of individual neurons for months at a time. And there's also an exciting one which allows real time movements of neurotransmitters to be observed … neurotransmitters involved in disorders like Alzheimer's, Parkinson's, schizophrenia and depression. So, I think its fair to say since the President's announcement a little over a year and a half ago NIH has made tremendous strides to take what is an audacious initiative and put a vision and a framework to help us achieve that. At NIH we agree that four and a half billion dollars is a realistic estimate of what will be required for this kind of a moonshot. And while that's a large investment still keep that in context that even at its proposed peak the BRAIN Initiative each year would still only comprise approximately ten percent of what NIH is investing in neuroscience which is about which is about five and a half billion dollars each year. But make no mistake, it's certainly important to maintain that broader neuroscience investment. The BRAIN Initiative must be an enabler and not a competitor for neuroscience funding at NIH. But it will be worth it. Some of the projects here have the ability to transform how we study the brain and new technologies and industries will likely be spawned. Possibly most importantly, the new insight we will ultimately gain from utilizing these new tools and technologies will enable researchers to develop new treatments and even cures discovered for devastating disorders and diseases of the brain and nervous system. While the BRAIN Initiative is a basic science effort to build a foundation of understanding in how the brain works, every disease research that we support will build upon this to try to understand and apply that understanding to better diagnosis and treatment. Just one example I mentioned a minute ago about the ability to track real time movements of neurotransmitters involved in disease disorders can certainly point to that pathway. So this is certainly a bold science initiative. These initial awards mark the first step in ambitious journey. So, we are taking on, with this launch, an amazing journey. We have called this a moonshot. For me as somebody who had the privilege of leading the human genome project this sort of has the same feel as October 1990 when the first genome centers were announced. We knew at that point we were going down a road that was going to be uncertain and needed a lot of technology developments and ultimately it turned out really well. I'm confident this one will as well even though none of us can quite predict the twists and turns in this exciting area of scientific research.
Dr. Thomas Insel: In spite of this being a celebration of all these new awards you hear all of us being very excited, the fact is we're all incredibly humble right now. We realize that relative to what we know about the heart, the kidney and the liver we don't even have a parts list for the brain. We don't know all the different cell types, we don't know where all the salient circuits are and even exactly how to define a circuit. So, as Cory said this is really a time of discovery so we'd love to sort of imagine where we'll be in a decade. But the reality is that it will probably be, wherever we are in a decade, it will probably be much more extraordinary than anything we can imagine right now. And we want to be open to that.
Dr. Francis Collins: We funded slightly less than ten percent of the applications. So this was a very rigorous and tough competition. And frankly, we probably, once again, left some really good science on the table, because of the inability to do more than we did. As you heard, we started at 40 and we bumped that up to 46. So that was about as far as we could go, with the current funding climate.
When the President announced this, in April 2013, part of that was to put forward a proposal that the various agencies involved would identify 110 million dollars to spend in FY14. Our part of that was 40 and we took that with great seriousness, because we were very excited about this. As a result, as Congressional appropriations process played out, there were funds specifically targeted in the direction of the BRAIN Initiative. But also some of the NIH Institutes that are part of our neuroscience group decided this was a high priority and they would basically identify additional funds to put into the BRAIN Initiative, even if it meant squeezing other parts of the agenda a little bit. As a result, we're able to put together this package of 46 million dollars. Again, I with it could have been more, but that's a chronic statement, I'm afraid, about the status of NIH research support since... Maggie, as you know, we've lost about 23 percent of our purchasing power for medical research over the last ten years. And that applies to cancer and diabetes and heart disease, rare diseases, common diseases – and neuroscience.
Dr. Tom Insel: There's a very proximal outcome that we're already very conscious of. And that was, when we set this up, as Cori talked about, the hope was that this was not really going be only for the "usual suspects" in the NIH pipeline. That we'd be reaching out to engineers and computational scientists – and people from very different fields. A lot of people who might be doing nanotechnology for electrode fabrication. People who maybe never really worked in neuroscience. So Story and I were thinking about this from the get-go that one of the most immediate outcomes for us is if we looked at the funding plan and we didn't recognize a lot of the names, that was good. And, in fact, that's very much the case. Either we may recognize one member of a team, but often what you have here are people who are not the usual suspects and are coming from other fields, maybe joining up with a neuroscientist. But this is, for us, very exciting as a first accomplishment, first measure of outcome. This is just what we wanted to see.
Cori Bargmann: So what the brain initiative is doing is its adding on to the valuable disease focus of the NIH to give a bigger emphasis on fundamental knowledge about the brain. So that instead of just studying the brain one disease at a time – as important as that is – the NIH will support a sustained effort to examine the whole system and the features that emerge from the brain as a whole, because our brains are not individual little parts. We have a coherent and unified perception of the world that results from all of those parts working together. So what the brain initiative is trying to do, and what the science is doing, is to build on the knowledge of the past 50 years, to unify dispersed kinds of knowledge and meet in the middle – at the level of the circuits and networks of nerve cells of nerve cells that transmit information through the brain. So on the one hand, we know a lot about molecules and individual neurons at a microscopic level. On the other hand, we know about brain functions like memory and emotion at a higher cognitive level. And the BRAIN Initiative wants to bring those things in the middle, to the level of groups of interacting neurons, interacting brain regions – the incredible flow of information through those brain regions that allows brain functions to emerge.
Now doing that has involved a whole set of changes in the way that neuroscience has to be done. It can't be business as usual to do this kind of project. And there's been a stimulation of a new culture of collaboration, where groups of people will be working together. And the NIH BRAIN Initiative involves a lot of collaborative groups that include both traditional biologists and people like physicists and engineers, working together to solve problems. So there are different kinds of expertise. There's more of a sense of cooperation. And there's a big emphasis on sharing both new technologies and new results as quickly as possible, to advance the field and to accelerate discoveries. And that's a new thing for the field that is also very exciting to see take shape. And it's been great that the NIH has been willing to look out and not just in to develop a scientific vision and collaboration with the scientific community. And then, once that vision was developed to really shape it into a set of specific goals – but then not impose those from the top but just to open the doors to let the best ideas emerge in a bottom-up, competitive way. To just let the very best ideas win. And you can see the results of that in the projects that are now being funded, because they are exciting and they're imaginative and they're very diverse. And they're diverse in the kinds of people who are involved. They include ….Some of the project leaders of these flagship projects are people who are just a couple of years after their Ph.D.s – young scientists starting out with a whole new approach to a problem. And some of them are the distinguished leaders of the field who've been in it for a long time. And many of these come from people who've changed fields, who haven't really been neuroscientists before. And so, I think that the idea of starting something to promote interest in the field has been very successful, looking at this first round of grants.
So, as Francis mentioned, the first goal of the BRAIN Initiative is really to stimulate technology. And there are all kinds of technology, I would say. Advances in optics and microscopy, driven by physicists. Advances in recording, driven by engineers. Real molecular biology tool kits, where the power of molecular genetics is being brought to the brain in a more sophisticated way. There are new ways of observing activity in the brain. There are new approaches to the human brain, which are going to be so important for understanding uniquely human abilities and human brain disorders.
I myself, as a scientist, am most excited about some of the first visions of science that are being explored here. There projects here to explore deep parts of the brain that are effectively terra incognita – that are crucial however for processes like action and emotion and motivation, that we have not been able to study in the deep brain before. And at the same time, there are parts of the brain that are some of the highest parts of the brain – involved in complex fluid operations, like working memory, that are going to be addressed in detail.
So, in summary: Just to say this is the first step in a long-term commitment. It's been exciting to watch the commitment develop. It's exciting to see that this will happen. It's going to take much more than one year and one set of grants. The real cracking of scientific problems of importance is something that takes ten years, at least, not really one. And, in fact, we may still be studying the brain a hundred years from now – but with a new kind of understanding. I think we're all excited and impatient to use the new tools that are emerging for studying new problems and how the brain works. It's a new era of exploration of inner space instead of outer space.
DR. THOMAS INSEL: The Follow That Cell Challenge is an exciting new initiative from the NIH Common Fund. This is part of the Single Cell Analysis Program, which will help us understand cells far more completely. As you know, the NIH has lots of grants supporting studies on populations of cells, watching cells, growing cells, microscopic imaging – a variety of different techniques. But here we're looking for something quite different. We're looking for new ways to measure how individual cells change over time. And what that can tell us about the health of a tissue or an organ system. This led us to think about what we as an agency could do differently to get new ideas into the mix. What we're trying to do here is really different. Instead of just funding a few grants, the NIH decided to offer a prize to the individual or the team that comes up with the most creative way measure changes in individual cells over time. We want new things – maybe even ideas that seem a little off the wall. And hope this challenge will stimulate those ideas from scientists – including scientists with very different backgrounds. We are looking for engineers, materials scientists, chemists -- partnering with cell biologists and disease specialists to help solve this challenge. Phase 1 of the challenge is theoretical, the idea phase. Finalists will be selected from this phase to move on to Phase 2, which will allow solvers to put their idea into practice. Phase 2 will be judged on how well the individual or team executed their plan and the quality of the data produced. Part of what's different here for the NIH is that no money is awarded until and unless a solution is deemed to be a "winner". There is still time to register and submit a solution—the deadline is December 15th, 2014. You can register for the Follow That Cell challenge at the Innocentive website. It's important that potential solvers read the announcement in the Federal Register closely to understand the details of the challenge. There's a lot of fine print. We look forward to seeing how this pans out and we hope we see innovative new approaches that open new doors for basic biology and disease related research.
Submit your Challenge via InnoCentive
NIH Single Cell Analysis Program
Federal Register Notice for eligibility criteria
Deadline for submissions - December 15, 2014
National Institute of General Medical Sciences - NIH
American Society for Cell Biology
Microglia cell - Miles Herkenham, NIMH, NIH
Purkinje cells - Yinghua Ma and Timothy Vartanian, Cornell University
Dividing pig cell - Nasser Rusan, NHLBI, NIH
Layers of nerve cells in retina - Wei Li, NEI, NIH
Human liver cell - Donna Beer Stolz, U. of Pittsburgh
Human cancer cell - Yi Wu, U. of North Carolina
Developing nerve cells - Torsten Wittmann, U. of California, San Francisco
Cells lining the trachea - Eva Mutunga, Kate Klein U. District of Columbia, National Institute of Standards
Cerebellum - Thomas Deerinck, National Center for Microscopy and Imaging Research, U California, San Diego
HIV infecting a human cell - Seth Pincus, Elizabeth Fischer, Austin Athman, NIAID, NIH
Fever bacteria in an infected cell - Robert Heinzen, Elizabeth Fischer, Anita Mora, NIAID, NIH
Vesicles (yellow) - Tatyana Svitkina, U. of Pennsylvania
The lab is located in the new Porter Neuroscience Center, which was formally dedicated in Spring, 2014. This state-of-the art resource is uniquely designed to foster collaboration on brain-related intramural studies across 10 NIH Institutes and Centers. After graduating, Heather returned to NIH as a post-baccalaureate IRTA fellow, in the Section on Bipolar Spectrum Disorders of the NIMH Emotion and Development Branch, which is using neuroimaging to study brain circuitry in children with bipolar disorder and severe, impairing irritability.
For more information:
NIMH Science Update:
How Might New Neurons Buffer Against Stress
Maturation and function of new neurons in the adult hippocampus
Heather Cameron, Ph.D., chief NIMH Unit on Neuroplasticity
Pediatric Bipolar Disorder, Irritability and New Approaches to Psychiatric Diagnosis
Ellen Leibenluft, M.D., chief, NIMH Section on Bipolar Spectrum Disorders
Porter Building Dedication, March 31, 2014
NIH Catalyst: Porter Neuroscience Research Center
Jay Giedd, M.D: Twins are the best way to address nature/nurture questions. Identical twins, or monozygotic, share almost one hundred percent of their DNA. And fraternal twins, or dizygotic, share out about fifty percent. So by seeing how much more alike the identical twins are than non-identical, we can get a sense for how much the DNA matters for brain or behavior or all kinds of different variables. Of course, its not nature versus nurture. Its nature and nurture -- and the interaction between the two that's really the key. These days that's usually called G by E interactions -- G for genes and E for environment. But what this paper demonstrates is that we need to add a third component to the G and the E. And that third component is age. And what that means is that in order to understand the effect of a particular gene in a particular environment, we also need to know where that individual is in the course of their development. So it may not seem that surprising land that age would matter, but to actually identify the specific facts and figures about how this age by Jean by environment interaction (works) hasn't been all that easy, partly because we have to follow people over time as they go from a child to an adolescent to a young adult. And in and this case, the people have been identical or non-identical twins, but also their brothers and sisters. Genetically, they also I'll share fifty percent their genes. And over the past decade we followed about eight hundred people, having them come to the NIH at about two year intervals where we did a scan of their brain. We see how they're doing in school, in life, their behavior, their emotions, their cognition. And we see how these factors change over the course of development. The main thing that we found was that it's a moving target. So which parts of the brain are more or less heritable changes a lot as you go from a baby to it a child to a teenager to an adult. And so what we've been able to do with these movies that you're seeing is to actually demonstrate the specifics of these changes. And what we see here are the areas in red other areas in the brain that are most charitable. And what we see is that it's not a one-size-fits-all. That certain parts of the brain become more heritable during adolescence. Other parts are more heritable in your early childhood, others in in middle ages. And why we think this is important is that the same brain areas that are changing in heritability during adolescence are also the parts for the brain that we acquired most recently in our evolutionary history and also they're the parts of the brain that are involved in illnesses that happen during adolescence. This has been one of the big mysteries in psychiatry. Why do things happen when they do? For a genetic illness like schizophrenia, you're born with those genes. You're born with those risks. So why doesn't it manifest when it does? Until late adolescence or young adulthood. This has always been one of the big research questions for us. And now we think we might have some insight into that. Because one way of looking at this is that the reason these brain parts get more heritable during adolescence is because they get expressed then. That if they're not being expressed any younger it doesn't matter if you're identical or non-identical, because those genes aren't doing anything. But whether it's puberty or other unknown timing factors, when these genes then become expressed, those parts for the brain become more heritable. But if this process goes awry, then it also may be why these illnesses are unleashed when they happen. Most illnesses actually manifest during adolescence -- psychosis, bipolar disorder, eating disorders, substance abuse, anxiety, panic attacks. So literally over fifty percent of mental illnesses when they happen occur during this adolescent period. And we're particularly interested in these parts of the brain that become more red during late adolescence, when many of the illnesses are emerging. And they're parts of the brain that we've acquired most recently in our evolutionary history -- so the most difference between us and chimpanzees and bonobos. So its all is converging upon this common story -- the things that take the longest to develop also have genetic factors that impact later and later in life. So the next step for us now will be to really try to explore this link between the illnesses that have their onset during this time and the typical brain changes possibly driven by the same underlying genes. At one age this particular gene might affect this particular brain in this way, and at a different age no effect -- or even an opposite effect. And so I think the whole field will be affected by these sort of findings, in terms of really trying to introduce age into the G by E interaction question.
Thomas Insel, M.D.: The Outreach Partnership Program, for us at NIMH, is really one of the jewels in our crown. The NIMH mission is to support research that improves the understanding of the mental disorders, leading to prevention, recovery and cure. And it's by working with partners, as we do in the Outreach Partnership Program, that we ensure that that particular mission is realized -- not only as an academic pursuit, but it's realized in communities across the country. What's pretty exciting about that is it gives us a chance not only to update people from all these different communities about the science that we're supporting, but it gives us a chance to hear from them about what science will be most important.
Diana Morales: NIMH and the outreach partners are working together to make sure that the public understands that mental disorders really are disorders of the brain. The goal of the Outreach Partnership Program really is to increase the public's access to information about mental health and mental illnesses that's research-based. In that way it helps inform their decisions about the treatment that they receive and also gives them hope about the future – where we're going in our understanding of the diagnosis, treatment, prevention -- and hopefully ultimately a cure -- for mental illnesses. And we do that by supporting 55 nonprofit mental health organizations from around the country. There's an outreach partner in every state, the District of Columbia, and Puerto Rico. And those organizations work with us. We support them to disseminate science and research-based information and to conduct outreach and education in their communities. And also to make the public aware of opportunities to actually participate in research. They really are in every community you can imagine. So they're working in Schools. They're working with parents. They're working with first responders. They work directly with health care providers and mental health providers and clinics and hospitals. They do a lot of direct outreach and educational programs, training sessions. They run support groups, do health fairs. They really reach very deeply into their communities. So they're really focused on making sure that everything that they do in the community has a strong evidence base -- and I look to NIMH for that information. NIMH provides its outreach partners with access to all of our science-based publications and other resources that we have. Every year we bring the outreach partners together for an annual meeting. And during that meeting, one of the things that that they really value is the opportunity to network with each other and learn about what their peers are doing and what they might take back into their communities.
Ann Kirkwood: We have been working on suicide prevention, primarily because our rate of suicide among young people is so high. While nationally it's it certainly high -- it's the third cause of death for 15-24 year-olds. In Idaho, it's the second leading cause of death. When it happens in a small community, there isn't anybody in a small community -- in a rural community -- that isn't impacted. So we've also experienced some suicide clusters. Ready access to the latest scientific treatment information has really been helpful as we provide communities with the information they need for suicide prevention -- but also for response. Particularly to a school suicide, we've been able to pull together best practices for them, so they are assured of doing the right thing after a suicide and can avoid a suicide cluster.
Dan Aune: I think what we count on with NIMH is that high quality research information about where we're going. And it really brings a hopefulness to people that there's really somebody out there who's dedicated to you figuring it out -- finding some answers. And for us to be able to take that information and not only have it is soft ways -- like the website or a handout – but actually to go out and recruit people who may want to do the clinical trials. To go to the state division of mental health and substance abuse and say "hey, you know, this is information you could push on. We want to partner." So it's nice to have that that national partnership -- and especially that direct relatedness to the research. And that somebody could actually say "hey, they're doing something."
Lisa Furst: It's been a tremendous benefit to us. For one thing, we have access to cutting-edge research that is sponsored by NIMH. We're able to distribute that to all the folks in New York City who want to know about mental health. We're able to let folks know what clinical trials are happening and how they might be a part of research if they want to be. We're able to use social media to broadcast the message. And we've even been able to bring in key researchers from NIMH to come to our locality and provide some really terrific cutting-edge information within our community. And I wouldn't have known about that information we wouldn't have had access to those researchers without the partnership.
>>Girl 1: This feels hard. Some parts are pretty dense. I saw brain models, but I never really saw a real brain, except like on the X-ray. I haven't really seen a real brain, so this is like a new experiment for me.
>>Girl 2: I don't really know anything about the brain -- only that it was squishy. I held it and it was kind of gross. I mean, I learned something new. Like, this side of your brain controls this side of your body and this side controls this side of your body. So it's like opposite. So, yes, I found that pretty cool.
>>Andrea: We started the Brain Awareness Week program fourteen years ago. So this is our 14th season of doing Brain Awareness Week. We partner with the Dana Alliance for Brain Initiatives -- and now the Society for Neuroscience -- to put on a program where we highlight the collections of the museum, as well as invite in partners, just like the NIH, who come in and make presentations about the brain for middle school students. There are a couple of favorite events during Brain Awareness Week. Since we've been partnering with NIH for so long, there are a lot of their stations that really are very memorable. We love working with the Drunken Brain tent, and having the students come in and see how neurons fire when we're having normal activity and then when we're inhibited, after we have taken substances into our body, it gives the students a real opportunity to understand how their brains react -- and why it might be a good idea to make other choices as they reach their teenage years and adult years. It's really fun to watch the student actually hold real brains and interact with technology. For example, this year we have the National Institute of Mental Health. And they are letting the students work with circuitry to understand how their nerves are reacting. It sounds like crickets as they actually move their fingers. And it's real exciting to the students to understand how in their own homes they can actually be brain scientists themselves. So really the main goal of our program is to inspire the next generation of neuroscientists. And we hope that this brain awareness week program will help to do that.
>>Phyllis: This year, the National Institute of Mental Health is the lead institute and center at the NIH that's responsible for coordinating. And each year we come here to the museum to just get kids and young people excited about science, excited about the brain.
>>Vinod: Show electrical activity in the brain. How the brain is made up of billions and billions of circuits. And so we're showing them just a simple circuit, which is the spinal activity of controlling their arms and fingers -- and how that relates back to the electricity in their brain. Just tinkered around. In fact, these little set-ups that we're doing for recording today -- I built radio speakers when I was in fifth and sixth grade, and things like that. And I liked to cut things up in science class, and so I always knew I wanted to be a scientist.
>>Leigh: We've come each year. I don't think there's any other place like this where they can see the kinds of things that they can see. And being able to do some hands-on activities that help them relate to what they've learned at school. I think the favorite thing is wearing the alcohol goggles, because it really throws them off. And that's the most physical thing that they go through when they're here. It's a unique experience. You can't do it anywhere else.
>>Boy: OK. I didn't make any shots, but it was just really neat, like, you thought that you were perfect -- like your vision was perfect -- but it wasn't. You're so dizzy.
>>Adult: Put the ball right in the middle. Right in the middle (childrens' laughter and applause)
[intro music]
>>Bulik: Now the first myth: You can tell by looking at someone whether they have an
eating disorder. This is a myth that you have to bust. Eating disorders come in all shapes and sizes. In fact, with the new DSM-5, you can be at normal or overweight and still get a diagnosis of atypical anorexia nervosa if you have lost a lot of weight. Similarly we will learn about binge eating disorders soon, but you don't have to be overweight or obese to have binge eating disorder. It can happen anywhere along the BMI spectrum.
[closing music]
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>>Bulik: Now we heard this already today and we're going to hear it again: One of the biggest myths about eating disorders--and our families have suffered from this myth--is that families are to blame. We need to bust that one and I need to give a special slide to Moms because Moms have really taken it on the chin for anorexia nervosa and they have been blamed for anorexia nervosa. Again, we're going to bust that missed myth because it's not true at all. This is so funny, I told Jordan that some of my slides really mimicked him and lo and behold, here comes The Refrigerator Mother and autism and The Schizophrenogenic Mother and schizophrenia only I added one more. As much as I love some of the writing itself in what Salvador Minuchin did--he was a lovely writer and a great clinician--he did start the myth that somehow families might be to blame for the development of anorexia nervosa. But what we know in eating disorders is that families are often our best allies in treatment—they don't cause the disorders, they are our allies in recovery. It's our job to help give them the blueprint about what they need to do to become allies in recovery.
[closing music]
[intro music]
And I need to give a special slide to moms, because moms have really taken it on the chin for anorexia nervosa -- and they have been blamed for anorexia nervosa. And again, we've got to bust that myth, because it's not true at all. Here comes the refrigerator mother and autism, and the schizophrenogenic mother in schizophrenia -- only I added one more. And as much as I love some of the writing that Salvador Minuchin did -- he was a lovely writer and a great clinician -- he did start the myth that somehow families might be to blame for the development of anorexia nervosa. But what we know in eating disorders is that families are often our best allies in treatment. they don't cause the disorders. They are our allies in recovery. It's our job to help give them the blueprint about what they need to do to become allies in recovery.
[closing music]
[intro music]
>>Bulik: So here's another huge myth--that eating disorders are a choice. I think this is perhaps the most damaging one that our patients have had to deal with. We still see this when patients go to the emergency room and they get triaged really far down the priority list because the physician thinks that somehow they chose to have a ruptured esophagus or they chose to have electrolyte imbalance. We're going to bust it now. One of the reasons that I think this myth has really stuck with anorexia nervosa, perhaps more than other psychiatric disorders, is what I call the tyranny of face validity. People see this all the time in People magazine. They see the Calvin Klein ads, they see Twiggy back in the sixties, or they see the models, and they may make an association between the cultural thin ideal and what they imagine to be anorexia nervosa. What they don't see is the difference between these two pictures. This would never be on the front of People magazine because that has nothing to do with the cultural thin ideal. If you ask our patients if something like People magazine or models was what put them on the path to develop anorexia nervosa, the vast majority of them say no. There might have been a role in the very beginning that made them think "I'm going to go on that first diet." But the minute they go on that first diet, their anomalous biology kicks in and anorexia nervosa just sends them down a path that they have no control over. So eating disorders are illnesses not choices.
[closing music]
So another myth – that eating disorders are somehow the province of white upper middle class teenage girls. Another one that's got to go. The number of middle age women that come into our clinic and say that they went to their physician and were told by their physician that they can't have an eating disorder because that's only for teenagers. Or the number of guys that show up and have the courage to say, "I think I'm suffering from this women's illness," and then their physician puts them through a huge battery of tests because you can't have a teenage girl's illness. That's the kind of things we're still running into out there. Running into out there that we need to get into medical education to change people's perceptions about who is affected by these disorders. Eating disorders absolutely do not care about your race, your ethnicity, your sex, your socioeconomic status. They cut across all of those lines. And so, we need to be vigilant and aware for everyone who comes through the door who might be at risk for these disorders. So these are the official U.S. epidemiological statistics. So anorexia nervosa, about one percent in females, about three percent in males. Bulimia, about 1.5 percent in females, .5 percent in males. Binge eating disorder as you can see is the most common eating disorder, afflicting about 3.5 percent of females and two percent of males. And this is just binge eating behavior. So binge eating just as a behavior occurs in about five percent of females and four percent of males. That all translates to about 14 million Americans – and that number is probably an under-estimate. And it goes up when you include sub threshold conditions. The PIMDs down there will take you directly to the article that I was referring to, or that I pulled the stats from.
Okay. So this is just a little bit about men. One of the reasons that we really had no idea how often men are afflicted by eating disorders is we just failed to ask them the questions. When we do ask them, they tell us. So this is a study in 1800 men in the northwestern United States. About 26 percent reported overeating, 20 percent talked about losing control, which, as you remember, is the hallmark feature of binge eating. Eight percent binge ate every week, 1.5 percent purged, and three percent used laxatives. So we need to ask men these questions in order to elicit this information. The only complicated thing in assessing bulimia and binge eating disorders in men is we found that men don't particularly like to say that they feel ou-of-control. It's just not something that flows naturally off their tongues. So we have to go around that question backwards sometimes and say things simply like, "do you ever feel like once you start eating you just can't just stop?" It's a lot easier for them to say yes to than actually asking the out-of-control question.
So here are some realities. So this is a really interesting work about African-Americans and eating disorders. So there's some suggestion that African-Americans women might be slightly protected against the development of anorexia, but there are higher rates of binge eating disorder in the African- American population. Here's a quote from Stephanie Armstrong, "I needed to suffer in silence, that somehow my legacy of strong, independent ancestors did not allow me to lean on anyone outside my community. These beliefs swallowed me up and separated me from the very people who would've been able to help me." So there's a second layer of shame about talking about eating disorders in various racial and ethnic groups, especially if it doesn't jibe with what the belief is about how you "should" feel about your body.
So eating disorders in Latinos. This is from Rosie Molinari. There is also a higher prevalence of binge eating disorder and bulimia nervosa in Latina women than in Caucasian women, but underutilization is a huge problem. So we're seeing much less use of healthcare than the prevalence would suggest. So Rosie says, "Many Latinas report feeling caught between two standards of beauty, leaving them either not feeling beautiful in either culture or feeling beautiful in one, but not the other. They feel as if they are on the precipice of judgment, caught between American pop culture and the values and cultural traditions of their families." I think nicely capturing that feeling – like you have a foot in two cultures and how that can be pulling you apart.
The LGBT community. So again, and this is another thing that has kept many from seeking treatment. This myth that if you have an eating disorder and you're a guy, of course you're gay because only gay men get eating disorders. Not the case at all. So the prevalence of eating disorders is somewhat higher in gay than in straight men, but we don't know if that's just because they're more comfortable disclosing that they have an eating disorder or seeking healthcare for it. There's no difference in prevalence between lesbian and straight women, and the myth that only gay men get eating disorders keep men from seeking treatment. And Frank Bruni, one of my favorite New York Times writers, tells a wonderful story about his development of anorexia and bulimia when he as at the University of North Carolina. And his one quote is, "It was Haagen-Dazs or love. I couldn't have both." But he tells a wonderful story about how it is to be coming out and dealing with an eating disorder as a man at the same time.
And then there's the age myth. Back to those teenage girls. So we have become increasingly interested, because when I opened my program in 2003, we were wedged between a child and adolescent psychiatric unit, because we thought most of our patients were going to be adolescents. But within three years, over 50 percent of our patients were over the age of 30. And now, at any given time, up to 70 percent of our patients are women and men in middle age and beyond. So we did an online survey of over 1800 women, ages 50 and over, just trying to find out what they're thinking about their body image and what kind of disordered eating behaviors they're exhibiting. Eight percent purging in the last five years. So remember, this is women 50 and older –3.5 percent binge eating.
Remember that's exactly the number that we saw in the national co-morbidity study – 7.5 percent diet pills, seven percent excessive exercise, 2.5 percent diuretics, two percent laxatives, one percent vomiting, and 41 percent of women over 50 checked their body daily. And this is an eating disorder behavior whereby people might pinch fat or measure their thighs or their waists just to see if the size is changing at all. So this is really common behavior in mid-life women. In 62 percent, their weight or shape negatively impacted their life. Thirty-six percent said that they spent at least half of their time in the last five years dieting. Seventy-nine percent said that weight or shape affected their self-perception, and 64 said that they thought about their weight or shape daily. This is robbing energy from a very important productive and growing portion of the United States population.
Why mid-life and why now? You'll find out in a minute that genetic factors underlie risk for eating disorders. But one of the things that's always interesting is what environmental factors might trigger the onset of that underlying genetic predisposition. And what we're starting to see is a lot of pressure on middle-aged women and men not to age, and to stay fit, and to not do what their bodies might naturally do as they get older. Expectations of aging have shifted, and you've probably heard this over and over again that 70 is the new 50. So the expectations are definitely there not to age.
Three patterns. So one pattern is people might've had an eating disorder when they were adolescents, and then it sort of went underground. It might've smoldered for a while. They never completely recovered. They might've gotten careers, gotten their education, had children, and then something happens again in mid-life, and it resurfaces. That's probably the biggest group. The second group in terms of size are people who have had chronic illness all along, and are still alive, and are still suffering from one of the other disorders. There's a lot of crossover across eating disorders, so someone might've had anorexia as a teen, and then bulimia or binge eating disorder later in their life. And then the intriguing group are those people who really do have onset in mid-life. This is a smaller group, but nonetheless really intriguing. And we dig and dig, but don't necessarily find a history in adolescence.
So some of the triggers that we're seeing when we look at the mid-life triggers -- infidelity, empty nest, lots of transition and loss – really captures it. Bounce back children. You launch them, they go off to college, they can't get a job. All of a sudden they end up back home. Lots of issues related to unemployment, illness, or surgery. A very understudied biological factor is peri-menopause. We're having so many women talk to us about the impact that menopause and peri- menopause has on their eating disorder symptoms. And then death, retirement, and trauma – either new trauma or reactivation of an old trauma.
And this is just a fun picture. Every once in a while these things just jump out at me. This is sort of a nice classic pizza making grandma. This is my great grandmother on my dad's side. She had so many talents. She had an ample lap. She read me lots of books. And then I see these pictures of the weight lifting grandma and the sort of hipster grandma. And the title of this was "Want to Look Like This at 72?" And I think that sort of shows how the expectations of grandma have changed over time.
[intro music]
So another myth that we need to bust right away is that eating disorders are somehow trivial or benign. They're not. And this is a slide from a paper that we just published, looking at suicide attempts in Sweden across a variety of eating disorders phenotypes. So, on the far right, this is the population who have no eating disorders. So the suicide attempt rate is under 2 percent. But if you look across the board -- anorexia nervosa restricting subtype, anorexia binge-purge subtype, people who had both anorexia and bulimia at some point in their life – (you see) really elevated rates. And these are all significant. Bulimia. binge eating disorder and purging disorder. So across the board, we're seeing high suicide risk in individuals with all presentations of eating disorders.
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>>Bulik: So the other thing we have to be careful about though is this sense that somehow genes are destiny. Because, I think, part of what I try to do in my world is figure out how best to take scientific information and convey it to the public and use it in therapy and to teach families and patients and advocates about how to talk about genetics--environment and genes are definitely not destiny. Hereditability for any of these disorders is not 100 percent. If environment didn't matter, heritability would be 100 percent. It's not. We've always got somewhere between 40 and 60 percent of variance that's unaccounted for, and that's when we have to start looking at the environment--gene-environment interaction epigenetic factors. So for eating disorders, the environment can have both positive and negative influences. In terms of negative influences, environment can increase risk. Some of the things we know about—perfect timing given that the Winter Olympics are on: 1. Sports with an appearance or weight focus (Ski jumping—nasty. Ski jumping has completely changed how they do their sport to decrease the number of people who develop anorexia nervosa.) 2. Dieting--the number one thing that people talk about as the first step toward developing eating disorders is "going on a diet." We have to be so careful in our obesity prevention efforts that we don't give people like me more business. We don't want our obesity interventions to create more eating disorders and that's why weight stigma and obesity stigma is such a concern. 3. Modeling--being obsessed with looks. We're finding out more and more that so many people with eating disorders have teasing or bullying histories--and not necessarily just about their physical appearance or their weight. But teasing is one of these nonspecific risk factors that I think we all see in our populations that many of these people have in their histories. But environment can also have positive influences. Some of the things that may decrease risk for the development of eating disorders: 1. Models for healthy eating—making sure that you really do model healthy eating, non-emotional eating, and making sure that your family is a place where healthy eating occurs. 2. Being able to separate body-esteem from self-esteem. The first thing people usually say about kids is what they look like. I always tell Moms, for example, if someone gives your child a compliment about especially her physical appearance, make sure you parrot right away with something like "Oh yeah, and she's also really great at playing the flute" or "She got an A in Chemistry" or something like that so your daughter is hearing more than just physical appearance–based compliments. 3. Role models for body respect. 4. Family Involvement. 5. Supportive peers who value who you are, not just how you look. 6. But also letting parents know that they can't control everything. You can have all the stuff in place and your child might still develop an eating disorder. Now this is one of the ways that I try to get people to understand the complexity of risk for an eating disorder. People like simple Yes-No, Black-White explanations, but we can't give them that. In fact, the truth is much more complex than the slide I'm going to show you. This slide at least breaks it down into four risk and protective quadrants and it's the way I like to help people think about what is changeable and what is not changeable. These are some very colorful human chromosomes. The first quadrant is genetic risk factors. So all of us are dealt a genetic hand of cards when we are born. The things that you see up here now are all things that we know are influenced by genetic factors. There's not a gene for appetite regulation. There's not a gene for binge eating. But all of these things have been shown to be heritable. What that means is that there are probably a whole slew of genes that code for a whole slew of proteins that somehow influence that end phenotype. So the first quadrant is genetic risk factors. The second quadrant, and this gets to the resilience question that we were talking about before, are genetic protective factors. There are traits, for example, constitutional thinness or someone who never has to go on that first diet. We know self-esteem is influenced by genetic factors. How that works biologically I'm not so sure, but it is heritable. There are probably a whole slew of other protective factors that are influenced by genes. Your genetic deck of cards has both risk factors and protective factors. That then comes into the mix of the third quadrant, which are environmental risk factors. These are Shakespeare's "slings and arrows about outrageous fortune" like teasing or dieting--things that are environmentally mediated that might actually have the ability to activate some of this underlying genetic risk. And then the fourth quadrant is environmental protection factors. Here we include: 1. Family meals-- because there have been a lot of data on family meals being protective against a whole array of adverse outcomes. 2. Breastfeeding--because breastfeeding is good for just about everything, and here, 3. This is a coach who was emphasizing strength and what your body can do rather than a sort of "thin to win" mentality. Everyone has a different pattern of genetic risk, genetic protection, environmental risk, and environmental protection quadrants. What matters is not just the relative balance of those four quadrants but also the timing. Some of these things might be--you might be more or less vulnerable to environmental activation, for example, during puberty or during menopause--so that sort of cross-cuts those four quadrants, the whole timing piece. And somehow people can often just begin to feel more comfortable with complexity if you can break it down into these four quadrants. But the other thing that you have to tell them is we can't do anything about the genes yet. The only thing we can do something about are the two environments. We can try to decrease the environmental insults and increase the environmental buffers.
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>>Bulik: So the ninth myth is that eating disorders are for life. And this gets a little complicated because some people do prefer, and this is a patient preference, to say that they are in recovery, sort of forever, to keep them vigilant about slipping or relapsing again. And I
think it's really important to validate and respect that patient preference. But the data show that eating disorders are not for life--so eating disorders are treatable. Recovery can and does
occur every age. For anorexia nervosa, nutritional rehabilitation and weight restoration are essential but only the first step in treatment. I know we have some family-based therapy advocates in the room. Whether your intervention is through family-based therapy or through in-patient re-feeding, the single most important thing to do is to get weight back on a patient first because their brains aren't working. You could do a lot of psychotherapy and get nowhere--you're just spinning your wheels in the mud because their brains simply aren't
working. I'm going take a little aside here because I didn't say it before and I want to make sure I do. I want to go back to the danger of that first diet. The reason it's dangerous is that we all respond to negative energy balance or not eating enough food--being hungry--differently. Most of us when we're hungry find that a really aversive experience. You might get more irritable, you might get a headache, you start foraging and looking around for
food, you might have difficulty making decisions because you're so hungry you don't know what to eat—it is not pleasant. People who have or who are vulnerable to developing anorexia nervosa: When they go on that first diet, they find it calming. So at baseline they're very
dysphoric and anxious and miserable. And it's the food deprivation that calms them. And so throughout their life, what they have to be really careful of is when they go through periods of stress again, falling back into that restriction trap because it gives them--it's like a drug, it's like a calming drug and that's their high risk for relapse. Figuring out the neurobiology of what makes food restriction reinforcing for them is a gold mine when it comes to understanding anorexia nervosa. Third thing: Cognitive behavioral therapy works well for bulimia nervosa and for binge eating disorder. No medications have been shown to be effective in the treatment of anorexia nervosa—the only FDA-approved medication we have is fluoxetine or Prozac for bulimia nervosa. No other meds for any of the eating disorders. And, in part, that's because we don't understand the underlying biology of the illness. Hopefully by doing this genetic research we might be able to unlock some new pathways that will help us understand the neurobiology of anorexia, bulimia, and binge eating disorder and eventually lead to new drug targets. Medication can and does play a role in the treatment of bulimia and binge eating disorder but short term. It doesn't lead to long-term effects from what we know so far. Psychotherapy does seem to give people the tools to be able to keep their behavior under control in the long run. And finally individuals with eating disorders can thrive after recovery.
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DR. CUTHBERT: Why are we doing RDoC? Well, it really goes back, as Greg said, to the way we diagnose mental disorders at the current time, and our diagnostic system really depends on our Western cultural heritage in many ways that actually goes back thousands of years, if you think about the ancient Greeks, who had the concept of melancholia, which is very similar to our modern concept of depression; melancholia literally meaning black bile, their theory about what was actually going wrong and causing this.
More recently, our notions of schizophrenia and bipolar disorder stem from the work of the classic German psychiatrists, like Eugen Bleuler and Emil Kraepelin, and Kraepelin first really seriously propounded the idea that there's this distinct pair of psychotic disorders, schizophrenia and bipolar disorder, that are really distinct and separate diseases.
And that sort of notion has come down to us in the present day, and, again, it's based really just on symptom presentations and looking at the course of disorders. And as Greg said, we know that the brain is by far the most complex organ in the body, and at those times, of course, virtually nothing was known about the brain, beyond its gross anatomy, so those people had to rely on clusters of signs and symptoms that patients came in with, but unfortunately, as Dr. Insel likes to say, that's more or less equivalent to saying that you have a headache disorder or a stomach pain disorder and not really going any farther to figure out what's actually wrong. And so you are necessarily limited in how you can move forward.
And it's also the case that now, as we move into this modern era and have techniques such as Greg was describing for neuroimaging, for structural and functional analyses of the brain, we're finding that these things simply don't map on very well to our disorder categories, and there seem to be many reasons for this. So we fund all this amazing amount of brain science and behavioral science, but yet it doesn't seem to line up very well with our disorders, and as Greg said, for all of our investment, we still don't have a single test using imaging or blood measures or anything that can really provide a diagnosis that would direct the clinician to do a very precise treatment that can actually help an individual patient.
So the fact that our disorders are different is referred to as heterogeneity, meaning lots of all different things sort of given the same name. And I'll just give you a couple examples of this in terms of understanding diseases and what that means for treatment.
A few years ago, the first stem cell report for schizophrenia came out titled "Schizophrenia in a Dish," and there was a lot of excitement about that. But in one of the comments about this exciting article, Michael Owen, one of the foremost psychiatric geneticists in the world, said, "These disorders," meaning schizophrenia, "are not really disorders. There's no such thing as schizophrenia. It's a syndrome. It's a collection of things psychiatrists have grouped together."
So, again, as Greg said, it may be the case that there are five or eight different actual disease entities that we all kind of lump together and call it schizophrenia, and some people have gone so far as to say that every single patient who gets a diagnosis of schizophrenia actually has something just a little bit different wrong with them because of the complexity of the brain and all the possible ways that things could go wrong. And we hope that it's not that extreme, but this represents the problem that we have to grapple with if we really want to develop effective therapies for individual patients.
And then again, for looking at developing new treatments, recently four scientists from AstraZeneca wrote a paper called "The Drug Hunters' Perspective," and in their paper, they state, "On average, a marketed psychiatric drug is efficacious in approximately half of the patients who take it."
One reason for this low response rate is the artificial grouping of heterogeneous syndromes with different pathophysiological mechanisms into one disorder. So if you're trying to develop a new treatment, whether it's a drug treatment or a behavioral treatment or a device, if you give this treatment to a group of patients, but only, you know, say, a third or 40 percent of them actually have a problem, a particular, specific problem that's being addressed by the drug or the treatment that you've developed, well, you're not going to see an effect because all these other people will not respond at all. It's -- that treatment is completely irrelevant to what's wrong with them, but they're looped together -- grouped together so you can't actually see an effect. So these are the kinds of problems that we face.
So this just brings us to this paradox that if we really want to have a diagnostic system based on our brain science, what we know about behavioral science and genetics and so forth, we'll never get that system until we have a research literature that can tell us how we ought to do that. What should we be paying attention to? What are the appropriate tests and so forth?
But we'll never get that database as long as we are doing diagnoses and conducting our clinical studies in line with our current system that ignores all these important distinctions rather than trying to fund studies exploring what these important aspects and dimensions and elements are.
So RDoC represents essentially an attempt to move forward and say, "Let's try to look at what the brain actually does and what's important and what the major systems are and explore that and try to think of mental disorders in those terms, rather than making these symptom categories and assuming that the problems in the brain and the problems in behavior should line up one to one with these categories that were defined in the complete absence of any knowledge about the brain anywhere from 100 to 2,000 years ago.
So the statement of RDoC is in our strategic plan, and it states, "Develop for research purposes new ways of classifying mental disorders based on dimensions of observable behavior and neurobiological measures." So and there are four important parts that will help you understand sort of what that means. The first component that is specified what RDoC ought to do is to, in fact, identify these fundamental components that may span multiple disorders.
So the idea here is that we now know that there are circuits in the brain that -- you couldn't really see them really clearly in Greg's slides, but there are major circuits in the brain like the major highways that carry out certain functions. We know there are circuits for responding to threatening situations. We know there are other circuits that help us respond and get food, shelter, and things that we want.
We know there are systems for memory and storing things away to remember them later. There's a different system for what we call working memory, the sort of temporary or scratchpad memory that if someone gives you a phone number, you can remember it for a few moments while you dial the number, and then you kind of forget it because you don't need it, but it's there for a few moments.
There are other circuits that help wake us up appropriately, you know, get the system going in the morning and give us energy and then sort of help us go to sleep at night. So we understand all of these different circuits in the brain, but, again, we don't have a very good idea of how these actually relate to mental disorders because in any one disorder, like depression, many of those different circuits may be disrupted, that in any one patient, some of the circuits may be wrong, and another patient, other circuits, different circuits may be impaired. So it's a matter of saying let's not call it depression. Let's actually figure out what specifically is wrong in this patient.
Greg used the metaphor of the highways. It's sort of like saying that, you know, the problem -- that somebody calls in to say that there's a problem with traffic in the Washington, D.C. area. We have a Washington, D.C. traffic problem. Well, what you really want to know is, well, is it a problem on I-95 north to Baltimore? Is it a problem on 270, going up to Pennsylvania and Breezewood? Is it a problem of I-95 south? You know, let's say which one it is, and then we can try to fix it. But we're sort of stuck saying we have a Washington, D.C. traffic problem, and that's sort of a simple metaphor for the problem that we have, and we have to now identify what are these major circuits, and how can we best study them?
Another important point for RDoC is that the goal states, "To determine the full range of variation from normal to abnormal." So this is really important because what we're saying is that because we're studying what are essentially normal brain functions, like memory and responding adaptively to threats and going after rewards, getting food and doing enjoyable things, these are all normal functions. That's what the brain evolved to do.
And so what we're saying is that we want to look at these functions across the full range of normal behavior and then out into where things get to be a little bit off or somewhat off or really severely off and understand that whole range, because importantly now, we really understand these problems as complex traits that are continuous. It's not as though you have a cancer that you're either healthy or you have cancer or you have a flu bug, you have a virus or you don't. It's not you're well or you're sick. It's more of a continuum, like blood pressure or like cholesterol levels that they kind of shade along.
And when you get a diagnosis, say, of hypertension, it's not that you totally didn't have hypertension, and now all of a sudden you have high blood pressure, it's that there's sort of a range, and the doctor knows when you're in the normal range enough that you don't need to worry. If your blood pressure's a little elevated, well, you need to cut down on your salt, watch your diet, exercise, all those things.
If you got much higher in blood pressure, then the doctor might say, "Okay, now you need to take some anti-hypertensive medications." But even then, he or she will look at exactly the kind of blood pressure problems you have to prescribe the right medication.
So that's the idea is that here, we're really making a shift. We're not trying to figure out that somebody has a mental disorder and then say, "Okay, we're defining this disorder, and now we'll see what is wrong with you in your brain." We're turning that around and saying, "Let's think about what the brain really does and what the whole range of normal brain functioning is, just as exactly what the Human Connectome is doing, and that will help us understand disorders in terms of dysregulation and impairments in these normal processes, rather than inventing these other categories, like schizophrenia or bipolar, and expecting the brain to match up with our cultural descriptions of what appears to be wrong. So this is a very important shift in how we're going about it.
A third point is to integrate genetic, neurobiological, behavioral, environmental, and experiential components, experiential obviously meaning our experience of these disorders. Because these are complex disorders, we may never be able to simply say, "We did an imaging test, and now we know you have schizophrenia." It's really going to examine how people can function, what goes wrong in the brain, what the genetics are, how that's affected by the environment, what they feel like their experience is, and we have to look at those things all at the same time. This is not a matter of just saying, "Okay, now we understand behavior in the brain" and will tell us everything about that. It's rather understanding the relationships between the brain measures and the behavioral measures to make sense out of these very complex syndromes.
And, finally, this is such a new approach, we don't have measures of any of these things. Our -- again, our diagnostic systems are simply based on rather simple, straightforward descriptions of problems, and we don't really measure any of these constructs. We know about them, but there aren't really ways that we can measure them in clinical trials or in actual clinical use, and so we have to do a lot of measurement development and fund the research on that.
So this is the RDoC work group. It's drawn from all segments of the institute. There's a little Mac-to-PC problem there that -- so I didn't stick Kevin Quinn and Chuck Sanislow in the corner for any reason.
So exactly -- now that I've told you why we're doing it, what is RDoC, exactly? What are we doing? Well, like all of the things that we do in the extramural program, it's a research grant funding initiative directed to a very specific area, these new studies of dimensions. And it's not that we're trying to create -- you know, we've defined a new classification system, and we're testing it. It would be more accurate to say that it's research toward a new classification system. We're trying to study and validate these dimensions of function, like threat and reward and working memory, that are affected across many of our current mental disorders.
And the goal, again, is to create a research literature, to fund studies that will create a research literature that lines up the genetics, other parts of neuroscience, like neuroimaging, and behavioral science that tell us how these circuits work, what the normal range is, what seems to go wrong when things become dysregulated or impaired, and then eventually to be able to use that research literature to say how we should be diagnosing patients in the future based on the brain science.
And we hope, just as in the example from the drug hunters, that if we do that, we'll also be able to improve our treatment, which, of course, is really what we're all about is by giving us better targets that we can define a more homogenous group of patients who, in fact, do all have the exact same thing wrong with them, and then when we develop a treatment, we will be able to get a treatment that's really effective for that particular group. But all of these things are in the future because we don't know how to do that right now, and that's exactly why we have to do this research program.
So this is what the RDoC matrix looks like. And I don't want to spend too much time in this, but I think we should have a little idea of how this is laid out. So this is the end? On this thing? Yeah, that's what I -- yeah. Yeah, got it. So if you look over in the left column, you'll see this is labeled domains/constructs, so the research domain criteria refers to five major domains of functioning: negative valence systems. That means how we respond to threat and loss, you know, aversive or negative situations. Positive valence systems; as I mentioned, those circuits that help us work for reward, learn about rewards, develop habits, and so forth. The various sorts of cognitive systems, like memory and working memory. Systems for social processes and arousal/modulatory systems, like biological rhythms, arousal systems, and so forth.
So we had a workshop with experts in the field over the last few years for each of these domains in turn. We had five workshops. And at the workshops, the participants defined exactly what the dimensions are. So for cognitive systems, I've listed them here. And there are the list for arousal/modulatory systems. I haven't shown you all of the constructs, but there are these dimensions under each one of these. And you can go to our website and see the full listing of the constructs under each domain.
We use the term "construct," which is a term from psychology that means our best idea about a specific aspect of functioning in a psychological sense. And we use that to indicate that we never -- probably will never have a complete, 100 percent understanding of these systems. It's our best idea about something, but we keep refining and improving our understanding of any of these things.
So, for instance, in reward systems, the first study of the reward system was in 1954, and some scientists looking at rats simply said, "We've discovered the brain's reward system," and that was all we knew, and we knew that was really important, but that was all that was known. Now we understand that there's one system for working to get rewards, another system for experiencing that the reward is good. You know, it's one thing to want something, another thing to get it and say, "Ahh, that milkshake is just really good." And a third thing for actually learning to associate rewards, that, you know, when you see the Dairy Queen, that's when you can get a really good milkshake, and you sort of have to learn that.
So there are actually different systems for all of these things, so over the years, we've refined how we understand the brain's systems, and that's referred to as a construct. And we think of these as dimensional constructs.
So this is the list of domains and the constructs, and then, as indicated in the strategic plan, we study each of these constructs across a large number of different ways of measuring them, and we term these units of analysis. And part of the workshop process was we asked the experts to tell us, once they had defined all these dimensional constructs, what would be the elements that could be used on the basis of the literature so far to measure those dimensions.
So this one is just an example of the cognitive control construct, which is essentially an impulsivity dimension, sort of being inhibited at one end to being very impulsive at the other end, related to things like ADHD, substance abuse, gambling, fighting, and so forth.
And you can see that they define different genes that are relevant, different circuits, various ways of behavior, different kinds of reports people make of these behaviors, and, finally, the laboratory paradigms that we could use to actually study this sort of behavior.
In some cases -- you can see here there's just a gap. There's nothing there, and that indicates an area where, in fact, the science hasn't given us any leads at all and helps us target areas where we might want to particularly do further research.
So that's sort of how this is set up, and each of these constructs is sort of a promising idea, an area for study that we would encourage researchers to do. Thank you.
The idea here is that we are working towards precision medicine, which is, as you know, popular across all areas of medicine now. And in late 2011, the Institute of Medicine released a big report called "Toward Precision Medicine," and the idea is that you take classes of measurement in many different areas, people's environmental affects or their exposure to things, the exposome, their clinical signs and symptoms, which, of course, are what people want to have cured, after all. That's why they come. Genetics, epigenetics, the microbiome, other types of patient data, and together, all of these different sets of analyses, zero in on one particular patient, and presumably ideally would help to indicate the exact treatment for that individual patient. We're not quite that ambitious. Mostly now precision medicine involves small groups of patients, but that's the idea.
So similarly here, what we would say is, okay, you have problems in what we would -- used to think of schizophrenia, but for you, we're actually going to break it down into what are the specific problems that this individual has? Is it language troubles, is it hallucinations, is it delusions, is it problems in cognitive functioning or remembering things? But actually in schizophrenia, there is a lot of heterogeneity there. And so the idea is that for each patient or for small groups of patients, we study the particular genetic patterns and how that affects molecules and cells, activity in circuits, ways of measuring that activity, like heart rate or skin conductance and so forth, looking at their actual behavior, and together, these give us a good idea of disruptions in something like working memory, that that's a big problem for many patients with many disorders, where you just -- you're so stressed or so disorganized, you can't remember a phone number. If somebody says, "Okay, you know, please call (301) 443-9782," and you're like, "Sorry, I can't get that." You know, it's that kind of thing that most of us normally can do. And so we can look at that and say, "Okay, we're studying different ways of disruptions in working memory," and that, in turn, results in cognitive deficits in real-world functioning, not just with patients with schizophrenia, but patients with depression, bipolar disorder, and many different disorders. So that's the idea, is to use all of these measurements to zero in on the particular idiosyncratic constellation of problems that a particular patient or small group of patients has and then understand that.
You're looking thoughtful. Did that address your question? Okay. Okay. Good. So there are two important things that should be added here. We're not such good multidimensional artists, but I've tried to show four dimensions here. Here is the matrix sort of shrunk down. One really important aspect is development. We increasingly understand our disorders to be disorders of neurodevelopment; that is, that as the brain matures over time in this incredibly complex sequence of brain development, there are critical periods, and that interacts with things that happen to you, whether you have a really happy, secure childhood, whether you're abused or neglected, whether you have a single traumatic event, like a car accident or something. And so we really have to study development in many of our adult disorders, like schizophrenia or bipolar, we can really understand as things that may happen really early in life, including during fetal development, and set the stage and risk patterns for really getting the disorder later.
So it's critical to do this, and we hope that RDoC actually will help focus this research because it's looking at specific kinds of circuit activity and behaviors rather than these broad, heterogeneous syndromes that we have now.
Similarly, as my example shows, we want to look at the environment and the effects of the environment, both in positive ways and in negative ways, as it affects neurodevelopment and essentially events throughout the lifespan.
So that's essentially the idea, and I'll show you two examples just to give you a little better feeling for what this would look like. This is a graph showing, from some grantees that we have funded, and this shows cognitive functioning. The backs (ph) is this group's composite cognitive functioning score, and the higher the number, the better off you are in cognitive functioning. And on this X axis, we have a score called the Schizo Bipolar Score. And at this end, a zero means that you are a classic textbook case of bipolar disorder, and at this end, a 9 means you're a classic textbook case of schizophrenia, with no symptoms of bipolar disorder. And Emil Kraepelin, in his famous dichotomy, would say that you should either be bipolar or schizophrenia, with a few right in the middle with something called schizoaffective disorder, but these should all be very distinct.
Instead, in these real-world data, what you see -- and each blue dot here represents one patient -- is that there's sort of a scattering of patients all along this scale, so a 2 here would mean you're mostly the bipolar, but you show some symptoms of schizophrenia. A 4 means you have just about 50/50, systems of both bipolar and schizophrenia. A 7 would mean, well, you're looking more like bipolar, but you have some symptoms of schizophrenia.
So you can see it's not a dichotomy, as Kraepelin proposed. It's really just this continuous flow. And you can see there's this strong linear relationship across this area, with a strong correlation that the close from -- as you go from bipolar towards the schizophrenia end, on the average, your cognitive functioning tends to be worse.
And the way we've always studied this is to say, "Okay, we'll take" -- even if you grant that these patients could be called reasonably bipolar, we study bipolar versus schizophrenia, and we say, "Yeah, sure enough, we know that patients with schizophrenia have worse cognitive functioning than patients with bipolar."
This ignores the fact that there's this whole group of patients in the middle that we don't really do anything about at all, which I think is a significant public health problem, it also ignores what you can see as this massive amount of variance here, that patients aren't all the same. It's not like all patients with schizophrenia are really bad and all patients with bipolar are really good. There's this tremendous range in here that we tend to miss with our simple statement that schizophrenia has worse cognitive functioning than bipolar, even though, on the average, that's not an untrue statement.
So what we're saying in RDoC is maybe what's really important is to examine the factors that, for each of these patients, tends to account for how we understand that no matter what your diagnosis is here, your score in this range, some people have relatively preserved cognitive functioning, and other people have really bad cognitive functioning. So even if you're a pure -- person with just pure bipolar disorder, you may still have very impaired cognitive functioning, whereas some patients who get a diagnosis of schizophrenia have fairly well-intact cognitive functioning; at least, less impaired.
So what may be important is to study the factors that relate to relatively good versus rather poor cognitive functioning, independent of what diagnosis they have.
And there's another example that we worry about now, given the emphasis on our soldiers coming back from the wars and PTSD and so forth. This is a graph showing many different anxiety disorders that you can see, and the measure here is a measure of fear reactivity in the laboratory. Essentially, if you're -- you know how if you're watching a really scary movie at night and it's dark and all of a sudden, the phone rings or somebody drops something or a door slams, you go, "Ahh." You know, you just jump up and everything, whereas if you're just sitting, you know, watching the news or something, and the same door slams, you kind of look like, "Oh, okay. What was that?" You know, you're not really very upset.
So this is a laboratory measure of exactly that kind of behavior, so the higher the bar here, the higher, more intense the fear reaction is. And in this case, patients are actually imagining their own personal anxiolytic, their anxiety-producing situations.
The point I want to make is that these are patients who have had a single traumatic PTSD event, like a car accident or having one crime occur to them. These two bars show patients who have had multiple traumatic events or who have had their PTSDs for just really a long time, and it's never remitted.
You can see that, for single trauma, these patients show the biggest startle reactions of all, you know, practically jumping out of their chairs as it will, where these patients hardly show any fear reactivity at all. They're very blunted. But yet we call these patients by exactly the same disorder, and we talk about doing a treatment for PTSD, as though the treatment for these people would be the same exact same as the treatment for those people.
Clearly, you can see something has to be very different with their fear reactivity systems. The one is very excessively reactive, while the other is blunted, but yet our current diagnostic system says we should treat them all the same. To me, this is almost unethical, that we should be taking this approach, but yet to do this, we need to develop practical tests to use this in the clinic, to see if they're reliable and valid and figure out how to do this, but if we do, we should be able to develop much more precise treatments for patients with what we like to think of as a post-traumatic syndrome that is this broad range of different things, and either match our current treatments much better to the patients or develop new treatments, based on a better understanding of what's going on here.
So that's essentially all I wanted to say about RDoC. I'll just say that you may have heard about some of our new contract trials, so-called fast, for fast fail. This is another new initiative of the institute, and what's significant with respect to RDoC here is that you notice that all the trials are devoted to spectrum, psychotic spectrum, of course, autism spectrum is that way in the DSM now, and the mood anxiety spectrum.
So rather than trying to treat a specific DSM disorder, like depression or PTSD, we're looking at a broad spectrum of disorders and trying to use RDoC dimensions as the treatment targets, and that, we hope, is the first test of how we can go about this more homogenous way of treatment development. So this is sort of an experiment in how we can start doing this.
So the timeframe for RDoC is long. We are just starting with our understanding of these things, so it's really something that will take a number of years to do, to develop this database, but already, as you can see from our treatment trials, we're already, you know, trying to use RDoC as much as possible to start moving the field in the directions that it needs to go.
So just to summarize of all this, again, this is a -- very much a translational medicine approach. We're taking basic science and translating that to look and see how we can understand these clinical problems and think about our disorders in terms of basic mechanisms that get disrupted rather than defining them all on their own and then expecting the brain to match up with how we defined it. And RDoC is really a framework. All of the dimensions that I showed you aren't the only ones people can study. It's more about a different way of doing the research. And so people can study other dimensions if they want to define them and say, "Here's the brain circuit. Here's the behavior that circuit produces, and we think this is really important." That's fine too, because we want to have this grow as it goes forward.
Again, I want to emphasize that this is the idea of a dimensional approach as well, that we're not saying you're well or you're sick. There are no actual disorder boundaries at this point. Again, what we need to do is to develop a lot of research literature, and people can make those decisions later, once they have a better idea of what things look like.
It's also important to say that we're not trying to develop this as a new system. We're not going to come out with RDoC as a competitor to the ICD or the DSM. Instead, it's to produce this kind of large research database that can be used to inform how future versions of these systems would be developed.
And, again, just in conclusion, we think that in the future, 10, 20, 30 years down the line, this could lead us to a much more precise personalized medicine approach for our disorders.
>>MALE SPEAKER: Yeah, and just talking about how this influences mental health in the world, the European Union is currently conducting a planning project called ROAMER, which stands for Roadmap Mental Health Europe, to examine and propose steps for their research needs in Europe in the coming decades. And their workgroups looking at biomedical and psychological research needs have actually adopted the RDoC matrix and structure as their organizational scheme for how they propose what is needed to move forward. And I just actually had to fly over to a meeting with the European Commission a few weeks ago when they had their big meeting for ROAMER, to talk about all of these things.
So our initiative may actually have a major role in contributing to how Europe sets up its entire mental health research system in the next several years. So it's already having a lot of influence.
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>> Taylor : With brain donation, it began because I was a scientist in a lab studying the brain disorder schizophrenia . I have a brother diagnosed with schizophrenia. As a sister and as a scientist, I wanted to understand what is the difference between my brother's brain, which results in hallucination and delusion, and my brain. Personally, I understand the value of brain donation because I understand that the only way for us to truly understand at a cellular level what's going on with these disorders is to look at the tissue. It's extremely valuable on all fronts. Unfortunately, there's a long-term shortage of some types of tissue donated. If we want more research into certain types of illnesses, then it's really important that we can provide the scientists with the tissue they need in order to do the work. I always encourage any family member or any individual who has any type of neurological or neuropsychiatric illness inside of their family to really consider brain donation first. If you don't have a neurological or neuropsychiatric illness, there's also a shortage of normal control tissue donated. When you stop to think about it, the only way that scientists in a microscope looking at the tissue can really understand what is altered that is resulting in some type of symptom for any of the disorders, they have to compare that tissue to normal control. There is normal control and, technically, if you don't a neuropsychiatric or a neurological disorder in your family, then you would be counted as normal control. It's really important that as soon as an individual dies or death is impending, the family calls one of the brain banks. Timing is everything when it comes to the cell tissue. A brain can generally be donated within the first 24 to 48 hours. It's also very important that the next of kin sign a form that releases the entire life history of medical records for that individual so that scientists then can go through that and we can have a better understanding about what was the normal progression of a disorder, if there was one, and which medications was this individual on so they can take that into account. When a person dies, their body becomes the property of their family. If there's a spouse, the body becomes the property of the spouse. If no spouse, then adult children. If not adult children, then parents. Ultimately then, after death, regardless of what has been put in writing, unless it's used as a formal contract, the family will make those decisions. It's really important that families get together and talk about brain donation. These mental illnesses, these major neurological disorders, they're genetically based. When you give that gift, you're really giving the gift of hope that your children, your grandchildren, your nieces and your nephews, if they do have these types of problems, we'll have a better understanding about what to do to help these people get better.
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>> Chambers: There have been a lot of efforts to try and improve depression care within the context of clinical trials. But often if you have effective interventions, there's not as much success in figuring out how do we implement those more broadly so that they reach the populations as well as they possibly can. This particular study was trying to take the next step of saying how can we take an effective model for depression care--collaborative care for depression--and scale it up within community settings, particularly for those who don't typically benefit from care or who don't receive any care. This was an innovative model that was looking at a community engagement approach toward trying to implement collaborative care and thinking about community agencies as a logical focus as opposed to assuming that a clinic-based model, which has been the more traditional approach, would be preferred by communities who may not have kind of infrastructure. This took place within south and east Los Angeles. The communities were primarily those with high levels of poverty, particularly high levels of comorbidity, and high levels of community stress--primarily African American and Latino populations. It's not just that it's testing a particular model, but the actual approach to the research was seen as a partnership between researchers and community agencies. The lead investigators were Ken Wells from UCLA-RAND as well as Loretta Jones from a nonprofit Healthy African American Families. Together with a council, they really ran the research. We have efforts to think about community-based participatory research just as a research approach. What was novel here is that they were thinking about those partnership principles both in terms of the intervention to try and implement effective care and the way in which they conducted the research itself.
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Pine: I think there are really two things to take away from the study. The first thing is that we've known for many, many years that there are tremendous differences in terms of how people react to stress. And these differences are particularly important in situations that are examined in this study- combat situations- since we're all tremendously concerned about the reactions of troops in the United States, in Israel, and elsewhere when they're exposed to stress. So, soldiers and other individuals react very differently when they're exposed to the same level of stress. So the question is how can we understand those differences. What can we do to predict before stress happens who's going to react with resilience and who's going to react by having problems after stress. So, that's the first thing to say about the study. The second thing to say about the study is that we've tried many different measures to try to predict these reactions. The ones that typically work best are when we talk to patients and we find out different aspects of how they respond- mentally and symptomatically to stress. And those are very, very helpful. The problem is those just give us kind of surface rendering- just one level of how people respond and what we're really trying to find is measures of behavior that we can link more tightly to individual differences in brain function. So, that's the second major aspect of this study… that the measure of behavior used here unlike in many other studies was a direct measure of attention- one that was based on behavior. And that gives us novel insights about what might be going on in the brain that might, in turn, predict people's reaction when they experience trauma or other forms of stress later in life.
DR. THOMAS LEHNER: The hope of the large-scale genetic studies is always, first, to find a signal. That is, to find a gene that's associated with a particular disorder - Alzheimer's in this case. And then, the next very difficult step is to then take this finding and move it forward into developing new drugs. Rudy Tanzi and his colleagues did exactly that. They took the finding and through a complex set of experiments in human brains, in cells, in mice - they actually could show, with strong confidence, that this gene and its product, is associated as a risk for Alzheimer's disease.
The gene involved, according to the study, is called CD33. We know it's involved in immune function somehow. But we don't know what it does in the brain. It is expressed - the protein that's coded by CD is produced in cells in the brain that are called microglia. Microglia are support cells that protect the brain from infection - that have an immune function in the brain.
CD33 is also involved in clearance of a protein beta-amyloid has long been associated with Alzheimer's. And CD33 helps to get rid of the over-production of that protein. The gene comes in two flavors. And it has been shown that one particular flavor is protective for Alzheimer's. And it also reduces the level of beta-amyloid that's present in the brain.
If the expression of CD33 is reduced in those particular microglial cells - these protective, support cells that have immune function. If the expression is reduced, the cells themselves can take up higher quantities of beta-amyloid, and eliminate beta amyloid - thus protecting the brain from Alzheimer's.
Until today, very few genetic signals have been found that increase the risk for Alzheimer's disease. Now, through large-scale genomic studies of recent years, we have a few more. Not too many, maybe three or four. This is one of those.
One of the reasons this finding is so exciting is that it opens a potential pathway to develop treatments. You could imagine that if there was a drug developed that crosses the blood-brain barrier - which is an additional difficulty - that oppresses the expression of that particular gene, that may be protective for Alzheimer's. But his is, you know, far. This is nothing that is imminent. This is a long process of drug development.
Michelle Freund, Ph.D.: The brain initiative recently announced by the White House is really designed to facilitate innovative strategies to better understand the brain. And in order to do that we need new technologies. CLARITY is a great example of the type of new technologies that will enable future brain studies.
So prior to this technology, scientists used methods where they would take thin slices of the brain. They would put these on glass slides, process them with antibodies, which illuminate what chemicals are there. And then they would have to use a microscope to study which transmitters are in which locations. Unfortunately, you can't see the structure of a neuron in a brain slice.
So with this technology, they're able to look at the entire neuron in a three dimensional volume. And with this three dimensional structure intact, you can see where the neuron starts and what brain region it projects to. In slices, you can only see what's in the position where you started. And what this technology will allow is to do is not only study what molecular or single elements of a cell are located in a neuron, but how those communicate with other elements in the brain.
So in the recent publication by Deisseroth and colleagues, they describe not only the ability to look at animal models – or whole brains of animals – but also the ability to look in human brain. So in a post-mortem brain from a child suffering from autism, they were able to trace neuronal projections from a significant volume of tissue. They're also able to use the technology to stain for neurochemicals located in that brain region. And the potential for this type of research is great for understanding how disruptions in neural circuitry are involved in disorders. It has really transformative potential.
The technology shows us in the video an area of the brain that's involved in memory, the hippocampus. And this video shows the neurons that are involved in processing memory, where they project, and what neurotransmitters, or chemicals are contained in those neurons. And it shows this in three dimensions, so you see not only where they start and where they project and how they might interact to form memories.
The video through an entire mouse brain shows us how neurons are connected. So the neural circuitry – which neurons project to which areas in the brain, how they might be involved in giving commands to execute certain functions that we know about from physiology studies, but we don't actually know how they connect to each other. This technology allows you to bring those together.
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Copeland: Obviously bullying behavior has gone on since the beginning of time. We can observe it in other cultures and certainly in animal groups as well. Research into it has really just kind of started in the 1980s. There were three boys in Norway that committed suicide and they each left notes that kind of described some of the bullying that they experienced at school and that generated a lot of interest, a national study in Norway, and that's kind of continued from there. Where our study kind of fits in is we kind of got a group of kids that we followed up over time for two decades so we could look at how they were doing as adults. Based upon the interviews that we did with our kids when they were children, ages 9 to 16, we were able to categorize them as either victims only, bullies only, bullies and victims, and neither. And then we followed them up into young adulthood, ages 19, 21, and 25, to see—to look—at their emotional/behavioral functioning. And what we saw is that the pure victims had elevated rates of anxiety disorders, things like agoraphobia, panic disorder, and generalized anxiety. The bully/victims really seemed to be the worst off. They had about five times higher risk of depression and five times higher risk of suicidal thoughts and behavior, as well as risks for some anxiety disorders too. The bullies did not have any kind of emotional problems in adulthood but they did still have some behavioral problems, suggesting that they might still be engaging in some kind of bullying—perhaps at work or home or elsewhere.
Sarampote: So one of the things that we know about the kids that are bullying that they're at greater risk for depression and anxiety. They may be more sad, lonely, have low self-esteem, have problems with disruptive sleep, disruptive eating. They may have problems, loss of pleasure, having fun, engaging in activities that they once thought were fun. We know they can have physical consequences. Kids who were bullied report all sorts of psychosomatic symptoms. They might report more headaches, more tummy aches, those kinds of things. And actually there's an interesting body of literature, some supported by NIMH, suggesting that immune system functioning is affected by peer victimization and trauma, so that there may be actual physical real outcomes and immune system functioning can affect a wide of everything from not only your ability to handle colds and to fight off and viruses and things—it can also affect your cognitive development and emotional development as well. There are all sorts of academic outcomes. Kids who are bullied may avoid school, they may do poorly in school, they tend to be more truant and drop out more often.
Copeland: A lot of this is about raising awareness that bullying is not a harmless rite of passage. This is something I think that people are starting to understand. I think we still kind of look at it as something that is kind of bad but maybe short-term kind of bad. Part of what we are learning from this study is that these kids, the victims and the bully/victims, are continuing to have trouble a decade after the bullying has stopped.
Sarampote: SAMHSA (Substance Abuse and Mental Health Services Administration, actually has a registry of prevention programs that are available to schools and to policymakers that includes online resources around bullying prevention. So that's a resource. Also a great resource put out by the Department of Health and Human Services is www.stopbullying.gov, which is a great resource for parents, for teachers, to identify what bullying is, the signs of bullying, the effects, and what one can do to prevent the bullying itself and the long-lasting effects of it.
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Dr. Gail Daumit: This is the longest and largest randomized behavioral weight loss trial with participants of serious mental illness that's ever been done.
We know this population has an extremely high risk of premature mortality- three times higher than the overall population. And about eighty percent are overweight or obese. They really need weight loss programs.
One issue has to do with the psychotropic medications that they take- that they need to take for their overall health. But many of these agents cause weight gain through increased appetite and other mechanisms.
Betty Laney: I cook the food. I order the food. I definitely use strict portion controls. We use less fat foods I try to introduce the clients on a regular daily basis to low fat foods, low calorie foods, how to prepare foods, what's better for you. I introduce them to things, they may have wouldn't or may have never tried before.
Dr. Gail Daumit: We found that we had significant weight loss in the intervention groups compared to the control groups- seven pounds- which is really consistent with mny of the other weight loss trials in the general population.
Jeff Richardson: Frankly, people do not think that people who have mental illness can be successful. And I think this study really supported how successful people are and how individualized peoples recoveries are. And the results were staggering and empowering to so many people here at Mosiac.
Dr. Gail Daumit: The change that we measured was weight and so we saw that physical health change but we also saw participants that felt better about themselves overall. We had a couple that went off and got exercise trainer certification and are now exercise leaders in their own psychiatric day programs after the studies ended.
Before now we weren't really sure that this could be done and now that it can be done we need to figure out how to spread it.