Technology
The Next Big Breakthrough
In this episode of the Insights on Psychiatry Podcast, Dr. Charlie Marmer discusses the advancements in precision psychiatry over the past two years. He emphasizes the importance of tailoring treatmen...
The Next Big Breakthrough
Technology •
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Interactive Transcript
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Welcome to the Insights on Psychiatry Podcast. I'm excited to introduce our guest today, Dr.
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Charlie Marmer, who is the chair of our psychiatry department at NYU Grosswood School of Medicine
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and NYU Langone Health. Dr. Marmer, thank you so much for being with us today.
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Dr. Gowler, it's a great pleasure to be with you. I especially have fun working with you on our
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shared innovative research projects to advance precision psychiatry, so perhaps we can talk about
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that too. Yeah, absolutely. And what's really interesting is that we were able to talk two years
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ago about precision medicine, especially in psychiatry. And can you feel us in, what have
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been the advances in the last two years in precision psychiatry? And are you happy with the pace at
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which things are moving? I would say the major advance, separate from specific studies,
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which aim to try to personalize treatment rather than to apply a one-size-fits-all. Or I would say
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to go beyond the traditional way in which we've tried to provide treatment guidelines. So we have
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over the last 30 years or longer been evolving specific guidelines for the evidence-based
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practice for the treatment of stress, anxiety, depression, psychosis, addiction, etc. And if you
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look at the guidelines that have been published by the American Psychiatric Association, the American
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Psychological Association, the World Health Organization, and many others, they will generally say
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it is recommended for a patient with a new onset of depression to start with the first line
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treatments. If they're successful, great, if not, go to the second line, then go to the third line,
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and then if the patients are still very difficult and refractory to treatment, use specialized
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approaches and special assessments and consultations for the very complex cases. That has been
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helpful to some extent. It's certainly an advance over one-size-fits-all treatment, but it's not
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precision medicine in the way that, let's say cancer is treated now. And the major
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advance, I think, has been a growing recognition in the field of psychiatry of the urgent need to
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develop precision medicine so that if I refer you a patient with depression, you'll be thinking
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about that patient not in terms of first and second and third line treatments, but who is the
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person I'm working with today? What are their unique biological features, age, gender, ethnicity,
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other features? What are their unique psychological features, their conflicts? What are their unique
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social and cultural features? Are they highly educated from stable families? Are they from
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really were disadvantaged in many ways? Didn't have good healthcare growing up and maybe not
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a great education? They may all present a younger woman, let's say, South Asian woman from a highly
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educated, prosperous family, presents with sadness, loss of interest, difficulty sleeping,
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concentration problems, feelings of despair and hopelessness, an older Caucasian male who's had a
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history of head trauma and comes from a violent neighborhood and has from a poor background,
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hasn't had great education or the privilege of excellent healthcare, and may also have the same
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symptoms, but clearly they're very, very different. We talk about the biopsychosocial model,
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but we're now beginning to ask the question, how are the unique biological, psychological,
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social and cultural characteristics of my patient that I'm working with today and how do I adjust
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the treatment? So there is much more buy-in to that. There's progress in some studies where
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beginning to find certain clinical features, cognitive features, and even genomic and neurosurgery
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features will help us say which treatment for which person at what time, but the biggest revolution
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is the understanding that we have to move in psychiatry to where cancer has moved so successful.
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And almost moving away from trial and error and moving more toward gathering all the data early on
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and then having a more precise treatment plan for that patient, moving forward and not just,
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hey, does this work for you or not? And then you have this pile or this grouping of treatment
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refractory patients who haven't benefited and I think precision medicine is saying we want to make
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sure that we're not having this group of treatment refractory patients that we don't know what to do
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with just because they didn't benefit from the first, second, third line treatment. Exactly.
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And I would say if we go back 30, 40, 50 years into the history of the treatment of psychiatric
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disorders, psychological disorders, not only was there trial and error approach, there was
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something even more problematic, which there was a school-based approach. I remember really on
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as an educator asking my a group of residents, when I was maybe junior faculty and I had a group
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of wonderful residents at the time I was an assistant professor at the University of California
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San Francisco UCSF, one of the great medical schools and I asked the residents I was teaching,
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I presented a case to them and it was a case of a patient, let's say, with a third occurrence
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of a major depressive illness. And I asked them each to present what they thought would be the best
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care plan for that patient. And the response actually was not to start with one common treatment,
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it was completely school-based. One resident was very interested in psychoanalytic psychotherapy
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and they started with a psychoanalytic formulation of another, was very interested in neuropharmacology
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and psychopharmacology. They started with a medication approach. Another was a behaviorally interested
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person. They started with a cognitive behavior therapy and a fourth was becoming interested in
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some other approach. And fundamentally, the treatment that they would have given that patient,
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if referred to them, was actually not based on the specific needs of the patient. It was based on
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the interest, passion, and bias, so to speak, of the clinician depending on the school. So,
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if they, in practice of a patient with depression at that time was referred with depression to a
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psychoanalyst, they would get psychoanalysis whether they had bipolar depression or not. If they
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were referred to a psychopharmacologist, they would get psychopharmacology whether or not the origins
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of their problems was in childhood trauma. If they were referred to someone with another point of
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view, they would get that approach. So, and I was thinking to myself as an assistant professor
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at the time, imagine if I was referring a patient with atrial fibrillation to a cardiologist.
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And the treatment for that arrhythmia was determined by the cardiologist preferred school of training
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as opposed to the basic needs of that patient. Yeah. And I think what we are saying is, if the more
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we can understand kind of the, all of the factors, then we can have a more precise treatment plan.
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And I think this is also really important. You think of how many people have comorbid conditions,
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then you add another layer of maybe that trial and error because we're not looking at kind of
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treating conditions maybe in concert. We have to look at what are the presenting problems?
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We have to look at all of the complexity of the medical illnesses, neurological illnesses.
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But we have to look also at education, culture. We have to look at life experience. We have to look
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at also biology, including sex. For example, there are some developing data to suggest that if a man
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in their mid-30s and a woman in their mid-30s both present with relatively similar depression
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symptoms and they are suitable for initial treatment with medication that on average,
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the woman will do better with a selective serotonin agent anytime from men or ketamine
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opause. And the man may be do better with some mixed receptor agents, drugs like wild butyimbium,
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bupropreon, ventilifaxine, pristectin, others because of the difference in the biology. And
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interestingly, after menopause, a woman who may have done very well with a selective serotonin drug
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may do less well and may need a drug more like the 35-year-old male may need unless they're also on
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estrogen replacement therapy after menopause. So just to simple forget about all the great complexity
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of culture and genetics and family background and brain imaging findings, just the simple age
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and sex may be profoundly important. And it makes so much sense. I guess the bigger question is how
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are we getting closer to that? And what are you excited about that's actually happening,
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getting us closer to kind of taking all this data and understanding the psychiatric complexities
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in an individual? Two ways, two things have happened which are very, very favorable.
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One is there's a growing consensus among clinicians, students, and researchers that this is
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essential to move our field together. The second thing is that there's a growing consensus about
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the agencies that provide the funding for the research to advance the NIH, DOD, VA, DARPA,
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and other agencies that fund the majority of psychiatric and psychological research.
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They are also becoming very, very interested in initiating requests for applications for precision
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psychiatry proposals. And the final thing is, which is very interesting, is our field is
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maturing to give us the tools we need. We're leaving aside simpler things like age and
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sex and education and cultural background, which we've been able to assess for a long time,
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of course. We now have sophisticated human genomics to study the genome in psychiatric illness.
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So more and more clinical trials now include collecting DNA and RNA so that we can study the
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genomic contributions. We also have much more sophisticated non-invasive brain imaging,
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and we have a whole series of other fascinating ways to try to understand the neurobiology of
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psychiatric illness. For example, there are brain banks of people who've been visionary and
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have said at the time they pass away, they'll contribute their brain because they've struggled
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life long history of bipolar disorder or PTSD or schizophrenia or some other alcoholism.
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And those studies, those post-mortem studies allow, of course, for a very detailed interrogation
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of brain structure and functioning, those become published in part of a public databases,
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and then researchers such as myself and others interested in precision measure can use those
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as reference samples to say, oh, so these specific genomic pathways may be disturbed differently
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in these disorders. Now I have the DNA and RNA of my patients and my trials. I can be informed
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by the post-mortem reference samples to know where to look in the genome in my patients.
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There are many other ideas. We go along blood. We're starting to learn about exosomes which are
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actually coming directly from the brain and how genomic cargo on them. We are doing studies,
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we're planning to do some collaboration at NYU with colleagues at the Mayo Clinic,
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or in which we're harvesting live cells in our clinical trials. And those cells can be,
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they will be blood cells, but they can be programmed backwards to stem cells and then forward to
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neurons. And we can even grow brain organoid sort of brains in a dish. And we can then study those
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brains. We can expose those brains to alcohol. We can expose them to drug treatments. So we're
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beginning to triangulate all of those things with animal models. And I believe we'll be able to
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advance our field and become precise. The goal is to do in psychiatry what is now done in
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breast cancer. Yeah, you remember how breast cancer was treated in the 50s? Do you have a sense of
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how if someone presented with breast cancer, how it was treated then? One size fits all. Everyone
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got some combination of surgery, radiation, and chemotherapy. It was not specific to the person
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or their general tumor. And it was often associated with great side effects and often not great
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outcomes. But we didn't know beyond the fact we knew that radiation could help some women with
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breast cancer. We knew that chemotherapy could help and we knew we had to remove the tumors with
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surgery where possible. But we didn't know in precisely for a patient has breast cancer now.
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Obviously we biopsy the tumor. We find his genomic features and we begin with
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treatments that are highly specific to that form of cancer. As a simple example, estrogen receptors are
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studied, progesterone receptors are studied, and a set of receptors called HER2 receptors are
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studied. And if the patient is estrogen negative, progesterone negative, and HER2 positive,
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they're likely to be started with the drug Horseptin, which is a monoclonal antibody specific to
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their tumor does not attack other parts of their body, does not attack healthy cells in their
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gut or their brain or elsewhere. And think of the enormous advance. This is a treatment specific
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to their form of cancer at which targets the vulnerability of those cancerous cells and does not
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attack the entire body of living cells. And it seems like psychiatry has not been able to have
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those advances in part because the animal models has been a possibility. But it seems like with
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technology and all these opportunities to gather more data in these larger systems or you said even
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after their death, it might help us to kind of make more of these precision medicine models.
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It's a wonderful observation. I think there are two major reasons that have limited
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three that have limited the advance of precision psychiatry. The first dose has been a failure
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of imagination to understand that we could do that in our field. That's changing. The second is we
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have animal models, but many of them are not very good representations of the illnesses. There
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are, so to speak, animal models for psychosis, but rodents don't have delusions. So they're very,
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very difficult. You have to do an animal model of let's say a circuit disturbance in the
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hippocampus, but not the illness itself. We have several diseases that are quite
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amenable to animal disease modeling. The best are trauma because the same circuits in rodents
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are altered when they're exposed to predator threat as are humans when they're exposed to combat.
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So that's very helpful. And perhaps the very best animal models are alcohol and drug abuse.
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Because for example, rodents will become addicted to cocaine. They will become addicted to alcohol
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and to stimulate other stimulant drugs. And there you can then understand the animal models
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are very close to what we need to do in humans. So, but the final thing is that has held us back
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up till now is in precision medicine and all other areas of medicine, we biopsy the organ of disease,
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breast cancer, prostate cancer. We have access to arrhythmias. We have access to the tissues
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of disease. In the case of human neuropsychiatric illness, except under unusual circumstances,
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we don't biopsy the living brain of the patient. So, what we're trying to do is approximate
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what is happening in the brain by looking very far downstream. Theodomisomy of that story about
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the person who lost their keys at night and they're looking under the lampost. But they didn't
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lose their keys. So they're asked why you're looking under the lampost? Well, that's where the light is.
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But the keys are not there. So the problem for us is when we study DNA and RNA in peripheral blood,
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the expression of DNA in peripheral blood cells is not necessarily closely related at all to
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single cell gene expression in specific neurons and specific areas of the brain in a given
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specific psychiatric disease. So the question is, can we find a proxy for the brain biopsy?
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We call them just for ease of communication, a liquid biopsy. Is there something in the blood
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that actually reflects what's going on in the brain? We're very interested in exosomes for that
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reason because they're in peripheral blood. They can be isolated. They're vesicles that carry a
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genomic cargo and they have some genomic features on them or markers that would tell us more or
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less where they're from. Are they from the brain or the liver or the kidney? If they're from the
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brain, where in the brain? Are they from the hippocampus, the amygdala or the basal ganglia or the frontal
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cortex, PFC? And maybe even more specifically among those that come from the amygdala, are they from
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the central nucleus of the amygdala or another nucleus in the amygdala? So that's interesting because
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in a way, those features are then much closer to what may be dysregulated in the brain. We also
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like the idea of these postmortem reference samples because they give us clues of where to look
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because we actually have the genomic features from specific brain cells and brain regions
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and we like the brain organoids also because they replicate actual brain structures. There may be
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other strategies, but even you ask me, what's held us back? A lack of understanding that this is
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critical, that's changing. A failure of animal models to closely replicate human brain diseases
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in psychiatry particularly diseases with cognitive disturbances such as in psychosis. And then
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a lack of ability to actually biopsy the organoidylists. We are the only field, psychology and
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psychiatry are the only field in medicine that does not routinely biopsy the organoidylness.
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Yeah, it sounds like what you're saying is that's brain scans are not the answer in kind of
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precision medicine necessarily. We need kind of scalable interventions or scalable ways to assess
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looking at, you know, like you said, these records are gathering data in these large scale kind
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of medical records will be. I would say brain scans are becoming more sophisticated, pet scans,
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MRI scans, other kinds of scans, spec scans. We have a lot. We're making progress. They provide
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useful information. I would say studying DNA and RNA in peripheral blood is useful. It provides
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information, but it's not going to be at the level of specificity of actually, for example,
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you and I have a shared deep interest in post-traumatic stress disorder. We have some pretty good ideas
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from animal models which circuits are involved. We know that we know the amygdala is involved,
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we know the hippocampus is involved, we know the insula is involved, and we know the prefrontal cortex
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is involved among other areas. But when we have, you and I are collaborating together in the clinic
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on a patient who's not responding well to treatment for complex trauma, we do not biopsy. They're
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amygdala to find out what's different about this patient. That's the main limitation we have. That's
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why we are much less advanced than the treatment of prostate and breast cancer.
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And the hope is that we find ways to make it more accessible and precise by looking at some of
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these records as well. Yeah, alternative models, more accurate sensitive animal models,
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post-mortem reference samples, exosomes, brain organised, and other things we haven't thought of
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but the point for our listeners is very straightforward until we can accurately reconstruct
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what the neuro transmitter and neurosurcut disturbances are in a patient-specific way.
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We will be somewhat limited in precision myths. And do you think that would be ultimately what do
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you hope that we are able to get that information or do you hope that in combination with other
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factors, I know you're into facial action coding and biovoice markers kind of using other
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kind of pieces of data to put it all together into a larger model to get more precise if we can't
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do these biopsies. Well, so great point. So in addition to advances in genomic psychiatry
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and imaging psychiatry, you and I and others are working together to advance digital psychiatry.
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The advantage of digital psychiatry of studying voice quality of studying the structure of language
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with large language models using AI, studying facial expression using facial action
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coding. I was very influenced by this, interested in this because in my years at UCSF,
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I got to know and had the privilege of knowing and becoming friendly with and asking for
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research advice, one of my senior mentors, Paul Eckman actually developed the facial action
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coding system. He was Paul's a remarkable person. He actually came to the conclusion that there
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was a limited number of unique human facial expressions. He mapped out the muscles that were involved
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creating those facial expressions and then he went to multiple different cultures, including
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South Pacific Island cultures, Asian cultures, many different cultures and found that even though
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cultural differences were great, even though language was different, that actually the same
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range or palette of human emotions, anger, sadness, shame, etc. were expressed in all these
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cultures in the same muscle groups, which is a fantastic discovery. So Paul really inspired me
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to do this work, but we can also use cell phones, which give enormous amount of information.
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We know that when people are depressed, they often, their digital location is different,
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they do less things, they stay home more, they retreat into bad, they avoid social situations,
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all of that's very interesting and valuable. And the final area, not the final, but another
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major area which is going to advance precision psychiatry is computational modeling.
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The ability to use advanced AI and form machine learning and very fast computers. I'm beginning
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a collaboration now which I hope will be radically interesting. I have a colleague, renowned quantum
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physicist, Dr. Javit Shabani at NYU, who is one of the world's leaders in developing quantum
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computing. His laboratory at NYU is developing next generation, Cubots which are like the chips for
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quantum computing, quantum computing, even in the kind of rough and inaccurate proof of concept
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models can handle vast amount of information and process it in lightning speed time. So we're going
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to collaborate together, Dr. Shabani and I on a project in precision psychiatry. In this particular
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study, it happens to be a clinical trial that was completed by NI AAA, 346 subjects. We have DNA
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and RNA on every one of them before treatment. They were treated with GABA pen, an anti-convulsive
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drug which reduces alcohol craving. And we also collected RNA after treatment because it changes
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with treatment. Okay, so I will ask you a question to be playful. How many unique variables do you
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think we have on each of these 346 participants, patients, that we could model to try to understand
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why some people respond well and others don't respond well to GABA pen for AUD, for alcohol use.
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Take a guess how many uniquely different variables are in the database on each of these patients?
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200. How many? 200. Okay, how about a little higher? Okay, 2000. How about a little higher?
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5,000. 22 million. We have 22 million unique features because in designing this study,
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I had identified, I am my team, other colleagues, had identified 1,300 genes in the human genome
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that we thought might be relevant for understanding how people respond or fail to respond or get
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side effects or don't get side effects to GABA pen for the treatment of alcohol use.
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And I asked the director of our wonderful NYU Human Genomes Genomic Center, Dr. Adriana Hege,
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a great colleague of ours, and part of this study, to estimate what the cost would be
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to sequence those specific genes and their transcripts. And she gave me a price that was pretty
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high and said, you know, Charlie, we can do something much more interesting because we have now the
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sequencing sophistication to sequence the entire human genome, 22 million features, for less money
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than the targeted sequencing of those 1,300 genes. And of course, you'll get those genes in
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their transcripts, but you'll get all 22,000 coding genes in their transcripts. And you will also
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get all of the so-called dark matter in the human genome, which plays an important regulatory role,
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even though those genes don't code for proteins and it directly affects cell function. They
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promote and remodel in transcription, factor regulation, post-transcriptional changes of the
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structure of transcripts, of proteins, etc. So we have it. And we have also, of course,
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clinical feature is we have other things, but the big data is the genome itself, right? So we have
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now we have 346 people with more than 22 million features. Now what were you taught in your statistics
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courses about how many subjects you needed for the number of variables? In other words, in
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traditional statistics, you're limited by sample size and you can, you need a certain number of
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subjects to variable ratio, right? And you remember what you were taught about that in conventional
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statistics? It's about, you know, you need maybe a 10 to 1 ratio or something.
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In the world of AI, there's not actually a limit on the number of features you're going to have
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per subject. There's a limit on the computational resources needed to manage that information and
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make sense of it. And we think that quantum computing will help solve that problem. So that's
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the next thing. But even using NYU Langone Medical Center's high capacity imaging, we can do pretty
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well. But right now when we run a machine learning model to say which genetic features or which
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imaging features or which clinical features or cognitive features, predict who will and will not
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be a likely responder to a trubanant, let's say Gabba Penton for alcohol use disorder, it can take
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weeks to run those models and these quantum computers can run them in a fraction of a second.
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And can make sense of like you said, and the other thing about quantum computing is it probably has
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the capacity to create a much more sophisticated map of the interrelationship of these factors
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than conventional computing. So it's not just light years faster, it's also going to be more
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precise. And is the goal you think to get even down to go to the complex to get more simple,
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because it's so many pieces of information and it might be overfitting the model or the data,
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is the goal then to kind of know what is actually most important and then we can kind of pull that
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out. The goal is to do some targeted hypothesis testing with a smaller number of features.
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Then do a very broad exploratory model with all the features and then reduce those to the most
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important features. Part of the output from AI models is a variable importance plot, which will
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read out among these 10,000, 100,000 million, 10,000, 20 million features or more, which five are
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ones carrying the signal. And then we can study those and we can ask which medications or
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psychotherapy or TMS or remodulation is likely to move those features. Yeah, so going from the
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complex to the more simple. And just in our final question here, looking ahead, what are you most
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excited to see happen in precision medicine in the next decade? I think we're actually going to do
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two dramatically interesting things. The first is we're going to take psychiatric illnesses
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which are not unitary, they're heterogeneous. For example, we already know that there's six or
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seven or more forms of depression. There's bipolar and unipolar. There's depression which involves
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psychotic symptoms or does not involve psychotic symptoms. There's typical and atypical depression.
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There's others as well. Okay, so we know that depression has multiple subtypes. We suspect that
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trauma probably does. We know there's PTSD that has prominent cognitive impairment. We know
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that in simple, those who have a suffer enormous trauma exposure in early development have a different
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set of problems than a high functioning person who gets survived a traffic accident.
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We know that there is PTSD with prominent association symptoms and not. So there's not one PTSD.
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There's probably a half a dozen major types of PTSD. I think we'll be able to confirm what they are
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and confirm them with biological and psychosocial features. The second thing is we'll be able to do
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these precision medicine treatment models that say who's likely to respond to which treatment
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for which subtype? Yeah, which will totally change the way that we're looking at psychiatric illness.
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And I think even starting with the diagnostics we're already starting to realize like you said
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there's a spectrum and there's all these different types. So the better that we can diagnose and then
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treat patients will lead to better outcomes. So a woman with a complex PTSD with associated
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features whose six years old is not going to be treated the same as a man with a more simple PTSD
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and a man who came from a very difficult background and had three tours of duty in the military
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or a woman who was in the military and has a very complex PTSD will not be treated the same
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as someone who was walking down the street as one of my patients was and tragically as they were
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walking down the street in San Francisco at the time I was doing the study. Someone jumped to
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their death from a building from high above and they witnessed this horrible event and the person
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had gruesome injuries of course and it was completely horrifying to them but they were very high
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functioning before they went through a period of nightmares flashbacks and startle reactions and
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but they responded to a you know short course of treatment and were very well obviously that's
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a different kind of PTSD than someone who was sexually assaulted and abused during their childhood
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and neglected and has suffered enormously during their lifetime. So yeah I think it's going to
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give a lot of hope to patients and also I think to doctors and clinicians being able to
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have more confidence in the treatments that they're actually disseminating and implementing
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with their patients. If a patient has a solitary nodule of breast cancer which has not escaped
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the duct they with certain genetic features they're going to be treated they are currently treated
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very differently obviously than someone who has a very aggressive metastatic breast cancer
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with other genomic features and so the illnesses are treated as precisely as possible
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for their stage their aggression their genetic features and other factors we want to be able to
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treat depression that way. Let me if we have time I'd like to conclude with a very interesting
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and dramatic example of precision psychiatry in depression. Around 2015 our neurology psychiatry
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program which we have at NYU where we have experts trained in both neurology and psychiatry
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their board certified neurologists and psychiatrists were asked to consult and this was on the
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in the department of neurology initially on a patient who had had roughly 20 years of completely
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failed treatment for depression. So let's say for the majority of their adult life they were
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depressed miserable very difficult to work very difficult to maintain love relations and family
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relations and enormous personal suffering that patient had been treated with all of the evidence-based
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treatments psychotherapies for PTSD, psychodynamic, cognitive behavioral others that patient had been
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treated with virtually every type of medication treatment for depression SSRIs non SSRIs other
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antidepressants mood stabilizing drugs, neuroleptic drugs and others completely failed.
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Not remembering right now if they had neuromodulation treatments but they definitely had ECT
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and it complete failure. The patient was thought to possibly have a rare more rare neurological
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disorder and it was justified to perform a brain biopsy to rule that out. So they had a small needle
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brain biopsy done under neurosurgical conditions and needle was presented through the orbit and into
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a silent part of the prefrontal cortex relatively safe thing to do the main complications infection
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but if it's done under neurosurgical conditions it's safe to do and then the tissue was taken
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and sent to a neuropathologist and the neuropathology report came back massive invasion of inflammatory
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cells quite unexpected and the patient was treated with a novel anti-inflammatory drug which crosses
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the blood brain barrier and for the first time in 20 years had significant relief from their depression.
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A single biopsy with a single confirmation. We can't do that routinely
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but I mentioned that case as a proof of concept as an illustration of what could be done
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if we knew what was actually occurring in the brain. Yeah and I think like you're saying even with
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that example is kind of the theme of this that going from the complex to the simple and maybe we
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understand more about the brain when we kind of understand all that maybe it does come down to
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you know one single biopsy like you said or like in what you're talking about it might come down
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to just understanding a few different factors and how they integrate together to present for this
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patient. Correct and if we knew that it was invasion of inflammatory cells in the brain that
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were causing the depression we might then be able to look in the blood or somewhere else or in
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brain imaging or in the genetic background to find a marker that was associated with that even
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though we weren't routinely biopsy. So let me give you another example we talked about it on
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an earlier drug. Casted it in the 1800s a common reason or perhaps the commonest reason why patients
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had long term hospitalization in state mental hospitals psychiatric hospitals in America
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including in New York was turned out to be the neurological complications of syphilis,
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neuro syphilis and so that was a more common reason to spend end up spending years, decades or
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your life in a state mental hospital then was let's say schizophrenia. When the the infectious
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basis of neural syphilis was discovered with the spirochet and treatments were developed of course
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now that disorder is an infectious disorder it's no longer considered a psychiatric disorder and it's
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treated and we don't have patients with neuro syphilis in psychiatric institutes if we really understood
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and that's an example of going from the complex and the treatment completely treatment on
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response of condition requiring long term psychiatric hospitalization to a clear simple idea of what
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is disturbed a specific infection of the brain by a specific organism with a specific treatment
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nothing could be more clear than that right so there is going from the complex and the enormous
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pain and suffering and a sense of hopelessness to an understanding a treatment and a cure.
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Well it's exciting for I think patients for clinicians and for researchers and I think it'll be great
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to see where it continues to grow thank you so much for talking with me. It was a pleasure talking to you
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and it's an even greater pleasure working and collaborating with you. Wonderful. Well thank you to
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all of our viewers and listeners and if you liked this episode please rate and subscribe to our
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podcast where you listen or watch our podcast. Thank you so much from all of us here at NYU Langone
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Health and the NYU's Grossman School of Medicine.
Topics Covered
Insights on Psychiatry Podcast
precision psychiatry
NYU Grossman School of Medicine
personalized treatment
biopsychosocial model
treatment refractory patients
genomic contributions
brain imaging
psychiatric disorders
comorbid conditions
mental health treatment
clinical trials
neurobiology of psychiatric illness
psychopharmacology
cognitive behavioral therapy