4. 5. 6. 7. 8. 9. 10. So good evening to those on the East Coast and good afternoon to those of you joining us from the West Coast. My name is Dr. Regina James and I am the deputy medical director and chief for the division of diversity and health equity here at the American Psychiatric Association, and I'll serve as your moderator for this webinar. Today we're going to discuss a very important topic the role that genomics can play in ameliorating mental health inequities. So to set the stage for the webinar, I'd like to share a few key points that I hope can serve as a springboard for discussion for the panelists. There was a 2011 report from the National Academy of Sciences that call for the adoption of precision medicine, where genomics, environmental exposure, and other data will be used to accurately guide individual diagnosis. Genomics is truly transforming all of healthcare by making it more targeted, personalized, and proactive. Genomics can not only help with the preventive side of care, but also with determining treatment options. And just of note, the cost of genetic testing has been coming down over the years, and I believe depending upon the test, you can get it for as low as $100. So with all of this data, information, and innovation comes responsibility. What about privacy and protection? How can we ensure that there is no unfair discrimination and misuse of genetic information? What about equity? How can we ensure that all of the advancements gained from genomics, particularly in psychiatry, benefit all populations in all communities? And finally, bottom line, what role can genomics play in ameliorating mental health inequities? So in our discussion tonight, that's exactly what we'll focus on, examining genomics and its role in mental health inequities. We have a fantastic panel that will lead this fruitful discussion, and let me introduce each of them for you. First, we will have a presentation by Mr. Vince Bonham. Mr. Bonham is the Acting Deputy Director at the National Human Genome Research Institute at the National Institutes of Health. He is also an Associate Investigator at the Genome Institute within the Division of Intramural Research's Social and Behavioral Research Branch. Mr. Bonham leads the Health Disparities Unit, which investigates the equitable integration of new genomic knowledge and precision medicine into clinical settings, and how genomics influences the use of the constructs of race and ethnicity in research and clinical care. Prior to his tenure at NIH, Mr. Bonham was a fellow in the American Association of Medical Colleges Health Services Research Program and a tenured faculty member at Michigan State University with appointments in both the College of Medicine and Law. So Mr. Bonham will be our first opening speaker, followed by Dr. Dolores Malaspina. Dr. Malaspina is a Professor of Psychiatry, Neuroscience, Genetics, and Genomics, and Vice Chair for DEI in Psychiatry at Icahn School of Medicine at Mount Sinai. She is an expert clinician with extensive scientific work in psychiatry. Throughout her 30-year career, Dr. Malaspina has made important scientific contributions, and I'll just name a few. First, being the first to propose that paternal aging is a predictor of sporadic schizophrenia risk. Another, demonstrating increased hippocampal activity at rest in schizophrenia, and demonstrating that olfaction, or the sense of smell, is related to social function in humans. A distinguished educator, Dr. Malaspina has lectured widely and published 300 peer-reviewed papers and scientific chapters. She is the editor of the International Journal of Mental Health and sits on the editorial boards of several journals. Welcome, Dr. Malaspina. And she will be followed by Dr. Ina Kinney. Dr. Kinney is the founding director of the Institute for Genomic Health and Professor of Medicine and Genetics at Mount Sinai. She leads research at the interface of genomics, medicine, and computer science. Her research spans a number of different fields, including population and statistical genetics, computational and machine learning approaches for genomics, biobank and cohort-based research on monogenetic disorders and common diseases, and polygenetic risk for human diseases and precision medicine. Her goal is to lead new paradigms for genomic research and to enable genomic medicine on a global scale. Dr. Kinney is principal investigator in six large international programs focused on genomic research, medicine, and health, and is in the top 20 NIH-funded genomics researchers in the United States. She is a scientific advisor to many genomic and genomic medicine initiatives in the government, nonprofit, and industry arenas. She's published over 90 papers in leading journals and has been cited over 13,000 times. Welcome, Dr. Kinney. So before we continue, I want to take this opportunity to thank our first APA president, Dr. Vivian Pinder, our CEO and medical director, Dr. Saul Levin, the APA Board of Trustees, council members, assembly members, caucuses, and administration for their continued and continuous support in advancing mental health equities. And at this point, I would like to take the virtual mic and hand it over to Mr. Bonham. Welcome, Mr. Bonham. Great. Thank you, Dr. James, and thank you for that great invitation. Can you see my slides? OK, great. So again, thank you for this invitation to participate in this fireside chat this evening with this great panel. And I'm looking forward to the conversation that we have. As stated by Dr. James, I'm at the National Human Genome Research Institute at the National Institutes of Health. And I'm pleased to help to lead many efforts that are going on within our institute with regards to health equity. And I want to explore from the perspective of psychiatry some of the key issues that I believe that we are addressing that I would love for our conversation this evening to include. So the question that was raised as part of the title for this session this evening is, what is the role of genomics in ameliorating health inequities? And I want to argue that there is a role, but I want to challenge us that that role may not be what we think when we think about the role of genomics and ameliorating health inequities. But let me start to say that we are at a really exciting time with regards to the field of genetics and genomics. This last decade has really been an explosion of new knowledge with regards to understanding of gene variants that may put an individual at risk for various types of diseases and conditions. We're learning and understanding better the role of the genome in health, disease, and our understanding how to address that with new treatments. And that's not limited to any one area. There's clearly with regards to psychiatry and genomics important work that has taken place over the last decade that really now we have this concept of precision psychiatry. And so as we explore this question about precision psychiatry and how we use genetic and genomic information and the treatment of individuals and their diseases and conditions, we need to raise some questions about what we understand today. And so I do that by framing this question this way. Will everyone benefit from genetics and genomics in psychiatry? And thinking about genomics and precision medicine, and we think about it related to diagnostics, risk assessments, pharmacogenomics, new drugs and treatments and gene therapy, how will this actually benefit everyone? And what are the issues that we need to grapple with as both a medical community and a scientific community to help to make sure that more individuals can benefit from genomic precision medicine? So I want to start my talk by framing it around issues of importance for you as a community with regards to various mental health disorders. And I want to go to a specific area of data that is being collected by the genomics community across the world, and that is conducting genome-wide association studies. These are studies to better understand variants in different ancestral populations that may be related and correlated with various types of diseases. And here I'm showing one page from the GWAS catalog and identification with regards to schizophrenia and identifying individual genetic components that are important to this condition. But the second slide here that's also from the study highlights two examples of studies within the GWAS catalog. And then these two are examples of a number of studies that we have of data across the world with regards to genetic variants and GWAS-related analyses and understanding of disease and health. And here I want to just highlight that these two examples of studies are very common because they are in European ancestral populations. This is a problem. This is an issue that the field of genomics is grappling with. This is a field that biomedical research is grappling with. And I argue this is a field that medicine and psychiatry must grapple with, that the vast majority of studies have been done on European ancestral populations. So as we think about how we move forward, there's actually been a lot of work over the last 15 years focusing on this problem. And I first want to highlight a study that was conducted and published in 2009 by David Goldstein and then Carlos Bustamante did some similar analyses that showed that more than 96% of all GWAS studies had European ancestral populations. So when you go to that catalog in 2009, more than 95% of all of the studies were of European ancestral populations. And you think about the global population, European ancestral populations are less than 15%. So all of the missing understanding of the genome and the variation that's important to understand disease. In 2016, Alice Popejoy and Malia Fullerton replicated that study. And this is the article that was published. And they showed in 2016 that there had been a shift, that we had gone from 96% of all of the studies were in European ancestral populations to 81% of the studies were in European ancestral populations. But what they showed that the significant increase and shift in other populations was primarily in East Asian populations. 78% of that change was in Asian ancestral populations. And if you think about all of the other ancestral populations of the world, it was still less than 4%. This is Common Drum, a drumbeat that has continued in my own research group, conducted a study where we actually looked at specific diseases. We looked at cancers, heart disease, and we tried to understand both for genome-wide association studies, as well as sequencing studies. What were the ancestral populations of most of the studies that were in our dbGaP at NIH and the GWAS catalog? We saw very similar findings, that the vast majority were European populations and other populations were missing. But this work continues. Dr. Martin and her group published in 2019 this great figure that shows the example of the bias that we have. And Dr. Morales published in 2018 this example here that showed that still 78% of the GWAS data in the catalogs were of European populations. The sampling bias has an impact on healthcare and medicine and our ability to use genetic information in disease. And finally, I just want to show this work from Sarah Tishkoff's group that shows a similar situation. Now, it's not that things are not getting better, and you see here when they published their work, that only 52% of the studies were exclusively in European populations. But if you looked at individuals, it still was over 75% were all European ancestral populations. So this is a challenge that we have for genomic medicine in psychiatry. It's a challenge that we have for genomic medicine in all areas of medicine. And we see this as an issue from the perspective of the National Human Genome Research Institute that we need to address. We need to break down the barriers that impede progress in genomics. And I argue one of the major barriers from equity perspective is the lack of diversity in the research studies that are being conducted. So the National Human Genome Research Institute is now leading a number of different studies that are targeting to include diverse ancestral populations, so that the vast majority of the participants in the study are not of European ancestral populations, and that we have greater diversity within the GWAS catalog, within the sequencing data, our understanding of the human genome. And I just want to highlight one of them, which is the polygenetic risk methods and diverse populations. The issue of polygenetic risk scores have limited benefit for populations that are non-European today. This is a problem. This is an inequity. And how can we get to a point where everyone can potentially benefit from this precision medicine in their treatment? So I want to make a shift for the last couple of minutes of my comments. And I want to talk about psychiatry, race, ethnicity, and genomics. And the challenge that we have to be very careful and thoughtful how we think about the constructs of race and ethnicity and genomics, including psychiatry, that we have to be careful not to identify variants with specific social groups in a way that could potentially cause harm and that are not based on valid scientific understanding. My colleagues and I in 2016 published a paper in the New England Journal of Medicine where we raised the question, will precision medicine move us beyond race? And we said, if the major challenges can be overcome, precision medicine could lead the way in reducing and ultimately eliminating the use of crude racial and ethnic census categories in drug prescribing. But we said three things must happen. First, we said that there must be education of physicians on how to use precision medicine to understand it and the benefit. Second, we must think about the costs related to precision medicine. And third, that we must have diverse ancestral populations in the studies to truly have precision medicine that can benefit everyone. My group in 2021 published a paper in the American Journal of Human Genetics that really pushes this question about the inappropriateness of use of race in genetic and genomic studies. And what we showed in a review of 70 years of history of the American Journal of Human Genetics, one of the most important human genetics journals, that there has been a change over time with regards to how populations are described in research. You see here in this figure from the journal, in figure A, that there's an increase in the use of ancestry to talk about populations. There has been an increase in the use of ethnicity and there has been a decrease in the use of race. And the complexity of the fluidity of these terms is important for the scientific community to grapple with as we move forward. I want to end by highlighting that the National Academies of Sciences has a consensus study that is currently being convened. It was sponsored by the National Institutes of Health, 14 institute centers and offices at NIH are co-sponsoring this consensus study. And the study members are reviewing existing methodologies and benefits and challenges in the use of race and ethnicity and other population descriptors in genomics research. On the first meeting, first public meeting is coming up of this group on April 4th from 11 a.m. to 5 p.m. Eastern Daylight Time. I encourage you to go to the website to register, to listen in on the conversation that's going on within the scientific community with regards to the use of race, ethnicity and ancestry as population descriptors in genomics research. So with that, I want to come to a conclusion and go back to the really what I thought was a question that was raised for the title of this fireside chat tonight. And this is my response. Genomics will not ameliorate health inequities. Health inequities are so embedded in structural issues within our country and our global world that we must address those inequities that deal with the social determinants of health. And genetics and genomics will not take care of those issues. However, failure to enhance diversity in genomics research and implementation of genomic and precision medicine and health care for all may increase inequities. If we don't be careful with regards to how we move forward to address these issues today. So with that, I wanna say thank you and I'm looking forward to our conversation. Dr. James, you're on mute. I'm just talking away. Thank you, Mr. Bonham for all that information that you have brought to the table. It really brought a lot of light and really some truly important issues. And I'm glad that you answered the question the way that you did. I'm also glad that you emphasized something that the president of our organization, Dr. Pender has as her platform, which is the significance and the importance of the social determinants of health on mental health outcomes. And you've actually truly underscored that as well. Now, as we, and thank you so much. As we continue, Dr. Malas-Pena, I'm gonna provide you an opportunity to reflect and please add your expertise to the table. Thank you. It's really my great pleasure to be a part of this looking forward symposium. And in doing so, I've done a bit of looking backward. Certainly I could not be more enthusiastic concerning Mr. Bonham's presentation and the enormous need we have that our genetic resources and our sampling are inclusive. What we can learn about human biology and what we can offer to individual persons can be greatly, greatly augmented. I have served at the interface as the psychiatrist in genetic studies, recruiting in the persons that we will evaluate, explaining to individuals why they should participate in genetic studies, doing the interviewing and providing those samples. We just completed for the genomic psychiatry cohort, recruiting in persons with African ancestry. And we are so pleased to be able to enrich the samples in psychiatry with black individuals. It was always a challenge to approach people and speak about why they should be in genetic studies. Sometimes there was a little bit of, I don't know, skepticism or, you know, what's going on here. But the idea of equity, the idea that they are underrepresented in this resource that may offer them treatment and cure is just a winning approach. And it was readily apparent that we could recruit these individuals. Currently, we were launching the Hispanic psychiatry cohort to also enrich the numbers of individuals with Latinx and Hispanic ancestry. Now, my first experience running a diagnostic site for genetic study goes back 30 years. I was the co-principal investigator for the Columbia University site of the NIMH Genetics Initiative. That was the first study launched and it had sites for Alzheimer's and bipolar. And at Columbia University, we were a schizophrenia site. And it was an amazing experience as a assistant professor to work with really the leaders in psychiatric genetics and to be at the table for the discussions about recruitment, about ascertainment, about the types of families we should look for. And those were the days of genetic linkage. So we were recruiting families that had two or more cases of schizophrenia. And then there was a big discussion about the interview and the diagnosis. And I will say after many months, the group decided that they just had to write their own diagnostic interview. And a lot of time was spent on the DIGS, the Diagnostic Interview for Genetic Studies, which is special in not being wet about a particular diagnostic categorization, not any version of the DSM or other diagnostic scheme, but instead gathers really rich and deep clinical information about patients so that algorithms could be used to frame the disease differently. Now, at the same time, I had launched with my colleagues at Columbia University, the New York State Psychiatric Institute's Schizophrenia Research Unit. And on that research unit, I was working very, very closely, not with patients recruited for genetic studies, but patients who were participating in research. And it was my first thought that that would be a very good place to meld the studies to identify the psychiatric history in the families of the individuals. But it turned out, I learned early on, that the vast majority of persons with a severe psychosis or with bipolar disorder do not have a family member who has the disease as well. Now, in our current association studies, that's not a requirement, but back at the time, I thought we really need much more history for these individuals in the Psychiatric Genetics Initiative. I was interested in how life course exposures, how trauma, how birth complications, how fateful life events could color the risk for psychosis. And perhaps it was a version back in the day of the nature versus nurture controversy of wanting to add life course information. And I was tutored on that by Bruce Dornwind, an amazing American psychiatric epidemiologist and sociologist who really had defined the trauma exposures with respect to PTSD after Vietnam. But the finding or the observation was that at that time, NIMH was not interested in the exposures. The response to my grant proposal at that time was the genetics will speak for itself. Also at that time, it was shown in our group that you could produce certain types of brain abnormalities that were related to the risk of schizophrenia. I'm thinking of hippocampal abnormality. And I submitted a grant on that topic and was told, and the title of that was stressed as a factor in hippocampal inflammation, that I was being very old fashioned, that the idea of stress and illnesses was an old fashioned idea. So you saw at that time, really a focus on the notion that the genes would tell the whole story. In fact, over time, it's been particularly this last year, really important and a relief to see the recognition that in fact, the social determinants of mental health are playing a very large role in the onset and the severity of psychiatric diseases. More so people would show in terms of severity and prognosis than the genes. Does that mean one is not important? Absolutely not. But it means that genetic research can include racially diverse persons, but also what we're hoping is information on the social determinants of mental health must be included with genetic analyses. It's possible, for example, that it's inflammatory pathways that are related to early trauma, prenatal adversity, and that these are coloring the onset and expression in people who have tremendous disadvantage. So thinking of the social determinants as a body of knowledge that must accompany the genetic information, I believe is where we are heading when we look forward at this point. You know, in psychiatry, we walk a very thin line about race and genetics. It was in the US that the eugenics movement was founded, whereby scientists tried to justify slavery with the idea that certain persons were inferior, genetically inferior. That eugenics movement led to the sterilization of many, many persons with schizophrenia, with the unfounded idea that this could purify the race and remove from it this taint of genetic schizophrenia, which was believed from the 1920s to be a very strong component of the risk. Now, the greatest horror of the eugenics movement was its adoption by the Third Reich and the justification that Hitler used for the extermination of the genetically inferior. As a psychiatrist, I must say that it was psychiatrists who brought this idea forward to the Third Reich, and that the first individuals who were murdered were all of the psychiatric patients in Germany. Moreover, Asperger, a psychiatric scientist, went door to door looking for the damaged young people he thought might have that taint. They were murdered as well. It's one of the reasons I'm happy to call it autistic spectrum disorder and not Asperger's. So we need to take great, great care and not at all, as Mr. Bonham said, use this data in any way that's discounting of the trauma that also causes psychiatric disease. And finally, because I could talk too much, I wanna point out the amazing science we're finding attributed to the gut microbiome. 100 times more of our genes are in the species, the bacteria that live within our guts and on our body, which are inherited from human to human through the mother at birth, and which serve as a major organ against which inflammation occurs. I was really moved at the last symposium looking forward that Regina James organized to really finally hear a focus on food insecurity. And I think we must also recognize that the food we eat shapes the bacteria that can live in us, and that further shapes our physiology and our ability to fight inflammation. And over fetal development as well, data shows that it is secretions from the mother's gut bacteria that are also influencing the health and development of her child. The complexity of it all is as exciting as it is daunting from a psychiatric perspective, and I will end there. Thank you so much, Dr. Malaspina. I can sit and listen all night to this conversation, but we will move on. Thank you so much. We will move on to Dr. E. McKinney. And Dr. Kinney, if you can reflect upon the presentation from Mr. Bonham and the comments made by Dr. Malaspina as well. I certainly will. And it's a great privilege to follow such two amazing speakers who I really have just been sitting and thinking about everything that you've been saying. And I will just add to what Dr. Malaspina just said, which is the future researchers. We really need to learn how to embrace complexity because the world is getting increasingly complex as is research. But I wanted to reflect a little bit in my time toward the future and think about the ways in which genomic information can be used. Some of the ways I would think it will be used to, if not, and I think that was very smart and wise thing Mr. Bonham said, if not to ameliorate health disparities, because that, I don't know, I completely agree, may not be achievable in genomic data alone, but at least not promulgate disparities. And that I think is the responsibility of us as the research community and as a clinical community to really ensure in the short term that that is not an outcome of the long-term. But I just want to take a step back and just think about where we're going into the future. I mean, today, genomic technology is building our biggest databases of knowledge that we've ever built. Upwards of hundreds of millions of humans on the planet have already had their genome assayed, whether by sequencing or by array chip. And it is only 21 years since we first sequenced the first human genome. And in the first 10 to 15 years, much of that sequencing was occurring almost exclusively in a research arena. But in the last 10 years or so, increasingly a lot of that generation of genomic data is happening in health systems and in hospitals around the world. And into the future, that's likely to be where the majority of sequencing will happen. It will happen on the clinical care side and health systems themselves are going to become the biggest generators of sequence data for humans around the planet. And as you heard from Mr. Bonham, this is igniting an evolution in how we think about routine clinical care, not as fast as some of us thought who were around back in the day of the sequencing of the first genome, but certainly increasing in pace. And the idea is that genomic information for you as an individual under care in a health system can be combined with risk factors for disease, like for example, your personal clinical history, potentially, and we heard from Dr. Malasina also how important family history really is to consider as another orthogonal piece of information that informs about health and disease over the life course of individuals. And then of course, social determinants of health and lifestyle factors that are impacting and sometimes have the outsized impact on your risk for developing disease. And of course, this is happening in an increasingly data-rich world. Health systems themselves are becoming increasingly digitized and data-rich and capturing a lot of information about their patients. There's a lot of data capture that's occurring also outside of health systems with digital health apps and others. There's a lot of additional biological information that's coming online. So today where we are in terms of genomic information coming more and more into healthcare, we can start to think that in a few years time we're gonna start to see other types of biological information, metabolomics, epigenomics, proteomics start to come into arenas of healthcare. And of course, we're living in an era of big data. So increasingly we're using machine learning and AI type approaches to integrate this data in a sort of multimodal way. And I think as we're talking about potential for exacerbating health disparities, we also have to consider the ways in which we apply these machine learning and AI type approaches. But, you know, genomics is failing on diversity as Mr. Bonham has exquisitely laid out for us. It's very true. Our massive genomic databases that are the engines for a lot of this change that we're going to see in our scene are skewed for representation for small minority in terms of the total humans of the planet. And this is not just on the research side, it is also on the implementation side where we really, the rubber hits the road and how we see how things actually play out in healthcare management. And I will point out that NHGRI actually is really at the forefront and has been for many, many years in recognizing this problem and acting for change in terms of enriching for diversity in both basic research and clinical research enterprises. But we have a long way to catch up and it's unrealistic to think that there's going to be a fast fix for this problem. And in the interim, it is going to be very important to understand how these biases impact the ways we are or are thinking about using genomic information in healthcare management. This is a question that is of being of research interest to my group for many years, over a decade actually since I came to Mount Sinai Health System as a junior faculty over 10 years ago. And one of the ways in which we looked at this is we asked in a paper that we published back in 2017, how will the lack of diversity in genomic research databases impact our ability to use genomic data to predict risk for disease? And at the time there was a lot of interest in emerging interest in using polygenic risk scores that you heard about, which are the aggregate of information across the genome into a score that is trained in research database and then it can be used out of sample to predict any human's risk for disease. And we found in that study that if you do that and you use predominantly the databases that are predominantly representing European ancestry individuals, and I would even go further and say predominantly representing Northwestern European ancestry individuals, then you're going to get a decrease in accuracy and how that product performs in other, in humans from the planet that come from other places in the world or have other ancestry. And that divergence really increases with the difference, the divergence between the research population and the human walking into the clinic. So in terms of thinking about what are the really key driving questions in an era of using genomic information routinely and thinking about how to treat and prevent diseases, I think the short-term things we really have to grapple with are how we transform genetic research into medical knowledge and what are the barriers and gaps in translation research and implementation research that we need to do to do that and how do we increase representation in those endeavors, but also reckon with the biases in our genomic databases, understand how they impact medical knowledge and act to mitigate that or delay implementation if it's not, if the tools are not meeting the standard that we need them to meet. I think some of the other arenas we can start to think about is if we are using genomic research to identify genes or variants or polygenic risk scores that we believe are clinically relevant in clinical settings, then how do we systematically identify the individuals and communities and populations who are at risk? And we are used to thinking about this in rare disease space where we really think about rare variants that impact severe disorders occurring in populations. In common disease space and in psychiatric disease space, this tends to really happen more at a community level. So how do we understand community? It can happen also in a family level, but really it's about communities and exposures and genetic architecture in addition to social determinants. So how do we recognize that and how do we engage with and understand not only the genetic factors, but also the other risk factors at play over a patient's life course? And then the other challenge I think we need to meet is really thinking about how we integrate this information broadly, not only in health systems, but how we're communicating to patients and communities in a way that will follow through and ensure that this is resulting in improvements of health care management and even health care access. So I'll just, I'll finish up, just briefly mention one or two ideas and then I'll stop and we can go to discussion. But you know, I mentioned that a lot of genetic data is being generated in health systems. Many health systems have also invested in research engines called biobanks that link genomic data to health system, to health records, and then they're used for the secondary purpose of research. And those biobanks can really be very translational engines and they can help us do the research and how these things are going to play out in the clinic before we get to the point where we're introducing new information or new products into the clinic. We do this at, in the Icahn School of Medicine here in New York City, and I just will point to one or two things that we have learned over the years. So our research biobank is called the BioMe Biobank. It is representative, so any patient who walks into our health system can participate in this research biobank, and it is very reflective of the diversity that we see here in New York City. So not only in terms of race and ethnicity, and in our biobank over a third of participants are self-identified as Hispanic-Latino, a quarter is African-American, but also in terms of the deep and multi-dimensional diversity connected to waves of diaspora and links to global communities. And, you know, over 65 percent of participants in our biobank can trace their, have three or more grandparents who are living out, who lived outside of mainland U.S. And so that's really tracing ancestry to over 160 countries around the world. Health systems themselves, interestingly enough, do a pretty poor job of even capturing basic information about race and ethnicity. Overall, about 25 percent of the time, over time, as you, as you utilize your health services, the health service will get it wrong about you. And this is even worse if you are Hispanic-Latino and Asian-American. The health systems do a pretty, pretty poor job of capturing that information. And of course, that information is important in some clinical contexts, not only because we do know there are disease variants in the genetic space or social determinants that do, can track with particular population groups. And in my lab, we use genetic ancestry and we ask whether genetic ancestry information can be used as a layer to improve our understanding of the communities at risk for specific diseases. And genetic ancestry is really capturing our recent past and our connections to our past relation back in time. And, you know, it's interesting because it's really sort of a twofer. So, you know, we're used to looking at genomes to understand the genetic predisposition or protection from risk. But using that same information, we can also understand our human history. And that can be correlated with cultural and heritage aspects of not only genetic, but also social determinants of health. So, one example I'll just end with so that we have time for discussion is by looking at genetic ancestry in New York City in our health system, we were able to show that our health system is less of a melting pot, more of a cluster of many, many communities living in New York with their own social and genetic determinants of health, and are able to then pinpoint specific diseases that are really tracking with specific communities. For example, peripheral artery disease, which is really enriched in New York City in individuals of Dominican descent in a way that it is not in other Hispanic Latino populations, or any other population. And so those pieces of information start to become and start to reveal themselves as you layer more nuance into even how we're thinking about communities and population groups. And so I'll end there. I don't want to go over time and leave time for questions. Thank you. Thank you so much, Dr. Kinney. And if we can bring all of the discussants back, we did have a few questions that came in so far. And the first one is, so Mr. Bonham mentioned in the beginning, the lack of diversity in the genomic database and how that translates into medicine, etc., and the impact of what we can and cannot do. And then you have the biobanks and healthcare systems that can also sort of provide biological samples to sort of help. How is it that, you know, Dr. Kinney, you're able to get folks to sort of donate to the biobank, but there seems to be an issue, Mr. Bonham, with, you know, people of color participating in research to enrich the database of genetic information. So I'll make two comments. First, Dr. Kinney is one of the examples of scientists across this country and across the world have truly had diverse cohorts. And so she stands head and shoulders above most. And part of that, I think, is the engagement that the healthcare system has had within the city of New York, and the service of the different diverse patient populations in the city, and the engagement with them. So I want to just applaud the important work that's been going on. But there are some interesting, challenging issues that you raised in that question, Dr. James, about that now much more of the actual sequencing and the data collection around genetics and genomics is within healthcare systems. So it's limited to those healthcare systems, and it's not in public databases so that researchers can study it and use information from other studies or other groups. So when a healthcare system has a closed door, that only the information can be used by the physicians and the scientists in that institution, or only for clinical care, it's not being used to enhance our knowledge to help to understand better disease and health. So those would be my two comments I would make. Okay, thank you. Any other comments? Well, I mean, I thank you so much, Benz, for your just completely kind and generous comments. But, you know, I think that I completely agree with you that along with this generation of data and health systems comes this tension, because health systems often have to make quite substantial capital investments in order to generate these databases and are not themselves research. I mean, many have academic medical schools, but the health system itself, the primary purpose of the health system is about tracking procedure codes and billing codes. And so the ways in which we're using the data that the health system generates for treating patients is not necessarily super aligned with what global research enterprise is and how we do that. I do also, maybe I'm a little bit hopeful, but I do also think that although health systems might not yet be used to this over time, much like we learned in the global genomics research community, that you need to share data to learn more. I think that health systems may also realize that you need to share data to learn more to benefit not only patients in your health, to better benefit patients in your health system and be motivated that way. Thank you. Okay, the next question is, genetic testing for psychiatric meds is currently available for numbers to treat illnesses such as bipolar depression, OCD. What are the criteria to determine when you should order the genetic testing as a psychiatrist when you see a patient? If I imagine that's directed at me, I would say it's somewhat controversial. I mean, too, too often patients come to me with their genetic data and tell me what medicine they should take. And I point out that those are based on liver metabolism and all sorts of things. And there may be something very unusual, but I think our best treatment algorithms really are clinical. And I think it's the experience of a clinician by and large that drives these. If someone is treatment refractory, you may visit it. But I, in my own experience, and there are many, many divergent opinions by people I greatly respect, but I did not make it a routine part of my care. A lot of it is marketed directly to patients to get this testing and bring it to their doctors. I mean, that happens so much in genetics right now. I think as psychiatrists, we see how much of the burden of mental illness is really through disadvantages in society or even inflammatory and cardiovascular. But someone will come to us with a little single polymorphism for a rare disease and really want to focus on that and not the lifestyle changes that could have a much more substantial impact on their health. And a little bit of the pharmacogenomics may fall in that category compared to the routine patient. Okay. Thank you. Thank you very much. The next question, it's a long one. Let me read it out. I have some local preliminary data suggesting clinically indicated genetic testing in ASD and DD has disparities in rates of implementation by rate, geography, as BioME has had relative success in getting underrepresented participation in genetic studies. If I may ask, how practically have you been able to do this? Is research participation in biobanks translating into clinical rates of indicated testing? That's a great question. So I think we addressed a little bit already why BioME is so diverse. And it's because it's an unselected hospital-based population that's serving communities. You know, it's physically located, the main hospital campus is physically located in Budding, East Harlem, Central Harlem, and the Upper East Side in New York City. So, and, you know, in general, biobanks, not every biobank around the world, but many biobanks are kind of fall into that more unselected patient population model. And so because of that, and depending on where there's infrastructure to build out biobanks, you start to see more diversity come in. But the second part of that question, if I'm remembering now, because it's just disappeared in front of me, hang on, I'm going to pull it up and just make sure I'm answering it. Yeah, so if research participation in biobanks is translating into clinical rates of indicated testing, and I think it is in a few ways. So I think the diversity in biobanks is translating to more translational science and more implementation science to generate an evidence base for how we're implementing genomic medicine. And the evidence base is, can be in the context of more diversity in biobanks, more inclusive of diverse patients and voices. And when that is, whether that's qualitative research, whether that's clinical trials, you know, there's whether that's, you know, building out sort of health, health system AI, when you start to have that research mechanism, that's really focused on health outcomes and, you know, how we're implementing genomic medicine, that's more inclusive, then you start to learn a lot, an awful lot more about where it is or not, or is not appropriate to make offerings, what patients attitudes are toward them, what are the barriers for uptake? What are providers attitudes toward them? What are the barriers for adoption? And, and really start to generate the evidence base that I think is sorely missing for a lot of these things. Okay. Thank you, Dr. Kinney. The next question, there was a mention that it would be beneficial for BIPOC people to be more involved in genetic studies. What are some approaches that are being done to improve participation, given the history of repeated abuse from the medical research establishment? So I'll start with that. And I'd love to hear from my colleagues. You know, I think one of the things from a funding perspective is a commitment to fund community-based research, to actually recognize that you have to build a relationship with communities. You can't just, you know, come in and parachute in and collect samples and leave, that we really need to build relationships over time. You know, I want to just recognize the All of Us program as one example, seeking to do that with regards to some of the work that's going on within that NIH initiative. But there's a recognition that, that this is important, but this is not easy. And you're absolutely right. There's been a history with regards to the field of genetics that includes scientific racism and issues that have had an adverse impact on many communities across this country and across the world. And so, you know, we always have to recognize that and be humble with regards to how we work within communities, but to build relationships, build trustworthy relationships. Others, please. Any comments? Oh, sorry. Well, I would just, I mean, I just would second that completely. I think that we really have to rethink, you know, how we approach research and understand that research is inextricably tied to the society we live in and engaged with the people whom we're asking to participate. And it is so important to hear the voices of the community in what we're thinking and partner in decision-making and partner in prioritizing what we should be spending our efforts to do. Okay, great. Question for you, Dr. Malaspina. Do foods which adults eat now affect their microbiome and susceptibility to disease? If so, what foods? Thanks. Simple question. Well, we know from a lot of research that adopting a Mediterranean diet and other dietary interventions really do even reverse certain types of chronic diseases. The most beneficial bacteria really live on fresh fruits and vegetables, and they secrete short chain fatty acids into our body that are very protective. Now that means no juice and smoothies, but fruits and vegetables. These really can impact health throughout life. There's evidence for fish oil, and increasingly some probiotics may have an evidence base. It's too soon to know that, of course, but processed foods really do negatively impact our microbiome. So do heavy uses of antibiotics, which many psychiatric patients turn to thinking it might cure some latent infection, and then conversely, they end up further damaging their microbiota. So I would really also tie some of the disadvantages that structural racism has caused to food insecurity to wholly inadequate amounts of fresh fruits and vegetables. So yes, go for the fresh fruits and vegetables. Okay. Thanks, Dr. Valaspino. Okay, and we're nearing the hours. We have one final question. Is there a thought that increasing the diversity of researchers will result in increasing diversity in samples? Focus on more diversity-focused research topics. I hope I read that right. Similarly, will an increased diversity of journal editors result in the publication of more diverse-focused topics? I think the answer is definitely yes. Yeah, a resounding shaking of the head, yes. Okay, all right. So that was an easy one to close with. Well, let me just thank all of you. Thank you, Mr. Bonham, for really opening up with that fabulous presentation that really set the stage for this great discussion. Thank you, Dr. Valaspino, for bringing your extensive years of doing psychiatric research to this discussion, and thank you, Dr. E. McKinney. I mean, you as well, with the work that you have been doing in the last 10 years in the New York area has really made a difference as we think about genomics and marginalized populations. So I just really want to thank you all, and I hope everyone this evening enjoyed this topic and this discussion as much as I have. And just please, thank you all so much and have a wonderful evening. Thank you. Good night. Good night, Vincent and Regina. That was really fun. Oh, good. I'm so glad she could make it. I hope we're not being recorded. Recording is still going on. Can we stop the recording, please? I see the sign up there.

genomics

mental health

inequities

diversity

precision medicine

research

social determinants of health

trauma

biobanks

equitable access