EP 243: How BD² is using genetics and deep phenotyping to transform bipolar research with Cara Altimus and Ben Neale

Hello and welcome to the Genetics Podcast. I'm your host, Patrick Short. My background is in population genomics and studying the genetic causes of rare disease. I did my PhD at the Sanger Institute and the University of Cambridge and have been in biotech since 2018, when I started Cyanogenetics. Sonogenetics helps academic and industry researchers to run large scale genetic testing programs that speed up their clinical trials, generate data sets for the next big breakthrough, and give participants the best possible experience taking part in research. Each episode of the Genetics Podcast, we bring you insights from the leading minds in genetics and precision medicine, including household names and Nobel Prize winners, as well as early career scientists and biotechs working on the next big breakthrough. Whether you are a scientist, entrepreneur, executive, patient advocate, or simply someone curious about how genetics shapes our world, you're in the right place. Thank you for listening and let's get started. Welcome, everyone, to the Genetics Podcast. I'm really excited to be here today with Dr. Kara Altemus and Ben Neal. Kara is the CEO of BD Squared, which is a really amazing new research initiative that's focused on cracking our understanding of bipolar disorder. If you've done any work in the field or familiar with psychiatric genetics, it's a really complex interplay of genotype and phenotyping. We're going to talk about this very ambitious program today and some of the new research that they've done that I think is going to be a watershed moment for the field. I'm also joined by Dr. Ben Neal, who is this statistical geneticist and has been in the field of psychiatric genetics for as long as I can remember when I was a PhD student, I remember reading some of Ben's papers and being amazed by the kind of work that was happening then. And the field has continued to move on. So Ben is an associate professor at Harvard Medical School and Massachusetts General Hospital, and he's an institute member of the Broad Institute, where he's the director of genetics for the Stanley center for Psychiatric Research. So, Ben and Kara, thank you. I really appreciate you joining me. Thanks for having us. Absolutely. Let's start with BD Squared. Cara, I want to start with you. You joined relatively recently as CEO to lead the effort. What told me a little bit about what made you interested in joining and about the initiative in general. Yeah. So VD Squared, we really launched about four years ago. I think first dollars went out the door actually to the Broad Institute about the work we're talking about today, but that those dollars were there maybe three and a half years in the making. And so BD Squared launched out of this idea and kind of finding that there was a real under investment in bipolar research and underinvestment in bipolar care, and that there wasn't a good path in the current funding environment, even as we were looking at it four years ago, to bring the resources necessary to elucidate the biology necessary to create the new tools to create the clinical understanding, to really change the the lives of people living with bipolar. And out of that problem, multiple families and funders came together to, to crowd in, to pool the resources and work against a common agenda. So BD Squared started as a philanthropic initiative, a combined initiative that just this year, actually In February of 2026, we spun out into an independent nonprofit and an independent organization. And so in some ways, my role with BD Squared has been there from the very get go as we worked with the funders to identify what these priorities were and how we were going to roll it forward in other ways. It's brand new because we are just, just now reaching that nonprofit status. And that's the boring stuff, because the exciting stuff really is that we are already. And what led to this spin out happening so rapidly is that with just three years of funding and focused effort across a number of areas, genetics, brain omics, neural circuits, improvement in clinical care, and a massive data collection effort and infrastructure, we are already changing what we know about bipolar and are already moving those changes into the clinic. And so that's what VD Square is really about, is how do we accelerate change, how do we bring community together, how do we crowd around and do science at scale. Amazing. So Ben, from your perspective, what were the big gaps in the field that you were looking to close with this? First and foremost, we know bipolar disorder runs in families. We know genetics matters. We also know that it's complex. It's not like Huntington's or other sort of brain diseases where there's a single genetic risk factor that pretty much dictates whether or not you're going to develop the illness. And so with that backdrop, the question has always been is what is the actual genetic variation that's contributing to this illness? Can we go out and find it? And the common variant scans, primarily led by the Psychiatric Genetics Consortium, have delivered common variant associations. But all of these associations are very modest, small effect sizes, odds ratios of maybe 1.05. So really, really tiny effects in the scheme of things. Together, they capture a huge amount of genetic risk, but they are very hard to interpret biologically. The effects are subtle. They're hard to model functionally. Most of them are non coding. They're not pointing to individual genes themselves. And so where we saw the major gap is really in trying to identify stronger acting variation that exerts a much bigger leverage over risk. But as a consequence of having bigger effect size, it will tend to be considerably rarer. And that's certainly true in bipolar disorder. It's true in other severe mental illnesses. And so the emergence of sequencing and really massively parallel sequencing technologies to really bring that kind of sample size scale that we saw for the common variants and that started to work and deliver on common variants. We've pushed forward on the rare variation side, particularly rare coding variation. And it's working. We're really excited that the kind of current results are actually showing us genes that give you maybe rather than a 1% chance of developing bipolar disorder, something like a 10% chance of developing the illness. And so these kinds of strong acting rare variant associations. Now identifying 13 distinct genes that all kind of fit that sort of profile gives us a whole set of new avenues for prosecuting the biology and trying to understand how this illness arises in the first place. So what have we Learned about those 13 genes? Are these loss of functions, are they gain of functions? Where are they acting in the brain? And where I kind of want to get at with this discussion as well is how much should we think about bipolar disorder as one disorder versus what we're learning about the different molecular subtypes of the disease and how to treat those subtypes and so on. So what do we know today? Yeah, so across the genes it's not any one thing. I think that that's probably the most important top line result in terms of the biological function. Some of these genes have a reasonable amount of study and have been pretty well characterized. Others of these genes we know very little. So amongst the strongest genetic is identified is a gene called ACAP11. It's an anchoring protein that brings together PKA with other proteins to phosphorylate other proteins. One of the proteins that it's been shown to bind to is GSK3 beta. And that's really important in the context of bipolar disorder because GSK3 beta is the thought target of lithium therapy, our frontline medication for treating bipolar disorder today. Why that matters we don't really know, but it is this starting point for some of that more mechanistic investigation. Other genes are more important in terms of binding DNA or transcription factors. Things like SP4 is emerging as a hit and that again complicated regulatory biology. It probably does many things and so pinning down what's actually going on is quite challenging. The genes themselves tend to be expressed in neurons. They don't tend to be specific beyond that. So we see them expressed in a wide range of neuronal populations from efforts like Brainspan or the Common Mind Consortium, where we can look at the single cell RNA sequencing and try and figure out where these genes are actually doing their business. And that's not particularly specific at this point in time. But I think the other thing that's important to say is that there's pretty good evidence that it's not just the rare variants that are driving the risk for illness in those individuals. These individuals also tend to carry more common genetic variant risk than you would by chance or compared to controls in the population. And so it really is underscoring that complexity, whether it's really like 50 different or 100 different, or five different kind of mechanistic subtypes that may exist. Too early to tell. I wouldn't say that we've been able to synthesize across the Riverian super well right now, but I'd say that we're sort of in this place where there's some things that connect some of them, but it's not an obvious single cellular population where the real business end of the biology is happening. In terms of the class of variation that matters, mostly it's loss of function. That's largely because we're doing this in a case control paradigm. And so the annotation of missense variation is still very challenging. That being said, advances in things like alpha missense and actually using the structural predictions have helped us identify genes that are driven more by missense or at. There's some non trivial contribution from missense variation. Included amongst those is a gene called ATP2B2, which is also associated to autism spectrum disorders. Again, focusing on missense variation. This gene is a calcium ion pump. It pumps calcium against a gradient. Where we're seeing the missense signal is where the calcium ion would tend to land in that pump. The functional evidence and the prediction that we're making is starting to fit with the genetics and helping us kind of develop some of those mechanistic hypotheses. So, Patrick, I'd love to follow up some of this idea that you asked Ben. Do we think that there are subtypes here? How are we, as Ben would say, prosecuting the biology? And I think there's two directions that BD squared has taken this and in effort to bring the field together and to give the data to the field that starts to answer these questions really quick. And so one of the initiatives that we've developed that is I think game changer for how we think about how science is done, particularly in biomedical research. We built an initiative alongside the genetics work that we refer to as the integrated network. And the integrated network is a series of clinical sites across the US and Canada. Currently hopes of moving that to be more global in time. But the integrated network is, it's, it's this merge of multiple science ideas. It is what we call a longitudinal cohort study. That longitudinal cohort study will follow individuals with bipolar for five years and collect all kinds of phenotypic data. So we will be collecting brain scans, we're collecting Fitbit data, we're collecting signals that come out of blood based assays, we're pairing that then with information that comes from apps, so things like surveys and wellness assessments, as well as the EHR record for these participants. So that will give this incredible profile of how bipolar actually shows up in real life, both in the medical context, but also in the context of someone's day to day just living. That longitudinal cohort sits inside of what we call a learning health network. And the learning health network is very much about how do we take learnings and in real time pump them back into our healthcare settings so that we're able to actually create discovery and say what is the right population that we can bring this to. The integrated Network today is across 12 sites. It has almost 1500 participants. And this is exciting. Last week we got all of it together so that the samples for those participants is actually headed to or maybe already arrived at broad and we're doing whole genome sequencing across all of those. And so it doesn't take too much imagination to see how incredibly cool this will be because we will be able to take the deep phenotyping of all of these individuals that also are part of a healthcare setting where we are understanding how can we improve healthcare. And we will understand which of these individuals have the particular mutations or the particular differences that Ben has identified in this big genetics work. And we'll be able to immediately correlate, well, what does that actually look like in real life and in real medicine? And if we find things like calcium channels, we actually would have a population to immediately say, what might you do about that with people that we know have it? Yeah, you've anticipated one of my questions, which is about how you think about the shape of the data set evolving because you've got, I think close to a quarter of a million participants that I assume comes from big consortium effort to pool together genetic data. And Ben, this is probably the traditional we want to get to scale as much as we can on case control for discovery, but then you can couple that with the deep longitudinal. That may not be as easy to get to hundreds of thousands, but you can really go in depth and collect lots of different phenotypes. My question or biomarkers, my question is, how do you think about the two of those evolving? And is the psychiatric genetics field in general increasing the N enough to drive the discoveries and then you all will be pushing into the depth of data, or do you think as well about how BD squared adds to just the sheer volume of GWAS case control data? Ben, maybe I'll start with you and then. Kara. Sure. So I think they are by their very nature complementary. And I think that that's kind of an important component of the strategy insofar as you say discovery needs scale. And for the discovery efforts that we've pursued, it's some combination of recruitment efforts that have been supported by BD squared, but also supported by NIMH and the Stanley Center. And those recruitment efforts are not necessarily going to the depth of phenotyping that we're seeing in the integrated health network. In some of those cohorts, we have access to electronic health record information, sometimes even stretching back 30, 40 years. And that provides us sort of of different opportunity for looking at phenotypic depth and trying to get at those sorts of things. But I think, as we all know, EHRs are an imperfect reflection of the clinical reality. And there are some knotty epidemiological confounds or biases that might crop up. And so it's actually really helpful to have this prospective longitudinal cohort to go out and evaluate at the same time the way we've done the genetic discovery efforts and particularly the recruitment efforts, because, you know, we're working in a lot of different places across the world. We have efforts in multiple countries throughout Africa. We have efforts in Pakistan that we support throughout east and Southeast Asia, as well as in South Asia and India, in addition to Pakistan, and through Central and South America, in addition to what's going on in the US and Europe that's been sort of the initial genetic discovery efforts. And we have to work internationally to get to the scale that we think is necessary to make the discoveries. Right. So we're at like 70 or so thousand cases and just getting to 13 genes. And we are by no means saturating genetic discovery. There are A bunch more genes yet to be discovered. But critically, these mutations do not occur in that many people, even with bipolar disorder. It's like one in a thousand people with bipolar disorder might carry an ACAP 11 loss of function mutation. And so if we want to do those deep follow up investigations of people that all carry the same kind of variant, the same, you know, maybe not the same loss of function mutation in the gene, but all carry a loss of function mutation in that gene, we're going to need to not only engage internationally, but we're going to need to make sure that we're investing in the infrastructure, that we're educating and training the people on how to do this kind of science so that they can go back and they can do the deep clinical assessments and we can kind of work together in that next phase of characterization of individuals carrying these mutations rather than just focusing purely on the discovery end of the activity. Yeah, Kara, how do you think about that matrix of data types to build out? It's something we've thought about from the very get go where we've said clearly we need to have a greater baseline understanding of what is bipolar, what is the biology that exists that drives bipolar. And we also need to be able to connect that to real people and we need to connect to real people across the globe. And so to maybe say we know. And I think if you an easy critique of science is it's not always scalable. We couldn't possibly carry out what we're doing in the integrated network to every person in the whole world, nor would every person want to engage in that kind of battery and data collection effort. But what we do think it does, particularly as you intersect with the large genetic architecture that is being developed for bipolar, is we start to be able to pull out the individual data elements that tell us the most and are the most predictive and are able to distinguish the important data nuances of biology that will then lead to better diagnostics, better and more specific treatments. And so while I see these architectures intersecting, I see us increasingly, rather than adding more and more and more data types, actually starting to identify what are the data that are the most informative and the most predictive and then expanding across those in broader populations and in more creative, like bigger geographies and more creative ways that don't involve such intensive in person clinic time. Yeah, interesting. What do you all see as the best candidates for that now? What are the types of biomarkers in addition to genetics that are going to give us the most signal and scale, the Best. That's a tough question. I mean, I think we're still early in the discovery phase for the biomarkers. I mean that includes, I think the biomarker that we're I think pursuing most aggressively but is very, very challenging is what can we actually get out of csf? And you know, if you look at the arc that Alzheimer's disease has gone through in terms of profiling initially in CSF and then getting reproducible signal, some indicator of the underlying disease process and then sort of bringing that forward and then seeing what you can do in blood and sort of plasma, I think that kind of playbook is very appealing. The challenge is in psychiatry we don't have a known locus of pathology. Right. There aren't plaques and tangles. There is no equivalent thing for bipolar disorder. There's no equivalent thing for schizophrenia. These illnesses are, are very different in terms of having an obvious place where they are arising. And that might be because of the heterogeneity. We don't know if there are lots of different subtypes that might be part of it. But it might also be that it's as much electrophysiological or that it's really biochemical rather than gross pathology that you can see in a kind of postmortem staining experiment like Alzheimer's figured out over a century ago. So I think those. But that question is still very salient. The genetics are great to getting you into new biology, into developing new hypotheses. And in some instances, some of these genetic risk factors are a better predictor of conversion from inpatient depression to bipolar disorder than anything else that we have clinically. And that's maybe a reflection of how important the genetics could be, but it could also be just a reflection of just how challenging it is to make concret projections about course of illness because we understand so little of the biology about what's going on. Yeah, Kara, you got to be thinking about treatment response and clinical trials. Go ahead and build on Ben, because maybe we're going to the same place with this. I bet so. So I was going to share. So every year we bring our investigators together to share all the details of everything that's happening. And we make them because we know when they're progress reporting what's happening. As the science team, we pretty much mandate that they share with everybody what's in their progress reports. So it's a semi public setting to our investigators. But there is a real deep discussion about what's being seen across all of the discovery grants, all of the genetics findings all through the clinical work and our effectively early biomarker assessment. And one of the things that struck me this year, so this was our third one just back in March and we had a real breadth of science being kind of put up on the screen for two days and really across the board. Ben, shout if you disagree. Every single presentation showed new, interesting. I would say stand out biology where you weren't back when I was at the bench. I would say I don't want to bother analyzing something if I can't squint at it and see the difference. Yeah. So you know, always using squinty eyed statistics and squinty eyed statistics for everything from neuroimaging to immune profiling to Fitbit to everything is really pointing to there are changes. We can measure them, they appear to cognition appear to have subtypes. And so if you take that basic premise of we can look across a lot of domains, we can start to see the shape of differences that you can assess using squinty eyes statistics and those appear to have subtypes. It is a very easy and very hopeful jump to say awesome. That sets the basis in very short order, particularly with the integrated network and all of the human biology that we are collecting, that we will be able to, to understand kind of different profiles and how that biology effectively reflects across systems to potentially give probably we're seeing many of the same phenotypes or same subtypes that show up across these domains, but where effectively you have a profile and that then leads to much more specific development of treatments, the identification of what is the right suite of things. And so we see that really as the next step. And that what we're doing then is both working on the biology side and then shifting that immediately to the creation of a network that will be able to run clinical trials in time. I broadly agree with what Kara was talking about in terms of the investigator meeting. I think there's a vibrant community that's come together and is not just doing work in their own heads down focused space, but actually engaging with the broader advances happening across the field. We on the genetic side collaborate with many of the other discovery grants to help them pick the genes and variants to try and prosecute in the model systems. It's really encouraging to see that kind of dynamic. I think often one of the plights of the geneticist is that they make a discovery and then no one does anything with it. And they're like, well, am I going to have to learn to work at the bench? Is that what is next for me if I want to actually see this move forward. But I think what BD squared has done, and hats off to Kara and the whole team because I think they've really been a driving force behind this. It is to take the work that others are doing, the discoveries that they are making and making sure that they are actually advancing that there is more effort put behind trying to understand and interpret that. And some of that might be in the integrated health network where it's characterization of the kinds of variation that we're finding. Some of it might be in the sort of brainomics and looking at those genes in the single cell transcriptomics and trying to understand and interpret what else it might be expressed with. What are some of the more complete cast of characters that that gene might be working in concert with to give rise to the apparent risk that we observe from losing one of those copies of those genes. But it may also be in the model organism work or the stem cell model work where you're going to try and knock down that perturb seek and then see what comes out the back end to try and again to finesse out more about the biology. And so this, this sort of integrative initiative, this approach of trying to actually steward the field together and steward from discovery all the way through to the translation of those kinds of discoveries is, is something that I'm really encouraged by. It absolutely makes the geneticist in me incredibly happy because it means that our work isn't dying on the vine, but it's actually having the kind of impact that we hope. Yeah, I love that. And if you think about the. I think the challenge that the field has right now, which is also an opportunity, is it seems like you all are almost rushing into a vacuum of opportunity. There's so much to do and if you assemble the data and the right people, everywhere you look there's an opportunity. But then it also means that you have constraints and I'm thinking about the patience in all this and there's. I can see a lot of challenges in this condition diagnostics, what even constitutes a bipolar diagnosis, an under diagnosis. And then there is ascertainment in the data of. I suspect you probably only see the most severe cases. How do you think about the patient priorities here? Like when you have patients and family members, what's top of mind for them of coming out of all of this amazing basic science research? These are the one or two things that will make the biggest difference to us this decade as an example. So I didn't share this at the Very beginning. But the actual initiation of BD squared was not a roundtable of scientists saying, here's the most important science. And it was not a roundtable of clinicians saying, here's what this looks like in a clinic. It was actually a survey. And it was like we had this experimental process where we said, what science would you prioritize if you started only with patient input? And so we made this survey. This was years ago now and it was basically like, what would it mean to you to live well with bipolar? And what research do you want to see in the field of bipolar? And we. So that report is ancient history now, but it was so insightful that there was a real pushback on a pure, you know, there was a research to date. Feels like it's very symptomatically focused and it's not focused on creating whole person health and wellness. And so if you look at our name, it's up here. It might be my other side. I don't know. It's there. You got it? I got it. Great. This mirror image thing is going to get me. But it's breakthrough discoveries for thriving with bipolar disorder. And that thriving is derived from our, the input of people living with bipolar that they very much said from the get go. What's important to us is that you research in a way that drives the greatest and best outcomes for whole life, whole life health and wellness. And so that means a lot of things and it's woven into the work that we do. I think the other. So outside of that, another big piece of it is actually this diagnostic piece that people talk about how long it takes in the US it's seven years on average to an accurate diagnosis. Bipolar UK, a charity that is operating in the UK, they estimate that more than 50% of people who are living with bipolar do not know or have a diagnosis of bipolar. And they're working on a big campaign this year and we're cheering them on and thinking about how we might mirror some of that here. And so there is, I think, a lot of time and understanding lost early. But then once someone does have a diagnosis, I think a lot of times the answers are not as helpful. And so that I think is where we are really stepping in and leaning in to say, how do we make that diagnosis faster and life whole and better when someone does have a diagnosis? The one thing I would add to everything that Kara said is that working in mental health, you know, I've worked in mental health for 20 plus years now and it is like medicine in many ways and Then it is very different from parts of medicine in other ways. And I think the place where there's the kind of most pronounced difference is that your behavior is a huge part of who you are. And it, and it's not just your behavior that we're really talking about here. It's also things like your motivation. Are you getting out of bed in the morning? Can you kind of engage in day to day activities? The, you know, and that's on the depressive side and then on the manic side, there's a lot of overlap with creativity and other sort of more inspirational things that may enrich a person's life as well as sometimes cause a lot of distress in their life in terms of how much control they have over their behavior. And that makes it just harder and it makes it different because it's not like, oh, you have a broken arm, I'm going to set it, and then it will knit and then you'll be cured and everything's great. It's about trying to ease off some of those more devastating behaviors that you might engage in when you are not yourself, as some patients have told me about how they sort of interact and engage with the illness itself. And so when I think about what does it mean to do this work, I think that word thriving is really important. I think BD squared's on exactly the right sort of direction with emphasizing and centering that kind of concept. I think there's also the question of, of how do we bring forward treatments that don't just flatline your mood and keep you completely flat and even. And so you don't have the highs and you don't have the lows, but you don't really have much of anything. And that, you know, that's a treatment, but that's not a treatment that people particularly relish and they sort of tolerate it depending on how bad things are getting. But it's not that, that's not a treatment that is actually addressing the core issue with preserving as much of them self as possible. And so when I think about what does real success look like in this space, it's not just finding the genetics or understanding the biology. It's about how we design interventions that are targeted to those things that are causing the most grief and strain and distress on the people with bipolar disorder. Are there any other analogous programs that you all are learning from as you do this? I'd love to hear if they're. Yeah, you're drawing inspiration from and what you're building on top of, I mean, so many Good programs, actually. So BD squared, if I look out one degree at some of the work, our funders. So BD squared is a board. Our major funders are the Sergey Brin Family foundation and the Downton Family Foundation. The Sergey Brin Family foundation has been in the space of funding neuroscience research through an initiative called CNS Quest for over the last decade. And in that, they've built large programs in Parkinson's, new programs in autism and bipolar work. And so we are highly integrated with some of those programs and partnerships. So we're bringing the very best of learnings and resource banks and approaches to the bipolar field. And we're able to do that really quickly because we're linking arms with these other initiatives and programs. If we look on the Downton Family foundation side, there are just as important partnerships that we bring to the table, and they look a little bit different where they're more bipolar oriented, they are more policy and education and stigma reduction. But we need all of that when we're working on bipolar. And so those are some of the early ones. And then Ben talked about looking to the field of Alzheimer's to ask, how do we advance a better biomarker approach in real biology? And then I would also say everyone in biology looks to the oncology space to ask questions like, how do we create big repositories and biobanks that are able to drive us towards more precision health approaches? I feel like we look to those and say, what's the best of there? So a whole number of things. But I do think that we are actually building the very best of. We are the only one that brings all of those and then bakes it directly into the health system in the way that we are and create a network out of that. So I do. It's my job to say it, but I really believe it. BD squared is the new model of how biomedical science will happen in the future. Yeah. And Ben, I wanted to ask you similar, but maybe with a lens towards some of the big neurogenetics consortiums and also how you think about bringing data together in a. In a macro sense. You work across schizophrenia and autism, ADHD and other neurological conditions. And, you know, what can we learn about some of the fundamental drivers behind all these diseases for bipolar disorder? We're absolutely always watching the methods and approaches and technologies that are being applied and developed across not just other neuropsychiatric conditions, but more generally, anything that's working in medicine. We're going to try and figure out whether we can bring it to bear on bipolar disorder. But I do think that there's a particularly important component as it relates to other neuropsychiatric illnesses, particularly schizophrenia and autism. But even developmental delay, there's a range of consequences for genetic risk factors that are emerging from each of those illnesses. And I will say that the genes and the biology have not read the dsm. We see overlapping genetic risk factors between bipolar disorder and schizophrenia. We see a lot of overlap between schizophrenia and autism and to some degree, developmental delay. But it's really a kind of complex spectrum. And so those patterns of pleiotropic effect, so the patterns of impact across the different conditions, we think might help us learn something about the biology, but they may also teach us something about what variation matters or even when the biological consequences of the genetic variant that's giving rise to risk for the illness is operating. So the things that may not show up in autism or developmental delay, but are really firmly restricted to schizophrenia and bipolar disorder, it's not unreasonable to speculate that those genes may be doing their business a little bit later developmentally than the stuff that's showing up when it's conferring risk to autism, but it's also conferring downstream risk to something like a psychotic disorder or schizophrenia or bipolar disorder. Very interesting. I have one more question for each of you as we wrap up. Ben, I think I'll start with you, and then I'll finish with Kara. I wanted to ask on the genetic side, Ben, it sounds like we're living in a world where there's very complex genetics and we're discovering hundreds of GWAS variants that confer a small amount of risk and probably collapse onto pathways and polygenic risk scores and other things people in the field are used to. You're also starting to discover some order of magnitude more impactful rare variants. And as you spoke about before, we kind of are going to figure out how to bridge these two worlds together. As the data sets grow, I want to ask how you think, if it's likely that relatively few patients are going to have one of these more monogenic forms or monogenic like, and most people are going to be in this complex polygenic world. How you think about how should people think about therapeutics in that world? Because it's much harder. Did the monogenic forms teach us something fundamental or how do you think about how, as those predict, as those two worlds come together, what it means for therapeutics? It's a great question, and I'm going to give an example that's emerging in schizophrenia. So Right now we are seeing loss of function mutations in a gene called CHRM4. It's a muscarinic receptor, M4 type. Still very rare, these mutations. So Maybe we've got nine or 10 in people with schizophrenia and one and three times as many controls, but looking pretty promising, but kind of bubbling around 10 to the minus 6. So just about in this place of converting to something that we would really believe. But the reason that I highlight it is CHRM4. That muscarinic receptor is one of the targets of Cabenfi, the most recently approved medication for schizophrenia and Kabenfi. At least when I engaged with people that were involved in the development and application of cabenfi, they say that it works in about half of people with schizophrenia. And so that sort of gives me some modest amount of confidence that at least for some of these strong acting genetic risk factors, if we had made that CHRM4 discovery, we might say we want to target an agonist of M4. That's what Kabemphi does, but it also hits M1, and that works in half of people. I think that that's an example of how you can take these very rare insights and have a run at a therapeutic hypothesis. Strategically, it probably makes the most sense to start with people that carry that kind of mutation because. Because there, you know, they are already, in a sense, representing that kind of biological risk. And so it may be an easier trial to see the kind of readout that you want to see when you do that in a kind of more precision, psychiatry targeted way, but spiraling out from there and trying it in a broader indication. If you get efficacy in that population where you think that there's already a healthy dose of that kind of risk already operating, that feels like a very reasonable strategy for the way to proceed, the way to start to develop new therapies to feed the clinical trial pipeline, but also de risk the problem because of the inherent heterogeneity and challenges associated with translating in the context of mental illness. These are long trials. You don't get a lot of objective readouts. This kind of quest for biomarkers that we talked about, there's no real underlying indicator of the disease process at this point in time. And so it's all about symptom alleviation and all of those kinds of things. And so it's a lot harder to do drug development in this space than it is in many other spaces. But I think there's a huge amount of promise there. Yeah, very cool. Kara, I wanted to ask you about the future from an institution building perspective, when something like BD squared gets created, it probably dies half a dozen deaths before it gets off the ground. But you have the amazing funders that you mentioned that have helped you all get to where you are. But these kinds of things, over time, they snowball and they require, require more philanthropic funding. They may eventually require government and core funding. I just want to hear a little bit about what, yeah. What it took to get this started, but then also as the momentum builds, how you think about continuing that over the next, however long your vision is for where you take this. Our vision is until all people with bipolar thrive. So however long that takes. But I do think we're on an accelerated path to get there. I. You mentioned earlier that BD squared was operating in kind of a funny and opportunistic space that we are like hurling into a void. And you are so right. We talk about that often internally, that we've been really lucky in a lot of ways that we've been able to build what we think is exactly the right thing because we aren't fighting the science political fights, that there isn't another thing that needs to be torn down to be rebuilt. We're just building it right and we're building it with the people that want to be part of a community and a collective effort that drives to a new spot. And so I think in a lot of ways we're going to continue operating in, in this. It's like unfortunate, fortunate if you think about it. But I think we're able to actually drive progress really quickly because we are, we're able to put it all together, where we go next and what comes next. We're in a J shape right now. Part of the spin out that happened in February was an acknowledgement that we hit major milestones around bringing institutions together, launching a data platform, making the first data release on our third anniversary, literal third anniversary public data release of, you know, thousands and thousands of data points and already being at the point of our first investigator that reached an IND a major FDA milestone to have new treatment tested. I mean, between new genes and thousands of data points, over a thousand participants, a new IND like those are big things. And we're seeing an early kind of alliance of movement in, of new funders and new funders on a global scale. And so I think we are in this space of actually we're not trying to own the bipolar space. We're trying to set a table that brings everyone that's excited about bipolar, everyone that's excited about the biology of mental health, new ideas of precision mental health, big data in mental health, or even the model of how do we change what happens and what drives biomedical research? That's what we're trying to be the answer to. And so I think BD squared is going to be in this expansion phase while we bring new funders to the table. But my ultimate hope is that this drives a new change in how mental health research happens and that ultimately this isn't a place that's scary for funders or for researchers to come into, but actually a place of hope, a place that there is a path and a place that we can create real change for people that are excited about real change. Amazing. I know most people, or at least many people listening to this podcast, will probably have someone that they're close to that's been affected by bipolar. So it's one of those conditions that affects almost everybody. So, yeah, thank you so much for taking the time to explain all the great work you're doing, but. But also the time you're dedicating to this. I think to me, one of the things that's also really exciting about this is it creates a, it creates a landing pad for early career researchers where they can come in and go, wow, there's a huge apparatus here that I can jump in and if I don't I know how to analyze data or I know I have an idea, I'm interested in this or that, I can jump in and really start to have an impact because you've made so much of what you're doing open. So I'm really glad to have you on the podcast today. And now I have to say it. Did you see yesterday we made an announcement for new data science fellows beginning. No, tell me, tell me. Oh my goodness. Perfect time for a shout out new funding opportunity. So we, one of our new philanthropic partners, an anonymous foundation, they were not immediately about bipolar. They were about training early career investigators and big science or big data. And they came to us and said, it seems like you have a lot of data. And I was like, hell yeah, we do. And we love to support early career researchers. And so we just, at the beginning of June, launched a new data science fellowship. It's for people that want to work on BD squared data and of any ways and types. And so you could work with Ben, you could work on the integrated network data, you could work on our brain omics data. It's going to be exciting and it is a commitment and how we bring more early career researchers into the space. Of Bipolar and plug them immediately into the best community in science. That is awesome. I love that. So check it out on if this sounds good to you, then you can check it out on Bipolar. Great. Thank you. Well, Karen Ben, thank you and appreciate everybody listening and we'll see you next time. Great to see you Patrick. Thanks as always for tuning in to the Genetics Podcast. If you enjoyed today's conversation, the best way you can support the show is by sharing it with a friend or colleague who might find it interesting as well. We'd also really appreciate if you could subscribe, rate and review us on Apple Podcasts, Spotify, or wherever you listen to podcasts. This helps other people discover the show when they're searching for content on genetics, precision medicine or biotech. We always want to hear from you as well. If you have feedback or questions or want to be featured on the show, you can email us@podcastanogenetics.com you can find me on LinkedIn. Patrick Short, you can find us as well Sonogenetics on LinkedIn or reach out on Instagram. The Genetics Podcast and finally, a special thank you to the team behind the show who makes this possible. Joy Ismail produces and manages the show and joining James Pearce from Selective Frequencies for his expert audio engineering. I'm Patrick Short, your host. Thanks again for listening and we'll see you next time on the Genetics Podcast.