Oby Ukadike-oyer: From the campus of Harvard Medical School, this is ThinkResearch, a podcast devoted to the stories behind clinical research. I'm Oby, your host. ThinkResearch is brought to you by Harvard Catalyst, Harvard University's Clinical and Translational Science Center, and by NCATS, the National Center for Advancing Translational Sciences.

Dr. Jason Vassy is an associate professor of Medicine at Harvard Medical School, a clinician investigator at the Veterans Affairs Boston Healthcare System and Brigham and Women's Hospital, and a founding member of Precision Population Health at Ariadne Labs. He is a practicing primary care internist and researcher in the implementation and evaluation of genomic medicine interventions.

Join us as we hear from Dr. Jason Vassy about the importance of genomics in medicine and the role it can play in an individual's healthcare.

Jason Vassy: Hi. My name is Jason Vassy. I'm an Associate Professor of Medicine at Harvard Medical School. And I'm also a primary care physician and genomic medicine researcher at the Veterans Affairs Hospital in Boston.

In my research, I study how a person's genetic information, or DNA, might be used to improve their healthcare and their health and disease prevention. So how did I come to be where I am now? I grew up in the upstate of South Carolina in a medium-sized town called Spartanburg, South Carolina, pretty typical suburban, somewhat rural upbringing.

My parents, my sister, typical childhood, interested in several things. I was good at school and started to have a bent towards science by the end of high school. That led me, I think as you'll see, to the career that I went on to lead.

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I stayed in South Carolina for college. So I went to a small liberal arts university called Furman University also in the upstate of South Carolina in a medium-sized town called Greenville. I was a biochemistry major. I think by my second or third year of college, I knew I wanted to go to medical school.

So I was starting to take prerequisites in that direction. But at the same time being in that liberal arts environment really gave me a broad exposure to the humanities. I was studying literature. I was studying history. I was studying sociology, and psychology, and all the other components of a liberal arts education.

And I really think that helped me decide to go into medicine as compared with, say, a more basic science or a laboratory-based science because what I liked about medicine was that it brought the science of biochemistry, and physiology, and anatomy to a person, to actually a human being, and all their humanity, their backgrounds, with their social situation brought to their lives, to their disease, to their health, and how an understanding of both of those factors, both the biomedical factors, but also the psychosocial and other contextual factors, are what really made the difference between a person's health or disease and their well-being.

And well-being being a more general term than just physical health. And yet at the end of the day, perhaps the more important thing a person experiences is their well-being versus whether they have a physical symptom. After a brief interlude for a year between college and medical school, when I went to teach English to just give myself a little break from the rigors of studies, I then settled back down into medical school.

I went to Washington University in St. Louis and had a phenomenal medical school education there. Really hunkered down and really learned the inner workings of the human body and what can go wrong with it. And towards the third year of medical school, I think I started to probably have a little bit of a hankering for that bigger picture that maybe the humanities of my liberal arts education had inspired in me.

So of course, I was starting to get experience taking care of individual patients and found that really rewarding. But then there was that part of me that wanted to see the bigger picture not only for that individual patient, but maybe more at the population or public health level too. So after my third year of medical school, I left for a year to get a master's of public health at Johns Hopkins in Baltimore, where I got to focus on some of those higher level population factors that influence not only an individual person's health, but also maybe the health of their community, their families, their town, their country.

In public health school is when I acquired some of the methodology needed to study patterns of disease in populations and people, so epidemiology, biostatistics. If we are seeing that a certain population experiences a certain disease in higher rates, how do we know that that's not by chance? And how do we know that instead that maybe it is actually due to some risk factor they're exposed to or some causal influence in their environment or in their community that's causing disease?

So the methodology and experiences that I gained in public health school really then came in handy for my future career. So it was a very productive year, very eye-opening year. And then when I came back to medical school to finish, and then to go on to internship and residency, had that broader perspective and was starting to accumulate some of the scientific methods to study that broader perspective.

By this point, I had decided I wanted to be an internist. I did not choose surgery. I did not choose pediatrics. I did not choose obstetrics. I wanted to go into internal medicine, which is the primary care of adults. Was still open minded to whether I might subspecialize beyond that. I actually did kind of enjoy the pathophysiology of the kidneys.

So I thought of becoming a nephrologist, but knew that internal medicine would be the first step. So I went to the University of Pennsylvania and specifically was in their primary care residency track there, where I had the typical grueling residency experience. So you're working 80 hours a week. You're sleeping in the hospital at times.

You are working at the intensive care unit. You're working in cardiology, and oncology, in general medicine, where you take care of pneumonia, and heart failure, and diabetes, and cancer. Phenomenal crucible of really learning how to apply all of the book learning that you learned in medical school and actually be the frontline doctor, taking care of a lot of patients that taught you a lot, that were, some of them, very ill, critically so.

And you were the main connection or touch point between the medical system and their healthcare. So incredible privilege and also an incredible responsibility to take care of these individuals. It was over the course of residency that I had decided I'm not ready to commit to any one organ or any one disease. So I think I will stay a generalist. And I was more interested in the ambulatory, or outpatient, primary care side of medicine than the hospital-based inpatient side.

By the end of residency, I was looking for, what would that primary care career look like for me? But I was not ready to give up this idea of research, the idea that I had something to contribute to the systems level or population level understanding of patterns of disease that brought an individual patient to my primary care doorstep, but that maybe could be addressed at a higher population level, or at least help contextualize what an individual patient was experiencing in that broader perspective.

So with that, I started a general internal medicine research fellowship at Massachusetts General Hospital after completing residency, where I did have a primary care practice of my own. But the focus of the fellowship was really to continue to hone some of my research skills in epidemiology and biostatistics, again, with that focus of, how can we start to study patterns of disease in people?

I took type II diabetes as an example disease, very common. We know that there are a lot of lifestyle factors that can lead an individual to develop type II diabetes, most notably becoming overweight, or obese, having low calorie expenditure in the form of low physical activity, or having increased caloric intake from food. And yet we also knew that type II diabetes ran in families.

So there was the suggestion that there was some kind of genetic cause of why some people might develop type II diabetes when others might not, even if they had the same health habits, same lack of physical activity, or same excess calories in their diet. One person might develop type II diabetes while another one did not. And that was still an unresolved question as to why that might be.

So even though I was not a type II diabetes expert, it was a useful disease to study because it's so common in primary care. And because there was a lot of discovery going on in the field of type II diabetes, genetics and genetics in general by the time I was coming along in fellowship. So I was very fortunate in my fellowship to be paired up with two mentors in a way that I couldn't have planned, but in hindsight was such a perfect marriage was James Meggs, who was a type II diabetes genetic epidemiologist, took me under his wing as a mentor, at the same time as a primary care provider named Richard Grant also took me under his wing.

And Richard and James worked together. Their combination of backgrounds and the projects they were working on turned out to be very formative for my own career. So James was working on the epidemiology discovery of new genetic markers that were associated with the risk of type II diabetes, and then putting these together and figuring out, can we identify patients or people that are at higher risk or lower risk for developing type II diabetes?

At the same time, Richard in collaboration with James was taking those new discoveries and saying, what would it look like to put this into the clinic? How would we use that information and actually get doctors and patients to use it? What would they do with it? What would we tell them to do with it? And would it make a difference if we told someone they're at higher genetic risk of type II diabetes? Would they actually change their behavior?

It's not a given that they would. We know it's very difficult to change behavior. People know they shouldn't smoke. And yet, they still do. All the learning that we were doing from these epidemiologic studies, could it actually be used in clinic to improve patient care? So Richard was working on a clinical trial of giving back genetic information to patients and doctors to see what they would do with that information.

While James was keeping his finger on the pulse of, what are these new discoveries at the epidemiologic level? So being a mentee in that environment was really rich and formative for what I would go on to do.

I mentioned that type II diabetes was that initial helpful model. And there was a lot of discovery going on in 2012 in this area. But there was no reason to stop with type II diabetes alone. We were learning a lot about the human genome in 2012, in 2015. And my career has kind of expanded as our understanding of the human genome has expanded.

And because I'm a generalist clinician instead of a specialist in a single disease, because I'm generally interested in primary care and all the things that might affect my patients, my own research interests started to include all the possible ways that a person's genome could help inform their own healthcare. I still had a focus on primary care and disease prevention. But it wasn't limited to type II diabetes.

It was all of the things that I think about for my patients, the diseases I try to prevent, the diseases I try to screen for. And so that interest, when those genomic discoveries came along, my interest was always, how could I use this in the clinic? Or could I? Or could I design a study that would use this information in the clinic?

Early on in my career, my projects looked at how primary care physicians and patients could use genome sequencing, so not just looking at type II diabetes. But actually, what if you sequenced a person's entire genome and tried to glean from that all the information you could about the risks of diseases they had and how you might be able to prevent that? And in one study called the MEDSEQ Project with a mentor named Robert Green, we gave primary care patients and their primary care physicians that information to interpret it in 2013, 2014, 2015, and to observe what they did with that information.

The punch line of that research study was that they did fine. They were not scared. They did not overreact. So they didn't order unnecessary tests or institute unnecessary treatments. But some real disease risks were observed. And the patients and doctors managed that appropriately. When we performed chart review afterwards and ran it by a team of experts, the experts thought the primary care physicians were able to guide their patients through understanding what their DNA might mean for their healthcare.

Other projects that I've been a part of have looked at a certain kind of genetic test known as a pharmacogenomic test. So this is the idea that your genetic makeup can help you and your doctor make a better decision about the medications that will be most effective for you or have the fewest side effects based on your own unique genetic makeup, based on your own unique profile. So pharmacogenetic associations have been identified for many medications that are commonly used by patients today, including cholesterol medications, blood thinners, antidepressants, medications that millions of people in the US and globally take.

And we now know that there are certain DNA profiles that might make a medication work better for you or not as well for you compared to your neighbor who doesn't have that same genetic profile. We still have a long way to go. Most patients know that their doctor is not ordering a pharmacogenetic profile test for them every time they walk in to the clinic. And there are a lot of reasons for that.

Our EHRs, our electronic health record systems, are not set up to facilitate that very well. Some insurance companies do not reimburse for that kind test. Some primary care providers and other kinds of physicians don't know how to use that information. It was not a part of their medical school training.

So there are a lot of implementation challenges not only for pharmacogenetic tests, but for a lot of the other genetic or genomic tests that I study in my research. These days I'm spending a lot of my research time looking at how a new type of genetic test called a polygenic score might help us improve disease prevention and screening. Polygenic scores are not a single yes/no kind of genetic result. It's not one of our classic genetic tests we think of.

Does this patient carry risk for cystic fibrosis, yes or no, is kind of our classic genetics 101 type genetics test. But these polygenic risk scores instead are calculated from a person's DNA to put that person somewhere on a spectrum or a bell curve of genetic predisposition to a certain disease. So it's not yes you've got the risk factor or no you don't. It's where are you on that spectrum from low risk to high risk?

There are dozens to hundreds of diseases that you could calculate a score for like this such as diabetes, such as breast cancer, coronary disease, and dozens, dozens more. And so many now in the field hypothesize that these scores might be able to help doctors and patients identify the low-risk people who maybe do not need to be screened for these diseases, who do not need to take preventive medications for it.

You could actually de-implement some of the preventive measures we implement in primary care if they're thought to be unnecessary for those individuals, but also perhaps more importantly, identify the people who are particularly high genetic risk for these diseases and target a lot of our preventive efforts to those individuals. Preventive efforts could mean screening tests, like cancer screening tests.

It could mean taking a preventive medication so that you don't develop the disease, implementing a specific lifestyle modification, like changing diet or changing exercise to prevent disease. So this is an active area of research. Many hypotheses abound that this kind of information, this kind of polygenic score, can help better risk stratify patients moving forward.

So my team and I have looked at this in a few ways through a few different clinical trials. But currently, we're spending a lot of our time on the launch of a large randomized clinical trial of what we're calling precision prostate cancer screening. So you might know that prostate cancer is very common among men. And yet, we don't have a great screening test in clinical care.

There is a blood test called the prostate-specific antigen test, or PSA. And if it's high, that can mean that a person has prostate cancer. But it might also not mean that. And so it's not a great screening test in that it can't really distinguish the people who have cancer from the people who do not.

And so unfortunately, a lot of men get this test, and then go on to get biopsies of their prostate and other invasive procedures and turn out not to have prostate cancer, which is good news for them. But it also means that they didn't need some of those biopsies to begin with. Genetic information has really matured in the area of prostate cancer genetics.

And so now, this new study that we're launching called the PROGRESS study, the Prostate Cancer Genetic Risk and Equitable Screening Study, is going to look at whether giving genetic information to patients and their physicians help them make more targeted decisions about their own screening approach to prostate cancer. So identifying the low-risk men who might be able to forgo prostate cancer screening and identifying the high-risk men who might be especially encouraged to undergo prostate cancer screening and to follow up regularly with those screenings.

That's a study that we're launching in early 2024. It will go on for at least five years. And we're really hoping that we can improve the benefit-to-harm ratio of prostate cancer screening for a large population of men. I am very excited to work in this field. I as a generalist, as a primary care physician have broad interests, both clinically and with research.

And what's nice about genetic testing or genomic testing is that it similarly has a broad scope. Imagine your entire genome and all of the information it could give you about your disease and health. The important thing is for scientists like us to make sure we don't overstate the case. Some of these associations are real.

Genetics is an important part of an individual's healthcare. But it's not everything. It's not deterministic. And it's just one piece of a larger puzzle. So going back to my days as a liberal arts student, it was important for me to contextualize some new biomedical information I was learning into the bigger picture of a patient's life and also the population that patient lives in.

Similarly, genetics is just the same. So genetics can be a risk factor or a protective factor for a lot of diseases. But it's not the end all be all for whether or not a person will get a disease or not. The things that we've always told our patients, lifestyle factors like diet, exercise, not smoking are still crucial. So are the social determinants that impact where a person lives, whether they feel safe, what the environmental exposures in their neighborhood might be.

These are also key to live a long, healthy, happy life. Genetics is one piece of that. But as I mentioned, it's not the full picture when it comes for a person's health or disease risk.

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Oby Ukadike-oyer: Thank you for listening. We are always looking to connect and collaborate with the research community and would like to hear from you. Please feel free to email us at onlineeducation.catalyst.harvard.edu to inquire about being a guest on the podcast.

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