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Carlos Bustamante is a population geneticist whose academic research focuses on analysing genome wide patterns of variation within and between species to address fundamental questions in biology, anthropology, and medicine.

Dr. Carlos Bustamante

Dr. Carlos Bustamante, Professor of Biomedical Data Science and Genetics, Stanford University

He has trained over 60 post-doctoral fellows and graduate students as primary advisor and co-authored over 130 papers. Most of his research is located at the interface of computational biology, mathematical genetics, and evolutionary genomics.  

Looking to implement a business strategy for your company? Carlos would probably be the guy to help with that too, as he also advises privately held companies and organisations on legal, IP and business strategy in genomics and healthcare.

What are you working on right now?

I’m really focused on applying genomics in the clinic at scale and so I’m working across two big federal projects.

The first is the ClinGen project, which involves annotating clinical genomes and developing the best resources to enable that. Ideally, I think that needs to move towards machine learning and artificial intelligence that can learn how to annotate and curate genomes at scale. 

The second project is a large-scale sequencing programme examining the genetics of common disease. We’re developing the framework for how we will sequence and analyse hundreds of thousands of genomes over the next four years, as part of the NHGRI, to identify genes responsible for common disease.

The last area, which is the newest and is what I’m most excited about, is beginning to think about how this all goes direct to consumer. For me, the future of medicine is direct to patients, distributed digitally, and deployed at scale, and I believe we’re moving towards a telemedicine system that can begin to solve the cost problems of healthcare. I’m a real believer that, if we do this right, with the right partnerships, we’ll be able to make a healthcare system that’s faster, better, and cheaper than the one we have today, which was designed a hundred years ago for acute care.

Part of that is figuring out how to bring accurate, actionable information to patient consumers; technology can really help in that domain. So we’re looking for partnerships with companies who have technologies that we can validate. One example that one of my colleagues is working on is using a smart watch trained in a clinic with an ECG to monitor the heart rate of dilated cardiomyopathy patients at home.

Name one big development that you would like to see in your field over the next 18 months.

I think it would be the serious deployment of artificial intelligence to improve clinical annotation of genomic and phenotypic information at scale. How are we going to approach that problem in a way that will help us overcome what will be a flood of data? As we sequence more and more genomes, we’re going to find mutations that we’ve never seen before, particularly in clinically relevant genes. How are we supposed to make a prediction about whether these mutations are pathogenic or not? That’s a big problem.

So, from a scale perspective, what we need to do is figure out how we can perform assays and tests to measure the impact of these mutations. If we have enough patient data with biochemical data, then we can begin to learn the rules using these types of tools.

We’ve started doing this type of smart learning, analysing the data in a way to learn things you could never have learned before.

The other area that this is very deeply related to is triage. I’m very interested in infectious diseases, particularly infections that seem to develop into other diseases, such as Lyme disease or PANS-PANDAS. This is a disease where a totally healthy child one day wakes up and has obsessive compulsive disorder, as a result of an infection. It takes months for these patients to find the right doctors, but if you had the right tools that could be deployed to help these people, then you might be able to get them into the clinic more quickly, test them when they’re infected, and treat them before a secondary condition develops. We’re really excited about this area because we feel it’s small enough to use it as a testing ground to learn.

What’s the biggest challenge you face in your work at the moment?

Genomics is in a privileged position and it’s an exciting area; there’s a lot of money sitting out there for people who are interested in this space. So while federal funding is, unfortunately, going down, I think there are lots of opportunities in my area. I’m far more worried about other areas, like basic research which might not have advocates.

I would say that the biggest challenge is building out schemes to study this and deploy at scale. That, in my opinion, has been the real success of genomics; there has been no programme in NIH history where we’ve invested resources and gotten so much reproducible research. We have now standardised this stuff so that the genotyping arrays are 99% accurate – there are few things out there that are as accurate as genotyping tests. That’s huge.

Secondly, we have a huge informatics structure that has been built out. It’s all about scale; how do we get to millions of people in secure platforms where you have phenotype-rich information to really amp up our search for genes related to disease and then interventions? That’s happening, and there are federal efforts there, but there’s a lot of additional capital that can be brought to bear on this. For example, you’re beginning to see pharma companies and health institutions take interest.

There’s never been a better time, technology-wise, to be studying genomics. The tools are just getting better and better, faster and faster. If we can find the right funding and the right model, then it’s unstoppable. The technology and the capital are there; it’s about aligning those in the right projects with the right themes, and getting that information into a platform where it’s verified and can be communicated.

There’s a huge amount of work to do, but I’m excited because I can see where this field is going and how we’re going to be transforming medicine over the next decade.  

What are you most proud of in your career?

That one’s easy: the people I’ve trained. I’ve had the privilege of having more than 60 graduate students, and I just could not be prouder. It is an incredible experience to have so many smart people, so many good people, spending time learning. And me from them, really, because, as everyone knows, the wonderful thing about running your own lab is you can surround yourself with people who are interested in what you’re passionate about and want to learn more about.

My students and postdocs have taught me all sorts of things about autosomal biology, agricultural genomics, statistics, math, and medicine… I get to be a student forever. Their success speaks far louder than my success, so it’s really about them.

Which scientists, living, dead, or fictional, would you invite to dinner, and why?

Louis Pasteur. I think, ultimately, diseases mirror society. In the late 19th century, we were living in crowded, filthy cities, trying to figure out what the hell was going on and how we could address the problem, and you can see germ theory. We had a lot of epidemiological data, like knowing people were getting sick around well water and understanding that something was wrong there.

Of course, the most important medicine is food, and Pasteur was really the first one to secure the food supply, which is the most basic and fundamental problem in society. He did it through a form of thinking that I think we need a hell of a lot more of, which is science being directed specifically at a question.

Basic science is amazing and I love being a basic scientist, but the directed approach of Pasteur is actually what the military uses. To me, it is what we need at this time, to solve more and more pressing issues. The disease of the 21st century is largely cancer, as we polluted and learned about the problems and consequences of the industrialisation of chemistry. We had a war on cancer in the ‘60s – that’s not a coincidence.

Now, we’re learning more about the biology of cancer: how to treat it, how to use and arm our own immune system. Cancer is going to get knocked out. We’ve got a good road map there. So I’d like to sit down with Pasteur and say, ‘Sir, you solved a lot of the problems around infectious disease and food supply, and we’re doing a good job with cancer, but we need help with mental disorders.’ I’d like to sit down and have dinner with him to think about that.

What advice do you wish someone had given you at the start of your career?

During my first year of graduate school, we had a wonderful dinner with Steve Palumbi, who was our Director of Graduate Studies, and he took all his first-year grad students to his house. We were all amped up, excited about our careers, and raring to go, and Steve gave us the most brilliant piece of advice, which I’ve passed on. It was, ‘For a lot of graduate schools, especially in the beginning, expectations are low.’ We all looked puzzled, and then he said, ‘Take advantage of that. Read widely, read deeply, think really hard about the area that you’re excited about, and become an expert in it. You have the time to do that now. Get engaged. Immerse yourself in the literature and think hard about the things that you want to tackle. Because if you don’t master what has been done and what others have thought, then how are you going to contribute to knowledge?’

I’ve remembered that ever since and it’s 100% true. The real gift of post-doctoral training, if it’s done right, is you can take a step back, think, immerse yourself deeply in an area, and grow out from there. You have to find your passion in graduate school. You’ll do a great thesis, but all science is incremental. We’re just adding our stone to the pile. To me, that’s the best advice and, luckily, someone did give it to me.

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Opinions and views expressed in The Short Read are the interviewee’s and not those of the home institution