#268 ‒ Genetics: testing, therapy, editing, association with disease risk, autism, and more | Wendy Chung, M.D., Ph.D.

Hey everyone. Welcome to the Drive Podcast. I'm your host Peter Attia. This podcast, my website and my weekly newsletter all focus on the goal of translating the science of longevity into something accessible for everyone. Our goal is to provide the best content in health and wellness and we've established a great team of analysts to make this happen. It is extremely important important to me to provide all of this content without relying on paid ads to do this. Our work is made entirely possible by our members and in return we offer exclusive member only content and benefits above and beyond what is available for free. If you want to take your knowledge of this space to the next level, it's our goal to ensure members get back much more than the price of a subscription. If you want to learn more about the benefits of our premium membership, head over to peterattiamd.com subscribe My guest this week is Dr. Wendy Chung. Wendy is a Board certified Clinical and Molecular Geneticist and the new Chief of Pediatrics at Boston Children's Hospital. Wendy earned her PhD in genetics from Rockefeller University and an MD from Cornell University Medical College. She completed her Residency in Pediatrics and her Fellowship in Molecular and Clinical Genetics at Columbia's New York Presbyterian Hospital where she then served as a Professor of Pediatrics and directed her research programs towards the genetics of obesity, diabetes, breast cancer, autism and rare diseases. Wendy has received numerous awards for her research as well as for her clinical and teaching contributions, including being elected to the National Academy of Medicine. In my conversation with Wendy, we focus on genetics from a variety of angles. We talk about what science and genetics looked like before we could decode the human genome, as well as what we know currently when it comes to whole genome and exome sequencing. This includes an understanding of the difference between clinical genetic testing and what's available commercially. We also speak about genetics and newborn screening as well as a project that Wendy is involved in called the Guardian Study. We talk about genetics as it relates to a variety of conditions, including pku, which some of you may have heard of. If you've ever noticed on a diet soda can it says if you have pku, don't drink this. Breast cancer, obesity, autism and cardiovascular disease. We ultimately talk about gene therapy, how it works and what's required to change a gene, and of course, the future and ethics of gene therapy. So without further delay, please enjoy my conversation with Dr. Wendy Chung. Hey Wendy, thanks for making time to chat today. This is an especially busy day as I learned you're literally in the process of moving from New York to Boston later today, no less so I'll try not to get in the way of that transition. But that's probably a good intro to kind of explain what it is you do. You're moving from one prestigious institution in New York to another in Boston. Tell us where you're going.

Sure. I'm going to be the Chair of Pediatrics at Boston Children's Hospital, and we'll be at Harvard Medical School.

You're both an MD and a PhD. How do you balance your time between. Let's not include the new responsibilities that will be administrative. But up until now, how have you balanced your time between the lab and clinical practice? How do those split?

So they split about 20% clinical, 80% research. But truth be told, they're really together. So when I think about things, I always say it starts with the patient and ends with the patient. So it starts with the patient. To me, in terms of clinically seething them, many times the answers aren't obvious. And so it becomes a research question. And at the end of the day, though, it has to go back to the patient. So within this, that split, I think, just signifies how much we have to learn and why research is so important to improve clinical care.

You didn't do a combined MSTP or MD PhD program. You did your PhD first and then went to medical school, or did you do the combined program?

Yeah, I did a combined program between Cornell and Rockefeller. And since Rockefeller doesn't have a medical school, we do that with Cornell.

I see. So presumably you knew you wanted to be a physician scientist as you went through training.

Yes, that's right.

What drew you to your current field of genetics? How would you describe to somebody what it is you do in the lab?

I'll give you the short version of this, but I was fortunate enough early in my career to be exposed to the National Institutes of Health and was able to spend, as an undergraduate, summers there. And that was really when I was a biochemistry major as an undergrad, but had the ability to work on phenylketonuria. And although it was mostly in the laboratory, was able to spend time at nih, at the hospital, and seeing patients, and realized this whole paradigm, which to this day is really how I do things about thinking about how these pieces fit together. And I couldn't really think about the science without thinking about the patients. And I couldn't move forward and fill the gaps in our knowledge for patients unless I did the science. I happened to, I think, be good at both. And so it was a natural to me to do both. And I was young and not so worried about the number of gray hairs that I would have by the time I finished and so set out on this relatively long training path, but one that suited me extremely well.

Let's talk a little bit about pku. It's maybe a good introduction to a genetic disease. Maybe tell folks what it is and how frequently it occurs.

PKU stands for phenylketonuria. We may come back to it a little later in the show, but it was actually how we started newborn screening. It was to me a paradigm in terms of patients and families really working together to improve care and being very much partners in that. And so that was even true for a condition that I started studying as a biochemistry major. I was interested specifically in the biochemistry of that. But I realized, and this was in the late 80s, that a lot of what I was doing was doing genetic sequencing to understand the genetic basis of this what we call Mendelian or single gene condition. In this particular case, we did know the gene for this condition, but there were so many other things that I were seeing that we didn't yet know the genes for these underlying conditions. And it was coincidental. But really just, I would say fortuitous for me that the year I started my MD PhD program was the year the Human Genome Project was announced in terms of going forward. And I had, I think the, I don't know, maybe foresight or good luck to be able to see that it was going to be a brand new future when we would have that entire encyclopedia of information to be able to think about human disease differently and thinking about opportunities in the future and what one could do with the information when we had it. And so I really planned my career in thinking about what I'd be able to do 10 or 20 years after I started. And that ended up proving well. And so I've spent a lot of my time using that information and trying to apply it to health.

So what's the clinical manifestation of pku?

So phenylketonuria is a bittersweet condition in the sense that can be associated with intellectual disabilities if not treated. But if caught early, and if treated with a diet that is restricted in phenylalanine, one of the amino acids that we see in proteins. If we restrict that, then even though individuals with PKU can't digest that and get rid of the toxic byproducts, we can prevent those toxic byproducts from building up in the body and essentially poisoning the brain. I say tragic because, and again, we may get to it, identified individuals who weren't picked up through newborn screening and picked up through some of my research studies, for instance, as teenagers, and had irreversible intellectual disabilities. But yet we can prevent those types of problems if these children are identified as newborns. And so that's what our whole newborn screening program was originally predicated on, is that early diagnosis, early intervention, changing lives, improving lives. And in fact, we do that extremely well for most individuals with pku.

Is PKU a dominant gene and is it fully penetrant or is there any variability in that?

That's a great question. So it's a recessive condition, meaning it takes two to tango. Both your parents are carriers for that condition. Within this, there is a spectrum. So we have individuals that are what we call hyperphenymic. So they don't technically have pku, they're not symptomatic, they wouldn't have problems with intellectual disabilities. But it's a spectrum of severity. So beyond a certain threshold, you have too much of the toxic build, and that's when you end up with the problems in terms of brain function. But there are some individuals who have what I'll call subclinical phenotypes. That is, I could see it if I measured, if I bothered to measure the phenylalanine in their blood, but they have enough of the enzyme to be able to clear the toxic byproduct. So that becomes one of the tricky things for us to do in screening newborns is to decide where that threshold is to adjudicate this and figure out who needs treatment.

So is the screening that's done on newborns a genetic screen where you're looking for two copies of the gene?

The traditional way we do this in the very old days, believe it or not, was based on looking at bacteria and how they would grow on an agar that was depleted in phenylalanine. And we would take a heel prick from a baby and put a little dried blood spot punch of that dried blood spot onto a bacterial lawn and see again where the bacteria would grow. So in the very old days, in the late 60s, early 70s, we did the screen in that way. We got more sophisticated and had ways of being able to directly measure phenylalanine. And we now do it with a process called tandem mass spectrometry. But we still use that dried blood spot to be able to do it. Interestingly enough, with a program that we've recently started called Guardian, we also have an orthogonal way of being able to screen, which is based on looking at the DNA and so that we've got two different, essentially data streams coming in to help us with the adjudication of what I was describing before. Who really needs treatment, where's that threshold? And being able to be better in terms of our test parameters, both sensitivity and specificity, so that we can really identify with greater certainty the babies who need treatment.

That's interesting. So just to make sure I understand, the reason you don't just rely on, say, a genome sequence at the moment, even though you know what gene to look for, it would be targeted, you wouldn't need to do a whole genome sequence, is because that wouldn't tell you about the phenotype fully. And the phenotype is just as important as the genotype, maybe more important as you make a clinical decision about dietary restriction.

Yep. So it's very insightful and I'm going to repeat it back just because it might be a subtle thing for some people reading out the DNA sequence we're good at, we're not perfect at. And so being able to decide based on your DNA sequence alone for phenylalanine hydroxylase, the relevant gene, we're not able to perfectly make that one to one correlation about whether or not you'll be beyond a threshold of disease in terms of phenylalanine levels. So we do need, in this case, I'll call the phenotype, the level of phenylalanine levels in the blood. We do need to have that phenotype before we get to the phenotype of intellectual disabilities, which is what we're trying to prevent. So you're right that in this case we use two different data streams to come in. The other reason why the phenotype alone is imperfect is, you can imagine, depending on what you've eaten, your phenylalanine levels fluctuate during the course of the day. And so do it as a cross sectional one time and you might happen to get a baby at just the wrong time or just a sort of higher level. And so being able to have both of those data streams come in allow us to be even better in terms of the accuracy.

Now, it's interesting, if you look at a can of soda or anything that has aspartame in it, it always presents this warning and says, if you have pku, beware. I always find that kind of interesting because the absolute amount of phenylalanine in a minuscule amount of aspartame, which is found in a Diet Coke or something, seems really small. Is that clinically significant? And if so wouldn't that suggest that even milligrams of this amino acid could be problematic to those afflicted?

So for those afflicted, they have to be really careful. If you actually have pku, then we have a very special diet for you. You're not taking diet sodas, you're not doing anything with aspartame. In fact, we may have you on what's effectively a pretty not so fun diet to be on. And in fact, many people don't to be on that diet for life because it's not the tastiest diet. But for women in particular, when they become pregnant, it becomes not only their own body they're influencing, but that of the fetus developing inside. And so we have to be quite careful with women with PKU when they're pregnant as well. And because of that, from a labeling point of view, we want to make sure they're aware of what's in different food products that they might be eating because they won't feel the effect right away. It's not as if they'd get a headache or something like that. And we don't want to see the effects on the developing fetus later on.

You know, given that amino acids show up in all sorts of places. I mean, and it's not just like, well, I'm eating eggs, so therefore I'm just eating methionine. I mean, are there actual protein sources that are completely void of phenylalanine? I mean, there must be, if you're able to subside on some sort of phenylalanine free diet. What types of foods are excluded completely from this diet?

We don't exclude 100% phenylalanine. So it's a low protein diet in general. So we still need some protein and you still have some essential amino acids for your body to be able to grow. You need to make muscle. Especially as a developing child. There's a lot of growth that's there, so we don't completely restrict and it's actually a titration, if you want to think of it that way, that is that we make dietary interventions and we check and then we go back and we diddle and we go back and forth to be able to get it just right. So it's a lifelong treatment in that way. And it becomes even more critical for young children as both their brain is developing, their body is developing. We have to get it just right. So not trivial to do. But on the other hand, when we're good about it, children grow up very healthy.

But it is lifelong treatment. In other words, just getting through adolescence is not enough. If you come off the diet later in life, will you still suffer cognitive changes? Or are you most sensitive to those during development? And by development I mean sort of adolescence and childhood.

You're most sensitive during childhood, for sure. When the brain is growing and when you're making those synapses and connections and being able to develop all of the things you're learning to do, you're definitely most sensitive then. I find that some people, adults in particular, will tell me about differences that they have in terms of clarity of their thinking and other things if they're just totally off the diet and not restricted whatsoever. But it is different in the sense that you don't crash and burn instantaneously. It's more subtle in terms of what you feel, how your body feels.

You know, there are certain diseases, we'll probably talk about them, like sickle cell anemia, where they're recessive conditions. But having one copy of the gene and therefore not having the full phenotype poses an advantage. And that's at least in some part explains the propagation of the gene. Is there any such analogy to be made here? Are there benefits in having one copy of this gene? And obviously there are huge detriments to having two copies.

So not that we know of. I will say that I don't think that we know everything, but it's not so obvious in terms of the frequency of these mutations. There are, I think, historical reasons why we see it in certain parts of the world versus others. But as far as we know, no selective advantage.

And is there an ethnic distribution?

There are. So we do tend to see this, for instance, more in, for instance, Ireland. It tends to be more frequent than we see in other parts of the world. Sub Saharan Africa, as an example. And you know, that has to do with historical reasons, in part, and where variants occurred, migration patterns of how peoples migrated around the world. But we do see it really for all four corners of the world. PKU is seen everywhere and in fact, in newborn screening, pretty universally screened throughout the world for places that have newborn.

Screening programs, just to paint the contours of it. In Ireland, what's the frequency that a child is born with this?

It's a good question. I'm going to hazard a guess, although I'd have to say I'd need to fact check myself. We're probably in the order of one in 5,000 or so.

Okay, and in the US, less than that. But by what, mark?

A little bit less than that. Maybe 1 in 10,000.

So still pretty common condition, relatively speaking.

Yep.

I suspect we're going to talk about this in much greater detail as we go on. But before we do, I'll want to build up a foundation so people understand the basics. But just before we leave pku, is this something that you think in your career will be a target of gene therapy?

It's a great question, and I have to say something I think a lot about. I think we have yet to see certainly many inborn errors of metabolism. So things that are conditions like phenylketonuria, but other things that have to do with the way the body digests, processes, metabolize foods are, some would say, easier targets for gene therapy. And we can go into more or less detail about this, but in part, many of these genes are expressed in the liver. So the liver is kind of the, if you want to think of about it, the metabolic brain of the body or the metabolic clearinghouse, the brain, or rather the liver, is a relatively easy place to target in terms of gene therapy. There are ways that the liver is clearing things, and some of the vectors and the delivery systems we use are relatively easy to get to the liver. And for certain conditions where these are recessive conditions with loss of function, you have to add back the missing enzyme or protein, but you probably don't have to get to 100%. And just for some of your listeners will be astute, you had alluded to carriers for these conditions, recessive individuals who have one copy of the gene that's working just fine, but one copy of the gene that's not. They tend to be fine. That was the point essentially of what you were saying. Do carriers have any advantage or disadvantage? And basically they're indistinguishable is what I would say. Which means for us, in terms of a gene therapy or gene addition or gene replacement strategy, you don't have to be perfect, you have to get some in there, you have to get enough in there, but you don't have to get 100%. And so for all those reasons, these types of conditions are interesting in terms of gene therapy targets. And as you alluded to, given that the treatment is lifelong, that kind of stinks. And so for something that could be transformational in terms of quality of life, many of these metabolic disorders certainly are interesting in terms of genetic therapies. So we may come back to it, but I will not be surprised if within our lifetimes people will be trying genetic therapies for pku.

I definitely want to come back to this both from a historical context and then also to talk about the future. But before we do, it might make sense now to pause and kind of go back to some of the basics. I know that our listeners are quite sophisticated in general, but I always think it helps to just put some foundational knowledge in place. So you talked about how you began your PhD. I'm just doing the math, but it sounds like you began your PhD in the early 90s. And this was about a decade before the human genome was sequenced. So at that time, you know, obviously we understood the structure of DNA. We understood that it was a double helix. We understood that DNA was a template that was used to make rna, and that RNA was then used to make protein. And that's essentially the axiomatic principle of life. Although there maybe we can talk about some edge cases there. How back in that era, like, how did you do genetic work? Maybe explain the differences between sequencing protein gels and what the state of science was a decade before the human genome was sequenced. And also, if you can remember, speculate on what was believed to be the outcome of the human genome sequence and how that differed from what was actually found.

So I'll give you a couple examples that'll bring a smile to some graduate student's face out there somewhere. So when I first started my PhD, eventually, PCR, which people know about polymerase chain reaction, is a molecular Xerox machine that we use to amplify DNA and use it for sequencing and other things, we, relatively soon after I started graduate school, had automated thermocyclers. But within pcr, one had to change the temperature for different stages of this amplification process. We had some where you'd have to denature the DNA, so you'd heat things up, others where the enzyme, the polymerase would work at a different temperature, so you'd have to bring the temperature down. And so there were three different temperatures that you'd cycle at. In the very early days, we didn't have machines that would cycle between these three different temperatures or go through 30 different, different cycles of this. So you can imagine the cheapest labor as a graduate student. So you'd have an ice bucket, you'd have a heating block, and you'd have, you know, sort of a bath, a water bath in terms of a different temperature with a timer in which you'd be literally moving samples. And you'd be essentially a robot being able to do this in the early days. And we'd work with radioactivity to do the DNA Sequencing, we'd have these gels where we'd be reading out these ladders of sequence. It was all very manual and not very high throughput. Certainly I did that, as I said, reading out the phenylalanine hydroxylase gene to be able to. To see all of this. And those were the early days. But if you think about scale and what was necessary to do this for 3 billion base pairs, there was no way that that could be scaled. And so whole industries evolved in terms of being able to do this in a more automated way, to be able to do this. And really, the whole world organized itself around ways to do this massive project. In the early days, we had different chromosomes that were designed to different areas. So Columbia used to be the chromosome 13, center of the universe. In terms of being in charge of that. That mean that chromosomes are ordered by largest with the smallest number. So chromosome one is the largest chromosome. So you'd have some groups that had bigger jobs than others, but we would spread these around, and different groups would come together from around the world for a chromosome 13 meeting, for instance, and try and compare notes. We would have things that we called yeast artificial chromosomes, in which we'd literally, under a microscope, dissect out these chromosomes and put these into these constructs so that we could make more of the DNA and be able to go through and sequence these. There have been transformational technologies that have allowed us to go through in terms of higher throughput, greater processivity. But one of the things that the Human Genome Project did that I think was really important was in the early days, data sharing, data access, really being able to make the world come together by allowing large groups of people to work together. It wasn't every person for themselves. It really was a scientific enterprise collectively. And that's, I think, a fundamental principle in which many of us, as genomicists, believe very firmly in terms of data sharing, privacy, and protecting individuals, individual patients, individual participants. But yet being able to make data freely available as immediately as we can so that we can all use it and get smarter together and learn from each other and be able to advance science as quickly as possible, I just.

Can'T help but want to go back even a little bit further. I remember one of the most interesting books I read, oh, probably in medical school, was the Double Helix, which is, of course, the relatively short but completely fascinating and gripping story of the discovery of the structure of DNA. Do you want to just briefly explain? Because I sort of think right now we are so far removed from how much ingenuity was required to figure out that structure and how that laid the foundation for all that came. And refresh my memory. So this was what, 1953, is that right?

Yeah, I think that's about right.

Yeah, in that ballpark. So up at that point, did we understand that there were 23 pairs of chromosomes? We already knew that, correct.

Believe it or not. There were arguments in the early days about whether it was 46 or 48 total chromosomes and pairs. And it was hard to visualize. Eventually, you know, we got the counting down. We were able to separate them out enough by size and eventually banding pattern. But in the early days, even controversy about that.

So what was it that the four individuals typically just gives credit to Watson and Crick, but really there were four people that played a pretty pivotal role in this. What was the breakthrough that they had that allowed them to understand the structure of this molecule?

So I won't say that this is my super subspecialty, but in terms of the crystallography structure, being able to do that, get a high enough resolution and really have, I think, the insight in terms of being able to imagine this was all of these things coming together quite technical, but also, as you said, I think some unsung heroes in this story as well.

Well, and really it was this remarkable ability to look at 2D images that were captured and understand the mathematics and the picture that this had to be a double helix. And it's interesting when you go back and look at some of the other proposed ideas. Each one of them had a shortcoming, each one of them made sense until you realize, nope, this wouldn't project in this way or that way. So what was the first, first human gene that was identified? How long after the structure of DNA? I'm curious as to what the gene was and more importantly, I guess what were the methods used to identify a gene? You know, long before we had sequencing.

So there were biochemical things that were done. So you mentioned sickle cell disease as an example. So we had proteins, we knew about proteins, protein electrophoresis, being able to see that. And so conditions like sickle cell disease and other hemoglobinopathies we knew at the protein level well before we knew at the dn. So that was something pretty characteristic. Other cases we knew based on enzymatic activity. And so we could see biochemically in a test tube, if you will, what the reaction that was run. So we knew about many of those things before we ever knew the exact DNA sequence or exactly what the genetic variants were that caused those Conditions and.

By the time you were a graduate student, so still pre human genome sequence. So right around the time that Rudi Leibel is figuring out what leptin is and things like that, that how much resolution did you have into what a gene looked like at that time?

So it was pretty painful at the time. We would use these things called linkage maps to try and figure out what chromosome, something, a condition was on. Be able to get closer through linkage analysis to the right neighborhood, the right zip code, eventually the right address. When we did this, we didn't have great signposts to be able to even figure out where we were within this. We didn't have things like structures of genes, references. So as you were doing this, you were sequencing not just one person with the disease, but also you had to sequence, quote, unquote, normal people or average people for comparison. We didn't have that as something you could just look up online. We didn't have the Internet as an example at the time. To be able to see, you know, have investigators work together from around the world is what's much more sort of old school, passing papers back and forth and, you know, meeting in various locations. So it was a lot slower, a lot more laborious. And with this, I have to say, and you had mentioned Rudy Leibel, he did have this big bold idea in terms of cloning a gene for obesity. And it's the first time he put in a grant putting out that idea. People thought it was just totally ridiculous. The idea that you could, we called it positional cloning, but identify a gene solely based on its position within the genome, understanding and not requiring any understanding of the biology or physiology, but just purely based on genetics and genetic mapping. People thought it was impossible to do so. And of course, subsequently, you know, a whole generation of disease or a whole generation of scientists found diseases that way. Way, if you can imagine that process was often a decades long process or longer. I mean, this was not something you did, you know, very quickly. So I often tell people, you know, the first gene that I cloned took eight years. The last gene I cloned took eight hours. So, you know, this is just absolutely, astronomically different in terms of how we now find disease genes.

Yeah, it's very interesting. I looked at a graph. The speed that you're describing even exceeds Moore's Law law. It's on a Moore's Law trajectory with an enormous step function. When high throughput sequencing came along, which we can probably get to later because I think it's important for folks to Understand that what was the first organism for which we had a whole genome sequence within that?

It was certainly a microorganism. I don't remember if it was E. Coli or something similar in terms of a bacteria, but definitely a very small organism. Yeast were another important part of our library, and so being able to understand those small organisms, certainly much easier. You know, even when it comes to the complexity of the human genome, some of us would say that, well, it's been announced repeatedly that the human genome project has been finished, but it's only been recently even that, as we say telomere to telomere, we've been able to see the sequence, really the entirety, including some of the cryptic portions that are hard to read through. So there's still things we have to discover even within the human genome.

So before the human genome was sequenced, which I think was around 2,000, the first announcement, yes, there was an expectation that humans would have how many genes, based on the understanding of how many genes these far, far simpler organisms had.

So there were estimates for some people, as many as 100,000 genes. By comparison, I think current estimates are about 20,000 genes. In terms of the complexity of people. Humans, that is. But yet the complexity at the individual gene level is probably more complicated than we appreciated. Our ability to have different, what we call isoforms or versions of the way gen are cut and pasted together, or how they're utilized in different ways over time and space by different organs or cell types. Any one gene could be made into a dozen or more different gene products. And so some of that complexity was not at the level of the individual gene, but how that gene is reused in slightly different ways. And so anyway, it was shocking the first time. I think we appreciated that it was about 20,000 genes in the genome. There were definitely, definitely people that were surprised by that.

Yeah, it seems like such a small number given the variation between individuals. In fact, outside of identical twins, we have, what, 8 billion people on this planet, all with distinct genomes. And yet the homology between us is how strong? Like, in other words, how similar are we all genetically?

So we're all 99.9% the same. About one in a thousand base pairs is what you and I probably differ by on average. So as humans, we're pretty similar to each other. And most of the genetic variants differences that we have are not meaningful. You know, they don't cause any differences in terms of the way our bodies function. On the other hand, you know, something as subtle as 1 in 3 billion base pairs can be the difference between life and death can be the difference in terms of the way the body or the brain functions. So small nucleotide differences can be profound depending on what genes and when those genes work.

So basically, 3 billion base pairs, 20,000 genes, 46 chromosomes, is sort of the hierarchy of organization. At what point? Well, maybe just explain to folks the difference between coding and non coding portions of the gene.

So when you think about all of those as T's, G's and C's that you talked about, it's a relatively small portion of that information that gets moved from the DNA to eventually the protein. So the portions of that that are made into the proteins are about, I don't say for round numbers, about a percentage and a half of all of that DNA sequence, that other, say 98 and a half percent. There's a lot of it that to be honest, we have no idea what it does. There are certain portions we do understand. They're very important for regulation to know where and when and how much that gene is expressed. There may be other things that are subtle in terms of being able to attract binding factors, transcription factors, other things that may modify the DNA, biochemical changes to the DNA itself which may affect expression. And there are also what people have called junk DNA as well in their repetitive sequences that probably don't do anything positive for us, but you know, get carried along in the ride. But there's a lot that we also don't know. We don't know everything clearly about this. And there may even be disease causing variations that are in that space that we haven't even recognized yet. To your point, it's a small minority that actually encodes ultimately what we think of as most of what forms the body, physically forms the body in terms of proteins, genes.

And in 2000, when the human Genome Project results were announced, what fraction of those 3 billion base pairs were identified?

So within that, I don't know, we'll say round numbers, about 70% or so.

Interesting. And did that include all of the coding segments or was it not yet understood at that time what fraction of those were coding and non coding?

The majority of the coding was identified at that time. To answer your question, there were a few portions of the genome that were hard to read out for various reasons, or hard to map and put the pieces together. One of the things just for the listener to realize is that there was a bit of a jigsaw puzzle when we did. And when we do do the sequencing, in many cases we're not sequencing, I use the term telomere to telomere or end to end along the chromosome. So it's not as if we get one continuous strand of the DNA sequence that comes off the sequencers where we can just read through it and know it. In many cases we have pieces of it and we have to informatically put the pieces back together and put it back into the right order. In some cases, that's because we have overlap between those pieces. And so we can see based on overlap, this is the first piece, that must be the second piece, that the third piece based on the overlaps. And so we make these things called contigs or contiguous sequences of DNA and put the puzzle and the pieces together in that way. There's certain regions of the genome that are complicated. They're what we call repetitive sequences and so they not be unique. And it may be hard to even sequence through those regions. And so putting those pieces back together in the right order in some cases has been challenging to do. And so sometimes you'll hear some of us, as geneticists say there's a dark matter or there's some cryptic regions of the genome that we haven't been able to really dig into. And that's because of some of these complexities of the sequences there and our ability to sequence through them. So even despite what you're saying in terms of knowing the genes or even knowing portions of the sequences, we didn't necessarily know that it was all part of one gene or that we had all the pieces or put it all together yet. And so some genes and some diseases were easier to crack than others as a result.

So today, if somebody goes out and gets a commercial genetic test, what's the difference between someone who goes out and gets a whole genome sequence and say someone that goes to one of the over the counter sequencing services like a 23andMe, what's the difference in the analysis and what's the difference in the information?

This is an important question. And if people are listening, this is time to perk up and listen closely. So there's a big difference. And not all genetic testing is the same. And I'm not being critical of any of the companies that do this, but just to realize they're trying to serve a different purpose. So 23andMe is an example, or Ancestry.com is another example. Those are more things that are not medically sort of targeted. They're not trying to answer a specific medical question of do you have an increased risk of breast cancer? Do you have an increased risk of heart attack? They're really not getting at that level of detail. Just as an example, Ancestry.com is very good at being able to understand your heritage, literally where your family is from, where your ancestors are from. It's quite detailed at this point in terms of being able to say what part of the world your family comes from. If you might be adopted as an example, not know about your heritage or your ancestry, be able to give you some of that. And I'll also say for better or for worse, if you're trying to find this out, you may identify some of your blood relatives, some people who you would know from a family reunion, and some people you might not know for some reason. And people sometimes find out about that. Like I said, even people who are adopted, I've known to find some of their actually their birth parents that way. So that's one type of thing. But that's not really for the intention of identifying information for a medical purpose. And so I just want to warn the listeners that if you get something back, or more importantly if you don't get something back from those tests, it doesn't mean an all clear for your health. It doesn't mean that you're free of cancer or won't have any increased risk risk. So on the other hand, there are other tests that are really designed for a medical purpose to answer a question. And you didn't ask about this specifically, but many of the listeners will know that they would have gotten a test, for instance, if they were thinking about having children, planning a family, wanting to know if they are children or if they were at increased risk of having a child with something like Tay Sachs disease or cystic fibrosis, one of those other recessive conditions that we alluded to. And so that's not what the attention for personal health so much as I said thinking about future children or families. And let me be clear, this is not necessarily about abortion, but this is about being able to care for a child long term and think about reproductive options. So that's another use case and a very common use case in terms of what people will do. Another common use case is for thinking about cancer risk. And so some people may have a family history of cancer, some people may say their particular heritage is such that for instance, if they happen to be of Jewish ancestry, they may may be concerned because they know there's a higher chance of having a brca, so called breast cancer one or brca, one or two mutation. And so some people do a very targeted test. And I'm emphasizing targeted, very specific clinical question. And again it's answering that question. It's not necessarily giving a genetic clean bill of health for everything. It's very focused. On the other hand, you alluded to what I'll call a genomic test. And I'm gonna make a distinction between genomic, genetic and genomic. And what I mean by genomic when I'm saying this is it's really including, as we talked about, all genes. So it's not focused on just a handful of genes, it's really focused on the genes in the genome. Those 20,000 genes, you can look at just the coding regions that we talked about before, those looking at the protein sequence that we call that in the aggregate an exome. Because those little pieces that code the genes are exons, E, X, O, N, S. And when you put them together in the aggregate, we call it the exome. Other individuals are interested in knowing all 3 billion of their base pairs, their entire genetic sequence. And we call that a genome. And that will include everything, both the coding and the non coding regions. I think of that in terms of genome sequence as being in some ways the genetic test. Right? It's all encompassing. One can blind yourself to look at very focused subsets of genes based on a clinical indication, or you can look at everything because you want to look at every everything about your health or because maybe you don't know all of the genes for your particular symptoms. And you have to be all encompassing in terms of that. And we may get to some of those use cases, but there are many conditions that are genetically heterogeneous or have many different genes that can cause them. And so we want to be all encompassing in terms of looking at that. Even though we can sequence all that data right now, we can't interpret it all. So as an example, out of those 20,000 genes, we have now assigned functions with disease for about 7,000. But that still means that for over 50% of those genes, we don't know of a gene disease association. And even I will say, because this happens to me with fair frequency, even when I think I know about an association of a gene with a disease, if we study it further, we'll realize that they don't map just one to one. There may be more than one disease associated with a gene. And so there's still things that we're figuring out about what those genes genes do.

So Wendy, let's just talk technically about those different options that you laid out. And let's start with the most comprehensive. So I've had a whole genome sequence done and I believe it was done off a couple of tubes of blood, maybe even just one tube of blood, if I recall, but no more than two, so 10cc of blood at the most. So I sent that over to. It was a university that did it. It was part of a clinical trial. What did that university do with those two tubes of blood to extract the insight to read the 3 billion base pairs that make up my whole genome.

So I'm guessing, but I'm guessing that what they did is in the white blood cells in that tube of blood, they open those up to extract what we call the genomic DNA. So the DNA included in each of the nuclei of those white blood cells from that they, depending on how they did this, they may have captured out specific fragments and then read through all of that using what we call short read sequen. Again, my guess in terms of this, that short read sequencing was probably less than 100 nucleotides for each little fragment. As they did that, they then had to do that informatic computational step of putting all of those pieces together. And in most cases they were probably able to do that because they had a reference sequence, they knew what the average person looked like, and they put your sequence right on top of that. And to the extent that those mapped uniquely, they could put that all together. There may have been though some of your sequence where they didn't know do to what, where it fit. And so it got sort of put aside in an area that they didn't even analyze. But there were some of your sequence that probably got put aside that they didn't know where it fit, how the pieces fit together. And in fact, the reason I say this, and this is very, very highly technical, is that we're not perfect at doing this. And so there are times when there's information over here on the side where we haven't used as they did that they're then able to read out and depending on the purpose of what your analysis was, they could read out and they could say, well, for instance, if you are interested, I don't know anything about your own medical sit, but if they said, well, we're interested in knowing whether or not you have pku, they could look at your phenylalanine hydroxylase gene, they could read out all the sequence and warn you, As I said, 1 in 1,000 base pairs, there's gonna be a difference in this. And so they see a difference, then they have to do an interpretation. And the interpretation is actually a lot more sophisticated than one might imagine because again, there are literally Tens of thousands of genetic variants in your genome and what they mean and whether or not they do anything whatsoever is hard, hard to know. Each of us has what people think of as mutations or genetic variants that are associated with disease and cause a problem. Each one of us has those. Some that are very, very powerful, some that are kind of wimpy, and they infer some very small risk. But in the aggregate, you put together a lot of these little wimpy genetic variants and it may amount to something more substantial. So depending on when your genome was sequenced, when it was most recently interpreted, you might have gotten really profound, powerful information in terms of cak care of yourself. And you might have gotten the sort of, eh, we don't see much here, you know, sort of you go on your merry way. And for the average person, my guess is if you were middle age when this was done, for the average middle aged person, it's mostly eh, we don't see much here because you've survived, hopefully as a relatively healthy person to this point, that you've essentially made it through some of the most devastating things we can see in the genome.

One more question before we leave the whole genome sequence and talk about the whole excellent sequence. One thing that they learned in me that was quite interesting was that I was mosaic for a certain gene. This was only realized because as part of this clinical trial, everyone in my family was sequenced and one of my children had a full copy of the gene, which they got from me. But I was mosaic for it, so I didn't have very much of it. Can you explain what that means?

So this can come up in a couple of different ways, and I can talk more or less about this if you're interested, but you would think we're the same, Every cell in our body ex exactly the same. But in fact that's not true. And your viewers or your listeners rather, will realize this. When we think of cancer, our genomes are not stable over our life course, from the point of conception to the point of death. And when you think about every cell division, if you have to copy over 3 billion letters, we're not perfect. And we have spell checkers to try and catch these things, but our body doesn't always catch them. And over time, mutations can accumulate in the body. And of course, as they accumulate, this may lead to aberrant cell growth, which is essentially what cancer is. And so at the heart of a genetic disease, but oftentimes not from the genes you're born with, but for the changes that happen over your Life course. Now, in certain individuals, and I'm guessing this was the case when you just described your family, this will be true not just of your skin cells, for instance, if there's too much UV damage to your skin in the summertime, but this can happen in your germline as well. So it can happen in the egg and the sperm. And when this happens again, as what we call somatic mutations or mutations over the the life course, again, if they're in the germline, they can be passed down to the next generation. And so you can be what we call a germline mosaic. You can be a mosaic. And mosaic, just like a tile pattern that you see in a bathroom or something, right, where you have some color tiles one color, and some other tiles another color, they're a different pattern because some cells have the mutation and some don't. And so in the same way, you can have what we call gonadal mosaics, meaning that the germline is affected in some cases. You can see those gonadal mosaicism, that mosaicism in. So what you were talking about in terms of getting a blood sample, you might see that a certain fraction of the cells have those mutations in the blood. And then if you see them in the next generation as well, you'll know that it was transmitted through the germline. I'll share an interesting factoid. For individuals, the number of those mutations in the germline actually increases over the life course. And so, in particular, if you think about the biological process for spermatogenesis with men, those sperm continue to divide over the life course, and those mutations can continue to accumulate over the life course. And so, in fact, some of the conditions that are associated with de novo mutations or new mutations, we see the frequency of that being greater for parents, for instance, who are older parents at the time of conception than for parents who are younger at the time of conception. And it's not, you know, that it's like astronomically exponentially higher. It's a linear process for those types of mutations. But we do see those increasing over the the life course.

Historically, we would assume that women are more susceptible to that via age. I mean, the rate of either aneuploidy or mutation seems to rise more sharply with women earlier, starting probably in mid to late 30s. You are pointing out that the same is true of spermatogenesis. Am I correct in saying that the egg seems more impacted by the sperm? And if so, why is that? Is it a more complex division?

So what you're bringing up up is that meiosis in the two sexes is different and it is susceptible to different underlying biological processes. So as you're saying for women, if you look at the curve in terms of problems, aneuploidy or sex, chrome or not sex, but rather chromosome differences, namely down syndrome, is what many people think about increases with advanced maternal age. And that has to do essentially with the stickiness of the chromosomes at meiosis and the ability to, to separate or not. And so the curve that is associated with that, which many people learned at some point is that there's an inflection. It's not a linear relationship with maternal age. But as you said, in the mid-30s, it starts to increase more significantly. And as a result of that, there's a whole sort of medical way that we can follow women when they're pregnant to try and pick up, if they're interested, those particular chromosome issues. The difference when it comes to women, what we call DNA sequence differences, so again, not whole chromosomes, but single letters, is that that process of being able to have the cell divide and replicate and copy over that information happens at every single cell division. And there's a certain probability that that will happen. And so that's a linear relationship in men. And based on the biology, men obviously from a reproductive point of view, may have children over a larger period of time. So we can see greater differences across men as they're reproducing. So biology' different between the two sexes.

We have a clear sense why you see more of these meiotic differences with age. In other words, what is the fundamental characteristic of aging that is driving that? Is it sort of like evolution says, well, I don't care because I don't want you to reproduce after a certain age. You know, again, not to anthropomorphize evolution, but therefore I'm not going to preserve the integrity of your genome beyond a certain age. I mean, I'm curious as to see. To me, that's strikes me as an explanation, but not the reason. The reason must be something more fundamental at the level of an aging hallmark process.

I hadn't thought of the question quite that way, but I do think if you think about throughout all of human history, the age at which people were reproducing and having children has skewed much younger than it is in terms of current society. So I think we have pushed the boundaries to a certain extent in terms of what the biology historically has been. I don't know if we had a use before, before date, in terms of ovaries and gonads before, but That I think just historically has been what's happened. So within that, the fundamental biology for women has been proteins that are responsible, as I said, in terms of meiosis and separating of the chromosomes and being able to have, if you remember, when meiosis starts in females, it actually is starting way, way early in gestation. So even during fetal life. And so those proteins have to be working and intact from before a fetus is even born, before child is born, lasting all the way through, whenever that pregnancy is conceived, essentially when those gametes are finally dividing. So that could be 30, 40 or more years for that process to have to work. And that's kind of asking a lot when you think about the biology for men. I'll just throw in another interesting factoid, that for some of these mutations that arise during the process of gametogenesis, there are even what we call selfish sperm mutations, that is that certain mutations may even give a selective advantage to those spermatocytes where they may have a reproductive division advantage, for instance. And so we may see more of those in terms of the biology of what we see in the next generation because of the effect they have, even in terms of directly on the sperm. So lots of biology at the root of that.

So let's go one step down from the whole genome sequence to the whole exome sequence. So if as part of my blood test, I only wanted the whole exome sequence, are they actually doing the whole genome sequence and just reporting out the exomes, or are they actually doing something technically different?

So to answer the question, you have to read the fine print on your genetic test report or your clinical trial consent or whatever it is. So I don't know the answer. You know, without knowing that, it certainly was the case that a few years ago, not that long ago, it was so expensive to sequence a genome that we rarely did it. It was really just cost prohibitive. The exome was a really good shortcut because we didn't know what a lot of the other information meant anyway. So we were kind of, it would have been just throwing it away, away. Increasingly we have a better sense of what the non coding regions do. We have better ability to interpret and recognize genetic variants. And so I would say as the sequencing costs have been coming down, there's more of a shift to going to genomes rather than exomes. But truly, most of what is medically used at this point is in the coding space. So even if you're sequencing a genome, it's still focused on the coding regions on a research basis, though very different. And of course, we have to do research before we can apply it clinically. A lot of the research now is understanding what all of those regions do and being able to eventually use that information clinically. So I do think within the next decade we're going to see a shift, and we may even shift from this, what we call short read sequencing of these 100 base pair fragments, even to things that are much longer in terms of accuracy, able to read through some of the greater, the areas that are more complex and probably that we've been missing out on before.

And a short read, you said is about 100, 100 base pairs, plus or minus.

Yep.

So what's the technical limitation for making that longer?

So as you do this, there's just lower and lower fidelity for each base pair that you do. And so at some point you start getting errors within your readout. Then you don't want to have too many errors because you can't distinguish between what are true biology versus what are artifacts of what you're doing in the laboratory.

How are you correcting the errors if you're getting even one error error every in one short read sequence? That would, given that we only differ from each other by 1 1/2% of those base pairs, that would be, for example, you wouldn't be able to use this information in court. How do we preserve the fidelity of this to make such bold claims as, hey, we found this blood at the scene of the crime and we absolutely know dispositively it belongs to this individual.

We do it not just once is the answer. So in fact, when we read this out, we have a term called read depth. It's how many times we look at any one nucleotide in the genome. We don't look at each position just once. Depending on how much we want to spend doing it, we might look at the read depth of 30x. So we might look at every one position on average 30 times. And if you see out of the 30 times 29 of one nucleotide, one of the other, you say, oh, that one, the odd ball there, that's probably just a sequencing error. That's an artifact of our method in the Lab. The other 29 are the ones that we want to pay attention to. In some cases, again, I bring in cancer. It becomes very important to know for those somatic mutations that weren't there from birth, that they may be there in a small number of cells, but cells that can be very, very dangerous for cancer. And so we may increase the read depth to be very, very high. We May go up to 1000x in terms of read depth to make sure we've got the accuracy to see something reproducibly, even in 10% of cells. But again, we're 10%. You need 10% of a large number to have the assurance that what you're seeing is in fact representative of the underlying biology, not an artifact.

Let's talk a little bit more about an example there. So you brought up BRCA1 and BRCA2. So typically the genetic tests that would be done off a whole genome sequence or even a targeted sequence, because let's say a person says I want specifically to be tested for breast cancer genetics, but you're still testing on the actual DNA taken from white blood cells. Correct.

So these days we do things lots of different ways. And just again, for some of the listeners, we've tried to make everything we do more accessible. This is a fundamental sort of core value for. So as an example, we can even now do things from cheek swabs, from saliva samples, from blood samples. So again, we try and make it less invasive, easier to do even potentially from home. And so for some people who have done something like 23andMe, they may have even done it that way.

Let's pick one of those examples, a cheek swab or a blood test, and you're going to do this enormous depth of readout to really make sure that there are no copies of the BRCA gene or any of the other genes that you're looking at. How many genes, by the way, when we do breast cancer genetic screen, how many known genes are we looking for?

So interestingly, it's a little bit of a la carte. So what I mean by that is it's your choice. It's your choice either as a doctor ordering the test, it's your choice as a patient that's getting the test. In some cases, you know, you have a family history of a BRCA mutation. And so within that case, we may know the exact address to go to. And it's a very simple plus minus readout. And we don't have to do a whole genome sequence sequence for that. We just need to look at one gene and say yay or nay, it's there or not there for that particular variant. Beyond that, there are even. I alluded to this before, but there are certain variants that are seen in certain communities. So as an example, if you happen to be Ashkenazi Jewish, there are three different spots in BRCA 1 or 2 that account for the vast majority of all mutations in those two genes. And if you know that we can take a shortcut and we can basically say for literally a small fraction of the cost of sequencing a genome, boop boop boop. We look at those three spots, we get yay or nay. And you've got got most of the information that you need. To your point, there are some people who come in with a family history of breast cancer and they say, but I want to be careful. And so in that circumstance, we may do a panel of 50 different genes, 5o different genes that'll cover most of the genes that we see for hereditary, not just breast cancer, but ovarian cancer, colon cancer, the most common cancers that we see that are driven by germline or inherited genetic factors. So for round numbers, 50 is a good number when you're trying to be really comprehensive. If you said, just give me the focus, breast cancer things, it might be more like 10.

You've said this twice now, but I think it's helpful for folks to listen. When last I checked, maybe 5% of cancer was accounted for by germline mutations, 95% of cancer is accounted for by somatic mutations. Is that still accurate, would you say?

I'd say I'm going to modify that just a little bit. Not to be a contrarian, but for the genes that I'll call monogenic, highly penetrant. Let me unpack that a little bit. Monogenic, monogenic single gene, highly penetrant. High probability that over the life course you'll develop cancer if you have this particular genetic variant. So when you limit yourself to that. Yes, about 5% of cancers are due to those powerful single genes, high probability of cancer. Now, on the other hand, over time we've realized that there are additional genes that all cause call moderate risk genes. Many of those genes may confer something like a two to threefold increased risk as opposed to something like a tenfold increased risk. So there's another probably 5% or so that are due to those. And then there's this other thing that we call polygenic risk. Poly meaning multiple genic genes, Polygenic multiple genes. And the number of genes we oftentimes look at in those circumstances may be anywhere from 100 to hundreds or even, even in some cases, thousands of genetic variants, all mathematically summed together to understand what the risk is associated with that package. All of us have genetic variants that go into that polygenic risk. And part of the question is along a distribution, are you at the high end of that risk curve or are you at the low end or at the average End. And so within that, this is now something that is not clinically being utilized routinely, but we are on a research point of view trying to understand clinical implementation. For now, those polygenic risks for cancer.

Assuming that that amounts to, I don't know, we'll figure it out. But that might amount to 10% of cases. You'd say, well, look, 20% of cancer has a genetic component as opposed to. And it's broken down into those three categories of monogenic, highly penetrant. I think the second category, was it monogenic, not highly penetrant, or not monogenic?

I'd call it monogenic, moderate risk, moderate.

Penetrant, and then polygenic. And those would be the three. And then going back to this case of, say, the breast cancer example, a woman says, I just want to do a deep dive on breast cancer. I don't know which genes it is because all my family's deceased, but four women in my family have died of breast cancer. We're going to do this cheek swab, and you're going to look at 10 genes that are associated, plus whatever the polygon. Why is it that you don't need to look directly at breast cells? Why is it that we can infer that what we see in a cheek cell, an endothelial cell, or an epithelial cell, rather in the cheek or in a monocyte in the blood, is also captured in mammary tissue?

Good question. And the answer is, it's probably not. So what you're doing when you're doing the cheek sample, the blood sample, is you're really getting at the germline. So you're mostly getting at what you were born inherited. Susceptibility is, as we talked about, though, your genes are changing over your life course. Your cells are changing over your life course. Cancer doesn't happen overnight. You don't go from a normal cell to a cancer cell overnight. There's a progression in terms of going through this. And so there are other ways that people have thought about that. I'll call it a liquid biopsy. So this idea that you might be able to. And it's a slightly different test than what I was describing before, but where you would look for these somatic mutations, you described this before, but when you. For that needle in a haystack, if you've got a tumor that's going to slough off some of that DNA into the circulation, you might be able to see some of that fragmented DNA floating around, and you might be able to pick up some of those mutations that might be reflective of that mammary cell that's either gone awry and is a cancer, but maybe not something that you're detecting on mammography or something else. And so this has in some ways been the holy grail of being able to do cancer screening. It's not quite ready for PR time yet. And people think about it more, I would say right now for thinking about recurrence of cancer. So how do you monitor someone who's had a previous cancer diagnosis? You think they're all clear in seeing whether or not they've had a recurrence? The other use case people have thought about is someone who might be at high risk of cancer. So someone who's identified in whatever reason based on an exposure, based on a genetic profile, but it's not ready yet for population screening in terms of being able to pick up cancers at an earlier stage. We're still relying on other, other things to do that.

So let's now talk about what happens at the level of the 23andmes and the ancestries and companies that are obviously doing something far less than a whole genome sequence or even a whole exome sequence just on the basis of the cost at which they can offer these things. What are they technically doing with the epithelial cell of your cheek or the saliva or the white blood cells that they get?

Again, and I'll say read the fine print of what you sign on the consent form, number one, it may change. And I don't represent any of those companies, so I don't want to misspeak in terms of what they're doing. They are in general, though, number one, not trying to detect cancer. So any of what I talked about, not the purpose of what they're doing, they're in general not trying to read out the genome, at least not for the purpose of getting you medical information for what I call news you can use to manage your own healthcare. They're largely doing it in a way that I'll call more recreational. And so with doing that, for any of you who have done 23andMe, you may find out something about. About, for instance, if you were to eat asparagus, what your urine might smell like, or what your earwax might be like, or if you're lactose intolerant, they are things that are related to how the biology of your body works. They are related to genetic variants. So those two things go together, but they're not telling you based on your earwax. If you're going to have major problems with hearing Loss down the road or, you know, cancer risk or things like that. So that's why I use the term recreational in that way.

But what are they technically doing?

Depending on the company and depending on what they're doing, they're oftentimes recreating, reading out what we call single nucleotide polymorphisms or so called SNPs. So they're not reading out the entirety of your genome, they're not reading out all 3 billion base pairs. They are selectively going in and saying, at this exact address, do you have an A or do you have a G? At this other address here, do you have a C or do you have a G? And based on that, they may selectively look at those particular variants and say with your profile, I know that your family originally came from Egypt or wherever it is in terms of being able to look at an stress re where they may say, based on looking at this, I know this particular genetic variant may predispose you to be lactose intolerant. I would expect that you're going to have problems in terms of eating ice cream for dessert tonight. That's generally the type of thing they're reporting out. Depending on again, the company and the terms of the agreements, there may be differences, but generically that's what all many of them are doing.

And so if a gene differs by more than one nucleotide, a SNP is not of much use unless you sample two SNPs in the same gene.

Gets tricky. So technically, a single nucleotide polymorphism could be a genetic variant that has a big, big effect on a gene and could from a medical point of view, be very, very impactful. So it's not just the size that matters. It's, you know, as some people would say, location, location, location. It's like real estate. So it all matters which variant we're talking about. But in general, the ones that they're looking at are not the ones that are medically impactful. They're just normal variants that are innocent bystanders, but help us understand where our ancestors came from. For the most part, that's what the.

Companies are doing, although they do comment on some important ones. So you mentioned isoforms as normal variants. So the APOE gene has three isoforms. The 2, 3, the 4 isoform all are relatively common. I mean, the 3 being the most common, then the 4, the 2 is not that common, but all would be considered, quote, unquote, normal variants. One obviously comes with a much higher risk of neurodegenerative disease. A 23andMe test does read out that prediction. Presumably that tells us that those genes only really differ by one base pair. Correct. The two, the three, the four only differ by one base pair. That's therefore the only place that they need to sample. But I've seen in 10 years several instances of a missed call, meaning the SNP read ends up not matching with the more rigorous exome sequence. Why do you think that's the case? Does that surprise you?

I will say that, you know, in doing this, I'm not someone, you know that has been asked to go in and QC or do quality control or anything like that. For the laboratories I have have known of things as simple as these are done in plates that oftentimes are 12 by 8 plates. And if you flip the plate the other way, you can have sample switches and you've got a different person being read out for a different thing. It can be something as simple as a logistic like that. And I have seen that lab error before. There can be sample switches at multiple places. And at the end of the day, I will say that if you are doing something from the recreational side to something where you are going to make a major healthcare decision, you are, as in a woman, for instance, going to go through and have a mastectomy, get a second opinion, like, be sure that this is really you and it's really the result you think it is before you do anything irreversible or go out and buy that big life insurance policy. And I would say that in general, if you were getting a second opinion.

About cancer diagnosis, you mentioned the Guardian study earlier. Can you say a little bit more about what that study is?

So the Guardian study, as you can imagine, based on what I started out, the conversation with phenylkech is I've always been wanting to be able to get information that people could use to be able to maximize health and being able to just be the best person they could be. And I started out in 1996 again, had started out in the space of PKU decades ago and had been studying a disease called spinal muscular atrophy for about a decade with colleagues of mine. And this is a neurodegenerative condition and used to be the most common genetic cause of death for children like than two years of age. And I realized starting in 2016 that we were just at the cusp of potentially a treatment that might slow down or stop the neurodegeneration. Yet tragically, if we didn't identify babies before they started showing symptoms, it would be too late. That is, we'd have this window of opportunity. So we started out a newborn screening program for sma. And then babies that were identified through that had the option, if they wanted to, of going into a clinical, clinical trial that ended up being quite synergistic in the sense that we did identify babies who would have been predicted to have the most severe type of sma. They did get into early clinical trials right away. They did benefit from those that helped in terms of the ultimate evidence that was necessary to show the efficacy of those treatments. And because of that, and because we were able to show that we could do it technically and that people wanted it, SMA has been added to the recommended universal screening panel for babies across the United States. And so now 4 million babies born each year in the United States, United States are screened for sma. And we have three FDA approved treatments including a one and done gene therapy. So babies can now be identified within the first week or two of life, get a one and done IV infusion of the gene and go on to have much, much better life, if not be quote unquote normal, at least as far as we can see so far. So that got me thinking about doing this on larger scale. We've since done newborn screening study for Duchenne muscular dystrophy and just recently actually was FDA approved a treatment for dmd, Duchenne's muscular dystroph. But I'm, I don't know, I'm getting older and I'm getting more impatient and I didn't want to do these one by one. I started thinking about how could we do these at scale for population health and not just for one condition at a time, but how could we do it for dozens or hundreds or potentially even more conditions? And so the Guardian study actually stands for something. It stands for genomic uniform screening against rare diseases in all newborns. And if you put the letters together from that, it spells out Guardian. And the idea behind that is to that same newborn screening dried blood spot that we use already for PKU that we talked about, sequence the genome, we don't need to read out everything in the genome. We only read out the genes that we consent people to read that they consent to in the study. And those genes are genes that have, I call it news. We can use information that has treatments immediately available. And in planning this study for almost four years, or just over four years, we with families, we had many, many iterations about what they wanted, what they wanted us to screen for, what should enable them to be the best parents and give their children the best chance at a healthy life. And we thought about also this dynamic change in what we'd have treatments for, the fact that the world is changing rapidly, and we wanted the flexibility that if a new treatment became approved tomorrow, boom, we could instantly change the screen and be able to implement that. We wouldn't have to wait a decade to gather the evidence to do that. We wanted to be nimble. So the reason for using the genome as the backbone is it gives us that infinite flexibility to be able to adapt and to be able to move the field forward. So we've been doing the Guardian study in New York City since September 2022, and right now have screened just over 3,000 babies. And it really has been remarkable to me in terms of being able to see just the broad support from our community in doing this in New York City. You should realize most of the listeners probably do realize the wonderful diversity we have in New York City, that is, of the people who participate. It's not just white folks. It's not just people who are from Ireland. We were talking about Irish individuals in pku, but it's people from around the world. We have about a quarter of people of European ancestry, of Latina ancestry, of black ancestry, of Asian and other ancestry. So it becomes really, I think, representativeness or representative basically of the world. And it also is geared to leave no baby behind, because newborn screening is kind of this one universal thing where everyone goes through the health system in the same way. And by making this free and being able to allow everyone to enter if they so chose, we can really see also what information people want and what they don't want within this. I guess one of the things that's been refreshing to me is to see that about 74% of parents that we approach and offer this to decide they want to do this. And that's an important number to me. When we did this for SMA, the number was 93%. When we did this for Duchenne Muscular dystrophy, it was 84%. And so within this, it's not 100% of people who want any of these genetic screens. And that's perfectly fine. I'm not trying to force anyone to do anything. But it's also not 10%. The majority of parents are saying, yes, if there's something I can do to ensure that I have a healthier child, give it to me. Help me be a better parent. Why would I not want to do this? Is mostly what we hear. Within this, I also appreciate, and we do this with regular newborn screening, just the traditional newborn screening. And we realize that traditional newborn screen screening isn't perfect. I never thought it was. Nothing ever is. But we realized that adding this additional dimension, and we've even done it for PKU within this study, this in additional dimension helps us to do a better job. And so just as an example, we've also identified part of newborn screening identifies some children with severe combined immunodeficiency, a problem where you can have an overwhelming infection and die from this, but a treatment is available, including a bone marrow transplant. And so because of that, we have as part of newborn screening, a way to screen and identify some, but not all, children that have that. We've added this now genome sequencing to enrich and improve that and in fact identified a baby that was missed by our traditional newborn screening for scid, yet is at increased risk in terms of this overwhelming infection, but yet with the opportunity to intervene at an early stage when a bone marrow transplant will be most effective. And so there are numerous examples where we've identified whether it's Wilson, whether it's severe combined immunodeficiency, whether it's achondroplasia, but other conditions that are treatable, that we just needed to identify those babies. And as we've done that, the number of children that. And I just know, because I've been practicing in New York City for 25 years, I know sort of how people navigate the system and how they get through. And we've been able to really get to many of the people who are usually unfortunately left behind, either because they're immigrants, they don't speak the language, they don't have the same health insurance. But individuals that we're seeing come out positive for this are very, very different in terms of reflecting our community than the people who navigate the healthcare system and get in to see us. And we realize, based on other studies that we've done, that most of the children that would have been diagnosed, if ever they were diagnosed, on average, aren't diagnosed until somewhere between 8, 9, 10 years of age. And so we're intervening or we're able to identify them literally a decade earlier, before a lot of damage has been done to their body. So it's just the beginning. You know, 3,000 is great. I think it demonstrates that we can do this. I think it tells us what our community wants out of this. It shows us some pitfalls in terms of how it's hard to do and what we need to do to do it better. But I do fully believe that this Both de risks this in terms of being able to also have groups that are working on therapies, be able to realize that this is something, there's an opportunity now for treatment for this and is a powerful way of moving forward, forward health equity, at least for children, for the next generation.

Is this something that's done only at Columbia or is it a multi center New York Hospital endeavor?

So right now this is done through our New York Presbyterian Hospital system. So it's not just Columbia, but it's through this hospital network. It's only so far in those hospitals. But based on our success for this, we are figuring out how we can be able to expand this more broadly and really think about this, as I said, as integrating within the public health infrastructure. Not trivial to do this on scale. As an example to doing this in New York State, if we were to do this for every baby, we'd need to do it for about 210,000 babies a year. So no small feat, but something that we're gaining the experience to know what the pain points are and how to solve for them.

Is this all funded by nih?

So within this, as you can imagine, this is not inexpensive to do. So in fact, none of this is funded by nih. Nih, I won't go into all the details, but NIH is able to fund programs that are about this big. People may or may not see this if they're just listening to me, but very small amount, this ends up being about two orders of magnitude larger in cost than anything that NIH can fund. And so it's a challenge in terms of as you think about big, bold, new transformative ideas, how do we as a scientific community accomplish these? And so we've done this by putting together many different stakeholders. I don't think any one group could be able to take this on. And truth be told, we're not completely there with the funding. I think we needed to demonstrate that we actually could do this in this first feasibility stage before gaining the resources to do this with what I hope will be at least 100,000 babies. To get to the sample size, we need to see some of these rare conditions and to know what the outcomes are and that we really can screen for them.

So what's the actual cost of doing the sequence for each baby? So to look at those 250 some odd conditions, what's the bench cost?

So as we started out doing this round number, $1,000 per baby. So thinking about generating the data, interpreting the data, getting it back to folks, cost of about $1,000 per. The goal is to be able to do this and get it down by an order of magnitude. Can we get it down to $100 per baby as an example? And in doing that, can we think about the economic impact, most importantly the health impact for the baby. But as we think about as a society, how to be able to afford doing this, we are doing the economic analysis to understand. But the good thing is sequencing costs are decreasing. Analysis interpretation costs are decreasing. More of this can be done in automated ways as we understand what normal variation is for people around the world. And that's one of the critical factors is doing that around the world.

Now that thousand dollars is a fully loaded cost. That's the interpretation, that's the overhead, that's the PI time and such. Right. The sequencing cost must be significantly less than that given that Illuminate could do a whole genome sequence for $1,000 now.

Right. Even over the course of this study, the sequencing costs have come down, if you can imagine it. And we just started it, like I said, September 2022, less than a year ago. But already the sequencing costs have come down. I expect they'll continue to come down in terms of, of this. And so data generation certainly can be done for well less than $1,000 now. But as you said, part of it is the interpretation and we have study staff that explain the study to everyone, explain results to paramily. So yep, includes multiple pieces.

So at the outset of this discussion you mentioned that SMA actually has a successful gene therapy. I was not aware of that.

Yes.

How many of these single gene highly penetrant conditions that children are born with, be it inborn errors of metabolism or neurotypical neurodegenerative diseases, et cetera. How many of them have FDA approved gene therapies already?

Not very many of them. So really the shining example is SMA or spinal muscular atrophy. There are very few gene therapies that are now approved. There are now. For instance, I mentioned Duchenne muscular dystrophy, hemophilia. There are a few other conditions, but it is still literally a handful for gene therapy. Literally gene therapy. Others have treatments available and I think for many of those. I'll just give one example that we've had through the Guardian study, a condition called Wilson Syndrome, for instance, that leads to ultimately liver failure and need for liver transplant. The treatment that we give children for this is zinc. So it's something that it doesn't require gene therapy. It doesn't need anything that fancy. We can simply use zinc to out compete copper and make sure that we don't end up with a copper overload situation. And we have treatments that are very well tolerated, pennies a day in terms of doing doing this, we hope extremely effective long term. So although gene therapy is wonderful, I want to underscore we don't always need gene therapy as long as we have that early diagnosis.

If there were three diseases today that you see in a pediatric practice that would be most amenable to gene therapy in terms of some aggregate score of the technical nature of doing the gene therapy and the lack of alternative therapies elsewhere and the number of kids afflicted. If you were of sort of to take that as your triple proxy, what would be. If you could wave a magic wand, what would be the three diseases you would want to put high on the list of gene therapy targets?

Hmm, that's a great question. I don't think I've ever thought that through exactly in that way. So there are a lot of neurological conditions. Let me start with that in terms of places that we are woefully behind in terms of treatments. And I'll give you one shining example of Tay Sachs disease as an example. Many individuals, the way they've dealt with this because there's no treatment, is simply not having children or not having children together or going through other reproductive options. But things like Tay Sachs disease is just a terrible condition and it has relatively high population prevalence to one of your points, and has really nothing available in terms of treatment today. And so those children are born healthy, normal children and die within the first few years of life with a degenerative course, oftentimes associated with epilepsy. So a condition, Tay Sachs or a condition like that, I think fulfills all the criteria that you're talking about. Other similar conditions like that, although we still need to understand treatability, are things like Fragile X another condition that we see in this case, X linked by the. You can tell from the name Fragile X similar in terms of high frequency. Really nothing in terms of treatability at this point. And perhaps the ability. It's a. We can get into it or not. But the gene therapy for this is a little bit trickier. Different strategy from a technical point of view than what one would take for Tay Sachs. So whether it's gene therapy or gene editing or other types of things, there would be a different technical strategy. And then I would say they're just a large group, I won't pick one. But large groups of inborn errors in terms of liver disease that primarily affect the liver. So whether you're talking about something like maple syrup, urine disease, propionic acidemia, but something like that, that we have good programs in place to identify those children's. And our treatments, they're just not up to snuff yet. They're not quite, quite as good as they should be.

Well, let's talk about how genetic therapy works. So, God, probably 23 years ago, we had a tragedy in one of the most highly publicized examples of early gene therapy. The tragedy, of course, really didn't have to do directly with the gene therapy. It had to do with the vector that was used to deliver it. And the young man who received that gene. I can't remember what it was for. It was for an invorn er of metabolism as well, wasn't it?

Urea cycle defect called ornithine transcarbamylase deficiency.

Yeah. And Jesse, what was his last name?

Jesse Gelsinger.

Gelsinger, yeah. And this was at Penn, at Chop, right? That's right about the year 2000, if my memory is correct.

That's about right. Maybe off by eight.

Yeah.

Yep.

And so let's talk about that. Let's talk technically about that. So they used an adenovirus, but explain what that means and what was the state of the, the art 25ish years ago. And let's contrast that with what's being done today.

For those of you who are listening, Adenoviruses obviously causes the common cold. And so whether it's adeno or adeno associated virus, we oftentimes use that as the vector or the delivery vehicle to deliver genes within this. The viruses are manipulated, they're engineered, so to speak, so that they're not gonna be contagious. So even though you might get a cold or pass it along to someone, you're not gonna do that with gene therapy. Yet there are problems with this because the common cold is. And so people may have been infected with adenoviruses and their body may try and mount an immune response when it's infected, as it would be with a cold. And that's where a lot of the mischief comes in. And unfortunately it hasn't ended with Jesse and Jesse's death. There have been other deaths in the gene therapy space with others that have had a response to the vectors, oftentimes an immunological response to that. In Jesse Gelsinger's case, it was the vector in the gene therapy was targeted at the liver. We've talked about a little bit of that already. But sometimes there can be an overwhelming response from the liver, where the liver starts to fail, where there's an immune response that goes on. And so, as I said, this has not been solved completely at this point. There have been other genetic therapies, other diseases, not just liver diseases, but where there have been similar responses. And I think one of the things that we've learned from this is we have to be very careful with people with underlying liver disease when it comes to this, because a fragile liver can get tipped over, especially with adenovirus. We also have to be careful about who's been exposed to those viruses. So sometimes we do screens to be able to see who might have one of these responses. But ultimately, and partly because of that, people have also been trying to figure out other delivery systems, other vehicles, other ways of being able to get those genes into cells that may not be as toxic or problematic.

Help me understand a little bit. You know, so an adenovirus virus is very common. Presumably in the case of Jesse, he'd already been exposed to some antigen that was related to this. And so he already had memory B cells and memory T cells that were ready to mount a healthy immune response. Should he have been exposed to that very common adenovirus? Again, the fact that he had such a harsh response to the gene therapy, was that because of the dose of adenovirus that he received, or does that imply that he would have had some sort of catastrophic multisystem organ failure had he just had another exposure to that exact adenovirus as a cold, and that, as you said, was a function of his underlying liver health?

So it's a very tricky situation. And I say this because there will be some either patients or doctors advising patients about genetic therapies or genetic therapy trials in the future. It's tricky in the following sense. You're right that there's a dose response in terms of the immunological response. And so you don't want to go too high on the dose because you don't want to have too big a response. On the other hand, with these gene therapies, you oftentimes get one chance at this in terms of doing this, because once you've given the therapy, the body is going to mount an immune response to that and would neutralize that same therapy if you were to give that again. And so the tricky thing about this is you don't want to go too high and you don't want to go too low, because if you underdose it and if you don't get enough in and that's your one shot on goal, you've burned it. And so within this, it's a tricky situation to figure out how to get it just right. And as it is many clinical trials, when you're first in human, you don't know right? It is first in human. Oftentimes there are non human primates in terms of trying to figure out as much as you can, but it's still not a person. And each person is unique. And so as you're doing it, it is a tricky situation in terms of getting it right. When you do the first person, you learn and you figure out from there whether you're going to go higher or lower. But there is someone who's going to be the first person.

And there's no way to engineer the adenovirus to make it invisible to the immune system while still able to insert its DNA package into the cell.

So there's certainly things that we do to try and do this better. As I alluded to, one of the advantages for someone, for instance, with sma, where we're dosing them at a week or two of life, is they haven't had the common cold, they haven't been exposed to these things, they've got a fresh immune system. So the likelihood they're going to have a response like this is much lower. So we haven't been seeing those types of things with newborns that we've been treating with sma. There are other vectors, or not just vectors, other delivery vehicles that we use, not viruses. And so that's something else that in terms of developing new technologies, things that may not pose the same problems, I don't want to guarantee that that's going to be the case, but certainly with the experience we've had, even from the COVID vaccine, from MRNA vaccines, and having delivery systems that were basically lipid nanoparticles to deliver nucleic acids to cells, we've learned a tremendous amount from millions of people who have been treated with that. And some of those technologies may prove to be helpful with other delivery systems.

Maybe this is a good time to explain what CRISPR is and how it factors into gene editing. Although I guess before we do that, explain what is required to change a gene. So, I don't know, pick someone with sickle cell anemia. So if you wanted to use gene therapy to fix, quote, unquote, sickle cell anemia, my vague recollection from medical school biochemistry is that was a one amino acid change, correct?

Correct.

Was valine one of them?

Yep. So the eighth amino acid. Exactly. In hemoglobin beta is that there are two different sort of variations or flavors that that amino acid you can change. But that causes sickle cell disease. Yes.

Okay. So if you want to permanently change that, it's not enough to do it in the red blood cells that are floating around in the bloodstream, because they're going to be trashed in the spleen a couple of months from now. You must change the DNA of the stem cells in the marrow, correct?

That's exactly right. You have to get those progenitor cells from which the future generations of red cells will be derived.

And let's assume you had the correct gene sequence. That's not hard to do. We know what that is. And we can put that into a virus and maybe just explain to people why viruses are great via. What is it about a virus that makes it an ideal candidate here?

Well, the nice thing about a virus is it was designed by mother nature to infect our cells. Right. So it's pretty good at being able to do that. The viruses that you're talking to and the way that I think about them are often helpful for gene addition. So where you've got a protein product that hasn't shown up for work, it's not working. It's a loss of function. It's not present. You need to be able to deliver or add back that gene. It may not be integrated into your genome. And in fact, there are probably some advantages if it's not. But the virus can bring that in and bring it into the cells. And to your point, and this is important, many times that means bringing it into stem cells so that they can have the longevity of continuing to populate the body over time.

And so is it safe to say that the real challenge is that step? It's not just putting the corrected version of hemoglobin, the gene for the corrected version of hemoglobin, into the virus of choice. It's fake. Figuring out how to get that to selectively infect a progenitor stem cell within the bone marrow. Is that presumably why we don't yet have genetic therapy for sickle cell anemia?

Well, sickle cell is interesting in that there are a couple different strategies people think of. So one is gene editing is the term I'm going to use. So it's fixing the gene in sort of where it is not adding a gene, but actually fixing the gene that's present. Another strategy that people think about, again, for the aficionados who are that, as I mentioned, hemoglobin beta, in terms of the adult form of hemoglobin there's also fetal hemoglobin that's made in utero. And so with that, that actually has a very tight binding of oxygen because the fetus needs to be able to get oxygen from the maternal blood, and it can substitute for adult hemoglobin actually quite efficiently. And so one thing one can do is actually turn up the amount of fetal hemoglobin expression and essentially be the in situ version of your gen therapy. It's just manipulating the gene expression, but for a gene that's already present in those individuals. And so there are ways of manipulating gene expression in that case for fetal hemoglobin. So there are multiple ways to skin a cat, so to speak, very technically different in terms of what we administer to people and what we're changing in terms of the gene therapy. But I want to pick up on what you were talking about with gene editing, because that's yet something else that's really insight to, and I want to.

Come back to that. Let's go back to one more thing on. On the gene addition. If you were to add a gene for a corrected version of beta hemoglobin, would you actually run into a problem now where you're making too much hemoglobin and half of it is appropriate and half of it is sickle and therefore not. And you could argue you're creating more problems because you've doubled the hemoglobin, but you still have the issue where the cells sickle and create all of the distal ischemia that the person has. So is that the real reason that nobody's interested in doing in addition therapy for sickle cell anemia?

So that's exactly right. Just for the listeners, we don't use the gene addition strategy for sickle cell anemia because we'd have to dilute out, so to speak, so much of the hemoglobin with the sickling that physiologically we run into other problems.

Okay, so gene editing would, hands down, be the best solution for certainly a situation like that, and probably many cases could it be done with high fidelity and ease? So I guess let's talk about gene editing in any way you see fit, in whatever way you want to tell the story. I mean, gene editing in and of itself is a whole podcast, I suppose, but what's the medium version of that story?

So from a simplistic way of thinking about this, it's going in and in situ, being able to correct the genetic variant. Now realizing we've talked about single nucleotide variants, those are the easiest ones to edit. There's just one single base pair that needs to be flipped. It actually matters what that base pair is if you have to change an A to a G or a C to a T. Believe it or not, there are different base editors that can do different types of nucleotide switches. But there are many mutations that are not just single nucleotides. There may be multiple nucleotides, there may be multiple repeats. These sort of complex things that we talked about with Fragile X. There may be entire chunks of chromosomes, they get very complicated. And furthermore, it may be. When you think about population genetics, you may have a mutation distribution across a gene that may be quite heterogeneous. Sickle cell is an easy one in the way that you mentioned. You're talking about the same position for everyone with sickle cell disease. Couple different nucleic acids, but it's the same position essentially. Whereas other genetic conditions, it may be that almost everyone has a different mutation. So you have lots of different things you need to edit and that may be easier or more difficult to do. So there are some nuances in terms of that. You mentioned CRISPR. So CRISPR Cas9 is something that many will know because Nobel laureates were awarded for this AM discovery which was, by the way, I will say, just really good science with creative women who are thinking about other ways to use it. It wasn't fundamentally the discovery was not made with the intention of doing genetic engineering or, you know, genetic manipulations, but really smart people thinking about it. The CRISPR Cas9 system has, I think of it as an Achilles heel of a double stranded DNA break. So it fundamentally, in terms of being able to make the correction, has to cut the DNA, cutting the two strands of the DNA to make the correct. And that fundamentally leads to some instability as the cell repairs. That process, which you use the word fidelity, which I like the use of that term because it really is all about fidelity and potential off target effects where you inadvertently introduce, other than the intended correction, other genetic changes. And sometimes those other genetic changes can cause mischief. We call them off target effects. So things where they may inadvertently destroy the gene, cause other changes to the gene, cause other change to other genes that you weren't even trying to target. But it can lead to problems of essentially promiscuity or inaccuracy or low fidelity. This is to me, in my opinion, the Achilles heel in terms of that particular system. So there are others in terms of thinking about other technologies, other strategies that in terms of doing a double stranded DNA break, will do a single Stranded DNA break. So it'll nick just one of the two copies, which in terms of the process that the cellular machinery has for the repair of that ends up being a much higher fidelity system. So there are lower off target, lower error rates. It tends to be a more robust system. So this is still very, very early. I want to underscore this very early in terms of doing this. There are lots of other complexities besides the machinery of what I just described was prime editing, but other complexities in terms of the machinery to go in and make the changes. What types of mutations can be repaired, prime editing to be able to do, just not single nucleotides, but much more complex mutations to be able to fix. But ultimately it's a vehicle for delivery. It's getting in early enough before the damage is done to the body. It's being able to get to the part of the body safely that you need to. It's sort of multiple pieces of the puzzle that have to all be solved simultaneously to get the whole package to work. So we're not quite there yet, but I am optimistic that we are, as a lot of scientists working together, realizing that this may be one sort solution eventually when all the components are there that may be scalable to deal with many different types of genetic conditions.

You were alluding to the differences in strategies between Tay Sachs and Fragile X syndrome. Do we have enough information now in this discussion for you to explain the different strategies there?

I think so. So let's start with Tay Sachs. Tay Sachs is due to an enzyme that's missing. We talked about recessives. It's a recessive condition. This is a degenerative condition. And so you want to be able to get in early for all the reasons that we've talked. And you could do a gene addition. The gene, the enzyme is missing, so you can just pop it back in. It doesn't have to integrate. You just need to get it early enough to do its job and not to cause any mischief along the way. So that strategy would be a good strategy. The tough part, you need to get it into the brain. You know, as you're thinking about the delivery system. Brain is a complex organ, so you want to be able to get it throughout the brain for function.

What does that mean, Wendy? That means you'd have to introduce like an intranasal virus. Is this something in glial cells, in neurons? Where does this enzyme normally get made within this?

As you said, there are multiple ways to access the brain. It's obviously a protected space in terms of the Blood brain barrier. I doubt we're going to be able to do it with intranasal, although there is some that you can get by putting this in that way. Some cases we do intrathecal. So for women who've had an epidural, it's basically the same way that we access the space for an epidural in some cases. For anyone who's thought about chemotherapy that we give for brain cancer, sometimes we actually have to do it into the ventricle. Sounds a little bit barbaric, baric. But we go through the skull and being able to do the injections there. But my point is it's not as simple as a simple intravenous infusion. It's not like we can just give it peripherally and get it to the brain where we need to. So it's challenging in that way. And as we think about it, in some cases we need to get throughout the brain, even into deep nuclei or different parts of the brain. So as an example, if you were to inject it and you had a high concentration on the left, but it didn't get to the right, that would be a problem. You need to be able to get even distribution as we're doing this anyway. With Tay Sachs, though, it is the case that, as I was alluding to before, you probably don't need to get to 100% of the protein or the enzyme that's there. Even 50%, I'm sure is enough. And it's possible you could get down to 20% and that would be just fine. And so that's one strategy. Fragile X is a little bit more complicated. The actual mutation itself is what we call a trinucleotide repeat. A repeat that's too big. And so we need to be able to make it smaller within doing this. It also has the same problems in terms of being in the brain, but it's not just simply adding back some additional Fragile X protein. So we can't just make it a gene addition strategy. We've gotta really think about the gene editing that I was alluding to, where you're fixing, shrinking the size of that repeat back down to the normal size. What's unknown. And I think one of the things we don't know until we do it in people is what is that window of treatability? And just to be provocative, to let the listeners think about this, is that window. Even if Guardian worked perfectly and we could identify these babies with this within the first week of life, is that early enough? Of course, my hope is that for many conditions that will be. It's possible that we'll need to go even earlier. And so there are some people that have thought about even in utero gene therapy or genetic treatments for some conditions, not all of them, but for some conditions where it might be necessary to get even during development, fetal development to have the maximal effect. So I'm not saying we're going there in anytime soon, but just to sort of think through that there may be imperfect solutions unless one gets to the right time and the right place. And to your point, the right cell type even.

And fragile X is also a recessive condition, so it can only impact women, presumably because you would need both copies of the X.

So fragile X, we do call it an X linked recessive. But what that also means is that it's mostly males who are affected because males only have the one X. If they have that repeat expansion, the males will be affected. Females can affected, although it's much more.

Unusual because they would need to have got the X from their father as well.

That's it.

I want to come back and talk more at the end of our discussion about kind of the future of gene editing and the ethics around it and things like that, which I'm sure is something you've thought a lot about. Before we do that, I want to talk about some of the more complex diseases that clearly have a genetic component, but they're probably much more polygenic. So let's start with what your colleagues down the hall are doing with respect to obesity. How much do we understand about the genetics of obesity and does genetic therapy play any role there?

So I'll start out about talking with obesity, but I may switch gears at some point soon after that. So obesity, we have ways of calculating heritability. It's to give us a scientific insight of how genetic is a certain condition. So you can do this by looking at twins, for instance. You can look at identical twins, you can fraternal twins, and you can see how similar they are in terms of body mass index, adiposity, things like that, as measures of obesity. And it does end up being highly heritable. It's not the most heritable factor, but it is highly heritable. So that sort of points in one direction that genes are important.

What's the heritability of obesity, by the way?

So the heritability running somewhere around 50% for round numbers or 0.5. Other conditions that are extremely heritable of course are closer to one. So as an example, and by comparison, type 2 diabetes or non insulin dependent diabetes, more Heritable, more strongly genetic in terms of that type 1 diabetes, less heritable. A complex interaction both of your immune system and the genetics that govern your immune system, but also what you're exposed to early on and sort of the cross reaction your immune system has between self and non self. So a little bit different model. On the other hand, clearly there are, I'll call them, environmental differences. And so you can look at what's happened to the average body mass index of the average American over the last generation. Our genes haven't changed. But on the other hand, and by most measures you can see that we're more prosperous in general, the average body mass index has increased. And there have been some interesting studies looking at particular groups of Pima Native Americans for instance, that have genetically the same genes. They come from the same original community, but they live in different environments. One in which it's more sort of a traditional environment in terms of the amount of access to calorically dense foods and the amount of physical energy that's expended on a day to day basis. And those same original groups, but in two different environments, you see much more obesity in the one group that has ready access to again obesogenic foods versus the other that doesn't. So again strongly suggesting that it's not just the genes in terms of this. Now on the other hand, and this goes back to. You were describing Rudi Leibel and his original work in terms of identifying leptin and the leptin receptor through positional cloning methods. Leptin and the leptin receptor in terms of mutation, mutations in those genes do not account for the vast majority of obesity. Very rare, I've certainly had patients with these conditions, but that's just because of the nature of who I am. But very rare and most people would not have seen this. On the other hand, understanding the fundamental biology of how body weight is regulated and governed, critical in terms of understanding those two molecules. And my point in this is, I don't know if it's going to be for obesity, but it may be for other conditions like myocardial infarction or coronary artery disease, that knowing about the biology and sort of the final common mechanism or the final common pathway through which the biology is regulated, one may have ways of either pharmacologically or some will say in terms of gene therapy, being able to make permanent manipulations. So statins as an example, in terms of treatment for hypercholesterolemia, there may be various different genetic mechanisms by which one has, has an increased risk for a heart attack. Yet statins seem to work for a lot of different people. And some have thought that, for instance, rather than using that as a medication, would there be a way of genetically making a manipulation? So it's kind of a one time and not having to require continued ongoing therapy. So I'm not saying that this is exactly where obesity treatment is going to be going. And I am in a good way excited that we certainly have better treatments for the first time, I think, for obesity now than we had five or 50 years ago. So we may be going in a better direction.

We didn't really talk about epigenetics, but I think obesity might be a good time to do a little bit of backtracking and explain what the epigenome is and how it changes, not just over a person's life, but perhaps more importantly, from one generation to the next. And the reason I'm asking the question is I wonder if it's playing a role in the propagation of obesity across generations, even though, as you pointed out, we're not really experiencing much genetic drift in the period of time that we're seeing an explosion in obesity. And so, with all of that said, my question is ultimately, do you think epigenetic changes could be explaining the increase we see in obesity as a susceptibility to obese adults, genic environmental factors?

I think the bottom line is we don't know. But for those who don't know what the term epigenetics is, break it down. Epi above, and then genetics, the genes. And so there are chemical modifications that happen to the genome which are used to affect gene regulation. Some of those chemical modifications include methylation. And those are dynamic. They can change over the life course, they can change by cell type. And there are ways to be able to coordinate regulation of potentially groups of genes. They're tricky to analyze from a methodological point of view. Scientifically, they're tricky because they do vary over the life course and they vary by cell type or tissue. And so using, for instance, we've talked about this a lot, but using a blood sample as a matter of trying to get the epigenetic profile for what's going on in your brain or your pancreas doesn't always work. And it's hard to even know whether or not it works because it's not as if we're going in and doing pancreatic or brain biopsies on most. So you can do things in animal models, you can get some indirect evidence, but it's hard to know for sure whether or not this is truly answering the question you're trying to answer. So I'll say there's a lot of conjecture in the area of epigenetics, and hard to know for sure exactly what that is. On the other hand, I will say that we've known about something called the agouti mouse, which is a mouse model for obesity. And depending on how much folate you give that mouse, for instance, while the dam, the mother mouse is carrying her pregnancy, see her little mice, depending on the amount of folate in her diet, does affect the epigenetics. Folate is used in terms of methylation for the DNA. And so you can see a readout of the effect. And depending on that, you can see a change in the coat color, you can see a change in the obesity for these agouti mice and for their progeny. And there are things in terms of, as you said, transgenerational, potentially. We don't entirely know the mechanism of how that might be occurring, whether it's epigenetics or other things, but there are things that we can see, but these are complicated. So I'll just say I personally feel like scientifically we have all the evidence to make definitive conclusions at this point. But one wonders about what many different contributors could be. Although I have to guess that this is not going to be the major, major driver.

Let's pivot to autism. Now. Autism is in the news all the time, it seems, and certainly appears as though it's increasing in frequency. And it's unclear how much of that is due to an increase in diagnosis and recognition for versus how much of that is triggered by other environmental factors. But there doesn't seem to be much confusion around the fact that there's a strong genetic component to it. So let's start with that. Based on all of the twin studies, what is the heritability of autism?

I will say, to your point, autism is even within the name, a spectrum. So it's not just one condition, it's a spectrum. And it goes from severe, what some people will call profound autism and can be associated with intellectual disabilities, to other individuals at the mild, milder end, who are quite talented in many ways, yet have social challenges. So within that entire spectrum, if one includes everything within that, the heritability is estimated to be approximately 0.8, although some individuals will say even as high as 0.9. The point within that, though, is that it's not 100%. And in fact, we do know of times over the life course, in particular prenatal and early childhood that are important to the developing brain and where changes in exposure beyond the genes can play a role. So as an example, prematurity is one of the more common, if you will, exposures. But in terms of what happens to the developing brain, and if you are born when you're 26 weeks old, much higher probability of autism than if you're born at term at 40 weeks. And so there are other factors beyond just the genes that are involved. But clearly the other point that I'll make about heritability is one calculates heritability as a measure of the inherited genetic factors. But you mentioned it once already. One of the factors in autism is that there are de novo or new genetic variants that occur for the first time in the individual with autism. And those individuals aren't captured in that measure of heritability, because heritability is fundamentally trying to get at transmitted genetic variants that are going from parent to child. And those de novo genetic events are, are new in the child and so their genetic aspects not included in heritability, if that makes sense.

Yep. So what are the genes that seem to be responsible for autism?

So, depending on who you ask and how you want to define this there, I think everyone would agree there are at least 100 genes that have been identified with high confidence as being associated with autism, depending on how rigorous you want to be about this process. You know, some people would say that we estimate that there are at least 1000 genes and we probably, you know, are about a third of the way there in terms of having some sense of those genes. Not surprisingly, those genes are genes that are in the brain. They're expressed in the brain, they function in the brain, not surprisingly. And many of those genes are especially active during development. And so what I mean is intrauterine fetal development within the brain specifically, and.

What do they code for? I mean, how many of those genes would be genes in the exome versus the intron?

Most of the ones we recognize underscore the ones we recognize are in the coding sequence. But that's a limitation of what we recognize. We do realize that statistically we see that there is a signal in the non coding space, but we have less evidence to implicate specific genes or specific genetic variants individually in the non coding space because the effect size or how powerful they are is somewhat reduced compared to those coding sequences. The other issue is not just where in the genes, but what genes are involved. And so the genes that are involved fundamentally can be genes that function at the synapse. So the connections between Brain cells and communicate between brain cells. That happens to be one thing that's quite important. They can be cells that are rather genes, that are important in regulation of genes and gene networks. And many of them are transcription factors, histone modifiers. We talked even about epigenetics, some of those genes that may be responsible for those epigenetic changes, but they often, I think of them as having multiple downstream genes that they affect. So it's not having a very, you know, sort of focus. It's more a universal effect that they have. Those genes that have that more global effect oftentimes have a more global effect on brain function and cognition. So it may not be that it's autism only, but they may also be associated with intellectual disabilities, they may be associated with epilepsy, they may be associated with more sort of global effects in terms of brain function function. And to the extent that that term autism is used across the spectrum, there are oftentimes those individuals described as profound autism. So there can be different things. There can also be. I'll just put as an example we mentioned. I'll go back to pku, believe it or not. So I happen to run a very large autism study called spark. And within spark, we identified a teenage young man who actually has his autism as a responsible of undiagnosed pku. Even autism can be caused by, you know, full circle, an inborn error of metabolism where there are toxic things that build up in the brain and then cause that dysfunction of the brain. So not everything is a sort of primarily in terms of the brain, but things that can diffuse to and have an effect on the function of the brain.

But to be clear, autism is a clinical diagnosis in the same way that familial hypercholesterolemia is a phenotypic diagnosis. It's a diagnosis in the case of FH, where LDL cholesterol has to be above 190 milligrams per deciliter off treatment. And it's incredibly heterogeneous in terms of the genes that are responsible. To my last count, I think there were more than 3,500 genes that could produce that phenotype of high LDL cholesterol. So autism is the same. Right. The diagnosis is clinical, it's effective, phenotypic, defined disease, and maybe up to a thousand genes involved in that or a thousand different ways to get there or more. Right?

Exactly right. So it is a DSM diagnosis in terms of clinical behavioral criteria. I know this gets confusing for people, but one can have a gene that's identified as Causal, but the diagnosis is still a behavioral diagnosis, simply a gene associated with that. And as you said, not just one single gene, it doesn't map one to one. In fact, no one gene or genetic factor accounts for more than 1% of individuals who have that clinical diagnosis of autism. So incredibly heterogeneous.

And what's the approximate prevalence of autism today?

Round numbers, 2%. You were alluding to it before, but this number has fluctuated over time. Whether it's for all the reasons you said, but about 2% today.

Does it just seem like it's more or is this really, really a function of greater awareness?

So I think it's a function of several things. It doesn't help that the definition has changed over time. So literally the DSM diagnostic criteria have changed over time. And so for that, not surprising, the prevalence has changed over time in a good way. There is greater recognition and diagnosis as you alluded to. We've seen this in particular for underserved individuals that are more frequently diagnosed now. So I think the disparities are decreasing and I think that's a good thing. But there are also, I'll say maybe there are things that are changing in terms of society, society changing the biology, I don't know, we haven't been able to put our finger on that. But there are possible contributing factors with that. And then there's also a motivation to a certain extent in terms of the way our society works to be able to access resources. And so people that may not have been motivated to get a label per se, they may still have known it, they may have thought it to themselves, but they didn't necessarily seek a diagnosis or a label except that there were resources, educational resources, support resources that were important and we want to make sure those individuals get those resources.

What are some other both neurologic and non neurologic sequelae of autism or call it comorbid conditions with autism.

So I think that's a good way to phrase it. Comorbid conditions is one of the things that I think about. So as an example, some individuals will have epilepsy associated with their autism. For some individuals that epilepsy will be recognized very early. For some individuals it won't come out until the teenagers or adolescents. But that can be incredibly important. Within this there are behavioral co occurring diagnoses, for instance of anxiety is quite frequent. ADHD or attention issues, again quite frequent. And I think some things we're just beginning to understand, although I think it's incredibly important, is that most of what we know about autism is based on individuals below the age of 20. Those are the individuals who've been studied most. And I think there's a whole lot we don't know about adults with autism. And I can say I do know some, some conditions that are associated as degenerative conditions as well, that when people are adults, there may be particular subtypes of autism that are neurodegenerative because the genes that are involved are responsible for neuromatenance being able to sustain the brain and continue functioning. And when they're not functioning at some point, start having things associated like Parkinsonism, Some subtypes that may be associated with increased risk of. We mentioned obesity. Believe it or not, Some of these same genes may also predispose to obesity. And especially, especially with some of the medications we use to treat some of these behavioral conditions, even increase the effects, the metabolic effects and weight gain and diabetes associated with that. And there may be other things as well, but to a large extent I would say it's under recognized and we have a lot of more gaps in our knowledge, but many people who continue to need that understanding. And I think earlier you used a term of precision medicine. I don't mean it to sound like a cliche, but you can imagine that it's a large part percentage, 2% of the population. Great heterogeneity. Everyone doesn't need to have the same sort of rules, that they're following the same rulebook or the same management guidelines. And how do we get greater specificity to not overburden people, but yet to be able to also allow them to achieve their full potential and lead their healthiest lives?

You mentioned that most of what we know about autism is based on studying people who are up to, but below typically 20 years old. Old. Does that suggest that prior to about the year 2000 there was nobody really studying this? Because presumably if we were, we would know about what people look like later in life today.

So many of the adults with autism, number one, were not diagnosed as having autism. They may have had, you know, some of these challenges, but things have just changed over time. And so having a label, having a diagnosis, has changed with society. Other individuals who were studied 20 years ago have not been followed longitudinally. And that's hard. Although there have been some epidemiological studies like Framingham that have followed individuals over long periods of time. It's hard to be able to do that. People move, people, you know, investigators lose funding, people die. I mean, you know, lots of things that happen. And so just knowing what someone looked like at 2 and that same person at 22. There are very few studies in terms of in children what that looks like. And so I think that's been a large part of the problem as well.

I mean, I'm shocked to hear that the heritability is as high as it is 0.8 to 0.0point. What is it for other DSM conditions such as bipolar disorder and schizophrenia?

So bipolar and disorder and schizophrenia certainly much lower, especially in even things like depression, major depression, lower still. So this is actually one of the highest heritable factors in terms of behavioral health or psychiatric conditions.

And just approximately what are the heritability factors for those other conditions you just mentioned?

So more in the neighborhood of 0.5 to 0.6 or for something like major depression, even lower, maybe more like 0.3.

Wow. What is the implication, by the way, if the heritability is 0.8 to 0.9, that almost implies for certain that a person with autism will have an autistic child, doesn't it?

Well, that's only half the equation, right? So it takes two to tango in terms of making a child. So both individuals are contributing genetic factors as we're thinking about this. And so, and it's the combination of those factors together within that combination. So if you're talking about, even if.

We'Re not talking about polygenic combinations. So in other words, of those, I think you said hundred to a thousand genes that seem to be implicated in autism, some individuals with autism may only have one of those genes, correct?

Oh, absolutely. So some of them may have only one gene that's the predominant sort of contributor in terms of this. Some will be more of that polygenic combination of factors.

But a single gene individual has a 50% chance of passing that gene gene onto their offspring. And assuming it's fully penetrant, they would have effectively a 40 to 50% chance of transmitting autism to their offspring.

That's correct. Now, for the types of genes that you mentioned, many of those individuals actually won't go on to have their own families. And so one of the factors within this is that those highly penetrant single gene factors, many individuals, for instance, you can imagine, if they're not living independently, if they're not verbal, you know, they want to pass those genes down.

Let's pivot for a moment to cardiovascular disease. There are a couple of things that stand out from a genetic perspective. One I've already mentioned briefly, which is fh. The other is LP attached to the LPA gene. I believe that LP is the most Prevalent atherogenic condition that is genetically associated. Roughly 1 in 10 people haven't elevated that. That would be another great example of how gene elevated addition therapy would be of no use because you'd want to be gene editing that. What else do we know about cardiovascular disease beyond those two special cases of elevated LP and familial hypercholesterolemia? How much of the rest of ASCVD appears to be heritable?

Well, the interesting thing is we alluded to this a little bit. When we think about myocardial infarctions, hyperlipidemia, in that sort of sort of cardiovascular health, there may be genetic factors that are numerous, but from a therapeutic point of view, we may not target all of those genetic contributors. There may be final common biology. And so I think that's a theme that I see most in terms of thinking about coronary artery disease, myocardial infarction, things like that. Within the cardiovascular disease space, though, I do think they're interesting. I'll just give one other example in terms of a relatively common but rare disease, that of cardiomyopathies. And so when you think about genetic cardiomyopathies, they affect on average about 1 in 500 individuals. And so that's not one in a million. It's also not 10% of the population. Right. We're somewhere in the middle. And I will say that I was waiting to see the data come out, but we've known about many of those genes for a long time. We've known about the mutations, we've known about frequency, we've known about natural history and waiting to see whether or not genetic therapies would be effective for those conditions. And it's not yet in people, but I will say the early data are looking promising in terms of animal models to be able to reverse this or prevent this. I still think the heart is a tricky organ to be futzing with. I'll just put it that way. It always makes me a little bit nervous because, you know, electrical things can happen very suddenly and can be quite dangerous. So, you know, that always makes me a little bit nervous to think about genetic therapies for the heart. But like I said, some of the early data from the sidemens in particular look like there could be promising roads ahead. And like I said, it's a common condition that otherwise oftentimes we treat with transplant, you know, when the heart finally fails. And so it'd be lovely if didn't have to wait for hearts for transplant.

Yeah, it's interesting. So, going back to what you said about the ASCVD side, it almost had sounds to me like you're saying that if genetic therapies and treatments are going to be deployed against conditions especially like fh, you would really do it to more mimic the drug than you would to try to correct the defect. And that makes a lot of sense in the case of FH because of the heterogeneity. Right. You know, to have 5,000 different gene therapies for the 5,000 different genes that can be altered in the result of hyperlipidemia is a bad idea. Whereas if you can Simply knock out PCSK9 as a gene, you basically take care of everyone. And so let's talk about what that means technically. So presumably there are genetic therapies that are already in the works at looking at targeting PCSK9. PCSK9 inhibitors as a class of drug have been perhaps the most exciting drug class in introduced in the last decade. And the results have lived up to the hype. I mean, when Helen Hobbs first made the discovery of the individuals that were both hyper and hypo functioning PCSK9, I still remember reading those papers 15 years ago thinking, this is too good to be true. This will not pan out. That was my dumb prediction. This will not pan out. And I was wrong. I'm delighted to be wrong. So what does that look like now? What does the gene therapy look like to silence a gene in this case, but without creating some unintended consequence?

It's going to start out with not just the average person who might have a higher risk. It's gonna start out at the extreme for someone we talked about, Jesse Gelsinger, who's gonna be willing to be the first in and try this and be that brave first person. And so I won't claim that I've designed the clinical trial that goes with this, but just to say it's gonna start at that extreme and, and there are gonna be a lot of complexities. I will say, and I'm sure many listeners are thinking of this, the cost with gene therapies is prohibitive right now. It's not as if we could, if any single gene therapy were $3 million, which is not uncommon for current gene therapies, we can't afford to spend $3 million per person. With the number of people who are at risk in the US population, that.

SMA single gene therapy is about a $3 million treatment.

I'll say the range of genetic therapies right now runs between, between about 1 and $3 million. So depending on which ones are out there and it gets complicated.

Sorry. Just to say one thing about that, it is worth keeping that in perspective, right? I'm not gonna sort of advocate one way or the other, but it's not uncommon to spend a million dollars on chemotherapy at the end of life for a year's worth of life extension. And if you contrast that with a million dollar gene therapy, therapy in infancy, that gives 80 or 90 years of life extension, it at least puts those two treatments in context.

I agree with you 100%. Health economists have been trying to get at that in terms of the value, you know, if we're talking about true value in terms of this, and I'm not gonna pit one against the other in terms of this, but you do have to think about, and I would argue not just the healthcare system cost to the person, but it's the societal cost to the family, to the community. There's a lot of cost goes into this if you do the economic analysis accurately. On the other hand, to say that that might be worthwhile in one case, you do have to think about scaling and I'll just throw out a number for you. 10% of the US population has a rare genetic condition. They may or may not know it, but that's just true in terms of these monogenic factors that we've been talking about. So that's 10% of the population. If you now think about the percentage of the population that's obese or that has obesity or type 2 diabetes, or some of these other common conditions that someday might be treated by these one and done types of things, then it becomes in terms of a society, what can we afford to do? What are the competing other healthcare costs or other societal costs in general that we have and how are we going to right size these? I will say that I'm confident that as we have more ability to understand how to do this, there's a lot of fixed costs, but the marginal cost is not nearly as high. I think you know what I mean by that in terms of, you know, both what it takes to design the clinical trials, to do the manufacturing, to do the monitoring, you know, all of these things, they won't scale linearly. And so I do think we'll have some cost realization that we can recoup. But you know, I think those are the big questions that we think about is how are we going to afford this and what are the key things that we need to do to enable doing this on scale. To your point, what are the competing alternatives? If it is, you know, a medication that you're taking every day if you can't really get, you know, to a good point in terms of the MI risk or anything, in terms of heart health or stroke health or other things. So all of those will go into it and eventually a health economist will price this out and figure out what a reasonable fee is to charge for such therapies.

Again, just going back to what it costs today on the gene therapy side, it still seems like I don't say this to be disparaging of the field at all, because the field is remarkable, but I just say it as more of an observation of where we are relative to, say, gene sequencing. We're still in its infancy, aren't we?

Oh, absolutely. I mean, as sad as it is to say, given what you said about Jesse Gelsinger's case was more than 20 years ago, we are still at our infancy in terms of being able to realize all the potential. I don't even think we have all the technologies or the vehicles or delivery systems that we're going to eventually be.

Effective again, thinking it through it that way. In the year 2000, it cost $1 billion to sequence a human genome. Today it costs $1,000. So that's a six log reduction in cost, in part through Moore's law, in part through the step function change of high throughput sequencing. We don't need a six log reduction in the cost of gene therapy to make it readily available. Quite frankly, a two log reduction would make this a game changer. Does that strike you as something that's feasible in the next two decades?

I would say yes. There are going to be certain catalytic transformative breakthroughs that will make and enable those changes that you're talking about. So again, I'll go back to what we did with the COVID vaccines. It was incumbent upon everyone to be able to come up with solutions. And the solutions that allowed for the adaptability and even change the vaccine on the fly were remarkable to me, at least from a scientific point of view. And I know some people may push back on me, but that is my true belief. If you could think about the same way with delivering an MRNA vaccine and doing the same thing and realize that it's different for genetic gene addition and doing it, but it's not entirely different in terms of how to do this. And so as you're talking about, I call it rinse and repeat. But it's being able to do this and having the infrastructure, the delivery system, the regulatory system, the manufacturing process, all those things. Once you get this and get this down. There are ways to scale this and to be able to, if the gene fits, if it's a certain size, if there's certain mutations, to be able to do this repeatedly. So I do have that hope. But there are going to be the function I think we're going to see. I call it a step function. Right. So you're going to see it's not going to be linear, it's not going to be right. So that's what we'll see.

So last year I read Walter Isaacson's biography of Jennifer Dadna and the story of the discovery of crispr. I thought it was a fantastic book. I can't recommend it highly enough to people who are listening or watching. I'm sure you've read it. There was a fantastic discussion of the ethics of this. And once you realize the power of gene editing, you very quickly start to pivot away from the discussion we're having today, which is a child is born with Tay Sachs disease. This child is going to be dead in a couple of years and it's a very ugly death. There's really nobody in their right mind that wouldn't be in favor of a therapy there. We could go through all the examples we've talked about and there's nobody I can imagine that's going to say if a woman is born with a BRCA mutation and she has the choice between a gene edit to fix it or a mastectomy to remove her breast, we'd probably prefer the former, if for no other reason than it ends the gene there and her daughter won't get it or her son won't get it, et cetera. How can people think, think about the next layer of complexity, which is, well, should we be able to take a person who has an APOE4 isoform and turn that into an APOE3 isoform or an APOE2 isoform, which would actually come with significant protection against neurodegenerative disease. That's a slightly different case because of course the penetrance and the risk profile is, is different. So how do you as a scientist think about this? Because I think that both ethicists and scientists need to be a part of this discussion.

So I agree completely and I have to admit. So one thing I think we universally agree on, I hope, is that we're not doing gene editing, gene manipulation to affect the next generation. So we're not looking for things that are transmissible in the germline. We're not trying to create superhuman where we're trying to fiddle with the genes to either correct them or to be able to enable, enhance them is the term that I'll use. That's transmissible. I think that's a line scientists and ethicists.

Sorry, would that be true even with something like Tay Sachs or cystic fibrosis or things like that?

That's what the consensus among the scientific community is, is that again that you would treat the soma or the body of the person that might be at risk or have those diseases, but you wouldn't try and do manipulations that would be transmissible to the next generation.

I see. So my argument for BRCA is only partially correct. I argued that the gene therapy would be favorable because it would spare the woman a mastectomy and spare the risk of transmission. You're saying no, you would only do it in the somatic cells, not the germline. She could still transmit that gene to her daughter.

That's correct. That's the current consensus scientifically. The other part of it is this tricky thing that you're talking about, which is enhancement in terms of it's not correcting something that's problematic, it's enhancing the body the way it is or trying to in some sense prevent a disease process. But I will say the enhancement, once you get to the point of enhancement, that's a trigger word for we shouldn't go there. And part of this is that we're not as smart as we think we are. You know, we can think that something's not going to have off target effects, that it's not going to disrupt a gene inadvertently. But I think in the short term what saves us is that the risk profile given the uncertainty in the long term is so high that there aren't going to be either scientific scientists or people, I think, who are going to, I hope, go for things that are trivial in terms of enhancements. I'd say that's the first part of this. But to your point, in the Apoe234 situation, I think is one that people think about. I also think that although probably the average listener here is more sophisticated about this, I think the average person walking down Broadway here is not going to think about this in quite the same way. And so they're going to think about things that will be an enhancement, whether it's being able to increase your earning potential, being able to be taller, more athletic, funnier. There are multiple dimensions in which people would, and people have been surveyed to figure out how they would value certain attributes, would definitely be thinking about doing that. I think at this point, it has to be just enhancement is a line that people are, I hope not crossing, that it really is about disease and being able to make people healthier as we're doing this. But to the extent that there are certain medical industries that are not covered by insurance, that people that are not regulated, there are certain parts of the world that do things differently, where people can go and seek certain things. I do hope that there is a consensus scientifically about places we don't go, because otherwise there will be ways that people will find to do things.

I mean, is it worth just explaining the story of kind of the initial blow up around CRISPR and what took place in China and how that brought the scientific community into, in some ways closer around this consensus?

So the circumstance in China was something I have to admit was I thought was a little unusual. So it was a circumstance in which the CCR5 gene was manipulated to try and prevent children from getting infected with hiv. By manipulating that gene. It's not as if that was curing a disease to your point, it's not as if it was preventing a disease. That was a foregone conclusion. It was preventing transmission of infectious agent that those children were at increased risk for. But it was not a foregone conclusion that they would have been HIV or HIV positive.

And so wasn't it also the case that there was very little chance they were going to be because these were children born of IVF and the sperm are washed in that situation and therefore, because in this case, I believe the father was HIV positive, the mother HIV negative, but it was a situation where it was almost entirely possible to prevent the transmission of HIV to the offspring. Is that correct?

Right. That was my point in terms of I don't think heroic measures needed to be made to be able to go. There were perfectly, I think, reasonable ways that are very effective. Not just reasonable, but very effective. So it was an odd sort of selection of a use case, I guess is the point that I'm making scientifically. If I were going to do something, I would have done it for this use case. But regardless of that, the scientific community also just, I think rallied around that a line had been crossed, right. That this was essentially a form of enhancement. It wasn't something that was saving a life, saving a high probability of something for which there were no other treatment, anything else. But I think, you know, the other point that I made is true, which is that this is the world is global and you know, scientists are in all sorts of places and it only takes one person to Be able to do something, something that's crossing a line. And there are people that there is tourism, medical tourism in places, and people I've seen go to, you know, where they feel that there's something that they think is important that they'll seek. And so I think it is important for hopefully, people to uphold certain ethical standards and for us to, you know, have those guiding principles so that people know where those lines are.

Do you think it would have been different if the first use of CRISPR in humans was to do something that we could all agree on would be a great use case. In other words, would the field be in a different place today? So what year was this, that, that. And I'm blanking on the name of the scientist who did this, but I know he's been basically, if not put in jail, certainly put out of science.

I can't recall the year either, but I'm trying to think of what would have been that perfect use case. What were you thinking?

Sickle cell? Let's say you took a Kidder, or Tay Sachs for that matter. You took a kid who had a disease that was going to significant, significantly impair the quality of their life. You used gene editing to fix the gene and produce a phenotype that could have a normal life expectancy. So, again, same technology, but far better application.

I think what most people in the field, and this is usually possible, is that rather than trying to diddle the genes, if you're at the stage of an embryo with in vitro fertilization, you can simply do selection of an embryo that doesn't have that genetic risk, and therefore you're not increasing the risk of something off target, and you're still accomplishing what it is that you were set out to achieve. I have seen some ethicists make the argument that if there were a very limited number of embryos and that were not possible to do, would that be, you know, a circumstance in which, like you said, for the purposes of direct therapy for a very bad disease, in which that couple had no other alternative in terms of having a biological child, would that that be possible, knowing that that would affect the germline so, as opposed to what we were talking about before, would be something. And that is what I would say gets us close to the edge in terms of thinking about that sort of the use case that you were talking about, but not as a matter of routine and not a routine goal in terms of the intention to do in a universal way.

It's incredibly fascinating. If you had a crystal ball, you know, and you could look into the future in 2040, probably you're coming to the end of your career, you're thinking about retiring, but you're looking back at a 40 plus year career in a space that has probably seen more transformation than most fields in all of medicine. What would you not be surprised to see happening in 2040 in this field?

I would not be surprised that diagnosis is trivial. I do hope we're getting to that point. I think there are. Not just with the cost of sequencing decreasing, but with machine learning, artificial intelligence, the ability to ingest huge amounts of information, genomic information, clinical information, other information, the diagnostic ability in medicine in general, and I won't say this is limited just to genetics and genomics, but is especially true in this field, diagnostics will be hopefully true, trivialize. And I hope, although I can't guarantee it's going to happen, I hope from an equity point of view we'll be more accessible to more people around the world just because that cost barrier will decrease. What I'm not sure of is on the therapeutic point of view to what we've been talking about, how much of that we will have realized within 20 years. While I'm optimistic we will have gotten a lot of that done, I'm not sure how much it will penetrate either parts of society in the United States or globally in, in terms of what we'll be able to do. And this is just, I think it's very hard for me to predict timing and I think Bill Gates has a quote similar to this. I do think within some point in the next hundred years we'll get to this point. Whether it's the next 20 years or not, and exactly what percentage of individuals we will have been able to serve, I'm not sure because there are gonna be, as I alluded to, these kind of step functions, these transformative things that it's just very hard for me to predict given that I feel like we got stuck for the last 20 years, but I do feel like we're gaining momentum. But it doesn't take much in society and in science to get us stuck. So I think that's just a word of caution. I would not have predicted. I hate to make things about COVID but I would not have predicted in society what's happened in the last 10 years or some of the trajectories we've had. So I will not use my crystal ball and I'll say we'll be much farther ahead, but I don't know. Big confidence interval on where we're going to be in 20 years.

Well, Wendy, congratulations on your new role at Boston Children's Hospital Hospital. Obviously for folks not aware, that's certainly probably one of the three most preeminent children's hospitals in North America, and maybe you would argue the single most. But anyway, that sounds like a wonderful opportunity. I assume you'll be able to stay involved in Spark and Guardian as a PI, as those tend to expand. So I especially want to thank you for making time on the day that you're literally moving to Boston to make time to sit down for so long. So congratulations and thank you again very much for your input.

Thanks. It's been a lot of fun.

Thank you for listening to this week's episode of the Drive. It's extremely important to me to provide all of this content without relying on paid ads to do this. Our work is made entirely possible by our members and in return we offer exclusive member only content and benefits above and beyond what is available for free. So if you want to take your knowledge of this space to the next level, it's our goal to ensure members get back much more than the price of the subscription. Premium membership includes several benefits. First, comprehensive podcast show notes that detail every topic, paper, person and thing that we discuss in each episode and the word on the street is Nobody's show notes Rival hours. Second, monthly Ask Me Anything or AMA episodes. These episodes are comprised of detailed responses to subscriber questions, tips typically focused on a single topic, and are designed to offer a great deal of clarity and detail on topics of special interest to our members. You'll also get access to the show notes for these episodes, of course. Third, delivery of our premium newsletter, which is put together by our dedicated team of research analysts. This newsletter covers a wide range of topics related to longevity and provides much more detail than our free weekly newsletter. Fourth, access to our private podcast feed that provides you with to access access to every episode including AMAs sans the spiel you're listening to now and in your regular podcast feed. Fifth the Qualys, an additional member only podcast we put together that serves as a highlight reel featuring the best excerpts from previous episodes of the Drive. This is a great way to catch up on previous episodes without having to go back and listen to each one of them. And finally, other benefits that are added along the way. If you want to learn more and access these these member only benefits, you can head over to Peterattiamd.com subscribe. You can also find me on YouTube, Instagram and Twitter, all with the handle Peterattiamd you can also leave us review on Apple Podcasts or whatever podcast player you use. This podcast is for general informational purposes only and does not constitute the practice of medicine, nursing, or other professional healthcare services, including the gift giving of medical advice. No doctor patient relationship is formed. The use of this information and the materials linked to this podcast is at the user's own risk. The content on this podcast is not intended to be a substitute for professional medical advice, diagnosis, or treatment. Users should not disregard or delay in obtaining medical advice from any medical condition they have, and they should seek the assistance of their healthcare professionals for any such conditions. Finally, I take all conflicts of interest very seriously. For all of my disclosures and the companies I invest in or Advise, please visit PeterAttiaMD.com about where I keep an up to date and active list of all disclosures.

It.