Parkinson's disease genetics: What's new | Congress 2026

[00:00:42] Divyani Garg: All right, Dr. Mata. So if you were to look at the last couple of years, what do you think has genuinely changed our understanding of the genetic architecture of Parkinson's disease?

[00:00:51] Ignacio Mata: Yeah. I feel like it's a very good time to be doing genetics, in the last maybe 20 years or so. But I would say in the last 2 to 5 years, I think, the difference has been the dramatic increase of people getting genetic testing either clinically or for research. And that increase in the number of individuals for which we have genetic data has allowed us to identify many different things.

Also, I think it's very important that this is a representation of the global community. We've moved from most genetic studies being mostly European to studies including other populations, which has allowed us to identify or see what differences and what similarities there are between the genetic component between these populations.

And I think, a very big example of this is the African GBA1 variant that was identified a couple of years ago, where a gene that we already knew it was important for Parkinson's disease, we identified a new mechanism of action. It's now pathogenic variants but also other variants that are perhaps more common in a population like Africa can modify RNA expression and therefore protein expression and also increase your risk to develop Parkinson's disease.

So I think it's been, again, very exciting because now we have a lot of data to answer many questions that I think we have.

[00:02:07] Divyani Garg: So one of the biggest developments has been actually the enormous expansion of the multi-ancestry datasets. How much has studying non-European populations actually changed what we know about Parkinson's genetics other than frequencies of known variants? So if you could just delve into that a little bit.

[00:02:23] Ignacio Mata: I think there's many advantages of studying different ancestries for genetics. One, as you said, you can find new things, either new genes, sometimes new variants in known genes, that might explain different ways of how the gene might be affecting Parkinson's disease. Obviously, the increasing number of samples in the GWAS, in the genome-wide association studies, have allowed us to identify more susceptibility genes as well.

Some of them are common amongst all populations. Some of them are population specific, like GBA1, LRRK2 in certain Asian ancestries, for example. But then the other cool thing that we've been able to do, taking advantage of the differences in linkage disequilibrium, so the haplotypes that are different between populations, is that in the known genes we've been able to, usually in a genome-wide association study, you get a big peak with many variants, sometimes hundreds of variants.

You don't really know which one is the important one. And by adding those multi-ancestry cohorts, what we've been able to do is actually, we call it fine mapping, which means that from all those variants, which one might be actually the important one, which is the one that you want to move to functional studies, for example.

So, for between 6 to 10 different genes, we've been able to actually identify a single variant that we think might be the causal variant for that specific peak or for the specific gene that might be the important one.

[00:03:40] Divyani Garg: So how do we actually decide that a newly discovered genetic association is actually a new PD gene? How do we interpret these newly emerging candidate genes?

If you can just get into how that actually happens.

[00:03:52] Ignacio Mata: There's two different ones in there. So one will be the familial ones, right? So, one of the advantages of having these really large cohorts, and I would say that, it's really good to increase the numbers, but it's been even more important what the Global Parkinson's Genetic Program, GP2, is doing, which is actually merging all that into one single dataset.

For example, now somebody in North Africa identifies something that looks like a new gene in a family from Morocco, for example. And then they can go into GP2, which has over 100,000 individuals that have been either genotype or also whole-genome sequenced, and see if there's any of the families in the world that might have the pathogenic variants in the same genes.

And then you can actually put those together and try to understand if that is an actual Parkinson's gene or not. Before, that would take years and years. Now, we have actually a browser where people can go and put their variant of interest, and it will tell you how many people in GP2 actually carry a variant, either in their gene or the same variant.

That's the familial side. On the common side, again, the numbers are allowing us to see what is actually real and what is noise and also identify the things that are different, because sometimes a variant might look very good if, for example, the GBA1 variant look very good, but it's only present in Africans.

So then when you look in other populations, you don't really see the variant. So again, it allows you to identify things that are specific to a certain population. And the increased number of samples, we can see, for example, the African component, we can also look at in African Americans in the US.

We have Africans in other parts of the world that also carry the variant that also increase the risk for Parkinson's disease. I think we have a lot more room for testing these new findings and see what's real and what's not.

[00:05:34] Divyani Garg: Do you think genetics is enough to explain the occurrence of Parkinson's disease? Because I know there's a lot of conversation around the exposome and gene-environment interactions.

So what are your thoughts on that and how does that interplay?

[00:05:46] Ignacio Mata: I think with the studies like PD Generation, where people are actually getting CLIA-certified genetic testing, we know that around maybe 10% to 15% of individuals with Parkinson's disease carry a variant that we would say pathogenic that is mostly causal for Parkinson's disease.

The rest of the individuals are, which again is the majority of them, is really an interaction between genetic susceptibility that you were born with and then all the environmental factors. Aging is also a big component. So all those things really interplaying it's really, for most people, what would influence their risk for Parkinson's disease.

So I think this is the newest stages, right? So once we have all these genes identified, the next thing is to look how they actually interact with the environment. The problem with environment is that there's not that many datasets that have the data that we need. So that's another emphasis within GP2, where we're trying to get more and more cohorts to use a standardized way to collect environmental data that then we can use together with the genetics to start to explain some of that interaction.

But that's gonna be a little bit harder to do because a lot of times it's just questionnaires, so it's recall bias. That's why I got into genetics, it's a lot easier to do than the environment itself. But there's a lot of efforts with the exposome, and I think it's probably the next phase.

Yeah

[00:07:03] Divyani Garg: Yeah. agree. I agree. But I do understand what you mentioned regarding the challenges of collecting data, because, if you look at pollution or you look at anything else, do we have enough data to extrapolate that towards analysis?

Yeah. The other question I wanted to ask you was that so we talk about genetics of susceptibility, but what about genetics of progression of disease? So yeah. The most interesting shift is that genetics is no longer asking who gets Parkinson's disease, but like you mentioned, what happens after someone develops it.

How much progress have we made in identifying genetic determinants of progression?

[00:07:36] Ignacio Mata: Yeah. So that's another barrier is that a lot of the studies that we have are cross-sectional. It's very hard to get funding for somebody to follow people for 10, 20 years, which is really what you would want to do. We do have ways to figure out what the progression might look like.

You can look at disease duration, and Hoehn and Yahr, you can classify people in maybe as slow progressers, fast progressers, but ideally, you really want that longitudinal data, that longitudinal follow-up. And there's two ways that we can look at this. I think there's been a lot of effort following your GBA1 carriers, your LRRK2 carriers, and we already have a good idea that GBA1 progresses much faster, both cognitively as well as motor-wise, compared to LRRK2 or parkin.

And because we have more people being genetic tested, we have more carriers, and then we can actually see this in real time. We have a lot more data to play with. It's a little bit harder to find those susceptibility genes, which might not be the same ones that are the risk genes, right? The progression genes could be completely different.

And in fact, we have suggestions that might be different just for preliminary studies that we have done. So identifying those susceptibility genes for progression is hard if you don't have that longitudinal data and you can't do those comparisons. But that, that's another effort.

So GP2 has a few different things that they're working on. Progression is definitely one. The environment is another one. But I think progression will be very interesting, and especially from a clinical trial perspective, like maybe identifying people that are faster progressers that you can put on some of these clinical trials will be very important.

And I think also the biomarkers that are being developed might also help with progression. So together, genetics with enviro-biomarkers might give us a good clue of how people are going to progress.

[00:09:16] Divyani Garg: Just going into that a little bit. So, one of the exciting developments in Parkinson's research is actually the emergence of biomarkers and alpha-synuclein seed amplification assays. So do you see genetics and molecular biomarkers converging to define biologically distinct subtypes of PD?

[00:09:32] Ignacio Mata: I think so. There's still a lot of variability, like depending on the biomarker, what fluid you use, and even the laboratory where it's being run. Right now it's not super standard, so it's hard to compare. But I think there are suggestions that some of the LRRK2s maybe are SAA-negative.

But a lot of the other genes, most people are SAA-positive. So I think we're starting to answer some of those questions. Again, that's another thing where it's quite novel, so we need to generate the data and then put that data together with the genetics and clinical data and all those things to really try to understand.

So again, I really want to give kudos to GP2 on putting all these things together, harmonizing, generating these data because the resource that is being generated, which by the way, anybody can access 'cause that's publicly available, will allow us to understand this and to answer those questions very rapidly because of the numbers of people that we have.

[00:10:24] Divyani Garg: Talking about GBA1 and LRRK2, these have arguably moved from being genetic discoveries to actually therapeutic targets. So has this changed the way you think about genetic testing in Parkinson's?

[00:10:35] Ignacio Mata: Yeah. Absolutely. In fact, when I started doing genetics of Parkinson's disease, we would always tell the patients that they needed to participate in genetic research because it would not have any impact on their care but probably in their kids' care or in their grandkids' care.

And I think the language has changed because now if you do genetic testing and you find out that you have LRRK2 or GBA1, now, depending on the study and if you meet all the other requirements, now you can actually be a candidate for this clinical trial.

So I think more patients want to know if they're carriers or not. And the perfect example is PD Generation. When it started a few years ago, they said, "we'll be lucky if we get, like, 15,000 people in the US to do this." And they met their goal a year and a half before the deadline, and now we're over 35,000 people all around the US, Canada, Latin America, and Israel that have been tested.

And I think there's more and more appetite for that. It's definitely something that we need to think about how we integrate that into our clinical work. Yeah.

[00:11:35] Divyani Garg: Yeah, just taking off from that. So for years altogether, PD genetics has been dominated by the GWAS studies. But considering our understanding of some of these variants that have therapeutic connotations, are we now entering a phase where rare coding variants or whole-exome, whole-genome sequencing is going to become equally important?

[00:11:53] Ignacio Mata: I think it is already important. With price going down as much as it has been, it doesn't make any sense anymore to just look at a few genes. It's better just to have the whole genome. And we're now seeing genes that are associated to perhaps other parkinsonisms that are also present in Parkinson's disease.

So really understand the spectrum of the disease itself can only be done if you do a whole-genome sequence and then you get all those data available for all the patients. We also know if you do a whole-genome sequence or even a really wide array that, for example, Neuron23 has a LRRK2 clinical trial where it's not only if you carry a LRRK2 pathogenic variant, but there's also other variants within the gene that might affect the pathway.

We're not really looking at a gene level, but we're looking at a pathway level. And those individuals could also benefit from LRRK2 clinical trials. So having this wide information on each individual will allow us to find the perfect patient for the perfect therapy. Precision medicine is what is really going to take us to the next level of treating, hopefully slowing down or stopping, Parkinson's disease.

[00:12:57] Divyani Garg: Now I just wanted to ask you about the polygenic risk scores. Are they ready to enter clinical practice? And how much of the problem is there that a lot of these scores are actually developed in European populations?

[00:13:09] Ignacio Mata: Yeah. Yeah. So as polygenic risk scores use genome-wide association study results to calculate a number, which the number doesn't mean much, but then it allows us to classify people into, low genetic risk versus high genetic risk, for example, depending on how many variants you have.

Until maybe 5 years ago, yeah, most of the GWAS results that we had in hand were 100% European. So the first job that we had in the past 5 years was to see how that translated into other populations now that we actually have information for other populations.

We did a study in Latinos where we saw that surprisingly it actually worked quite well. Latinos have part European, so it makes a little bit of sense. But we know, for example, in African populations, the polygenic risk score doesn't work very well. But as we're generating GWAS for these populations, we'll be able to integrate this.

And in fact my lab is working on a polygenic risk score that will use local ancestry. So if an individual is ethnic, so if it has ancestry from African, European, it can actually tell where the part of the genome came from, and then use the polygenic risk score from the GWAS from that population.

And I think that's what it makes it really accurate. But from moving it from the research side to the bedside, to the clinical side, is going to be a little bit trickier. I think the low-hanging fruit of the use of polygenic risk score is going to be something like what Neuron23 is doing, where again, you look at certain pathways, see how many variants you carry in the pathway, and then you can see if those individuals that carry those polygenic risk scores are also good candidates for possible clinical therapies.

Once we integrate polygenic risk scores with progression data, for example, we might also use that as well in the clinic to get an idea of what our patient might look like in 5 years or in 10 years, what kind of things we can look for. But I think we're a little bit far from that.

We still need to generate a lot of data. And I think polygenic risk scores on their own, without the environment, 'cause if you have a pathogenic variant, the genetic effect is very big. But polygenic risk scores, even if you add all the variants, still account for a little bit of the effect.

And you need also the environment and you need other factors. So I think what we're going to need is we're going to need a polygenic risk score, an exposome score, and then add those two together, and then maybe that will give us a better idea about the clinical presentation, the progression, and therapeutic targets for that specific individual.

Yeah.

[00:15:31] Divyani Garg: So, given everything we've learned recently, should genetic testing now routinely be offered to patients in clinical practice? Because this is the question that clinicians would be asking.

[00:15:39] Ignacio Mata: I'm biased, right? So I'm a ge- geneticist. I've been saying to people that I think it's worth doing. Right now it can really guide certain clinical aspects. For example, if you have a GBA1 carrier in front of you when you're talking about DBS, you might have that into consideration and see what the cognitive status of the person is and maybe the risks for this.

So I think in the last 5 years we've moved to say "If you have a family history, if you have early onset, or if you have a certain ancestry, you should probably do it," to "I think everybody should do it," because we see LRRK2 patients that don't have any family history, just isolating by that, or we see variants in GBA in late-onset Parkinson's, not only in early-onset Parkinson's.

So I think having that information for everybody will help, not only from the clinical side, but also to be able to do research and really understand progression and some of the other things.

[00:16:31] Divyani Garg: Where do you predict the next big breakthrough is going to come in the field of genetics in Parkinson's?

[00:16:37] Ignacio Mata: That's a very good question. My hope is that we really put all these things together into really understanding the key, I don't know, two or three pathways. And we can develop targets that are not gene-specific, but they're actually pathway-specific. Basically widening the range of individuals that we can include.

Because obviously one of the problems with clinical trials is having enough number of people to participate in them and also having people that are close to where the clinical trial is being done. So I think if we can identify ways to find other patients that might benefit from the same clinical trial, we'll increase the pool of people that we have access to.

And then maybe we'll be more successful in finding this. I think we also need to understand time. So we were talking about progression, how early or late can we actually use some of these new therapies? I think that's another thing that we want to do within GP2. A third thing that we're also focusing on is prodromal, to try to understand what happens before the motor symptoms start.

And I think that will also give us an idea of who converts, what things might be important in people that are transitioning from having a variant or having a polygenic risk score or having some symptoms that might predict that you might develop Parkinson's disease.

And understanding that, together with biomarkers, and then trying to treat people earlier, which I think eventually that's what is going to give us the better handle of being able to slow the progression, is if we can address this when there's still a lot of the dopaminergic neurons still alive and functional.

So, I'm hoping that, again, putting all these data together in the same place and having many people analyzing this and answering some of these questions might put us in a really good spot to have finally an FDA-approved medication that slows the progression of PD.

[00:18:19] Divyani Garg: Thank you so much for joining me today, Dr. Mata. It was great having you.

[00:18:22] Ignacio Mata: Thank you so much.