Hello, and welcome to Wave's 2026 Research Day. We ask that you please hold all questions until the completion of the formal remarks, at which time you will be given instructions for the question and answer session. Also, as a reminder, this conference is being recorded today. I will now turn the call over to Kate Rausch, Vice President of Corporate Affairs and Investor Relations.
Good morning, everyone, and welcome to Wave's 2026 Research Day. The slides accompanying today's presentation will be available following the event in the investor section of our website at www.wavelifesciences.com. Before we begin, I would like to remind you that management may make forward-looking statements during today's presentation. These statements are subject to risks and uncertainties that could cause our actual results to differ materially from those described in these forward-looking statements. The factors that could cause actual results to differ are discussed in our SEC filings, including our most recent annual report on Form 10-K and our most recent quarterly report on Form 10-Q. We undertake no obligation to update or revise any forward-looking statement for any reason. Today, you will hear from Paul Bolno, our President and Chief Executive Officer, Erik Ingelsson, our Chief Scientific Officer, and Chandra Vargeese, our Chief Technology Officer.
We are also pleased to welcome Dr. Arun Sanyal, who will share his perspective on PNPLA3 I148M liver disease and the opportunity for an RNA editing correction approach. Following the presentations, our speakers will be available for Q&A, as well as Chris Wright, our CMO. With that, I will turn the presentation over to Paul.
Thanks, Kate. Good morning, and thank you for joining us today. Today marks our eighth annual research day. Each year, we use this time to showcase emerging programs in our pipeline, our platform capabilities, and our recent innovations. As an organization, we are relentlessly focused on our mission of unlocking the broad potential of RNA medicines to transform human health. At Wave, we bring together deep genetic insights and our proprietary chemistry to rapidly advance a pipeline of transformational RNA medicines. There are thousands of known genetically defined diseases, and understanding of how the genetic variations drives disease continues to deepen. At the same time, larger genetic studies and better tools for analyzing big datasets are rapidly expanding the number of strong genetic targets for common diseases. With our multimodal platform, Wave is uniquely positioned to leverage these insights.
For most of the field's history, oligonucleotide innovation has advanced through sugar and backbone modifications. Even today, traditional oligonucleotides are made as a stereorandom mixture with potentially up to 1 million unique isomers in a single dose. Wave's founding premise was to bring rational drug design to oligonucleotides to solve for this, resulting in improved distribution and pharmacologic and safety profiles. With the introduction of controlling backbone stereochemistry, PN chemistry, and modified bases, we've built the foundation for SpiNA-designed siRNAs and pioneered new modalities like RNA editing and bifunctionals. We've demonstrated clinical translation of our proprietary chemistry, RNA editing, allele-selective silencing, and recently, our SpiNA design, further setting us apart in the field and demonstrating the differentiation of our platform. We've been developing a way to extend these innovations beyond the liver, and today, we will provide an update on our PN conjugates.
We have established an Oligonucleotide Center of Excellence for accelerating these innovations into better RNA medicines. The process starts with selecting targets with strong human genetic support. We've built in-house systems to integrate large datasets into our discovery engine. Wave is uniquely situated to have options for choosing the right tool to silence, edit, or upregulate any given target, thereby enabling us to pair the modality that best addresses the target, including the ability to combine multiple modalities together. As you'll hear later, PNPLA3 is a perfect example of where RNA editing enables distinct advantages over siRNA. Using PRISM, we can leverage predictive modeling and rational design to optimize favorable pharmacology and safety profiles for our therapeutics. We've been compounding these learnings for over a decade and continuously improve the platform.
The result is that we develop clinical candidates rapidly at no additional cost to standard oligo development and reproducibly with scalable, cost-effective manufacturing behind them. The most recent example of this process is our WVE-007 INHBE siRNA, which was 18 months from our first in vitro experiment to first human dose. Today, we'll begin in RNA editing and highlight our PNPLA3 program. This program builds on our clinical success with WVE-006 for AATD. PNPLA3 liver disease is a similar story driven by a single base change and with strong human genetic support. We are pleased to be joined today by Dr. Arun Sanyal, who will discuss the unmet need for PNPLA3 I148M patients with liver disease and the opportunity for RNA editing. Erik will then discuss our WVE-008 program, which is advancing towards the clinic.
Chandra will then cover the foundation of our RNAi portfolio and how our SpiNA designs are enabling dramatic improvements in potency and duration of activity, and how they're translating in the clinic with WVE-007 with a safe and well-tolerated profile. Next, she'll speak about how we're using our chemistry to advance PN conjugates to unlock extrahepatic delivery and provide an update on our bifunctional modalities that provide the ability to silence, edit, and/or upregulate two distinct targets with a single construct. Now, joining from The Liver Meeting in Denver, I'm delighted to welcome one of the most influential figures in hepatology, Dr. Arun Sanyal. Dr. Sanyal is a Professor of Medicine and Physiology and Molecular Pathology at VCU, and Director of the Stravitz-Sanyal Institute for Liver Disease and Metabolic Health.
He has chaired the NIH NASH Clinical Research Network, served as president of the American Association for the Study of Liver Diseases, and authored more than 500 publications. He's pioneered diagnostics and therapeutics for fatty liver and end-stage liver disease, and as recently as last week, he was awarded the American Liver Foundation's Leadership Award. Dr. Sanyal will share his perspective on PNPLA3 I148M liver disease and the opportunity for a genetic correction approach. Without further ado, I'll turn the call to Dr. Sanyal.
Thank you, Paul. May I have the next slide, please? It's a real pleasure for me to give this talk, and we're going to talk today about PNPLA3, specifically a mutation at the 148 position that has been associated with more aggressive disease in the context of first, steatotic liver disease, but now across a whole spectrum of chronic liver diseases. The first identification of PNPLA3 as a potential gene mutation linked to hepatic steatosis came from epidemiological studies with the Dallas Heart Study in 2008. Since then, there have been a number of landmark findings which have provided insight into how this leads to disease, what are its clinical associations, and we are now poised to really talk about how the mutation itself can be modified to change the trajectory of the disease, and that's really going to be the theme of what I'm going to talk about.
Next slide, please. Beyond linking this gene mutation to having excess fat in the liver, there are now data indicating that if you have this gene mutation, you are much more likely to have cirrhosis. So within cirrhotic populations, this gene mutation is enriched. What is interesting is, it is not just metabolic dysfunction-associated steatotic liver disease, but whether you talk about alcohol-related liver disease, even viral hepatitis, having this gene sets you up for liver trouble if your liver does get into trouble. Next slide, please. What has occurred is that now, with PNPLA3 as the very first sort of gene that was identified, we have a slew of genes that have been linked to steatotic liver disease. But PNPLA3 I148M remains the clearest genotype-defined MASLD target, where whether you look at common polygenic susceptibility variants, it is a central anchor of all of those.
There are other protective genes that have been identified, and I think this is important that there are gene interactions. The evidence ladder, if you look in the lower right side of this slide, from starting with an association signal, we now know much more about the rare disease burden. We have understanding of disease biology, and we are getting ready to talk about functional and therapeutic validation of this as a target. Next slide, please. The global prevalence of PNPLA3, and this is another way of describing the same mutation, across the world is quite variable, but you can see certain areas where it is particularly overrepresented.
If you look at Latin America, it is very, very overrepresented, but there are other areas such as China, and here in the U.S., it is estimated we have about 18 million people who have or who carry this gene mutation. Similarly, in Japan and Mexico, many million individuals actually carry this mutation. The public health relevance of today's conversation is underscored by the fact that there are many, many individuals, literally millions, who actually carry this mutation. When you think about the prevalence of steatotic liver disease in a third or more of the general population, and you layer these one on top of the other, that puts a lot of patients at risk from this mutation. Next slide. It is also the strongest genetic risk factor for progressive scarring.
It is not just cirrhosis, but along the way to cirrhosis, as the liver gets more scarred, PNPLA3, again, across multiple etiologies, has been shown to be a very important genetic driver of accelerated progression of fibrosis and accelerated development of cirrhosis. Once you get there, it is one of the strongest genetic risk factors for the development of hepatocellular carcinoma, which is one of the cancers where we have still not tamed the beast. That creates another opportunity for prevention of hepatocellular carcinoma or to actually flatten that curve. Next slide. If you look at individuals who already have established steatotic liver disease or MASLD, we see first that the impact of the mutation on the likelihood of developing a liver outcome is also age-related, so there is an interaction term with increasing age.
If you look at our patients who already have advanced fibrosis, they are much older than people who have very early-stage disease, and so this is an important point. On the right-hand side, when you look at the disease allele and the risk of a liver outcome, and these are if you related to having advanced fibrosis, and then you are already seeing the data for the sub-hazard ratio for age over 60. You are seeing that in diabetics, there is an interaction as well. All of these show that while there is a general impact on overall risk of liver outcomes, particularly in older diabetic patients, this is particularly relevant. Again, as you know, with more advanced fibrosis, there is an over-enrichment of people with type 2 diabetes, which has been associated with accelerated disease progression also. Next slide, please. Having this mutation is associated with poorer mortality.
If you look at liver disease mortality, these are Kaplan-Meier curves. The homozygous people clearly are separated or differentiated from the heterozygous state. Similarly, if you look at cirrhosis-free survival time, in people who did not have advanced fibrosis at baseline, once again, having homozygous I148 mutation is associated with much poorer outcome. These provide a rationale that if you can convert somebody from a homozygous to a heterozygous state, that you might actually improve their clinical outcomes, which would start looking like the curves at the top. This is an important point, and so in this study, the gene mutation was associated with decompensation or a composite endpoint after adjusting for age, gender, diabetes, and BMI, which we know are co-factors with which the gene interacts. Of course, these data are continuing to be analyzed. Next slide, please.
Now, if you look at, we talked about obesity. Here we have data with obesity and with ongoing alcohol, and in both settings, for the same degree of obesity or same degree of alcohol consumption, you are seeing an amplification of the risk of development of hepatocellular carcinoma, if you have this gene mutation. Now, mechanistically, what is happening is that the protein that is encoded by this gene sits at the surface of the lipid droplets. It's a triglyceride lipase, so it takes the triglyceride in the liver and modulates the function of how you break that triglyceride down to release fatty acids that can be used for cellular energy or for other functions or to be exported. This is a loss of function mutation. So when you get decreased function, you cannot mobilize your triglycerides.
So at any given degree of fatty acid triglyceride flux through the liver, you start accumulating triglycerides. PNPLA3 gene is also important in the stellate cells, where if you have the mutation, it impairs retinol ester hydrolysis and thus accelerates collagen production by the stellate cells, and it's believed this is an important additional mechanism by which it contributes to increased fibrosis. It also attenuates proteasome autophagy, and so it leads to more fat, and when you start accumulating more fat, you also drive lipids into other aberrant pathways such as ceramides, et cetera, which are altered and which can also contribute to additional inflammation and fibrosis. Clinically, when you talk about treatment of MASH, there are data that MASH resolution with tirzepatide was weaker if you have the gene mutation.
It's not that it's bad, it's just that less than what you would see in the CC carriers. This again provides an opportunity that if you can change a homozygous to a homozygous I148M mutation to a heterozygous state, you might be able to even improve the response to background GLP therapies. Although I will note that with semaglutide and some of the others, and survodutide, which data will be shown at AASLD, the PNPLA, those drugs worked regardless of the presence or absence of these gene mutation. This has been really shown in the context of tirzepatide. So, why is mutation correction really a cool solution for people who have this and have liver disease? One, that because it interacts with regulatory proteins and maintains lipid homeostasis, mutation correction, it would be expected to restore lipid homeostasis, reduce steatosis, and prevent liver injury.
Because of its role through retinol homeostasis, mutation correction should be able to attenuate hepatic inflammation and oxidative stress, and should be able to lower fibrosis and lead to MASH resolution. So with that, I think this is my last slide. Can we have the next, please? So I will hand it back over to Paul. Thank you.
Thank you. I will hand it to Erik.
Thank you, Dr. Sanyal. As I think you will agree, Dr. Sanyal has just made an excellent case for why PNPLA3 is one of the strongest genetically defined targets in liver disease. I will now walk through how we are addressing it with WVE-008, our wholly owned GalNAc-conjugated RNA editing candidate. 008 builds directly on what we have already demonstrated in the clinic with WVE-006 in AATD. With 006, we have shown efficient and consistent RNA editing. We have demonstrated increased M protein and decreased Z protein to levels seen in MC individuals, as well as restored the dynamic physiological response to inflammatory stimuli, supporting that our RNA editing approach is not only showing target engagement, but the intended downstream treatment effects. The editing has been durable enough to support infrequent dosing, and 006 has been generally safe and well tolerated.
Together, these data establish Wave as a leading RNA editing company. They also give us a validated foundation to bring RNA editing to additional genetically defined diseases, starting with PNPLA3 I148M liver disease. As you already heard from Dr. Sanyal, PNPLA3 is a compelling target, with strong human genetic evidence and a clear path to early clinical proof of concept. There are over 9 million people in the U.S. and Europe who are homozygous for PNPLA3 I148M and are living with liver disease. Homozygous carriers have a significantly higher risk of a range of liver diseases. These include MASLD, MASH, and alcohol-associated liver disease, and they extend to cirrhosis and hepatocellular carcinoma. As you can see in the survival curve to the right, homozygous I148M carriers have an approximately ninefold higher risk of liver-related death than non-carriers.
Heterozygous carriers, by contrast, have about 80% lower risk of liver-related death than homozygous carriers. This observation defines our therapeutic goal. We aim to edit at least 50% of PNPLA3 transcripts in the liver, restoring a functional heterozygous-like state that is associated with dramatically lower risk of liver complications and death. Our GalNAc RNA editing approach is uniquely designed to restore PNPLA3 function and fully address this genetic driver of disease. We believe it will be superior not only to PNPLA3 silencing, but also to non-precision approaches in MASH. Why edit rather than silence? The wild type protein plays important roles in the liver's lipid and retinol metabolism. Multiple preclinical models highlight the potential liabilities of removing PNPLA3 altogether. To the left, in iPSC-derived human liver organoids, silencing PNPLA3 worsens steatosis. In the middle, in primary human hepatocytes, silencing increases inflammation-induced liver cell death.
To the right, in hepatic stellate cells, a PNPLA3 siRNA worsens the fibrotic response. These findings are consistent with emerging clinical experience. As Dr. Sanyal noted, the emerging data from trials with PNPLA3 silencing agents have been disappointing, with a recent trial that even showed dose-dependent increases in liver enzymes. The message is that functional PNPLA3 is essential for liver health, both for sustained fat metabolism and to avoid inflammation and fibrosis. This slide shows the mechanism. The I148M variant acts through a gain-of-function effect. The mutant protein builds up on lipid droplets and sequesters CGI-58, the cofactor of adipose triglyceride lipase, ATGL. This inhibits the lipase activity of ATGL, blocking lipids from being mobilized out of the liver. I148M also suppresses retinol metabolism, which worsens inflammation and fibrosis by promoting fat accumulation and fibrosis via activation of stellate cells. Silencing PNPLA3 can only partially address this biology.
Knockdown creates a PNPLA3 loss of function. ATGL activity is only partly rescued, and retinol metabolism is not restored. As a result, silencing may partially address steatosis while inflammation, ballooning, and fibrosis persist. By contrast, correcting I148M with RNA editing is expected to restore full PNPLA3 activity and lipid mobilization. That would reverse not only steatosis, but also inflammation, ballooning, and fibrosis, treating across the stages of liver disease. This is the key rationale for RNA editing over knockdown. WVE-008 is a GalNAc-conjugated RNA editing oligonucleotide, an AIMer. It incorporates Wave's proprietary chemistry and builds on our learnings from 006. It is administered by subcutaneous injection with potential for infrequent dosing. In the left panel, you can see the dose response curve showing potent editing with 008.
In the middle, you see results from RNA sequencing in two separate primary human hepatocyte lines, showing an ideal editing profile with strong on-target editing and no evidence of off-target editing elsewhere in the transcriptome, which gives us confidence in 008's specificity. In the right panel, you can see high liver tissue exposure in preclinical studies supporting excellent delivery and feasibility of durable infrequent dosing. Together, these data provide a strong translational foundation as we advance 008 towards the clinic, building on the clinical success of RNA editing capability with 006 for AAT. Next, we looked at whether editing translates into a functional benefit on liver fat. We compared our PNPLA3 AIMer with a PNPLA3 siRNA using our best-in-class SpiNA format in two human hepatocyte models.
In the upper row, you can see how PNPLA3 editing significantly decreased lipid accumulation in HepatoPac, a 3D human liver cell culture model, homozygous for I148M. At the bottom, you can see that 008 again decreased liver fat, this time in a monolayer culture of primary hepatocytes. These results reinforce the biological importance of preserving wild-type PNPLA3 function and the rationale for correcting I148M rather than silencing PNPLA3. For liver disease that progresses across the hepatic lobular zones, it is important that our AIMer oligonucleotide reaches all cells throughout the liver, not just in one region. Here, wild-type mice received a single subcutaneous dose of a surrogate PNPLA3 AIMer, and liver tissue was examined a week after that single dose. The red signal shows the AIMer. You can see even distribution across all three zones of the liver.
Zone one, periportal hepatocytes near the portal triad, zone two, intermediate hepatocytes, and zone three, pericentral hepatocytes around the central vein. This broad uniform distribution is a critical finding since it supports our goal of editing PNPLA3 throughout the liver, which is important for treatment of MASH and other PNPLA3-driven liver diseases. This data is also encouraging for our other AIMer programs, such as our 006 program, as uniform distribution of the drug is important for all liver diseases. Beyond hepatocytes, we also wanted to understand whether our AIMers reach the hepatic stellate cells that drive fibrosis. Hepatocytes are only part of the story in PNPLA3 liver disease. As Dr. Sanyal described, the I148M variant also impairs retinol ester hydrolysis in hepatic stellate cells, or HSCs. HSCs are the main drivers of fibrosis in the liver, so it's important to know whether our AIMers reach these cells.
In this study, wild-type mice received our surrogate PNPLA3 AIMer. Desmin, shown in green, marks the stellate cells, and AIMer is shown in red. Where the two overlap, you see yellow, which confirms that our AIMers are inside HSCs. As you can see, a substantial fraction of HSCs shows uptake. We then asked whether the AIMer actually edits PNPLA3 inside stellate cells, not just reaches them. In the panel to the right, you can see that we observe over 60% RNA editing in stellate cells. This confirms that the AIMers are active in these cells, not just present. These observations are critical because they suggest 008 could do more than correct PNPLA3 in hepatocytes. The data indicates that they also act directly in the cells that drive fibrosis, which gives us a direct antifibrotic mechanism on top of the expected benefit from reduced liver fat.
To bring it all together, the PNPLA3 I148M variant is a well-established driver of steatosis, inflammation, ballooning, and fibrosis. Yet there are no approved medicines that directly address this biology. Preclinical and clinical data increasingly suggest that simply knocking down PNPLA3 is not the answer. Losing PNPLA3 function can make the very features we're trying to treat worse. Our approach is different. With 008, we edit PNPLA3 rather than silence it. The goal is to correct the variant that causes the disease and restore normal PNPLA3 function in two key cell types, hepatocytes and hepatic stellate cells, contributing to restoration of lipid mobilization and reduction of liver fat, as well as restoration of retinol metabolism, which directly counters inflammation and fibrosis.
Our preclinical data so far support each part of this approach with potent and highly specific editing with no bystander edits, reductions in liver fat in human hepatocyte models, even distribution across all three zones of the liver, presence and editing in hepatic stellate cells in addition to hepatocytes. Together, these data support 008's potential to reduce hepatosteatosis, inflammation, and fibrosis, and to improve MASH resolution in people who are homozygous for PNPLA3 I148M. 008 also builds on our clinically validated RNA editing platform. If successful, it could be a first-in-class disease-modifying treatment for a large genetically defined population with no targeted options today. In summary, 008 meets every criterion we set before advancing a program addressing PNPLA3 I148M liver disease into the clinic.
As we just outlined, there are strong supporting human genetics and a large addressable population of more than 9 million homozygous I148M individuals with no treatment options that directly targets the driver of their disease. Our preclinical data support each element of the approach. We have demonstrated substantial, highly specific editing that exceeds the threshold expected to shift these individuals towards the lower-risk heterozygous phenotype. We have shown restoration of lipid regulation and decreases in liver fat in human HepatoPac models. We have shown broad distribution across all three zones of the liver, as well as uptake and editing in hepatic stellate cells, which supports a direct antifibrotic mechanism on top of the benefit we expect from reduced liver fat. With strong preclinical data validating the translation of our best-in-class AIMer chemistry, we are excited to take 008 into the clinic.
We will leverage previously genotyped populations to efficiently identify homozygous I148M carriers and accelerate enrollment, and we remain on track to file a CTA for 008 in the fourth quarter of this year. Now, I would like to turn the call over to Chandra, who will discuss our latest platform innovations.
Thank you, Erik. I will begin with the foundation of our SpiNA designs and how they have enabled significant improvements over industry-leading ASOs, while extending our delivery to both hepatic and extrahepatic tissues. Next, I will discuss how we are applying our best-in-class chemistry in RNA editing and RNAi to develop bifunctional oligonucleotides with the potential to address historically hard-to-target indications. For more than a decade, Wave has advanced RNA medicines through innovations in nucleic acid chemistry. We began with novel proprietary backbone chemistry, enabling us to rationally design oligonucleotides and to study structural activity relationships in single well-defined compounds. Since then, we have expanded our toolkit with novel base, sugar, and backbone modifications, optimizing sequence, stereochemistry, pharmacological, and safety profiles all together. Our PN backbone modification improves cellular uptake, endosomal release, residency, nuclear uptake, and target engagement. Our novel base modifications, such as N3U, has dramatically increased RNA editing efficiency.
Together, these advances have delivered step changes in potency, efficacy, durability, and delivery across hepatic and extrahepatic tissues. A hallmark of our platform is that insights from one modality inform the others and helping us move quickly into new targets. Today, I want to spend a moment on stereochemistry. Stereochemistry is a foundational aspect of chemistry relating to the three-dimensional arrangements of atoms. It has long been recognized that molecules differing solely by their stereochemistry have radically different properties. Given this, stereochemistry has been a central feature for several Nobel Prizes in both chemistry and medicine. This year's Nobel Prize in Chemistry recognized the foundational breakthrough in asymmetric organic synthesis and molecular chirality. Critically, it should be noted that synthetic methods can be developed that overwhelmingly produce a single stereoisomer efficiently and without wasteful steps in separation, a principle we have built an entire company around.
Chemically modified nucleic acids with chiral backbone, including RNA editing oligonucleotides and siRNAs, exist as mixture of stereoisomers unless their stereochemistry is deliberately controlled. Why does this matter? The case of thalidomide taught us the importance of characterizing chirality decades ago. The middle of this slide shows two stereoisomers with identical target engagement can have markedly different tolerability profiles. The same sequence, the same chemistry, and the same knockdown, but different liver enzyme responses. The field has learned this lesson with small molecules, and it applies to oligonucleotides as well. At Wave, we design and manufacture fully characterized single isomer RNA therapeutics. This capability is supported by a dominant IP portfolio and our unique ability to synthesize and screen stereopure oligonucleotides at scale. Controlling stereochemistry also enables rational structural-based design.
For example, for our siRNAs, that means positioning the guide strand with the MID and PIWI domain of AGO2 to maximize AGO2 loading. A mixture of hundreds and thousands of molecules does not offer the same precision. As a reminder, SpiNA is our stereopure interfering nucleic acid design. By increasing AGO2 loading, it enhances RNA-mediated silencing, delivering greater potency and durability than earlier designed siRNAs and industry benchmarks. The left panel here shows TTR mRNA silencing following a single dose of GalNAc siRNA. All constructs share the same sequence and two-prime modification as the literature reference. Against this common background, SpiNA designs deliver substantially greater potency and durability of silencing than both the reference and our previously published constructs. The right panel shows corresponding reductions in TTR protein following a single dose. Here too, SpiNA designs deliver an unprecedented improvement in potency and duration of activity.
What drives this? In our Nucleic Acids Research publication, we showed that our earlier designs gained potency and duration mainly from AGO2 loading. With SpiNA design, the shift is even larger. It comes from several-fold increases in both pharmacokinetics, shown on the left as liver tissue levels, and AGO2 loading, shown on the right. SpiNA delivers more than 10-fold improvement in AGO2 loading versus the reference siRNA. The SpiNA advantage extends even beyond TTR. Here, we evaluated PCSK9, a clinically validated cardiovascular target, comparing two SpiNA designs with a construct based on the inclisiran sequence and chemistry. Both SpiNA designs show durable reduction in circulating PCSK9 protein compared to the reference siRNA, at least through day 56 after a single dose. On the right, we also saw a corresponding increase in liver LDLR protein, which is a downstream effect that lowers LDL cholesterol.
Together, these results give us confidence that SpiNA's gain in efficacy and durability reflect the impact of our chemistry rather than an effect specific to a single target. We will now describe applying our SpiNA design to a clinical target in hepcidin. Our approach with the INHBE program relies on starting with the target with strong human genetics. What distinguishes our molecule WVE-007 from others pursuing their biology is our SpiNA design, proprietary chemistry, and PN chemistry that enhance interactions with AGO2, stabilize the RISC complex, and improve liver exposure. As we just shared, these designs achieve greater than 10-fold improvement in AGO2 loading versus a reference siRNA, and we will discuss momentarily. This approach has translated in the clinic.
While our INLIGHT trial is investigating otherwise healthy participants with a markedly lower BMI compared to other obesity trials, no diet and no exercise modification, this study provided us with a strong proof-of-concept approach. We demonstrated potent dose-dependent suppression of serum Activin E sustained through at least seven months after a single dose, supporting once or twice-a-year dosing, as seen on the left. The potent reductions translated to substantial reductions in total and visceral fat, reduction in waist circumference, stabilization of lean mass, all with favorable safety. Both our clinical data I just described, as well as the preclinical data, provide us with strong conviction for our approach and our ongoing phase II clinical trial. We can look to our preclinical data to demonstrate specifically the importance of baseline adiposity to this mechanism.
As we shared previously, our INHBE SpiNA demonstrated substantial reduction in both total and visceral fat with the preservation of muscle in DIO mice. In these DIO mice, in other words, mice with greater adiposity following a single dose of SpiNA, we also observed weight loss on par with semaglutide. However, when we looked at the impact of INHBE siRNA in lean mice, we see no effect on weight loss, as you can see on the graph on the right. These preclinical data support the potential to deliver an even more pronounced improvement in body composition in phase IIa portion of INLIGHT, which includes individuals with higher adiposity or excess fat at baseline. In addition to our ongoing phase IIa INLIGHT monotherapy trial, we are also making strong progress on our strategy to evaluate WVE-007 in the combination and maintenance settings.
We believe WVE-007's orthogonal mechanism, ability to drive reductions in fat while preserving muscle, and favorable safety profile are well-suited to both approaches. We have shared compelling preclinical data which supports both use cases. As shown on the left, we have observed approximately twofold greater weight loss as an add-on to incretins versus incretin alone. On the right, we have demonstrated the ability to curtail weight regain following cessation of incretin. We believe the translation of SpiNA designs in the clinic unlocks opportunities for WVE-007 across treatment settings and provides strong validation for our emerging pipeline. While GalNAc has transformed delivery to hepatocytes, reaching tissues beyond the liver has remained a major challenge for RNAi for more than a decade. Our approach starts with backbone.
By modifying PN linkages to create what we call PN conjugates, we can tune the physicochemical properties of the whole molecule and, in turn, its tissue distribution. The heat map on the right illustrates this flexibility. We evaluated the same sequence with 15 different PN conjugates, measuring knockdown in kidney, liver, and white adipose tissues. Each conjugate produced a distinct silencing profile determined entirely by backbone chemistry. This flexibility lets us steer distributions to our different tissues and tune target engagement in each tissue. Rather than relying on a single fixed conjugate, we have a library of different conjugates and can match the design to the biology of the target. This slide illustrates how we put the flexibility into practice with results from an eight-week mouse study following a single dose. The far left panel shows the well-established activity of GalNAc, which delivers oligonucleotides to hepatocytes.
It also illustrates the constraints of its cell and tissue-specific delivery. GalNAc does not enable silencing in other tissues of interest, such as adipose tissue. The middle and the right panels show how non-GalNAc designs with PN conjugates enable silencing of up to 90% in adipose alone or in both liver and adipose tissue together. We achieve this by tuning physicochemical properties, allowing us to select a design that best fits the target and indication. Now, I'll share how we have applied this to a historically elusive target A. Target A is a cardiometabolic target supported by human genetics. Carriers of loss-of-function variants have a lower risk of both coronary artery disease and insulin resistance. This follows the same genetics-first approach for INHBE. The unmet need is substantial. Insulin resistance drives type 2 diabetes, yet available insulin sensitizers offer either modest efficacy or meaningful safety concerns.
Because this target acts in both liver and adipose tissue, our goal is to silence it in both tissues. That's what we observed. Deep knockdown in liver and comparably deep knockdown in both epididymal and inguinal white adipose tissues, sustained for at least up to three months after a single dose. Durable silencing across multiple tissues with a single subcutaneous dose, a profile no one else in the field has demonstrated. We have replicated similar datasets for other cardiometabolic targets requiring dual-tissue targeting of liver and adipose. As we shared before, we have also extended SpiNA into kidney. Most oligonucleotides that reach the kidney go to the proximal tubule cells as a part of reabsorption, but that delivery usually does not affect the target.
Through structural activity studies, we identified SpiNA variants with PN conjugate that achieved 75% SOD1 mRNA knockdown in mice, and a 50% reduction was sustained up to three months after a single five or 10 mg/kg dose. The images on the right confirm both broad oligo distributions and reduced protein, mainly in the cortex and outer medulla. We have also confirmed knockdown across many cell types, including proximal tubule, distal tubule, endothelial cells, and podocytes. Now, let me turn to how we are using our best-in-class SpiNA capabilities to open up new ways of building RNA medicines. As highlighted earlier in the presentation, our GalNAc-conjugated SpiNAs achieve robust and durable silencing across multiple targets, including TTR, INHBE, and PCSK9. Using our unique chemistry design, we have built a single bifunctional SpiNA construct that silences two different transcripts at the same time in the same cell.
This could unlock complex indications that require engaging more than one target. It also has practical advantages over combining two separate drugs. One molecule to manufacture, with the potential to reduce cost of goods, one drug through development rather than two drugs, and delivery to the same cell, so both targets are modulated together. Here, that approach is in action with two well-validated cardiovascular targets, LPA and PCSK9. In transgenic mice, a single bifunctional LPA-PCSK9 construct produced robust, durable reduction in both serum LPA and serum PCSK9, with activity comparable to each corresponding mono-SpiNA alone. Other dual siRNA approaches have sometimes shown reduced activity or durability compared with single-target counterparts. Our chemistry preserves the activity of both arms, delivering performance on par with the current industry-leading designs and supporting potential once or twice-a-year dosing.
We continue to generate additional data with our bifunctional SpiNAs and look forward to presenting more data in 2027. As we shared last year, we are also using PRISM to combine SpiNA silencing and AIMer editing or upregulation into one oligonucleotide. The single construct engages both endogenous AGO2 and ADAR. It can silence one target while editing or upregulating a different target, which opens up complex indications that need more than one target engaged. Because the construct loads up into AGO2, we believe it may extend how the longer editing compared to the AIMer alone. We confirmed this in vivo with a GalNAc-conjugated construct designed to edit UGP2 and silence TTR. Mice received a single subcutaneous dose at equimolar levels. On left, in mouse liver, the bifunctional construct achieved higher, more durable UGP2 editing than the UGP2 AIMer alone.
As I noted earlier, we believe AGO2 loading may explain this. On the right, in the same mice, the construct silenced TTR mRNA as robustly as the TTR SpiNA alone. Before turning to our bifunctional silencing and upregulating oligonucleotides, let me briefly explain what we aim to achieve with upregulation. Many gene transcripts contain regulatory motifs that act as built-in brakes. These motifs recruit decay machinery, shortening the life of the mRNA and limiting how much protein it produces. The gene is active, but its output is constrained. Our upregulators recruit ADAR to make a single A-to-I edit within a regulatory motif, disrupting that brake on the edited transcript. This stabilizes the mRNA, allowing it to persist longer and produce substantially more protein. Remember, we are not introducing a transgene, delivering a protein, or altering DNA.
Instead, we remove a specific regulatory constraint to increase protein production from the gene's own transcripts while retaining endogenous localization and processing. For diseases driven by insufficient proteins rather than excess, this offers a novel way to address the underlying deficit. Here, we revisit our application of this approach to hypercholesterolemia by silencing PCSK9 while upregulating LDLR. These targets act within the same pathway. The goal is to increase the LDL receptor levels on the hepatocyte surface while reducing PCSK9-mediated receptor degradation. As we have shown previously in primary human hepatocytes, our bifunctional constructs increase the LDLR protein to a level comparable to LDLR upregulator alone. In the same experiment, it achieved PCSK9 silencing comparable to PCSK9 silencer alone. Together, these results demonstrate the potential to address complex indications by engaging multiple targets with a single construct.
Finally, we have brought silencing and upregulation together in vivo with results that demonstrate the potential for synergy. Using an undisclosed pair of targets, the bifunctional constructs maintained potent AGO2-mediated silencing of target X, as shown on the right. Notably, the target X silencer or the target Y upregulator alone produce only a modest upregulation of target Y by themselves, as shown on the left. However, the bifunctional construct, while effectively silencing target X on the right, also achieved a greater than fivefold upregulation of target Y, substantially more potent than either component alone. These findings illustrate the synergy we can achieve by pairing appropriate targets in a single bifunctional construct, engaging two different modalities. Beyond the examples I have shared today, we continue to expand what is possible with RNA medicines, with a goal of bringing innovative therapies to patients in need.
With that, I will turn it back to Paul for closing remarks.
Thank you, Chandra. As we reviewed today, Wave brings together deep genetic insights and proprietary chemistry to rapidly advance transformational RNA medicines. Our Oligonucleotide Center of Excellence integrates large datasets in-house and applies rational design and combines a multimodal platform with our own manufacturing. We are advancing WVE-008 for PNPLA3 liver disease, an approach with strong support from human genetics and advantages over siRNA. Our SpiNA design is translating in the clinic, and our novel PN conjugates are enabling extrahepatic delivery with potential to unlock new therapeutic targets. Finally, with our bifunctional modalities, we can simultaneously silence, edit, or upregulate two unique targets with a single oligonucleotide construct, with potential to drive efficiencies in development and deliver value to patients, providers, and payers.
Looking ahead, we continue to expect to deliver multiple milestones this year, including filing a CTA on 008, initiating a maintenance trial for 007, and for sharing data from the 600 milligram cohort of our phase I INLIGHT trial, as well as sharing data from our 600 milligram cohort of our RestorAATion-2 clinical trial of 006. I would like to close by thanking Dr. Sanyal for joining us today and by thanking our team for their continued commitment and to our mission of reimagining what is possible for patients. With that, I will turn the call over to the operator for Q&A. As a reminder, Dr. Sanyal has stayed on with us for Q&A. Thank you.
We will now move into our Q&A session. For those of you who are joining us via the Q&A webcast, if you would like to ask a question at this time, please raise your hand by clicking the raise hand at the bottom of your window. We would like to ask all analysts to please limit yourself to one question per person. Once called upon, please unmute your audio to ask your question. Our first question comes from Yun Zhong with Wedbush. Please unmute your line and ask your question.
Hi. Good morning. Thank you very much for taking the question, and thank you for the presentation. It's very interesting concept and very interesting data, of course, but my question to both Dr. Sanyal and maybe to the company is that, for the clinical development plan, is that going to be a While this is talking about the liver indication, is it going to be the standard anti-MASH therapy targeting the typical MASH patient that have been enrolled in previous studies? Because theoretically, this is really should be a preventive, given the fact that the mutation increases patients' risk for MASH. Is preventive therapy, I know it's very challenging, a possibility at all? Also, another question is, what's the current status of genotyping, please? Thank you very much.
Yeah. Perhaps I'll start with our approach, and then Dr. Sanyal, I'll hand it over to you to talk about the biology more. Our general approach to your point, I'll take the last part first, which is, how available is genotyping for patients? I think what's really important here, and we've had some of the foundations come in very recently, this is a mutation that's in 23andMe and is commercially available for genetic testing. So, to Dr. Sanyal's point, this is a very prevalent mutation, and oftentimes people are unaware that they actually are walking around with it.
With the improvement in access to genetic testing, that number is continuing, not just to grow, but people are actually coming and saying, to your point, "What should I do with this mutation?" Nonetheless, for drug development, and while prevention is interesting, meaning correct the enzyme over time and prevent the chronicity of damage and the evolution of disease, there is the ability to develop this in a standard MASH way where you could look at improvement in steatosis and fibrosis. However, we also plan to use these genotype patients and establish a homogeneous population for the purpose of a clinical trial to evaluate it, but always have that ability to look at the broader market. Dr. Sanyal, I don't know if you have anything you'd like to add.
Yeah, maybe just a couple of points to build on what you said, Paul. First, that this is a new area in the MASH space that we are entering. If you go into prevention, it takes a long time to show clinical outcomes, and therefore, you're creating a very long pathway. The low-hanging fruit really are taking people who have established disease, but who are also carrying the mutation, and therefore at higher risk of progression to cirrhosis, as well as clinical outcomes. Despite the availability of GLPs, as you know, there are still a lot of non-responders in terms of fibrosis. There are people who are intolerant. All of these, particularly if you have this particular gene mutation, may not get the kind of benefit that one might hope just with the existing drugs that are out there.
That creates, one, an opportunity to build on what is already out there and further enhance for this particular subpopulation. Then for those who are non-responders, this really gives an entirely new way of managing these patients, because if you looked at those Kaplan-Meier curves that we showed, if you can bring the survival curve up to what you see with the heterozygotes, that is actually a substantial improvement in both liver outcomes and liver-related mortality. So that creates the rationale for why that probably should be the first thing to tackle, and then deal with the more long-term issues of prevention. Also, if you are otherwise healthy, having the mutation, the clinical impact of that may not be as significant as if you have underlying obesity and insulin resistance.
Thank you. I will just return to Chris for a couple comments.
I am just going to add to what Dr. Sanyal said was, is that pre-clinically, we have seen that we can reduce the levels of fat in hepatocytes, so we know that it has a direct effect there as well as on fibrosis and inflammation. In the other clinical studies with knockdown, you do see effects, direct effects on fat levels. So, I think it is not just that it is preventative, but that could be therapeutic as well.
Which is, by the way, consistent with the genetics. The genetics is there across all stages of the disease. It is not only to develop MASH or MAFLD in the first place, or any liver disease, it is also in relation to survival. Dr. Sanyal showed those curves already.
Thank you.
Our next question comes from Joon Lee with UBS. Please unmute your line and ask your question.
Hi, thanks for the webinar and taking our questions. Just a quick clarifying question on Yun's question. People with PNPLA3 mutation are born with it and get MASH and other complications, but can editing it as an adult be enough to reverse MASH? How does PNPLA3 mutation actually rank compared to maybe other targets for MASH? Then just a follow-up question on WVE-007. Is there a range of DIO models to test your hypothesis that higher BMI would indeed drive greater weight loss? In other words, would it be possible to generate mice with degrees of obesity by controlling for their diet to test your hypothesis that higher BMI in humans would indeed lead to greater weight loss for your WVE-007 program? Thank you.
Yeah, I'll take the last one first, Yun, then hand it to Erik to follow up on the PNPLA3 question, and can also follow up on the WVE-007. I think this is compelling where we know, and we've seen this now in humans, even looking at the 400 milligram, looking at a differentiation in humans with different levels of adiposity, it's very clear with increasing adiposity, you get increasing driver for fat reduction. That's something that we've always said is a core driver in achieving the weight loss off of fat loss. I think what was interesting about these models is that's exactly what we've seen pre-clinically, correct, right? The DIO is an obese mouse model with high adiposity, and you can achieve weight loss similar to GLP-1s with that fat to lose. In very lean mice, fed lean diets, there is no effect.
You do need that increasing adiposity. Again, it's translating into phase I, where these patients do have increased adiposity versus a completely lean, low BMI patient population. We see an effect on 14%, 15% reduction in visceral fat, 5% reduction in subcutaneous fat, 3.3% reduction in waist circumference. So even in the human subjects, we're seeing that this change comes out with the increasing adiposity. What will be compelling is we've got a 2a study running in, as Chris mentioned in earnings, that are achieving those higher levels of adiposity. So we are going to be able to evaluate this in humans.
Thanks, Joon. I think that in terms of the editing as an adult and if it's enough to reverse MASH, I think we have evidence that that would be the case across a couple of different levels, starting with human genetics, as we talked about already. We know it is associated not only with developing MASH in the first place, but also survival in MASH and progression to cirrhosis and cancer, as Dr. Sanyal already pointed out. So genetics would support that it could be a reversible situation. The second thing is the preclinical. We've presented data today and before, both reversal of fat and of fibrosis, inflammation of fibrosis. I think that's also second layer of evidence that it would be reversible in adults. The third layer is the clinical data that already exists. You actually do see some reversal of the steatosis side of MASH.
It's just the fibrosis that hasn't been possible to do with the total knockdown of PNPLA3. Plus we also think that actually restoring it back to wild type would be more efficient for the fat as well. So we think it's a superior modality, but there is some clinical evidence as well. So I think just across both genetics, preclinical, and clinical data, it's pretty strong evidence that it's reversible in MASH in adults. Your second question was about how this variant ranks among different MASH targets. I think Dr. Sanyal showed very nice overviews of that, where this is the strongest association. It was the first one really to be established through GWAS back in around 20 years ago now. So it's definitely the strongest genetically, and it's also attractive because it's such a large population.
It really allows for a precision medicine approach in a very large population of carriers.
Thank you.
Our next question comes from Alethia Young with William Blair. Please unmute your line and ask your question.
Hey, guys. Thanks for taking my question, and thanks for putting all this together today and having Dr. Sanyal on the phone. A couple questions. One, the subgroup data, it seems to show a stronger risk association in patients with advanced fibrosis and diabetes. Do you think this suggests a greater dependence on the PNPLA3 biology, or does it just kind of suggest that they're identify high-risk patients, and can you use this for trial selection? My second question is, I'm just curious how much SpiNA design carries over from one target to the next, when you're kind of thinking about across TTR or PCSK9, are the same stereochemical patterns working, or do you need to kind of re-optimize as you go through each sequence?
Great. Maybe for the first question, Dr. Sanyal, would you like to take that?
Yeah. I think there is no question there is an interaction between increasing age and type 2 diabetes and having the PNPLA3 mutation. Now, there could be two potential sort of scenarios over here. One, that the PNPLA3, that when you have diabetes, you already have a more severe insulin resistance, more severe lipotoxicity, and already more aggressive fibrogenesis. And in that setting, having this, you could argue which one is the sub fire and which one is the catalyst, but the two together, they sort of synergize. If you take one of these away, you return things to sort of more of a baseline situation.
Certainly these could be used as enrichment factors for clinical outcomes, but I would suspect that based on the biology, that the benefits of fixing the mutation would not be restricted only to those who have diabetes or are over the age of 60, although one could imagine stratification just if you had to show that there were differences in clinical outcomes that would help enrich for the clinical outcomes. Hope that makes sense.
Thank you, Dr. Sanyal. Chandra, do you want to do the SpiNA question?
Yeah. The SpiNA question you asked us about the sequence dependency. The chemistry that we have developed, as I said, it's mainly looking at how the sequence is docked onto the AGO2, and this is actually sequence-independent phenomenon, and we have translated our learnings from our TTR through our INHBE. Remember, we also have a clinical candidate declared for GSK. They're developing, they've taken it for development. All this actually shows us that our technology is not sequence-dependent at all for SpiNA.
Thank you.
Our next question comes from Samantha Semenkow with Citi. Please unmute your line and ask your question.
Hi. Thanks very much for taking the question, and thanks for putting this together today. My question is, with correcting this, the I148M mutation with OA, is the therapeutic goal here reversal of disease, or would prevention of further progression be enough for this market? I guess what I'm getting at is, what do you need to show competitively in the clinic here to be used over some of the other obesity drugs, GLP-1s, and others that are in development? Thanks very much.
No, thank you, and I'll start, and I'll let Erik. I think the short answer is both, and I think the opportunity we have on both the steatosis side and the fibrosis side give us a point of differentiation. As we've seen, there was a substantial investment in siRNA silencing to try to approach this disease with early data on the steatosis side, but again, without being able to address the fibrosis side. I think there is a strong therapeutic component to this, not just preventive. To that point, a lot of the other mechanisms are how to really address and focus on the steatosis side by taking down that fat. Again, mechanistically, and again, in patients that have this specific mutation, both is the operative term.
Yeah, I am not sure if I have so much more to add. Again, yes, both. I think it would be a great drug if it could entirely stop progression, because typically individuals with MASH, they do die more from the cirrhosis stuff. So even if it, within quotation marks, only put a brake on it would be great. But we do think, based on the biology and what we know at this point, that there is also a potential to actually reverse and push it backwards in the stages. So, both.
Thank you.
Our next question comes from Rick Bienkowski with Ladenburg. Please unmute your line and ask your question.
Morning, everyone. This has been a really informative presentation, and thanks for taking the questions. For Dr. Sanyal, you showed some evidence earlier in that MASH resolution with tirzepatide is weaker in PNPLA3 carriers than in wild-type patients. I was curious to get your opinion on the RNA editing mechanism of action here. Would you expect to see resolution of MASH with an RNA editing monotherapy in heterozygous and homozygous patients, or do you think the mechanism would really shine brighter here in a combination setting?
Dr. Sanyal.
I think my answer would have to be a little bit speculative. In this kind of setting, first of all, these findings from the phase II-B study have to be confirmed and validated in larger studies. Assuming that is so, I would imagine this could really potentially, if there is a causal basis for those with mutation to have less of a response, then there could be a way to enhance the MASH resolution. The MASH resolution over time would be expected to reduce progression to cirrhosis, because the fibrosis progression does not occur in a vacuum. It is the disease activity or the steatohepatitic activity that drives the fibrosis progression. To that extent, I think it could enhance the therapeutic benefits of a molecule like tirzepatide. Remind me again, there was a second part to your question as well, wasn't there?
Rick, your line is unmuted if you'd like to go ahead.
Right, thank you. I guess the second part of the question was about, pre-clinically, we've seen between 50% and 60% correction of the PNPLA3 transcript. Do you think that would be sufficient for heterozygous and homozygous patients, or just one of those populations?
Well, I think if you saw the survival curves, the heterozygote and the completely normal individuals, they were the CC phenotype, they were not really that differentiated. That is the premise, that when you switch this from a homozygous mutation to a heterozygous state, it is sort of the PNPLA3, you have to remember, is one thing that is a little bit weird, and it is hard to wrap your head around, that on the one hand, it is a triglyceride lipase, and having the mutation decreases triglyceride lipase activity. On the other hand, you need increased expression of the gene for the phenotype to develop. That is a sort of interesting construct over there. That has to be taken into consideration in terms of trying to understand whether a 50%, 60%, or more would be sufficient.
You probably do not want to completely wipe out all triglyceride lipase activity, because then you have no way to mobilize your triglycerides. Then you will essentially start accumulating triglycerides. More is not always better. This is a little bit of a Goldilocks situation, I think, where you just want to hit it just right. Not too much, not too little, get it right in the middle. Gene editing gives you that opportunity, as opposed to gene silencing, which will wipe out all your triglyceride lipase activity, then you cannot mobilize triglycerides, or substantially impairs your triglyceride mobilization capabilities, which can have other unintended consequences.
Maybe if I could just add one thing. Thanks, Dr. Sanyal. I agree with all of that, and that is also why we set out 50% as kind of our bar for this development. Now, just for the record, the 60% we showed today is, that is in stellate cells, and it is also for a surrogate AIMer for the mouse studies. Now, in our human, with the compound that we are taking into clinic, we have seen up to 85% editing in hepatocytes, just for the record.
Thanks for the question, Rick.
Our next question comes from Amine Chaherli with B. Riley Securities. Please unmute your line and ask your question.
Hi, everyone. Thank you so much for the comprehensive update and for bringing on Dr. Sanyal today. I just had a question with regards to WVE-008. I guess if you could talk about how you're thinking about demonstrating target engagement in humans, and I guess, how that kind of interacts with that genotype-first enrollment approach that you've described. Then I just had a question about- Basically, if you could just inform about the time course, once the editing is established, and whether clearance of the preexisting protein pool is kind of the rate-limiting step of the efficacy versus just the editing itself. Thank you.
It's a wonderful question. We'll obviously give more updates on the trial design as the CTA is submitted and the trial initiates, but I think the premise really takes two approaches. One, because we can enrich, and this is a study in PNPLA3 patients, the ability we have to start identifying those patients, and creating those relationships starts before the study goes. So we can actually start identifying patients with PNPLA3 mutations. Second, to your point on evaluating efficacy, there are biomarkers, and we've spoken to this briefly in the past, that we can identify to look at target engagement as well as other measurements we can use to look at editing, and then have other approaches that we can look on physiology. I don't know, Chris, if there's anything you'd like to add to that.
I think we covered most of it. We're planning to ensure that we have a number of patients that are pre-screened that have the actual genotype that we're looking for so that we can enroll them rapidly into the study. So I think just to come from that perspective, and as Paul mentioned, you can look at other sponsors' trials where they looked at various lipid components to show that they were hitting their target. So, it's possible to do that from a biochemical perspective or from biopsies, as you mentioned.
Our next question comes from Cha Cha Yang with Jefferies. Please unmute your line and ask your question.
Hi, this is Cha Cha on for Roger. Thank you for hosting this event and thank you for taking our question. My question is for WVE-008. My understanding for the ADAR-mediated RNA editing is that for the A to I edit, you would generate the I148V substitution rather than converting to wild type isoleucine. Can you just share with us more data or how we're thinking about the functional activity of the edited protein with the valine in that position versus the wild type isoleucine?
Sure.
Yeah, I can take this. We actually looked at a lot of these genotypes actually naturally exist. There's a lot of species that have the valine substitution, substituted for isoleucine. This is where we think that it's actually, structurally, they're also very related, and so this helps us to generate. Of course, we are not converting back to the wild type, but we are actually making it to valine, which is actually a good substitution for isoleucine. That's where this is coming from. Again, it's supported by genetic data in lots of different species, in monkeys, and even in bovine, this is where it exists.
Maybe, if I can add, that was the starting point, both structure and conservation across species, et cetera. Now, that was a little bit of a bet, but now I think we've shown in a lot of preclinical study that it actually, that's reverted back to a functional protein as we expected based on the conservation of the protein and the structure.
To that point, where we could look at it in comparison with other substrates, like siRNA, is to look at comparable effects, so on the control side. It was a great exercise both in understanding basic biology and translating that into a therapeutic.
Our next question comes from Catherine Novack with JonesTrading. Please unmute your line and ask your question.
Hi. Morning. Thanks so much for taking the question. Just wanted to get a little clarity on the road and the timeline to proof of mechanism data in humans for PNPLA3. The first-in-human data, I know you're focusing on genotyping, but will these patients also have clinically significant MAFLD, and what percent liver fat reduction would be considered meaningful? From a timing standpoint, the duration of dosing, how many weeks do you expect to first efficacious data in the phase I trial? Thanks.
No, thank you. I think once again, once we're filed and initiated, we'll give more definition of where we're going to get to and on the various side of the trial. I think the thing to step back from, if I think about the 30,000-foot view, is the goal initiation is to look at this in an expeditious, experimental way of unlocking the potential here. Meaning, how quickly can we identify in these patients with the mutations and underlying disease the ability to show high degree of editing, distribution, durability, change of biomarkers, change in physiology, all of which are going to allow us to de-risk the mechanism and then continue on the study. I think to step back, speed and efficiency coupled with the ability to differentiate in this space will be the focus of the clinical trial.
I think interestingly enough too, in terms of population enrichment, I think as Dr. Sanyal presented, there are ways to think about populations that have large numbers of patients. It is not just a screening strategy. There are areas where we can run these studies where we can get access to substantial number of patients to be able to run those studies. Chris, anything else you want to add?
Our next question comes from Ananda Ghosh with H.C. Wainwright & Co. Please unmute your line and ask your question.
Hey, thanks for the question, and thanks for arranging this call. I think the first few questions are directed to Dr. Sanyal. I wanted to know how well are these patients diagnosed currently, and with respect to the trial design, what is the sweet spot one should think about when one is thinking about the inclusion criteria for a POC trial, and also from the comorbidity point of view? Is there a way to kind of enrich homogeneous patient population if one has to design a POC trial? The other question is, what is a good animal model to study steatosis in this disease? Strategically, this is for the company, strategically, how are you thinking about the developmental plan given the long timelines one sees in MASH trials? Thank you.
Dr. Sanyal, if you want to take the question to start?
Sure. I think the proof of concept trial design, we use individuals who have established steatotic liver disease with criteria where they already have started scarring down their liver, so we have a well-defined natural history. You can actually model how many patients you will need and how long you have to follow them to first show less progression to cirrhosis. If you win that battle, almost certainly in the long term, the clinical outcome will improve because without cirrhosis, you do not really get clinical outcomes. That is one of the basic clinical tenets of hepatology. Your second part of that question was, how many of these patients are currently diagnosed? Right now, probably a very small minority, but it is a self-fulfilling prophecy because the reason nobody is looking for them is what are you going to do with that information? How will it change your therapeutics?
Third-party payers are not willing to pay for extra testing just to satisfy one's curiosity. Now, if it would modify your therapeutic approach, then there is a strong rationale for doing it, and the beauty is that we already have the technologies. These are widely available, commercially available, and to eventually, once the clinical benefit is established, the scale-up could happen almost in real time because doing genetic testing in other disease states is routine practice, for example, heart failure, lipodystrophy, other kind of situations. I think given that infrastructure already exists, this would be just another place to send a test. I do not perceive that as any kind of a real significant barrier. The proof of concept, of course, would be demonstration of improvement in steatosis, but we look at steatosis in multiple ways.
It is not like there is one magic threshold that tells you yay or nay, and it is a thumbs up or a thumbs down. You look at people who have more than 30% improvement in steatosis, but it also depends where you start. Number two would be the proportion of people who drop below 5% steatosis, who completely wipe out their fat. We know that 30% is good, but 50% improvement is better, and 70% is even more, and completely defatting the liver is probably ideal. I think we will look at the totality of the data to make go/no-go decisions for further things. If it was my molecule, I am of course only a consultant to Wave, but I would look at the totality of the data. Of course, we are going into fibrosis patients who have already started scarring down their liver.
I would like to see some improvement in biomarkers of fibrogenesis to show that fibrogenic drive is also improving. That gives me the confidence that I will hit all my clinical endpoints in a larger, bigger study.
Chris, you want to
So, really the only thing I would have to add is that from the recruitment perspective, as mentioned, there is a number of genetic databases with people that are already well-characterized, so you can leverage those to pre-identify patients to move them forward into your study. Then maybe just to cover from the MASH perspective, I think it is very well described what an approval pathway looks like for MASH, and it is like a year and a half long study, and you can use surrogate endpoints to start with and get an accelerated approval. So, you can move forward pretty quickly from that perspective and then follow up with a pivotal confirmatory trial following that.
Thank you.
Our next question comes from Alec Stranahan with Bank of America. Please unmute your line and ask your question.
Hey, guys. Thanks for taking our question. Maybe just on the endpoints from the phase I guess, which of the non-invasive liver measures, if you are measuring these, such as liver fat, cT1, ALT, et cetera, should we focus on in the early data? I guess, how quickly would you expect those markers to move after dosing? Then, just quickly, sorry if I missed this, but just the rationale pursuing the CTA route versus the IND route. Any color there would be great. Thank you.
Yeah, so I think as Paul mentioned earlier, we will be looking at a number of measures, including MRI, but as we file our CTA and initiate the study, we will provide more of the details around the assessments and the timing from that perspective.
To Dr. Sanyal's point, the ability to look at these other biomarkers in conjunction also enrich in an early study the ability to differentiate mechanism and de-risk. The last question-
Oh, CTA versus IND. This is something that I know a number of you, we have this conversation. We use CTA, I always say, in the broadest sense possible, in that these studies can be U.S. and ex-U.S., so we will provide a filing sequence. But we use CTA just in general to mean the initiation of the trial.
Our next question comes from Steve Seedhouse with Cantor Fitzgerald. Please unmute your line and ask your question.
Great, thank you. Interesting data on the INHBE knockdown in lean mice, and my question's actually about the clinical study. I am curious, in the high BMI cohort of INLIGHT, are you protocolizing diet and exercise? If so, how are you doing that? If not, do you think it's not important with this mechanism? I am just curious if any of the preclinical data that you've generated recently has informed that at all as well. Thanks.
Yeah, I think as we also mentioned at earnings, not only are we having a protocol for diet and exercise, it's a very standard approach that other anti-obesity medicines use, we're also evaluating measures up front from the MRI perspective to ensure that the participants have increased levels of adiposity, and that's what we're seeing. So, that's really how we're managing that up front to ensure the highest likelihood of success, and kind of reproducing what we're seeing in the preclinical data in these individuals with higher adiposity.
I think the other piece to add to that, to your second part of the question, Steve, which is really interesting, because we have run extensive models, multiple models across settings, and I think the fact that caloric consumption is not a driver mechanistically for this, I think, is an important notion. Again, standardizing things as part of these studies is always important to be able to compare and to run the clinical trials in a way that is benchmarked well, how others have done it. But across all of the preclinical studies, that caloric consumption piece has not played a role. I will say that in two veins.
One, if we look at the DIO mouse model, just the comparison with the GLP-1, I think what's still astonishing, that weight loss, if you look at the two curves, the slope of GLP-1, where now we know looking at the BELIEVE early data with semaglutide, 40% of that early initial weight loss is driven off of lean mass loss. So, there's a very good mechanistic rationale when we look at the body composition in the DIO mouse that we're actually losing potentially even more fat, right, to get to that equivalent rate in weight loss. I think that's encouraging, and again, independent of caloric consumption.
The other place where we see that directly, which I think is probably going to be one of the most interesting opportunities long term as we think about maintenance opportunity for this mechanism, which is completely orthogonal to this weight loss component that I know folks are indexed on. But in maintenance, that driver at that point where the incretin was stopped, and because it is a preclinical experiment and you do measure caloric consumption in these mice, that we saw the opposite, right? These mice who were on incretins who had it removed had a massive increase, right, in their caloric consumption, and equivalently, whether they were on INHBE or not. And yet, those who were treated when the brake came off lipolysis didn't restore that excess energy in terms of fat.
I think across multiple preclinical settings, and again, in the clinic, we're seeing that caloric consumption's not the driver here. Again, the study in the phase II-A, across monotherapy, combination, and maintenance, are all going to recapitulate, I think, a lot of this degree of high adiposity as a requirement in terms of seeing those changes.
Our next question comes from Jenny Gonzalez-Armenta with Leerink Partners. Please unmute your line and ask your question.
Hi, guys. This is Jenny on for Joe. Thank you for putting this together. It has been really helpful. Maybe just another question on biomarkers and early data in PNPLA3, maybe for Doctor and the team. Are there any other early and sensitive markers that we could see in these phase I data that would suggest or even definitively differentiate WVE-008 on eventual fibrosis benefit, especially versus knockdown approaches, since you were talking about that being a potential differentiator? Thank you.
Yeah, thank you, Jenny. Dr. Sanyal, would you like to start?
Yeah, I think the low-hanging fruit really relates to quantification of the fat for a couple of reasons. One, it is directly in the biological pathway. Fatty acids come into the liver, they are very toxic, so the liver cell packages it as triglyceride, which is sort of a storage form that is relatively safe. Of course, when you accumulate that, it is easy to see with MRI and quantify. You can quantify it with CAP score, et cetera, and you can see it under the microscope as well. That is the obvious thing. The ability to mobilize those triglyceride droplets is linked. That is where PNPLA3 comes in. If you facilitate the ability, you open the release valve, if you will, then you should see a decrease in fat, and that should be an immediate readout.
Now, the improvement of improving throughput of fat through the liver should be reducing lipotoxicity to the liver, so you would expect less liver injury. The next thing I would look at are the liver enzymes, which are markers of liver injury, and to see whether they are actually declining. In addition to that, if you reduce these two, remember that this represents disease activity and injury. The injury activates fibrogenic drive. There are now biomarkers such as Pro-C3, et cetera, that are more reflective of fibrogenic drive rather than the fibrosis burden itself. It takes a while to shift the actual fibrosis itself, but the fibrogenic drive can be cooled off. I think you can capture that also with these biomarkers. Another biomarker that is now sort of looking good and more data are coming is the ILS 2+.
This is based on microRNA-34a and YKL-40. It is again measuring a couple of things. 34a is very much linked to the metabolic disruption in the liver. If you are restoring metabolic homeostasis, you might expect to see an improvement in 34a, and YKL-40 is linked in the fibrogenic pathway. There are now data showing that ILS 2+ reflects a composite biomarker that tells you whether you have the kind of MASH that requires pharmacologic treatment. What we call at-risk MASH, it is a biomarker for at-risk MASH as a composite. There are some early data that with effective treatment, the ILS 2+ drops below the threshold for having. More to come on this, but that is another potential biomarker. As you know, this biomarker space is very, very mobile and active.
Everything I tell you today, there could be new biomarkers in play a year from now. These are some of the best in class today that we can talk about.
As Chris mentioned, we are embedding biomarker-driven studies in addition to being able to look at target engagement as a number of early signals as well.
Thanks, Jay.
Our next question comes from Michael King with Rodman & Renshaw. Please unmute your line and ask your question.
Thanks for taking the question, guys, and putting this webinar together. It's been super helpful. I wanted to see if you could address the topic of CIDEB, C-I-D-E-B. It was a target that was found at the Regeneron Genetics Center, and some phase I data, I believe, was presented at The Liver Meeting. A single dose of an antibody reduced liver fat to about 70%. So I wonder how you think about that incorporated into your thinking about development of PNPLA3. Then I have a separate question, but I want to ask that one first.
Yeah, I mean, I think there's a number of movements of ways of reducing liver fat. We know INHBE in the clinic substantially reduces liver fat as well, and we're exploring that through MRI-PDFF based on the clinical trial. But I think a lot of that has to do, as Dr. Sanyal was saying earlier, with this steatosis side of the disease. I think what's really important for these patients who have PNPLA3 mutations is the fibrosis and inflammation component of the enzyme. Again, whether or not eventually these patients who have the mutation need the mutation corrected and then also get the benefit of having these other therapies, or in the case of the early data of these tumors, appetite that show those patients are less responsive.
I think these are things that will all, as this field continues to grow with therapeutic options, I think what's intriguing for us is the strong genetic correlation on the enzyme that it has this functionality on driving this kind of retinol inflammation pathway. I don't know, Erik, if there's anything to add.
Not really. Maybe not more than that these are different mechanisms. As far as I know, there aren't interactions necessarily between the CIDEB variants and PNPLA3 variants. So you would expect that this interesting targets, but this is an independent mechanism. Again, there are a very large number of homozygous carriers here where this is the exact right way to treat it because it's treating the direct cause of liver injury in these individuals.
Our next question comes from Ben Burnett with Wells Fargo. Please unmute your line and ask your question.
Good morning, team. This is OPS on for Ben. Thank you for the detailed presentation. In light of WVE-008, your bifunctional platform, and as you go into new indications, could you share what your thinking is when it comes to developing assets by yourself versus partnering? Specifically, what pieces of the platform and at what stage would you be open to partnering? Thank you.
Oh, thank you. I mean, I think there's a variety of targets that have provoked conversations because they are interesting mechanistically and pathway-wise. So I think the key is continuing to be able to bring interesting, innovative programs and products to the clinic, de-risk platforms both on the RNA editing side as we've seen with alpha-1 antitrypsin and its applicability here. As we've shared before, INHBE broadly is garnering interest and relative to what we can do with SpiNA, and particularly to Chandra's point, the fact that we're seeing the translation of candidates to our partners at GSK means the platform's now validated from an engine. So, with Monika joining, one of the core focus has been how do we think about the balance of a portfolio programs and how do we think about the platform capability and capacity more broadly?
I think our view is to continue to drive optionality across the portfolio to optimize what's going to be best and most expedient for patients and an efficient use of our capital to de-risk and accelerate programs.
Our next question comes from Cassie Ivan with RBC Capital Markets. Please unmute your line and ask your question.
Oh, great. Thank you for hosting another wonderful virtual research day. This is Cassie for Luca. Dr. Sanyal, and maybe also Paul on WVE-008. Paul, you spoke of speed and efficiency in your clinical execution to bring therapy to patients. If I may follow up and ask about comparing the expected disease progression and disease prognosis between PNPLA3 patients in your prospective trial versus typical MASH or MASLD patients. As you touched on, in MASH, comparators, liver fat reduction, signal sphere, the MRI are detectable within 24 weeks or maybe even 12 weeks, but fibrosis improvement on histology generally requires a year or multiple years. Where does PNPLA3 patients fall on this timeline, given, Dr. Sanyal, you've talked about wanting to see fibrogenesis improvement and also the prognosis differs amongst patients with different baseline and comorbidities. Any color there on that is much appreciated. Thank you.
No, absolutely. I'll start, and then Dr. Sanyal, I'll hand it over. I think the first path for us is, how do we get as rapidly as possible to finding that dose and editing efficiency, right? How do we get to that ability to look at target engagement, change in biomarkers, and the medicine de-risking from a biology perspective? Then there's de-risking it from a pathology perspective. I think we're actively in the efficiency side, again, because we can identify these patients that have the mutation. As Dr. Sanyal pointed out, there's things we can do to enrich on pathology too, to optimize signal.
I think we think about that study as having kind of two components to it to accelerate. The first being as rapidly as possible, kind of de-risking the PNPLA3 targeting. Then how do we unlock the potential as we think about then de-risking the pathological changes. I think that is, we roll out the trial design on the other side. I think that's something that you'll see is the ability for us to think about those two pieces so that we can be efficient in de-risking the program. Dr. Sanyal, I don't know if you want to add on the pathology side and how we think about de-risking that.
Yeah, I think you, Nova, basically agree with you. In the early phases, of course, you get a signal for reduction in liver fat. Fat is extremely mobile. There's all kinds of data going back 50 years that fat can move in and move out of the liver within a matter of literally hours to days. Certainly within 12 weeks, one should expect to see a significant improvement in overall steatosis and markers of injury. As we move forward, depending on how you select your population, that will determine the trajectory towards cirrhosis. It is based on the relative numbers of F2 versus F3 population, in terms of likelihood of progression to cirrhosis. With the F3 patients, you would expect 7%-10% over a matter of a year or two would progress to cirrhosis.
If you were to do a three or four-year study, you would have about almost a quarter of these patients would have progressed to cirrhosis. Again, I think we are in a little bit uncharted territory, but if you look at the Kaplan-Meier curves for the clinical outcomes, then you would be able to see that first we have to show less progression to cirrhosis. You would want to see an effect size that would reduce the hazard ratio to at least 0.8 or greater. Greater is better, but it's very hard given current data to be absolutely certain where you'll land. But I would project somewhere between 0.5 and 0.8 is where we hope to land with this type of approach.
Thank you.
Our last question comes from Danielle Brill with Truist Securities. Please unmute your line and ask your question.
Hey, guys. This is Alex on for Danielle. Thanks for taking the question. Just a qualitative one on WVE-008. I believe you said you are going to be initially investigating the efficacy of WVE-008 in previously identified and genotyped homozygous I148M patients. Is there anything about these patients that led them to get genotyped in the first place? I am just curious where on the bell curve do these patients fall versus a potential typical bucket of patients that you might recruit for future clinical trials as it pertains to disease severity, comorbidities, et cetera? Thanks so much.
What I would say, just maybe to start from the last part of your question and move up, is that we are designing the trial with inclusion/exclusion criteria that allow us to best be able to detect the types of differences we are looking for. So, obviously not too far, not too mild, but in that sweet spot where you can actually see a change. That is kind of irrespective of where the patient comes from. They will have to meet those criteria. Then to your earlier point, I mean, there are lots of different genetic databases out there that you could imagine, either private or public, where people just get tested for different reasons, and it may not be for liver disease per se. But then, you do have all that information, and you can utilize that to pre-identify individuals.
Again, there may be other settings and liver clinics, hepatology clinics where people have been genotyped over time because of the interest of the individuals there. That is another way that you could potentially accelerate the approach versus just taking all comers and hoping that they have the genotype of interest.
Thank you.
Thank you. There are no further questions at this time. I will now turn the call over to Paul Bolno for closing remarks.
Thank you, everyone, for joining us today, and we look forward to connecting with many of you in the near future at the multiple upcoming conferences. Have a great day.