Genes, Panels, and Patients: A Practical Approach to Genetic Testing in Cystic Kidney Disease

OK, hello everyone, and warmly welcome to today's educational webinar titled Genes, Panels and Patients.  A practical approach to Genetic Testing in Acoustic Kidney Disease. The webinar is brought to you by Blueprint Genetics, a genetic knowledge company committed to providing an innovative approach to genetic testing and to ensure accurate and confidence in your clinical practice. My name is Taina Vuopio and I have the privilege of hosting today's webinar. Please submit any questions you may have in the QFI box. You can submit them throughout the webinar and we will answer as many as possible at the end. We are excited to have Alicia Gosa as our speaker today. She's a broad certified genetic counsellor and a clinical genomic liaison within the Clinical Genetic Services team at Blueprint Genetics. Alicia received her Bachelor of Science in Forensic science from Trent University and her Master of Science in Human Genetics from Sarah Lawrence College. She has held diverse roles in her over 10 years career in genetics and genomics. For instance, providing in person and telehealth clinical genetic counselling for a variance of indications, client facing laboratory support for complex cases and tests utilization management. She also enjoys mentoring students and early professionals. Thank you for being here today, Alicia. Please. Thanks so much, China, and thanks so much for that lovely introduction. Welcome, everybody. It's a pleasure to be here with you today. I'm excited to dive into the world of genetic testing for the indication of cystic kidney disease with you. Please know that this work that I'll present today is on behalf of the entire team here at Blueprint Genetics. And I also want to give a specific mention to two individuals who spent time with our Blueprint team as students completing their Master's training and genetic counseling, Brandon Schultz and Aaron Tapper. During their time working with us at Blueprint, they engaged with projects focusing on genetic testing for cystic kidney disease, and some of the content that is presented here was created with their influence. Thanks so much for your collaboration, Brandon and Aaron. All right, so this is our plan for our time together today. First, we'll define the monogenic contribution to cystic kidney disease and review the value of genetic testing for this clinical indication. Second, we'll summarize the key findings from a retrospective study of patients receiving multi gene panel testing at Blueprint Genetics and compare that to recent literature. And then ultimately we'll discuss features to consider when assessing panel test options for cystic kidney disease. Let's go and 1st define what we mean by cystic kidney disease. So we're on the same page. So cystic kidney diseases are characterized by the formation of cysts in one or both of the kidneys. Cysts are stacks filled with fluid or another semi solid substance and are considered generally non cancerous neoplasms or abnormal tissue growth. They can cause problems on their own, but they can also cause problems if they rupture or become infected. Cysts on the kidneys are typically diagnosed via imaging like ultrasound or CT, or Mr. Is this also, this type of imaging often accompanies things like urinalysis and blood work to assess analytes that can indicate how the kidneys are filtering our blood. And there's some instances where more invasive diagnostics are needed, like kidney biopsy. The presence of just one cyst is not necessarily indicative of cystic kidney disease. It's really possible to develop a renal cyst at random. But the cystic kidney diseases that we'll talk about today most often presents with numerous cystic kidney, numerous cysts in your kidneys over time. The main issue in cystic kidney disease is that over time these cysts start to replace normal functioning kidney tissue. So you can imagine that as the cystic burden increases in both sides and number, more and more normal kidney tissue is replaced by, you know, by our cystic kidneys. And this impairs our kidneys ability to filter our blood and work as expected. You'll see on the picture on this slide, they as the kidneys become more cystic, they can also grow beyond their normal size. And the normal size of the kidneys are approximately the size of your fist, right. So this enlargement can lead to physically impeding and affecting nearby organs. Cysts in certain parts of the kidney, though, can also cause the kidney to shrink, which can impair function in its own way. And overall, increasing cyst burden on the kidneys leads to increase impairment of renal function. The cyst can be drained or surgically removed, but a lot of patients that progress to advanced kidney disease leading to kidney failure can be placed on dialysis or require a kidney transplant. The thick kidney diseases are collectively one of the most common causes of advanced kidney disease and kidney failure, and we see estimates of up to 25% of patients with advanced kidney disease having genetic causes for their condition. These estimates are really based on both registry data like the European Rare Kidney Disease Registry, and also specific cohort studies from various institutions globally. In general, children or adolescents with advanced kidney disease are thought to have a higher probability for a genetic etiology than older adults with advanced kidney disease. But of course, there can be certain presentations that can indicate a likely genetic etiology. Today, we'll focus solely on monogenic etiologies of cystic kidney disease. Monogenic meaning that variance in a single gene is causing the cystic kidney disease. These monogenic conditions can be inherited in autosomal dominant, recessive and excellent manners and cystic kidney disease due to the interaction of like multiple genetic and environmental factors is out of scope for today's discussion. There are several monogenic conditions associated with cystic kidney presentations and these can generally be separated into the two groups that you see here, the ciliopathies and the focalmatosis. The ciliopathies include conditions like polycystic kidney disease, both autosomal dominant and recessive forms, nephronothysis, autosomal dominant, tubular interstitial kidney disease which was formerly known as medullary cystic kidney disease if you're more familiar with that term. These conditions, these ciliopathy conditions really are a result of the non motile cilia present in the nephron being impaired. These cilia normally have a sensory function to initiate cell signaling, but the impairment of sensory cilia can lead to fluid not moving as expected, which can cause the formation of both kidney cysts and fibrosis or scarring in those kidneys. If we think about the ficomatosis, they include the tuberous sclerosis complex, von Hippel Lindau syndrome and Dicer 1 related conditions. These are conditions that affect tissues originating from the neuroactoderm during embryonic development. Neuroactoderm, namely tissue drives, namely the nervous system, the skin, the eyes and this is due to dysregulation of key cellular growth pathways which generally leads to over activity and then the formation of cyst and other growth. Let's focus on the most common of these genetic kidney conditions for a second and this is polycystic kidney disease or PKDE as we call it. As mentioned, PKD can be inherited in an autosomal dominant or recessive manner. If we think about autosomal dominant PKD, this effects one in 400 to up to 1 to one in 1000 people worldwide. It accounts for at least 10% of those patients we talked about with advanced kidney disease. When we think about autosomal recessive PKD, this condition effects less individuals, one in 20,000 individuals worldwide, which means really that the carrier frequency of this recessive form of PKD is approximately 1 in 70 individuals in the general population. As autosomal dominant PKD is one of the most common cystic kidney presentations. I just want to highlight a little bit more about this further. We know that variants in many different genes can cause autosomal dominant PKD. Around 70 to 80% of of ADPKD are due to genetic variants in PKD 1 and cases due to PKD 1. Variants are also associated typically with more severe disease than other forms, meaning earlier age of onset or earlier age of diagnosis and potentially earlier age of onset of potential kidney failure. The second most common cause of ADPKD is PKD 2. This is attributable to about 15% of individuals with this clinical diagnosis and in general, the presentation of ADPKD related to PKD 2 variance is thought to be more mild when compared to PKD 1. About half of individuals who reach their 7th decade of life may reach it without kidney failure as opposed to PKD one where most most individuals who reach their 7th decade. Do you have kidney failure. However, you might be most familiar with PKD 1 and PKD 2 as causes for ADPKD, but more recently in 20 and 20 22, the IFT 140 gene has been identified to cause approximately 1 to 2% of ADPKD. The typical presentation is a mild PKD phenotype using usually consisting of a few larger cysts that can result in kidney enlargement. We also see some other genes contributing that are more rare causes of this condition that that are listed on the screen below this they account for less than 1% of ADPKD each and varying clinical presentation. So when we think about ADPKD, even one of the most common presentations of cystic kidney disease, we see many genes that are causing this one condition. Apart from the kidney cyst, which is what we focused on so far, we also see many extra renal features in ADPKD. These includes this and other organs like the liver and the pancreas. Individuals with PKD can also have cardiovascular involvement like valvular disease, most commonly mitral valve prolapse and left ventricular hypertrophy due to persistent hypertension if left untreated. Also, the prevalence of intracranial aneurysms is about fivefold higher than in the general population and further increase in those with a positive family history. The mean age of rupture of these intracranial aneurysms is lower an individual with ADPKD than in the general population as well. And we also see things like male infertility arising rarely due to cysts in the Seminole vesicles or issues with sperm motility. Not every individual with ADPKD is going to have all of these extra renal features. There's substantial clinical variability in the presence and severity of these features even among individuals with ADPKD. And just to bring it back to, you know, our discussion of all kinds of cystic kidney presentations, it's not just ADPKD where we see that type of genetic heterogeneity and clinical heterogeneity. So here I'm showing you that same grouping of cystic kidney conditions that we've previously seen, all associated with kidney cysts of course, but now highlighting some of the most common genes associated with these conditions and that's highlighted below each condition in blue. Extra renal manifestations are common in individuals with these conditions too. We see several eye and neurologic symptoms can be present in individuals with both isolated and syndromic nephronolysis. We see endocrine involvement in the form of maturity onset diabetes of the young or Modi in the autosomal dominant tubulo interstitial kidney disease related to variants in the H and F1 beta gene. You may also be familiar with the characteristic skin abnormalities of the tuberous sclerosis complex and increased risk for various malignancies with those conditions listed in the ficomatosis. Despite all of this genetic and clinical heterogeneity, really genetic testing has not historically been a part of the diagnostic work up for cystic kidney diseases. They have traditionally been diagnosed based on clinical presentation, imaging studies, and in some cases, you know, a positive family history. There have been potential barriers, barriers to the adoption of genetic testing and diagnostic workflows. This includes the cost of testing, a lack of perceived clinical benefit, uncertainty about what genetic test to choose or which patients might benefit from testing, and generally unfamiliarity with interpretation and the complexity of genetic results. However, we do see this changing. Today, more nephrologists and other renal specialists are incorporating genetic testing as a routine part of their practice. A lot of times, due to this clinical and genetic heterogeneity seen here, this is also likely happening as more evidence mounts to show that there's clinical utility and uncovering A precise molecular etiology. Even in individuals where clinical diagnosis may have historically thought to be straightforward, knowing the causative genetic variants can inform monitoring for extra renal features. As we just discussed, referrals for evaluation of these features known to be associated with specific genes can aid both in the prognostication for patients and also lead to proactive management of these features. It's also useful in clarifying the inheritance pattern of the condition to determine who in the family may be at risk. This can particularly benefit individuals without a positive family history to date or for individuals where the desire is for prenatal or pre implantation genetic diagnosis right in the near future. Additionally, uncovering precise genetic causes can aid in selection of a related but unaffected kidney donor in applicable clinical situations. Of course, and increasingly we also see the use of genetic testing results in identifying potential therapeutic targets or relevant clinical trials. And in recognition of this potential utility gained with identifying molecular etiology, the consortium called the Kidney Disease Improving Global Outcomes released a recent guideline that incorporate that suggests that incorporating the causal gene into the disease nomenclature for individuals diagnosed with ADPKD at least have is helpful. And so they share that in people with ADPKD with a pathogenic variant and either PKD 1, PKD 2 or a minor gene of which we've discussed them for pathogenicity is well supported. The nomenclature should include ADPKD followed by the gene name, and an example of this is using a DPKD dash PKD one to describe the condition of a patient who's clinically diagnosed with a DPKD. But we know that their causative variant is in PKD 1. If you're looking at this figure on the screen I'm showing here, the example I just shared using like a DPKD dash. PKD 1 is in the middle flow of this diagram detailed in figure one of the Torres paper. I'll draw your attention now to the outside flow paths here which shows people who have an ADPKD spectrum phenotype that have not had genetic testing or with no pathogenic variant in ADPKD in their gene identify in a gene identified or who have a variant in a minor gene for with pathogenicity remains uncertain. These should these individuals should continue being termed as just having ADPKD and not including the gene information in their disease nomenclature. But really the benefit of this nomenclature and including the gene allows the maintenance of familiar like both the familiar name of the disease ADPKD but also can imply the characteristics associated with the specific causal gene. So for example, knowing that a patient is affected with ADPKDP due to PKD, one could imply a more severe presentation and higher risk of kidney failure than ADPKD due to a more minor gene. And this proposed nomenclature has been further proposed beyond autosomal dominant PKD in some recent publications. You can see here a table from a recent publication by Stark and colleagues that are proposing similar nomenclature across many other forms of renal disease that are genetic. So genetic testing to investigate molecular etiology of rare disease is typically done using what we call exome targeted short read next generation sequencing technology, which is quite a robust methodology. As many of you may be familiar, the typical workflow start starts when a patient sample arrives to the lab and the DNA is extracted and fragmented into small pieces. These small pieces of patient DNA attached to targets from protein coding parts of the genome, which is called the axiom. The sequence of the bases in many different fragments of DNA is read simultaneously and generates short reads of usually about 50 to 300 DNA base pairs long. There's some quality control steps that are in place to check that sequence read data to make sure they can confidently be taken to the next step of analysis. And then the sequence reads are aligned to the reference genome and variants are called and annotated. Then analysis is done on the genes requested by a team who specializes in clinical interpretation of genomic data. And finally, a report is generated to communicate results to the clinician who ordered the test. This type of methodology allows for both sequence and copy number variants to be called in protein coding axons of DNA. Sequence variants are changes that are just one or a few DNA bases, and copy number variants are changes that delete or duplicate larger portions of DNA. Both types of variations can be seen in individuals with genetic form of cystic kidney disease and this methodology is in a is really effective in finding many molecular causes of disease and it's the methodology that we use at Blueprint Genetics. I bring this up because the accessibility and efficacy of genetic testing as a tool for patients undergoing evaluation for cystic kidney disease has really evolved over time. Historically, genetic testing for cystic kidney disease was limited to like sequential testing of a small number of genes. Maybe you'd start with PKD 1 and if no variants were found you'd, you know, progress to doing sequencing of PKD 2 and so on. Also detection of sequence variants and of copy number variants was also was often done separately using different technologies. This sort of stepwise approach to genetic testing was both time consuming and costly. But as the number of genes that we've been associated with cystic kidney disease have grown, the sequential approach really is becoming prohibitive. Now multi gene panel testing is the most common approach recommended for genetic testing in this space. And this is done using only really I'm able to be done using that exome targeted short read next generation sequencing that we discussed in the previous slide. On this slide, we see a quote from the international consensus statement published by Gimple and colleagues and they share that they currently recommend next generation sequencing panel examination rather than testing single ADPKD genes because of the large phenotypic overlap between cystic kidney diseases and large amounts of genetic heterogeneity. They really in this guideline and I suggest that that you definitely dive in if you're interested. They go on to suggest that cystic kidney disease panels should include adequate coverage of PKD 1 and PKD 2, but also genes associated with more rare cause of both ADPKD and other forms of cystic kidney presentations including autosomal dominant tubular interstitial kidney disease, the nephronthiasis and more. So here at Blueprint Genetics, we do offer two curated panels for the investigation of cystic kidney disease, sort of in line with the recommendations of multi gene panel testing. Our polycystic kidney disease panel includes 13 genes related specifically to abysmal dominant and recessive causes of PKD and some cystic liver disorders. The broader cystic kidney disease panel looks at 43 genes in total, including all genes on the PKD panel plus others associated with groupings of cystic kidney disorders that we had previously discussed. This panel includes analysis of both sequence variants and copy number variants. And while we target mostly the coding regions of the genes, we sequence and analyze up to 20 base pairs into the intron Exxon boundary and also target some known disease associated variants in the non coding space. The gene content on our curated panels is customizable, so there's the ability to add or remove genes of interest. And I'm pleased to share with you that we conducted a recently a cross-sectional retrospective review of results of our PKD and cystic kidney panel testing. And we'll share some of these key findings with you throughout the next few slides. If it helps to Orient you visually, it does for me. Watch for the blue background on the title of any given slide. Moving forward, this will indicate that the data presented on these slides are scientific insights from our study. A manuscript sharing these details have have also been recently accepted into the journal Kidney Medicine. And the QR code that you see on the screen will take you to the online article, which is impress. This QR code will also appear on slides moving forward for your convenience. So let's dive in to the study. Here we investigated findings shared on the genetic testing reports for 12135 patients across the globe receiving panel testing for an indication of cystic kidney disease. Patient facts as indicated at the by the clinician at the time of the test order was female in about half of reports, male in almost half of the reports, but unreported in 2% of reports, which were most often in the case of fetal testing and I'll discuss this further as we go. The cohort was made-up of fetal samples in addition to pediatric and adult samples. We've defined pediatric as up to age 19 and adults like further than and of course fetal samples being those tested before birth. 34% of the reports were from patients receiving the larger, more broad cystic kidney disease panel and 66% of these are the individuals had received the polycystic kidney disease panel. So results from this analysis really showed that panel testing is quite a powerful tool. A positive result in a gene associated with cystic kidney disease was identified in almost half, so 49.4% of patients patient reports in this cohort. And so for the purposes of this study, we wanted to define the that a positive result is the identification of 1 pathogenic or likely pathogenic variant consistent with the patient's reported phenotype in genes associated with dominant or excellent conditions. And then, of course, or two pathogenic or likely pathogenic variants consistent with the patient's reported phenotype in genes associated with recessive conditions. Of note, this means that cases with a single heterozygous pathogenic or likely pathogenic variant in genes associated with only an autosomal recessive condition were not included among those who that are defined as positive results. These findings really of, you know almost half of the cohort receiving a positive genetic test result compares to what we see in the literature. So we do see cohorts receiving genetic testing for an indication of cystic kidney disease or a broader indication of chronic kidney disease ranging from about 48 to 53% across the literature. These high positivity rates in our study, in addition to others in the public published literature to date probably represent a slight bias in offering panel testing to patients with a more compelling clinical presentation or family history and therefore a higher a priori risk of an underlying genetic condition. If you, you know, we're testing individuals with without these compelling family histories perhaps and and personal histories, then perhaps the positivity rate would be lower. We did see a significant relationship between the frequency of positive results associated with autosomal recessive conditions and and the and the age group tested. As you can see from this figure that we've put at the bottom of the slide here, the fetal case group had the highest proportion of positive results related to autosomal recessive disease compared to pediatric and adult groups. This is somewhat expected given that cystic kidney diseases with autosomal recessive inheritance can often present with earlier onset. So we'd like to further use these results of the study to highlight some of the key factors to assess when selecting A genetic test for the investigation of cystic kidney disease. Given that we know there's lots of options available for panel tests across laboratories. These include the gene content of the panel, the laboratories technical capabilities in being able to resolve challenging genomic regions, the test sensitivity to detect copy number variant, and the laboratory reporting policies with respect to variance of uncertain significance or the USS. I'll walk through each of these factors in the coming slides. And it's helpful for individuals ordering genetic testing really to recognize the potential variability between panel test options when looking to investigate cystic kidney disease for your patients and understand the implications of the differences when selecting your test for your patient. Really this can help you, you know, maximize diagnostic potential for patients, but also accurately interpret a negative result to know potentially if further testing is needed. First, let's explore together the factor of gene content in a panel. So it's fairly well known really across genetic indications, but also for cystic kidney disease that panel panel gene content can vary between laboratory. Here's a figure from a recent publication by Gateau and colleagues and it shows specifically the variability in gene content of kidney disease panels from laboratory clinical laboratories registered in the genetic testing registry. Just to Orient you to this figure, the orange bars on the scale on the rightmost axis represents the number of genes included in a polycystic kidney disease panel from these different laboratories. This is typically the more narrow indication, right, the polycystic kidney disease panel and really this, these range from about 5 genes to over about 40 genes in these polycystic kidney disease panels. While let now let's focus on the blue bars and the scale on the leftmost access. And this represents the number of genes included in a broader kidney disease panel. Notably, not just maybe a cystic kidney disease panel, but potentially even more broad to like span all hereditary kidney diseases. And the estimates here, like really the showings of the number of genes included on these panels range from over 40 genes to over 500 genes. There isn't necessarily one right approach to selecting gene content for a panel test. This, like wild variation typically exists due to the differing definition of what's in scope for a particular clinical indication or the needs of the patients and preferences of those providers initiating genetic testing for patients. So there's a lot of times there's something for everyone out there. For example, a lot of these questions might cross your mind or a lab's mind when they're trying to determine what gene should go on a panel you know. Should the genes on the polycystic kidney disease panel only include those with one particular pattern of inheritance or be limited to the most common genes causing disease? Or should it include all known genes associated with all forms of polycystic kidney disease? Specifically, what about gene those genes associated with disease mimics, meaning that those that can present in with multiple this in their kidneys, but may not be strictly classified as polycystic kidney diseases? Should it include genes with well established gene disease associations only? Or what about genes that have more limited or emerging evidence in association with PKD? As you can see, everyone's navigating the answers to these questions and really labs are doing this with the help of the individuals using the genetic test to investigate cystic kidney disease and, and input there to further add to, you know, the complicating factors. Genes associated with kidney disease continue to emerge in the published scientific literature and clinical genetic testing. Labs will assess these proposed gene disease associations for validity using a process called gene curation. Gene curation can be useful in so many ways, including within this topic that we're discussing what genes fit into a lab's intended scope of their curated panels. Gene curation can power publicly available tools that you might be familiar with, such as the Genomics England Panel App and Panel App Australia. And on this slide here, the end. This intentionally busy figure from the Gateau paper that we talked about in the last slide shows the many steps that go into the curation of a gene disease association to understand the evidence posed and determine the validity of the association. This is often a fairly intensive process of literature review and mining public databases containing valuable genetic and experimental information. Really the goal and the outcome of these gene creation processes can include assigning A classification to a gene disease association and to communicate the validity through that classification and the strength of the association. Across the world we see many frameworks have been developed to perform gene curation and one of the most well known is called the Klingen framework for assessing gene disease validity. At Blueprint, our gene curation process is based on the principles of the Klingen framework and currently there's international efforts underway to harmonize gene creation efforts through a coalition called the Gen. CC. As you can imagine, gene curation needs are constant. It takes time and, and, you know, effort to keep up with assessing emerging gene disease associations and for many clinical labs then to perform these curations and determine if the genes fit within the intended scope of their curated panels and to update that panel content if appropriate. This is another source of variability in that gene content across panels targeting similar clinical presentations, including those with cystic kidney diseases or, you know, broader hereditary kidney diseases. And we know gene content can certainly influence potential results from panel testing. So as you can see on this slide from our retrospective review, we confirmed the genetic heterogeneity of cystic kidney diseases. Really positive results in this cohort spanned 468 pathogenic or likely pathogenic variant in 20 unique genes. Looking at the rightmost column of this table, you'll see that the most common genes in which positive results were identified included PKD 1, PKD 2 H and F1 beta and PKHD one and then 16 different genes each contributed to 1% or less of the total positive results, but cumulatively represent almost 7% of all positive results. These data can collectively show that panel testing can evaluate for common and rare molecular ideologies simultaneously, which I think is what a lot of the guidance around, you know, doing these multi gene panel testings is based around. I'll draw your eye now to the PKD one most common finding here. When we stratify the causative gene by the mode of inheritance, we see that about 71% of positive results in this cohort amongst genes with autosomal dominant disease were due to PKD 1. This reflects really mirrors the information that we previously discussed that PKD 1 underlies about 70 to 80% of clinically diagnosed ADPKD. One consideration to keep in mind while viewing these data here, in the study. The IFT 140, ALG 5 and ALG 9 genes associated with ADPKD were not standardly included in the blueprint curated panels. So you're not seeing. Any positive results in these genes, not because there were none and they were tested, but because these genes were not tested as part of this study. Really given the potential morbidity and mortality really related to the extra renal features that we see in these heterogeneous genetic conditions associated with cystic kidney disease in this cohort, I think it's pretty important to have an understanding of the genetic etiology of an individual cystic kidney disease. So think about all these individuals that we see with the H and F1 beta findings. This is associated with variably expressed renal cysts and diabetes syndrome. So if really if these individuals identified are not already cared for by an endocrinology specialist, these individuals may benefit from referral to endocrinology for assessment for or maybe even but you know, personalized management of their maturity onset diabetes at the younger Modi. It's also important to recognize that management implications for like something like a biological female with cystic kidneys due to a variant in OFD 1 gene associated with the variably expressed oral facial digital syndrome type one. This can be dramatically different than for those with a biological female with cystic kidney disease due to ovarian and say, PKD 2. The individual with OFD one could warrant additional referrals to specialist to be evaluated for neurological, skeletal or oral extra renal features. And also this is an excellent condition that is typically gestationally lethal and affected males. And therefore this information just about inheritance alone has significant impact on the reproductive care and counseling for families of affected women. In this study, we also looked at the frequency of positive results across age groupings at the time of testing. We see that the genetic heterogeneity really falls across groups, age groups. This highlights the possibility for panel testing to be helpful even when clinical diagnosis seem straightforward. For example, while it's recognized that ADPKD can be presented can present prenatally, it's most often expected to present in adulthood and therefore might not be considered a likely diagnosis when considering the differential for a fetus with cystic kidneys on imaging. However, we see here that more than half of the fetal diagnosis in this cohort were due to variance in PKD 1 and H and F1 beta. These are genes responsible with other the most dominant forms of cystic kidney disease. The known diversity in age of onset and potentially complex clinical presentations of cystic kidney disease really reinforce the importance of including all genes with both autosomal dominant and recessive conditions when selecting your panel testing for to maximize precision molecular diagnostics. Let's now discuss the importance of knowing the capabilities of the laboratory to resolve technically challenging regions. And here we'll explore the example of PKD, one which we you may know is a challenging gene to sequence via short read next generation sequencing. This is challenging due to its large size and high GC content, but quite importantly it's also really difficult to sequence because of the interference of 6 partial pseudo genes. Pseudo genes are those segments of DNA that resemble a gene that's functional, but they don't code for a functional protein. They do have a similar sequence to this functional gene though, and we term this sequence analogy. PKD 1 Pseudo genes are over 90 to 99% identical to the PKD 1 gene in certain regions and due to that high similarity when you're sequencing PKD one, it can be difficult to tell if the sequence that you're reading is from PKD one or from one of these non functional pseudogenes. Pathogenic variants are found in all regions of these genes, including those that have sequence homology to pseudogenes. And clinically this is really significant. If you happen to find a genetic variant in a patient, sorry about that. If you you might find a genetic variant in a patient, it could also be a variant in PKD, one that disease causing, but it could also be a part of the pseudo gene. So confirming really which if it is part of the the gene or part of the pseudo gene is a really important part of things. This slide shows how the degree of that sequence homology in pseudo genes can really confound read mapping using short read NGS. As a reminder here, once sequences are generated from patient data and short read next generation sequencing, they're then aligned with a reference sequence and this is the inequality threshold is applied to this alignment process which is referred to as mapping quality. A parent gene and a pseudo gene with only 70% homology will have sequences that are different enough from each other so that when it comes time to align the parent reads with the reference sequence, only the parent gene reads will like align to the parent gene in the reference sequence. But as sequence homology increases closer to 98% sequence homology, this becomes more problematic. Really, when the sequence are similar enough, they might actually be aligned in the parent gene to the reference sequence with less accuracy, and you might either see a false negative if the patient has a variant in their parent gene but the read does not align to that reference sequence. Or on the other hand, you can get a false positive if there's a variant in a pseudo gene and the pseudo gene maps read maps to the reference sequence instead. This further increases in areas of the genome that are nearly 100% similar. Labs can really optimize PKD one coverage though leveraging the small differences in sequence within those homologous regions. Blueprint Genetics has done a lot of work to improve the coverage of this challenging gene using this methodology, using 2 important steps in the library prep and the target capture steps. In this screenshot of read data from a sequence the our sequencing of PKD 1 you it shows a short read pile ups and resulting depth of coverage across the genome. The most challenging regions are in Exxons 1 to 33, which you saw on the slides earlier and you can see that if you know your laboratory or your test is done using Capture Kit one or Capture Kit 2 as represented on this screen, you might have very limited read data across those exons of this of PKD One. However, you can see with capture three with our current blueprint whole XM sequencing capture that there is uniform coverage across these this gene and the most challenging you know areas of of this gene as well. We look at the performance of 380 samples that analyze PKD 1 and we see that we have a coverage of 99.6% at over 20X at a map and quality of 20 and a mean depth of 205 reads. This This work really allows us to have more confidence in reducing the likelihood of a false negative due to gaps in coverage and to help minimize the potential of false positives. PKD 1 next generation sequencing variants are confirmed orthogonally if they don't meet our robust quality metrics when detected on via next generation sequencing initially. This optimization of PKD 1 is important and we can see here in our cohort study that variance in PKD 1 contributed to about 65% of of findings in our study. So specifically of these PKD 1 related positive results, most of them were sequence variants. And we see 3 PKD 1 related positive results that were a signature of several rare missense variants in the same region indicating a potential gene conversion between PKD one and the pseudo gene PKD 1P3. These findings that were initially seen on next generation sequencing were confirmed via Singer sequencing and really the, you know, high positivity rate here in EKD 1. And you know, the the potential for identifying these complex findings highlights the importance of both the sensitivity of variant calling, I think and then the use of orthogonal strategies and confirming findings. And to drive the point home even further, notably we see about 76% of positive results in PKD 1 affecting exons. You know one through 33 of the main coding transcript for this gene, which if you remember are the axons impacted by sequence homology ranging from 90 to 98%. This is striking as a laboratory who offers panel testing but hasn't optimized their methodology in PKD one to account for the sequence homology regions could really be missing detecting important variants here and again, optimization of of this of PKD 1 sequencing can include improving read alignment and variant calling by customizing your assay and confidently capturing the differences in these, the small differences and sequences and also includes confirmation of called variants that don't meet robust quality metrics. So next let's move on to the importance of knowing the sensitivity of the test to be able to detect copy number variant, those those variants that are missing or extra pieces of DNA. We know that copy number variants come in many different sizes, from a segment of DNA that ranges 50 base pairs to several mega bases, and in general identifying larger copy number variations are considered easier than detection of smaller copy number variations. Calling these small, maybe introgenic copy number variants will require often require specialized bioinformatic tools and most genetic testing laboratories providing panel testing for the indication of cystic kidney disease are including copy number varying analysis alongside sequence varying analysis. But it's important to ask questions about their sensitivity to detect copy number of variants of all sizes, especially those tricky ones in the smaller, the smaller tricky ones like those that are under 4 exons or under 1000 base pairs in size. And while the frequency of CN BS in patients with cystic kidney disease have really not widely been shared or is available in the medical literature, we do know that copy number variants are a mechanism of of genetic forms of cystic kidney disease. We see in our retrospective study that almost one in 10 positive results in this cohort included a CNV, and with an eye to these small CN BS, we see about 30% of deletions identified as positive results consisting of four exons or less. Interestingly, the individuals identified to have the smallest deletions, about 200 to 400 base pairs also had negative prior testing including PKD one analysis at other laboratories. Blueprint uses a specialized in house developed bioinformatic algorithm to assist in the calling of the small copy number variants and in general, this really shows the importance of ensuring CNB analysis is a a part of your panel test and B optimized to to detect even small CN BS as well. Last, let's consider the value and understanding laboratories reporting policy for variance of uncertain significance termed VU s s. You're you may be aware that most laboratories use these ACMG and AMP guidelines for variant classification, which results in variance being classified as pathogenic, likely pathogenic variants of uncertain significance, likely benign or benign, and this really communicates the likelihood that the variant is associated with disease. A variant classification of the US means there is insufficient or conflicting evidence to classify it as either pathogenic or benign, and really means there's not adequate information to confirm or deny its role in causing disease. Which variants are reported back to the ordering clinician on the laboratory reports really depends on laboratory policy, and often this can include consideration of variant classification. Some laboratories will only report out variants classified as pathogenic and likely pathogenic, and the variability in these reporting policies could result in a variant being excluded from a report if it's currently classified as of the US We know that variant classification is dynamic and can change over time as evidence accumulates, and so recognizing the potential for an evolving variant classification can help maximize the opportunity for a positive result. We may wish to identify a particularly suspicious the US and you know, that might prompt next steps, which we'll discuss in a second. And we really encourage the discussion of variant classification criteria with the testing laboratory as this may, you know, produce, you know, further insight and steps to take in the future. And here in our study, we see that suspicious variance of uncertain significance can be commonly represented in reports labeled as inconclusive. And these results really may benefit from follow up. So of inconclusive reports in our study over half had a suspicious V last. And we have defined inconclusive reports as where a report where variants were included on a patient report, but they didn't meet criteria to be called a positive result. For the purposes of these studies, an inconclusive result is defined differently than a negative result where there was no variance reported on a patient's report. Suspicious the US is often benefit from relevant family member testing and showing that a variance de Novo in a patient or confirmation that variance are likely in trans could lead to reclassification of of the US to LP. For example, in 11 inconclusive reports, a heterozygous suspicious VOS in PKHD, one associated with autosomal dominant autosomal recessive disease was reported in addition to a heterozygous pathogenic or likely pathogenic variant in the same gene. And parental testing to help determine if these are on different parental alleles or intrans would result in a suspicious VOS being reclassified to likely pathogenic and thus a positive result this. The implications of the US and. Organizing family member testing may be daunting for some clinicians, but enlisting the expertise of trained medical genetics professionals like genetic counselors can be really helpful in organizing family testing and understanding what individuals might be helpful for analysis. Labs can help with this understanding of which in individuals might be helpful as well. All right. So overall, the results of our retrospective analysis really highlight that carefully curated and optimized next generation sequencing based panels offer clinicians A valuable resource to investigate molecular etiology for cystic kidney disease. And we really suggest that panel testing options should be carefully evaluated prior to test ordering for factors including relevant gene content capability for technically challenging genes like PKD, one sensitivity to detect copy number variance, especially those under 4 exons in size, and the laboratory policy for reporting variance of uncertain significance. Thank you so much for your engagement on behalf of the entire Blueprint Genetics team. Ty and I know we're tight on time for questions, but wanted to open it up. Yeah, thank you, Alice, excellent presentation. OK, we can take one question because this is a very good one. OK. Thank you for the information about suspicious versus and the availability of family testing. Can you share what type of woos results most commonly benefits from family member testing, meaning reclassification from woos to pathogenic or likely pathogenic, and what family members would need to be involved? Oh OK. Yeah. So good to to dive into this. Really I think it comes down to two things. Identifying those variants in recessive disease. If one is pathogenic and likely pathogenic and the other is of the US, then familial segregation data can really determine if they're in this or in trans, meaning the same parental alleles are different one. And if there's really like, if there's data to support that these variants are in trans, then we can likely add this as a piece of evidence towards pathogenicity, which could then reclassify the variant to pathogenic or likely pathogenic. That was the example that we used of PKHD 1. But also when you identify a variant in association with dominant disease, this is and this is classified as of the US. Sometimes determining if the variant most likely occurred to Novo in the patient, so absent from their parents can lead to like another piece of evidence which can lead to reclassification. So those are the the most common scenarios that would result in reclassification. And most often the family members that are most helpful are either parents or an offspring, but sometimes can be, you know, additional individuals in the family. And it's a really great idea to connect with the genetic testing laboratory that you know has, has done the the testing. If you have questions about, you know, what would be most helpful in with respect to variant reclassification and showing the variant segregation within the family. Does that help? Yes, thank you, Alicia. So once more excellent presentation and, and thank you and thank you for all participants and I hope that everybody has great rest of the week. Thank you. Thanks so much, Tina. Thanks everyone. Have a great day.