The Genetic Landscape of Hypertrophic Cardiomyopathy (with Echocardiography Cases)

Hypertrophic Cardiomyopathy: Unmasking the Molecular Mysteries

Hypertrophic cardiomyopathy (HCM) stands as one of the most prevalent genetic cardiovascular disorders, characterized by the abnormal thickening of the heart muscle, especially the left ventricle. Despite being recognized for over a century, the intricate genetic architecture underlying HCM has remained a subject of intense scientific inquiry. Recent advancements in genomics have paved the way for a deeper understanding of the molecular mechanisms driving this condition, offering hope for more precise diagnostics and targeted therapies.

Watch these Echocardiography Videos of HCM, and its variant known as Yamaguchi syndrome:

 

 

The Genetic Code

HCM exhibits a complex inheritance pattern, with the majority of cases arising from mutations in genes encoding sarcomeric proteins, the fundamental components of cardiac muscle contraction. Genes such as MYH7, MYBPC3, TNNT2, TNNI3, and others have been implicated, with mutations altering the structure and function of these proteins, ultimately leading to hypertrophy and impaired cardiac function.

With the advent of next-generation sequencing (NGS) technologies, researchers have been able to comprehensively analyze the genetic landscape of HCM. Whole exome sequencing (WES) and whole genome sequencing (WGS) have enabled the identification of rare variants and novel genes associated with the disease, shedding light on its underlying genetic heterogeneity.
 

From Bench to Bedside

Understanding the genetic basis of HCM has profound implications for clinical practice. Genetic testing has emerged as a valuable tool for diagnosing HCM, especially in cases where the clinical presentation is ambiguous. By identifying pathogenic mutations, clinicians can not only confirm the diagnosis but also provide valuable prognostic information regarding disease progression and the risk of sudden cardiac death.

Moreover, genetic testing plays a pivotal role in familial screening, enabling the early detection of HCM in asymptomatic relatives of affected individuals. This allows for timely interventions and personalized management strategies, such as lifestyle modifications and pharmacological therapies, aimed at mitigating the progression of the disease.
 

Challenges and Future Directions

Despite significant advancements, challenges persist in our quest to decipher the genomics of HCM. The clinical interpretation of genetic variants remains a formidable task, particularly in the context of rare or novel mutations with uncertain significance. Additionally, the variable penetrance and expressivity of HCM-associated mutations further complicate their clinical interpretation and management.

Furthermore, while sarcomeric genes account for the majority of HCM cases, there exists considerable genetic heterogeneity, with non-sarcomeric genes also implicated in the pathogenesis of the disease. Exploring these non-sarcomeric pathways may uncover novel therapeutic targets and expand our understanding of HCM beyond its traditional molecular framework.
 

Conclusion

The genomics of hypertrophic cardiomyopathy represent a fascinating and rapidly evolving field of study. Through collaborative efforts between researchers, clinicians, and geneticists, we continue to unravel the molecular mysteries underlying this prevalent cardiovascular disorder. As our knowledge deepens and technologies advance, the translation of genomic insights into clinical practice holds the promise of more accurate diagnostics, personalized therapeutics, and improved outcomes for individuals affected by HCM.

Before we embark further on our discussion watch these echocardiography clips and try to diagnose the type of Hypertrophic Cardiomyopathy:

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 Expert Reviews on Genomics involved in HCM:

Welcome to our session on review of cardiovascular genomics, as well as an overview of the genomics of metabolic syndrome. We welcome all of you to this article, and just a reminder, it is a deep dive. So briefly, to introduce all of those speakers, the first speaker is Shu-Fen Wung. Dr. Wung is an associate professor of nursing at the University of Arizona, and her program of research has been focused on the assessment and management of common cardiovascular diseases resulting in myocardial ischemia and arrhythmias. Also presenting today will be Dr. Kathleen Hickey, and she is an assistant professor of nursing and a nurse practitioner in the Division of Cardiology at Columbia University. Her research is on the interrelated areas of arrhythmias, cardiogenetics, and the prevention of sudden cardiac death. And also of note, Dr. Hickey is currently the president of the International Society of Nurses in Genetics. Dr. Jacquelyn Taylor is also with us today, and she is an associate professor in the pediatric nurse practitioner specialty at Yale University School of Nursing. Her research has focused on addressing genomic health disparities and hypertension among African-Americans and West African families. And then lastly, but not least, is Dr. Matthew Gallek, who is an assistant professor in the College of Nursing at the University of Arizona, and his primary research has been examining the role of genetics and genomics on outcomes following brain injuries, including subarachnoid hemorrhage and ischemic stroke. So we'll turn it over to Dr. Wung and her colleagues.

Shu-Fen Wung: First I would like to thank the co-authors who contributed their expertise to this manuscript. [inaudible] is the leading cause of death worldwide. Genetics play a role in nearly all cardiovascular disorders. In this overview, we will briefly highlight the current knowledge on cardiovascular genomics using three examples arts [spelled phonetically]. I will be presenting genomics in myocardial infarction and coronary artery disease. Stroke genomics will be presented by Dr. Gallek. Dr. Hickey will present sudden cardiac death. And finally, Dr. Taylor will discuss health disparities between racial, ethnic, and gender groups that may have basis in genetic variation related to cardiovascular disease and its risk factor. Since 1990s there has been an explosion of studies examining genetic markers in myocardial infarction and coronary artery disease. [inaudible] linkage analyses of families, candidate gene approach, and genome-wide association studies. Using family base linkage analyses, several chromosomal regions harboring MI/CAD genes have been identified. However, identification of mutation only affected a single family or had no functional relevance in other studies. Worth mentioning is the linkage analysis performed by the DeKalb group, finding a peak at the short arm of chromosome-13 in Icelandic families with a history of MI. These researchers found an ALOX5AP gene associated with MI. The ALOX5AP genetic variants have been linked to heightened inflammation [inaudible]. Later on, these investigators reported that ALOX5AP gene was associated with CAD in British, and stroke in Icelandic and Scottish populations. Using the candidate-gene approach involved analyzed genes with presenting different pathways in the development of MI and CAD.

Since 1990s, association between greater than 150 candidate genes and coronary artery disease or MI have been analyzed. Among these, both positive and negative associations were found for nearly all genes, but reproducible associations are few. There are only limited genes affecting low-density lipoprotein cholesterol such as APO E [inaudible] has been shown to be associated with MI and CADs. The genome-wide association study approach genotypes the complete genome and has the potential to identify disease-associated markers in unknown genes. In 2007, three landmark GWAS studies identify a locus on the short arm of chromosome 9 associated with MI and CAD. Since then, several studies have confirmed the role of this locus on [unintelligible] for MI/CAD, making it the strongest and most replicated genetic effect on MI/CAD risks known today. The 9p21 locus only harbors a lone noncoding RNA. Researchers are actively investigating the role of this noncoding RNA in atherosclerosis. Most recently, a global consortium, the CARDIoGRAM, analyzed GWAS studies data from more than 20,000 CAD cases and 16,000 controls, and discovered 13 novel, as well as confirmed 10 previously reported chromosomal loci associated with CAD. The majority of these established and novel loci are not associated with traditional cardiovascular risk factors, and they are located in regions not previously suspected in the pathogenesis of coronary artery disease. This suggests that most genetic markers may act through novel pathways; however, these 23 loci are only able to explain a limited fraction of CAD heritability, about 10 percent.

This CAD are yet unknown. So, in summary, research is still ongoing to discover comprehensive genetic marker in MI/CAD. However, several commercial cardiovascular disease genotyping panels are being marketed to health care providers and general public. However, there is no consistency on the commercial genotyping panels so far. For example, the genes being tested are not readily available from this company. They do test heart disease, but there is no information on what genetic markers are being tested. With this company genotyping the 9p21 locus, and this company genotypes a panel of 23 genes. In summary, it is very important for nurses to understand current development of MI/CAD genomics, and the inconsistency in commercial genotyping panels so that information can be provided to patients and families interested in genetic testing. Matthew Gallek: Okay, stroke is the fourth leading cause of death. There are approximately 795,000 strokes a year. That's a stroke every 40 seconds. The direct and indirect cost is estimated at $38.6 billion a year, and about 6.8 million Americans have had a stroke in the past. Stroke is the leading cause of adult disability. These disabilities range from minor weaknesses to the need for skilled nursing homes. Eighty-seven percent of strokes are ischemic stroke, 10 percent are hemorrhagic, and about 3 percent are subarachnoid hemorrhage. Risk factors for stroke are similar to the risk factors for MI and CAD. These include hypertension, dyslipidemia, diabetes, obesity, and inflammation. Family history of stroke or MI also puts one at higher risk for stroke. In fact, the paternal history of stroke puts a person at higher risk for stroke than maternal history. In twin studies, a five-fold increase in stroke was seen in monozygotic twins when compared to dizygotic twins. The estimated prevalence of stroke are as follows: African-Americans, about 3.8 percent; Caucasians at 2.5 percent; and Asians at 1.3 percent. Most genetic research in stroke has been completed on Caucasians from North America and Europe. We are starting to see replicated data in other ethnicities such as Japanese and Chinese. However, we need to do more research in these other ethnicities. Genes that have been associated with stroke. For ischemic stroke, the 9p21 locus that Dr. Wung mentioned earlier, it was also associated with stroke. Apolipoprotein E, prothrombin, and ICAM are just a few of the other genes associated with ischemic stroke. With hemorrhagic stroke, it has been associated, again, with Apolipoprotein E, Factor 7, Factor 8, and endoglin, while subarachnoid hemorrhage outcomes, such as vasospasm, have been associated with eNOS and haptoglobin. For a more complete list of these genes, there was a review in the Annual Review of Nursing Research, Volume 29. In addition, some rare genetic disorders have been associated with stroke. This includes mitochondrial myopathy, encephalopathy, and Fabry disease. When there is suspicion of these rare genetic disorders, testing can be ordered by the health care professional. As with MI and CAD risks, the direct-to-consumer testing can be used to evaluate stroke, but at this time, it's inconsistent what they are testing for stroke. There are no clinically recommended genetic tests for stroke risks, and the ones that are out there continue to have the inconsistent results.

Now I would like to pass the presentation over to Dr. Kathleen Hickey. Kathleen Hickey: Okay, so let's begin. Sudden cardiac death affects approximately 1 million people per year. It's the leading cause of death in the world, and, in fact, most of the individuals who suffer an acute myocardial infarction die of sudden cardiac death. There is a broad category of inherited cardiomyopathies and channelopathies which account for some cardiac death in those under the age of 50. With the advent of the human genome and genetic etiology of many of these inherited cardiac monogenetic disorders, we now are able to test commercially by genetic testing for these disorders. Could you go to the next slide, please? The primary electrical diseases or channelopathies listed here, Long QT syndrome accounts for about 1 in 3000 people, Brugada syndrome accounts for about 35 out of 100,000 people, and those with other disorders such as CPVT or ARVD are other primary channelopathies. The chief characteristics and the clinical history is very helpful in those disorders where we are able to see very specific changes on the EKG. In the case here on this slide of Long QT syndrome, we see an up-sloping of the ST segments in Long QT Type 1. A common trigger for this disorder is swimming, and the incidence is about 30 to 35 percent of individuals. In the case of [spelled phonetically] Long QT Type 2, an auditory stimulation such as a loud doorbell or fireworks can account for this syndrome, and classically, we see a broad and flat T wave. In the case of Long QT Type 3 syndrome, this occurs commonly with sleep. It affects about 5 to 10 percent of the population. You can go to the next slide. So in regards to the channelopathies, or rather cardiomyopathies, excuse me, in this image what we see is, in Panel A, a hypertrophic cardiomyopathy heart from autopsy. You can notice the very thick and enlarged septum, and that's where, you know, blood and just volume is unable to be pumped effectively and efficiently. Hypertrophic cardiomyopathy accounts for about 1 in 500 individuals. Shown in Panel B is a normal heart, normal myocardial thickness, papillary muscles, and normal cavity size, and therefore normal function and contractility of the heart. Shown in Panel C is dilated cardiomyopathy.

This accounts for about 1 in 1,000 individuals, and you can really see the extreme dilatation that occurs of the vessels there. We now also are able to identify the genes associated with many of these cardiomyopathies, and test individual families for many of the mutations that are specific to individual members. The beta-myosin heavy chain and myosin-binding protein C genes account for the majority of inherited cardiomyopathies, and specifically, hypertrophic cardiomyopathy. Once we've identified a proband within the family who has no mutation, we are able to then test for other family members and do cascade screening. So, nursing implications. Nurses, as we know, play a vital and critical role in cardiogenetic testing, and are involved in the direct clinical care of patients and families. Nurses are on the forefront of obtaining EKGs, identifying potentially abnormal findings on the EKG, providing support, counseling, and education to patients and families, and they are certainly leading the way and being aware of many of the arrhythmogenic triggers and explaining to patients and families prescribed therapies for protection against sudden cardiac death. Some of these therapies may include beta blocker therapy or ICD therapy.

So, in conclusion, the channelopathies and inherited channelopathies have really been evaluated in recent years with the advent of the Human Genome Project completion and the availability of commercial and genetic testing. In all likelihood in the years ahead we'll see gene therapy and other advances in this area. Thank you for your attention. Jacquelyn Taylor: So, as you can see here, we highlight in our paper on Table 1 some of the ethnic differences that you can find in the genomics of cardiovascular disease, and some are even cited in some of the work that I do, such as some of the SNPs that are more deleterious for hypertension in African-Americans than in other ethnic groups. But I wanted to highlight some of the similarities that you can find as well within and between ethnic groups. So some that are highlighted in Table 1, you can find that there are similarities with the SCN5A gene and the SNC10A gene with African-Americans, Asians, Europeans, and that's with men and women. And in all of these groups you can see that there is an increased prolonged PR interval on electrocardiogram. And then other similarities include the SCARB1 gene, which results in increase cardiac -- CAC, common internal and carotid intimal medial thickness. And this can be found with African-American, Asians, Europeans, and Hispanic men and women. And then finally, another similarity that you find with Mexican women and Native American women are the FOCAD genes which result in increased heart rate. So one other point that I wanted to make with racial and ethnic differences is that particularly when you are doing genome-wide studies, that you should consider ancestry-informative markers when conducting work because we know that there is a lot of ethnic admixture, particularly with American populations. And that's all I have on this particular slide. Now I'll turn it back over to Shu-Fen. Shu-Fen Wung: So, in summary, genetic testing for common cardiovascular disease like MI and stroke is commercially available but not recommended for clinical use at this time; however, there are some academic institutes that do offer this in their clinic. However, I think health care providers need to know that genetic markers to comprehensively profile these diseases are still ongoing. On the other hand, genetic testing for long QT syndrome and hypertrophic cardiomyopathy can provide valuable information for nurses to tailor prevention and management strategies for individuals at risk for sudden cardiac death. We leave you some clinical resources that may be helpful when you want it to look for genetics related to cardiovascular disorders. Thank you. Female Speaker: So thank you very much to the speakers. I appreciate that they are in different locations, and some of them are a little bit lighter to hear than others. I'm sorry for that in terms of the technology. But if you have questions now and clarification, or anything you want to follow up on what the speakers are talking about, please feel free to go ahead and write those in currently and I will submit them to the speakers. Okay, if no questions, then we'll move on to the next presentation. And hold on one second, Kathy, and I'll let you introduce the next speakers. Kathleen Calzone: Okay, for those of you who are joining late, we'll re-introduce our next set of presenters. And we have an overlap, and that's going to include Dr. Jacquelyn Taylor. And she's an associate professor in the pediatric nurse practitioner specialty at Yale University School of Nursing, and her research has focused on addressing genomic health disparities and hypertension among African-Americans and West African families.

In addition, we also have Dr. Ann Cashion, and she is the currently the acting scientific director of the National Institute of Nursing Research Division of Intramural Research. And prior to coming to the National Institutes of Health, she was a professor and chair of the Department of Acute and Chronic Care in the College of Nursing at the University of Tennessee Health Science Center. Her research and clinical interest is focused on genetic and genomic environmental components associated with the outcomes of organ transplantation. And then lastly, we do have two of the other authors who are going to be participating, and that includes Ansley Stansfill and Ashley Clark, both who are doctoral students at Yale and working with Dr. Taylor on their projects. Jacquelyn Taylor: Okay. So we're going to start by giving you the general definition of metabolic syndrome. So our paper covered an overview of the genomics of metabolic syndrome. And determining exactly what metabolic syndrome is really depends on who you ask because there are several independent and expert organizations that have differing definitions of what metabolic syndrome really is.

But generally, metabolic syndrome is widely recognized -- a widely-recognized concept generally defined as the clustering of risk factors including hypertension, insulin resistance, and obesity. This clustering of risk factors then leads to an increased risk for diabetes and cardiovascular disease. I can't see the slides, but we're on the second slide. Metabolic syndrome -- it's estimated that in the United States it affects more than 34 percent of the population, and it leads to a three-fold increase in cardiovascular-related deaths. This lack of consensus on establishing diagnostic criteria for metabolic syndrome leads to an uncertain clinical utility of the diagnosis. Next slide, please. So what we have defined in our paper from the Alberti, et al. paper in 2009 is the harmonizing definition of metabolic syndrome that takes into account the definitions of the three major expert panels that define metabolic syndrome. So one of the first expert panels that we looked at for a definition of metabolic syndrome was the ATP3, which is the National Cholesterol Education Program Adult Treatment Panel Three. And their primary outcome for metabolic syndrome focuses mainly on cardiovascular disease, while the American Association of Clinical Endocrinologists, or the AACE, their primary outcome focuses in on insulin resistance. And then we looked at the definition of the World Health Organization, which looked at a diagnosis being made of metabolic syndrome that focused mainly on markers of insulin resistance.

So with the harmonizing definition of metabolic syndrome, it takes in to account many of the factors defined in -- with the three major organizations that look at metabolic syndrome, but it looks at many other factors as well. So it looks at obesity, where you look at increased waist circumference by populations and country -- using country-specific definitions, elevated triglycerides, reduced HDLC, elevated blood pressure levels, and a elevated fasting blood sugar level, or type 2 diabetes. Next slide. So some of the risk factors associated with development of metabolic syndrome are similar to those associated with hypertension, obesity, and renal disease, and diabetes. And looking at these risk factors, we do understand that although there are genomic precursors for each one of these factors and development of metabolic syndrome, we also recognize that there are lifestyle, gender, and ethnic differences that have to be considered when examining development of metabolic syndrome. Many studies have been completed looking at metabolic syndrome and its risk factors including genome-wide association studies, epigenetic studies, and proteomic-type studies. And although certain risks alleles that have relevance for the individual components of the disease may also have overlapping value and the overall risk for the development of metabolic syndrome. So not only do these studies look at metabolic syndrome as a whole, they look at all those disorders that make up metabolic syndrome, so hypertension, diabetes, renal disease, and obesity. So in our paper, we looked at the possible contributors to metabolic syndrome individually, and then as a whole. So what we're going to do here is first we're going to talk about cardiovascular factors in metabolic syndrome, and we just went through -- so we should be on the slide with cardiovascular factors in metabolic syndrome, or Slide 5 -- so we just went through a whole seminar on cardiovascular genomics, so we're not going to go into great detail, but we're going to talk about some of the factors that affect obtaining a diagnosis of metabolic syndrome.

So one of the major cardiovascular risk factors in metabolic syndrome is dyslipidemia and hypertension. So looking at dyslipidemia first, this leads to alterations in circulating blood lipid levels, or predisposition to -- for a predisposition to development of metabolic syndrome. And some of the things we look for with this dyslipidemia is a familial hypercholesterolemia, or increases in triglyceride and HDL levels. And the major mutations that we found in our search were mutations in the LPL and APOE genes, or the lipoprotein metabolism. Next slide on cardiovascular factors in metabolic syndrome include looking at hypertension, which is one of the major risk factors for metabolic syndrome. When we did our search, we found more than 50 genes that were associated with blood pressure or hypertension that were related to metabolic syndrome. So again, when you look at hypertension, it's important to assess a familial -- to do a family pedigree so that you can assess any type of inherited risk for hypertension. So we look at familial hypertension, and this leads us to believe that these risks are -- you have greater risk if you have familial hypertension rather than those that are due to secondary types of hypertension. And then other genes that are responsible for hypertension can also lead to proteins that may affect the renal, electrolyte, and water handling system in the body that lead to high blood pressure. And these genes can be found in the seminal works created by Lifton, et al. And some of these are even some of the rare renal disorders like Bartter Syndrome, Liddle Syndrome, and the like. So next we're going to talk about diabetes in metabolic syndrome, so we should be on the diabetes slide. So type 2 diabetes is what we're more interested in in terms of metabolic syndrome, and in type 2 diabetes, we're looking at an overnight fasting glucose of greater -- equal -- 126 milligrams per deciliter or greater, or -- and/or an HbA1C of greater than 6.5 percent. So a hemoglobin A1C, as you all know, is a three-month average of your blood sugar levels. And although diabetes may be more prevalent among specific ethnic and racial groups, we know that this can be true for the other risk factors that we're looking at in metabolic syndrome as well. So hypertension, obesity, dyslipidemia, all of those can have certain ethnic and racial pre-existing factors or genetic predisposition for all of those particular risk factors. But here we just wanted to highlight some of the differences that you can find in terms of ethnic and racial breakdown for a particular risk factor. So although you see that there are more than 15.7 million non-Hispanic whites that have received a diagnosis of diabetes, non-Hispanic blacks have a greater percentage of the population. So they -- although there are only 4.9 million non-Hispanic blacks with type 2 diabetes, that accounts for 18.7 percent of the black population. And then you can also find differences within ethnic groups as well. So when you are looking at Hispanics, you can see that 7.6 percent of the diagnoses for diabetes can be found for Cuban, Central, and South American Hispanics, while, when you look at Mexican Americans and Puerto Ricans, they have a greater prevalence at 13.3 percent to 13.8 percent. So just something just you want to keep in mind when looking at different ethnic groups and ethnic risk factors for particular disorders. Next slide for type 2 diabetes risk alleles. So when looking at risk alleles for type 2 diabetes, the major variant that we found in the literature for type 2 diabetes risk in metabolic syndrome was the TCF7L2 gene. And although we know that this particular gene can cause excess fat, glycogen deposition in the liver, hyperlipidemia, glucose intolerance, and lead to type 2 diabetes, we know that the effects of individual SNPs are relatively small compared to some of the synergistic effects that you can see that contribute to the development of metabolic syndrome. And we have added in a supplement of a schematic of the synergistic effects of type 2 diabetes risk alleles on development of metabolic syndrome that can be found on the online version of this paper at the Journal of Nursing Scholarship website. So now I'm going to turn the presentation over to Ann Cashion who's going to talk about obesity in metabolic syndrome, and some of the clinical resources for implications for practice and research. Ann Cashion: Thank you, Jacquie [spelled phonetically], can you hear me? Okay. So Kathy, if you will continue to work the slides, that would be wonderful. Body mass index, or BMI, has been used to clinically evaluate obesity for the last several decades. In terms of metabolic syndrome, we are most concerned about individuals who are overweight, which is a BMI greater than 25, or obese, which is a BMI greater than 40. The reason for our clinical concern about these individuals is that those who are overweight are five- to six-fold more likely to have metabolic syndrome, and those who are obese, the greater than 30 BMI, are actually 32 times more likely to develop metabolic syndrome. So those are significant numbers, and we need to think about that in terms of obesity may be a genetic trigger for metabolic syndrome. So an individual may have many risks for metabolic syndrome, but then when they become obese, it more or less is the straw that breaks the camel's back, and it flips on the "on" switch for interactions between the genes that actually lead to the metabolic syndrome component parts. So we are -- however, we also see that some obese patients are not at risk for metabolic syndrome, and that can happen. So there is some factors such as the gynoid fat distribution in women that may actually protect against metabolic syndrome, whereas those with central fat obesity, which is the accumulation of the fat between the organs, that these individuals may be at greater risk for metabolic syndrome.

If you could turn to the next slide, the obesity risk alleles. Thank you. Now let's discuss a few top obesity gene candidates or alleles. The two main ones that are implicated are melanocortin receptor 4 gene, which is called MC4R, and it's been associated with that accumulation. Another top gene frequently mentioned, and I think you can basically tell by the name of this gene how people thought it was going to be very important, that the name of the gene is fat mass and obesity gene. And this has also been associated with the development of metabolic syndrome. MC4R gene is most commonly associated with monogenetic forms of obesity; possibly, it's also involved in some polygenetic forms of common central obesity. And in some cases, specific SNPs in the MC4R gene have actually been shown to protect against metabolic syndrome. The FTO gene is actually thought to control increase in PKA nutrients and decreased satiety. So that means when the FTO gene is active, people feel hungry, and they actually eat more. But you can tell from the fact that we know these two particular genes but yet we can't treat obesity using a genetic approach, that there's not a common -- it's not consistently found what response these genes have. So two other genes that can be implicated in that syndrome that Jacquie talked about a little while ago was the LPL and the APOE gene. Next slide, please. Go down a few more slides to the implications for practice and research. People are probably guessing that we changed our slide order. So with the implications for clinical practice, we're looking at -- we would love to have some genomic-based applications, but unfortunately, they are not clinically available at this point, but they are certainly being developed in labs across the country. The combination of environmental and genetic factors add to the complexity of the clinical management of metabolic syndrome. Because of this complexity, at this time the best approach is to manage your clients individually based on what component of the metabolic syndrome they have. For example, if they have cardiovascular disease, then manage that according to clinical guidelines; the same with obesity and diabetes. So there's no real solid clinical management of Met syndrome; it's managing the individual components using established clinical guidelines. Nursing management frequently includes: to promote lifestyle strategies that target the prevention of metabolic syndrome and the management of the individual components of that syndrome. One of the things that we do recommend is to look at -- obtain a minimum of a three-generation pedigree. In the article, it refers you to the surgeon general's website for obtaining family history, and I know that I have used that website for years to teach how to obtain a family history and asked students to do that on their family. It's been a very well-received component of the teaching of genetics to undergraduate students. Next slide, please. So when we're looking at clinical practice, then one of the first things that we need to be thinking about is the personalized health care that we hope to see come about soon. And hopefully it will revolutionize the treatment of metabolic syndrome because it will be tailoring the health care of the person to their individual genetic makeup as well as to the environmental factors. So it is the responsibility of the health care provider at this point in time to be aware of the best practices for interpreting and delivering results to the patient and using them to manage the care. I do want to discuss briefly the direct-to-consumer genetic testing websites. Using these websites is cautioned by the layperson, and even so by the health care provider as well, because we're really not sure at this point in time about the clinical validity, the reliability, and I think most importantly, the clinical utility of these websites. One of the largest concerns being that you may find out you have an allele that puts you at risk for a specific component of the metabolic syndrome, but yet there's no actual treatment or management for that, so we're just not sure how to approach that at this point in time. Next slide, please. So the implications for research are also many. Our science has progressed a lot in the last two years, and we are now able to look at the biologic underpinnings and identify specific genes that are associated with metabolic syndrome.

So researchers are moving their research studies from a single gene approach to more of a complex disorder approach. We've gone from linkage analysis to genome-wide association studies to the current one for epigenetic approaches. So -- however, there are multiple limitations for each of those specific types of designs and technologies. So, for example, on the genome-wide association studies, while they have been prevalent in the literature, what we see is that they actually account for a very small percent of the variability in inheritable disorders such as metabolic syndrome. We also need to take into effect, particularly with genome-wide association studies, the fact -- the ethnic ancestry and admixture mapping that Dr. Taylor has already talked about. So if you go to the next slide, as I said, we looked at most researchers are using technologies and designs including linkage analysis, and genome-wide association studies, and epigenetic studies, which is looking at actual changes in the genetic makeup due to environmental reasons later on in life, and then you can also be moving into the area of proteomics. Next slide. However, we really think the future of genetics in metabolic syndrome probably lies in the area of system-based approaches, and this is using expression arrays, particularly gene expression arrays, or other technologies, such as mass spectrometry, and then combining bioinformatics techniques to actually analyze large datasets. This is what we're seeing and what's being called the "big data" approaches to understanding the biologic underpinnings of disease. So using these systems, researchers can actually address input from hundreds of genes in environmental factors. The interactions with the components may be more important than the individual components themselves, is what we're finding. So direct sequencing of the entire genome is also coming into the future because of the decrease that we're seeing in the cost of actually sequencing this large component. For clinical practice, the goal of genomic health care is the integration of clinical and biological data for improving health outcomes. Next slide, please. These are our clinical resources that we have used to identify in the -- identify in our clinical resources so the evaluation of genomic applications -- I think you can basically read through these and see which ones are most helpful to you. Thank you. Female Speaker: So I'm going to open it up for questions. There were two questions that came in after Dr. Wung's and her group's presentation. The first was, "Can you address the connection of medications with the genomics of cardiac disease treatment at this point in time?" And that question came from Ingrid. And so, Shu-Fen, I will open it up for you and if you want to identify yourself or someone else to answer the question. Shu-Fen? Okay. Does anyone else in the group want to answer that question in terms of -- Kathleen Hickey Yeah, hi, this is Kathleen. Female Speaker Who is this? I thought it was Kathleen Hickey. Kathleen Hickey: Hi there. Can you hear me? Female Speaker: Yeah. Kathleen Hickey: I'm here. So in the case of -- can you hear me ok? Female Speaker: Yes. Kathleen Hickey: Yeah. So in the case of the long QT syndrome, we know that certain beta blockers are preventative of a sudden cardiac death, for instance, in long QT type one or two. But, in fact, we find that in long QT type 3, they can be more detrimental, so knowing the genotype and the actual potential to either prolong the long QT interval or have an adverse effect is important. Now in the case of general cardiovascular disease, I'll turn that over to some of my other members, but in the case of hypertrophic cardiomyopathy, we know that beta blockers and calcium channel blockers are, in fact, very helpful as well. Thank you. Female Speaker: Now we'll go to the next question. What is the next step for genetics research in cardiology? Kathleen Hickey: So -- this is Kathleen -- I think the next step is going to be further genetic testing, but then a specific targets and development, perhaps, of new medications or new gene treatments in the area of the myopathies, and the utility of whole exome sequencing to its full capacity, I think, is what we are going to see laying ahead for some of these arrhythmia-based disorders. Female Speaker: Thank you, Kathleen. The next question is, "In my view, metabolic syndrome is a very heterogeneous phenomenon with different phenotypes that could have different risk factors and different outcomes, and/or different risk for different outcomes. What is the best way to study MetS linked to CBD, study the risk factors and corresponding outcomes: separately or combine them together to study simultaneously?" And I'm going to open this one up to Jacquie and Ann. Jacquelyn Taylor: This is Jacquie. Can you hear me? Hello? Can you hear me? Female Speaker Yes, yes. Jacquelyn Taylor: So when looking at metabolic syndrome, because there are so many risk factors involved, and so many traits in terms of defining the disorder, I think you do have to take a step back and look at these individually. So whoever posed the question, that's correct, it is a heterogeneous, polygenetic, multi-factorial type of disorder, so I think you do have to look at individually in terms of the various risk factors, but then you also have to take in to account some of the environmental factors that lead to some of the individual risk factors like diet, physical activity, and so on. And I think that once we look at things individually, we can look at some of the interaction effects of the various individual variables, and maybe start looking at it in terms of mixed modeling effects. Ann Cashion: I think I basically would like to agree with Jacquie.

I think the concern is really the numbers of subjects you'd need to actually look at individual components right now, and our science and our ability to analyze the data isn't far enough long for us to take smaller sample sizes and look at metabolic syndrome, so that's why are limited to looking at each component, primarily, at this point in time. Thanks. Jacquelyn Taylor: And I think that some of the larger genome-wide studies can be useful in looking at metabolic syndrome where we have some of the larger numbers of individuals with DNA available for us to look at various issues in terms of cardiovascular, diabetes, obesity, and the like. So some of the larger family blood pressure program conglomerates might be useful when thinking about looking at metabolic syndrome. Female Speaker: Thanks to Ann and Jacquie for those responses. We have about three more minutes, so if there are any questions. I see hands raised, but I'm not very good at knowing how to address those hands, so if you have your hand raised and you have a question, please just type it into the question format for me, if you will. And I'd also -- while we're waiting on those last questions, I'd like to highlight that our next webinar will be held March 20th, from 3:30 to 4:30; we'll have two groups of presenters at that time as well. Dr. Jane DeLuca and Dr. Alex Kemper will be presenting on Implications of Newborn Screening for Nurses. And Dr. Martha Turner, from the American Nurses Association, will be discussing the Ethical, Legal, and Social Issues in the Translation of Genomics into Healthcare. And the sign up for that is also available through GoToMeeting, and you can find that link at the webinar site on genome.gov. So are there any other questions that have come in in the meantime, or comments from the presenters? Female Speaker: Unmuted. Female Speaker: I have unmuted everyone. Jacquelyn Taylor: No, I can't think of any, Camille [spelled phonetically]. Ann Cashion: [inaudible] Female Speaker: It's hard -- I keep hearing echoes so I'm going to have to shut everybody back down. [laughs] Sorry. Okay. One of -- there is one more question. One says "Thanks to all of you," and I agree, and "Is the effectiveness on exercise on CVA or MetS depending on genetics?" So I'm going to ask that of Jacquie and Ann Cashion. Ann Cashion: [unintelligible] -- Jacquelyn Taylor: Well I think it's -- go ahead, Ann. Ann Cashion: You go first. Jacquelyn Taylor: Well, I think it's more than just looking at exercise alone, I think it's looking at the impact of physical activity, diet, the genetic risk factors for obesity, hypertension, and all of those things that can contribute to those individual risk factors that lead to metabolic syndrome. So I think it's more than just one particular environmental factor; I think it's the additive effects of environmental and genomic risk factors that lead to the development of metabolic syndrome. Female Speaker: I'd just like to add to Jacquie, I did a little bit of research on this this summer, and so exercise actually attenuates the relationship between a person's genetic architecture and then the environment. So there is a link, but like Jacquie was saying, it's also due to diet, not just exercise alone and environmental factors. Female Speaker: Thank you. There is also a question about, "Is there availability of continuing nursing education for these webinars?" And unfortunately, we have not applied for that, or received CNE process for this webinar, so it's more for your own learning. There's also a question about, "Can I save the PowerPoint?" And the speakers have allowed us for both these presentations to upload their PowerPoints, which we will do in the next day or so, along with the recording that has been done for today's session. So both of those things will be available on the genome.gov site, and I will post that before we leave. Okay. I've had a couple of "Thank you, wonderful," and "Thank you to the speakers," and I'd like to echo that. I know it takes a lot with this technology to make sure that we're getting those who want to speak to be able to speak and to get the questions answered, so I thank you all.

 

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