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Editorial commentary: Genetic contributions to cardiovascular disease: The blurred lines between monogenic and polygenic traits
Author’s Accepted Manuscript Genetic contributions to cardiovascular disease: The blurred lines between monogenic and polygenic traits Jodie Ingles, J. Martijn Bos www.elsevier.com/locate/tcm
PII: DOI: Reference:
S1050-1738(17)30048-8 http://dx.doi.org/10.1016/j.tcm.2017.04.001 TCM6389
To appear in: Trends in Cardiovascular Medicine Cite this article as: Jodie Ingles and J. Martijn Bos, Genetic contributions to cardiovascular disease: The blurred lines between monogenic and polygenic t r a i t s , Trends in Cardiovascular Medicine, http://dx.doi.org/10.1016/j.tcm.2017.04.001 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting galley proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
Genetic contributions to cardiovascular disease: the blurred lines between monogenic and polygenic traits Jodie Ingles,1,2,3 J. Martijn Bos4 1
Agnes Ginges Centre for Molecular Cardiology, Centenary Institute, Sydney, Australia; 2 3
4
Sydney Medical School, University of Sydney, Australia;
Department of Cardiology, Royal Prince Alfred Hospital, Sydney, Australia;
Department of Molecular Pharmacology and Experimental Therapeutics, Windland Smith Rice Sudden Death Genomics Laboratory, Mayo Clinic, Rochester, MN, USA.
ACKNOWLEDGEMENTS JI is the recipient of a National Heart Foundation of Australia Future Leader Fellowship (#100833). Address for Correspondence: Doctor Jodie Ingles Agnes Ginges Centre for Molecular Cardiology Centenary Institute Locked Bag 6 Newtown NSW 2042 Australia Ph: 61-2-9565 6293 Email: [email protected] Understanding the genetic contribution to cardiovascular disease has been a research focus for decades. From ascertaining the numerous variants that each contribute to a small proportion of a polygenic trait such as coronary artery disease (CAD), to careful tracking of a single pathogenic variant through a large pedigree, like in autosomal dominantly inherited hypertrophic cardiomyopathy (HCM). CAD is one of the leading causes of death globally1 and the underlying pathophysiology involves numerous environmental and genetic factors. Increased familial risk has been observed for decades, and indeed population-based studies such as the Framingham Heart Study have demonstrated increased incidence amongst those with an affected parent2. There is no doubt environmental factors exert the greatest influence on development of CAD, and Page 1
disentangling independent, genetic contributions to a disease like this has always been challenging. So far, over 60 distinct genetic loci have been identified, most ending up common variants that only exert a small to moderate effect size3.
In this issue of the Journal, Auer and Stitziel provide a comprehensive review of genetic association studies in cardiovascular disease, specifically focusing on the issue of statistical power4. As we move into an era of precision medicine, delineation of the many numerous factors influencing disease phenotypes will be increasingly important. The unique combination of both genetic and environmental influences will in the future guide our prevention and treatment regimens at an individual level. The ability of the general clinician to navigate the literature and appropriately weigh the quality of scientific evidence will become even more necessary. Moreover, with the advent of large scale genetic analysis tools such as whole exome and whole genome sequencing, the significant price drop of these assays, the ability to directly link this to one’s medical record combined with increasing computational power to analyze this enormous amount of data, we have opened the door for a whole new approach to genetic research. It remains, however, that a solid study design, including careful evaluation of one’s study’s statistical power is of the utmost importance in interpreting study outcomes, and indeed highlights the need for robust replication studies. Auer and Stitziel4 demonstrate that, while the draw of ‘big data’ is appealing, study design and validation remain key.
The authors outline the pros and cons of genetic association studies, and clearly show how these studies can be used to understand the genetic background of polygenic cardiac diseases. However, while the longstanding approach has been binning conditions in to either complex polygenic traits or monogenic familial diseases, it is clear that the lines separating the two have become increasingly blurred. In the field of cardiomyopathies and
Page 2
channelopathies, including HCM, arrhythmogenic right ventricular cardiomyopathy (ARVC), familial dilated cardiomyopathy (DCM) and Brugada syndrome (BrS), our expanding knowledge of genetics has challenged the prevailing view that many of these diseases are exclusively Mendelian. A proportion most certainly has familial disease caused by a single pathogenic variant that is inherited from one of the parents. Such variants are often exceedingly rare, or even absent from large population databases, including the Exome Aggregation Consortium (ExAC), are highly penetrant and exert a large effect size. Recent reports, however, have identified certain patient sub-populations with more complex disease pathophysiology, including non-familial HCM that may occur in up to 40% of cases5. The presence of a positive family history of disease amongst HCM probands has been shown across multiple studies to give a high prior probability of a causative variant being identified by HCM genetic testing6-8. The overall yield of genetic testing, when tested for known HCM-associated genes, can increase from 30% to 70% when a positive family history is demonstrated. Elucidating the underlying disease mechanism for those not harboring a single causative genetic variant is the next step in understanding these diseases, especially among these sub-populations of patients, and will lean heavily on the large scale genomic techniques, combined with statistical approaches, sufficient power, and methods developed to understand more complex polygenic traits.
The story of BrS has been likewise turbulent, with approximately 20% of cases due to pathogenic SCN5A variants 9, and the remainder likely comprising multiple diverse environmental and genetic influences, a large proportion of patients remain without a clear genetic explanation for their disease. A landmark study demonstrated the genetic complexity of BrS, using a genome-wide association approach to study 312 patients and 1,115 controls. The investigators identified 2 genetic loci, both associations being
Page 3
replicated in independent samples, as well as a third locus identified by an independent case-control study10. The cumulative effect of these 3 variants on phenotype was clear, and demonstrated for the first time that genome-wide association studies can be applied to rarer cardiac conditions to identify important genetic modifiers. Further, this approach shed light on the underlying disease mechanisms involved in BrS, with the role of transcription factors early in life now considered to play a critical role in development of disease. This study, as well as the work by Auer and Stitziel4 presented in this issue, provides an important focus on a key issue and challenge, namely the size of the cohort needed to discover a measurable effect size. While Bezzina and colleagues10 were able to find 3 loci with a little over 300 patients, future studies to identify variants with more subtle effects will require larger cohorts, which will be no easy feat considering the relative rarity of inherited cardiomyopathies and channelopathies.
Our ability to precisely understand the influence of both genes and environment on cardiovascular disease phenotypes will allow us to move closer to a precision medicine model of care. As genetics begins to plays an increasing role in the management of complex diseases such as CAD, and other causes are attributed to seemingly monogenic diseases, one thing is certain: the role of highly skilled cardiac genetic counselors will be ever more important. The time and expertise required to effectively communicate the intricacies of genetic inheritance to the proband, in a way that empowers them to pass this on to their own potentially at-risk family members, is not trivial. Further, they play a role in ensuring that patients are fully informed of the potential outcomes of genetic testing with the ability to consider their own personal preferences and values to make important decisions about their own health are critical11. Cardiac genetic counselors are equipped to manage such issues, and will be increasingly called upon, as genetic contributions to cardiovascular disease are understood.
Page 4
Understanding the contribution of both small and large effect size variants to cardiovascular disease has exciting potential. Whether it is uncovering new disease mechanisms, identifying new drug targets, or more precisely communicating inheritance risk to patients, the underpinnings of genetics will continue to alter our field. REFERENCES 1. Lozano R, Naghavi M, Foreman K, et al.: 2012. Global and regional mortality from 235 causes of death for 20 age groups in 1990 and 2010: a systematic analysis for the Global Burden of Disease Study 2010. Lancet 380:2095-2128. 2. Lloyd-Jones DM, Nam BH, D'Agostino RB, Sr., et al.: 2004. Parental cardiovascular disease as a risk factor for cardiovascular disease in middle-aged adults: a prospective study of parents and offspring. Jama 291:2204-2211. 3. Khera AV, Kathiresan S: 2017. Genetics of coronary artery disease: discovery, biology and clinical translation. Nat Rev Genet. 4. Auer PL, Stitziel NO: 2017. Genetic association studies in cardiovascular diseases: do we have enough power? Trends in cardiovascular medicine. IN PRESS 2017 5. Ingles J, Burns C, Bagnall RD, et al.: 2017. Non-familial hypertrophic cardiomyopathy: Prevalence, natural history and clinical implications. Circulation: Cardiovascular Genetics Accepted Feb 15. 6. Bos JM, Will ML, Gersh BJ, Kruisselbrink TM, Ommen SR, Ackerman MJ: 2014. Characterization of a phenotype-based genetic test prediction score for unrelated patients with hypertrophic cardiomyopathy. Mayo Clin Proc 89:727-737. 7. Gruner C, Ivanov J, Care M, et al.: 2013. Toronto hypertrophic cardiomyopathy genotype score for prediction of a positive genotype in hypertrophic cardiomyopathy. Circ Cardiovasc Genet 6:19-26. 8. Ingles J, Sarina T, Yeates L, et al.: 2013. Clinical predictors of genetic testing outcomes in hypertrophic cardiomyopathy. Genet Med 15:972-977. 9. Kapplinger JD, Tester DJ, Alders M, et al.: 2010. An international compendium of mutations in the SCN5A-encoded cardiac sodium channel in patients referred for Brugada syndrome genetic testing. Heart Rhythm 7:33-46. 10. Bezzina CR, Barc J, Mizusawa Y, et al.: 2013. Common variants at SCN5A-SCN10A and HEY2 are associated with Brugada syndrome, a rare disease with high risk of sudden cardiac death. Nat Genet 45:1044-1049. 11. Ingles J, Semsarian C: 2014. The value of cardiac genetic testing. Trends in cardiovascular medicine 24:217-224.
Page 5
PII: DOI: Reference:
S1050-1738(17)30048-8 http://dx.doi.org/10.1016/j.tcm.2017.04.001 TCM6389
To appear in: Trends in Cardiovascular Medicine Cite this article as: Jodie Ingles and J. Martijn Bos, Genetic contributions to cardiovascular disease: The blurred lines between monogenic and polygenic t r a i t s , Trends in Cardiovascular Medicine, http://dx.doi.org/10.1016/j.tcm.2017.04.001 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting galley proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
Genetic contributions to cardiovascular disease: the blurred lines between monogenic and polygenic traits Jodie Ingles,1,2,3 J. Martijn Bos4 1
Agnes Ginges Centre for Molecular Cardiology, Centenary Institute, Sydney, Australia; 2 3
4
Sydney Medical School, University of Sydney, Australia;
Department of Cardiology, Royal Prince Alfred Hospital, Sydney, Australia;
Department of Molecular Pharmacology and Experimental Therapeutics, Windland Smith Rice Sudden Death Genomics Laboratory, Mayo Clinic, Rochester, MN, USA.
ACKNOWLEDGEMENTS JI is the recipient of a National Heart Foundation of Australia Future Leader Fellowship (#100833). Address for Correspondence: Doctor Jodie Ingles Agnes Ginges Centre for Molecular Cardiology Centenary Institute Locked Bag 6 Newtown NSW 2042 Australia Ph: 61-2-9565 6293 Email: [email protected] Understanding the genetic contribution to cardiovascular disease has been a research focus for decades. From ascertaining the numerous variants that each contribute to a small proportion of a polygenic trait such as coronary artery disease (CAD), to careful tracking of a single pathogenic variant through a large pedigree, like in autosomal dominantly inherited hypertrophic cardiomyopathy (HCM). CAD is one of the leading causes of death globally1 and the underlying pathophysiology involves numerous environmental and genetic factors. Increased familial risk has been observed for decades, and indeed population-based studies such as the Framingham Heart Study have demonstrated increased incidence amongst those with an affected parent2. There is no doubt environmental factors exert the greatest influence on development of CAD, and Page 1
disentangling independent, genetic contributions to a disease like this has always been challenging. So far, over 60 distinct genetic loci have been identified, most ending up common variants that only exert a small to moderate effect size3.
In this issue of the Journal, Auer and Stitziel provide a comprehensive review of genetic association studies in cardiovascular disease, specifically focusing on the issue of statistical power4. As we move into an era of precision medicine, delineation of the many numerous factors influencing disease phenotypes will be increasingly important. The unique combination of both genetic and environmental influences will in the future guide our prevention and treatment regimens at an individual level. The ability of the general clinician to navigate the literature and appropriately weigh the quality of scientific evidence will become even more necessary. Moreover, with the advent of large scale genetic analysis tools such as whole exome and whole genome sequencing, the significant price drop of these assays, the ability to directly link this to one’s medical record combined with increasing computational power to analyze this enormous amount of data, we have opened the door for a whole new approach to genetic research. It remains, however, that a solid study design, including careful evaluation of one’s study’s statistical power is of the utmost importance in interpreting study outcomes, and indeed highlights the need for robust replication studies. Auer and Stitziel4 demonstrate that, while the draw of ‘big data’ is appealing, study design and validation remain key.
The authors outline the pros and cons of genetic association studies, and clearly show how these studies can be used to understand the genetic background of polygenic cardiac diseases. However, while the longstanding approach has been binning conditions in to either complex polygenic traits or monogenic familial diseases, it is clear that the lines separating the two have become increasingly blurred. In the field of cardiomyopathies and
Page 2
channelopathies, including HCM, arrhythmogenic right ventricular cardiomyopathy (ARVC), familial dilated cardiomyopathy (DCM) and Brugada syndrome (BrS), our expanding knowledge of genetics has challenged the prevailing view that many of these diseases are exclusively Mendelian. A proportion most certainly has familial disease caused by a single pathogenic variant that is inherited from one of the parents. Such variants are often exceedingly rare, or even absent from large population databases, including the Exome Aggregation Consortium (ExAC), are highly penetrant and exert a large effect size. Recent reports, however, have identified certain patient sub-populations with more complex disease pathophysiology, including non-familial HCM that may occur in up to 40% of cases5. The presence of a positive family history of disease amongst HCM probands has been shown across multiple studies to give a high prior probability of a causative variant being identified by HCM genetic testing6-8. The overall yield of genetic testing, when tested for known HCM-associated genes, can increase from 30% to 70% when a positive family history is demonstrated. Elucidating the underlying disease mechanism for those not harboring a single causative genetic variant is the next step in understanding these diseases, especially among these sub-populations of patients, and will lean heavily on the large scale genomic techniques, combined with statistical approaches, sufficient power, and methods developed to understand more complex polygenic traits.
The story of BrS has been likewise turbulent, with approximately 20% of cases due to pathogenic SCN5A variants 9, and the remainder likely comprising multiple diverse environmental and genetic influences, a large proportion of patients remain without a clear genetic explanation for their disease. A landmark study demonstrated the genetic complexity of BrS, using a genome-wide association approach to study 312 patients and 1,115 controls. The investigators identified 2 genetic loci, both associations being
Page 3
replicated in independent samples, as well as a third locus identified by an independent case-control study10. The cumulative effect of these 3 variants on phenotype was clear, and demonstrated for the first time that genome-wide association studies can be applied to rarer cardiac conditions to identify important genetic modifiers. Further, this approach shed light on the underlying disease mechanisms involved in BrS, with the role of transcription factors early in life now considered to play a critical role in development of disease. This study, as well as the work by Auer and Stitziel4 presented in this issue, provides an important focus on a key issue and challenge, namely the size of the cohort needed to discover a measurable effect size. While Bezzina and colleagues10 were able to find 3 loci with a little over 300 patients, future studies to identify variants with more subtle effects will require larger cohorts, which will be no easy feat considering the relative rarity of inherited cardiomyopathies and channelopathies.
Our ability to precisely understand the influence of both genes and environment on cardiovascular disease phenotypes will allow us to move closer to a precision medicine model of care. As genetics begins to plays an increasing role in the management of complex diseases such as CAD, and other causes are attributed to seemingly monogenic diseases, one thing is certain: the role of highly skilled cardiac genetic counselors will be ever more important. The time and expertise required to effectively communicate the intricacies of genetic inheritance to the proband, in a way that empowers them to pass this on to their own potentially at-risk family members, is not trivial. Further, they play a role in ensuring that patients are fully informed of the potential outcomes of genetic testing with the ability to consider their own personal preferences and values to make important decisions about their own health are critical11. Cardiac genetic counselors are equipped to manage such issues, and will be increasingly called upon, as genetic contributions to cardiovascular disease are understood.
Page 4
Understanding the contribution of both small and large effect size variants to cardiovascular disease has exciting potential. Whether it is uncovering new disease mechanisms, identifying new drug targets, or more precisely communicating inheritance risk to patients, the underpinnings of genetics will continue to alter our field. REFERENCES 1. Lozano R, Naghavi M, Foreman K, et al.: 2012. Global and regional mortality from 235 causes of death for 20 age groups in 1990 and 2010: a systematic analysis for the Global Burden of Disease Study 2010. Lancet 380:2095-2128. 2. Lloyd-Jones DM, Nam BH, D'Agostino RB, Sr., et al.: 2004. Parental cardiovascular disease as a risk factor for cardiovascular disease in middle-aged adults: a prospective study of parents and offspring. Jama 291:2204-2211. 3. Khera AV, Kathiresan S: 2017. Genetics of coronary artery disease: discovery, biology and clinical translation. Nat Rev Genet. 4. Auer PL, Stitziel NO: 2017. Genetic association studies in cardiovascular diseases: do we have enough power? Trends in cardiovascular medicine. IN PRESS 2017 5. Ingles J, Burns C, Bagnall RD, et al.: 2017. Non-familial hypertrophic cardiomyopathy: Prevalence, natural history and clinical implications. Circulation: Cardiovascular Genetics Accepted Feb 15. 6. Bos JM, Will ML, Gersh BJ, Kruisselbrink TM, Ommen SR, Ackerman MJ: 2014. Characterization of a phenotype-based genetic test prediction score for unrelated patients with hypertrophic cardiomyopathy. Mayo Clin Proc 89:727-737. 7. Gruner C, Ivanov J, Care M, et al.: 2013. Toronto hypertrophic cardiomyopathy genotype score for prediction of a positive genotype in hypertrophic cardiomyopathy. Circ Cardiovasc Genet 6:19-26. 8. Ingles J, Sarina T, Yeates L, et al.: 2013. Clinical predictors of genetic testing outcomes in hypertrophic cardiomyopathy. Genet Med 15:972-977. 9. Kapplinger JD, Tester DJ, Alders M, et al.: 2010. An international compendium of mutations in the SCN5A-encoded cardiac sodium channel in patients referred for Brugada syndrome genetic testing. Heart Rhythm 7:33-46. 10. Bezzina CR, Barc J, Mizusawa Y, et al.: 2013. Common variants at SCN5A-SCN10A and HEY2 are associated with Brugada syndrome, a rare disease with high risk of sudden cardiac death. Nat Genet 45:1044-1049. 11. Ingles J, Semsarian C: 2014. The value of cardiac genetic testing. Trends in cardiovascular medicine 24:217-224.
Page 5