{"title":"Genetics and Ischemic Heart Disease: Should We Opt for Genetic Testing for Primary Prevention?","authors":"Tariq Ashraf, Taseer Ahmed, Mehir-un-Nisa Iqbal, Asif Nadeem","doi":"10.47144/phj.v56i3.2642","DOIUrl":null,"url":null,"abstract":"Cardiovascular diseases (CVD) are a prevalent health concern within the general population of Pakistan, where the average lifespan is notably lower than the global average, with men typically living to 67 years and women to 69 years. According to the 2019 Global Burden of Disease study, Pakistan had an estimated age-standardized incidence rate of CVD at 918.18 per 100,000 (compared to the global rate of 684.33 per 100,000), along with an age-standardized death rate of 357.88 per 100,000 (globally, this rate is 239.85 per 100,000).1 Coronary heart disease (CHD), as revealed by the Framingham Heart Study focusing on individuals aged 40 to 94 without prior heart disease, displayed a lifetime risk of 49% for men and 32% for women when reaching the age of 40.2 There has been a declining trend in death rates in the United States attributed to CVD, CHD, and stroke since 1975. Data from 2000 to 2008 also indicate a decline in CHD mortality.3 Worryingly, the World Health Organization (WHO) reports a concerning rise in CHD-related fatalities in Pakistan. In 2020, 240,720 individuals died due to CHD, accounting for 16.49% of all deaths. This highlights an escalating trend of CHD-related mortality in Pakistan. It's important to note that most individuals presenting with cardiac events have one or more established or borderline risk factors aside from age and gender.4-6 While some essential risk factors are discernible, others may remain elusive. The screening of these risk factors and the evidence for targeted therapeutic interventions are still emerging and require further exploration.7 The starting point for assessing CVD risk factors is variables used to predict major cardiovascular events. These include age, sex, blood pressure, cholesterol levels, diabetes mellitus, and smoking status. Although risk assessment tools like the Pooled Cohort Equation in 2014 and Astro-CHARM have been developed, they have yet to provide satisfactory assessments for potential new CVD risk factors.8 CHD is recognized as a multifactorial disorder resulting from genetic and environmental factors interplay. Environmental risk factors have been identified in approximately 80% of CHD cases.9 Several risk scores, such as the Framingham Risk Score, PROCAM, Reynolds Risk Score, and QRISK 2, have been proposed to guide the use of statins in high-risk groups.10-14 Yet, these risk scores often lack precision and may either overestimate or underestimate future CHD events.15,16 The variation in disease susceptibility among individuals with similar environmental factors and conventional coronary artery disease risk factors (CRFs) may be attributed to genetic variations.17 Genetic analysis can potentially enhance risk discrimination beyond the consideration of CRFs alone. Family history of heart disease, accounting for more than 40% of risk estimation, has long been considered a part of CRFs.18 Candidate gene studies have been conducted to identify common variants in genes associated with disease pathways.19 Single-nucleotide polymorphisms (SNPs) have been employed as markers of genetic diversity. Among these SNPs, those located on the 9p21 locus have shown the strongest association with CHD risk to date.20,21 However, despite the clear link between these variants and incident CHD, 9p21 locus SNPs have not definitively improved the prediction or classification of CHD risk compared to traditional risk factors.22-24 It is important to note that most genetic studies on CHD have predominantly focused on European/Caucasian populations, and their applicability to the South Asian population, including Pakistan, requires further investigation.25,26 In this context, the Pakistani population, much like other Asian countries, is underrepresented in genetic research on CHD. Shahid SU et al. did some work in this respect,27 showing 21 SNPs risk score for genetic risk analysis in the Pakistani population. In conclusion, while different risk assessment tools have been developed for the Pakistani population aged 40 years and above, there is an urgent need to expand cardiac risk evaluation by identifying genetic markers related to CHD, particularly in the younger population. This will be crucial for advancing our understanding of CHD risk factors and developing more effective prevention and intervention strategies. References Samad Z, Hanif B. Cardiovascular Diseases in Pakistan: Imagining a Postpandemic, Postconflict Future. Circulation. 2023;147(17):1261-3. Lloyd-Jones DM, Larson MG, Beiser A, Levy D. Lifetime risk of developing coronary heart disease. Lancet. 1999;353(9147):89-92. Cooper R, Cutler J, Desvigne-Nickens P, Fortmann SP, Friedman L, Havlik R, et al. Trends and disparities in coronary heart disease, stroke, and other cardiovascular diseases in the United States: findings of the national conference on cardiovascular disease prevention. Circulation. 2000;102(25):3137-47. Greenland P, Knoll MD, Stamler J, Neaton JD, Dyer AR, Garside DB, et al. Major risk factors as antecedents of fatal and nonfatal coronary heart disease events. JAMA. 2003;290(7):891-7. Khot UN, Khot MB, Bajzer CT, Sapp SK, Ohman EM, Brener SJ, et al. Prevalence of conventional risk factors in patients with coronary heart disease. JAMA. 2003;290(7):898-904. Vasan RS, Sullivan LM, Wilson PW, Sempos CT, Sundström J, Kannel WB, et al. Relative importance of borderline and elevated levels of coronary heart disease risk factors. Ann Intern Med. 2005;142(6):393-402. Hackam DG, Anand SS. Emerging risk factors for atherosclerotic vascular disease: a critical review of the evidence. JAMA. 2003;290(7):932-40. Pencina MJ, D'Agostino Sr RB, D'Agostino Jr RB, Vasan RS. Evaluating the added predictive ability of a new marker: from area under the ROC curve to reclassification and beyond. Stat Med. 2008;27(2):157-72. Aziz KU, Faruqui AM, Patel N, Jaffery H. Prevalence and awareness of cardiovascular disease including life styles in a lower middle class urban community in an Asian country. Pak Heart J. 2008;41(3-4):11-20. Beaney KE, Cooper JA, Ullah Shahid S, Ahmed W, Qamar R, Drenos F, et al. Clinical utility of a coronary heart disease risk prediction gene score in UK healthy middle aged men and in the Pakistani population. PloS One. 2015;10(7):e0130754. Belsky DW, Moffitt TE, Sugden K, Williams B, Houts R, McCarthy J, et al. Development and evaluation of a genetic risk score for obesity. Biodemograp Soc Biol. 2013;59(1):85-100. Bennet AM, Di Angelantonio E, Ye Z, Wensley F, Dahlin A, Ahlbom A, et al. Association of apolipoprotein E genotypes with lipid levels and coronary risk. JAMA. 2007;298(11):1300-11. Brindle P, Beswick A, Fahey T, Ebrahim S. Accuracy and impact of risk assessment in the primary prevention of cardiovascular disease: a systematic review. Heart. 2006;92(12):1752-9. Casas JP, Cooper J, Miller GJ, Hingorani AD, Humphries SE. Investigating the Genetic Determinants of Cardiovascular Disease Using Candidate Genes and Meta‐analysis of Association Studies. Ann Hum Genet. 2006;70(2):145-69. Collins GS, Altman DG. An independent and external validation of QRISK2 cardiovascular disease risk score: a prospective open cohort study. BMJ. 2010;340:340:c2442. Conroy RM, Pyörälä K, Fitzgerald AE, Sans S, Menotti A, De Backer G, et al. Estimation of ten-year risk of fatal cardiovascular disease in Europe: the SCORE project. Eur Heart J. 2003;24(11):987-1003. IBC 50K CAD Consortium. Large-scale gene-centric analysis identifies novel variants for coronary artery disease. PLoS Genet. 2011;7(9):e1002260. Cooper JA, Miller GJ, Humphries SE. A comparison of the PROCAM and Framingham point-scoring systems for estimation of individual risk of coronary heart disease in the Second Northwick Park Heart Study. Atherosclerosis. 2005;181(1):93-100. Cordell HJ. Detecting gene–gene interactions that underlie human diseases. Nat Rev Genet. 2009;10(6):392-404. Samani NJ, Erdmann J, Hall AS, Hengstenberg C, Mangino M, Mayer B, et al. Genomewide association analysis of coronary artery disease. N Engl J Med. 2007;357(5):443-53. Paynter NP, Chasman DI, Buring JE, Shiffman D, Cook NR, Ridker PM. Cardiovascular disease risk prediction with and without knowledge of genetic variation at chromosome 9p21.3. Ann Intern Med. 2009;150(2):65-72. Palomaki GE, Melillo S, Bradley LA. Association between 9p21 genomic markers and heart disease: a meta-analysis. JAMA. 2010;303(7):648-56. Patel RS, Asselbergs FW, Quyyumi AA, Palmer TM, Finan CI, Tragante V, et al. Genetic variants at chromosome 9p21 and risk of first versus subsequent coronary heart disease events: a systematic review and meta-analysis. J Am Coll Cardiol. 2014;63(21):2234-45. Dutta A, Henley W, Lang IA, Murray A, Guralnik J, Wallace RB, et al. The coronary artery disease–associated 9p21 variant and later life 20-year survival to cohort extinction. Circ Cardiovasc Genet. 2011;4(5):542-8. Hernesniemi JA, Seppälä I, Lyytikäinen LP, Mononen N, Oksala N, Hutri-Kähönen N, et al. Genetic profiling using genome-wide significant coronary artery disease risk variants does not improve the prediction of subclinical atherosclerosis: the cardiovascular risk in young finns study, the bogalusa heart study and the health 2000 survey–a meta-analysis of three independent studies. PloS One. 2012;7(1):e28931. Hippisley-Cox J, Coupland C, Vinogradova Y, Robson J, Minhas R, Sheikh A, et al. Predicting cardiovascular risk in England and Wales: prospective derivation and validation of QRISK2. BMJ. 2008;336(7659):1475-82. Shahid SU, Cooper JA, Beaney KE, Li K, Rehman A, Humphries SE. Genetic risk analysis of coronary artery disease in Pakistani subjects using a genetic risk score of 21 variants. Atherosclerosis. 2017;258:1-7.","PeriodicalId":42273,"journal":{"name":"Pakistan Heart Journal","volume":null,"pages":null},"PeriodicalIF":0.2000,"publicationDate":"2023-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Pakistan Heart Journal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.47144/phj.v56i3.2642","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"CARDIAC & CARDIOVASCULAR SYSTEMS","Score":null,"Total":0}
引用次数: 0
Abstract
Cardiovascular diseases (CVD) are a prevalent health concern within the general population of Pakistan, where the average lifespan is notably lower than the global average, with men typically living to 67 years and women to 69 years. According to the 2019 Global Burden of Disease study, Pakistan had an estimated age-standardized incidence rate of CVD at 918.18 per 100,000 (compared to the global rate of 684.33 per 100,000), along with an age-standardized death rate of 357.88 per 100,000 (globally, this rate is 239.85 per 100,000).1 Coronary heart disease (CHD), as revealed by the Framingham Heart Study focusing on individuals aged 40 to 94 without prior heart disease, displayed a lifetime risk of 49% for men and 32% for women when reaching the age of 40.2 There has been a declining trend in death rates in the United States attributed to CVD, CHD, and stroke since 1975. Data from 2000 to 2008 also indicate a decline in CHD mortality.3 Worryingly, the World Health Organization (WHO) reports a concerning rise in CHD-related fatalities in Pakistan. In 2020, 240,720 individuals died due to CHD, accounting for 16.49% of all deaths. This highlights an escalating trend of CHD-related mortality in Pakistan. It's important to note that most individuals presenting with cardiac events have one or more established or borderline risk factors aside from age and gender.4-6 While some essential risk factors are discernible, others may remain elusive. The screening of these risk factors and the evidence for targeted therapeutic interventions are still emerging and require further exploration.7 The starting point for assessing CVD risk factors is variables used to predict major cardiovascular events. These include age, sex, blood pressure, cholesterol levels, diabetes mellitus, and smoking status. Although risk assessment tools like the Pooled Cohort Equation in 2014 and Astro-CHARM have been developed, they have yet to provide satisfactory assessments for potential new CVD risk factors.8 CHD is recognized as a multifactorial disorder resulting from genetic and environmental factors interplay. Environmental risk factors have been identified in approximately 80% of CHD cases.9 Several risk scores, such as the Framingham Risk Score, PROCAM, Reynolds Risk Score, and QRISK 2, have been proposed to guide the use of statins in high-risk groups.10-14 Yet, these risk scores often lack precision and may either overestimate or underestimate future CHD events.15,16 The variation in disease susceptibility among individuals with similar environmental factors and conventional coronary artery disease risk factors (CRFs) may be attributed to genetic variations.17 Genetic analysis can potentially enhance risk discrimination beyond the consideration of CRFs alone. Family history of heart disease, accounting for more than 40% of risk estimation, has long been considered a part of CRFs.18 Candidate gene studies have been conducted to identify common variants in genes associated with disease pathways.19 Single-nucleotide polymorphisms (SNPs) have been employed as markers of genetic diversity. Among these SNPs, those located on the 9p21 locus have shown the strongest association with CHD risk to date.20,21 However, despite the clear link between these variants and incident CHD, 9p21 locus SNPs have not definitively improved the prediction or classification of CHD risk compared to traditional risk factors.22-24 It is important to note that most genetic studies on CHD have predominantly focused on European/Caucasian populations, and their applicability to the South Asian population, including Pakistan, requires further investigation.25,26 In this context, the Pakistani population, much like other Asian countries, is underrepresented in genetic research on CHD. Shahid SU et al. did some work in this respect,27 showing 21 SNPs risk score for genetic risk analysis in the Pakistani population. In conclusion, while different risk assessment tools have been developed for the Pakistani population aged 40 years and above, there is an urgent need to expand cardiac risk evaluation by identifying genetic markers related to CHD, particularly in the younger population. This will be crucial for advancing our understanding of CHD risk factors and developing more effective prevention and intervention strategies. References Samad Z, Hanif B. Cardiovascular Diseases in Pakistan: Imagining a Postpandemic, Postconflict Future. Circulation. 2023;147(17):1261-3. Lloyd-Jones DM, Larson MG, Beiser A, Levy D. Lifetime risk of developing coronary heart disease. Lancet. 1999;353(9147):89-92. Cooper R, Cutler J, Desvigne-Nickens P, Fortmann SP, Friedman L, Havlik R, et al. Trends and disparities in coronary heart disease, stroke, and other cardiovascular diseases in the United States: findings of the national conference on cardiovascular disease prevention. Circulation. 2000;102(25):3137-47. Greenland P, Knoll MD, Stamler J, Neaton JD, Dyer AR, Garside DB, et al. Major risk factors as antecedents of fatal and nonfatal coronary heart disease events. JAMA. 2003;290(7):891-7. Khot UN, Khot MB, Bajzer CT, Sapp SK, Ohman EM, Brener SJ, et al. Prevalence of conventional risk factors in patients with coronary heart disease. JAMA. 2003;290(7):898-904. Vasan RS, Sullivan LM, Wilson PW, Sempos CT, Sundström J, Kannel WB, et al. Relative importance of borderline and elevated levels of coronary heart disease risk factors. Ann Intern Med. 2005;142(6):393-402. Hackam DG, Anand SS. Emerging risk factors for atherosclerotic vascular disease: a critical review of the evidence. JAMA. 2003;290(7):932-40. Pencina MJ, D'Agostino Sr RB, D'Agostino Jr RB, Vasan RS. Evaluating the added predictive ability of a new marker: from area under the ROC curve to reclassification and beyond. Stat Med. 2008;27(2):157-72. Aziz KU, Faruqui AM, Patel N, Jaffery H. Prevalence and awareness of cardiovascular disease including life styles in a lower middle class urban community in an Asian country. Pak Heart J. 2008;41(3-4):11-20. Beaney KE, Cooper JA, Ullah Shahid S, Ahmed W, Qamar R, Drenos F, et al. Clinical utility of a coronary heart disease risk prediction gene score in UK healthy middle aged men and in the Pakistani population. PloS One. 2015;10(7):e0130754. Belsky DW, Moffitt TE, Sugden K, Williams B, Houts R, McCarthy J, et al. Development and evaluation of a genetic risk score for obesity. Biodemograp Soc Biol. 2013;59(1):85-100. Bennet AM, Di Angelantonio E, Ye Z, Wensley F, Dahlin A, Ahlbom A, et al. Association of apolipoprotein E genotypes with lipid levels and coronary risk. JAMA. 2007;298(11):1300-11. Brindle P, Beswick A, Fahey T, Ebrahim S. Accuracy and impact of risk assessment in the primary prevention of cardiovascular disease: a systematic review. Heart. 2006;92(12):1752-9. Casas JP, Cooper J, Miller GJ, Hingorani AD, Humphries SE. Investigating the Genetic Determinants of Cardiovascular Disease Using Candidate Genes and Meta‐analysis of Association Studies. Ann Hum Genet. 2006;70(2):145-69. Collins GS, Altman DG. An independent and external validation of QRISK2 cardiovascular disease risk score: a prospective open cohort study. BMJ. 2010;340:340:c2442. Conroy RM, Pyörälä K, Fitzgerald AE, Sans S, Menotti A, De Backer G, et al. Estimation of ten-year risk of fatal cardiovascular disease in Europe: the SCORE project. Eur Heart J. 2003;24(11):987-1003. IBC 50K CAD Consortium. Large-scale gene-centric analysis identifies novel variants for coronary artery disease. PLoS Genet. 2011;7(9):e1002260. Cooper JA, Miller GJ, Humphries SE. A comparison of the PROCAM and Framingham point-scoring systems for estimation of individual risk of coronary heart disease in the Second Northwick Park Heart Study. Atherosclerosis. 2005;181(1):93-100. Cordell HJ. Detecting gene–gene interactions that underlie human diseases. Nat Rev Genet. 2009;10(6):392-404. Samani NJ, Erdmann J, Hall AS, Hengstenberg C, Mangino M, Mayer B, et al. Genomewide association analysis of coronary artery disease. N Engl J Med. 2007;357(5):443-53. Paynter NP, Chasman DI, Buring JE, Shiffman D, Cook NR, Ridker PM. Cardiovascular disease risk prediction with and without knowledge of genetic variation at chromosome 9p21.3. Ann Intern Med. 2009;150(2):65-72. Palomaki GE, Melillo S, Bradley LA. Association between 9p21 genomic markers and heart disease: a meta-analysis. JAMA. 2010;303(7):648-56. Patel RS, Asselbergs FW, Quyyumi AA, Palmer TM, Finan CI, Tragante V, et al. Genetic variants at chromosome 9p21 and risk of first versus subsequent coronary heart disease events: a systematic review and meta-analysis. J Am Coll Cardiol. 2014;63(21):2234-45. Dutta A, Henley W, Lang IA, Murray A, Guralnik J, Wallace RB, et al. The coronary artery disease–associated 9p21 variant and later life 20-year survival to cohort extinction. Circ Cardiovasc Genet. 2011;4(5):542-8. Hernesniemi JA, Seppälä I, Lyytikäinen LP, Mononen N, Oksala N, Hutri-Kähönen N, et al. Genetic profiling using genome-wide significant coronary artery disease risk variants does not improve the prediction of subclinical atherosclerosis: the cardiovascular risk in young finns study, the bogalusa heart study and the health 2000 survey–a meta-analysis of three independent studies. PloS One. 2012;7(1):e28931. Hippisley-Cox J, Coupland C, Vinogradova Y, Robson J, Minhas R, Sheikh A, et al. Predicting cardiovascular risk in England and Wales: prospective derivation and validation of QRISK2. BMJ. 2008;336(7659):1475-82. Shahid SU, Cooper JA, Beaney KE, Li K, Rehman A, Humphries SE. Genetic risk analysis of coronary artery disease in Pakistani subjects using a genetic risk score of 21 variants. Atherosclerosis. 2017;258:1-7.