Genetics and Ischemic Heart Disease: Should We Opt for Genetic Testing for Primary Prevention?

IF 0.2 Q4 CARDIAC & CARDIOVASCULAR SYSTEMS
Tariq Ashraf, Taseer Ahmed, Mehir-un-Nisa Iqbal, Asif Nadeem
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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. 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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.
遗传学与缺血性心脏病:我们应该选择基因检测进行一级预防吗?
心血管疾病是巴基斯坦普通人口中普遍存在的健康问题,巴基斯坦人的平均寿命明显低于全球平均水平,男性通常活到67岁,女性为69岁。根据2019年全球疾病负担研究,巴基斯坦的心血管疾病年龄标准化发病率估计为每10万人918.18例(全球为每10万人684.33例),年龄标准化死亡率为每10万人357.88例(全球为每10万人239.85例)弗雷明汉心脏研究(Framingham heart Study)对40 - 94岁无心脏病的人群进行了研究,结果显示,在40.2岁时,男性患冠心病(CHD)的风险为49%,女性为32%。自1975年以来,美国因心血管疾病、冠心病和中风导致的死亡率呈下降趋势。2000年至2008年的数据也表明冠心病死亡率有所下降令人担忧的是,世界卫生组织(世卫组织)报告称,巴基斯坦与冠心病相关的死亡人数出现了令人担忧的上升。2020年,冠心病死亡240720人,占总死亡人数的16.49%。这突出表明巴基斯坦与冠心病相关的死亡率呈上升趋势。值得注意的是,除了年龄和性别之外,大多数出现心脏事件的人都有一个或多个确定的或边缘性的危险因素。虽然一些基本的风险因素是可识别的,但其他的可能仍然难以捉摸。这些危险因素的筛选和针对性治疗干预的证据仍在不断涌现,需要进一步探索评估心血管疾病危险因素的起点是用于预测主要心血管事件的变量。这些因素包括年龄、性别、血压、胆固醇水平、糖尿病和吸烟状况。尽管2014年的Pooled Cohort Equation和Astro-CHARM等风险评估工具已经开发出来,但它们尚未对潜在的新心血管疾病风险因素提供令人满意的评估冠心病被认为是一种遗传和环境因素相互作用的多因素疾病。环境风险因素已在大约80%的冠心病病例中被确定一些风险评分,如Framingham风险评分、PROCAM、Reynolds风险评分和QRISK 2,已被提出用于指导高危人群使用他汀类药物。10-14然而,这些风险评分往往缺乏准确性,可能高估或低估未来的冠心病事件。15,16具有相似环境因素和常规冠状动脉疾病危险因素(CRFs)的个体之间的疾病易感性差异可能归因于遗传变异遗传分析可以潜在地增强风险区分,而不仅仅是考虑CRFs。心脏病家族史占风险估计的40%以上,长期以来一直被认为是crfs的一部分候选基因研究已经进行,以确定与疾病途径相关的基因的常见变异单核苷酸多态性(snp)已被用作遗传多样性的标记。在这些snp中,位于9p21位点的snp与冠心病风险的相关性最强。20,21然而,尽管这些变异与冠心病事件之间存在明确的联系,但与传统的危险因素相比,9p21位点snp并没有明确地改善冠心病风险的预测或分类。22-24值得注意的是,大多数关于冠心病的遗传研究主要集中在欧洲/高加索人群,其对包括巴基斯坦在内的南亚人群的适用性需要进一步调查。25,26在这种情况下,巴基斯坦人口,就像其他亚洲国家一样,在冠心病的基因研究中代表性不足。Shahid SU等人在这方面做了一些工作,27在巴基斯坦人群中显示了21个snp风险评分,用于遗传风险分析。总之,尽管针对巴基斯坦40岁及以上人群开发了不同的风险评估工具,但迫切需要通过识别与冠心病相关的遗传标记来扩大心脏风险评估,特别是在年轻人群中。这对于提高我们对冠心病危险因素的认识和制定更有效的预防和干预策略至关重要。萨马德Z,哈尼夫B.巴基斯坦的心血管疾病:想象大流行后、冲突后的未来。循环。2023;147(17):1261 - 3。刘建军,刘建军,刘建军,等。冠状动脉粥样硬化的研究进展。柳叶刀》。1999;353(9147):89 - 92。李建军,李建军,李建军,等。美国冠心病、中风和其他心血管疾病的趋势和差异:心血管疾病预防全国会议的结果。循环。2000;102(25):3137 - 47。Greenland P, Knoll MD, Stamler J, Neaton JD, Dyer AR, Garside DB,等。
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来源期刊
Pakistan Heart Journal
Pakistan Heart Journal CARDIAC & CARDIOVASCULAR SYSTEMS-
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