본문 바로가기
KERD
논문KCI 등재

Mendelian Randomization Studies in Atherosclerotic Cardiovascular Diseases

2

조회

0

다운로드

0

인용

0

참고문헌

키워드

초록

This review aimed to highlight the pivotal role of Mendelian randomization (MR) in advancing atherosclerotic cardiovascular disease (ASCVD) research—a field often hindered by the complexities and limitations of traditional studies. MR, which uses genetic variants as instrumental variables, provides a robust mechanism for inferring causality, offering insights untainted by the confounding factors and biases often prevalent in observational and randomized controlled trials. We explored the significant contributions of MR for elucidating the causal relationship between low-density lipoprotein cholesterol and ASCVD, and analyzed its assumptions and methodological nuances. We discussed issues surrounding instrumental variable selection, pleiotropy, and ethical considerations, in an effort to offer a balanced and insightful analysis. We highlighted the promising integration of MR with emerging technologies and global data sharing, as well as its potential to drive personalized medicine. This review provided a concise yet comprehensive journey into MR’s transformative impact on ASCVD research, offering a blend of current insights and challenges, in addition to future prospects. We aimed to serve a valuable resource for those seeking to navigate the intricate pathways of causality and intervention in ASCVD, to aid the development of enhanced understanding and targeted treatment strategies in the future.

Abstract

This review aimed to highlight the pivotal role of Mendelian randomization (MR) in advancing atherosclerotic cardiovascular disease (ASCVD) research—a field often hindered by the complexities and limitations of traditional studies. MR, which uses genetic variants as instrumental variables, provides a robust mechanism for inferring causality, offering insights untainted by the confounding factors and biases often prevalent in observational and randomized controlled trials. We explored the significant contributions of MR for elucidating the causal relationship between low-density lipoprotein cholesterol and ASCVD, and analyzed its assumptions and methodological nuances. We discussed issues surrounding instrumental variable selection, pleiotropy, and ethical considerations, in an effort to offer a balanced and insightful analysis. We highlighted the promising integration of MR with emerging technologies and global data sharing, as well as its potential to drive personalized medicine. This review provided a concise yet comprehensive journey into MR’s transformative impact on ASCVD research, offering a blend of current insights and challenges, in addition to future prospects. We aimed to serve a valuable resource for those seeking to navigate the intricate pathways of causality and intervention in ASCVD, to aid the development of enhanced understanding and targeted treatment strategies in the future.

참고문헌 (69)

  1. Benjamin EJ, "Heart disease and stroke statistics-2019 update : a report from the American Heart Association", Circulation, 139, pp.e56~ (2019)
  2. Roth GA, "Global burden of cardiovascular diseases and risk factors, 1990-2019 : update from the GBD 2019 Study", J Am Coll Cardiol, 76, pp.2982~3021 (2020)
  3. Libby P, "Atherosclerosis", Nat Rev Dis Primers, 5, pp.56~ (2019)
  4. Kronzon I, "Aortic atherosclerotic disease and stroke", Circulation, 114, pp.63~75 (2006)
  5. Libby P, "Inflammation and atherosclerosis", Circulation, 105, pp.1135~1143 (2002)
  6. Valanti EK, "Advances in biological therapies for dyslipidemias and atherosclerosis", Metabolism, 116, pp.154461~ (2021)
  7. Cuzick J, "The importance of long-term follow up of participants in clinical trials", Br J Cancer, 128, pp.432~438 (2023)
  8. Meuli L, "Understanding confounding in observational studies", Eur J Vasc Endovasc Surg, 55, pp.737~ (2018)
  9. Hwang TJ, "Failure of investigational drugs in late-stage clinical development and publication of trial results", JAMA Intern Med, 176, pp.1826~1833 (2016)
  10. FitzGerald GA, "Testing cardiovascular drug safety and efficacy in randomized trials", Circ Res, 114, pp.1156~1161 (2014)
  11. Swanson SA, "Nature as a trialist? : deconstructing the analogy between Mendelian randomization and randomized trials", Epidemiology, 28, pp.653~659 (2017)
  12. Goldstein CE, "Ethical issues in pragmatic randomized controlled trials : a review of the recent literature identifies gaps in ethical argumentation", BMC Med Ethics, 19, pp.14~ (2018)
  13. Niewada M, "Lifestyle modification for stroke prevention : facts and fiction", Curr Opin Neurol, 29, pp.9~13 (2016)
  14. McEvoy RD, "Randomized clinical trials of cardiovascular disease in obstructive sleep apnea: understanding and overcoming bias", Sleep (Basel), 44, pp.zsab019~ (2021)
  15. Davey Smith G, "Mendelian randomization : genetic anchors for causal inference in epidemiological studies", Hum Mol Genet, 23, pp.R89~ (2014)
  16. Davey Smith G, "Mendel’s laws, Mendelian randomization and causal inference in observational data : substantive and nomenclatural issues", Eur J Epidemiol, 35, pp.99~111 (2020)
  17. Sattar N, "Reverse causality in cardiovascular epidemiological research : more common than imagined?", Circulation, 135, pp.2369~2372 (2017)
  18. Arsenault BJ, "From the garden to the clinic : how Mendelian randomization is shaping up atherosclerotic cardiovascular disease prevention strategies", Eur Heart J, 43, pp.4447~4449 (2022)
  19. Richmond RC, "Mendelian randomization : concepts and scope", Cold Spring Harb Perspect Med, 12, pp.a040501~ (2022)
  20. Greenland S, "An introduction to instrumental variables for epidemiologists", Int J Epidemiol, 47, pp.358~ (2018)
  21. Martens EP, "Instrumental variables : application and limitations", Epidemiology, 17, pp.260~267 (2006)
  22. Mortensen MB, "Low-density lipoprotein cholesterol is predominantly associated with atherosclerotic cardiovascular disease events in patients with evidence of coronary atherosclerosis : the Western Denmark Heart Registry", Circulation, 147, pp.1053~1063 (2023)
  23. Ference BA, "Low-density lipoproteins cause atherosclerotic cardiovascular disease. 1. Evidence from genetic, epidemiologic, and clinical studies. A consensus statement from the European Atherosclerosis Society Consensus Panel", Eur Heart J, 38, pp.2459~2472 (2017)
  24. Ference BA, "Variation in PCSK9 and HMGCR and risk of cardiovascular disease and diabetes", N Engl J Med, 375, pp.2144~2153 (2016)
  25. Sabatine MS, "Efficacy and safety of evolocumab in reducing lipids and cardiovascular events", N Engl J Med, 372, pp.1500~1509 (2015)
  26. Sabatine MS, "Evolocumab and clinical outcomes in patients with cardiovascular disease", N Engl J Med, 376, pp.1713~1722 (2017)
  27. Kosoglou T, "Ezetimibe : a review of its metabolism, pharmacokinetics and drug interactions", Clin Pharmacokinet, 44, pp.467~494 (2005)
  28. Holmes MV, "Mendelian randomization of blood lipids for coronary heart disease", Eur Heart J, 36, pp.539~550 (2015)
  29. Cannon CP, "Safety of anacetrapib in patients with or at high risk for coronary heart disease", N Engl J Med, 363, pp.2406~2415 (2010)
  30. ACCORD Study Group, "Effects of combination lipid therapy in type 2 diabetes mellitus", N Engl J Med, 362, pp.1563~1574 (2010)
  31. Shah S, "Causal relevance of blood lipid fractions in the development of carotid atherosclerosis : Mendelian randomization analysis", Circ Cardiovasc Genet, 6, pp.63~72 (2013)
  32. Do R, "Common variants associated with plasma triglycerides and risk for coronary artery disease", Nat Genet, 45, pp.1345~1352 (2013)
  33. Maranhão RC, "Lipoprotein(a) : structure, pathophysiology and clinical implications", Arq Bras Cardiol, 103, pp.76~84 (2014)
  34. Tsimikas S, "Emerging RNA therapeutics to lower blood levels of Lp(a) : JACC Focus Seminar 2", 4, 2021, pp.77, 1576~1589
  35. Li C, "The correlation between lipoprotein(a)and coronary atherosclerotic lesion is stronger than LDL-C, when LDL-C is less than 104 mg", dL, 2021, pp.21, 41~
  36. Wang S, "The relationship between lipoprotein(a)and risk of cardiovascular disease : a Mendelian randomization analysis", Eur J Med Res, 27, pp.211~ (2022)
  37. Sampson UK, "Residual cardiovascular risk despite optimal LDL cholesterol reduction with statins : the evidence, etiology, and therapeutic challenges", Curr Atheroscler Rep, 14, pp.1~10 (2012)
  38. Navarese EP, "Association between baseline LDL-C level and total and cardiovascular mortality after LDL-C lowering : a systematic review and meta-analysis", JAMA, 319, pp.1566~1579 (2018)
  39. Navarese EP, "Independent causal effect of remnant cholesterol on atherosclerotic cardiovascular outcomes : a Mendelian randomization study", Arterioscler Thromb Vasc Biol, 43, pp.e373~ (2023)
  40. Pepys MB, "C-reactive protein : a critical update", J Clin Invest, 111, pp.1805~1812 (2003)
  41. Emerging Risk Factors Collaboration, "C-reactive protein concentration and risk of coronary heart disease, stroke, and mortality : an individual participant meta-analysis", Lancet, 375, pp.132~140 (2010)
  42. Zhang YX, "Coronary C-reactive protein distribution : its relation to development of atherosclerosis", Atherosclerosis, 145, pp.375~379 (1999)
  43. C Reactive Protein Coronary Heart Disease Genetics Collaboration(CCGC), "Association between C reactive protein and coronary heart disease : Mendelian randomisation analysis based on individual participant data", BMJ, 342, pp.d548~ (2011)
  44. Ridker PM, "Plasma concentration of interleukin-6 and the risk of future myocardial infarction among apparently healthy men", Circulation, 101, pp.1767~1772 (2000)
  45. Danesh J, "Long-term interleukin-6 levels and subsequent risk of coronary heart disease : two new prospective studies and a systematic review", PLoS Med, 5, pp.e78~ (2008)
  46. Sattar N, "Are markers of inflammation more strongly associated with risk for fatal than for nonfatal vascular events?", PLoS Med, 6, pp.e1000099~ (2009)
  47. Smith GD, "‘Mendelian randomization’ : can genetic epidemiology contribute to understanding environmental determinants of disease?", Int J Epidemiol, 32, pp.1~22 (2003)
  48. Burgess S, "Avoiding bias from weak instruments in Mendelian randomization studies", Int J Epidemiol, 40, pp.755~764 (2011)
  49. Levin MG, "Genetics of smoking and risk of atherosclerotic cardiovascular diseases : a Mendelian randomization study", JAMA Netw Open, 4, pp.e2034461~ (2021)
  50. Pierce BL, "The effect of non-differential measurement error on bias, precision and power in Mendelian randomization studies", Int J Epidemiol, 41, pp.1383~1393 (2012)
  51. Burgess S, "Mendelian randomization with a binary exposure variable : interpretation and presentation of causal estimates", Eur J Epidemiol, 33, pp.947~952 (2018)
  52. Bowden J, "Mendelian randomization with invalid instruments : effect estimation and bias detection through Egger regression", Int J Epidemiol, 44, pp.512~525 (2015)
  53. Price AL, "Principal components analysis corrects for stratification in genome-wide association studies", Nat Genet, 38, pp.904~909 (2006)
  54. Sudlow C, "UK biobank : an open access resource for identifying the causes of a wide range of complex diseases of middle and old age", PLoS Med, 12, pp.e1001779~ (2015)
  55. Hemani G, "The MR-base platform supports systematic causal inference across the human phenome", eLife, 7, pp.e34408~ (2018)
  56. Relton CL, "Two-step epigenetic Mendelian randomization : a strategy for establishing the causal role of epigenetic processes in pathways to disease", Int J Epidemiol, 41, pp.161~176 (2012)
  57. Holmes MV, "Mendelian randomization in cardiometabolic disease : challenges in evaluating causality", Nat Rev Cardiol, 14, pp.577~590 (2017)
  58. Palmer TM, "Using multiple genetic variants as instrumental variables for modifiable risk factors", Stat Methods Med Res, 21, pp.223~242 (2012)
  59. Burgess S, "Mendelian randomization analysis with multiple genetic variants using summarized data", Genet Epidemiol, 37, pp.658~665 (2013)
  60. Inouye M, "Genomic risk prediction of coronary artery disease in 480, 000 adults : implications for primary prevention", J Am Coll Cardiol, 72, pp.1883~1893 (2018)
  61. Barabási AL, "Network medicine : a network-based approach to human disease", Nat Rev Genet, 12, pp.56~68 (2011)
  62. MacArthur J, "The new NHGRI-EBI Catalog of published genome-wide association studies(GWAS Catalog)", Nucleic Acids Res, 45, pp.D896~D901 (2017)
  63. Walker VM, "Mendelian randomization : a novel approach for the prediction of adverse drug events and drug repurposing opportunities", Int J Epidemiol, 46, pp.2078~2089 (2017)
  64. Shabani M, "Rules for processing genetic data for research purposes in view of the new EU General Data Protection Regulation", Eur J Hum Genet, 26, pp.149~156 (2018)
  65. Global Alliance for Genomics and Health, "GENOMICS. A federated ecosystem for sharing genomic, clinical data", Science, 352, pp.1278~1280 (2016)
  66. Khera AV, "Genome-wide polygenic scores for common diseases identify individuals with risk equivalent to monogenic mutations", Nat Genet, 50, pp.1219~1224 (2018)
  67. Athieniti E, "A guide to multi-omics data collection and integration for translational medicine", Comput Struct Biotechnol J, 21, pp.134~149 (2022)
  68. Malina S, "Deep Mendelian randomization : Investigating the causal knowledge of genomic deep learning models", PLOS Comput Biol, 18, pp.e1009880~ (2022)
  69. Leong A, "Cardiometabolic risk factors for COVID-19 susceptibility and severity : a Mendelian randomization analysis", PLoS Med, 18, pp.e1003553~ (2021)

관련 논문AI추천

이 간행물의 다른 논문 (9건)