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Iribarren C, Lu M, Elosua R, Gulati M, Wong ND, Blumenthal RS, Nissen S, Rana JS. Polygenic risk and incident coronary heart disease in a large multiethnic cohort. Am J Prev Cardiol 2024; 18:100661. [PMID: 38601895 PMCID: PMC11004687 DOI: 10.1016/j.ajpc.2024.100661] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2024] [Revised: 03/08/2024] [Accepted: 03/25/2024] [Indexed: 04/12/2024] Open
Abstract
Objective Many studies support the notion that polygenic risk scores (PRS) improve risk prediction for coronary heart disease (CHD) beyond conventional risk factors. However, PRS are not yet considered risk-enhancing factor in guidelines. Our objective was to determine the predictive performance of a commercially available PRS (CARDIO inCode-Score®) compared with the Pooled Cohorts Equations (PCE) in a contemporary, multi-ethnic cohort. Methods Participants (n = 63,070; 67 % female; 18 % non-European) without prior CHD were followed from 2007 through 12/31/2022. The association between the PRS and incident CHD was assessed using Cox regression adjusting for genetic ancestry and risk factors. Event rates were estimated by categories of PCE and by low/intermediate/high genetic risk within PCE categories; risk discrimination and net reclassification improvement (NRI) were also assessed. Results There were 3,289 incident CHD events during 14 years of follow-up. Adjusted hazard ratio (aHR) for incident CHD per 1 SD increase in PRS was 1.18 (95 % CI:1.14-1.22), and the aHR for the upper vs lower quintile of the PRS was 1.66 (95 % CI:1.49-1.86). The association was consistent in both sexes, in European participants compared with all minority groups combined and was strongest in the first 5 years of follow-up. The increase in the C-statistic was 0.004 (0.747 vs. 0.751; p < 0.0001); the NRI was 2.4 (0.9-3.8) for the entire cohort and 9.7 (7.5-12.0) for intermediate PCE risk individuals. After incorporating high genetic risk, a further 10 percent of participants at borderline/intermediate PCE risk would be candidates for statin therapy. Conclusion Inclusion of polygenic risk improved identification of primary prevention individuals who may benefit from more intensive risk factor modification.
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Affiliation(s)
- Carlos Iribarren
- Kaiser Permanente Northern California Division of Research, Oakland, CA, USA
| | - Meng Lu
- Kaiser Permanente Northern California Division of Research, Oakland, CA, USA
| | - Roberto Elosua
- Cardiovascular Epidemiology and Genetics, Institut Hospital del Mar d'Investigacions Mèdiques (IMIM), Spain and CIBER Cardiovascular Diseases (CIBERCV), Barcelona, Spain
- Faculty of Medicine, University of Vic-Central University of Catalonia (UVic-UCC), Vic, Spain
| | - Martha Gulati
- Barbra Streisand Women's Heart Center, Smidt Heart Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Nathan D. Wong
- Heart Disease Prevention Program, Division of Cardiology, Department of Medicine, University of California Irvine, Irvine, CA, USA
| | - Roger S. Blumenthal
- Ciccarone Center for the Prevention of Cardiovascular Disease, Johns Hopkins School of Medicine, Baltimore, MD, USA
| | - Steven Nissen
- Cardiovascular Medicine, Cleveland Clinic, Cleveland, OH, USA
| | - Jamal S. Rana
- Kaiser Permanente Northern California Division of Research, Oakland, CA, USA
- Department of Cardiology, The Permanente Medical Group, Kaiser Permanente Oakland Medical Center, Oakland, CA, USA
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Menotti A, Puddu PE. In Search of Risk Factors: The Origin and Early Stages of Cardiovascular Epidemiology. J Cardiovasc Dev Dis 2024; 11:20. [PMID: 38248890 PMCID: PMC10816974 DOI: 10.3390/jcdd11010020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2023] [Revised: 01/06/2024] [Accepted: 01/09/2024] [Indexed: 01/23/2024] Open
Abstract
Based mainly on their personal experience, the authors try to describe the origin of cardiovascular disease (CVD) epidemiology and the problems and difficulties practitioners attempted to tackle and solve during the first few decades of this discipline, which started around the middle of the last century. Beyond identifying the characteristics of those who became CVD epidemiologists, a description is given of the initial structures of the involved studies, participation rates, risk factors measurements and standardization, clinical measurements and diagnostic criteria, mortality data collection and coding, data loading and analysis, plus a number of problems still unsolved at the beginning of the 2000s. Despite many obstacles, and the initial hostility of the medical-scientific establishment, CVD epidemiology represented a revolution in researching in the bio-medical field. In the end, it also affected clinical research introducing the use of the quantitative approach bound to mathematical-statistical procedures. After decades of hard work and the development of a number of innovative tools, CVD epidemiology received its deserved recognition, eventually being accepted as a reputable and independent scientific discipline. Yet, in several countries, especially those from Southern Europe, an academic recognition of CVD epidemiology is still lacking.
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Tsegaselassie W, Jian Y, Berhanu GG, Tianyuan L, April M, Tali E, Fasil TA, Timothy TA, Jordana C, Marguerite IR, Robert SM, Michael VW, Kristine Y, Myriam F, Donald LJM, Mario S, Daichi S, Yuichiro Y, Paul M, Adam B. Associations of cardiometabolic polygenic risk scores with cardiovascular disease in African Americans. RESEARCH SQUARE 2023:rs.3.rs-3228815. [PMID: 37693576 PMCID: PMC10491340 DOI: 10.21203/rs.3.rs-3228815/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/12/2023]
Abstract
Background Cardiovascular disease (CVD) is a complex disease, and genetic factors contribute individually or cumulatively to CVD risk. While African American women and men are disproportionately affected by CVD, their lack of representation in genomic investigations may widen disparities in health. We investigated the associations of cardiometabolic polygenic risk scores (PRSs) with CVD risk in African Americans. Methods We used the Jackson Heart Study, a prospective cohort study of CVD in African American adults and the predicted atherosclerotic cardiovascular disease (ASCVD) 10-year risk. We included 40-79 years old adults without a history of coronary heart disease (CHD) or stroke at baseline. We derived genome-wide PRSs for systolic blood pressure (SBP), diastolic blood pressure (DBP), total cholesterol, LDL cholesterol, hemoglobin A1c (HbA1c), triglycerides, and C-reactive protein (CRP) separately for each of the participants, using African-origin UK Biobank participants' genome-wide association summary statistics. We estimated the associations between PRSs and 10-year predicted ASCVD risk adjusting for age, sex, study visit date, and genetic ancestry using linear and logistic regression models. Results Participants (n=2,077) were 63% female and 66% never-smokers. They had mean (SD) 56 (10) years of age, 127.8 (16.3) mmHg SBP, 76.3 (8.7) mmHg DBP, 200.4 (40.2) mg/dL total cholesterol, 51.7 (14.7) mg/dL HDL cholesterol, 127.2 (36.7) mg/dL LDL cholesterol, 6.0 (1.3) mmol/mol HbA1c, 108.9 (81.7) mg/dL triglycerides and 0.53 (1.1) CRP. Their median (interquartile range) predicted 10-year predicted ASCVD risk was 8.0 (4.0-15.0). Participants in the >75th percentile for HbA1c PRS had 1.42 percentage-point greater predicted 10-year ASCVD risk (1.42 [95% CI: 0.58-2.26]) and higher odds of ≥10% predicted 10-year ASCVD risk (OR: 1.46 [95% CI: 1.03-2.07]) compared with those in the <25th percentile for HbA1c PRS. Participants in the >75th percentile for SBP PRS had higher odds of ≥10% predicted 10-year ASCVD risk (OR: 1.52 [95% CI: 1.07-2.15]) compared with those in the <25th percentile for SBP PRS. Conclusion Among 40-79 years old African Americans without CHD and stroke, higher PRSs for HbA1c and SBP were associated with CVD risk. PRSs may help stratify individuals based on their clinical risk factors for CVD early prevention and clinical management.
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Affiliation(s)
| | | | | | - Lu Tianyuan
- Lady Davis Institute for Medical Research, Jewish General Hospital
| | | | | | | | | | | | | | | | | | | | | | | | - Sims Mario
- University of Mississippi Medical Center
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Bebo A, Jarmul JA, Pletcher MJ, Hasbani NR, Couper D, Nambi V, Ballantyne CM, Fornage M, Morrison AC, Avery CL, de Vries PS. Coronary heart disease and ischemic stroke polygenic risk scores and atherosclerotic cardiovascular disease in a diverse, population-based cohort study. PLoS One 2023; 18:e0285259. [PMID: 37327218 PMCID: PMC10275447 DOI: 10.1371/journal.pone.0285259] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2022] [Accepted: 04/18/2023] [Indexed: 06/18/2023] Open
Abstract
The predictive ability of coronary heart disease (CHD) and ischemic stroke (IS) polygenic risk scores (PRS) have been evaluated individually, but whether they predict the combined outcome of atherosclerotic cardiovascular disease (ASCVD) remains insufficiently researched. It is also unclear whether associations of the CHD and IS PRS with ASCVD are independent of subclinical atherosclerosis measures. 7,286 White and 2,016 Black participants from the population-based Atherosclerosis Risk in Communities study who were free of cardiovascular disease and type 2 diabetes at baseline were included. We computed previously validated CHD and IS PRS consisting of 1,745,179 and 3,225,583 genetic variants, respectively. Cox proportional hazards models were used to test the association between each PRS and ASCVD, adjusting for traditional risk factors, ankle-brachial index, carotid intima media thickness, and carotid plaque. The hazard ratios (HR) for the CHD and IS PRS were significant with HR of 1.50 (95% CI: 1.36-1.66) and 1.31 (95% CI: 1.18-1.45) respectively for the risk of incident ASCVD per standard deviation increase in CHD and IS PRS among White participants after adjusting for traditional risk factors. The HR for the CHD PRS was not significant with an HR of 0.95 (95% CI: 0.79-1.13) for the risk of incident ASCVD in Black participants. The HR for the IS PRS was significant with an HR of 1.26 (95%CI: 1.05-1.51) for the risk of incident ASCVD in Black participants. The association of the CHD and IS PRS with ASCVD was not attenuated in White participants after adjustment for ankle-brachial index, carotid intima media thickness, and carotid plaque. The CHD and IS PRS do not cross-predict well, and predict better the outcome for which they were created than the composite ASCVD outcome. Thus, the use of the composite outcome of ASCVD may not be ideal for genetic risk prediction.
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Affiliation(s)
- Allison Bebo
- Human Genetics Center, Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, United States of America
| | - Jamie A. Jarmul
- Gillings School of Public Health, Department of Health Policy and Management, University of North Carolina, Chapel Hill, Chapel Hill, NC, United States of America
- School of Medicine, University of North Carolina, Chapel Hill, Chapel Hill, NC, United States of America
| | - Mark J. Pletcher
- Departments of Epidemiology and Biostatistics and Medicine, University of California, San Francisco, San Francisco, CA, United States of America
| | - Natalie R. Hasbani
- Human Genetics Center, Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, United States of America
| | - David Couper
- Gillings School of Public Health, Department of Biostatistics, University of North Carolina, Chapel Hill, Chapel Hill, NC, United States of America
- Collaborative Studies Coordinating Center, University of North Carolina, Chapel Hill, Chapel Hill, NC, United States of America
| | - Vijay Nambi
- Baylor College of Medicine, Houston, TX, United States of America
- Michael E DeBakey Veterans Affairs Medical Center, Houston, TX, United States of America
| | | | - Myriam Fornage
- Human Genetics Center, Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, United States of America
- McGovern Medical School Institute of Molecular Medicine Research Center for Human Genetics, Houston, TX, United States of America
| | - Alanna C. Morrison
- Human Genetics Center, Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, United States of America
| | - Christy L. Avery
- Gillings School of Public Health, Department of Epidemiology, University of North Carolina, Chapel Hill, Chapel Hill, NC, United States of America
- Carolina Population Center, University of North Carolina–Chapel Hill, Chapel Hill, NC, United States of America
| | - Paul S. de Vries
- Human Genetics Center, Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, United States of America
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Tang J, Sheng C, Wu YY, Yan LL, Wu C. Association of Joint Genetic and Social Environmental Risks With Incident Myocardial Infarction: Results From the Health and Retirement Study. J Am Heart Assoc 2023; 12:e028200. [PMID: 36892065 PMCID: PMC10111548 DOI: 10.1161/jaha.122.028200] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 03/10/2023]
Abstract
Background Myocardial infarction (MI) is a significant clinical and public health problem worldwide. However, little research has assessed the interplay between genetic susceptibility and social environment in the development of MI. Methods and Results Data were from the HRS (Health and Retirement Study). The polygenic risk score and polysocial score for MI were classified as low, intermediate, and high. Using Cox regression models, we assessed the race-specific association of polygenic score and polysocial score with MI and examined the association between polysocial score and MI in each polygenic risk score category. We also examined the joint effect of genetic (low, intermediate, and high) and social environmental risks (low/intermediate, high) on MI. A total of 612 Black and 4795 White adults aged ≥65 years initially free of MI were included. We found a risk gradient of MI across the polygenic risk score and polysocial score among White participants; no significant risk gradient across the polygenic risk score was found among Black participants. A disadvantaged social environment was associated with a higher risk of incident MI among older White adults with intermediate and high genetic risk but not those with low genetic risk. We revealed the joint effect of genetics and social environment in the development of MI among White participants. Conclusions Living in a favorable social environment is particularly important for people with intermediate and high genetic risk for MI. It is critical to developing tailored interventions to improve social environment for disease prevention, especially among adults with a relatively high genetic risk.
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Affiliation(s)
- Junhan Tang
- Global Health Research Center Duke Kunshan University Kunshan Jiangsu China
| | - Chen Sheng
- Shanghai Medical College Fudan University Shanghai China
| | - Yan Yan Wu
- Thompson School of Social Work & Public Health University of Hawai'i at Mānoa HI Honolulu USA
| | - Lijing L Yan
- Global Health Research Center Duke Kunshan University Kunshan Jiangsu China
| | - Chenkai Wu
- Global Health Research Center Duke Kunshan University Kunshan Jiangsu China
- Duke Global Health Institute Duke University Durham NC USA
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Functionally Significant Variants in Genes Associated with Abdominal Obesity: A Review. J Pers Med 2023; 13:jpm13030460. [PMID: 36983642 PMCID: PMC10056771 DOI: 10.3390/jpm13030460] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2022] [Revised: 02/23/2023] [Accepted: 02/26/2023] [Indexed: 03/05/2023] Open
Abstract
The high prevalence of obesity and of its associated diseases is a major problem worldwide. Genetic predisposition and the influence of environmental factors contribute to the development of obesity. Changes in the structure and functional activity of genes encoding adipocytokines are involved in the predisposition to weight gain and obesity. In this review, variants in genes associated with adipocyte function are examined, as are variants in genes associated with metabolic aberrations and the accompanying disorders in visceral obesity.
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Parcha V, Pampana A, Shetty NS, Irvin MR, Natarajan P, Lin HJ, Guo X, Rich SS, Rotter JI, Li P, Oparil S, Arora G, Arora P. Association of a Multiancestry Genome-Wide Blood Pressure Polygenic Risk Score With Adverse Cardiovascular Events. CIRCULATION. GENOMIC AND PRECISION MEDICINE 2022; 15:e003946. [PMID: 36334310 PMCID: PMC9812363 DOI: 10.1161/circgen.122.003946] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/16/2022] [Accepted: 11/04/2022] [Indexed: 11/07/2022]
Abstract
BACKGROUND Traditional cardiovascular risk factors and the underlying genetic risk of elevated blood pressure (BP) determine an individual's composite risk of developing adverse cardiovascular events. We sought to evaluate the relative contributions of the traditional cardiovascular risk factors to the development of adverse cardiovascular events in the context of varying BP genetic risk profiles. METHODS Genome-wide polygenic risk score (PRS) was computed using multiancestry genome-wide association estimates among US adults who underwent whole-genome sequencing in the Trans-Omics for Precision program. Individuals were stratified into high, intermediate, and low genetic risk groups (>80th, 20-80th, and <20th centiles of systolic BP [SBP] PRS). Based on the ACC/AHA Pooled Cohort Equations, participants were stratified into low and high (10 year-atherosclerotic cardiovascular disease [CVD] risk: <10% or ≥10%) cardiovascular risk factor profile groups. The primary study outcome was incident cardiovascular event (composite of incident heart failure, incident stroke, and incident coronary heart disease). RESULTS Among 21 897 US adults (median age: 56 years; 56.0% women; 35.8% non-White race/ethnicity), 1 SD increase in the SBP PRS, computed using 1.08 million variants, was associated with SBP (β: 4.39 [95% CI, 4.13-4.65]) and hypertension (odds ratio, 1.50 [95% CI, 1.46-1.55]), respectively. This association was robustly seen across racial/ethnic groups. Each SD increase in SBP PRS was associated with a higher risk of the incident CVD (multivariable-adjusted hazards ratio, 1.07 [95% CI, 1.04-1.10]) after controlling for ACC/AHA Pooled Cohort Equations risk scores. Among individuals with a high SBP PRS, low atherosclerotic CVD risk was associated with a 58% lower hazard for incident CVD (multivariable-adjusted hazards ratio, 0.42 [95% CI, 0.36-0.50]) compared to those with high atherosclerotic CVD risk. A similar pattern was noted in intermediate and low genetic risk groups. CONCLUSIONS In a multiancestry cohort of >21 000 US adults, genome-wide SBP PRS was associated with BP traits and adverse cardiovascular events. Adequate control of modifiable cardiovascular risk factors may reduce the predisposition to adverse cardiovascular events among those with a high SBP PRS.
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Affiliation(s)
- Vibhu Parcha
- Division of Cardiovascular Disease, Univ of Alabama at Birmingham, Birmingham, AL
| | - Akhil Pampana
- Division of Cardiovascular Disease, Univ of Alabama at Birmingham, Birmingham, AL
| | - Naman S. Shetty
- Division of Cardiovascular Disease, Univ of Alabama at Birmingham, Birmingham, AL
| | - Marguerite R. Irvin
- Dept of Epidemiology, School of Public Health, Univ of Alabama at Birmingham, Birmingham, AL
| | - Pradeep Natarajan
- Cardiology Division, Dept of Medicine, Massachusetts General Hospital
- Cardiovascular Research Center, Massachusetts General Hospital, Harvard Medical School, Boston
- Program in Medical & Population Genetics, Broad Institute of Harvard & MIT, Cambridge, MA
| | - Henry J. Lin
- The Institute for Translational Genomics & Population Sciences, Dept of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA
| | - Xiuqing Guo
- The Institute for Translational Genomics & Population Sciences, Dept of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA
| | - Stephen S. Rich
- Center for Public Health, Univ of Virginia, Charlottesville, VA
| | - Jerome I. Rotter
- The Institute for Translational Genomics & Population Sciences, Dept of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA
| | - Peng Li
- School of Nursing, Univ of Alabama at Birmingham, Birmingham, AL
| | - Suzanne Oparil
- Division of Cardiovascular Disease, Univ of Alabama at Birmingham, Birmingham, AL
| | - Garima Arora
- Division of Cardiovascular Disease, Univ of Alabama at Birmingham, Birmingham, AL
| | - Pankaj Arora
- Division of Cardiovascular Disease, Univ of Alabama at Birmingham, Birmingham, AL
- Section of Cardiology, Birmingham Veterans Affairs Medical Center, Birmingham, AL
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Prognostic Modelling Studies of Coronary Heart Disease—A Systematic Review of Conventional and Genetic Risk Factor Studies. J Cardiovasc Dev Dis 2022; 9:jcdd9090295. [PMID: 36135440 PMCID: PMC9505820 DOI: 10.3390/jcdd9090295] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2022] [Revised: 08/19/2022] [Accepted: 08/25/2022] [Indexed: 11/25/2022] Open
Abstract
This study aims to provide an overview of multivariable prognostic modelling studies developed for coronary heart disease (CHD) in the general population and to explore the optimal prognostic model by comparing the models’ performance. A systematic review was performed using Embase, PubMed, Cochrane, Web of Science, and Scopus databases until 30 November 2019. In this work, only prognostic studies describing conventional risk factors alone or a combination of conventional and genomic risk factors, being developmental and/or validation prognostic studies of a multivariable model, were included. A total of 4021 records were screened by titles and abstracts, and 72 articles were eligible. All the relevant studies were checked by comparing the discrimination, reclassification, and calibration measures. Most of the models were developed in the United States and Canada and targeted the general population. The models included a set of similar predictors, such as age, sex, smoking, cholesterol level, blood pressure, BMI, and diabetes mellitus. In this study, many articles were identified and screened for consistency and reliability using CHARM and GRIPS statements. However, the usefulness of most prognostic models was not demonstrated; only a limited number of these models supported clinical evidence. Unfortunately, substantial heterogeneity was recognized in the definition and outcome of CHD events. The inclusion of genetic risk scores in addition to conventional risk factors might help in predicting the incidence of CHDs; however, the generalizability of the existing prognostic models remains open. Validation studies for the existing developmental models are needed to ensure generalizability, improve the research quality, and increase the transparency of the study.
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Mars N, Kerminen S, Feng YCA, Kanai M, Läll K, Thomas LF, Skogholt AH, della Briotta Parolo P, Neale BM, Smoller JW, Gabrielsen ME, Hveem K, Mägi R, Matsuda K, Okada Y, Pirinen M, Palotie A, Ganna A, Martin AR, Ripatti S. Genome-wide risk prediction of common diseases across ancestries in one million people. CELL GENOMICS 2022; 2:None. [PMID: 35591975 PMCID: PMC9010308 DOI: 10.1016/j.xgen.2022.100118] [Citation(s) in RCA: 26] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/21/2021] [Revised: 08/24/2021] [Accepted: 03/18/2022] [Indexed: 12/14/2022]
Abstract
Polygenic risk scores (PRS) measure genetic disease susceptibility by combining risk effects across the genome. For coronary artery disease (CAD), type 2 diabetes (T2D), and breast and prostate cancer, we performed cross-ancestry evaluation of genome-wide PRSs in six biobanks in Europe, the United States, and Asia. We studied transferability of these highly polygenic, genome-wide PRSs across global ancestries, within European populations with different health-care systems, and local population substructures in a population isolate. All four PRSs had similar accuracy across European and Asian populations, with poorer transferability in the smaller group of individuals of African ancestry. The PRSs had highly similar effect sizes in different populations of European ancestry, and in early- and late-settlement regions with different recent population bottlenecks in Finland. Comparing genome-wide PRSs to PRSs containing a smaller number of variants, the highly polygenic, genome-wide PRSs generally displayed higher effect sizes and better transferability across global ancestries. Our findings indicate that in the populations investigated, the current genome-wide polygenic scores for common diseases have potential for clinical utility within different health-care settings for individuals of European ancestry, but that the utility in individuals of African ancestry is currently much lower.
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Affiliation(s)
- Nina Mars
- Institute for Molecular Medicine Finland, FIMM, HiLIFE, University of Helsinki, Biomedicum 2U, Tukholmankatu 8, 00290 Helsinki, Finland
| | - Sini Kerminen
- Institute for Molecular Medicine Finland, FIMM, HiLIFE, University of Helsinki, Biomedicum 2U, Tukholmankatu 8, 00290 Helsinki, Finland
| | - Yen-Chen A. Feng
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA,Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA,Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA,Institute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan University, Taipei, Taiwan
| | - Masahiro Kanai
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA,Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA,Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Kristi Läll
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Laurent F. Thomas
- Department of Clinical and Molecular Medicine, Norwegian University of Science and Technology, Trondheim, Norway,K. G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Faculty of Medicine and Health, Norwegian University of Science and Technology, Trondheim, Norway,BioCore - Bioinformatics Core Facility, Norwegian University of Science and Technology, Trondheim, Norway
| | - Anne Heidi Skogholt
- K. G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Faculty of Medicine and Health, Norwegian University of Science and Technology, Trondheim, Norway
| | - Pietro della Briotta Parolo
- Institute for Molecular Medicine Finland, FIMM, HiLIFE, University of Helsinki, Biomedicum 2U, Tukholmankatu 8, 00290 Helsinki, Finland
| | | | | | - Benjamin M. Neale
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA,Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA,Harvard Medical School, Boston, MA, USA
| | - Jordan W. Smoller
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA,Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA,Harvard Medical School, Boston, MA, USA
| | - Maiken E. Gabrielsen
- K. G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Faculty of Medicine and Health, Norwegian University of Science and Technology, Trondheim, Norway,HUNT Research Center, Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway
| | - Kristian Hveem
- K. G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Faculty of Medicine and Health, Norwegian University of Science and Technology, Trondheim, Norway
| | - Reedik Mägi
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Koichi Matsuda
- Department of Computational Biology and Medical Sciences, Graduate school of Frontier Sciences, the University of Tokyo, Tokyo, Japan
| | - Yukinori Okada
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan,Laboratory of Statistical Immunology, Immunology Frontier Research Center (WPI-IFReC), Osaka University, Suita, Japan,Integrated Frontier Research for Medical Science Division, Institute for Open and Transdisciplinary Research Initiatives, Osaka University, Suita, Japan,Laboratory for Systems Genetics, RIKEN Center for Integrative Medical Sciences, Kanagawa, Japan
| | - Matti Pirinen
- Institute for Molecular Medicine Finland, FIMM, HiLIFE, University of Helsinki, Biomedicum 2U, Tukholmankatu 8, 00290 Helsinki, Finland,Department of Public Health, University of Helsinki, Helsinki, Finland,Department of Mathematics and Statistics, University of Helsinki, Helsinki, Finland
| | - Aarno Palotie
- Institute for Molecular Medicine Finland, FIMM, HiLIFE, University of Helsinki, Biomedicum 2U, Tukholmankatu 8, 00290 Helsinki, Finland,Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA,Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Andrea Ganna
- Institute for Molecular Medicine Finland, FIMM, HiLIFE, University of Helsinki, Biomedicum 2U, Tukholmankatu 8, 00290 Helsinki, Finland,Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA,Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Alicia R. Martin
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA,Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA,Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Samuli Ripatti
- Institute for Molecular Medicine Finland, FIMM, HiLIFE, University of Helsinki, Biomedicum 2U, Tukholmankatu 8, 00290 Helsinki, Finland,Department of Public Health, University of Helsinki, Helsinki, Finland,Broad Institute of MIT and Harvard, Cambridge, MA, USA,Corresponding author
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Arthur VL, Li Z, Cao R, Oetting WS, Israni AK, Jacobson PA, Ritchie MD, Guan W, Chen J. A Multi-Marker Test for Analyzing Paired Genetic Data in Transplantation. Front Genet 2021; 12:745773. [PMID: 34721531 PMCID: PMC8548646 DOI: 10.3389/fgene.2021.745773] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2021] [Accepted: 09/23/2021] [Indexed: 12/02/2022] Open
Abstract
Emerging evidence suggests that donor/recipient matching in non-HLA (human leukocyte antigen) regions of the genome may impact transplant outcomes and recognizing these matching effects may increase the power of transplant genetics studies. Most available matching scores account for either single-nucleotide polymorphism (SNP) matching only or sum these SNP matching scores across multiple gene-coding regions, which makes it challenging to interpret the association findings. We propose a multi-marker Joint Score Test (JST) to jointly test for association between recipient genotype SNP effects and a gene-based matching score with transplant outcomes. This method utilizes Eigen decomposition as a dimension reduction technique to potentially increase statistical power by decreasing the degrees of freedom for the test. In addition, JST allows for the matching effect and the recipient genotype effect to follow different biological mechanisms, which is not the case for other multi-marker methods. Extensive simulation studies show that JST is competitive when compared with existing methods, such as the sequence kernel association test (SKAT), especially under scenarios where associated SNPs are in low linkage disequilibrium with non-associated SNPs or in gene regions containing a large number of SNPs. Applying the method to paired donor/recipient genetic data from kidney transplant studies yields various gene regions that are potentially associated with incidence of acute rejection after transplant.
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Affiliation(s)
- Victoria L. Arthur
- Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, United States
| | - Zhengbang Li
- Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, United States
- Departments of Statistics, Central China Normal University, Wuhan, China
| | - Rui Cao
- Division of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, MN, United States
| | - William S. Oetting
- Department of Experimental and Clinical Pharmacology, College of Pharmacy, University of Minnesota, Minneapolis, MN, United States
| | - Ajay K. Israni
- Minneapolis Medical Research Foundation, Minneapolis, MN, United States
- Department of Medicine, Hennepin County Medical Center, Minneapolis, MN, United States
- Department of Epidemiology and Community Health, University of Minnesota, Minneapolis, MN, United States
| | - Pamala A. Jacobson
- Department of Experimental and Clinical Pharmacology, College of Pharmacy, University of Minnesota, Minneapolis, MN, United States
| | - Marylyn D. Ritchie
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Weihua Guan
- Division of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, MN, United States
| | - Jinbo Chen
- Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, United States
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11
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Salas E, Farm M, Pich S, Onelöv L, Guillen K, Ortega I, Antovic JP, Soria JM. Predictive Ability of a Clinical-Genetic Risk Score for Venous Thromboembolism in Northern and Southern European Populations. TH OPEN 2021; 5:e303-e311. [PMID: 34263111 PMCID: PMC8266419 DOI: 10.1055/s-0041-1729626] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2020] [Accepted: 03/01/2021] [Indexed: 11/01/2022] Open
Abstract
Venous thromboembolism (VTE) is a complex, multifactorial problem, the development of which depends on a combination of genetic and acqfiguired risk factors. In a Spanish population, the Thrombo inCode score (or TiC score), which combines clinical and genetic risk components, was recently proven better at determining the risk of VTE than the commonly used model involving the analysis of two genetic variants associated with thrombophilia: the Factor V Leiden (F5 rs6025) and the G20210A prothrombin (F2 rs1799963). The aim of the present case-control study was to validate the VTE risk predictive capacity of the TiC score in a Northern European population (from Sweden). The study included 173 subjects with VTE and 196 controls. All were analyzed for the genetic risk variants included in the TiC gene panel. Standard measures -receiver operating characteristic (ROC) area under the curve (AUC), sensitivity, specificity, and odds ratio (OR)-were calculated. The TiC score returned an AUC value of 0.673, a sensitivity of 72.25%, a specificity of 60.62%, and an OR of 4.11. These AUC, sensitivity, and OR values are all greater than those associated with the currently used combination of genetic variants. A TiC version adjusted for the allelic frequencies of the Swedish population significantly improved its AUC value (0.783). In summary, the TiC score returned more reliable risk estimates for the studied Northern European population than did the analysis of the Factor V Leiden and the G20210A genetic variations in combination. Thus, the TiC score can be reliably used with European populations, despite differences in allelic frequencies.
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Affiliation(s)
- Eduardo Salas
- Scientific Department, Gendiag, c/ Lepant, 141-4-1, 08013 Barcelona, Spain
| | - Maria Farm
- Institute for Molecular Medicine and Surgery and Department of Clinical Chemistry, Karolinska Institutet and Karolinska University Hospital, Stockholm, Sweden
| | - Sara Pich
- Scientific Department, Gendiag, c/ Lepant, 141-4-1, 08013 Barcelona, Spain
| | - Liselotte Onelöv
- Institute for Molecular Medicine and Surgery and Department of Clinical Chemistry, Karolinska Institutet and Karolinska University Hospital, Stockholm, Sweden
| | - Kevin Guillen
- Scientific Department, Gendiag, c/ Lepant, 141-4-1, 08013 Barcelona, Spain
| | - Israel Ortega
- Scientific Department, Gendiag, c/ Lepant, 141-4-1, 08013 Barcelona, Spain
| | - Jovan P Antovic
- Institute for Molecular Medicine and Surgery and Department of Clinical Chemistry, Karolinska Institutet and Karolinska University Hospital, Stockholm, Sweden
| | - Jose Manuel Soria
- Genomic of Complex Diseases, Institut d'Investigació Sant Pau (IIB-Sant Pau), Barcelona, Spain
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12
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Roberts R, Fair J. Genetics, its role in preventing the pandemic of coronary artery disease. Clin Cardiol 2021; 44:771-779. [PMID: 34080689 PMCID: PMC8207986 DOI: 10.1002/clc.23627] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/03/2021] [Revised: 04/23/2021] [Accepted: 04/30/2021] [Indexed: 01/14/2023] Open
Abstract
Epidemiologists have claimed for decades that about 50% of predisposition for coronary artery disease (CAD) is genetic. Advances in technology made possible the discovery of hundreds of genetic risk variants predisposing to CAD. Multiple clinical trials have shown that cardiac events can be prevented by drugs to lower plasma low-density lipoprotein cholesterol (LDL-C). A major barrier to primary prevention is the lack of markers to identify those individuals at risk prior to the development of symptoms of the disease. Conventional risk factors are age-dependent, occurring mostly in the sixth or seventh decade, which is less than desirable for early primary prevention. A polygenic risk score, derived from the number of genetic risk variants predisposing to CAD inherited by an individual, has been evaluated in over 1 million individuals. The risk for CAD is stratified into high, intermediate, and low. Polygenic risk scores derived from retrospective genotyping of several clinical trials evaluating the effect of statin therapy or PCSK9 inhibitors show the genetic risk is reduced 40%-50% by decreasing plasma LDL-C. Prospective randomized placebo-controlled clinical trials document a 40%-50% reduction in cardiac events in individuals at high genetic risk associated with favorable lifestyle changes and increased physical activity. The polygenic risk score is not age-dependent and remains the same throughout life. Thus, the GRS is superior to conventional risk factors in identifying asymptomatic individuals at risk for CAD early in life for primary prevention. These results indicate clinical embracement of the GRS in primary prevention would be a paradigm shift in the treatment of the number one killer, CAD.
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Affiliation(s)
- Robert Roberts
- College of Medicine, Phoenix, St. Joseph's Hospital and Medical Center, The University of Arizona, Phoenix, Arizona, USA
| | - Jacques Fair
- College of Medicine, Phoenix, St. Joseph's Hospital and Medical Center, The University of Arizona, Phoenix, Arizona, USA
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13
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Semaev S, Shakhtshneider E. Genetic Risk Score for Coronary Heart Disease: Review. J Pers Med 2020; 10:jpm10040239. [PMID: 33233501 PMCID: PMC7712936 DOI: 10.3390/jpm10040239] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2020] [Revised: 11/05/2020] [Accepted: 11/17/2020] [Indexed: 12/27/2022] Open
Abstract
The present review deals with the stages of creation, methods of calculation, and the use of a genetic risk score for coronary heart disease in various populations. The concept of risk factors is generally recognized on the basis of the results of epidemiological studies in the 20th century; according to this concept, the high prevalence of diseases of the circulatory system is due to lifestyle characteristics and associated risk factors. An important and relevant task for the healthcare system is to identify the population segments most susceptible to cardiovascular diseases (CVDs). The level of individual risk of an unfavorable cardiovascular prognosis is determined by genetic factors in addition to lifestyle factors.
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Affiliation(s)
- Sergey Semaev
- Institute of Internal and Preventive Medicine—Branch of Institute of Cytology and Genetics, Siberian Branch of Russian Academy of Sciences (SB RAS), Bogatkova Str. 175/1, Novosibirsk 630089, Russia;
- Federal Research Center Institute of Cytology and Genetics, SB RAS, Prospekt Lavrentyeva 10, Novosibirsk 630090, Russia
| | - Elena Shakhtshneider
- Institute of Internal and Preventive Medicine—Branch of Institute of Cytology and Genetics, Siberian Branch of Russian Academy of Sciences (SB RAS), Bogatkova Str. 175/1, Novosibirsk 630089, Russia;
- Federal Research Center Institute of Cytology and Genetics, SB RAS, Prospekt Lavrentyeva 10, Novosibirsk 630090, Russia
- Correspondence: or ; Tel./Fax: +7-(383)-264-2516
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14
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Polygenic Risk Score: Clinically Useful Tool for Prediction of Cardiovascular Disease and Benefit from Lipid-Lowering Therapy? Cardiovasc Drugs Ther 2020; 35:627-635. [PMID: 33156471 PMCID: PMC8481165 DOI: 10.1007/s10557-020-07105-7] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 10/28/2020] [Indexed: 11/16/2022]
Abstract
Improvement in risk prediction of atherosclerotic cardiovascular disease (ASCVD) using information on the genetic predisposition at an individual level might offer new possibilities for the successful management of such complex trait. Latest developments in genetic research with the conduction of genome-wide association studies have facilitated a broader utility of polygenic risk score (PRS) as a potent risk prognosticator, being strongly associated with future cardiovascular events. Although its discriminative ability beyond traditional risk factors is still a matter of controversy, PRS possesses at least comparable risk information to that provided by traditional risk tools. More importantly, increased genetic risk for ASCVD might be discovered at younger ages, much longer before conventional risk factors become manifest, thereby providing a potent instrument for aggressive primordial and primary prevention in those at high risk. Furthermore, there is strong evidence that inherited risk may be successfully modulated by a healthy lifestyle or medication use (e.g., statins or PCSK-9 inhibitors). Here, we provide a short overview of the current research related to the possible application of PRS in clinical routine and critically discuss existing pitfalls, which still limit a widespread utility of PRS outside a research setting.
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15
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Pechlivanis S, Lehmann N, Hoffmann P, Nöthen MM, Jöckel KH, Erbel R, Moebus S. Risk prediction for coronary heart disease by a genetic risk score - results from the Heinz Nixdorf Recall study. BMC MEDICAL GENETICS 2020; 21:178. [PMID: 32912153 PMCID: PMC7487988 DOI: 10.1186/s12881-020-01113-y] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/14/2020] [Accepted: 08/31/2020] [Indexed: 01/14/2023]
Abstract
Background A Genetic risk score for coronary artery disease (CAD) improves the ability of predicting coronary heart disease (CHD). It is unclear whether i) the use of a CAD genetic risk score is superior to the measurement of coronary artery calcification (CAC) for CHD risk assessment and ii) the CHD risk assessment using a CAD genetic risk score differs between men and women. Methods We included 4041 participants (age-range: 45–76 years, 1919 men) of the Heinz Nixdorf Recall study without CHD or stroke at baseline. A standardized weighted CAD genetic risk score was constructed using 70 known genetic variants. The risk score was divided into quintiles (Q1-Q5). We specified low (Q1), intermediate (Q2-Q4) and high (Q5) genetic risk groups. Incident CHD was defined as fatal and non-fatal myocardial infarction, stroke and coronary death. The association between the genetic risk score and genetic risk groups with incident CHD was assessed using Cox models to estimate hazard ratios (HR) and 95%-confidence intervals (CI). The models were adjusted by age and sex (Model1), as well as by established CHD risk factors (RF) and CAC (Model2). The analyses were further stratified by sex and controlled for multiple testing. Results During a median follow-up time of 11.6 ± 3.7 years, 343 participants experienced CHD events (219 men). Per-standard deviation (SD) increase in the genetic risk score was associated with 18% increased risk for incident CHD (Model1: p = 0.002) which did not change after full adjustment (Model2: HR = 1.18 per-SD (p = 0.003)). In Model2 we observed a 60% increased CHD risk in the high (p = 0.009) compared to the low genetic risk group. Stratifying by sex, only men showed statistically significantly higher risk for CHD (Model2: HR = 1.23 per-SD (p = 0.004); intermediate: HR = 1.52 (p = 0.04) and high: HR = 1.88 (p = 0.008)) with no statistically significant risk observed in women. Conclusion Our results suggest that the CAD genetic risk score could be useful for CHD risk prediction, at least in men belonging to the higher genetic risk group, but it does not outbalance the value of CT-based quantification of CAC which works independently on both men and women and allows better risk stratification in both the genders.
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Affiliation(s)
- Sonali Pechlivanis
- Institute for Medical Informatics, Biometry and Epidemiology, University Hospital of Essen, University Duisburg-Essen, Essen, Germany.
| | - Nils Lehmann
- Institute for Medical Informatics, Biometry and Epidemiology, University Hospital of Essen, University Duisburg-Essen, Essen, Germany
| | - Per Hoffmann
- Department of Genomics, Life & Brain Center, University of Bonn, Bonn, Germany.,Division of Medical Genetics, Department of Biomedicine, University of Basel, Basel, Switzerland
| | - Markus M Nöthen
- Department of Genomics, Life & Brain Center, University of Bonn, Bonn, Germany
| | - Karl-Heinz Jöckel
- Institute for Medical Informatics, Biometry and Epidemiology, University Hospital of Essen, University Duisburg-Essen, Essen, Germany
| | - Raimund Erbel
- Institute for Medical Informatics, Biometry and Epidemiology, University Hospital of Essen, University Duisburg-Essen, Essen, Germany
| | - Susanne Moebus
- Institute for Medical Informatics, Biometry and Epidemiology, University Hospital of Essen, University Duisburg-Essen, Essen, Germany.,Centre for Urban Epidemiology, University Hospital Essen, Essen, Germany
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16
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Yanes T, McInerney-Leo AM, Law MH, Cummings S. The emerging field of polygenic risk scores and perspective for use in clinical care. Hum Mol Genet 2020; 29:R165-R176. [DOI: 10.1093/hmg/ddaa136] [Citation(s) in RCA: 27] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2020] [Revised: 06/30/2020] [Accepted: 07/01/2020] [Indexed: 02/06/2023] Open
Abstract
Abstract
Genetic testing is used widely for diagnostic, carrier and predictive testing in monogenic diseases. Until recently, there were no genetic testing options available for multifactorial complex diseases like heart disease, diabetes and cancer. Genome-wide association studies (GWAS) have been invaluable in identifying single-nucleotide polymorphisms (SNPs) associated with increased or decreased risk for hundreds of complex disorders. For a given disease, SNPs can be combined to generate a cumulative estimation of risk known as a polygenic risk score (PRS). After years of research, PRSs are increasingly used in clinical settings. In this article, we will review the literature on how both genome-wide and restricted PRSs are developed and the relative merit of each. The validation and evaluation of PRSs will also be discussed, including the recognition that PRS validity is intrinsically linked to the methodological and analytical approach of the foundation GWAS together with the ethnic characteristics of that cohort. Specifically, population differences may affect imputation accuracy, risk magnitude and direction. Even as PRSs are being introduced into clinical practice, there is a push to combine them with clinical and demographic risk factors to develop a holistic disease risk. The existing evidence regarding the clinical utility of PRSs is considered across four different domains: informing population screening programs, guiding therapeutic interventions, refining risk for families at high risk, and facilitating diagnosis and predicting prognostic outcomes. The evidence for clinical utility in relation to five well-studied disorders is summarized. The potential ethical, legal and social implications are also highlighted.
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Affiliation(s)
- Tatiane Yanes
- Dermatology Research Centre, The University of Queensland Diamantina Institute, The University of Queensland, Brisbane, QLD 4102, Australia
| | - Aideen M McInerney-Leo
- Dermatology Research Centre, The University of Queensland Diamantina Institute, The University of Queensland, Brisbane, QLD 4102, Australia
| | - Matthew H Law
- Statistical Genetics Lab, QIMR Berghofer Medical Research Institute, Herston QLD 4006, Australia
- Faculty of Health, School of Biomedical Sciences, and Institute of Health and Biomedical Innovation, Queensland University of Technology, Kelvin Grove QLD 4059, Australia
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17
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Dikilitas O, Schaid DJ, Kosel ML, Carroll RJ, Chute CG, Denny JA, Fedotov A, Feng Q, Hakonarson H, Jarvik GP, Lee MTM, Pacheco JA, Rowley R, Sleiman PM, Stein CM, Sturm AC, Wei WQ, Wiesner GL, Williams MS, Zhang Y, Manolio TA, Kullo IJ. Predictive Utility of Polygenic Risk Scores for Coronary Heart Disease in Three Major Racial and Ethnic Groups. Am J Hum Genet 2020; 106:707-716. [PMID: 32386537 DOI: 10.1016/j.ajhg.2020.04.002] [Citation(s) in RCA: 82] [Impact Index Per Article: 20.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2019] [Accepted: 03/31/2020] [Indexed: 12/28/2022] Open
Abstract
Because polygenic risk scores (PRSs) for coronary heart disease (CHD) are derived from mainly European ancestry (EA) cohorts, their validity in African ancestry (AA) and Hispanic ethnicity (HE) individuals is unclear. We investigated associations of "restricted" and genome-wide PRSs with CHD in three major racial and ethnic groups in the U.S. The eMERGE cohort (mean age 48 ± 14 years, 58% female) included 45,645 EA, 7,597 AA, and 2,493 HE individuals. We assessed two restricted PRSs (PRSTikkanen and PRSTada; 28 and 50 variants, respectively) and two genome-wide PRSs (PRSmetaGRS and PRSLDPred; 1.7 M and 6.6 M variants, respectively) derived from EA cohorts. Over a median follow-up of 11.1 years, 2,652 incident CHD events occurred. Hazard and odds ratios for the association of PRSs with CHD were similar in EA and HE cohorts but lower in AA cohorts. Genome-wide PRSs were more strongly associated with CHD than restricted PRSs were. PRSmetaGRS, the best performing PRS, was associated with CHD in all three cohorts; hazard ratios (95% CI) per 1 SD increase were 1.53 (1.46-1.60), 1.53 (1.23-1.90), and 1.27 (1.13-1.43) for incident CHD in EA, HE, and AA individuals, respectively. The hazard ratios were comparable in the EA and HE cohorts (pinteraction = 0.77) but were significantly attenuated in AA individuals (pinteraction= 2.9 × 10-3). These results highlight the potential clinical utility of PRSs for CHD as well as the need to assemble diverse cohorts to generate ancestry- and ethnicity PRSs.
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Affiliation(s)
- Ozan Dikilitas
- Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN 55905, USA
| | - Daniel J Schaid
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN 55905, USA
| | - Matthew L Kosel
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN 55905, USA
| | - Robert J Carroll
- Department of Biomedical Informatics, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN 37212, USA
| | - Christopher G Chute
- Schools of Medicine, Public Health, and Nursing, Johns Hopkins University, Baltimore, MD 21205, USA
| | - Joshua A Denny
- Department of Biomedical Informatics, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN 37212, USA
| | - Alex Fedotov
- Irving Institute for Clinical and Translational Research, Columbia University Medical Center, New York, NY 10032, USA
| | - QiPing Feng
- Division of Clinical Pharmacology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN 37212, USA
| | - Hakon Hakonarson
- Center for Applied Genomics, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Gail P Jarvik
- Department of Medicine, University of Washington, Seattle, WA 98195, USA
| | | | - Jennifer A Pacheco
- Center for Genetic Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA
| | - Robb Rowley
- National Human Genome Research Institute, Bethesda, MD 20892, USA
| | - Patrick M Sleiman
- Center for Applied Genomics, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - C Michael Stein
- Division of Clinical Pharmacology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN 37212, USA
| | | | - Wei-Qi Wei
- Department of Biomedical Informatics, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN 37212, USA
| | - Georgia L Wiesner
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN 37212, USA
| | | | | | - Teri A Manolio
- National Human Genome Research Institute, Bethesda, MD 20892, USA
| | - Iftikhar J Kullo
- Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN 55905, USA.
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18
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Abstract
PURPOSE OF REVIEW Large genome-wide association studies (GWAS) have identified variants accounting for a substantial portion of the heritable risk for coronary artery disease (CAD). These studies have catalyzed drug discovery and generated the possibility of improved risk prediction and stratification. Here, we review the current state-of-the art in polygenic risk scores (PRSs) and look to the future, as these scores move towards clinical application. RECENT FINDINGS Over the last decade, multilocus PRSs for CAD have expanded to include millions of variants and demonstrated strong association with CAD outcomes, even when adjusted for traditional risk factors. Recently, PRSs have shown better prediction of CAD outcomes than any single traditional risk factor alone. Advances in statistical methods used to generate PRSs have improved their predictive ability and transferability between populations with varied ancestries. Initial clinical studies have also demonstrated the potential of genetic information to impact shared decision-making between patients and providers, leading to improved outcomes. SUMMARY PRSs can improve risk stratification for CAD especially in white/European populations and have the potential to alter routine clinical care. However, unlocking this potential will require additional research in PRSs in nonwhite populations and substantial investment in clinical implementation studies.
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