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Wang J, Liu Z, Hu C, Zhao R, Zhu D, Xie Y, Zhang P, Cui M, Xu K, Zhao G, Jin L, Chen X, Suo C, Jiang Y. Healthy lifestyles are associated with alleviating the single-nucleotide polymorphism-based genetic risks of ischaemic stroke, intracerebral haemorrhage and myocardial infarction. Stroke Vasc Neurol 2024:svn-2024-003257. [PMID: 38925676 DOI: 10.1136/svn-2024-003257] [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: 03/24/2024] [Accepted: 06/04/2024] [Indexed: 06/28/2024] Open
Abstract
BACKGROUND Both genetic and lifestyle factors contribute to myocardial infarction (MI) and stroke, including ischaemic stroke (IS) and intracerebral haemorrhage (ICH). We explored how and the extent to which a healthy lifestyle, by considering a comprehensive list, could counteract the genetic risk of those diseases, respectively. METHODS 315 044 participants free of stroke and MI at baseline were identified from the UK Biobank. Genetic risk scores (GRS) for those diseases were constructed separately and categorised as low, intermediate and high by tertile. Lifestyle risk scores (LRS) were constructed separately using smoking, alcohol intake, physical activity, dietary patterns and sleep patterns. Similarly, participants were categorised into low, intermediate and high LRS. The data were analysed using Cox proportional hazard models. RESULTS Over a median follow-up of 12.8 years, 4642, 1046 and 9485 participants developed IS, ICH and MI, respectively. Compared with participants with low levels of GRS and LRS, the HRs of those with high levels of GRS and LRS were 3.45 (95% CI 2.71 to 4.41), 2.32 (95% CI 1.40 to 3.85) and 4.89 (95% CI 4.16 to 5.75) for IS, ICH and MI, respectively. Moreover, among participants with high GRS, the standardised 14-year rates of IS events were 4.40% (95% CI 3.45% to 5.36%) among those with high LRS. In contrast, it is only 1.78% (95% CI 1.63% to 1.94%) among those with low LRS. Similarly for MI, the high LRS group had standardised rates of 8.60% (95% CI 7.38% to 9.81%), compared with 3.34% (95% CI 3.12% to 3.56%) in low LRS. Among the high genetic risk group of ICH, the rate is reduced by about half compared low LRS to high LRS, although the rate was low for both (0.36% (95% CI 0.31% to 0.42%) and 0.71% (95% CI 0.36% to 1.05%), respectively). CONCLUSION Healthy lifestyles were substantially associated with a reduction in the risk of IS, ICH and MI and attenuated the genetic risk of IS, ICH and MI by at least half, respectively.
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Affiliation(s)
- Jingru Wang
- Department of Epidemiology and Ministry of Education Key Laboratory of Public Health Safety, School of Public Health, Fudan University, Shanghai, Shanghai, China
| | - Zhenqiu Liu
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, and National Clinical Research Center for Aging and Medicine, Huashan Hospital, Fudan University, Shanghai, Shanghai, China
- Fudan University Taizhou Institute of Health Sciences, Taizhou, Jiangsu, China
| | - Chengxin Hu
- Department of Cardiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China
| | - Renjia Zhao
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, and National Clinical Research Center for Aging and Medicine, Huashan Hospital, Fudan University, Shanghai, Shanghai, China
| | - Dongliang Zhu
- Department of Epidemiology and Ministry of Education Key Laboratory of Public Health Safety, School of Public Health, Fudan University, Shanghai, Shanghai, China
| | - Yijing Xie
- Department of Epidemiology and Ministry of Education Key Laboratory of Public Health Safety, School of Public Health, Fudan University, Shanghai, Shanghai, China
| | - Pengyan Zhang
- Department of Epidemiology and Ministry of Education Key Laboratory of Public Health Safety, School of Public Health, Fudan University, Shanghai, Shanghai, China
| | - Mei Cui
- Department of Neurology, Huashan Hospital, Fudan University, Shanghai, Shanghai, China
| | - Kelin Xu
- Department of Biostatistics, School of Public Health, Fudan University, Shanghai, Shanghai, China
| | - Genming Zhao
- Department of Epidemiology and Ministry of Education Key Laboratory of Public Health Safety, School of Public Health, Fudan University, Shanghai, Shanghai, China
| | - Li Jin
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, and National Clinical Research Center for Aging and Medicine, Huashan Hospital, Fudan University, Shanghai, Shanghai, China
- Fudan University Taizhou Institute of Health Sciences, Taizhou, Jiangsu, China
| | - Xingdong Chen
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, and National Clinical Research Center for Aging and Medicine, Huashan Hospital, Fudan University, Shanghai, Shanghai, China
- Fudan University Taizhou Institute of Health Sciences, Taizhou, Jiangsu, China
- Yiwu Research Institute of Fudan University, Yiwu, Zhejiang, China
| | - Chen Suo
- Department of Epidemiology and Ministry of Education Key Laboratory of Public Health Safety, School of Public Health, Fudan University, Shanghai, Shanghai, China
- Fudan University Taizhou Institute of Health Sciences, Taizhou, Jiangsu, China
- Shanghai Institute of Infectious Disease and Biosecurity, Shanghai, Shanghai, China
| | - Yanfeng Jiang
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, and National Clinical Research Center for Aging and Medicine, Huashan Hospital, Fudan University, Shanghai, Shanghai, China
- Fudan University Taizhou Institute of Health Sciences, Taizhou, Jiangsu, China
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Rout M, Tung GK, Singh JR, Mehra NK, Wander GS, Ralhan S, Sanghera DK. Polygenic Risk Score Assessment for Coronary Artery Disease in Asian Indians. J Cardiovasc Transl Res 2024:10.1007/s12265-024-10511-z. [PMID: 38658478 DOI: 10.1007/s12265-024-10511-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/24/2024] [Accepted: 04/11/2024] [Indexed: 04/26/2024]
Abstract
We evaluated the performance of various polygenic risk score (PRS) models derived from European (EU), South Asian (SA), and Punjabi Asian Indians (AI) studies on 13,974 subjects from AI ancestry. While all models successfully predicted Coronary artery disease (CAD) risk, the AI, SA, and EU + AI were superior predictors and more transportable than the EU model; the predictive performance in training and test sets was 18% and 22% higher in AI and EU + AI models, respectively than in EU. Comparing individuals with extreme PRS quartiles, the AI and EU + AI captured individuals with high CAD risk showed 2.6 to 4.6 times higher efficiency than the EU. Interestingly, including the clinical risk score did not significantly change the performance of any genetic model. The enrichment of diversity variants in EU PRS improves risk prediction and transportability. Establishing population-specific normative and risk factors and inclusion into genetic models would refine the risk stratification and improve the clinical utility of CAD PRS.
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Affiliation(s)
- Madhusmita Rout
- Department of Pediatrics, Section of Genetics, College of Medicine, University of Oklahoma Health Sciences Center, 940 Stanton L. Young Blvd., Rm 317 BMSB, Oklahoma City, OK, 73104, USA
| | - Gurleen Kaur Tung
- Department of Pediatrics, Section of Genetics, College of Medicine, University of Oklahoma Health Sciences Center, 940 Stanton L. Young Blvd., Rm 317 BMSB, Oklahoma City, OK, 73104, USA
| | | | | | | | - Sarju Ralhan
- Hero DMC Heart Institute, Ludhiana, Punjab, India
| | - Dharambir K Sanghera
- Department of Pediatrics, Section of Genetics, College of Medicine, University of Oklahoma Health Sciences Center, 940 Stanton L. Young Blvd., Rm 317 BMSB, Oklahoma City, OK, 73104, USA.
- Department of Pharmaceutical Sciences, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA.
- Department of Physiology, College of Medicine, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA.
- Oklahoma Center for Neuroscience, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA.
- Harold Hamm Diabetes Center, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA.
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Cornelissen A, Gadhoke NV, Ryan K, Hodonsky CJ, Mitchell R, Bihlmeyer NA, Duong T, Chen Z, Dikongue A, Sakamoto A, Sato Y, Kawakami R, Mori M, Kawai K, Fernandez R, Ghosh SKB, Braumann R, Abebe B, Kutys R, Kutyna M, Romero ME, Kolodgie FD, Miller CL, Hong CC, Grove ML, Brody JA, Sotoodehnia N, Arking DE, Schunkert H, Mitchell BD, Guo L, Virmani R, Finn AV. Polygenic Risk Score Associates With Atherosclerotic Plaque Characteristics at Autopsy. Arterioscler Thromb Vasc Biol 2024; 44:300-313. [PMID: 37916415 DOI: 10.1161/atvbaha.123.319818] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2023] [Accepted: 10/19/2023] [Indexed: 11/03/2023]
Abstract
BACKGROUND Polygenic risk scores (PRSs) for coronary artery disease (CAD) potentially improve cardiovascular risk prediction. However, their relationship with histopathologic features of CAD has never been examined systematically. METHODS From 4327 subjects referred to CVPath by the State of Maryland Office Chief Medical Examiner for sudden death between 1994 and 2015, 2455 cases were randomly selected for genotyping. We generated PRS from 291 known CAD risk loci. Detailed histopathologic examination of the coronary arteries was performed in all subjects. The primary study outcome measurements were histopathologic plaque features determining severity of atherosclerosis, including %stenosis, calcification, thin-cap fibroatheromas, and thrombotic CAD. RESULTS After exclusion of cases with insufficient DNA sample quality or with missing data, 954 cases (mean age, 48.8±14.7 years; 75.7% men) remained in the final study cohort. Subjects in the highest PRS quintile exhibited more severe atherosclerosis compared with subjects in the lowest quintile, with greater %stenosis (80.3%±27.0% versus 50.4%±38.7%; adjusted P<0.001) and a higher frequency of calcification (69.6% versus 35.8%; adjusted P=0.004) and thin-cap fibroatheroma (26.7% versus 9.5%; adjusted P=0.007). Even after adjustment for traditional CAD risk factors, subjects within the highest PRS quintile had higher odds of severe atherosclerosis (ie, ≥75% stenosis; adjusted odds ratio, 3.77 [95% CI, 2.10-6.78]; P<0.001) and plaque rupture (adjusted odds ratio, 4.05 [95% CI, 2.26-7.24]; P<0.001). Moreover, subjects within the highest quintile had higher odds of CAD-associated cause of death, especially among those aged ≤50 years (adjusted odds ratio, 4.08 [95% CI, 2.01-8.30]; P<0.001). No statistically significant associations were observed with plaque erosion after adjusting for covariates. CONCLUSIONS This is the first autopsy study investigating associations between PRS and atherosclerosis severity at the histopathologic level in subjects with sudden death. Our pathological analysis suggests PRS correlates with plaque burden and features of advanced atherosclerosis and may be useful as a method for CAD risk stratification, especially in younger subjects.
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Affiliation(s)
- Anne Cornelissen
- CVPath Institute, Gaithersburg, MD (A.C., N.V.G., A.D., A.S., Y.S., R. Kawakami, M.M., K.K., R.F., S.K.B.G., R.B., B.A., R. Kutys, M.K., M.E.R., F.D.K., L.G., R.V., A.V.F.)
- Department of Cardiology, University Hospital RWTH Aachen, Germany (A.C.)
| | - Neel V Gadhoke
- CVPath Institute, Gaithersburg, MD (A.C., N.V.G., A.D., A.S., Y.S., R. Kawakami, M.M., K.K., R.F., S.K.B.G., R.B., B.A., R. Kutys, M.K., M.E.R., F.D.K., L.G., R.V., A.V.F.)
| | - Kathleen Ryan
- Department of Medicine, University of Maryland School of Medicine, Baltimore (K.R., C.C.H., B.D.M., A.V.F.)
| | - Chani J Hodonsky
- Department of Public Health Sciences, Center for Public Health Genomics, University of Virginia School of Medicine, Charlottesville (C.J.H., C.L.M.)
| | - Rebecca Mitchell
- Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD (R.M., N.A.B., T.D., M.L.G., N.S., D.E.A.)
| | - Nathan A Bihlmeyer
- Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD (R.M., N.A.B., T.D., M.L.G., N.S., D.E.A.)
| | - ThuyVy Duong
- Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD (R.M., N.A.B., T.D., M.L.G., N.S., D.E.A.)
| | - Zhifen Chen
- Department of Cardiology, Deutsches Herzzentrum München, Technische Universität München, Munich, Germany (Z.C., H.S.)
- Deutsches Zentrum für Herz-und Kreislauferkrankungen (DZHK), Partner Site Munich Heart Alliance, Germany (Z.C., H.S.)
| | - Armelle Dikongue
- CVPath Institute, Gaithersburg, MD (A.C., N.V.G., A.D., A.S., Y.S., R. Kawakami, M.M., K.K., R.F., S.K.B.G., R.B., B.A., R. Kutys, M.K., M.E.R., F.D.K., L.G., R.V., A.V.F.)
| | - Atsushi Sakamoto
- CVPath Institute, Gaithersburg, MD (A.C., N.V.G., A.D., A.S., Y.S., R. Kawakami, M.M., K.K., R.F., S.K.B.G., R.B., B.A., R. Kutys, M.K., M.E.R., F.D.K., L.G., R.V., A.V.F.)
| | - Yu Sato
- CVPath Institute, Gaithersburg, MD (A.C., N.V.G., A.D., A.S., Y.S., R. Kawakami, M.M., K.K., R.F., S.K.B.G., R.B., B.A., R. Kutys, M.K., M.E.R., F.D.K., L.G., R.V., A.V.F.)
| | - Rika Kawakami
- CVPath Institute, Gaithersburg, MD (A.C., N.V.G., A.D., A.S., Y.S., R. Kawakami, M.M., K.K., R.F., S.K.B.G., R.B., B.A., R. Kutys, M.K., M.E.R., F.D.K., L.G., R.V., A.V.F.)
| | - Masayuki Mori
- CVPath Institute, Gaithersburg, MD (A.C., N.V.G., A.D., A.S., Y.S., R. Kawakami, M.M., K.K., R.F., S.K.B.G., R.B., B.A., R. Kutys, M.K., M.E.R., F.D.K., L.G., R.V., A.V.F.)
| | - Kenji Kawai
- CVPath Institute, Gaithersburg, MD (A.C., N.V.G., A.D., A.S., Y.S., R. Kawakami, M.M., K.K., R.F., S.K.B.G., R.B., B.A., R. Kutys, M.K., M.E.R., F.D.K., L.G., R.V., A.V.F.)
| | - Raquel Fernandez
- CVPath Institute, Gaithersburg, MD (A.C., N.V.G., A.D., A.S., Y.S., R. Kawakami, M.M., K.K., R.F., S.K.B.G., R.B., B.A., R. Kutys, M.K., M.E.R., F.D.K., L.G., R.V., A.V.F.)
| | - Saikat Kumar B Ghosh
- CVPath Institute, Gaithersburg, MD (A.C., N.V.G., A.D., A.S., Y.S., R. Kawakami, M.M., K.K., R.F., S.K.B.G., R.B., B.A., R. Kutys, M.K., M.E.R., F.D.K., L.G., R.V., A.V.F.)
| | - Ryan Braumann
- CVPath Institute, Gaithersburg, MD (A.C., N.V.G., A.D., A.S., Y.S., R. Kawakami, M.M., K.K., R.F., S.K.B.G., R.B., B.A., R. Kutys, M.K., M.E.R., F.D.K., L.G., R.V., A.V.F.)
| | - Biniyam Abebe
- CVPath Institute, Gaithersburg, MD (A.C., N.V.G., A.D., A.S., Y.S., R. Kawakami, M.M., K.K., R.F., S.K.B.G., R.B., B.A., R. Kutys, M.K., M.E.R., F.D.K., L.G., R.V., A.V.F.)
| | - Robert Kutys
- CVPath Institute, Gaithersburg, MD (A.C., N.V.G., A.D., A.S., Y.S., R. Kawakami, M.M., K.K., R.F., S.K.B.G., R.B., B.A., R. Kutys, M.K., M.E.R., F.D.K., L.G., R.V., A.V.F.)
| | - Matthew Kutyna
- CVPath Institute, Gaithersburg, MD (A.C., N.V.G., A.D., A.S., Y.S., R. Kawakami, M.M., K.K., R.F., S.K.B.G., R.B., B.A., R. Kutys, M.K., M.E.R., F.D.K., L.G., R.V., A.V.F.)
| | - Maria E Romero
- CVPath Institute, Gaithersburg, MD (A.C., N.V.G., A.D., A.S., Y.S., R. Kawakami, M.M., K.K., R.F., S.K.B.G., R.B., B.A., R. Kutys, M.K., M.E.R., F.D.K., L.G., R.V., A.V.F.)
| | - Frank D Kolodgie
- CVPath Institute, Gaithersburg, MD (A.C., N.V.G., A.D., A.S., Y.S., R. Kawakami, M.M., K.K., R.F., S.K.B.G., R.B., B.A., R. Kutys, M.K., M.E.R., F.D.K., L.G., R.V., A.V.F.)
| | - Clint L Miller
- Department of Public Health Sciences, Center for Public Health Genomics, University of Virginia School of Medicine, Charlottesville (C.J.H., C.L.M.)
| | - Charles C Hong
- Department of Medicine, University of Maryland School of Medicine, Baltimore (K.R., C.C.H., B.D.M., A.V.F.)
| | - Megan L Grove
- Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD (R.M., N.A.B., T.D., M.L.G., N.S., D.E.A.)
| | - Jennifer A Brody
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle (J.A.B.)
| | - Nona Sotoodehnia
- Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD (R.M., N.A.B., T.D., M.L.G., N.S., D.E.A.)
| | - Dan E Arking
- Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD (R.M., N.A.B., T.D., M.L.G., N.S., D.E.A.)
| | - Heribert Schunkert
- Department of Cardiology, Deutsches Herzzentrum München, Technische Universität München, Munich, Germany (Z.C., H.S.)
- Deutsches Zentrum für Herz-und Kreislauferkrankungen (DZHK), Partner Site Munich Heart Alliance, Germany (Z.C., H.S.)
| | - Braxton D Mitchell
- Department of Medicine, University of Maryland School of Medicine, Baltimore (K.R., C.C.H., B.D.M., A.V.F.)
- Geriatrics Research and Education Clinical Center, Baltimore Veterans Administration Medical Center, MD (B.D.M.)
| | - Liang Guo
- CVPath Institute, Gaithersburg, MD (A.C., N.V.G., A.D., A.S., Y.S., R. Kawakami, M.M., K.K., R.F., S.K.B.G., R.B., B.A., R. Kutys, M.K., M.E.R., F.D.K., L.G., R.V., A.V.F.)
| | - Renu Virmani
- CVPath Institute, Gaithersburg, MD (A.C., N.V.G., A.D., A.S., Y.S., R. Kawakami, M.M., K.K., R.F., S.K.B.G., R.B., B.A., R. Kutys, M.K., M.E.R., F.D.K., L.G., R.V., A.V.F.)
| | - Aloke V Finn
- CVPath Institute, Gaithersburg, MD (A.C., N.V.G., A.D., A.S., Y.S., R. Kawakami, M.M., K.K., R.F., S.K.B.G., R.B., B.A., R. Kutys, M.K., M.E.R., F.D.K., L.G., R.V., A.V.F.)
- Department of Medicine, University of Maryland School of Medicine, Baltimore (K.R., C.C.H., B.D.M., A.V.F.)
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Harmata GIS, Barsotti EJ, Casten LG, Fiedorowicz JG, Williams A, Shaffer JJ, Richards JG, Sathyaputri L, Schmitz SL, Christensen GE, Long JD, Gaine ME, Xu J, Michaelson JJ, Wemmie JA, Magnotta VA. Cerebellar morphological differences and associations with extrinsic factors in bipolar disorder type I. J Affect Disord 2023; 340:269-279. [PMID: 37562560 PMCID: PMC10529949 DOI: 10.1016/j.jad.2023.08.018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/04/2023] [Revised: 07/18/2023] [Accepted: 08/03/2023] [Indexed: 08/12/2023]
Abstract
BACKGROUND The neural underpinnings of bipolar disorder (BD) remain poorly understood. The cerebellum is ideally positioned to modulate emotional regulation circuitry yet has been understudied in BD. Literature suggests differences in cerebellar activity and metabolism in BD, however findings on structural differences remain contradictory. Potential reasons include combining BD subtypes, small sample sizes, and potential moderators such as genetics, adverse childhood experiences (ACEs), and pharmacotherapy. METHODS We collected 3 T MRI scans from participants with (N = 131) and without (N = 81) BD type I, as well as blood and questionnaires. We assessed differences in cerebellar volumes and explored potentially influential factors. RESULTS The cerebellar cortex was smaller bilaterally in participants with BD. Polygenic propensity score did not predict any cerebellar volumes, suggesting that non-genetic factors may have greater influence on the cerebellar volume difference we observed in BD. Proportionate cerebellar white matter volumes appeared larger with more ACEs, but this may result from reduced ICV. Time from onset and symptom burden were not associated with cerebellar volumes. Finally, taking sedatives was associated with larger cerebellar white matter and non-significantly larger cortical volume. LIMITATIONS This study was cross-sectional, limiting interpretation of possible mechanisms. Most of our participants were White, which could limit the generalizability. Additionally, we did not account for potential polypharmacy interactions. CONCLUSIONS These findings suggest that external factors, such as sedatives and childhood experiences, may influence cerebellum structure in BD and may mask underlying differences. Accounting for such variables may be critical for consistent findings in future studies.
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Affiliation(s)
- Gail I S Harmata
- Department of Psychiatry, The University of Iowa, United States; Iowa Neuroscience Institute, The University of Iowa, United States; Department of Radiology, The University of Iowa, United States
| | - Ercole John Barsotti
- Department of Psychiatry, The University of Iowa, United States; Department of Epidemiology, The University of Iowa, United States
| | - Lucas G Casten
- Department of Psychiatry, The University of Iowa, United States; Interdisciplinary Graduate Program in Genetics, The University of Iowa, United States
| | - Jess G Fiedorowicz
- Department of Psychiatry, The University of Iowa, United States; Iowa Neuroscience Institute, The University of Iowa, United States; Department of Psychiatry, University of Ottawa, Canada
| | - Aislinn Williams
- Department of Psychiatry, The University of Iowa, United States; Iowa Neuroscience Institute, The University of Iowa, United States
| | - Joseph J Shaffer
- Department of Psychiatry, The University of Iowa, United States; Iowa Neuroscience Institute, The University of Iowa, United States; Department of Radiology, The University of Iowa, United States; Department of Biosciences, Kansas City University, United States
| | | | | | | | - Gary E Christensen
- Department of Electrical and Computer Engineering, The University of Iowa, United States; Department of Radiation Oncology, The University of Iowa, United States
| | - Jeffrey D Long
- Department of Psychiatry, The University of Iowa, United States; Department of Biostatistics, The University of Iowa, United States
| | - Marie E Gaine
- Department of Psychiatry, The University of Iowa, United States; Iowa Neuroscience Institute, The University of Iowa, United States; Department of Pharmaceutical Sciences and Experimental Therapeutics (PSET), College of Pharmacy, The University of Iowa, United States
| | - Jia Xu
- Department of Radiology, The University of Iowa, United States
| | - Jake J Michaelson
- Department of Psychiatry, The University of Iowa, United States; Iowa Neuroscience Institute, The University of Iowa, United States; Interdisciplinary Graduate Program in Genetics, The University of Iowa, United States
| | - John A Wemmie
- Department of Psychiatry, The University of Iowa, United States; Iowa Neuroscience Institute, The University of Iowa, United States; Department of Molecular Physiology and Biophysics, The University of Iowa, United States; Department of Neurosurgery, The University of Iowa, United States; Veterans Affairs Medical Center, Iowa City, United States
| | - Vincent A Magnotta
- Department of Psychiatry, The University of Iowa, United States; Iowa Neuroscience Institute, The University of Iowa, United States; Department of Radiology, The University of Iowa, United States; Department of Biomedical Engineering, The University of Iowa, United States.
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Manikpurage HD, Paulin A, Girard A, Eslami A, Mathieu P, Thériault S, Arsenault BJ. Contribution of Lipoprotein(a) to Polygenic Risk Prediction of Coronary Artery Disease: A Prospective UK Biobank Analysis. CIRCULATION. GENOMIC AND PRECISION MEDICINE 2023; 16:470-477. [PMID: 37753708 DOI: 10.1161/circgen.123.004137] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/02/2023] [Accepted: 08/23/2023] [Indexed: 09/28/2023]
Abstract
BACKGROUND Lp(a) (lipoprotein[a]) is a highly atherogenic lipoprotein subfraction that may contribute to polygenic risk of coronary artery disease (CAD), but the extent of this contribution is unknown. Our objective was to estimate the contribution of Lp(a) to polygenic risk of CAD and to evaluate the respective contributions of Lp(a) and a CAD polygenic risk score (PRS) to CAD. METHODS A total of 372 385 UK Biobank participants of European ancestry free of CAD at baseline were included. Plasma Lp(a) levels were measured and a CAD-PRS was calculated using the LDpred2 algorithm. Over the median follow-up of 12.6 years, 13 538 participants had incident CAD (myocardial infarction, coronary artery bypass grafting, or coronary angioplasty). RESULTS The LPA region contribution to the CAD-PRS-mediated CAD risk was modest (7.2% [95% CI, 6.1-8.3]). Lp(a) levels significantly increased the predictive performance of a CAD-PRS including age and sex in Cox regression (C statistic 0.751 versus 0.746, difference, 0.005 [95% CI, 0.004-0.006]). Compared with participants in the bottom CAD-PRS quintile with Lp(a) levels <25 nmol/L (CAD event rate, 1.4%), the hazard ratio for incident CAD in participants in the top CAD-PRS quintile with Lp(a) levels ≥125 nmol/L was 5.45 (95% CI, 4.93-6.03; P=9.35×10-242, CAD event rate 6.6%). CONCLUSIONS Compared with individuals with a low genetic risk of CAD (low CAD-PRS and low Lp[a] levels), those with a high genetic risk (high CAD-PRS and high Lp[a] levels) had a 5-fold higher CAD risk. These results highlight a substantial contribution of genetic risk factors to CAD and that accurate estimation of genetic risk of CAD may need to consider blood levels of Lp(a).
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Affiliation(s)
- Hasanga D Manikpurage
- Centre de recherche de l'Institut Universitaire de Cardiologie et de Pneumologie de Québec (H.D.M., A.P., A.G., A.E., P.M., S.T., B.J.A.), Faculty of Medicine, Université Laval, Québec (QC), Canada
| | - Audrey Paulin
- Centre de recherche de l'Institut Universitaire de Cardiologie et de Pneumologie de Québec (H.D.M., A.P., A.G., A.E., P.M., S.T., B.J.A.), Faculty of Medicine, Université Laval, Québec (QC), Canada
| | - Arnaud Girard
- Centre de recherche de l'Institut Universitaire de Cardiologie et de Pneumologie de Québec (H.D.M., A.P., A.G., A.E., P.M., S.T., B.J.A.), Faculty of Medicine, Université Laval, Québec (QC), Canada
| | - Aida Eslami
- Centre de recherche de l'Institut Universitaire de Cardiologie et de Pneumologie de Québec (H.D.M., A.P., A.G., A.E., P.M., S.T., B.J.A.), Faculty of Medicine, Université Laval, Québec (QC), Canada
- Department of Social and Preventive Medicine (A.E.), Faculty of Medicine, Université Laval, Québec (QC), Canada
| | - Patrick Mathieu
- Centre de recherche de l'Institut Universitaire de Cardiologie et de Pneumologie de Québec (H.D.M., A.P., A.G., A.E., P.M., S.T., B.J.A.), Faculty of Medicine, Université Laval, Québec (QC), Canada
- Department of Surgery (P.M.), Faculty of Medicine, Université Laval, Québec (QC), Canada
| | - Sébastien Thériault
- Centre de recherche de l'Institut Universitaire de Cardiologie et de Pneumologie de Québec (H.D.M., A.P., A.G., A.E., P.M., S.T., B.J.A.), Faculty of Medicine, Université Laval, Québec (QC), Canada
- Department of Molecular Biology, Medical Biochemistry and Pathology (S.T.), Faculty of Medicine, Université Laval, Québec (QC), Canada
| | - Benoit J Arsenault
- Centre de recherche de l'Institut Universitaire de Cardiologie et de Pneumologie de Québec (H.D.M., A.P., A.G., A.E., P.M., S.T., B.J.A.), Faculty of Medicine, Université Laval, Québec (QC), Canada
- Department of Medicine (B.J.A.), Faculty of Medicine, Université Laval, Québec (QC), Canada
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6
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Krittanawong C, Khawaja M, Tamis‐Holland JE, Girotra S, Rao SV. Acute Myocardial Infarction: Etiologies and Mimickers in Young Patients. J Am Heart Assoc 2023; 12:e029971. [PMID: 37724944 PMCID: PMC10547302 DOI: 10.1161/jaha.123.029971] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 09/21/2023]
Abstract
Acute myocardial infarction is an important cause of death worldwide. While it often affects patients of older age, acute myocardial infarction is garnering more attention as a significant cause of morbidity and mortality among young patients (<45 years of age). More specifically, there is a focus on recognizing the unique etiologies for myocardial infarction in these younger patients as nonatherosclerotic etiologies occur more frequently in this population. As such, there is a potential for delayed and inaccurate diagnoses and treatments that can carry serious clinical implications. The understanding of acute myocardial infarction manifestations in young patients is evolving, but there remains a significant need for better strategies to rapidly diagnose, risk stratify, and manage such patients. This comprehensive review explores the various etiologies for acute myocardial infarction in young adults and outlines the approach to efficient diagnosis and management for these unique patient phenotypes.
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Affiliation(s)
| | - Muzamil Khawaja
- Cardiology DivisionEmory University School of MedicineAtlantaGAUSA
| | | | - Saket Girotra
- Division of Cardiovascular MedicineUniversity of Texas Southwestern Medical CenterDallasTXUSA
| | - Sunil V. Rao
- New York University Langone Health SystemNew YorkNYUSA
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7
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Gupta R. Genetics-based risk scores for prediction of premature coronary artery disease. Indian Heart J 2023; 75:327-334. [PMID: 37633460 PMCID: PMC10568063 DOI: 10.1016/j.ihj.2023.08.003] [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: 01/30/2023] [Revised: 07/24/2023] [Accepted: 08/20/2023] [Indexed: 08/28/2023] Open
Abstract
Premature coronary artery disease (CAD) is endemic in India. Global Burden of Diseases study has reported that it led to 286,000 deaths in 2019 in India. Many of these patients have standard risk factors but a third have none. Clinical risk algorithms and imaging provide limited risk information in premature CAD. CAD is multifactorial and studies have now focused on the predictive capability of clusters of genes and single nucleotide polymorphisms (SNPs) using gene risk score (GRS). Older studies combined data from 10 to 12 genes and 100-500 SNPs to calculate GRS, however, following the advent of genome-wide association studies (GWAS), millions of SNPs have been incorporated. Studies have reported that GWAS-based GRS may be more discriminative than conventional tools. Recent studies, especially among South Asians, have reported that GRS improves net reclassification by 15% (12-19%) for younger individuals. Aggressive lifestyle interventions and lipid-lowering therapies can ameliorate risk in high-GRS individuals and potentially prevent premature CAD.
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Affiliation(s)
- Rajeev Gupta
- Department of Preventive Cardiology & Medicine, Eternal Heart Care Centre & Research Institute, Jaipur, India.
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8
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Patel AP, Wang M, Ruan Y, Koyama S, Clarke SL, Yang X, Tcheandjieu C, Agrawal S, Fahed AC, Ellinor PT, Tsao PS, Sun YV, Cho K, Wilson PWF, Assimes TL, van Heel DA, Butterworth AS, Aragam KG, Natarajan P, Khera AV. A multi-ancestry polygenic risk score improves risk prediction for coronary artery disease. Nat Med 2023; 29:1793-1803. [PMID: 37414900 PMCID: PMC10353935 DOI: 10.1038/s41591-023-02429-x] [Citation(s) in RCA: 26] [Impact Index Per Article: 26.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2022] [Accepted: 05/30/2023] [Indexed: 07/08/2023]
Abstract
Identification of individuals at highest risk of coronary artery disease (CAD)-ideally before onset-remains an important public health need. Prior studies have developed genome-wide polygenic scores to enable risk stratification, reflecting the substantial inherited component to CAD risk. Here we develop a new and significantly improved polygenic score for CAD, termed GPSMult, that incorporates genome-wide association data across five ancestries for CAD (>269,000 cases and >1,178,000 controls) and ten CAD risk factors. GPSMult strongly associated with prevalent CAD (odds ratio per standard deviation 2.14, 95% confidence interval 2.10-2.19, P < 0.001) in UK Biobank participants of European ancestry, identifying 20.0% of the population with 3-fold increased risk and conversely 13.9% with 3-fold decreased risk as compared with those in the middle quintile. GPSMult was also associated with incident CAD events (hazard ratio per standard deviation 1.73, 95% confidence interval 1.70-1.76, P < 0.001), identifying 3% of healthy individuals with risk of future CAD events equivalent to those with existing disease and significantly improving risk discrimination and reclassification. Across multiethnic, external validation datasets inclusive of 33,096, 124,467, 16,433 and 16,874 participants of African, European, Hispanic and South Asian ancestry, respectively, GPSMult demonstrated increased strength of associations across all ancestries and outperformed all available previously published CAD polygenic scores. These data contribute a new GPSMult for CAD to the field and provide a generalizable framework for how large-scale integration of genetic association data for CAD and related traits from diverse populations can meaningfully improve polygenic risk prediction.
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Affiliation(s)
- Aniruddh P Patel
- Division of Cardiology, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Center for Genomic Medicine, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA
| | - Minxian Wang
- CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, China.
| | - Yunfeng Ruan
- Center for Genomic Medicine, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Satoshi Koyama
- Center for Genomic Medicine, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Veteran Affairs Boston Healthcare System, Boston, MA, USA
| | - Shoa L Clarke
- Stanford University School of Medicine, Palo Alto, CA, USA
- Veterans Affairs Palo Alto Healthcare System, Palo Alto, CA, USA
| | - Xiong Yang
- CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, China
| | | | - Saaket Agrawal
- Center for Genomic Medicine, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - Akl C Fahed
- Division of Cardiology, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Center for Genomic Medicine, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA
| | - Patrick T Ellinor
- Division of Cardiology, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Center for Genomic Medicine, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA
| | - Philip S Tsao
- Stanford University School of Medicine, Palo Alto, CA, USA
- Veterans Affairs Palo Alto Healthcare System, Palo Alto, CA, USA
| | - Yan V Sun
- Veteran Affairs Atlanta Healthcare System, Decatur, GA, USA
| | - Kelly Cho
- Veteran Affairs Boston Healthcare System, Boston, MA, USA
| | | | - Themistocles L Assimes
- Stanford University School of Medicine, Palo Alto, CA, USA
- Veterans Affairs Palo Alto Healthcare System, Palo Alto, CA, USA
| | - David A van Heel
- Blizard Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Adam S Butterworth
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, and Centre of Research Excellence, University of Cambridge, Cambridge, UK
| | - Krishna G Aragam
- Division of Cardiology, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Center for Genomic Medicine, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA
| | - Pradeep Natarajan
- Division of Cardiology, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Center for Genomic Medicine, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA
| | - Amit V Khera
- Center for Genomic Medicine, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA.
- Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
- Department of Medicine, Harvard Medical School, Boston, MA, USA.
- Verve Therapeutics, Boston, MA, USA.
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9
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Khawaja M, Siddiqui R, Virani SS, Amos CI, Bandyopadhyay D, Virk HUH, Alam M, Jneid H, Krittanawong C. Integrative Genetic Approach Facilitates Precision Strategies for Acute Myocardial Infarction. Genes (Basel) 2023; 14:1340. [PMID: 37510245 PMCID: PMC10379681 DOI: 10.3390/genes14071340] [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: 05/22/2023] [Revised: 06/12/2023] [Accepted: 06/22/2023] [Indexed: 07/30/2023] Open
Abstract
Acute myocardial infarction remains a significant cause of mortality worldwide and its burden continues to grow. Its pathophysiology is known to be complex and multifactorial, with several acquired and inherited risk factors. As advances in technology and medical therapy continue, there is now increasing recognition of the role that genetics play in the development and management of myocardial infarction. The genetic determinants of acute coronary syndrome are still vastly understudied, but the advent of whole-genome scanning and genome-wide association studies has significantly expanded the current understanding of genetics and simultaneously fostered hope that genetic profiling and gene-guided treatments could substantially impact clinical outcomes. The identification of genes associated with acute myocardial infarction can help in the development of personalized medicine, risk stratification, and improved therapeutic strategies. In this context, several genes have been studied, and their potential involvement in increasing the risk for acute myocardial infarction is being investigated. As such, this article provides a review of some of the genes potentially related to an increased risk for acute myocardial infarction as well as the latest updates in gene-guided risk stratification and treatment strategies.
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Affiliation(s)
- Muzamil Khawaja
- Department of Cardiology, Emory University School of Medicine, Atlanta, GA 30322, USA
| | - Rehma Siddiqui
- Department of Internal Medicine, The University of Mississippi Medical Center, Jackson, MS 39216, USA
| | - Salim S Virani
- Department of Cardiology, The Aga Khan University, Karachi 74800, Pakistan
- Department of Cardiology, Baylor College of Medicine, Houston, TX 77030, USA
| | - Christopher I Amos
- Department of Medicine, Dan L Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, TX 77054, USA
| | - Dhrubajyoti Bandyopadhyay
- Department of Cardiology, Westchester Medical Centre, New York Medical College, Valhalla, NY 10595, USA
| | - Hafeez Ul Hassan Virk
- Department of Cardiology, University Hospitals Cleveland Medical Center, Case Western Reserve University, Cleveland, OH 44106, USA
| | - Mahboob Alam
- Department of Cardiology, The Texas Heart Institute, Baylor College of Medicine, Houston, TX 77030, USA
| | - Hani Jneid
- Department of Cardiology, University of Texas Medical Branch, Houston, TX 77030, USA
| | - Chayakrit Krittanawong
- Department of Cardiology, NYU Langone Health and NYU School of Medicine, New York, NY 10016, USA
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10
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Smith JL, Schaid DJ, Kullo IJ. Implementing Reporting Standards for Polygenic Risk Scores for Atherosclerotic Cardiovascular Disease. Curr Atheroscler Rep 2023; 25:323-330. [PMID: 37223852 PMCID: PMC10495216 DOI: 10.1007/s11883-023-01104-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/13/2023] [Indexed: 05/25/2023]
Abstract
PURPOSE OF REVIEW There is considerable interest in using polygenic risk scores (PRSs) for assessing risk of atherosclerotic cardiovascular disease (ASCVD). A barrier to the clinical use of PRSs is heterogeneity in how PRS studies are reported. In this review, we summarize approaches to establish a uniform reporting framework for PRSs for coronary heart disease (CHD), the most common form of ASCVD. RECENT FINDINGS Reporting standards for PRSs need to be contextualized for disease specific applications. In addition to metrics of predictive performance, reporting standards for PRSs for CHD should include how cases/control were ascertained, degree of adjustment for conventional CHD risk factors, portability to diverse genetic ancestry groups and admixed individuals, and quality control measures for clinical deployment. Such a framework will enable PRSs to be optimized and benchmarked for clinical use.
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Affiliation(s)
- Johanna L Smith
- Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN, USA
| | - Daniel J Schaid
- Department of Quantitative Health Sciences, Rochester, MN, USA
| | - Iftikhar J Kullo
- Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN, USA.
- Gonda Vascular Center, Rochester, MN, USA.
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11
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Tsao NL, Judy R, Levin MG, Shakt G, Voight BF, Chen J, Damrauer SM. Evaluation of the Performance of the RECODe Equation with the Addition of Polygenic Risk Scores for Adverse Cardiovascular Outcomes in Individuals with Type II Diabetes. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.05.03.23289457. [PMID: 37205500 PMCID: PMC10187440 DOI: 10.1101/2023.05.03.23289457] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/21/2023]
Abstract
Aims/Hypothesis Individuals with T2D are at an increased risk of developing cardiovascular complications; early identification of individuals can lead to an alteration of the natural history of the disease. Current approaches to risk prediction tailored to individuals with T2D are exemplified by the RECODe algorithms which predict CVD outcomes among individuals with T2D. Recent efforts to improve CVD risk prediction among the general population have included the incorporation of polygenic risk scores (PRS). This paper aims to investigate the utility of the addition of a coronary artery disease (CAD), stroke and heart failure risk score to the current RECODe model for disease stratification. Methods We derived PRS using summary statistics for ischemic stroke (IS) from the coronary artery disease (CAD) and heart failure (HF) and tested prediction accuracy in the Penn Medicine Biobank (PMBB). A Cox proportional hazards model was used for time-to-event analyses within our cohort, and we compared model discrimination for the RECODe model with and without a PRS using AUC. Results The RECODe model alone demonstrated an AUC [95% CI] of 0.67 [0.62-0.72] for ASCVD; the addition of the three PRS to the model demonstrated an AUC [95% CI] of 0.66 [0.63-0.70]. A z-test to compare the AUCs of the two models did not demonstrate a detectable difference between the two models (p=0.97). Conclusions/Interpretation In the present study, we demonstrate that although PRS associate with CVD outcomes independent of traditional risk factors among individuals with T2D, the addition of PRS to contemporary clinical risk models does not specifically improve the predictive performance as compared to the baseline model.
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Affiliation(s)
- Noah L. Tsao
- Corporal Michael Crescenz VA Medical Center, Philadelphia, PA, USA
- Department of Surgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Renae Judy
- Corporal Michael Crescenz VA Medical Center, Philadelphia, PA, USA
- Department of Surgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Michael G. Levin
- Corporal Michael Crescenz VA Medical Center, Philadelphia, PA, USA
- Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Gabrielle Shakt
- Corporal Michael Crescenz VA Medical Center, Philadelphia, PA, USA
- Department of Surgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | | | | | - Benjamin F. Voight
- Corporal Michael Crescenz VA Medical Center, Philadelphia, PA, USA
- Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Institute for Translational Medicine and Therapeutics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Jinbo Chen
- Department of Biostatistics and Epidemiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Scott M. Damrauer
- Corporal Michael Crescenz VA Medical Center, Philadelphia, PA, USA
- Department of Surgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Cardiovascular Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
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12
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Abstract
Polygenic scores quantify inherited risk by integrating information from many common sites of DNA variation into a single number. Rapid increases in the scale of genetic association studies and new statistical algorithms have enabled development of polygenic scores that meaningfully measure-as early as birth-risk of coronary artery disease. These newer-generation polygenic scores identify up to 8% of the population with triple the normal risk based on genetic variation alone, and these individuals cannot be identified on the basis of family history or clinical risk factors alone. For those identified with increased genetic risk, evidence supports risk reduction with at least two interventions, adherence to a healthy lifestyle and cholesterol-lowering therapies, that can substantially reduce risk. Alongside considerable enthusiasm for the potential of polygenic risk estimation to enable a new era of preventive clinical medicine is recognition of a need for ongoing research into how best to ensure equitable performance across diverse ancestries, how and in whom to assess the scores in clinical practice, as well as randomized trials to confirm clinical utility.
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Affiliation(s)
- Aniruddh P Patel
- Division of Cardiology and Center for Genomic Medicine, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA; , .,Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA.,Department of Medicine, Harvard Medical School, Boston, Massachusetts, USA
| | - Amit V Khera
- Division of Cardiology and Center for Genomic Medicine, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA; , .,Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA.,Department of Medicine, Harvard Medical School, Boston, Massachusetts, USA.,Verve Therapeutics, Cambridge, Massachusetts, USA
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13
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King A, Wu L, Deng HW, Shen H, Wu C. Polygenic risk score improves the accuracy of a clinical risk score for coronary artery disease. BMC Med 2022; 20:385. [PMID: 36336692 PMCID: PMC9639312 DOI: 10.1186/s12916-022-02583-y] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/14/2022] [Accepted: 09/26/2022] [Indexed: 11/09/2022] Open
Abstract
BACKGROUND The value of polygenic risk scores (PRSs) towards improving guideline-recommended clinical risk models for coronary artery disease (CAD) prediction is controversial. Here we examine whether an integrated polygenic risk score improves the prediction of CAD beyond pooled cohort equations. METHODS: An observation study of 291,305 unrelated White British UK Biobank participants enrolled from 2006 to 2010 was conducted. A case-control sample of 9499 prevalent CAD cases and an equal number of randomly selected controls was used for tuning and integrating of the polygenic risk scores. A separate cohort of 272,307 individuals (with follow-up to 2020) was used to examine the risk prediction performance of pooled cohort equations, integrated polygenic risk score, and PRS-enhanced pooled cohort equation for incident CAD cases. The performance of each model was analyzed by discrimination and risk reclassification using a 7.5% threshold. RESULTS In the cohort of 272,307 individuals (mean age, 56.7 years) used to analyze predictive accuracy, there were 7036 incident CAD cases over a 12-year follow-up period. Model discrimination was tested for integrated polygenic risk score, pooled cohort equation, and PRS-enhanced pooled cohort equation with reported C-statistics of 0.640 (95% CI, 0.634-0.646), 0.718 (95% CI, 0.713-0.723), and 0.753 (95% CI, 0.748-0.758), respectively. Risk reclassification for the addition of the integrated polygenic risk score to the pooled cohort equation at a 7.5% risk threshold resulted in a net reclassification improvement of 0.117 (95% CI, 0.102 to 0.129) for cases and - 0.023 (95% CI, - 0.025 to - 0.022) for noncases [overall: 0.093 (95% CI, 0.08 to 0.104)]. For incident CAD cases, this represented 14.2% correctly reclassified to the higher-risk category and 2.6% incorrectly reclassified to the lower-risk category. CONCLUSIONS Addition of the integrated polygenic risk score for CAD to the pooled cohort questions improves the predictive accuracy for incident CAD and clinical risk classification in the White British from the UK Biobank. These findings suggest that an integrated polygenic risk score may enhance CAD risk prediction and screening in the White British population.
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Affiliation(s)
- Austin King
- Department of Statistics, Florida State University, Tallahassee, FL, USA
| | - Lang Wu
- Cancer Epidemiology Division, Population Sciences in the Pacific Program, University of Hawaii Cancer Center, University of Hawaii at Manoa, Honolulu, HI, USA
| | - Hong-Wen Deng
- Center of Bioinformatics and Genomics, Department of Global Biostatistics and Data Science, Tulane University, New Orleans, LA, USA
| | - Hui Shen
- Center of Bioinformatics and Genomics, Department of Global Biostatistics and Data Science, Tulane University, New Orleans, LA, USA
| | - Chong Wu
- Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
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14
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St.-Pierre J, Zhang X, Lu T, Jiang L, Loffree X, Wang L, Bhatnagar S, Greenwood CMT. Considering strategies for SNP selection in genetic and polygenic risk scores. Front Genet 2022; 13:900595. [PMID: 36819922 PMCID: PMC9930898 DOI: 10.3389/fgene.2022.900595] [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: 03/20/2022] [Accepted: 10/05/2022] [Indexed: 02/04/2023] Open
Abstract
Genetic risk scores (GRS) and polygenic risk scores (PRS) are weighted sums of, respectively, several or many genetic variant indicator variables. Although they are being increasingly proposed for clinical use, the best ways to construct them are still actively debated. In this commentary, we present several case studies illustrating practical challenges associated with building or attempting to improve score performance when there is expected to be heterogeneity of disease risk between cohorts or between subgroups of individuals. Specifically, we contrast performance associated with several ways of selecting single nucleotide polymorphisms (SNPs) for inclusion in these scores. By considering GRS and PRS as predictors that are measured with error, insights into their strengths and weaknesses may be obtained, and SNP selection approaches play an important role in defining such errors.
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Affiliation(s)
- Julien St.-Pierre
- Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montréal, QC, Canada
| | - Xinyi Zhang
- Department of Statistical Sciences, University of Toronto, Toronto, ON, Canada
| | - Tianyuan Lu
- Lady Davis Institute for Medical Research, Jewish General Hospital, Montréal, QC, Canada,Quantitative Life Sciences, McGill University, Montréal, QC, Canada
| | - Lai Jiang
- Lady Davis Institute for Medical Research, Jewish General Hospital, Montréal, QC, Canada
| | - Xavier Loffree
- Lady Davis Institute for Medical Research, Jewish General Hospital, Montréal, QC, Canada,Department of Statistics and Actuarial Sciences, University of Waterloo, Waterloo, ON, Canada
| | - Linbo Wang
- Department of Statistical Sciences, University of Toronto, Toronto, ON, Canada
| | - Sahir Bhatnagar
- Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montréal, QC, Canada
| | - Celia M. T. Greenwood
- Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montréal, QC, Canada,Lady Davis Institute for Medical Research, Jewish General Hospital, Montréal, QC, Canada,Quantitative Life Sciences, McGill University, Montréal, QC, Canada,Gerald Bronfman Department of Oncology, McGill University, Montréal, QC, Canada,*Correspondence: Celia M. T. Greenwood,
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15
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Aggarwal B, Jelic S. Harnessing the Potential of Genetics to Understand the Impact of Sleep Apnea on Cardiovascular Risk. CIRCULATION. GENOMIC AND PRECISION MEDICINE 2022; 15:e003922. [PMID: 36173702 PMCID: PMC9588754 DOI: 10.1161/circgen.122.003922] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Affiliation(s)
- Brooke Aggarwal
- Division of Cardiology, Department of Medicine, Columbia University Irving Medical Center, New York, NY
- Sleep Center of Excellence, Department of Medicine, Columbia University Irving Medical Center, New York, NY
| | - Sanja Jelic
- Sleep Center of Excellence, Department of Medicine, Columbia University Irving Medical Center, New York, NY
- Division of Pulmonary, Allergy, and Critical Care Medicine, Columbia University Irving Medical Center, New York, NY
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Al Rifai M, Yao J, Guo X, Post WS, Malik S, Blumenthal RS, Ballantyne CM, Budoff M, Taylor KD, Lin HJ, Rich SS, Hajek C, Greenland P, Rotter JI, Virani SS. Association of polygenic risk scores with incident atherosclerotic cardiovascular disease events among individuals with coronary artery calcium score of zero: The multi-ethnic study of atherosclerosis. Prog Cardiovasc Dis 2022; 74:19-27. [PMID: 35952728 PMCID: PMC10240572 DOI: 10.1016/j.pcad.2022.08.003] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/02/2022] [Accepted: 08/02/2022] [Indexed: 11/29/2022]
Abstract
BACKGROUND Polygenic risk scores (PRS) are associated with atherosclerotic cardiovascular disease (ASCVD) events. We studied incident ASCVD among individuals with absent coronary artery calcium (CAC = 0), to investigate the association of PRS with incident ASCVD among such individuals. METHODS Data was used from Multi-Ethnic Study of Atherosclerosis (MESA), a prospective cohort study of participants free of clinical CVD at baseline. PRS were developed based on a literature-derived list of single-nucleotide polymorphisms (SNPs) weighted by effect size. The coronary heart disease (CHD) PRS contained 180 SNPs, and the stroke PRS had 32 SNPs. These SNPs were combined to compute an ASCVD PRS. The PRS were calculated among 3132 participants with CAC = 0. Multivariable-adjusted Cox proportional hazards models evaluated the association between each PRS (top 20% vs bottom 50%) and ASCVD. RESULTS The study population included 3132 individuals with CAC = 0 [mean (SD) age 58 (9) years; 63% female, 33% White, 31% Black, 12% Chinese-American, 24% Hispanic]. Over a median follow-up of 16 years, there were 108 incident CHD events and 93 stroke events. ASCVD event rates were generally <7.5 per 1000-person years for all ASCVD events regardless of PRS risk stratum. The ASCVD PRS was significantly associated with incident ASCVD: (HR; 95% CI) (1.63; 1.11, 2.39). The CHD PRS was not associated with any ASCVD outcome, whereas the stroke PRS was significantly associated with ASCVD (1.84; 1.27, 2.68), CHD (1.79; 1.05, 3.06), and stroke (1.96; 1.19, 3.23). The stroke PRS results were significant among women and non-Whites. CONCLUSIONS Among individuals with CAC = 0, the ASCVD PRS was associated with incident ASCVD events. This appears to be driven by genetic variants related to stroke but not CHD, and particularly among women and non-Whites. ASCVD event rates remained below the threshold recommended for consideration for initiation of statin therapy even in the high PRS groups.
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Affiliation(s)
- Mahmoud Al Rifai
- Section of Cardiology, Baylor College of Medicine, Houston, TX, United States of America
| | - Jie Yao
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, United States of America
| | - Xiuqing Guo
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, United States of America
| | - Wendy S Post
- The Ciccarone Center for the Prevention of Cardiovascular Disease, Johns Hopkins University, Baltimore, MD, United States of America
| | - Shaista Malik
- Division of Cardiology, University of California Irvine School of Medicine, Irvine, CA, United States of America
| | - Roger S Blumenthal
- The Ciccarone Center for the Prevention of Cardiovascular Disease, Johns Hopkins University, Baltimore, MD, United States of America
| | - Christie M Ballantyne
- Section of Cardiology, Baylor College of Medicine, Houston, TX, United States of America
| | - Matthew Budoff
- The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, United States of America
| | - Kent D Taylor
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, United States of America
| | - Henry J Lin
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, United States of America
| | - Stephen S Rich
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, United States of America
| | - Catherine Hajek
- Department of Internal Medicine and Medical Genetics, Sanford Health, Sioux Falls, SD, United States of America
| | - Philip Greenland
- Department of Preventive Medicine and Division of Cardiology, Northwestern University Feinberg School of Medicine, Chicago, IL, United States of America
| | - Jerome I Rotter
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, United States of America
| | - Salim S Virani
- Section of Cardiology, Baylor College of Medicine, Houston, TX, United States of America; Section of Cardiology, Michael E. DeBakey Veterans Affairs Medical Center, Houston, TX, United States of America.
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