Genomic Risk Prediction of Coronary Artery Disease in 480,000 Adults: Implications for Primary Prevention
Coronary artery disease (CAD) has substantial heritability and a polygenic architecture. However, the potential of genomic risk scores to help predict CAD outcomes has not been evaluated comprehensively, because available studies have involved limited genomic scope and limited sample sizes. This stu...
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| Veröffentlicht in: | Journal of the American College of Cardiology 2018-10, Vol.72 (16), p.1883-1893 |
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| creator | Inouye, Michael Abraham, Gad Nelson, Christopher P Wood, Angela M Sweeting, Michael J Dudbridge, Frank Lai, Florence Y Kaptoge, Stephen Brozynska, Marta Wang, Tingting Ye, Shu Webb, Thomas R Rutter, Martin K Tzoulaki, Ioanna Patel, Riyaz S Loos, Ruth J F Keavney, Bernard Hemingway, Harry Thompson, John Watkins, Hugh Deloukas, Panos Di Angelantonio, Emanuele Butterworth, Adam S Danesh, John Samani, Nilesh J |
| description | Coronary artery disease (CAD) has substantial heritability and a polygenic architecture. However, the potential of genomic risk scores to help predict CAD outcomes has not been evaluated comprehensively, because available studies have involved limited genomic scope and limited sample sizes.
This study sought to construct a genomic risk score for CAD and to estimate its potential as a screening tool for primary prevention.
Using a meta-analytic approach to combine large-scale, genome-wide, and targeted genetic association data, we developed a new genomic risk score for CAD (metaGRS) consisting of 1.7 million genetic variants. We externally tested metaGRS, both by itself and in combination with available data on conventional risk factors, in 22,242 CAD cases and 460,387 noncases from the UK Biobank.
The hazard ratio (HR) for CAD was 1.71 (95% confidence interval [CI]: 1.68 to 1.73) per SD increase in metaGRS, an association larger than any other externally tested genetic risk score previously published. The metaGRS stratified individuals into significantly different life course trajectories of CAD risk, with those in the top 20% of metaGRS distribution having an HR of 4.17 (95% CI: 3.97 to 4.38) compared with those in the bottom 20%. The corresponding HR was 2.83 (95% CI: 2.61 to 3.07) among individuals on lipid-lowering or antihypertensive medications. The metaGRS had a higher C-index (C = 0.623; 95% CI: 0.615 to 0.631) for incident CAD than any of 6 conventional factors (smoking, diabetes, hypertension, body mass index, self-reported high cholesterol, and family history). For men in the top 20% of metaGRS with >2 conventional factors, 10% cumulative risk of CAD was reached by 48 years of age.
The genomic score developed and evaluated here substantially advances the concept of using genomic information to stratify individuals with different trajectories of CAD risk and highlights the potential for genomic screening in early life to complement conventional risk prediction. |
| doi_str_mv | 10.1016/j.jacc.2018.07.079 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_pubme</sourceid><recordid>TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_6176870</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2117124277</sourcerecordid><originalsourceid>FETCH-LOGICAL-p294t-4ebc6323b9f6159084c1b907a05c0effa4e8faf2ef4b3e6ba8793680043166423</originalsourceid><addsrcrecordid>eNpdkdtKxDAQhoMouh5ewAsJeOOFXSdNmoMXwrIeQVBEr0uaTTRr26xNu-Dbm8UDKgQGMt9884cgtE9gTIDwk_l4ro0Z50DkGEQ6ag2NSFHIjBZKrKMRCFpkBJTYQtsxzgGAS6I20RYFCopxNkL-yrah8QY_-PiK7zs786b3ocXB4WnoQqu7dzzpepvKuY9WR4t9i5mE46TDk9lQ9_EU3zSL2hu9mozYhS6ZfLMaTcalbVf3u2jD6Trava-6g54uLx6n19nt3dXNdHKbLXLF-ozZynCa00o5TgoFkhlSKRAaCgPWOc2sdNrl1rGKWl5pKRTlEoBRwjnL6Q46-_QuhqqxM5O2d7ouF5-ByqB9-bfT-pfyOSxLTgSXApLg6EvQhbfBxr5sfDS2rnVrwxDLnBCl8rSJJfTwHzoPQ9em560oQRIlRKIOfif6ifL9C_QDRZ2KVw</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2117124277</pqid></control><display><type>article</type><title>Genomic Risk Prediction of Coronary Artery Disease in 480,000 Adults: Implications for Primary Prevention</title><source>MEDLINE</source><source>Elsevier ScienceDirect Journals</source><source>Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals</source><source>Alma/SFX Local Collection</source><creator>Inouye, Michael ; Abraham, Gad ; Nelson, Christopher P ; Wood, Angela M ; Sweeting, Michael J ; Dudbridge, Frank ; Lai, Florence Y ; Kaptoge, Stephen ; Brozynska, Marta ; Wang, Tingting ; Ye, Shu ; Webb, Thomas R ; Rutter, Martin K ; Tzoulaki, Ioanna ; Patel, Riyaz S ; Loos, Ruth J F ; Keavney, Bernard ; Hemingway, Harry ; Thompson, John ; Watkins, Hugh ; Deloukas, Panos ; Di Angelantonio, Emanuele ; Butterworth, Adam S ; Danesh, John ; Samani, Nilesh J</creator><creatorcontrib>Inouye, Michael ; Abraham, Gad ; Nelson, Christopher P ; Wood, Angela M ; Sweeting, Michael J ; Dudbridge, Frank ; Lai, Florence Y ; Kaptoge, Stephen ; Brozynska, Marta ; Wang, Tingting ; Ye, Shu ; Webb, Thomas R ; Rutter, Martin K ; Tzoulaki, Ioanna ; Patel, Riyaz S ; Loos, Ruth J F ; Keavney, Bernard ; Hemingway, Harry ; Thompson, John ; Watkins, Hugh ; Deloukas, Panos ; Di Angelantonio, Emanuele ; Butterworth, Adam S ; Danesh, John ; Samani, Nilesh J ; UK Biobank CardioMetabolic Consortium CHD Working Group</creatorcontrib><description>Coronary artery disease (CAD) has substantial heritability and a polygenic architecture. However, the potential of genomic risk scores to help predict CAD outcomes has not been evaluated comprehensively, because available studies have involved limited genomic scope and limited sample sizes.
This study sought to construct a genomic risk score for CAD and to estimate its potential as a screening tool for primary prevention.
Using a meta-analytic approach to combine large-scale, genome-wide, and targeted genetic association data, we developed a new genomic risk score for CAD (metaGRS) consisting of 1.7 million genetic variants. We externally tested metaGRS, both by itself and in combination with available data on conventional risk factors, in 22,242 CAD cases and 460,387 noncases from the UK Biobank.
The hazard ratio (HR) for CAD was 1.71 (95% confidence interval [CI]: 1.68 to 1.73) per SD increase in metaGRS, an association larger than any other externally tested genetic risk score previously published. The metaGRS stratified individuals into significantly different life course trajectories of CAD risk, with those in the top 20% of metaGRS distribution having an HR of 4.17 (95% CI: 3.97 to 4.38) compared with those in the bottom 20%. The corresponding HR was 2.83 (95% CI: 2.61 to 3.07) among individuals on lipid-lowering or antihypertensive medications. The metaGRS had a higher C-index (C = 0.623; 95% CI: 0.615 to 0.631) for incident CAD than any of 6 conventional factors (smoking, diabetes, hypertension, body mass index, self-reported high cholesterol, and family history). For men in the top 20% of metaGRS with >2 conventional factors, 10% cumulative risk of CAD was reached by 48 years of age.
The genomic score developed and evaluated here substantially advances the concept of using genomic information to stratify individuals with different trajectories of CAD risk and highlights the potential for genomic screening in early life to complement conventional risk prediction.</description><identifier>ISSN: 0735-1097</identifier><identifier>EISSN: 1558-3597</identifier><identifier>DOI: 10.1016/j.jacc.2018.07.079</identifier><identifier>PMID: 30309464</identifier><language>eng</language><publisher>United States: Elsevier Limited</publisher><subject>Adults ; Age ; Angioplasty ; Antihypertensives ; Assessment centers ; Blood pressure ; Body mass ; Body mass index ; Body size ; Cardiology ; Cardiovascular disease ; Cholesterol ; Confidence intervals ; Coronary artery ; Coronary artery disease ; Coronary Artery Disease - diagnosis ; Coronary Artery Disease - epidemiology ; Coronary Artery Disease - genetics ; Coronary vessels ; Diabetes ; Diabetes mellitus ; Disease prevention ; Family medical history ; Female ; Genetic diversity ; Genetic variance ; Genetics ; Genome-Wide Association Study ; Genomes ; Genomics - methods ; Genomics - statistics & numerical data ; Health and safety screening ; Health risk assessment ; Health risks ; Heart attacks ; Heart diseases ; Heritability ; Hospitals ; Humans ; Hypertension ; Lipids ; Male ; Mass Screening - methods ; Middle Aged ; Multifactorial Inheritance ; Population ; Predictive Value of Tests ; Primary Prevention - methods ; Research Design ; Risk analysis ; Risk Assessment - methods ; Risk Factors ; Smoking ; Studies ; Trajectories ; United Kingdom - epidemiology</subject><ispartof>Journal of the American College of Cardiology, 2018-10, Vol.72 (16), p.1883-1893</ispartof><rights>Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.</rights><rights>Copyright Elsevier Limited Oct 16, 2018</rights><rights>2018 The Authors 2018</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>230,314,776,780,881,27901,27902</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/30309464$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Inouye, Michael</creatorcontrib><creatorcontrib>Abraham, Gad</creatorcontrib><creatorcontrib>Nelson, Christopher P</creatorcontrib><creatorcontrib>Wood, Angela M</creatorcontrib><creatorcontrib>Sweeting, Michael J</creatorcontrib><creatorcontrib>Dudbridge, Frank</creatorcontrib><creatorcontrib>Lai, Florence Y</creatorcontrib><creatorcontrib>Kaptoge, Stephen</creatorcontrib><creatorcontrib>Brozynska, Marta</creatorcontrib><creatorcontrib>Wang, Tingting</creatorcontrib><creatorcontrib>Ye, Shu</creatorcontrib><creatorcontrib>Webb, Thomas R</creatorcontrib><creatorcontrib>Rutter, Martin K</creatorcontrib><creatorcontrib>Tzoulaki, Ioanna</creatorcontrib><creatorcontrib>Patel, Riyaz S</creatorcontrib><creatorcontrib>Loos, Ruth J F</creatorcontrib><creatorcontrib>Keavney, Bernard</creatorcontrib><creatorcontrib>Hemingway, Harry</creatorcontrib><creatorcontrib>Thompson, John</creatorcontrib><creatorcontrib>Watkins, Hugh</creatorcontrib><creatorcontrib>Deloukas, Panos</creatorcontrib><creatorcontrib>Di Angelantonio, Emanuele</creatorcontrib><creatorcontrib>Butterworth, Adam S</creatorcontrib><creatorcontrib>Danesh, John</creatorcontrib><creatorcontrib>Samani, Nilesh J</creatorcontrib><creatorcontrib>UK Biobank CardioMetabolic Consortium CHD Working Group</creatorcontrib><title>Genomic Risk Prediction of Coronary Artery Disease in 480,000 Adults: Implications for Primary Prevention</title><title>Journal of the American College of Cardiology</title><addtitle>J Am Coll Cardiol</addtitle><description>Coronary artery disease (CAD) has substantial heritability and a polygenic architecture. However, the potential of genomic risk scores to help predict CAD outcomes has not been evaluated comprehensively, because available studies have involved limited genomic scope and limited sample sizes.
This study sought to construct a genomic risk score for CAD and to estimate its potential as a screening tool for primary prevention.
Using a meta-analytic approach to combine large-scale, genome-wide, and targeted genetic association data, we developed a new genomic risk score for CAD (metaGRS) consisting of 1.7 million genetic variants. We externally tested metaGRS, both by itself and in combination with available data on conventional risk factors, in 22,242 CAD cases and 460,387 noncases from the UK Biobank.
The hazard ratio (HR) for CAD was 1.71 (95% confidence interval [CI]: 1.68 to 1.73) per SD increase in metaGRS, an association larger than any other externally tested genetic risk score previously published. The metaGRS stratified individuals into significantly different life course trajectories of CAD risk, with those in the top 20% of metaGRS distribution having an HR of 4.17 (95% CI: 3.97 to 4.38) compared with those in the bottom 20%. The corresponding HR was 2.83 (95% CI: 2.61 to 3.07) among individuals on lipid-lowering or antihypertensive medications. The metaGRS had a higher C-index (C = 0.623; 95% CI: 0.615 to 0.631) for incident CAD than any of 6 conventional factors (smoking, diabetes, hypertension, body mass index, self-reported high cholesterol, and family history). For men in the top 20% of metaGRS with >2 conventional factors, 10% cumulative risk of CAD was reached by 48 years of age.
The genomic score developed and evaluated here substantially advances the concept of using genomic information to stratify individuals with different trajectories of CAD risk and highlights the potential for genomic screening in early life to complement conventional risk prediction.</description><subject>Adults</subject><subject>Age</subject><subject>Angioplasty</subject><subject>Antihypertensives</subject><subject>Assessment centers</subject><subject>Blood pressure</subject><subject>Body mass</subject><subject>Body mass index</subject><subject>Body size</subject><subject>Cardiology</subject><subject>Cardiovascular disease</subject><subject>Cholesterol</subject><subject>Confidence intervals</subject><subject>Coronary artery</subject><subject>Coronary artery disease</subject><subject>Coronary Artery Disease - diagnosis</subject><subject>Coronary Artery Disease - epidemiology</subject><subject>Coronary Artery Disease - genetics</subject><subject>Coronary vessels</subject><subject>Diabetes</subject><subject>Diabetes mellitus</subject><subject>Disease prevention</subject><subject>Family medical history</subject><subject>Female</subject><subject>Genetic diversity</subject><subject>Genetic variance</subject><subject>Genetics</subject><subject>Genome-Wide Association Study</subject><subject>Genomes</subject><subject>Genomics - methods</subject><subject>Genomics - statistics & numerical data</subject><subject>Health and safety screening</subject><subject>Health risk assessment</subject><subject>Health risks</subject><subject>Heart attacks</subject><subject>Heart diseases</subject><subject>Heritability</subject><subject>Hospitals</subject><subject>Humans</subject><subject>Hypertension</subject><subject>Lipids</subject><subject>Male</subject><subject>Mass Screening - methods</subject><subject>Middle Aged</subject><subject>Multifactorial Inheritance</subject><subject>Population</subject><subject>Predictive Value of Tests</subject><subject>Primary Prevention - methods</subject><subject>Research Design</subject><subject>Risk analysis</subject><subject>Risk Assessment - methods</subject><subject>Risk Factors</subject><subject>Smoking</subject><subject>Studies</subject><subject>Trajectories</subject><subject>United Kingdom - epidemiology</subject><issn>0735-1097</issn><issn>1558-3597</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNpdkdtKxDAQhoMouh5ewAsJeOOFXSdNmoMXwrIeQVBEr0uaTTRr26xNu-Dbm8UDKgQGMt9884cgtE9gTIDwk_l4ro0Z50DkGEQ6ag2NSFHIjBZKrKMRCFpkBJTYQtsxzgGAS6I20RYFCopxNkL-yrah8QY_-PiK7zs786b3ocXB4WnoQqu7dzzpepvKuY9WR4t9i5mE46TDk9lQ9_EU3zSL2hu9mozYhS6ZfLMaTcalbVf3u2jD6Trava-6g54uLx6n19nt3dXNdHKbLXLF-ozZynCa00o5TgoFkhlSKRAaCgPWOc2sdNrl1rGKWl5pKRTlEoBRwjnL6Q46-_QuhqqxM5O2d7ouF5-ByqB9-bfT-pfyOSxLTgSXApLg6EvQhbfBxr5sfDS2rnVrwxDLnBCl8rSJJfTwHzoPQ9em560oQRIlRKIOfif6ifL9C_QDRZ2KVw</recordid><startdate>20181016</startdate><enddate>20181016</enddate><creator>Inouye, Michael</creator><creator>Abraham, Gad</creator><creator>Nelson, Christopher P</creator><creator>Wood, Angela M</creator><creator>Sweeting, Michael J</creator><creator>Dudbridge, Frank</creator><creator>Lai, Florence Y</creator><creator>Kaptoge, Stephen</creator><creator>Brozynska, Marta</creator><creator>Wang, Tingting</creator><creator>Ye, Shu</creator><creator>Webb, Thomas R</creator><creator>Rutter, Martin K</creator><creator>Tzoulaki, Ioanna</creator><creator>Patel, Riyaz S</creator><creator>Loos, Ruth J F</creator><creator>Keavney, Bernard</creator><creator>Hemingway, Harry</creator><creator>Thompson, John</creator><creator>Watkins, Hugh</creator><creator>Deloukas, Panos</creator><creator>Di Angelantonio, Emanuele</creator><creator>Butterworth, Adam S</creator><creator>Danesh, John</creator><creator>Samani, Nilesh J</creator><general>Elsevier Limited</general><general>Elsevier Biomedical</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>7T5</scope><scope>7TK</scope><scope>H94</scope><scope>K9.</scope><scope>NAPCQ</scope><scope>7X8</scope><scope>5PM</scope></search><sort><creationdate>20181016</creationdate><title>Genomic Risk Prediction of Coronary Artery Disease in 480,000 Adults: Implications for Primary Prevention</title><author>Inouye, Michael ; Abraham, Gad ; Nelson, Christopher P ; Wood, Angela M ; Sweeting, Michael J ; Dudbridge, Frank ; Lai, Florence Y ; Kaptoge, Stephen ; Brozynska, Marta ; Wang, Tingting ; Ye, Shu ; Webb, Thomas R ; Rutter, Martin K ; Tzoulaki, Ioanna ; Patel, Riyaz S ; Loos, Ruth J F ; Keavney, Bernard ; Hemingway, Harry ; Thompson, John ; Watkins, Hugh ; Deloukas, Panos ; Di Angelantonio, Emanuele ; Butterworth, Adam S ; Danesh, John ; Samani, Nilesh J</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-p294t-4ebc6323b9f6159084c1b907a05c0effa4e8faf2ef4b3e6ba8793680043166423</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><topic>Adults</topic><topic>Age</topic><topic>Angioplasty</topic><topic>Antihypertensives</topic><topic>Assessment centers</topic><topic>Blood pressure</topic><topic>Body mass</topic><topic>Body mass index</topic><topic>Body size</topic><topic>Cardiology</topic><topic>Cardiovascular disease</topic><topic>Cholesterol</topic><topic>Confidence intervals</topic><topic>Coronary artery</topic><topic>Coronary artery disease</topic><topic>Coronary Artery Disease - diagnosis</topic><topic>Coronary Artery Disease - epidemiology</topic><topic>Coronary Artery Disease - genetics</topic><topic>Coronary vessels</topic><topic>Diabetes</topic><topic>Diabetes mellitus</topic><topic>Disease prevention</topic><topic>Family medical history</topic><topic>Female</topic><topic>Genetic diversity</topic><topic>Genetic variance</topic><topic>Genetics</topic><topic>Genome-Wide Association Study</topic><topic>Genomes</topic><topic>Genomics - methods</topic><topic>Genomics - statistics & numerical data</topic><topic>Health and safety screening</topic><topic>Health risk assessment</topic><topic>Health risks</topic><topic>Heart attacks</topic><topic>Heart diseases</topic><topic>Heritability</topic><topic>Hospitals</topic><topic>Humans</topic><topic>Hypertension</topic><topic>Lipids</topic><topic>Male</topic><topic>Mass Screening - methods</topic><topic>Middle Aged</topic><topic>Multifactorial Inheritance</topic><topic>Population</topic><topic>Predictive Value of Tests</topic><topic>Primary Prevention - 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Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Journal of the American College of Cardiology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Inouye, Michael</au><au>Abraham, Gad</au><au>Nelson, Christopher P</au><au>Wood, Angela M</au><au>Sweeting, Michael J</au><au>Dudbridge, Frank</au><au>Lai, Florence Y</au><au>Kaptoge, Stephen</au><au>Brozynska, Marta</au><au>Wang, Tingting</au><au>Ye, Shu</au><au>Webb, Thomas R</au><au>Rutter, Martin K</au><au>Tzoulaki, Ioanna</au><au>Patel, Riyaz S</au><au>Loos, Ruth J F</au><au>Keavney, Bernard</au><au>Hemingway, Harry</au><au>Thompson, John</au><au>Watkins, Hugh</au><au>Deloukas, Panos</au><au>Di Angelantonio, Emanuele</au><au>Butterworth, Adam S</au><au>Danesh, John</au><au>Samani, Nilesh J</au><aucorp>UK Biobank CardioMetabolic Consortium CHD Working Group</aucorp><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Genomic Risk Prediction of Coronary Artery Disease in 480,000 Adults: Implications for Primary Prevention</atitle><jtitle>Journal of the American College of Cardiology</jtitle><addtitle>J Am Coll Cardiol</addtitle><date>2018-10-16</date><risdate>2018</risdate><volume>72</volume><issue>16</issue><spage>1883</spage><epage>1893</epage><pages>1883-1893</pages><issn>0735-1097</issn><eissn>1558-3597</eissn><abstract>Coronary artery disease (CAD) has substantial heritability and a polygenic architecture. However, the potential of genomic risk scores to help predict CAD outcomes has not been evaluated comprehensively, because available studies have involved limited genomic scope and limited sample sizes.
This study sought to construct a genomic risk score for CAD and to estimate its potential as a screening tool for primary prevention.
Using a meta-analytic approach to combine large-scale, genome-wide, and targeted genetic association data, we developed a new genomic risk score for CAD (metaGRS) consisting of 1.7 million genetic variants. We externally tested metaGRS, both by itself and in combination with available data on conventional risk factors, in 22,242 CAD cases and 460,387 noncases from the UK Biobank.
The hazard ratio (HR) for CAD was 1.71 (95% confidence interval [CI]: 1.68 to 1.73) per SD increase in metaGRS, an association larger than any other externally tested genetic risk score previously published. The metaGRS stratified individuals into significantly different life course trajectories of CAD risk, with those in the top 20% of metaGRS distribution having an HR of 4.17 (95% CI: 3.97 to 4.38) compared with those in the bottom 20%. The corresponding HR was 2.83 (95% CI: 2.61 to 3.07) among individuals on lipid-lowering or antihypertensive medications. The metaGRS had a higher C-index (C = 0.623; 95% CI: 0.615 to 0.631) for incident CAD than any of 6 conventional factors (smoking, diabetes, hypertension, body mass index, self-reported high cholesterol, and family history). For men in the top 20% of metaGRS with >2 conventional factors, 10% cumulative risk of CAD was reached by 48 years of age.
The genomic score developed and evaluated here substantially advances the concept of using genomic information to stratify individuals with different trajectories of CAD risk and highlights the potential for genomic screening in early life to complement conventional risk prediction.</abstract><cop>United States</cop><pub>Elsevier Limited</pub><pmid>30309464</pmid><doi>10.1016/j.jacc.2018.07.079</doi><tpages>11</tpages><oa>free_for_read</oa></addata></record> |
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| identifier | ISSN: 0735-1097 |
| ispartof | Journal of the American College of Cardiology, 2018-10, Vol.72 (16), p.1883-1893 |
| issn | 0735-1097 1558-3597 |
| language | eng |
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| source | MEDLINE; Elsevier ScienceDirect Journals; Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals; Alma/SFX Local Collection |
| subjects | Adults Age Angioplasty Antihypertensives Assessment centers Blood pressure Body mass Body mass index Body size Cardiology Cardiovascular disease Cholesterol Confidence intervals Coronary artery Coronary artery disease Coronary Artery Disease - diagnosis Coronary Artery Disease - epidemiology Coronary Artery Disease - genetics Coronary vessels Diabetes Diabetes mellitus Disease prevention Family medical history Female Genetic diversity Genetic variance Genetics Genome-Wide Association Study Genomes Genomics - methods Genomics - statistics & numerical data Health and safety screening Health risk assessment Health risks Heart attacks Heart diseases Heritability Hospitals Humans Hypertension Lipids Male Mass Screening - methods Middle Aged Multifactorial Inheritance Population Predictive Value of Tests Primary Prevention - methods Research Design Risk analysis Risk Assessment - methods Risk Factors Smoking Studies Trajectories United Kingdom - epidemiology |
| title | Genomic Risk Prediction of Coronary Artery Disease in 480,000 Adults: Implications for Primary Prevention |
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