Effect of Disclosing Genetic Risk for Coronary Heart Disease on Information Seeking and Sharing: The MI-GENES Study (Myocardial Infarction Genes)

Polygenic Risk Score Informed Clinical Model for Improving Abdominal Aortic Aneurysm Screening

BACKGROUND

Abdominal aortic aneurysm (AAA) is a complex disease with environmental and genetic risk factors. Polygenic risk scores (PRSs) based on disease-specific risk-associated single nucleotide variants (SNVs) have demonstrated effectiveness in stratifying individual-level disease risk for cardiovascular diseases. This prospective cohort study assessed associations of PRS of AAA (PRSAAA) with risk of incident AAA, analyzed the effectiveness of a combined clinical-genetic risk model, and explored the clinical utility of the model in identifying high-risk individuals for AAA screening.

METHODS

PRSAAA was calculated using 911,440 SNVs and PRS of coronary artery disease was calculated using 2,324,683 SNVs derived from mixed ancestry genome-wide association studies. The UK Biobank was used as the study cohort. All individuals with complete genetic data available and no diagnosis of AAA at the time of recruitment were included in the analysis and followed prospectively to assess for incident AAA. A PRS-informed clinical model, Prob-AAA, was developed using clinically significant variables and PRSAAA.

RESULTS

Four hundred eighty-one thousand one hundred 5 individuals were included in the analysis with 2,668 incident AAA cases. Incident AAA increased from 0.30 to 0.93% between the lowest and highest decile of PRSAAA; similarly, severe AAA, requiring surgery and/or presenting with rupture, increased from 23 to 39% of incident AAA cases across deciles. PRSAAA was a predictor of incident AAA diagnosis (hazard ratio 2.06 [1.70-2.48]) independent of other clinical risk factors including male sex, older age, and smoking history. Prob-AAA was an independent predictor of incident AAA (hazard ratio 1.92 [1.69-2.20]), and identified 9.6% of cases of incident AAA compared to only 4.2% by PRSAAA. Current screening guidelines captured 5.7% of the overall cohort, with an incident AAA rate of approximately 3.2%. Among males not included by current guidelines, Prob-AAA identified an additional cohort, approximately 2% of the overall cohort, with a similar rate of incident AAA.

CONCLUSIONS

Prob-AAA, a PRS-informed clinical model for AAA, improved upon the predictive power of current, clinical risk factor-informed, screening guidelines for AAA.

Effect of disclosing a polygenic risk score for coronary heart disease on adverse cardiovascular events: 10-year follow-up of the MI-GENES randomized clinical trial

Background

The MI-GENES clinical trial (NCT01936675), in which participants at intermediate risk of coronary heart disease (CHD) were randomized to receive a Framingham risk score (FRSg, n=103), or an integrated risk score (IRSg, n=104) that additionally included a polygenic risk score (PRS), demonstrated that after 6 months, participants randomized to IRSg had higher statin initiation and lower low-density lipoprotein cholesterol (LDL-C).

Objectives

In a post hoc 10-year follow-up analysis of the MI-GENES trial, we investigated whether disclosure of a PRS for CHD was associated with a reduction in adverse cardiovascular events.

Methods

Participants were followed from randomization beginning in October 2013 until September 2023 to ascertain adverse cardiovascular events, testing for CHD, and changes in risk factors, by blinded review of electronic health records. The primary outcome was the time from randomization to the occurrence of the first major adverse cardiovascular event (MACE), defined as cardiovascular death, non-fatal myocardial infarction, coronary revascularization, and non-fatal stroke. Statistical analyses were conducted using Cox proportional hazards regression and linear mixed-effects models.

Results

We followed all 203 participants who completed the MI-GENES trial, 100 in FRSg and 103 in IRSg (mean age at the end of follow-up: 68.2±5.2, 48% male). During a median follow-up of 9.5 years, 9 MACEs occurred in FRSg and 2 in IRSg (hazard ratio (HR), 0.20; 95% confidence interval (CI), 0.04 to 0.94; P=0.042). In FRSg, 47 (47%) underwent at least one test for CHD, compared to 30 (29%) in IRSg (HR, 0.51; 95% CI, 0.32 to 0.81; P=0.004). IRSg participants had a longer duration of statin therapy during the first four years post-randomization and a greater reduction in LDL-C for up to 3 years post-randomization. No significant differences between the two groups were observed for hemoglobin A1C, systolic and diastolic blood pressures, weight, and smoking cessation rate during follow-up.

Conclusions

The disclosure of an IRS that included a PRS to individuals at intermediate risk for CHD was associated with a lower incidence of MACE after a decade of follow-up, likely due to a higher rate of initiation and longer duration of statin therapy, leading to lower LDL-C levels.

Simplified rules-based tool to facilitate the application of up-to-date management recommendations in cardio-oncology

BACKGROUND

Millions of cancer survivors are at risk of cardiovascular diseases, a leading cause of morbidity and mortality. Tools to potentially facilitate implementation of cardiology guidelines, consensus recommendations, and scientific statements to prevent atherosclerotic cardiovascular disease (ASCVD) and other cardiovascular diseases are limited. Thus, inadequate utilization of cardiovascular medications and imaging is widespread, including significantly lower rates of statin use among cancer survivors for whom statin therapy is indicated.

METHODS

In this methodological study, we leveraged published guidelines documents to create a rules-based tool to include guidelines, expert consensus, and medical society scientific statements relevant to point of care cardiovascular disease prevention in the cardiovascular care of cancer survivors. Any overlap, redundancy, or ambiguous recommendations were identified and eliminated across all converted sources of knowledge. The integrity of the tool was assessed with use case examples and review of subsequent care suggestions.

RESULTS

An initial selection of 10 guidelines, expert consensus, and medical society scientific statements was made for this study. Then 7 were kept owing to overlap and revisions in society recommendations over recent years. Extensive formulae were employed to translate the recommendations of 7 selected guidelines into rules and proposed action measures. Patient suitability and care suggestions were assessed for several use case examples.

CONCLUSION

A simple rules-based application was designed to provide a potential format to deliver critical cardiovascular disease best-practice prevention recommendations at the point of care for cancer survivors. A version of this tool may potentially facilitate implementing these guidelines across clinics, payers, and health systems for preventing cardiovascular diseases in cancer survivors.

TRIAL REGISTRATION

ClinicalTrials.Gov Identifier: NCT05377320.

Polygenic Risk, Rare Variants, and Family History: Independent and Additive Effects on Coronary Heart Disease

Background

Genetic factors are not included in prediction models for coronary heart disease (CHD).

Objectives

The authors assessed the predictive utility of a polygenic risk score (PRS) for CHD (defined as myocardial infarction, coronary revascularization, or cardiovascular death) and whether the risks due to monogenic familial hypercholesterolemia (FH) and family history (FamHx) are independent of and additive to the PRS.

Methods

In UK-biobank participants, PRSCHD was calculated using metaGRS, and 10-year risk for incident CHD was estimated using the pooled cohort equations (PCE). The area under the curve (AUC) of the receiver operator curve and net reclassification improvement (NRI) were assessed. FH was defined as the presence of a pathogenic or likely pathogenic variant in LDLR, APOB, or PCSK9. FamHx was defined as a diagnosis of CHD in first-degree relatives. Independent and additive effects of PRSCHD, FH, and FamHx were evaluated in stratified analyses.

Results

In 323,373 participants with genotype data, the addition of PRSCHD to PCE increased the AUC from 0.759 (95% CI: 0.755-0.763) to 0.773 (95% CI: 0.769-0.777). The AUC and NRIEvent for PRSCHD were higher before the age of 55 years. Of 199,997 participants with exome sequence data, 10,000 had a PRSCHD ≥95th percentile (PRSP95), 673 had FH, and 46,163 had FamHx. The CHD risk associated with PRSP95 was independent of FH and FamHx. The risks associated with combinations of PRSCHD, FH, and FamHx were additive and comprehensive estimates could be obtained by multiplying the risk from each genetic factor.

Conclusions

Incorporating PRSCHD into the PCE improves risk prediction for CHD, especially at younger ages. The associations of PRSCHD, FH, and FamHx with CHD were independent and additive.

Education and electronic medical records and genomics network, challenges, and lessons learned from a large-scale clinical trial using polygenic risk scores

Polygenic risk scores (PRS) have potential to improve health care by identifying individuals that have elevated risk for common complex conditions. Use of PRS in clinical practice, however, requires careful assessment of the needs and capabilities of patients, providers, and health care systems. The electronic Medical Records and Genomics (eMERGE) network is conducting a collaborative study which will return PRS to 25,000 pediatric and adult participants. All participants will receive a risk report, potentially classifying them as high risk (∼2-10% per condition) for 1 or more of 10 conditions based on PRS. The study population is enriched by participants from racial and ethnic minority populations, underserved populations, and populations who experience poorer medical outcomes. All 10 eMERGE clinical sites conducted focus groups, interviews, and/or surveys to understand educational needs among key stakeholders-participants, providers, and/or study staff. Together, these studies highlighted the need for tools that address the perceived benefit/value of PRS, types of education/support needed, accessibility, and PRS-related knowledge and understanding. Based on findings from these preliminary studies, the network harmonized training initiatives and formal/informal educational resources. This paper summarizes eMERGE's collective approach to assessing educational needs and developing educational approaches for primary stakeholders. It discusses challenges encountered and solutions provided.

Patient similarity and other artificial intelligence machine learning algorithms in clinical decision aid for shared decision-making in the Prevention of Cardiovascular Toxicity (PACT): a feasibility trial design

BACKGROUND

The many improvements in cancer therapies have led to an increased number of survivors, which comes with a greater risk of consequent/subsequent cardiovascular disease. Identifying effective management strategies that can mitigate this risk of cardiovascular complications is vital. Therefore, developing computer-driven and personalized clinical decision aid interventions that can provide early detection of patients at risk, stratify that risk, and recommend specific cardio-oncology management guidelines and expert consensus recommendations is critically important.

OBJECTIVES

To assess the feasibility, acceptability, and utility of the use of an artificial intelligence (AI)-powered clinical decision aid tool in shared decision making between the cancer survivor patient and the cardiologist regarding prevention of cardiovascular disease.

DESIGN

This is a single-center, double-arm, open-label, randomized interventional feasibility study. Our cardio-oncology cohort of > 4000 individuals from our Clinical Research Data Warehouse will be queried to identify at least 200 adult cancer survivors who meet the eligibility criteria. Study participants will be randomized into either the Clinical Decision Aid Group (where patients will use the clinical decision aid in addition to current practice) or the Control Group (current practice). The primary endpoint of this study is to assess for each patient encounter whether cardiovascular medications and imaging pursued were consistent with current medical society recommendations. Additionally, the perceptions of using the clinical decision tool will be evaluated based on patient and physician feedback through surveys and focus groups. This trial will determine whether a clinical decision aid tool improves cancer survivors' medication use and imaging surveillance recommendations aligned with current medical guidelines.

TRIAL REGISTRATION

ClinicalTrials.Gov Identifier: NCT05377320.

Polygenic risk scores in coronary artery disease

PURPOSE OF REVIEW

Recent advances in genetics have facilitated the calculation of polygenic risk scores (PRSs) based on common genetic risk variants of coronary artery disease (CAD). Here, we provide an explanation of the genetic basis for PRSs and review recent literature investigating PRSs and the clinical utility for different aspects of CAD.

RECENT FINDINGS

CAD-based PRSs are strongly associated with atherosclerosis burden in the coronary arteries and other vascular beds. In multiple studies, PRSs have proven to be a measure of CAD risk, more powerful than most established risk factors alone, that can be used from early life to stratify individuals into varying trajectories of lifetime risk. When implemented in risk stratification models for primary prevention of cardiovascular disease, PRSs provide modest improvements in discrimination (C-index generally increasing 0-4% points) and reclassification, but yield significant clinical benefit as a risk enhancer. Additionally, data suggest possible value of PRSs for aiding decisions in other aspects of diagnostics and treatment in CAD.

SUMMARY

Once genotyped, the genetic information may be used to calculate an infinite number of PRSs and contribute to personalize medicine providing clinical value for risk stratification, diagnostics and treatment in CAD as well as in other diseases.

Genomics and multimorbidity

Multimorbidity has increased in prevalence world-wide. It is anticipated to affect over 1 in 6 of the UK population by 2035 and is now recognised as a global priority for health research. Genomic medicine has rapidly advanced over the last 20 years from the first sequencing of the human genome to integration into clinical care for rarer conditions. Genetic studies help identify new disease mechanisms as they are less susceptible to the bias and confounding that affects epidemiological studies, as genetics are assigned from conception. There is also genetic variation in the efficacy of medications and the risk of side effects, pharmacogenetics. Genomic approaches offer the potential to improve our understanding of mechanisms underpinning multiple long-term conditions/multimorbidity and guide precision approaches to risk, diagnosis and optimisation of management. In this commentary as part of the Age and Ageing 50th anniversary commentary series, we summarise genomics and the potential utility of genomics in multimorbidity.

How Communicating Polygenic and Clinical Risk for Atherosclerotic Cardiovascular Disease Impacts Health Behavior: an Observational Follow-up Study

BACKGROUND

Prediction tools that combine polygenic risk scores with clinical factors provide a new opportunity for improved prediction and prevention of atherosclerotic cardiovascular disease, but the clinical utility of polygenic risk score has remained unclear.

METHODS

We collected a prospective cohort of 7342 individuals (64% women, mean age 56 years) and estimated their 10-year risk for atherosclerotic cardiovascular disease both by a traditional risk score and a composite score combining the effect of a polygenic risk score and clinical risk factors. We then tested how returning the personal risk information with an interactive web-tool impacted on the participants' health behavior.

RESULTS

When reassessed after 1.5 years by a clinical visit and questionnaires, 20.8% of individuals at high (>10%) 10-year atherosclerotic cardiovascular disease risk had seen a doctor, 12.4% reported weight loss, 14.2% of smokers had quit smoking, and 15.4% had signed up for health coaching online. Altogether, 42.6% of persons at high risk had made one or more health behavioral changes versus 33.5% of persons at low/average risk such that higher baseline risk predicted a favorable change (OR [CI], 1.53 [1.37-1.72] for persons at high risk versus the rest, P<0.001), with both high clinical (P<0.001) and genomic risk (OR [CI], 1.10 [1.03-1.17], P=0.003) contributing independently.

CONCLUSIONS

Web-based communication of personal atherosclerotic cardiovascular disease risk-data including polygenic risk to middle-aged persons motivates positive changes in health behavior and the propensity to seek care. It supports integration of genomic information into clinical risk calculators as a feasible approach to enhance disease prevention.

Clinical utility of polygenic risk scores for coronary artery disease

Over the past decade, substantial progress has been made in the discovery of alleles contributing to the risk of coronary artery disease. In addition to providing causal insights into disease, these endeavours have yielded and enabled the refinement of polygenic risk scores. These scores can be used to predict incident coronary artery disease in multiple cohorts and indicate the clinical response to some preventive therapies in post hoc analyses of clinical trials. These observations and the widespread ability to calculate polygenic risk scores from direct-to-consumer and health-care-associated biobanks have raised many questions about responsible clinical adoption. In this Review, we describe technical and downstream considerations for the derivation and validation of polygenic risk scores and current evidence for their efficacy and safety. We discuss the implementation of these scores in clinical medicine for uses including risk prediction and screening algorithms for coronary artery disease, prioritization of patient subgroups that are likely to derive benefit from treatment, and efficient prospective clinical trial designs.

Responsible use of polygenic risk scores in the clinic: potential benefits, risks and gaps

Polygenic risk scores (PRSs) aggregate the many small effects of alleles across the human genome to estimate the risk of a disease or disease-related trait for an individual. The potential benefits of PRSs include cost-effective enhancement of primary disease prevention, more refined diagnoses and improved precision when prescribing medicines. However, these must be weighed against the potential risks, such as uncertainties and biases in PRS performance, as well as potential misunderstanding and misuse of these within medical practice and in wider society. By addressing key issues including gaps in best practices, risk communication and regulatory frameworks, PRSs can be used responsibly to improve human health. Here, the International Common Disease Alliance's PRS Task Force, a multidisciplinary group comprising expertise in genetics, law, ethics, behavioral science and more, highlights recent research to provide a comprehensive summary of the state of polygenic score research, as well as the needs and challenges as PRSs move closer to widespread use in the clinic.

Genetic predisposition to coronary artery disease is predictive of recurrent events: a Chinese prospective cohort study

Evidence of the effects of genetic risk score (GRS) on secondary prevention is scarce and mixed. We investigated whether coronary artery disease (CAD) susceptible loci can be used to predict the risk of major adverse cardiovascular events (MACEs) in a cohort with acute coronary syndromes (ACSs). A total of 1667 patients hospitalized with ACS were enrolled and prospectively followed for a median of 2 years. We constructed a weighted GRS comprising 79 CAD risk variants and investigated the association between GRS and MACE using a multivariable cox proportional hazard regression model. The incremental value of adding GRS into the prediction model was assessed by integrated discrimination improvement (IDI) and decision curve analysis (DCA). In the age- and sex-adjusted model, each increase in standard deviation in the GRS was associated with a 33% increased risk of MACE (hazard ratio: 1.33; 95% confidence interval: 1.10-1.61; P = 0.003), with this association not attenuating after further adjustment for traditional cardiovascular risk factors. The addition of GRS to a prediction model of seven clinical risk factors and EPICOR prognostic model slightly improved risk stratification for MACE as calculated by IDI (+1.7%, P = 0.006; +0.3%, P = 0.024, respectively). DCA demonstrated positive net benefits by adding GRS to other models. GRS was associated with MACE after multivariable adjustment in a cohort comprising Chinese ACS patients. Future studies are needed to validate our results and further evaluate the predictive value of GRS in secondary prevention.

Genetic Risk Assessment for Atherosclerotic Cardiovascular Disease: A Guide for the General Cardiologist

Genetic testing for cardiovascular (CV) disease has had a profound impact on the diagnosis and evaluation of monogenic causes of CV disease, such as hypertrophic and familial cardiomyopathies, long QT syndrome, and familial hypercholesterolemia (FH). The success in genetic testing for monogenic diseases has prompted special interest in utilizing genetic information in the risk assessment of more common diseases such as atherosclerotic cardiovascular disease (ASCVD). Polygenic risk scores (PRS) have been developed to assess the risk of coronary artery disease (CAD) that now include millions of single-nucleotide polymorphisms (SNPs) that have been identified through genome-wide association studies (GWAS). While these PRS have demonstrated a strong association with CAD in large cross-sectional population studies, there remains intense debate regarding the added value that PRS contribute to existing clinical risk prediction models such as the pooled cohort equations (PCEs). In this review, we provide a brief background of genetic testing for monogenic drivers of CV disease and then focus on the recent developments in genetic risk assessment of ASCVD, including the use of PRS. We outline the genetic testing that is currently available to all cardiologists in the clinic and discuss the evolving sphere of specialized cardiovascular genetics programs (CVGPs) that integrate the expertise of cardiologists, geneticists, and genetic counselors. Finally, we review the possible implications that PRS and pharmacogenomic data may soon have on clinical practice in the care for patients with or at risk of developing ASCVD.

Predictive Utility of Polygenic Risk Scores for Coronary Heart Disease in Three Major Racial and Ethnic Groups

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 (PRS_Tikkanen and PRS_Tada; 28 and 50 variants, respectively) and two genome-wide PRSs (PRS_metaGRS and PRS_LDPred; 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. PRS_metaGRS, 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 (p_interaction = 0.77) but were significantly attenuated in AA individuals (p_interaction= 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.

Hypertension genetic risk score is associated with burden of coronary heart disease among patients referred for coronary angiography

BACKGROUND

Recent GWAS studies have identified more than 300 SNPs associated with variation in blood pressure. We investigated whether a genetic risk score constructed from these variants is associated with burden of coronary heart disease.

METHODS

From 2010-2014, 4,809 individuals admitted to coronary angiography in Capital Region of Copenhagen were genotyped. We calculated hypertension GRS comprised of GWAS identified SNPs associated with blood pressure. We performed logistic regression analyses to estimate the risk of hypertension and prevalent CHD. We also assessed the severity of CHD associated with the GRS. The analyses were performed using GRS quartiles. We used the Inter99 cohort to validate our results and to investigate for possible pleiotropy for the GRS with other CHD risk factors.

RESULTS

In COGEN, adjusted odds ratios comparing the 2nd, 3rd and 4th cumulative GRS quartiles with the reference were 1.12(95% CI 0.95-1.33), 1.35(95% CI 1.14-1.59) and 1.29(95% CI 1.09-1.53) respectively, for prevalent CHD. The adjusted multinomial logistic regression showed that 3rd and 4th GRS quartiles were associated with increased odds of developing two(OR 1.33, 95% CI 1.04-1.71 and OR 1.36, 95% CI 1.06-1.75, respectively) and three coronary vessel disease(OR 1.77, 95% CI 1.36-2.30 and OR 1.65, 95% CI 1.26-2.15, respectively). Similar results for incident CHD were observed in the Inter99 cohort. The hypertension GRS did not associate with type 2 diabetes, smoking, BMI or hyperlipidemia.

CONCLUSION

Hypertension GRS quartiles were associated with an increased risk of hypertension, prevalent CHD, and burden of coronary vessel disease in a dose-response pattern. We showed no evidence for pleiotropy with other risk factors for CHD.

The Genetic Sphygmomanometer: an argument for routine genome-wide genotyping in the population and a new view on its use to inform clinical practice

Initial genomewide association studies were exceptional owing to an ability to yield novel and reliable evidence for heritable contributions to complex disease and phenotype. However the top results alone were certainly not responsible for a wave of new predictive tools. Despite this, even studies small by contemporary standards were able to provide estimates of the relative contribution of all recorded genetic variants to outcome. Sparking efforts to quantify heritability, these results also provided the material for genomewide prediction. A fantastic growth in the performance of human genetic studies has only served to improve the potential of these complex, but potentially informative predictors. Prompted by these conditions and recent work, this letter explores the likely utility of these predictors, considers how clinical practice might be altered through their use, how to measure the efficacy of this and some of the potential ethical issues involved. Ultimately we suggest that for common genetic variation at least, the future should contain an acceptance of complexity in genetic architecture and the possibility of useful prediction even if only to shift the way we interact with clinical service providers.

Associations of Combined Genetic and Lifestyle Risks With Incident Cardiovascular Disease and Diabetes in the UK Biobank Study

Importance

Genetic and lifestyle factors both contribute to the risk of developing cardiovascular disease, but whether poor health behaviors are associated with similar increases in risk among individuals with low, intermediate, or high genetic risk is unknown.

Objective

To investigate the association of combined health behaviors and factors within genetic risk groups with coronary artery disease, atrial fibrillation, stroke, hypertension, and type 2 diabetes as well as to investigate the interactions between genetic risk and lifestyle.

Design, Setting, and Participants

The UK Biobank cohort study includes more than 500 000 participants aged 40 to 70 years who were recruited from 22 assessment centers across the United Kingdom from 2006 to 2010. A total of 339 003 unrelated individuals of white British descent with available genotype and matching genetic data and reported sex were included in this study from the UK Biobank population-based sample. Individuals were included in the analyses of 1 or more new-onset diseases. Data were analyzed from April 2006 to March 2015.

Main Outcomes and Measures

Risks of new-onset cardiovascular disease and diabetes associated with genetic risk and combined health behaviors and factors. Genetic risk was categorized as low (quintile 1), intermediate (quintiles 2-4), or high (quintile 5). Within each genetic risk group, the risks of incident events associated with ideal, intermediate, or poor combined health behaviors and factors were investigated and compared with low genetic risk and ideal lifestyle.

Results

Of 339 003 individuals, 181 702 (53.6%) were female, and the mean (SD) age was 56.86 (7.99) years. During follow-up, 9771 of 325 133 participants (3.0%) developed coronary artery disease, 7095 of 333 637 (2.1%) developed atrial fibrillation, 3145 of 332 971 (0.9%) developed stroke, 11 358 of 234 651 (4.8%) developed hypertension, and 4379 of 322 014 (1.4%) developed diabetes. Genetic risk and lifestyle were independent predictors of incident events, and there were no interactions for any outcome. Compared with ideal lifestyle in the low genetic risk group, poor lifestyle was associated with a hazard ratio of up to 4.54 (95% CI, 3.72-5.54) for coronary artery disease, 5.41 (95% CI, 4.29-6.81) for atrial fibrillation, 4.68 (95% CI, 3.85-5.69) for hypertension, 2.26 (95% CI, 1.63-3.14) for stroke, and 15.46 (95% CI, 10.82-22.08) for diabetes in the high genetic risk group.

Conclusions and Relevance

In this large contemporary population, genetic composition and combined health behaviors and factors had a log-additive effect on the risk of developing cardiovascular disease. The relative effects of poor lifestyle were comparable between genetic risk groups. Behavioral lifestyle changes should be encouraged for all through comprehensive, multifactorial approaches, although high-risk individuals may be selected based on the genetic risk.

Cardiovascular Precision Medicine in the Genomics Era

Precision medicine strives to delineate disease using multiple data sources-from genomics to digital health metrics-in order to be more precise and accurate in our diagnoses, definitions, and treatments of disease subtypes. By defining disease at a deeper level, we can treat patients based on an understanding of the molecular underpinnings of their presentations, rather than grouping patients into broad categories with one-size-fits-all treatments. In this review, the authors examine how precision medicine, specifically that surrounding genetic testing and genetic therapeutics, has begun to make strides in both common and rare cardiovascular diseases in the clinic and the laboratory, and how these advances are beginning to enable us to more effectively define risk, diagnose disease, and deliver therapeutics for each individual patient.

Genetics in the 21st Century: Implications for patients, consumers and citizens

The first human genome project, completed in 2003, uncovered the genetic building blocks of humankind. Painstakingly cataloguing the basic constituents of our DNA ('genome sequencing') took ten years, over three billion dollars and was a multinational collaboration. Since then, our ability to sequence genomes has been finessed so much that by 2018 it is possible to explore the 20,000 or so human genes for under £1000, in a matter of days. Such testing offers clues to our past, present and future health, as well as information about how we respond to medications so that truly 'personalised medicine' is now moving closer to a reality. The impact of such a 'genomic era' is likely to have some level of impact on an increasingly large number of us, even if we are not directly using healthcare services ourselves. We explore how advancements in genetics are likely to be experienced by people, as patients, consumers and citizens; and urge policy makers to take stock of the pervasive nature of the technology as well as the human response to it.

Genetics in the 21st Century: Implications for patients, consumers and citizens

The first human genome project, completed in 2003, uncovered the genetic building blocks of humankind. Painstakingly cataloguing the basic constituents of our DNA ('genome sequencing') took ten years, over three billion dollars and was a multinational collaboration. Since then, our ability to sequence genomes has been finessed so much that by 2017 it is possible to explore the 20,000 or so human genes for under £1000, in a matter of days. Such testing offers clues to our past, present and future health, as well as information about how we respond to medications so that truly 'personalised medicine' is now a reality.   The impact of such a 'genomic era' is likely to have some level of impact on all of us, even if we are not directly using healthcare services ourselves. We explore how advancements in genetics are likely to be experienced by people, as patients, consumers and citizens; and urge policy makers to take stock of the pervasive nature of the technology as well as the human response to it.