Incorporating a Genetic Risk Score Into Coronary Heart Disease Risk Estimates: Effect on Low-Density Lipoprotein Cholesterol Levels (the MI-GENES Clinical Trial)

Use of polygenic risk scores to assess weight loss after bariatric surgery: a five-year follow-up study

BACKGROUND

Bariatric surgery is currently the most effective long-term treatment for severe obesity. However, the interindividual variability observed in surgical outcomes suggests a moderating effect of several factors, including individual genetic background. Our goal was to investigate the contribution of the genetic architecture of BMI to the variability in weight loss outcomes after bariatric surgery.

METHODS

A total of 106 patients with severe obesity who underwent Roux-en-Y gastric bypass or sleeve gastrectomy were followed up for five years. Changes in body mass index (BMIchange) and percentage of total weight loss (%TWL) were evaluated during the postoperative period. Polygenic risk scores including 50 genetic variants were calculated for each participant to determine their individual genetic risk for high BMI based on a previous GWAS. Generalized estimating equation models were used to study the role of the individual's polygenic score, as well as other factors, on BMIchange and %TWL in the long term after surgery.

RESULTS

We found an effect of the polygenic score on %TWL and BMIchange, where subjects with lower scores had better outcomes after surgery than those with higher scores. Furthermore, when analyzing only patients who underwent Roux-en-Y gastric bypass, these results were replicated showing greater weight loss after surgery for those with lower polygenic scores.

DISCUSSION

These results indicate that genetic background assessed with polygenic risk scores, along with other individual factors such as sex, age, and preoperative BMI, has an impact on bariatric surgery outcomes and could represent a useful tool for estimating surgical outcomes in advance.

A polygenic risk score added to a QRISK®2 cardiovascular disease risk calculator demonstrated robust clinical acceptance and clinical utility in the primary care setting

AIMS

The aim of the study was to assess the real-world feasibility, acceptability, and impact of an integrated risk tool for cardiovascular disease (CVD IRT, combining the standard QRISK®2 risk algorithm with a polygenic risk score), implemented within routine primary practice in the UK National Health Service.

METHODS AND RESULTS

The Healthcare Evaluation of Absolute Risk Testing Study (NCT05294419) evaluated participants undergoing primary care health checks. Both QRISK2 and CVD IRT scores were returned to the healthcare providers (HCPs), who then communicated the results to participants. The primary outcome of the study was feasibility of CVD IRT implementation. Secondary outcomes included changes in CVD risk (QRISK2 vs. CVD IRT) and impact of the CVD IRT on clinical decision-making. A total of 832 eligible participants (median age 55 years, 62% females, 97.5% White ethnicity) were enrolled across 12 UK primary care practices. Cardiovascular disease IRT scores were obtained on 100% of the blood samples. Healthcare providers stated that the CVD IRT could be incorporated into routine primary care in a straightforward manner in 90.7% of reports. Participants stated they were 'likely' or 'very likely' to recommend the use of this test to their family or friends in 86.9% of reports. Participants stated that the test was personally useful (98.8%) and that the results were easy to understand (94.6%). When CVD IRT exceeded QRISK2, HCPs planned changes in management for 108/388 (27.8%) of participants and 47% (62/132) of participants with absolute risk score changes of >2%.

CONCLUSION

Amongst HCPs and participants who agreed to the trial of genetic data for refinement of clinical risk prediction in primary care, we observed that CVD IRT implementation was feasible and well accepted. The CVD IRT results were associated with planned changes in prevention strategies.

Genetically determined telomere length and its association with chronic obstructive pulmonary disease and interstitial lung disease in biobank Japan: A Mendelian randomization study

Importance

Chronic obstructive pulmonary disease (COPD) and interstitial lung disease (ILD) have been linked to shorter telomere length (TL). While understanding this association has critical clinical implications for respiratory diseases, previous studies exploring these associations were conducted in European populations. The present study aims to investigate this relationship in an Asian population.

Objective

To examine the causal relationship between leukocyte TL and COPD and ILD in an Asian population.

Design

Setting, and Participants: We used a genome-wide association study summary statistics-based two-sample Mendelian randomization (MR) design to investigate the association between leukocyte TL, genetically predicted by nine single-nucleotide polymorphisms and the risk of COPD and ILD. Participants were Japanese individuals enrolled in the Biobank Japan Project, including 3315 COPD patients and 806 ILD patients.

Exposure

Leukocyte TL was genetically predicted by nine single-nucleotide polymorphisms.

Results

The inverse-variance weighted estimates showed a significant inverse association between leukocyte TL and COPD (odds ratio [OR] = 0.78; 95 % confidence interval [CI]: 0.64, 0.95; P = 0.01) and ILD (OR = 0.29; 95 % CI: 0.14, 0.61; P = 0.001), respectively. All sensitivity analyses yielded consistent results. The MR-Egger regression intercept test showed no evidence of horizontal pleiotropy (Pintercept: COPD, 0.56; ILD: 0.70).

Conclusion

and Relevance: Our findings suggest that leukocyte telomere shortening may causally increase the risk of COPD and ILD. These results highlight the potential importance of TL for these respiratory diseases.

Joint Association of Polygenic Risk and Social Determinants of Health with Coronary Heart Disease in the United States

Background

The joint effects of polygenic risk and social determinants of health (SDOH) on coronary heart disease (CHD) in the United States are unknown.

Methods

In 67,256 All of Us (AoU) participants with available SDOH data, we ascertained self-reported race/ethnicity and calculated a polygenic risk score for CHD (PRS CHD ). We used 90 SDOH survey questions to develop an SDOH score for CHD (SDOH CHD ). We assessed the distribution of SDOH CHD across self-reported races and US states. We tested the joint association of SDOH CHD and PRS CHD with CHD in regression models that included clinical risk factors.

Results

SDOH CHD was highest in self-reported black and Hispanic people. Self-reporting as black was associated with higher odds of CHD but not after adjustment for SDOH CHD . Median SDOH CHD values varied by US state and were associated with heart disease mortality. A 1-SD increase in SDOH CHD was associated with CHD (OR=1.36; 95% CI, 1.29 to 1.46) and incident CHD (HR=1.73; 95% CI, 1.27 to 2.35) in models that included PRS CHD and clinical risk factors. Among people in the top 20% of PRS CHD , CHD prevalence was 4.8% and 7.8% in the bottom and top 20% of SDOH CHD , respectively.

Conclusions

Increased odds of CHD in self-reported black people are likely due to higher SDOH burden. SDOH and PRS were independently associated with CHD in the US. Our findings emphasize the need to consider both PRS and SDOH for equitable disease risk assessment.

Clinical applications of polygenic risk score for coronary artery disease through the life course

Coronary artery disease (CAD) remains a leading cause of morbidity and mortality worldwide, highlighting the limitations of current primary and secondary prevention frameworks. In this review, we detail how the polygenic risk score for CAD can improve our current preventive and treatment frameworks across three clinical applications that span the life course: (i) identification and treatment of people at increased risk early in the life course prior to the onset of clinical risk factors, (ii) improving the precision around risk estimation in middle age, and (ii) guiding treatment decisions and enabling more efficient clinical trials even after the onset of CAD. We end by summarizing the efforts needed as we head towards more widespread use of polygenic risk score for CAD in clinical practice.

Applying polygenic risk score methods to pharmacogenomics GWAS: challenges and opportunities

Polygenic risk scores (PRSs) have emerged as promising tools for the prediction of human diseases and complex traits in disease genome-wide association studies (GWAS). Applying PRSs to pharmacogenomics (PGx) studies has begun to show great potential for improving patient stratification and drug response prediction. However, there are unique challenges that arise when applying PRSs to PGx GWAS beyond those typically encountered in disease GWAS (e.g. Eurocentric or trans-ethnic bias). These challenges include: (i) the lack of knowledge about whether PGx or disease GWAS/variants should be used in the base cohort (BC); (ii) the small sample sizes in PGx GWAS with corresponding low power and (iii) the more complex PRS statistical modeling required for handling both prognostic and predictive effects simultaneously. To gain insights in this landscape about the general trends, challenges and possible solutions, we first conduct a systematic review of both PRS applications and PRS method development in PGx GWAS. To further address the challenges, we propose (i) a novel PRS application strategy by leveraging both PGx and disease GWAS summary statistics in the BC for PRS construction and (ii) a new Bayesian method (PRS-PGx-Bayesx) to reduce Eurocentric or cross-population PRS prediction bias. Extensive simulations are conducted to demonstrate their advantages over existing PRS methods applied in PGx GWAS. Our systematic review and methodology research work not only highlights current gaps and key considerations while applying PRS methods to PGx GWAS, but also provides possible solutions for better PGx PRS applications and future research.

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.

The efficacy of genotype-based dietary or physical activity advice in changing behavior to reduce the risk of cardiovascular disease, type II diabetes mellitus or obesity: a systematic review and meta-analysis

CONTEXT

Despite clear evidence that adherence to dietary and physical activity advice can reduce the risk of cardiometabolic disease, a significant proportion of the population do not follow recommendations. Personalized advice based on genetic variation has been proposed for motivating behavior change, although research on its benefits to date has been contradictory.

OBJECTIVE

To evaluate the efficacy of genotype-based dietary or physical activity advice in changing behavior in the general population and in individuals who are at risk of cardiovascular disease (CVD) or type II diabetes mellitus (T2DM).

DATA SOURCES

MEDLINE, EMBASE, PsycInfo, and the Cochrane Central Register of Controlled Trials (CENTRAL) were searched up to January 7, 2022. Randomized controlled trials of a genotype-based dietary and/or physical activity advice intervention that aimed to change dietary and/or physical activity behavior were included.

DATA EXTRACTION

Abstracts of 7899 records were screened, and 14 reports from 11 studies met the inclusion criteria.

DATA ANALYSIS

Genotype-based dietary or physical activity advice was found to have no effect on dietary behavior in any of the studies (standardized mean difference [SMD] .00 [-.11 to .11], P = .98), even when analyzed by subgroup: "at risk" (SMD .00 [-.16 to .16, P = .99]; general population (SMD .01 [-.14 to .16], P = .87). The physical activity behavior findings were similar for all studies (SMD -.01 [-.10 to .08], P = .88), even when analyzed by subgroup: "at risk" (SMD .07 [-.18 to .31], P = .59); general population (SMD -.02 [-.13 to .10], P = .77). The quality of the evidence for the dietary behavior outcome was low; for the physical activity behavior outcome it was moderate.

CONCLUSIONS

Genotype-based advice does not affect dietary or physical activity behavior more than general advice or advice based on lifestyle or phenotypic measures. This was consistent in studies that recruited participants from the general population as well as in studies that had recruited participants from populations at risk of CVD or T2DM.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO registration no. CRD42021231147.

Impact of providing genetics-based future cardiovascular risk on LDL-C in patients with familial hypercholesterolemia

BACKGROUND

Familial hypercholesterolemia (FH) is an autosomal dominant monogenic disease characterized by high low-density lipoprotein cholesterol (LDL-C) levels. Although carrying causative FH variants is associated with coronary heart disease (CHD), it remains unclear whether disclosing its associated cardiovascular risk affects outcomes in patients with FH.

OBJECTIVE

We aimed to evaluate the efficacy of providing future cardiovascular risk based on genetic testing in addition to a standard FH education program.

METHODS

We conducted a randomized, wait-list controlled, open-label, single-center trial. In the intervention group, we reported a future cardiovascular risk based on the genetic testing adding to standard FH education at week 0. In the wait-list control group, we only disseminated standard FH education according to the guidelines at week 0; they later received a genetic testing-based cardiovascular risk assessment at week 24. The primary endpoint of this study was the plasma LDL-C level at week 24.

RESULTS

Fifty eligible patients with clinically diagnosed FH, without a history of CHD, were allocated to the intervention group (n = 24) or the wait-list control group (n = 26). At week 24, the intervention group had a significantly greater reduction in LDL-C levels than the wait-list control group (mean changes, -13.1 mg/dL vs. 6.6 mg/dL; difference, -19.7 mg/dL; 95% confidence interval, -34 to -5.6; p = 0.009). This interventional effect was consistent with FH causative variant carriers but not with non-carriers.

CONCLUSIONS

In addition to standard FH care, providing future cardiovascular risk based on genetic testing can further reduce plasma LDL-C levels, particularly among FH causal variant carriers.

REGISTRATION

Japan Registry of Clinical Trials (jRCTs04218002). URL: https://jrct.niph.go.jp/latest-detail/jRCTs042180027.

Barriers and shortcomings in access to cardiovascular management and prevention for familial hypercholesterolemia during the COVID-19 pandemic

Familial hypercholesterolemia (FH) is a hereditary condition caused by mutations in the lipid pathway. The goal in managing FH is to reduce circulating low-density lipoprotein cholesterol and, therefore, reduce the risk of developing atherosclerotic cardiovascular disease (ASCVD). Because FH patients were considered high risk groups due to an increased susceptible for contracting COVID-19 infection, we hypothesized whether the effects of the pandemic hindered access to cardiovascular care. In this review, we conducted a literature search in databases Pubmed/Medline and ScienceDirect. We included a comprehensive analysis of findings from articles in English related and summarized the effects of the pandemic on cardiovascular care through direct and indirect effects. During the COVID-19 pandemic, FH patients presented with worse outcomes and prognosis, especially those that have suffered from early ASCVD. This caused avoidance in seeking care due to fear of transmission. The pandemic severely impacted consultations with lipidologists and cardiologists, causing a decline in lipid profile evaluations. Low socioeconomic communities and ethnic minorities were hit the hardest with job displacements and lacked healthcare coverage respectively, leading to treatment nonadherence. Lock-down restrictions promoted sedentary lifestyles and intake of fatty meals, but it is unclear whether these factors attenuated cardiovascular risk in FH. To prevent early atherogenesis in FH patients, universal screening programs, telemedicine, and lifestyle interventions are important recommendations that could improve outcomes in FH patients. However, the need to research in depth on the disproportionate impact within different subgroups should be the forefront of FH research.

Implementing Reporting Standards for Polygenic Risk Scores for Atherosclerotic Cardiovascular Disease

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.

Polygenic Risk Prediction in Diverticulitis

OBJECTIVE

To derive and validate a polygenic risk score (PRS) to predict the occurrence and severity of diverticulitis and to understand the potential for incorporation of a PRS in current decision-making.

BACKGROUND

PRS quantifies genetic variation into a continuous measure of risk. There is a need for improved risk stratification to guide surgical decision-making that could be fulfilled by PRS. It is unknown how surgeons might integrate PRS in decision-making.

METHODS

We derived a PRS with 44 single-nucleotide polymorphisms associated with diverticular disease in the UK Biobank and validated this score in the Michigan Genomics Initiative (MGI). We performed a discrete choice experiment of practicing colorectal surgeons. Surgeons rated the influence of clinical factors and a hypothetical polygenic risk prediction tool.

RESULTS

Among 2812 MGI participants with diverticular disease, 1964 were asymptomatic, 574 had mild disease, and 274 had severe disease. PRS was associated with occurrence and severity. Patients in the highest PRS decile were more likely to have diverticulitis [odds ratio (OR)=1.84; 95% confidence interval (CI), 1.42-2.38)] and more likely to have severe diverticulitis (OR=1.61; 95% CI, 1.04-2.51) than the bottom 50%. Among 213 surveyed surgeons, extreme disease-specific factors had the largest utility (3 episodes in the last year, +74.4; percutaneous drain, + 69.4). Factors with strongest influence against surgery included 1 lifetime episode (-63.3), outpatient management (-54.9), and patient preference (-39.6). PRS was predicted to have high utility (+71).

CONCLUSIONS

A PRS derived from a large national biobank was externally validated, and found to be associated with the incidence and severity of diverticulitis. Surgeons have clear guidance at clinical extremes, but demonstrate equipoise in intermediate scenarios. Surgeons are receptive to PRS, which may be most useful in marginal clinical situations. Given the current lack of accurate prognostication in recurrent diverticulitis, PRS may provide a novel approach for improving patient counseling and decision-making.

Leveraging electronic health records to streamline the conduct of cardiovascular clinical trials

Conventional randomized controlled trials (RCTs) can be expensive, time intensive, and complex to conduct. Trial recruitment, participation, and data collection can burden participants and research personnel. In the past two decades, there have been rapid technological advances and an exponential growth in digitized healthcare data. Embedding RCTs, including cardiovascular outcome trials, into electronic health record systems or registries may streamline screening, consent, randomization, follow-up visits, and outcome adjudication. Moreover, wearable sensors (i.e. health and fitness trackers) provide an opportunity to collect data on cardiovascular health and risk factors in unprecedented detail and scale, while growing internet connectivity supports the collection of patient-reported outcomes. There is a pressing need to develop robust mechanisms that facilitate data capture from diverse databases and guidance to standardize data definitions. Importantly, the data collection infrastructure should be reusable to support multiple cardiovascular RCTs over time. Systems, processes, and policies will need to have sufficient flexibility to allow interoperability between different sources of data acquisition. Clinical research guidelines, ethics oversight, and regulatory requirements also need to evolve. This review highlights recent progress towards the use of routinely generated data to conduct RCTs and discusses potential solutions for ongoing barriers. There is a particular focus on methods to utilize routinely generated data for trials while complying with regional data protection laws. The discussion is supported with examples of cardiovascular outcome trials that have successfully leveraged the electronic health record, web-enabled devices or administrative databases to conduct randomized trials.

Advances and Challenges for GWAS Analysis in Cardiac Diseases: A Focus on Coronary Artery Disease (CAD)

The achievement of genome-wide association studies (GWAS) has rapidly progressed our understanding of the etiology of coronary artery disease (CAD). It unlocks new strategies to strengthen the stalling of CAD drug development. In this review, we highlighted the recent drawbacks, mainly pointing out those involved in identifying causal genes and interpreting the connections between disease pathology and risk variants. We also benchmark the novel insights into the biological mechanism behind the disease primarily based on outcomes of GWAS. Furthermore, we also shed light on the successful discovery of novel treatment targets by introducing various layers of "omics" data and applying systems genetics strategies. Lastly, we discuss in-depth the significance of precision medicine that is helpful to improve through GWAS analysis in cardiovascular research.

A review on experimental surgical models and anesthetic protocols of heart failure in rats

Heart failure (HF) is a serious health and economic burden worldwide, and its prevalence is continuously increasing. Current medications effectively moderate the progression of symptoms, and there is a need for novel preventative and reparative treatments. The development of novel HF treatments requires the testing of potential therapeutic procedures in appropriate animal models of HF. During the past decades, murine models have been extensively used in fundamental and translational research studies to better understand the pathophysiological mechanisms of HF and develop more effective methods to prevent and control congestive HF. Proper surgical approaches and anesthetic protocols are the first steps in creating these models, and each successful approach requires a proper anesthetic protocol that maintains good recovery and high survival rates after surgery. However, each protocol may have shortcomings that limit the study's outcomes. In addition, the ethical regulations of animal welfare in certain countries prohibit the use of specific anesthetic agents, which are widely used to establish animal models. This review summarizes the most common and recent surgical models of HF and the anesthetic protocols used in rat models. We will highlight the surgical approach of each model, the use of anesthesia, and the limitations of the model in the study of the pathophysiology and therapeutic basis of common cardiovascular diseases.

Examining the Impact of Polygenic Risk Information in Primary Care

BACKGROUND

Polygenic risk testing examines variation across multiple genes to estimate a risk score for a particular disease, including risk scores for many common, chronic health conditions. Although polygenic risk information (PRI) may be a promising tool for enhancing preventive counseling and facilitating early identification of disease, its potential impact on primary-care encounters and disease prevention efforts has not been well characterized.

METHODS

We conducted in-depth, semi-structured interviews of patients to assess their understandings of PRI and their beliefs about its relevance to disease prevention.

RESULTS

We completed interviews with 19 participants. Participants described enthusiasm for the generation of PRI and recognized its utility for disease prevention. Participants also described the value of PRI as limited if not corroborated by non-genetic risk factors. Finally, participants noted that PRI, by itself, would be insufficient as a trigger for initiating many preventive interventions.

CONCLUSION

PRI has the potential to become an important tool in primary care. However, patient views about PRI as well as the complexities of disease prevention in the primary care context may limit the impact of PRI on disease prevention.

Advances and Applications of Polygenic Scores for Coronary Artery Disease

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.

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.

Components, prospects and challenges of personalized prevention

Effective preventive strategies are urgently needed to address the rising burden of non-communicable diseases such as cardiovascular disease and cancer. To date, most prevention efforts to reduce disease incidence have primarily targeted populations using "one size fits all" public health recommendations and strategies. However, the risk for complex heterogeneous diseases is based on a multitude of clinical, genetic, and environmental factors, which translate into individual sets of component causes for every person. Recent advances in genetics and multi-omics enable the use of new technologies to stratify disease risks at an individual level fostering personalized prevention. In this article, we review the main components of personalized prevention, provide examples, and discuss both emerging opportunities and remaining challenges for its implementation. We encourage physicians, health policy makers, and public health professionals to consider and apply the key elements and examples of personalized prevention laid out in this article while overcoming challenges and potential barriers to their implementation.

Models of communication for polygenic scores and associated psychosocial and behavioral effects on recipients: A systematic review

PURPOSE

This study aimed to systematically review current models for communicating polygenic scores (PGS) and psycho-behavioral outcomes of receiving PGSs.

METHODS

Original research on communicating PGSs and reporting on psycho-behavioral outcomes was included. Search terms were applied to 5 databases and were limited by date (2009-2021).

RESULTS

In total, 28 articles, representing 17 studies in several disease settings were identified. There was limited consistency in PGS communication and evaluation/reporting of outcomes. Most studies (n = 14) presented risk in multiple ways (ie, numerically, verbally, and/or visually). Three studies provided personalized lifestyle advice and additional resources. Only 1 of 17 studies reported using behavior change theory to inform their PGS intervention. A total of 8 studies found no evidence of long-term negative psychosocial effects up to 12 months post result. Of 14 studies reporting on behavior, 9 found at least 1 favorable change after PGS receipt. When stratified by risk, 7 out of 9 studies found high PGS was associated with favorable changes including lifestyle, medication, and screening. Low-risk PGS was not associated with maladaptive behaviors (n = 4).

CONCLUSION

PGS has the potential to benefit health behavior. High variability among studies emphasizes the need for developing standardized guidelines for communicating PGSs and evaluating psycho-behavioral outcomes. Our findings call for development of best communication practices and evidence-based interventions informed by behavior change theories.

Associations of genetic and infectious risk factors with coronary heart disease

Coronary heart disease (CHD) is one of the most pressing health problems of our time and a major cause of preventable death. CHD results from complex interactions between genetic and environmental factors. Using multiplex serological testing for persistent or frequently recurring infections and genome-wide analysis in a prospective population study, we delineate the respective and combined influences of genetic variation, infections, and low-grade inflammation on the risk of incident CHD. Study participants are enrolled in the CoLaus|PsyCoLaus study, a longitudinal, population-based cohort with baseline assessments from 2003 through 2008 and follow-up visits every 5 years. We analyzed a subgroup of 3459 individuals with available genome-wide genotyping data and immunoglobulin G levels for 22 persistent or frequently recurring pathogens. All reported CHD events were evaluated by a panel of specialists. We identified independent associations with incident CHD using univariable and multivariable stepwise Cox proportional hazards regression analyses. Of the 3459 study participants, 210 (6.07%) had at least one CHD event during the 12 years of follow-up. Multivariable stepwise Cox regression analysis, adjusted for known cardiovascular risk factors, socioeconomic status, and statin intake, revealed that high polygenic risk (hazard ratio [HR] 1.31, 95% CI 1.10-1.56, p=2.64 × 10^-3) and infection with Fusobacterium nucleatum (HR 1.63, 95% CI 1.08-2.45, p=1.99 × 10^-2) were independently associated with incident CHD. In a prospective, population-based cohort, high polygenic risk and infection with F. nucleatum have a small, yet independent impact on CHD risk.

Effectiveness and feasibility of cardiovascular disease personalized prevention on high polygenic risk score subjects: a randomized controlled pilot study

Aims

The aim of this study was to evaluate the effect of the intervention by proactively sharing a patient's high polygenic risk score (PRS) for coronary artery disease (CAD). Outcomes included: (i) reduction in cardiovascular disease (CVD) risk factors over 12 months; (ii) difference in purchased prescriptions of lipid-lowering and anti-hypertensive drugs between intervention group and control group subjects; and (iii) opinion of the participating physicians and subjects on PRS usefulness.

Methods and results

This randomized controlled trial was conducted among middle-aged subjects with a top 20% CAD PRS in a family medicine setting. Participants were selected from 26 953 Estonian Biobank cohort participants. Subjects were informed and counselled about their PRS score and CAD risk using the visual tool at baseline (Visit I), counselling session (Visit II), and on the final Visit III at 12 months. The primary endpoint was not significantly different. However, the intervention group participants had a significantly higher probability of initiating statin treatment compared with the controls. Their levels of LDL-cholesterol (LDL-C) were significantly decreased compared with baseline on Visit III and significantly lower than in the control group. The vast majority of participating family physicians believe that finding out about genetic risks will affect the subject's lifestyle and medication compliance.

Conclusion

Most of our outcome measures were in favour of this intervention. Participants achieved larger changes in cholesterol and blood pressure values. The vast majority (98.4%) of family physicians are interested in continuing to use genetic risk assessment in practice.

Validation of Polygenic Risk Scores for Coronary Heart Disease in a Middle Eastern Cohort Using Whole Genome Sequencing

BACKGROUND

Enthusiasm for using polygenic risk scores (PRSs) in clinical practice is tempered by concerns about their portability to diverse ancestry groups, thus motivating genome-wide association studies in non-European ancestry cohorts.

METHODS

We conducted a genome-wide association study for coronary heart disease in a Middle Eastern cohort using whole genome sequencing and assessed the performance of 6 PRSs developed with methods including LDpred (PGS000296), metaGRS (PGS000018), Pruning and Thresholding (PGS000337), and an EnsemblePRS we developed. Additionally, we evaluated the burden of rare variants in lipid genes in cases and controls. Whole genome sequencing at 30× coverage was performed in 1067 coronary heart disease cases (mean age=59 years; 70.3% males) and 6170 controls (mean age=40 years; 43.5% males).

RESULTS

The majority of PRSs performed well; odds ratio (OR) per 1 SD increase (OR_1sd) was highest for PGS000337 (OR_1sd=1.81, 95% CI [1.66-1.98], P=3.07×10^-41). EnsemblePRS performed better than individual PRSs (OR_1sd=1.8, 95% CI [1.66-1.96], P=5.89×10^-44). The OR for the 10th decile versus the remaining deciles was >3.2 for PGS000337, PGS000296, PGS000018, and reached 4.58 for EnsemblePRS. Of 400 known genome-wide significant loci, 33 replicated at P<10^-4. However, the 9p21 locus did not replicate. Six suggestive (P<10^-5) new loci/genes with plausible biological function were identified (eg, CORO7, RBM47, PDE4D). The burden of rare functional variants in LDLR, APOB, PCSK9, and ANGPTL4 was greater in cases than controls.

CONCLUSIONS

Overall, we demonstrate that PRSs derived from European ancestry genome-wide association studies performed well in a Middle Eastern cohort, suggesting these could be used in the clinical setting while ancestry-specific PRSs are developed.

The clinical utility of polygenic risk scores in genomic medicine practices: a systematic review

Genomic medicine aims to improve health using the individual genomic data of people to inform care. While clinical utility of genomic medicine in many monogenic, Mendelian disorders is amply demonstrated, clinical utility is less evident in polygenic traits, e.g., coronary artery disease or breast cancer. Polygenic risk scores (PRS) are subsets of individual genotypes designed to capture heritability of common traits, and hence to allow the stratification of risk of the trait in a population. We systematically reviewed the PubMed database for unequivocal evidence of clinical utility of polygenic risk scores, using stringent inclusion and exclusion criteria. While we identified studies demonstrating clinical validity in conditions where medical intervention based on a PRS is likely to benefit patient outcome, we did not identify a single study demonstrating unequivocally such a benefit, i.e. clinical utility. We conclude that while the routine use of PRSs hold great promise, translational research is still needed before they should enter mainstream clinical practice.

Cost-Effectiveness of Polygenic Risk Scores to Guide Statin Therapy for Cardiovascular Disease Prevention

BACKGROUND

Atherosclerotic cardiovascular diseases (CVDs) are leading causes of death despite effective therapies and result in unnecessary morbidity and mortality throughout the world. We aimed to investigate the cost-effectiveness of polygenic risk scores (PRS) to guide statin therapy for Canadians with intermediate CVD risk and model its economic outlook.

METHODS

This cost-utility analysis was conducted using UK Biobank prospective cohort study participants, with recruitment from 2006 to 2010, and at least 10 years of follow-up. We included nonrelated white British-descent participants (n=96 116) at intermediate CVD risk with no prior lipid lowering medication or statin-indicated conditions. A coronary artery disease PRS was used to inform decision to use statins. The effects of statin therapy with and without PRS, as well as CVD events were modelled to determine the incremental cost-effectiveness ratio from a Canadian public health care perspective. We discounted future costs and quality-adjusted life-years by 1.5% annually.

RESULTS

The optimal economic strategy was when intermediate risk individuals with a PRS in the top 70% are eligible for statins while the lowest 1% are excluded. Base-case analysis at a genotyping cost of $70 produced an incremental cost-effectiveness ratio of $172 906 (143 685 USD) per quality-adjusted life-year. In the probabilistic sensitivity analysis, the intervention has approximately a 50% probability of being cost-effective at $179 100 (148 749 USD) per quality-adjusted life-year. At a $0 genotyping cost, representing individuals with existing genotyping information, PRS-guided strategies dominated standard care when 12% of the lowest PRS individuals were withheld from statins. With improved PRS predictive performance and lower genotyping costs, the incremental cost-effectiveness ratio demonstrates possible cost-effectiveness under thresholds of $150 000 and possibly $50 000 per quality-adjusted life-year.

CONCLUSIONS

This study suggests that using PRS alongside existing guidelines might be cost-effective for CVD. Stronger predictiveness combined with decreased cost of PRS could further improve cost-effectiveness, providing an economic basis for its inclusion into clinical care.

Use of Polygenic Risk Scores for Coronary Heart Disease in Ancestrally Diverse Populations

PURPOSE OF REVIEW

A polygenic risk score (PRS) is a measure of genetic liability to a disease and is typically normally distributed in a population. Individuals in the upper tail of this distribution often have relative risk equivalent to that of monogenic form of the disease. The majority of currently available PRSs for coronary heart disease (CHD) have been generated from cohorts of European ancestry (EUR) and vary in their applicability to other ancestry groups. In this report, we review the performance of PRSs for CHD across different ancestries and efforts to reduce variability in performance including novel population and statistical genetics approaches.

RECENT FINDINGS

PRSs for CHD perform robustly in EUR populations but lag in performance in non-EUR groups, particularly individuals of African ancestry. Several large consortia have been established to enable genomic studies in diverse ancestry groups and develop methods to improve PRS performance in multi-ancestry contexts as well as admixed individuals. These include fine-mapping to ascertain causal variants, trans ancestry meta-analyses, and ancestry deconvolution in admixed individuals. PRSs are being used in the clinical setting but enthusiasm has been tempered by the variable performance in non-EUR ancestry groups. Increasing diversity in genomic association studies and continued innovation in methodological approaches are needed to improve PRS performance in non-EUR individuals for equitable implementation of genomic medicine.

Polygenic scores in biomedical research

Public health strategies aimed at disease prevention or early detection and intervention have the potential to advance human health worldwide. However, their success depends on the identification of risk factors that underlie disease burden in the general population. Genome-wide association studies (GWAS) have implicated thousands of single-nucleotide polymorphisms (SNPs) in common complex diseases or traits. By calculating a weighted sum of the number of trait-associated alleles harboured by an individual, a polygenic score (PGS), also called a polygenic risk score (PRS), can be constructed that reflects an individual’s estimated genetic predisposition for a given phenotype. Here, we ask six experts to give their opinions on the utility of these probabilistic tools, their strengths and limitations, and the remaining barriers that need to be overcome for their equitable use.

Pharmacogenetics of Cardiovascular Prevention in Diabetes: From Precision Medicine to Identification of Novel Targets

Pharmacogenetics—a branch of precision medicine—holds the promise of becoming a novel tool to reduce the social and healthcare burdens of cardiovascular disease (CVD) and coronary artery disease (CAD) in diabetes. The improvement in cardiovascular risk stratification resulting from adding genetic characteristics to clinical data has moved from the modest results obtained with genetic risk scores based on few genetic variants, to the progressively better performances of polygenic risk scores based on hundreds to millions of variants (CAD-PGRS). Similarly, over the past few years, the number of studies investigating the use of CAD-PGRS to identify different responses to cardio-preventive treatment has progressively increased, yielding striking results for lipid-lowering drugs such as proprotein convertase subtilisin/kexin type 9 (PCSK9) inhibitors and statins. The use of CAD-PGRS to stratify patients based on their likely response to diabetes-specific interventions has been less successful, but promising results have been obtained with regard to specific genetic variants modulating the effects of interventions such as intensive glycemic control and fenofibrate. The finding of diabetes-specific CAD-loci, such as GLUL, has also led to the identification of promising new targets that might hopefully result in the development of specific therapies to reduce CVD burden in patients with diabetes. As reported in consensus statements from international diabetes societies, some of these pharmacogenetic approaches are expected to be introduced in clinical practice over the next decade. For this to happen, in addition to continuing to improve and validate these tools, it will be necessary to educate physicians and patients about the opportunities and limits of pharmacogenetics, as summarized in this review.

Clinicians' Perceptions towards Precision Medicine Tools for Cardiovascular Disease Risk Stratification in South Africa

Cardiovascular diseases (CVDs) are a leading cause of mortality and morbidity in South Africa. Risk stratification is the preferred approach to disease prevention, but identifying patients at high risk for CVD remains challenging. Assessing genetic risk could improve stratification and inform a clinically relevant precision medicine (PM) approach. Clinicians are critical to PM adoption, thus, this study explores practicing clinicians’ perceptions of PM-based CVD risk stratification in South Africa’s public health setting. Practicing clinicians (n = 109) at four teaching hospitals in Johannesburg, South Africa, completed an electronic self-administered survey. The effect of demographic and professional characteristics on PM-based CVD risk stratification perceptions was assessed. Fewer than 25% of respondents used clinical genetic testing, and 14% had formal genetics training. 78% had a low mean knowledge score, with higher scores associated with genetic training (p < 0.0005) and research involvement (p < 0.05). Despite limited knowledge and resources, 84% perceived PM approaches positively. 57% felt confident in applying the PM-based approach, with those already undertaking CVD risk stratification more confident (p < 0.001). High cost and limited access to genetics services are key barriers. Integrating genetic information into established clinical tools will likely increase confidence in using PM approaches. Addressing the genetics training gap and investment into the country’s genomics capacity is needed to advance PM in South Africa.

Polygenic Risk Scores for Cardiovascular Disease: A Scientific Statement From the American Heart Association

Cardiovascular disease is the leading contributor to years lost due to disability or premature death among adults. Current efforts focus on risk prediction and risk factor mitigation' which have been recognized for the past half-century. However, despite advances, risk prediction remains imprecise with persistently high rates of incident cardiovascular disease. Genetic characterization has been proposed as an approach to enable earlier and potentially tailored prevention. Rare mendelian pathogenic variants predisposing to cardiometabolic conditions have long been known to contribute to disease risk in some families. However, twin and familial aggregation studies imply that diverse cardiovascular conditions are heritable in the general population. Significant technological and methodological advances since the Human Genome Project are facilitating population-based comprehensive genetic profiling at decreasing costs. Genome-wide association studies from such endeavors continue to elucidate causal mechanisms for cardiovascular diseases. Systematic cataloging for cardiovascular risk alleles also enabled the development of polygenic risk scores. Genetic profiling is becoming widespread in large-scale research, including in health care-associated biobanks, randomized controlled trials, and direct-to-consumer profiling in tens of millions of people. Thus, individuals and their physicians are increasingly presented with polygenic risk scores for cardiovascular conditions in clinical encounters. In this scientific statement, we review the contemporary science, clinical considerations, and future challenges for polygenic risk scores for cardiovascular diseases. We selected 5 cardiometabolic diseases (coronary artery disease, hypercholesterolemia, type 2 diabetes, atrial fibrillation, and venous thromboembolic disease) and response to drug therapy and offer provisional guidance to health care professionals, researchers, policymakers, and patients.

Challenges and Opportunities for Developing More Generalizable Polygenic Risk Scores

Polygenic risk scores (PRS) estimate an individual's genetic likelihood of complex traits and diseases by aggregating information across multiple genetic variants identified from genome-wide association studies. PRS can predict a broad spectrum of diseases and have therefore been widely used in research settings. Some work has investigated their potential applications as biomarkers in preventative medicine, but significant work is still needed to definitively establish and communicate absolute risk to patients for genetic and modifiable risk factors across demographic groups. However, the biggest limitation of PRS currently is that they show poor generalizability across diverse ancestries and cohorts. Major efforts are underway through methodological development and data generation initiatives to improve their generalizability. This review aims to comprehensively discuss current progress on the development of PRS, the factors that affect their generalizability, and promising areas for improving their accuracy, portability, and implementation.

Clinical Implementation of Combined Monogenic and Polygenic Risk Disclosure for Coronary Artery Disease

BACKGROUND

State-of-the-art genetic risk interpretation for a common complex disease such as coronary artery disease (CAD) requires assessment for both monogenic variants—such as those related to familial hypercholesterolemia—as well as the cumulative impact of many common variants, as quantified by a polygenic score.

OBJECTIVES

The objective of the study was to describe a combined monogenic and polygenic CAD risk assessment program and examine its impact on patient understanding and changes to clinical management.

METHODS

Study participants attended an initial visit in a preventive genomics clinic and a disclosure visit to discuss results and recommendations, primarily via telemedicine. Digital postdisclosure surveys and chart review evaluated the impact of disclosure.

RESULTS

There were 60 participants (mean age 51 years, 37% women, 72% with no known CAD), including 30 (50%) referred by their cardiologists and 30 (50%) self-referred. Two (3%) participants had a monogenic variant pathogenic for familial hypercholesterolemia, and 19 (32%) had a high polygenic score in the top quintile of the population distribution. In a postdisclosure survey, both the genetic test report (in 80% of participants) and the discussion with the clinician (in 89% of participants) were ranked as very or extremely helpful in understanding the result. Of the 42 participants without CAD, 17 or 40% had a change in management, including statin initiation, statin intensification, or coronary imaging.

CONCLUSIONS

Combined monogenic and polygenic assessments for CAD risk provided by preventive genomics clinics are beneficial for patients and result in changes in management in a significant portion of patients.

Inherited genetics of adult diffuse glioma and polygenic risk scores-a review

Knowledge about inherited and acquired genetics of adult diffuse glioma has expanded significantly over the past decade. Genomewide association studies (GWAS) stratified by histologic subtype identified six germline variants that were associated specifically with glioblastoma (GBM) and 12 that were associated with lower grade glioma. A GWAS performed using the 2016 WHO criteria, stratifying patients by IDH mutation and 1p/19q codeletion (as well as TERT promoter mutation), discovered that many of the known variants are associated with specific WHO glioma subtypes. In addition, the GWAS stratified by molecular group identified two additional novel regions: variants in D2HGDH that were associated with tumors that had an IDH mutation and a variant near FAM20C that was associated with tumors that had both IDH mutation and 1p/19q codeletion. The results of these germline associations have been used to calculate polygenic risk scores, from which to estimate relative and absolute risk of overall glioma and risk of specific glioma subtypes. We will review the concept of polygenic risk models and their potential clinical utility, as well as discuss the published adult diffuse glioma polygenic risk models. To date, these prior genetic studies have been done on European populations. Using the published glioma polygenic risk model, we show that the genetic associations published to date do not generalize across genetic ancestries, demonstrating that genetic studies need to be done on more diverse populations.

Development and validation of a trans-ancestry polygenic risk score for type 2 diabetes in diverse populations

BACKGROUND

Type 2 diabetes (T2D) is a worldwide scourge caused by both genetic and environmental risk factors that disproportionately afflicts communities of color. Leveraging existing large-scale genome-wide association studies (GWAS), polygenic risk scores (PRS) have shown promise to complement established clinical risk factors and intervention paradigms, and improve early diagnosis and prevention of T2D. However, to date, T2D PRS have been most widely developed and validated in individuals of European descent. Comprehensive assessment of T2D PRS in non-European populations is critical for equitable deployment of PRS to clinical practice that benefits global populations.

METHODS

We integrated T2D GWAS in European, African, and East Asian populations to construct a trans-ancestry T2D PRS using a newly developed Bayesian polygenic modeling method, and assessed the prediction accuracy of the PRS in the multi-ethnic Electronic Medical Records and Genomics (eMERGE) study (11,945 cases; 57,694 controls), four Black cohorts (5137 cases; 9657 controls), and the Taiwan Biobank (4570 cases; 84,996 controls). We additionally evaluated a post hoc ancestry adjustment method that can express the polygenic risk on the same scale across ancestrally diverse individuals and facilitate the clinical implementation of the PRS in prospective cohorts.

RESULTS

The trans-ancestry PRS was significantly associated with T2D status across the ancestral groups examined. The top 2% of the PRS distribution can identify individuals with an approximately 2.5-4.5-fold of increase in T2D risk, which corresponds to the increased risk of T2D for first-degree relatives. The post hoc ancestry adjustment method eliminated major distributional differences in the PRS across ancestries without compromising its predictive performance.

CONCLUSIONS

By integrating T2D GWAS from multiple populations, we developed and validated a trans-ancestry PRS, and demonstrated its potential as a meaningful index of risk among diverse patients in clinical settings. Our efforts represent the first step towards the implementation of the T2D PRS into routine healthcare.

Capturing additional genetic risk from family history for improved polygenic risk prediction

Family history of complex traits may reflect transmitted rare pathogenic variants, intra-familial shared exposures to environmental and lifestyle factors, as well as a common genetic predisposition. We developed a latent factor model to quantify trait heritability in excess of that captured by a common variant-based polygenic risk score, but inferable from family history. For 941 children in the Avon Longitudinal Study of Parents and Children cohort, a joint predictor combining a polygenic risk score for height and mid-parental height was able to explain ^~55% of the total variance in sex-adjusted adult height z-scores, close to the estimated heritability. Marginal yet consistent risk prediction improvements were also achieved among ^~400,000 European ancestry participants for 11 complex diseases in the UK Biobank. Our work showcases a paradigm for risk calculation, and supports incorporation of family history into polygenic risk score-based genetic risk prediction models.

Use of coronary computed tomography or polygenic risk scores to prompt action to reduce coronary artery disease risk: the CAPAR-CAD trial

BACKGROUND

The traditional primary prevention paradigm for coronary artery disease (CAD) centers on population-based algorithms to classify individual risk. However, this approach often misclassifies individuals and leaves many in the 'intermediate' category, for whom there is no clear preferred prevention strategy. Coronary artery calcium (CAC) and polygenic risk scoring (PRS) are 2 contemporary tools for risk prediction to enhance the impact of effective management.

AIMS

To determine how these CAC and PRS impact adherence to pharmacotherapy and lifestyle measures in asymptomatic individuals with subclinical atherosclerosis.

METHODS

The CAPAR-CAD study is a multicenter, open, randomized controlled trial in Victoria, Australia. Participants are self-selected individuals aged 40 to 70 years with no prior history of cardiovascular disease (CVD), intermediate 10-year risk for CAD as determined by the pooled cohort equation (PCE), and CAC scores >0. All participants will have a health assessment, a full CT coronary angiogram (CTCA), and PRS calculation. They will then be randomized to receive their risk presented either as PCE and CAC, or PCE and PRS. The intervention includes e-Health coaching focused on risk factor management, health education and pharmacotherapy, and follow-up to augment adherence to a statin medication. The primary endpoint is a change in low-density lipoprotein cholesterol (LDL-C) from baseline to 12 months. The secondary endpoint is between-group differences in behavior modification and adherence to statin pharmacotherapy.

RESULTS

As of July 31, 2021, we have screened 1,903 individuals. We present the results of the 574 participants deemed eligible after baseline assessment.

Perspectives of diverse Spanish- and English-speaking patients on the clinical use of polygenic risk scores

PURPOSE

As polygenic risk scores (PRS) emerge as promising tools to inform clinical care, there is a pressing need for patient-centered evidence to guide their implementation, particularly in diverse populations. Here, we conducted in-depth interviews of diverse Spanish- and English-speaking patients to explore their perspectives on clinical PRS.

METHODS

We enrolled 30 biobank participants aged 35-50 years through a purposive sampling strategy, ensuring that >75% self-reported as African/African American or Hispanic/Latinx and half were Spanish-speaking. Semistructured interviews in Spanish or English explored attitudes toward PRS, barriers to adoption, and communication preferences. Data were analyzed using an inductive thematic analysis approach.

RESULTS

Perceived utility of clinical PRS focused on the potential for personal health benefits, and most participants stated that high-risk results would prompt physician consultations and health behavior changes. There was little concern among participants about the limited predictive power of PRS for non-European populations. Barriers to uptake of PRS testing and adoption of PRS-related recommendations included socioeconomic factors, insurance status, race, ethnicity, language, and inadequate understanding of PRS. Participants favored in-person PRS result disclosure by their physician.

CONCLUSION

Findings provide valuable insight into diverse patients' attitudes and potential barriers related to clinical PRS, guiding future research and patient-centered clinical implementation.

Contribution of Genome-Wide Polygenic Score to Risk of Coronary Artery Disease in Childhood Cancer Survivors

Background

Adverse cardiovascular outcomes such as coronary artery disease (CAD) are the leading noncancer causes of morbidity and mortality among childhood cancer survivors.

Objectives

The aim of this study was to assess the role of a genome-wide polygenic score (GPS) for CAD, well validated in the general population, and its interplay with cancer-related risk factors among childhood cancer survivors.

Methods

In a cohort study of 2,472 5-year childhood cancer survivors from the St. Jude Lifetime Cohort, the association between the GPS and the risk of CAD was performed using Cox regression models adjusted for age at cancer diagnosis, sex, cumulative dose of anthracyclines, and mean heart radiation dose.

Results

Among survivors of European ancestry, the GPS was significantly associated with the risk of CAD (HR per 1 SD of the GPS: 1.25; 95% CI: 1.04-1.49; P = 0.014). Compared with the first tertile, survivors in the upper tertile had a greater risk of CAD (1.51-fold higher HR of CAD [95% CI: 0.96-2.37; P = 0.074]), although the difference was not statistically significant. The GPS-CAD association was stronger among survivors diagnosed with cancer at age <10 years exposed to >25 Gy heart radiation (HR top vs. bottom tertile of GPS: 15.49; 95% CI: 5.24-45.52; P_trend = 0.005) but not among those diagnosed at age ≥10 years (P_trend ≥ 0.77) and not among those diagnosed at age <10 years exposed to ≤25 Gy heart radiation (P_trend = 0.23). Among high-risk survivors, defined by an estimated relative hazard ≥3.0 from fitted Cox models including clinical risk factors alone, the cumulative incidence of CAD at 40 years from diagnosis was 29% (95% CI: 13%-45%). After incorporating the GPS into the model, the cumulative incidence increased to 48% (95% CI: 26%-69%).

Conclusions

Childhood cancer survivors are at risk for premature CAD. A GPS may help identify those who may benefit from targeted screening and personalized preventive interventions.

2022 Prevention of chronic non-communicable diseases in Of the Russian Federation. National guidelines

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Impact of polygenic risk communication: an observational mobile application-based coronary artery disease study

We developed a smartphone application, MyGeneRank, to conduct a prospective observational cohort study (NCT03277365) involving the automated generation, communication, and electronic capture of response to a polygenic risk score (PRS) for coronary artery disease (CAD). Adults with a smartphone and an existing 23andMe genetic profiling self-referred to the study. We evaluated self-reported actions taken in response to personal CAD PRS information, with special interest in the initiation of lipid-lowering therapy. 19% (721/3,800) of participants provided complete responses for baseline and follow-up use of lipid-lowering therapy. 20% (n = 19/95) of high CAD PRS vs 7.9% (n = 8/101) of low CAD PRS participants initiated lipid-lowering therapy at follow-up (p-value = 0.002). Both the initiation of statin and non-statin lipid-lowering therapy was associated with degree of CAD PRS: 15.2% (n = 14/92) vs 6.0% (n = 6/100) for statins (p-value = 0.018) and 6.8% (n = 8/118) vs 1.6% (n = 2/123) for non-statins (p-value = 0.022) in high vs low CAD PRS, respectively. High CAD PRS was also associated with earlier initiation of lipid lowering therapy (average age of 52 vs 65 years in high vs low CAD PRS respectively, p-value = 0.007). Overall, degree of CAD PRS was associated with use of any lipid-lowering therapy at follow-up: 42.4% (n = 56/132) vs 28.5% (n = 37/130) (p-value = 0.009). We find that digital communication of personal CAD PRS information is associated with increased and earlier lipid-lowering initiation in individuals of high CAD PRS. Loss to follow-up is the primary limitation of this study. Alternative communication routes, and long-term studies with EHR-based outcomes are needed to understand the generalizability and durability of this finding.

Heart Disease and Stroke Statistics-2022 Update: A Report From the American Heart Association

BACKGROUND

The American Heart Association, in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, diet, and weight) and health factors (cholesterol, blood pressure, and glucose control) that contribute to cardiovascular health. The Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, congenital heart disease, rhythm disorders, subclinical atherosclerosis, coronary heart disease, heart failure, valvular disease, venous disease, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs).

METHODS

The American Heart Association, through its Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States to provide the most current information available in the annual Statistical Update. The 2022 Statistical Update is the product of a full year's worth of effort by dedicated volunteer clinicians and scientists, committed government professionals, and American Heart Association staff members. This year's edition includes data on the monitoring and benefits of cardiovascular health in the population and an enhanced focus on social determinants of health, adverse pregnancy outcomes, vascular contributions to brain health, and the global burden of cardiovascular disease and healthy life expectancy.

RESULTS

Each of the chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics.

CONCLUSIONS

The Statistical Update represents a critical resource for the lay public, policymakers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.

LDL-C Concentrations and the 12-SNP LDL-C Score for Polygenic Hypercholesterolaemia in Self-Reported South Asian, Black and Caribbean Participants of the UK Biobank

Background: Monogenic familial hypercholesterolaemia (FH) is an autosomal dominant disorder characterised by elevated low-density lipoprotein cholesterol (LDL-C) concentrations due to monogenic mutations in LDLR, APOB, PCSK9, and APOE. Some mutation-negative patients have a polygenic cause for elevated LDL-C due to a burden of common LDL-C-raising alleles, as demonstrated in people of White British (WB) ancestry using a 12-single nucleotide polymorphism (SNP) score. This score has yet to be evaluated in people of South Asian (SA), and Black and Caribbean (BC) ethnicities. Objectives: 1) Compare the LDL-C and 12-SNP score distributions across the three major ethnic groups in the United Kingdom: WB, SA, and BC individuals; 2) compare the association of the 12-SNP score with LDL-C in these groups; 3) evaluate ethnicity-specific and WB 12-SNP score decile cut-off values, applied to SA and BC ethnicities, in predicting LDL-C concentrations and hypercholesterolaemia (LDL-C>4.9 mmol/L). Methods: The United Kingdom Biobank cohort was used to analyse the LDL-C (adjusted for statin use) and 12-SNP score distributions in self-reported WB (n = 353,166), SA (n = 7,016), and BC (n = 7,082) participants. To evaluate WB and ethnicity-specific 12-SNP score deciles, the total dataset was split 50:50 into a training and testing dataset. Regression analyses (logistic and linear) were used to analyse hypercholesterolaemia (LDL-C>4.9 mmol/L) and LDL-C. Findings: The mean (±SD) measured LDL-C differed significantly between the ethnic groups and was highest in WB [3.73 (±0.85) mmol/L], followed by SA [3.57 (±0.86) mmol/L, p < 2.2 × 10^-16], and BC [3.42 (±0.90) mmol/L] participants (p < 2.2 × 10^-16). There were significant differences in the mean (±SD) 12-SNP score between WB [0.90 (±0.23)] and BC [0.72 (±0.25), p < 2.2 × 10^-16], and WB and SA participants [0.86 (±0.19), p < 2.2 × 10^-16]. In all three ethnic groups the 12-SNP score was associated with measured LDL-C [R ² (95% CI): WB = 0.067 (0.065-0.069), BC = 0.080 (0.063-0.097), SA = 0.027 (0.016-0.038)]. The odds ratio and the area under the curve for hypercholesterolaemia were not statistically different when applying ethnicity-specific or WB deciles in all ethnic groups. Interpretation: We provide information on the differences in LDL-C and the 12-SNP score distributions in self-reported WB, SA, and BC individuals of the United Kingdom Biobank. We report the association between the 12-SNP score and LDL-C in these ethnic groups. We evaluate the performance of ethnicity-specific and WB 12-SNP score deciles in predicting LDL-C and hypercholesterolaemia.

A systematic review and analysis of the use of polygenic scores in pharmacogenomics

Polygenic scores (PGS) have emerged as promising tools for complex trait risk prediction. The application of these scores to pharmacogenomics provides new opportunities to improve the prediction of treatment outcomes. To gain insight into this area of research, we conducted a systematic review and accompanying analysis. This review uncovered 51 papers examining the use of PGS for drug-related outcomes, with the majority of these papers focusing on the treatment of psychiatric disorders (n=30). Due to difficulties in collecting large cohorts of uniformly treated patients, the majority of pharmacogenomic PGS were derived from large-scale genome-wide association studies of disease phenotypes that were related to the pharmacogenomic phenotypes under investigation (e.g. schizophrenia-derived PGS for antipsychotic response prediction). Examination of the research participants included in these studies revealed that the majority of cohort participants were of European descent (78.4%). These biases were also reflected in research affiliations, which were heavily weighted towards institutions located in Europe and North America, with no first or last authors originating from institutions in Africa or South Asia. There was also substantial variability in the methods used to develop PGS, with between 3 and 6.6 million variants included in the PGS. Finally, we observed significant inconsistencies in the reporting of PGS analyses and results, particularly in terms of risk model development and application, coupled with a lack of data transparency and availability, with only three pharmacogenomics PGS deposited on the PGS Catalog. These findings highlight current gaps and key areas for future pharmacogenomic PGS research.

Genetic Analysis for Coronary Artery Disease Toward Diverse Populations

Coronary artery disease is one of the leading causes of death in the world, and as such, it is one of the diseases for which genetic analyses have been actively conducted. In the early days, analyses of families with the aggregation of early-onset myocardial infarction, such as those with familial hypercholesterolemia, was the main focus, but since the practical application of genome-wide association study, the analysis of coronary artery disease as a common disease has progressed, and many disease-susceptibility loci have been identified. In addition, with the advancement of technologies, it has become possible to identify relatively rare genetic variants in a population-based analysis. These advances have not only revealed the detailed disease mechanisms but have also enabled the quantification of individual genetic risk and the development of new therapeutic agents. In this paper, some of those items, which are important to know in the current genetic analyses for coronary artery disease, are discussed.

Unsupervised Learning for Automated Detection of Coronary Artery Disease Subgroups

Background The promise of precision population health includes the ability to use robust patient data to tailor prevention and care to specific groups. Advanced analytics may allow for automated detection of clinically informative subgroups that account for clinical, genetic, and environmental variability. This study sought to evaluate whether unsupervised machine learning approaches could interpret heterogeneous and missing clinical data to discover clinically important coronary artery disease subgroups. Methods and Results The Genetic Determinants of Peripheral Arterial Disease study is a prospective cohort that includes individuals with newly diagnosed and/or symptomatic coronary artery disease. We applied generalized low rank modeling and K-means cluster analysis using 155 phenotypic and genetic variables from 1329 participants. Cox proportional hazard models were used to examine associations between clusters and major adverse cardiovascular and cerebrovascular events and all-cause mortality. We then compared performance of risk stratification based on clusters and the American College of Cardiology/American Heart Association pooled cohort equations. Unsupervised analysis identified 4 phenotypically and prognostically distinct clusters. All-cause mortality was highest in cluster 1 (oldest/most comorbid; 26%), whereas major adverse cardiovascular and cerebrovascular event rates were highest in cluster 2 (youngest/multiethnic; 41%). Cluster 4 (middle-aged/healthiest behaviors) experienced more incident major adverse cardiovascular and cerebrovascular events (30%) than cluster 3 (middle-aged/lowest medication adherence; 23%), despite apparently similar risk factor and lifestyle profiles. In comparison with the pooled cohort equations, cluster membership was more informative for risk assessment of myocardial infarction, stroke, and mortality. Conclusions Unsupervised clustering identified 4 unique coronary artery disease subgroups with distinct clinical trajectories. Flexible unsupervised machine learning algorithms offer the ability to meaningfully process heterogeneous patient data and provide sharper insights into disease characterization and risk assessment. Registration URL: https://www.clinicaltrials.gov; Unique identifier: NCT00380185.

Hypertension genetics past, present and future applications

Essential hypertension is a complex trait where the underlying aetiology is not completely understood. Left untreated it increases the risk of severe health complications including cardiovascular and renal disease. It is almost 15 years since the first genome-wide association study for hypertension, and after a slow start there are now over 1000 blood pressure (BP) loci explaining ∼6% of the single nucleotide polymorphism-based heritability. Success in discovery of hypertension genes has provided new pathological insights and drug discovery opportunities and translated to the development of BP genetic risk scores (GRSs), facilitating population disease risk stratification. Comparing highest and lowest risk groups shows differences of 12.9 mm Hg in systolic-BP with significant differences in risk of hypertension, stroke, cardiovascular disease and myocardial infarction. GRSs are also being trialled in antihypertensive drug responses. Drug targets identified include NPR1, for which an agonist drug is currently in clinical trials. Identification of variants at the PHACTR1 locus provided insights into regulation of EDN1 in the endothelin pathway, which is aiding the development of endothelin receptor EDNRA antagonists. Drug re-purposing opportunities, including SLC5A1 and canagliflozin (a type-2 diabetes drug), are also being identified. In this review, we present key studies from the past, highlight current avenues of research and look to the future focusing on gene discovery, epigenetics, gene-environment interactions, GRSs and drug discovery. We evaluate limitations affecting BP genetics, including ancestry bias and discuss streamlining of drug target discovery and applications for treating and preventing hypertension, which will contribute to tailored precision medicine for patients.