Utility Of Polygenic Risk Scores Research Articles

Stacked neural network for predicting polygenic risk score

In recent years, the utility of polygenic risk scores (PRS) in forecasting disease susceptibility from genome-wide association studies (GWAS) results has been widely recognised. Yet, these models face limitations due to overfitting and the potential overestimation of effect sizes in correlated variants. To surmount these obstacles, we devised the Stacked Neural Network Polygenic Risk Score (SNPRS). This novel approach synthesises outputs from multiple neural network models, each calibrated using genetic variants chosen based on diverse p-value thresholds. By doing so, SNPRS captures a broader array of genetic variants, enabling a more nuanced interpretation of the combined effects of these variants. We assessed the efficacy of SNPRS using the UK Biobank data, focusing on the genetic risks associated with breast and prostate cancers, as well as quantitative traits like height and BMI. We also extended our analysis to the Korea Genome and Epidemiology Study (KoGES) dataset. Impressively, our results indicate that SNPRS surpasses traditional PRS models and an isolated deep neural network in terms of accuracy, highlighting its promise in refining the efficacy and relevance of PRS in genetic studies.

Use of polygenic and clinical risk scores in wide spectrum congenital heart malformations: a diagnostic and therapeutic perspective

Worldwide, congenital heart defects (CHDs) are a leading cause of mortality and morbidity. Globally, the annual prevalence rate of CHDs is about 1.5 million. It is one of the most common life-threatening congenital malformations, with a visible difference between high-income countries (HICs) and developing countries. This difference may be attributed to the diagnostic facilities and interventions.1 Moreover, the use of genetic and clinical risk scores is less studied in this field compared to other diagnostic and therapeutic approaches. Thus, we comprehensively review the available literature on adult and pediatric syndromic or non-syndromic CHDs and propose limitations and future directions in this field. Risk factors for this fatal disease include genetic and environmental factors.2,3 Risk stratification based on prenatal diagnosis with genetic counseling has shown better clinical outcomes. The modified World Health Organization (mWHO) guidelines are among the first proposed for risk stratification based on clinical scores.4 The combination of polygenic risk scores (PRS) and clinical risk evaluation has been adopted in various populations as better diagnostic and therapeutic approaches for various diseases, including coronary artery disease,5 diabetes,6 obesity,7 and cancers.8,9 However, unlike these diseases, polygenic risk scores are rarely used for the genetic diagnosis of CHD patients. The clinical utility of polygenic risk scores for CHDs is still in the early stages and requires validation studies in different cohorts. Incorporating PRS into the clinical setting may improve CHD diagnosis and therapeutic strategies.10 Recently, an initial attempt was made to determine the clinical utility of polygenic risk scores in a large dataset of the European cohort. Data from this study suggested a high potential for PRS in distinguishing between clinical phenotypes (mild, moderate, and severe) of congenital heart malformations.11 Furthermore, this hypothesis was tested in patients with transposition of the great arteries (TGA) to assess the utility of risk stratification after arterial switch operation. The cumulative risk score was computed for single nucleotide polymorphisms (SNPs) that reached the threshold statistical significance of p<1×10−5 in the initial analysis. Combined clinical and polygenic risk scores showed improved risk stratification in mild, moderate, and severe TGA phenotypes.12 Similarly, in another European cohort, the risk allele frequency was higher in the diseased group compared to the control group. However, statistical analysis suggested a non-significant association with p>0.05. Interestingly, combined risk scores constructed for selected SNPs showed a significant association with the disease with a p-value of 0.002. This evidence further supports the hypothesis that the cumulative effect of polymorphisms has better diagnostic and therapeutic efficacy than individual SNPs.13 There are certain limitations to its clinical use. Firstly, social stigma and lack of awareness regarding this disease are major hurdles. Secondly, there is a need to recruit a large number of samples from different populations to validate the clinical utility of PRS. Additionally, a lack of resources in developing countries also contributes to fatal outcomes. We recommend conducting large cohort studies in different ethnic groups to predict better risk associations, develop better therapeutic strategies, and formulate management guidelines.

Evaluating genomic polygenic risk scores for childhood acute lymphoblastic leukemia in Latinos

The utility of polygenic risk score (PRS) models has not been comprehensively evaluated for childhood acute lymphoblastic leukemia (ALL), the most common type of cancer in children. Previous PRS models for ALL were based on significant loci observed in genome-wide association studies (GWASs), even though genomic PRS models have been shown to improve prediction performance for a number of complex diseases. In the United States, Latino (LAT) children have the highest risk of ALL, but the transferability of PRS models to LAT children has not been studied. In this study, we constructed and evaluated genomic PRS models based on either non-Latino White (NLW) GWAS or a multi-ancestry GWAS. We found that the best PRS models performed similarly between held-out NLW and LAT samples (PseudoR2= 0.086 ± 0.023 in NLW vs. 0.060 ± 0.020 in LAT), and can be improved for LAT if we performed GWAS in LAT-only (PseudoR2= 0.116 ± 0.026) or multi-ancestry samples (PseudoR2= 0.131 ± 0.025). However, the best genomic models currently do not have better prediction accuracy than a conventional model using all known ALL-associated loci in the literature (PseudoR2= 0.166 ± 0.025), which includes loci from GWAS populations that we could not access to train genomic PRS models. Our results suggest that larger and more inclusive GWASs may be needed for genomic PRS to be useful for ALL. Moreover, the comparable performance between populations may suggest a more oligogenic architecture for ALL, where some large effect loci may be shared between populations. Future PRS models that move away from the infinite causal loci assumption may further improve PRS for ALL.

The Ethics of Risk Prediction for Psychosis and Suicide Attempt in Youth Mental Health

To identify potential clinical utility of polygenic risk scores (PRS) and exposomic risk scores (ERS) for psychosis and suicide attempt in youth and assess the ethical implications of these tools. We conducted a narrative literature review of emerging findings on PRS and ERS for suicide and psychosis as well as a literature review on the ethics of PRS. We discuss the ethical implications of the emerging findings for the clinical potential of PRS and ERS. Emerging evidence suggests that PRS and ERS may offer clinical utility in the relatively near future but that this utility will be limited to specific, narrow clinical questions, in contrast to the suggestion that population-level screening will have sweeping impact. Combining PRS and ERS might optimize prediction. This clinical utility would change the risk-benefit balance of PRS, and further empirical assessment of proposed risks would be necessary. Some concerns for PRS, such as those about counseling, privacy, and inequities, apply to ERS. ERS raise distinct ethical challenges as well, including some that involve informed consent and direct-to-consumer advertising. Both raise questions about the ethics of machine-learning/artificial intelligence approaches. Predictive analytics using PRS and ERS may soon play a role in youth mental health settings. Our findings help educate clinicians about potential capabilities, limitations, and ethical implications of these tools. We suggest that a broader discussion with the public is needed to avoid overenthusiasm and determine regulations and guidelines for use of predictive scores.

1478-P: Polygenic Risk Score Predicts Incident Cardiovascular Disease in People with Diabetes at Borderline or Intermediate 10-Year ASCVD Risk

People with type 2 diabetes (T2D) and 10-year atherosclerotic cardiovascular disease (ASCVD) of 20% or higher are recommended for intense lipid management. However, the role of genetic predisposition to ASCVD on determining the intensity of statin therapy in patients with T2D at borderline (5-7.5%) or intermediate (7.5-20%) risk for incident ASCVD is unclear. We aimed to investigate the utility of polygenic risk score (PRS) in predicting incident ASCVD in people with T2D at borderline and intermediate risk from UK Biobank. We calculated 10-year ASCVD risk using pooled cohort risk equations and PRS for coronary artery disease by Bayesian regression (PRS-CS) in participants of UK Biobank. We performed time-to-event analysis for incident ASCVD and assessed improvement of C-statistic when PRS was added to 10-year ASCVD risk. In addition, risk of ASCVD was estimated for those who were in the top 20 percentile of PRS compared to the remainders. During a median follow-up of 9 years, the incidence of ASCVD in people with T2D was 5.9% and 8.6% in borderline (N=2511) and intermediate (N=8292) group, respectively. The normalized mean PRS for those who developed ASCVD was higher in each group: 0.20±0.96 vs −0.02±1.01 in borderline and 0.20±1.02 vs −0.02±0.99 in intermediate group (all P<0.01). Adding PRS to 10-year ASCVD risk improved the C statistic from 0.51 (95% CI 0.46-0.55) to 0.57 (0.52-0.62) in borderline and from 0.55 (0.53-0.57) to 0.58 (0.56-0.60) in intermediate group. Standardized PRS was associated with incident ASCVD in each group: HR 1.22 (CI 1.05-1.45, P<0.05) and 1.24 (1.15-1.34, P<0.001). Moreover, those who were in the top 20 percentile had increased risk of ASCVD: HR 1.63 (1.14-2.33, P<0.01) and 1.43 (1.21-1.70, P<0.001), respectively. In conclusion, genetic information in people with T2D at borderline and intermediate ASCVD risk could be used to identify those who are at higher risk for incident ASCVD and require high intensity statin treatment. Disclosure J.Choi: None. H.Lee: None. J.S.Lee: None. T.Rhee: None. K.Park: None. S.Kwak: None. Funding National Human Genome Research Institute (FAIN U01HG011723)

How do experts in psychiatric genetics view the clinical utility of polygenic risk scores for schizophrenia?

Polygenic risk scores (PRS) are promising for identifying common variant-related inheritance for psychiatric conditions but their integration into clinical practice depends on their clinical utility and psychiatrists' understanding of PRS. Our online survey explored these issues with 276 professionals working in psychiatric genetics (RR: 19%). Overall, participants demonstrated knowledge of how to interpret PRS results. Their performance on knowledge-based questions was positively correlated with participants' self-reported familiarity with PRS (r = 0.21, p = 0.0006) although differences were not statistically significant (Wald Chi-square = 3.29, df = 1, p = 0.07). However, only 48.9% of all participants answered all knowledge questions correctly. Many participants (56.5%), especially researchers (42%), indicated having at least occasional conversations about the role of genetics in psychiatric conditions with patients and/or family members. Most participants (62.7%) indicated that PRS are not yet sufficiently robust for assessment of susceptibility to schizophrenia; most significant obstacles were low predictive power and lack of population diversity in available PRS (selected, respectively, by 53.6% and 29.3% of participants). Nevertheless, 89.8% of participants were optimistic about the use of PRS in the next 10 years, suggesting a belief that current shortcomings could be addressed. Our findings inform about the perceptions of psychiatric professionals regarding PRS and the application of PRS in psychiatry.

Clinical utility of polygenic risk scores: a critical 2023 appraisal

Since their first appearance in the context of schizophrenia and bipolar disorder in 2009, polygenic risk scores (PRSs) have been described for a large number of common complex diseases. However, the clinical utility of PRSs in disease risk assessment or therapeutic decision making is likely limited because PRSs usually only account for the heritable component of a trait and ignore the etiological role of environment and lifestyle. We surveyed the current state of PRSs for various diseases, including breast cancer, diabetes, prostate cancer, coronary artery disease, and Parkinson disease, with an extra focus upon the potential improvement of clinical scores by their combination with PRSs. We observed that the diagnostic and prognostic performance of PRSs alone is consistently low, as expected. Moreover, combining a PRS with a clinical score at best led to moderate improvement of the power of either risk marker. Despite the large number of PRSs reported in the scientific literature, prospective studies of their clinical utility, particularly of the PRS-associated improvement of standard screening or therapeutic procedures, are still rare. In conclusion, the benefit to individual patients or the health care system in general of PRS-based extensions of existing diagnostic or treatment regimens is still difficult to judge.

Leveraging related health phenotypes for polygenic prediction of impulsive choice, impulsive action, and impulsive personality traits in 1534 European ancestry community adults.

Impulsivity refers to a number of conceptually related phenotypes reflecting self-regulatory capacity that are considered promising endophenotypes for mental and physical health. Measures of impulsivity can be broadly grouped into three domains, namely, impulsive choice, impulsive action, and impulsive personality traits. In a community-based sample of ancestral Europeans (n = 1534), we conducted genome-wide association studies (GWASs) of impulsive choice (delay discounting), impulsive action (behavioral inhibition), and impulsive personality traits (UPPS-P), and evaluated 11 polygenic risk scores (PRSs) of phenotypes previously linked to self-regulation. Although there were no individual genome-wide significant hits, the neuroticism PRS was positively associated with negative urgency (adjusted R2 = 1.61%, p = 3.6 × 10-7 ) and the educational attainment PRS was inversely associated with delay discounting (adjusted R2 = 1.68%, p = 2.2 × 10-7 ). There was also evidence implicating PRSs of attention-deficit/hyperactivity disorder, externalizing, risk-taking, smoking cessation, smoking initiation, and body mass index with one or more impulsivity phenotypes (adjusted R2 s: 0.35%-1.07%; FDR adjusted ps = 0.05-0.0006). These significant associations between PRSs and impulsivity phenotypes are consistent with established genetic correlations. The combined PRS explained 0.91%-2.46% of the phenotypic variance for individual impulsivity measures, corresponding to 8.7%-32.5% of their reported single-nucleotide polymorphism (SNP)-based heritability, suggesting a non-negligible portion of the SNP-based heritability can be recovered by PRSs. These results support the predictive validity and utility of PRSs, even derived from related phenotypes, to inform the genetics of impulsivity phenotypes.

Polygenic risk scores for the prediction of common cancers in East Asians: A population-based prospective cohort study.

To evaluate the utility of polygenic risk scores (PRSs) in identifying high-risk individuals, different publicly available PRSs for breast (n=85), prostate (n=37), colorectal (n=22), and lung cancers (n=11) were examined in a prospective study of 21,694 Chinese adults. We constructed PRS using weights curated in the online PGS Catalog. PRS performance was evaluated by distribution, discrimination, predictive ability, and calibration. Hazard ratios (HR) and corresponding confidence intervals (CI) of the common cancers after 20 years of follow-up were estimated using Cox proportional hazard models for different levels of PRS. A total of 495 breast, 308 prostate, 332 female-colorectal, 409 male-colorectal, 181 female-lung, and 381 male-lung incident cancers were identified. The area under receiver operating characteristic curve for the best-performing site-specific PRS were 0.61 (PGS000873, breast), 0.70 (PGS00662, prostate), 0.65 (PGS000055, female-colorectal), 0.60 (PGS000734, male-colorectal), 0.56 (PGS000721, female-lung), and 0.58 (PGS000070, male-lung), respectively. Compared to the middle quintile, individuals in the highest cancer-specific PRS quintile were 64% more likely to develop cancers of the breast, prostate, and colorectal. For lung cancer, the lowest cancer-specific PRS quintile was associated with 28-34% decreased risk compared to the middle quintile. In contrast, the HR observed for quintiles 4 (female-lung: 0.95 [0.61-1.47]; male-lung: 1.14 [0.82-1.57]) and 5 (female-lung: 0.95 [0.61-1.47]) were not significantly different from that for the middle quintile. Site-specific PRSs can stratify the risk of developing breast, prostate, and colorectal cancers in this East Asian population. Appropriate correction factors may be required to improve calibration. This work is supported by the National Research Foundation Singapore (NRF-NRFF2017-02), PRECISION Health Research, Singapore (PRECISE) and the Agency for Science, Technology and Research (A*STAR). WP Koh was supported by National Medical Research Council, Singapore (NMRC/CSA/0055/2013). CC Khor was supported by National Research Foundation Singapore (NRF-NRFI2018-01). Rajkumar Dorajoo received a grant from the Agency for Science, Technology and Research Career Development Award (A*STAR CDA - 202D8090), and from Ministry of Health Healthy Longevity Catalyst Award (HLCA20Jan-0022).The Singapore Chinese Health Study was supported by grants from the National Medical Research Council, Singapore (NMRC/CIRG/1456/2016) and the U.S. National Institutes of Health (NIH) (R01 CA144034 and UM1 CA182876).

Polygenic risk scores cannot make their mark on psychiatry without considering epigenetics.

We generally agree with Burt's thesis. However, we note that the author did not discuss epigenetics, the study of how the environment can alter gene structure and function. Given epigenetic mechanisms, the utility of polygenic risk scores (PRS) is limited in studies of development and mental illness. Finally, in this commentary we expand upon the risks of reliance upon PRSs.

Predictive Utility of a Coronary Artery Disease Polygenic Risk Score in Primary Prevention

The clinical utility of polygenic risk scores (PRS) for coronary artery disease (CAD) has not yet been established. To investigate the ability of a CAD PRS to potentially guide statin initiation in primary prevention after accounting for age and clinical risk. This was a longitudinal cohort study with enrollment starting on January 1, 2006, and ending on December 31, 2010, with data updated to mid-2021, using data from the UK Biobank, a long-term population study of UK citizens. A replication analysis was performed in Biobank Japan. The analysis included all patients without a history of CAD and who were not taking lipid-lowering therapy. Data were analyzed from January 1 to June 30, 2022. Polygenic risk for CAD was defined as low (bottom 20%), intermediate, and high (top 20%) using a CAD PRS including 241 genome-wide significant single-nucleotide variations (SNVs). The pooled cohort equations were used to estimate 10-year atherosclerotic cardiovascular disease (ASCVD) risk and classify individuals as low (<5%), borderline (5-<7.5%), intermediate (7.5-<20%), or high risk (≥20%). Myocardial infarction (MI) and ASCVD events (defined as incident clinical CAD [including MI], stroke, or CV death). A total of 330 201 patients (median [IQR] age, 57 [40-74] years; 189 107 female individuals [57%]) were included from the UK Biobank. Over the 10-year follow-up, 4454 individuals had an MI. The CAD PRS was significantly associated with the risk of MI in all age groups but had significantly stronger risk prediction at younger ages (age <50 years: hazard ratio [HR] per 1 SD of PRS, 1.72; 95% CI, 1.56-1.89; age 50-60 years: HR, 1.46; 95% CI, 1.38-1.53; age >60 years: HR, 1.42; 95% CI, 1.37-1.48; P for interaction <.001). In patients younger than 50 years, those with high PRS had a 3- to 4-fold increased associated risk of MI compared with those in the low PRS category. A significant interaction between CAD PRS and age was replicated in Biobank Japan. When CAD PRS testing was added to the clinical ASCVD risk score in individuals younger than 50 years, 591 of 4373 patients (20%) with borderline risk were risk stratified into intermediate risk, warranting initiation of statin therapy and 3198 of 7477 patients (20%) with both borderline or intermediate risk were stratified as low risk, thus not warranting therapy. Results of this cohort study suggest that the predictive ability of a CAD PRS was greater in younger individuals and can be used to better identify patients with borderline and intermediate clinical risk who should initiate statin therapy.

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

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. 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. 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. 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.

Utility of Polygenic Risk Scoring to Predict Cognitive Impairment as Measured by Preclinical Alzheimer Cognitive Composite Score.

The utility of Polygenic Risk Scores (PRS) is gaining increasing attention for generating an individual genetic risk profile to predict subsequent likelihood of future onset of Alzheimer's disease (AD), especially those carry two copies of the APOE E3 allele, currently considered at neutral risk in all populations studied. To access the performance of PRS in predicting individuals whilst pre-symptomatic or with mild cognitive impairment who are at greatest risk of progression of cognitive impairment due to Alzheimer's Disease from the Alzheimer's Disease Neuroimaging Initiative (ADNI) as measured by the Preclinical Alzheimer Cognitive Composite (PACC) score profile. Design: A longitudinal analysis of data from the ADNI study conducted across over 50 sites in the US and Canada. Multi-centre genetics study. 594 subjects either APOE E3 homozygotes or APOE E3/E4 heterozygotes who upon entry to the study were diagnosed as cognitively normal or with mild cognitive impairment. Use of genotyping and/or whole genome sequencing data to calculate polygenic risk scores and assess its ability to predict subsequent cognitive decline as measured by PACC over 5 years. Results: Assessing both cognitively normal and mild cognitive impaired subjects using a PRS threshold of greater than 0.6, the high genetic risk participant group declined more than the low risk group over 5 years as measured by PACC score (PACC score reduced by time). Our findings have shown that polygenic risk score provides a promising tool to identify those with higher risk to decline over 5 years regardless of their APOE alleles according to modified PACC profile, especially its ability to identify APOE3/E3 cognitively normal individuals who are at most risk for early cognitive decline. This genotype accounts for approximately 60% of the general population and 35% of the AD population but currently would not be considered at higher risk without access to expensive or invasive biomarker testing.

Evaluating the Clinical Utility of Polygenic Risk Score for Heart Failure

Evaluating the Clinical Utility of Polygenic Risk Score for Heart Failure

Polygenic risk scores predict cognitive impairment as measured by the Preclinical Alzheimer Cognitive Composite (PACC) score in the ADNI cohort

AbstractBackgroundThe development of diagnostic tools to identify disease risk is critical to enable selection of suitable individuals for inclusion in clinical trials and cohort studies. The utility of Polygenic Risk Scores (PRS) is gaining increasing attention for generating an individual genetic risk profile and subsequent estimation of future disease risk in Alzheimer’s Disease. We have previously reported on the performance of our PRS to differentiate Alzheimer Disease cases from healthy controls in the ADNI cohort and also cognitive decline using ADAS‐Cog13 and CDR‐SB scales. In this work we have analysed whether the PRS is able to predict more subtle changes in cognition by using PACC scores of ADNI cohort participants. The aim being to demonstrate the utility of PRS approaches in longitudinal studies and future clinical practice.MethodThis study explored the performance of the Cytox genoSCORE™ PRS algorithm as measured using a receiver operating characteristic curve (ROC) curve to predict a PACC score of &lt;‐1, as measured upon entry into the study. 724 subjects who entered the study as either cognitively normal, or with a diagnosis of mild cognitive impairment are included in the analysis based on availability of PACC scores and of genetic data in the ADNI database. Further analyses to predict longitudinal changes in PACC have also been performed.ResultIn a population of 724 individuals genoSCORE™ has an accuracy as measured by area under the curve (AUC) of 65.6% in predicting those individuals with cognitive impairment as measured by the PACC scale (threshold &lt;‐1). A similar analysis performed using age as the predictor in the same group showed no discernible correlation with lower PACC scores.ConclusionIdentifying individuals of higher risk for cognitive decline due to Alzheimer’s Disease irrespective of their baseline cognitive performance will allow clinical trialists to enrich their studies with more appropriate patients. In addition, use of such risk evaluation techniques in clinical practice will enable clinicians to make more informed decisions on how to manage their patients. Cytox is able to provide a robust end‐to‐end process to provide this comprehensive genetic risk assessment.

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.

Abstract 12224: Predictive Power and Value of a CAD Polygenic Risk Score in Primary Prevention Based on Age and Clinical Risk

Background: The clinical utility of polygenic risk scores (PRS) for CAD has not yet been established. We investigated the ability of a CAD PRS to potentially guide statin initiation after accounting for age and clinical risk. Methods: We performed a prospective cohort study in the UK Biobank that included all individuals without a history of CAD and who were not on lipid-lowering therapy. The CAD PRS was comprised of 241 genome-wide significant SNPs. Genetic risk categories were defined as low (bottom 20%), intermediate, and high (top 20%). HRs were calculated as a function of age. Next, 10-year ASCVD risk score was used to classify individuals as low, borderline, intermediate, or high risk. Each ASCVD risk group was further stratified by genetic risk to determine whether genetics could reclassify individuals to help guide decisions regarding statin initiation with more precision. ASCVD events were defined as incident clinical CAD (including MI), stroke, or CV death. Results: The 333,245 patients included in this study were ages 40-74 years (avg 57) and 57% were female. Over the 10-yr follow-up, there were 4,552 MIs. The CAD PRS significantly predicted MI in all age groups but had significantly stronger risk prediction at younger ages (p-int &lt;0.001) ( Figure, A ). This gradient of risk was especially pronounced under 50 years of age, where those with high PRS approached a 6-fold increased risk of MI compared with those in the low PRS category. When CAD PRS testing was added to the 71,534 patients &lt;50 years old, 20% of borderline risk patients were reclassified into intermediate risk, warranting initiation of statin therapy to reduce LDL-C, and 20% of borderline and intermediate risk patients were reclassified as low risk, thus not warranting therapy ( Figure, B ). Conclusion: The predictive ability of a CAD PRS is especially strong in individuals under the age of 50 and can be used to identify more precisely who should be initiated on statin therapy.

Genetic liability for substance use associated with medical comorbidities in electronic health records of African- and European-ancestry individuals.

Polygenic risk scores (PRS) represent an individual's summed genetic risk for a trait and can serve as biomarkers for disease. Less is known about the utility of PRS as a means to quantify genetic risk for substance use disorders (SUDs) than for many other traits. Nonetheless, the growth of large, electronic health record-based biobanks makes it possible to evaluate the association of SUD PRS with other traits. We calculated PRS for smoking initiation, alcohol use disorder (AUD), and opioid use disorder (OUD) using summary statistics from the Million Veteran Program sample. We then tested the association of each PRS with its primary phenotype in the Penn Medicine BioBank (PMBB) using all available genotyped participants of African or European ancestry (AFR and EUR, respectively) (N= 18,612). Finally, we conducted phenome-wide association analyses (PheWAS) separately by ancestry and sex to test for associations across disease categories. Tobacco use disorder was the most common SUD in the PMBB, followed by AUD and OUD, consistent with the population prevalence of these disorders. All PRS were associated with their primary phenotype in both ancestry groups. PheWAS results yielded cross-trait associations across multiple domains, including psychiatric disorders and medical conditions. SUD PRS were associated with their primary phenotypes; however, they are not yet predictive enough to be useful diagnostically. The cross-trait associations of the SUD PRS are indicative of a broader genetic liability. Future work should extend findings to additional population groups and for other substances of abuse.

Polygenic risk in familial breast cancer: Changing the dynamics of communicating genetic risk.

Hereditary breast cancer is associated with known genetic changes: either variants that affect function in a few rare genes or an ever-increasing number of common genomic risk variants, which combine to produce a cumulative effect, known as a polygenic risk (PR) score. While the clinical validity and utility of PR scores are still being determined, the communication of PR is a new challenge for genetic health professionals. This study investigated how PR scores are discussed in the familial cancer clinic compared with a previous study assessing the communication of monogenic risk (MR) for breast cancer. Sixty-five PR consultations between genetic health professionals and women at familial risk of breast cancer were audiotaped, transcribed, and coded using a methodology adapted from the MR study. Analysis of consultations shows that while there were similarities in communicating MR and PR, the complexity and novelty of the polygenic information influenced the style of counseling used by genetic health professionals toward a teaching model of genetic counseling, rather than a patient-centered approach. In particular, compared to MR consultations, in PR consultations significantly fewer counselees (a) were asked about their reasons for attending genetic counseling; or (b) had their information preferences, decision-making style, medical knowledge, understanding, or concerns checked. In conclusion, it is anticipated that PR scores will become part of standard clinical practice. Thus, it will be important for all genetic health professionals to be appropriately educated so that they can tailor their communication to meet patient needs.

Clinical Utility of Polygenic Risk Score in Sleep Disorder

Clinical Utility of Polygenic Risk Score in Sleep Disorder