Advancing genomics to improve health equity.

Health equity is the state in which everyone has fair and just opportunities to attain their highest level of health. The field of human genomics has fallen short in increasing health equity, largely because the diversity of the human population has been inadequately reflected among participants of genomics research. This lack of diversity leads to disparities that can have scientific and clinical consequences. Achieving health equity related to genomics will require greater effort in addressing inequities within the field. As part of the commitment of the National Human Genome Research Institute (NHGRI) to advancing health equity, it convened experts in genomics and health equity research to make recommendations and performed a review of current literature to identify the landscape of gaps and opportunities at the interface between human genomics and health equity research. This Perspective describes these findings and examines health equity within the context of human genomics and genomic medicine.

Risk factors affecting polygenic score performance across diverse cohorts.

Apart from ancestry, personal or environmental covariates may contribute to differences in polygenic score (PGS) performance. We analyzed effects of covariate stratification and interaction on body mass index (BMI) PGS (PGSBMI) across four cohorts of European (N=491,111) and African (N=21,612) ancestry. Stratifying on binary covariates and quintiles for continuous covariates, 18/62 covariates had significant and replicable R2 differences among strata. Covariates with the largest differences included age, sex, blood lipids, physical activity, and alcohol consumption, with R2 being nearly double between best and worst performing quintiles for certain covariates. 28 covariates had significant PGSBMI-covariate interaction effects, modifying PGSBMI effects by nearly 20% per standard deviation change. We observed overlap between covariates that had significant R2 differences among strata and interaction effects - across all covariates, their main effects on BMI were correlated with their maximum R2 differences and interaction effects (0.56 and 0.58, respectively), suggesting high-PGSBMI individuals have highest R2 and increase in PGS effect. Using quantile regression, we show the effect of PGSBMI increases as BMI itself increases, and that these differences in effects are directly related to differences in R2 when stratifying by different covariates. Given significant and replicable evidence for context-specific PGSBMI performance and effects, we investigated ways to increase model performance taking into account non-linear effects. Machine learning models (neural networks) increased relative model R2 (mean 23%) across datasets. Finally, creating PGSBMI directly from GxAge GWAS effects increased relative R2 by 7.8%. These results demonstrate that certain covariates, especially those most associated with BMI, significantly affect both PGSBMI performance and effects across diverse cohorts and ancestries, and we provide avenues to improve model performance that consider these effects.

Key Contextual Factors Involved with Participation in Medical and Genomic Screening and Research for African American and Caucasian Americans: A Qualitative Inquiry American Journal of Community Genetics.

Tremendous progress has been made promoting diversity in recruitment for genomic research, yet challenges remain for several racial demographics. Research has cited intertwined fears of racial discrimination and medical mistrust as contributing factors. This study aimed to identify key factors to establishing trust in medical and genomic screening and research among African Americans and White Americans. Participants completed online focus groups and resulting transcripts were analyzed using a qualitative descriptive approach, with content analysis methods based on recommendations by Schreier. Fifteen African Americans and 23 Caucasian Americans participated in the study, 63% of which were female. The mean age of participants was 38.53 (SD = 16.6). The Overarching Theme of Trust is Context Dependent was identified, along with the following five themes describing elements influencing trustworthiness for our participants: 1) Professional Experience, Education, and Training Bolster Trust; 2) Trust Depends on Relationships; 3) Cross-checking Provided Information is Influential in Establishing Trust; 4) Trust is Undermined by Lack of Objectivity and Bias; and 5) Racism is an Embedded Concern and a Medical Trust Limiting Component for African Americans. To effectively address mistrust and promote recruitment of diverse participants, genomic research initiatives must be communicated in a manner that resonates with the specific diverse communities targeted. Our results suggest key factors influencing trust that should be attended to if we are to promote equity appropriately and respectfully by engaging diverse populations in genomic research.

Polygenic Risk for Type 2 Diabetes in African Americans.

African Americans (AAs) have been underrepresented in polygenic risk score (PRS) studies. Here, we integrated genome-wide data from multiple observational studies on type 2 diabetes (T2D), encompassing a total of 101,987 AAs, to train and optimize an AA-focused T2D PRS (PRSAA), using a Bayesian polygenic modeling method. We further tested the score in three independent studies with a total of 7,275 AAs and compared the PRSAA with other published scores. Results show that a 1-SD increase in the PRSAA was associated with 40-60% increase in the odds of T2D (odds ratio [OR] 1.60, 95% CI 1.37-1.88; OR 1.40, 95% CI 1.16-1.70; and OR 1.45, 95% CI 1.30-1.62) across three testing cohorts. These models captured 1.0-2.6% of the variance (R2) in T2D on the liability scale. The positive predictive values for three calculated score thresholds (the top 2%, 5%, and 10%) ranged from 14 to 35%. The PRSAA, in general, performed similarly to existing T2D PRS. The need remains for larger data sets to continue to evaluate the utility of within-ancestry scores in the AA population.

Selection, optimization and validation of ten chronic disease polygenic risk scores for clinical implementation in diverse US populations.

Polygenic risk scores (PRSs) have improved in predictive performance, but several challenges remain to be addressed before PRSs can be implemented in the clinic, including reduced predictive performance of PRSs in diverse populations, and the interpretation and communication of genetic results to both providers and patients. To address these challenges, the National Human Genome Research Institute-funded Electronic Medical Records and Genomics (eMERGE) Network has developed a framework and pipeline for return of a PRS-based genome-informed risk assessment to 25,000 diverse adults and children as part of a clinical study. From an initial list of 23 conditions, ten were selected for implementation based on PRS performance, medical actionability and potential clinical utility, including cardiometabolic diseases and cancer. Standardized metrics were considered in the selection process, with additional consideration given to strength of evidence in African and Hispanic populations. We then developed a pipeline for clinical PRS implementation (score transfer to a clinical laboratory, validation and verification of score performance), and used genetic ancestry to calibrate PRS mean and variance, utilizing genetically diverse data from 13,475 participants of the All of Us Research Program cohort to train and test model parameters. Finally, we created a framework for regulatory compliance and developed a PRS clinical report for return to providers and for inclusion in an additional genome-informed risk assessment. The initial experience from eMERGE can inform the approach needed to implement PRS-based testing in diverse clinical settings.

Risk scores for major bleeding from direct oral anticoagulants: comparing predictive performance in patients with atrial fibrillation.

Background: Despite direct oral anticoagulants (DOACs) being safer than warfarin for stroke prevention in atrial fibrillation (AF), major bleeding concerns persist. Most bleeding risk scores predate DOAC approval. Objectives: This study aimed to compare the Age, history of Bleeding, and non-bleeding related Hospitalisation [ABH] score's performance-derived for DOAC-treated patients-with those of 5 other scores (Anticoagulation and Risk Factors in Atrial Fibrillation [ATRIA], Hypertension, Abnormal renal/liver function, Stroke, Bleeding history or predisposition, Labile international normalized ratio, Elderly [>65 years], Drugs/alcohol concomitantly [HAS-BLED], Hepatic, Hepatic or Renal Disease, Ethanol Abuse, Malignancy, Older Age, Reduced Platelet Count or Function, Re-Bleeding, Hypertension, Anemia, Genetic Factors, Excessive Fall Risk and Stroke [HEMORR2HAGES], Outcomes Registry for Better Informed Treatment of Atrial Fibrillation [ORBIT-AF], and Congestive heart failure, Hypertension, Age ≥75 [doubled], Diabetes, Stroke [doubled]-Vascular disease, Age 65-74, Sex category [CHA2DS2-VASc]) in predicting DOAC-related major bleeding in patients with AF. Methods: In this retrospective study of 2364 patients with nonvalvular AF on rivaroxaban or apixaban (median age, 68.3 years; 32.1% women), International Society on Thrombosis and Haemostasis-defined major bleeding (incidence, 4.1%; n = 97) was analyzed. C-statistics from time-dependent receiver operating characteristic (ROC) curves for continuous risk scores were the primary comparison metric, but other metrics, such as decision curves, were also compared. Results: At 100 days, C-statistics were highest for ORBIT-AF and ATRIA (0.62 and 0.61, respectively, with other scores having an area under the ROC curve of <0.60); some significant differences favored ORBIT-AF. At 1100 days, C-statistics remained highest for ORBIT-AF and ATRIA (0.62 and 0.61, respectively, with other scores having an area under the ROC curve of <0.60 again), and ORBIT-AF had significantly higher C-statistics than those for all other risk scores (P < .05), except for ATRIA. At 2100 days, all C-statistics were <0.60 with no significant differences. Decision curves showed the greatest net benefit for ORBIT-AF and ATRIA at 100 days and for ATRIA at 1100 days, with no discernible net benefit for any of the scores at 2100 days. Conclusion: ORBIT-AF and ATRIA provided the best bleeding risk prediction within the first 1100 days. None of the 6 bleeding risk scores provided predictive benefit over 2100 days of DOAC treatment.

Participant-guided development of bilingual genomic educational infographics for Electronic Medical Records and Genomics Phase IV study.

OBJECTIVE: Developing targeted, culturally competent educational materials is critical for participant understanding of engagement in a large genomic study that uses computational pipelines to produce genome-informed risk assessments. MATERIALS AND METHODS: Guided by the Smerecnik framework that theorizes understanding of multifactorial genetic disease through 3 knowledge types, we developed English and Spanish infographics for individuals enrolled in the Electronic Medical Records and Genomics Network. Infographics were developed to explain concepts in lay language and visualizations. We conducted iterative sessions using a modified "think-aloud" process with 10 participants (6 English, 4 Spanish-speaking) to explore comprehension of and attitudes towards the infographics. RESULTS: We found that all but one participant had "awareness knowledge" of genetic disease risk factors upon viewing the infographics. Many participants had difficulty with "how-to" knowledge of applying genetic risk factors to specific monogenic and polygenic risks. Participant attitudes towards the iteratively-refined infographics indicated that design saturation was reached. DISCUSSION: There were several elements that contributed to the participants' comprehension (or misunderstanding) of the infographics. Visualization and iconography techniques best resonated with those who could draw on prior experiences or knowledge and were absent in those without. Limited graphicacy interfered with the understanding of absolute and relative risks when presented in graph format. Notably, narrative and storytelling theory that informed the creation of a vignette infographic was most accessible to all participants. CONCLUSION: Engagement with the intended audience who can identify strengths and points for improvement of the intervention is necessary to the development of effective infographics.

Strong protective effect of the APOL1 p.N264K variant against G2-associated focal segmental glomerulosclerosis and kidney disease.

African Americans have a significantly higher risk of developing chronic kidney disease, especially focal segmental glomerulosclerosis -, than European Americans. Two coding variants (G1 and G2) in the APOL1 gene play a major role in this disparity. While 13% of African Americans carry the high-risk recessive genotypes, only a fraction of these individuals develops FSGS or kidney failure, indicating the involvement of additional disease modifiers. Here, we show that the presence of the APOL1 p.N264K missense variant, when co-inherited with the G2 APOL1 risk allele, substantially reduces the penetrance of the G1G2 and G2G2 high-risk genotypes by rendering these genotypes low-risk. These results align with prior functional evidence showing that the p.N264K variant reduces the toxicity of the APOL1 high-risk alleles. These findings have important implications for our understanding of the mechanisms of APOL1-associated nephropathy, as well as for the clinical management of individuals with high-risk genotypes that include the G2 allele.

Strong protective effect of the APOL1 p.N264K variant against G2-associated focal segmental glomerulosclerosis and kidney disease.

Black Americans have a significantly higher risk of developing chronic kidney disease (CKD), especially focal segmental glomerulosclerosis (FSGS), than European Americans. Two coding variants (G1 and G2) in the APOL1 gene play a major role in this disparity. While 13% of Black Americans carry the high-risk recessive genotypes, only a fraction of these individuals develops FSGS or kidney failure, indicating the involvement of additional disease modifiers. Here, we show that the presence of the APOL1 p.N264K missense variant, when co-inherited with the G2 APOL1 risk allele, substantially reduces the penetrance of the G1G2 and G2G2 high-risk genotypes by rendering these genotypes low-risk. These results align with prior functional evidence showing that the p.N264K variant reduces the toxicity of the APOL1 high-risk alleles. These findings have important implications for our understanding of the mechanisms of APOL1 -associated nephropathy, as well as for the clinical management of individuals with high-risk genotypes that include the G2 allele.

Selection, optimization, and validation of ten chronic disease polygenic risk scores for clinical implementation in diverse populations.

Polygenic risk scores (PRS) have improved in predictive performance supporting their use in clinical practice. Reduced predictive performance of PRS in diverse populations can exacerbate existing health disparities. The NHGRI-funded eMERGE Network is returning a PRS-based genome-informed risk assessment to 25,000 diverse adults and children. We assessed PRS performance, medical actionability, and potential clinical utility for 23 conditions. Standardized metrics were considered in the selection process with additional consideration given to strength of evidence in African and Hispanic populations. Ten conditions were selected with a range of high-risk thresholds: atrial fibrillation, breast cancer, chronic kidney disease, coronary heart disease, hypercholesterolemia, prostate cancer, asthma, type 1 diabetes, obesity, and type 2 diabetes. We developed a pipeline for clinical PRS implementation, used genetic ancestry to calibrate PRS mean and variance, created a framework for regulatory compliance, and developed a PRS clinical report. eMERGE's experience informs the infrastructure needed to implement PRS-based implementation in diverse clinical settings.

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

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

Hypertension severity, apparent treatment resistant hypertension and hyperuricemia in the REasons for Geographic And Racial Differences in Stroke (REGARDS) study.

BACKGROUND: Prior studies have identified an association between hypertension and hyperuricemia; however, there has been limited research on the association between hypertension severity and hyperuricemia. METHOD: We studied 997 Black and white adults with serum urate data from the reasons for geographic and racial differences in stroke (REGARDS) study. Hypertension was defined as SBP ≥ 140 mmHg or DBP ≥ 90 mmHg or self-reported use of antihypertensive medication. Apparent treatment-resistant hypertension (aTRH) was defined as a SBP ≥ 140 mmHg or DBP ≥ 90 mmHg with concurrent use of three classes of antihypertensive medications, or taking four or more classes of antihypertensive medication regardless of BP level. Controlled BP was defined as SBP <140 mmHg and DBP <90 mmHg. RESULTS: Overall 5.9% of participants had aTRH and 36.6% had hyperuricemia, defined as serum urate >7.0 mg/dl for men and >6.0 mg/dl for women. After full multivariable adjustment, the odds ratio (OR) for hyperuricemia associated with hypertension was 1.60 [95% confidence interval (95% CI): 1.06-2.40]. Compared to participants not taking antihypertensive medication, the ORs for hyperuricemia for participants taking one, two and three classes of antihypertensive medication without aTRH were 1.98 (95% CI: 1.23-3.20), 2.08 (95% CI: 1.25-3.43), 4.31 (95% CI: 2.07-8.97), respectively, and 3.96 (95% CI: 1.75-8.96) for aTRH. Compared to participants without hypertension, the odds ratios for hyperuricemia were 1.67 (95% CI: 1.08-2.58) and 1.46 (95% CI: 0.88-2.44) among those with hypertension with and without controlled BP, respectively. Diuretic use was associated with a higher odds of hyperuricemia. CONCLUSION: This study suggests that individuals taking more classes of antihypertensive medication may benefit from monitoring for hyperuricemia.

Does genetic testing offer utility as a supplement to traditional family health history intake for inherited disease risk?

CONTENT: This study examines the potential utility of genetic testing as a supplement to family health history to screen for increased risk of inherited disease. Medical conditions are often misreported or misunderstood, especially those related to different forms of cardiac disease (arrhythmias vs. structural heart disease vs. coronary artery disease), female organ cancers (uterine vs. ovarian vs. cervical), and type of cancer (differentiating primary cancer from metastases to other organs). While these nuances appear subtle, they can dramatically alter medical management. For example, different types of cardiac failure (structural, arrhythmia, and coronary artery disease) have inherited forms that are managed with vastly different approaches. METHODS: Using a dataset of over 6,200 individuals who underwent genetic screening, we compared the ability of genetic testing and traditional family health history to identify increased risk of inherited disease. A further, in-depth qualitative study of individuals for whom risk identified through each method was discordant, explored whether this discordance could be addressed through changes in family health history intake. FINDINGS: Of 90 individuals for whom genetic testing indicated significant increased risk for inherited disease, two-thirds (66%) had no corroborating family health history. Specifically, we identify cardiomyopathy, arrhythmia, and malignant hyperthermia as conditions for which discordance between genetic testing and traditional family health history was greatest, and familial hypercholesterolaemia, Lynch syndrome, and hereditary breast and ovarian cancer as conditions for which greater concordance existed. CONCLUSION: We conclude that genetic testing offers utility as a supplement to traditional family health history intake over certain conditions.

Pharmacogenetic actionability and medication prescribing in people with cystic fibrosis.

Although major advancements have been made in the therapeutics for people with cystic fibrosis (PwCF), many still require the use of multiple medications to manage acute exacerbations of disease and maintain health. Iterative trial and error processes of pharmacotherapeutic management can be optimized by assessing and incorporating pharmacogenetics. For 82 PwCF, we reviewed 2 years of medication use and response history and interrogated metabolizer status for common pharmacogenes, revealing 3336 medication exposure events (MEEs) to 286 unique medications. As expected, the more frequent MEEs were those commonly used to treat cystic fibrosis (CF), such as antibiotics and respiratory medications. Antibiotics also comprised 56.7% of the undesirable drug responses. The impact of gene variants on drug responses was assessed using Pharmacogenomics Knowledgebase (PharmGKB) and Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines. Thirty-three (11.5%) medications have strong evidence of genetic influence on response as evidenced by gene-based dosing guidelines. 110 (38.5%) unique medications had at least one association with a very important pharmacogene, whereas 143 (50%) were associated with at least one clinical or variant annotation. Over 97% of participants had at least one actionable genotype. Eleven (13.4%) patients with an actionable genotype, taking the impacted medication, had an undesirable drug response described in the CPIC guidelines that could potentially have been mitigated with a priori knowledge of the genotype. PwCF take many medications for disease management, with frequent dose changes to elicit a desired clinical effect. As CF care evolves, implementing pharmacogenetics testing can improve efficiency and safety of prescribing practices using precision selection and dosing at medication initiation.

Returning integrated genomic risk and clinical recommendations: The eMERGE study.

PURPOSE: Assessing the risk of common, complex diseases requires consideration of clinical risk factors as well as monogenic and polygenic risks, which in turn may be reflected in family history. Returning risks to individuals and providers may influence preventive care or use of prophylactic therapies for those individuals at high genetic risk. METHODS: To enable integrated genetic risk assessment, the eMERGE (electronic MEdical Records and GEnomics) network is enrolling 25,000 diverse individuals in a prospective cohort study across 10 sites. The network developed methods to return cross-ancestry polygenic risk scores, monogenic risks, family history, and clinical risk assessments via a genome-informed risk assessment (GIRA) report and will assess uptake of care recommendations after return of results. RESULTS: GIRAs include summary care recommendations for 11 conditions, education pages, and clinical laboratory reports. The return of high-risk GIRA to individuals and providers includes guidelines for care and lifestyle recommendations. Assembling the GIRA required infrastructure and workflows for ingesting and presenting content from multiple sources. Recruitment began in February 2022. CONCLUSION: Return of a novel report for communicating monogenic, polygenic, and family history-based risk factors will inform the benefits of integrated genetic risk assessment for routine health care.

Pharmacogenomic Profiling of Pediatric Patients on Psychotropic Medications in an Emergency Department.

OBJECTIVE: The aim of the study was to evaluate the ability of a combinatorial pharmacogenomic test to predict medication blood levels and relative clinical improvements in a selected pediatric population. METHODS: This study enrolled patients between ages 3 to 18 years who presented to a pediatric emergency department with acute psychiatric, behavioral, or mental health crisis and/or concerns, and had previously been prescribed psychotropic medications. Patients received combinatorial pharmacogenomic testing with medications categorized according to gene-drug interactions (GDIs); medications with a GDI were considered "incongruent," and medications without a GDI were considered "congruent." Blood levels for escitalopram, fluoxetine, aripiprazole, and clonidine were evaluated according to level of GDI. Relative clinical improvements in response to the prescribed psychotropic medications were measured using a parent-rated Clinical Global Impression of Improvement (CGI-I) assessment, where lower scores corresponded with greater improvement. RESULTS: Of the 100 patients enrolled, 73% reported taking ≥1 incongruent medication. There was no significant difference in CGI-I scores between patients prescribed congruent versus incongruent medications (3.37 vs 3.68, P = 0.343). Among patients who presented for depression or suicidal ideation, those prescribed congruent medications had significantly lower CGI-I scores compared with those taking incongruent medications ( P = 0.036 for depression, P = 0.018 for suicidal ideation). There was a significant association between medication GDI and blood levels for aripiprazole (n = 15, P = 0.01) and escitalopram (n = 10, P = 0.01). CONCLUSIONS: Our preliminary findings suggest that combinatorial pharmacogenomic testing can predict medication blood levels and relative outcomes based on medication congruency in children presenting to an emergency department with acute psychiatric/behavioral crises. Additional studies will be needed to confirm these findings.

Evaluation of Potential Racial Disparities in CYP2C19-Guided P2Y12 Inhibitor Prescribing After Percutaneous Coronary Intervention.

Black patients suffer worse outcomes after percutaneous coronary intervention (PCI) than White patients. Inequities in antiplatelet prescribing may contribute to this health disparity. We compared P2Y12 inhibitor prescribing by race following CYP2C19 genotyping to guide antiplatelet therapy selection after PCI. Patients from 9 sites that performed clinical CYP2C19 genotyping after PCI were included. Alternative therapy (e.g., prasugrel or ticagrelor) was recommended for CYP2C19 no-function allele carriers, in whom clopidogrel is predicted to be less effective. The primary outcome was choice of P2Y12 inhibitor (clopidogrel vs. alternative therapy) based on genotype. Of 3,342 patients included, 2,448 (73%) were White, and 659 (20%) were Black. More Black than White patients had a no-function allele (34.3% vs. 29.7%, P = 0.024). At hospital discharge following PCI, 44.2% of Black and 44.0% of White no-function allele carriers were prescribed alternative therapy. At the time of the last follow-up within 12 months, numerically fewer Black (51.8%) than White (56.7%) no-function allele carriers were prescribed alternative therapy (P = 0.190). However, the difference was not significant after accounting for other factors associated with P2Y12 inhibitor selection (odds ratio 0.79, 95% confidence interval 0.58-1.08). Alternative therapy use did not differ between Black (14.3%) and White (16.7%) patients without a no-function allele (P = 0.232). Among real-world patients who received CYP2C19 testing after PCI, P2Y12 inhibitor prescribing rates did not differ between Black and White patients. Our data suggest an absence of racial disparity in genotype-guided antiplatelet prescribing among patients receiving CYP2C19 testing.

Personalizing Direct Oral Anticoagulant Therapy for a Diverse Population: Role of Race, Kidney Function, Drug Interactions, and Pharmacogenetics.

Oral anticoagulants (OACs) are commonly used to reduce the risk of venous thromboembolism and the risk of stroke in patients with atrial fibrillation. Endorsed by the American Heart Association, American College of Cardiology, and the European Society of Cardiology, direct oral anticoagulants (DOACs) have displaced warfarin as the OAC of choice for both conditions, due to improved safety profiles, fewer drug-drug and drug-diet interactions, and lack of monitoring requirements. Despite their widespread use and improved safety over warfarin, DOAC-related bleeding remains a major concern for patients. DOACs have stable pharmacokinetics and pharmacodynamics; however, variability in DOAC response is common and may be attributed to numerous factors, including patient-specific factors, concomitant medications, comorbid conditions, and genetics. Although DOAC randomized controlled trials included patients of varying ages and levels of kidney function, they failed to include patients of diverse ancestries. Additionally, current evidence to support DOAC pharmacogenetic associations have primarily been derived from European and Asian individuals. Given differences in genotype frequencies and disease burden among patients of different biogeographic groups, future research must engage diverse populations to assess and quantify the impact of predictors on DOAC response. Current under-representation of patients from diverse racial groups does not allow for proper generalization of the influence of clinical and genetic factors in relation to DOAC variability. Herein, we discuss factors affecting DOAC response, such as age, sex, weight, kidney function, drug interactions, and pharmacogenetics, while offering a new perspective on the need for further research including frequently excluded groups.

Predictive models for abdominal aortic aneurysms using polygenic scores and PheWAS-derived risk factors.

Abdominal aortic aneurysms (AAA) are common enlargements of the abdominal aorta which can grow larger until rupture, often leading to death. Detection of AAA is often by ultrasonography and screening recommendations are mostly directed at men over 65 with a smoking history. Recent large-scale genome-wide association studies have identified genetic loci associated with AAA risk. We combined known risk factors, polygenic risk scores (PRS) and precedent clinical diagnoses from electronic health records (EHR) to develop predictive models for AAA, and compared performance against screening recommendations. The PRS included genome-wide summary statistics from the Million Veteran Program and FinnGen (10,467 cases, 378,713 controls of European ancestry), with optimization in Vanderbilt's BioVU and validated in the eMERGE Network, separately across both White and Black participants. Candidate diagnoses were identified through a temporally-oriented Phenome-wide association study in independent EHR data from Vanderbilt, and features were selected via elastic net. We calculated C-statistics in eMERGE for models including PRS, phecodes, and covariates using regression weights from BioVU. The AUC for the full model in the test set was 0.883 (95% CI 0.873-0.892), 0.844 (0.836-0.851) for covariates only, 0.613 (95% CI 0.604-0.622) when using primary USPSTF screening criteria, and 0.632 (95% CI 0.623-0.642) using primary and secondary criteria. Brier scores were between 0.003 and 0.023 for our models indicating good calibration, and net reclassification improvement over combined primary and secondary USPSTF criteria was 0.36-0.60. We provide PRS for AAA which are strongly associated with AAA risk and add to predictive model performance. These models substantially improve identification of people at risk of a AAA diagnosis compared with existing guidelines, with evidence of potential applicability in minority populations.

Quantifying factors that affect polygenic risk score performance across diverse ancestries and age groups for body mass index.

Polygenic risk scores (PRS) have led to enthusiasm for precision medicine. However, it is well documented that PRS do not generalize across groups differing in ancestry or sample characteristics e.g., age. Quantifying performance of PRS across different groups of study participants, using genome-wide association study (GWAS) summary statistics from multiple ancestry groups and sample sizes, and using different linkage disequilibrium (LD) reference panels may clarify which factors are limiting PRS transferability. To evaluate these factors in the PRS generation process, we generated body mass index (BMI) PRS (PRSBMI) in the Electronic Medical Records and Genomics (eMERGE) network (N=75,661). Analyses were conducted in two ancestry groups (European and African) and three age ranges (adult, teenagers, and children). For PRSBMI calculations, we evaluated five LD reference panels and three sets of GWAS summary statistics of varying sample size and ancestry. PRSBMI performance increased for both African and European ancestry individuals using cross-ancestry GWAS summary statistics compared to European-only summary statistics (6.3% and 3.7% relative R2 increase, respectively, pAfrican=0.038, pEuropean=6.26x10-4). The effects of LD reference panels were more pronounced in African ancestry study datasets. PRSBMI performance degraded in children; R2 was less than half of teenagers or adults. The effect of GWAS summary statistics sample size was small when modeled with the other factors. Additionally, the potential of using a PRS generated for one trait to predict risk for comorbid diseases is not well understood especially in the context of cross-ancestry analyses - we explored clinical comorbidities from the electronic health record associated with PRSBMI and identified significant associations with type 2 diabetes and coronary atherosclerosis. In summary, this study quantifies the effects that ancestry, GWAS summary statistic sample size, and LD reference panel have on PRS performance, especially in cross-ancestry and age-specific analyses.