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Asthma is the most common chronic condition in children and the third leading cause of hospitalization in pediatrics. The genome-wide association study catalog reports 140 studies with genome-wide significance. A polygenic risk score (PRS) with predictive value across ancestries has not been evaluated for this important trait.This study aimed to train and validate a PRS relying on genetic determinants for asthma to provide predictions for disease occurrence in pediatric cohorts of diverse ancestries.This study applied a Bayesian regression framework method using the Trans-National Asthma Genetic Consortium genome-wide association study summary statistics to derive a multiancestral PRS score, used one Electronic Medical Records and Genomics (eMERGE) cohort as a training set, used a second independent eMERGE cohort to validate the score, and used the UK Biobank data to replicate the findings. A phenome-wide association study was performed using the PRS to identify shared genetic etiology with other phenotypes.The multiancestral asthma PRS was associated with asthma in the 2 pediatric validation datasets. Overall, the multiancestral asthma PRS has an area under the curve (AUC) of 0.70 (95% CI, 0.69-0.72) in the pediatric validation 1 and AUC of 0.66 (0.65-0.66) in the pediatric validation 2 datasets. We found significant discrimination across pediatric subcohorts of European (AUC, 95% CI, 0.60 and 0.66), African (AUC, 95% CI, 0.61 and 0.66), admixed American (AUC, 0.64 and 0.70), Southeast Asian (AUC, 0.65), and East Asian (AUC, 0.73) ancestry. Pediatric participants with the top 5% PRS had 2.80 to 5.82 increased odds of asthma compared to the bottom 5% across the training, validation 1, and validation 2 cohorts when adjusted for ancestry. Phenome-wide association study analysis confirmed the strong association of the identified PRS with asthma (odds ratio, 2.71, PsubFDR/sub = 3.71 × 10sup-65/sup) and related phenotypes.A multiancestral PRS for asthma based on Bayesian posterior genomic effect sizes identifies increased odds of pediatric asthma.

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. SUMMARY: 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.

Background: The implications of secondary findings detected in large-scale sequencing projects remain uncertain. We assessed prevalence and penetrance of pathogenic familial hypercholesterolemia (FH) variants, their association with coronary heart disease (CHD), and 1-year outcomes following return of results in phase III of the electronic medical records and genomics network. Methods: Adult participants (n=18 544) at 7 sites were enrolled in a prospective cohort study to assess the clinical impact of returning results from targeted sequencing of 68 actionable genes, including LDLR , APOB , and PCSK9 . FH variant prevalence and penetrance (defined as low-density lipoprotein cholesterol >155 mg/dL) were estimated after excluding participants enrolled on the basis of hypercholesterolemia. Multivariable logistic regression was used to estimate the odds of CHD compared to age- and sex-matched controls without FH-associated variants. Process (eg, referral to a specialist or ordering new tests), intermediate (eg, new diagnosis of FH), and clinical (eg, treatment modification) outcomes within 1 year after return of results were ascertained by electronic health record review. Results: The prevalence of FH-associated pathogenic variants was 1 in 188 (69 of 13,019 unselected participants). Penetrance was 87.5%. The presence of an FH variant was associated with CHD (odds ratio, 3.02 [2.00–4.53]) and premature CHD (odds ratio, 3.68 [2.34–5.78]). At least 1 outcome occurred in 92% of participants; 44% received a new diagnosis of FH and 26% had treatment modified following return of results. Conclusions: In a multisite cohort of electronic health record–linked biobanks, monogenic FH was prevalent, penetrant, and associated with presence of CHD. Nearly half of participants with an FH-associated variant received a new diagnosis of FH and a quarter had treatment modified after return of results. These results highlight the potential utility of sequencing electronic health record–linked biobanks to detect FH.

BackgroundPreeclampsia, a pregnancy complication characterized by hypertension after 20 gestational weeks, is a major cause of maternal and neonatal morbidity and mortality. The mechanisms leading to preeclampsia are unclear; however, there is evidence that preeclampsia is highly heritable. We evaluated the association of polygenic risk scores (PRS) for blood pressure traits and preeclampsia to assess whether there is shared genetic architecture.MethodsParticipants were obtained from Vanderbilt University’s BioVU, the Electronic Medical Records and Genomics network, and the Penn Medicine Biobank. Non-Hispanic Black and White females of reproductive age with indications of pregnancy and genotype information were included. Preeclampsia was defined by ICD codes. Summary statistics for diastolic blood pressure (DBP), systolic blood pressure (SBP), and pulse pressure (PP) PRS were obtained from Giri et al 2019. Associations between preeclampsia and each PRS were evaluated separately by race and study population before evidence was meta-analyzed. Prediction models were developed and evaluated using 10-fold cross validation.ResultsIn the 3,504 Black and 5,009 White individuals included, the rate of preeclampsia was 15.49%. The DBP and SBP PRSs were associated with preeclampsia in Whites but not Blacks. The PP PRS was significantly associated with preeclampsia in Blacks and Whites. In trans-ancestry meta-analysis, all PRSs were associated with preeclampsia (ORDBP=1.10, 95% CI=1.02-1.17,p=7.68×10−3; ORSBP=1.16, 95% CI=1.09-1.23,p=2.23×10−6; ORPP=1.14, 95% CI=1.07-1.27,p=9.86×10−5). However, addition of PRSs to clinical prediction models did not improve predictive performance.ConclusionsGenetic factors contributing to blood pressure regulation in the general population also predispose to preeclampsia.

Genomic medicine holds great promise for improving health care, but integrating searchable and actionable genetic data into electronic health records (EHRs) remains a challenge. Here we describe Neptune, a system for managing the interaction between a clinical laboratory and an EHR system during the clinical reporting process. We developed Neptune and applied it to two clinical sequencing projects that required report customization, variant reanalysis, and EHR integration. Neptune has been applied for the generation and delivery of over 15,000 clinical genomic reports. This work spans two clinical tests based on targeted gene panels that contain 68 and 153 genes respectively. These projects demanded customizable clinical reports that contained a variety of genetic data types including single-nucleotide variants (SNVs), copy-number variants (CNVs), pharmacogenomics, and polygenic risk scores. Two variant reanalysis activities were also supported, highlighting this important workflow. Methods are needed for delivering structured genetic data to EHRs. This need extends beyond developing data formats to providing infrastructure that manages the reporting process itself. Neptune was successfully applied on two high-throughput clinical sequencing projects to build and deliver clinical reports to EHR systems. The software is open source and available at https://gitlab.com/bcm-hgsc/neptune .

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.

Leveraging linkage disequilibrium (LD) patterns as representative of population substructure enables the discovery of additive association signals in genome-wide association studies (GWAS). Standard GWAS are well-powered to interrogate additive models; however, new approaches are required to investigate other modes of inheritance such as dominance and epistasis. Epistasis, or non-additive interaction between genes, exists across the genome but often goes undetected due to lack of statistical power. Furthermore, the adoption of LD pruning as customary in standard GWAS excludes detection of sites in LD that may underlie the genetic architecture of complex traits. We hypothesize that uncovering long-range interactions between loci with strong LD due to epistatic selection can elucidate genetic mechanisms underlying common diseases. To investigate this hypothesis, we tested for associations between 23 common diseases and 5,625,845 epistatic SNP-SNP pairs (determined by Ohta’sDstatistics) in long-range LD (> 0.25cM). We identified five significant associations across five disease phenotypes that replicated in two large genotype-phenotype datasets (UK Biobank and eMERGE). The genes that were most likely involved in the replicated associations were 1) members of highly conserved gene families with complex roles in multiple pathways, 2) essential genes, and/or 3) associated in the literature with complex traits that display variable expressivity. These results support the highly pleiotropic and conserved nature of variants in long-range under epistatic selection. Our work supports the hypothesis that epistatic interactions regulate diverse clinical mechanisms and may especially be driving factors in conditions with a wide range of phenotypic outcomes.SignificanceCurrent knowledge of genotype-phenotype relationships is largely contingent on traditional univariate approaches to genomic analysis. Yet substantial evidence supports non-additive modes of inheritance and regulation, such as epistasis, as being abundant across the genome. In this genome-wide study, we probe the biomolecular mechanisms underlying complex human diseases by testing the association of pairwise genetic interactions with disease occurrence in large-scale biobank data. Specifically, we tested intrachromosomal and interchrosomal long-range interactions between regions of the genome in high linkage disequilibrium, these regions are typically excluded from genomic analyses. The results from this study suggest that essential gene, members of highly conserved gene families, and phenotypes with variable expressivity, are particularly enriched with epistatic and pleiotropic activity.

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.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 (PRS), 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.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.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.

Supplemental Digital Content is available in the text., Background: Abdominal aortic aneurysm (AAA) is an important cause of cardiovascular mortality; however, its genetic determinants remain incompletely defined. In total, 10 previously identified risk loci explain a small fraction of AAA heritability. Methods: We performed a genome-wide association study in the Million Veteran Program testing ≈18 million DNA sequence variants with AAA (7642 cases and 172 172 controls) in veterans of European ancestry with independent replication in up to 4972 cases and 99 858 controls. We then used mendelian randomization to examine the causal effects of blood pressure on AAA. We examined the association of AAA risk variants with aneurysms in the lower extremity, cerebral, and iliac arterial beds, and derived a genome-wide polygenic risk score (PRS) to identify a subset of the population at greater risk for disease. Results: Through a genome-wide association study, we identified 14 novel loci, bringing the total number of known significant AAA loci to 24. In our mendelian randomization analysis, we demonstrate that a genetic increase of 10 mm Hg in diastolic blood pressure (odds ratio, 1.43 [95% CI, 1.24–1.66]; P=1.6×10−6), as opposed to systolic blood pressure (odds ratio, 1.06 [95% CI, 0.97–1.15]; P=0.2), likely has a causal relationship with AAA development. We observed that 19 of 24 AAA risk variants associate with aneurysms in at least 1 other vascular territory. A 29-variant PRS was strongly associated with AAA (odds ratioPRS, 1.26 [95% CI, 1.18–1.36]; PPRS=2.7×10−11 per SD increase in PRS), independent of family history and smoking risk factors (odds ratioPRS+family history+smoking, 1.24 [95% CI, 1.14–1.35]; PPRS=1.27×10−6). Using this PRS, we identified a subset of the population with AAA prevalence greater than that observed in screening trials informing current guidelines. Conclusions: We identify novel AAA genetic associations with therapeutic implications and identify a subset of the population at significantly increased genetic risk of AAA independent of family history. Our data suggest that extending current screening guidelines to include testing to identify those with high polygenic AAA risk, once the cost of genotyping becomes comparable with that of screening ultrasound, would significantly increase the yield of current screening at reasonable cost.

Background/Objectives Melanocortin-4 receptor (MC4R) plays an essential role in food intake and energy homeostasis. More than 170 MC4R variants have been described over the past two decades, with conflicting reports regarding the prevalence and phenotypic effects of these variants in diverse cohorts. To determine the frequency of MC4R variants in large cohort of different ancestries, we evaluated the MC4R coding region for 20,537 eMERGE participants with sequencing data plus additional 77,454 independent individuals with genome-wide genotyping data at this locus. Subjects/Methods The sequencing data were obtained from the eMERGE phase III study, in which multisample variant call format calls have been generated, curated, and annotated. In addition to penetrance estimation using body mass index (BMI) as a binary outcome, GWAS and PheWAS were performed using median BMI in linear regression analyses. All results were adjusted for principal components, age, sex, and sites of genotyping. Results Targeted sequencing data of MC4R revealed 125 coding variants in 1839 eMERGE participants including 30 unreported coding variants that were predicted to be functionally damaging. Highly penetrant unreported variants included (L325I, E308K, D298N, S270F, F261L, T248A, D111V, and Y80F) in which seven participants had obesity class III defined as BMI ≥ 40 kg/m2. In GWAS analysis, in addition to known risk haplotype upstream of MC4R (best variant rs6567160 (P = 5.36 × 10−25, Beta = 0.37), a novel rare haplotype was detected which was protective against obesity and encompassed the V103I variant with known gain-of-function properties (P = 6.23 × 10−08, Beta = −0.62). PheWAS analyses extended this protective effect of V103I to type 2 diabetes, diabetic nephropathy, and chronic renal failure independent of BMI. Conclusions MC4R screening in a large eMERGE cohort confirmed many previous findings, extend the MC4R pleotropic effects, and discovered additional MC4R rare alleles that probably contribute to obesity.

Objective Familial hypercholesterolemia (FH), a prevalent genomic disorder that increases risk of coronary heart disease, remains significantly underdiagnosed. Clinical decision support (CDS) tools have the potential to increase FH detection. We describe our experience in the development and implementation of a genomic CDS for FH at a large academic medical center.Methods CDS development and implementation were conducted in four phases: (1) development and validation of an algorithm to identify “possible FH”; (2) obtaining approvals from institutional committees to develop the CDS; (3) development of the initial prototype; and (4) use of an implementation science framework to evaluate the CDS.Results The timeline for this work was approximately 4 years; algorithm development and validation occurred from August 2018 to February 2020. During this 4-year period, we engaged with 15 stakeholder groups to build and integrate the CDS, including health care providers who gave feedback at each stage of development. During CDS implementation six main challenges were identified: (1) need for multiple institutional committee approvals; (2) need to align the CDS with institutional knowledge resources; (3) need to adapt the CDS to differing workflows; (4) lack of institutional guidelines for CDS implementation; (5) transition to a new institutional electronic health record (EHR) system; and (6) limitations of the EHR related to genomic medicine.Conclusion We identified multiple challenges in different domains while developing CDS for FH and integrating it with the EHR. The lessons learned herein may be helpful in streamlining the development and deployment of CDS to facilitate genomic medicine implementation.

Accurate colorectal cancer (CRC) risk prediction models are critical for identifying individuals at low and high risk of developing CRC, as they can then be offered targeted screening and interventions to address their risks of developing disease (if they are in a high-risk group) and avoid unnecessary screening and interventions (if they are in a low-risk group). As it is likely that thousands of genetic variants contribute to CRC risk, it is clinically important to investigate whether these genetic variants can be used jointly for CRC risk prediction. In this paper, we derived and compared different approaches to generating predictive polygenic risk scores (PRS) from genome-wide association studies (GWASs) including 55,105 CRC-affected case subjects and 65,079 control subjects of European ancestry. We built the PRS in three ways, using (1) 140 previously identified and validated CRC loci; (2) SNP selection based on linkage disequilibrium (LD) clumping followed by machine-learning approaches; and (3) LDpred, a Bayesian approach for genome-wide risk prediction. We tested the PRS in an independent cohort of 101,987 individuals with 1,699 CRC-affected case subjects. The discriminatory accuracy, calculated by the age- and sex-adjusted area under the receiver operating characteristics curve (AUC), was highest for the LDpred-derived PRS (AUC = 0.654) including nearly 1.2 M genetic variants (the proportion of causal genetic variants for CRC assumed to be 0.003), whereas the PRS of the 140 known variants identified from GWASs had the lowest AUC (AUC = 0.629). Based on the LDpred-derived PRS, we are able to identify 30% of individuals without a family history as having risk for CRC similar to those with a family history of CRC, whereas the PRS based on known GWAS variants identified only top 10% as having a similar relative risk. About 90% of these individuals have no family history and would have been considered average risk under current screening guidelines, but might benefit from earlier screening. The developed PRS offers a way for risk-stratified CRC screening and other targeted interventions.

Uterine fibroids (UF) are common pelvic tumors in women, heritable, and genome-wide association studies (GWAS) have identified ~ 30 loci associated with increased risk in UF. Using summary statistics from a previously published UF GWAS performed in a non-Hispanic European Ancestry (NHW) female subset from the Electronic Medical Records and Genomics (eMERGE) Network, we constructed a polygenic risk score (PRS) for UF. UF-PRS was developed using PRSice and optimized in the separate clinical population of BioVU. PRS was validated using parallel methods of 10-fold cross-validation logistic regression and phenome-wide association study (PheWAS) in a seperate subset of eMERGE NHW females (validation set), excluding samples used in GWAS. PRSice determined p

Introduction: Clonal hematopoiesis of indeterminate potential (CHIP) refers to the formation of genetically distinct subpopulations of blood cells due to somatic mutations. CHIP is associated with a variety of adverse outcomes, including hematological cancers, cardiovascular disease, and death. We sought to investigate the association of CHIP with incident venous thromboembolism (VTE). Methods: We analyzed exome sequence data from 200,628 individuals in the UK Biobank cohort using Mutect2 to identify a prespecified list of somatic mutations in DNMT3A, TET2, and ASXL1, which are known genetic drivers of CHIP. CHIP was defined as harboring a somatic mutation at a variant allele fraction (VAF) ≥10% and individuals with VAF Results: Among 200,628 individuals, we identified 3,885 individuals with CHIP at baseline and 748 incident VTE events during a median follow-up of 9.2 years. In 748 incident cases and 5984 matched controls, CHIP was associated with increased risk of incident VTE independent of conventional risk factors for VTE, namely, age, sex, BMI, smoking, and history of malignancy (incidence rate ratio [95% confidence interval]; 1.60 [1.04-2.46], p=0.032). When we restricted the cases to individuals with incident pulmonary embolism (n=441), we observed a stronger association with CHIP (1.80 [1.08-3.05], p=0.025). Conclusions: CHIP is associated with increased risk of VTE independent of history of malignancy and other conventional risk factors. The pathophysiological basis for this association needs further investigation.

Introduction: The prevalence of atrial fibrillation (AF) increases with age and inflammation plays a key pathophysiologic role. Somatic mosaicism increases with age and promotes inflammation. Therefore, we investigated whether Clonal Hematopoiesis of Indeterminate Potential (CHIP) is a risk factor for incident AF. Methods: We assessed exome sequence (ES) data from 200,628 participants in the UK biobank. Using the Genome Analysis Toolkit pipeline, we ascertained a predefined list of CHIP mutations in DNMT3A , TET2 , and ASXL1 . CHIP was defined as variant allele frequency (VAF) >10% and those with VAF Results: Of 200,628 participants, 3885 (1.9%) had CHIP. The number of participants with mutations in DNMT3A , TET2 , and ASXL1 was 2512, 1065, and 439, respectively. During a median follow-up of 9 years, 4,676 incident AF and 3,584 incident lone AF occurred. CHIP was an independent risk factor for developing incident AF and also for developing lone AF. CHIP in TET2 and ASXL1 but not DNMT3A was associated with AF ( Table 1 ). Conclusions: The presence of CHIP involving TET2 and ASXL1 is associated with an increased risk of incident AF including the subset with lone AF. Our findings reveal somatic mosaicism in blood cells to be a novel risk factor for AF.

Chronic kidney disease (CKD) is a common complex condition associated with high morbidity and mortality. Polygenic prediction could enhance CKD screening and prevention; however, this approach has not been optimized for ancestrally diverse populations. By combining APOL1 risk genotypes with genome-wide association studies (GWAS) of kidney function, we designed, optimized and validated a genome-wide polygenic score (GPS) for CKD. The new GPS was tested in 15 independent cohorts, including 3 cohorts of European ancestry (n = 97,050), 6 cohorts of African ancestry (n = 14,544), 4 cohorts of Asian ancestry (n = 8,625) and 2 admixed Latinx cohorts (n = 3,625). We demonstrated score transferability with reproducible performance across all tested cohorts. The top 2% of the GPS was associated with nearly threefold increased risk of CKD across ancestries. In African ancestry cohorts, the APOL1 risk genotype and polygenic component of the GPS had additive effects on the risk of CKD.

Importance Multiple polygenic risk scores (PRSs) for breast cancer have been developed from large research consortia; however, their generalizability to diverse clinical settings is unknown. Objective To examine the performance of previously developed breast cancer PRSs in a clinical setting for women of European, African, and Latinx ancestry. Design, Setting, and Participants This cohort study using the Electronic Medical Records and Genomics (eMERGE) network data set included 39 591 women from 9 contributing medical centers in the US that had electronic medical records (EMR) linked to genotype data. Breast cancer cases and controls were identified through a validated EMR phenotyping algorithm. Main Outcomes and Measures Multivariable logistic regression was used to assess the association between breast cancer risk and 7 previously developed PRSs, adjusting for age, study site, breast cancer family history, and first 3 ancestry informative principal components. Results This study included 39 591 women: 33 594 with European, 3801 with African, and 2196 with Latinx ancestry. The mean (SD) age at breast cancer diagnosis was 60.7 (13.0), 58.8 (12.5), and 60.1 (13.0) years for women with European, African, and Latinx ancestry, respectively. PRSs derived from women with European ancestry were associated with breast cancer risk in women with European ancestry (highest odds ratio [OR] per 1-SD increase, 1.46; 95% CI, 1.41-1.51), women with Latinx ancestry (highest OR, 1.31; 95% CI, 1.09-1.58), and women with African ancestry (OR, 1.19; 95% CI, 1.05-1.35). For women with European ancestry, this association with breast cancer risk was largest in the extremes of the PRS distribution, with ORs ranging from 2.19 (95% CI, 1.84-2.53) to 2.48 (95% CI, 1.89-3.25) for the 3 different PRSs examined for those in the highest 1% of the PRS compared with those in the middle quantile. Among women with Latinx and African ancestries at the extremes of the PRS distribution, there were no statistically significant associations. Conclusions and Relevance This cohort study found that PRS models derived from women with European ancestry for breast cancer risk generalized well for women with European, Latinx, and African ancestries across different clinical settings, although the effect sizes for women with African ancestry were smaller, likely because of differences in risk allele frequencies and linkage disequilibrium patterns. These results highlight the need to improve representation of diverse population groups, particularly women with African ancestry, in genomic research cohorts.

Background: Lp(a) (lipoprotein [a]) levels are higher in individuals of African ancestry (AA) than in individuals of European ancestry (EA). We examined associations of genetically predicted Lp(a) levels with (1) atherosclerotic cardiovascular disease subtypes: coronary heart disease, cerebrovascular disease, peripheral artery disease, and abdominal aortic aneurysm and (2) nonatherosclerotic cardiovascular disease phenotypes, stratified by ancestry. Methods: We performed (1) Mendelian randomization analyses for previously reported cardiovascular associations and (2) Mendelian randomization–phenome-wide association analyses for novel associations. Analyses were stratified by ancestry in electronic Medical Records and Genomics, United Kingdom Biobank, and Million Veteran Program cohorts separately and in a combined cohort of 804 507 EA and 103 580 AA participants. Results: In Mendelian randomization analyses using the combined cohort, a 1-SD genetic increase in Lp(a) level was associated with atherosclerotic cardiovascular disease subtypes in EA—odds ratio and 95% CI for coronary heart disease 1.28 (1.16–1.41); cerebrovascular disease 1.14 (1.07–1.21); peripheral artery disease 1.22 (1.11–1.34); abdominal aortic aneurysm 1.28 (1.17–1.40); in AA, the effect estimate was lower than in EA and nonsignificant for coronary heart disease 1.11 (0.99–1.24) and cerebrovascular disease 1.06 (0.99–1.14) but similar for peripheral artery disease 1.16 (1.01–1.33) and abdominal aortic aneurysm 1.34 (1.11–1.62). In EA, a 1-SD genetic increase in Lp(a) level was associated with aortic valve disorders 1.34 (1.10–1.62), mitral valve disorders 1.18 (1.09–1.27), congestive heart failure 1.12 (1.05–1.19), and chronic kidney disease 1.07 (1.01–1.14). In AA, no significant associations were noted for aortic valve disorders 1.08 (0.94–1.25), mitral valve disorders 1.02 (0.89–1.16), congestive heart failure 1.02 (0.95–1.10), or chronic kidney disease 1.05 (0.99–1.12). Mendelian randomization–phenome-wide association analyses identified novel associations in EA with arterial thromboembolic disease, nonaortic aneurysmal disease, atrial fibrillation, cardiac conduction disorders, and hypertension. Conclusions: Many cardiovascular associations of genetically increased Lp(a) that were significant in EA were not significant in AA. Lp(a) was associated with atherosclerotic cardiovascular disease in four major arterial beds in EA but only with peripheral artery disease and abdominal aortic aneurysm in AA. Additionally, novel cardiovascular associations were detected in EA.

Background: Sequencing Mendelian arrhythmia genes in individuals without an indication for arrhythmia genetic testing can identify carriers of pathogenic or likely pathogenic (P/LP) variants. However, the extent to which these variants are associated with clinically meaningful phenotypes before or after return of variant results is unclear. In addition, the majority of discovered variants are currently classified as variants of uncertain significance, limiting clinical actionability. Methods: The eMERGE-III study (Electronic Medical Records and Genomics Phase III) is a multicenter prospective cohort that included 21 846 participants without previous indication for cardiac genetic testing. Participants were sequenced for 109 Mendelian disease genes, including 10 linked to arrhythmia syndromes. Variant carriers were assessed with electronic health record–derived phenotypes and follow-up clinical examination. Selected variants of uncertain significance (n=50) were characterized in vitro with automated electrophysiology experiments in HEK293 cells. Results: As previously reported, 3.0% of participants had P/LP variants in the 109 genes. Herein, we report 120 participants (0.6%) with P/LP arrhythmia variants. Compared with noncarriers, arrhythmia P/LP carriers had a significantly higher burden of arrhythmia phenotypes in their electronic health records. Fifty-four participants had variant results returned. Nineteen of these 54 participants had inherited arrhythmia syndrome diagnoses (primarily long-QT syndrome), and 12 of these 19 diagnoses were made only after variant results were returned (0.05%). After in vitro functional evaluation of 50 variants of uncertain significance, we reclassified 11 variants: 3 to likely benign and 8 to P/LP. Conclusions: Genome sequencing in a large population without indication for arrhythmia genetic testing identified phenotype-positive carriers of variants in congenital arrhythmia syndrome disease genes. As the genomes of large numbers of people are sequenced, the disease risk from rare variants in arrhythmia genes can be assessed by integrating genomic screening, electronic health record phenotypes, and in vitro functional studies. Registration: URL: https://www.clinicaltrials.gov ; Unique identifier; NCT03394859.

The coronavirus disease 2019 (COVID-19) pandemic continues its global spread. Coordinated effort on a vast scale is required to halt its progression and to save lives. Electronic health record (EHR) data are a valuable resource to mitigate the COVID-19 pandemic. We review how the EHR could be used for disease surveillance and contact tracing. When linked to "omics" data, the EHR could facilitate identification of genetic susceptibility variants, leading to insights into risk factors, disease complications, and drug repurposing. Real-time monitoring of patients could enable early detection of potential complications, informing appropriate interventions and therapy. We reviewed relevant articles from PubMed, MEDLINE, and Google Scholar searches as well as preprint servers, given the rapidly evolving understanding of the COVID-19 pandemic.

We investigated monogenic and polygenic causes of hypercholesterolemia in a population-based cohort, excluding secondary hypercholesterolemia, and using an established framework to identify pathogenic variants. We studied 1682 individuals (50.2 ± 8.6 years, 41.3% males) from southeast Minnesota with primary hypercholesterolemia (low-density lipoprotein cholesterol (LDL-C) ≥155 mg/dl in the absence of identifiable secondary causes). Familial hypercholesterolemia (FH) phenotype was defined as a Dutch Lipid Clinic Network (DLCN) score ≥6. Participants underwent sequencing of LDLR, APOB, and PCSK9, and genotyping of 12 LDL-C-associated single-nucleotide variants to construct a polygenic score (PGS) for LDL-C. The presence of a pathogenic/likely pathogenic variant was considered monogenic etiology and a PGS ≥90th percentile was considered polygenic etiology. The mean LDL-C level was 187.3 ± 32.3 mg/dl and phenotypic FH was present in 8.4% of the cohort. An identifiable genetic etiology was present in 17.1% individuals (monogenic in 1.5% and polygenic in 15.6%). Phenotypic and genetic FH showed poor overlap. Only 26% of those who met the clinical criteria of FH had an identifiable genetic etiology and of those with an identifiable genetic etiology only 12.9% met clinical criteria for FH. Genetic factors explained 7.4% of the variance in LDL-C. In conclusion, in adults with primary hypercholesterolemia, 17.1% had an identifiable genetic etiology and the overlap between phenotypic and genetic FH was modest.

The advancement of precision medicine requires new methods to coordinate and deliver genetic data from heterogeneous sources to physicians and patients. The eMERGE III Network enrolled >25,000 participants from biobank and prospective cohorts of predominantly healthy individuals for clinical genetic testing to determine clinically actionable findings. The network developed protocols linking together the 11 participant collection sites and 2 clinical genetic testing laboratories. DNA capture panels targeting 109 genes were used for testing of DNA and sample collection, data generation, interpretation, reporting, delivery, and storage were each harmonized. A compliant and secure network enabled ongoing review and reconciliation of clinical interpretations, while maintaining communication and data sharing between clinicians and investigators. A total of 202 individuals had positive diagnostic findings relevant to the indication for testing and 1,294 had additional/secondary findings of medical significance deemed to be returnable, establishing data return rates for other testing endeavors. This study accomplished integration of structured genomic results into multiple electronic health record (EHR) systems, setting the stage for clinical decision support to enable genomic medicine. Further, the established processes enable different sequencing sites to harmonize technical and interpretive aspects of sequencing tests, a critical achievement toward global standardization of genomic testing. The eMERGE protocols and tools are available for widespread dissemination.

Coronary artery disease (CAD) is a leading cause of death, yet its genetic determinants are not fully elucidated. We report a multi-ethnic genome-wide association study of CAD involving nearly a quarter of a million cases, incorporating the largest cohorts to date of Whites, Blacks, and Hispanics from the Million Veteran Program with existing studies including CARDIoGRAMplusC4D, UK Biobank, and Biobank Japan. We verify substantial and nearly equivalent heritability of CAD across multiple ancestral groups, discover 107 novel loci including the first nine on the X-chromosome, identify the first eight genome-wide significant loci among Blacks and Hispanics, and demonstrate that two common haplotypes are largely responsible for the risk stratification at the well-known 9p21 locus in most populations except those of African origin where both haplotypes are virtually absent. We identify 15 loci for angiographically derived burden of coronary atherosclerosis, which robustly overlap with the strongest and earliest loci reported to date for clinical CAD. Phenome-wide association analyses of novel loci and externally validated polygenic risk scores (PRS) augment signals from the insulin resistance cluster of risk factors and consequences, extend previously established pleiotropic associations of loci with traditional risk factors to include smoking and family history, and confirm a substantially reduced transferability of existing PRS to Blacks. Downstream integrative genomic analyses reinforce the critical role of endothelial, fibroblast, and smooth muscle cells within the coronary vessel wall in CAD susceptibility. Our study highlights the value of a multi-ethnic design in efficiently characterizing the genetic architecture of CAD across all human populations.

Introduction: Several clinical trials evaluating the efficacy of a carotid revascularization procedure excluded patients above age 80. In the current study, we sought to assess the differences in characteristics of octogenarians undergoing carotid endarterectomy (CEA) and carotid artery stenting (CAS) for carotid stenosis using “real-world” data from a national surgical quality registry. Methods: The National Surgical Quality Improvement Program (NSQIP) targeted datasets for CEA and CAS were queried for patients aged ≥80 years between 2012-2018. Results: We identified 5,814 patients undergoing CEA and 189 patients undergoing CAS. Patients in the CAS group were more likely to be ≥90 years (p=0.004), diabetic (p=0.04), had a history of CHF (p=0.012) and a bleeding-disorder (p80%-100%) of the ipsilateral carotid, while 13(14.5%) in the CAS group and 302 (11%) in the CEA group had severe or total stenosis of contralateral carotid. Among symptomatic patients, 58(61.7%) in the CAS group and 1527 (57.5%) in the CEA group were found to have severe/total stenosis of the ipsilateral-carotid, while 12(12.8%) in the CAS group and 208(7.8%) in the CEA group were found to have severe/total occlusion of the contralateral carotid. In the carotid endarterectomy group, 12.2% (n=711) underwent CEA-alone, 44.3% (n=2,575) CEA with angioplasty, 29.9% (n=1,737) CEA with angioplasty and shunt, 2.9% (n=166) CEA with shunt and 10.7%(n=166) eversion CEA. In the CAS group, 52.4%(n=99) underwent CAS with a single tapered stent, 29.1%(n=55) CAS with single tapered stent with CPD, 11.1%(n=21) single straight stent with CPD and 1.6%(n=3) a single straight stent alone. Conclusion: These analyses from real-world data show that there may be some differences in demographic and comorbid characteristics between octogenarians undergoing CAS and CEA.

Introduction: Due to their exclusion from most clinical trials, outcomes of carotid revascularization via a carotid endarterectomy (CEA) or carotid artery stenting (CAS) among octogenarians are not well studied. Herein, we present analysis of thirty-day stroke and mortality of patients aged ≥ 80 using real-world data from a national surgical quality registry. Methods: The National Surgical Quality Improvement Program (NSQIP) targeted dataset for CEA and CAS was queried for patients aged ≥ 80 undergoing CEA and CAS between 2012-2018. Results: A total of 94 and 2,656 patients aged ≥ 80 with symptomatic carotid stenosis undergoing CAS and CEA (respectively) were identified. Patients in the CAS group were more likely to be over 90 (p=0.006). Patients in the CAS group were more likely to have high-risk anatomy (p Conclusion: Real world analysis from a surgical quality registry show that both CAS and CEA are associated with optimal 30-day outcomes among octogenarians with symptomatic carotid stenosis.

Accurate colorectal cancer (CRC) risk prediction models are critical for identifying individuals at low and high risk of developing CRC, as they can then be offered targeted screening and interventions to address their risks of developing disease (if they are in a high-risk group) and avoid unnecessary screening and interventions (if they are in a low-risk group). As it is likely that thousands of genetic variants contribute to CRC risk, it is clinically important to investigate whether these genetic variants can be used jointly for CRC risk prediction. In this paper, we derived and compared different approaches to generating predictive polygenic risk scores (PRS) from genome-wide association studies (GWASs) including 55,105 CRC-affected case subjects and 65,079 control subjects of European ancestry. We built the PRS in three ways, using (1) 140 previously identified and validated CRC loci; (2) SNP selection based on linkage disequilibrium (LD) clumping followed by machine-learning approaches; and (3) LDpred, a Bayesian approach for genome-wide risk prediction. We tested the PRS in an independent cohort of 101,987 individuals with 1,699 CRC-affected case subjects. The discriminatory accuracy, calculated by the age- and sex-adjusted area under the receiver operating characteristics curve (AUC), was highest for the LDpred-derived PRS (AUC = 0.654) including nearly 1.2 M genetic variants (the proportion of causal genetic variants for CRC assumed to be 0.003), whereas the PRS of the 140 known variants identified from GWASs had the lowest AUC (AUC = 0.629). Based on the LDpred-derived PRS, we are able to identify 30% of individuals without a family history as having risk for CRC similar to those with a family history of CRC, whereas the PRS based on known GWAS variants identified only top 10% as having a similar relative risk. About 90% of these individuals have no family history and would have been considered average risk under current screening guidelines, but might benefit from earlier screening. The developed PRS offers a way for risk-stratified CRC screening and other targeted interventions.