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Abstract Preeclampsia, a pregnancy complication characterized by hypertension after 20 gestational weeks, is a major cause of maternal and neonatal morbidity and mortality. Mechanisms leading to preeclampsia are unclear; however, there is evidence of high heritability. We evaluated the association of polygenic scores (PGS) for blood pressure traits and preeclampsia to assess whether there is shared genetic architecture. Non-Hispanic Black and White reproductive age females with pregnancy indications and genotypes were obtained from Vanderbilt University’s BioVU, Electronic Medical Records and Genomics network, and Penn Medicine Biobank. Preeclampsia was defined by ICD codes. Summary statistics for diastolic blood pressure (DBP), systolic blood pressure (SBP), and pulse pressure (PP) PGS were acquired from Giri et al. Associations between preeclampsia and each PGS were evaluated separately by race and data source before subsequent meta-analysis. Ten-fold cross validation was used for prediction modeling. In 3504 Black and 5009 White included individuals, the rate of preeclampsia was 15.49%. In cross-ancestry meta-analysis, all PGSs 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). Addition of PGSs to clinical prediction models did not improve predictive performance. Genetic factors contributing to blood pressure regulation in the general population also predispose to preeclampsia.

Precision medicine, which among other aspects includes an individual's genomic data in diagnosis and management, has become the standard‐of‐care for Mendelian cardiovascular disease (CVD). However, early identification and management of asymptomatic patients with potentially lethal and manageable Mendelian CVD through screening, which is the promise of precision health, remains an unsolved challenge. The reduced costs of genomic sequencing have enabled the creation of biobanks containing in‐depth genetic and health information, which have facilitated the understanding of genetic variation, penetrance, and expressivity, moving us closer to the genotype‐first screening of asymptomatic individuals for Mendelian CVD. This approach could transform health care by diagnostic refinement and facilitating prevention or therapeutic interventions. Yet, potential benefits must be weighed against the potential risks, which include evolving variant pathogenicity assertion or identification of variants with low disease penetrance; costly, stressful, and inappropriate diagnostic evaluations; negative psychological impact; disqualification for employment or of competitive sports; and denial of insurance. Furthermore, the natural history of Mendelian CVD is often unpredictable, making identification of those who will benefit from preventive measures a priority. Currently, there is insufficient evidence that population‐based genetic screening for Mendelian CVD can reduce adverse outcomes at a reasonable cost to an extent that outweighs the harms of true‐positive and false‐positive results. Besides technical, clinical, and financial burdens, ethical and legal aspects pose unprecedented challenges. This review highlights key developments in the field of genotype‐first approaches to Mendelian CVD and summarizes challenges with potential solutions that can pave the way for implementing this approach for clinical care.

Abstract Polygenic variation unrelated to disease contributes to interindividual variation in baseline white blood cell (WBC) counts, but its clinical significance is uncharacterized. We investigated the clinical consequences of a genetic predisposition toward lower WBC counts among 89,559 biobank participants from tertiary care centers using a polygenic score for WBC count (PGSWBC) comprising single nucleotide polymorphisms not associated with disease. A predisposition to lower WBC counts was associated with a decreased risk of identifying pathology on a bone marrow biopsy performed for a low WBC count (odds-ratio = 0.55 per standard deviation increase in PGSWBC [95%CI, 0.30−0.94], p = 0.04), an increased risk of leukopenia (a low WBC count) when treated with a chemotherapeutic (n = 1724, hazard ratio [HR] = 0.78 [0.69−0.88], p = 4.0 × 10−5) or immunosuppressant (n = 354, HR = 0.61 [0.38–0.99], p = 0.04). A predisposition to benign lower WBC counts was associated with an increased risk of discontinuing azathioprine treatment (n = 1,466, HR = 0.62 [0.44−0.87], p = 0.006). Collectively, these findings suggest that there are genetically predisposed individuals who are susceptible to escalations or alterations in clinical care that may be harmful or of little benefit.

Abstract Severe hypercholesterolemia/possible familial hypercholesterolemia (FH) is relatively common but underdiagnosed and undertreated. We investigated whether implementing clinical decision support (CDS) was associated with lower low-density lipoprotein cholesterol (LDL-C) in patients with severe hypercholesterolemia/possible FH (LDL-C ≥ 190 mg/dL). As part of a pre-post implementation study, a CDS alert was deployed in the electronic health record (EHR) in a large health system comprising 3 main sites, 16 hospitals and 53 clinics. Data were collected for 3 months before (‘silent mode’) and after (‘active mode’) its implementation. Clinicians were only able to view the alert in the EHR during active mode. We matched individuals 1:1 in both modes, based on age, sex, and baseline lipid lowering therapy (LLT). The primary outcome was difference in LDL-C between the two groups and the secondary outcome was initiation/intensification of LLT after alert trigger. We identified 800 matched patients in each mode (mean ± SD age 56.1 ± 11.8 y vs. 55.9 ± 11.8 y; 36.0% male in both groups; mean ± SD initial LDL-C 211.3 ± 27.4 mg/dL vs. 209.8 ± 23.9 mg/dL; 11.2% on LLT at baseline in each group). LDL-C levels were 6.6 mg/dL lower (95% CI, −10.7 to −2.5; P = 0.002) in active vs. silent mode. The odds of high-intensity statin use (OR, 1.78; 95% CI, 1.41–2.23; P

Abstract 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.

Abstract Clostridioides difficile (C. diff.) infection (CDI) is a leading cause of hospital acquired diarrhea in North America and Europe and a major cause of morbidity and mortality. Known risk factors do not fully explain CDI susceptibility, and genetic susceptibility is suggested by the fact that some patients with colons that are colonized with C. diff. do not develop any infection while others develop severe or recurrent infections. To identify common genetic variants associated with CDI, we performed a genome-wide association analysis in 19,861 participants (1349 cases; 18,512 controls) from the Electronic Medical Records and Genomics (eMERGE) Network. Using logistic regression, we found strong evidence for genetic variation in the DRB locus of the MHC (HLA) II region that predisposes individuals to CDI (P > 1.0 × 10–14; OR 1.56). Altered transcriptional regulation in the HLA region may play a role in conferring susceptibility to this opportunistic enteric pathogen.

Abstract Genes act in concert with each other in specific contexts to perform their functions. Determining how these genes influence complex traits requires a mechanistic understanding of expression regulation across different conditions. It has been shown that this insight is critical for developing new therapies. Transcriptome-wide association studies have helped uncover the role of individual genes in disease-relevant mechanisms. However, modern models of the architecture of complex traits predict that gene-gene interactions play a crucial role in disease origin and progression. Here we introduce PhenoPLIER, a computational approach that maps gene-trait associations and pharmacological perturbation data into a common latent representation for a joint analysis. This representation is based on modules of genes with similar expression patterns across the same conditions. We observe that diseases are significantly associated with gene modules expressed in relevant cell types, and our approach is accurate in predicting known drug-disease pairs and inferring mechanisms of action. Furthermore, using a CRISPR screen to analyze lipid regulation, we find that functionally important players lack associations but are prioritized in trait-associated modules by PhenoPLIER. By incorporating groups of co-expressed genes, PhenoPLIER can contextualize genetic associations and reveal potential targets missed by single-gene strategies.

Summary: Ebstein’s anomaly, a rare congenital heart disease, is distinguished by the failure of embryological delamination of the tricuspid valve leaflets from the underlying primitive right ventricle myocardium. Gaining insight into the genetic basis of Ebstein’s anomaly allows a more precise definition of its pathogenesis. In this study, two distinct cohorts from the Chinese Han population were included: a case-control cohort consisting of 82 unrelated cases and 125 controls without cardiac phenotypes and a trio cohort comprising 36 parent-offspring trios. Whole-exome sequencing data from all 315 participants were utilized to identify qualifying variants, encompassing rare (minor allele frequency

The complex structure and function of low density lipoprotein receptor (LDLR) makes classification of protein-coding missense variants challenging. Deep generative models, including Evolutionary model of Variant Effect (EVE), Evolutionary Scale Modeling (ESM), and AlphaFold 2 (AF2), have enabled significant progress in the prediction of protein structure and function. ESM and EVE directly estimate the likelihood of a variant sequence but are purely data-driven and challenging to interpret. AF2 predicts LDLR structures, but variant effects are explicitly modeled by estimating changes in stability. We tested the effectiveness of these models for predicting variant pathogenicity compared to established methods. AF2 produced two distinct conformations based on a novel hinge mechanism. Within ESM’s hidden space, benign and pathogenic variants had different distributions. In EVE, these distributions were similar. EVE and ESM were comparable to Polyphen-2, SIFT, REVEL, and Primate AI for predicting binary classifications in ClinVar. However, they were more strongly correlated with experimental measures of LDL uptake. AF2 poorly performed in these tasks. Using the UK Biobank to compare association with clinical phenotypes, ESM and EVE were more strongly associated with serum LDL-C than Polyphen-2. ESM was able to identify variants with more extreme LDL-C levels than EVE and had a significantly stronger association with atherosclerotic cardiovascular disease. In conclusion, AF2 predicted LDLR structures do not accurately model variant pathogenicity. ESM and EVE are competitive with prior scoring methods for prediction based on binary classifications in ClinVar but are superior based on correlations with experimental assays and clinical phenotypes.

Summary: Ebstein’s anomaly is a rare congenital heart disease characterized by tricuspid valve downward displacement and is associated with additional cardiac phenotypes such as left ventricle non-compaction. The genetic basis of Ebstein’s anomaly has yet to be fully elucidated, although several genes (e.g., NKX2-5, MYH7, TPM1, and FLNA) may contribute to Ebstein’s anomaly. Here, in two Ebstein’s anomaly families (a three-generation family and a trio), we identified independent heterozygous nonsense variants in laminin subunit 3 α (LAMA3), cosegregated with phenotypes in families with reduced penetrance. Furthermore, knocking out Lama3 in mice revealed that haploinsufficiency of Lama3 led to Ebstein’s malformation of the tricuspid valve and an abnormal basement membrane structure. In conclusion, we identified a novel gene-disease association of LAMA3 implicated in Ebstein’s anomaly, and the findings extended our understanding of the role of the extracellular matrix in Ebstein’s anomaly etiology.

Abstract The electronic Medical Records and Genomics (eMERGE) Network assessed the feasibility of deploying portable phenotype rule-based algorithms with natural language processing (NLP) components added to improve performance of existing algorithms using electronic health records (EHRs). Based on scientific merit and predicted difficulty, eMERGE selected six existing phenotypes to enhance with NLP. We assessed performance, portability, and ease of use. We summarized lessons learned by: (1) challenges; (2) best practices to address challenges based on existing evidence and/or eMERGE experience; and (3) opportunities for future research. Adding NLP resulted in improved, or the same, precision and/or recall for all but one algorithm. Portability, phenotyping workflow/process, and technology were major themes. With NLP, development and validation took longer. Besides portability of NLP technology and algorithm replicability, factors to ensure success include privacy protection, technical infrastructure setup, intellectual property agreement, and efficient communication. Workflow improvements can improve communication and reduce implementation time. NLP performance varied mainly due to clinical document heterogeneity; therefore, we suggest using semi-structured notes, comprehensive documentation, and customization options. NLP portability is possible with improved phenotype algorithm performance, but careful planning and architecture of the algorithms is essential to support local customizations.

Abstract Background Genetic variants within nearly 1000 loci are known to contribute to modulation of blood lipid levels. However, the biological pathways underlying these associations are frequently unknown, limiting understanding of these findings and hindering downstream translational efforts such as drug target discovery. Results To expand our understanding of the underlying biological pathways and mechanisms controlling blood lipid levels, we leverage a large multi-ancestry meta-analysis (N = 1,654,960) of blood lipids to prioritize putative causal genes for 2286 lipid associations using six gene prediction approaches. Using phenome-wide association (PheWAS) scans, we identify relationships of genetically predicted lipid levels to other diseases and conditions. We confirm known pleiotropic associations with cardiovascular phenotypes and determine novel associations, notably with cholelithiasis risk. We perform sex-stratified GWAS meta-analysis of lipid levels and show that 3–5% of autosomal lipid-associated loci demonstrate sex-biased effects. Finally, we report 21 novel lipid loci identified on the X chromosome. Many of the sex-biased autosomal and X chromosome lipid loci show pleiotropic associations with sex hormones, emphasizing the role of hormone regulation in lipid metabolism. Conclusions Taken together, our findings provide insights into the biological mechanisms through which associated variants lead to altered lipid levels and potentially cardiovascular disease risk.

Summary: Background: Arterial stiffening is central to the vascular ageing process and a powerful predictor and cause of diverse vascular pathologies and mortality. We investigated age and sex trajectories, regional differences, and global reference values of arterial stiffness as assessed by pulse wave velocity (PWV). Methods: Measurements of brachial-ankle or carotid-femoral PWV (baPWV or cfPWV) in generally healthy participants published in three electronic databases between database inception and August 24th, 2020 were included, either as individual participant-level or summary data received from collaborators (n = 248,196) or by extraction from published reports (n = 274,629). Quality was appraised using the Joanna Briggs Instrument. Variation in PWV was estimated using mixed-effects meta-regression and Generalized Additive Models for Location, Scale, and Shape. Findings: The search yielded 8920 studies, and 167 studies with 509,743 participants from 34 countries were included. PWV depended on age, sex, and country. Global age-standardised means were 12.5 m/s (95% confidence interval: 12.1–12.8 m/s) for baPWV and 7.45 m/s (95% CI: 7.11–7.79 m/s) for cfPWV. Males had higher global levels than females of 0.77 m/s for baPWV (95% CI: 0.75–0.78 m/s) and 0.35 m/s for cfPWV (95% CI: 0.33–0.37 m/s), but sex differences in baPWV diminished with advancing age. Compared to Europe, baPWV was substantially higher in the Asian region (+1.83 m/s, P = 0.0014), whereas cfPWV was higher in the African region (+0.41 m/s, P

Abstract Background Type 2 diabetes (T2D) is a worldwide scourge caused by both genetic and environmental risk factors that disproportionately afflicts communities of color. Leveraging existing large-scale genome-wide association studies (GWAS), polygenic risk scores (PRS) have shown promise to complement established clinical risk factors and intervention paradigms, and improve early diagnosis and prevention of T2D. However, to date, T2D PRS have been most widely developed and validated in individuals of European descent. Comprehensive assessment of T2D PRS in non-European populations is critical for equitable deployment of PRS to clinical practice that benefits global populations. Methods We integrated T2D GWAS in European, African, and East Asian populations to construct a trans-ancestry T2D PRS using a newly developed Bayesian polygenic modeling method, and assessed the prediction accuracy of the PRS in the multi-ethnic Electronic Medical Records and Genomics (eMERGE) study (11,945 cases; 57,694 controls), four Black cohorts (5137 cases; 9657 controls), and the Taiwan Biobank (4570 cases; 84,996 controls). We additionally evaluated a post hoc ancestry adjustment method that can express the polygenic risk on the same scale across ancestrally diverse individuals and facilitate the clinical implementation of the PRS in prospective cohorts. Results The trans-ancestry PRS was significantly associated with T2D status across the ancestral groups examined. The top 2% of the PRS distribution can identify individuals with an approximately 2.5–4.5-fold of increase in T2D risk, which corresponds to the increased risk of T2D for first-degree relatives. The post hoc ancestry adjustment method eliminated major distributional differences in the PRS across ancestries without compromising its predictive performance. Conclusions By integrating T2D GWAS from multiple populations, we developed and validated a trans-ancestry PRS, and demonstrated its potential as a meaningful index of risk among diverse patients in clinical settings. Our efforts represent the first step towards the implementation of the T2D PRS into routine healthcare.

Abstract Introduction Currently, one of the commonly used methods for disseminating electronic health record (EHR)-based phenotype algorithms is providing a narrative description of the algorithm logic, often accompanied by flowcharts. A challenge with this mode of dissemination is the potential for under-specification in the algorithm definition, which leads to ambiguity and vagueness. Methods This study examines incidents of under-specification that occurred during the implementation of 34 narrative phenotyping algorithms in the electronic Medical Record and Genomics (eMERGE) network. We reviewed the online communication history between algorithm developers and implementers within the Phenotype Knowledge Base (PheKB) platform, where questions could be raised and answered regarding the intended implementation of a phenotype algorithm. Results We developed a taxonomy of under-specification categories via an iterative review process between two groups of annotators. Under-specifications that lead to ambiguity and vagueness were consistently found across narrative phenotype algorithms developed by all involved eMERGE sites. Discussion and conclusion Our findings highlight that under-specification is an impediment to the accuracy and efficiency of the implementation of current narrative phenotyping algorithms, and we propose approaches for mitigating these issues and improved methods for disseminating EHR phenotyping algorithms.

Background: Polygenic risk testing examines variation across multiple genes to estimate a risk score for a particular disease, including risk scores for many common, chronic health conditions. Although polygenic risk information (PRI) may be a promising tool for enhancing preventive counseling and facilitating early identification of disease, its potential impact on primary-care encounters and disease prevention efforts has not been well characterized. Methods: We conducted in-depth, semi-structured interviews of patients to assess their understandings of PRI and their beliefs about its relevance to disease prevention. Results: We completed interviews with 19 participants. Participants described enthusiasm for the generation of PRI and recognized its utility for disease prevention. Participants also described the value of PRI as limited if not corroborated by non-genetic risk factors. Finally, participants noted that PRI, by itself, would be insufficient as a trigger for initiating many preventive interventions. Conclusion: PRI has the potential to become an important tool in primary care. However, patient views about PRI as well as the complexities of disease prevention in the primary care context may limit the impact of PRI on disease prevention.

Background: Contemporary prevalence, awareness, and control of severe hypercholesterolemia (SH) and familial hypercholesterolemia (FH) and the associated atherosclerotic cardiovascular disease risk in the US are unknown. Method: Using electronic health records, we assessed the burden of SH and FH in Olmsted County, Minnesota, US, between 2004 and 2015. We defined SH as low-density lipoprotein cholesterol (LDL-C) level ≥190 mg/dl without secondary causes of hypercholesterolemia and FH as a Dutch Lipid Clinic Network score ≥6. Controls were age- and sex-matched individuals with LDL-C level

Fibromuscular dysplasia is a cardiovascular disease affecting mostly women with a mostly unknown genetic basis. Here the authors have performed a genome-wide association meta-analysis of Fibromuscular dysplasia to identify genetic loci, some of which are shared with common cardiovascular disease and traits.

Abstract Labeling clinical data from electronic health records (EHR) in health systems requires extensive knowledge of human expert, and painstaking review by clinicians. Furthermore, existing phenotyping algorithms are not uniformly applied across large datasets and can suffer from inconsistencies in case definitions across different algorithms. We describe here quantitative disease risk scores based on almost unsupervised methods that require minimal input from clinicians, can be applied to large datasets, and alleviate some of the main weaknesses of existing phenotyping algorithms. We show applications to phenotypic data on approximately 100,000 individuals in eMERGE, and focus on several complex diseases, including Chronic Kidney Disease, Coronary Artery Disease, Type 2 Diabetes, Heart Failure, and a few others. We demonstrate that relative to existing approaches, the proposed methods have higher prediction accuracy, can better identify phenotypic features relevant to the disease under consideration, can perform better at clinical risk stratification, and can identify undiagnosed cases based on phenotypic features available in the EHR. Using genetic data from the eMERGE-seq panel that includes sequencing data for 109 genes on 21,363 individuals from multiple ethnicities, we also show how the new quantitative disease risk scores help improve the power of genetic association studies relative to the standard use of disease phenotypes. The results demonstrate the effectiveness of quantitative disease risk scores derived from rich phenotypic EHR databases to provide a more meaningful characterization of clinical risk for diseases of interest beyond the prevalent binary (case-control) classification.

Abstract 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.

Objective: To evaluate usability of a quality improvement tool that promotes guideline-based care for patients with peripheral arterial disease (PAD). Patients and Methods: The study was conducted from July 19, 2018, to August 21, 2019. We compared the usability of a PAD cohort knowledge solution (CKS) with standard management supported by an electronic health record (EHR). Two scenarios were developed for usability evaluation; the first for the PAD-CKS while the second evaluated standard EHR workflow. Providers were asked to provide opinions about the PAD-CKS tool and to generate a System Usability Scale (SUS) score. Metrics analyzed included time required, number of mouse clicks, and number of keystrokes. Results: Usability evaluations were completed by 11 providers. SUS for the PAD-CKS was excellent at 89.6. Time required to complete 21 tasks in the CKS was 4 minutes compared with 12 minutes for standard EHR workflow (median, P = .002). Completion of CKS tasks required 34 clicks compared with 148 clicks for the EHR (median, P = .002). Keystrokes for CKS task completion was 8 compared with 72 for EHR (median, P = .004). Providers indicated that overall they found the tool easy to use and the PAD mortality risk score useful. Conclusions: Usability evaluation of the PAD-CKS tool demonstrated time savings, a high SUS score, and a reduction of mouse clicks and keystrokes for task completion compared to standard workflow using the EHR. Provider feedback regarding the strengths and weaknesses also created opportunities for iterative improvement of the PAD-CKS tool.

Abstract Background Elevated triglycerides (TG) are associated with, and may be causal for, cardiovascular disease (CVD), and co-morbidities such as type II diabetes and metabolic syndrome. Pathogenic variants in APOA5 and APOC3 as well as risk SNVs in other genes [APOE (rs429358, rs7412), APOA1/C3/A4/A5 gene cluster (rs964184), INSR (rs7248104), CETP (rs7205804), GCKR (rs1260326)] have been shown to affect TG levels. Knowledge of genetic causes for elevated TG may lead to early intervention and targeted treatment for CVD. We previously identified linkage and association of a rare, highly conserved missense variant in SLC25A40, rs762174003, with hypertriglyceridemia (HTG) in a single large family, and replicated this association with rare, highly conserved missense variants in a European American and African American sample. Methods Here, we analyzed a longitudinal mixed-ancestry cohort (European, African and Asian ancestry, N = 8966) from the Electronic Medical Record and Genomics (eMERGE) Network. We tested associations between median TG and the genes of interest, using linear regression, adjusting for sex, median age, median BMI, and the first two principal components of ancestry. Results We replicated the association between TG and APOC3, APOA5, and risk variation at APOE, APOA1/C3/A4/A5 gene cluster, and GCKR. We failed to replicate the association between rare, highly conserved variation at SLC25A40 and TG, as well as for risk variation at INSR and CETP. Conclusions Analysis using data from electronic health records presents challenges that need to be overcome. Although large amounts of genotype data is becoming increasingly accessible, usable phenotype data can be challenging to obtain. We were able to replicate known, strong associations, but were unable to replicate moderate associations due to the limited sample size and missing drug information.

A significant proportion of patients with elevated LDL and a clinical presentation of familial hypercholesterolemia do not carry known genetic mutations associated with hypercholesterolemia, such as defects in the LDL receptor. To identify new genes involved in the cellular uptake of LDL, we developed a novel whole-genome clustered regularly interspaced short palindromic repeat-Cas9 KO screen in HepG2 cells. We identified transgelin (TAGLN), an actin-binding protein, as a potentially new gene involved in LDL endocytosis. In silico validation demonstrated that genetically predicted differences in expression of TAGLN in human populations were significantly associated with elevated plasma lipids (triglycerides, total cholesterol, and LDL-C) in the Global Lipids Genetics Consortium and lipid-related phenotypes in the UK Biobank. In biochemical studies, TAGLN-KO HepG2 cells showed a reduction in cellular LDL uptake, as measured by flow cytometry. In confocal microscopy imaging, TAGLN-KO cells had disrupted actin filaments as well as an accumulation of LDL receptor on their surface because of decreased receptor internalization. Furthermore, TAGLN-KO cells exhibited a reduction in total and free cholesterol content, activation of SREBP2, and a compensatory increase in cholesterol biosynthesis. TAGLN deficiency also disrupted the uptake of VLDL and transferrin, other known cargoes for receptors that depend upon clathrin-mediated endocytosis. Our data suggest that TAGLN is a novel factor involved in the actin-dependent phase of clathrin-mediated endocytosis of LDL. The identification of novel genes involved in the endocytic uptake of LDL may improve the diagnosis of hypercholesterolemia and provide future therapeutic targets for the prevention of cardiovascular disease.

Objective There is no coordinated cascade testing program for familial hypercholesterolemia (FH) in the U.S. We evaluated the contemporary cost-effectiveness of cascade genetic testing relatives of FH probands with a pathogenic variant. Methods: A simulation model was created to simulate multiple family trees starting with progenitor individuals carrying a pathogenic variant for FH who were followed through several generations. This approach allowed us to examine a family tree that had grown sufficiently to have large numbers of relatives across multiple degrees of relatedness. The model estimated costs and life years gained (LYG) when cascade genetic testing was implemented for relatives of FH probands identified through standard care who were at or older than designated age thresholds (5, 10, 15, 20, 25, 30, 35, 40). Costs were valued in 2018 U.S. dollars. Future costs and LYG projected by the model were discounted at an annual rate of 3%. Results: For 1st degree relatives, cascade testing at every age threshold resulted in a positive number of average LYG per person, though this number decreased as testing was started at higher age thresholds. Testing was not cost-effective if initiated at an age threshold of 40 and older but was cost-effective at younger age thresholds, with a discounted cost per LYG per person of less than $50,000. For 2nd degree relatives, testing was cost-effective with a screening age threshold of 10 but no longer cost-effective at a threshold of 15 or higher. In more distant relatives, cascade genetic testing was not beneficial or cost-effective. Conclusions: Based on our simulation model, cascade genetic testing for FH in the U.S. is cost-effective if started before age 40 in 1st degree relatives and before age 15 in 2nd degree relatives.

The purpose of the study was to determine which out-of-office BP measurement modality has the best correlation with central aortic systolic BP, arterial stiffness (a determinant of central aortic pressure) and LV mass index (LVMI) which represents LV adaptation to elevated central aortic pressures. In this prospective study, we demonstrated that 24h ambulatory systolic BP has better correlation with central aortic systolic BP (arterial load) and LVMI as compared to home systolic BP. 24h ambulatory systolic BP also correlated with arterial stiffness (determinant of arterial load), although this correlation was comparable to that observed with home systolic BP. Collectively, these results suggest that ambulatory systolic BP provides the best approximation of arterial load, which is the underpinning hemodynamic stress leading to LV remodeling, end-organ dysfunction, and cardiovascular mortality in patients with COA. These findings provide a foundation for further studies to determine whether titrating antihypertensive therapy based on ambulatory BP indices will slow the progression of LV remodeling and end-organ dysfunction due to hypertension, and in turn, reduce cardiovascular death in this population.

Familial hypercholesterolemia (FH) is a relatively common autosomal dominant disorder associated with a significantly increased risk of coronary heart disease (CHD). Most (~85–90%) cases are due to pathogenic variants in the LDL-receptor gene (LDLR), while the remaining are due to pathogenic variants in the apolipoprotein B (APOB) and proprotein convertase subtilisin/kexin type 9 (PCSK9) genes, though the proportion may vary depending on geographic location. Even though at least a quarter of the world's FH population lives in Southeast and East Asia, there are substantial gaps in knowledge regarding the epidemiology of FH due to low awareness, the absence of national screening programs, and limited availability of genetic testing. In this review, we discuss the most recent and relevant information available related to diagnostic criteria, prevalence, awareness, clinical characteristics, genetic epidemiology, and treatment in the FH population of Southeast and East Asia. Increasing awareness and improving the diagnosis and management of FH will reduce the burden of premature CHD in these regions of the world.

Background Hypertriglyceridemia is associated with increased risk of coronary heart disease but the association is often attributed to concomitant metabolic abnormalities. We investigated the epidemiology of primary isolated hypertriglyceridemia (PIH) and associated cardiovascular risk in a population‐based setting. Methods and Results We identified adults with at least one triglyceride level ≥500 mg/dL between 1998 and 2015 in Olmsted County, Minnesota. We also identified age‐ and sex‐matched controls with triglyceride levels

Abstract Background Non-alcoholic fatty liver disease (NAFLD) is a common chronic liver illness with a genetically heterogeneous background that can be accompanied by considerable morbidity and attendant health care costs. The pathogenesis and progression of NAFLD is complex with many unanswered questions. We conducted genome-wide association studies (GWASs) using both adult and pediatric participants from the Electronic Medical Records and Genomics (eMERGE) Network to identify novel genetic contributors to this condition. Methods First, a natural language processing (NLP) algorithm was developed, tested, and deployed at each site to identify 1106 NAFLD cases and 8571 controls and histological data from liver tissue in 235 available participants. These include 1242 pediatric participants (396 cases, 846 controls). The algorithm included billing codes, text queries, laboratory values, and medication records. Next, GWASs were performed on NAFLD cases and controls and case-only analyses using histologic scores and liver function tests adjusting for age, sex, site, ancestry, PC, and body mass index (BMI). Results Consistent with previous results, a robust association was detected for the PNPLA3 gene cluster in participants with European ancestry. At the PNPLA3-SAMM50 region, three SNPs, rs738409, rs738408, and rs3747207, showed strongest association (best SNP rs738409 p = 1.70 × 10− 20). This effect was consistent in both pediatric (p = 9.92 × 10− 6) and adult (p = 9.73 × 10− 15) cohorts. Additionally, this variant was also associated with disease severity and NAFLD Activity Score (NAS) (p = 3.94 × 10− 8, beta = 0.85). PheWAS analysis link this locus to a spectrum of liver diseases beyond NAFLD with a novel negative correlation with gout (p = 1.09 × 10− 4). We also identified novel loci for NAFLD disease severity, including one novel locus for NAS score near IL17RA (rs5748926, p = 3.80 × 10− 8), and another near ZFP90-CDH1 for fibrosis (rs698718, p = 2.74 × 10− 11). Post-GWAS and gene-based analyses identified more than 300 genes that were used for functional and pathway enrichment analyses. Conclusions In summary, this study demonstrates clear confirmation of a previously described NAFLD risk locus and several novel associations. Further collaborative studies including an ethnically diverse population with well-characterized liver histologic features of NAFLD are needed to further validate the novel findings.

We investigated electronic health record (EHR) access as an indicator of cardiovascular health promotion by patients in their social networks, by identifying individuals who viewed their coronary heart disease (CHD) risk information in the EHR and shared this information in their social networks among various spheres of influence. In a secondary analysis of the Myocardial Infarction Genes trial, Olmsted County MN residents (2013–2015; n = 203; whites, ages 45–65 years) at intermediate CHD risk were randomized to receive their conventional risk score (CRS; based on traditional risk factors) alone or also their genetic risk score (GRS; based on 28 genomic variants). We assessed self-reported and objectively quantified EHR access via a patient portal at three and six months after risk disclosure, and determined whether this differed by GRS disclosure. Data were analyzed using logistic regression and adjusted for sociodemographic characteristics, family history, and baseline CRS/GRS. Self-reported EHR access to view CHD risk information was associated with a high frequency of objectively quantified EHR access (71(10) versus 37(5) logins; P = 0.0025) and a high likelihood of encouraging others to be screened for their CHD risk (OR 2.936, CI 1.443–5.973, P = 0.0030), compared to the absence of self-reported EHR access to view CHD risk information. We thereby used EHR access trends to identify individuals who may function as disseminators of CHD risk information in social networks, compared to individuals on the periphery of their social networks who did not exhibit this behavior. Partnering with such individuals could amplify CHD health promotion.Clinical Trial Registration: Myocardial Infarction Genes (MI-GENES) Study, NCT01936675, https://clinicaltrials.gov/ct2/show/NCT01936675. Keywords: Genetics, Risk factors, Risk assessment, Behavior modification, Electronic health records, Personal health records, Patient portals, Patient engagement, Social network

Introduction: Minority communities have had limited access to advances in genomic medicine. Mayo Clinic and Mountain Park Health Center, a Federally Qualified Health Center in Phoenix, Arizona, partnered to assess the feasibility of offering genomic screening to Latino patients receiving care at a community-based health center. We examined primary care provider (PCP) experiences reporting genomic screening results and integrating those results into patient care. Methods: We conducted open-ended, semi-structured interviews with PCPs and other members of the health care team charged with supporting patients who received positive genomic screening results. Interviews were recorded, transcribed, and analyzed thematically. Results: Of the 500 patients who pursued genomic screening, 10 received results indicating a genetic variant that warranted clinical management. PCPs felt genomic screening was valuable to patients and their families, and that genomic research should strive to include underrepresented minorities. Providers identified multiple challenges integrating genomic sequencing into patient care, including difficulties maintaining patient contact over time; arranging follow-up medical care; and managing results in an environment with limited genetics expertise. Providers also reflected on the ethics of offering genomic sequencing to patients who may not be able to pursue diagnostic testing or follow-up care due to financial constraints. Conclusions: Our results highlight the potential benefits and challenges of bringing advances in precision medicine to community-based health centers serving under-resourced populations. By proactively considering patient support needs, and identifying financial assistance programs and patient-referral mechanisms to support patients who may need specialized medical care, PCPs and other health care providers can help to ensure that precision medicine lives up to its full potential as a tool for improving patient care.

Background Atherosclerosis in >1 vascular bed (ie, polyvascular disease), often a feature of peripheral artery disease (PAD), is associated with high morbidity and mortality. We sought to identify risk factors for polyvascular involvement in patients with PAD. Methods and Results We performed 2‐sample Mendelian randomization using an inverse‐variance‐weighted approach, to assess 60 exposures including size and lipid content of atherogenic lipoproteins, blood pressure, glycated hemoglobin, and smoking as causal mediators for polyvascular disease in patients with PAD. Genetic instruments for these exposures were obtained from prior genome‐wide association studies. Patients with PAD were from the Mayo Vascular Disease Biorepository, and polyvascular disease (ie, concomitant coronary heart disease, cerebrovascular disease, and/or abdominal aortic aneurysm) was ascertained by validated phenotyping algorithms. Of 3279 patients with PAD, 61% had polyvascular disease. Genetically predicted levels of the lipid content and/or particle measures of very small and small size very low‐density lipoprotein, intermediate‐density lipoprotein, and large low‐density lipoprotein were associated with polyvascular disease: odds ratios (OR) of 1.80 (95% CI, 1.23–2.61), 1.70 (95% CI, 1.17–2.61), and 1.40 (95% CI, 1.09–1.80) per 1 SD increase in genetically determined levels, respectively. Both genetically predicted diastolic and systolic blood pressure were associated with polyvascular disease; OR per 10 mm Hg genetic increase in diastolic and systolic blood pressure were 1.66 (95% CI, 1.19–2.33) and 1.31 (95% CI, 1.07–1.60), respectively. Conclusions Lifetime exposure to increased lipid content and levels of very small and small very low‐density lipoprotein, intermediate‐density lipoprotein, and large low‐density lipoprotein particles as well as elevated blood pressure are associated with polyvascular involvement in patients with PAD. Reduction in levels of such exposures may limit progression of atherosclerosis in patients with PAD.

Abstract Background A 61‐year‐old woman underwent direct to consumer genetic testing and was found to be homozygous for the C282Y HFE variant (c.845G>A :p.Cys282Tyr) which is classified as pathogenic/likely pathogenic for hereditary hemochromatosis. However, no action was taken by the individual. Methods The individual took part in the Mayo Clinic Return of Actionable Variants Empiric (RAVE) study and the actionable finding was confirmed and results disclosed in person by a genetic counselor with subsequent referral to a hepatologist. Results Further testing revealed iron overload with an elevated ferritin level (560 ng/ml) and increased ferritin saturation (74%). Phlebotomy was initiated with subsequent normalization of the ferritin levels (252 ng/ml). Conclusion This case highlights that actionable genetic results may not be acted on after direct to consumer testing and the need for effective genetic counseling after such testing.

Biomarker identification requires prohibitively large cohorts with gene expression and phenotype data. The approach introduced here learns polygenic predictors of expression from genetic and expression data, used to infer biomarker levels in patients with genetic and disease information.

Objective: To develop clinical decision support (CDS) for familial hypercholesterolemia (FH), based on physician input obtained by a mixed methods approach. Introduction: Awareness, detection, and control of FH—a relatively common genetic disorder—is low. Clinical decision support could address knowledge gaps and provide point-of-care guidance for the management of FH. Methods: A 16-question survey that assessed familiarity with FH and sought input on potential content of the CDS tool was emailed to 1161 clinicians including 208 cardiologists. In addition, 4 physician focus groups were held to gather input on the structure and form of the CDS tool. This study took place between September 12, 2016, and January 16, 2017. Results: The response rate to the survey was 18.1%. Clinicians were overwhelmingly (97.6%) in favor of a CDS tool that assists in managing patients with FH at the point of care and this was confirmed in the focus group discussions. Key themes emerged during the focus groups including providers' knowledge and understanding of FH, facilitators and barriers to implementing a CDS tool, and suggestions for its design and content. Conclusion: Clinicians were supportive of development of a CDS tool to assist with the evaluation and treatment of FH and provided feedback related to the design and implementation of such a tool.

Objective: To quantify compliance with guideline recommendations for secondary prevention in peripheral artery disease (PAD) using natural language processing (NLP) tools deployed to an electronic health record (EHR) and investigate provider opinions regarding clinical decision support (CDS) to promote improved implementation of these strategies. Patients and Methods: Natural language processing was used for automated identification of moderate to severe PAD cases from narrative clinical notes of an EHR of patients seen in consultation from May 13, 2015, to July 27, 2015. Guideline-recommended strategies assessed within 6 months of PAD diagnosis included therapy with statins, antiplatelet agents, angiotensin-converting enzyme inhibitors or angiotensin receptor blockers, and smoking abstention. Subsequently, a provider survey was used to assess provider knowledge regarding PAD clinical practice guidelines, comfort in recommending secondary prevention strategies, and potential role for CDS. Results: Among 73 moderate to severe PAD cases identified by NLP, only 12 (16%) were on 4 guideline-recommended strategies. A total of 207 of 760 (27%) providers responded to the survey; of these 141 (68%) were generalists and 66 (32%) were specialists. Although 183 providers (88%) managed patients with PAD, 51 (25%) indicated they were uncomfortable doing so; 138 providers (67%) favored the development of a CDS system tailored for their practice and 146 (71%) agreed that an automated EHR-derived mortality risk score calculator for patients with PAD would be helpful. Conclusion: Natural language processing tools can identify cases from EHRs to support quality metric studies. Findings of this pilot study demonstrate gaps in application of guideline-recommended strategies for secondary risk prevention for patients with moderate to severe PAD. Providers strongly support the development of CDS systems tailored to assist them in providing evidence-based care to patients with PAD at the point of care.

Unfavorable lipid levels during childhood are associated with subsequent development of atherosclerotic cardiovascular disease. The American Academy of Pediatrics and National Heart, Lung and Blood Institute in 2011 recommended universal lipid screening for children between ages 9–11years and between ages 17–21years. The objective of the study was to determine temporal trends in lipid testing among children and young adults in a mid-western population. The Rochester Epidemiology Project database was used to identify lipid testing in ages 2–21years (n=51,176) in the Olmsted County population from January 1, 2008 through December 31, 2014. Generalized estimating equations with Poisson distribution were used to test for temporal trends in lipid testing across the age groups. There was modest increase in lipid testing in children in the age groups, 9–11years and 17–21years (1.5% in 2008 to 2.2% in 2014, P

Abstract Background The genetic etiology of human lipid quantitative traits is not fully elucidated, and interactions between variants may play a role. We performed a gene-centric interaction study for four different lipid traits: low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), total cholesterol (TC), and triglycerides (TG). Results Our analysis consisted of a discovery phase using a merged dataset of five different cohorts (n = 12,853 to n = 16,849 depending on lipid phenotype) and a replication phase with ten independent cohorts totaling up to 36,938 additional samples. Filters are often applied before interaction testing to correct for the burden of testing all pairwise interactions. We used two different filters: 1. A filter that tested only single nucleotide polymorphisms (SNPs) with a main effect of p

Uterine fibroids affect up to 77% of women by menopause and account for up to $34 billion in healthcare costs each year. Although fibroid risk is heritable, genetic risk for fibroids is not well understood. We conducted a two-stage case-control meta-analysis of genetic variants in European and African ancestry women with and without fibroids classified by a previously published algorithm requiring pelvic imaging or confirmed diagnosis. Women from seven electronic Medical Records and Genomics (eMERGE) network sites (3,704 imaging-confirmed cases and 5,591 imaging-confirmed controls) and women of African and European ancestry from UK Biobank (UKB, 5,772 cases and 61,457 controls) were included in the discovery genome-wide association study (GWAS) meta-analysis. Variants showing evidence of association in Stage I GWAS (P < 1 × 10-5) were targeted in an independent replication sample of African and European ancestry individuals from the UKB (Stage II) (12,358 cases and 138,477 controls). Logistic regression models were fit with genetic markers imputed to a 1000 Genomes reference and adjusted for principal components for each race- and site-specific dataset, followed by fixed-effects meta-analysis. Final analysis with 21,804 cases and 205,525 controls identified 326 genome-wide significant variants in 11 loci, with three novel loci at chromosome 1q24 (sentinel-SNP rs14361789; P = 4.7 × 10-8), chromosome 16q12.1 (sentinel-SNP rs4785384; P = 1.5 × 10-9) and chromosome 20q13.1 (sentinel-SNP rs6094982; P = 2.6 × 10-8). Our statistically significant findings further support previously reported loci including SNPs near WT1, TNRC6B, SYNE1, BET1L, and CDC42/WNT4. We report evidence of ancestry-specific findings for sentinel-SNP rs10917151 in the CDC42/WNT4 locus (P = 1.76 × 10-24). Ancestry-specific effect-estimates for rs10917151 were in opposite directions (P-Het-between-groups = 0.04) for predominantly African (OR = 0.84) and predominantly European women (OR = 1.16). Genetically-predicted gene expression of several genes including LUZP1 in vagina (P = 4.6 × 10-8), OBFC1 in esophageal mucosa (P = 8.7 × 10-8), NUDT13 in multiple tissues including subcutaneous adipose tissue (P = 3.3 × 10-6), and HEATR3 in skeletal muscle tissue (P = 5.8 × 10-6) were associated with fibroids. The finding for HEATR3 was supported by SNP-based summary Mendelian randomization analysis. Our study suggests that fibroid risk variants act through regulatory mechanisms affecting gene expression and are comprised of alleles that are both ancestry-specific and shared across continental ancestries.

Background Automated individualized risk prediction tools linked to electronic health records (EHRs) are not available for management of patients with peripheral arterial disease. The goal of this study was to create a prognostic tool for patients with peripheral arterial disease using data elements automatically extracted from an EHR to enable real‐time and individualized risk prediction at the point of care. Methods and Results A previously validated phenotyping algorithm was deployed to an EHR linked to the Rochester Epidemiology Project to identify peripheral arterial disease cases from Olmsted County, MN, for the years 1998 to 2011. The study cohort was composed of 1676 patients: 593 patients died over 5‐year follow‐up. The c‐statistic for survival in the overall data set was 0.76 (95% confidence interval [CI], 0.74–0.78), and the c‐statistic across 10 cross‐validation data sets was 0.75 (95% CI, 0.73–0.77). Stratification of cases demonstrated increasing mortality risk by subgroup (low: hazard ratio, 0.35 [95% CI, 0.21–0.58]; intermediate‐high: hazard ratio, 2.98 [95% CI, 2.37–3.74]; high: hazard ratio, 8.44 [95% CI, 6.66–10.70], all P

BackgroundIntracranial aneurysms (IAs), abdominal aortic aneurysms (AAAs), and thoracic aortic aneurysms (TAAs) all have a familial predisposition. Given that aneurysm types are known to co‐occur, we hypothesized that there may be shared genetic risk factors for IAs, AAAs, and TAAs. Methods and ResultsWe performed a mega‐analysis of 1000 Genomes Project‐imputed genome‐wide association study (GWAS) data of 4 previously published aneurysm cohorts: 2 IA cohorts (in total 1516 cases, 4305 controls), 1 AAA cohort (818 cases, 3004 controls), and 1 TAA cohort (760 cases, 2212 controls), and observed associations of 4 known IA, AAA, and/or TAA risk loci (9p21, 18q11, 15q21, and 2q33) with consistent effect directions in all 4 cohorts. We calculated polygenic scores based on IA‐, AAA‐, and TAA‐associated SNPs and tested these scores for association to case‐control status in the other aneurysm cohorts; this revealed no shared polygenic effects. Similarly, linkage disequilibrium–score regression analyses did not show significant correlations between any pair of aneurysm subtypes. Last, we evaluated the evidence for 14 previously published aneurysm risk single‐nucleotide polymorphisms through collaboration in extended aneurysm cohorts, with a total of 6548 cases and 16 843 controls (IA) and 4391 cases and 37 904 controls (AAA), and found nominally significant associations for IA risk locus 18q11 near RBBP8 to AAA (odds ratio [OR]=1.11; P=4.1×10−5) and for TAA risk locus 15q21 near FBN1 to AAA (OR=1.07; P=1.1×10−3). ConclusionsAlthough there was no evidence for polygenic overlap between IAs, AAAs, and TAAs, we found nominally significant effects of two established risk loci for IAs and TAAs in AAAs. These two loci will require further replication.

Genomic regions that influence LDL particle size in African Americans are not known. We performed family-based linkage analyses to identify genomic regions that influence LDL particle size and also exert pleiotropic effects on two closely related lipid traits, high density lipoprotein cholesterol (HDL-C) and triglycerides, in African Americans. Subjects (n = 1,318, 63.0 ± 9.5 years, 70% women, 79% hypertensive) were ascertained through sibships with two or more individuals diagnosed with essential hypertension before age 60. LDL particle size was measured by polyacrylamide gel electrophoresis, and triglyceride levels were log-transformed to reduce skewness. Genotypes were measured at 366 microsatellite marker loci distributed across the 22 autosomes. Univariate and bivariate linkage analyses were performed using a variance components approach. LDL particle size was highly heritable (h2 = 0.78) and significantly (P < 0.0001) genetically correlated with HDL-C (ρG = 0.32) and log triglycerides (ρG = −0.43). Significant evidence of linkage for LDL particle size was present on chromosome 19 [85.3 centimorgan (cM), log of the odds (LOD) = 3.07, P = 0.0001], and suggestive evidence of linkage was present on chromosome 12 (90.8 cM, LOD = 2.02, P = 0.0011). Bivariate linkage analyses revealed tentative evidence for a region with pleiotropic effects on LDL particle size and HDL-C on chromosome 4 (52.9 cM, LOD = 2.06, P = 0.0069). These genomic regions may contain genes that influence interindividual variation in LDL particle size and potentially coronary heart disease susceptibility in African Americans.

The electronic MEdical Records & GEnomics (eMERGE) network was established in 2007 by the National Human Genome Research Institute (NHGRI) of the National Institutes of Health (NIH) in part to explore the utility of electronic medical records (EMRs) in genome science. The initial focus was on discovery primarily using the genome-wide association paradigm, but more recently, the network has begun evaluating mechanisms to implement new genomic information couple to clinical decision support into EMRs. Herein, we describe this evolution including the development of the individual and merged eMERGE genomic datasets, the contribution the network has made towards genomic discovery and human health, and the steps taken towards the next generation genotype-phenotype association studies and clinical implementation.

The electronic Medical Records and Genomics (eMERGE) (Phase I) network was established in 2007 to further genomic discovery using biorepositories linked to the electronic health record (EHR). In Phase II, which began in 2011, genomic discovery efforts continue and in addition the network is investigating best practices for implementing genomic medicine for patient care, in particular, the return of genomic results in the EHR for use by physicians at point-of-care. To develop strategies for addressing the challenges of implementing genomic medicine in the clinical setting, the eMERGE network is conducting studies that return clinically-relevant genomic results to research participants and their health care providers. These genomic medicine pilot studies include returning individual genetic variants associated with disease susceptibility or drug response, as well as genetic risk scores for common ‘complex’ disorders. Additionally, as part of a network-wide pharmacogenomics-related project, targeted resequencing of 84 pharmacogenes is being performed and select genotypes of pharmacogenetic relevance are being placed in the EHR to guide individualized drug therapy. Individual sites within the eMERGE network are exploring mechanisms to address incidental findings generated by resequencing of the 84 pharmacogenes. In this paper, we describe studies being conducted within the eMERGE network to develop best practices for integrating genomic findings into the EHR, and the challenges associated with such work.

Although mosaic autosomal chromosomal abnormalities are being increasingly detected as part of high-density genotyping studies, the clinical correlates are unclear. From an electronic medical record (EMR)–based genome-wide association study (GWAS) of peripheral arterial disease, log-R-ratio and B-allele-frequency data were used to identify mosaic autosomal chromosomal abnormalities including copy number variation and loss of heterozygosity. The EMRs of patients with chromosomal abnormalities and those without chromosomal abnormalities were reviewed to compare clinical characteristics. Among 3336 study participants, 0.75% (n = 25, mean age = 74.8 ± 10.7 years, 64% men) had abnormal intensity plots indicative of autosomal chromosomal abnormalities. A hematologic malignancy was present in 8 patients (32%), of whom 4 also had a solid organ malignancy while 2 patients had a solid organ malignancy only. In 50 age- and sex-matched participants without chromosomal abnormalities, there was a lower rate of hematologic malignancies (2% vs 32%, P < .001) but not solid organ malignancies (20% vs 24%, P = .69). We also report the clinical characteristics of each patient with the observed chromosomal abnormalities. Interestingly, among 5 patients with 20q deletions, 4 had a myeloproliferative disorder while all 3 men in this group had prostate cancer. In summary, in a GWAS of 3336 adults, 0.75% had autosomal chromosomal abnormalities and nearly a third of them had hematologic malignancies. A potential novel association between 20q deletions, myeloproliferative disorders, and prostate cancer was also noted.