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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.

We investigated the association of daylight saving time (DST) transitions with the rates of adverse cardiovascular events in a large, US-based nationwide study. The study cohort included 36,116,951 unique individuals from deidentified administrative claims data of the OptumLabs Data Warehouse. There were 74,722 total adverse cardiovascular events during DST transition and the control weeks (2 weeks before and after) in spring and autumn of 2015-2019. We used Bayesian hierarchical Poisson regression models to estimate event rate ratios representing the ratio of composite adverse cardiovascular event rates between DST transition and control weeks. There was an average increase of 3% (95% uncertainty interval, −3% to −10%) and 4% (95% uncertainty interval, −2% to −12%) in adverse cardiovascular event rates during Monday and Friday of the spring DST transition, respectively. The probability of this being associated with a moderate-to-large increase in the event rates (estimate event rate ratio, >1.10) was estimated to be less than 6% for Monday and Friday, and less than 1% for the remaining days. During autumn DST transition, the probability of any decrease in adverse cardiovascular event rates was estimated to be less than 46% and a moderate-to-large decrease in the event rates to be less than 4% across all days. Results were similar when adjusted by age. In conclusion, spring DST transition had a suggestive association with a minor increase in adverse cardiovascular event rates but with a very low estimated probability to be of clinical importance. Our findings suggest that DST transitions are unlikely to meaningfully impact the rate of cardiovascular events.

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 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.

Heart failure is a major cause of cardiovascular morbidity and mortality. Here, the authors report results of a genome-wide association study meta-analysis, characterizing the role of common genetic variants in heart failure, finding overlap with common cardiovascular risk factors and imaging measures of cardiac structure/function.

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.

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 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.

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.

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.

Lipid levels are important markers for the development of cardio-metabolic diseases. Although hundreds of associated loci have been identified through genetic association studies, the contribution of genetic factors to variation in lipids is not fully understood, particularly in U.S. minority groups. We performed genome-wide association analyses for four lipid traits in over 45,000 ancestrally diverse participants from the Population Architecture using Genomics and Epidemiology (PAGE) Study, followed by a meta-analysis with several European ancestry studies. We identified nine novel lipid loci, five of which showed evidence of replication in independent studies. Furthermore, we discovered one novel gene in a PrediXcan analysis, minority-specific independent signals at eight previously reported loci, and potential functional variants at two known loci through fine-mapping. Systematic examination of known lipid loci revealed smaller effect estimates in African American and Hispanic ancestry populations than those in Europeans, and better performance of polygenic risk scores based on minority-specific effect estimates. Our findings provide new insight into the genetic architecture of lipid traits and highlight the importance of conducting genetic studies in diverse populations in the era of precision medicine.