Citations

Background: The Clinical Genome Resource Consortium (ClinGen) recommends MaxEntScan (MES) model to predict the effects of LDLR splice variants. We developed “MaxSpliZer”, a software tool to automate the implementation of MES, and validated it using ClinVar and UK-Biobank (UKBB) data. Method: We tested concordance of MaxSpliZer predictions with ClinVar classifications of benign/likely benign (B/LB) and pathogenic/likely pathogenic (P/LP) for LDLR variants with potential effect on splicing. We also annotated LDLR splice variants in 200,618 UKBB participants, categorizing them using MaxSpliZer as deleterious (n=90) and non-deleterious (n=7,404). Low-density lipoprotein cholesterol (LDL-C) levels were compared in these two groups after adjustment for lipid-lowering medication use. Results: MaxSpliZer prediction was concordant with the ClinVar classification in 128 of 138 P/LP variants (sensitivity 93%) and 432 of 436 B/LB variants (specificity 99%). In the UKBB, splice variants predicted as deleterious by MaxSpliZer had higher LDL-C than non-deleterious splice variants (158.7±47.4 vs. 146.0±34.8mg/dL, p-value = 0.014). Compared to manual curation time of 12±7 min per variant, MaxSpliZer took 0.52±0.11 min for single entries and 1.5 s per variant for biobank-scale data. Conclusion: MaxSpliZer, a software tool that implements MES based on the ClinGen guideline, can accurately classify LDLR splice variants in a rapid automated fashion.

Introduction: We aimed to identify and characterize carotid artery stenosis (CAS), defined as ≥40% stenosis in the internal carotid artery (ICA) or the common carotid artery (CCA), among participants of the Mayo Vascular Disease Biorepository (VDB, n = 11,814). Hypothesis: A string-based text processing (TP) tool coded in R can analyze radiology text reports to ascertain and characterize CAS. Methods: After importing a radiology report into R, it was segmented for analysis and each segment was tested for 22 unique features. The TP tool was able to i) identify stenosis in the ICA or the CCA while excluding stenosis of vertebral arteries, subclavian arteries, or external carotid arteries, ii) recognize both quantitative and qualitative descriptions of CAS, iii) interpret numerical expressions by considering the surrounding text, iv) detect negations, and v) ascertain previous revascularization procedures if mentioned in the text. We manually ascertained CAS and characterized it in 800 randomly selected radiology reports to assess the performance of the TP tool in terms of precision, recall, and F-score. Results: We retrieved 21,651 imaging reports for 6,342 unique patients including 20,461 ultrasonography reports, 812 magnetic resonance imaging reports, 357 computed tomography scan reports, and 21interventional radiology reports. The performance of TP is outlined in Table 1 . Conclusion: We demonstrate that a string-based TP tool coded in R is efficient and accurate in identifying and characterizing CAS from carotid radiology reports. The tool does not require natural language processing and could be used in a wide range of settings for genetic and biomarker studies.

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 <2% were deemed as non-carriers. VTE was ascertained using verbal interview data and diagnostic/procedural codes and defined as a composite of the following: thrombophlebitis of deep veins of lower limbs, embolism/thrombosis of vena cava, pulmonary embolism, venous thrombectomy of lower limb veins or IVC filter insertion. We implemented a nested case-control design with incidence density sampling to identify incident cases and controls matched (1:8 ratio) for sex, smoking status, and history of malignancy at baseline. Conditional logistic regression analysis adjusted for age, BMI, and genetic ancestry was performed to assess the association between CHIP and incident VTE. 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 <2% served as controls. AF was ascertained based on self-report and ICD codes. Lone AF was defined as AF in the absence of heart failure, mitral stenosis, mitral valve repair/valvotomy/replacement, and congenital heart disease. Those with AF prior to or at the time of enrollment were excluded from analyses to ascertain incident events. Cox proportional hazard models adjusted for age, sex, self-reported race/ethnicity, diabetes, hypertension, smoking, and obesity were used to identify associations between CHIP and incident AF. 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.

The Clinical Genome Resource Consortium (ClinGen) recommends MaxEntScan (MES) model to predict effects of LDLR splice variants. We developed “MaxSpliZer”, a software tool to automate implementation of MES and validated it using ClinVar and UK-Biobank (UKBB) data. We tested concordance of MaxSpliZer predictions with ClinVar classifications of pathogenicity of variants in LDLR and FBN1 with potential effect on splicing. We also annotated LDLR splice variants in 200,618 UKBB participants, categorizing them using MaxSpliZer as deleterious (n=90) and non-deleterious (n=7,404). Low-density lipoprotein cholesterol (LDL-C) levels were compared in these two groups after adjustment for lipid lowering medication use. MaxSpliZer prediction was concordant with the ClinVar classification in 96% of LDLR variants and 98% of FBN1 variants. In the UKBB, splice variants predicted as deleterious by MaxSpliZer had higher LDL-C than non-deleterious splice variants (158.7±47.4 vs. 146.0±34.8mg/dL, p-value = 0.014). Compared to manual curation time of 12±7 min per variant, MaxSpliZer took 0.52±0.11 min for single entries and 1.5 s per variant for biobank-scale data. MaxSpliZer, a software tool that implements MES based on the ClinGen guideline, can accurately classify splice variants in a rapid automated fashion.

The Clinical Genome Resource Consortium (ClinGen) recommends MaxEntScan (MES) model to predict effects of LDLR splice variants. We developed “MaxSpliZer”, a software tool to automate implementation of MES and validated it using ClinVar and UK-Biobank (UKBB) data. We tested concordance of MaxSpliZer predictions with ClinVar classifications of benign/likely benign (B/LB) and pathogenic/likely pathogenic (P/LP) for LDLR variants with potential effect on splicing. We also annotated LDLR splice variants in 200,618 UKBB participants, categorizing them using MaxSpliZer as deleterious (n=90) and non-deleterious (n=7,404). Low-density lipoprotein cholesterol (LDL-C) levels were compared in these two groups after adjustment for lipid lowering medication use. MaxSpliZer prediction was concordant with the ClinVar classification in 128 of 138 P/LP variants (sensitivity 93%) and 432 of 436 B/LB variants (specificity 99%). In the UKBB, splice variants predicted as deleterious by MaxSpliZer had higher LDL-C than non-deleterious splice variants (158.7±47.4 vs. 146.0±34.8mg/dL, p-value = 0.014). Compared to manual curation time of 12±7 min per variant, MaxSpliZer took 0.52±0.11 min for single entries and 1.5 s per variant for biobank-scale data. MaxSpliZer, a software tool that implements MES based on the ClinGen guideline, can accurately classify LDLR splice variants in a rapid automated fashion.

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 <150 mg/dL. There were 3329 individuals with elevated triglyceride levels; after excluding those with concomitant hypercholesterolemia, a secondary cause of high triglycerides, age <18 years or an incomplete record, 517 patients (49.4±14.0 years, 72.0% men) had PIH (triglyceride 627.6±183.6 mg/dL). The age‐ and sex‐adjusted prevalence of PIH in adults was 0.80% (0.72–0.87); the diagnosis was recorded in 60%, 46% were on a lipid‐lowering medication for primary prevention and a triglyceride level <150 mg/dL was achieved in 24.1%. The association of PIH with coronary heart disease was attenuated but remained significant after adjustment for demographic, socioeconomic, and conventional cardiovascular risk factors (hazard ratio [HR], 1.53; 95% CI, 1.06‐2.20; P = 0.022). There was no statistically significant association between PIH and cerebrovascular disease (HR, 1.06; 95% CI, 0.65‐1.73, P = 0.813), peripheral artery disease (HR, 1.27; 95% CI, 0.43‐3.75; P = 0.668), or the composite end point of all 3 (HR, 1.28; 95% CI, 0.92‐1.80; P =0.148) in adjusted models. Conclusions PIH was associated with incident coronary heart disease events (although there was attenuation after adjustment for conventional risk factors), supporting a causal role for triglycerides in coronary heart disease. The condition is relatively prevalent but awareness and control are low.

Introduction: Current risk equations for coronary heart disease (CHD) do not take into account family history or cumulative exposure to LDL-C. We modified CHD risk equations for use in familial hypercholesterolemia (FH) patients and developed a decision aid (DA) for FH to facilitate shared decision making (SDM). Methods: Literature review, evidence synthesis and expert input were used to adapt the 30-year Framingham Risk Score (FRS) and 10-year ACC/AHA pooled cohort equations to calculate the CHD risk in individuals with FH aged 20-39 years and ≥40 years, respectively. Based on published data, estimated risk was multiplied by 2 for family history of early CHD or 3 in the presence of a pathogenic variant. Treatment benefit of lipid lowering was estimated based on the ‘cumulative exposure to LDL-C’ model ( JACC 2012; 60 ) using the following equations: Post-treatment 30-yr risk in those aged 20-39 years = Baseline Risk (FRS) x 0.54 delta LDL-C (mmol/L) Post-treatment 10-yr risk in those aged ≥40 years = Baseline Risk (ACC/AHA Pooled Cohort) x 0.72 delta LDL-C (mmol/L) To convey CHD risk and treatment benefit, we developed a DA using an iterative, patient-centered design process for use in FH encounters. Results: Using the DA, providers can discuss baseline CHD risk estimates, lipid lowering drug (LLD) options and the expected post-treatment risk reduction with FH patients. The estimated % LDL-C reduction for each LLD and the predicted risk reduction per mmol/L of LDL-C lowered were obtained from literature review. Lowering LDL-C by 1 mmol/L (39 mg/dL) was associated with a 28% CHD risk reduction over 10 years and a 46% reduction over 30 years ( Eur Heart J 2017; 38 ). We describe 2 examples of estimating CHD risk and treatment benefit in FH cases in Table 1 . Conclusion: We adapted CHD risk prediction equations to account for family history of CHD and presence of a pathogenic FH variant and designed a DA to convey personalized CHD risk estimates and treatment benefit to facilitate SDM with FH patients.

Background: Nonrheumatic valvular diseases are common; however, no studies have estimated their global or national burden. As part of the Global Burden of Disease Study 2017, mortality, prevalence, and disability-adjusted life-years (DALYs) for calcific aortic valve disease (CAVD), degenerative mitral valve disease, and other nonrheumatic valvular diseases were estimated for 195 countries and territories from 1990 to 2017. Methods: Vital registration data, epidemiologic survey data, and administrative hospital data were used to estimate disease burden using the Global Burden of Disease Study modeling framework, which ensures comparability across locations. Geospatial statistical methods were used to estimate disease for all countries, because data on nonrheumatic valvular diseases are extremely limited for some regions of the world, such as Sub-Saharan Africa and South Asia. Results accounted for estimated level of disease severity as well as the estimated availability of valve repair or replacement procedures. DALYs and other measures of health-related burden were generated for both sexes and each 5-year age group, location, and year from 1990 to 2017. Results: Globally, CAVD and degenerative mitral valve disease caused 102 700 (95% uncertainty interval [UI], 82 700–107 900) and 35 700 (95% UI, 30 500–42 500) deaths, and 12.6 million (95% UI, 11.4 million–13.8 million) and 18.1 million (95% UI, 17.6 million–18.6 million) prevalent cases existed in 2017, respectively. A total of 2.5 million (95% UI, 2.3 million–2.8 million) DALYs were estimated as caused by nonrheumatic valvular diseases globally, representing 0.10% (95% UI, 0.09%–0.11%) of total lost health from all diseases in 2017. The number of DALYs increased for CAVD and degenerative mitral valve disease between 1990 and 2017 by 101% (95% UI, 79%–117%) and 35% (95% UI, 23%–47%), respectively. There is significant geographic variation in the prevalence, mortality rate, and overall burden of these diseases, with highest age-standardized DALY rates of CAVD estimated for high-income countries. Conclusions: These global and national estimates demonstrate that CAVD and degenerative mitral valve disease are important causes of disease burden among older adults. Efforts to clarify modifiable risk factors and improve access to valve interventions are necessary if progress is to be made toward reducing, and eventually eliminating, the burden of these highly treatable diseases.

AbstractAimAchieving the optimal apposition of coronary stents during percutaneous coronary intervention is not always feasible. The risks and benefits of stent postdilation in primary percutaneous coronary intervention (PPCI) in patients with ST‐elevation myocardial infarction (STEMI) have remained controversial. We sought to evaluate the immediate angiographic and long‐term outcomes in patients with and without stent postdilation.MethodsA cohort of patients (n = 1,224) with STEMI, treated with PPCI (n = 500 postdilated; n = 724 controls), were studied. The flow grade, the myocardial blush grade, and the frame count were considered angiographic outcomes. The clinical outcomes were major adverse cardiovascular events (MACE)—comprising cardiac death, nonfatal MI, and repeat revascularization—and the device‐oriented composite endpoint (DOCE)—consisting of cardiac death, target lesion revascularization, and target vessel revascularization.ResultsThe flow and myocardial blush grades were not different between the two groups, and the frame count was significantly lower in the postdilation group (15.7 ± 8.4 vs. 17 ± 10.4; p < .05). The patients were followed up for 348 ± 399 days. DOCE (2.2% vs. 5.8%) and cardiac mortality (1.2% vs. 3.2%) were lower in the postdilation group. In the fully adjusted propensity score‐matched analysis, postdilation was associated with decreased DOCE (HR = 0.40 [0.18–0.87], p = .021).ConclusionsSelective postdilation improved some angiographic and clinical outcomes and could not be discouraged in PPCI on patients with STEMI.