Citations

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.

Introduction: The potential use of polygenic risk scores (PRSs) in clinical practice is tempered by concern about their portability among diverse populations. To prevent disparities in genomic medicine, there is an urgent need to conduct genome-wide association studies in non-European ancestry cohorts. Methods: We conducted whole genome sequencing (WGS) with 30x coverage on coronary heart disease patients (n=1,067, mean age ± SD = 59.96 years ± 10.99; 70.32% males) and controls (n=6,170, mean age ± SD = 40.02 years ± 12.56; 43.45% males) in a Middle Eastern cohort to compare the performance of available PRSs for CHD (LDpred, metaGRS, lassosum, and P+T) and identify common variants associated with CHD (via generalized linear mixed models). Results: Excepting lassosum, all PRSs performed well. LDpred and metaGRS performed similarly (AUC= ~0.685) and outperformed P+T (AUC=0.667). Based on the OR per 1 SD increase (OR 1sd ), P+T (OR 1sd =1.85 [1.69-2.02], P =3.69x10 -41 ) outperformed other PRSs (OR 1sd =1.61 [1.48-1.74], P =3.02x10 -31 for LDpred and OR 1sd =1.61 [1.49-1.75], P =9.47x10 -31 for metaGRS). After binning PRSs into 10 deciles, the odds of CHD in the top decile compared to all others was highest for metaGRS (3.87 [3.07-4.88]) and LDpred (3.45 [2.74-4.341]). Thirty-two known GWAS loci (e.g., ABCG8 , CELSR2 , and SLC22A4 ) were replicated in our analysis with P <0.05. Seven suggestive new loci/genes ( P <10 -6 ) with relevant biological function were identified (e.g., CORO7 , RBM47 , and PDE4D ). The well-established 9p21 locus was not replicated. Conclusions: Genome-wide PRSs derived from European ancestry cohorts performed well in a Middle Eastern cohort. Further studies are needed to develop and validate an ancestry specific PRS and to confirm the suggestive loci/genes.

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.

Introduction: Chronic elevation of left heart filling pressure causes pulmonary vascular remodeling, pulmonary hypertension, and right heart dysfunction. Although diastolic dysfunction is relatively common in patients with coarctation of aorta (COA), there are limited data about the prevalence and prognostic implications of pulmonary hypertension and right heart dysfunction in this population. The purpose of the study was to assess right heart function and hemodynamics in patients with COA, and to determine the relationship between right heart indices and clinical outcomes. Methods: Right heart structure, function and hemodynamics were assessed with these indices: right atrial (RA) volume, RA pressure, RA reservoir strain, right ventricular (RV) global longitudinal strain, RV end-diastolic area, RV systolic pressure, and tricuspid regurgitation severity. These indices were used to generate a composite right heart hemodynamic score (RHHS), range 0-5. We then assessed the relationship between RHHS and primary outcome (death/transplant) and secondary outcomes (heart failure hospitalization and hepatorenal function). Results: Of 821 COA patients, RA dysfunction, RV dysfunction, and pulmonary hypertension were present in 16%, 14%, and 20% of patients respectively. RHHS was independently associated with primary and secondary outcomes (p<0.001). For every unit increase in RHHS, we observed 83% increase in death/transplant and 71% increase in heart failure hospitalization. Conclusions: The current study underscores an important point, which is that COA is not just a disease of the left heart but can result in right heart dysfunction, and that the onset of right heart dysfunction is associated with adverse outcomes.

Introduction: Valvuloarterial impedance (Zva) is used for assessment of left ventricular (LV) global pressure load in patients with aortic stenosis (AS) and impaired arterial compliance. Since patients with coarctation of aorta (COA) have impaired arterial compliance, we hypothesized that COA patients with ≥moderate AS (AS-COA group) will have higher Zva, symptomatic progression, and cardiovascular events, as compared to non-COA patients with similar AS severity (AS group). Methods: 1:1 propensity matching of 71 AS-COA and 71 AS patients based on age, sex, body mass index, and aortic valve mean gradient. Results: The AS-COA group had higher Zva (4.2±0.6 vs 3.5±0.4 mmHg/ml*m 2 , p<0.001), more advanced cardiac remodeling, and higher 5-year incidence of symptomatic progression (85% vs 51%, p<0.001). Pre-operative Zva was independently associated with cardiac remodeling (r=0.66, p<0.001) and symptomatic progression (HR 1.08, 1.05-1.12, per mmHg/ml*m 2 increase in Zva). Of 172 patients, 117 underwent aortic valve replacement (AVR). The AS-COA group had higher residual Zva(3.3±0.5 vs 2.4±0.4 mmHg/ml*m 2 , p<0.001), less robust LV mass index (LVMI) regression at 1-year post-AVR, and higher 5-year incidence of cardiovascular events. Post-operative Zva was independently associated with LVMI regression (r=-0.46, p<0.001) and cardiovascular events (HR 1.06, 1.02-1.10, per mmHg/ml*m 2 increase in Zva). Conclusions: Adults with repaired COA repair and moderate-severe AS had higher LV global pressure load, cardiac remodeling, symptomatic progression, and cardiovascular events as compared to non-COA patients with similar severity of AS. Zva can identify patients at risk for adverse outcomes, and perhaps should be used for risk stratification with regards to timing of AVR.

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