| Literature DB >> 34503678 |
Antonio de Marvao1, Kathryn A McGurk2, Sean L Zheng3, Marjola Thanaj1, Wenjia Bai4, Jinming Duan5, Carlo Biffi6, Francesco Mazzarotto7, Ben Statton1, Timothy J W Dawes8, Nicolò Savioli1, Brian P Halliday3, Xiao Xu3, Rachel J Buchan3, A John Baksi3, Marina Quinlan1, Paweł Tokarczuk1, Upasana Tayal3, Catherine Francis3, Nicola Whiffin9, Pantazis I Theotokis1, Xiaolei Zhang2, Mikyung Jang3, Alaine Berry1, Antonis Pantazis3, Paul J R Barton10, Daniel Rueckert11, Sanjay K Prasad3, Roddy Walsh12, Carolyn Y Ho13, Stuart A Cook14, James S Ware15, Declan P O'Regan16.
Abstract
BACKGROUND: Hypertrophic cardiomyopathy (HCM) is caused by rare variants in sarcomere-encoding genes, but little is known about the clinical significance of these variants in the general population.Entities:
Keywords: cardiovascular magnetic resonance; deep learning; genetics; hypertrophic cardiomyopathy; penetrance
Mesh:
Year: 2021 PMID: 34503678 PMCID: PMC8434420 DOI: 10.1016/j.jacc.2021.07.017
Source DB: PubMed Journal: J Am Coll Cardiol ISSN: 0735-1097 Impact factor: 24.094
Figure 1Cardiac Image Analysis in the UK Biobank
(A) Machine learning segmentation of the heart from cardiac magnetic resonance imaging (right atrium: light blue; right ventricle: dark blue; left atrium: yellow; left ventricle: red; left ventricular myocardium: green). Motion analysis was used to derive strain and strain rates (radial strain in diastole and systole shown). Regional analysis of left ventricular (LV) wall thickness was performed by using 3-dimensional modeling. Mean wall thickness for 21,322 UK Biobank participants is mapped onto the LV surface; the right ventricle is shown as a mesh. (B) Histogram of maximum LV wall thickness according to sex.
Figure 2Flowchart of UKBB Participants
We included 200,548 participants with whole exome sequencing (WES) in the UK Biobank (UKBB) and stratified them according to variant pathogenicity for outcome analysis. Machine learning was also used to characterize left ventricular traits in 39,551 participants, of whom 21,322 also had sequencing. aIndividuals excluded if carriers of: 1) rare variants in genes associated with HCM genocopies or LV phenotype; 2) intermediate frequency variants (0.00004 < AF < 0.001); 3) variant classes not robustly established as disease causing. bCMRs excluded from WT measure due to nondiagnostic imaging, incomplete sequences, and other technical reasons. AF = allele frequency; CMR = cardiac magnetic resonance imaging; HCM = hypertrophic cardiomyopathy; SARC-HCM-P/LP = pathogenic or likely pathogenic variants for hypertrophic cardiomyopathy in sarcomere-encoding genes; SARC-IND = indeterminate variants in hypertrophic cardiomyopathy–associated sarcomere-encoding genes (rare variants that do not meet criteria for pathogenic/likely pathogenic annotation); SARC-NEG = genotype negative; WT = wall thickness.
Subject Characteristics and CMR-Derived Cardiac Measurements According to Genotype
| SARC-NEG (n = 157,922) | SARC-IND (n = 5,219) | SARC-HCM-P/LP (n = 493) | SARC-NEG vs SARC-HCM-P/LP | SARC-NEG vs SARC-IND | SARC-IND vs SARC-HCM-P/LP | |
|---|---|---|---|---|---|---|
| Female | 86,710 (54.9) | 2,866 (54.9) | 276 (56.0) | |||
| Age, y | 56.5 ± 8.1 | 56.3 ± 8.2 | 56.2 ± 8.1 | |||
| White | 150,403 (95.2) | 4,756 (91.1) | 461 (93.5) | 0.11 | 0.11 | |
| SBP, mm Hg | 139.7 ± 19.6 | 139.5 ± 19.8 | 139.2 ± 20.2 | |||
| DBP, mm Hg | 82.2 ± 10.7 | 82.2 ± 10.5 | 81.4 ± 10.7 | |||
| BSA, m2 | 1.9 ± 0.22 | 1.9 ± 0.22 | 1.9 ± 0.22 | |||
| eGFR, mL/min/1.73 m2 | 90.7 ± 13.4 | 91.1 ± 13.3 | 90.1 ± 13.3 | |||
| Hypercholesterolemia | 29,137 (18.5) | 950 (18.2) | 94 (19.1) | |||
| Hypertension | 52,356 (33.2) | 1,723 (33.0) | 168 (34.1) | |||
| Diabetes | 8,429 (5.3) | 309 (5.9) | 25 (5.1) | |||
| Aortic valve disease | 1,567 (1.0) | 37 (0.7) | 8 (1.6) | |||
| Known HCM | 109 (0.07) | 9 (0.17) | 18 (3.65) | |||
| Known DCM | 265 (0.17) | 9 (0.17) | 1 (0.2) | |||
| On medication for cholesterol, blood pressure, diabetes | 18,537 (11.7) | 599 (11.5) | 64 (13.0) |
Values are n (%) or mean ± SD. Table includes data for genotype-negative individuals (SARC-NEG), individuals with pathogenic or likely pathogenic sarcomeric variants (SARC-HCM-P/LP), or those with other rare indeterminate sarcomeric variants (SARC-IND). BoldP values are statistically significant. Kruskal-Wallis tests were conducted for each variable to determine whether differences in participants’ characteristics between genotype group were significant; if so, a Wilcoxon test was used to perform pairwise comparisons between groups, with Benjamini-Hochberg adjustment for multiple testing, and those adjusted P values are shown. For the cardiac magnetic resonance imaging (CMR)-derived cardiac parameters, analysis was adjusted for age, sex, race, systolic blood pressure (SBP), and body surface area (BSA) using an analysis of covariance; when differences between genotype groups were significant, a Tukey post hoc test was applied for pairwise multiple comparisons, and those P values are shown.
concentricity = (left ventricular mass/left ventricular end-diastolic volume); DBP = diastolic blood pressure; DCM = dilated cardiomyopathy; eGFR = estimated glomerular filtration rate; FD = fractal dimension; HCM = hypertrophic cardiomyopathy; LAEDV = left atrial end-diastolic volume; LAEF = left atrial ejection fraction; LAESV = left atrial end-systolic volume; LV = left ventricular; LVEDV = left ventricular end-diastolic volume; LVEF = left ventricular ejection fraction; LVESV = left ventricular end-systolic volume; LVM = left ventricular mass; PDSR = peak diastolic strain rate; RAEF = right atrial ejection fraction; RVEDV = right ventricular end-diastolic volume; RVESV = right ventricular end-systolic volume; WT = wall thickness.
Figure 3Relationship Between Rare Variants in HCM-Associated Genes and WT
(A) Dot and boxplots of maximum wall thickness according to genotype. (B and C) 3-dimensional modeling of LV geometry with standardized beta-coefficients showing the strength of association between genotype and regional WT. Contour lines indicate significant regions (P < 0.05) after correction for multiple testing. LV projections are septal (left) and anterior (right). ∗∗∗P ≤ 0.001; ∗∗∗∗P ≤ 0.0001. ns = not significant; other abbreviations as in Figures 1 and 2.
Figure 4Outcomes Stratified According to Variant Pathogenicity
Cumulative hazard curves with zoomed plots for lifetime risk of: (A) death and major adverse cardiovascular events (MACE), consisting of heart failure, arrhythmia, stroke, and cardiac arrest events, or (B) heart failure, stratified according to genotype, consisting of SARC-NEG, SARC-IND, or SARC-HCM-P/LP. (C) Forest plot of comparative lifetime risk of clinical endpoints (Cox proportional hazards models adjusted for sex) according to genotype. Sex refers to male subjects compared with female subjects. Abbreviations as in Figure 2.
Central IllustrationOutcomes and Expression of Rare Variants in Hypertrophic Cardiomyopathy–Associated Genes
In 200,000 adults, the prevalence of variants pathogenic or likely pathogenic for hypertrophic cardiomyopathy (SARC-HCM-P/LP) was 1 in 407, whereas the aggregate prevalence of indeterminate sarcomeric variants was 1 in 38. The SARC-HCM-P/LP variants were associated with increased risk of death and major adverse cardiovascular events. We found associations with hypertrophic cardiomyopathy–like imaging phenotypes although the prevalence of overt cardiomyopathy was low. SARC-IND = indeterminate variants in hypertrophic cardiomyopathy–associated sarcomere-encoding genes (rare variants that do not meet criteria for pathogenic/likely pathogenic annotation); SARC-NEG = genotype negative.