We performed a meta-analysis of 14 genome-wide association studies of coronary artery disease (CAD) comprising 22,233 cases and 64,762 controls of European descent, followed by genotyping of top association signals in 60,738 additional individuals. This genomic analysis identified 13 novel loci harboring one or more SNPs that were associated with CAD at P<5×10−8 and confirmed the association of 10 of 12 previously reported CAD loci. The 13 novel loci displayed risk allele frequencies ranging from 0.13 to 0.91 and were associated with a 6 to 17 percent increase in the risk of CAD per allele. Notably, only three of the novel loci displayed significant association with traditional CAD risk factors, while the majority lie in gene regions not previously implicated in the pathogenesis of CAD. Finally, five of the novel CAD risk loci appear to have pleiotropic effects, showing strong association with various other human diseases or traits.
A novel pulse sequence scheme is presented that allows the measurement and mapping of myocardial T 1 in vivo on a 1.5 Tesla MR system within a single breath-hold. Two major modifications of conventional Look-Locker (LL) imaging are introduced: 1) selective data acquisition, and 2) merging of data from multiple LL experiments into one data set. Each modified LL inversion recovery (MOLLI) study consisted of three successive LL inversion recovery (IR) experiments with different inversion times. We acquired images in late diastole using a single-shot steady-state free-precession (SSFP) technique, combined with sensitivity encoding to achieve a data acquisition window of <200 ms duration. We calculated T 1 using signal intensities from regions of interest and pixel by pixel. T 1 accuracy at different heart rates derived from simulated ECG signals was tested in phantoms. Key words: spin-lattice relaxation time; Look-Locker; heart; myocardium Despite recent technological advances, in vivo T 1 quantification of the myocardium with modern magnetic resonance (MR) systems remains a challenge because of severe time constraints due to cardiac and respiratory motion. While myocardial T 1 is shorter and therefore relatively easier to measure at low field strengths, it has a value of ϳ1000 ms at a field strength of 1.5 T, exceeding the duration of the cardiac cycle (ϳ600 -1200 ms) in most subjects (1,2). Since standard inversion recovery (IR) measurements require a relaxation period of four to five times T 1 to allow for full magnetization recovery after each 180°pulse (3), only four to five such single-point IR experiments can be performed within one breath-hold (ca. 20 s). To achieve accurate T 1 estimates from a three-parameter curve-fitting procedure, as is commonly employed, data from at least six to 10 time points should be available (4). The multipoint approach, as first described by Look and Locker (5), samples the relaxation curve multiple times after an initial preparation pulse (6). This technique has been shown theoretically to be highly efficient (7), and has been widely used for T 1 measurements of the brain (8 -11). It is not suitable for pixel-by-pixel T 1 mapping of the heart because data acquisition is performed continuously throughout the cardiac cycle without regard for cardiac motion, which means that T 1 values can only be derived for regions of interest (ROIs) that must be defined manually for every frame (1). The resultant T 1 values may consequently be subject to inaccuracy caused by misregistration effects.In this work we present a pulse sequence scheme that allows for accurate in vivo T 1 measurements and T 1 mapping of myocardium with high spatial resolution and within a single breath-hold. To overcome the limitations of the conventional LL approach for cardiac applications, we propose a modified LL IR scheme (MOLLI), which introduces two principles to the standard LL sequence: 1) selective data acquisition at a given time of the cardiac cycle over successive heartbeats, and (2) merging of image sets...
Coronary artery disease (CAD) is the commonest cause of death. Here, we report an association analysis in 63,746 CAD cases and 130,681 controls identifying 15 loci reaching genome-wide significance, taking the number of susceptibility loci for CAD to 46, and a further 104 independent variants (r2 < 0.2) strongly associated with CAD at a 5% false discovery rate (FDR). Together, these variants explain approximately 10.6% of CAD heritability. Of the 46 genome-wide significant lead SNPs, 12 show a significant association with a lipid trait, and 5 show a significant association with blood pressure, but none is significantly associated with diabetes. Network analysis with 233 candidate genes (loci at 10% FDR) generated 5 interaction networks comprising 85% of these putative genes involved in CAD. The four most significant pathways mapping to these networks are linked to lipid metabolism and inflammation, underscoring the causal role of these activities in the genetic etiology of CAD. Our study provides insights into the genetic basis of CAD and identifies key biological pathways.
Purpose:To establish normal ranges of left ventricular (LV) and right ventricular (RV) dimensions as determined by the current pulse sequences in cardiac magnetic resonance imaging (MRI). Materials and Methods:Sixty normal subjects (30 male and 30 female; age range, 20 -65) were examined; both turbo gradient echo (TGE) and steady-state free precession (SSFP) pulse sequences were used to obtain contiguous short-axis cine data sets from the ventricular apex to the base of the heart. The LV and RV volumes and LV mass were calculated by modified Simpson's rule.Results: Normal ranges were established and indexed to both body surface area (BSA) and height. There were statistically significant differences in the measurements between the genders and between TGE and SSFP pulse sequences. For TGE the LV end-diastolic volume (EDV)/BSA (mL/m 2 ) in males was 74.4 Ϯ 14.6 and in females was 70.9 Ϯ 11.7, while in SSFP in males it was 82.3 Ϯ 14.7 and in females it was 77.7 Ϯ 10.8. For the TGE the LV mass/ BSA (g/m 2 ) in males was 77.8 Ϯ 9.1 and in females it was 61.5 Ϯ 7.5, while in SSFP in males it was 64.7 Ϯ 9.3 and in females it was 52.0 Ϯ 7.4. For TGE the RV EDV/BSA (mL/ m 2 ) in males was 78.4 Ϯ 14.0 and in females it was 67.5 Ϯ 12.7, while in SSFP in males it was 86.2 Ϯ 14.1 and in females it was 75.2 Ϯ 13.8. Conclusion:We have provided normal ranges that are gender specific as well as data that can be used for age-specific normal ranges for both SSFP and TGE pulse sequences. CARDIAC MAGNETIC RESONANCE IMAGING (MRI) has been shown to be an accurate and reproducible tool for the estimation of both left ventricular (LV) and right ventricular (RV) measurements (1-8). Currently, the two pulse sequences, which are in common clinical and research use for acquisition of volumes data sets, are segmented k-space turbo gradient echo (TGE) and the more recent steady-state free precession (SSFP) technique. The latter sequence has been validated in animal studies (9). TGE acquisition has been compared to previously validated sequences with excellent correlation (7).Lorenz et al published the first normal range for cardiac MRI LV mass (g) and volumes, utilizing a conventional cine gradient echo sequence performed with free breathing (10). Another normal range for TGE with breath holding was developed by Marcus et al (11). There is a difference between the values obtained by the two groups. Lorenz et al report a mean LV mass of 178 Ϯ 31 for men (N ϭ 47) and of 125 Ϯ 26 for women (N ϭ 28), while Marcus et al report a mean LV mass of 142 Ϯ 20 for men (N ϭ 32) and 102 Ϯ 15.9 for women (N ϭ 29). These differences remained after indexation to body surface area (BSA). Therefore, there is a need for further work to establish a normal range for the TGE pulse sequence, which remains in common use. Furthermore, because of improved delineation of the endocardial borders and faster acquisition time, it is anticipated that SSFP pulse sequences will be the most frequently used technique in the future. Comparative values for ventricular volumes based...
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.