Inter-scan reproducibility of coronary calcium measurement using Multi Detector-Row Computed Tomography (MDCT)

Purpose: To assess inter-scan reproducibility of coronary calcium measurements obtained from Multi Detector-Row CT (MDCT) images and to evaluate whether this reproducibility is affected by different measurement protocols, slice thickness, cardiovascular risk factors and/or technical variables. Design: Cross-sectional study with repeated measurements. Materials and methods: The study population comprised 76 healthy women. Coronary calcium was assessed in these women twice in one session using 16-MDCT (Philips Mx 8000 IDT 16). Images were reconstructed with 1.5 mm slice thickness and 3.0 mm slice thickness. The 76 repeated scans were scored. The Agatston score, a volume measurement and a mass measurement were assessed. Reproducibility was determined by estimation of mean, absolute, relative difference, the weighted kappa value for agreement and the Intra-class correlation coefficient (ICCC). Results: Fifty-five participants (72.4%) had a coronary calcification of more than zero in Agatston (1.5 mm slice thickness). The reproducibility of coronary calcium measurements between scans in terms of ranking was excellent with Intra-class correlation coefficients of >0.98, and kappa values above 0.80. The absolute difference in calcium score between scans increased with increasing calcium levels, indicating that measurement error increases with increasing calcium levels. However, no relation was found between the mean difference in scores and calcium levels, indicating that the increase in measurement error is likely to result in random misclassification in calcium score. Reproducibility results were similar for 1.5 mm slices and for 3.0 mm slices, and equal for Agatston, volume and mass measurements. Conclusion: Inter-scan reproducibilility of measurement of coronary calcium using images from MDCT is excellent, irrespective of slice thickness and type of calcium parameter

Computed tomography segmental calcium score (SCS) to predict stenosis severity of calcified coronary lesions

To estimate the probability of ≥50 % coronary stenoses based on computed tomography (CT) segmental calcium score (SCS) and clinical factors. The Institutional Review Board approved the study. A training sample of 201 patients underwent CT calcium scoring and conventional coronary angiography (CCA). All patients consented to undergo CT before CCA after being informed of the additional radiation dose. SCS and calcification morphology were assessed in individual coronary segments. We explored the predictive value of patient’s symptoms, clinical history, SCS and calcification morphology. We developed a prediction model in the training sample based on these variables then tested it in an independent test sample. The odds ratio (OR) for ≥50 % coronary stenosis was 1.8-fold greater (p = 0.006) in patients with typical chest pain, twofold (p = 0.014) greater in patients with acute coronary syndromes, twofold greater (p < 0.001) in patients with prior myocardial infarction. Spotty calcifications had an OR for ≥50 % stenosis 2.3-fold (p < 0.001) greater than the absence of calcifications, wide calcifications 2.7-fold (p < 0.001) greater, diffuse calcifications 4.6-fold (p < 0.001) greater. In middle segments, each unit of SCS had an OR 1.2-fold (p < 0.001) greater than in distal segments; in proximal segments the OR was 1.1-fold greater (p = 0.021). The ROC curve area of the prediction model was 0.795 (0.95 confidence interval 0.602–0.843). Validation in a test sample of 201 independent patients showed consistent diagnostic performance. In conjunction with calcification morphology, anatomical location, patient’s symptoms and clinical history, SCS can be helpful to estimate the probability of ≥50 % coronary stenosis

Triglycerides and blood pressure in relation to circulating CD34-positive cell levels among community-dwelling elderly Japanese men: a cross-sectional study

Background: Triglycerides are reported to be positively associated with blood pressure (both systolic and diastolic). However, in a previous study, we reported a significant positive association between triglycerides and circulating CD34-positive cells (endothelial repair) among non-hypertensive, but not hypertensive, participants. Since hypertension and endothelial dysfunction have a bi-directional association (vicious cycle), the status of circulating CD34-positive cells may influence the association between triglycerides and hypertension. Methods: Since antihypertensive medication use may influence results of the present study, we conducted a cross-sectional study of 327 community dwelling elderly (aged 60-69 years) Japanese participants who were not taking anti-hypertensive medication and who had participated in a general health check-up in 2013-2015. Results: Participants were classified into two groups based on median values of circulating CD34-positive cells (0.93 cells/μL). For participants with lower circulating CD34-positive cells (n = 165), a significant positive association was seen between triglycerides and blood pressure, but not for participants with higher circulating CD34-positive cells (n = 162). The multivariable standardized parameter estimates (β) and p values of systolic blood pressure and diastolic blood pressure were 0.23 (p = 0.007) and 0.18 (p = 0.036) for participants with lower circulating CD34-positive cells and 0.08 (p = 0.409) and 0.03 (p = 0.786) for those with higher circulating CD34-positive cells. Conclusion: A significant positive association between triglycerides and blood pressure exists among those with lower, but not higher, circulating CD34-positive cells. The level of circulating CD34-positive cells acts as a determinant factor for the association between triglycerides and blood pressure

Publisher Correction: Sex-dimorphic genetic effects and novel loci for fasting glucose and insulin variability.

Correction to: Nature Communications https://doi.org/10.1038/s41467-020-19366-9, published online 5 January 2021. The original version of this Article contained an error in Fig. 2, in which panels a and b were inadvertently swapped. This has now been corrected in the PDF and HTML versions of the Article

Genome-wide physical activity interactions in adiposity. A meta-analysis of 200,452 adults

Physical activity (PA) may modify the genetic effects that give rise to increased risk of obesity. To identify adiposity loci whose effects are modified by PA, we performed genome-wide interaction meta-analyses of BMI and BMI-adjusted waist circumference and waist-hip ratio from up to 200,452 adults of European (n = 180,423) or other ancestry (n = 20,029). We standardized PA by categorizing it into a dichotomous variable where, on average, 23% of participants were categorized as inactive and 77% as physically active. While we replicate the interaction with PA for the strongest known obesity-risk locus in the FTO gene, of which the effect is attenuated by similar to 30% in physically active individuals compared to inactive individuals, we do not identify additional loci that are sensitive to PA. In additional genome-wide meta-analyses adjusting for PA and interaction with PA, we identify 11 novel adiposity loci, suggesting that accounting for PA or other environmental factors that contribute to variation in adiposity may facilitate gene discovery.Peer reviewe

Publisher Correction: Sex-dimorphic genetic effects and novel loci for fasting glucose and insulin variability.

Correction to: Nature Communications https://doi.org/10.1038/s41467-020-19366-9, published online 5 January 2021. The original version of this Article contained an error in Fig. 2, in which panels a and b were inadvertently swapped. This has now been corrected in the PDF and HTML versions of the Article

A Large-Scale Multi-ancestry Genome-wide Study Accounting for Smoking Behavior Identifies Multiple Significant Loci for Blood Pressure

Genome-wide association analysis advanced understanding of blood pressure (BP), a major risk factor for vascular conditions such as coronary heart disease and stroke. Accounting for smoking behavior may help identify BP loci and extend our knowledge of its genetic architecture. We performed genome-wide association meta-analyses of systolic and diastolic BP incorporating gene-smoking interactions in 610,091 individuals. Stage 1 analysis examined similar to 18.8 million SNPs and small insertion/deletion variants in 129,913 individuals from four ancestries (European, African, Asian, and Hispanic) with follow-up analysis of promising variants in 480,178 additional individuals from five ancestries. We identified 15 loci that were genome-wide significant (p <5 x 10(-8)) in stage 1 and formally replicated in stage 2. A combined stage 1 and 2 meta-analysis identified 66 additional genome-wide significant loci (13, 35, and 18 loci in European, African, and trans-ancestry, respectively). A total of 56 known BP loci were also identified by our results (p <5 x 10(-8)). Of the newly identified loci, ten showed significant interaction with smoking status, but none of them were replicated in stage 2. Several loci were identified in African ancestry, highlighting the importance of genetic studies in diverse populations. The identified loci show strong evidence for regulatory features and support shared pathophysiology with cardiometabolic and addiction traits. They also highlight a role in BP regulation for biological candidates such as modulators of vascular structure and function (CDKN1B, BCAR1-CFDP1, PXDN, EEA1), ciliopathies (SDCCAG8, RPGRIP1L), telomere maintenance (TNKS, PINX1, AKTIP), and central dopaminergic signaling MSRA, EBF2).Peer reviewe

Refining the accuracy of validated target identification through coding variant fine-mapping in type 2 diabetes

We aggregated coding variant data for 81,412 type 2 diabetes cases and 370,832 controls of diverse ancestry, identifying 40 coding variant association signals (P &lt; 2.2 × 10-7); of these, 16 map outside known risk-associated loci. We make two important observations. First, only five of these signals are driven by low-frequency variants: even for these, effect sizes are modest (odds ratio ≤1.29). Second, when we used large-scale genome-wide association data to fine-map the associated variants in their regional context, accounting for the global enrichment of complex trait associations in coding sequence, compelling evidence for coding variant causality was obtained for only 16 signals. At 13 others, the associated coding variants clearly represent 'false leads' with potential to generate erroneous mechanistic inference. Coding variant associations offer a direct route to biological insight for complex diseases and identification of validated therapeutic targets; however, appropriate mechanistic inference requires careful specification of their causal contribution to disease predisposition.</p