Cross-ancestry genome-wide association analysis of corneal thickness strengthens link between complex and Mendelian eye diseases

Central corneal thickness (CCT) is a highly heritable trait associated with complex eye diseases such as keratoconus and glaucoma. We perform a genome-wide association meta-analysis of CCT and identify 19 novel regions. In addition to adding support for known connective tissue-related pathways, pathway analyses uncover previously unreported gene sets. Remarkably, >20% of the CCT-loci are near or within Mendelian disorder genes. These included FBN1, ADAMTS2 and TGFB2 which associate with connective tissue disorders (Marfan, Ehlers-Danlos and Loeys-Dietz syndromes), and the LUM-DCN-KERA gene complex involved in myopia, corneal dystrophies and cornea plana. Using index CCT-increasing variants, we find a significant inverse correlation in effect sizes between CCT and keratoconus (r =-0.62, P = 5.30 × 10-5) but not between CCT and primary open-angle glaucoma (r =-0.17, P = 0.2). Our findings provide evidence for shared genetic influences between CCT and keratoconus, and implicate candidate genes acting in collagen and extracellular matrix regulation

Biomarkers of abdominal aortic aneurysm progression. Part 2: inflammation

Defining progression of abdominal aortic aneurysm (AAA) is complicated by several factors, including measurement error, duration of follow-up, and the imaging modality used to assess AAA expansion. Investigations of biomarkers of AAA progression should be standardized so that valid comparisons can be made. Previous research has shown some promising advances towards identifying a reliable and individual predictor of AAA progression. In this second part of our Review on biomarkers of AAA progression, we examine direct and indirect markers of inflammation including various cytokines, C-reactive protein, activators of tissue plasminogen activator and urokinase plasminogen activator, and osteopontin

Biomarkers of AAA progression. Part 1: extracellular matrix degeneration

Abdominal aortic aneurysm (AAA) is an important health problem. Elective surgical treatment is recommended on the basis of an individual's risk of rupture, which is predicted by AAA diameter. However, the natural history of AAA differs between patients and a reliable and individual predictor of AAA progression (growth and expansion rates) has not been established. Several circulating biomarkers are candidates for an AAA diagnostic tool. However, they have yet to meet the triad of biomarker criteria: biological plausibility, correlation with AAA progression, and prediction of treatment effect on disease outcome. Circulating levels of markers of extracellular matrix degeneration, such as elastin peptides, aminoterminal propeptide of type III procollagen, elastase-alpha1-antitrypsin complexes, matrix metalloproteinase 9, cystatin C, plasmin-antiplasmin complexes and tissue plasminogen activator, have been correlated with AAA progression and have biological plausibility. Although studies of these markers have shown promising results, they have not yet led to a clinically applicable biomarker. In future studies, adjustment for initial AAA size, smoking history and the measurement error for determination of AAA size, among other variables, should be taken into account. A large, prospective, standardized, follow-up study will be needed to investigate multiple circulating biomarkers for their potential role in the prediction of AAA progression, followed by a study to investigate the effect of treatment on the circulating levels of biomarkers

Quantification of abdominal aortic aneurysm wall enhancement with dynamic contrast-enhanced MRI: Feasibility, reproducibility, and initial experience.

Keywords: dynamic contrast-enhanced MRI; abdominal aortic aneurysm; microvascularization; vessel wall imaging Purpose : To investigate the feasibility and reproducibility of dynamic contrast-enhanced MRI (DCE-MRI) to quantify abdominal aortic aneurysm (AAA) vessel wall enhancement dynamics which may reflect the amount of wall microvasculature. AAA vessel wall microvasculature has been linked with aneurysm progression and rupture. Materials and Methods : Thirty patients with AAA underwent DCE-MRI at 1.5 Tesla. Enhancement dynamics of the aneurysm wall were quantified in regions-of-interest (ROIs) in the vessel wall by calculating the transfer constant (Ktrans) using pharmacokinetic modeling and the area-under-gadolinium-curve (AUC). To assess reproducibility, 10 patients were imaged twice on different occasions. ROIs were drawn by two independent observers. The intraclass correlation coefficients (ICC) and coefficients of variation (CV) were determined to investigate intra-, interobserver, and interscan variability. Results : Twenty-eight analyzable MR examinations were included for pharmacokinetic analysis after excluding two examinations due to severe motion artifacts. Intra-, interobserver, and interscan variability for Ktrans were small (all ICC > 0.90, CV <14%) as well as for AUC measurements (all ICC > 0.88, CV <23%). Conclusion: Quantitative analysis of AAA vessel wall enhancement dynamics with DCE-MRI is feasible and reproducible. J. Magn. Reson. Imaging 2014;39:1449–1456. © 2013 Wiley Periodicals, Inc

Suitability of Pharmacokinetic Models for Dynamic Contrast-Enhanced MRI of Abdominal Aortic Aneurysm Vessel Wall: A Comparison

PURPOSE: Increased microvascularization of the abdominal aortic aneurysm (AAA) vessel wall has been related to AAA progression and rupture. The aim of this study was to compare the suitability of three pharmacokinetic models to describe AAA vessel wall enhancement using dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). MATERIALS AND METHODS: Patients with AAA underwent DCE-MRI at 1.5 Tesla. The volume transfer constant (K(trans) ), which reflects microvascular flow, permeability and surface area, was calculated by fitting the blood and aneurysm vessel wall gadolinium concentration curves. The relative fit errors, parameter uncertainties and parameter reproducibilities for the Patlak, Tofts and Extended Tofts model were compared to find the most suitable model. Scan-rescan reproducibility was assessed using the interclass correlation coefficient and coefficient of variation (CV). Further, the relationship between K(trans) and AAA size was investigated. RESULTS: DCE-MRI examinations from thirty-nine patients (mean age+/-SD: 72+/-6 years; M/F: 35/4) with an mean AAA maximal diameter of 49+/-6 mm could be included for pharmacokinetic analysis. Relative fit uncertainties for K(trans) based on the Patlak model (17%) were significantly lower compared to the Tofts (37%) and Extended Tofts model (42%) (p<0.001). K(trans) scan-rescan reproducibility for the Patlak model (ICC = 0.61 and CV = 22%) was comparable with the Tofts (ICC = 0.61, CV = 23%) and Extended Tofts model (ICC = 0.76, CV = 22%). K(trans) was positively correlated with maximal AAA diameter (Spearman's rho = 0.38, p = 0.02) using the Patlak model. CONCLUSION: Using the presented imaging protocol, the Patlak model is most suited to describe DCE-MRI data of the AAA vessel wall with good K(trans) scan-rescan reproducibility