Arteriosclerosis, Thrombosis, and Vascular Biology最新文献

Background: Pulmonary hypertension (PH) represents an important phenotype in heart failure with preserved ejection fraction (HFpEF). However, management of PH-HFpEF is challenging because mechanisms involved in the regulation of PH-HFpEF remain unclear.

Methods: We used a mass spectrometry-based comparative plasma proteomics approach as a sensitive and comprehensive hypothesis-generating discovery technique to profile proteins in patients with PH-HFpEF and control subjects. We then validated and investigated the role of one of the identified proteins using in vitro cell cultures, in vivo animal models, and independent cohort of human samples.

Results: Plasma proteomics identified high protein abundance levels of B2M (β2-microglobulin) in patients with PH-HFpEF. Interestingly, both circulating and skeletal muscle levels of B2M were increased in mice with skeletal muscle SIRT3 (sirtuin-3) deficiency or high-fat diet-induced PH-HFpEF. Plasma and muscle biopsies from a validation cohort of PH-HFpEF patients were found to have increased B2M levels, which positively correlated with disease severity, especially pulmonary capillary wedge pressure and right atrial pressure at rest. Not only did the administration of exogenous B2M promote migration/proliferation in pulmonary arterial vascular endothelial cells but it also increased PCNA (proliferating cell nuclear antigen) expression and cell proliferation in pulmonary arterial vascular smooth muscle cells. Finally, B2m deletion improved glucose intolerance, reduced pulmonary vascular remodeling, lowered PH, and attenuated RV hypertrophy in mice with high-fat diet-induced PH-HFpEF.

Conclusions: Patients with PH-HFpEF display higher circulating and skeletal muscle expression levels of B2M, the magnitude of which correlates with disease severity. Our findings also reveal a previously unknown pathogenic role of B2M in the regulation of pulmonary vascular proliferative remodeling and PH-HFpEF. These data suggest that circulating and skeletal muscle B2M can be promising targets for the management of PH-HFpEF.

Background: Epidemiological and mechanistic data support a potential causal link between cardiovascular disease (CVD) and cancer. Abdominal aortic aneurysms (AAAs) represent a common form of CVD with at least partially distinct genetic and biologic pathogenesis from other forms of CVD. The risk of cancer and how this risk differs compared with other forms of CVD, is unknown among AAA patients. We conducted a retrospective cohort study using the IBM MarketScan Research Database to test whether individuals with AAA have a higher cancer risk independent of traditional shared risk factors.

Methods: All individuals ≥18 years of age with ≥36 months of continuous coverage between 2008 and 2020 were enrolled. Those with potential Mendelian etiologies of AAA, aortic aneurysm with nonspecific anatomic location, or a cancer diagnosis before the start of follow-up were excluded. A subgroup analysis was performed of individuals having the Health Risk Assessment records including tobacco use and body mass index. The following groups of individuals were compared: (1) with AAA, (2) with non-AAA CVD, and (3) without any CVD.

Results: The propensity score-matched cohort included 58 993 individuals with AAA, 117 986 with non-AAA CVD, and 58 993 without CVD. The 5-year cumulative incidence of cancer was 13.1% (12.8%-13.5%) in participants with AAA, 10.1% (9.9%-10.3%) in participants with non-AAA CVD, and 9.6% (9.3%-9.9%) in participants without CVD. Multivariable-adjusted Cox proportional hazards regression models found that patients with AAA exhibited a higher cancer risk than either those with non-AAA CVD (hazard ratio, 1.28 [95% CI, 1.23-1.32]; P<0.001) or those without CVD (hazard ratio, 1.32 [95% CI, 1.26-1.38]; P<0.001). Results remained consistent after excluding common smoking-related cancers and when adjusting for tobacco use and body mass index.

Conclusions: Patients with AAA may have a unique risk of cancer requiring further mechanistic study and investigation of the role of enhanced cancer screening.

Clinical problem: Most abdominal aortic aneurysms (AAAs) are small with low rupture risk (<1%/y) when diagnosed but slowly expand to ≥55 mm and undergo surgical repair. Patients and clinicians require medications to limit AAA growth and rupture, but drugs effective in animal models have not translated to patients.

Recommendations for increasing translation from mouse models: Use models that simulate human AAA tissue pathology, growth patterns, and rupture; focus on the clinically relevant outcomes of growth and rupture; design studies with the rigor required of human clinical trials; monitor AAA growth using reproducible ultrasound; and perform studies in both males and females.

Summary of strengths and weaknesses of mouse models: The aortic adventitial elastase oral β-aminopropionitrile model has many strengths including simulating human AAA pathology and modeling prolonged aneurysm growth. The Ang II (angiotensin II) model performed less well as it better simulates acute aortic syndrome than AAA. The elastase plus TGFβ (transforming growth factor-β) blocking antibody model displays a high rupture rate, making prolonged monitoring of AAA growth not feasible. The elastase perfusion and calcium chloride models both display limited AAA growth.

Background: Arterial stiffening may contribute to the pathogenesis of metabolic dysfunction-associated steatotic liver disease. We aimed to assess relations of vascular hemodynamic measures with measures of hepatic steatosis and fibrosis in the community.

Methods: Our sample was drawn from the Framingham Offspring, New Offspring Spouse, Third Generation, Omni-1, and Omni-2 cohorts (N=3875; mean age, 56 years; 54% women). We used vibration-controlled transient elastography to assess controlled attenuation parameter and liver stiffness measurements as measures of liver steatosis and liver fibrosis, respectively. We assessed noninvasive vascular hemodynamics using arterial tonometry. We assessed cross-sectional relations of vascular hemodynamic measures with continuous and dichotomous measures of hepatic steatosis and fibrosis using multivariable linear and logistic regression.

Results: In multivariable models adjusting for cardiometabolic risk factors, higher carotid-femoral pulse wave velocity (estimated β per SD, 0.05 [95% CI, 0.01-0.09]; P=0.003), but not forward pressure wave amplitude and central pulse pressure, was associated with more liver steatosis (higher controlled attenuation parameter). Additionally, higher carotid-femoral pulse wave velocity (β=0.11 [95% CI, 0.07-0.15]; P<0.001), forward pressure wave amplitude (β=0.05 [95% CI, 0.01-0.09]; P=0.01), and central pulse pressure (β=0.05 [95% CI, 0.01-0.09]; P=0.01) were associated with more hepatic fibrosis (higher liver stiffness measurement). Associations were more prominent among men and among participants with obesity, diabetes, and metabolic syndrome (interaction P values, <0.001-0.04). Higher carotid-femoral pulse wave velocity, but not forward pressure wave amplitude and central pulse pressure, was associated with higher odds of hepatic steatosis (odds ratio, 1.16 [95% CI, 1.02-1.31]; P=0.02) and fibrosis (odds ratio, 1.40 [95% CI, 1.19-1.64]; P<0.001).

Conclusions: Elevated aortic stiffness and pressure pulsatility may contribute to hepatic steatosis and fibrosis.

Background: Analysis of vascular networks is an essential step to unravel the mechanisms regulating the physiological and pathological organization of blood vessels. So far, most of the analyses are performed using 2-dimensional projections of 3-dimensional (3D) networks, a strategy that has several obvious shortcomings. For instance, it does not capture the true geometry of the vasculature and generates artifacts on vessel connectivity. These limitations are accepted in the field because manual analysis of 3D vascular networks is a laborious and complex process that is often prohibitive for large volumes.

Methods: To overcome these issues, we developed 3DVascNet, a deep learning-based software for automated segmentation and quantification of 3D retinal vascular networks. 3DVascNet performs segmentation based on a deep learning model, and it quantifies vascular morphometric parameters such as vessel density, branch length, vessel radius, and branching point density. We tested the performance of 3DVascNet using a large data set of 3D microscopy images of mouse retinal blood vessels.

Results: We demonstrated that 3DVascNet efficiently segments vascular networks in 3D and that vascular morphometric parameters capture phenotypes detected by using manual segmentation and quantification in 2 dimension. In addition, we showed that, despite being trained on retinal images, 3DVascNet has high generalization capability and successfully segments images originating from other data sets and organs.

Conclusions: Overall, we present 3DVascNet, a freely available software that includes a user-friendly graphical interface for researchers with no programming experience, which will greatly facilitate the ability to study vascular networks in 3D in health and disease. Moreover, the source code of 3DVascNet is publicly available, thus it can be easily extended for the analysis of other 3D vascular networks by other users.