| 21. |
- Tschiderer, Lena, et al.
(författare)
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Association of Intima-Media Thickness Measured at the Common Carotid Artery With Incident Carotid Plaque : Individual Participant Data Meta-Analysis of 20 Prospective Studies
- 2023
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Ingår i: Journal of the American Heart Association. - : Ovid Technologies (Wolters Kluwer Health). - 2047-9980. ; 12:12
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Tidskriftsartikel (refereegranskat)abstract
- Background: The association between common carotid artery intima-media thickness (CCA-IMT) and incident carotid plaque has not been characterized fully. We therefore aimed to precisely quantify the relationship between CCA-IMT and carotid plaque development.Methods and Results: We undertook an individual participant data meta-analysis of 20 prospective studies from the Proof-ATHERO (Prospective Studies of Atherosclerosis) consortium that recorded baseline CCA-IMT and incident carotid plaque involving 21 494 individuals without a history of cardiovascular disease and without preexisting carotid plaque at baseline. Mean baseline age was 56 years (SD, 9 years), 55% were women, and mean baseline CCA-IMT was 0.71 mm (SD, 0.17 mm). Over a median follow-up of 5.9 years (5th-95th percentile, 1.9-19.0 years), 8278 individuals developed first-ever carotid plaque. We combined study-specific odds ratios (ORs) for incident carotid plaque using random-effects meta-analysis. Baseline CCA-IMT was approximately log-linearly associated with the odds of developing carotid plaque. The age-, sex-, and trial arm-adjusted OR for carotid plaque per SD higher baseline CCA-IMT was 1.40 (95% CI, 1.31-1.50; I-2=63.9%). The corresponding OR that was further adjusted for ethnicity, smoking, diabetes, body mass index, systolic blood pressure, low- and high-density lipoprotein cholesterol, and lipid-lowering and antihypertensive medication was 1.34 (95% CI, 1.24-1.45; I-2=59.4%; 14 studies; 16 297 participants; 6381 incident plaques). We observed no significant effect modification across clinically relevant subgroups. Sensitivity analysis restricted to studies defining plaque as focal thickening yielded a comparable OR (1.38 [95% CI, 1.29-1.47]; I-2=57.1%; 14 studies; 17 352 participants; 6991 incident plaques).Conclusions: Our large-scale individual participant data meta-analysis demonstrated that CCA-IMT is associated with the long-term risk of developing first-ever carotid plaque, independent of traditional cardiovascular risk factors.
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| 22. |
- Vontell, Regina T., et al.
(författare)
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Association of region-specific hippocampal reduction of neurogranin with inflammasome proteins in post mortem brains of Alzheimer's disease
- 2024
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Ingår i: ALZHEIMERS & DEMENTIA-TRANSLATIONAL RESEARCH & CLINICAL INTERVENTIONS. - 2352-8737. ; 10:1
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Tidskriftsartikel (refereegranskat)abstract
- INTRODUCTION: Neurogranin (Ng) is considered a biomarker for synaptic dysfunction in Alzheimer's disease (AD). In contrast, the inflammasome complex has been shown to exacerbate AD pathology.METHODS: We investigated the protein expression, morphological differences of Ng, and correlated Ng to hyperphosphorylated tau in the post mortem brains of 17 AD cases and 17 age- and sex-matched controls. In addition, we correlated the Ng expression with two different epitopes of apoptosis-associated speck-like protein containing a caspase recruitment domain (ASC).RESULTS: We show a reduction of Ng immunopositive neurons and morphological differences in AD compared to controls. Ng immunostaining was negatively correlated with neurofibrillary tangles, humanized anti-ASC (IC100) positive neurons and anti-ASC positive microglia, in AD.DISCUSSION: The finding of a negative correlation between Ng and ASC speck protein expression in post mortem brains of AD suggests that the activation of inflammasome/ASC speck pathway may play an important role in synaptic degeneration in AD.
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| 23. |
- Willeit, Peter, et al.
(författare)
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Inflammatory markers and extent and progression of early atherosclerosis : Meta-analysis of individual-participant-data from 20 prospective studies of the PROG-IMT collaboration
- 2016
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Ingår i: European Journal of Preventive Cardiology. - : Oxford University Press (OUP). - 2047-4873 .- 2047-4881. ; 23:2, s. 194-205
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Tidskriftsartikel (refereegranskat)abstract
- BackgroundLarge-scale epidemiological evidence on the role of inflammation in early atherosclerosis, assessed by carotid ultrasound, is lacking. We aimed to quantify cross-sectional and longitudinal associations of inflammatory markers with common-carotid-artery intima-media thickness (CCA-IMT) in the general population. MethodsInformation on high-sensitivity C-reactive protein, fibrinogen, leucocyte count and CCA-IMT was available in 20 prospective cohort studies of the PROG-IMT collaboration involving 49,097 participants free of pre-existing cardiovascular disease. Estimates of associations were calculated within each study and then combined using random-effects meta-analyses. ResultsMean baseline CCA-IMT amounted to 0.74mm (SD=0.18) and mean CCA-IMT progression over a mean of 3.9 years to 0.011mm/year (SD=0.039). Cross-sectional analyses showed positive linear associations between inflammatory markers and baseline CCA-IMT. After adjustment for traditional cardiovascular risk factors, mean differences in baseline CCA-IMT per one-SD higher inflammatory marker were: 0.0082mm for high-sensitivity C-reactive protein (p<0.001); 0.0072mm for fibrinogen (p<0.001); and 0.0025mm for leucocyte count (p=0.033). Inflammatory load', defined as the number of elevated inflammatory markers (i.e. in upper two quintiles), showed a positive linear association with baseline CCA-IMT (p<0.001). Longitudinal associations of baseline inflammatory markers and changes therein with CCA-IMT progression were null or at most weak. Participants with the highest inflammatory load' had a greater CCA-IMT progression (p=0.015). ConclusionInflammation was independently associated with CCA-IMT cross-sectionally. The lack of clear associations with CCA-IMT progression may be explained by imprecision in its assessment within a limited time period. Our findings for inflammatory load' suggest important combined effects of the three inflammatory markers on early atherosclerosis.
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| 24. |
- Wu, Ona, et al.
(författare)
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Big Data Approaches to Phenotyping Acute Ischemic Stroke Using Automated Lesion Segmentation of Multi-Center Magnetic Resonance Imaging Data
- 2019
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Ingår i: Stroke. - 1524-4628. ; 50:7, s. 1734-1741
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Tidskriftsartikel (refereegranskat)abstract
- Background and Purpose- We evaluated deep learning algorithms' segmentation of acute ischemic lesions on heterogeneous multi-center clinical diffusion-weighted magnetic resonance imaging (MRI) data sets and explored the potential role of this tool for phenotyping acute ischemic stroke. Methods- Ischemic stroke data sets from the MRI-GENIE (MRI-Genetics Interface Exploration) repository consisting of 12 international genetic research centers were retrospectively analyzed using an automated deep learning segmentation algorithm consisting of an ensemble of 3-dimensional convolutional neural networks. Three ensembles were trained using data from the following: (1) 267 patients from an independent single-center cohort, (2) 267 patients from MRI-GENIE, and (3) mixture of (1) and (2). The algorithms' performances were compared against manual outlines from a separate 383 patient subset from MRI-GENIE. Univariable and multivariable logistic regression with respect to demographics, stroke subtypes, and vascular risk factors were performed to identify phenotypes associated with large acute diffusion-weighted MRI volumes and greater stroke severity in 2770 MRI-GENIE patients. Stroke topography was investigated. Results- The ensemble consisting of a mixture of MRI-GENIE and single-center convolutional neural networks performed best. Subset analysis comparing automated and manual lesion volumes in 383 patients found excellent correlation (ρ=0.92; P<0.0001). Median (interquartile range) diffusion-weighted MRI lesion volumes from 2770 patients were 3.7 cm3 (0.9-16.6 cm3). Patients with small artery occlusion stroke subtype had smaller lesion volumes ( P<0.0001) and different topography compared with other stroke subtypes. Conclusions- Automated accurate clinical diffusion-weighted MRI lesion segmentation using deep learning algorithms trained with multi-center and diverse data is feasible. Both lesion volume and topography can provide insight into stroke subtypes with sufficient sample size from big heterogeneous multi-center clinical imaging phenotype data sets.
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