Dataset Information

Excessive Visit-to-Visit Small and Dense Low-Density Lipoproteins Elevate Cerebral Small Vessel Disease Progression Risk in the Elderly.

ABSTRACT:

Objective

Small and dense low-density lipoprotein (sdLDL) elevation may be among the most sensitive early biomarkers for nascent cardiovascular disease. This study, therefore, investigated the association between visit-to-visit changes in sdLDL and cerebral small vessel disease (CSVD) progression in older individuals, and the influence of Apolipoprotein E (APOE) genotype on this association.

Methods

Between April 2007 and July 2009, 1,143 participants ≥60 years old were recruited from the Shandong region of China, and sdLDL was measured at baseline and at each follow-up visit. White matter hyperintensities (WMHs), lacunes, microbleeds, and enlarged perivascular spaces (EPVSs) were assessed by magnetic resonance imaging. The APOE genotype was determined and participants were stratified as ε4-positive or ε4-negative.

Results

During an average follow-up of 86.0 months, 225 participants (19.7%) developed WMH progression, 193 (16.9%) lacune progression, 170 (14.9%) microbleed progression, and 185 (16.2%) EPVS progression. Compared with patients in the first (lowest) tertile of visit-to-visit mean sdLDL, those in the second and third tertiles demonstrated significantly greater risks of WMH progression (53.5 and 105.3% higher), lacune progression (53.3 and 60.8%), microbleed progression (47.2 and 127.6%), and EPVS progression (54.0 and 135.0%) after adjustment for confounders (all adjusted P values for trends <0.001). Compared with patients in the first tertile of visit-to-visit sdLDL SD, those in the second and third tertiles also demonstrated significantly greater risks of WMH progression (49.9% and 143.6%), lacune progression (75.3 and 178.0%), microbleed progression (12.7 and 64.7%), and EPVS progression (41.7 and 114.6%) after adjustment (all P < 0.001). There were significant and positive visit-to-visit mean sdLDL × visit-to-visit sdLDL SD, visit-to-visit mean sdLD×ε4-positive, visit-to-visit sdLDL SD×ε4-positive, and visit-to-visit mean sdLDL×visit-to-visit sdLDL SD×ε4-positive interactions influencing CSVD progression after confounder adjustment (all P < 0.05).

Conclusion

Large and variable visit-to-visit changes in sdLDL are independent predictors of aggressive CSVD progression, and this association is strongly influenced by APOE ε4 allele genotype.

SUBMITTER: Liu W

PROVIDER: S-EPMC9277007 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Excessive Visit-to-Visit Small and Dense Low-Density Lipoproteins Elevate Cerebral Small Vessel Disease Progression Risk in the Elderly.

Liu Weike W Xu Jing J Song Huajing H Zhang Chunju C Yao Yanli Y Zhang Hua H Li Yue-Chun YC Liu Zhendong Z

Frontiers in neurology 20220629

<h4>Objective</h4>Small and dense low-density lipoprotein (sdLDL) elevation may be among the most sensitive early biomarkers for nascent cardiovascular disease. This study, therefore, investigated the association between visit-to-visit changes in sdLDL and cerebral small vessel disease (CSVD) progression in older individuals, and the influence of <i>Apolipoprotein E</i> (<i>APOE</i>) genotype on this association.<h4>Methods</h4>Between April 2007 and July 2009, 1,143 participants ≥60 years old w ...[more]

PMID: 35847226

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Project description:BackgroundCerebral small vascular disease (CSVD) is one of the leading causes of death in the aged population and is closely related to abnormalities in low-density lipoprotein cholesterol (LDL-C). Our study aims to clarify the relationship between small and dense low-density lipoprotein cholesterol (sdLDL-C) (a subcomponent of LDL-C) and neuroimaging markers of CSVD.MethodsIn total, 1211 Chinese adults aged ≥45 years with cranial magnetic resonance imaging (MRI) were recruited in this retrospective study from January 2018 to May 2021. Serum lipids and other baseline characteristics were investigated in relation to the occurrence of CSVD. A logistic regression model was performed to analyze the relationships between LDL subtypes and CSVD risk, and the Pearson correlation coefficient was used to analyze the correlation between clinical characteristics and CSVD risk. ROC curves and AUCs were created and depicted to predict the best cutoff value of LDL-C subtypes for CSVD risk. Based on these data, we performed comprehensive analyses to investigate the risk factors for CSVD.ResultsUltimately, 623 eligible patients were included in the present study. Of the 623 eligible patients, 487 were included in the CSVD group, and 136 were included in the group without CSVD (control group). We adjusted for confounders in the multivariate logistic regression model, and LDL-C3 was still higher in the CSVD patients than in the group of those without CSVD (OR (95% CI), 1.22(1.08-1.38), P < 0.05). Pearson correlation showed that there was a positive correlation between the levels of LDL-C3, LDL-C4, LDL-C5, glucose, age, hypertension, previous ischemic stroke and CSVD risk (r > 0.15, P < 0.01). Moreover, the best cutoff value of LDL-C3 to predict CSVD was 9.5 mg/dL with 68.4% sensitivity and 72.8% specificity, and the best cutoff value of LDL-C4 to predict CSVD was 5.5 mg/dL with 50.5% sensitivity and 90.4% specificity.ConclusionThe results indicate that LDL-C3 is an independent risk factor for CSVD. A new prediction model based on LDL-C3 and LDL-C4 can help clinicians identify high-risk CSVD, even in people with normal LDL-C levels. The levels of sdLDL-C should be considered in the assessment and management of CSVD.

Project description:Small cerebral blood vessels are largely inaccessible to existing clinical in vivo imaging technologies. This study aims to present a novel analysis pipeline for vessel density mapping of small cerebral blood vessels from high-resolution 3D black-blood MRI at 3T. Twenty-eight subjects (10 under 35 years old, 18 over 60 years old) were imaged with the T1-weighted turbo spin-echo with variable flip angles (T1w TSE-VFA) sequence optimized for black-blood small vessel imaging with iso-0.5 mm spatial resolution (interpolated from 0.51×0.51×0.64 mm3) at 3T. Hessian-based vessel segmentation methods (Jerman, Frangi and Sato filter) were evaluated by vessel landmarks and manual annotation of lenticulostriate arteries (LSAs). Using optimized vessel segmentation, large vessel pruning and non-linear registration, a semiautomatic pipeline was proposed for quantification of small vessel density across brain regions and further for localized detection of small vessel changes across populations. Voxel-level statistics was performed to compare vessel density between two age groups. Additionally, local vessel density of aged subjects was correlated with their corresponding gross cognitive and executive function (EF) scores using Montreal Cognitive Assessment (MoCA) and EF composite scores compiled with Item Response Theory (IRT). Jerman filter showed better performance for vessel segmentation than Frangi and Sato filter which was employed in our pipeline. Small cerebral blood vessels including small artery, arterioles, small veins, and venules on the order of a few hundred microns can be delineated using the proposed analysis pipeline on 3D black-blood MRI at 3T. The mean vessel density across brain regions was significantly higher in young subjects compared to aged subjects. In the aged subjects, localized vessel density was positively correlated with MoCA and IRT EF scores. The proposed pipeline is able to segment, quantify, and detect localized differences in vessel density of small cerebral blood vessels based on 3D high-resolution black-blood MRI. This framework may serve as a tool for localized detection of small vessel density changes in normal aging and cerebral small vessel disease.

Dataset Information

Excessive Visit-to-Visit Small and Dense Low-Density Lipoproteins Elevate Cerebral Small Vessel Disease Progression Risk in the Elderly.

Objective

Methods

Results

Conclusion

Publications

Excessive Visit-to-Visit Small and Dense Low-Density Lipoproteins Elevate Cerebral Small Vessel Disease Progression Risk in the Elderly.

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