ArticleBMC neurology2021
Association between small dense low-density lipoprotein cholesterol and neuroimaging markers of cerebral small vessel disease in middle-aged and elderly Chinese populations.
Article in BMC neurology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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11 citing papers in PubMed, 14 citations in OpenAlex.
- A web-based dynamic nomogram for individualized risk prediction of magnetic resonance imaging-defined cerebral small-vessel disease: Model development and internal validation.The Journal of international medical research · 2026Article
- Correlation Between Blood Glucose Level and Cerebral Small Vessel Disease Markers in Neurologically Asymptomatic, Nondiabetic Individuals.Aging medicine (Milton (N.S.W)) · 2025Article
- Bridging the gap: Exploring the intercurrent relationship between knee osteoarthritis and cerebral small vessel disease.Caspian journal of internal medicine · 2025Review
- Lipids, Apolipoproteins, Lipid-Lowering Drugs, and the Risk of Cerebral Small Vessel Disease: A Mendelian Randomization Study.Journal of the American Heart Association · 2024Article
- Establishment and evaluation of a clinical prediction model for cognitive impairment in patients with cerebral small vessel disease.BMC neuroscience · 2024Article
- SGLT1 and SGLT2 inhibition, circulating metabolites, and cerebral small vessel disease: a mediation Mendelian Randomization study.Cardiovascular diabetology · 2024Article
- Atherogenic circulating lipoproteins in ischemic stroke.Frontiers in cardiovascular medicine · 2024Review
- Alternations of Lipoprotein Profiles in the Plasma as Biomarkers of Huntington's Disease.Cells · 2023Article
- HDL-C/LDL-C and Risk of Cerebral White Matter Hyperintensities: A Cross-Sectional Study.International journal of general medicine · 2023Article
- Differential associations of lipoprotein(a) level with cerebral large artery and small vessel diseases.Stroke and vascular neurology · 2022Article
- Cerebral small vessel disease combined with cerebral collaterals to predict the prognosis of patients with acute large artery atherosclerotic stroke.Frontiers in neurology · 2022Article
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Authors and funding
9 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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.
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