Associations between low circulatory low-density lipoprotein cholesterol level and brain health in non-stroke non-demented subjects

Lipoproteins and metabolites in diagnosing and predicting Alzheimer's disease using machine learning

BACKGROUND

Alzheimer's disease (AD) is a chronic neurodegenerative disorder that poses a substantial economic burden. The Random forest algorithm is effective in predicting AD; however, the key factors influencing AD onset remain unclear. This study aimed to analyze the key lipoprotein and metabolite factors influencing AD onset using machine-learning methods. It provides new insights for researchers and medical personnel to understand AD and provides a reference for the early diagnosis, treatment, and early prevention of AD.

METHODS

A total of 603 participants, including controls and patients with AD with complete lipoprotein and metabolite data from the Alzheimer's disease Neuroimaging Initiative (ADNI) database between 2005 and 2016, were enrolled. Random forest, Lasso regression, and CatBoost algorithms were employed to rank and filter 213 lipoprotein and metabolite variables. Variables with consistently high importance rankings from any two methods were incorporated into the models. Finally, the variables selected from the three methods, with the participants' age, sex, and marital status, were used to construct a random forest predictive model.

RESULTS

Fourteen lipoprotein and metabolite variables were screened using the three methods, and 17 variables were included in the AD prediction model based on age, sex, and marital status of the participants. The optimal random forest modeling was constructed with "mtry" set to 3 and "ntree" set to 300. The model exhibited an accuracy of 71.01%, a sensitivity of 79.59%, a specificity of 65.28%, and an AUC (95%CI) of 0.724 (0.645-0.804). When Mean Decrease Accuracy and Gini were used to rank the proteins, age, phospholipids to total lipids ratio in intermediate-density lipoproteins (IDL_PL_PCT), and creatinine were among the top five variables.

CONCLUSIONS

Age, IDL_PL_PCT, and creatinine levels play crucial roles in AD onset. Regular monitoring of lipoproteins and their metabolites in older individuals is significant for early AD diagnosis and prevention.

Associations of Triglycerides and Atherogenic Index of Plasma with Brain Structure in the Middle-Aged and Elderly Adults

Triglyceride (TG) and atherogenic index of plasma (AIP) have been acknowledged to be risk factors for vascular insults, but their impacts on the brain system remain elusive. To fill in some gaps, we investigated associations of TG and AIP with brain structure, leveraging the UK Biobank database. TG and high-density lipoprotein cholesterol (HDL-C) were examined at baseline and AIP was calculated as log (TG/HDL-C). We build several linear regression models to estimate associations of TG and AIP with volumes of brain grey matter phenotypes. Significant inverse associations of TG and AIP with volumes of specific subcortical traits were observed, among which TG and AIP were most significantly associated with caudate nucleus (TG: β [95% confidence interval CI] = -0.036 [-0.051, -0.022], AIP: -0.038 [-0.053, -0.023]), thalamus (-0.029 [-0.042, -0.017], -0.032 [-0.045, -0.019]). Higher TG and AIP were also considerably related with reduced cortical structure volumes, where two most significant associations of TG and AIP were with insula (TG: -0.035 [-0.048, -0.022], AIP: -0.038 [-0.052, -0.025]), superior temporal gyrus (-0.030 [-0.043, -0.017], -0.033 [-0.047, -0.020]). Modification effects of sex and regular physical activity on the associations were discovered as well. Our findings show adverse associations of TG and AIP with grey matter volumes, which has essential public health implications for early prevention in neurodegenerative diseases.

Important roles of linoleic acid and α-linolenic acid in regulating cognitive impairment and neuropsychiatric issues in metabolic-related dementia

Metabolic syndrome (MetS), which is characterized by insulin resistance, high blood glucose, obesity, and dyslipidemia, is known to increase the risk of dementia accompanied by memory loss and depression. The direct pathways and specific mechanisms in the central nervous system (CNS) for addressing fatty acid imbalances in MetS have not yet been fully elucidated. Among polyunsaturated acids, linoleic acid (LA, n6-PUFA) and α-linolenic acid (ALA, n3-PUFA), which are two essential fatty acids that should be provided by food sources (e.g., vegetable oils and seeds), have been reported to regulate various cellular mechanisms including apoptosis, inflammatory responses, mitochondrial biogenesis, and insulin signaling. Furthermore, inadequate intake of LA and ALA is reported to be involved in neuropathology and neuropsychiatric diseases as well as imbalanced metabolic conditions. Herein, we review the roles of LA and ALA on metabolic-related dementia focusing on insulin resistance, dyslipidemia, synaptic plasticity, cognitive function, and neuropsychiatric issues. This review suggests that LA and ALA are important fatty acids for concurrent treatment of both MetS and neurological problems.

Association of Plasma Lipids with White Matter Hyperintensities in Patients with Acute Ischemic Stroke

Purpose

White matter hyperintensities (WMH) are the common marker of cerebral small vessel disease (CSVD). Dyslipidemia plays a notable role in the pathogenesis of CSVD. However, the relationship between dyslipidemia and WMH is poorly elucidated. This study aims to investigate the association between serum lipid fractions and WMH in patients with acute ischemic stroke (AIS).

Patients and Methods

A total of 901 patients with AIS were included in this study. The burden of WMH, including deep white matter hyperintensities (DWMH), periventricular white matter hyperintensities (PVWMH), and total WMH load, were evaluated on magnetic resonance imaging (MRI) by the Fazekas scale. All the WMH burden were set as dichotomous variables. Serum levels of triglycerides (TG), total cholesterol (TC), low-density lipoprotein cholesterol (LDL-c), and high-density lipoprotein cholesterol (HDL-c) were collected. The association of serum lipid fractions with WMH burden was analyzed using univariate and multivariate logistic regression models.

Results

The average age of the participants was 67.6±11.6 years, and 584 cases (64.8%) were male. About 33.5% (n = 302) patients were smoker, and 23.5% (n = 212) patients had a history of alcohol consumption. The proportion of previous diabetes, ischemic cardiomyopathy and hypertension was 39.0% (n = 351), 21.2% (n = 191) and 75.9% (n = 684), respectively. The average of serum HDL-c, TC, TG, LDL-c levels for all participants were 1.26 ± 0.28 mmol/l, 4.54 ± 1.06 mmol/l, 1.67 ± 1.09 mmol/l, 3.08 ± 0.94 mmol/l. There were no statistical associations between HDL-c, TG, TC, LDL-c and each type of WMH burden (P > 0.05) in multivariate logistic regression analysis. Similar findings were found in subgroup analysis based on gender classification.

Conclusion

Serum lipid levels were not associated with the presence of any type of WMH in patients with AIS.

The global burden of cerebral small vessel disease in low- and middle-income countries: A systematic review and meta-analysis

BACKGROUND

Cerebral small vessel disease (cSVD) is a major cause of stroke and dementia. Previous studies on the prevalence of cSVD are mostly based on single geographically defined cohorts in high-income countries. Studies investigating the prevalence of cSVD in low- and middle-income countries (LMICs) are expanding but have not been systematically assessed.

AIM

This study aims to systematically review the prevalence of cSVD in LMICs.

RESULTS

Articles were searched from the Ovid MEDLINE and EMBASE databases from 1 January 2000 to 31 March 2022, without language restrictions. Title/abstract screening, full-text review, and data extraction were performed by two to seven independent reviewers. The prevalence of cSVD and study sample size were extracted by pre-defined world regions and health status. The Risk of Bias for Non-randomized Studies tool was used. The protocol was registered on PROSPERO (CRD42022311133). A meta-analysis of proportion was performed to assess the prevalence of different magnetic resonance imaging markers of cSVD, and a meta-regression was performed to investigate associations between cSVD prevalence and type of study, age, and male: female ratio. Of 2743 studies identified, 42 studies spanning 12 global regions were included in the systematic review. Most of the identified studies were from China (n = 23). The median prevalence of moderate-to-severe white matter hyperintensities (WMHs) was 20.5%, 40.5%, and 58.4% in the community, stroke, and dementia groups, respectively. The median prevalence of lacunes was 0.8% and 33.5% in the community and stroke groups. The median prevalence of cerebral microbleeds (CMBs) was 10.7% and 22.4% in the community and stroke groups. The median prevalence of moderate-to-severe perivascular spaces was 25.0% in the community. Meta-regression analyses showed that the weighted median age (51.4 ± 0.0 years old; range: 36.3-80.2) was a significant predictor of the prevalence of moderate-to-severe WMH and lacunes, while the type of study was a significant predictor of the prevalence of CMB. The heterogeneity of studies was high (>95%). Male participants were overrepresented.

CONCLUSIONS

This systematic review and meta-analysis provide data on cSVD prevalence in LMICs and demonstrated the high prevalence of the condition. cSVD research in LMICs is being published at an increasing rate, especially between 2010 and 2022. More data are particularly needed from Sub-Saharan Africa and Central Europe, Eastern Europe, and Central Asia.

Dyslipidemia induced large-scale network connectivity abnormality facilitates cognitive decline in the Alzheimer's disease

BACKGROUND

Although lipid metabolite dysfunction contributes substantially to clinical signs and pathophysiology of Alzheimer's disease (AD), how dyslipidemia promoting neuropathological processes and brain functional impairment subsequently facilitates the progression of AD remains unclear.

METHODS

We combined large-scale brain resting-state networks (RSNs) approaches with canonical correlation analysis to explore the accumulating effects of lipid gene- and protein-centric levels on cerebrospinal fluid (CSF) biomarkers, dynamic trajectory of large-scale RSNs, and cognitive performance across entire AD spectrum. Support vector machine model was used to distinguish AD spectrum and pathway analysis was used to test the influences among these variables.

RESULTS

We found that the effects of accumulation of lipid-pathway genetic variants and lipoproteins were significantly correlated with CSF biomarkers levels and cognitive performance across the AD spectrum. Dynamic trajectory of large-scale RSNs represented a rebounding mode, which is characterized by a weakened network cohesive connector role and enhanced network incohesive provincial role following disease progression. Importantly, the fluctuating large-scale RSNs connectivity was significantly correlated with the summative effects of lipid-pathway genetic variants and lipoproteins, CSF biomarkers, and cognitive performance. Moreover, SVM model revealed that the lipid-associated twenty-two brain network connections represented higher capacity to classify AD spectrum. Pathway analysis further identified dyslipidemia directly influenced brain network reorganization or indirectly affected the CSF biomarkers and subsequently caused cognitive decline.

CONCLUSIONS

Dyslipidemia exacerbated cognitive decline and increased the risk of AD via mediating large-scale brain networks integrity and promoting neuropathological processes. These findings reveal a role for lipid metabolism in AD pathogenesis and suggest lipid management as a potential therapeutic target for AD.

The Relationship Between Low-Density Lipoprotein Cholesterol and Progression of Mild Cognitive Impairment: The Influence of rs6859 in PVRL2

Background: Genome-wide association studies have identified many Alzheimer’s disease (AD) genetic-risk single nucleotide polymorphisms (SNPs) and indicated the important role of the cholesterol/lipid metabolism pathway in AD pathogenesis. This study aims to investigate the effects of cholesterol and genetic risk factors on progression of mild cognitive impairment (MCI) to AD.

Methods: We prospectively followed 316 MCI participants aged ≥50 years with a baseline cholesterol profile and SNP genotyping data for 4.5 years on average in a sub-cohort of the Shanghai Aging Study. Total cholesterol, low-density lipoprotein cholesterol (LDL-C), and high-density lipoprotein cholesterol in serum were measured at baseline. SNP genotyping was performed using a MassARRAY system. At follow-up, consensus diagnosis of incident dementia and AD were established based on medical, neurological, and neuropsychological examinations. Cox regression models were used to assess the association of cholesterol and SNP with incident AD.

Results: The AG/AA genotypes of PVRL2 rs6859 were significantly associated with increased incident AD in MCI participants, compared with GG genotype (adjusted hazard ratio [HR] 2.75, 95% confidence interval [CI] 1.32–5.76, p = .007, false discovery rate–adjusted p = .030). In PVRL2 rs6859 AG/AA carriers, each-1 mmol/L higher level of LDL-C was significantly associated with a 48% decreased risk of AD (adjusted HR 0.52, 95%CI 0.33–0.84, p = .007). Consistent results were obtained when using LDL-C as the categorical variable (P for trend = 0.016).

Conclusion: The relationship between LDL-C and progression of MCI may be influenced by genetic variants.

Associations of dietary markers with brain volume and connectivity: A systematic review of MRI studies

The high prevalence of unhealthy dietary patterns and related brain disorders, such as dementia, emphasizes the importance of research that examines the effect of dietary factors on brain health. Identifying markers of brain health, such as volume and connectivity, that relate to diet is an important first step towards understanding the lifestyle determinants of healthy brain ageing. We conducted a systematic review of 52 studies (total n = 21,221 healthy participants aged 26-80 years, 55 % female) that assessed with a range of MRI measurements, which brain areas, connections, and cerebrovascular factors were associated with dietary markers. We report associations between regional brain measures and dietary health. Collectively, lower diet quality was related to reduced brain volume and connectivity, especially in white and grey matter of the frontal, temporal and parietal lobe, cingulate, entorhinal cortex and the hippocampus. Associations were also observed in connecting fibre pathways and in particular the default-mode, sensorimotor and attention networks. However, there were also some inconsistencies in research methods and findings. We recommend that future research use more comprehensive and consistent dietary measures, more representative samples, and examine the role of key subcortical regions previously highlighted in relevant animal work.

Elevated lipids are associated with reduced regional brain structure in youth with bipolar disorder

OBJECTIVE

Abnormal blood lipid levels are common in bipolar disorder (BD) and correlate with mood symptoms and neurocognition. However, studies have not examined the lipid-brain structure association in BD or youth.

METHODS

This study examined low-density lipoprotein (LDL-C), high-density lipoprotein (HDL-C), triglycerides, and total cholesterol (TC) levels in relation to brain structure utilizing T1-weighted images, among participants ages 13-20 with BD (n = 55) and healthy controls (HC; n = 47). General linear models investigated group differences in the association of lipids with anterior cingulate cortex (ACC), hippocampus, and inferior parietal lobe structure, controlling for age, sex, body mass index, and intracranial volume. For significant associations, post hoc within-group analyses were undertaken. Exploratory vertex-wise analyses further investigated group differences in the lipid-brain structure association.

RESULTS

There were significant group differences in the association of LDL-C (β = -0.29 p = 0.001), and TC (β = -0.21 p = 0.016), with hippocampal volume, and triglycerides with ACC volume (β = -0.25 p = 0.01) and area (β = -0.26 p = 0.004). Elevated lipids were associated with smaller brain structure to a significantly greater extent in BD vs HC. Post hoc analyses revealed that elevated LDL-C (β = -0.27 p = 0.007) and reduced HDL-C (β = 0.24 p = 0.01) were associated with smaller hippocampal volume in the BD group. Exclusion of BD second-generation antipsychotic users did not alter these results. Vertex-wise analyses further showed that elevated lipids were associated with smaller brain structure to a significantly greater extent in BD vs HC, across the cortex.

CONCLUSION

Elevated lipids are associated with smaller brain structure in BD. Research evaluating lipid-brain structure associations prospectively and whether lipid optimization has salutary effects on brain structure is necessary.

Preliminary Study of Subclinical Brain Alterations in Patients With Asymptomatic Carotid Vulnerable Plaques Using Intravoxel Incoherent Motion Imaging by Voxelwise Comparison: A Study of Whole-Brain Imaging Measures

Objective

To preliminarily explore subclinical brain alterations in an asymptomatic carotid vulnerable plaque group based on intravoxel incoherent motion (IVIM) imaging through voxelwise comparison in the whole brain.

Materials and Methods

Forty-nine elderly participants underwent multi-b-value DWI, of whom 24 participants with asymptomatic carotid vulnerable plaques and <50% stenosis served as the test group, while the rest served as the healthy control group. After fitting the double-exponential model, slow ADC (Ds) and the fraction of fast ADC (f) values of the whole brain were obtained, which then were compared in a voxelwise manner by two-sample t-test. Multiple comparisons were corrected by the family-wise error (FWE) method with a corrected threshold of P < 0.05. Pearson correlations between IVIM parameters in altered brain regions and blood pressure, glucose, lipid, and homocysteine were calculated.

Results

For the test group, the Z-normalized Ds values were significantly higher in the left median cingulate and paracingulate gyrus (DCG.L), posterior cingulate gyrus (PCG. L), and left precuneus gyrus (PCUN.L) (cluster size = 156) and in the left middle frontal gyrus (MFG.L), orbital middle frontal gyrus (ORBmid.L), and superior frontal gyrus (SFG.L) (cluster size = 165); the Z-normalized Ds values were significantly lower in the right middle temporal gyrus (MTG.R) and inferior temporal gyrus (ITG.R) (cluster size = 116); and the Z-normalized f-values were significantly lower in the MTG.R and ITG.R (cluster size = 85) (p < 0.05, FWE correction). LDL-C was negatively correlated with the Z-normalized Ds values in the DCG.L, PCG.L, and PCUN.L (r = 0.601, p = 0.002). LDL-C was positively correlated with the Z-normalized f-value in the MTG.R and ITG.R (r = 0.405, p = 0.05). Systolic blood pressure was positively correlated with the Z-normalized Ds values in the MFG.L, ORBmid.L, and SFG.L (r = 0.433, p = 0.035).

Conclusion

This study was the first to detect subclinical brain alterations in asymptomatic carotid vulnerable plaque group through IVIM using whole-brain voxelwise comparisons, which were partially correlated with blood pressure and lipids. Thus, IVIM might be utilized as a noninvasive biomarker of microvascular and microstructural brain changes in the asymptomatic carotid vulnerable plaque group.

Low Cholesterol Level Linked to Reduced Semantic Fluency Performance and Reduced Gray Matter Volume in the Medial Temporal Lobe

Hyperlipidemia has been proposed as a risk factor of dementia and cognitive decline. However, the findings of the relationship between cholesterol level and cognitive/brain function have been inconsistent. Here, using a well-controlled sample from the Parkinson's Progression Markers Initiative (PPMI), we investigated the probable non-linear relationship between plasma total cholesterol (TC) level, gray matter volume (GMv), and cognitive performance in 117 non-demented subjects (mean age, 61.5 ± 8.9 years), including 67 Parkinson's disease (PD) patients and 50 demographically matched controls. A quadratic relationship between semantic fluency (SF) performance and TC levels was identified. Within the subjects with a desirable TC level (TC < 200 mg/dl), low TC (lTC) levels were associated with reduced SF performance, as well as reduced GMv in three medial temporal regions [including bilateral anterior hippocampus (HIP)]. In contrast, no significant relationship between TC and cognition performance/GMv was found in individuals with a high cholesterol level (i.e., TC ≥ 200 mg/dl). Further region of interest (ROI)-based analysis showed that individuals with TC levels ranging from 100 to 160 mg/dl had the lowest GMv in the medial temporal regions. These findings suggest that low-normal TC level may be associated with reduced cognitive function and brain atrophy in regions implicated in neurodegenerative diseases, adding to a growing body of literature supporting a probable non-linear relationship between cholesterol level and brain health. However, this finding needs to be verified with other large public cohort data that do not include PD patients.

Gray matter reduction related to decreased serum creatinine and increased triglyceride, Hemoglobin A1C, and low-density lipoprotein in subjects with obesity

PURPOSE

Altered brain volume and metabolic variables have been found in subjects with obesity. However, the role of metabolic parameters in gray matter volume (GMV) has been poorly investigated. This study aimed to investigate the relationship between the metabolic parameters and brain volume in subjects with obesity.

METHODS

Thirty-seven subjects with obesity and 39 age and sex matched normal-weight controls were included in this study. Eighteen of the 37 participants who underwent sleeve gastrectomy were included in the longitudinal analysis. Blood samples and high-resolution 3T T1-weighted magnetic resonance images were collected. Metabolic parameters in plasma and GMV were measured.

RESULTS

Multiple linear regression analysis showed that gray matter reduction in several cognition-related cortices including right angular gyrus, superior occipital cortex, superior parietal cortex, and cerebellum was related to decreased creatinine, as well as increased triglyceride, HbA1c, and low-density lipoprotein in plasma in subjects with obesity. Weight loss after the surgery induced significant recovery of altered metabolic parameters and decreased gray matter volume. Furthermore, changes in the four metabolic parameters before and after the surgery were associated with changes in gray matter volume.

CONCLUSION

Our results suggest that the gray matter reduction is related to decreased creatinine as well as increased triglyceride, HbA1c, and low-density lipoprotein in plasma in subjects with obesity.

Characterization of White Matter Hyperintensities in Large-Scale MRI-Studies

Background: White matter hyperintensities of presumed vascular origin (WMH) are a common finding in elderly people and a growing social malady in the aging western societies. As a manifestation of cerebral small vessel disease, WMH are considered to be a vascular contributor to various sequelae such as cognitive decline, dementia, depression, stroke as well as gait and balance problems. While pathophysiology and therapeutical options remain unclear, large-scale studies have improved the understanding of WMH, particularly by quantitative assessment of WMH. In this review, we aimed to provide an overview of the characteristics, research subjects and segmentation techniques of these studies.

Methods: We performed a systematic review according to the PRISMA statement. One thousand one hundred and ninety-six potentially relevant articles were identified via PubMed search. Six further articles classified as relevant were added manually. After applying a catalog of exclusion criteria, remaining articles were read full-text and the following information was extracted into a standardized form: year of publication, sample size, mean age of subjects in the study, the cohort included, and segmentation details like the definition of WMH, the segmentation method, reference to methods papers as well as validation measurements.

Results: Our search resulted in the inclusion and full-text review of 137 articles. One hundred and thirty-four of them belonged to 37 prospective cohort studies. Median sample size was 1,030 with no increase over the covered years. Eighty studies investigated in the association of WMH and risk factors. Most of them focussed on arterial hypertension, diabetes mellitus type II and Apo E genotype and inflammatory markers. Sixty-three studies analyzed the association of WMH and secondary conditions like cognitive decline, mood disorder and brain atrophy. Studies applied various methods based on manual (3), semi-automated (57), and automated segmentation techniques (75). Only 18% of the articles referred to an explicit definition of WMH.

Discussion: The review yielded a large number of studies engaged in WMH research. A remarkable variety of segmentation techniques was applied, and only a minority referred to a clear definition of WMH. Most addressed topics were risk factors and secondary clinical conditions. In conclusion, WMH research is a vivid field with a need for further standardization regarding definitions and used methods.