Genetic overlap between Alzheimer's disease and blood lipid levels

Exploration of plasma biomarkers for Alzheimer's disease by targeted lipid metabolomics based on nuclear magnetic resonance (NMR) spectroscopy

Alzheimer's disease (AD) is the most common cause of dementia, but the disease lacks convenient and cost-effective alternative biomarkers currently. We utilized targeted lipid metabolomics based on nuclear magnetic resonance (NMR) spectroscopy to identify plasma biomarkers in AD patients. Our study was a cross-sectional study that enrolled 58 AD patients and 40 matched health controls (HCs). Firstly, we identified plasma lipid metabolites that were significantly different between the two groups based on P < 0.05 and variable importance in the projection (VIP) > 1. Then we examined the correlation between the lipid metabolites and cognitive function using partial correlation analysis and assessed the diagnostic ability of the lipid metabolites using receiver operating characteristic (ROC) curves. Seventeen lipoproteins showed significant differences between AD patients and HCs among 114 lipid metabolites. All 17 lipoproteins were subtypes of low-density lipoprotein (LDL). Among them, LDL-3 particle number, LDL-3 apolipoprotein-B, LDL-3 phospholipids, LDL free cholesterol and LDL phospholipids were significantly correlated with cognitive function. The ROC curves showed that LDL-2 triglycerides (TG) and LDL-3 TG could significantly distinguish AD patients from HCs, with the area under the curve (AUC) above 0.7. In addition, we explored a strategy of combined diagnosis that significantly improved the diagnostic efficacy for AD (AUC = 0.879). Our study provides insight into the lipoprotein alterations associated with AD and potential biomarkers for its diagnosis and cognitive function assessment.

Investigating Genetic Overlap between Alzheimer's Disease, Lipids, and Coronary Artery Disease: A Large-Scale Genome-Wide Cross Trait Analysis

There is evidence to support a link between abnormal lipid metabolism and Alzheimer's disease (AD) risk. Similarly, observational studies suggest a comorbid relationship between AD and coronary artery disease (CAD). However, the intricate biological mechanisms of AD are poorly understood, and its relationship with lipids and CAD traits remains unresolved. Conflicting evidence further underscores the ongoing investigation into this research area. Here, we systematically assess the cross-trait genetic overlap of AD with 13 representative lipids (from eight classes) and seven CAD traits, leveraging robust analytical methods, well-powered large-scale genetic data, and rigorous replication testing. Our main analysis demonstrates a significant positive global genetic correlation of AD with triglycerides and all seven CAD traits assessed-angina pectoris, cardiac dysrhythmias, coronary arteriosclerosis, ischemic heart disease, myocardial infarction, non-specific chest pain, and coronary artery disease. Gene-level analyses largely reinforce these findings and highlight the genetic overlap between AD and three additional lipids: high-density lipoproteins (HDLs), low-density lipoproteins (LDLs), and total cholesterol. Moreover, we identify genome-wide significant genes (Fisher's combined p value [FCPgene] < 2.60 × 10-6) shared across AD, several lipids, and CAD traits, including WDR12, BAG6, HLA-DRA, PHB, ZNF652, APOE, APOC4, PVRL2, and TOMM40. Mendelian randomisation analysis found no evidence of a significant causal relationship between AD, lipids, and CAD traits. However, local genetic correlation analysis identifies several local pleiotropic hotspots contributing to the relationship of AD with lipids and CAD traits across chromosomes 6, 8, 17, and 19. Completing a three-way analysis, we confirm a strong genetic correlation between lipids and CAD traits-HDL and sphingomyelin demonstrate negative correlations, while LDL, triglycerides, and total cholesterol show positive correlations. These findings support genetic overlap between AD, specific lipids, and CAD traits, implicating shared but non-causal genetic susceptibility. The identified shared genes and pleiotropic hotspots are valuable targets for further investigation into AD and, potentially, its comorbidity with CAD traits.

Upstream lipid and metabolic systems are potential causes of Alzheimer's disease, Parkinson's disease and dementias

Brain health requires circuits, cells and molecular pathways to adapt when challenged and to promptly reset once the challenge has resolved. Neurodegeneration occurs when adaptability becomes confined, causing challenges to overwhelm neural circuitry. Studies of rare and common neurodegenerative diseases suggest that the accumulation of lipids can compromise circuit adaptability. Using microglia as an example, we review data that suggest increased lipid concentrations cause dysfunctional inflammatory responses to immune challenges, leading to Alzheimer's disease, Parkinson's disease and dementia. We highlight current approaches to treat lipid metabolic and clearance pathways and identify knowledge gaps towards restoring adaptive homeostasis in individuals who are at-risk of losing cognition.

Gut microbiota in combination with blood metabolites reveals characteristics of the disease cluster of coronary artery disease and cognitive impairment: a Mendelian randomization study

Background

The coexistence of coronary artery disease (CAD) and cognitive impairment has become a common clinical phenomenon. However, there is currently limited research on the etiology of this disease cluster, discovery of biomarkers, and identification of precise intervention targets.

Methods

We explored the causal connections between gut microbiota, blood metabolites, and the disease cluster of CAD combined with cognitive impairment through two-sample Mendelian randomization (TSMR). Additionally, we determine the gut microbiota and blood metabolites with the strongest causal associations using Bayesian model averaging multivariate Mendelian randomization (MR-BMA) analysis. Furthermore, we will investigate the mediating role of blood metabolites through a two-step Mendelian randomization design.

Results

We identified gut microbiota that had significant causal associations with cognitive impairment. Additionally, we also discovered blood metabolites that exhibited significant causal associations with both CAD and cognitive impairment. According to the MR-BMA results, the free cholesterol to total lipids ratio in large very low density lipoprotein (VLDL) was identified as the key blood metabolite significantly associated with CAD. Similarly, the cholesteryl esters to total lipids ratio in small VLDL emerged as the primary blood metabolite with a significant causal association with dementia with lewy bodies (DLB). For the two-step Mendelian randomization analysis, we identified blood metabolites that could potentially mediate the association between genus Butyricicoccus and CAD in the potential causal links.

Conclusion

Our study utilized Mendelian randomization (MR) to identify the gut microbiota features and blood metabolites characteristics associated with the disease cluster of CAD combined with cognitive impairment. These findings will provide a meaningful reference for the identification of biomarkers for the disease cluster of CAD combined with cognitive impairment as well as the discovery of targets for intervention to address the problems in the clinic.

Metabolic Overlap between Alzheimer's Disease and Metabolic Syndrome Identifies the PVRL2 Gene as a New Modulator of Diabetic Dyslipidemia

BACKGROUND

Alzheimer's disease (AD) and type 2 diabetes mellitus (T2DM) share metabolic alterations such as abnormal insulin and lipid metabolism and have some common genetic factors such as APOE genotype. Taking this into account, we hypothesized that we could identify common genetic factors involved in the development of diabetes and cardiovascular diseases.

METHODOLOGY

We first genotyped 48 single nucleotide polymorphisms (SNPs) previously associated with AD in a cohort composed of 330 patients with cognitive impairment (CI) to assess their association with plasma lipids. Second, we conducted pleiotropy-informed conjunctional false discovery rate (FDR) analysis designed to identify shared variants between AD and plasma lipid levels. Finally, we used the SNPs to be found associated with lipid parameters and AD to search for associations with lipoprotein parameters in 281 patients with cardiometabolic risk.

RESULTS

Five SNPs were significantly associated with lower levels of cholesterol transported in remnant lipoprotein particles (RLPc) in subjects with CI; among these SNPs was the rs73572039 variant in PVRL2. Stratified QQ-plots were conducted on GWAS designed for AD and triglycerides (TG). The cross-trait analysis resulted in a total of 22 independent genomic loci associated with both AD and TG levels with a conjFDR < 0.05. Among these loci, two pleiotropic variants were located in PVRL2 (rs12978931 and rs11667640). The three SNPs in PVRL2 were significantly associated with RLPc, TG, and number of circulating VLDL and HDL particles in subjects with cardiometabolic risk.

CONCLUSIONS

We have identified three variants in PVRL2 that predispose individuals to AD that also influence the lipid profile that confers cardiovascular risk in T2DM subjects. PVRL2 is a potential new modulating factor of atherogenic dyslipidemia.

Metabolic perspective of astrocyte dysfunction in Alzheimer's disease and type 2 diabetes brains

The term type III diabetes (T3DM) has been proposed for Alzheimer's disease (AD) due to the shared molecular and cellular features between type 2 diabetes (T2DM) and insulin resistance-associated memory deficits and cognitive decline in elderly individuals. Astrocytes elicit neuroprotective or deleterious effects in AD progression and severity. Patients with T2DM are at a high risk of cognitive impairment, and targeting astrocytes might be promising in alleviating neurodegeneration in the diabetic brain. Recent studies focusing on cell-specific activities in the brain have revealed the important role of astrocytes in brain metabolism (e.g., glucose metabolism, lipid metabolism), neurovascular coupling, synapses, and synaptic plasticity. In this review, we discuss how astrocytes and their dysfunction result in multiple pathological and clinical features of AD and T2DM from a metabolic perspective and the potential comorbid mechanism in these two diseases from the perspective of astrocytes.

Quantitative NMR-Based Lipoprotein Analysis Identifies Elevated HDL-4 and Triglycerides in the Serum of Alzheimer’s Disease Patients

Alzheimer’s disease (AD) is the most common form of dementia in the elderly and has been associated with changes in lipoprotein metabolism. We performed quantitative lipoprotein analysis in a local cohort of cognitively impaired elderly and control subjects using standardized nuclear magnetic resonance (NMR) spectroscopy. A commercially available quantitative NMR-based assay covering 112 lipoprotein main and subtype variables was used to investigate blood serum samples from a moderate cohort size of 161 persons (71 female, 90 male), including measures of quality control. Additionally, clinical metadata and cerebrospinal fluid AD biomarkers were collected and used for analysis. High-density lipoprotein (HDL) HDL-4 subfraction levels were mostly high in female individuals with mild cognitive impairment (MCI), followed by AD. Low-density lipoprotein (LDL) LDL-2 cholesterol was slightly elevated in male AD patients. HDL-2 apolipoprotein Apo-A1, HDL-2 phospholipids, and HDL-3 triglycerides were highly abundant in AD and MCI women compared to men. When considering clinical biomarkers (Aβ, tau), very low-density lipoprotein (VLDL) VLDL-1 and intermediate-density lipoprotein (IDL) triglycerides were substantially higher in AD compared to MCI. In addition, triglyceride levels correlated positively with dementia. Different lipoprotein serum patterns were identified for AD, MCI, and control subjects. Interestingly, HDL-4 and LDL-2 cholesterol parameters revealed strong gender-specific changes in the context of AD-driven dementia. As gender-based comparisons were based on smaller sub-groups with a low n-number, several statistical findings did not meet the significance threshold for multiple comparisons testing. Still, our finding suggests that serum HDL-4 parameters and various triglycerides correlate positively with AD pathology which could be a read-out of extended lipids traveling through the blood-brain barrier, supporting amyloid plaque formation processes. Thereof, we see herein a proof of concept that this quantitative NMR-based lipoprotein assay can generate important and highly interesting data for refined AD diagnosis and patient stratification, especially when larger cohorts are available.