AI Article Synopsis
- - Research has found links between lipids, cerebrospinal fluid (CSF) metabolites, and Late-Onset Alzheimer's Disease (LOAD), but how they causally interact is still uncertain.
- - Using statistical data from GWAS, the study examined the causal relationship between lipids and LOAD, revealing that predicted cholesterol decreases LOAD risk, while a specific type of phosphatidylcholine increases it, with a CSF metabolite identified as a potential mediator.
- - The results emphasize the importance of CSF metabolites in understanding how lipids contribute to LOAD, suggesting they could serve as valuable biomarkers for diagnosis and prevention.
Article Abstract
Background: Although research has indicated correlations between lipids, cerebrospinal fluid (CSF) metabolites, and Late-Onset Alzheimer's Disease (LOAD), the specific causal relationships among these elements, as well as the roles and mechanisms of the cerebrospinal fluid metabolites, remain unclear.
Methods: Statistical datasets derived from Genome-Wide Association Studies (GWAS) were utilized to assess the bidirectional causal relationships between lipids and LOAD. Subsequently, genetic variants associated with CSF metabolites and established lipids underwent a two-step Mendelian randomization (MR) analysis to explore potential mediators and analyze mediation effects. Sensitivity analyses were employed to assess the robustness of the detection systems.
Results: Genetically predicted cholesterol (IVW OR = 0.989; 95% CI 0.982-0.996) was found to reduce the risk of LOAD, whereas Phosphatidylcholine (PC) (18:1_0:0) (IVW OR = 1.015; 95% CI 1.005-1.025) posed a risk factor. The potential mediator, CSF metabolite N-acetylneuraminate (NeuAC), was identified with a mediation proportion of 21.02% (3.25%, 45.50%). No pleiotropy or heterogeneity was detected across MR analyses.
Conclusions: The findings underscore the pivotal role of CSF metabolomics in elucidating the lipid-mediated pathogenesis of LOAD, highlighting potential diagnostic and preventative biomarkers.
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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11603644 | PMC |
| http://dx.doi.org/10.1186/s12967-024-05796-2 | DOI Listing |
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