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Investigating associations between blood metabolites, later life brain imaging measures, and genetic risk for Alzheimer's disease. | LitMetric

AI Article Synopsis

  • - The study investigates how blood metabolites are linked to brain health, specifically looking at brain volume and signs of Alzheimer's disease among participants aged 60-64, using data from the Insight 46 study.
  • - Researchers analyzed data from 1019 metabolites across 1740 participants, utilizing imaging techniques and advanced statistical methods to identify significant associations between metabolites and brain health indicators.
  • - Three identified lipid metabolite groups showed a strong correlation with brain volume measures, including a group enriched with sphingolipids linked to hippocampal volume and another linked to fatty acid pathways impacting whole-brain volume.

Article Abstract

Background: Identifying blood-based signatures of brain health and preclinical pathology may offer insights into early disease mechanisms and highlight avenues for intervention. Here, we systematically profiled associations between blood metabolites and whole-brain volume, hippocampal volume, and amyloid-β status among participants of Insight 46-the neuroscience sub-study of the National Survey of Health and Development (NSHD). We additionally explored whether key metabolites were associated with polygenic risk for Alzheimer's disease (AD).

Methods: Following quality control, levels of 1019 metabolites-detected with liquid chromatography-mass spectrometry-were available for 1740 participants at age 60-64. Metabolite data were subsequently clustered into modules of co-expressed metabolites using weighted coexpression network analysis. Accompanying MRI and amyloid-PET imaging data were present for 437 participants (age 69-71). Regression analyses tested relationships between metabolite measures-modules and hub metabolites-and imaging outcomes. Hub metabolites were defined as metabolites that were highly connected within significant (p < 0.05) modules or were identified as a hub in a previous analysis on cognitive function in the same cohort. Regression models included adjustments for age, sex, APOE genotype, lipid medication use, childhood cognitive ability, and social factors. Finally, associations were tested between AD polygenic risk scores (PRS), including and excluding the APOE region, and metabolites and modules that significantly associated (p < 0.05) with an imaging outcome (N = 1638).

Results: In the fully adjusted model, three lipid modules were associated with a brain volume measure (p < 0.05): one enriched in sphingolipids (hippocampal volume: ß = 0.14, 95% CI = [0.055,0.23]), one in several fatty acid pathways (whole-brain volume: ß =  - 0.072, 95%CI = [- 0.12, - 0.026]), and another in diacylglycerols and phosphatidylethanolamines (whole-brain volume: ß =  - 0.066, 95% CI = [- 0.11, - 0.020]). Twenty-two hub metabolites were associated (p < 0.05) with an imaging outcome (whole-brain volume: 22; hippocampal volume: 4). Some nominal associations were reported for amyloid-β, and with an AD PRS in our genetic analysis, but none survived multiple testing correction.

Conclusions: Our findings highlight key metabolites, with functions in membrane integrity and cell signalling, that associated with structural brain measures in later life. Future research should focus on replicating this work and interrogating causality.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9945600PMC
http://dx.doi.org/10.1186/s13195-023-01184-yDOI Listing

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