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Genetic and Phenotypic Architecture of Brain Glymphatic System
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AbstractBackgroundThe glymphatic system plays a crucial role in clearing metabolic waste from the brain, facilitating waste exchange between cerebrospinal fluid and interstitial fluid, and supporting brain homeostasis. However, quantifying glymphatic function has been challenging. The Diffusion Tensor Imaging Along the Perivascular Space (DTI-ALPS) method offers a non-invasive approach to assess glymphatic function by calculating an index that reflects fluid mobility within the brain. This study aimed to identify genetic variants associated with the ALPS index and explore its relationships with metabolic, immune, cognitive, and health-related phenotypes.MethodsData from 43,823 participants in the UK Biobank were analyzed. After rigorous quality control, 36,997 individuals with valid bilateral ALPS indices were included. A genome-wide association study (GWAS) was conducted to identify genetic loci linked to the ALPS index. The study also explored correlations between the ALPS index and various non-imaging traits, including cognitive performance, blood pressure, and lifestyle factors. Statistical analyses included GWAS, gene enrichment analysis, polygenic risk score validation, Cox regression, and Mendelian randomization.ResultsThe GWAS identified 14 independent loci, encompassing 3,814 single-nucleotide polymorphisms, associated with white matter integrity, brain volume, fiber tract connectivity, inflammation, and metabolism. Key candidate genes, such asGNA12,SERPIND1, and MAPT, were linked to vascular function and neurodegenerative diseases. Enrichment analysis revealed significant roles for neuronal development, signal transduction, and metabolic pathways. The ALPS index showed significant associations with non-imaging phenotypes: higher indices correlated with better physical exercise, cognitive performance, and lower metabolic risks, while negative associations were found with smoking and excessive computer use. Polygenic risk scores confirmed these associations. Further analyses suggested that higher ALPS indices may protect against Alzheimer’s disease and multiple sclerosis.ConclusionsThis study represents the largest genome-wide analysis of the ALPS index to date, revealing key genetic variants that influence glymphatic function and their potential role in neurological health. The ALPS index may serve as a promising biomarker for neurodegenerative disease risk and offers new avenues for therapeutic interventions aimed at improving glymphatic clearance.
Title: Genetic and Phenotypic Architecture of Brain Glymphatic System
Description:
AbstractBackgroundThe glymphatic system plays a crucial role in clearing metabolic waste from the brain, facilitating waste exchange between cerebrospinal fluid and interstitial fluid, and supporting brain homeostasis.
However, quantifying glymphatic function has been challenging.
The Diffusion Tensor Imaging Along the Perivascular Space (DTI-ALPS) method offers a non-invasive approach to assess glymphatic function by calculating an index that reflects fluid mobility within the brain.
This study aimed to identify genetic variants associated with the ALPS index and explore its relationships with metabolic, immune, cognitive, and health-related phenotypes.
MethodsData from 43,823 participants in the UK Biobank were analyzed.
After rigorous quality control, 36,997 individuals with valid bilateral ALPS indices were included.
A genome-wide association study (GWAS) was conducted to identify genetic loci linked to the ALPS index.
The study also explored correlations between the ALPS index and various non-imaging traits, including cognitive performance, blood pressure, and lifestyle factors.
Statistical analyses included GWAS, gene enrichment analysis, polygenic risk score validation, Cox regression, and Mendelian randomization.
ResultsThe GWAS identified 14 independent loci, encompassing 3,814 single-nucleotide polymorphisms, associated with white matter integrity, brain volume, fiber tract connectivity, inflammation, and metabolism.
Key candidate genes, such asGNA12,SERPIND1, and MAPT, were linked to vascular function and neurodegenerative diseases.
Enrichment analysis revealed significant roles for neuronal development, signal transduction, and metabolic pathways.
The ALPS index showed significant associations with non-imaging phenotypes: higher indices correlated with better physical exercise, cognitive performance, and lower metabolic risks, while negative associations were found with smoking and excessive computer use.
Polygenic risk scores confirmed these associations.
Further analyses suggested that higher ALPS indices may protect against Alzheimer’s disease and multiple sclerosis.
ConclusionsThis study represents the largest genome-wide analysis of the ALPS index to date, revealing key genetic variants that influence glymphatic function and their potential role in neurological health.
The ALPS index may serve as a promising biomarker for neurodegenerative disease risk and offers new avenues for therapeutic interventions aimed at improving glymphatic clearance.
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