A Systems Approach To Cerebrospinal Fluid Analysis

Pixabay License | Source: Gerd Altmann , no changes made.

Found in the brain and spinal cord, the cerebrospinal fluid (CSF) is a clear, colorless fluid with a total volume of about 125ml per person, produced by specialized neuroglia called ependymal cells, that acts as a buffer and cushioning solution. The brain and spinal chord including the CSF are normally isolated from the blood circulatory system by the blood-brain barrier. CSF samples may be obtained by a clinician using the technique of lumbar puncture, otherwise known as spinal tap, which reflect the status of the central nervous system (CNS).

Metabolomics is the study of the totality of small molecule metabolites found within cells, biofluids such as CSF, tissues or organisms. It represents the molecular phenotype which can be analyzed using mass or nuclear magnetic resonance spectroscopy. Systems biology and functional genomics attempts to integrate genomics, transcriptomic, proteomic, and metabolomic information to understand the tissue or even organism phenotype (observed traits).

A study jointly led by Corinne D. Engelman and Qiongshi Lu of the University of Wisconsin-Madison, released on the bioRxiv preprint server, took a systems biology approach to conducted the first CSF metabolome-wide and genome-wide association study (GWAS) and used the results to build CSF metabolite prediction models for a variety of brain-related phenotypes.

CSF metabolomics and genomic data came from the Wisconsin Alzheimer’s Disease Research Center (WADRC) and Wisconsin Registry for Alzheimer’s Prevention (WRAP) studies. Only data from cognitively healthy participants were included in the data-set of 291 unrelated European-ancestry individuals analysed for 338 CSF metabolites. Single nucleotide polymorphism (SNP) and metabolite associations were estimated using GWAS conducted on WADRC for discovery and WRAP for replication.

In GWAS meta-analysis 1,183 significant SNPs across 16 metabolites (p < 1.48×10-10) were identified, with a single distinct genetic locus of association per metabolite. Of the 16 metabolites, 6 genetic associations were novel, N-acetylglutamate, 2-hydroxyadipate, 1-ribosylimidazoleacetate, and N6-methyllysine or associated with a novel genetic loci in CSF (oxalate and betaine).

Nineteen metabolite-phenotype associations that were identified including with schizophrenia, cognitive performance, alcoholic drinks per week, smoking behavior, sleep duration, post-traumatic stress disorder, and attention deficit hyperactivity disorder (ADHD).

Limitations of the study included sample size, homogeneity of ancestry and the fact that the metabolite phenotype associations may not be causal.

“These findings collectively provide insight into the genetic architecture of the CSF metabolome and the roles of CSF metabolites in disease, demonstrating the potential of this framework to make inroads into the omics of scarce sample types,” concluded the authors.

Sources

  1. https://www.biorxiv.org/content/10.1101/2020.02.14.948398v1
  2. https://www.ebi.ac.uk/training/online/course/introduction-metabolomics