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Metabolomic Analysis of Rat Brain by High Resolution Nuclear Magnetic Resonance Spectroscopy of Tissue Extracts

Metabolomic Analysis of Rat Brain by High Resolution Nuclear Magnetic Resonance Spectroscopy of Tissue Extracts

Published on: September 21, 2014

Machine learning based metabolomic and genetic profiles for predicting multiple brain phenotypes.

Xueli Zhang^1,2,3, Yu Huang^1,4, Shunming Liu¹

¹Department of Ophthalmology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, 510080, China.

Journal of Translational Medicine

|December 3, 2024

Summary

This summary is machine-generated.

Metabolomic state significantly impacts brain volumes, while genetic risk scores (GRS) offer moderate predictive value. Both are key predictors for various brain phenotypes.

Keywords:

Brain phenotype Genetic risk score Metabolomic profiles Metabolomic state Moderation analysis Prediction value

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Metabolomic Analysis of Rat Brain by High Resolution Nuclear Magnetic Resonance Spectroscopy of Tissue Extracts

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Published on: September 21, 2014

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Area of Science:

Neuroscience
Genetics
Metabolomics

Background:

The relationship between metabolomic state, genetic risk scores (GRS), and brain volumes remains unclear.
Understanding the variance in brain volumes attributable to metabolomic state or GRS is crucial.

Purpose of the Study:

To investigate the association between metabolomic state/GRS and brain volumes.
To determine the proportion of variance in brain volumes explained by metabolomic state and GRS.

Main Methods:

Analysis of 8635 UK Biobank participants (aged 40-70).
Assessment of metabolomic profiles via nuclear magnetic resonance.
Measurement of brain volumes using magnetic resonance imaging.
Application of machine learning to generate metabolomic state and GRS for 21 brain phenotypes.

Main Results:

Top 20% metabolomic state associated with 2.4–35.7% larger brain volumes; GRS associated with 1.5–32.8% larger volumes.
Metabolomic state explained 2.2–19.4% of brain volume variance; GRS explained 0.8–8.7%.
Metabolomic state offered minimal additional prediction beyond age/sex; GRS provided moderate additional prediction (0.8–8.8%).
Lipids and fatty acids were strong predictors of brain volumes.

Conclusions:

Metabolomic state strongly correlates with brain volumes but adds little predictive value beyond age and sex.
GRS, while a weaker contributor than metabolomic state, offers moderate additional predictive value.
Both metabolomic state and GRS are significant predictors of multiple brain phenotypes.