» Articles » PMID: 25616565

Metabolic Profiling and Phenotyping of Central Nervous System Diseases: Metabolites Bring Insights into Brain Dysfunctions

Overview
Date 2015 Jan 25
PMID 25616565
Citations 20
Authors
Affiliations
Soon will be listed here.
Abstract

Metabolic phenotyping corresponds to the large-scale quantitative and qualitative analysis of the metabolome i.e., the low-molecular weight <1 KDa fraction in biological samples, and provides a key opportunity to advance neurosciences. Proton nuclear magnetic resonance and mass spectrometry are the main analytical platforms used for metabolic profiling, enabling detection and quantitation of a wide range of compounds of particular neuro-pharmacological and physiological relevance, including neurotransmitters, secondary messengers, structural lipids, as well as their precursors, intermediates and degradation products. Metabolic profiling is therefore particularly indicated for the study of central nervous system by probing metabolic and neurochemical profiles of the healthy or diseased brain, in preclinical models or in human samples. In this review, we introduce the analytical and statistical requirements for metabolic profiling. Then, we focus on key studies in the field of metabolic profiling applied to the characterization of animal models and human samples of central nervous system disorders. We highlight the potential of metabolic profiling for pharmacological and physiological evaluation, diagnosis and drug therapy monitoring of patients affected by brain disorders. Finally, we discuss the current challenges in the field, including the development of systems biology and pharmacology strategies improving our understanding of metabolic signatures and mechanisms of central nervous system diseases.

Citing Articles

Metabolic Profiling of Aromatic Compounds.

Pautova A Metabolites. 2024; 14(2).

PMID: 38392999 PMC: 10890443. DOI: 10.3390/metabo14020107.


Metabolomic Signatures of Alzheimer's Disease Indicate Brain Region-Specific Neurodegenerative Progression.

Ambeskovic M, Hopkins G, Hoover T, Joseph J, Montina T, Metz G Int J Mol Sci. 2023; 24(19).

PMID: 37834217 PMC: 10573054. DOI: 10.3390/ijms241914769.


Using metabolomics to predict severe traumatic brain injury outcome (GOSE) at 3 and 12 months.

Banoei M, Lee C, Hutchison J, Panenka W, Wellington C, Wishart D Crit Care. 2023; 27(1):295.

PMID: 37481590 PMC: 10363297. DOI: 10.1186/s13054-023-04573-9.


Cerebrospinal Fluid-Basic Concepts Review.

Czarniak N, Kaminska J, Matowicka-Karna J, Koper-Lenkiewicz O Biomedicines. 2023; 11(5).

PMID: 37239132 PMC: 10216641. DOI: 10.3390/biomedicines11051461.


Serum metabolic profiling of targeted bile acids reveals potentially novel biomarkers for primary biliary cholangitis and autoimmune hepatitis.

Ma Z, Wang X, Wu R, Hao D, Sun L, Li P World J Gastroenterol. 2022; 28(39):5764-5783.

PMID: 36338890 PMC: 9627419. DOI: 10.3748/wjg.v28.i39.5764.


References
1.
Lalande J, Halley H, Balayssac S, Gilard V, Dejean S, Martino R . 1H NMR metabolomic signatures in five brain regions of the AβPPswe Tg2576 mouse model of Alzheimer's disease at four ages. J Alzheimers Dis. 2013; 39(1):121-43. DOI: 10.3233/JAD-130023. View

2.
Oresic M, Hyotylainen T, Herukka S, Sysi-Aho M, Mattila I, Seppanan-Laakso T . Metabolome in progression to Alzheimer's disease. Transl Psychiatry. 2012; 1:e57. PMC: 3309497. DOI: 10.1038/tp.2011.55. View

3.
Ji Y, Hebbring S, Zhu H, Jenkins G, Biernacka J, Snyder K . Glycine and a glycine dehydrogenase (GLDC) SNP as citalopram/escitalopram response biomarkers in depression: pharmacometabolomics-informed pharmacogenomics. Clin Pharmacol Ther. 2010; 89(1):97-104. PMC: 3034442. DOI: 10.1038/clpt.2010.250. View

4.
Yao J, Dougherty Jr G, Reddy R, Keshavan M, Montrose D, Matson W . Homeostatic imbalance of purine catabolism in first-episode neuroleptic-naïve patients with schizophrenia. PLoS One. 2010; 5(3):e9508. PMC: 2831068. DOI: 10.1371/journal.pone.0009508. View

5.
Davidovic L, Navratil V, Bonaccorso C, Catania M, Bardoni B, Dumas M . A metabolomic and systems biology perspective on the brain of the fragile X syndrome mouse model. Genome Res. 2011; 21(12):2190-202. PMC: 3227107. DOI: 10.1101/gr.116764.110. View