Dambrova 2022 MitoFit

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Dambrova 2022 MitoFit

Publications in the MiPMap
Dambrova M, Cecatto C, Vilskersts R, Liepinsh E (2022) Mitochondrial metabolites acylcarnitines: therapeutic potential and drug targets. https://doi.org/10.26124/mitofit:2022-0020 - Published 2022-11-25 in Bioenerg Commun 2022.15.

Β» MitoFit Preprints 2022.20.

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Mitochondrial metabolites acylcarnitines: therapeutic potential and drug targets Β»Watch the presentationΒ«

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Abstract:

Graphical abstract

Dambrova 2022 Abstract Bioblast: Acylcarnitines are esters of L-carnitine that emerge from the fatty acid metabolism pathways in mitochondria and peroxisomes. Metabolomic profiling assays that investigate disease and nutrition states often include measurements of different acylcarnitines. This has resulted in increased interest regarding the consequences of increased/decreased levels of plasma acylcarnitine concentrations and the mechanisms associated with these changes. Altered acylcarnitine metabolome is characteristic of certain inborn errors of fatty acid metabolism, as well as cardiovascular, metabolic, and neurological diseases in addition to some forms of cancer. Long-chain acylcarnitines accumulate under conditions of insufficient mitochondrial functionality reaching tissue levels that can affect enzyme and ion channel activities, and impact energy metabolism pathways and cellular homeostasis.

A better understanding of biochemical and molecular mechanisms behind the changes in acylcarnitine levels and their physiological and pathological roles forms the basis for future therapeutic target selection and preclinical drug discovery, as well as explains off-target effects of some clinically used drugs. β€’ Keywords: acylcarnitine, mitochondrial physiology, energy metabolism, biomarkers, cardiometabolic diseases β€’ Bioblast editor: Tindle-Solomon L β€’ O2k-Network Lab: AT Innsbruck Oroboros, LV Riga Liepins E

ORCID:ORCID.png Dambrova Maija, ORCID.png Cecatto Cristiane, ORCID.png Vilskersts Reinis, ORCID.png Liepinsh Edgars

Support

This work was part of the FAT4BRAIN project, with funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement nΒΊ 857394..


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