Mitochondrial DNA abnormalities and metabolic syndrome

Front Cell Dev Biol. 2023 Mar 10:11:1153174. doi: 10.3389/fcell.2023.1153174. eCollection 2023.

Abstract

Metabolic syndrome (MetS) is a complex pathological condition that involves disrupted carbohydrate, protein, and fat metabolism in the human body, and is a major risk factor for several chronic diseases, including diabetes, cardiovascular disease, and cerebrovascular disease. While the exact pathogenesis of metabolic syndrome is not yet fully understood, there is increasing evidence linking mitochondrial dysfunction, which is closely related to the mitochondrial genome and mitochondrial dynamics, to the development of this condition. Recent advancements in genetic sequencing technologies have allowed for more accurate detection of mtDNA mutations and other mitochondrial abnormalities, leading to earlier diagnosis and intervention in patients with metabolic syndrome. Additionally, the identification of specific mechanisms by which reduced mtDNA copy number and gene mutations, as well as abnormalities in mtDNA-encoded proteins and mitochondrial dynamics, contribute to metabolic syndrome may promote the development of novel therapeutic targets and interventions, such as the restoration of mitochondrial function through the targeting of specific mitochondrial defects. Additionally, advancements in genetic sequencing technologies may allow for more accurate detection of mtDNA mutations and other mitochondrial abnormalities, leading to earlier diagnosis and intervention in patients with MetS. Therefore, strategies to promote the restoration of mitochondrial function by addressing these defects may offer new options for treating MetS. This review provides an overview of the research progress and significance of mitochondrial genome and mitochondrial dynamics in MetS.

Keywords: metabolic syndrome; mitochondrial copy number; mitochondrial dynamics; mitochondrial gene mutations; mitochondrial proteases; mitochondrial-encoded proteins.

Publication types

  • Review

Grants and funding

The work was supported by the National Natural Science Foundation of China (FUND#81800763) and the Natural Science Foundation of Liaoning Province of China (FUND#2022-MS-236).