4.2 Article

Whole blood genome-wide expression profiling and network analysis suggest MELAS master regulators

期刊

NEUROLOGICAL RESEARCH
卷 33, 期 6, 页码 638-655

出版社

TAYLOR & FRANCIS LTD
DOI: 10.1179/1743132810Y.0000000016

关键词

Gene expression; Microarrays; Mitochondrial disorders; MELAS; Disease-modifying genes

资金

  1. Medical Faculty Carl Gustav Carus at the Technical University of Dresden
  2. Roland Ernst Foundation [AZ 21-0563]
  3. Deutsche Forschungsgemeinschaft [GRK 864]

向作者/读者索取更多资源

Background: The heteroplasmic mitochondrial DNA (mtDNA) mutation A3243G causes the mitochondrial encephalomyopathy, lactic acidosis, and stroke-like episodes (MELAS) syndrome as one of the most frequent mitochondrial diseases. The process of reconfiguration of nuclear gene expression profile to accommodate cellular processes to the functional status of mitochondria might be a key to MELAS disease manifestation and could contribute to its diverse phenotypic presentation. Objective: To determine master regulatory protein networks and disease-modifying genes in MELAS syndrome. Methods: Analyses of whole blood transcriptomes from 10 MELAS patients using a novel strategy by combining classic Affymetrix oligonucleotide microarray profiling with regulatory and protein interaction network analyses. Results: Hierarchical cluster analysis elucidated that the relative abundance of mutant mtDNA molecules is decisive for the nuclear gene expression response. Further analyses confirmed not only transcription factors already known to be involved in mitochondrial diseases (such as TFAM), but also detected the hypoxia-inducible factor 1 complex, nuclear factor Y and cAMP responsive element-binding protein-related transcription factors as novel master regulators for reconfiguration of nuclear gene expression in response to the MELAS mutation. Correlation analyses of gene alterations and clinico-genetic data detected significant correlations between A3243G-induced nuclear gene expression changes and mutant mtDNA load as well as disease characteristics. These potential disease-modifying genes influencing the expression of the MELAS phenotype are mainly related to clusters primarily unrelated to cellular energy metabolism, but important for nucleic acid and protein metabolism, and signal transduction. Discussion: Our data thus provide a framework to search for new pathogenetic concepts and potential therapeutic approaches to treat the MELAS syndrome.

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