Evidence map›Paper›PMID 26114427›Full record

ArticlePloS one2015

Metabolomic Analysis of the Skeletal Muscle of Mice Overexpressing PGC-1α.

Yukino Hatazawa, Nanami Senoo, Miki Tadaishi, Yoshihiro Ogawa, Osamu Ezaki, Yasutomi Kamei, Shinji Miura

Abstract read
In one paragraph

Article in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 45 papers.

0numbers the graph read from it
0cells of the map it votes in
45citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

45 citing papers in PubMed.

  1. Article
  2. International journal of molecular sciences · 2025
    Article
  3. Article
  4. Review
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Review
  11. Review
  12. Review
  13. Article
  14. Article
  15. Article
  16. Review
  17. Article
  18. Article
  19. Article
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Yukino HatazawaDepartment of Molecular Endocrinology and Metabolism, Graduate School of Medical and Dental Sciences, Tokyo Medical and Dental University, Tokyo, Japan; Laboratory of Molecular Nutrition, Graduate School of Environmental and Life Science, Kyoto Prefectural University, Kyoto, Japan.
Nanami SenooLaboratory of Nutritional Biochemistry, Graduate School of Nutritional and Environmental Sciences, University of Shizuoka, Shizuoka, Japan.
Miki TadaishiDepartment of Nutritional Science, Faculty of Applied Bio-Science, Tokyo University of Agriculture, Tokyo, Japan.
Yoshihiro OgawaDepartment of Molecular Endocrinology and Metabolism, Graduate School of Medical and Dental Sciences, Tokyo Medical and Dental University, Tokyo, Japan.
Osamu EzakiDepartment of Human Health and Design, Showa Women's University, Tokyo, Japan.
Yasutomi KameiLaboratory of Molecular Nutrition, Graduate School of Environmental and Life Science, Kyoto Prefectural University, Kyoto, Japan.
Shinji MiuraLaboratory of Nutritional Biochemistry, Graduate School of Nutritional and Environmental Sciences, University of Shizuoka, Shizuoka, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Peroxisome proliferator-activated receptor (PPAR) γ coactivator 1α (PGC-1α) is a coactivator of various nuclear receptors and other transcription factors whose expression increases in the skeletal muscle during exercise. We have previously made transgenic mice overexpressing PGC-1α in the skeletal muscle (PGC-1α-Tg mice). PGC-1α upregulates the expression of genes associated with red fibers, mitochondrial function, fatty acid oxidation, and branched chain amino acid (BCAA) degradation. However, global analyses of the actual metabolic products have not been investigated. In this study, we conducted metabolomic analysis of the skeletal muscle in PGC-1α-Tg mice by capillary electrophoresis with electrospray ionization time-of-flight mass spectrometry. Principal component analysis and hierarchical cluster analysis showed clearly distinguishable changes in the metabolites between PGC-1α-Tg and wild-type control mice. Changes were observed in metabolite levels of various metabolic pathways such as the TCA cycle, pentose phosphate pathway, nucleotide synthesis, purine nucleotide cycle, and amino acid metabolism, including BCAA and β-alanine. Namely, metabolic products of the TCA cycle increased in PGC-1α-Tg mice, with increased levels of citrate (2.3-fold), succinate (2.2-fold), fumarate (2.8-fold), and malate (2.3-fold) observed. Metabolic products associated with the pentose phosphate pathway and nucleotide biosynthesis also increased in PGC-1α-Tg mice. Meanwhile, BCAA levels decreased (Val, 0.7-fold; Leu, 0.8-fold; and Ile, 0.7-fold), and Glu (3.1-fold) and Asp (2.2-fold) levels increased. Levels of β-alanine and related metabolites were markedly decreased in PGC-1α-Tg mice. Coordinated regulation of the TCA cycle and amino acid metabolism, including BCAA, suggests that PGC-1α plays important roles in energy metabolism. Moreover, our metabolomics data showing the activation of the purine nucleotide pathway, malate-aspartate shuttle, as well as creatine metabolism, which are known to be active during exercise, further suggests that PGC-1α regulates metabolism in exercise. Thus, we demonstrated the roles of PGC-1α in the skeletal muscle at the metabolite level.

Indexed as

Gene ExpressionMetabolomeMetabolomicsAmino AcidsAnimalsCitric Acid CycleCluster AnalysisEnergy MetabolismFemaleMaleMiceMice, TransgenicMuscle, SkeletalNucleotidesPentose Phosphate PathwayPeroxisome Proliferator-Activated Receptor Gamma Coactivator 1-alphaAmino AcidsNucleotidesPeroxisome Proliferator-Activated Receptor Gamma Coactivator 1-alphaPpargc1a protein, mouseTranscription Factors

Identifiers

PMID26114427
PMCPMC4482640

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.