Evidence map›Paper›PMID 39062577›Full record

ReviewBiomolecules2024

Roles of Lysine Methylation in Glucose and Lipid Metabolism: Functions, Regulatory Mechanisms, and Therapeutic Implications.

Zhen Wang, Huadong Liu

Abstract readReview
In one paragraph

Review in Biomolecules, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Article
  6. Article
  7. Review
  8. Article
  9. Review
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

2 authors.

Zhen WangSchool of Health and Life Sciences, University of Health and Rehabilitation Sciences, Qingdao 266113, China.
Huadong LiuSchool of Health and Life Sciences, University of Health and Rehabilitation Sciences, Qingdao 266113, China.

Funding

National Key R&D Program of China 2023YFA1801200Natural Science Foundation of Shandong ZR2022LSW003
6 · The paper itself

Abstract

Glucose and lipid metabolism are essential energy sources for the body. Dysregulation in these metabolic pathways is a significant risk factor for numerous acute and chronic diseases, including type 2 diabetes (T2DM), Alzheimer's disease (AD), obesity, and cancer. Post-translational modifications (PTMs), which regulate protein structure, localization, function, and activity, play a crucial role in managing cellular glucose and lipid metabolism. Among these PTMs, lysine methylation stands out as a key dynamic modification vital for the epigenetic regulation of gene transcription. Emerging evidence indicates that lysine methylation significantly impacts glucose and lipid metabolism by modifying key enzymes and proteins. This review summarizes the current understanding of lysine methylation's role and regulatory mechanisms in glucose and lipid metabolism. We highlight the involvement of methyltransferases (KMTs) and demethylases (KDMs) in generating abnormal methylation signals affecting these metabolic pathways. Additionally, we discuss the chemical biology and pharmacology of KMT and KDM inhibitors and targeted protein degraders, emphasizing their clinical implications for diseases such as diabetes, obesity, neurodegenerative disorders, and cancers. This review suggests that targeting lysine methylation in glucose and lipid metabolism could be an ideal therapeutic strategy for treating these diseases.

Indexed as

GlucoseLipid MetabolismLysineProtein Processing, Post-TranslationalAnimalsDiabetes Mellitus, Type 2Epigenesis, GeneticHumansMethylationNeoplasmsGlucoseLysineglucose metabolismlipid metabolismlysine methylation

Identifiers

PMID39062577
PMCPMC11274642

What OpenQuestion holds

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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.