PXD066143

PXD066143 is an original dataset announced via ProteomeXchange.

Title	Spatio-temporal analysis deciphers the energy metabolism disorders in depression based on stable isotope-resolved metabolomics
Description	The severe harm of depression on human life has attracted great attention. However, due to its unclear and extremely complex pathogenesis, the efficacy of existing marketed antidepressants is far from satisfactory. Consequently, it is urgent to understand the pathogenesis of depression from novel perspectives and develop next-generation antidepressants targeting innovative mechanisms. In recent years, the hypothesis of energy metabolism disorders in depression has emerged as a groundbreaking research direction. Here, we provided a new strategy for deciphering energy metabolism disorders in depression through spatio-temporal analysis based on stable isotope-resolved metabolomics. We used the classic depression model—chronic unpredictable mild stress (CUMS) rats—as the experimental subjects and the nephrotic syndrome (NS) rat model, which also exhibits energy metabolism abnormalities, as the comparison object. Sable isotope tracing technology and the pseudo-first-order kinetics mathematical model were introduced to evaluate the metabolic rates and the isotope distribution across various tissues from spatio-temporal dimension. Our findings revealed that CUMS rats exhibited impaired TCA cycle activity and activated gluconeogenesis, whereas NS rats showed impaired TCA cycle and enhanced fatty acid β-oxidation. In addition, our results showed an interesting phenomenon that caecum had the lowest abundances in all metabolic pathways, while serum, brain and heart, brain, brain, kidney displayed the highest abundances in glycolysis/gluconeogenesis, TCA cycle, neurotransmitters metabolism, amino acids metabolism, fatty acids metabolism, respectively. The results comprehensively and accurately revealed the specific pathway of energy metabolism disorders in depression from spatio-temporal perspective. Our study provided a novel insight for exploring the pathological mechanisms of depression, identifying new therapeutic targets, and developing ideal antidepressants.
HostingRepository	iProX
AnnounceDate	2025-07-14
AnnouncementXML	Submission_2025-07-15_01:02:28.923.xml
DigitalObjectIdentifier
ReviewLevel	Peer-reviewed dataset
DatasetOrigin	Original dataset
RepositorySupport	Unsupported dataset by repository
PrimarySubmitter	Ting Linghu
SpeciesList	scientific name: Rattus rattus; NCBI TaxID: 10117;
ModificationList	No PTMs are included in the dataset
Instrument	Orbitrap Exploris 240

Revision	Datetime	Status	ChangeLog Entry
0	2025-07-15 01:02:11	ID requested
⏵ 1	2025-07-15 01:02:29	announced

Dataset with its publication pending

submitter keyword: depression, energy metabolism, stable isotope-resolved metabolomics, spatio-temporal analysis, nephrotic syndrome

Ruiping Zhang
contact affiliation	Shanxi Medicine University
contact email	zrp_7142@sxmu.edu.cn
lab head
Ting Linghu
contact affiliation	Shanxi Medicine University
contact email	linghuting@sxmu.edu.cn
dataset submitter

iProX dataset URI