Evidence mapPaperPMID 31493765Full record

ArticleAging2019

Age-specific urinary metabolite signatures and functions in patients with major depressive disorder.

Jian-Jun Chen, Jing Xie, Wen-Wen Li, Shun-Jie Bai, Wei Wang, Peng Zheng, Peng Xie

Abstract read
In one paragraph

Article in Aging, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed, 1 pooled it
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

23 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Trial
  3. Trial
  4. Review
  5. Review
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Review
  12. Article
  13. Brain Functional Network and Amino Acid Metabolism Association in Females with Subclinical Depression.International journal of environmental research and public health · 2022
    Article
  14. Review
  15. Article
  16. Review
  17. Article
  18. Article
  19. Article
  20. Bacterial Metabolites of Human Gut Microbiota Correlating with Depression.International journal of molecular sciences · 2020
    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

7 authors.

Jian-Jun ChenInstitute of Life Sciences, Chongqing Medical University, Chongqing 400016, China.
Jing XieDepartment of Endocrinology and Nephrology, Chongqing University Central Hospital, Chongqing Emergency Medical Center, Chongqing 400014, China.
Wen-Wen LiDepartment of Pathology, Faculty of Basic Medicine, Chongqing Medical University, Chongqing 400016, China.
Shun-Jie BaiDepartment of Laboratory, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China.
Wei WangNHC Key Laboratory of Diagnosis and Treatment on Brain Functional Diseases, Chongqing Medical University, Chongqing 400016, China.
Peng ZhengNHC Key Laboratory of Diagnosis and Treatment on Brain Functional Diseases, Chongqing Medical University, Chongqing 400016, China.
Peng XieNHC Key Laboratory of Diagnosis and Treatment on Brain Functional Diseases, Chongqing Medical University, Chongqing 400016, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Major depressive disorder (MDD) patients in different age ranges might have different urinary metabolic phenotypes, because age could significantly affect the physiological and psychological status of person. Therefore, it was very important to take age into consideration when studying MDD. Here, a dual platform metabolomic approach was performed to profile urine samples from young and middle-aged MDD patients. In total, 18 and 15 differential metabolites that separately discriminated young and middle-aged MDD patients, respectively, from their respective HC were identified. Only ten metabolites were significantly disturbed in both young and middle-aged MDD patients. Meanwhile, two different biomarker panels for diagnosing young and middle-aged MDD patients, respectively, were identified. Additionally, the TCA cycle was significantly affected in both young and middle-aged MDD patients, but the Glyoxylate and dicarboxylate metabolism and phenylalanine metabolism were only significantly affected in young and middle-aged MDD patients, respectively. Our results would be helpful for developing age-specific diagnostic method for MDD and further investigating the pathogenesis of this disease.

Indexed as

AdultAge FactorsBiomarkersFemaleHumansMajor Depressive DisorderMaleMetabolomicsMiddle AgedYoung AdultBiomarkersbiomarkermajor depressive disordermetabolitemetabolomics

Identifiers

PMID31493765
PMCPMC6756884

What Socratic 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 Socratic graph.