Evidence map›Paper›PMID 36463101›Full record

ArticleClinical proteomics2022

Proteomics profiles of blood glucose-related proteins involved in a Chinese longevity cohort.

Rong Zhang, Fengjuan Liu, Shengliang Ye, Xi Du, Li Ma, Haijun Cao, Zongkui Wang, Changqing Li

Open access · goldAbstract read
In one paragraph

Article in Clinical proteomics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.3field-weighted citation impact, top 43% of its field
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

2 citing papers in PubMed, 4 citations in OpenAlex.

  1. Article
  2. 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

8 authors at 1 institution in 1 country.

Rong ZhangInstitute of Blood Transfusion, Chinese Academy of Medical Sciences & Peking Union Medical College, Chengdu, 610052, China.
Fengjuan LiuInstitute of Blood Transfusion, Chinese Academy of Medical Sciences & Peking Union Medical College, Chengdu, 610052, China.
Shengliang YeInstitute of Blood Transfusion, Chinese Academy of Medical Sciences & Peking Union Medical College, Chengdu, 610052, China.
Xi DuInstitute of Blood Transfusion, Chinese Academy of Medical Sciences & Peking Union Medical College, Chengdu, 610052, China.
Li MaInstitute of Blood Transfusion, Chinese Academy of Medical Sciences & Peking Union Medical College, Chengdu, 610052, China.
Haijun CaoInstitute of Blood Transfusion, Chinese Academy of Medical Sciences & Peking Union Medical College, Chengdu, 610052, China.
Zongkui WangInstitute of Blood Transfusion, Chinese Academy of Medical Sciences & Peking Union Medical College, Chengdu, 610052, China. zongkui.wang@ibt.pumc.edu.cn.
Changqing LiInstitute of Blood Transfusion, Chinese Academy of Medical Sciences & Peking Union Medical College, Chengdu, 610052, China. changqing.li@ibt.pumc.edu.cn.
Chinese Academy of Medical Sciences & Peking Union Medical College · CN

Funding

CAMS Innovation Fund for Medical Sciences 2021-I2M-1-060Department of Science and Technology of Sichuan Province 2019YFS0308
6 · The paper itself

Abstract

backgroundHigh blood glucose level is one of the main characteristics of diabetes mellitus. Based on previous studies, it is speculated longevity families may have certain advantages in blood glucose regulation. However, limited information on these items has been reported. The purpose of this study was to profile differences of plasma proteomics between longevity subjects (with normal fructosamine (FUN) level) and non-longevity area participants (with exceeding standard FUN level).

methodsIn this study, a TMT-based proteomics analysis was used to profile differences of plasma proteomics between longevity subjects (with normal FUN level) and non-longevity area participants (with exceeding standard FUN level). Results were validated by Luminex detection.

resultsA total of 155 differentially expressed proteins (DEPs) were identified between these two groups. The DEPs related to blood glucose regulation were mainly involved in glycolysis/gluconeogenesis, pyruvate metabolism and propanoate metabolism, and most of the DEPs were contained in carbohydrate metabolism, PI3K-Akt pathway, glucagon signaling pathway and inflammatory response. Validation by Luminex detection confirmed that CD163 was down-regulated, and SPARC, PARK 7 and IGFBP-1 were up-regulated in longevity participants.

conclusionsThis study not only highlighted carbohydrate metabolism, PI3K-Akt pathway, glucagon signaling pathway and inflammatory response may play important roles in blood glucose regulation, but also indicated that YWHAZ, YWHAB, YWHAG, YWHAE, CALM3, CRP, SAA2, PARK 7, IGFBP1 and VNN1 may serve as potential biomarkers for predicting abnormal blood glucose levels.

Indexed as

Blood glucoseFructosamineLongevityProteomicsTMT

Identifiers

PMID36463101
PMCPMC9719669
OpenAlexW4310774274

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.