Evidence map›Paper›PMID 39485549›Full record

ArticleActa diabetologica2025

Time-dependent electroretinogram, metabolomics and lipidomics screened metabolic markers for monitoring the process of diabetic retinopathy from scratch.

Yue Tian, Yan-Ling Liu, Qian Wang, Ming-Shuang Wang, Ya-Hong Chen, Hong-Juan Wang, Jian-Mei Huang

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Article in Acta diabetologica, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

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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

1 citing paper in PubMed.

  1. 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.

Yue TianSchool of Chinese Materia Medica, Beijing University of Chinese Medicine, Liangxiang Town, Fangshan District, Beijing, 102488, China.
Yan-Ling LiuSchool of Chinese Materia Medica, Beijing University of Chinese Medicine, Liangxiang Town, Fangshan District, Beijing, 102488, China.
Qian WangSchool of Chinese Materia Medica, Beijing University of Chinese Medicine, Liangxiang Town, Fangshan District, Beijing, 102488, China.
Ming-Shuang WangSchool of Chinese Materia Medica, Beijing University of Chinese Medicine, Liangxiang Town, Fangshan District, Beijing, 102488, China.
Ya-Hong ChenSchool of Chinese Materia Medica, Beijing University of Chinese Medicine, Liangxiang Town, Fangshan District, Beijing, 102488, China.
Hong-Juan WangSchool of Chinese Materia Medica, Beijing University of Chinese Medicine, Liangxiang Town, Fangshan District, Beijing, 102488, China. whj1226a@126.com.ORCID http://orcid.org/0009-0002-7377-3234
Jian-Mei HuangSchool of Chinese Materia Medica, Beijing University of Chinese Medicine, Liangxiang Town, Fangshan District, Beijing, 102488, China. huangjm@bucm.edu.cn.

Funding

National Natural Science Foundation of China 81774014
6 · The paper itself

Abstract

aimsDiabetic retinopathy (DR) is a severe complication of diabetes mellitus (DM), and it is challenging to diagnose DR at an early stage by conventional methods. The aim of the present work is to propose an innovative approach to monitor the process of DR from scratch.

methodsThe plasma metabolites changed with DM were obtained by time-dependent metabolomics and lipidomics; the change of retinal function was measured by b-wave amplitude and total Ops-wave amplitude in electroretinography (ERG). Multivariate statistical analysis, logistic regression and correlation analysis were employed to identify metabolic markers from metabolites for the monitoring of DR and investigate the relationship between metabolic markers and retinal function.

resultsThe metabolic markers LPE18:0, LPC15:0, SM d14:2/26:0, SM d12:0/28:2 and MG 21:0 associated with DR can be utilized as metabolic markers to monitor the process of DR; The decrease in myo-inositol and LPC22:5 and increase in xylonic acid and TAG10:0/16:0/18:1 indicated retinal dysfunction.

conclusionsThe levels of metabolic markers can be used as an indicator of the onset of DR or as a means of monitoring changes in retinal function.

Indexed as

BiomarkersDiabetic RetinopathyLipidomicsMetabolomicsAdultElectroretinographyFemaleHumansMaleMiddle AgedRetinaBiomarkersDiabetic retinopathyElectroretinogramLipidomicsMetabolic markersMetabolomics

Identifiers

PMID39485549

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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.