Evidence map›Paper›PMID 28969616›Full record

ArticleBMC ophthalmology2017

Assessment of biomarkers using multiplex assays in aqueous humor of patients with diabetic retinopathy.

Hui Chen, Xiongze Zhang, Nanying Liao, Feng Wen

Registry-linked trialOpen access · goldAbstract read
In one paragraph

Article in BMC ophthalmology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04856670 (Assessing the Impact of Diabetes Mellitus on Anterior Chamber Cytokine Production and Postoperative Macular Edema in Patients Undergoing Femtosecond Laser-assisted Cataract Surgery), which is not on this map. Cited by 50 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
50citing papers in PubMed, 3 pooled it
2.9field-weighted citation impact, top 8% 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.

NCT04856670 unknown statusnot on this mapstarted 2021, after this paper: background citation

Assessing the Impact of Diabetes Mellitus on Anterior Chamber Cytokine Production and Postoperative Macular Edema in Patients Undergoing Femtosecond Laser-assisted Cataract Surgery

TypeobservationalSponsorUptown Eye SpecialistsRan2021 to 2021Enrolled140ConditionsCystoid Macular Edema, Diabetes Mellitus, CataractArmsCataract surgery
3 · Its place in the literature

Who cites it

50 citing papers in PubMed, 3 syntheses or guidelines pooled it, 77 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Trial
  5. Review
  6. Inflammatory Biomarkers in Diabetic Macular Edema.Journal of clinical medicine · 2026
    Review
  7. Molecular stress and neurovascular injury in the diabetic retina.The Journal of clinical investigation · 2026
    Review
  8. Article
  9. Article
  10. Article
  11. Tear fluid participates in systemic immunity.Zhong nan da xue xue bao. Yi xue ban = Journal of Central South University. Medical sciences · 2025
    Review
  12. Review
  13. Article
  14. Article
  15. Review
  16. Review
  17. Review
  18. Chemokines in diabetic eye disease.Diabetology & metabolic syndrome · 2024
    Article
  19. Review
  20. Modulation of CXCL10 activity as a therapeutic target of ocular toxoplasmosis in diabetic mice.Journal of parasitic diseases : official organ of the Indian Society for Parasitology · 2024
    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

4 authors at 1 institution in 1 country.

Hui ChenState Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, 510060, China.
Xiongze ZhangState Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, 510060, China.
Nanying LiaoState Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, 510060, China.
Feng WenState Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, 510060, China. wenfeng208@foxmail.com.
Sun Yat-sen University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundWith the high prevalence of type 2 diabetes, diabetic retinopathy (DR) has become a leading health problem worldwide. The pathogenesis of DR is complex and several vascular, inflammatory, and neuronal mechanisms are involved. The purpose of this study was to assess the levels of immune and inflammatory biomarkers in the aqueous humor of patients with different severities of DR and to analyze the correlations between Interleukin-6 (IL-6) and these biomarkers, and between IL-6 and the severity of the disease.

methodsAqueous humor samples were obtained from 51 non-diabetic patients and 151 diabetic patients. Levels of 45 different cytokines, chemokines, and growth factors were measured using a multiplex bead immunoassay.

resultsIL-6, IL-8, Inducible Protein-10 (IP-10), leukemia inhibitory factor (LIF), hepatocyte growth factor (HGF) and vascular endothelial growth factor (VEGF)-A were significantly higher (p < 0.05) in the aqueous humor of the DR patients compared to the non-diabetic patients, while the concentrations of IL-1α, IL-4, IL-9, IL-21, IL-23, IL-27, IL-31, RANTES, interferon-α, growth regulated oncogene (GRO), and tumor necrosis factor (TNF)-α were significantly lower (p < 0.05) in the DR patients. The IL-6 levels increased as the severity of DR increased. In addition, the IL-6 level positively correlated with the IL-8, HGF and LIF levels, while negatively with the IL-31and GRO levels.

conclusionsThese findings suggest that inflammation and immune response may contribute to the pathogenesis of DR, and these biomarkers may potentially be new therapeutic targets for DR.

Indexed as

Aqueous HumorBiomarkersCytokinesDiabetes Mellitus, Type 2Diabetic RetinopathyFemaleHumansImmunoassayInterleukin-6MaleMiddle AgedSeverity of Illness IndexBiomarkersCytokinesIL6 protein, humanInterleukin-6Aqueous humorChemokinesCytokinesDiabetic retinopathyGrowth factors

Identifiers

PMID28969616
PMCPMC5625688
OpenAlexW2763308465

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Registered trials

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.