Article in Diabetologia, 2026. 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
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.
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
19 authors.
Jiahui Cao *Guangdong Eye Institute, Department of Ophthalmology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong, China.ORCID http://orcid.org/0009-0005-8022-0007
Fenghao Liu *Department of Radiation Medicine, Guangdong Provincial Key Laboratory of Tropical Disease Research, NMPA Key Laboratory for Safety Evaluation of Cosmetics, School of Public Health, Southern Medical University, Guangzhou, Guangdong, China.ORCID http://orcid.org/0009-0001-5603-7908
Huiqian Kong *Guangdong Eye Institute, Department of Ophthalmology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong, China.ORCID http://orcid.org/0000-0002-6646-484X
Chunran LaiGuangdong Eye Institute, Department of Ophthalmology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong, China.ORCID http://orcid.org/0009-0004-0413-2876
Zijing DuGuangdong Eye Institute, Department of Ophthalmology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong, China.ORCID http://orcid.org/0000-0002-8676-8293
Ting SuGuangdong Eye Institute, Department of Ophthalmology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong, China.ORCID http://orcid.org/0009-0000-6557-8565
Chenxiao ShenGuangdong Eye Institute, Department of Ophthalmology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong, China.ORCID http://orcid.org/0009-0003-3155-0283
Qinyi LiGuangdong Eye Institute, Department of Ophthalmology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong, China.ORCID http://orcid.org/0009-0007-7947-9462
Ying FangGuangdong Eye Institute, Department of Ophthalmology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong, China.ORCID http://orcid.org/0000-0002-5651-0611
Yijun HuGuangdong Eye Institute, Department of Ophthalmology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong, China.ORCID http://orcid.org/0000-0002-6424-7905
Xianwen ShangSchool of Optometry, The Hong Kong Polytechnic University, Kowloon, Hong Kong; Research Centre for SHARP Vision (RCSV), The Hong Kong Polytechnic University, Kowloon, Hong Kong.ORCID http://orcid.org/0000-0002-2362-3222
Mingguang HeSchool of Optometry, The Hong Kong Polytechnic University, Kowloon, Hong Kong; Research Centre for SHARP Vision (RCSV), The Hong Kong Polytechnic University, Kowloon, Hong Kong.ORCID http://orcid.org/0000-0002-6912-2810
Meijuan ZhouDepartment of Radiation Medicine, Guangdong Provincial Key Laboratory of Tropical Disease Research, NMPA Key Laboratory for Safety Evaluation of Cosmetics, School of Public Health, Southern Medical University, Guangzhou, Guangdong, China. fyzmj@163.com.ORCID http://orcid.org/0000-0003-4962-3164
Xiayin ZhangSingapore Eye Research Institute, Singapore National Eye Centre, Singapore, Republic of Singapore. zhang.xiayin@snec.com.sg.ORCID http://orcid.org/0000-0003-0250-0247
Honghua YuGuangdong Eye Institute, Department of Ophthalmology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong, China. yuhonghua@gdph.org.cn.ORCID http://orcid.org/0000-0002-0782-346X
Funding
Basic and Applied Basic Research Foundation of Guangdong Province 2023B1515120028China Postdoctoral Science Foundation 2024T170185National Natural Science Foundation of China 82271125National Natural Science Foundation of China 82301205National Natural Science Foundation of China 82301260National Natural Science Foundation of China U24A20707
6 · The paper itself
Abstract
aims/hypothesisThe aim of this study was to identify conserved biomarkers for diabetic retinopathy progression, addressing the lack of minimally invasive biomarkers to track the entire continuum of diabetic retinopathy.
methodsWe conducted high-throughput proteomics (SomaScan v4.1) on aqueous humour from the Guangdong DR Multiple-Omics Study (n=32). Temporal protein clusters were identified using soft clustering of temporal trajectories. Candidates were validated in a US dataset and localised via single-cell RNA-seq in an oxygen-induced retinopathy mouse model. The clinical relevance of plasma-detectable markers was assessed cross-sectionally and prospectively in individuals with diabetes from the UK Biobank (n=2495).
resultsIn the discovery dataset (mean age 68.5±9.0 years; 56.3% men, 43.8% women), temporal proteomic profiling identified 40 candidate biomarkers whose concentration showed monotonic changes during diabetic retinopathy progression. Of these, 25 showed conserved directional patterns in the validation dataset (17 increasing and eight decreasing, all p<0.05). Single-cell mapping further localised 15 candidates, including neurofilament light chain (NFL), to retinal neurons and glia. In the UK Biobank individuals, baseline plasma NFL distinguished those with diabetic retinopathy from control individuals (OR 1.98 [95% CI 1.61, 2.42]) and predicted incident diabetic retinopathy (HR 2.01 [95% CI 1.48, 2.73]) and vascular complications (microvascular, HR 2.28 [95% CI 1.94, 2.69]; macrovascular, HR 1.49 [95% CI 1.26, 1.77]) over a median follow-up of 12 years. Plasma NFL enhanced the predictability of a conventional risk factor model for diabetic retinopathy (net reclassification improvement [NRI] 0.194 [95% CI 0.042, 0.297]; integrated discrimination improvement [IDI] 0.015 [95% CI 0.003, 0.047]) and enabled risk stratification of vascular complications. CONCLUSIONS/
interpretationNFL represents a pan-stage biomarker for diabetic retinopathy progression, detectable through minimally invasive plasma testing, and is associated with risks of diabetic vascular complications.
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.
Integrated intraocular-plasma proteomics reveals conserved biomarkers for diabetic retinopathy progression: a multi-fluid biopsy study. · full record | OpenQuestion