Evidence map›Paper›PMID 40659721›Full record

ArticleNPJ digital medicine2025

Phenotypic screening and genetic insights for predicting major vascular-related diseases using retinal imaging.

Menglin Lu, Yiheng Mao, Hui Zhu, Yesheng Xu, Yu-Feng Yao, Fei Wu, Zhengxing Huang

Abstract read
In one paragraph

Article in NPJ digital medicine, 2025. 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
–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

2 citing papers in PubMed.

  1. Article
  2. 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.

Menglin LuCollege of Computer Science and Technology, Zhejiang University, Hangzhou, China.
Yiheng MaoCollege of Computer Science and Technology, Zhejiang University, Hangzhou, China.
Hui ZhuCollege of Computer Science and Technology, Zhejiang University, Hangzhou, China.
Yesheng XuDepartment of Ophthalmology, Affiliated Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, China.
Yu-Feng YaoDepartment of Ophthalmology, Affiliated Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, China.
Fei WuCollege of Computer Science and Technology, Zhejiang University, Hangzhou, China. wufei@zju.edu.cn.
Zhengxing HuangCollege of Computer Science and Technology, Zhejiang University, Hangzhou, China. zhengxinghuang@zju.edu.cn.

Funding

National Key Research and Development Program of China 2022YFF1202400National Natural Science Foundation of China 82272129
6 · The paper itself

Abstract

Retinal photography is a valuable non-invasive tool for assessing vascular health, but genetic evidence linking retinal microcirculation to major vascular-related diseases (e.g., myocardial infarction [MI], stroke, and chronic kidney disease [CKD]) remains scarce. This study investigates their relationships from both phenotypic and genetic perspectives. Phenotypically, we developed a retinal imaging-based screening model to evaluate 10-year risk of these conditions, incorporating quantitative analyses to pinpoint specific vascular abnormalities. Genetically, we analyzed retinal image-derived traits to explore their genetic and causal relationships with vascular-related diseases. Internal validation with 25,840 UK Biobank participants and external temporal validation with 4558 participants confirmed the model's superiority over traditional risk models. Mendelian randomization suggested causal relationships between retinal traits and stroke and MI, as well as the impact of CKD on retinal microcirculation. These findings reinforce the connection between retinal microcirculation and major vascular-related events, highlighting the potential of retinal imaging for early detection in clinical settings.

Identifiers

PMID40659721
PMCPMC12259969

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.