Evidence map›Paper›PMID 39240552›Full record

ArticleInvestigative ophthalmology & visual science2024

Association of Retinal Nerve Fiber Layer Thinning With Elevated High Density Lipoprotein Cholesterol in UK Biobank.

Yiyuan Ma, Yue Wu, Ling Jin, Leyi Hu, Wen Chen, Charlotte Aimee Young, Xinyu Zhang, Danying Zheng, Zhenzhen Liu, Guangming Jin

Abstract read
In one paragraph

Article in Investigative ophthalmology & visual science, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Longitudinal hemifield-specific macular ganglion cell complex thinning and its association with arterial stiffness in eyes without baseline glaucomatous abnormalities.Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie · 2026
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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

10 authors.

Yiyuan MaState Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-Sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, China.
Yue WuState Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-Sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, China.
Ling JinState Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-Sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, China.
Leyi HuState Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-Sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, China.
Wen ChenState Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-Sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, China.
Charlotte Aimee YoungAlbany Medical College, Albany, New York, United States.
Xinyu ZhangState Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-Sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, China.
Danying ZhengState Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-Sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, China.
Zhenzhen LiuState Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-Sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, China.
Guangming JinState Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-Sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: The purpose of this study was to investigate the association between retinal nerve fiber layer (RNFL) thickness and high-density lipoprotein cholesterol (HDL-C) in a healthy population. Methods: This cross-sectional study included 31,738 UK Biobank participants with high quality optical coherence tomography (OCT) images, excluding those with neurological or ocular diseases. The locally estimated scatterplot smoothing (LOESS) curve and multivariable piecewise linear regression models were applied to assess the association between HDL-C and RNFL thickness, and HDL-C subclasses were further analyzed using nuclear magnetic resonance (NMR) spectroscopy. Results: Multivariate piecewise linear regression revealed that high HDL-C levels (>1.7 mmol/L in women or > 1.5 mmol/L in men) were associated with thinner RNFL thickness (women: β = -0.13, 95% confidence interval [CI] = -0.23 to -0.02, P = 0.017; male: β = -0.23, 95% CI = -0.37 to -0.10, P = 0.001). Conversely, a significant positive association between HDL-C and RNFL thickness was observed when HDL-C was between 1.4 and 1.7 mmol/L for female participants (β = 0.13, 95% CI = 0.02 to 0.24, P = 0.025). NMR analysis showed that these associations are potentially driven by distinct HDL-C subclasses. Conclusions: This study revealed an association between HDL-C levels and retinal markers of neurodegenerative diseases, suggesting that elevated HDL-C may serve as a new risk factor for neurodegenerative conditions. These findings may contribute to the implementation of preventive interventions and improved patient outcomes.

Indexed as

Cholesterol, HDLNerve FibersRetinal Ganglion CellsTomography, Optical CoherenceAdultAgedBiological Specimen BanksCross-Sectional StudiesFemaleHumansMaleMiddle AgedUK BiobankUnited KingdomCholesterol, HDL

Identifiers

PMID39240552
PMCPMC11382965

What OpenQuestion holds

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Registered trials

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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.