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Associations between lipid abnormalities and diabetic retinopathy across a large United States national database

Eye (2024)Cite this article

Subjects

Abstract

Background/Objectives

While dyslipidaemia has been suggested as a potential risk factor for diabetic retinopathy (DR), previous studies have reported conflicting findings. This study aimed to better characterize the relationship between abnormal serum levels of various lipid markers and the risk of the development and progression of DR.

Subjects/Methods

This retrospective cohort study utilized a United States national database of electronic medical records. Adults with a history of type 2 diabetes mellitus without type 1 diabetes mellitus were divided into cohorts based on the presence of abnormal serum levels of various lipid markers. Propensity score matching was performed to match cohorts with abnormal lipid levels to those with normal lipid levels on covariates. The cohorts were then compared to evaluate the hazard ratios (HR) of receiving a new DR diagnosis, pars plana vitrectomy, panretinal photocoagulation, vitreous haemorrhage, proliferative diabetic retinopathy, diabetic macular oedema (DMO), and traction retinal detachment.

Results

The database contained 1,126,231 eligible patients (mean age: 60.8 [14.2] years; 46.0% female). Among patients without prior DR, low HDL (HR = 0.94, CI = 0.90–0.98), total cholesterol (HR = 0.88, CI = 0.85–0.91), and high triglyceride (HR = 0.91, CI = 0.86–0.97) levels were associated with a decreased risk of receiving a DR diagnosis. Among patients with preexisting DR, high LDL levels was associated with an increased risk of DMO (HR = 1.42, CI = 1.15–1.75), whereas low HDL levels was associated with a marginally decreased risk (HR = 0.92, CI = 0.85–0.99).

Conclusions

Elevated levels of markers of dyslipidaemia are inversely associated with the risk of receiving a DR diagnosis, but this relationship is blunted after the onset of DR.

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Data availability

The de-identified data used in this research is available in the TriNetX research platform at https://live.trinetx.com, but a request may be necessary and costs may be incurred.

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Acknowledgements

We would like to thank Dr. David Kaelber and the MetroHealth Medical Center in Cleveland for providing access to the TriNetX database.

Funding

This study was supported by the Clinical and Translational Science Collaborative (CTSC) of Cleveland which is funded by the National Institutes of Health (NIH), National Center for Advancing Translational Science (NCATS), Clinical and Translational Science Award (CTSA) grant, UL1TR002548. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH. Additional support was provided by P30EY025585(BA-A), the Research to Prevent Blindness (RPB) Challenge Grant, Cleveland Eye Bank Foundation Grant.

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Authors and Affiliations

  1. Case Western Reserve University School of Medicine, Cleveland, OH, USA

    Hejin Jeong & Christopher M. Maatouk

  2. Center for Ophthalmic Bioinformatics, Cole Eye Institute, Cleveland Clinic, Cleveland, OH, USA

    Christopher M. Maatouk, Matthew W. Russell & Rishi P. Singh

  3. Cleveland Clinic Lerner College of Medicine of Case Western Reserve University, Cleveland, OH, USA

    Matthew W. Russell

  4. Cleveland Clinic Martin Health, Cleveland Clinic Florida, Stuart, FL, USA

    Rishi P. Singh

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Contributions

All authors contributed to the conception and design of the study, revised the manuscript, and reviewed the final manuscript. Data collection and statistical analysis were performed by HJ and CMM. Interpretation of the data, writing of the manuscript, and revision of the study design were performed by HJ.

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Correspondence to Rishi P. Singh.

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RPS reports personal fees from Genentech/Roche, personal fees from Alcon/Novartis, grants from Apellis and Graybug, personal fees from Zeiss, personal fees from Bausch + Lomb, personal fees from Regeneron Pharmaceuticals, Inc. Inc. All other authors report no disclosures.

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Jeong, H., Maatouk, C.M., Russell, M.W. et al. Associations between lipid abnormalities and diabetic retinopathy across a large United States national database. Eye (2024). https://doi.org/10.1038/s41433-024-03022-3

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