About

Robert N. Weinreb is a Professor of Ophthalmology at UC San Diego School of Medicine. His research activities and funding focus on the diagnosis and monitoring of glaucoma, including the use of Optical Coherence Tomography Angiography and other imaging techniques. He has led numerous clinical trials and studies aimed at understanding glaucoma progression, ocular hypertension, and systemic health indicators related to eye health. His work includes contributions to the development of innovative monitoring methods, the application of artificial intelligence in glaucoma detection, and the exploration of systemic health factors such as cardiovascular and metabolic syndrome in relation to ocular conditions. Weinreb's extensive publication record reflects his significant role in advancing ophthalmic research and clinical practice.

Research topics

• Medicine
• Ophthalmology
• Computer Science
• Optometry
• Internal medicine
• Artificial Intelligence
• Biology
• Neuroscience
• Genetics
• Surgery
• Cell biology
• Mathematics
• Statistics
• Pathology
• Engineering
• Machine Learning
• Physics
• Endocrinology
• Optics
• Geometry
• Immunology
• Algorithm
• Anesthesia
• Telecommunications

Selected publications

• Greater Outflow Facility Increase After Targeted Trabecular Bypass In Angiographically Determined Low-Flow Regions

  2026-03-31

  articleOpen access
  PublisherDOI

• Association of Deep Optic Nerve Head Structural Remodeling with Choroidal Microvasculature Dropout in Glaucoma with and without Myopia

  American Journal of Ophthalmology · 2026-04-15

  article
  PublisherDOI

• Associations of Biomarkers of Kidney Tubule Health with Retinal Microvascular Signs

  Kidney360 · 2025-09-05 · 1 citations

  articleOpen access

  Key Points Kidney injury molecule-1 and soluble urokinase plasminogen activator receptor are associated with retinal microvascular changes in individuals without CKD, diabetes, or cardiovascular disease. Tubule biomarkers may reveal microvascular pathways linking kidney dysfunction to cardiovascular risk beyond eGFR or albumin-to-creatinine ratio. Background CKD is strongly associated with cardiovascular disease (CVD), yet the etiology responsible for this link remains elusive. Novel blood and urine biomarkers reflecting kidney tubule dysfunction and injury may provide novel insights to mechanisms linking the kidney to CVD. Methods In 470 participants of the Multi-Ethnic Study of Atherosclerosis without type 2 diabetes, CVD, or CKD, we measured six plasma (kidney injury molecule-1 [KIM-1], monocyte chemoattractant protein-1, soluble urokinase plasminogen activator receptor, tumor necrosis factor receptor 1 and 2, and anti–chitinase-3-like protein 1) and six urinary ( α 1 microglobulin, EGF, KIM-1, monocyte chemoattractant protein-1, anti–chitinase-3-like protein 1, and uromodulin) kidney tubule health biomarkers. To assess microvascular health, we used retinal microvascular measurements assessed from fundus photography: central retinal arteriolar and venular equivalents (central retinal artery equivalent [CRAE] and central retinal venular equivalent [CRVE], respectively). Multivariable linear regression evaluated associations of tubule biomarkers and kidney function with CRAE and CRVE. Results The mean participant age was 60±10 years with 52% female. The racial and ethnic distribution was 46% White, 24% Black, 18% Hispanic, and 11% Chinese. The mean eGFR was 92.1±13.3 ml/min per 1.73 m 2 , and the median urine albumin-to-creatinine ratio was 4.7 mg/g (interquartile range, 3.0–9.4). Higher plasma KIM-1 ( β , −5.14; 95% confidence interval [CI], −9.84 to −0.45) and urine KIM-1 ( β, −5.68; 95% CI, −10.15 to −1.22) concentrations were individually associated with narrower CRAE, while plasma soluble urokinase plasminogen activator receptor concentrations were individually associated with wider CRAE ( β , 9.15; 95% CI, 0.89 to 17.4) and CRVE ( β , 21.49; 95% CI, 9.39 to 33.59). There were no significant associations between the remaining tubule health biomarkers and CRAE or CRVE nor were there associations between eGFR or urine albumin-to-creatinine ratio with CRAE and CRVE. Conclusions In this study of community-living individuals without CKD, diabetes, or CVD, selected kidney tubule health markers are associated with retinal microvascular changes. These findings suggest that kidney tubule biomarkers may reflect or contribute to systemic microvascular dysfunction, above and beyond glomerular damage. Tubular biomarkers may help elucidate the shared microvascular mechanisms linking CKD and CVD.

  PublisherDOI

• Retinal nerve fibre layer optical texture analysis: retinal nerve fibre bundle defect patterns and the extent of macular involvement across different stages of glaucoma

  British Journal of Ophthalmology · 2025-11-04 · 2 citations

  articleOpen accessSenior authorCorresponding

  BACKGROUND/AIMS: To apply retinal nerve fibre layer (RNFL) optical texture analysis (ROTA) to investigate (1) the patterns of RNFL bundle defects, and (2) the frequency of papillomacular and papillofoveal bundle involvement across early, moderate and advanced glaucoma. METHODS: All eyes underwent 24-2 visual field (VF) testing and optical coherence tomography (OCT) for ROTA. The borders of RNFL defects were delineated from ROTA, and the involvement of the arcuate, papillomacular and papillofoveal bundles was determined for each eye. 24-2 VF stimulus projections were mapped onto the corresponding topographic areas of ROTA images. Multilevel logistic regression analysis was applied to evaluate the structure-function association. RESULTS: Papillomacular bundle defects were highly prevalent in glaucoma, increasing from 87.7% in early to 95.35% in moderate and 100% in advanced glaucoma. Papillofoveal bundle defects were also common, increasing from 29.7% in early to 36.05% in moderate and 60.98% in advanced glaucoma. Central four 24-2 test locations that projected onto the trajectories of papillomacular or papillofoveal RNFL bundle defects demonstrated significantly increased likelihood of VF sensitivity abnormality (ORs of 22.42 at PDP<5% and 20.26 at TDP<5%, respectively, p<0.001 for both). CONCLUSION: ROTA uncovers a wide spectrum of RNFL bundle defects spanning the entire glaucoma continuum. It also provides visualisation of the preserved RNFL bundles in advanced glaucoma. Papillomacular and papillofoveal RNFL bundle defects are present in a considerable proportion of eyes with early, moderate and advanced glaucoma, and, when detected, they significantly increase the likelihood of abnormality in the corresponding central 24-2 test locations.

  PublisherOA PDFDOI

• Glaucoma detection in myopic eyes using deep learning autoencoder-based regions of interest

  Frontiers in Ophthalmology · 2025-08-04 · 2 citations

  articleOpen access

  Purpose: To evaluate the diagnostic accuracy of a deep learning autoencoder-based model utilizing regions of interest (ROI) from optical coherence tomography (OCT) texture enface images for detecting glaucoma in myopic eyes. Methods: This cross-sectional study included a total of 453 eyes from 315 participants from the multi-center "Swept-Source OCT (SS-OCT) Myopia and Glaucoma Study", composed of 268 eyes from 168 healthy individuals and 185 eyes from 147 glaucomatous individuals. All participants underwent swept-source optical coherence tomography (SS-OCT) imaging, from which texture enface images were constructed and analyzed. The study compared four methods: (1) global RNFL thickness, (2) texture enface image, (3) a single autoencoder model trained only on healthy eyes, and (4) a dual autoencoder model trained on both healthy and glaucomatous eyes. Diagnostic accuracy was assessed using the area under the receiver operating curves (AUROC) and precision recall curves (AUPRC). Results: The dual autoencoder model achieved the highest AUROC (95% CI) (0.92 [0.88, 0.95]), significantly outperforming the single autoencoder model trained only on healthy eyes (0.86 [0.83, 0.88], p = 0.01), the global RNFL thickness model (0.84 [0.80, 0.86], p = 0.003), and the texture enface model (0.83 [0.79, 0.85], p = 0.005). Using AUPRC (95% CI), the dual autoencoder model (0.86 [0.83, 0.89]) also outperformed the single autoencoder model trained only on healthy eyes (0.80 [0.78, 0.82], p = 0.02), the global RNFL thickness model (0.74 [0.70, 0.76], p = 0.001), and the texture enface model (0.71 [0.68, 0.73], p<0.001). No significant difference was observed between the global RNFL thickness measurement and the texture enface measurement (p = 0.47). Discussion: The dual autoencoder model, which integrates reconstruction errors from both healthy and glaucomatous training data, demonstrated superior diagnostic accuracy compared to the single autoencoder model, global RNFL thickness and texture enface-based approaches. These findings suggest that deep learning models leveraging ROI-based reconstruction error from texture enface images may enhance glaucoma classification in myopic eyes, providing a robust alternative to conventional structural thickness metrics.

  PublisherOA PDFDOI

• Short-Term Rates of Visual Field Change Predict Glaucoma Progression

  Ophthalmology Glaucoma · 2025-06-03 · 2 citations

  articleSenior authorCorresponding
  PublisherDOI

• Initial circumpapillary retinal nerve fibre layer rates of change predict glaucomatous progression

  Eye · 2025-09-22

  articleSenior author
  PublisherDOI

• Association of metformin use with primary open-angle glaucoma using data from the National Institutes of Health <i>All of Us</i> Program

  BMJ Open Ophthalmology · 2025-09-01 · 2 citations

  articleOpen access

  BACKGROUND: Few studies have assessed the impact of metformin use on glaucoma risk. The purpose of this study was to examine the association between metformin use and the incidence of primary open-angle glaucoma (POAG) in a diverse and large nationwide cohort. METHODS: Research Program aged 40 years or older, with a diagnosis of diabetes mellitus and without a diagnosis of POAG prior to diabetes diagnosis or metformin use. Bivariate logistic regression, multivariable logistic regression and survival analysis were used to analyse the association between ever use of metformin and incidence of POAG. RESULTS: Within the cohort, 240 participants acquired a diagnosis of POAG during all available follow-up time, while 18 200 did not. In regression-based bivariate analysis, metformin use was significantly associated with a lower odds of developing POAG (OR 0.35, 95% CI 0.26 to 0.47, p<0.001). In multivariable regression analysis, metformin remained protective against POAG (OR 0.33, 95% CI 0.21 to 0.50, p<0.001), while the use of other diabetic medications was associated with an increased odds of developing POAG (OR 2.39, 95% CI 1.48 to 3.90, p<0.001). In survival analysis, the probability of developing POAG was significantly lower for the participants using metformin than for the participants not using metformin (log-rank p<0.001, Cox proportional HR 0.38, 95% CI 0.29 to 0.51). CONCLUSIONS: This study provides additional large-scale observational health data supporting the protective role of metformin in the development of POAG. However, limitations include the study's observational design and lack of data on metformin dosage and duration, glaucoma severity and ocular exam findings. Despite these limitations, our findings contribute to the growing body of evidence suggesting a potential protective effect of metformin against POAG.

  PublisherOA PDFDOI

• A Novel Multimodal Implementation of a Foundation Artificial Intelligence Model Using Optic Nerve Head Fundus Photographs and OCT Imaging for Glaucoma Detection

  Ophthalmology Science · 2025-11-20

  articleOpen access

  Purpose: To compare the performance of unimodal and multimodal implementation of the self-supervised learning model RETFound in detecting glaucoma using color fundus photographs (CFPs) and OCT images, and to assess its generalizability across different ethnicities, age groups, and disease severities. Design: Evaluation of a diagnostic technology. Subjects Participants and Controls: Fourteen thousand five hundred ten CFPs and 32 640 OCTs from 1948 eyes of 1098 participants (60.8% glaucoma, 39.2% healthy) from the Diagnostic Innovations in Glaucoma Study and the African Descent and Glaucoma Evaluation Study were included. Glaucoma was defined as photograph-based glaucomatous optic neuropathy with or without repeatable glaucoma visual field damage. Methods: A multimodal RETFound model was developed using paired CFPs and OCT images. The model was compared to unimodal RETFound models using solely CFP or OCT images. Performance was also stratified by race (Black vs. White), age (<60 vs. ≥60 years), and disease severity (mild vs. moderate-to-severe glaucoma). Main Outcome Measures: Diagnostic accuracy of unimodal and multimodal RETFound models using CFP and OCT for detecting glaucoma was assessed using the area under the receiver operating characteristic curve (AUC), precision, and recall. Results: = 0.005) models. Conclusions: The multimodal RETFound model demonstrated improved diagnostic ability compared with the CFP unimodal model but did not significantly outperform the OCT unimodal model in glaucoma detection. As clinical implementation of a unimodal artificial intelligence (AI) model is easier than a multimodal counterpart, our results suggest unimodal OCT AI models may be sufficient for detecting glaucoma. Financial Disclosures: Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

  PublisherDOI

• Artificial Intelligence Characterization of Spatial Patterns of Macula and Their Association With Central Visual Field Progression in Glaucoma

  Graduate Medical Education Research Journal · 2025-06-01

  articleOpen accessSenior author

  Background: Rosai-Dorfman disease (RDD) is a rare histiocytic disorder with an excellent prognosis involving nodal and extra-nodal tissues.Although skin and soft tissue is the most common extra-nodal site, cutaneous RDD (CRDD) is extremely rare and shows subtle differences in histological findings from extra-cutaneous RDD.Possible association with IgG4-related sclerosing disease has been reported with many cases showing increased IgG4(+) plasma cells.However, there is little data regarding the number and proportion of IgG4(+) plasma cells in CRDD.Methods: Following IRB approval, a total of 68 patients of RDD were retrieved over a period of 34 years and their clinicopathologic, immunohistochemical, and survival information were evaluated.Immunohistochemistry (IHC) for IgG4, IgG, and BRAF V600E was performed in 53 cases in which tissue was available for study.Results: Immunohistochemistry for BRAF V600E was negative (53/53).Cyclin D1 was positive (41/41), and ALK was negative (41/41).CRDD demonstrated no increase in IgG4 (5/5) (0/HPF) or IgG (5/5) in our study.In contrast, extra-CRDD demonstrated a significant increase in IgG4/IgG (10-60%), and IgG4 ranged from 7-35/HPF (30/41).Of 49 patients with known follow-up, only 5 patients (10%) with soft tissue involvement (extra-CRDD) had residual disease or suspected residual disease.No patients died or developed any widespread dissemination. Conclusion:This study further highlights the heterogeneous nature of RDD, with divergence of expression of IgG4(+) plasma cells in CRDD versus extra-CRDD.Interestingly, all patients in this study with residual disease had extra-CRDD.Thus, there continues to be a need for understanding the pathogenesis of RDD for guiding clinical management.

  PublisherOA PDFDOI

Recent grants

• NIH Grant R01EY019692

  NIH · $1.8M · 2014

• NIH Grant R01EY005990

  NIH · $5.6M · 2009

• Ophthalmology and Visual Sciences Career Development K12 Program

  NIH · $4.3M · 2015–2027

• Diagnosis and Monitoring of Glaucoma with Optical Coherence Tomography Angiography

  NIH · $4.2M · 2018–2026

• NIH Grant U10EY011158

  NIH · $5.0M · 2010

Frequent coauthors

• Linda M. Zangwill

  University of California, San Diego

  997 shared

• Felipe A. Medeiros

  University of Miami

  520 shared

• Christopher Bowd

  Fleet Science Center

  457 shared

• Sasan Moghimi

  University of California, San Diego

  417 shared

• Jeffrey M. Liebmann

  268 shared

• Pamela A. Sample

  University of California, San Diego

  242 shared

• Christopher A. Girkin

  University of Alabama at Birmingham

  233 shared

• Akram Belghith

  University of California, San Diego

  170 shared

Education

• M.D., Ophthalmology

  University of California, San Diego

  1983

• B.S., Biology

  University of California, San Diego

  1979