Retinol binding protein 3 is increased in the retina of patients with diabetes resistant to diabetic retinopathy

Yokomizo, Hisashi; Maeda, Yasutaka; Park, Kyoungmin; Clermont, Allen C.; Hernandez, Sonia L.; Fickweiler, Ward; Li, Qian; Wang, Chih-Hao; Paniagua, Samantha M.; Simão, Fabrício; Ishikado, Atsushi; Sun, Bei; Wu, I-Hsien; Katagiri, Seiji; Pober, David M.; Tinsley, Liane J.; Avery, Robert L.; Feener, Edward P.; Kern, Timothy S.; Keenan, Hillary A.; Aiello, Lloyd Paul; Sun, Jennifer K.; King, George L.

doi:10.1126/scitranslmed.aau6627

Cited by 68 publications

(66 citation statements)

References 40 publications

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“…To extend the application in studying disease, we applied PSM-EA with gene burden analysis for evaluating the burden of predicted damaging rare variants of each gene in the IRD dataset. Statistical evidence showed 25 genes harbored predicted-damaging variants more than expectation significantly ( Table S5 ), in which 24 genes existed in 503 causative genes and the novel gene RBP3 was reported with critical function for vision in a recent study[45]. The lambda genomic factor 0.45 indicated no inflation of statistic method and/or no stratification of population.…”

Section: Resultsmentioning

confidence: 93%

A phenotype-specific framework for identifying the eye abnormalities causative nonsynonymous-variants

Liu

Dang

Guan

et al. 2020

Preprint

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The most important role of variant pathogenicity predictors is to identify the disease-phenotype causative variant in studying monogenic diseases. In the last decade, machine-learning based predictors exhibited a relatively accurate performance for distinguishing the pathogenic variants and contributed a significant role for all disease-spectrums. Yet, few predictors can investigate the phenotypic significance of variants.Here we presented a phenotype-specific framework aimed to directly point out the phenotypic significance of predicted candidates, and showed its advancing performance in eye abnormalities. By training on eye-abnormalities causative variants, our method presented 96.2% accuracy, 96.1% precision, 93.4% recall for pathogenicity identification. Inconsistent with the modeling performance, identifying the single phenotype-causative variant from various sequencing variants is challenging for all predictors. Underlying the phenotype-oriented, our method significantly promoted the precision and reduced the cost for identifying the single causative variant from thousands of candidates. These advances highlight the significance of the phenotype-specific training method for studying disease.

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Section: Resultsmentioning

confidence: 93%

A phenotype-specific framework for identifying the eye abnormalities causative nonsynonymous-variants

Liu

Dang

Guan

et al. 2020

Preprint

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“…These studies not only challenge duration of diabetes as a strong predictor for retinopathy, but also indicate that "protective factors", perhaps genetic or environmental, which may exist and could possibly contribute to the slowing or prevention of retinopathy. Interestingly, proteomic analysis of retinas and vitreous in this same cohort has already identified photoreceptor-secreted retinol binding protein 3 (RBP3) as a protective factor from advanced DR [80].…”

Section: Duration Of Diabetesmentioning

confidence: 92%

Genotypes and Phenotypes: A Search for Influential Genes in Diabetic Retinopathy

Cabrera

Mankad

Marek

et al. 2020

IJMS

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Although gene–environment interactions are known to play an important role in the inheritance of complex traits, it is still unknown how a genotype and the environmental factors result in an observable phenotype. Understanding this complex interaction in the pathogenesis of diabetic retinopathy (DR) remains a big challenge as DR appears to be a disease with heterogenous phenotypes with multifactorial influence. In this review, we examine the natural history and risk factors related to DR, emphasizing distinct clinical phenotypes and their natural course in retinopathy. Although there is strong evidence that duration of diabetes and metabolic factors play a key role in the pathogenesis of DR, accumulating new clinical studies reveal that this disease can develop independently of duration of diabetes and metabolic dysfunction. More recently, studies have emphasized the role of genetic factors in DR. However, linkage analyses, candidate gene studies, and genome-wide association studies (GWAS) have not produced any statistically significant results. Our recently initiated genomics study, the Diabetic Retinopathy Genomics (DRGen) Study, aims to examine the contribution of rare and common variants in the development DR, and how they can contribute to clinical phenotype, rate of progression, and response to available therapies. Our preliminary findings reveal a novel set of genetic variants associated with proangiogenic and inflammatory pathways that may contribute to DR pathogenesis. Further investigation of these variants is necessary and may lead to development of novel biomarkers and new therapeutic targets in DR.

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“…The protective effects of RBP3 were also seen in overexpression studies using a common mouse model of diabetes. Although RBP3 is an integral protein in the retinoid cycle, its mechanism of action in DR could be related to direct binding and negative regulation of GLUT1 transporter-the major glucose transporter in the retina (Yokomizo et al, 2019).…”

Section: Clinical Evidencementioning

confidence: 99%

Photoreceptor responses to light in the pathogenesis of diabetic retinopathy

Majidi

Rajagopal

2020

Vis Neurosci

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Vision loss, among the most feared complications of diabetes, is primarily caused by diabetic retinopathy, a disease that manifests in well-recognized, characteristic microvascular lesions. The reasons for retinal susceptibility to damage in diabetes are unclear, especially considering that microvascular networks are found in all tissues. However, the unique metabolic demands of retinal neurons could account for their vulnerability in diabetes. Photoreceptors are the first neurons in the visual circuit and are also the most energy-demanding cells of the retina. Here, we review experimental and clinical evidence linking photoreceptors to the development of diabetic retinopathy. We then describe the influence of retinal illumination on photoreceptor metabolism, effects of light modulation on the severity of diabetic retinopathy, and recent clinical trials testing the treatment of diabetic retinopathy with interventions that impact photoreceptor metabolism. Finally, we introduce several possible mechanisms that could link photoreceptor responses to light and the development of retinal vascular disease in diabetes. Collectively, these concepts form the basis for a growing body of investigative efforts aimed at developing novel pharmacologic and nonpharmacologic tools that target photoreceptor physiology to treat a very common cause of blindness across the world.

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Retinol binding protein 3 is increased in the retina of patients with diabetes resistant to diabetic retinopathy

Cited by 68 publications

References 40 publications

A phenotype-specific framework for identifying the eye abnormalities causative nonsynonymous-variants

A phenotype-specific framework for identifying the eye abnormalities causative nonsynonymous-variants

Genotypes and Phenotypes: A Search for Influential Genes in Diabetic Retinopathy

Photoreceptor responses to light in the pathogenesis of diabetic retinopathy

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