TGFβ1 Induces Senescence and Attenuated VEGF Production in Retinal Pericytes

Investigation and validation of genes associated with endoplasmic reticulum stress in diabetic retinopathy using various machine learning algorithms

BACKGROUND

Diabetic retinopathy (DR) is a common complication of diabetes, with Endoplasmic reticulum stress (ERS) playing a key role in cellular adaptation, injury, or apoptosis, impacting disease pathology. This study aimed to identify early diagnostic markers for personalized DR treatment.

METHODS

DR and healthy control (HC) samples were collected from the Gene Expression Omnibus (GEO) database. Differentially expressed ERS-related genes (DE-ERSRGs) were identified, and machine learning algorithms were used to pinpoint DR-specific feature DE-ERSRGs (FDE-ERSRGs). Diagnostic accuracy was assessed using ROC curve analysis. Further analyses included differential expression, co-expression, GO functional, KEGG pathway enrichment, and immune cell infiltration profiling in DR.

RESULTS

A total of 55 DE-ERSRGs were initially identified, and after further analysis, two key FDE-ERSRGs, SELENOS and heat shock protein family A member 5 (HSPA5), were highlighted due to their robust differential expression patterns between DR and healthy controls. Both genes exhibited high diagnostic potential, with AUC values of 0.792 and 0.799, respectively, indicating their promise as biomarkers for DR. Additionally, we examined the differential and co-expression patterns of DE-ERSRGs between high- and low-expression groups. We investigated the molecular functions and biological pathways associated with DR, analyzed immune cell infiltration differences between DR and HC groups, and assessed their correlation with FDE-ERSRGs.

CONCLUSIONS

Our findings provide new insights into the molecular mechanisms and metabolic pathways involved in DR, potentially paving the way for the identification of novel diagnostic and immunotherapeutic biomarkers.

Decoding senescence of aging single cells at the nexus of biomaterials, microfluidics, and spatial omics

Aging has profound effects on the body, most notably an increase in the prevalence of several diseases. An important aging hallmark is the presence of senescent cells that no longer multiply nor die off properly. Another characteristic is an altered immune system that fails to properly self-surveil. In this multi-player aging process, cellular senescence induces a change in the secretory phenotype, known as senescence-associated secretory phenotype (SASP), of many cells with the intention of recruiting immune cells to accelerate the clearance of these damaged senescent cells. However, the SASP phenotype results in inducing secondary senescence of nearby cells, resulting in those cells becoming senescent, and improper immune activation resulting in a state of chronic inflammation, called inflammaging, in many diseases. Senescence in immune cells, termed immunosenescence, results in further dysregulation of the immune system. An interdisciplinary approach is needed to physiologically assess aging changes of the immune system at the cellular and tissue level. Thus, the intersection of biomaterials, microfluidics, and spatial omics has great potential to collectively model aging and immunosenescence. Each of these approaches mimics unique aspects of the body undergoes as a part of aging. This perspective highlights the key aspects of how biomaterials provide non-cellular cues to cell aging, microfluidics recapitulate flow-induced and multi-cellular dynamics, and spatial omics analyses dissect the coordination of several biomarkers of senescence as a function of cell interactions in distinct tissue environments. An overview of how senescence and immune dysregulation play a role in organ aging, cancer, wound healing, Alzheimer's, and osteoporosis is included. To illuminate the societal impact of aging, an increasing trend in anti-senescence and anti-aging interventions, including pharmacological interventions, medical procedures, and lifestyle changes is discussed, including further context of senescence.

An Association between HTRA1 and TGF-β2 in the Vitreous Humor of Patients with Chorioretinal Vascular Diseases

Background: The aim of this paper was to investigate the protein concentrations of high-temperature requirement A 1 (HTRA1) and transforming growth factor-β (TGF-β) in the vitreous humor of patients with chorioretinal vascular diseases. Methods: This study measured protein concentrations of HTRA1, TGF-β1-3, and vascular endothelial growth factor A (hereinafter called VEGF) in the vitreous humor from seven eyes of patients with chorioretinal vascular diseases (age-related macular degeneration, diabetic macular edema, and retinal vein occlusion) and six control eyes (idiopathic epiretinal membrane and macular hole). We analyzed the mutual relationship among the protein levels. Results: The protein levels of HTRA1 and VEGF were significantly increased in the chorioretinal vascular disease group compared with the control group (1.57 ± 0.79 ×10-9 mol/mL vs. 0.68 ± 0.79 ×10-9 mol/mL, p = 0.039; 3447.00 ± 3423.47 pg/mL vs. 35.33 ± 79.01 pg/mL, p = 0.046, respectively). TGF-β2 levels were not significantly different between groups (2222.71 ± 1151.25 pg/mL for the chorioretinal vascular disease group vs. 1918.83 ± 744.01 pg/mL for the control group, p = 0.62). The concentration of HTRA1 was strongly associated with TGF-β2 levels in the vitreous humor, independent of VEGF (r = 0.80, p = 0.0010). Conclusions: We revealed that vitreous HTRA1 was increased in patients with chorioretinal vascular diseases and strongly correlated with TGF-β2.

Modeling early pathophysiological phenotypes of diabetic retinopathy in a human inner blood-retinal barrier-on-a-chip

Diabetic retinopathy (DR) is a microvascular disorder characterized by inner blood-retinal barrier (iBRB) breakdown and irreversible vision loss. While the symptoms of DR are known, disease mechanisms including basement membrane thickening, pericyte dropout and capillary damage remain poorly understood and interventions to repair diseased iBRB microvascular networks have not been developed. In addition, current approaches using animal models and in vitro systems lack translatability and predictivity to finding new target pathways. Here, we develop a diabetic iBRB-on-a-chip that produces pathophysiological phenotypes and disease pathways in vitro that are representative of clinical diagnoses. We show that diabetic stimulation of the iBRB-on-a-chip mirrors DR features, including pericyte loss, vascular regression, ghost vessels, and production of pro-inflammatory factors. We also report transcriptomic data from diabetic iBRB microvascular networks that may reveal drug targets, and examine pericyte-endothelial cell stabilizing strategies. In summary, our model recapitulates key features of disease, and may inform future therapies for DR.