RESUMO
We investigated the association between the SDF-1-3' (c801G > A) variant and the development of diabetic macular edema (DME) or proliferative diabetic retinopathy (PDR) in a Hungarian cohort. SDF-1-3' (c801G > A) was genotyped in 103 patients with diabetic retinopathy and 31 age- and sex-matched non-diabetic controls. Central retinal and choroidal thickness was measured by swept-source optical coherence tomography. The distribution of heterozygous and homozygous SDF-1-3' (c801G > A) genotypes was similar in diabetic and control subjects. The SDF-3'(c801AA) genotype was associated with DME (n = 94 eyes, allele distribution p = 0.006, genotype distribution p = 0.01 OR: 2.48, 95% CL: 1.21-5.08) in both univariable and multivariable modelling, independent of duration and type of diabetes, HbA1C, hypertension and microalbuminuria (p = 0.03). DME occurred earlier in patients carrying the SDF-1 (c801A) allele (Kaplan-Meier analysis, log-rank test p = 0.02). A marginally significant association was found between the presence of the SDF-1 (c801A) allele and the development of PDR (n = 89 eyes, p = 0.06). The SDF-1-3' (c801A) allele also showed a correlation with central retinal (p = 0.006) and choroidal (p = 0.08) thickness. SDF-1-3' (c801G > A) is involved in the development of macular complications in DM independent of critical clinical factors, suggesting that SDF-1 may be a future therapeutic target for high-risk patients, especially those carrying the SDF-1 (c801A) allele.
Assuntos
Quimiocina CXCL12 , Retinopatia Diabética , Humanos , Quimiocina CXCL12/genética , Retinopatia Diabética/genética , Feminino , Masculino , Hungria , Pessoa de Meia-Idade , Idoso , Alelos , Polimorfismo de Nucleotídeo Único , Predisposição Genética para Doença , Genótipo , Estudos de Casos e Controles , Tomografia de Coerência Óptica , Edema Macular/genéticaRESUMO
Perinatal asphyxia (PA) poses a significant threat to multiple organs, particularly the kidneys. Diagnosing PA-associated kidney injury remains challenging, and treatment options are inadequate. Furthermore, there is a lack of long-term follow-up data regarding the renal implications of PA. In this study, 7-day-old male Wistar rats were exposed to PA using a gas mixture (4% O2; 20% CO2 in N2 for 15 min) to investigate molecular pathways linked to renal tubular damage, hypoxia, angiogenesis, heat shock response, inflammation, and fibrosis in the kidney. In a second experiment, adult rats with a history of PA were subjected to moderate renal ischemia-reperfusion (IR) injury to test the hypothesis that PA exacerbates renal susceptibility. Our results revealed an increased gene expression of renal injury markers (kidney injury molecule-1 and neutrophil gelatinase-associated lipocalin), hypoxic and heat shock factors (hypoxia-inducible factor-1α, heat shock factor-1, and heat shock protein-27), proinflammatory cytokines (interleukin-1ß, interleukin-6, tumor necrosis factor-α, and monocyte chemoattractant protein-1), and fibrotic markers (transforming growth factor-ß, connective tissue growth factor, and fibronectin) promptly after PA. Moreover, a machine learning model was identified through random forest analysis, demonstrating an impressive classification accuracy (95.5%) for PA. Post-PA rats showed exacerbated functional decline and tubular injury and more intense hypoxic, heat shock, proinflammatory, and profibrotic response after renal IR injury compared with controls. In conclusion, PA leads to subclinical kidney injury, which may increase the susceptibility to subsequent renal damage later in life. In addition, the parameters identified through random forest analysis provide a robust foundation for future biomarker research in the context of PA.NEW & NOTEWORTHY This article demonstrates that perinatal asphyxia leads to subclinical kidney injury that permanently increases renal susceptibility to subsequent ischemic injury. We identified major molecular pathways involved in perinatal asphyxia-induced renal complications, highlighting potential targets of therapeutic approaches. In addition, random forest analysis revealed a model that classifies perinatal asphyxia with 95.5% accuracy that may provide a strong foundation for further biomarker research. These findings underscore the importance of multiorgan follow-up for perinatal asphyxia-affected patients.