Background To compare and analyze the imaging differences between anterior segment optical coherence tomography (AS-OCT) and ultrasound biomicroscopy (UBM) in acute keratoconus. Method The features of AS-OCT and UBM images of acute keratoconus patients in Hebei Eye Hospital were analyzed retrospectively. Result From May 2016 to December 2020, 38 patients (38 eyes) with acute keratoconus were treated in Hebei Eye Hospital. Both AS-OCT and UBM images showed rupture of the posterior elastic layer of cornea, edema and thickening of stroma layer, and cracks formed in it to communicate with anterior chamber. AS-OCT image showed that corneal epithelium was intact, and 26 cases had subcutaneous effusion. UBM images showed delamination of the posterior elastic layer interface in 26 cases. Paired t test showed that there was significant difference between preoperative and postoperative best corrected visual acuity in all patients (t = 11.861, P < 0.05). There was no significant difference in preoperative and postoperative best corrected visual acuity between group 1 and group 2 by independent sample t test (t = 0.751, P> 0.05, t = 0.219, P > 0.05). There was significant difference in the height of rupture between group 1 and group 2 (t =-7.533, P < 0.001). Pearson correlation analysis showed that there was a significant correlation between fracture size and fracture height (r = 0.766, P < 0.001), but no correlation between fracture size and post-elastic layer delamination (r =-0.107, P > 0.05). No corneal perforation was found in 38 cases (38 eyes). In the healing stage after deep lamellar keratoplasty, obvious stroma scar appeared, accompanied by corneal stroma thickening and corneal flattening. Conclusion AS-OCT and UBM can complement each other, provide accurate corneal imaging images and parameter measurement, and predict and evaluate the development of the disease.
Background: Phenomics provides a new technologies and platforms as a systematic phenome-genome approach. However, few studies have reported on the system mining of shared genetics among clinical biochemical indices based on Phenomics methods, especially in China. This study aimed to apply phenomics to systematically explore shared genetics among 29 biochemical indices based on the Fangchenggang Area Male Health and Examination Survey cohort. Result: A total of 1,999 subjects with 29 biochemical indices and 709,211 single nucleotide polymorphisms were subjected to phenomics analysis. Three bioinformatics methods, namely, Pearson test, Jaccard index, and linkage disequilibrium score regression , were used. Results showed that 29 biochemical indices were from a network. IgA, IgG, IgE, IgM, HCY, AFP and B12 were in the central community of 29 biochemical indices. Key genes and loci associated with metabolism traits were further identified, shared-genetics analysis showed that 29 SNPs (P < 10 -4 ) were associated with three or more traits. After integrating the SNPs related to two or more traits with the GWAS catalog, 31 SNPs were found to be associated with several diseases (P < 10 -8 ). Taking ALDH2 as an example to preliminarily explore its biological function, we also confirmed that rs671 (ALDH2) polymorphism affected multiple traits of osteogenesis and adipogenesis differentiation in 3T3-L1 preadipocytes. Conclusion: All these findings indicated a network of shared genetics and 29 biochemical indices, which will helpfully understand the genetics participated in biochemical metabolism.
Background: Phenomics provides new technologies and platforms as a systematic phenome-genome approach. However, few studies have reported on the systematic mining of shared genetics among clinical biochemical indices based on phenomics methods, especially in China. This study aimed to apply phenomics to systematically explore shared genetics among 29 biochemical indices based on the Fangchenggang Area Male Health and Examination Survey cohort. Result: A total of 1,999 subjects with 29 biochemical indices and 709,211 single nucleotide polymorphisms (SNPs) were subjected to phenomics analysis. Three bioinformatics methods, namely, Pearson’s test, Jaccard’s index, and linkage disequilibrium score regression, were used. The results showed that 29 biochemical indices were from a network. IgA, IgG, IgE, IgM, HCY, AFP and B12 were in the central community of 29 biochemical indices. Key genes and loci associated with metabolism traits were further identified, and shared genetics analysis showed that 29 SNPs (P < 10-4) were associated with three or more traits. After integrating the SNPs related to two or more traits with the GWAS catalogue, 31 SNPs were found to be associated with several diseases (P < 10-8). Using ALDH2 as an example to preliminarily explore its biological function, we also confirmed that the rs671 (ALDH2) polymorphism affected multiple traits of osteogenesis and adipogenesis differentiation in 3T3-L1 preadipocytes. Conclusion: All these findings indicated a network of shared genetics and 29 biochemical indices, which will help fully understand the genetics participating in biochemical metabolism.
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