Abstract

PurposeTo investigate the effect of age on wound healing after small incision lenticule extraction (SMILE) and the underlying metabolomic mechanisms. MethodsThis prospective study was conducted on 216 patients in four groups: the 18–20 (n = 38, Group I), 21–30 (n = 84, Group Ⅱ), 31–40 (n = 58, Group Ⅲ), and 41–50 (n = 36, Group IV) age groups. The density of corneal epithelial wing cells, basal cells, corneal stromal cells, endothelial cells and corneal nerves were examined with a laser confocal microscope (HRT III-RCM) before and 1 month, 3 month, 6 month and 1 year after SMILE. The central nerve fiber length (CNFL), the central corneal nerve fibre density (CNFD), and the central corneal nerve branch density (CNBD) were analyzed by Nero J. The corneal stroma lenticules were obtained from SMILE to analyze metabolites by high-performance liquid chromatography coupled with quadrupole time-of-flight tandem mass spectrometry (HPLC-QTOF-MS). ResultsThe density of corneal wing epithelial cells and basal epithelial cells have no significant difference among the four groups. The CNFL was 21.90 ± 1.68 mm/mm2 in Group Ⅰ and 21.63 ± 2.09 mm/mm2 in Group Ⅱ after 1 year of SMILE, which represented a return to the preoperative level, whereas the CNFL of Group Ⅲ (19.40 ± 0.98 mm/mm2) and Group Ⅳ (18.94 ± 0.72 mm/mm2) were lower than that preoperation (P ˂0.01). CNFL repair had a negative correlation with age after surgery (Pearson's R = −0.572, P ˂0.01). The CNFD and the CNBD showed the same trend with the CNFL (Pearson's R = −0.602 and −0.531, P ˂0.05). Through screening the significantly different metabolites between the 18–30 age group (including Group I and Group Ⅱ) and other two groups, 6 common remarkably different metabolites were identified. Meanwhile, 5 unique different metabolites were identified only between the 18–30 age group and the 31–40 age group. Six unique different metabolites were identified only between the 18–30 age group and the 41–50 age group. ConclusionCorneal nerve repair after SMILE was significantly affected by age. The identified age-associated differences in metabolites were mainly related to inflammation, oxidation, nerve protection and regeneration.

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