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Association of 2 Lysyl Oxidase Gene Single Nucleotide Polymorphisms with Keratoconus: A Nationwide Registration Study

Overview
Journal Ophthalmol Sci
Specialty Ophthalmology
Date 2023 Feb 7
PMID 36748061
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Abstract

Purpose: Keratoconus (KC) is the most common primary ectatic corneal disease, characterized by progressive thinning of the cornea, affecting its shape and structure and leading to visual loss. Lysyl oxidase is an important component of the extracellular matrix and contributes to the homeostasis of corneal stromal extracellular matrix via enzymatic reaction. This nationwide registration study aims to examine the association of KC with 2 known single nucleotide polymorphisms, rs2956540 and rs10519694, in a population of Iranian descent.

Design: Case-control.

Participants: One hundred seventy-eight subjects with KC and 180 clinically healthy subjects participated in the study.

Methods: Genomic DNA was extracted from peripheral blood samples, and their genotypes were determined using tetra-primer amplification refractory mutation system-polymerase chain reaction.

Main Outcome Measures: Allele frequency for rs2956540 and rs10519694.

Results: Genotype frequency was significantly different between cases and controls for rs2956540 ( value = 0.019). The rs2956540 C allele carriers were significantly more frequent among KC cases than healthy controls ( value = 0.015, value = 0.017). There was a significant difference in genotype frequency between groups for rs10519694 ( value = 0.001). T allele carriers were significantly more frequent among KC patients ( value = 0.002, value = 0.001). Sex stratification revealed no significant differences in genotype frequency between males and females in cases and controls. Fitting the general linear model showed that rs10519694 could be considered a predictor for the development of KC ( value = 0.001); however, this was not observed for rs2956540 ( value = 0.323).

Conclusions: rs2956540 and rs10519694 are associated with KC in a population of Iranian descent. rs10519694 could potentially be used for KC risk prediction.

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