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DOI 10.1167/iovs.17-21436

Медицинская библиотека · Investigative ophthalmology & visual science · 2017

Oxidative Stress Measures of Lipid and DNA Damage in Human Tears.

Haworth Kristina M, Chandler Heather L

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Аннотация

PURPOSE: We evaluate feasibility and repeatability of measures for lipid peroxidation and DNA oxidation in human tears, as well as relationships between outcome variables, and compared our findings to previously reported methods of evaluation for ocular sun exposure.

METHODS

A total of 50 volunteers were seen for 2 visits 14 ± 2 days apart. Tear samples were collected from the inferior tear meniscus using a glass microcapillary tube. Oxidative stress biomarkers were quantified using enzyme-linked immunosorbent assay (ELISA): lipid peroxidation by measurement of hexanoyl-lysine (HEL) expression; DNA oxidation by measurement of 8-oxo-2'-deoxyguinosone (8OHdG) expression. Descriptive statistics were generated. Repeatability estimates were made using Bland-Altman plots with mean differences and 95% limits of agreement were calculated. Linear regression was conducted to evaluate relationships between measures.

RESULTS

Mean (±SD) values for tear HEL and 8OHdG expression were 17368.02 (±9878.42) nmol/L and 66.13 (±19.99) ng/mL, respectively. Repeatability was found to be acceptable for both HEL and 8OHdG expression. Univariate linear regression supported tear 8OHdG expression and spring season of collection to be predictors of higher tear HEL expression; tear HEL expression was confirmed as a predictor of higher tear 8OHdG expression.

CONCLUSIONS

We demonstrate feasibility and repeatability of estimating previously unreported tear 8OHdG expression. Seasonal temperature variation and other factors may influence tear lipid peroxidation. Support is demonstrated to suggest lipid damage and DNA damage occur concurrently on the human ocular surface.

Для цитирования: Haworth Kristina M, Chandler Heather L. Oxidative Stress Measures of Lipid and DNA Damage in Human Tears.. Investigative ophthalmology & visual science. 2017. DOI: 10.1167/iovs.17-21436.

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