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Tin Aung, Chiea Chuen Khor, Ching-Yu Cheng, Rahat Husain, Tina T Wong, Shamira Perera, Tien Y Wong, Eranga Nishanthie Vithana, Monisha Esther Nongpiur; Integration of Genetic and Biometric Risk Factors for Detection of Primary Angle-Closure Glaucoma. Invest. Ophthalmol. Vis. Sci. 2019;60(9):1606. doi: https://doi.org/.
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© ARVO (1962-2015); The Authors (2016-present)
Several genetic loci are associated with primary angle closure glaucoma (PACG). The purpose of this study is to investigate whether knowledge of these genetic loci allows improved prediction of PACG, compared to anterior segment parameters measured by imaging.
In this case-control study we evaluated a total of 1453 subjects with PACG and 927 controls of Chinese ethnicity from Singapore. The 8 PACG SNPs (rs11024102 at PLEKHA7, rs3753841 at COL11A1, rs1015213 located between PCMTD1 and ST18 on Chromosome 8q, rs3816415 at EPDR1, rs1258267 at CHAT, rs736893 at GLIS3, rs7494379 at FERMT2, and rs3739821 mapping in between DPM2 and FAM102A) were genotyped by Taqman assays. Customized software was used to measure anterior segment optical coherence tomography (ASOCT) parameters, namely anterior chamber depth, width, and area (ACD, ACW, ACA) and lens vault (LV). Statistical analysis for positive predictive values was modelled using the Receiver operating characteristic curve. Statistical significance comparing predictive power of the different parameters was calculated using permutation.
A total of 388 PACG subjects and 751 controls with both ASOCT and genetic data were available for analysis. Anterior segment parameters including ACD, ACA, and LV had excellent predictive value (AUC >0.94), except ACW (AUC = 0.65) for identifying PACG. The inclusion of additional genetic risk alleles (either singly or as a composite genetic risk score for 8 GWAS SNPs) to ACD only provided a +0.50% improvement in re-classifying PACG cases and controls over and above the discriminatory value of ACD. This +0.50% improvement was not statistically significant (P>0.05).The mean weighted genetic risk scores were 0.54±0.14 and 0.46±0.13 in PACG and controls, respectively (P<0.001). After adjusting for age and gender, higher weighted genetic risk score was associated significantly with higher risk of PACG status, with an OR of 7.00 (95% CI, 4.51, 10.78; p<0.001) comparing the lowest quartile with the highest quartile.
Although significant on their own, the incorporation of genetic data in the context of anterior segment imaging parameters like ACD provided only a marginal improvement of PACG detection.
This abstract was presented at the 2019 ARVO Annual Meeting, held in Vancouver, Canada, April 28 - May 2, 2019.
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