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  1. New SH, Leow SN, Vasudevan SK, Idris IB, Tang SF, Din NM
    PLoS One, 2021;16(2):e0246830.
    PMID: 33630879 DOI: 10.1371/journal.pone.0246830
    OBJECTIVE: To evaluate the retinal nerve fiber layer (RNFL) and macular thicknesses and identify systemic risk factors for thinning of these layers in patients with metabolic syndrome (MetS).

    METHODOLOGY: A cross-sectional observational study was performed on patients diagnosed with MetS and compared to normal controls. All patients underwent ophthalmic and anthropometric examination, serological and biochemical blood investigations; and ocular imaging using spectral-domain optical coherence tomography. Patients with ocular pathology were excluded. Unpaired t-test was used to compare mean thickness between the two groups. One-way ANOVA with Bonferroni correction for multiple comparisons was used to compare mean thickness between different tertiles of MetS parameters, and a generalized estimating equation was used to correct for inter-eye correlation and to assess association between mean thickness and covariates.

    RESULTS: Two hundred and forty-eight eyes from 124 participants (1:1 ratio of MetS patients to controls) were included. Age ranged between 30 to 50 years old, and mean age was 40 ± 6.6 years. RNFL thickness was lower globally (93.6 ± 9.9 μm vs 99.0 ± 9.3, p<0.001) and in the inferior (124.5 ± 17.5 μm vs 131.0 ± 16.4 μm, p = 0.002), superior (117.2 ± 16.0 μm vs 126.3 ± 14.4 μm, p<0.001) and temporal (65.5 ± 10.2 μm vs 69.5 ± 9.8, p = 0.002) sectors in MetS patients compared to controls. Only the central (237.0 ± 14.0 μm vs 243.6 ± 18.0 μm, p = 0.002) and inferior parafoveal (307.8 ± 20.9 vs 314.6 ± 14.6, p = 0.004) area of the macula was significantly thinner. The inferior RNFL sector had the most difference (mean difference = 9.1 μm). The Generalized Estimating Equation found that, after adjusting for age, diastolic blood pressure, BMI, HDL and obesity; the number of MetS components and elevated triglyceride levels were independent risk factors for reduced thickness in global RNFL (β = -4.4, 95% CI = -7.29 to -1.5, p = 0.003) and inferior parafovea (β = -6.85, 95% CI = -11.58 to -2.13, p = 0.004) thickness respectively.

    CONCLUSION: RNFL thinning was seen more than macula thinning in MetS patients, suggesting RNFL susceptibility to neurodegeneration than the macula. A higher number of metabolic components and elevated triglyceride levels were independent risk factors for retinal thinning in this group of patients.

    Matched MeSH terms: Retinal Neurons/pathology*
  2. Chai X, Low KY, Tham YC, Chee ML, Thakur S, Zhang L, et al.
    Invest Ophthalmol Vis Sci, 2020 08 03;61(10):37.
    PMID: 32821913 DOI: 10.1167/iovs.61.10.37
    Purpose: Genome-wide association studies have identified several genes associated with glaucoma. However, their roles in the pathogenesis of glaucoma remain unclear, particularly their effects on retinal nerve fiber layer (RNFL) thickness. The aim of this study was to investigate the associations between the identified glaucoma risk genes and RNFL thickness.

    Methods: A total of 3843 participants (7,020 healthy eyes) were enrolled from the Singapore Epidemiology of Eye Diseases (SEED) study, a population-based study composing of three major ethnic groups-Malay, Indian, and Chinese-in Singapore. Ocular examinations were performed, and spectral-domain optical coherence tomography (SD-OCT) was used to measure circumpapillary RNFL thickness. We selected 35 independent glaucoma-associated genetic loci for analysis. An linear regression model was conducted to determine the association of these variants with circumpapillary RNFL, assuming an additive genetic model. We conducted association analysis in each of the three ethnic groups, followed by a meta-analysis of them.

    Results: The mean age of the included participants was 59.4 ± 8.9 years, and the mean RFNL thickesss is 92.3 ± 11.2 µm. In the meta-analyses, of the 35 glacuoma loci, we found that only SIX6 was significantly associated with reduction in global RNFL thickness (rs33912345; β = -1.116 um per risk allele, P = 1.64E-05), and the effect size was larger in the inferior RNFL quadrant (β = -2.015 µm, P = 2.9E-6), and superior RNFL quadrant (β = -1.646 µm, P = 6.54E-5). The SIX6 association were consistently observed across all three ethnic groups. Other than RNFL, we also found several genetic varaints associated with vertical cuo-to-disc ratio (ATOH7, CDKN2B-AS1, and TGFBR3-CDC7), rim area (SIX6 and CDKN2B-AS1), and disc area (SIX6, ATOH7, and TGFBR3-CDC7). The association of SIX6 rs33912345 with NRFL thickness remained similar after further adjusting for disc area and 3 other disc parameter associated SNPs (ATOH7, CDKN2B-AS1, and TGFBR3-CDC7).

    Conclusions: Of the 35 glaucoma identified risk loci, only SIX6 is significantly and independently associated with thinner RNFL. Our study further supports the involvement of SIX6 with RNFL thickness and pathogensis of glaucoma.

    Matched MeSH terms: Retinal Neurons/pathology*
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