This Burmese population, particularly women, has a relatively short AL and ACD. NO is the strongest predictor of refractive error across all age groups in this population.

Adult stature is independently associated with vitreous chamber length and corneal radius in this Burmese population. Heavier persons were slightly hyperopic.

Underlying diagnosis of neovascular glaucoma is a significant risk factor for hypotony post TCP.

No abstract

Normal tension glaucoma (NTG) is a major form of glaucoma, associated with intraocular pressures that are within the statistically normal range of the population. OPA1, the gene responsible for autosomal dominant optic atrophy represents an excellent candidate gene for NTG, as the clinical phenotypes are similar and OPA1 is expressed in the retina and optic nerve. Eighty-three well-characterized NTG patients were screened for mutations in OPA1 by heteroduplex analysis and bi-directional sequencing. Sequences found to be altered in NTG subjects were examined for variations in 100 population controls. A second cohort of 80 NTG patients and 86 population controls was subsequently screened to determine whether the initial findings could be replicated. A single nucleotide polymorphism (SNP) on intervening sequence (IVS) 8 (IVS8 + 4 C/T) was found to be strongly associated with the occurrence of NTG in both cohorts (chi(2)=7.97, P=0.005 in the first cohort, chi(2)=9.93, P=0.002 in the second cohort; odds ratio 3.1 (95% CI: 1.8-5.6). A second SNP (IVS8 + 32 T/C) appeared to be associated with disease in the first cohort (chi(2)=4.71, P=0.030), but this finding could not be replicated in the second cohort. In the combined cohort, the compound at-risk genotype IVS8 + 4 C/T, + 32 T/C was strongly associated with the occurrence of NTG (chi(2)=22.04, P=0.00001 after correcting for testing four genotypes). These results indicate that polymorphisms in the OPA1 gene are associated with NTG and may be a marker for the disease.

Heavy alcohol consumption is an established risk factor for hypertension; the mechanism by which alcohol consumption impact blood pressure (BP) regulation remains unknown. We hypothesized that a genome-wide association study accounting for gene-alcohol consumption interaction for BP might identify additional BP loci and contribute to the understanding of alcohol-related BP regulation. We conducted a large two-stage investigation incorporating joint testing of main genetic effects and single nucleotide variant (SNV)-alcohol consumption interactions. In Stage 1, genome-wide discovery meta-analyses in ≈131K individuals across several ancestry groups yielded 3,514 SNVs (245 loci) with suggestive evidence of association (P < 1.0 x 10−5). In Stage 2, these SNVs were tested for independent external replication in ≈440K individuals across multiple ancestries. We identified and replicated (at Bonferroni correction threshold) five novel BP loci (380 SNVs in 21 genes) and 49 previously reported BP loci (2,159 SNVs in 109 genes) in European ancestry, and in multi-ancestry meta-analyses (P < 5.0 x 10−8). For African ancestry samples, we detected 18 potentially novel BP loci (P < 5.0 x 10−8) in Stage 1 that warrant further replication. Additionally, correlated meta-analysis identified eight novel BP loci (11 genes). Several genes in these loci (e.g., PINX1, GATA4, BLK, FTO and GABBR2) have been previously reported to be associated with alcohol consumption. These findings provide insights into the role of alcohol consumption in the genetic architecture of hypertension.

and for the BONSAI (Brain and Optic Nerve Study with Artificial Intelligence) Study Group Objective: To compare the diagnostic performance of an artificial intelligence deep learning system with that of expert neuro-ophthalmologists in classifying optic disc appearance. Methods: The deep learning system was previously trained and validated on 14,341 ocular fundus photographs from 19 international centers. The performance of the system was evaluated on 800 new fundus photographs (400 normal optic discs, 201 papilledema [disc edema from elevated intracranial pressure], 199 other optic disc abnormalities) and compared with that of 2 expert neuro-ophthalmologists who independently reviewed the same randomly presented images without clinical information. Area under the receiver operating characteristic curve, accuracy, sensitivity, and specificity were calculated. Results: The system correctly classified 678 of 800 (84.7%) photographs, compared with 675 of 800 (84.4%) for Expert 1 and 641 of 800 (80.1%) for Expert 2. The system yielded areas under the receiver operating characteristic curve of 0.97 (95% confidence interval [CI] = 0.96-0.98), 0.96 (95% CI = 0.94-0.97), and 0.89 (95% CI = 0.87-0.92) for the detection of normal discs, papilledema, and other disc abnormalities, respectively. The accuracy, sensitivity, and specificity of the system's classification of optic discs were similar to or better than the 2 experts. Intergrader agreement at the eye level was 0.71 (95% CI = 0.67-0.76) between Expert 1 and Expert 2, 0.72 (95% CI = 0.68-0.76) between the system and Expert 1, and 0.65 (95% CI = 0.61-0.70) between the system and Expert 2. Interpretation: The performance of this deep learning system at classifying optic disc abnormalities was at least as good as 2 expert neuro-ophthalmologists. Future prospective studies are needed to validate this system as a diagnostic aid in relevant clinical settings.

Prevalence of anisometropia is relatively high in this rural adult population in Myanmar. Myopia and cataract, but not increasing age, are the potential risk factors of anisometropia in this population.