The potential of current polygenic risk scores to predict high myopia and myopic macular degeneration in multi-ethnic Singapore adults

Purpose: To evaluate the trans-ancestry portability of current myopia polygenic risk scores (PRS) to predict high myopia (HM) and myopic macular degeneration (MMD) in an Asian population. Design: Population-based study. Subjects: A total of 5,894 (2,141 Chinese, 1,913 Indians, and 1,840 Malays) adults from the Singapore Epidemiology of Eye Diseases (SEED) study were included in the analysis. The mean age was 57.0 (standard deviation, SD = 9.31) years. A total of 361 adults had HM (spherical equivalent, SE -0.5D). Methods: The PRS, derived from 687,289 HapMap3 SNPs from the largest genome-wide association study of myopia in Europeans to date (n = 260,974), was assessed on its ability to predict HM and MMD versus controls. Main outcome measures: The primary outcomes were the area under the receiver operating characteristic curve (AUROC) to predict HM and MMD. Results: The PRS had an AUROC of 0.73 (95% CI: 0.70, 0.75) for HM and 0.66 (95% CI: 0.63, 0.70) for MMD versus no myopia controls. The inclusion of the PRS with other predictors (age, sex, educational attainment (EA), and ancestry; age-by-ancestry; sex-by-ancestry and EA-by-ancestry interactions; and 20 genotypic principal components) increased the AUROC to 0.84 (95% CI: 0.82, 0.86) for HM and 0.79 (95% CI: 0.76, 0.82) for MMD. Individuals with a PRS in the top 5% had 4.66 (95% CI: 3.34, 6.42) times higher risk for HM and 3.43 (95% CI: 2.27, 5.05) times higher risk for MMD compared to the remaining 95% of individuals. Conclusion: The PRS is a good predictor for HM and will facilitate the identification of high-risk children to prevent myopia progression to HM. In addition, the PRS also predicts MMD and will help to identify high-risk myopic adults who require closer monitoring for myopia-related complications.info:eu-repo/semantics/publishedVersio

Class based Influence Functions for Error Detection

Influence functions (IFs) are a powerful tool for detecting anomalous examples in large scale datasets. However, they are unstable when applied to deep networks. In this paper, we provide an explanation for the instability of IFs and develop a solution to this problem. We show that IFs are unreliable when the two data points belong to two different classes. Our solution leverages class information to improve the stability of IFs. Extensive experiments show that our modification significantly improves the performance and stability of IFs while incurring no additional computational cost.Comment: Thang Nguyen-Duc, Hoang Thanh-Tung, and Quan Hung Tran are co-first authors of this paper. 12 pages, 12 figures. Accepted to ACL 202

New Polygenic Risk Score to Predict High Myopia in Singapore Chinese Children

PurposeThe purpose of this study was to develop an Asian polygenic risk score (PRS) to predict high myopia (HM) in Chinese children in the Singapore Cohort of Risk factors for Myopia (SCORM) cohort.MethodsWe included children followed from 6 to 11 years old until teenage years (12-18 years old). Cycloplegic autorefraction, ultrasound biometry, Illumina HumanHap 550, or 550 Duo Beadarrays, demographics, and environmental factors data were obtained. The PRS was generated from the Consortium for Refractive Error and Myopia genomewide association study (n = 542,934) and the Strabismus, Amblyopia, and Refractive Error in Singapore children Study (n = 500). The Growing Up in Singapore Towards healthy Outcomes Cohort study (n = 339) was the replication cohort. The outcome was teenage HM (≤ -5.00 D) with predictive performance assessed using the area under the curve (AUC).ResultsMean baseline age ± SD was 7.85 ± 0.84 (n = 1004) and 571 attended the teenage visit; 23.3% had HM. In multivariate analysis, the PRS was associated with a myopic spherical equivalent with an incremental R2 of 0.041 (95% confidence interval [CI] = 0.010, 0.073; P < 0.001). AUC for HM (0.77 [95% CI = 0.71-0.83]) performed better (P = 0.02) with the PRS compared with a model without (0.72 [95% CI = 0.65, 0.78]). Children at the top 25% PRS risk had a 2.34-fold-greater risk of HM (95% CI = 1.53, 3.55; P < 0.001).ConclusionsThe new Asian PRS improved the predictive performance to detect children at risk of HM.Translational relevanceClinicians may use the PRS with other predictive factors to identify high risk children and guide interventions to reduce the risk of HM later in life

Gene therapy in patient-specific stem cell lines and a preclinical model of retinitis pigmentosa with membrane frizzled-related protein defects

Defects in Membrane Frizzled-related Protein (MFRP) cause autosomal recessive retinitis pigmentosa (RP). MFRP codes for a retinal pigment epithelium (RPE)-specific membrane receptor of unknown function. In patient-specific induced pluripotent stem (iPS)-derived RPE cells, precise levels of MFRP, and its dicistronic partner CTRP5, are critical to the regulation of actin organization. Overexpression of CTRP5 in naive human RPE cells phenocopied behavior of MFRP-deficient patient RPE (iPS-RPE) cells. AAV8 (Y733F) vector expressing human MFRP rescued the actin disorganization phenotype and restored apical microvilli in patient-specific iPS-RPE cell lines. As a result, AAV-treated MFRP mutant iPS-RPE recovered pigmentation and transepithelial resistance. The efficacy of AAV-mediated gene therapy was also evaluated in Mfrp(rd6)/Mfrp(rd6) mice--an established preclinical model of RP--and long-term improvement in visual function was observed in AAV-Mfrp-treated mice. This report is the first to indicate the successful use of human iPS-RPE cells as a recipient for gene therapy. The observed favorable response to gene therapy in both patient-specific cell lines, and the Mfrp(rd6)/Mfrp(rd6) preclinical model suggests that this form of degeneration caused by MFRP mutations is a potential target for interventional trials

Deep learning system to predict the 5-year risk of high myopia using fundus imaging in children

Our study aims to identify children at risk of developing high myopia for timely assessment and intervention, preventing myopia progression and complications in adulthood through the development of a deep learning system (DLS). Using a school-based cohort in Singapore comprising 998 children (aged 6-12 years old), we train and perform primary validation of the DLS using 7456 baseline fundus images of 1878 eyes; with external validation using an independent test dataset of 821 baseline fundus images of 189 eyes together with clinical data (age, gender, race, parental myopia, and baseline spherical equivalent (SE)). We derive three distinct algorithms - image, clinical, and mix (image + clinical) models to predict high myopia development (SE ≤ -6.00 diopter) during teenage years (5 years later, age 11-17). Model performance is evaluated using the area under the receiver operating curve (AUC). Our image models (Primary dataset AUC 0.93-0.95; Test dataset 0.91-0.93), clinical models (Primary dataset AUC 0.90-0.97; Test dataset 0.93-0.94) and mixed (image + clinical) models (Primary dataset AUC 0.97; Test dataset 0.97-0.98) achieve clinically acceptable performance. The addition of 1 year SE progression variable has minimal impact on the DLS performance (clinical model AUC 0.98 versus 0.97 in the primary dataset, 0.97 versus 0.94 in the test dataset; mixed model AUC 0.99 versus 0.97 in the primary dataset, 0.95 versus 0.98 in test dataset). Thus, our DLS allows prediction of the development of high myopia by teenage years amongst school-going children. This has potential utility as a clinical decision support tool to identify "at-risk" children for early intervention.info:eu-repo/semantics/publishedVersio

TextANIMAR: Text-based 3D Animal Fine-Grained Retrieval

3D object retrieval is an important yet challenging task, which has drawn more and more attention in recent years. While existing approaches have made strides in addressing this issue, they are often limited to restricted settings such as image and sketch queries, which are often unfriendly interactions for common users. In order to overcome these limitations, this paper presents a novel SHREC challenge track focusing on text-based fine-grained retrieval of 3D animal models. Unlike previous SHREC challenge tracks, the proposed task is considerably more challenging, requiring participants to develop innovative approaches to tackle the problem of text-based retrieval. Despite the increased difficulty, we believe that this task has the potential to drive useful applications in practice and facilitate more intuitive interactions with 3D objects. Five groups participated in our competition, submitting a total of 114 runs. While the results obtained in our competition are satisfactory, we note that the challenges presented by this task are far from being fully solved. As such, we provide insights into potential areas for future research and improvements. We believe that we can help push the boundaries of 3D object retrieval and facilitate more user-friendly interactions via vision-language technologies.Comment: arXiv admin note: text overlap with arXiv:2304.0573

INVESTIGATING THE ANTI-INFLAMMATORY ACTIVITY OF AN ETHANOLIC EXTRACT FROM ARTOCARPUS TONKINENSIS LEAVES USING A COLLAGEN ANTIBODY-INDUCED ARTHRITIC MOUSE MODEL

The obtained results here demonstrate that the 70% ethanolic leaf extract of A. tonkinensis (AT2), traditionally used in Vietnamese folk medicine for treating arthritic symtoms, has beneficial effects on pro-inflammatory cytokine inhibition and in an experimental arthritic mouse model. LPS-stimulated RAW 264.7 macrophages treated with AT2 showed a significant decrease in the production of IL-6 and TNFa at concentrations of 12.5, 25 and 50 µg/mL (P0.05), indicating its potential anti-inflammatory properties. Treatment of CAIA mice with AT2 also led to diminish the incidence of arthritis at doses of 200 and 300 mg/kg body weight

Meibomian gland lipid alterations and ocular surface sequela in Awat2 knockout murine model of meibomian gland dysfunction and evaporative dry eye disease

PurposeThere is an urgent need for animal models of meibomian gland dysfunction (MGD) and evaporative dry eye disease (EDED) to understand their pathophysiology and investigate novel therapeutics. This study sought to further define the acyl-CoA: wax alcohol acyltransferase 2 knockout (Awat2 KO) mouse as a model of EDED using a combination of novel clinical, biochemical, and biophysical endpoints.MethodsWildtype and Awat2 KO mice between 1 and 18 months of age were used. Ocular examinations and advanced imaging were performed. The lipidomic composition and in situ melting temperature of meibum were determined. qPCR was performed to define ocular surface gene and pro-inflammatory transcript expression. Dynamic contact angle goniometry was performed to assess the adherence capability of the ocular surface.ResultsAwat2 KO mice have mild, white, hyperreflective corneal opacities of the anterior stroma and significantly enlarged apical epithelial cells (P = 0.0004). In Awat2 KO meibum, wax esters were 9-10 times lower than in wildtype meibum. Additionally, meibum melting temperature increased from 32° to 47 °C (P < 0.0001), leading to impaired meibum secretion and dilation of the central duct. Awat2 KO corneal epithelia had significantly decreased mucin expression (Muc1 and Muc4, P = 0.0043) and increased interferon-γ production (P = 0.0303). Awat2 KO globes have a significantly shortened time of droplet adherence to their ocular surface (P = 0.0053), indicating a decreased tear film adherence capacity. Wildtype corneal epithelia does not express Awat2, indicating that the EDED phenotype is secondary to the loss of Awat2 from the meibomian glands.ConclusionsAwat2 KO mice recapitulate many of features of human MGD and EDED, representing a model to test novel therapeutics