High-throughput characterization of functional variants highlights heterogeneity and polygenicity underlying lung cancer susceptibility.

Genome-wide association studies (GWASs) have identified numerous lung cancer risk-associated loci. However, decoding molecular mechanisms of these associations is challenging since most of these genetic variants are non-protein-coding with unknown function. Here, we implemented massively parallel reporter assays (MPRAs) to simultaneously measure the allelic transcriptional activity of risk-associated variants. We tested 2,245 variants at 42 loci from 3 recent GWASs in East Asian and European populations in the context of two major lung cancer histological types and exposure to benzo(a)pyrene. This MPRA approach identified one or more variants (median 11 variants) with significant effects on transcriptional activity at 88% of GWAS loci. Multimodal integration of lung-specific epigenomic data demonstrated that 63% of the loci harbored multiple potentially functional variants in linkage disequilibrium. While 22% of the significant variants showed allelic effects in both A549 (adenocarcinoma) and H520 (squamous cell carcinoma) cell lines, a subset of the functional variants displayed a significant cell-type interaction. Transcription factor analyses nominated potential regulators of the functional variants, including those with cell-type-specific expression and those predicted to bind multiple potentially functional variants across the GWAS loci. Linking functional variants to target genes based on four complementary approaches identified candidate susceptibility genes, including those affecting lung cancer cell growth. CRISPR interference of the top functional variant at 20q13.33 validated variant-to-gene connections, including RTEL1, SOX18, and ARFRP1. Our data provide a comprehensive functional analysis of lung cancer GWAS loci and help elucidate the molecular basis of heterogeneity and polygenicity underlying lung cancer susceptibility.

Massively parallel reporter assays and variant scoring identified functional variants and target genes for melanoma loci and highlighted cell-type specificity.

The most recent genome-wide association study (GWAS) of cutaneous melanoma identified 54 risk-associated loci, but functional variants and their target genes for most have not been established. Here, we performed massively parallel reporter assays (MPRAs) by using malignant melanoma and normal melanocyte cells and further integrated multi-layer annotation to systematically prioritize functional variants and susceptibility genes from these GWAS loci. Of 1,992 risk-associated variants tested in MPRAs, we identified 285 from 42 loci (78% of the known loci) displaying significant allelic transcriptional activities in either cell type (FDR < 1%). We further characterized MPRA-significant variants by motif prediction, epigenomic annotation, and statistical/functional fine-mapping to create integrative variant scores, which prioritized one to six plausible candidate variants per locus for the 42 loci and nominated a single variant for 43% of these loci. Overlaying the MPRA-significant variants with genome-wide significant expression or methylation quantitative trait loci (eQTLs or meQTLs, respectively) from melanocytes or melanomas identified candidate susceptibility genes for 60% of variants (172 of 285 variants). CRISPRi of top-scoring variants validated their cis-regulatory effect on the eQTL target genes, MAFF (22q13.1) and GPRC5A (12p13.1). Finally, we identified 36 melanoma-specific and 45 melanocyte-specific MPRA-significant variants, a subset of which are linked to cell-type-specific target genes. Analyses of transcription factor availability in MPRA datasets and variant-transcription-factor interaction in eQTL datasets highlighted the roles of transcription factors in cell-type-specific variant functionality. In conclusion, MPRAs along with variant scoring effectively prioritized plausible candidates for most melanoma GWAS loci and highlighted cellular contexts where the susceptibility variants are functional.

Genome-wide association study identifies high-impact susceptibility loci for HCC in North America.

BACKGROUND AND AIMS: Despite the substantial impact of environmental factors, individuals with a family history of liver cancer have an increased risk for HCC. However, genetic factors have not been studied systematically by genome-wide approaches in large numbers of individuals from European descent populations (EDP). APPROACH AND RESULTS: We conducted a 2-stage genome-wide association study (GWAS) on HCC not affected by HBV infections. A total of 1872 HCC cases and 2907 controls were included in the discovery stage, and 1200 HCC cases and 1832 controls in the validation. We analyzed the discovery and validation samples separately and then conducted a meta-analysis. All analyses were conducted in the presence and absence of HCV. The liability-scale heritability was 24.4% for overall HCC. Five regions with significant ORs (95% CI) were identified for nonviral HCC: 3p22.1, MOBP , rs9842969, (0.51, [0.40-0.65]); 5p15.33, TERT , rs2242652, (0.70, (0.62-0.79]); 19q13.11, TM6SF2 , rs58542926, (1.49, [1.29-1.72]); 19p13.11 MAU2 , rs58489806, (1.53, (1.33-1.75]); and 22q13.31, PNPLA3 , rs738409, (1.66, [1.51-1.83]). One region was identified for HCV-induced HCC: 6p21.31, human leukocyte antigen DQ beta 1, rs9275224, (0.79, [0.74-0.84]). A combination of homozygous variants of PNPLA3 and TERT showing a 6.5-fold higher risk for nonviral-related HCC compared to individuals lacking these genotypes. This observation suggests that gene-gene interactions may identify individuals at elevated risk for developing HCC. CONCLUSIONS: Our GWAS highlights novel genetic susceptibility of nonviral HCC among European descent populations from North America with substantial heritability. Selected genetic influences were observed for HCV-positive HCC. Our findings indicate the importance of genetic susceptibility to HCC development.

Functional studies of lung cancer GWAS beyond association.

Fourteen years after the first genome-wide association study (GWAS) of lung cancer was published, approximately 45 genomic loci have now been significantly associated with lung cancer risk. While functional characterization was performed for several of these loci, a comprehensive summary of the current molecular understanding of lung cancer risk has been lacking. Further, many novel computational and experimental tools now became available to accelerate the functional assessment of disease-associated variants, moving beyond locus-by-locus approaches. In this review, we first highlight the heterogeneity of lung cancer GWAS findings across histological subtypes, ancestries and smoking status, which poses unique challenges to follow-up studies. We then summarize the published lung cancer post-GWAS studies for each risk-associated locus to assess the current understanding of biological mechanisms beyond the initial statistical association. We further summarize strategies for GWAS functional follow-up studies considering cutting-edge functional genomics tools and providing a catalog of available resources relevant to lung cancer. Overall, we aim to highlight the importance of integrating computational and experimental approaches to draw biological insights from the lung cancer GWAS results beyond association.

Metabolomic phenotyping of obesity for profiling cardiovascular and ocular diseases.

BACKGROUND: We aimed to evaluate the impacts of metabolomic body mass index (metBMI) phenotypes on the risks of cardiovascular and ocular diseases outcomes. METHODS: This study included cohorts in UK and Guangzhou, China. By leveraging the serum metabolome and BMI data from UK Biobank, this study developed and validated a metBMI prediction model using a ridge regression model among 89,830 participants based on 249 metabolites. Five obesity phenotypes were obtained by metBMI and actual BMI (actBMI): normal weight (NW, metBMI of 18.5-24.9 kg/m2), overweight (OW, metBMI of 25-29.9 kg/m2), obesity (OB, metBMI ≥ 30 kg/m2), overestimated (OE, metBMI-actBMI > 5 kg/m2), and underestimated (UE, metBMI-actBMI < - 5 kg/m2). Additional participants from the Guangzhou Diabetes Eye Study (GDES) were included for validating the hypothesis. Outcomes included all-cause and cardiovascular (CVD)-cause mortality, as well as incident CVD (coronary heart disease, heart failure, myocardial infarction [MI], and stroke) and age-related eye diseases (age-related macular degeneration [AMD], cataracts, glaucoma, and diabetic retinopathy [DR]). RESULTS: In the UKB, although OE group had lower actBMI than NW group, the OE group had a significantly higher risk of all-cause mortality than those in NW prediction group (HR, 1.68; 95% CI 1.16-2.43). Similarly, the OE group had a 1.7-3.6-fold higher risk than their NW counterparts for cardiovascular mortality, heart failure, myocardial infarction, and coronary heart disease (all P < 0.05). In addition, risk of age-related macular denegation (HR, 1.96; 95% CI 1.02-3.77) was significantly higher in OE group. In the contrast, UE and OB groups showed similar risks of mortality and of cardiovascular and age-related eye diseases (all P > 0.05), though the UE group had significantly higher actBMI than OB group. In the GDES cohort, we further confirmed the potential of metabolic BMI (metBMI) fingerprints for risk stratification of cardiovascular diseases using a different metabolomic approach. CONCLUSIONS: Gaps of metBMI and actBMI identified novel metabolic subtypes, which exhibit distinctive cardiovascular and ocular risk profiles. The groups carrying obesity-related metabolites were at higher risk of mortality and morbidity than those with normal health metabolites. Metabolomics allowed for leveraging the future of diagnosis and management of 'healthily obese' and 'unhealthily lean' individuals.

TET-dependent GDF7 hypomethylation impairs aqueous humor outflow and serves as a potential therapeutic target in glaucoma.

Glaucoma is the leading cause of irreversible vision loss, affecting more than 70 million individuals worldwide. Circulatory disturbances of aqueous humor (AH) have long been central pathological contributors to glaucomatous lesions. Thus, targeting the AH outflow is a promising approach to treat glaucoma. However, the epigenetic mechanisms initiating AH outflow disorders and the targeted treatments remain to be developed. Studying glaucoma patients, we identified GDF7 (growth differentiation factor 7) hypomethylation as a crucial event in the onset of AH outflow disorders. Regarding the underlying mechanism, the hypomethylated GDF7 promoter was responsible for the increased GDF7 production and secretion in primary open-angle glaucoma (POAG). Excessive GDF7 protein promoted trabecular meshwork (TM) fibrosis through bone morphogenetic protein receptor type 2 (BMPR2)/Smad signaling and upregulated pro-fibrotic genes, α-smooth muscle actin (α-SMA) and fibronectin (FN). GDF7 protein expression formed a positive feedback loop in glaucomatous TM (GTM). This positive feedback loop was dependent on the activated TET (ten-eleven translocation) enzyme, which kept the GDF7 promoter region hypomethylated. The phenotypic transition in TM fortified the AH outflow resistance, thus elevating the intraocular pressure (IOP) and attenuating the nerve fiber layer. This methylation-dependent mechanism is also confirmed by a machine-learning model in silico with a specificity of 84.38% and a sensitivity of 89.38%. In rhesus monkeys, we developed GDF7 neutralization therapy to inhibit TM fibrosis and consequent AH outflow resistance that contributes to glaucoma. The neutralization therapy achieved high-efficiency control of the IOP (from 21.3 ± 0.3 to 17.6 ± 0.2 mmHg), a three-fold improvement in the outflow facility (from 0.1 to 0.3 µL/min · mmHg), and protection of nerve fibers. This study provides new insights into the epigenetic mechanism of glaucoma and proposes an innovative GDF7 neutralization therapy as a promising intervention.

Loss-of-function mutations in FREM2 disrupt eye morphogenesis.

Cryptophthalmos is a rare congenital disorder characterized by ocular dysplasia with eyelid malformation. Complete cryptophthalmos is characterized by the presence of continuous skin from the forehead over the eyes and onto the cheek, along with complete fusion of the eyelids. In the present study, we characterized the clinical manifestations of three patients with isolated bilateral cryptophthalmos. These patients shared the same c.6499C > T missense mutation in the FRAS1-related extracellular matrix protein 2 (FREM2) gene, while each individual presented an additional nonsense mutation in the same gene (Patient #1, c.2206C > T; Patient #2, c.5309G > A; and Patient #3, c.4063C > T). Then, we used CRISPR/Cas9 to generate mice carrying Frem2R725X/R2156W compound heterozygous mutations, and showed that these mice recapitulated the human isolated cryptophthalmos phenotype. We detected FREM2 expression in the outer plexiform layer of the retina for the first time in the cryptophthalmic eyes, and the levels were comparable to the wild-type mice. Moreover, a set of different expressed genes that may contribute secondarily to the phenotypes were identified by performing RNA sequencing (RNA-seq) of the fetal Frem2 mutant mice. Our findings extend the spectrum of FREM2 mutations, and provide insights into opportunities for the prenatal diagnosis of isolated cryptophthalmos. Furthermore, our work highlights the importance of the FREM2 protein during the development of eyelids and the anterior segment of the eyeballs, establishes a suitable animal model for studying epithelial reopening during eyelid development and serves as a valuable reference for further mechanistic studies of the pathogenesis of isolated cryptophthalmos.

Prediction of myopia development among Chinese school-aged children using refraction data from electronic medical records: A retrospective, multicentre machine learning study.

BACKGROUND: Electronic medical records provide large-scale real-world clinical data for use in developing clinical decision systems. However, sophisticated methodology and analytical skills are required to handle the large-scale datasets necessary for the optimisation of prediction accuracy. Myopia is a common cause of vision loss. Current approaches to control myopia progression are effective but have significant side effects. Therefore, identifying those at greatest risk who should undergo targeted therapy is of great clinical importance. The objective of this study was to apply big data and machine learning technology to develop an algorithm that can predict the onset of high myopia, at specific future time points, among Chinese school-aged children. METHODS AND FINDINGS: Real-world clinical refraction data were derived from electronic medical record systems in 8 ophthalmic centres from January 1, 2005, to December 30, 2015. The variables of age, spherical equivalent (SE), and annual progression rate were used to develop an algorithm to predict SE and onset of high myopia (SE ≤ -6.0 dioptres) up to 10 years in the future. Random forest machine learning was used for algorithm training and validation. Electronic medical records from the Zhongshan Ophthalmic Centre (a major tertiary ophthalmic centre in China) were used as the training set. Ten-fold cross-validation and out-of-bag (OOB) methods were applied for internal validation. The remaining 7 independent datasets were used for external validation. Two population-based datasets, which had no participant overlap with the ophthalmic-centre-based datasets, were used for multi-resource validation testing. The main outcomes and measures were the area under the curve (AUC) values for predicting the onset of high myopia over 10 years and the presence of high myopia at 18 years of age. In total, 687,063 multiple visit records (≥3 records) of 129,242 individuals in the ophthalmic-centre-based electronic medical record databases and 17,113 follow-up records of 3,215 participants in population-based cohorts were included in the analysis. Our algorithm accurately predicted the presence of high myopia in internal validation (the AUC ranged from 0.903 to 0.986 for 3 years, 0.875 to 0.901 for 5 years, and 0.852 to 0.888 for 8 years), external validation (the AUC ranged from 0.874 to 0.976 for 3 years, 0.847 to 0.921 for 5 years, and 0.802 to 0.886 for 8 years), and multi-resource testing (the AUC ranged from 0.752 to 0.869 for 4 years). With respect to the prediction of high myopia development by 18 years of age, as a surrogate of high myopia in adulthood, the algorithm provided clinically acceptable accuracy over 3 years (the AUC ranged from 0.940 to 0.985), 5 years (the AUC ranged from 0.856 to 0.901), and even 8 years (the AUC ranged from 0.801 to 0.837). Meanwhile, our algorithm achieved clinically acceptable prediction of the actual refraction values at future time points, which is supported by the regressive performance and calibration curves. Although the algorithm achieved balanced and robust performance, concerns about the compromised quality of real-world clinical data and over-fitting issues should be cautiously considered. CONCLUSIONS: To our knowledge, this study, for the first time, used large-scale data collected from electronic health records to demonstrate the contribution of big data and machine learning approaches to improved prediction of myopia prognosis in Chinese school-aged children. This work provides evidence for transforming clinical practice, health policy-making, and precise individualised interventions regarding the practical control of school-aged myopia.

Preoperative profile of inflammatory factors in aqueous humor correlates with postoperative inflammatory response in patients with congenital cataract.

Purpose: To measure the aqueous humor concentrations of inflammatory factors in patients with congenital cataract and to investigate the relationship between the levels and postoperative inflammatory responses. Methods: Aqueous humor samples were prospectively collected from 65 eyes of children with congenital cataracts from January to June 2015. The levels of 41 inflammation-related cytokines, chemokines, and growth factors in aqueous humor were measured using multiplex bead immunoassay. Data on patient demographics and postoperative inflammatory response evaluation of posterior capsule opacification (EPCO) scores were collected for correlation analysis of short- and long-term postoperative inflammatory responses, respectively. Results: Fifteen inflammatory factors were differentially expressed between congenital cataract and age-related cataract. EGF and IL-3 were positively correlated, whereas IL-8 and MCP-1 were negatively correlated with age. TNFα, IL-17A, IL-3, and sCD40L were preferably expressed in specific morphological types of congenital cataract. One month and 3 months postoperatively, PDGF-AA exhibited a positive correlation with the EPCO scores, whereas IL-1RA exhibited a negative correlation. Macrophage-derived chemokine (MDC) showed a positive correlation with the EPCO scores 1 year postoperatively. Conclusions: This study provided a comprehensive preoperative profile of inflammatory factors and their correlations with postoperative inflammatory responses in patients with congenital cataract. These factors may serve as potential biomarkers to predict the postoperative inflammatory response. These findings will also facilitate the development of anti-inflammatory medications in the perioperative period.

Dynamic response to initial stage blindness in visual system development.

Sensitive periods and experience-dependent plasticity have become core issues in visual system development. Converging evidence indicates that visual experience is an indispensable factor in establishing mature visual system circuitry during sensitive periods and the visual system exhibits substantial plasticity while facing deprivation. The mechanisms that underlie the environmental regulation of visual system development and plasticity are of great interest but need further exploration. Here, we investigated a unique sample of human infants who experienced initial stage blindness (beginning at birth and lasting for 2-8 months) before the removal of bilateral cataracts. Retinal thickness (RT), axial length (AL), refractive status, visual grating acuity and genetic integrity were recorded during the preoperative period or at surgery and then during follow-up. The results showed that the development of the retina is malleable and associated with external environmental influences. Our work supported that the retina might play critical roles in the development of the experience-dependent visual system and its malleability might partly contribute to the sensitive period plasticity.

Automatic diagnosis of imbalanced ophthalmic images using a cost-sensitive deep convolutional neural network.

BACKGROUND: Ocular images play an essential role in ophthalmological diagnoses. Having an imbalanced dataset is an inevitable issue in automated ocular diseases diagnosis; the scarcity of positive samples always tends to result in the misdiagnosis of severe patients during the classification task. Exploring an effective computer-aided diagnostic method to deal with imbalanced ophthalmological dataset is crucial. METHODS: In this paper, we develop an effective cost-sensitive deep residual convolutional neural network (CS-ResCNN) classifier to diagnose ophthalmic diseases using retro-illumination images. First, the regions of interest (crystalline lens) are automatically identified via twice-applied Canny detection and Hough transformation. Then, the localized zones are fed into the CS-ResCNN to extract high-level features for subsequent use in automatic diagnosis. Second, the impacts of cost factors on the CS-ResCNN are further analyzed using a grid-search procedure to verify that our proposed system is robust and efficient. RESULTS: Qualitative analyses and quantitative experimental results demonstrate that our proposed method outperforms other conventional approaches and offers exceptional mean accuracy (92.24%), specificity (93.19%), sensitivity (89.66%) and AUC (97.11%) results. Moreover, the sensitivity of the CS-ResCNN is enhanced by over 13.6% compared to the native CNN method. CONCLUSION: Our study provides a practical strategy for addressing imbalanced ophthalmological datasets and has the potential to be applied to other medical images. The developed and deployed CS-ResCNN could serve as computer-aided diagnosis software for ophthalmologists in clinical application.

Proteomics analysis and proteogenomic characterization of different physiopathological human lenses.

BACKGROUND: The aim of the present study was to identify the proteomic differences among human lenses in different physiopathological states and to screen for susceptibility genes/proteins via proteogenomic characterization. METHODS: The total proteomes identified across the regenerative lens with secondary cataract (RLSC), congenital cataract (CC) and age-related cataract (ARC) groups were compared to those of normal lenses using isobaric tagging for relative and absolute protein quantification (iTRAQ). The up-regulated proteins between the groups were subjected to biological analysis. Whole exome sequencing (WES) was performed to detect genetic variations. RESULTS: The most complete human lens proteome to date, which consisted of 1251 proteins, including 55.2% previously unreported proteins, was identified across the experimental groups. Bioinformatics functional annotation revealed the common involvement of cellular metabolic processes, immune responses and protein folding disturbances among the groups. RLSC-over-expressed proteins were characteristically enriched in the intracellular immunological signal transduction pathways. The CC groups featured biological processes relating to gene expression and vascular endothelial growth factor (VEGF) signaling transduction, whereas the molecular functions corresponding to external stress were specific to the ARC groups. Combined with WES, the proteogenomic characterization narrowed the list to 16 candidate causal molecules. CONCLUSIONS: These findings revealed common final pathways with diverse upstream regulation of cataractogenesis in different physiopathological states. This proteogenomic characterization shows translational potential for detecting susceptibility genes/proteins in precision medicine.

Height, weight and body mass index of children with congenital cataracts before surgical treatment.

BACKGROUND: To investigate the distribution of the height, weight and body mass index (BMI) of children with congenital cataracts (CC) before surgical treatment. METHODS: This prospective study included children with CC ≤14 years of age presenting at the Zhongshan Ophthalmic Center from Jan. 2013 to Aug. 2016. The height, weight, and BMI measurements of all participating children were obtained and compared with the World Health Organization Child Growth Reference (WHO Reference), matched by age and gender. The presence of a family history of CC or complicated systemic diseases as well as parental education levels and family income were also recorded. RESULTS: In total, 595 children with CC were included. The mean age was 52.75 ± 33.99 months, and 34.29% (204/595) of them were unilateral cases. Among all of the children, 6.72% (40/595) of cases were complicated by systemic diseases. More than 1/5 (21.01%, 125/595) of the children had a family history of CC and exhibited bilateral involvement. Less than 1/4 (23.2) of the mothers were highly educated, and more than half of the families had a family income below the city average. Height, weight, and BMI measurements of most children with CC were within the normal ranges (±95% CI of the WHO Reference). Compared to the WHO Reference, both girls and boys aged 2-5 years revealed shorter heights, and the girls aged 5-14 years exhibited a shorter height, lower body weight and lower BMI. The heights of the children with CC and systemic diseases were also shorter than the WHO Reference. The children with CC who had a family history of disease had shorter heights and lower BMIs than children with CC but no family history, and the measurements of both groups were lower than the WHO Reference values. CONCLUSIONS: The height, weight and BMI of most of the children with CC in this study were within the normal ranges of the WHO Reference. However, the children with CC and concomitant systemic diseases and those with a family history of CC had shorter heights and lower BMIs. This information aids in our understanding of the physical development of children with CC.

Construction and implications of structural equation modeling network for pediatric cataract: a data mining research of rare diseases.

BACKGROUND: The majority of rare diseases are complex diseases caused by a combination of multiple morbigenous factors. However, uncovering the complex etiology and pathogenesis of rare diseases is difficult due to limited clinical resources and conventional statistical methods. This study aims to investigate the interrelationship and the effectiveness of potential factors of pediatric cataract, for the exploration of data mining strategy in the scenarios of rare diseases. METHODS: We established a pilot rare disease specialized care center to systematically record all information and the entire treatment process of pediatric cataract patients. These clinical records contain the medical history, multiple structural indices, and comprehensive functional metrics. A two-layer structural equation model network was applied, and eight potential factors were filtered and included in the final modeling. RESULTS: Four risk factors (area, density, location, and abnormal pregnancy experience) and four beneficial factors (axis length, uncorrected visual acuity, intraocular pressure, and age at diagnosis) were identified. Quantifiable results suggested that abnormal pregnancy history may be the principle risk factor among medical history for pediatric cataracts. Moreover, axis length, density, uncorrected visual acuity and age at diagnosis served as the dominant factors and should be emphasized in regular clinical practice. CONCLUSIONS: This study proposes a generalized evidence-based pattern for rare and complex disease data mining, provides new insights and clinical implications on pediatric cataract, and promotes rare-disease research and prevention to benefit patients.

Interocular anatomical and visual functional differences in pediatric patients with unilateral cataracts.

BACKGROUND: Congenital cataracts are often complicated by anterior segment dysgenesis. This study aims to compare bilateral anterior segment parameters, macular thickness, and best-corrected visual acuity (BCVA) in pediatric cataract patients at 3 months after unilateral cataract extraction with intraocular lens implantation. METHODS: Fifty-three pediatric patients with uncomplicated unilateral total cataracts were included. At 3 months post-surgery, bilateral corneal thickness at the thinnest location (CTTL), anterior chamber depth (ACD), and anterior chamber volume (ACV) were measured using Pentacam. Central macular thickness (CMT) was evaluated using spectral-domain optical coherence tomography. BCVA was measured by experienced optometrists concurrently. Descriptive statistics and bivariate corrections were performed to analyze the interocular differences in bilateral anatomic parameters and their relationships with BCVA. RESULTS: For all 53 included patients (mean age 5.2 ± 2.3 years), the median BCVA was 10/40 in the operated eyes and 40/40 in the contralateral eyes, which indicates a significant interocular difference. BCVA values in the contralateral eyes were significantly correlated with patient age at surgery, but this result differed for BCVA in the operated eyes. The Pentacam analysis revealed no significant interocular differences in bilateral CTTL and ACV, but significant differences were found for ACD. CONCLUSIONS: At 3 months after surgery, unilateral pediatric cataract patients exhibited no significant interocular differences in identified anatomical parameters (except for ACD), and these parameters were not significantly correlated with BCVA in bilateral eyes. Therefore, amblyopia, but not anatomical factors, might be the main cause of interocular visual functional differences in our study population. TRIAL REGISTRATION: ClinicalTrial.gov, NCT02765230 , 05/05/2016, retrospectively registered.

Comparisons of the in-the-bag stabilities of single-piece and three-piece intraocular lenses for age-related cataract patients: a randomized controlled trial.

BACKGROUND: To compare the in-the-bag stability and visual function of single-piece intraocular lenses (IOLs) and three-piece IOLs. METHODS: A total of 65 patients with age-related cataracts (80 eyes) were enrolled and randomly assigned to receive in-the-bag implantation of either a single-piece IOL (40 eyes) or a three-piece IOL (40 eyes). Follow-up visits were conducted at 1 week, 1 month and 3 months postoperatively. Visual acuity, refraction and total aberration were examined. IOL position stability (including axial movement, decentration and tilt) was measured using a Scheimpflug imaging system. RESULTS: At the 3-month follow-up visit, single-piece IOLs did not exhibit significant axial movement (0.07 ± 0.30 mm, p = 0.13) compared with their axial position at 1 week postoperatively, whereas three-piece IOLs displayed forward axial movement of -0.22 ± 0.23 mm (p < 0.0001). The mean manifest spherical equivalence (SE) of eyes with single-piece IOL was 0.15 ± 0.18D, whereas in eyes with three-piece IOLs, the mean manifest SE was -0.34 ± 0.15D (p < 0.001). There was no statistically significant difference in IOL decentration, tilt, uncorrected visual acuity, best-corrected visual acuity or total spherical aberration between the two groups. CONCLUSIONS: Three months after implantation, single-piece IOLs exhibit better axial stability and more stable refractive outcome than three-piece IOLs, but both IOLs perform equally well in terms of decentration, tilt, visual acuity and total aberration. TRIAL REGISTRATION: ClinicalTrial.gov, NCT02609997 , 11/18/2015, retrospectively registered.

Ambient ultraviolet radiation and ocular melanoma incidence in the United States, 2000-2019.

BACKGROUND/OBJECTIVES: Ocular melanoma is a rare, but deadly cancer. This large cancer registry study examines the associations between solar ultraviolet radiation (UVR) and incidence of different anatomical sites of ocular melanoma by sex, age, laterality, and race and ethnicity. METHODS: Incidence data were derived from 21 cancer registries in the US for the years 2000-2019. Satellite-based UVR estimates were linked to county of residence at diagnosis. Incidence rate ratios (IRRs) and 95% confidence intervals (CIs) were calculated for UVR quartiles using Poisson models. RESULTS: UVR was not associated with total ocular melanoma (N = 18,089) comparing Q4 versus Q1 (IRR = 0.98; 95%CI:0.94,1.03; p-trend = 0.07) or conjunctival melanoma (IRR = 0.99; 95%CI:0.82,1.19; p-trend = 0.81). However, in analyses of continuous UVR (per 10 mW/m2), risks were reduced for total ocular melanoma (IRR = 0.97; 95% CI: 0.96, 0.99). Incidence was increased for ciliary body/iris melanoma in the highest UVR quartile (IRR = 1.63; 95%CI:1.43,1.87; p-trend < 0.0001) and remained increased in non-Hispanic White individuals only. Incidence was reduced for choroidal melanoma in the highest UVR quartile (IRR = 0.86; 95%CI:0.82,0.91; p-trend < 0.0001). CONCLUSIONS: UVR may be associated with increased risk of ciliary body/iris melanoma. Reduced risk of choroidal melanoma may be due to higher diffuse UVR exposure to posterior ocular sites in locations at higher latitudes. Our results support and expand previous findings of associations of UVR using various surrogates on ocular melanoma risk and serve as a starting point for understanding the differences in the relationship between UVR and specific anatomical sites.

Outpatient reception via collaboration between nurses and a large language model: a randomized controlled trial.

Reception is an essential process for patients seeking medical care and a critical component influencing the healthcare experience. However, current communication systems rely mainly on human efforts, which are both labor and knowledge intensive. A promising alternative is to leverage the capabilities of large language models (LLMs) to assist the communication in medical center reception sites. Here we curated a unique dataset comprising 35,418 cases of real-world conversation audio corpus between outpatients and receptionist nurses from 10 reception sites across two medical centers, to develop a site-specific prompt engineering chatbot (SSPEC). The SSPEC efficiently resolved patient queries, with a higher proportion of queries addressed in fewer rounds of queries and responses (Q&Rs; 68.0% ≤2 rounds) compared with nurse-led sessions (50.5% ≤2 rounds) (P = 0.009) across administrative, triaging and primary care concerns. We then established a nurse-SSPEC collaboration model, overseeing the uncertainties encountered during the real-world deployment. In a single-center randomized controlled trial involving 2,164 participants, the primary endpoint indicated that the nurse-SSPEC collaboration model received higher satisfaction feedback from patients (3.91 ± 0.90 versus 3.39 ± 1.15 in the nurse group, P < 0.001). Key secondary outcomes indicated reduced rate of repeated Q&R (3.2% versus 14.4% in the nurse group, P < 0.001) and reduced negative emotions during visits (2.4% versus 7.8% in the nurse group, P < 0.001) and enhanced response quality in terms of integrity (4.37 ± 0.95 versus 3.42 ± 1.22 in the nurse group, P < 0.001), empathy (4.14 ± 0.98 versus 3.27 ± 1.22 in the nurse group, P < 0.001) and readability (3.86 ± 0.95 versus 3.71 ± 1.07 in the nurse group, P = 0.006). Overall, our study supports the feasibility of integrating LLMs into the daily hospital workflow and introduces a paradigm for improving communication that benefits both patients and nurses. Chinese Clinical Trial Registry identifier: ChiCTR2300077245 .

Deep learning-enhanced R-loop prediction provides mechanistic implications for repeat expansion diseases.

R-loops play diverse functional roles, but controversial genomic localization of R-loops have emerged from experimental approaches, posing significant challenges for R-loop research. The development and application of an accurate computational tool for studying human R-loops remains an unmet need. Here, we introduce DeepER, a deep learning-enhanced R-loop prediction tool. DeepER showcases outstanding performance compared to existing tools, facilitating accurate genome-wide annotation of R-loops and a deeper understanding of the position- and context-dependent effects of nucleotide composition on R-loop formation. DeepER also unveils a strong association between certain tandem repeats and R-loop formation, opening a new avenue for understanding the mechanisms underlying some repeat expansion diseases. To facilitate broader utilization, we have developed a user-friendly web server as an integral component of R-loopBase. We anticipate that DeepER will find extensive applications in the field of R-loop research.