Exome-wide association study identifies KDELR3 mutations in extreme myopia.

Extreme myopia (EM), defined as a spherical equivalent (SE) ≤ -10.00 diopters (D), is one of the leading causes of sight impairment. Known EM-associated variants only explain limited risk and are inadequate for clinical decision-making. To discover risk genes, we performed a whole-exome sequencing (WES) on 449 EM individuals and 9606 controls. We find a significant excess of rare protein-truncating variants (PTVs) in EM cases, enriched in the retrograde vesicle-mediated transport pathway. Employing single-cell RNA-sequencing (scRNA-seq) and a single-cell polygenic burden score (scPBS), we pinpointed PI16 + /SFRP4+ fibroblasts as the most relevant cell type. We observed that KDELR3 is highly expressed in scleral fibroblast and involved in scleral extracellular matrix (ECM) organization. The zebrafish model revealed that kdelr3 downregulation leads to elongated ocular axial length and increased lens diameter. Together, our study provides insight into the genetics of EM in humans and highlights KDELR3's role in EM pathogenesis.

Whole-Exome Sequencing Among School-Aged Children With High Myopia.

Importance: High myopia (HM) is one of the leading causes of visual impairment worldwide. Genetic factors are known to play an important role in the development of HM. Objective: To identify risk variants in a large HM cohort and to examine the implications of genetic testing of schoolchildren with HM. Design, Setting, and Participants: This cohort study retrospectively reviewed whole-exome sequencing (WES) results in 6215 schoolchildren with HM who underwent genetic testing between September 2019 and July 2020 in Wenzhou City, China. HM is defined as a spherical equivalent refraction (SER) of -6.00 diopters (D) or less. The study setting was a genetic testing laboratory and a multicenter school census. Data were analyzed from July 2021 to June 2022. Main Outcomes and Measures: The frequency and distribution of positive germline variants, the percentage of individuals with HM in both eyes, and subsequent variant yield for common high myopia (CHM; -8.00 D ≤ SER ≤ -6.00 D), ultra myopia (UM; -10.00 D ≤ SER < -8.00 D), and extreme myopia (EM; SER < -10.00 D). Results: Of the 6215 schoolchildren with HM, 3278 (52.74%) were male. Their mean (SD) age was 14.87 (2.02) years, including 355 students in primary school, 1970 in junior high school, and 3890 in senior high school. The mean (SD) SER was -7.51 (-1.36) D for the right eye and -7.46 (-1.34) D for the left eye. Among schoolchildren with HM, genetic testing yielded 271 potential pathogenic variants in 75 HM candidate genes in 964 diagnoses (15.52%). A total of 36 known variants were found in 490 HM participants (7.88%) and 235 protein-truncating variants (PTVs) in 506 participants (8.14%). Involved variant yield was significantly positively associated with SER (Cochran-Armitage test for trend Z = 2.5492; P = .01), which ranged from 7.66% in the CHM group, 8.70% in the UM group, to 11.90% in the EM group. We also found that primary school students with EM had the highest variant yield of PTVs (8 of 35 students [22.86%]), which was 1.77 and 4.78 times that of the UM and CHM, respectively. Conclusions and Relevance: In this cohort study of WES for HM, several potential pathogenic variants were identified in a substantial number of schoolchildren with HM. The high variation frequency in younger students with EM can provide clues for genetic screening and clinical examinations of HM to promote long-term follow-up assessment.

Sequencing of 19,219 exomes identifies a low-frequency variant in FKBP5 promoter predisposing to high myopia in a Han Chinese population.

High myopia (HM) is one of the leading causes of visual impairment and blindness worldwide. Here, we report a whole-exome sequencing (WES) study in 9,613 HM cases and 9,606 controls of Han Chinese ancestry to pinpoint HM-associated risk variants. Single-variant association analysis identified three newly identified -genetic loci associated with HM, including an East Asian ancestry-specific low-frequency variant (rs533280354) in FKBP5. Multi-ancestry meta-analysis with WES data of 2,696 HM cases and 7,186 controls of European ancestry from the UK Biobank discerned a newly identified European ancestry-specific rare variant in FOLH1. Functional experiments revealed a mechanism whereby a single G-to-A transition at rs533280354 disrupted the binding of transcription activator KLF15 to the promoter of FKBP5, resulting in decreased transcription of FKBP5. Furthermore, burden tests showed a significant excess of rare protein-truncating variants among HM cases involved in retinal blood vessel morphogenesis and neurotransmitter transport.

A tiered probabilistic approach to assess antibiotic ecological and resistance development risks in the fresh surface waters of China.

Exposure to antibiotics can result in not only ecotoxicity on aquatic organisms but also the development of antibiotic resistance. In the study, the ecotoxicity data and minimum inhibitory concentrations of the antibiotics were screened to derive predicted no-effect concentrations of ecological (PNECeco) and resistance development risks (PNECres) for 36 antibiotics in fresh surface waters of China. The derived PNECeco and PNECres values were ranged from 0.00175 to 2351 µg/L and 0.037-50 µg/L, respectively. Antibiotic ecological and resistance development risks were geographically widespread, especially in the Yongding River, Daqing River, and Ziya River basins of China. Based on the risk quotients, 11 and 14 of 36 target antibiotics were at high ecological risks and high resistance development risks in at least one basin, respectively. The higher tiered assessments provided more detailed risk descriptions by probability values and ß-lactams (penicillin and amoxicillin) were present at the highest levels for ecological and resistance development risks. Although there was uncertainty based on the limited data and existing methods, this study can indicate the overall situation of the existing risk levels and provide essential insights and data supporting antibiotic management.

Genome-wide association meta-analysis of 88,250 individuals highlights pleiotropic mechanisms of five ocular diseases in UK Biobank.

BACKGROUND: Ocular diseases may exhibit common clinical symptoms and epidemiological comorbidity. However, the extent of pleiotropic mechanisms across ocular diseases remains unclear. We aim to examine shared genetic etiology in age-related macular degeneration (AMD), diabetic retinopathy (DR), glaucoma, retinal detachment (RD), and myopia. METHODS: We analyzed genome-wide association analyses for the five ocular diseases in 43,877 cases and 44,373 controls of European ancestry from UK Biobank, estimated their genetic relationships (LDSC, GNOVA, and Genomic SEM), and identified pleiotropic loci (ASSET and METASOFT). FINDINGS: The genetic correlation of common SNPs revealed a meaningful genetic structure within these diseases, identifying genetic correlations between AMD, DR, and glaucoma. Cross-trait meta-analysis identified 23 pleiotropic loci associated with at least two ocular diseases and 14 loci unique to individual disorders (non-pleiotropic). We found that the genes associated with these shared genetic loci are involved in neuron differentiation (P = 8.80 × 10-6) and eye development systems (P = 3.86 × 10-5), and single cell RNA sequencing data reveals their heightened gene expression from multipotent progenitors to other differentiated retinal cells during retina developmental process. INTERPRETATION: These results highlighted the potential common genetic architectures among these ocular diseases and can deepen the understanding of the molecular mechanisms underlying the related diseases. FUNDING: The National Natural Science Foundation of China (61871294), Zhejiang Provincial Natural Science Foundation of China (LR19C060001), and the Scientific Research Foundation for Talents of Wenzhou Medical University (QTJ18023).

Tiered ecological risk assessment of nonylphenol and tetrabromobisphenol A in the surface waters of China based on the augmented species sensitivity distribution models.

The ecological risks of nonylphenol (NP) and tetrabromobisphenol A (TBBPA) have received continued attention owing to their large consumption, frequently detection, adverse effects on the reproductive fitness, and lack of risk assessment technical systems. The geometric mean of the median concentrations of NP in the 22 surface waters was 0.278 µg/L, and TBBPA in the seven surface waters was 0.014 µg/L in China. The species sensitivity distribution (SSD) models were augmented by extrapolated reproductive toxicity data of native species to reduce uncertainty. The SSD models and the hazardous concentrations for 5% of species exhibited good robustness and reliability using the bootstrap method and minimum sample size determination. The acute and reproductive predicted no-effect concentrations (PNECs) were derived as 9.88 and 0.187 µg/L for NP, and 56.6 and 0.0878 µg/L for TBBPA, respectively. The risk quotients indicated that 11 of 22 locations for NP, and 3 of 7 locations for TBBPA were at high ecological risk levels based on the reproductive PNECs. Furthermore, the higher tier ecological risk assessment (ERA) based on potential affected fraction and joint probability curves indicated that the ecological risks in the four of above locations needed further concern. The ERA based on both the acute and reproductive toxicity is essential for assessing the ecological risks of NP and TBBPA, otherwise using acute PNECs only may result in an underestimation of ecological risk. The developed tiered ERA method and its framework can provide accurate, detailed, quantitative, locally applicable, and economically technical support for ERA of typical endocrine-disrupting chemicals in China.

Estrogenic activity and ecological risk of steroids, bisphenol A and phthalates after secondary and tertiary sewage treatment processes.

Effluents of sewage treatment plants (STPs) are an important source of estrogenic substances to the receiving water bodies affecting their ecological safety. In this study, steroids, bisphenol A (BPA) and phthalates were assessed in the secondary (SE) and tertiary effluent (TE) of three typical urban STPs in Beijing (China). In addition, the overall estrogenic activity in these effluents was assessed by an in-vitro bioassay (ERE-CALUX). Results showed that the concentrations and activities of estrogenic compounds in TE were lower than those in SE. The residual concentration of 17ß-estradiol (E2) was the highest among the detected steroids, accounting for 51.6 ± 5.1% in SE and 57.5 ± 24.8% in TE. The residual level (25.2-41.6 ng/L) of BPA in effluents was significantly higher than that of steroids (0.2-28.8 ng/L). The residual concentration of diethyl phthalate was the highest among the detected phthalates accounting for 47.1 ± 5.1% in SE and 37.6 ± 11.5% in TE. Steroids and BPA had a higher removal rate (83.5% and 96.7%) in secondary and tertiary treatment than phthalates (68.8% and 83.1%). The hydrophobic characteristics of these estrogenic compounds determined the removal mechanism. The removal of steroids, BPA, dimethyl phthalate and diethyl phthalate (LogKow= 1.61-4.15) mainly occurred through biodegradation in the water phase, while the removal of dibutyl phthalate, butylbenzyl phthalate and di(2-ethylhexyl) phthalate (LogKow= 4.27-7.50) mainly occurred in the solid phase after adsorption on and sedimentation of the suspended particulate matter. According to ERE-CALUX, the estrogenic activity in the final STP effluents was 3.2-45.6 ng E2-equivalents/L, which is higher than reported levels in the effluents of European STPs. Calculation of estrogenic equivalents by using substance specific chemical analysis indicated that the dominant contributor was E2 (56.4-88.4%), followed by 17α-ethinylestradiol (EE2) (4.1-34.8%), both also exerting a moderate risk to the aquatic ecosystem. While the upgrade of treatment processes in STPs has efficiently reduced the emission of estrogenic substances, their ecological risk was not yet phased out.

A 110 Year Sediment Record of Polycyclic Aromatic Hydrocarbons Related to Economic Development and Energy Consumption in Dongping Lake, North China.

A sedimentary record of the 16 polycyclic aromatic hydrocarbon (PAH) pollutants from Dongping Lake, north China, is presented in this study. The influence of regional energy structure changes for 2-6-ring PAHs was investigated, in order to assess their sources and the impact of socioeconomic developments on the observed changes in concentration over time. The concentration of the ΣPAH16 ranged from 77.6 to 628.0 ng/g. Prior to the 1970s, the relatively low concentration of ΣPAH16 and the average presence of 44.4% 2,3-ring PAHs indicated that pyrogenic combustion from grass, wood, and coal was the main source of PAHs. The rapid increase in the concentration of 2,3-ring PAHs between the 1970s and 2006 was attributed to the growth of the urban population and the coal consumption, following the implementation of the Reform and Open Policy in 1978. The source apportionment, which was assessed using a positive matrix factorization model, revealed that coal combustion was the most important regional source of PAHs pollution (>51.0%). The PAHs were mainly transported to the site from the surrounding regions by atmospheric deposition rather than direct discharge.

EyeDiseases: an integrated resource for dedicating to genetic variants, gene expression and epigenetic factors of human eye diseases.

Eye diseases are remarkably common and encompass a large and diverse range of morbidities that affect different components of the visual system and visual function. With advances in omics technology of eye disorders, genome-scale datasets have been rapidly accumulated in genetics and epigenetics field. However, the efficient collection and comprehensive analysis of different kinds of omics data are lacking. Herein, we developed EyeDiseases (https://eyediseases.bio-data.cn/), the first database for multi-omics data integration and interpretation of human eyes diseases. It contains 1344 disease-associated genes with genetic variation, 1774 transcription files of bulk cell expression and single-cell RNA-seq, 105 epigenomics data across 185 kinds of human eye diseases. Using EyeDiseases, we investigated SARS-CoV-2 potential tropism in eye infection and found that the SARS-CoV-2 entry factors, ACE2 and TMPRSS2 are highly correlated with cornea and keratoconus, suggest that ocular surface cells are susceptible to infection by SARS-CoV-2. Additionally, integrating analysis of Age-related macular degeneration (AMD) GWAS loci and co-expression data revealed 9 associated genes involved in HIF-1 signaling pathway and voltage-gate potassium channel complex. The EyeDiseases provides a valuable resource for accelerating the discovery and validation of candidate loci and genes contributed to the molecular diagnosis and therapeutic vulnerabilities with various eyes diseases.

Correction: Tracking and Monitoring Mood Stability of Patients With Major Depressive Disorder by Machine Learning Models Using Passive Digital Data: Prospective Naturalistic Multicenter Study.

[This corrects the article DOI: 10.2196/24365.].

Tracking and Monitoring Mood Stability of Patients With Major Depressive Disorder by Machine Learning Models Using Passive Digital Data: Prospective Naturalistic Multicenter Study.

BACKGROUND: Major depressive disorder (MDD) is a common mental illness characterized by persistent sadness and a loss of interest in activities. Using smartphones and wearable devices to monitor the mental condition of patients with MDD has been examined in several studies. However, few studies have used passively collected data to monitor mood changes over time. OBJECTIVE: The aim of this study is to examine the feasibility of monitoring mood status and stability of patients with MDD using machine learning models trained by passively collected data, including phone use data, sleep data, and step count data. METHODS: We constructed 950 data samples representing time spans during three consecutive Patient Health Questionnaire-9 assessments. Each data sample was labeled as Steady or Mood Swing, with subgroups Steady-remission, Steady-depressed, Mood Swing-drastic, and Mood Swing-moderate based on patients' Patient Health Questionnaire-9 scores from three visits. A total of 252 features were extracted, and 4 feature selection models were applied; 6 different combinations of types of data were experimented with using 6 different machine learning models. RESULTS: A total of 334 participants with MDD were enrolled in this study. The highest average accuracy of classification between Steady and Mood Swing was 76.67% (SD 8.47%) and that of recall was 90.44% (SD 6.93%), with features from all types of data being used. Among the 6 combinations of types of data we experimented with, the overall best combination was using call logs, sleep data, step count data, and heart rate data. The accuracies of predicting between Steady-remission and Mood Swing-drastic, Steady-remission and Mood Swing-moderate, and Steady-depressed and Mood Swing-drastic were over 80%, and the accuracy of predicting between Steady-depressed and Mood Swing-moderate and the overall Steady to Mood Swing classification accuracy were over 75%. Comparing all 6 aforementioned combinations, we found that the overall prediction accuracies between Steady-remission and Mood Swing (drastic and moderate) are better than those between Steady-depressed and Mood Swing (drastic and moderate). CONCLUSIONS: Our proposed method could be used to monitor mood changes in patients with MDD with promising accuracy by using passively collected data, which can be used as a reference by doctors for adjusting treatment plans or for warning patients and their guardians of a relapse. TRIAL REGISTRATION: Chinese Clinical Trial Registry ChiCTR1900021461; http://www.chictr.org.cn/showprojen.aspx?proj=36173.

How has Beijing's urban weight and composition changed with socioeconomic development?

A city's in-use stock comprises the built environment and manufactured products, which shape a city's weight and play vital roles in human activities. However, researchers have not accurately quantified urban weight and its composition, or how stock types change during urbanization. We quantified Beijing's in-use stock from 1978 to 2015 by bottom-up material-flow analysis for building, infrastructure, and manufactured product stocks, with 11 sub-types (e.g., roads), and 54 accounting items (e.g., expressways). We discuss the driving factors for changes in these stocks and their composition. Beijing's in-use stock increased from 224 Mt in 1978 to 1925 Mt in 2015, an increase of nearly 9 times (19 times the global stock per unit area). This resulted primarily from increases in stocks that accounted for >20% of the total: urban residential buildings (30%), non-residential buildings (26%), and roads (20%), which grew to 15, 5, and 11 times the 1978 levels, respectively. However, the growth rate of these stocks slowed by the end of the study period. Manufactured products represented <4% of the stock, but grew fastest (increasing to 41 times the 1978 value), especially for durable consumer goods and vehicles. This category cannot be neglected because of the increasing purchasing power of residents. The trends for the stock weights remained strongly coupled with population factors, whereas the stocks showed relative decoupling from economic factors (e.g., GDP, investment). These results will help policymakers diagnose problems with Beijing's urban development, thereby improving estimates of future resource demand and providing insights into strategies to slow the increase in urban weight.

Urban weight and its driving forces: A case study of Beijing.

Massive resource and energy consumption greatly increase a city's domestic material consumption (its "weight"), resulting in proportionally large pressure on the environment. Understanding the causes and driving forces behind urban weight can therefore promote more sustainable urban development. To improve our understanding, we analyzed the composition of Beijing's urban weight from 2000 to 2015. We then defined the key metabolic processes (including both metabolic components and paths between them) that contributed to weight changes during this period using the logarithmic mean Divisia index model to identify the underlying driving forces. Beijing's weight grew by 82.6% during the study period, with non-metallic minerals being the material most consumed (about 45% of the total weight). Beijing depended heavily on imports, and extraction within the city's administrative boundaries has gradually declined. The Construction and Industry sectors were the dominant metabolic components; their material exchanges with both the internal and external environments of the city represented the largest flow pathways. The largest proportion of urban weight that was dissipated was air pollution, which therefore represents the biggest environmental challenge facing Beijing. Economic activity was the largest driver of urban weight growth, followed by population growth, with decreasing material consumption intensity (per unit GDP) somewhat reducing the city's weight. The results help us to understand the characteristics of urban weight change over a long period, and this knowledge can be used to prioritize structural adjustment, determine targets for regulation, refine processes, and guide future policy development to focus on the drivers of weight change.

Urban Metabolism: A Review of Current Knowledge and Directions for Future Study.

During the 50 years since the concept of urban metabolism was proposed, this field of research has evolved slowly. On the basis of an analogy with an organism's metabolism, the concept of urban metabolism has become an effective method to evaluate the flows of energy and materials within an urban system, thereby providing insights into the system's sustainability and the severity of urban problems such as excessive social, community, and household metabolism at scales ranging from global to local. Researchers have improved this approach, evolving from models of linear to cyclic processes and then to network models. Researchers account for flows of energy and materials, ecological footprints, inputs and outputs, and the characteristics of the system's ecological network. However, the practical methods of analysis need to be improved. Future analysis should focus on establishing a multilevel, unified, and standardized system of categories to support the creation of consistent inventory databases; it should also seek to improve the methods used in the analysis to provide standards and guidance that will help governments to achieve sustainable development. Finally, researchers must improve the ability to provide spatially explicit analyses that facilitate the task of applying research results to guide practical decision-support.