Integration of human organoids single-cell transcriptomic profiles and human genetics repurposes critical cell type-specific drug targets for severe COVID-19 (preprint)

Human organoids recapitulate the cell type diversity and function of their primary organs holding tremendous potentials for basic and translational research. Advances in single-cell RNA sequencing (scRNA-seq) technology and genome-wide association study (GWAS) have accelerated the biological and therapeutic interpretation of trait-relevant cell types or states. Here, we constructed a computational framework to integrate atlas-level organoid scRNA-seq data, GWAS summary statistics, expression quantitative trait loci, and gene-drug interaction data for distinguishing critical cell populations and drug targets relevant to COVID-19 severity. We found that 39 cell types across eight kinds of organoids were significantly associated with COVID-19 outcomes. Notably, subset of lung mesenchymal stem cells (MSCs) increased proximity with fibroblasts predisposed to repair COVID-19-damaged lung tissue. Brain endothelial cell subset exhibited significant associations with severe COVID-19, and this cell subset showed a notable increase in cell-to-cell interactions with other brain cell types, including microglia. We repurposed 33 druggable genes, including IFNAR2, TYK2, and VIPR2, and their interacting drugs for COVID-19 in a cell-type-specific manner. Overall, our results showcase that host genetic determinants have cellular specific contribution to COVID-19 severity, and identification of cell type-specific drug targets may facilitate to develop effective therapeutics for treating severe COVID-19 and its complications.

Multi-site, Multi-domain Airway Tree Modeling (ATM'22): A Public Benchmark for Pulmonary Airway Segmentation (preprint)

Open international challenges are becoming the de facto standard for assessing computer vision and image analysis algorithms. In recent years, new methods have extended the reach of pulmonary airway segmentation that is closer to the limit of image resolution. Since EXACT'09 pulmonary airway segmentation, limited effort has been directed to quantitative comparison of newly emerged algorithms driven by the maturity of deep learning based approaches and clinical drive for resolving finer details of distal airways for early intervention of pulmonary diseases. Thus far, public annotated datasets are extremely limited, hindering the development of data-driven methods and detailed performance evaluation of new algorithms. To provide a benchmark for the medical imaging community, we organized the Multi-site, Multi-domain Airway Tree Modeling (ATM'22), which was held as an official challenge event during the MICCAI 2022 conference. ATM'22 provides large-scale CT scans with detailed pulmonary airway annotation, including 500 CT scans (300 for training, 50 for validation, and 150 for testing). The dataset was collected from different sites and it further included a portion of noisy COVID-19 CTs with ground-glass opacity and consolidation. Twenty-three teams participated in the entire phase of the challenge and the algorithms for the top ten teams are reviewed in this paper. Quantitative and qualitative results revealed that deep learning models embedded with the topological continuity enhancement achieved superior performance in general. ATM'22 challenge holds as an open-call design, the training data and the gold standard evaluation are available upon successful registration via its homepage.

The highly conserved RNA-binding specificity of nucleocapsid protein facilitates the identification of drugs with broad anti-coronavirus activity (preprint)

The binding of SARS-CoV-2 nucleocapsid (N) protein to both the 5'- and 3'-ends of genomic RNA has different implications arising from its binding to the central region during virion assembly. However, the mechanism underlying selective binding remains unknown. Herein, we performed the high-throughput RNA-SELEX (HTR-SELEX) to determine the RNA-binding specificity of the N proteins of various SARS-CoV-2 variants as well as other {beta}-coronaviruses and showed that N proteins could bind two unrelated sequences, both of which were highly conserved across all variants and species. Interestingly, both these sequence motifs are virtually absent from the human transcriptome; however, they exhibit a highly enriched, mutually complementary distribution in the coronavirus genome, highlighting their varied functions in genome packaging. Our results provide mechanistic insights into viral genome packaging, thereby increasing the feasibility of developing drugs with broad-spectrum anti-coronavirus activity by targeting RNA binding by N proteins.

Allosteric hotspots in the main protease of SARS-CoV-2 (preprint)

Inhibiting the main protease of SARS-CoV-2 is of great interest in tackling the COVID-19 pandemic caused by the virus. Most efforts have been centred on inhibiting the binding site of the enzyme. However, considering allosteric sites, distant from the active or orthosteric site, broadens the search space for drug candidates and confers the advantages of allosteric drug targeting. Here, we report the allosteric communication pathways in the main protease dimer by using two novel fully atomistic graph theoretical methods: bond-to-bond propensity analysis, which has been previously successful in identifying allosteric sites without a priori knowledge in benchmark data sets, and, Markov transient analysis, which has previously aided in finding novel drug targets in catalytic protein families. We further score the highest-ranking sites against random sites in similar distances through statistical bootstrapping and identify four statistically significant putative allosteric sites as good candidates for alternative drug targeting.

Predictive value of the neutrophil to lymphocyte ratio for disease deterioration and serious adverse outcomes in patients with COVID-19: a prospective cohort study (preprint)

Background: Early identification of patients who are at high risk of poor clinical outcomes is of great importance in saving the lives of patients with novel coronavirus disease 2019 (COVID-19) in the context of limited medical resources. Objective: To evaluate the value of the neutrophil to lymphocyte ratio (NLR), calculated at hospital admission and in isolation, for the prediction of the subsequent presence of disease progression and serious clinical outcomes (e.g., shock, death). Methods: : We designed a prospective cohort study of 352 hospitalized patients with COVID-19 between January 9 and February 26, 2020, in Yichang City, Hubei Province. Patients with an NLR equal to or higher than the cutoff value derived from the receiver operating characteristic curve method were classified as the exposed group. The primary outcome was disease deterioration, defined as an increase of the clinical disease severity classification during hospitalization (e.g., moderate to severe/critical; severe to critical). The secondary outcomes were shock and death during the treatment. Results: : During the follow-up period, 51 (14.5%) patients’ conditions deteriorated, 15 patients (4.3%) had complicated septic shock, and 15 patients (4.3%) died. The NLR was higher in patients with deterioration than in those without deterioration (median: 5.33 vs. 2.14, P <0.001), and higher in patients with serious clinical outcomes than in those without serious clinical outcomes (shock vs. no shock: 6.19 vs. 2.25, P <0.001; death vs. survival: 7.19 vs. 2.25, P <0.001). The NLR measured at hospital admission had high value in predicting subsequent disease deterioration, shock and death (all the areas under the curve > 0.80). The sensitivity of an NLR ≥ 2.6937 for predicting subsequent disease deterioration, shock and death was 82.0% (95% confidence interval, 69.0 to 91.0), 93.3% (68.0 to 100), and 92.9% (66.0 to 100), and the corresponding negative predictive values were 95.7% (93.0 to 99.2), 99.5% (98.6 to 100) and 99.5% (98.6 to 100), respectively. Conclusions: : The NLR measured at admission and in isolation can be used to effectively predict the subsequent presence of disease deterioration and serious clinical outcomes in patients with COVID-19.

COVID-19 Quarantine Reveals Grade-specific Behavioral Modification of Myopia: One-Million Chinese Schoolchildren Study (preprint)

BackgroundHigh prevalence of myopia of adolescent has been a global public health concern. Their risk factors and effective prevention methods for myopia across schoolchildren developmental stages are critically needed but remain uncertain due to the difficulty in implementing intervention measurements under normal life situation. We aimed to study the impact of the COVID-19 quarantine on myopia development among over one-million schoolchildren. MethodsWe designed the ongoing longitudinal project of Myopic Epidemiology and Intervention Study (MEIS) to biannually examine myopia among millions of schoolchildren for ten years in Wenzhou City, Zhejiang Province, China. In the present study, we performed three examinations of myopia in 1,305 elementary and high schools for schoolchildren in June 2019, December 2019 and June 2020. We used the normal period (June-December 2019) and COVID-19 quarantine period (January-June 2020) for comparisons. Myopia was defined as an uncorrected visual acuity of 20/25 or less and a spherical equivalent refraction (SER) of -0.5 diopters (D) or less. High myopia was defined as an SER of -6.0 D or less. FindingsIn June 2019, 1,001,749 students aged 7-18 were eligible for examinations. In the 6-month and 12-month follow-up studies, there were 813,755 eligible students (81.2%) and 768,492 eligible students (76.7%), respectively. Among all students, we found that half-year myopia progression increased approximate 1.5 times from -0.263 D (95% CI, -0.262 to -0.264) during normal period to -0.39 D (95% CI, -0.389 to -0.391) during COVID-19 quarantine (P < 0.001). Multivariate Cox regression analysis identified grade rather than age was significantly associated with myopia (Hazard ratio [HR]: 1.10, 95% CI, 1.08 to 1.13; P < 0.001) and high myopia (HR: 1.40, 95% CI, 1.35 to 1.46; P < 0.001) after adjustment for other factors. The prevalence, progression, and incidence of myopia and high myopia could be categorized into two grade groups: I (grades 1-6) and II (grades 7-12). Specifically, COVID-19 quarantine for 6 months sufficiently increased risk of developing myopia (OR: 1.36, 95% CI, 1.33 to 1.40) or high myopia (OR: 1.30, 95% CI, 1.22 to 1.39) in Grade Group I, but decreased risk of developing myopia (OR: 0.45, 95% CI, 0.43 to 0.48) or high myopia (OR: 0.57, 95% CI, 0.54 to 0.59) in Grade Group II. InterpretationThe finding that behavioral modifications for six months during COVID-19 quarantine sufficiently and grade-specifically modify myopia development offers the largest human behavioral intervention data at the one million scale to identify the grade-specific causal factors and effective prevention methods for guiding the formulation of myopia prevention and control policies. FundingKey Program of National Natural Science Foundation of China; the National Natural Science Foundation of China; Scientific Research Foundation for Talents of Wenzhou Medical University; Key Research and Development Program of Zhejiang Province. Research in contextO_ST_ABSEvidence before this studyC_ST_ABSMyopia is the most-common refractive error worldwide. Myopia with younger onset may result in developing high myopia, which is associated with sight-threatening ocular diseases such as maculopathy, retinal detachment, opticneuropathy, glaucoma, retinal atrophy, choroidal neovascularization. In light of the increasing prevalence of myopia and high myopia has been a global public health concern, the impact of COVID-19 lockdown on myopia development has gained substantial attention. We searched PubMed, Google Scholar, and MEDLINE databases for original articles reported between database inception and November 10, 2020, using the following search terms: (coronavirus OR COVID* OR SARS-COV-2 OR lockdown OR quarantine) AND (myopia OR short-sightedness OR refractive error). To date, there was no original study reported to uncover the influence of COVID-19 quarantine on myopia progression. Added value of this studyThis study provides the largest longitudinal intervention data on myopia progression in Chinese schoolchildren covering all grades of schoolchildren at one-million scale. COVID-19 quarantine model uncovers that behavioral modifications for six months may lead to significant increase of overall prevalence of myopia associated with their increased screen times and decreased outdoor activity times. Importantly, their effects on developing myopia or high myopia of students are grade-dependent, which were risk factors for elementary schools period but protective factors for high schools period partly due to reduced school education burden. Implications of all the available evidenceThis one-million schoolchildren myopia survey offers evidence that six months behavioral modifications sufficiently and grade-specifically change the progression of myopia and high myopia. In view of the increased use of electronic devices is an unavoidable trend, effective myopia prevention strategy according to grade among students is urgently needed. Since COVID-19 outbreak is still ongoing and spreading, international collaborate efforts are warranted to uncover the influence of COVID-19 on myopia progression to further substantiate these findings.

Allosteric hotspots in the main protease of SARS-CoV-2 (preprint)

Inhibiting the main protease of SARS-CoV-2 is of great interest in tackling the COVID-19 pandemic caused by the virus. Most efforts have been centred on inhibiting the binding site of the enzyme. However, considering allosteric sites, distant from the active or orthosteric site, broadens the search space for drug candidates and confers the advantages of allosteric drug targeting. Here, we report the allosteric communication pathways in the main protease dimer by using two novel fully atomistic graph theoretical methods: Bond-to-bond propensity analysis, which has been previously successful in identifying allosteric sites without a priori knowledge in benchmark data sets, and, Markov transient analysis, which has previously aided in finding novel drug targets in catalytic protein families. We further score the highest ranking sites against random sites in similar distances through statistical bootstrapping and identify four statistically significant putative allosteric sites as good candidates for alternative drug targeting.

Integrative Genomics Analysis Reveals a Novel 21q22.11 Locus Contributing to Susceptibility of COVID-19 (preprint)

The systematic identification of host genetic risk factors is essential for the understanding and treatment of COVID-19. By performing a meta-analysis of two independent genome-wide association (GWAS) summary datasets (N = 680,128), a novel locus at 21q22.11 was identified to be associated with COVID-19 infection (rs9976829 in IFNAR2 and upstream of IL10RB, OR = 1.16, 95% CI = 1.09 - 1.23, P = 2.57x10-6). The rs9976829 represents a strong splicing quantitative trait locus (sQTL) for both IFNAR2 and IL10RB genes, especially in lung tissue (P 1.8x10-24). Gene-based association analysis also found IFNAR2 was significantly associated with COVID-19 infection (P = 2.58x10-7). Integrative genomics analysis of combining GWAS with eQTL data showed the expression variations of IFNAR2 and IL10RB have prominent effects on COVID-19 in various types of tissues, especially in lung tissue. The majority of IFNAR2-expressing cells were dendritic cells (40%) and plasmacytoid dendritic cells (38.5%), and IL10RB-expressing cells were mainly nonclassical monocytes (29.6%). IFNAR2 and IL10RB are targeted by several interferons-related drugs. Together, our results uncover 21q22.11 as a novel susceptibility locus for COVID-19, in which individuals with G alleles of rs9976829 have a higher probability of COVID-19 susceptibility than those with non-G alleles.

An artificial intelligence system for predicting the deterioration of COVID-19 patients in the emergency department (preprint)

During the coronavirus disease 2019 (COVID-19) pandemic, rapid and accurate triage of patients at the emergency department is critical to inform decision-making. We propose a data-driven approach for automatic prediction of deterioration risk using a deep neural network that learns from chest X-ray images and a gradient boosting model that learns from routine clinical variables. Our AI prognosis system, trained using data from 3,661 patients, achieves an area under the receiver operating characteristic curve (AUC) of 0.786 (95% CI: 0.745-0.830) when predicting deterioration within 96 hours. The deep neural network extracts informative areas of chest X-ray images to assist clinicians in interpreting the predictions and performs comparably to two radiologists in a reader study. In order to verify performance in a real clinical setting, we silently deployed a preliminary version of the deep neural network at New York University Langone Health during the first wave of the pandemic, which produced accurate predictions in real-time. In summary, our findings demonstrate the potential of the proposed system for assisting front-line physicians in the triage of COVID-19 patients.

Moderating effect of people-oriented public health services on depression among socially isolated people during COVID-19: A cross-sectional study in China (preprint)

Background:Public health measures including social isolationare essential forCOVID-19 control,but also increase the risk of depression. This study examined the influencing and moderating factors on socially isolated people’s depressive symptoms. Methods: Data were collected from people in mandatory home or centralizedsocial isolation in Shenzhen, China from February 28 to March 6 in 2020. We assessed their perceived COVID-19risk, perceived tone of media coverage, perceived quality of people-oriented public health services, and depressive symptoms.Three stepwise multiple regressions were performed to examine the moderating effects controlling age, gender, education, monthly income, socially isolated venue,time spent on COVID-related news, and online social support.Results:We examined data from 340 people. 57.6% men, averaged age at 35.5 years old (SD = 8.37), 55.6% held bachelor’s degree or above.Overall, people in social isolation reported a moderate level ofdepressive symptoms (M =1.24, SD = 0.4). The perceived susceptibility of being infected was relatively low (M = 1.36, SD = 0.54), and the perceived tone of media coverage was mainly positive (M = 1.97, SD = 1.05). In terms of perceived quality of public health services, 3.2% (n = 11) participants reported low-level, 49.1% (n = 167) medium-level, and 47.6 (n =162) high-level quality ofpeople-oriented services. Perceived riskwas significantly associated with depression (β= .12, p< 0.01), and perceived tone of media coverage was negatively associated with depression (β= -.05, p< 0.01).The quality of people-centered public health service moderated the association between perceived riskand depressive symptoms(β= -.15, p< 0.05), and the relationship between perceived tone of media coverage and depressive symptoms(β= .01, p< 0.01).Conclusions:This studyfound thatpeople-oriented public health servicesreduced the effect of risk perception and media tone on depressive symptoms among COVID-19 socially isolated people, suggesting a critical role for frontline public health workers in protecting public mental health. 

The network investigation on knowledge, attitude and practice about Novel coronavirus pneumonia of the residents in Anhui Province / 中华预防医学杂志

Objective@#To analyze the current situation of the knowledge, attitudes and practice about Novelcoronavirus pneumonia (NCP) of the residents in Anhui Province.@*Methods@#Anonymous network sampling survey was carried out with an electronic questionnaire that designed by the questionnaire star, and a total of 4016 subjects from Anhui province were investigated. The content of the survey includes that the basic information of subjects,the residents’ knowledge, attitudes and practice about NCP, as well as their satisfaction with the prevention and control measures adopted by the government and health authorities and the suggestions on future prevention. The questionnaire doesn’t involve any privacy information, and all questions were mandatory to ensure the response rate.@*Results@#The M (P25, P75) age the 4016 subjects was 21 (19, 24), and the ranging from 7 to 80 years old. The number of males was1431(35.6%). Social networking tools such as WeChat and QQ were the main sources of epidemic information for residents (97.8%, 3 929 respondents). Residents have a high awareness rate of the main symptoms, transmission routes, using of masks, hand washing and treatment information of NCP, while a low awareness rate of the atypical symptoms. 92.6% of the subjects (n=3 720) think that the outbreak was scary. In terms of psychological behavior scores, the results showed that female (9.38±4.81), the urban (9.37±5.02) and the medical workers (10.79±5.19) had a poorer mental health than the male (8.45±5.00) , the rural (8.71±4.75) and the non-medical workers (the students: 8.85±4.83; public institude workers: 9.02±5.08; others: 8.97±5.39) (P < 0.05). 71.9% of the residents (n=2 887)were satisfied with the local epidemic control measures. The residents took various of the measures to prevent and control the epidemic. The ratio of residents that could achieve "no gathering and less going out" , "wear masks when going out" and "do not go to crowded and closed places" was up to 97.4% (n=3 913), 93.6% (n=3758) and 91.5% (n=3 673) respectively.@*Conclusion@#The residents in Anhui province have a good KAP about NCP, yet it is necessary to strengthen the community publicity, the mental health maintenance of residents and students’ health education.