Genetic and Survey Data Improves Performance of Machine Learning Model for Long COVID (preprint)

Over 200 million SARS-CoV-2 patients have or will develop persistent symptoms (long COVID). Given this pressing research priority, the National COVID Cohort Collaborative (N3C) developed a machine learning model using only electronic health record data to identify potential patients with long COVID. We hypothesized that additional data from health surveys, mobile devices, and genotypes could improve prediction ability. In a cohort of SARS-CoV-2 infected individuals (n=17,755) in the All of Us program, we applied and expanded upon the N3C long COVID prediction model, testing machine learning infrastructures, assessing model performance, and identifying factors that contributed most to the prediction models. For the survey/mobile device information and genetic data, extreme gradient boosting and a convolutional neural network delivered the best performance for predicting long COVID, respectively. Combined survey, genetic, and mobile data increased specificity and the Area Under Curve the Receiver Operating Characteristic score versus the original N3C model.

Risk factors for severe COVID-19 outcomes: a study of immune-mediated inflammatory diseases, immunomodulatory medications, and comorbidities in a large US healthcare system (preprint)

Background COVID-19 outcomes, in the context of immune-mediated inflammatory diseases (IMIDs), are incompletely understood. Reported outcomes vary considerably depending on the patient population studied. It is essential to analyse data for a large population, while considering the effects of the pandemic time period, comorbidities, long term use of immunomodulatory medications (IMMs), and vaccination status. Methods In this retrospective case-control study, patients of all ages with IMIDs were identified from a large U.S. healthcare system. COVID-19 infections were identified based on SARS-CoV-2 NAAT test results. Controls without IMIDs were selected from the same database. Severe outcomes were hospitalisation, mechanical ventilation (MV), and death. We analysed data from 1 March 2020 to 30 August 2022, looking separately at both pre-Omicron and Omicron predominant periods. Factors including IMID diagnoses, comorbidities, long term use of IMMs, and vaccination and booster status were analysed using multivariable logistic regression (LR) and extreme gradient boosting (XGB). Findings Out of 2 167 656 patients tested for SARS-CoV-2, there were 290 855 with confirmed COVID-19 infection: 15 397 patients with IMIDs and 275 458 controls (patients without IMIDs). Age and most chronic comorbidities were risk factors for worse outcomes, whereas vaccination and boosters were protective. Patients with IMIDs had higher rates of hospitalisation and mortality compared with controls. However, in multivariable analyses, few IMIDs were rarely risk factors for worse outcomes. Further, asthma, psoriasis and spondyloarthritis were associated with reduced risk. Most IMMs had no significant association, but less frequently used IMM drugs were limited by sample size. XGB outperformed LR, with the AUROCs for models across different time periods and outcomes ranging from 0.77 to 0.92. Interpretation For patients with IMIDs, as for controls, age and comorbidities were risk factors for worse COVID-19 outcomes, whereas vaccinations were protective. Most IMIDs and immunomodulatory therapies were not associated with more severe outcomes. Interestingly, asthma, psoriasis and spondyloarthritis were associated with less severe COVID-19 outcomes than those expected for the population overall. These results can help inform clinical, policy and research decisions. Funding Pfizer, Novartis, Janssen, NIH

Exposure to negative foreign COVID-19 news predicts lower support for immigration policy in China.

We present a framework for studying the spillover effect of negative foreign COVID-19 news on attitudes towards immigration. Our framework proposes that exposure to negative COVID-19 news from foreign countries can activate negative associations with foreigners, reduce positive attitudes towards them, and increase perceived threat, ultimately leading to decreased support for immigration. We conducted three studies to test this framework. Study 1 found that exposure to negative COVID-19 news about a foreign country increased negative valence associations with that country. Study 2 showed that exposure to more negative COVID-19 news about foreign countries was associated with lower acceptance of immigration policies in real life. Study 3 replicated the spillover effect of negative news exposure using a scenario manipulation. The effects of negative news exposure on immigration policy acceptance in both Studies 2 and 3 were mediated by changes in foreigner attitudes and intergroup threat. Our results demonstrate the important spillover effect of negative foreign COVID-19 news exposure on immigration attitudes and highlight the association perspective as a foundation for understanding attitude changes during the COVID-19 pandemic.

Identifying Contextual and Spatial Risk Factors for Post-Acute Sequelae of SARS-CoV-2 Infection: An EHR-based Cohort Study from the RECOVER Program (preprint)

Post-acute sequelae of SARS-CoV-2 infection (PASC) affects a wide range of organ systems among a large proportion of patients with SARS-CoV-2 infection. Although studies have identified a broad set of patient-level risk factors for PASC, little is known about the contextual and spatial risk factors for PASC. Using electronic health data of patients with COVID-19 from two large clinical research networks in New York City and Florida, we identified contextual and spatial risk factors from nearly 200 environmental characteristics for 23 PASC symptoms and conditions of eight organ systems. We conducted a two-phase environment-wide association study. In Phase 1, we ran a mixed effects logistic regression with 5-digit ZIP Code tabulation area (ZCTA5) random intercepts for each PASC outcome and each contextual and spatial factor, adjusting for a comprehensive set of patient-level confounders. In Phase 2, we ran a mixed effects logistic regression for each PASC outcome including all significant (false positive discovery adjusted p-value < 0.05) contextual and spatial characteristics identified from Phase I and adjusting for confounders. We identified air toxicants (e.g., methyl methacrylate), criteria air pollutants (e.g., sulfur dioxide), particulate matter (PM2.5) compositions (e.g., ammonium), neighborhood deprivation, and built environment (e.g., food access) that were associated with increased risk of PASC conditions related to nervous, respiratory, blood, circulatory, endocrine, and other organ systems. Specific contextual and spatial risk factors for each PASC condition and symptom were different across New York City area and Florida. Future research is warranted to extend the analyses to other regions and examine more granular contextual and spatial characteristics to inform public health efforts to help patients recover from SARS-CoV-2 infection.

The Potential to Fight Obesity with Adipogenesis Modulating Compounds.

Obesity is an increasingly severe public health problem, which brings huge social and economic burdens. Increased body adiposity in obesity is not only tightly associated with type 2 diabetes, but also significantly increases the risks of other chronic diseases including cardiovascular diseases, fatty liver diseases and cancers. Adipogenesis describes the process of the differentiation and maturation of adipocytes, which accumulate in distributed adipose tissue at various sites in the body. The major functions of white adipocytes are to store energy as fat during periods when energy intake exceeds expenditure and to mobilize this stored fuel when energy expenditure exceeds intake. Brown/beige adipocytes contribute to non-shivering thermogenesis upon cold exposure and adrenergic stimulation, and thereby promote energy consumption. The imbalance of energy intake and expenditure causes obesity. Recent interest in epigenetics and signaling pathways has utilized small molecule tools aimed at modifying obesity-specific gene expression. In this review, we discuss compounds with adipogenesis-related signaling pathways and epigenetic modulating properties that have been identified as potential therapeutic agents which cast some light on the future treatment of obesity.

Imputing Missing Observations with Time Sliced Synthetic Minority Oversampling Technique (preprint)

We present a simple yet novel time series imputation technique with the goal of constructing an irregular time series that is uniform across every sample in a data set. Specifically, we fix a grid defined by the midpoints of non-overlapping bins (dubbed "slices") of observation times and ensure that each sample has values for all of the features at that given time. This allows one to both impute fully missing observations to allow uniform time series classification across the entire data and, in special cases, to impute individually missing features. To do so, we slightly generalize the well-known class imbalance algorithm SMOTE \cite{smote} to allow component wise nearest neighbor interpolation that preserves correlations when there are no missing features. We visualize the method in the simplified setting of 2-dimensional uncoupled harmonic oscillators. Next, we use tSMOTE to train an Encoder/Decoder long-short term memory (LSTM) model with Logistic Regression for predicting and classifying distinct trajectories of different 2D oscillators. After illustrating the the utility of tSMOTE in this context, we use the same architecture to train a clinical model for COVID-19 disease severity on an imputed data set. Our experiments show an improvement over standard mean and median imputation techniques by allowing a wider class of patient trajectories to be recognized by the model, as well as improvement over aggregated classification models.

Retinal toxicity caused by hydroxychloroquine in patients with systemic lupus erythematosus: A case report.

RATIONALE: Hydroxychloroquine has excellent anti-inflammatory and immunomodulatory effects as one of the antimalarial drugs. In particular, hydroxychloroquine was once widely used as a treatment for the new coronavirus pneumonia epidemic in 2020. Retinopathy caused by hydroxychloroquine is normally irreversible, but little attention has been paid to it. PATIENT CONCERNS: A 38-year-old young Chinese woman was taking oral hydroxychloroquine 400 mg daily to control lupus disease activity for six years after the diagnosis of systemic lupus erythematosus (SLE). She did not have any history of eye disease and was admitted to the hospital with a sudden blurring of both eyes. DIAGNOSES: The diagnosis of retinal macular degeneration caused by hydroxychloroquine was made after excluding other interfering diseases based on the patient's long-term use of hydroxychloroquine and the results of the eye examination. INTERVENTIONS: The patient was discontinued from hydroxychloroquine. To control the recurrence of SLE, she was given intravenous methylprednisolone, oral tacrolimus and mycophenolate. Meanwhile, she was asked to take extra care of her eyes and to come to the hospital every three months to have her vision checked. OUTCOMES: The patient's blurred vision improved one week later. Three months later, her vision examination showed no further decline (0.4 in the right eye and 0.6 in the left eye). Meanwhile, the SLE disease activity index (SLEDAI) decreased from six points to five points currently. LESSONS: Retinopathy caused by hydroxychloroquine is irreversible and there is no particularly effective treatment. Discontinuation of hydroxychloroquine, better daily eye protection, and regular vision checks are the keys to preventing retinopathy. Although hydroxychloroquine causing retinal toxicity was mentioned several years ago, the rate and severity of retinal toxicity require further research. How to get more patients to take care of their eyes requires continuous and increased education by doctors.

Genomic Elucidation of a COVID-19 Resurgence and Local Transmission of SARS-CoV-2 in Guangzhou, China.

While China experienced a peak and decline in coronavirus disease 2019 (COVID-19) cases at the start of 2020, regional outbreaks continuously emerged in subsequent months. Resurgences of COVID-19 have also been observed in many other countries. In Guangzhou, China, a small outbreak, involving less than 100 residents, emerged in March and April 2020, and comprehensive and near-real-time genomic surveillance of SARS-CoV-2 was conducted. When the numbers of confirmed cases among overseas travelers increased, public health measures were enhanced by shifting from self-quarantine to central quarantine and SARS-CoV-2 testing for all overseas travelers. In an analysis of 109 imported cases, we found diverse viral variants distributed in the global viral phylogeny, which were frequently shared within households but not among passengers on the same flight. In contrast to the viral diversity of imported cases, local transmission was predominately attributed to two specific variants imported from Africa, including local cases that reported no direct or indirect contact with imported cases. The introduction events of the virus were identified or deduced before the enhanced measures were taken. These results show the interventions were effective in containing the spread of SARS-CoV-2, and they rule out the possibility of cryptic transmission of viral variants from the first wave in January and February 2020. Our study provides evidence and emphasizes the importance of controls for overseas travelers in the context of the pandemic and exemplifies how viral genomic data can facilitate COVID-19 surveillance and inform public health mitigation strategies.

Inpatient Use of Metformin and Acarbose Is Associated with Reduced Mortality of COVID-19 Patients with Type 2 Diabetes Mellitus (preprint)

Type 2 diabetes mellitus (T2DM) is a strong risk factor for complications of coronavirus disease 2019 (COVID-19). The effect of T2DM medications on COVID-19 outcomes remains unclear. In a retrospective analysis of a cohort of 131 patients with T2DM hospitalized for COVID-19 in Wuhan, we have previously found that metformin use prior to hospitalization is associated with reduced mortality. Here we continue to investigate the effects of inpatient use of T2DM medications, including metformin, acarbose, insulin, and sulfonylureas, on the mortality of COVID-19 patients with T2DM during hospitalization. We found that patients using metformin and acarbose, alone or both together, after admission were significantly more likely to survive than those who did not use either metformin or acarbose. Thus, our analyses suggest that inpatient use of metformin and acarbose together or alone during hospitalization should be studied in randomized trials.

Clinical features and potential mechanism of coronavirus disease 2019-associated liver injury.

Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2, has posed a serious threat to global public health security. With the increase in the number of confirmed cases globally, the World Health Organization has declared the outbreak of COVID-19 an international public health emergency. Despite atypical pneumonia as the primary symptom, liver dysfunction has also been observed in many clinical cases and is associated with the mortality risk in patients with COVID-19, like severe acute respiratory syndrome and Middle East respiratory syndrome. Here we will provide a schematic overview of the clinical characteristics and the possible mechanisms of liver injury caused by severe acute respiratory syndrome coronavirus 2 infection, which may provide help for optimizing the management of liver injury and reducing mortality in COVID-19 patients.

ConceptWAS: a high-throughput method for early identification of COVID-19 presenting symptoms (preprint)

ObjectiveIdentifying symptoms highly specific to COVID-19 would improve the clinical and public health response to infectious outbreaks. Here, we describe a high-throughput approach - Concept-Wide Association Study (ConceptWAS) that systematically scans a diseases clinical manifestations from clinical notes. We used this method to identify symptoms specific to COVID-19 early in the course of the pandemic. MethodsUsing the Vanderbilt University Medical Center (VUMC) EHR, we parsed clinical notes through a natural language processing pipeline to extract clinical concepts. We examined the difference in concepts derived from the notes of COVID-19-positive and COVID-19-negative patients on the PCR testing date. We performed ConceptWAS using the cumulative data every two weeks for early identifying specific COVID-19 symptoms. ResultsWe processed 87,753 notes 19,692 patients (1,483 COVID-19-positive) subjected to COVID-19 PCR testing between March 8, 2020, and May 27, 2020. We found 68 clinical concepts significantly associated with COVID-19. We identified symptoms associated with increasing risk of COVID-19, including "absent sense of smell" (odds ratio [OR] = 4.97, 95% confidence interval [CI] = 3.21-7.50), "fever" (OR = 1.43, 95% CI = 1.28-1.59), "with cough fever" (OR = 2.29, 95% CI = 1.75-2.96), and "ageusia" (OR = 5.18, 95% CI = 3.02-8.58). Using ConceptWAS, we were able to detect loss sense of smell or taste three weeks prior to their inclusion as symptoms of the disease by the Centers for Disease Control and Prevention (CDC). ConclusionConceptWAS is a high-throughput approach for exploring specific symptoms of a disease like COVID-19, with a promise for enabling EHR-powered early disease manifestations identification.

Genomic Elucidation of a COVID-19 Resurgence and Local Transmission of SARS-CoV-2 in Guangzhou, China (preprint)

The resurgence of coronavirus disease 2019 (COVID-19) has been seen in many counties where outbreaks appear to be leveling off. While China experienced a dramatic decline of COVID-19 at the outset of 2020, regional outbreaks continuously emerged in recent months. In Guangzhou, a small outbreak emerged in March and April involving less than 100 residents, and a comprehensive and near-real-time genomic surveillance of SARS-CoV-2 was conducted. When confirmed cases among overseas travelers increased, public health authorities enhanced measures as shifting self-quarantine to central quarantine and SARS-CoV-2 testing for all overseas travelers. From 109 imported cases we found diverse viral variants distributing in the global viral phylogeny, which were usually shared within households but not among passengers on the same flight. Nonetheless, local transmission was predominately attributed to two specific variants imported from Africa, including the local cases who reported no direct/indirect contact with imported cases. The introducing events of the virus were identified or deduced before enhanced measures were taken. These results show that the interventions are effective in containing the spread of SARS-CoV-2, and also rule out the possibility of cryptic transmission of viral variants from the first wave in January and February. Moreover, we found that intra-host viral diversity was usually different between close contacts, implying a transmission bottleneck of SARS-CoV-2. Our study provides evidence and emphasizes the importance of controls for oversea travelers in the context of the pandemic, and exemplifies how viral genomic data facilitates COVID-19 surveillance and prevention.Funding: This study was supported by National Natural Science Foundation of China (31870079, 91953122, 31871326), National Science and Technology Major Project of the Ministry of Science and Technology of China (2017ZX10103011, 2018ZX10305410, 2018ZX10201001), Guangdong Provincial Novel Coronavirus Scientific and Technological Project (2020111107001), Guangdong Basic and Applied Basic Research Foundation (2020A1515010776 and 2020B1515020057) and the Beijing Nova Program (Z181100006218114 and Z181100006218110) to M.N. and P.L..Conflict of Interest: The authors declare no competing interests.Ethical Approval: This study was approved by the ethics committee of the Center for Disease Control and Prevention (CDC) of Guangzhou (GZCDC-ECHR-2020P0002). Written informed consent was obtained from patients about the surveillance and data related to disease control and further analysis. All information regarding individual persons has been anonymized in this study.

Tracking and Analyzing Public Emotion Evolutions During COVID-19: A Case Study from the Event-Driven Perspective on Microblogs

Objective: Coronavirus disease 2019 (COVID-19) has caused substantial panic worldwide since its outbreak in December 2019. This study uses social networks to track the evolution of public emotion during COVID-19 in China and analyzes the root causes of these public emotions from an event-driven perspective. Methods: A dataset was constructed using microblogs (n = 125,672) labeled with COVID-19-related super topics (n = 680) from 40,891 users from 1 December 2019 to 17 February 2020. Based on the skeleton and key change points of COVID-19 extracted from microblogging contents, we tracked the public"s emotional evolution modes (accumulated emotions, emotion covariances, and emotion transitions) by time phase and further extracted the details of dominant social events. Results: Public emotions showed different evolution modes during different phases of COVID-19. Events about the development of COVID-19 remained hot, but generally declined, and public attention shifted to other aspects of the epidemic (e.g., encouragement, support, and treatment). Conclusions: These findings suggest that the public"s feedback on COVID-19 predated official accounts on the microblog platform. There were clear differences in the trending events that large users (users with many fans and readings) and common users paid attention to during each phase of COVID-19.

Genomic surveillance of a resurgence of COVID-19 in Guangzhou, China (preprint)

In the middle of March, the World Health Organization declared the outbreak of COVID-19 caused by SARS-CoV-2 infection a global pandemic. While China experienced a dramatic decline in daily growth rate of COVID-19, multiple importations of new cases from other countries and their related local infections caused a rapid rise. Between March 12 and April 15, we collected nasopharyngeal samples from 109 imported cases from 25 countries and 69 local cases in Guangzhou, China. In order to characterize the transmission patterns and genetic evolution of this virus among different populations, we sequenced the genome of SARS-CoV-2. The imported viral strains were assigned to lineages distributed in Europe (33.0%), America (17.4%), Africa (25.7%), or Southeast/West Asia (23.9%). Importantly, 10 imported cases from Africa formed two novel sub-lineages not identified in global tree previously. A detailed analysis showed that the imported viral strains from Philippines and Pakistan were closely related and within the same sub-lineage, whereas Ethiopia had varied lineages in the African phylogenetic tree. In spite of the diversity of imported SARS-CoV-2, 60 of 69 local infections could be traced back to two specific small lineages imported from Africa. A combined genetic and epidemiological analysis revealed a high-resolution transmission network of the imported SARS-CoV-2 in local communities, which might help inform the public health response and genomic surveillance in other cities and regions. Finally, we observed in-frame deletions on seven loci of SARS-CoV-2 genome, some of which were intra-host mutations, and they exhibited no enrichment on the S protein. Our findings provide new insight into the viral phylodynamics of SARS-CoV-2 and beta coronavirus.

Spatial Heterogeneity of Housing Space Consumption in Urban China: Locals vs. Inter- and Intra-Provincial Migrants

The relationships between migration and housing congestion have attracted attention in engaging the public against the COVID-19 pandemic and some other public health crises. In recent years in China, promoting the citizenization ("shimin hua") of migrants and improving the quality of urbanization have become the focus of attention in the new-type urbanization today. The housing space consumption of migrants is one of the important indices to look into regarding their real living status in the receiving cities: how do the housing consumption behavior and residential quality vary between the local, inter-and intra-provincial migratory patterns? This article uses the micro household data of the 1% population sampling survey conducted in 2015 by the National Bureau of Statistics of China to look into the spatial variance of the aggregate housing space consumption behaviors of the local and non-local population at the prefectural level and above in urban China. This study finds that: (a) the longer migratory pattern indicates a thriftier housing space consumption that implies a higher probability of residential overcrowding among the inter-provincial migrants;at the same time, the locals enjoy the greater living comfort than their migrant peers;(b) the spatial variance in terms of housing space consumption can be attributed to a series of destination city contexts, such as the geological background, city administrative rank, areal location, local-nonlocal demography, municipal economic growth, and the local residential development levels. The results show that the more "targeted" housing policies are needed to solve the housing difficulties with migrant workers for a goal of human-centered urbanization development. Although we lack the more detailed data-sets to examine the correlation between public health risks (like the COVID-19 pandemic) and housing congestion problems (especially with the population on the move), this research is still illuminating in terms of how to cut down the public health risk in a highly mobile and rapidly urbanizing context like China.