Genetic predisposition between coronavirus disease 2019 and rheumatic diseases: A 2-sample Mendelian randomization study.

OBJECTIVE: The causalities between the coronavirus disease 2019 (COVID-19) and the risk of rheumatic diseases remain unclear. The purpose of this study was to investigate the causal effect of COVID-19 on rheumatic disease occurrence. METHODS: Single nucleotide polymorphisms (SNPs), acquired from published genome-wide association studies, were used to perform 2-sample Mendelian randomization (MR) on cases diagnosed with COVID-19 (n = 13 464), rheumatic diseases (n = 444 199), juvenile idiopathic arthritis (JIA, n = 15 872), gout (n = 69  374), systemic lupus erythematosus (SLE, n = 3094), ankylosing spondylitis (n = 75 130), primary biliary cholangitis (PBC, n = 11 375) and primary Sjögren's syndrome (n = 95 046). Three MR methods were used in the analysis based on different heterogeneity and pleiotropy using the Bonferroni correction. RESULTS: The results revealed a causality between COVID-19 and rheumatic diseases with an odds ratio (OR) of 1.010 (95% confidence interval [CI], 1.006-1.013; P = .014). In addition, we observed that COVID-19 was causally associated with an increased risk of JIA (OR 1.517; 95%CI, 1.144-2.011; P = .004), PBC (OR 1.370; 95%CI, 1.149-1.635; P = .005), but a decreased risk of SLE (OR 0.732; 95%CI, 0.590-0.908; P = .004). Using MR, 8 SNPs were identified to associate with COVID-19 and recognized as significant variables. None of them were previously reported in any other diseases. CONCLUSIONS: This is the first study to use MR to explore the impact of COVID-19 on rheumatic diseases. From a genetic perspective, we found that COVID-19 could increase the risk of rheumatic diseases, such as PBC and JIA, but decrease that of SLE, thereby suggesting a potential surge in the disease burden of PBC and JIA following the COVID-19 pandemic.

Contact Tracing over Uncertain Indoor Positioning Data (Extended Version) (preprint)

Pandemics often cause dramatic losses of human lives and impact our societies in many aspects such as public health, tourism, and economy. To contain the spread of an epidemic like COVID-19, efficient and effective contact tracing is important, especially in indoor venues where the risk of infection is higher. In this work, we formulate and study a novel query called Indoor Contact Query (ICQ) over raw, uncertain indoor positioning data that digitalizes people's movements indoors. Given a query object o, e.g., a person confirmed to be a virus carrier, an ICQ analyzes uncertain indoor positioning data to find objects that most likely had close contact with o for a long period of time. To process ICQ, we propose a set of techniques. First, we design an enhanced indoor graph model to organize different types of data necessary for ICQ. Second, for indoor moving objects, we devise methods to determine uncertain regions and to derive positioning samples missing in the raw data. Third, we propose a query processing framework with a close contact determination method, a search algorithm, and the acceleration strategies. We conduct extensive experiments on synthetic and real datasets to evaluate our proposals. The results demonstrate the efficiency and effectiveness of our proposals.

Corrigendum: Genetic predisposition between COVID-19 and four mental illnesses: A bidirectional, two-sample Mendelian randomization study.

[This corrects the article DOI: 10.3389/fpsyt.2021.746276.].

Genetic Predispositions Between COVID-19 and Three Cardio-Cerebrovascular Diseases.

Aims: This study was aimed to apply a Mendelian randomization design to explore the causal association between coronavirus disease 2019 (COVID-19) and three cardio-cerebrovascular diseases, including atrial fibrillation, ischemic stroke, and coronary artery disease. Methods: Two-sample Mendelian randomization was used to determine the following: 1) the causal effect of COVID-19 on atrial fibrillation (55,114 case participants vs 482,295 control participants), coronary artery disease (34,541 case participants vs 261,984 control participants), and ischemic stroke (34,217 case participants vs 40,611 control participants), which were obtained from the European Bioinformatics Institute, and 2) the causal effect of three cardio-cerebrovascular diseases on COVID-19. The single-nucleotide polymorphisms (SNPs) of COVID-19 were selected from the summary-level genome-wide association study data of COVID-19-hg genome-wide association study (GWAS) meta-analyses (round 5) based on the COVID-19 Host Genetics Initiative for participants with European ancestry. The random-effects inverse-variance weighted method was conducted for the main analyses, with a complementary analysis of the weighted median and Mendelian randomization (MR)-Egger approaches. Results: Genetically predicted hospitalized COVID-19 was suggestively associated with ischemic stroke, with an odds ratio (OR) of 1.049 [95% confidence interval (CI) 1.003-1.098; p = 0.037] in the COVID-19 Host Genetics Initiative GWAS. When excluding the UK Biobank (UKBB) data, our analysis revealed a similar odds ratio of 1.041 (95% CI 1.001-1.082; p = 0.044). Genetically predicted coronary artery disease was associated with critical COVID-19, with an OR of 0.860 (95% CI 0.760-0.973; p = 0.017) in the GWAS meta-analysis and an OR of 0.820 (95% CI 0.722-0.931; p = 0.002) when excluding the UKBB data, separately. Limited evidence of causal associations was observed between critical or hospitalized COVID-19 and other cardio-cerebrovascular diseases included in our study. Conclusion: Our findings provide suggestive evidence about the causal association between hospitalized COVID-19 and an increased risk of ischemic stroke. Besides, other factors potentially contribute to the risk of coronary artery disease in patients with COVID-19, but not genetics.

Genetic Predisposition Between COVID-19 and Four Mental Illnesses: A Bidirectional, Two-Sample Mendelian Randomization Study.

Background: The outbreak of 2019 coronavirus disease (COVID-19) has become a global pandemic. Although it has long been suspected that COVID-19 could contribute to the development of mental illness, and individuals with a pre-existing mental illness may have a higher risk of and poorer outcomes from COVID-19 infection, no evidence has established a causal association between them thus far. Methods: To investigate associations in support of a causal association between the severity of COVID-19 and mental illnesses, we leveraged large-scale genetic summary data from genome-wide association study (GWAS) summary datasets, including attention-deficit/hyperactivity disorder (ADHD) (n = 55,374), schizophrenia (n = 77,096), bipolar disorder (n = 51,710), and depression (n = 173,005), based on a previous observational study. The random-effects inverse-variance weighted method was conducted for the main analyses, with a complementary analysis of the weighted median and MR-Egger approaches and multiple sensitivity analyses assessing horizontal pleiotropy and removing outliers in two different COVID-19 databases. Results: The Mendelian randomization (MR) analysis indicated that ADHD [odds ratio (OR) = 1.297; 95% confidence interval (CI), 1.029-1.634; p = 0.028] increased the risk of hospitalization due to COVID-19. A similar association was obtained in MR sensitivity analyses of the weighted median. In addition, genetically predicted COVID-19 was significantly associated with schizophrenia (OR = 1.043; 95% CI, 1.005-1.082; p = 0.027). Conclusions: Although many studies have reported a causal relationship between COVID-19 and mental illness, our study shows that this increased risk is modest. However, considering the characteristics of ADHD that might further increase the individuals' vulnerability to being infected by COVID-19, the ongoing massive worldwide exposure to COVID-19, and the high burden of schizophrenia, we believe that it is necessary to offer preventative measures to these populations and to provide more evidence in understanding the neurological impact of COVID-19.

Genetic predisposition to COVID-19 may increase the risk of hypertension disorders in pregnancy: A two-sample Mendelian randomization study.

AIMS: The aim of this study was to apply the Mendelian randomization (MR) design to explore the potential causal association between COVID-19 and the risk of hypertension disorders in pregnancy. METHODS: Our primary genetic instrument comprised 8 single-nucleotide polymorphisms (SNPs) associated with COVID-19 at genome-wide significance. Data on the associations between the SNPs and the risk of hypertension disorders in pregnancy were obtained from study based on a very large cohort of European population. The random-effects inverse-variance weighted method was conducted for the main analyses, with a complementary analysis of the weighted median and MR-Egger approaches. RESULTS: Using IVW, we found that genetically predicted COVID-19 was significantly positively associated with hypertension disorders in pregnancy, with an odds ratio (OR) of 1.111 [95% confidence interval (CI) 1.042-1.184; P = 0.001]. Weighted median regression also showed directionally similar estimates [OR 1.098 (95% CI, 1.013-1.190), P = 0.023]. Both funnel plots and MR-Egger intercepts suggest no directional pleiotropic effects observed. CONCLUSIONS: Our findings provide direct evidence that there is a shared genetic predisposition so that patients infected with COVID-19 may be causally associated with increased risk of hypertension disorders in pregnancy.

Impact of COVID-19 on IoT Adoption in Healthcare, Smart Homes, Smart Buildings, Smart Cities, Transportation and Industrial IoT (preprint)

COVID-19 has disrupted normal life and has enforced a substantial change in the policies, priorities and activities of individuals, organisations and governments. These changes are proving to be a catalyst for technology and innovation. In this paper, we discuss the pandemic's potential impact on the adoption of the Internet of Things (IoT) in various broad sectors namely healthcare, smart homes, smart buildings, smart cities, transportation and industrial IoT. Our perspective and forecast of this impact on IoT adoption is based on a thorough research literature review, a careful examination of reports from leading consulting firms and interactions with several industry experts. For each of these sectors, we also provide the details of notable IoT initiatives taken in wake of COVID-19. We also highlight the challenges that need to be addressed and important research directions that will facilitate accelerated IoT adoption.

Longitudinal single-cell immune profiling revealed distinct innate immune response in asymptomatic COVID-19 patients (preprint)

Recent studies have characterized the single-cell immune landscape of host immune response of coronavirus disease 2019 (COVID-19), specifically focus on the severe condition. However, the immune response in mild or even asymptomatic patients remains unclear. Here, we performed longitudinal single-cell transcriptome sequencing and T cell/B cell receptor sequencing on 3 healthy donors and 10 COVID-19 patients with asymptomatic, moderate, and severe conditions. We found asymptomatic patients displayed distinct innate immune responses, including increased CD56briCD16- NK subset, which was nearly missing in severe condition and enrichment of a new Th2-like cell type/state expressing a ciliated cell marker. Unlike that in moderate condition, asymptomatic patients lacked clonal expansion of effector CD8+ T cells but had a robust effector CD4+ T cell clonal expansion, coincide with previously detected SARS-CoV-2-reactive CD4+ T cells in unexposed individuals. Moreover, NK and effector T cells in asymptomatic patients have upregulated cytokine related genes, such as IFNG and XCL2. Our data suggest early innate immune response and type I immunity may contribute to the asymptomatic phenotype in COVID-19 disease, which could in turn deepen our understanding of severe COVID-19 and guide early prediction and therapeutics.

Effects of home quarantine for COVID-19 community control in Shenzhen, China, 2020 (preprint)

Background: Shenzhen implement classification management to prevent and control coronavirus disease 2019 (COVID-19) outbreak. Individuals with epidemic histories (came from Hubei and any other affected regions), but without symptoms were instructed to take home quarantine for 14 days and nucleic acid testing (NAT) for SARS-CoV-2. We described the infection status of the home-quarantined individuals, and effects of community control strategies in the three incubations after Wuhan closure in Shenzhen.Methods: This was a descriptive research, the sample size was 2,004 individuals based on multistage sampling during the pre-investigation. And the formal investigation expanded the sample size to 57,012 individuals based on pre-investigation. A single throat swab was collected from each individual for nucleic acid testing (NAT) by reverse transcription-polymerase chain reaction (RT-PCR). NAT was performed by a third-party institution. We collected information related to demographics, disease history, travel history, and personal protective measures before home quarantine, and monitored close-contact histories using the We Chat questionnaire.Results: The total infection rate of home-quarantined individuals was 0.12‰ (95% CI: 0.05‰–0.24‰) out of the total sample size of 59,016. The detection period for seven confirmed cases was primarily concentrated between February 8 and 18, 2020, which was during the second incubation period after Wuhan's closure. The home quarantined individuals with epidemic histories (came from Hubei and any other affected regions) were considered the high risk population during the first two incubations after Wuhan’s closure. No positive cases were detected from February 25 to March 5(the third incubation after Wuhan’s closure). The number of newly-confirmed cases per day was 0 for eight consecutive days from February 22 to 29 in Shenzhen.Conclusions: The community control strategies for home-quarantined individuals with epidemic histories (came from Hubei and any other affected regions), but without symptoms to take the NAT in the first two incubations is effective to control COVID-19. But it is not advocating for home-quarantined person to take the NAT since the third incubation.

Research on COVID-19 prevention and control strategies, and the effect of home quarantine in Shenzhen, China, 2020 (preprint)

AbstractBackground: To study the prevention and control strategies of coronavirus disease 2019 (COVID-19), and to analyze the infection of the home-quarantined individuals with epidemic histories (came from Hubei and any other affected regions), but without symptoms in the three incubations after Wuhan closure in Shenzhen.Methods: The sample size was 2,004 individuals based on multistage sampling during the pre-investigation. Based on the results of the pre-investigation, the formal investigation expanded the sample size to 57,012 individuals. A single throat swab was collected from each individual for nucleic acid testing (NAT) by reverse transcription-polymerase chain reaction (RT-PCR). NAT was performed by a third-party institution, BGI. We collected information related to demographics, disease history, travel history, and personal protective measures before home quarantine, and monitored close-contact histories using the We Chat questionnaire.Results: The total infection rate of home-quarantined individuals was 0.11% (95% CI: 0.05%–0.24%) out of the total sample size of 59,016. The detection period for seven confirmed cases was primarily concentrated between February 8 and 18, 2020, which was during the second incubation period after Wuhan's closure. The home quarantined individuals with epidemic histories (came from Hubei and any other affected regions) were considered the high risk population during the first two incubations after Wuhan’s closure. No positive cases were detected from February 25 to present (the third incubation after Wuhan’s closure). The number of newly-confirmed cases per day was 0 for 8 days from February 22 to 29 in Shenzhen. Thus, the strategies of prevention and control were effective.Conclusions: The strategies and policies were effective for the prevention and control of COVID-19. Additionally, the strategy of implementing NAT during the first two incubations for home-quarantined individuals with epidemic histories (came from Hubei and any other affected regions), but without symptoms, facilitated early detection, early reporting, early diagnosis, early quarantining, and early treatment. However, our findings do not support NAT for home quarantined persons during the third incubation after Wuhan’s closure to present.