Systematic review of host genetic association with Covid‐19 prognosis and susceptibility: What have we learned in 2020?

Araújo, João Locke Ferreira de; Menezes, Diego; Saraiva-Duarte, Julia Maria; Ferreira, Luciana de Lima; Aguiar, Renato Santana; Souza, Renan P.

doi:10.1002/rmv.2283

Cited by 16 publications

(8 citation statements)

References 74 publications

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“…Since data suggest that symptomatic cases represent a fraction of persons infected with SARS-CoV-2, official statistics were expected to be underestimated (Wu et al, 2020). Several aspects may influence COVID-19 symptom presentation (Araújo et al, 2021;Rossi et al, 2021). Epidemiological surveillance using prevalence studies is needed to evaluate the true extent of SARS-CoV-2 dispersion, significantly extending testing to asymptomatic subjects.…”

Section: Introductionmentioning

confidence: 99%

Seroprevalence, Prevalence, and Genomic Surveillance: Monitoring the Initial Phases of the SARS-CoV-2 Pandemic in Betim, Brazil

et al. 2022

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The COVID-19 pandemic has created an unprecedented need for epidemiological monitoring using diverse strategies. We conducted a project combining prevalence, seroprevalence, and genomic surveillance approaches to describe the initial pandemic stages in Betim City, Brazil. We collected 3239 subjects in a population-based age-, sex- and neighborhood-stratified, household, prospective; cross-sectional study divided into three surveys 21 days apart sampling the same geographical area. In the first survey, overall prevalence (participants positive in serological or molecular tests) reached 0.46% (90% CI 0.12–0.80%), followed by 2.69% (90% CI 1.88–3.49%) in the second survey and 6.67% (90% CI 5.42–7.92%) in the third. The underreporting reached 11, 19.6, and 20.4 times in each survey. We observed increased odds to test positive in females compared to males (OR 1.88 95% CI 1.25–2.82), while the single best predictor for positivity was ageusia/anosmia (OR 8.12, 95% CI 4.72–13.98). Thirty-five SARS-CoV-2 genomes were sequenced, of which 18 were classified as lineage B.1.1.28, while 17 were B.1.1.33. Multiple independent viral introductions were observed. Integration of multiple epidemiological strategies was able to adequately describe COVID-19 dispersion in the city. Presented results have helped local government authorities to guide pandemic management.

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Section: Introductionmentioning

confidence: 99%

Seroprevalence, Prevalence, and Genomic Surveillance: Monitoring the Initial Phases of the SARS-CoV-2 Pandemic in Betim, Brazil

et al. 2022

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“…In addition, a large number of other genetic polymorphisms have been reported to be associated with the severity of COVID-19 (16,(18)(19)(20). However, no genetic polymorphisms strongly associated with severe disease that could be used for diagnosis have been reported, suggesting that genetic factors have a limited impact on the severity of the disease.…”

Section: (P5)mentioning

confidence: 99%

Tools and factors predictive of the severity of COVID-19

Sugiyama

2023

GHM

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The outbreak of the novel coronavirus infection caused worldwide confusion. The problem with this infection is that it causes severe illness in some patients, resulting in a high rate of death if appropriate treatment is not given. If patients with severe illness that requires treatment are appropriately identified, treatment can be focused on these patients. However, in the early days of the COVID-19 outbreak, the inability to predict and diagnose the disease led to hospitals being overwhelmed. Therefore, various methods for the diagnosis of severe disease were developed early on, and various methods are still being investigated to predict high-risk patients. The currently available prediction methods are divided into those that predict the onset of severe disease and those used to determine the severity of the disease. Specifically, the main methods include genetic factors, serum humoral factors, laboratory tests, and diagnostic imaging. Since each of these factors has different features, using them in combination is likely to be advantageous.

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“…Tissue residence markers including ITGA1, CXCR6 and JAML show upregulation of genes involved in activation, migration, and cytokinerelated pathways in moderate cases of COVID-19 and translation-initiation, cell homeostasis and nucleoside metabolic pathways in severe cases of COVID-19, respectively [28][29][30] . Reports show that the variations within STXBP5 / STXBP5-AS1 and their interactions could potentially elevate the risk of death among COVID-19 patients through endothelial exocytosis related mechanisms 31,32 .…”

Section: Common Genes In Kidney Covid-aki Snrna-seq and Covid-aki Bul...mentioning

confidence: 99%

Single Nucleus RNA Sequencing of Remnant Kidney Biopsies and Urine Cell RNA Sequencing Reveal Cell Specific Markers of Covid-19 Acute Kidney Injury

Ghag,

Kaushal,

Nwanne

et al. 2023

Preprint

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Acute kidney injury (AKI) in COVID-19 patients is associated with high mortality and morbidity. Critically ill COVID-19 patients are at twice the risk of in-hospital mortality compared to non-COVID AKI patients. We know little about the cell-specific mechanism in the kidney that contributes to worse clinical outcomes in these patients. New generation single cell technologies have the potential to provide insights into physiological states and molecular mechanisms in COVID-AKI. One of the key limitations is that these patients are severely ill posing significant risks in procuring additional biopsy tissue. We recently generated single nucleus RNA-sequencing data using COVID-AKI patient biopsy tissue as part of the human kidney atlas. Here we describe this approach in detail and report deeper comparative analysis of snRNAseq of 4 COVID-AKI, 4 reference, and 6 non-COVID-AKI biopsies. We also generated and analyzed urine transcriptomics data to find overlapping COVID-AKI-enriched genes and their corresponding cell types in the kidney from snRNA-seq data. We identified all major and minor cell types and states by using by using less than a few cubic millimeters of leftover tissue after pathological workup in our approach. Differential expression analysis of COVID-AKI biopsies showed pathways enriched in viral response, WNT signaling, kidney development, and cytokines in several nephron epithelial cells. COVID-AKI profiles showed a much higher proportion of altered TAL cells than non-COVID AKI and the reference samples. In addition to kidney injury and fibrosis markers indicating robust remodeling we found that, 17 genes overlap between urine cell COVID-AKI transcriptome and the snRNA-seq data from COVID-AKI biopsies. A key feature was that several of the distal nephron and collecting system cell types express these markers. Some of these markers have been previously observed in COVID-19 studies suggesting a common mechanism of injury and potentially the kidney as one of the sources of soluble factors with a potential role in disease progression.Translational StatementThe manuscript describes innovation, application and discovery that impact clinical care in kidney disease. First, the approach to maximize use of remnant frozen clinical biopsies to inform on clinically relevant molecular features can augment existing pathological workflow for any frozen tissue without much change in the protocol. Second, this approach is transformational in medical crises such as pandemics where mechanistic insights are needed to evaluate organ injury, targets for drug therapy and diagnostic and prognostic markers. Third, the cell type specific and soluble markers identified and validated can be used for diagnoses or prognoses in AKI due to different etiologies and in multiorgan injury.

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Systematic review of host genetic association with Covid‐19 prognosis and susceptibility: What have we learned in 2020?

Cited by 16 publications

References 74 publications

Seroprevalence, Prevalence, and Genomic Surveillance: Monitoring the Initial Phases of the SARS-CoV-2 Pandemic in Betim, Brazil

Seroprevalence, Prevalence, and Genomic Surveillance: Monitoring the Initial Phases of the SARS-CoV-2 Pandemic in Betim, Brazil

Tools and factors predictive of the severity of COVID-19

Single Nucleus RNA Sequencing of Remnant Kidney Biopsies and Urine Cell RNA Sequencing Reveal Cell Specific Markers of Covid-19 Acute Kidney Injury

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