A genomic region associated with protection against severe COVID-19 is inherited from Neandertals

Zeberg, Hugo; Pääbo, Svante

doi:10.1073/pnas.2026309118

Cited by 194 publications

(159 citation statements)

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“…In a paper published in Nature , Pairo-Castineira et al (2021) identified a significant genetic variant rs10735079 associated with critical illness of COVID-19 in the gene cluster encodes OAS1 , OAS2 , and OAS3 . Interestingly, recent work on archaic human (Neandertal) DNA has identified an additional haplotype in the region of Chromosome 12 containing OAS1 , OAS2 , and OAS3 that protects against severe COVID-19 ( Zeberg and Paabo, 2020 ). Klaassen et al (2020) identified six genetic variants in innate immunity-related genes, including OAS1 (p.Arg130His), which might have predictive value for COVID-19 infection.…”

Section: Resultsmentioning

confidence: 99%

Profiling COVID-19 Genetic Research: A Data-Driven Study Utilizing Intelligent Bibliometrics

Zhang

Grosser³

et al. 2021

Front. Res. Metr. Anal.

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The COVID-19 pandemic constitutes an ongoing worldwide threat to human society and has caused massive impacts on global public health, the economy and the political landscape. The key to gaining control of the disease lies in understanding the genetics of SARS-CoV-2 and the disease spectrum that follows infection. This study leverages traditional and intelligent bibliometric methods to conduct a multi-dimensional analysis on 5,632 COVID-19 genetic research papers, revealing that 1) the key players include research institutions from the United States, China, Britain and Canada; 2) research topics predominantly focus on virus infection mechanisms, virus testing, gene expression related to the immune reactions and patient clinical manifestation; 3) studies originated from the comparison of SARS-CoV-2 to previous human coronaviruses, following which research directions diverge into the analysis of virus molecular structure and genetics, the human immune response, vaccine development and gene expression related to immune responses; and 4) genes that are frequently highlighted include ACE2, IL6, TMPRSS2, and TNF. Emerging genes to the COVID-19 consist of FURIN, CXCL10, OAS1, OAS2, OAS3, and ISG15. This study demonstrates that our suite of novel bibliometric tools could help biomedical researchers follow this rapidly growing field and provide substantial evidence for policymakers’ decision-making on science policy and public health administration.

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Section: Resultsmentioning

confidence: 99%

Profiling COVID-19 Genetic Research: A Data-Driven Study Utilizing Intelligent Bibliometrics

Zhang

Grosser³

et al. 2021

Front. Res. Metr. Anal.

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“…Zeberg and Pääbo have recently reported that the risk of developing clinically more severe COVID-19 is linked to chromosome 3 genetic variations, whereas the risk of developing clinically less severe COVID-19 is linked to chromosome 12 genetic variations. 5,29 Moreover, these risk-altering haplotypes are of Neanderthal origin, and are more prevalent in European populations, compared to populations where COVID-19 death rates are relatively lower (i.e. sub-Saharan Africa, China).…”

Section: Discussionmentioning

confidence: 99%

“…2 Moreover, several human genomic variants have been linked to variations in COVID-19 outcomes. 3-5 On the other hand, COVID-19 traits associated with a positive disease prognosis have received less attention from investigators. One such trait may be headache.…”

Section: Introductionmentioning

confidence: 99%

The impact of headache disorders on COVID-19 survival: a world population-based analysis

Shapiro

Caronna

et al. 2021

Preprint

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Importance: COVID-19 has not impacted people or countries uniformly. This disparity has prompted investigations to identify clinical and genetic predictors of COVID-19 mortality. Headache, a COVID-19 symptom, has been associated with positive disease prognosis. It is logical to consider whether primary headache disorders, among the most prevalent and disabling diseases globally, may also be associated with reduced viral mortality and thereby may have arisen as adaptive host defences. Objective: To study the relationship between COVID-19 mortality and primary headache disorders. Main outcome measure: Using a generalized additive model regression (GAM), we analysed data across 171 nations to identify variables which impact COVID-19 mortality rates (demographics, national wealth and government effectiveness, pandemic management indexes, latitude of the country's capital, prevalence of headache disorders and other diseases). We performed similar analyses of seasonal influenza mortality. Separately, we meta-analysed studies of COVID-19 inpatient survival reporting headache, using PRISMA guidelines. Results: In the global population-level analysis, we observed that a higher prevalence of headache disorders was associated with a higher COVID-19 mortality rate, and represented the main variable contributing to differences in COVID-19 mortality rates between countries (37.8%; F value=10.68). By contrast, we observed a negative trend between the prevalence of headache disorders and influenza death rates. Controversially, when considering headache as a symptom of COVID-19, in the 48 meta-analysed studies we observed a significantly higher risk ratio of survival (RR:2.178 [1.882-2.520], p<0.0001) among COVID-19 inpatients with headache. Conclusions and Relevance: Headache as a primary disorder is more prevalent in nations with higher COVID-19 mortality, whereas headache as a COVID-19 symptom is associated with enhanced survival. Further studies should clarify whether primary headache disorders represent a risk factor for mortality for COVID-19 or, rather, whether this association reflects evolutionary adaptive processes to enhance survival that, in the case of COVID-19, are insufficiently protective.

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“…Both OAS genes had reported associations with Urbani infections in human lung cell cultures [32]. Further, associations between the OAS pathway and MERS-CoV and SARS-CoV2 infections have been reported [69] and single nucleotide polymorphisms in OAS genes were found to be involved in the protective effects of Neandertal haplotypes against SARS-CoV2 [70,71]. IFIT3 was one of four IFN-induced proteins with tetratricopeptide repeats whose expression was greatly enhanced by viral infection, IFN treatment, and pathogen-associated molecular patterns [72].…”

Section: Discussionmentioning

confidence: 99%

Gene Expression Meta-Analysis Reveals Interferon-induced Genes

Park

Harris

2020

Preprint

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BackgroundSevere Acute Respiratory Syndrome (SARS) corona virus (SARS-CoV) infections are a serious public health threat because of their pandemic-causing potential. This work uses mRNA expression data to predict genes associated with SARS-CoV infection through an innovative meta-analysis examining gene signatures (i.e., gene lists ranked by differential gene expression between SARS and mock infection).MethodsThis work defines 29 gene signatures representing SARS infection across seven strains with established mutations that vary virulence (infectious clone SARS (icSARS), Urbani, MA15, ΔORF6, BAT-SRBD, ΔNSP16, and ExoNI) and host (human lung cultures and/or mouse lung samples) and examines them through Gene Set Enrichment Analysis (GSEA). To do this, first positive and negative icSARS gene panels were defined from GSEA-identified leading-edge genes between 500 genes from positive or negative tails of the GSE47960-derived icSARSvsmock signature and the GSE47961-derived icSARSvsmock signature, both from human cultures. GSEA then was used to assess enrichment and identify leading-edge icSARS panel genes in the other 27 signatures. Genes associated with SARS-CoV infection are predicted by examining membership in GSEA-identified leading-edges across signatures.ResultsSignificant enrichment (GSEA p<0.001) was observed between GSE47960-derived and GSE47961-derived signatures, and those leading-edges defined the positive (233 genes) and negative (114 genes) icSARS panels. Non-random (null distribution p<0.001) significant enrichment (p<0.001) was observed between icSARS panels and all verification icSARSvsmock signatures derived from human cultures, from which 51 over- and 22 under-expressed genes were shared across leading-edges with 10 over-expressed genes already being associated with icSARS infection. For the icSARSvsmock mouse signature, significant, non-random enrichment (both p<0.001) held for only the positive icSARS panel, from which nine genes were shared with icSARS infection in human cultures. Considering other SARS strains, significant (p<0.01), non-random (p<0.002) enrichment was observed across signatures derived from other SARS strains for the positive icSARS panel. Five positive icSARS panel genes, CXCL10, OAS3, OASL, IFIT3, and XAF1, were found in mice and human signatures.ConclusionThe GSEA-based meta-analysis approach used here identified genes with and without reported associations with SARS-CoV infections, highlighting this approach’s predictability and usefulness in identifying genes that have potential as therapeutic targets to preclude or overcome SARS infections.

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A genomic region associated with protection against severe COVID-19 is inherited from Neandertals

Cited by 194 publications

References 50 publications

Profiling COVID-19 Genetic Research: A Data-Driven Study Utilizing Intelligent Bibliometrics

Profiling COVID-19 Genetic Research: A Data-Driven Study Utilizing Intelligent Bibliometrics

The impact of headache disorders on COVID-19 survival: a world population-based analysis

Gene Expression Meta-Analysis Reveals Interferon-induced Genes

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