Genetic risks and association with severe COVID-19 among global populations.
Ontology highlight
ABSTRACT:
SUBMITTER: Mauleekoonphairoj J
PROVIDER: S-EPMC8168748 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:Although most SARS-CoV-2-infected individuals experience mild COVID-19, some patients suffer from severe COVID-19, which is accompanied by acute respiratory distress syndrome and systemic inflammation. To identify factors driving severe progression of COVID-19, we performed single-cell RNA-seq using peripheral blood mononuclear cells (PBMCs) obtained from healthy donors, patients with mild or severe COVID-19, and patients with severe influenza. Patients with COVID-19 exhibited hyper-inflammatory signatures across all types of cells among PBMCs, particularly upregulation of the TNF/IL-1beta-driven inflammatory response as compared to severe influenza. In classical monocytes from patients with severe COVID-19, type I IFN response co-existed with the TNF/IL-1beta-driven inflammation, and this was not seen in patients with milder COVID-19 infection. Based on this, we propose that the type I IFN response exacerbates inflammation in patients with severe COVID-19 infection.
2020-07-06 | GSE149689 | GEO
Project description:BackgroundAccurate assessment of health disparities requires unbiased knowledge of genetic risks in different populations. Unfortunately, most genome-wide association studies use genotyping arrays and European samples. Here, we integrate whole genome sequence data from global populations, results from thousands of genome-wide association studies (GWAS), and extensive computer simulations to identify how genetic disease risks can be misestimated.ResultsIn contrast to null expectations, we find that risk allele frequencies at known disease loci are significantly different for African populations compared to other continents. Strikingly, ancestral risk alleles are found at 9.51% higher frequency in Africa, and derived risk alleles are found at 5.40% lower frequency in Africa. By simulating GWAS with different study populations, we find that non-African cohorts yield disease associations that have biased allele frequencies and that African cohorts yield disease associations that are relatively free of bias. We also find empirical evidence that genotyping arrays and SNP ascertainment bias contribute to continental differences in risk allele frequencies. Because of these causes, polygenic risk scores can be grossly misestimated for individuals of African descent. Importantly, continental differences in risk allele frequencies are only moderately reduced if GWAS use whole genome sequences and hundreds of thousands of cases and controls. Finally, comparisons between uncorrected and corrected genetic risk scores reveal the benefits of considering whether risk alleles are ancestral or derived.ConclusionsOur results imply that caution must be taken when extrapolating GWAS results from one population to predict disease risks in another population.
| S-EPMC6234640 | biostudies-literature
Project description:With the growing evidence on the variable human susceptibility against COVID-19, it is evident that some genetic loci modulate the severity of the infection. Recent studies have identified several loci associated with greater severity. More recently, a study has identified a 50 kb genomic segment introgressed from Neanderthal adding a risk for COVID-19, and this genomic segment is present among 16% and 50% people of European and South Asian descent, respectively. Our studies on ACE2 identified a haplotype present among 20% and 60% of European and South Asian populations, respectively, which appears to be responsible for the low case fatality rate among South Asian populations. This result was also consistent with the real-time infection rate and case fatality rate among various states of India. We readdressed this issue using both of the contrasting datasets and compared them with the real-time infection rates and case fatality rate in India. We found that the polymorphism present in the 50 kb introgressed genomic segment (rs10490770) did not show any significant correlation with the infection and case fatality rate in India.
| S-EPMC8196069 | biostudies-literature
Project description: Not available
| S-BSST416 | biostudies-other
Project description:Background Information about the distribution of clinically significant genetic markers in different populations may be helpful in elaborating personalized approaches to the clinical management of COVID-19 in the absence of consensus guidelines. Aim Analyze frequencies and distribution patterns of two markers associated with severe COVID-19 (rs11385942 and rs657152) and look for potential correlations between these markers and deaths from COVID-19 among populations in Russia and across the world. Methods We genotyped 1883 samples from 91 ethnic groups pooled into 28 populations representing Russia and its neighbor states. We also compiled a dataset on 32 populations from other regions using genotypes extracted or imputed from the available databases. Geographic maps showing the frequency distribution of the analyzed markers were constructed using the obtained data. Results The cartographic analysis revealed that rs11385942 distribution follows the West Eurasian pattern: the marker is frequent among the populations of Europe, West Asia and South Asia but rare or absent in all other parts of the globe. Notably, the transition from high to low rs11385942 frequencies across Eurasia is not abrupt but follows the clinal variation pattern instead. The distribution of rs657152 is more homogeneous. The analysis of correlations between the frequencies of the studied markers and the epidemiological characteristics of COVID-19 in a population revealed that higher frequencies of both risk alleles correlated positively with mortality from this disease. For rs657152, the correlation was especially strong (r = 0.59, p = 0.02). These reasonable correlations were observed for the “Russian” dataset only: no such correlations were established for the “world” dataset. This could be attributed to the differences in methodology used to collect COVID-19 statistics in different countries. Conclusion Our findings suggest that genetic differences between populations make a small yet tangible contribution to the heterogeneity of the pandemic worldwide.
| S-EPMC8575442 | biostudies-literature
Project description:While SARS-CoV-2 infection has pleiotropic and systemic effects in some patients, many others experience milder symptoms. We sought a holistic understanding of the severe/mild distinction in COVID-19 pathology, and its origins. We performed a whole-blood preserving single-cell analysis protocol to integrate contributions from all major cell types including neutrophils, monocytes, platelets, lymphocytes and the contents of serum. Patients with mild COVID-19 disease display a coordinated pattern of interferon-stimulated gene (ISG) expression across every cell population and these cells are systemically absent in patients with severe disease. Severe COVID-19 patients also paradoxically produce very high anti-SARS-CoV-2 antibody titers and have lower viral load as compared to mild disease. Examination of the serum from severe patients demonstrates that they uniquely produce antibodies that functionally block the production of the mild disease-associated ISG-expressing cells, by engaging conserved signaling circuits that dampen cellular responses to interferons. Overzealous and auto-directed antibody responses pit the immune system against itself in many COVID-19 patients and this defines targets for immunotherapies to allow immune systems to provide viral defense.
2021-01-22 | GSE163668 | GEO
Project description:Early in the COVID-19 pandemic, type 2 diabetes (T2D) was marked as a risk-factor for severe disease. Inflammation is central to the aetiology of both conditions where immune responses influence disease course. Identifying at-risk groups through immuno-inflammatory signatures can direct personalised care and help develop potential targets for precision therapy. This observational study characterised immunophenotypic variation associated with COVID-19 severity in T2D. Broad-spectrum immunophenotyping quantified 15 leukocyte populations in circulation from a cohort of 45 hospitalised COVID-19 patients with and without T2D. Lymphocytopenia, of CD8+ lymphocytes, was associated with severe COVID-19 and intensive care admission in non-diabetic and T2D patients. A morphological anomaly of increased monocyte size and monocytopenia of classical monocytes were specifically associated with severe COVID-19 in patients with T2D requiring intensive care. Over-expression of inflammatory markers reminiscent of the type-1 interferon pathway underlaid the immunophenotype associated with T2D. These changes may contribute to severity of COVID-19 in T2D. These findings show characteristics of severe COVID-19 in T2D as well as provide evidence that type-1 interferons may be actionable targets for future studies.
| S-SCDT-EMM-2020-13038 | biostudies-other
Project description:The study aims at investigating the specifical transcriptional signatures of severe COVID-19
2021-01-15 | GSE164805 | GEO
Project description:Among approximately 4.6 million members of Kaiser Permanente Northern California, we examined associations of severe COVID-19 with demographic factors and comorbidities. As of July 23, 2021, 16 182 had been hospitalized, 2416 admitted to an ICU, and 1525 died due to COVID-19. Age was strongly associated with hospitalization, ICU admission, and death. Black persons and Hispanic ethnicity had higher risk of death compared with Whites. Among the comorbidities examined, Alzheimer's disease was associated with the highest risk for hospitalization (aHR 3.19, CI: 2.88-3.52) and death (aHR 4.04, CI: 3.32-4.91). Parkinson's disease had the second highest risk of death (aHR = 2.07, CI: 1.50-2.87).
| S-EPMC8652998 | biostudies-literature
Project description:Analysis of COVID-19 hospitalized patients, with different kind of symptoms, by human rectal swabs collection and 16S sequencing approach.
2022-09-22 | E-MTAB-12236 | biostudies-arrayexpress