Dataset Information

The Genomic Profile Associated with Risk of Severe Forms of COVID-19 in Amazonian Native American Populations.

ABSTRACT: Genetic factors associated with COVID-19 disease outcomes are poorly understood. This study aimed to associate genetic variants in the SLC6A20, LZTFL1, CCR9, FYCO1, CXCR6, XCR1, and ABO genes with the risk of severe forms of COVID-19 in Amazonian Native Americans, and to compare the frequencies with continental populations. The study population was composed of 64 Amerindians from the Amazon region of northern Brazil. The difference in frequencies between the populations was analyzed using Fisher's exact test, and the results were significant when p ≤ 0.05. We investigated 64 polymorphisms in 7 genes; we studied 47 genetic variants that were new or had impact predictions of high, moderate, or modifier. We identified 15 polymorphisms with moderate impact prediction in 4 genes (ABO, CXCR6, FYCO1, and SLC6A20). Among the variants analyzed, 18 showed significant differences in allele frequency in the NAM population when compared to others. We reported two new genetic variants with modifier impact in the Amazonian population that could be studied to validate the possible associations with COVID-19 outcomes. The genomic profile of Amazonian Native Americans may be associated with protection from severe forms of COVID-19. This work provides genomic data that may help forthcoming studies to improve COVID-19 outcomes.

SUBMITTER: Pastana LF

PROVIDER: S-EPMC9027999 | biostudies-literature | 2022 Apr

REPOSITORIES: biostudies-literature

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The Genomic Profile Associated with Risk of Severe Forms of COVID-19 in Amazonian Native American Populations.

Pastana Lucas Favacho LF Silva Thays Amâncio TA Gellen Laura Patrícia Albarello LPA Vieira Giovana Miranda GM de Assunção Letícia Almeida LA Leitão Luciana Pereira Colares LPC da Silva Natasha Monte NM Coelho Rita de Cássia Calderaro RCC de Alcântara Angélica Leite AL Vinagre Lui Wallacy Morikawa Souza LWMS Rodrigues Juliana Carla Gomes JCG Borges Leal Diana Feio da Veiga DFDV Fernandes Marianne Rodrigues MR de Souza Sandro José SJ Kroll José Eduardo JE Ribeiro-Dos-Santos André Mauricio AM Burbano Rommel Mario Rodríguez RMR Guerreiro João Farias JF de Assumpção Paulo Pimentel PP Ribeiro-Dos-Santos Ândrea Campos ÂC Dos Santos Sidney Emanuel Batista SEB Dos Santos Ney Pereira Carneiro NPC

Journal of personalized medicine 20220401 4

Genetic factors associated with COVID-19 disease outcomes are poorly understood. This study aimed to associate genetic variants in the SLC6A20, LZTFL1, CCR9, FYCO1, CXCR6, XCR1, and ABO genes with the risk of severe forms of COVID-19 in Amazonian Native Americans, and to compare the frequencies with continental populations. The study population was composed of 64 Amerindians from the Amazon region of northern Brazil. The difference in frequencies ...[more]

PMID: 35455670

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Project description:BackgroundInformation 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.AimAnalyze 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.MethodsWe 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.ResultsThe 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.ConclusionOur findings suggest that genetic differences between populations make a small yet tangible contribution to the heterogeneity of the pandemic worldwide.

Project description:The etiology of severe forms of COVID19, especially in young patients, remains a salient unanswered question. Here we build built on a 3-tier cohort where all individuals/patients were strictly below 50 years of age and where a number of comorbidities were excluded at study onset. Besides healthy controls (N=22), these included patients in the intensive care unit with Acute Respiratory Distress Syndrome (ARDS) (“critical group”; N=47), and those in a non-critical care ward under supplemental oxygen (“non-critical group”, N=25). This highly curated cohort allowed us to perform a deep multi-omics approach, which included whole genome sequencing, whole blood RNA-sequencing, plasma and peripheral-blood mononuclear cells proteomics, multiplex cytokine profiling, mass-cytometry-based immune cell profiling in conjunction with viral parameters i.e. anti-SARS-Cov-2 neutralizing antibodies and multi-target antiviral serology. Critical patients were characterized by an exacerbated inflammatory state, perturbed lymphoid and myeloid cell compartments, signatures of dysregulated blood coagulation and active regulation of viral entry into the cells. A unique gene signature that differentiates critical from non-critical patients was identified by an ensemble of machine learning, deep learning and quantum annealing approachmethods. Within this gene networksignature, Sstructural Causal causal Modeling modeling identified several genes that may potentially drivepromote ARDS driver genes etiology, among which the up-regulated metalloprotease ADAM9 seems to be a key driver. Inhibition of ADAM9 ex vivo interfered with SARS-Cov-2 uptake and replication in human epithelial cells. In brief, Hence we applyied an advanced integrated machine learning approach and probabilistic programming strategy to identify causal molecular driver geness for of severe forms of COVID-19 in a small, uncluttered tightly controlled cohort of patients, the importance of which were then validated with experiments.

Project description:BackgroundCoronaviruses can induce the production of interleukin (IL)-1β, IL-6, tumour necrosis factor, and other cytokines implicated in autoinflammatory disorders. It has been postulated that anakinra, a recombinant IL-1 receptor antagonist, might help to neutralise the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-related hyperinflammatory state, which is considered to be one cause of acute respiratory distress among patients with COVID-19. We aimed to assess the off-label use of anakinra in patients who were admitted to hospital for severe forms of COVID-19 with symptoms indicative of worsening respiratory function.MethodsThe Ana-COVID study included a prospective cohort from Groupe Hospitalier Paris Saint-Joseph (Paris, France) and a historical control cohort retrospectively selected from the Groupe Hospitalier Paris Saint-Joseph COVID cohort, which began on March 18, 2020. Patients were included in the prospective cohort if they were aged 18 years or older and admitted to Groupe Hospitalier Paris Saint-Joseph with severe COVID-19-related bilateral pneumonia on chest x-ray or lung CT scan. The other inclusion criteria were either laboratory-confirmed SARS-CoV-2 or typical lung infiltrates on a lung CT scan, and either an oxygen saturation of 93% or less under oxygen 6 L/min or more, or aggravation (saturation ≤93% under oxygen 3 L/min) with a loss of 3% of oxygen saturation in ambient air over the previous 24 h. The historical control group of patients had the same inclusion criteria. Patients in the anakinra group were treated with subcutaneous anakinra (100 mg twice a day for 72 h, then 100 mg daily for 7 days) as well as the standard treatments at the institution at the time. Patients in the historical group received standard treatments and supportive care. The main outcome was a composite of either admission to the intensive care unit (ICU) for invasive mechanical ventilation or death. The main analysis was done on an intention-to-treat basis (including all patients in the anakinra group who received at least one injection of anakinra).FindingsFrom March 24 to April 6, 2020, 52 consecutive patients were included in the anakinra group and 44 historical patients were identified in the Groupe Hospitalier Paris Saint-Joseph COVID cohort study. Admission to the ICU for invasive mechanical ventilation or death occurred in 13 (25%) patients in the anakinra group and 32 (73%) patients in the historical group (hazard ratio [HR] 0·22 [95% CI 0·11-0·41; p<0·0001). The treatment effect of anakinra remained significant in the multivariate analysis (HR 0·22 [95% CI 0·10-0·49]; p=0·0002). An increase in liver aminotransferases occurred in seven (13%) patients in the anakinra group and four (9%) patients in the historical group.InterpretationAnakinra reduced both need for invasive mechanical ventilation in the ICU and mortality among patients with severe forms of COVID-19, without serious side-effects. Confirmation of efficacy will require controlled trials.FundingGroupe Hospitalier Paris Saint-Joseph.

Dataset Information

The Genomic Profile Associated with Risk of Severe Forms of COVID-19 in Amazonian Native American Populations.

Publications

The Genomic Profile Associated with Risk of Severe Forms of COVID-19 in Amazonian Native American Populations.

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