Genome-wide analysis provides genetic evidence that ACE2 influences COVID-19 risk and yields risk scores associated with severe disease

How could our genetics impact COVID-19 vaccine response?

INTRODUCTION

The COVID-19 pandemic, caused by the SARS-CoV-2 virus, has posed unprecedented global health challenges since its emergence in December 2019. The rapid availability of vaccines has been estimated to save millions of lives, but there is variation in how individuals respond to vaccines, influencing their effectiveness at an individual, and population level.

AREAS COVERED

This review focuses on human genetic factors influencing the immune response and effectiveness of vaccines, highlighting the importance of associations across the HLA locus. Genome-Wide Association Studies (GWAS) and other genetic association analyses have identified statistically significant associations between specific HLA alleles including HLA-DRB1*13, DBQ1*06, and A*03 impacting antibody responses and the risk of breakthrough infections post-vaccination. Relationships between these associations and potential mechanisms and links with risks of natural infection or disease are explored, and this review concludes by emphasizing how understanding the mechanisms of these genetic determinants may inform the development of tailored vaccination strategies.

EXPERT OPINION

Although complex, we believe these findings from the SARS-CoV2 pandemic offer a unique opportunity to understand the relationships between HLA and infection and vaccine response, with a goal of optimizing individual protection against COVID-19 in the ongoing pandemic, and possibly influencing wider vaccine development in the future.

GWAS-significant loci and severe COVID-19: analysis of associations, link with thromboinflammation syndrome, gene-gene, and gene-environmental interactions

Objective

The aim of this study was to replicate associations of GWAS-significant loci with severe COVID-19 in the population of Central Russia, to investigate associations of the SNPs with thromboinflammation parameters, to analyze gene-gene and gene-environmental interactions.

Materials and Methods

DNA samples from 798 unrelated Caucasian subjects from Central Russia (199 hospitalized COVID-19 patients and 599 controls with a mild or asymptomatic course of COVID-19) were genotyped using probe-based polymerase chain reaction for 10 GWAS-significant SNPs: rs143334143 CCHCR1, rs111837807 CCHCR1, rs17078346 SLC6A20-LLZTFL1, rs17713054 SLC6A20-LLZTFL1, rs7949972 ELF5, rs61882275 ELF5, rs12585036 ATP11A, rs67579710 THBS3, THBS3-AS1, rs12610495 DPP9, rs9636867 IFNAR2.

Results

SNP rs17713054 SLC6A20-LZTFL1 was associated with increased risk of severe COVID-19 in the entire group (risk allele A, OR = 1.78, 95% CI = 1.22-2.6, p = 0.003), obese individuals (OR = 2.31, 95% CI = 1.52-3.5, p = 0.0002, (p bonf = 0.0004)), patients with low fruit and vegetable intake (OR = 1.72, 95% CI = 1.15-2.58, p = 0.01, (p bonf = 0.02)), low physical activity (OR = 1.93, 95% CI = 1.26-2.94, p = 0.0035, (p bonf = 0.007)), and nonsmokers (OR = 1.65, 95% CI = 1.11-2.46, p = 0.02). This SNP correlated with increased BMI (p = 0.006) and worsened thrombodynamic parameters (maximum optical density of the formed clot, D (p = 0.02), delayed appearance of spontaneous clots, Tsp (p = 0.02), clot size 30 min after coagulation activation, CS (p = 0.036)). SNP rs17078346 SLC6A20-LZTFL1 was linked with increased BMI (p = 0.01) and severe COVID-19 in obese individuals (risk allele C, OR = 1.72, 95% CI = 1.15-2.58, p = 0.01, (p bonf = 0.02)). SNP rs12610495 DPP9 was associated with increased BMI (p = 0.01), severe COVID-19 in obese patients (risk allele G, OR = 1.48, 95% CI = 1.09-2.01, p = 0.01, (p bonf = 0.02)), and worsened thrombodynamic parameters (time to the start of clot growth, Tlag (p = 0.01)). For rs7949972 ELF5, a protective effect against severe COVID-19 was observed in non-obese patients (effect allele T, OR = 0.67, 95% CI = 0.47-0.95, p = 0.02, (p bonf = 0.04)), improving thrombodynamic parameters (CS (p = 0.02), stationary spatial clot growth rates, Vst (p = 0.02)). Finally, rs12585036 ATP11A exhibited a protective effect against severe COVID-19 in males (protective allele A, OR = 0.51, 95% CI = 0.32-0.83, p = 0.004). SNPs rs67579710 THBS3, THBS3-AS1, rs17713054 SLC6A20-LZTFL1, rs7949972 ELF5, rs9636867 IFNAR2-were involved in two or more of the most significant G×G interactions (p perm ≤ 0.01). The pairwise combination rs67579710 THBS3, THBS3-AS1 × rs17713054 SLC6A20-LZTFL1 was a priority in determining susceptibility to severe COVID-19 (it was included in four of the top five most significant SNP-SNP interaction models).

Conclusion

Overall, this study represents a comprehensive molecular-genetic and bioinformatics analysis of the involvement of GWAS-significant loci in the molecular mechanisms of severe COVID-19, gene-gene and gene-environmental interactions, and provides evidence of their relationship with thromboinflammation parameters in patients hospitalized in intensive care units.

COVID-19 vaccine effectiveness among South Asians in Canada

We evaluated the effectiveness of COVID-19 vaccines among South Asians living in Ontario, Canada compared to non-South Asians and compared the odds of symptomatic COVID-19 infection and related hospitalizations and deaths among non-vaccinated South Asians and non-South Asians. This was a test negative design study conducted in Ontario, Canada between December 14, 2020 and November 15, 2021. All eligible individuals >18 years with symptoms of COVID-19 were subdivided by ethnicity (South Asian vs other) and vaccination status (vaccinated versus not). The primary outcome was vaccine effectiveness as defined by COVID-19 infections, hospitalizations, and deaths, and secondary outcome was the odds of COVID-19 infections, hospitalizations, and death comparing non-vaccinated South Asians to non-vaccinated non-South Asians. 883,155 individuals were included. Among South Asians, two doses of COVID-19 vaccine prevented 93.8% (95% CI 93.2, 94.4) of COVID-19 infections and 97.5% (95% CI 95.2, 98.6) of hospitalizations and deaths. Among non-South Asians, vaccines prevented 86.6% (CI 86.3, 86.9) of COVID-19 infections and 93.1% (CI 92.2, 93.8) of hospitalizations and deaths. Non-vaccinated South Asians had higher odds of symptomatic SARS-CoV-2 infection compared to non-vaccinated non-South Asians (OR 2.35, 95% CI 2.3, 2.4), regardless of their immigration status. COVID-19 vaccines are effective in preventing infections, hospitalizations and deaths among South Asians living in Canada. The observation that non-vaccinated South Asians have higher odds of symptomatic COVID-19 infection warrants further investigation.

Genetic risk factors for COVID-19 and influenza are largely distinct

Coronavirus disease 2019 (COVID-19) and influenza are respiratory illnesses caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and influenza viruses, respectively. Both diseases share symptoms and clinical risk factors1, but the extent to which these conditions have a common genetic etiology is unknown. This is partly because host genetic risk factors are well characterized for COVID-19 but not for influenza, with the largest published genome-wide association studies for these conditions including >2 million individuals2 and about 1,000 individuals3-6, respectively. Shared genetic risk factors could point to targets to prevent or treat both infections. Through a genetic study of 18,334 cases with a positive test for influenza and 276,295 controls, we show that published COVID-19 risk variants are not associated with influenza. Furthermore, we discovered and replicated an association between influenza infection and noncoding variants in B3GALT5 and ST6GAL1, neither of which was associated with COVID-19. In vitro small interfering RNA knockdown of ST6GAL1-an enzyme that adds sialic acid to the cell surface, which is used for viral entry-reduced influenza infectivity by 57%. These results mirror the observation that variants that downregulate ACE2, the SARS-CoV-2 receptor, protect against COVID-19 (ref. 7). Collectively, these findings highlight downregulation of key cell surface receptors used for viral entry as treatment opportunities to prevent COVID-19 and influenza.

Exploring non-coding genetic variability in ACE2: Functional annotation and in vitro validation of regulatory variants

The surge in human whole-genome sequencing data has facilitated the study of non-coding region variations, yet understanding their biological significance remains a challenge. We used a computational workflow to assess the regulatory potential of non-coding variants, with a particular focus on the Angiotensin Converting Enzyme 2 (ACE2) gene. This gene is crucial in physiological processes and serves as the entry point for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus causing coronavirus disease 19 (COVID-19). In our analysis, using data from the gnomAD population database and functional annotation, we identified 17 significant Single Nucleotide Variants (SNVs) in ACE2, particularly in its enhancers, promoters, and 3' untranslated regions (UTRs). We found preliminary evidence supporting the regulatory impact of some of these variants on ACE2 expression. Our detailed examination of two SNVs, rs147718775 and rs140394675, in the ACE2 promoter revealed that these co-occurring SNVs, when mutated, significantly enhance promoter activity, suggesting a possible increase in specific ACE2 isoform expression. This method proves effective in identifying and interpreting impactful non-coding variants, aiding in further studies and enhancing understanding of molecular bases of monogenic and complex traits.

Genomic Landscape of Susceptibility to Severe COVID-19 in the Slovenian Population

Determining the genetic contribution of susceptibility to severe SARS-CoV-2 infection outcomes is important for public health measures and individualized treatment. Through intense research on this topic, several hundred genes have been implicated as possibly contributing to the severe infection phenotype(s); however, the findings are complex and appear to be population-dependent. We aimed to determine the contribution of human rare genetic variants associated with a severe outcome of SARS-CoV-2 infections and their burden in the Slovenian population. A panel of 517 genes associated with severe SARS-CoV-2 infection were obtained by combining an extensive review of the literature, target genes identified by the COVID-19 Host Genetic Initiative, and the curated Research COVID-19 associated genes from PanelApp, England Genomics. Whole genome sequencing was performed using PCR-free WGS on DNA from 60 patients hospitalized due to severe COVID-19 disease, and the identified rare genomic variants were analyzed and classified according to the ACMG criteria. Background prevalence in the general Slovenian population was determined by comparison with sequencing data from 8025 individuals included in the Slovenian genomic database (SGDB). Results show that several rare pathogenic/likely pathogenic genomic variants in genes CFTR, MASP2, MEFV, TNFRSF13B, and RNASEL likely contribute to the severe infection outcomes in our patient cohort. These results represent an insight into the Slovenian genomic diversity associated with a severe COVID-19 outcome.

Shared genetics and causal association between plasma levels of SARS-CoV-2 entry receptor ACE2 and Alzheimer's disease

BACKGROUND

Alzheimer's disease (AD) is the highest risk of COVID-19 infection, hospitalization, and mortality. However, it remains largely unclear about the link between AD and COVID-19 outcomes. ACE2 is an entry receptor for SARS-CoV-2. Circulating ACE2 is a novel biomarker of death and associated with COVID-19 outcomes.

METHODS

Here, we explored the shared genetics and causal association between AD and plasma ACE2 levels using large-scale genome-wide association study, gene expression, expression quantitative trait loci, and high-throughput plasma proteomic profiling datasets.

RESULTS

We found a significant causal effect of genetically increased circulating ACE2 on increased risk of AD. Cross-trait association analysis identified 19 shared genetic variants, and three variants rs3104412, rs2395166, and rs3135344 at chromosome 6p21.32 were associated with COVID-19 infection, hospitalization, and severity. We mapped 19 variants to 117 genes, which were significantly upregulated in lung, spleen, and small intestine, downregulated in brain tissues, and involved in immune system, immune disease, and infectious disease pathways. The plasma proteins corresponding to LST1, AGER, TNXB, and APOC1 were predominantly associated with COVID-19 infection, ventilation, and death.

CONCLUSION

Together, our findings suggest the shared genetics and causal association between AD and plasma ACE2 levels, which may partially explain the link between AD and COVID-19.

Human angiotensin-converting enzyme 2-specific antisense oligonucleotides reduce infection with SARS-CoV-2 variants

BACKGROUND

The Spike protein mutation severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) led to decreased protective effect of various vaccines and mAbs, suggesting that blocking SARS-CoV-2 infection by targeting host factors would make the therapy more resilient against virus mutations. Angiotensin-converting enzyme 2 (ACE2) is the host receptor of SARS-CoV-2 and its variants, as well as many other coronaviruses. Downregulation of ACE2 expression in the respiratory tract may prevent viral infection. Antisense oligonucleotides (ASOs) can be rationally designed on the basis of sequence data, require no delivery system, and can be administered locally.

OBJECTIVE

We sought to design ASOs that can block SARS-CoV-2 by downregulating ACE2 in human airway.

METHODS

ACE2-targeting ASOs were designed using a bioinformatic method and screened in cell lines. Human primary nasal epithelial cells cultured at the air-liquid interface and humanized ACE2 mice were used to detect the ACE2 reduction levels and the safety of ASOs. ASO-pretreated nasal epithelial cells and mice were infected and then used to detect the viral infection levels.

RESULTS

ASOs reduced ACE2 expression on mRNA and protein level in cell lines and in human nasal epithelial cells. Furthermore, they efficiently suppressed virus replication of 3 different SARS-CoV-2 variants in human nasal epithelial cells. In vivo, ASOs also downregulated human ACE2 in humanized ACE2 mice and thereby reduced viral load, histopathologic changes in lungs, and increased survival of mice.

CONCLUSIONS

ACE2-targeting ASOs can effectively block SARS-CoV-2 infection. Our study provides a new approach for blocking SARS-CoV-2 and other ACE2-targeting virus in high-risk populations.

Low-coverage whole genome sequencing for a highly selective cohort of severe COVID-19 patients

Despite the advances in genetic marker identification associated with severe COVID-19, the full genetic characterisation of the disease remains elusive. This study explores imputation in low-coverage whole genome sequencing for a severe COVID-19 patient cohort. We generated a dataset of 79 imputed variant call format files using the GLIMPSE1 tool, each containing an average of 9.5 million single nucleotide variants. Validation revealed a high imputation accuracy (squared Pearson correlation ≍0.97) across sequencing platforms, showcasing GLIMPSE1's ability to confidently impute variants with minor allele frequencies as low as 2% in individuals with Spanish ancestry. We carried out a comprehensive analysis of the patient cohort, examining hospitalisation and intensive care utilisation, sex and age-based differences, and clinical phenotypes using a standardised set of medical terms developed to characterise severe COVID-19 symptoms. The methods and findings presented here can be leveraged for future genomic projects to gain vital insights into health challenges like COVID-19.

Association of ACE2 and TMPRSS2 genes variants with disease severity and most important biomarkers in COVID-19 patients in Bosnia and Herzegovina

AIM

To assess the association of single nucleotide polymorphisms (SNPs) in the ACE2 and TMPRSS2 genes with COVID-19 severity and key biomarkers.

METHODS

The study involved 750 COVID-19 patients from Bosnia and Herzegovina, divided into three groups: mild, moderate, and severe cases. Genetic variations within the ACE2 (rs2285666) and TMPRSS2 (rs2070788) genes were examined with real-time polymerase chain reaction. Biochemical markers were determined with standard procedures.

RESULTS

There was a significant difference in the rs2070788 genotype distribution between patients with mild and moderate symptoms, but not between other groups. For the rs2285666 polymorphism, no significant difference in genotype distribution was found. In patients with mild symptoms, carriers of the GG genotype of rs2070788 had significantly higher total bilirubin levels than carriers of the AA genotype. Similarly, carriers of the TT genotype of rs2285666 had significantly higher activated partial thromboplastin time and international normalized ratio, and lower lactate dehydrogenase levels compared with the CC genotype. Among patients with severe symptoms, carriers of the GG genotype showed significantly higher potassium levels than carriers of the AA genotype, while carriers of the TT genotype showed significantly higher erythrocyte count as well as hemoglobin and hematocrit levels compared with the CC genotype.

CONCLUSION

This study highlights the role of genetic factors, particularly SNPs in the ACE2 and TMPRSS2 genes, in determining COVID-19 severity, aiding patient risk assessment and prognosis.

TAFRO Syndrome and COVID-19

TAFRO syndrome is a systemic inflammatory disease characterized by thrombocytopenia and anasarca. It results from hyperinflammation and produces severe cytokine storms. Severe acute respiratory syndrome coronavirus 2, which led to the coronavirus disease 2019 (COVID-19) pandemic, also causes cytokine storms. COVID-19 was reported to be associated with various immune-related manifestations, including multisystem inflammatory syndrome, hemophagocytic syndrome, vasculitis, and immune thrombocytopenia. Although the pathogenesis and complications of COVID-19 have not been fully elucidated, the pathogeneses of excessive immunoreaction after COVID-19 and TAFRO syndrome both involve cytokine storms. Since the COVID-19 pandemic, there have been a few case reports about the onset of TAFRO syndrome after COVID-19 or COVID-19 vaccination. Castleman disease also presents with excessive cytokine production. We reviewed the literature about the association between TAFRO syndrome or Castleman disease and COVID-19 or vaccination against it. While the similarities and differences between the pathogeneses of TAFRO syndrome and COVID-19 have not been investigated previously, the cytokines and genetic factors associated with TAFRO syndrome and COVID-19 were reviewed by examining case reports. Investigation of TAFRO-like manifestations after COVID-19 or vaccination against COVID-19 may contribute to understanding the pathogenesis of TAFRO syndrome.

Correlation between Genomic Variants and Worldwide COVID-19 Epidemiology

COVID-19 is a systemic disease caused by the etiologic agent SARS-CoV-2, first reported in Hubei Province in Wuhan, China, in late 2019. The SARS-CoV-2 virus has evolved over time with distinct transmissibility subvariants from ancestral lineages. The clinical manifestations of the disease vary according to their severity and can range from asymptomatic to severe. Due to the rapid evolution to a pandemic, epidemiological studies have become essential to understand and effectively combat COVID-19, as the incidence and mortality of this disease vary between territories and populations. This study correlated epidemiological data on the incidence and mortality of COVID-19 with frequencies of important SNPs in GWAS studies associated with the susceptibility and mortality of this disease in different populations. Our results indicated significant correlations for 11 genetic variants (rs117169628, rs2547438, rs2271616, rs12610495, rs12046291, rs35705950, rs2176724, rs10774671, rs1073165, rs4804803 and rs7528026). Of these 11 variants, 7 (rs12046291, rs117169628, rs1073165, rs2547438, rs2271616, rs12610495 and rs35705950) were positively correlated with the incidence rate, these variants were more frequent in EUR populations, suggesting that this population is more susceptible to COVID-19. The rs2176724 variant was inversely related to incidence rates; therefore, the higher the frequency of the allele is, the lower the incidence rate. This variant was more frequent in the AFR population, which suggests a protective factor against SARS-CoV-2 infection in this population. The variants rs10774671, rs4804803, and rs7528026 showed a significant relationship with mortality rates. SNPs rs10774671 and rs4804803 were inversely related to mortality rates and are more frequently present in the AFR population. The rs7528026 variant, which is more frequent in the AMR population, was positively related to mortality rates. The study has the potential to identify and correlate the genetic profile with epidemiological data, identify populations that are more susceptible to severe forms of COVID-19, and relate them to incidence and mortality.

Relationship between HLA genetic variations, COVID-19 vaccine antibody response, and risk of breakthrough outcomes

The rapid global distribution of COVID-19 vaccines, with over a billion doses administered, has been unprecedented. However, in comparison to most identified clinical determinants, the implications of individual genetic factors on antibody responses post-COVID-19 vaccination for breakthrough outcomes remain elusive. Here, we conducted a population-based study including 357,806 vaccinated participants with high-resolution HLA genotyping data, and a subset of 175,000 with antibody serology test results. We confirmed prior findings that single nucleotide polymorphisms associated with antibody response are predominantly located in the Major Histocompatibility Complex region, with the expansive HLA-DQB1*06 gene alleles linked to improved antibody responses. However, our results did not support the claim that this mutation alone can significantly reduce COVID-19 risk in the general population. In addition, we discovered and validated six HLA alleles (A*03:01, C*16:01, DQA1*01:02, DQA1*01:01, DRB3*01:01, and DPB1*10:01) that independently influence antibody responses and demonstrated a combined effect across HLA genes on the risk of breakthrough COVID-19 outcomes. Lastly, we estimated that COVID-19 vaccine-induced antibody positivity provides approximately 20% protection against infection and 50% protection against severity. These findings have immediate implications for functional studies on HLA molecules and can inform future personalised vaccination strategies.

Genetic variants in ATP2B2 as risk factors for mortality in patients unrelated but not associated with families with severe COVID-19

Introduction

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative agent of Coronavirus Disease 2019 (COVID-19). The disease has a wide range of clinical manifestations, from asymptomatic to severe. Ancestral contribution, sex, immune response, and genetic factors influence the presentation of the disease. The objective of the present study was to validate these genetic variants in patients with severe COVID-19 who died and in survivor patients. Methods: Single nucleotide variants (SNVs) in six genes: ATPase plasma membrane Ca2+ transporting 2 (ATP2B2), transmembrane serine protease 2 (TMPRSS2), dedicator of cytokinesis 2 (DOCK2), (interferon alpha and beta receptor subunit 2) IFNAR2, tumor necrosis factor receptor superfamily, member 1A (TNFRSF1A), and tumor necrosis factor receptor superfamily, member 1B (TNFRSF1B), were explored in two groups: the first consisted of severe COVID-19-related patients (familial cases from 58 families, n = 130), and the second group of unrelated severe COVID-19 patients (n = 1045). In each study group, death was evaluated as the outcome.

Results

In non-related patients with severe COVID-19, carriers of GG genotype (rs2289274) in the ATP2B2 gene showed a high-risk probability of non-surviving (OR = 1.43). Survival analysis to 75 days indicates that carriers of GG have a higher risk than GA or AA genotypes (p = 0.0059). The haplotype GG (rs2289273-rs2289274) in ATP2B2 was found to be associated with a high risk of death in severe non-related COVID-19 patients. No significant associations were found between severe COVID-19-related patients and SNVs in ATP2B2, TMPRSS2, DOCK2, IFNAR2, TNFRSF1A, or TNFRSF1B.

Conclusions

Unrelated patients with severe COVID-19 that carry the GG genotype (rs2289274) in ATP2B2 showed a high death risk. Survival analysis to 75 days indicates that carriers of GG have a higher risk of non-survival compared to GA or AA genotypes.

Single nucleotide variants in the CCL2, OAS1 and DPP9 genes and their association with the severity of COVID-19 in an Ecuadorian population

COVID-19 has a broad clinical spectrum, ranging from asymptomatic-mild form to severe phenotype. The severity of COVID-19 is a complex trait influenced by various genetic and environmental factors. Ethnic differences have been observed in relation to COVID-19 severity during the pandemic. It is currently unknown whether genetic variations may contribute to the increased risk of severity observed in Latin-American individuals The aim of this study is to investigate the potential correlation between gene variants at CCL2, OAS1, and DPP9 genes and the severity of COVID-19 in a population from Quito, Ecuador. This observational case-control study was conducted at the Carrera de Biologia from the Universidad Central del Ecuador and the Hospital Quito Sur of the Instituto Ecuatoriano de Seguridad Social (Quito-SUR-IESS), Quito, Ecuador. Genotyping for gene variants at rs1024611 (A>G), rs10774671 (A>G), and rs10406145 (G>C) of CCL2, OAS1, and DPP9 genes was performed on 100 COVID-19 patients (43 with severe form and 57 asymptomatic-mild) using RFLP-PCR. The genotype distribution of all SNVs throughout the entire sample of 100 individuals showed Hardy Weinberg equilibrium (P=0.53, 0.35, and 0.4 for CCL2, OAS1, and DPP9, respectively). The HWE test did not find any statistically significant difference in genotype distribution between the study and control groups for any of the three SNVs. The multivariable logistic regression analysis showed that individuals with the GG of the CCL2 rs1024611 gene variant had an increased association with the severe COVID-19 phenotype in a recessive model (P = 0.0003, OR = 6.43, 95% CI 2.19-18.89) and for the OAS1 rs10774671 gene variant, the log-additive model showed a significant association with the severe phenotype of COVID-19 (P=0.0084, OR=3.85, 95% CI 1.33-11.12). Analysis of haplotype frequencies revealed that the coexistence of GAG at CCL2, OAS1, and DPP9 variants, respectively, in the same individual increased the presence of the severe COVID-19 phenotype (OR=2.273, 95% CI: 1.271-4.068, P=0.005305). The findings of the current study suggests that the ethnic background affects the allele and genotype frequencies of genes associated with the severity of COVID-19. The experience with COVID-19 has provided an opportunity to identify an ethnicity-based approach to recognize genetically high-risk individuals in different populations for emerging diseases.

Next-generation sequencing of host genetics risk factors associated with COVID-19 severity and long-COVID in Colombian population

Coronavirus disease 2019 (COVID-19) was considered a major public health burden worldwide. Multiple studies have shown that susceptibility to severe infections and the development of long-term symptoms is significantly influenced by viral and host factors. These findings have highlighted the potential of host genetic markers to identify high-risk individuals and develop target interventions to reduce morbimortality. Despite its importance, genetic host factors remain largely understudied in Latin-American populations. Using a case-control design and a custom next-generation sequencing (NGS) panel encompassing 81 genetic variants and 74 genes previously associated with COVID-19 severity and long-COVID, we analyzed 56 individuals with asymptomatic or mild COVID-19 and 56 severe and critical cases. In agreement with previous studies, our results support the association between several clinical variables, including male sex, obesity and common symptoms like cough and dyspnea, and severe COVID-19. Remarkably, thirteen genetic variants showed an association with COVID-19 severity. Among these variants, rs11385942 (p < 0.01; OR = 10.88; 95% CI = 1.36-86.51) located in the LZTFL1 gene, and rs35775079 (p = 0.02; OR = 8.53; 95% CI = 1.05-69.45) located in CCR3 showed the strongest associations. Various respiratory and systemic symptoms, along with the rs8178521 variant (p < 0.01; OR = 2.51; 95% CI = 1.27-4.94) in the IL10RB gene, were significantly associated with the presence of long-COVID. The results of the predictive model comparison showed that the mixed model, which incorporates genetic and non-genetic variables, outperforms clinical and genetic models. To our knowledge, this is the first study in Colombia and Latin-America proposing a predictive model for COVID-19 severity and long-COVID based on genomic analysis. Our study highlights the usefulness of genomic approaches to studying host genetic risk factors in specific populations. The methodology used allowed us to validate several genetic variants previously associated with COVID-19 severity and long-COVID. Finally, the integrated model illustrates the importance of considering genetic factors in precision medicine of infectious diseases.

Canadian COVID-19 host genetics cohort replicates known severity associations

The HostSeq initiative recruited 10,059 Canadians infected with SARS-CoV-2 between March 2020 and March 2023, obtained clinical information on their disease experience and whole genome sequenced (WGS) their DNA. We analyzed the WGS data for genetic contributors to severe COVID-19 (considering 3,499 hospitalized cases and 4,975 non-hospitalized after quality control). We investigated the evidence for replication of loci reported by the International Host Genetics Initiative (HGI); analyzed the X chromosome; conducted rare variant gene-based analysis and polygenic risk score testing. Population stratification was adjusted for using meta-analysis across ancestry groups. We replicated two loci identified by the HGI for COVID-19 severity: the LZTFL1/SLC6A20 locus on chromosome 3 and the FOXP4 locus on chromosome 6 (the latter with a variant significant at P < 5E-8). We found novel significant associations with MRAS and WDR89 in gene-based analyses, and constructed a polygenic risk score that explained 1.01% of the variance in severe COVID-19. This study provides independent evidence confirming the robustness of previously identified COVID-19 severity loci by the HGI and identifies novel genes for further investigation.

Host genetic variants associated with COVID-19 reconsidered in a Slovak cohort

We present the results of an association study involving hospitalized coronavirus disease 2019 (COVID-19) patients with a clinical background during the 3rd pandemic wave of COVID-19 in Slovakia. Seventeen single nucleotide variants (SNVs) in the eleven most relevant genes, according to the COVID-19 Host Genetics Initiative, were investigated. Our study confirms the validity of the influence of LZTFL1 and 2'-5'-oligoadenylate synthetase (OAS)1/OAS3 genetic variants on the severity of COVID-19. For two LZTFL1 SNVs in complete linkage disequilibrium, rs17713054 and rs73064425, the odds ratios of baseline allelic associations and logistic regressions (LR) adjusted for age and sex ranged in the four tested designs from 2.04 to 2.41 and from 2.05 to 3.98, respectively. The OAS1/OAS3 haplotype 'gttg' carrying a functional allele G of splice-acceptor variant rs10774671 manifested its protective function in the Delta pandemic wave. Significant baseline allelic associations of two DPP9 variants in all tested designs and two IFNAR2 variants in the Omicron pandemic wave were not confirmed by adjusted LR. Nevertheless, adjusted LR showed significant associations of NOTCH4 rs3131294 and TYK2 rs2304256 variants with severity of COVID-19. Hospitalized patients' reported comorbidities were not correlated with genetic variants, except for obesity, smoking (IFNAR2), and hypertension (NOTCH4). The results of our study suggest that host genetic variations have an impact on the severity and duration of acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Considering the differences in allelic associations between pandemic waves, they support the hypothesis that every new SARS-CoV-2 variant may modify the host immune response by reconfiguring involved pathways.

Host genetics and the profile of COVID-19 in indigenous people from the Brazilian Amazon: A pilot study with variants of the ACE1, ACE2 and TMPRSS2 genes

This pilot study aimed to investigate genetic factors that may have contributed to the milder clinical outcomes of COVID-19 in Brazilian indigenous populations. 263 Indigenous from the Araweté, Kararaô, Parakanã, Xikrin do Bacajá, Kayapó and Munduruku peoples were analyzed, 55.2% women, ages ranging from 10 to 95 years (average 49.5 ± 20.7). Variants in genes involved in the entry of SARS-CoV-2 into the host cell (ACE1 rs1799752 I/D, ACE2 rs2285666 C/T, ACE2 rs73635825 A/G and TMPRSS2 rs123297605 C/T), were genotyped in indigenous peoples from the Brazilian Amazon, treated during the SARS-CoV-2 pandemic between 2020 and 2021. The distribution of genotypes did not show any association with the presence or absence of IgG antibodies. Additionally, the influence of genetic variations on the severity of the disease was not examined extensively because a significant number of indigenous individuals experienced the disease with either mild symptoms or no symptoms. It is worth noting that the frequencies of risk alleles were found to be lower in Indigenous populations compared to both continental populations and Brazilians. Indigenous Brazilian Amazon people exhibited an ethnic-specific genetic profile that may be associated with a milder disease, which could explain the unexpected response they demonstrated to COVID-19, being less impacted than Brazilians.

Integration of human organoids single-cell transcriptomic profiles and human genetics repurposes critical cell type-specific drug targets for severe COVID-19

Human organoids recapitulate the cell type diversity and function of their primary organs holding tremendous potentials for basic and translational research. Advances in single-cell RNA sequencing (scRNA-seq) technology and genome-wide association study (GWAS) have accelerated the biological and therapeutic interpretation of trait-relevant cell types or states. Here, we constructed a computational framework to integrate atlas-level organoid scRNA-seq data, GWAS summary statistics, expression quantitative trait loci, and gene-drug interaction data for distinguishing critical cell populations and drug targets relevant to coronavirus disease 2019 (COVID-19) severity. We found that 39 cell types across eight kinds of organoids were significantly associated with COVID-19 outcomes. Notably, subset of lung mesenchymal stem cells increased proximity with fibroblasts predisposed to repair COVID-19-damaged lung tissue. Brain endothelial cell subset exhibited significant associations with severe COVID-19, and this cell subset showed a notable increase in cell-to-cell interactions with other brain cell types, including microglia. We repurposed 33 druggable genes, including IFNAR2, TYK2, and VIPR2, and their interacting drugs for COVID-19 in a cell-type-specific manner. Overall, our results showcase that host genetic determinants have cellular-specific contribution to COVID-19 severity, and identification of cell type-specific drug targets may facilitate to develop effective therapeutics for treating severe COVID-19 and its complications.

ABO blood group-related mechanism of infection of SARS-CoV-2: an overview of systematic reviews

Among the host genetic factors playing a role in the susceptibility to infectious diseases, the ABO blood group system is of utmost importance. Following the first reports in early 2020, the association between ABO blood groups and SARS-CoV-2 infection or COVID-19 severity has been thoroughly investigated. The aim of this narrative review is to provide an overview of systematic reviews regarding the link between ABO blood groups and such risks. The possible molecular mechanisms underlying these associations will also be discussed. ABO blood group has a robust association with susceptibility to infection but not with disease severity, and studies on long COVID anre still missing.Prov.

Priority index for critical Covid-19 identifies clinically actionable targets and drugs

While genome-wide studies have identified genomic loci in hosts associated with life-threatening Covid-19 (critical Covid-19), the challenge of resolving these loci hinders further identification of clinically actionable targets and drugs. Building upon our previous success, we here present a priority index solution designed to address this challenge, generating the target and drug resource that consists of two indexes: the target index and the drug index. The primary purpose of the target index is to identify clinically actionable targets by prioritising genes associated with Covid-19. We illustrate the validity of the target index by demonstrating its ability to identify pre-existing Covid-19 phase-III drug targets, with the majority of these targets being found at the leading prioritisation (leading targets). These leading targets have their evolutionary origins in Amniota ('four-leg vertebrates') and are predominantly involved in cytokine-cytokine receptor interactions and JAK-STAT signaling. The drug index highlights opportunities for repurposing clinically approved JAK-STAT inhibitors, either individually or in combination. This proposed strategic focus on the JAK-STAT pathway is supported by the active pursuit of therapeutic agents targeting this pathway in ongoing phase-II/III clinical trials for Covid-19.

A linear weighted combination of polygenic scores for a broad range of traits improves prediction of coronary heart disease

Polygenic scores (PGS) for coronary heart disease (CHD) are constructed using GWAS summary statistics for CHD. However, pleiotropy is pervasive in biology and disease-associated variants often share etiologic pathways with multiple traits. Therefore, incorporating GWAS summary statistics of additional traits could improve the performance of PGS for CHD. Using lasso regression models, we developed two multi-PGS for CHD: 1) multiPGSCHD, utilizing GWAS summary statistics for CHD, its risk factors, and other ASCVD as training data and the UK Biobank for tuning, and 2) extendedPGSCHD, using existing PGS for a broader range of traits in the PGS Catalog as training data and the Atherosclerosis Risk in Communities Study (ARIC) cohort for tuning. We evaluated the performance of multiPGSCHD and extendedPGSCHD in the Mayo Clinic Biobank, an independent cohort of 43,578 adults of European ancestry which included 4,479 CHD cases and 39,099 controls. In the Mayo Clinic Biobank, a 1 SD increase in multiPGSCHD and extendedPGSCHD was associated with a 1.66-fold (95% CI: 1.60-1.71) and 1.70-fold (95% CI: 1.64-1.76) increased odds of CHD, respectively, in models that included age, sex, and 10 PCs, whereas an already published PGS for CHD (CHD_PRSCS) increased the odds by 1.50 (95% CI: 1.45-1.56). In the highest deciles of extendedPGSCHD, multiPGSCHD, and CHD_PRSCS, 18.4%, 17.5%, and 16.3% of patients had CHD, respectively.

Genetic justification of COVID-19 patient outcomes using DERGA, a novel data ensemble refinement greedy algorithm

Complement inhibition has shown promise in various disorders, including COVID-19. A prediction tool including complement genetic variants is vital. This study aims to identify crucial complement-related variants and determine an optimal pattern for accurate disease outcome prediction. Genetic data from 204 COVID-19 patients hospitalized between April 2020 and April 2021 at three referral centres were analysed using an artificial intelligence-based algorithm to predict disease outcome (ICU vs. non-ICU admission). A recently introduced alpha-index identified the 30 most predictive genetic variants. DERGA algorithm, which employs multiple classification algorithms, determined the optimal pattern of these key variants, resulting in 97% accuracy for predicting disease outcome. Individual variations ranged from 40 to 161 variants per patient, with 977 total variants detected. This study demonstrates the utility of alpha-index in ranking a substantial number of genetic variants. This approach enables the implementation of well-established classification algorithms that effectively determine the relevance of genetic variants in predicting outcomes with high accuracy.

Genetic characteristics involved in COVID-19 severity. The CARGENCORS case-control study and meta-analysis

Pre-existing coronary artery disease (CAD), and thrombotic, inflammatory, or virus infectivity response phenomena have been associated with COVID-19 disease severity. However, the association of candidate single nucleotide variants (SNVs) related to mechanisms of COVID-19 complications has been seldom analysed. Our aim was to test and validate the effect of candidate SNVs on COVID-19 severity. CARGENCORS (CARdiovascular GENetic risk score for Risk Stratification of patients positive for SARS-CoV-2 [COVID-19] virus) is an age- and sex-matched case-control study with 818 COVID-19 cases hospitalized with hypoxemia, and 1636 controls with COVID-19 treated at home. The association between severity and SNVs related to CAD (n = 32), inflammation (n = 19), thrombosis (n = 14), virus infectivity (n = 11), and two published to be related to COVID-19 severity was tested with adjusted logistic regression models. Two external independent cohorts were used for meta-analysis (SCOURGE and UK Biobank). After adjustment for potential confounders, 14 new SNVs were associated with COVID-19 severity in the CARGENCORS Study. These SNVs were related to CAD (n = 10), thrombosis (n = 2), and inflammation (n = 2). We also confirmed eight SNVs previously related to severe COVID-19 and virus infectivity. The meta-analysis showed five SNVs associated with severe COVID-19 in adjusted analyses (rs11385942, rs1561198, rs6632704, rs6629110, and rs12329760). We identified 14 novel SNVs and confirmed eight previously related to COVID-19 severity in the CARGENCORS data. In the meta-analysis, five SNVs were significantly associated to COVID-19 severity, one of them previously related to CAD.

Type 2 diabetes and its genetic susceptibility are associated with increased severity and mortality of COVID-19 in UK Biobank

Type 2 diabetes (T2D) is known as one of the important risk factors for the severity and mortality of COVID-19. Here, we evaluate the impact of T2D and its genetic susceptibility on the severity and mortality of COVID-19, using 459,119 individuals in UK Biobank. Utilizing the polygenic risk scores (PRS) for T2D, we identified a significant association between T2D or T2D PRS, and COVID-19 severity. We further discovered the efficacy of vaccination and the pivotal role of T2D-related genetics in the pathogenesis of severe COVID-19. Moreover, we found that individuals with T2D or those in the high T2D PRS group had a significantly increased mortality rate. We also observed that the mortality rate for SARS-CoV-2-infected patients was approximately 2 to 7 times higher than for those not infected, depending on the time of infection. These findings emphasize the potential of T2D PRS in estimating the severity and mortality of COVID-19.

Evaluation of Genetic or Cellular Impairments in Type I IFN Immunity in a Cohort of Young Adults with Critical COVID-19

Several genetic and immunological risk factors for severe COVID-19 have been identified, with monogenic conditions relating to 13 genes of type I interferon (IFN) immunity proposed to explain 4.8% of critical cases. However, previous cohorts have been clinically heterogeneous and were not subjected to thorough genetic and immunological analyses. We therefore aimed to systematically investigate the prevalence of rare genetic variants causing inborn errors of immunity (IEI) and functionally interrogate the type I IFN pathway in young adults that suffered from critical COVID-19 yet lacked comorbidities. We selected and clinically characterized a cohort of 38 previously healthy individuals under 50 years of age who were treated in intensive care units due to critical COVID-19. Blood samples were collected after convalescence. Two patients had IFN-α autoantibodies. Genome sequencing revealed very rare variants in the type I IFN pathway in 31.6% of the patients, which was similar to controls. Analyses of cryopreserved leukocytes did not indicate any defect in plasmacytoid dendritic cell sensing of TLR7 and TLR9 agonists in patients carrying variants in these pathways. However, lymphocyte STAT phosphorylation and protein upregulation upon IFN-α stimulation revealed three possible cases of impaired type I IFN signaling in carriers of rare variants. Together, our results suggest a strategy of functional screening followed by genome analyses and biochemical validation to uncover undiagnosed causes of critical COVID-19.

Human genetic determinants of COVID-19 in Brazil: challenges and future plans

COVID-19 pandemic represented a worldwide major challenge in different areas, and efforts undertaken by the scientific community led to the understanding of some of the genetic determinants that influence the different COVID-19 outcomes. In this paper, we review the studies about the role of human genetics in COVID-19 severity and how Brazilian studies also contributed to those findings. Rare variants in genes related to Inborn Errors of Immunity (IEI) in the type I interferons pathway, and its phenocopies, have been described as being causative of severe outcomes. IEI and its phenocopies are present in Brazil, not only in COVID-19 patients, but also in autoimmune conditions and severe reactions to yellow fever vaccine. In addition, studies focusing on common variants and GWAS studies encompassing worldwide patients have found several loci associated with COVID-19 severity. A GWAS study including only Brazilian COVID-19 patients identified a new locus 1q32.1 associated with COVID-19 severity. Thus, more comprehensive studies considering the Brazilian genomic diversity should be performed, since they can help to reveal not only what are the genetic determinants that contribute to the different outcomes for COVID-19 in the Brazilian population, but in the understanding of human genetics in different health conditions.

Interaction Between Genetic Susceptibility and COVID-19 Pathogenesis in Pediatric Multisystem Inflammatory Disorders: The Role of Immune Responses

Numerous studies have highlighted the emergence of coronavirus disease (COVID-19) symptoms reminiscent of Kawasaki disease in children, including fever, heightened multisystem inflammation, and multiorgan involvement, posing a life-threatening complication. Consequently, extensive research endeavors in pediatric have aimed to elucidate the intricate relationship between COVID-19 infection and the immune system. COVID-19 profoundly impacts immune cells, culminating in a cytokine storm that particularly inflicts damage on the pulmonary system. The gravity and vulnerability to COVID-19 are closely intertwined with the vigor of the immune response. In this context, the human leukocyte antigen (HLA) molecule assumes pivotal significance in shaping immune responses. Genetic scrutiny of HLA has unveiled the presence of at least one deleterious allele in children afflicted with multisystem inflammatory syndrome in children (MIS-C). Furthermore, research has demonstrated that COVID-19 exploits the angiotensin-converting enzyme 2 (ACE-2) receptor, transmembrane serine protease type 2, and various other genes to gain entry into host cells, with individuals harboring ACE-2 polymorphisms being at higher risk. Pediatric studies have employed diverse genetic methodologies, such as genome-wide association studies (GWAS) and whole exome sequencing, to scrutinize target genes. These investigations have pinpointed two specific genomic loci linked to the severity and susceptibility of COVID-19, with the HLA locus emerging as a notable risk factor. In this comprehensive review article, we endeavor to assess the available evidence and consolidate data, offering insights into current clinical practices and delineating avenues for future research. Our objective is to advance early diagnosis, stabilization, and appropriate management strategies to mitigate genetic susceptibility's impact on the incidence of COVID-19 in pediatric patients with multisystem inflammation.

Cytokines as drivers: Unraveling the mechanisms of epithelial-mesenchymal transition in COVID-19 lung fibrosis

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), like other viruses, can induce proliferation of myofibroblasts and even lead to fibrosis in the lung. Epithelial-mesenchymal transition (EMT) is thought to play an essential role in the pathogenesis of Coronavirus disease 19 (COVID-19). EMT is originally a critical process that regulates the development of different tissues in the embryo, but in inflammatory situations, EMT tries to be activated again to control inflammation or even heal inflammatory damage. However, in pathological situations, such as chronic viral infections (e.g., COVID-19) or pulmonary fibrosis initiation, this benign healing transforms into sinister nature, pushing the lung into the fibrotic process. Notably, the cytokines released by inflammatory cells and the chronic inflammatory microenvironment shared by fibrotic cells promote each other as critical factors in the induction of pathological EMT. In the induction of SARS-CoV-2 virus, cytokines are an essential mediator of EMT transformation, and a summary of whether COVID-19 patients, during the infection phase, have many persistent inflammatory mediators (cytokines) that are a causative factor of EMT has not yet appeared. The following common signaling drivers, including Transforming growth factor beta (TGF-β), cytokines, Notch signaling pathway, Wnt and hypoxia signaling pathways, drive the regulation of EMT. In this review, we will focus on 3 key EMT signaling pathways: TGF-β, Leucine zipper transcription factor like 1 (LZTFL1) and the common interleukin family expressed in the lung. TGF-β-induced SNAIL and LZTFL1 were identified as regulatory EMT in COVID-19. For cytokines, the interleukin family is a common inducer of EMT and plays an essential role in the formation of the microenvironment of fibrosis. We sought to demonstrate that cytokines act as "communicators" and build the "microenvironment" of fibrosis together with EMT as a "bridge" to induce EMT in fibrosis. The mechanisms utilized by these two pathways could serve as templates for other mesenchymal transformations and provide new potential therapeutic targets.

Sex and gender affect immune aging

The proposed review aims to elucidate the intricate interplay between biological factors (sex differences) and socially constructed factors (gender differences) in the context of immune aging. While the influence of biological differences between men and women on various aspects of immune responses has long been recognized, it is crucial to acknowledge that gender, encompassing the social and cultural roles and expectations associated with being male or female, also significantly shapes these processes. Gender can either accelerate immune aging or promote longevity. By recognizing the impact of both biological and social factors, this work seeks to offer a comprehensive understanding of why men and women may experience divergent trajectories in immune aging and varying outcomes in terms of longevity. Discrepancies in perceived roles of the sexes, both within families and at work, contribute to differing patterns of antigen exposure. Additionally, variations in micronutrient intake and access to preventive healthcare facilities may exist. Health promotion knowledge often correlates with educational attainment, which is unequally represented between males and females in many cultures and across generations in the Western world. In countries without a universal healthcare system, access to healthcare relies on family prioritization strategies to cope with economic constraints, potentially limiting access to specific treatments and affecting immune responses negatively. As a result, both biological factors and social and behavioral factors associated with gender contribute to disparities in immune responses, susceptibility to infections, autoimmune diseases, and vaccine responses among older individuals. However, as demonstrated by the COVID-19 pandemic, older females exhibit greater resilience to infections than older males. Given the crucial role of the immune system in achieving longevity, it is not surprising that women live longer than men, and the number of female centenarians surpasses that of male centenarians.

Public Health Response Measures for COVID-19 in Kazakhstan

The article describes measures developed to counter the spread of coronavirus infection in the Republic of Kazakhstan. The first cases of coronavirus disease 2019 (COVID-19) in Kazakhstan were detected on March 13, 2020, among people who arrived from Germany. After declaring the state of emergency in the country, the Ministry of Healthcare of the Republic of Kazakhstan began to formulate and implement a comprehensive package of measures aimed at slowing down and stopping the transmission of infection, preventing outbreaks, ensuring optimal care for all patients, especially the seriously ill, minimizing the negative impact of the pandemic on health systems, social services, and economic activities. Developed set of restrictive measures was approved by the Country Office of Word Health Organization (WHO) in Kazakhstan, being later adapted by the European Union (EU) countries and applied in Kyrgyzstan. In addition, article identifies Kazakhstan's experience in creating epidemiological surveillance systems, studying virus mutations, and the clinical aspects of dealing with it to combat the infection. It also indicates the impact of the epidemic on health-care workers and the development of measures to protect them, strengthening infection prevention, and control in medical organizations.

SCARF Genes in COVID-19 and Kidney Disease: A Path to Comorbidity-Specific Therapies

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) causes coronavirus disease 2019 (COVID-19), which has killed ~7 million persons worldwide. Chronic kidney disease (CKD) is the most common risk factor for severe COVID-19 and one that most increases the risk of COVID-19-related death. Moreover, CKD increases the risk of acute kidney injury (AKI), and COVID-19 patients with AKI are at an increased risk of death. However, the molecular basis underlying this risk has not been well characterized. CKD patients are at increased risk of death from multiple infections, to which immune deficiency in non-specific host defenses may contribute. However, COVID-19-associated AKI has specific molecular features and CKD modulates the local (kidney) and systemic (lung, aorta) expression of host genes encoding coronavirus-associated receptors and factors (SCARFs), which SARS-CoV-2 hijacks to enter cells and replicate. We review the interaction between kidney disease and COVID-19, including the over 200 host genes that may influence the severity of COVID-19, and provide evidence suggesting that kidney disease may modulate the expression of SCARF genes and other key host genes involved in an effective adaptive defense against coronaviruses. Given the poor response of certain CKD populations (e.g., kidney transplant recipients) to SARS-CoV-2 vaccines and their suboptimal outcomes when infected, we propose a research agenda focusing on CKD to develop the concept of comorbidity-specific targeted therapeutic approaches to SARS-CoV-2 infection or to future coronavirus infections.

Participation of Single-Nucleotide Variants in IFNAR1 and IFNAR2 in the Immune Response against SARS-CoV-2 Infection: A Systematic Review

Host genetic factors significantly influence susceptibility to SARS-CoV-2 infection and COVID-19 severity. Among these genetic factors are single-nucleotide variants (SNVs). IFNAR2 and IFNAR1 genes have been associated with severe COVID-19 in populations from the United Kingdom, Africa, and Latin America. IFNAR1 and IFNAR2 are subunits forming the type I interferon receptor (IFNAR). SNVs in the IFNAR genes impact protein function, affecting antiviral response and disease phenotypes. This systematic review aimed to describe IFNAR1 and IFNAR2 variants associated with COVID-19 susceptibility and severity. Accordingly, the current review focused on IFNAR1 and IFNAR2 studies published between January 2021 and February 2023, utilizing the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) protocol. The electronic search was conducted in PubMed databases using Boolean operators and inclusion and exclusion criteria. Of the 170 literature pieces, 11 studies were included. We include case reports of rare SNVs, defined by minor allele frequency (MAF) < 1%, and genome-wide associated studies (GWAS). Variants in IFNAR1 and IFNAR2 could potentially be new targets for therapies that limit the infection and the resulting inflammation by SARS-CoV-2 infection.

Integration of risk variants from GWAS with SARS-CoV-2 RNA interactome prioritizes FUBP1 and RAB2A as risk genes for COVID-19

The role of host genetic factors in COVID-19 outcomes remains unclear despite various genome-wide association studies (GWAS). We annotate all significant variants and those variants in high LD (R2 > 0.8) from the COVID-19 host genetics initiative (HGI) and identify risk genes by recognizing genes intolerant nonsynonymous mutations in coding regions and genes associated with cis-expression quantitative trait loci (cis-eQTL) in non-coding regions. These genes are enriched in the immune response pathway and viral life cycle. It has been found that host RNA binding proteins (RBPs) participate in different phases of the SARS-CoV-2 life cycle. We collect 503 RBPs that interact with SARS-CoV-2 RNA concluded from in vitro studies. Combining risk genes from the HGI with RBPs, we identify two COVID-19 risk loci that regulate the expression levels of FUBP1 and RAB2A in the lung. Due to the risk allele, COVID-19 patients show downregulation of FUBP1 and upregulation of RAB2A. Using single-cell RNA sequencing data, we show that FUBP1 and RAB2A are expressed in SARS-CoV-2-infected upper respiratory tract epithelial cells. We further identify NC_000001.11:g.77984833C>A and NC_000008.11:g.60559280T>C as functional variants by surveying allele-specific transcription factor sites and cis-regulatory elements and performing motif analysis. To sum up, our research, which associates human genetics with expression levels of RBPs, identifies FUBP1 and RAB2A as two risk genes for COVID-19 and reveals the anti-viral role of FUBP1 and the pro-viral role of RAB2A in the infection of SARS-CoV-2.

SSLpheno: a self-supervised learning approach for gene-phenotype association prediction using protein-protein interactions and gene ontology data

MOTIVATION

Medical genomics faces significant challenges in interpreting disease phenotype and genetic heterogeneity. Despite the establishment of standardized disease phenotype databases, computational methods for predicting gene-phenotype associations still suffer from imbalanced category distribution and a lack of labeled data in small categories.

RESULTS

To address the problem of labeled-data scarcity, we propose a self-supervised learning strategy for gene-phenotype association prediction, called SSLpheno. Our approach utilizes an attributed network that integrates protein-protein interactions and gene ontology data. We apply a Laplacian-based filter to ensure feature smoothness and use self-supervised training to optimize node feature representation. Specifically, we calculate the cosine similarity of feature vectors and select positive and negative sample nodes for reconstruction training labels. We employ a deep neural network for multi-label classification of phenotypes in the downstream task. Our experimental results demonstrate that SSLpheno outperforms state-of-the-art methods, especially in categories with fewer annotations. Moreover, our case studies illustrate the potential of SSLpheno as an effective prescreening tool for gene-phenotype association identification.

AVAILABILITY AND IMPLEMENTATION

https://github.com/bixuehua/SSLpheno.

The Relationship between COVID-19 Severity in Children and Immunoregulatory Gene Polymorphism

Coronavirus disease (COVID-19) and its outcomes remain one of the most challenging problems today. COVID-19 in children could be asymptomatic, but can result in a fatal outcome; therefore, predictions of the disease severity are important. The goal was to investigate the human genetic factors that could be associated with COVID-19 severity in children. Single-nucleotide polymorphisms of the following genes were studied: ACE2 (rs2074192), IFNAR2 (rs2236757), TYK2 (rs2304256), OAS1 (rs10774671), OAS3 (rs10735079), CD40 (rs4813003), FCGR2A (rs1801274) and CASP3 (rs113420705). In the case-control study were 30 children with mild or moderate course of the disease; 30 with severe COVID-19 symptoms and multisystem inflammatory syndrome in children (MIS-C) and 15 who were healthy, and who did not have SARS-CoV-2 (PCR negative, Ig G negative). The study revealed that ACE2 rs2074192 (allele T), IFNAR2 rs2236757 (allele A), OAS1 rs10774671 (allele A), CD40 rs4813003 (allele C), CASP3 rs113420705 (allele C) and male sex contribute to severe COVID-19 course and MIS-C in 85.6% of cases. The World Health Organization reported that new SARS-CoV-2 variants may cause previously unseen symptoms in children. Although the study has limitations due to cohort size, the findings can help provide a better understanding of SARS-CoV-2 infection and proactive pediatric patient management.

A computational framework for improving genetic variants identification from 5,061 sheep sequencing data

BACKGROUND

Pan-genomics is a recently emerging strategy that can be utilized to provide a more comprehensive characterization of genetic variation. Joint calling is routinely used to combine identified variants across multiple related samples. However, the improvement of variants identification using the mutual support information from multiple samples remains quite limited for population-scale genotyping.

RESULTS

In this study, we developed a computational framework for joint calling genetic variants from 5,061 sheep by incorporating the sequencing error and optimizing mutual support information from multiple samples' data. The variants were accurately identified from multiple samples by using four steps: (1) Probabilities of variants from two widely used algorithms, GATK and Freebayes, were calculated by Poisson model incorporating base sequencing error potential; (2) The variants with high mapping quality or consistently identified from at least two samples by GATK and Freebayes were used to construct the raw high-confidence identification (rHID) variants database; (3) The high confidence variants identified in single sample were ordered by probability value and controlled by false discovery rate (FDR) using rHID database; (4) To avoid the elimination of potentially true variants from rHID database, the variants that failed FDR were reexamined to rescued potential true variants and ensured high accurate identification variants. The results indicated that the percent of concordant SNPs and Indels from Freebayes and GATK after our new method were significantly improved 12%-32% compared with raw variants and advantageously found low frequency variants of individual sheep involved several traits including nipples number (GPC5), scrapie pathology (PAPSS2), seasonal reproduction and litter size (GRM1), coat color (RAB27A), and lentivirus susceptibility (TMEM154).

CONCLUSION

The new method used the computational strategy to reduce the number of false positives, and simultaneously improve the identification of genetic variants. This strategy did not incur any extra cost by using any additional samples or sequencing data information and advantageously identified rare variants which can be important for practical applications of animal breeding.

MAP3K19 regulatory variation in populations with African ancestry may increase COVID-19 severity

To identify ancestry-linked genetic risk variants associated with COVID-19 hospitalization, we performed an integrative analysis of two genome-wide association studies and resolved four single nucleotide polymorphisms more frequent in COVID-19-hospitalized patients with non-European ancestry. Among them, the COVID-19 risk SNP rs16831827 shows the largest difference in minor allele frequency (MAF) between populations with African and European ancestry and also shows higher MAF in hospitalized COVID-19 patients among cohorts of mixed ancestry (odds ratio [OR] = 1.20, 95% CI: 1.10-1.30) and entirely African ancestry (OR = 1.30, 95% CI: 1.02-1.67). rs16831827 is an expression quantitative trait locus of MAP3K19. MAP3K19 expression is induced during ciliogenesis and most abundant in ciliated tissues including lungs. Single-cell RNA sequencing analyses revealed that MAP3K19 is highly expressed in multiple ciliated cell types. As rs16831827∗T is associated with reduced MAP3K19 expression, it may increase the risk of severe COVID-19 by reducing MAP3K19 expression.

A cell-based assay for rapid assessment of ACE2 catalytic function

Angiotensin-converting enzyme II (ACE2) is a monocarboxypeptidase expressed throughout multiple tissues and its catalysis of bioactive peptides regulates the renin-angiotensin system mediating blood pressure homeostasis. ACE2 is implicated in a variety of diseases, including obesity, diabetes, and cardiovascular diseases, and is the obligate entry receptor for SARS-CoV-2 infection. Disease-associated genetic variants of ACE2 are increasingly being identified but are poorly characterized. To aid this problem, we introduce a fluorometric cell-based assay for evaluating surface-expressed ACE2 catalytic activity that preserves the native glycosylation of the host environment and is amenable to high-throughput analysis of ACE2 variants in multi-well plates. We demonstrate sensitivity to detecting catalysis of the key ACE2 substrates, Angiotensin II, Apelin-13, and des-Arg9-bradykinin, and impact of a catalytically-deficient ACE2 variant. Normalizing catalytic measures to surface ACE2 expression accounts for variability in ACE2 variant transfection, surface delivery or stability. This assay provides a convenient and powerful approach for investigating the catalytic characteristics of ACE2 variants involved in cardiovascular peptide cascades and homeostasis of multiple organs.

The impact of immunoglobulin G N-glycosylation level on COVID-19 outcome: evidence from a Mendelian randomization study

Background

The coronavirus disease 2019 (COVID-19) pandemic has exerted a profound influence on humans. Increasing evidence shows that immune response is crucial in influencing the risk of infection and disease severity. Observational studies suggest an association between COVID-19 and immunoglobulin G (IgG) N-glycosylation traits, but the causal relevance of these traits in COVID-19 susceptibility and severity remains controversial.

Methods

We conducted a two-sample Mendelian randomization (MR) analysis to explore the causal association between 77 IgG N-glycosylation traits and COVID-19 susceptibility, hospitalization, and severity using summary-level data from genome-wide association studies (GWAS) and applying multiple methods including inverse-variance weighting (IVW), MR Egger, and weighted median. We also used Cochran's Q statistic and leave-one-out analysis to detect heterogeneity across each single nucleotide polymorphism (SNP). Additionally, we used the MR-Egger intercept test, MR-PRESSO global test, and PhenoScanner tool to detect and remove SNPs with horizontal pleiotropy and to ensure the reliability of our results.

Results

We found significant causal associations between genetically predicted IgG N-glycosylation traits and COVID-19 susceptibility, hospitalization, and severity. Specifically, we observed reduced risk of COVID-19 with the genetically predicted increased IgG N-glycan trait IGP45 (OR = 0.95, 95% CI = 0.92-0.98; FDR = 0.019). IGP22 and IGP30 were associated with a higher risk of COVID-19 hospitalization and severity. Two (IGP2 and IGP77) and five (IGP10, IGP14, IGP34, IGP36, and IGP50) IgG N-glycosylation traits were causally associated with a decreased risk of COVID-19 hospitalization and severity, respectively. Sensitivity analyses did not identify any horizontal pleiotropy.

Conclusions

Our study provides evidence that genetically elevated IgG N-glycosylation traits may have a causal effect on diverse COVID-19 outcomes. Our findings have potential implications for developing targeted interventions to improve COVID-19 outcomes by modulating IgG N-glycosylation levels.

Human Genomics of COVID-19 Pneumonia: Contributions of Rare and Common Variants

SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) infection is silent or benign in most infected individuals, but causes hypoxemic COVID-19 pneumonia in about 10% of cases. We review studies of the human genetics of life-threatening COVID-19 pneumonia, focusing on both rare and common variants. Large-scale genome-wide association studies have identified more than 20 common loci robustly associated with COVID-19 pneumonia with modest effect sizes, some implicating genes expressed in the lungs or leukocytes. The most robust association, on chromosome 3, concerns a haplotype inherited from Neanderthals. Sequencing studies focusing on rare variants with a strong effect have been particularly successful, identifying inborn errors of type I interferon (IFN) immunity in 1-5% of unvaccinated patients with critical pneumonia, and their autoimmune phenocopy, autoantibodies against type I IFN, in another 15-20% of cases. Our growing understanding of the impact of human genetic variation on immunity to SARS-CoV-2 is enabling health systems to improve protection for individuals and populations.

COVID-19 annual update: a narrative review

Three and a half years after the pandemic outbreak, now that WHO has formally declared that the emergency is over, COVID-19 is still a significant global issue. Here, we focus on recent developments in genetic and genomic research on COVID-19, and we give an outlook on state-of-the-art therapeutical approaches, as the pandemic is gradually transitioning to an endemic situation. The sequencing and characterization of rare alleles in different populations has made it possible to identify numerous genes that affect either susceptibility to COVID-19 or the severity of the disease. These findings provide a beginning to new avenues and pan-ethnic therapeutic approaches, as well as to potential genetic screening protocols. The causative virus, SARS-CoV-2, is still in the spotlight, but novel threatening virus could appear anywhere at any time. Therefore, continued vigilance and further research is warranted. We also note emphatically that to prevent future pandemics and other world-wide health crises, it is imperative to capitalize on what we have learnt from COVID-19: specifically, regarding its origins, the world's response, and insufficient preparedness. This requires unprecedented international collaboration and timely data sharing for the coordination of effective response and the rapid implementation of containment measures.

Integrative analysis of functional genomic screening and clinical data identifies a protective role for spironolactone in severe COVID-19

We demonstrate that integrative analysis of CRISPR screening datasets enables network-based prioritization of prescription drugs modulating viral entry in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) by developing a network-based approach called Rapid proXimity Guidance for Repurposing Investigational Drugs (RxGRID). We use our results to guide a propensity-score-matched, retrospective cohort study of 64,349 COVID-19 patients, showing that a top candidate drug, spironolactone, is associated with improved clinical prognosis, measured by intensive care unit (ICU) admission and mechanical ventilation rates. Finally, we show that spironolactone exerts a dose-dependent inhibitory effect on viral entry in human lung epithelial cells. Our RxGRID method presents a computational framework, implemented as an open-source software package, enabling genomics researchers to identify drugs likely to modulate a molecular phenotype of interest based on high-throughput screening data. Our results, derived from this method and supported by experimental and clinical analysis, add additional supporting evidence for a potential protective role of the potassium-sparing diuretic spironolactone in severe COVID-19.

Associations between polygenic risk score and covid-19 susceptibility and severity across ethnic groups: UK Biobank analysis

BACKGROUND

COVID-19 manifests with huge heterogeneity in susceptibility and severity outcomes. UK Black Asian and Minority Ethnic (BAME) groups have demonstrated disproportionate burdens. Some variability remains unexplained, suggesting potential genetic contribution. Polygenic Risk Scores (PRS) can determine genetic predisposition to disease based on Single Nucleotide Polymorphisms (SNPs) within the genome. COVID-19 PRS analyses within non-European samples are extremely limited. We applied a multi-ethnic PRS to a UK-based cohort to understand genetic contribution to COVID-19 variability.

METHODS

We constructed two PRS for susceptibility and severity outcomes based on leading risk-variants from the COVID-19 Host Genetics Initiative. Scores were applied to 447,382 participants from the UK-Biobank. Associations with COVID-19 outcomes were assessed using binary logistic regression and discriminative power was validated using incremental area under receiver operating curve (ΔAUC). Variance explained was compared between ethnic groups via incremental pseudo-R2 (ΔR2).

RESULTS

Compared to those at low genetic risk, those at high risk had a significantly greater risk of severe COVID-19 for White (odds ratio [OR] 1.57, 95% confidence interval [CI] 1.42-1.74), Asian (OR 2.88, 95% CI 1.63-5.09) and Black (OR 1.98, 95% CI 1.11-3.53) ethnic groups. Severity PRS performed best within Asian (ΔAUC 0.9%, ΔR2 0.98%) and Black (ΔAUC 0.6%, ΔR2 0.61%) cohorts. For susceptibility, higher genetic risk was significantly associated with COVID-19 infection risk for the White cohort (OR 1.31, 95% CI 1.26-1.36), but not for Black or Asian groups.

CONCLUSIONS

Significant associations between PRS and COVID-19 outcomes were elicited, establishing a genetic basis for variability in COVID-19. PRS showed utility in identifying high-risk individuals. The multi-ethnic approach allowed applicability of PRS to diverse populations, with the severity model performing well within Black and Asian cohorts. Further studies with larger sample sizes of non-White samples are required to increase statistical power and better assess impacts within BAME populations.

Comorbidity genetic risk and pathways impact SARS-CoV-2 infection outcomes

Understanding the genetic risk and mechanisms through which SARS-CoV-2 infection outcomes and comorbidities interact to impact acute and long-term sequelae is essential if we are to reduce the ongoing health burdens of the COVID-19 pandemic. Here we use a de novo protein diffusion network analysis coupled with tissue-specific gene regulatory networks, to examine putative mechanisms for associations between SARS-CoV-2 infection outcomes and comorbidities. Our approach identifies a shared genetic aetiology and molecular mechanisms for known and previously unknown comorbidities of SARS-CoV-2 infection outcomes. Additionally, genomic variants, genes and biological pathways that provide putative causal mechanisms connecting inherited risk factors for SARS-CoV-2 infection and coronary artery disease and Parkinson's disease are identified for the first time. Our findings provide an in depth understanding of genetic impacts on traits that collectively alter an individual's predisposition to acute and post-acute SARS-CoV-2 infection outcomes. The existence of complex inter-relationships between the comorbidities we identify raises the possibility of a much greater post-acute burden arising from SARS-CoV-2 infection if this genetic predisposition is realised.

Angiotensin-converting enzyme 2 (ACE2) polymorphisms and susceptibility of severe SARS-CoV-2 in a subset of Pakistani population

Science is digging for the varied presentation of COVID-19 patients exposed to the same risk factors, and medical conditions may be influenced by the presence of polymorphic genetic variants. This study investigated the link between ACE2 gene polymorphisms and the severity of SARS-CoV-2. This cross-sectional study recruited COVID-19 PCR-positive patients by consecutive sampling from Ziauddin Hospital from April to September 2020. DNA was extracted from whole blood, followed by gene amplification and Sanger's sequencing. Most of the patients, 77: 53.8%, were serious. Males were higher (80; 55.9%) with age more than 50 years (106: 74.1%). We found 22 ACE2 SNPs. rs2285666 SNP was most prevalent with 49.2% CC, 45.2% TT, 4.8% CT heterozygosity, and 0.8% AA genotypes. Variants with multiple genotypes were also insignificantly associated with the severity of COVID-19 in the analysis of the dominant model. Only rs2285666 had a significant statistical link with gender (p-value 0.034, OR; 1.438, CI; 1.028-2.011) while rs768883316 with age groups (p-value 0.026, OR; 1.953, CI; 1.085-3.514). Haplotypes ATC of three polymorphisms (rs560997634, rs201159862, and rs751170930) commonly found in 120 (69.77%) and TTTGTAGTTAGTA haplotype consisting of 13 polymorphisms (rs756737634, rs146991645, rs1601703288, rs1927830489, rs1927831624, rs764947941, rs752242172, rs73195521, rs781378335, rs756597390, rs780478736, rs148006212, rs768583671) in 112 (90.32%) had statistically significant association with the severity having p = value 0.029 and 0.001 respectively. Males of old age and diabetics are found to have more severe COVID-19 infection in the current study. We also found that common ACE2 polymorphism rs2285666 influences the susceptibility of acquiring the severe SARS-CoV-2 infection.

Host Genetic Factors, Comorbidities and the Risk of Severe COVID-19

BACKGROUND

Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), was varied in disease symptoms. We aim to explore the effect of host genetic factors and comorbidities on severe COVID-19 risk.

METHODS

A total of 20,320 COVID-19 patients in the UK Biobank cohort were included. Genome-wide association analysis (GWAS) was used to identify host genetic factors in the progression of COVID-19 and a polygenic risk score (PRS) consisted of 86 SNPs was constructed to summarize genetic susceptibility. Colocalization analysis and Logistic regression model were used to assess the association of host genetic factors and comorbidities with COVID-19 severity. All cases were randomly split into training and validation set (1:1). Four algorithms were used to develop predictive models and predict COVID-19 severity. Demographic characteristics, comorbidities and PRS were included in the model to predict the risk of severe COVID-19. The area under the receiver operating characteristic curve (AUROC) was applied to assess the models' performance.

RESULTS

We detected an association with rs73064425 at locus 3p21.31 reached the genome-wide level in GWAS (odds ratio: 1.55, 95% confidence interval: 1.36-1.78). Colocalization analysis found that two genes (SLC6A20 and LZTFL1) may affect the progression of COVID-19. In the predictive model, logistic regression models were selected due to simplicity and high performance. Predictive model consisting of demographic characteristics, comorbidities and genetic factors could precisely predict the patient's progression (AUROC = 82.1%, 95% CI 80.6-83.7%). Nearly 20% of severe COVID-19 events could be attributed to genetic risk.

CONCLUSION

In this study, we identified two 3p21.31 genes as genetic susceptibility loci in patients with severe COVID-19. The predictive model includes demographic characteristics, comorbidities and genetic factors is useful to identify individuals who are predisposed to develop subsequent critical conditions among COVID-19 patients.

Molecular mechanisms involved in fetal programming and disease origin in adulthood

Fetal programming occurs during the gestational age when exposure to environmental stimuli can cause long-term changes in the fetus, predisposing it to develop chronic non-communicable diseases (CNCD) in adulthood. Herein, we summarized the role of low-calorie or high-fat diets during pregnancy as fetal programming agents that induce intrauterine growth restriction (IUGR), amplified de novo lipogenesis, and increased amino acid transport to the placenta, which favor the CNCD onset in the offspring. We also outlined how maternal obesity and gestational diabetes act as fetal programming stimuli by reducing iron absorption and oxygen transport to the fetus, stimulating inflammatory pathways that boost neurological disorders and CNCD in the progeny. Moreover, we reviewed the mechanisms through which fetal hypoxia elevates the offspring's risk of developing hypertension and chronic kidney disease in adult life by unbalancing the renin-angiotensin system and promoting kidney cell apoptosis. Finally, we examined how inadequate vitamin B12 and folic acid consumption during pregnancy programs the fetus to greater adiposity, insulin resistance, and glucose intolerance in adulthood. A better understanding of the fetal programming mechanisms may help us reduce the onset of insulin resistance, glucose intolerance, dyslipidemia, obesity, hypertension, diabetes mellitus, and other CNCD in the offspring during adulthood.