The COVID-19 pandemic has led to over 2.26 million deaths for almost 104 million confirmed cases worldwide, as of 4 February 2021 (WHO). Risk factors include pre-existing conditions such as cancer, cardiovascular disease, diabetes, and obesity. Although several vaccines have been deployed, there are few alternative anti-viral treatments available in the case of reduced or non-existent vaccine protection. Adopting a long-term holistic approach to cope with the COVID-19 pandemic appears critical with the emergence of novel and more infectious SARS-CoV-2 variants. Our objective was to identify comorbidity-associated single nucleotide polymorphisms (SNPs), potentially conferring increased susceptibility to SARS-CoV-2 infection using a computational meta-analysis approach. SNP datasets were downloaded from a publicly available genome-wide association studies (GWAS) catalog for 141 of 258 candidate COVID-19 comorbidities. Gene-level SNP analysis was performed to identify significant pathways by using the program MAGMA. An SNP annotation program was used to analyze MAGMA-identified genes. Differential gene expression was determined for significant genes across 30 general tissue types using the Functional and Annotation Mapping of GWAS online tool GENE2FUNC. COVID-19 comorbidities (n = 22) from six disease categories were found to have significant associated pathways, validated by Q–Q plots (p < 0.05). Protein–protein interactions of significant (p < 0.05) differentially expressed genes were visualized with the STRING program. Gene interaction networks were found to be relevant to SARS and influenza pathogenesis. In conclusion, we were able to identify the pathways potentially affected by or affecting SARS-CoV-2 infection in underlying medical conditions likely to confer susceptibility and/or the severity of COVID-19. Our findings have implications in future COVID-19 experimental research and treatment development.
The endogenous microbiome of healthy individuals in oral cavities is diverse, representing over 700 bacterial species. Imbalance in oral and gut microbiome composition and associated gene expression has been linked to different forms of hematological (blood) cancers. Our objective is to compare oral microbiome profiles of patients with blood cancers (BC group: N = 39 patients, n = 124 oral samples) to those of healthy control subjects (HC group: N = 27 subjects, n = 100 oral samples). Saliva samples and swabs of buccal mucosa, supragingival plaque, and tongue were collected from blood cancer patients and healthy controls. Next-generation sequencing (16S-rRNA gene V3–V4 region) was used to determine the relative abundance of bacterial taxa present at the genus and species levels. Differences in oral microbiome beta-diversity were determined using multivariate permutational analysis of variance (PERMANOVA). Linear discriminant analysis (LDA) effect size (LEfSe) analysis was performed to identify differentiating bacterial taxa in pairwise comparisons. The PATRICv3.6.7 online tool was used to determine the predominance of potential pathogenicity in the BC group. The oral microbiome beta-diversities of the BC and HC groups differed and corresponded to a reduced alpha-diversity in the BC group. LEfSe analysis showed significant LDA scores for Actinomyces and Rothia spp., differentiating the BC group from the HC group. In silico analysis using PATRICv3.6.7 demonstrated that the groups of bacteria possessing traits of “antibiotic resistance”, “oral pathogen”, and “virulence” was enriched in the BC group. Although 56% of the BC patients received antibiotics within two weeks of the oral bacterial sampling, Actinomyces genus remained the top differentiating feature in the BC group regardless of the administration of antibiotics, while Rothia dentocariosa was detected as the top differentiating feature in the BC patients who did not receive antibiotics, but not in those who received antibiotics. Further investigation is needed to better understand the interactions of certain oral species with the host immune system to better characterize clinically relevant associations with hematological cancers.
Background: Oral mucositis (OM) is a common side effect of conditioning therapy implemented before hematopoietic stem cell transplantation (HSCT). The role of oral microbiome in OM is not fully elucidated. Objective: To determine oral microbiome profile changes post-conditioning in HSCT patients who developed moderate OM, or mild to no OM. Design: Patient groups were: Muc0-1 with OM-score = 0-1 (43 paired samples) and Muc2 with WHO OM-score = 2 (36 paired samples). Bacterial DNA was isolated from oral samples (saliva, swabs of buccal mucosa, tongue, and supragingival plaque) at pre-conditioning (T 0 ), post-conditioning mucositis onset (T Muc ), and one-year post-conditioning (T Year ). 16S-rRNA gene next-generation sequencing was used to determine the relative abundance (RA) of >700 oral species. Alpha-diversity, beta-diversity and linear discriminant analyses (LDA) were performed Muc2 versus Muc0-1. Results: Muc2 oral microbiome alphaand beta-diversity differed between T 0 and T Muc . Muc2 alpha-diversity and Muc0-1 beta-diversity did not differ between T 0 and T Year . T 0 to T Muc LDA scores were significant in Muc2 for Gammaproteobacteria. For Muc2 patients, the average RA decreased for Haemophilus parainfluenza, a species known as mucosal surfaces protector, but increased for Escherichia-Shigella genera. Conclusions: Post-conditioning OM might contribute to long-term oral microbiome changes affecting Gammaproteobacteria, in HSCT patients.
ObjectivesHuman papillomavirus (HPV) is a known etiological factor of oropharyngeal head and neck cancer (HNC). HPV positivity and periodontal disease have been associated with higher HNC risk, suggesting a role for oral bacterial species. Our objective was to determine oral microbiome profiles in HNC patients (HPV-positive and HPV-negative) and in healthy controls (HC).MethodsSaliva samples and swabs of buccal mucosa, supragingival plaque, and tongue were collected from HNC patients (N = 23 patients, n = 92 samples) before cancer therapy. Next-generation sequencing (16S-rRNA gene V3–V4 region) was used to determine bacterial taxa relative abundance (RA). β-Diversities of HNC HPV+ (N = 16 patients, n = 64 samples) and HNC HPV– (N = 7 patients, n = 28 samples) groups were compared using PERMANOVA (pMonte Carlo < 0.05). LEfSe discriminant analysis was performed to identify differentiating taxa (Log LDA > 2.0). RA differences were analyzed by Mann–Whitney U-test (α = 0.05). CombiROC program was used to determine multi-marker bacterial signatures. The Microbial Interaction Network Database (MIND) and LitSuggest online tools were used for complementary analyses.ResultsHNC vs. HC and HNC HPV+ vs. HNC HPV– β-diversities differed significantly (pMonte Carlo < 0.05). Streptococcus was the most abundant genus for HNC and HC groups, while Rothia mucilaginosa and Haemophilus parainfluenzae were the most abundant species in HNC and HC patients, respectively, regardless of antibiotics treatment. LEfSe analysis identified 43 and 44 distinctive species for HNC HPV+ and HNC HPV– groups, respectively. In HNC HPV+ group, 26 periodontal disease-associated species identified by LefSe had a higher average RA compared to HNC HPV– group. The significant species included Alloprevotella tannerae, Fusobacterium periodonticum, Haemophilus pittmaniae, Lachnoanaerobaulum orale, and Leptotrichia spp. (Mann–Whitney U-test, p < 0.05). Of 43 LEfSe-identified species in HPV+ group, 31 had a higher RA compared to HPV– group (Mann–Whitney U-test, p < 0.05). MIND analysis confirmed interactions between Haemophilus and Leptotrichia spp., representing a multi-marker signature per CombiROC analysis [area under the curve (AUC) > 0.9]. LitSuggest correctly classified 15 articles relevant to oral microbiome and HPV status.ConclusionOral microbiome profiles of HNC HPV+ and HNC HPV– patients differed significantly regarding periodontal-associated species. Our results suggest that oral bacterial species (e.g., Leptotrichia spp.), possessing unique niches and invasive properties, coexist with HPV within HPV-induced oral lesions in HNC patients. Further investigation into host–microbe interactions in HPV-positive HNC patients may shed light into cancer development.
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