Effects of Gut Microbiome Modulation on Reducing Adverse Health Outcomes among Elderly and Diabetes Patients during the COVID-19 Pandemic: A Randomised, Double-Blind, Placebo-Controlled Trial (IMPACT Study).

Gut microbiota is believed to be a major determinant of health outcomes. We hypothesised that a novel oral microbiome formula (SIM01) can reduce the risk of adverse health outcomes in at-risk subjects during the coronavirus disease 2019 (COVID-19) pandemic. In this single-centre, double-blind, randomised, placebo-controlled trial, we recruited subjects aged ≥65 years or with type two diabetes mellitus. Eligible subjects were randomised in a 1:1 ratio to receive three months of SIM01 or placebo (vitamin C) within one week of the first COVID-19 vaccine dose. Both the researchers and participants were blinded to the groups allocated. The rate of adverse health outcomes was significantly lower in the SIM01 group than the placebo at one month (6 [2.9%] vs. 25 [12.6], p < 0.001) and three months (0 vs. 5 [3.1%], p = 0.025). At three months, more subjects who received SIM01 than the placebo reported better sleep quality (53 [41.4%] vs. 22 [19.3%], p < 0.001), improved skin condition (18 [14.1%] vs. 8 [7.0%], p = 0.043), and better mood (27 [21.2%] vs. 13 [11.4%], p = 0.043). Subjects who received SIM01 showed a significant increase in beneficial Bifidobacteria and butyrate-producing bacteria in faecal samples and strengthened the microbial ecology network. SIM01 reduced adverse health outcomes and restored gut dysbiosis in elderly and diabetes patients during the COVID-19 pandemic.

Multi-kingdom gut microbiota analyses define COVID-19 severity and post-acute COVID-19 syndrome.

Our knowledge of the role of the gut microbiome in acute coronavirus disease 2019 (COVID-19) and post-acute COVID-19 is rapidly increasing, whereas little is known regarding the contribution of multi-kingdom microbiota and host-microbial interactions to COVID-19 severity and consequences. Herein, we perform an integrated analysis using 296 fecal metagenomes, 79 fecal metabolomics, viral load in 1378 respiratory tract samples, and clinical features of 133 COVID-19 patients prospectively followed for up to 6 months. Metagenomic-based clustering identifies two robust ecological clusters (hereafter referred to as Clusters 1 and 2), of which Cluster 1 is significantly associated with severe COVID-19 and the development of post-acute COVID-19 syndrome. Significant differences between clusters could be explained by both multi-kingdom ecological drivers (bacteria, fungi, and viruses) and host factors with a good predictive value and an area under the curve (AUC) of 0.98. A model combining host and microbial factors could predict the duration of respiratory viral shedding with 82.1% accuracy (error ± 3 days). These results highlight the potential utility of host phenotype and multi-kingdom microbiota profiling as a prognostic tool for patients with COVID-19.

Faecal microbiome-based machine learning for multi-class disease diagnosis.

Systemic characterisation of the human faecal microbiome provides the opportunity to develop non-invasive approaches in the diagnosis of a major human disease. However, shared microbial signatures across different diseases make accurate diagnosis challenging in single-disease models. Herein, we present a machine-learning multi-class model using faecal metagenomic dataset of 2,320 individuals with nine well-characterised phenotypes, including colorectal cancer, colorectal adenomas, Crohn's disease, ulcerative colitis, irritable bowel syndrome, obesity, cardiovascular disease, post-acute COVID-19 syndrome and healthy individuals. Our processed data covers 325 microbial species derived from 14.3 terabytes of sequence. The trained model achieves an area under the receiver operating characteristic curve (AUROC) of 0.90 to 0.99 (Interquartile range, IQR, 0.91-0.94) in predicting different diseases in the independent test set, with a sensitivity of 0.81 to 0.95 (IQR, 0.87-0.93) at a specificity of 0.76 to 0.98 (IQR 0.83-0.95). Metagenomic analysis from public datasets of 1,597 samples across different populations observes comparable predictions with AUROC of 0.69 to 0.91 (IQR 0.79-0.87). Correlation of the top 50 microbial species with disease phenotypes identifies 363 significant associations (FDR < 0.05). This microbiome-based multi-disease model has potential clinical application in disease diagnostics and treatment response monitoring and warrants further exploration.

Gut microbiota-derived synbiotic formula (SIM01) as a novel adjuvant therapy for COVID-19: An open-label pilot study.

BACKGROUND AND AIM: Gut dysbiosis is associated with immune dysfunction and severity of COVID-19. Whether targeting dysbiosis will improve outcomes of COVID-19 is unknown. This study aimed to assess the effects of a novel gut microbiota-derived synbiotic formula (SIM01) as an adjuvant therapy on immunological responses and changes in gut microbiota of hospitalized COVID-19 patients. METHODS: This was an open-label, proof-of-concept study. Consecutive COVID-19 patients admitted to an infectious disease referral center in Hong Kong were given a novel formula of Bifidobacteria strains, galactooligosaccharides, xylooligosaccharide, and resistant dextrin (SIM01). The latter was derived from metagenomic databases of COVID-19 patients and healthy population. COVID-19 patients who were admitted under another independent infectious disease team during the same period without receiving SIM01 acted as controls. All patients received standard treatments for COVID-19 according to the hospital protocol. We assessed antibody response, plasma proinflammatory markers, nasopharyngeal SARS-CoV-2 viral load, and fecal microbiota profile from admission up to week 5. RESULTS: Twenty-five consecutive COVID-19 patients received SIM01 for 28 days; 30 patients who did not receive the formula acted as controls. Significantly more patients receiving SIM01 than controls developed SARS-CoV-2 IgG antibody (88% vs 63.3%; P = 0.037) by Day 16. One (4%) and 8 patients (26.7%) in the SIM01 and control group, respectively, failed to develop positive IgG antibody upon discharge. At week 5, plasma levels of interleukin (IL)-6, monocyte chemoattractant protein-1 (MCP-1), macrophage colony-stimulating factor (M-CSF), tumor necrosis factor (TNF-α), and IL-1RA reduced significantly in the SIM01 but not in the control group. There was a significant negative correlation of nasopharyngeal SARS-CoV-2 viral load and SIM01 intervention. Metagenomic analysis showed that bacterial species in SIM01 formula were found in greater abundance leading to enrichment of commensal bacteria and suppression of opportunistic pathogens in COVID-19 patients by week 4 and week 5. CONCLUSIONS: This proof-of-concept study suggested that the use of a novel gut microbiota-derived synbiotic formula, SIM01, hastened antibody formation against SARS-CoV-2, reduced nasopharyngeal viral load, reduced pro-inflammatory immune markers, and restored gut dysbiosis in hospitalised COVID-19 patients.