For millions of years, humans have been home to the microbiome — the collection of all microorganisms and their corresponding set of genes within an organism. G-NiiB focuses on the microbiome located in the human gut. A common misunderstanding is that all these microorganisms are harmful. This is untrue because some microorganisms assist the body’s immunological, metabolic, and nutritional functions. Over 100 trillion of microbes live inside our body and it makes up 1-3% of human mass, reflecting the influence of the microbiome on human health. Interestingly, big data analysis on G-NiiB’s extensive database reveals Asian and Chinese populations have unique microbiomes compared to other ethnicities. G-NiiB is one of few companies that offers microbiome solutions tailored to the Asian and Chinese populations.
Dysbiosis is shown to correlate with numerous chronic or autoimmune diseases such as obesity, inflammatory bowel disease (IBD), diabetes mellitus, metabolic syndrome, atherosclerosis, autism, schizophrenia, colorectal cancers, hepatocellular carcinoma, rheumatoid arthritis, muscular dystrophy, and multiple sclerosis. These correlations supports the microbiome as an avenue for disease diagnosis, prevention, and treatment. G-NiiB develops microbial diagnostic test and therapies in relation to seven disease indications:
There are ample evidence to support that dysbiosis (imbalance of beneficial and pathogenic microbes in the human microbiome) correlates with numerous chronic or autoimmune diseases. Understanding the microbes in our body forms the basis for accurate diagnosis and treatment of human diseases.
Mircobiome precision is "an emerging approach for disease diagnosis, treatment and prevention that takes into account individual variability in the genes of human mircrobiome, environment, and lifestyle for each person." This approach will allow doctors and researchers to predict more accurately which treatment and prevention strategies for a particular disease will work in which groups of people. It is in contrast to a one-size-fits-all approach, in which disease treatment and prevention strategies are developed for the average person, with less consideration for the differences between individuals.
From big data, AI machine learning to microbiome precision
Microbiome precision can only be achievable by analyzing a large amount of raw data through machine learning.
Using our unique in-house data and those from publicly available sources, we have developed proprietary machine learning algorithms to accurately identify novel microbes as non-invasive diagnostic biomarkers and potential therapeutic solutions to a variety of diseases such as COVID-19, colorectal cancer, obesity, high cholesterol, autism, eczema, and hair loss.
Collection of large specific population sample 🡪 metagenomics sequencing to reveal the individual gut mircobes 🡪 AI machine learning analytics to develop meaningful insights (biomarkers) 🡪 blueprint for precision diagnostics, prevention and therapeutics
COVID-19 and the microbiome
The human gut microbiome is relevant to COVID-19. The intestinal micro-ecology dominates our immunity. When this micro-ecology is out of balance, we are vulnerable to viruses.
The Centre for Gut Microbiota Research of The Chinese University of Hong Kong discovered for the first time worldwide in June 2020 that COVID-19 patients had missing good bacteria affecting their immunity against infections. There is also sufficient literature to support that lack of these good bacteria will reduce immunity. These findings indicate that COVID-19 infection can cause major changes in the human microbial flora, and the microbial flora may help the diagnosis, treatment and prevention of coronavirus infection.
Using big data analysis and metagenomics derived from COVID-19 patients, researchers in CU Medicine hasdeveloped a unique oral microbiome formula that targets gut dysbiosis. Clinical data showed the recovery ofCOVID-19 patients who received the microbiome immunity formula outperformed those with standard care in manyaspects. These include the achievement of complete symptom resolution; significant reduction of proinflammatorymarkers in their blood, increase in favourable bacteria in their stool and development of neutralising antibody.
Amid the third wave of COVID-19 outbreak in Hong Kong, the CU Medicine team recruited 55 hospitalised patientswith COVID-19; 25 patients were treated with the microbiome immunity formula and 30 received standard care. Keyfindings are as follow:
- 100% of patients treated with the microbiome immunity formula achieved complete resolution of symptoms compared with half in the control group by week 2.
- 88% of patients in the microbiome immunity formula group developed neutralizing antibody compared with 63% in the control group.
- The blood level of pro-inflammatory cytokines was significantly reduced in the microbiome immunity formula group, indicating that inflammation was under control.
- The levels of favourable bacteria recovered from stool in patients receiving the microbiome immunity formula was significantly increased, suggesting that the formula could restore gut dysbiosis. The benefit of G-NiiB Immunity formula is not limited to COVID-19 patients. In 1000 healthy individuals in Hong Kong, almost 40% had imbalance of the gut bacteria (a marker of impaired immunity against infections), which could predispose them to infections including COVID-19.
Situation of “Long COVID”
A recent study by the Faculty of Medicine at The Chinese University of Hong Kong (CU Medicine) discovered that composition of gut microorganisms (microbiota) in COVID-19 patients is very different from uninfected individuals and is linked to disease severity. 80% of COVID-19 Patients in Hong Kong Suffer from “Long COVID”. COVID-19 patients lack certain good bacteria known to regulate their immune system and the abnormal gut microbiota (dysbiosis) persists after clearance of the virus, which could contribute to lingering symptoms, known as “Long COVID”. The study results suggest gut microbiome may influence the severity of COVID-19 as well as the magnitude of the immune response to the infection. Clinical management not only should aim at clearing the virus but also restoring the abnormal gut microbiota. The findings have been published in the international journal Gut and its global press release.
“Long COVID”, known as post-COVID syndrome, are signs and symptoms that develop during or following an infection including COVID-19 which continue for more than 12 weeks and are not explained by an alternative diagnosis. The five most common symptoms are fatigue, poor memory, difficulty in sleeping, breathlessness and hair loss.
CU Medicine followed up 30 COVID-19 patients in Hong Kong and found that 80% of patients had at least one persistent symptom at six months after infection and one-third of the patients had more than three symptoms at six months.
To understand if gut microbiome might affect immune system response to COVID-19 infection, CU Medicine researchers collected blood and stool samples, as well as clinical data, from 100 people admitted to hospitals with laboratory-confirmed COVID-19 between February and May 2020. To characterise the gut microbiome, 41 of the COVID-19 patients provided multiple stool samples while in hospital, 27 provided serial stool samples up to 30 days after clearance of SARS-CoV-2. Levels of inflammatory cytokines and blood markers were measured from plasma. The data were compared with samples from 78 people without COVID-19.
Below are the major findings:
- Composition of the gut microbiota in COVID-19 patients is concordant with disease severity.
- Gut dysbiosis is closely associated with the magnitude of plasma concentrations of several inflammatory cytokines, chemokines and blood markers of tissue damage.
- Patients had higher numbers of “bad bacteria” including Ruminococcus gnavus, Ruminococcus torques and Bateroides dorei species than people without the infection.
- COVID-19 patients had less “good bacteria” that can influence immune system response, such as Faecalibacterium prausnitzii, Eubacterium rectale and Bifidobacterium adolescentis. Lower numbers of good bacteria F. prausnitzii and Bifidobacterium bifidum were associated with infection severity.
- The numbers of the “good bacteria” remained low in samples collected up to 30 days after infected patients had cleared the virus from their bodies
Metagenomic sequencing and machine learning
G-NiiB is an avid adopter of big data and machine learning to generate deeper insights on the microbiome. With a proprietary database of over 10,000 subjects, The research team conducted next-generation metagenomic sequencing of over 1,400 samples. Using these big data, our proprietary machine learning algorithm identified specific, naturally occurring food-grade bacteria strains that correlate with health in Asians. This algorithmic approach underpins the design of G-NiiB’s evidence based microbiome precision formula (G-NiiB Immunity+).