Research Focus Areas
Viome is on a mission to embrace a paradigm shift in how chronic diseases are treated by embracing a systems biology approach to prevent, manage, and treat chronic diseases.
Following specific key focuses areas in disease research, Viome scientists are currently targeting clinical gaps in knowledge in the following fields:
Metabolic Diseases
Cancer
Current research efforts have proposed a direct relationship between the root cause of diseases from within the gut microbiome, changing the prevalence of various associated chronic diseases.
A global epidemic, these conditions are changing the way the world views health and altering the quality of life as we know it. However, current understanding of nutrition has failed to produce a one-size-fits-all approach to an optimal diet that can broadly reduce the biological mechanisms that cause diseases of interest, such as metabolic diseases and cancer.
Viome’s research initiative currently is focused on these two growing areas of disease research to clinically validate our findings.
Viome is dedicated to establishing partnerships that bridge this gap and expand the current understanding of gut microbial interactions that influence metabolic disease progression. Together, our combined efforts can reduce and resolve chronic diseases by attenuating precise molecular signatures that impact their development.
Metabolic Diseases
Our mRNA platform offers an advanced breakthrough in technology that is anticipated to revolutionize how disease states are monitored, assessed, and ultimately prevented. Featuring biological data from ~300,000 samples, Viome’s vision is to expand our sample database and further the impact of innovative metatranscriptomic research to uncover the patterns and trends underlying gut microbial interactions with host (human) diseases.
Viome Study Initiatives
Rather than simply focus on simplified generalizations in disease care and therapeutics, understanding the pathophysiology of these disorders requires thorough analysis over the key metabolic pathways that mediate their development. Moreover, further research initiatives must focus on how to close the gap between developmental therapeutics and real-world application.
Gut microbiome activity contributes to individual variation in glycemic response in adults
Abstract
Limiting post-meal glycemic response is an important factor in reducing the risk of chronic metabolic diseases, and contributes to significant health benefits in people with elevated levels of blood sugar. In this study, we collected gut microbiome activity (i.e., metatranscriptomic) data and measured the glycemic responses of 550 adults who consumed more than 30,000 meals from omnivore or vegetarian/gluten-free diets.
We demonstrate that gut microbiome activity makes a statistically significant contribution to individual variation in glycemic response, in addition to anthropometric factors and the nutritional composition of foods.
We describe predictive models (multilevel mixed-effects regression and gradient boosting machine) of variation in glycemic response among individuals ingesting the same foods.
We introduce functional features aggregated from microbial activity data as candidates for association with mechanisms of glycemic control.
We propose for the first time that metatranscriptomic activity of the gut microbiome is correlated with glycemic response among adults.
Examples of individual variation in glycemic response. Ingestion of two meals (blue and green lines) results in opposite blood glucose responses in two participants (P3 & P4).
Gut microbiome activity predicts risk of type 2 diabetes and metformin control in a large human cohort
Abstract
Recognizing and treating the early stages of type 2 diabetes (T2D) is the most cost effective way to decrease prevalence, before heart disease, renal disease, blindness, and limb amputation become inevitable. In this study, we employ high resolution gut microbiome metatranscriptomic analysis of stool samples from 53,970 individuals to identify predictive biomarkers of type 2 diabetes progression and potential for diagnosis and treatment response.
The richness of the metatranscriptomic data enabled us to develop a T2D risk model to delineate individuals with glycemic dysregulation from those within normal glucose levels, with ROC-AUC of 0.83+/-0.04.
This risk score can predict the probability of having insulin dysregulation before detecting high glycated hemoglobin (HbA1c), the standard-of-care marker for prediabetes and diabetes.
A machine learning model was able to distinguish novel metatranscriptomic features that segregate patients who receive metformin and are able to control their HbA1c from those who do not. These discoveries set the stage for developing multiple therapeutic avenues for prevention and treatment of T2D.
(a) ROC performance of 0.83 for the machine-learnt diagnostic classifiers for Type 2 Diabetes. This is a general classifier with microbial functions (KOs) and species which is informative enough to provide a risk score that can predict whether an individual has a high risk of being diagnosed with T2D using the gut microbiome.
(b) Independent validation of the T2D Risk Score. In the validation cohort (n=3028) our model can distinguish between type 2 diabetes (mean=62.81) and non-diabetic (mean=44.10) individuals (t-test, p=2.41e-47), as well as between prediabetic(mean=53.25) and non-diabetic (p=2.88e-24) and also between T2D vs. pre-diabetic individuals (p=6.76e-07)
Oncology/Cancer
Viome has set out to identify the host and/or microbial molecular determinant of specific cancers by systematically evaluating the inflammatory conditions which have already been proven to increase the relative risk of cancer (e.g Inflammatory Bowel Disease as a precursor of colorectal cancer).
The precise characterization of the molecular signature associated with cancer pathogenesis might not only be used to predict or diagnose such cancer but also to support therapy with a companion diagnostic. Furthermore, specific molecular insights in the pathogenesis might also pave the way for the discovery and the development of new therapeutic approaches.
Designated Breakthrough Device for Accelerated Review by FDA
Viome has already achieved proof of concept for the detection of oral and throat cancers using saliva samples. Viome’s AI has discovered a molecular signature that includes several cancer hallmarks that represent molecular processes in human cancer cells, as well as a number of microbial pathways that are active in the oral cavity of cancer patients. This test was designated Breakthrough Device for accelerated Review by FDA.
The salivary host/microbe metatranscriptome as an accurate detection indicator of oral cancer
Abstract
Despite advances in cancer treatment, the five-year mortality rate for oral cancers (OC) is 40%, mainly due to the lack of early diagnostics. To advance early diagnostics for high-risk and average-risk populations, we developed and evaluated machine-learning (ML) classifiers using metatranscriptomic data from saliva samples (n=??) collected from patients with oral cavity cancer (n=??), oropharyngeal cancers (n=??) and normal controls (n=??). Our diagnostic classifiers yielded a receiver operating characteristics (ROC) area under the curve (AUC) up to 0.9, sensitivity up to ??% and specificity up to ??%. Our host/microbe metatranscriptomic signature incorporates both taxonomic and functional microbiome features, and reveals a number of taxa and functional pathways associated with OCC and OPC. We demonstrate the potential clinical utility of an AI/ML model for diagnosing OC early, opening a new era of non-invasive diagnostics, enabling early intervention and improved patient outcomes.
This test represents many firsts: it is not only the first oral and throat cancer screening test, but also the first screening test based on mRNA gene expression signature, the first microbiome/host based detection test to be designated Breakthrough Device for accelerated Review by FDA, and the first AI/ML based molecular screening test for cancer.
Viome Study Initiatives
Cancer Research
Besides head and neck cancers, Viome has an extensive ongoing clinical study pipeline in gastrointestinal cancers including colorectal cancer, pancreatic, ovarian, cervical and biliary cancers. We currently have cancer research trials that use saliva, blood, stool and tumor biopsies to understand the onset and progression of the cancer. By identifying the biomarkers that lead to the development of cancers, Viome can optimize early detection and to identify the right therapeutic targets.