Personalized Medicine Model Aiming To Improve Diagnosis and Treatment of Chronic Diseases
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Taking its name from the Greek pan, meaning “all”, and dis, representing disease, PANDIS is an Australian consortium of patients, clinicians and scientists investigating the roles of microorganisms in chronic diseases.
To learn more about the model, its aims, and how it can be used to help diagnose and treat patients suffering from a range of conditions spanning from cancers to “mystery chronic diseases”, Technology Networks spoke with PANDIS’s founders, Professor Gilles Guillemin and Catherine Stace.
Anna MacDonald (AM): Can you tell us about the history and aims of the PANDIS model?
Gilles Guillemin (GG): PANDIS was co-created by Catherine and myself in 2018. It all started by an original focus on tick-borne diseases (called Debilitating Symptoms Complex Attributed to Ticks - DSCATT - in Australia) in 2018 and was officially launched on October 25, 2019.
The aim of PANDIS is to identify environmental/infectious pathogens in Australian patients with various types of chronic diseases.
Catherine Stace (CS): Having previously been part of the team behind GBM Agile when I fell ill in 2015 with a mystery disease, which is very similar to COVID-19 long haulers but attributed to a vector-bite, I knew about future models in health and medical research. I didn’t fit into the classical diagnostic system and was rather brutally denied access to treatments and care. At this point you have two options; give in and suffer or do something about it and in my case, gather brilliant minds and go deep into co-design.
We had three criteria to fulfil – the model needed to be an innovative new research model harnessing new technologies; we had to design our own protocols and processes to properly investigate causation and, it had to be agnostic and plug and play with current medical research assets and organizational research projects.
This became our passion project. It ticks all the boxes – ethically, morally and from a future-fit perspective. We had in effect broken up with traditional diagnostic bands and PCR’s which are limited to what is already known and restrictive to siloed disease management.
In 2018 Gilles submitted the project as a grant to the NHMRC Targeted Call for Research into tick-borne diseases (DSCATT). Whilst the grant was unsuccessful, our personalized medicine model and tier one team remained committed, and have since become a not-for-profit organization offering disease groups an “out of the box” personalized medicine model and biobank to run patient cohorts investigating causative agents and correlating factors in chronic diseases including cancers.
Karen Steward (KS): Some microbes are “normal” flora and even beneficial in some locations, settings or patients whilst the same microbes can be harmful in other scenarios. How do you deal with this in your model?
CS: We have designed data points and use bioinformatics to sort pathogenic from productive microbes, and anaerobic from aerobic microbial weightings. We are most interested in overpopulated or under expressed microbes, indicating imbalance, which has a cascading impact on the patient, and new discoveries. We also overlay data, for example, with microbial lipid and nutrient sources and a patients’ nutrient profile, to gain an in-depth profile of a patient’s microbiome – throughout the body – including brain, gut, organs, blood, central nervous system, stool and spinal fluid. There are known pathogens that we are also looking out for, and are mindful of new discoveries, including native species and synergetic relationships between biofilm, virus, bacteria, fungus and parasites.
GG: It is all about numbers, types and microbial balance and unbalance. However our main aim at the moment is to focus on vector-borne diseases and more specifically the causes of tick-borne diseases (borrelia, rickettsia, babesia, bartonella, viruses,…).
Molly Campbell (MC): Can you discuss the use of metagenomics to create the PANDIS maps? Why is this technology superior to PCR?
GG: RNA metagenomics can detect almost any microorganism, even new strands of virus or bacteria for example, whereas PCR will only detect already known microorganisms.
CS: Not all metascriptomic technologies are equal and not everyone who has the top technologies holds detailed knowledge to be comprehensive in their protocol design and factor in barriers to success. To design the protocols requires a deep understanding of both the patient and how microbes behave and survive.
Ruairi MacKenzie (RM): What data sources are you using to build your model and biobank? What steps are you taking to make handling this data practical?
GG: I have a strong expertise of developing and managing a biobank. We aim to collect longitudinal samples from “naive” (no treatment and recently bitten) patients with tick-borne disease. We also plan to use AI to analyze all the data from the patients (biomarker results, clinical and environmental questionnaire, etc...).
CS: Depending on the disease working group protocols we have designed 360-degrees of data points, each working group can incorporate from natural and built environments, geolocation data and pathobiome profiles in patient cohorts, and then overlay this data with, for example, disease type and stage. We are looking for correlation and geographic clusters between environment and human disease and overlay different disease types to a microbial common – where patients of different diseases have shared causative agents.
KS: What is your data mining telling you about the flow of microbes around the globe and between species? Are there any particular trends that are standing out?
CS: Whilst most OECD countries are preparing for spikes in pathobiome diseases such as blue green algae and zoonotic diseases, Australia is the only OECD country that doesn’t have a Centre for Disease Control, to unify research, map clusters and clearly articulate the scale and impact of pathogenic microbes in human health. A country cannot reduce the burden of disease and mitigate future pathogenic threats if the health and medical research system is poorly designed, fragmented and reactive. PANDIS is designed to unify research findings and data, and support a rapid response to policymakers, and for patients to access effective treatments without any lag.
International travel, changes in climate - especially water as it increases vector, parasitic and algae populations, cattle exports, agribusiness can move pathogenic microbes around the world.
Laura Lansdowne (LL): Can you elaborate on how the PANDIS maps are used to discover biomarkers and identify effective treatment options for patients?
GG: Our study has multi-levels:
1. Identifications of pathogens (using state of the art RNA metagenomics)
2. Identification of levels of multiple biomarkers in patients’ blood (multi-omic approach: lipidomic, proteomic, NADomic, plus > 70 cytokines/chemokines,…) that will allow us to identify specific signatures for sub-types on infections but also explains some symptoms and finally and even more importantly assess response to treatments given to these patients.
3. Once we have all the data, this will assist clinicians to adapt and personalize their treatments. Our model includes data apps that will allow us to link patients to ”geographical hot spot” areas in natural and built environments and map pathobiome species, making it easier in the future to diagnose and treat patients.
LL: The link between gut microbes and cancer is attracting increasing attention from researchers. Can you comment on this? How can PANDIS help advance our understanding in this area?
GG: Recent publications in scientific journals found microorganisms in various types of tumors. The concept is symbiosis (a bit like the clown fish and the sea anemone) the tumor feeds bacteria with sugar and the bacteria catabolize anti-cancer drugs.
We have already collected different types of tumors (glioblastomas, breast, liver and colorectal cancers) and we aim to run metagenomic studies on them. Patients want to know if they have a pathobiome profile, and if it matches with others within their patient cohort.
CS: We are talking to funders now. Our first hurdle is to get funders to understand that we have technologies and protocols to investigate causative agents without it being a costly “needle in a haystack exercise”. The race is on as we are now focused on cause, it’s a complete flip on the old system of siloed research projects that look at mechanism of action.
RM: What is the evidence that neurodegenerative and neuroinflammatory disorders could be caused by microbes?
GG: Many recent papers have looked at microorganisms in brain diseases. There are many scientific publications about MS and microorganisms, Parkinson’s disease, motor neuron disease. Last year, a strong study also demonstrated the association of gum bacteria with Alzheimer’s diseases. One of the current treatments in clinical trial for MND is an antiviral drug (Triumeq), a 3-drug combination for HIV.
CS: US Psychiatrist Dr Robert Bransfield has compiled over 500 peer reviewed publications on the role of microbes in mental health including anxiety, depression, suicide ideation and bi-polar. This is a big wake up call for mental health charities and government agencies to start directing funds into causative agents.
AM: How can PANDIS help us to understand emerging and “mystery” chronic diseases, such as DSCATT, and reduce the chances of misdiagnosis of these conditions?
CS: PANDIS yields adaptive data that becomes meaningful with each patient cohort informing the next. Models such as PANDIS help funders, and policy makers to shift cognitive bias on causative agents in chronic disease, and will help serve their constituents, patients, in a more accurate, compassionate way.
Findings from new data sets will enable us to tell a different narrative on pathobiome profiles in chronic diseases, and help to shed more insight into cause and correlation that validates a patient’s need to be treated as a “whole of person” system that a blood diagnosis alone, developed on what is already known, cannot convey. It’s as if we are lifting the shackles off patients for them to see the whole picture for the first time.
What have we ignited? Our research model is also a social change model that we have affectionately coined a “whole of patient” movement.
Gilles Guillemin and Catherine Stace were talking to Anna MacDonald, Dr Karen Steward, Molly Campbell, Laura Lansdowne and Ruairi MacKenzie, Science Writers for Technology Networks.
Gilles Guillemin is Professor of Neurosciences, Macquarie University, and Founder and Lead Scientist for PANDIS.
Catherin Stace is Director for PANDIS and was previously Chief Executive Officer of Cure Brain Cancer Foundation.