Geoff’s Narration
The GIST
This is the next in a series of blogs exploring ongoing projects in ME/CFS, FM and long COVID. The first featured the RECOVER project’s next set of long COVID clinical trials.
PrecisionLife thinks they can do it all: explain these diseases, uncover subsets, produce biomarkers, enable “smart clinical trials,” and develop cheap diagnostic tests.
I gaped when I saw what PrecisionLife is attempting to do in ME/CFS and long COVID. PrecisionLife believes they can have it all. Not only is it trying to identify genetically based subsets, but it’s attempting to identify the mechanisms driving those subsets, identify biomarkers for those subsets, find drugs that move those mechanisms, and test them. It’s an all-in-one package.
Potentially, that means finding treatments that are targeted to specific biologically based subsets which, in ME/CFS, is basically what we’ve been hoping for, for quite a while.
Health Rising’s Quickie Summer Donation Drive is On!Will they be able to pull it off? Time will tell. One thing, though, this company has been laser-focused on ME/CFS. I was astonished to learn that PrecisionLife fully funded its ME/CFS studies.
In my talk with PrecisionLife founder, Steve Gardner, I asked why a company would go out of its way to study “the disease of a 1,000 names”, which has been described, by some as a “wastebasket disease” and which is surely larded with subsets. Why would anyone take on what is arguably the most complex of the complex, chronic diseases?
Gardner acknowledged these diseases presented “a big challenge” but asserted that PrecisionLife can “deal with the complexity” and stated that complex, chronic diseases are PrecisionLife’s raison d’être – they’re its reason for being. For two, PrecisionLife isn’t simply being nice by taking on this neglected disease.
They believe their work in ME/CFS will help them out. If they can break the code on the disease others fear to touch, they can break the code on any disease. Referring to “the weird and wonderful mechanisms” at play in these diseases, it was easy to see that Gardner is simply fascinated by how a respiratory infection like COVID-19 can produce over 200 symptoms in long COVID.
Because the company’s work with pharmaceutical companies involves commercial interests, and cannot be published, they wanted a public test case. DecodeME’s publication of the first large genomic dataset on ME/CFS in 2020 gave them the data they needed. The fact that they think they’re ready enough for these diseases to devote funding for them says something in itself.
“Upon demonstrating success for ME/CFS and long Covid patients, we hope to also apply this precision medicine approach to multiple diseases of aging in respiratory, dementia, autoimmune, and metabolic diseases to benefit millions more people.” PrecisionLife
Why does PrecisionLife think it can jumpstart this disease into a new era? I talked with CEO and co-founder Steve Gardner about that.
THE GIST
I gaped when I saw what PrecisionLife is attempting to do in ME/CFS and long COVID. PrecisionLife believes they can have it all. Not only is it trying to identify genetically based subsets, but it’s attempting to identify the mechanisms driving those subsets, identify biomarkers for those subsets, find drugs that move those mechanisms, and test them. It’s an all-in-one package.- I was also astonished to learn that PrecisionLife fully funded its ME/CFS and long-COVID studies. That’s right – this company really, really wants to work on ME/CFS. Why? So they show the world that they can crack the code on two of the most complex chronic diseases there are.
- In a Zoom interview, I asked Steve Gardner, the CEO and co-founder of PrecisionLife, why they think they can do that.
- PrecisionLife is bringing two new techniques, called combinatorial analytics and mechanostics, to bear on these diseases. In combinatorial analytics, instead of assessing gene variants one by one, they assess the biological world that those genes have created; i.e., they assess the pathways and interactions those genes are involved in.
- Despite relying solely on genetic analyses, the 15 communities PrecisionLife identified in ME/CFS make perfect sense given ME/CFS research results. They include communities like neural-autonomic / urea cycle / stress signaling / mitochondrial-metabolic / vascular-endothelial/immune-inflammatory / metabolic-stress response / vascular-endothelia.
- That allows them to uncover the biological communities that permeate these diseases. Next in mechanostics, they seek to understand the mechanisms at play in these disease communities.
- Gardner referred to the “Victorian or Edwardian, clinical observations” that have produced many of the labels we currently use to refer to diseases. If PrecisionLife is on the right track, they will ultimately create new disease classifications that more accurately reflect the biological mechanisms at play.
- So did the mechanostic clusters. They included groups focused on viral/bacterial susceptibility, metabolic dysfunction, and autoimmune-neuroimmune signaling. While many mechanisms may be present, Gardner believes that the symptoms that most people with these diseases have are driven by one or two core mechanisms.
- For instance, in ME/CFS, mitochondrial genes were highlighted in people with severe post-exertional malaise, and neurotransmitter genes were highlighted in people with more severe brain fog.
- PrecisionLife also found that many of the long-COVID gene variants appeared in their ME/CFS analysis. The two diseases are close enough that Gardner believes “ME is a sort of endpoint for something that starts through long COVID”.
- PrecisionLife’s mechanostics program next asks two questions: “What exact mechanism (molecular pathway) is broken, and can they measure it?” If they can assess the “brokenness” of a molecular pathway, they can biologically assess how effective treatments are – exactly what the drug companies are waiting for. If drugs exist that specifically target those broken pathways (and clinical trials can be funded), the game is on.
- The ability to now target precise subsets of patients – PrecisionLife calls them “super-responders” – who are likely to do well should result in “smart clinical trials” and better results than current clinical trials, which simply throw everyone with ME/CFS into the mix.
- It’s the throw-everyone-into-the-mix approach in this very heterogeneous disease that has made pharma take a hands-off approach.
- PrecisionLife has identified nine generic drug candidates it wants to test in ME/CFS and/or long COVID and has honed in, in particular, on TLR4-targeting drugs. (Low-dose naltrexone is a TLR4-targeted drug.)
- It’s now analyzing the full spread of DecodeME data available to it (@ 11,500 samples), and not surprisingly, is finding many more genes associated with ME/CFS. Gardner said that because the new analyses validate past findings and open up new ones, PrecisionLife has “high confidence” that it’ll be able to find targets that are “going to be beneficial for patients.
- Note, though, how complex these efforts are. PrecisionLife could stumble if it doesn’t have enough access to enough high-quality data, which is at a premium in ME/CFS (but is improving).
- PrecisionLife is working with the Complex Disorders Alliance (formerly Metrodora) to verify and expand its results, to begin a large clinical trial, and in the Mello study, to dramatically expand its analyses to include multi-omics data.
- A preprint that analyzed DecodeME data, which Gardner reported validated past results and opened up new ones is due soon.
I gaped when I saw what
Support Health Rising and Keep the Information Flowing!
Health Rising is not a 501 c (3) non-profit
“Respecting the Biological Complexity of Diseases” or, Genetics on Steroids…
You may have heard that 10-20% of the risk for a disease is due to genetics. The recent DecodeME study, for instance, found that common genetic variants accounted for about 10% of the risk of developing ME/CFS.
Precisionlife believes the techniques they use better reflect what’s happening in the body.
Not so fast, says Steve Gardner. That’s true if you assess the gene variants piece by piece. But what if instead of focusing on the gene variants, you analyze all the pathways those genes participate in? Once you assess the molecular pathways those genetic variants affect and how they interact, Gardner and Precisionlife say our genetic inheritance looms much larger.
Gardner calls this approach “respecting the biological complexity of chronic diseases”. In a 2021 opinion paper, “Combinatorial analytics: An essential tool for the delivery of precision medicine and precision agriculture“, he asserted that a gene-by-gene approach is only really effective in rare diseases caused by single-gene mutations and in cancer.
Take the APOE gene in Alzheimer’s. Even though it presents a major risk factor, clinical trials in Alzheimer’s have almost universally failed. Over 1,000 genetic association studies and 75 GWAS (genome-wide association studies) Alzheimer’s studies have identified just 29 risk genes, and even worse, have not produced any effective treatments. The lack of success led researchers to dig even deeper, seeking rarer and rarer gene variants – all to no avail. This is because, despite the clear genetic risk factors found in Alzheimer’s, at its heart, Alzheimer’s is a complex, multifactorial, polygenic disease; i.e., many genes contribute to the development of Alzheimer’s in ways that GWAS studies can’t hope to pluck out.
A similar effort to understand COVID-19 occurred early on. A global GWAS effort involving almost 14,000 patients with severe disease and over 2 million controls identified four genome-wide significant loci (genetic regions that increase risk) associated with SARS-CoV-2 infection and 11 genetic regions associated with severe COVID-19. The genetic regions identified were not surprising – most had to do with lung, autoimmune, and inflammatory diseases. The results hardly matched the range of symptoms and problems associated with long COVID and offered few new treatment approaches.
Compare those results to a much, much (much) smaller (a few hundred people) COVID-19 study, which used a combinatorial approach to identify 156 severe-disease-associated loci mapping to 68 protein-coding genes (proteins do the work in cells) across a range of mechanisms. They were subsequently validated and opened the door to new treatments.
That, Gardner says, is why using something called “combinatorial analytics” is so much more effective.
Combinatorial Analytics
The FM and DecodeME GWAS studies sought “disease architectures”; i.e., genomic regions containing genetic variants that appear to increase the risk of these diseases.
The disease architectures PrecisionLife is looking for exist on a whole other scale. It’s like they’re playing 3-dimensional chess. PrecisionLife is looking for gene combinations whose pathways correlate strongly with ME/CFS and/or long COVID. The disease signatures get grouped into disease “communities” (patients sharing overlapping combinations).
One goal – using combinatorial analytics to uncover the hidden molecular pathways driving symptoms.
The 15 communities identified by combinatorial analysis in their 2023 paper “Genetic risk factors for severe and fatigue-dominant long COVID and commonalities with ME/CFS identified by combinatorial analysis” make sense in light of past ME/CFS research findings.
They include communities such as neural-autonomic / urea cycle / stress signaling / mitochondrial-metabolic / vascular-endothelial / immune-inflammatory / metabolic-stress response / vascular-endothelial.
The similarities are intriguing, given that these communities are based solely on the genetic variants and pathways found in ME/CFS.
In fact, Steven Gardner said they didn’t know much about ME/CFS when they did their first study. When he went to DecodeME to show them their findings, Chris Ponting promptly accused them of confirmation bias.
If PrecisionLife is right, then the genes we are born with set us up in a major way for ME/CFS.
Next Step – Identify the Mechanisms
Next, in its mechanostics platform, PrecisionLife seeks to find the mechanisms underlying these disease signatures. It’s as if the engine in your car seized. You can see that the engine will not crank, but you don’t know why. You have to get into the guts of the engine to understand what happened.
Next – identify the mechanisms driving those molecular pathways.
PrecisionLife’s mechanostic approach is part of an emerging paradigm of diagnosing diseases by mechanism rather than “manifestation“, such as symptoms or even clinical findings.
In our talk, Gardner referred to the “Victorian or Edwardian, clinical observations” that have produced many of the labels we currently use to refer to diseases.
Ultimately, Precisionlife’s work should yield new disease labels that reflect the mechanisms underlying ME/CFS, FM, long COVID, and related diseases.
Combinatorial analytics has found, for instance, that multiple pathways produce the wheezing found in asthma. One molecular subset with high T-helper cell type 2 (eosinophilic/T2) expression has drugs that can help. Another molecular subset without high T-helper cell type 2 does not.
The genes associated with the second group are entirely different and are even involved in non-immune pathways (!), including fatty acid synthesis, LDL oxidation, and modulators of GABA, purinergic, and glutamate signaling. This suggests this group would benefit from very different drugs.
Pleiotropic Diseases
The high levels of pleiotropy (the same genes produce different results) found in the recent fibromyalgia GWAS study suggests diseases like FM, ME/CFS, and long COVID can benefit from a combinatorial analysis that’s able to disentangle the different mechanisms producing the subsets in these diseases. (Note that many of the loci found in FM also showed up in the ME/CFS GWAS study.)
Check out some of the provisional mechanistic clusters PrecisionLife has identified in ME/CFS and long COVID. (ChatGPT 5.0 derived – names may be different)
- Viral/Bacterial Susceptibility: key genes S100PBP; CDON; USP6NL – pathways involved; entry/adhesion and innate immune signaling.
- Metabolic Dysfunction: key gene AKAP1 – pathways involved – mitochondrial scaffolding, respiration, post-exertional recovery.
- Autoimmune- neuro-immune signaling: Key genes GPC5; PHACTR2 + more; pathways involved – immune-neuro.
Gardner reported that while eight mechanisms may be in play in an ME/CFS or long-COVID patient, only one or two mechanisms may be the principal drivers of their symptoms. For instance, in ME/CFS, mitochondrial genes were highlighted in people with severe post-exertional malaise. People displaying genetic issues with neurotransmitters tended to experience more severe brain fog.
In long COVID, PrecisionLife uncovered critical genetic variants in two major cohorts: 86 in the “severe cohort” and 84 in the “fatigue dominant” cohort. The fact that at least 74 unique gene variants were found in each cohort suggested PrecisionLife had discovered genetically distinct subsets.
Interestingly, though. PrecisionLife found that, while the variants differed, similar genes were also highlighted in both cohorts. Twenty-eight of 43 genes highlighted in the severe cohort were also associated with the fatigue-dominant cohort. Twenty-five of the 35 genes highlighted in the fatigue-dominant cohort were also found in the severe cohort.
One or two mechanisms may be the main drivers of symptoms in most ME/CFS and long-COVID patients.
As in ME/CFS, genes uniquely associated with the severe long-COVID cohort aligned remarkably well with what we know about it. They impacted fat metabolism, autophagy (mitochondria), insulin resistance/metabolic syndrome, viral resistance, and the innate immune response.
So too are the genes uniquely associated with the fatigue-dominant cohort. They affected acetyl-CoA signaling (mitochondria), muscle function and lipid metabolism, NADH dehydrogenase (mitochondria), oxidative stress, mitochondrial muscle activity, and monocytes.
While there were differences between the cohorts, it was also interesting to see similar general themes (innate immune response, energy production, lipid metabolism) driven by distinct genes or gene variants pop up in many of the cohorts.
PrecisionLife also found that many of the long-COVID gene variants were present in its ME/CFS analysis. The two diseases are close enough that Gardner believes “ME is a sort of endpoint for something that starts through long COVID”.
Super-Responders and Smart Clinical Trials
PrecisionLife’s mechanostics program then asks two questions: “What exact mechanism (molecular pathway) is broken, and can they measure it?” If they can assess the “brokenness” of a molecular pathway, they can determine if any drugs are available that could return it to health, exactly what the drug companies are waiting for. If drugs exist that specifically target those broken pathways (and clinical trials can be funded), the game is on.
A major goal – identify the “super-responders” who are most likely to benefit – and get them into targeted clinical trials.
The ability to target precise subsets of patients – PrecisionLife calls them “super-responders” – who are likely to do well should result in “smart clinical trials” and better results than our current clinical trials, which simply throw everyone with ME/CFS or long COVID into the mix.
It’s the throw-everyone-into-the-mix approach in these very heterogeneous diseases that has resulted in pharma taking a hands-off approach.
Gardner’s goal is to give pharma the confidence it needs to enter the ME/CFS and long-COVID space. As a bonus, if those trials succeed, a low-cost genotypic test to identify patients would be the next step.
PrecisionLife has identified nine generic drug candidates it wants to test in ME/CFS and/or long COVID and has honed in, in particular, on TLR4-targeting drugs. (Low-dose naltrexone is a TLR4-targeted drug.)
The Future
On the plus side, PrecisionLife has been able to generate its findings quickly and cost-effectively. Its focus on repurposed drugs means that, if funded, clinical trials can occur quickly. Its technology appears robust; it’s been doing this for 10 years and is working across more than 60 disease groups. It presents the potential of cheap diagnostic tests.
Because virtually everyone recognizes that precision medicine – the ability to link a treatment to a specific biological state – is the future, if PrecisionLife can deliver, its future should be bright. Gardner stated that a new, greatly expanded ME/CFS paper will be out soon.
I asked ChatGPT 5.0 what could derail this effort. Not enough good data could. Because data is the lifeblood of PrecisionLife’s work, the more high-quality data PrecisionLife has, the better it should do.
PrecisionLife has analyzed more high-quality data. Will it be able to uncover the disease signatures at play in ME/CFS, long COVID, and fibromyalgia?
Replicated or validated datasets provide very high-quality data, and DecodeME appears to be the only major dataset currently available that meets that criterion in ME/CFS. PrecisionLife obtained its first results without using DecodeME (and replicated most of its results in the UK DecodeME and the US “All of Us” cohorts). Ian Lipkin’s current NIH-funded US GWAS study should provide more high-quality data.
PrecisionLife is now analyzing the full spread of DecodeME data available to it (@ 11,500 samples), and not surprisingly, is finding many more genes associated with ME/CFS. Gardner said that because the new analyses validate past findings and open up new ones,
Gardner reported in the interview that PrecisionLife has “high confidence” that it’ll be able to find targets that are “going to be beneficial for patients”. The rubber meets the road for the company in the clinical trials, where its findings are put to the test. It’s in the clinical trials that we’ll learn if PrecisionLife can accurately identify biological subsets and the mechanisms driving them, and find treatments that help a particular group of patients.
Citing work by Action for ME, DecodeME, the Complex Disorders Alliance, and ChronicleBio (an R&D partner), as well as the steadily growing patient databases, Gardner said he was encouraged by the ecosystem emerging around ME/CFS.
Gardner noted, though, the “very big computational challenges” PrecisionLife’s work faces. False positives can be a problem in diseases with generally weak genetic signals like ME/CFS. PrecisionLife has a way to guard against these, but ChatGPT reported that the best bulwark against them is larger, validated, genetic studies such as DecodeME and Lipkin’s study.
Another question is how well the field will be able to test PrecisionLife’s findings and whether it can withstand less-than-stellar early results. PrecisionLife can do the analytics, but they can’t put on the clinical trials needed to validate them. (One is underway – see below).
We ended the interview with Gardner saying that while much remains to be done, “I do feel confident saying that we understand the disease much better now and will do, particularly with the next set of studies that come out, than we ever have in the past.”
Metrodora / Complex Disease Alliance ME/CFS Studies
“Our partnership with Metrodora has the potential to transform the lives of tens of millions of patients affected by these and many other debilitating diseases.” PrecisionLife, Sept, 2024
The Mello study is dramatically expanding the datasets used.
In September 2024, PrecisionLife shared insights gathered from a $1 million grant from the Metrodora Foundation, which aimed to recruit up to 1,000 ME/CFS and long-COVID patients.
The Metrodora Institute, which is no longer seeing patients, is separate from the Metrodora Foundation. The Metrodora Foundation formed the Complex Disorders Alliance (“CODA”) and continues to work with PrecisionLife. The new website states it has:
- collaborated with PrecisionLife to confirm key genetic drivers of Long COVID in a diverse U.S. cohort.
- funded the MELO Study, in collaboration with PrecisionLife, to uncover the genetic drivers of ME/CFS and Long COVID, using deep phenotyping and multi-omic analysis to identify subtypes and treatment targets. The MELO study is particularly interesting because it combines PrecisionLife’s genetic mechanostic factors with multi-omic (genomic, transcriptomic, proteomic, and metabolic profiling) and immune factors (immune cell types, cytokines, markers of inflammation, and blood work). Gardner said 400 people have been recruited in the Mello study, and a genetic swab test is being developed.
Support Health Rising and Keep the Information Flowing!
Health Rising is not a 501 c (3) non-profit
Exciting times! Thanks as always Cort for the top notch reporting!
Thanks!
I have to admit I didn’t took the time to dive into deep detail, mainly because for me it has a lot of signs written over it:
It sounds a lot like a version of 23andME wrapped in a bit of machine learning (often called AI) and plenty of overpromissing marketing.
When I read “I was astonished to learn that PrecisionLife fully funded its ME/CFS studies.” and combine it with ”
Understanding complex biology at unprecedented scale to predict, treat and prevent disease
Across >60 chronic diseases
Benefiting >5 billion lives
Reducing >80% of healthcare costs”
on their website then I read: “Buy a gene test on our website now! We can do all sorts of magic things on a never seen scale in the world before! For near any chronic condition you may suffer from! Just sign away the right to analyze your genetic data away! And give us a very complete list of medical details otherwise it’s useless for us to analyze all that data with AI! Forget privacy! And forget what we promissed if we don’t deliver on any of it! We just need more data to find the patterns! So help us spread the good news and convince even more people to pay us for this research (aka basic machine learning on all the data you provide)!”
Forgive me if I am wrong, but “fully funded it’s ME/CFS studies?”. It sounds more like very clever marketing, letting the patients pay for gene tests first, then for online data analysis tools on their own data later and earn the real big money on selling the honeypot of data (genetic data plus detailed medical *and personal* info provided by patients) later to the highest bidding corportations.
The scale to gather good data for machine learning (aka AI) IMO requires them to gather tremendous amounts of data to accomplish anything usefull PLUS rather good *and well funded* scientists on board to find and explore and understand these patterns. I doubt that will ever happen (by this company). If they do, they’ll fetch some top dollar for that data plus those analysis tools. If they don’t, they’ll probably be bought over for “precision marketing” of drugs to vulnerable patients where the new owner has no qualms to try and sell anything it can at a high markup to patients the most in need and gain a few more dollars to sell information to insurers so they can increase prices of insurance for the chronic ill and exclude as many as possible pre-existing conditions as possible.
I am sorry if I am wrong, but I now feel as harsh about it as I write.
Yah, Pretty harsh DeJurgen. You said you didn’t dig into the article. I encourage you to read further. I think you’ve come away with some incorrect assumptions about what PrecisionLife is doing and how they are doing it. Plus its hardly fair to knock any company so hard without learning more about it.
A bit of machine learning… This is way beyond that. Here are some of Gardner and company’s papers. Papers like these are written because they constitute advances in the field.
Increasing Healthspan – Predicting & Preventing Complex Chronic Diseases
PrecisionLife used ME/CFS databases to get their results (including DecodeME – not by asking patients to pay for genetic tests. The genetic tests would ONLY come after studies indicated they identified which patients would likely benefit from a specific treatment.
And this….The quotes suggest this came from the website but it didn’t.
If the quotes I used suggest that it came from the website, then that was definately not intended to sound like that. I thought the tone of what is inside those quotes makes it more then clear that those words came from me since no single company would every write it to promote their product and or businessmodel.
In my opinion, the analysis on those 11000 decodeME samples is part of the effort to kickstart their business, not the business itself. It creates a showcase.
Then the remaining question is: how to keep funding a big commercial organisation? Without the willingness to publish, one cannot expect meaningfull long term government / university / research funding. Then IMO the two biggest remaining candidates for (mid term) funding left are big drug companies and starting to provide tests to patients. Small charity organisations can only go so far without huge sponsors.
If they were not to provide tests in a later phase, they could only use their analysis service on patient / genetic data provided by these big drug companies or big government provided studies opening their datasets.
Big companies are not eager to provide a startup with so much data and in addition pay for it. (By my knowledge there are even no pharmaceutical companies holding big ME/CFS specific datasets to start with.) If they do, expect any new drug comming out of it to be very expensive as long as the patents run. Development time, approaval time plus then patent time all together would be enough to make most results comming out of such collaboration unaffordable the next 30+ years.
As for big open datasets from public studies on ME/CFS, I am not aware of any big datasets (or ongoing research producing such datasets) that well surpass the size of decodeME. And with my understanding of the uses of machine learning aka AI on the decode ME dataset, most of the correlations and relationships (as that is what machine learning is good at extracting out of it) should already be extracted out of it. If that were a giant success, we’d see either publications comming up (which they are not willing to do so far) or drugs to be developped by big companies (who tend to charge more then a patient can afford so long they are pattented).
Getting further IMO will require vastly more data, and that can only be provided by skillfully analyzing plenty and plenty of genomes in combination with detailed symptom discription and biological samples from patients. Unless we get government ME/CFS research funding doing that on a far larger scale then decodeME had and combining these three parts of data and opening this dataset, that data and the money needed for it in practice can IMO only come from patients providing it themselves. I don’t see these studies happening soon at such scale, unfortunately.
Big companies don’t do any on ME/CFS either so they won’t be able to provide these datasets either. So again: the logic business model going forward IMO is providing a 23andME + AI analysis like service to patients.
As elaborate datasets like decodeME don’t come publicly online every few months or even years, IMO working AI magic on them doesn’t provide a business case going forward. It seems that they actually already did most of what they could on an IMO business demonstration by telling what they could do with that data. So logic asks what’s next after the few big open datasets are analyzed and dried up. Hence my original post.
But, let us agree to disagree. I certainly hope to be sooner rather then later wrong and see plenty of us getting good and affordable treaments. I am more then willing to swallow any pride I may have for that.
PrecisionLife has been around for over a decade. It’s stated that it’s working with dozens of pharmaceutical companies. In other words, it’s not a startup – it’s an established business. Does it want to use ME/CFS and long COVID to publicly showcase what it can do? Yes, absolutely. Having a company want to showcase how effective it can be in figuring out and finding treatments for ME/CFS for me is a big plus. I wish we had more of that.
Being unwilling to publish is not a problem. Actually, publishing appears to be part of the solution for them as they’ve published two studies on ME/CFS (https://pubmed.ncbi.nlm.nih.gov/37915075/, https://pubmed.ncbi.nlm.nih.gov/36517845/ and one on long COVID and ME/CFS
Yes, they need funding for the clinical trials but do they need funding from pharmaceutical companies or more accurately could they get funding from pharmaceutical companies? Let’s hope at some point these company’s get interested but pharmaceutical companies clearly not interested in ME/CFS or even long COVID with its massive patient population. Isn’t that the goal, by the way? To get companies with deep pockets interested enough in these diseases to fund the large studies needed to get FDA approval for drugs?) –
PrecisionLife believes that by elucidating the molecular pathways driving these diseases and finding drugs that impact these pathways, drug companies will finally get involved.
Anyway at this point you look elsewhere for funding – foundations, federal funding – whatever – to do proof of concept trials. They’re in the midst of a 400 person trial – they have funding for that.
That’s one way but they’re not doing that are they? So let’s not prejudge them. See below for a possible way out of the trap you think you’ve identified.
What a cheery thought! The long time span to bring new drugs to market is why PrecisionLife is focusing on repurposed drugs.
You can find the DecodeME studies here – https://pubmed.ncbi.nlm.nih.gov/?term=ponting+chronic+fatigue+syndrome&sort=date&size=200. I don’t see anyone doing genotypic pathway analysis aka the combinatorial approach that PL is doing.
Remember that PL has gotten where it is now without the DecodeME data. A paper is due on that shortly. Gardner in his paper referred to a small COVID-19 combinatorial study which was far more effective than the very large GWAS studies in elucidating mechanisms and uncovering possible treatments – so while more data is better, PL may not need those huge datasets to move forward. Indeed, Gardner said the new paper will validate what they found in the first studies and provide new leads and they are already in the midst of a 400 person clinical trial.
Again, the results thus far – which have made sense – did not come from DecodeME. DecodeME was used to assess the validity of the results but did not produce them.
My understanding is that the datasets are necessary for the analytic work, which helps them uncover potential subsets, finding the mechanisms driving them. Once they’ve done that, though, they no longer need the datasets. At that point they need to identify biomarkers, uncover drugs that can move the needle on them, and, since they have demonstrated that it makes sense to try them, to test them, and produce diagnostic tests to uncover the subsets.
I don’t know much about business models but I assume diagnostic tests are one place here PL makes some money. I imagine, though, that the real payoff for it comes when PL publicly shows that its process works and more companies and disease groups sign on to have them do their analyses and come up with solutions.
Yes, bigger datasets provide more information and ultimately a better understanding of these diseases but they don’t necessarily need them. All they need is enough data to uncover disease signatures, communities, and mechanisms – which they’ve already done.
Let me agree you countered many of my points of scepticism towards the company.
When it comes to being a startup or not, the info I found so far states that in 2024 they had another round of venture capital funding and now have around 34 employees. Recruiting venture capital near always means that the company still is in the phase of higher expenses then income, often referred to as burning capital. Looking at it in a possitive way, it means that they are investing more then they have steady income to fund it themselves.
So long a company (likely, as that is very common for companies still relying on successive capitalisation rounds) burns more money then it has income, it is in my books still a startup. Most startups fold, some get bought and even fewer find a way to sustained profit themselves. It is a good sign they last already so long. When they get bought, the new owner historically often demonstrates very few regards to the standards and ideals of the founders.
Having seen this pattern many times plus being disappointed many times as an ME/CFS patient can make it hard to remain hopefull at times and make me sour I must admit. I still hope to be one day proven wrong. And, even if it doesn’t seem like it, I still appreciate your work on this particular blog. I just fail to share your optimism.
Thank the gods 🙂 (Battlestar Galactica quote)
I guess many startups start with the focus of being sold leaving the employees with riches beyond belief. Not all companies are built that way though. Is Gardner and company’s goal to cash out at some point and count their money?
I don’t know, but I’m skeptical that that’s the whole story here. Sure just about everyone wants to be rich if for nothing more than the validation it brings.
That would not get me up in the morning, though. It seems like PL is attempting to change how we think of and study diseases. Now that is a big reward! Just think if you could achieve that. (That’s REAL validation) That would get me up in the morning.
Dear dejurgen,
Is it possible for you to use chat GPT to get your point across in 2 paragraphs. I’ve used up my energy for the day reading your endless comments. After which I have learned nothing useful, positive or hopeful.
Some of us who are on the edge of despair come here looking for hope. It doesn’t have to be perfect, guaranteed, and delivered tomorrow. We just want a glimmer to get us through a bit. Don’t take that away from us with your unnecessary negativity, inaccuracies (I thought all those quotes were from the company website), misspellings, and desire to completely monopolize this space.
Dear Roger,
I have no desire to monopolize this space. I have since long proposed expandable comments on this site, where the first 10 to 20 lines are shown and the reader can expand to see more if desired. It is a standard on many sites but Cort’s choices are his to make and I respect that.
My search for answers and many long writtings cost me more energy and health / recovery potential than most readers might imagine. I do not do it for pleasure nor so called honor.
If you think my input is useless or useless to you, please ignore reading any of my comments. There are many people who feel like you and there are other people who feel that from time to time I get genuine deep ideas. Quality is hit and miss for me too.
For me it’s a dilemma too. Do I bug the many people who have no use to reading my writtings and tank my quality of life and recovery potential in the hopes that over time I can contribute to actual answers for this dissease or just try and have some more health and quality of life for my own? Do I not only waste your time and energy but my own too?
As to misspellings, not everyone has English as a first language. Having ME/CFS and writting difficult texts in another language is challenging.
Kind Regards, dejurgen
My search for answers and many long writtings cost me more energy and health / recovery potential than most readers might imagine.
Believe me, I can imagine – and sympathize!
You have so many insight DeJurgen – you are a creative thinker and thanks for bringing that to us. Please note that a blog that puts things together is always very welcome!
Thank you for your kind words Cort.
I try and work on a bigger and coherent overview. I learned that smaller blog-sized parts can stand on their own without contradictions but when you put them next to each other things fall apart. That forces a series of later revisions of all parts. That IMO will waste any chance to capture the attention of professional researchers.
If / when that is out and published, skilled writters like you will be appreciated to make it accessible to a wider audience. My main skill is analysis, not writting. I will have to write the initial text though since any schematics or summaries are still completely incomprehensible.
Difficult points are hard to make in 2 paragraphs. Summarizing them with GPT produces useless content. I did not intended to continue on this conversation, but I try to do this here for you an others:
* A large amount of people on this forum are very wary of what they call Big Pharma. They believe they are only in it for the money and will go to great lengths to maximize profits. They don’t trust Big Pharma one bit to advance the field.
* In many fields, including technology (my own), startups (companies that remain in the stage of burning capital provided by successive venture capital rounds) are on a constant search to find a way to monetization. If they succeed they become multimillionaires. If they fail before capital runs out, they have nothing for years of poorly paid effort.
* I my field most of the startups that succeed to $$ end up at lower behavioral standards then what was usual in Big Tech so far.
* In this field, personalized health data plus genetic information is the new gold. That holds tripple so in any company using AI as a main tool.
* The value of that very sensitive data is highly dependent on how much restraints are attached to it. That holds for the startup but triple so for a potential big company buyout.
* The past has proven that many startups holding large amounts of data are bought mainly for their data treasure. It also has shown that data privacy rules and previous anonymization of data are undone in record pace. It costs plenty of money and effort to truly anonymize data and decreases value for takeover candidates.
* Health data of chronicle ill people can easily be weaponized against said chronicle ill people and create true havoc in their lives.
* Therefore IMO such sensitive personal health data is only safe-ish in well funded organizations who are determined to remain independent, prioritize data safety over any potential income source and have deep skill, knowledge and spent plenty of effort to maximally protect said data.
=> My points:
* be very AWARE of the very real risks of providing any deep personal information to startups in far more need to find a route to monetization then Big Tech and Big Pharma
* in an AI first health company, think about any offer such startups provide and what it could contribute to the value of their real gold: deeply personal health details
* do not judge the risk by what they promise, but by what happens if a vulture corporation buys them out or buys their data treasure when they go bankrupt and are unable to protect it any longer
=> So I admit I sounded more then harsh to this particular company. I am in no position to judge their personal intend. I fully agree. I failed to make clear that my very strong feelings are against the risks imposed by their category of business: a starting company in the fields of both AI and genetic health. Regardless of their intend, that is *bound* to attract the eyes of plenty of eager vultures and small companies are often not strong enough to keep fending them off even if they really wanted too.
That point in my opinion is long term more then relevant to patients here. Desperate patients are willing to take risks in exchange for a sparkle of hope, have few energy left to search out how to defend their interests and massively underestimate what harm can be done if their information gets aqcuired by the wrong people.
I can see the counter argument here: most readers didn’t provide any information. My simple counter argument is: chances are very high more ME/CFS patient’s data will be needed to make a dent, and patients here are an ideal public for contributing to that. I have no intent to
“take hopes away with unnecessary negativity”, rather the contrary: to provide IMO essential info on the risks going forward. Understand that if ones very detailed health information gets in the wrong hands, much more can be losed then hope.
@Cort: feel free to delete all my previous comments here (not this one) and replace by “deleted on user request” if you feel that is the right thing to do.
Dear dejurgen,
I respect your views and passion and will simply say:
1. Consider starting your own newsletter, blog or Facebook page to promulgate your ideas further
2. Your very long comments are overwhelming in an energy limiting site
3. I mentioned misspellings sarcastically as you were so harsh in your expectations of a company that’s trying to help us, yet you failed to use simple spell check
4. Long comments on a blog will not “contribute to actual answers for this dissease”
5. I’ve already lost my health. If you want my data for research, please take it!
6. You’ve made your points, no need to reply further. Thank you
No need to delete earlier comments. I’m sure you were not alone in your concerns.
Thanks for providing your experience and insights in this area. Everyone should note, though, that as of now, these worries do not apply to PrecisionLife as my understanding is that they’re getting all their data from public databases where patient concerns have been taken care of.
I understand the feelings toward Big Pharma and I share some of them. Let me say, though, that that attitude is completely counterproductive to what we want to accomplish.
Indeed, perhaps our chief goal is to find a way to get “Big Pharma” interested in and devote resources to this field. All you need to do to understand why that’s so is to go back several decades compare the treatments for rheumatoid arthritis then (steroids) and now (dozens are available).
You might also consider how well relying on small pharmaceutical companies like Hemispherx/AIM has gone.
Thank you and Rick as well for your comments.
My initial response was very defensive, and too harsh when discussing a company I did not research enough about.
I still feel we should take great care towards further developments of handing over in depth health information in combination with in depth analysis.
The PACE trial in essence was 641 ill people handing over modest amounts of health information and the right to analyze it in seeking to help themselves and the community. Few more information then their responses on questionairies at the start and the end of the trial plus some very wonky analysis lead us to what we all know: decades of setback of the field and countless people who heavily suffered directly from it.
Data plus analysis is not per definition harmless, and harm does not limit itself to those who agree to participate.
Roger, I find your comment “a waste of my energy”. Who forced you to read Dejurgen’s comments? Who forced you to reply to them? People with scientific minds appreciate respectful debate – that, in essence, is what science is. Most people have forgotten this, but science isn’t “what men in white lab coats say” – it’s the scientific method of questioning everything, being skeptical of everything, until something is repeatedly proven to be as close to factual as possible. If you want “hope,” there are a million snake-oil salesmen that will sell it to you (I’ve been to dozens over the years). If you are afraid of science and debate, then you really should conserve your energy and stay off of comment sections. Who are you to dictate what the rest of us can read? Who do you think you are?
Dear Rick,
Could you specify exactly where I said “a waste of my energy”
I’m a nobody and don’t seek to dictate what people can read. But I did find dejurgen’s comments to be negative and inaccurate. He has a right to his opinion and I accept that.
Well said.
From both your and Cort’s comment, I learned that my usage of quotes can lead to confusion. While correct grammar, I’ll use incorrect grammar from now on and replace them with single quotes for emphasing ‘read this with non-conventional meaning usage of quotes’ on Healthrising.
This is good news. Almost no pharmaceutical company wants to invest in ME/CFS, or even collaborate in units to fund studies. We are in a complex disease and any initiative adds up.
On the other hand, I know I am getting off topic but: could you tell us if the findings that have given the Nobel Prize in Medicine to three researchers could benefit research into ME/CFS?
The winners identified the “security guards of the immune system”, regulatory T cells, which prevent immune cells from attacking our own body. In the case of ME/CFS there is research on these cells and some points in common with the research. At ACSFCEM we are discussing the issue but we have not yet been able to talk about it with specialized doctors.
”finding treatments that are targeted to specific biologically based subsets which, in ME/CFS,”
This is the key to many diseases and treatments, and not one size fits all. This is true modern science.
We’ll see if PL can pull this off but finding biologically based subsets is where things are heading. Nancy Klimas said – we have to get subset based trials. If not PL somebody else is going to decipher and treat these diseases this way. It’s the future.
Very encouraging to read of companies like this who have understood that these diseases are quite different from the classic illness model.
It sounds like they have also identified a way forward that helps investors see why it’s good to invest.
I’m delighted to read of such approaches, that recognize the complexity and individuality among humans, and the need for much more targeted definitions and treatment approaches.
Let’s hope they can continue at a similar pace and achieve progress that patients can benefit from.
I really liked the “Respecting the biological complexity of disease” quote. That really resonated with me.
Ditto.
Their ingenuity and original ideas should be congratulated, not criticised. This is exactly what we need for a complex illness like ME – new innovative ideas which will hopefully help researchers and doctors start to understand this illness a little better.
This sounds like exactly the kind of holistic, complex research that I have been PRAYING for. I really hope they can deliver some understanding and treatments for all of us.
Thanks for covering this Cort. I was listening to the David Tuller interview with Chris Ponting and he mentioned Precision Life as a potential source of treatments and I thought it seemed really interesting.
I hope PrecisionLife will also decide to take their approach to tackle fibromyalgia
I wouldn’t be surprised. Gardner noted that the results were very close to FM. 🙂
If there’s one thing I’ve learned in over 20 years of illness, it’s that profit-driven medicine is not interested in curing chronic disease. It’s a structural problem with our capitalist, money-driven society, not a moral one. The whole machinery – pharma companies, health insurance industry- literally profits off of our suffering, our endless doctor appointments, our endless search for answers. I’m not sure how Cort has maintained this site after so many years of dead ends- and I’m thankful for his courageous contributions to the discourse- but I am deeply skeptical of this “start up”. I hope I am wrong. And for everyone in the comment section yelling at people for “negativity”- playing the role of the gatekeeper – I’d invite you to look up the definition of “science.” It literally means “be skeptical of everything until you can prove otherwise.” No scientific breakthrough has ever been made from “hope.”
:). There was a time when the field seemed like it was spinning its wheels a bit – where we were stuck on the HPA axis, inconsistent immune studies with some EBV thrown in. With the advent of the omics particularly metabolomics seems like it’s been plowing forward. (This is why NIH funding is so important).
We are also seeing more treatment options pop up. I don’t have the feeling that they’re that tied to research findings – it seems more things are simply being tried (like stellate ganglion blocks…).
Researchwise we haven’t gotten to the point where the findings are strong enough for pharmaceutical companies to plunk money down on big trials. To me that’s the big hurdle facing us. Big studies like DecodeME that legitimize this disease can only help.
HERE HERE!!!
Cort, I’m grateful for the Steve Gardner interview.
While I have believed in the role of genetics since 1994, I’m grateful to Steve Gardner for introducing the concept of confirmation bias—a valuable lens through which to understand how people often process information about health.
Technical evolution has brought us the science of genetics, offering deeper insights into the true causes of many diseases. It’s time we move beyond outdated Edwardian-era beliefs that attributed illness to vague concepts like miasma.
When individuals lack education about certain diseases, they may fall into confirmation bias—interpreting new evidence in ways that reinforce their existing beliefs—instead of exploring cause-and-effect relationships grounded in genetics and epigenetics. While pharmaceuticals can offer relief or manage symptoms, they often come with side effects and may fail to address the underlying biological mechanisms of illness.
For example, human genetics have evolved to support an omnivorous diet. The growing trend toward veganism may influence health outcomes—either positively or negatively—depending on an individual’s unique genetic and epigenetic profile.
Moreover, the genetic blueprint itself can be influenced by chronic stress and trauma. These experiences can alter DNA methylation patterns, a key epigenetic mechanism, potentially triggering a cascade of interconnected medical conditions. This highlights the importance of understanding health through a multifactorial lens—one that includes genetic, epigenetic, environmental, and psychological factors.
Thanks! I really enjoyed talking to Steve. This (below) is such a good point – and doesn’t it help explain a lot of the history of ME/CFS.
People see what they want to see. Without showing that biological mechanisms are driving these diseases, some people will still see “wastebasket disease” and malingerers. I wonder if confirmation bias is one of the biggest problems that our deeply divided sociaties face. W
I think we should all get a course in logic, rhetoric, debate, and confirmation bias.
Cort:
ME/CFS has, from the start, been shaped by confirmation bias—both in public perception and within the medical field. Even basic principles of logic and critical thinking have failed to correct this, which helps explain why the condition remains unresolved.
The only meaningful path forward is to seek explanations grounded in biological mechanisms—a direction that Steve actively explores. I believe this is the only approach capable of revealing true cause-and-effect relationships, rather than relying on speculation or assumption.
We need only look at how many chronic illnesses remain poorly understood due to a mix of unfounded skepticism, limited knowledge, or simple disinterest.
To make real progress, we must move beyond personal agendas and flawed reasoning that perpetuate bias. These failures have led not to solutions, but to misdiagnosis and the endurance of outdated, symbolic, or myth-driven beliefs.
Cort:
We are once again experiencing a significant shift—and accompanying criticism—in our understanding of genes and their connection to health.
This moment recalls past scientific breakthroughs that initially faced skepticism. Rosalind Franklin provided critical evidence that contributed to the discovery of DNA’s double helix structure. Barbara McClintock defied the long-held belief in a fixed genetic code by uncovering that genes can move within the genome. And Nettie Stevens was the first to show that sex determination is governed by chromosomes—the carriers of genetic information.
Later, Jennifer Doudna and Emmanuelle Charpentier faced criticism during a prolonged patent dispute over their CRISPR-Cas9 gene-editing technology, which placed their groundbreaking work in direct competition with researchers at the Broad Institute.
As with many scientific advancements, resistance often arises—whether from fear, uncertainty, or competing interests. But such resistance must not hinder progress, especially when the goal is to improve human health.
I took tetracycline for 1.5 years at the age of 14.
It took many years for tetracycline manifest into disease
Why would I take more drugs that nobody knows if these drugs are safe.knowbody knows the long term effects of drugs
Many of us sufferers cannot take drugs
What i have learned by listening to real board certified GOOD doctors is that all drugs are toxic.
Ive worried for many years that this is the direction of all of this would eventually end up…MORE DRUGS
It’s always about the $$$$
Go online…you will find many companies trying to take your money and profit from your illnesses…not just me/cfs. People start companies with one goal in mind…PROFIT.
I know of a woman that is wealthy that was desperately ill with me/cfs and spent tens of thousands on false promises on her me/cfs.She came home from the usa in worse shape than before she left for treatment.
Once they get your money, there is nothing you can do to get it back.
With millions of sufferers its not too difficult to realize there is potentially a shitload of money to be made off of us all
I’ll stick with the researchers that use private funding and researchers that are in this because they have a loved one that suffers.
Roonie, nothing is ever simple in life. Several medications used to test for mast cell disease triggered my narrow angle glaucoma. This was nobody’s fault; just a rare occurrence. Now I take glaucoma drops several times a day to try to save my vision. And I am glad the pharmaceutical companies developed them.
On the other hand, a drug was developed for pregnancy morning sickness just because it had a huge marketing potential. They combined two drugs and vitamin B-6. These were already on the market so no special testing in pregnant women was conducted even though a combination of drugs can have different effects than a single drug. The combination product was approved in just 28 days.
It would have probably been a rather benign drug except that new laws had been passed requiring proof of safety and efficacy. The drug was never shown to be more than 11% effective than a placebo. So without notice to any prescribing doctors, the drug company made changes in the medication that made it much more potent.
Reports of children with missing limbs began to come in to regulatory agencies all over the world. Our son was one of the children born with a missing hand. When we asked the FDA about it, whistleblowers told us to pursue this drug and helped us behind the scenes.
It took 10 years and much litigation to get the drug removed from the world-wide market.
This is pretty amazing stuff from Dr Younger:
https://m.youtube.com/watch?v=Hb_tzJQfjeM
The brain is clearly the key issue in ME/CFS.
All work to find ME/CFS pathways and biomarkers depends on the quality of ME/CFS cases that investigators are using.
We need a Biomarker and Biobank protocol to build up databases of clinically diagnosed CCC/ICC ME/CFS patients, so that we have the high quality ME/CFS cases for training AI’s and biomarker discovery. We also need a biobank for blood and tissue from 2-Day CPETs and Moreau Cuff and Hexoskin, so that we can have a biobank of objectively diagnosed ME/CFS patients to test biomarkers or train A.I.
Right now Precisions Life, Open Medicine Foundation (Melbourne Collaboration), and Decode M.E/CFS all have studies from the UK Biobank (which uses self-reported CFS diagnosis and doesn’t adhere every patient being diagnosed CCC or ICC (PEM). Or they have used UK ME/CFS biobank which unfortunately uses CCC “and/or CDC 1994” – which means the bad are mixed in with the good.
Precision Life’s Combinatorial Analytics used UK Biobank samples which cannot be considered ME/CFS high quality samples.
ME/CFS patients and researchers do not have money to burn.
We need a strictly regimented Biomarker and Biobank protocol that involve clinically diagnosed ME/CFS CCC/ICC patients to ensure high quality cases for biomarker discovery, A.I training, and drug targeting.
We have to begin with high quality inputs, to get equally high quality outcomes.
Precision Life and Metrodora and other For-Profit companies are welcome to the ME/CFS world of research – but they need to be using high quality ME/CFS cases to do their important work.
Yes, high quality samples are key and I hope we get better ones focused on CCC/ICC. These samples may be good enough, for now, though, as PL’s findings are in sync with what we know about ME/CFS. Even studies based on the Fukuda definition largely replicated results from studies that used better definitions. While we definitely want those ICC/CCC based samples, I think what we have is good enough to move forward.
I enrolled in the Melo study last year and just received notification today that my results should be available later this week. Thank you Cort for all that you do to help us understand and move forward.
Very nice! Such a cool study. I wonder what they will show….:)