International Long COVID Day highlights need for diagnostics as PrecisionLife unlocks genetic breakthroughs

March 15th marked International Long COVID Awareness Day. This debilitating condition is estimated to affect at least 65 million people and is increasing annually, creating a rising healthcare burden of over $1 trillion globally.

Long COVID has a variety of commonalities with  Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS),  a complex, chronic illness characterised by profound fatigue that is not improved by rest and worsens with physical or mental activity. Both conditions are difficult to diagnose and treat due to the large number of different disease symptoms and organs that are affected.

However, in spite of their enormous personal and public health impacts, we still have no tools to accurately diagnose patients and no drugs that treat the underlying causes of the diseases. This has led to widespread misunderstanding, lack of awareness, and even denial of the diseases in the clinical and social care communities, which further harms sufferers.

UK precision medicine company  PrecisionLife leverages AI and combinatorial analytics to find deeper genetic associations than traditional analysis methods, explain more about how complex diseases manifest in patients, and uncover hidden patterns in high-dimensional, complex patient data. This can enable breakthroughs in diagnostics, drug discovery, and precision medicine. 

I recently met PrecisionLife co-founder and CEO Steve Gardner at the Hevolution global healthspan summit in Riyadh, where he shared the company’s insights and their success in bringing new insights to aid the diagnosis and treatment of long COVID and other complex chronic diseases. 

Transforming disease understanding through advanced data analytics

PrecisionLife’s AI-driven approach goes beyond traditional genome-wide association studies (GWAS) by identifying combinations of genetic and non-genetic factors that drive disease in different patient subgroups.

Gardener explains the technological foundation of the company:

“Technologically, we reimagine how you analyse data, and this is really the genesis of the company—bringing two sets of technology together. One that I had developed over the last 20 years and another that my co-founder, a mathematician and computer scientist, had been developing for even longer—actually 30 years. 

We realised that if we put those two things together, we would actually have a way of dealing with these hyper-complex, big patient datasets with all of the genomic information, all the multi-omics, proteomics, epigenetics, and everything else like that, and correlating it with things like longitudinal electronic medical records (EMR) or electronic health records (EHR) and epidemiological and environmental information.”

The scientists had seen the transformation in the delivery of oncology:

“It’s grown from being an organ-mediated diagnosis into “this molecular characterisation of tumours, and a nuanced palette of options for a clinician to choose from based on the makeup of specific tumour types. 

I wanted to do the same for all those diseases that didn’t work.”

This has led to the company tackling highly complex diseases like Alzheimer’s, long-term COVID-19, schizophrenia, and endometriosis — conditions where there isn’t a single gene responsible but rather a network of genetic and non-genetic components influencing risk, disease onset, and progression.

Gardner calls ME/CFS “the poster child for hard diseases.”

According to Gardener, there are many different genetic components within these diseases, but also non-genetic components that influence, increase risk, trigger disease, and show how that disease will manifest itself in individual patients. 

“Getting into that level of understanding of the drivers of disease biology—and the patients for whom a specific driver was relevant, and therefore which therapy they might respond to—was not something that we could do with traditional genetic analysis, the genome-wide association study-based approaches.”

Since then, the company has applied this methodology to around 60 different diseases, gaining what Gardener describes as “world-leading insights into many of those.”

In the case of long COVID, Gardner shared:  

“Today, we have zero approved diagnostics for long COVID. We have zero approved disease-modifying therapies. We don’t even know which organs in the body are involved for an individual patient. 

We know it impacts many tissues, but we know little about it.”

A key aspect of PrecisionLife’s approach is that it is based on the belief that there are many different causes of disease in patients. 

Patients may be given the same diagnosis just because their symptoms appear similar, e.g., they all have fatigue, but that doesn’t mean their diseases are the same.

Therefore, drugs that benefit one patient may not work in another if their cause of disease (their disease ‘mechanism’) is different. 

Gardner explains, “We generate patient stratification biomarkers to deliver precision medicine insights across dozens of chronic diseases.”

A series of key genetic discoveries in COVID, Long COVID, and ME/CFS

PrecisionLife has leveraged its combinatorial analytics platform to make significant genetic discoveries related to COVID, long COVID, and CFS/ME:

• In 2020, it identified 68 novel gene targets linked to severe COVID-19, of which 70 percent were later validated. This resulted in 29 opportunities for approved drugs and candidates that could be repurposed as COVID-19 treatments. Thirteen of these drug candidates were evaluated in clinical trials.
• In 2022, it provided the first replicable genetic risk factors for ME/CFS in over 30 years, identifying 14 genes and 199 SNPs, explaining 91% of studied cases.
• In mid 2023, PrecisionLife accessed Sano Genetics’ GOLD long COVID patient dataset.  It looked at two sets of

In the latter’s case, Gardner detailed: “We identified over 5,000 SNPs and 73 genes associated with long COVID. This is massively more than has been found by any other study to date, even those that have analysed over 50,000 patients10.”

.Nine of the genes were also found in the original 14 genes from the ME/CFS analysis.

First-ever replicated genetic associations for ME/CFS & Long COVID discovered

Currently, PrecisionLife is collaborating with the  Metrodora Foundation and its Institute, based in Salt Lake City, Utah. Metrodora was set up to bring researchers, doctors, and patients together to rapidly improve diagnostics, treatments, and outcomes in complex conditions(like ME/CFS and long COVID.

PrecisionLife is running a series of clinical studies on 1,000 patients – 500 with ME and 500 with long COVID. 

“The speed and precision of our progress in these trials is remarkable,” said Gardner. 

“We identified and published the first-ever replicated genetic associations in both ME/CFS and Long COVID.”

Gardner detailed 

“We have started returning results to Metrodora patients based on the specific disease risk signatures a patient has and the symptoms they are most likely to experience. 

“Patients come to us, and they say, this is brilliant. You know, it’s the first time a test has reflected my personal view of what’s going wrong in my disease. And clinicians love it because it guides them to amending therapy.”

According to Gardner, this has great possibilities for personalised medicine:

“Just think about this: clinically validated novel targets and the ability to select patients who will benefit from drugs modulating that target. That’s incredible. It’s like the NHS-led RECOVERY trial in COVID-19 that discovered dexamethasone—but on steroids—because we’re using genetic evidence to pick the most promising treatments.”

Further, last month, the partnership successfully reproduced key genetic risk factors for Long COVID in diverse populations, confirming 88 percent of previously identified genes. 

This marks the strongest genetic evidence for Long COVID and supports biomarker-driven diagnostics and targeted treatments. 

Additionally, 11 out of 13 drug repurposing candidates were validated, paving the way for clinical trials and personalised therapeutics.

What’s exciting about PrecisionLife’s work is its potential across a variety of spaces in medical research. 

The company initially focused on biopharma, working with pharmaceutical companies and Contract Research Organizations (CROs) to uncover novel drug targets.

For example, as AGardner detailed, “When you’ve seen the same target underpinning disease in 30–40% of a major market, that might offer an opportunity to indication-switch an existing asset into a new indication. There’s real value in that.”

PrecisionLife is also using genetic-based diagnostics to improve early disease identification and clinical decision-making. 

“Take endometriosis—it takes 8–10 years for a confirmed diagnosis via surgery. If we can turn that into a buccal swab that reports in two weeks and refers a patient accurately to a gynecologist that’s a game-changer. 

Individually, these advances are crucial for patients. But when you add up the costs of delayed diagnosis and misclassification, they become very significant.” 

Additionally, PrecisionLife’s insights can optimise patient triage, Gardner shared: 

“For example, we’re working with the healthcare system where 5,000 patients are referred to rheumatology yearly due to a non-specific ANA test. Only 10 per cent actually have a rheumatological condition. That’s a massive misclassification problem blocking the system.”

Rather than building its own diagnostic business, PrecisionLife is licensing its tests and decision support systems to existing healthcare infrastructures. 

“We don’t want to build a massive diagnostic business ourselves. The platforms we use are standard and available globally. We can license the content and clinical decision support system to operate these tests across multiple markets. And what’s exciting is that it’s almost disease-agnostic.” 

This model allows for scalability, making their technology accessible across multiple conditions and healthcare markets worldwide.

Is the future ‘actively protective’ genes that shield against disease?

PrecisionLife is pioneering a new approach to disease prevention by identifying ‘actively protective’ genes—genetic factors that shield certain high-risk individuals from developing diseases. Traditionally, genetic research focuses on identifying disease-causing mutations, but this new method flips the process, searching instead for individuals who should have developed a disease but remain healthy despite having high genetic risk and exposure to disease triggers. 

A recent study on ME/CFS identified nine protein-coding genes with protective effects, potentially counteracting known disease mechanisms related to insulin signaling, stress response, and autoimmunity. 

These findings open up possibilities for new preventative therapies, including drug targets that function similarly to statins, which lower cholesterol to prevent heart disease. 

Additionally, some of these protective genes could be harnessed for mRNA-based treatments, using the same technology as COVID-19 vaccines to boost natural disease resistance. This could lead to personalised protective treatments, extending healthspan and improving quality of life for high-risk individuals before disease ever develops.

Lead image: Freepik.