Study is expected to result in new clinical laboratory test biomarkers based on proteins shown to be associated with specific diseases
In January, the UK Biobank announced the launch of the “world’s most comprehensive study” of the human proteome. The study focuses on proteins circulating throughout the human body. Researchers involved in this endeavor hope the project will transform disease detection and lead to clinical laboratory blood tests that help diagnosticians identify illnesses earlier than with conventional diagnostics.
Building on the results of a 2023 pilot project that studied “the effects of common genetic variation on proteins circulating in the blood and how these associations can contribute to disease,” according to a UK Biobank news release, the 2025 UK Biobank Pharma Proteomics Project (UKB-PPP) plans to analyze up to 5,400 proteins in 600,000 samples to explore how an individual’s protein levels changes over time and how those changes may influence the existence of diseases in mid-to-late life.
The specimens being analyzed include 500,000 samples extracted from UK Biobank participants and an additional 100,000 set of second samples taken from volunteers up to 15 years later.
“The data collected in the study will allow scientists around the world to conduct health-related research, exploring how lifestyle, environment, and genetics lead through proteins to some people developing particular diseases, while others do not,” Sir Rory Collins, FMedSci FRS, professor of medicine and epidemiology at University of Oxford and principal investigator and chief executive of the UK Biobank, told The Independent.
“That will allow us to identify who it is, who’s likely to develop disease well before they do, and we can then look at ways in which to prevent those conditions before they develop,” he added.
“It really might be possible to develop simple blood tests that can detect disease much earlier than currently exists,” said Naomi Allen, MSc, DPhil (above), chief scientist for UK Biobank and professor of epidemiology at Oxford Population Health, University of Oxford, in an interview with The Independent. “So, it adds a crucial piece in the jigsaw puzzle for scientists to figure out how disease develops and gives us firm clues on what we can do to prevent and treat it.” Clinical laboratories may soon have new test biomarkers that help identify proteins associated with specific diseases. (Photo copyright: UK Biobank.)
Developing New Protein-based Biomarkers
A proteome is the entire set of proteins expressed by an organism, cell, or tissue and the study of the proteome is known as proteomics. The proteome is an expression of an organism’s genome, but it can change over time between cell types and growth conditions.
The human genome contains approximately 20,000 genes and human cells have between 80,000 and 400,000 proteins with specific cells having their own proteomes. Proteomics can help ascertain how proteins function and interact with each other and assist in the identification of biomarkers for new drug discoveries and development.
“This is hugely valuable, because it will enable researchers to see how changes in protein levels within individuals over mid- to late-life influence the development of a whole range of different diseases,” said Naomi Allen, MSc, DPhil, chief scientist for UK Biobank and professor of epidemiology at the Oxford Population Health, University of Oxford, in The Independent. “It will accelerate research into the causes of disease and the development of new treatments that target specific proteins associated with those diseases.
“The pilot data is already showing that specific proteins are elevated in those who go on to develop many different types of cancers up to seven years before a clinical diagnosis is made. And for dementia, up to 10 years before clinical diagnosis is made,” she added.
According to the project’s website, the UK Biobank’s proteomics dataset will allow researchers to:
Examine proteomic and genetic data from half a million people to provide a more detailed picture of the biological processes involved in disease progression.
Examine how and why protein levels change over time to understand age-related changes in healthy individuals.
Utilize proteomic data together with imaging data to understand disease mechanisms.
“Data from the pilot study has shown that specific proteins are substantially elevated in individuals with autoimmune conditions like multiple sclerosis and Crohn’s disease and so on,” Allen noted. “So, you can see how a simple blood test could be used to complement existing diagnostic measures in order to diagnose these types of diseases more accurately and perhaps more quickly.”
An Invaluable Resource of Knowledge
The initial UK Biobank started in 2006 and, to date, has collected biological and medical data from more than half a million individuals. The subjects of the UKB-PPP study are between the ages of 40 and 69 and reside in the UK. The database is globally accessible to approved researchers and scientists engaging in research into various diseases.
The full dataset of the latest research is expected to be added to the UK Biobank Research Analysis Platform by the year 2027. The newest study is backed by a consortium of 14 pharmaceutical firms.
Allen also noted that evidence from the research has emphasized how some drugs may be useful in treating a variety of conditions.
“Some proteins that are known to be important for immunity are related to developing a range of psychiatric conditions like schizophrenia, depression, bipolar disorder and so on,” she told The Independent. “And given there are drugs already available that specifically target some of these proteins that are used for other conditions, it presents a real opportunity for repurposing those existing drugs for these neuropsychiatric conditions.”
This type of comprehensive study of the human proteome may have a great impact on patient diagnosis and treatment once the study is completed and the results are disclosed.
“The data will be invaluable. The value of the data is infinite,” Collins told The Independence.
Since it is clinical laboratories that will be engaged in testing for proteins that have become associated with specific diseases, this new UK Biobank study has the potential to expand knowledge about useful protein markers for both diagnosis and therapeutic solutions (prescription drugs).
Declining health of UK’s population also affecting performance of the country’s national health service, report notes
England’s National Health Service (NHS) is “in serious trouble” due to long waiting times, outdated technology, misallocated resources, and numerous other problems, with dire consequences for the country’s populace. That’s according to a new report by NHS surgeon and former Health Minister Lord Ara Darzi, OM KBE FRS FMedSci HonFREng, who was tasked by the United Kingdom’s new Labor government to investigate the ailing healthcare system. His report may contain lessons for US healthcare—including clinical laboratories—as well.
“Although I have worked in the NHS for more than 30 years, I have been shocked by what I have found during this investigation—not just in the health service but in the state of the nation’s health,” Darzi stated in a UK government press release. “We want to deliver high quality care for all but far too many people are waiting for too long and in too many clinical areas, quality of care has gone backwards.”
Many of the problems he identified relate to wait times.
“From access to GPs (general practitioners) and to community and mental health services, on to accident and emergency, and then to waits not just for more routine surgery and treatment but for cancer and cardiac services, waiting time targets are being missed,” he wrote in his report.
For example, “as of June 2024, more than one million people were waiting for community services, including more than 50,000 people who had been waiting for over a year, 80% of whom are children and young people,” he wrote.
Accident and emergency care (A/E) “is in an awful state,” the report noted, “with A/E queues more than doubling from an average of just under 40 people on a typical evening in April 2009 to over 100 in April 2024. One in 10 patients are now waiting for 12 hours or more.”
“In the last 15 years, the NHS was hit by three shocks—austerity and starvation of investment, confusion caused by top-down reorganization, and then the pandemic which came with resilience at an all-time low. Two out of three of those shocks were choices made in Westminster,” said NHS surgeon and former Health Minister Lord Ara Darzi in a government press release. “It took more than a decade for the NHS to fall into disrepair so it’s going to take time to fix it. But we in the NHS have turned things around before, and I’m confident we will do it again.” (Photo copyright: Health Data Research UK.)
Delays in Other Critical Tests
Genetic test results are lagging as well. “In 2024, more than 35,000 genomic tests are being completed each month but only around 60% on time,” Darzi wrote.
He also noted that “only around 5% of eligible patients with brain cancer are able to access whole genome sequencing (WGS), which is important for treatment selection.” Just two-thirds (65.8%) get their first treatment within 62 days, and more than 30% wait more than 31 days for radical radiotherapy, according to the report.
Overall, “the UK has appreciably higher cancer mortality rates than other countries, with no progress whatsoever made in diagnosing cancer at stage one and two between 2013 and 2021,” he wrote.
Patients have also experienced delays in access to cardiovascular treatment. For example, in 2013-2014, high-risk heart attack patients waited an average of 114 minutes for intervention to unblock an artery, Darzi noted in his report. However, in 2022-2023, the average time was 146 minutes, a 28% increase.
“For the most part, once people are in the system, they receive high quality care,” he wrote. “But there are some important areas of concerns, such as maternity care, where there have been a succession of scandals and inquiries.”
Key Factors Leading to Delays
Darzi pointed to four key factors that have led to the problems.
Lack of funding. “The 2010s was the most austere decade since the NHS was founded, with spending growing at around 1% in real terms,” Darzi wrote, compared with a long-term average of 3.4%.
One result was that administrators took funds from the capital budget to cover day-to-day needs, leading to “crumbling buildings that hit productivity,” he noted.
“The backlog maintenance bill now stands at more than £11.6 billion and a lack of capital means that there are too many outdated scanners, too little automation, and parts of the NHS are yet to enter the digital era,” he wrote.
The COVID-19 pandemic. Given the preceding “decade of austerity,” NHS had fewer resources to deal with the crisis than most other high-income health systems, he wrote. As a result, NHS “delayed, cancelled, or postponed far more routine care during the pandemic than any comparable health system.” This led to “a bigger backlog than other health systems.”
Lack of patient and staff engagement. Patient satisfaction “has declined and the number of complaints has increased, while patients are less empowered to make choices about their care,” he wrote. In addition, “too many staff have become disengaged, and there are distressingly high-levels of sickness absence—as much as one working month a year for each nurse and each midwife working in the NHS.”
Management structures and systems. Darzi laid considerable blame on the UK’s Health and Social Care Act of 2012, which led to what he described as “a costly and distracting process of almost constant reorganization of the ‘headquarters’ and ‘regulatory’ functions of the NHS.”
One consequence, he wrote, is that too many clinicians have been deployed in hospitals instead of community-based care, despite years of promises by successive governments to put more emphasis on the latter.
National Health in Decline
Along with issues within the NHS, “the health of the nation has deteriorated and that impacts its performance,” Darzi wrote. “There has been a surge in multiple long-term conditions, and, particularly among children and young people, in mental health needs. Fewer children are getting the immunizations they need to protect their health, and fewer adults are participating in some of the key screening programs, such as for breast cancer.”
Darzi’s investigation included frontline visits to NHS facilities as well as focus groups with NHS staff and patients, the press release states. He also consulted an expert reference group consisting of more than 70 organizations and examined analyses from NHS England, the UK’s Department of Health and Social Care, and external groups.
It is interesting that there is no mention of anatomic pathology and medical laboratory testing services in Lord Darzi’s report. As reported in recent years by new outlets in the United Kingdom, delays in cancer diagnoses—often as long as six months—were severe enough that, in 2018, the NHS announced funding for a program to create a national digital pathology network to improve productivity of pathologists and shorten wait times for the results of cancer tests.
Though not biomarkers per se, these scores for certain genetic traits may someday be used by clinical laboratories to identify individuals’ risk for specific diseases
Can polygenic risk scores (a number that denotes a person’s genetic predisposition for certain traits) do a better job at predicting the likelihood of developing specific diseases, perhaps even before the onset of symptoms? Researchers at the Broad Institute of MIT and Harvard (Broad Institute) believe so, and their study could have implications for clinical laboratories nationwide.
In cooperation with medical centers across the US, the scientists “optimized 10 polygenic scores for use in clinical research as part of a study on how to implement genetic risk prediction for patients,” according to a Broad Institute news release.
The research team “selected, optimized, and validated the tests for 10 common diseases [selected from a total of 23 conditions], including heart disease, breast cancer, and type 2 diabetes. They also calibrated the tests for use in people with non-European ancestries,” the news release notes.
As these markers for genetic risk become better understood they may work their way into clinical practice. This could mean clinical laboratories will have a role in sequencing patients’ DNA to provide physicians with information about the probability of a patient’s elevated genetic risk for certain conditions.
However, the effectiveness of polygenic risk scores has faced challenges among diverse populations, according to the news release, which also noted a need to appropriately guide clinicians in use of the scores.
“With this work, we’ve taken the first steps toward showing the potential strength and power of these scores across a diverse population,” said Niall Lennon, PhD (above), Chief Scientific Officer of Broad Clinical Labs. “We hope in the future this kind of information can be used in preventive medicine to help people take actions that lower their risk of disease.” Clinical laboratories may eventually be tasked with performing DNA sequencing to determine potential genetic risk for certain diseases. (Photo copyright: Broad Institute.)
Polygenic Scores Need to Reflect Diversity
“There have been a lot of ongoing conversations and debates about polygenic risk scores and their utility and applicability in the clinical setting,” said Niall Lennon, PhD, Chair and Chief Scientific Officer of Broad Clinical Labs and first author of the study, in the news release. However, he added, “It was important that we weren’t giving people results that they couldn’t do anything about.”
In the paper, Lennon and colleagues explained polygenic risk scores “aggregate the effects of many genetic risk variants” to identify a person’s genetic predisposition for a certain disease or phenotype.
“But their development and application to clinical care, particularly among ancestrally diverse individuals, present substantial challenges,” they noted. “Clinical use of polygenic risk scores may ultimately prevent disease or enable its detection at earlier, more treatable stages.”
The scientists set a research goal to “optimize polygenic risk scores for a diversity of people.”
While performing the polygenic risk score testing on participants, Broad Clinical Labs focused on 10 conditions—including cardiometabolic diseases and cancer—selected by the research team based on “polygenic risk score performance, medical actionability, and clinical utility,” the Nature Medicine paper explained.
For each condition, the researchers:
Identified “exact spots in the genome that they would analyze to calculate the risk score.”
Used information from the NIH’s All of Us Research Program to “create a model to calibrate a person’s polygenic risk score according to that individual’s genetic ancestry.”
The All of Us program, which aims to collect health information from one million US residents, has three times more people of non-European ancestry than other data sources developing genetic risk scores, HealthDay News reported.
20% of Study Participants Showed High Risk for Disease
To complete their studies, Broad Institute researchers processed a diverse group of eMERGE participants to determine their clinical polygenic risk scores for each of the 10 diseases between July 2022 and August 2023.
Listed below are all conditions studied, as well as the number of participants involved in each study and the number of people with scores indicating high risk of the disease, according to their published paper:
Over 500 people (about 20%) of the 2,500 participants, had high risk for at least one of the 10 targeted diseases, the study found.
Participants in the study self-reported their race/ancestry as follows, according to the paper:
White: 32.8%
Black: 32.8%
Hispanic: 25.4%
Asian: 5%
American Indian: 1.5%
Middle Eastern: 0.9%
No selection: 0.8%
“We can’t fix all biases in the risk scores, but we can make sure that if a person is in a high-risk group for a disease, they’ll get identified as high risk regardless of what their genetic ancestry is,” Lennon said.
Further Studies, Scoring Implications
With 10 tests in hand, Broad Clinical Labs plans to calculate risk scores for all 25,000 people in the eMERGE network. The researchers also aim to conduct follow-up studies to discover what role polygenic risk scores may play in patients’ overall healthcare.
“Ultimately, the network wants to know what it means for a person to receive information that says they’re at high risk for one of these diseases,” Lennon said.
The researchers’ findings about disease risk are likely also relevant to healthcare systems, which want care teams to make earlier, pre-symptomatic diagnosis to keep patients healthy.
Clinical laboratory leaders may want to follow Broad Clinical Labs’ studies as they perform the 10 genetic tests and capture information about what participants may be willing to do—based on risk scores—to lower their risk for deadly diseases.
Findings could lead to new biomarkers clinical laboratories would use for identifying cancer in patients and monitoring treatments
As DNA “dark matter” (the DNA sequences between genes) continues to be studied, researchers are learning that so-called “junk DNA” (non-functional DNA) may influence multiple health conditions and diseases including cancer. This will be of interest to pathologists and clinical laboratories engaged in cancer diagnosis and may lead to new non-invasive liquid biopsy methods for identifying cancer in blood draws.
This technique could enable non-invasive monitoring of cancer treatment and cancer diagnosis, Technology Networks noted.
“Our study shows that ARTEMIS can reveal genomewide repeat landscapes that reflect dramatic underlying changes in human cancers,” said study co-leader Akshaya Annapragada (above), an MD/PhD student at the Johns Hopkins University School of Medicine, in a news release. “By illuminating the so-called ‘dark genome,’ the work offers unique insights into the cancer genome and provides a proof-of-concept for the utility of genomewide repeat landscapes as tissue and blood-based biomarkers for cancer detection, characterization, and monitoring.” Clinical laboratories may soon have new biomarkers for the detection of cancer. (Photo copyright: Johns Hopkins University.)
Detecting Early Lung, Liver Cancer
Artemis is a Greek word meaning “hunting goddess.” For the Johns Hopkins researchers, ARTEMIS also describes a technique “to analyze junk DNA found in tumors” and which float in the bloodstream, Financial Times explained.
“It’s like a grand unveiling of what’s behind the curtain,” said geneticist Victor Velculescu, MD, PhD, Professor of Oncology and co-director of the Cancer Genetics and Epigenetics Program at Johns Hopkins Kimmel Cancer Center, in the news release.
“Until ARTEMIS, this dark matter of the genome was essentially ignored, but now we’re seeing that these repeats are not occurring randomly,” he added. “They end up being clustered around genes that are altered in cancer in a variety of different ways, providing the first glimpse that these sequences may be key to tumor development.”
ARTEMIS could “lead to new therapies, new diagnostics, and new screening approaches for cancer,” Velculescu noted.
Repeats of DNA Sequences Tough to Study
For some time technical limitations have hindered analysis of repetitive genomic sequences by scientists.
“Genetic changes in repetitive sequences are a hallmark of cancer and other diseases, but characterizing these has been challenging using standard sequencing approaches,” the study authors wrote in their Science Translational Medicine paper.
“We developed a de novok-mer (short sequences of DNA)-finding approach called ARTEMIS to identify repeat elements from whole-genome sequencing,” the researchers wrote.
The scientists put ARTEMIS to the test in laboratory experiments.
The first analysis involved 1,280 types of repeating genetic elements “in both normal and tumor tissues from 525 cancer patients” who participated in the Pan-Cancer Analysis of Whole Genomes (PCAWG), according to Technology Networks, which noted these findings:
A median of 807 altered elements were found in each tumor.
About two-thirds (820) had not “previously been found altered in human cancer.”
Second, the researchers explored “genomewide repeat element changes that were predictive of cancer,” by using machine learning to give each sample an ARTEMIS score, according to the Johns Hopkins news release.
The scoring detected “525 PCAWG participants’ tumors from the healthy tissues with a high performance” overall Area Under the Curve (AUC) score of 0.96 (perfect score being 1.0) “across all cancer types analyzed,” the Johns Hopkins’ release states.
Liquid Biopsy Deployed
The scientists then used liquid biopsies to determine ARTEMIS’ ability to noninvasively diagnose cancer. Researchers used blood samples from:
ARTEMIS classified patients with lung cancer with an AUC of 0.82.
ARTEMIS detected people with liver cancer, as compared to others with cirrhosis or viral hepatitis, with a score of AUC 0.87.
Finally, the scientists used their “ARTEMIS blood test” to find the origin of tumors in patients with cancer. They reported their technique was 78% accurate in discovering tumor tissue sources among 12 tumor types.
“These analyses reveal widespread changes in repeat landscapes of human cancers and provide an approach for their detection and characterization that could benefit early detection and disease monitoring of patients with cancer,” the researchers wrote in Science Translational Medicine.
Large Clinical Trials Planned
Velculescu said more research is planned, including larger clinical trials.
“While still at an early stage, this research demonstrates how some cancers could be diagnosed earlier by detecting tumor-specific changes in cells collected from blood samples,” Hattie Brooks, PhD, Research Information Manager, Cancer Research UK (CRUK), told Financial Times.
Should ARTEMIS prove to be a viable, non-invasive blood test for cancer, it could provide pathologists and clinical laboratories with new biomarkers and the opportunity to work with oncologists to promptly diagnosis cancer and monitor patients’ response to treatment.
Speedy DNA sequencing and on-the-spot digital imaging may change the future of anatomic pathology procedures during surgery
Researchers at the Center for Molecular Medicine (CMM) at UMC Utrecht, a leading international university medical center in the Netherlands, have paired artificial intelligence (AI) and machine learning with DNA sequencing to develop a diagnostic tool cancer surgeons can use during surgeries to determine in minutes—while the patient is still on the operating table—whether they have fully removed all the cancerous tissue.
The method, “involves a computer scanning segments of a tumor’s DNA and alighting on certain chemical modifications that can yield a detailed diagnosis of the type and even subtype of the brain tumor,” according to The New York Times, which added, “That diagnosis, generated during the early stages of an hours-long surgery, can help surgeons decide how aggressively to operate, … In the future, the method may also help steer doctors toward treatments tailored for a specific subtype of tumor.”
This technology has the potential to reduce the need for frozen sections, should additional development and studies confirm that it accurately and reliably shows surgeons that all cancerous cells were fully removed. Many anatomic pathologists would welcome such a development because of the time pressure and stress associated with this procedure. Pathologists know that the patient is still in surgery and the surgeons are waiting for the results of the frozen section. Most pathologists would consider fewer frozen sections—with better patient outcomes—to be an improvement in patient care.
“It’s imperative that the tumor subtype is known at the time of surgery,” Jeroen de Ridder, PhD (above), associate professor in the Center for Molecular Medicine at UMC Utrecht and one of the study leaders, told The New York Times. “What we have now uniquely enabled is to allow this very fine-grained, robust, detailed diagnosis to be performed already during the surgery. It can figure out itself what it’s looking at and make a robust classification,” he added. How this discovery affects the role of anatomic pathologists and pathology laboratories during cancer surgeries remains to be seen. (Photo copyright: UMC Utrecht.)
Rapid DNA Sequencing Impacts Brain Tumor Surgeries
The UMC Utrecht scientists employed Oxford Nanopore’s “real-time DNA sequencing technology to address the challenges posed by central nervous system (CNS) tumors, one of the most lethal type of tumor, especially among children,” according to an Oxford Nanopore news release.
The researchers called their new machine learning AI application the “Sturgeon.”
According to The New York Times, “The new method uses a faster genetic sequencing technique and applies it only to a small slice of the cellular genome, allowing it to return results before a surgeon has started operating on the edges of a tumor.”
Jeroen de Ridder, PhD, an associate professor in the Center for Molecular Medicine at UMC Utrecht, told The New York Times that Sturgeon is “powerful enough to deliver a diagnosis with sparse genetic data, akin to someone recognizing an image based on only 1% of its pixels, and from an unknown portion of the image.” Ridder is also a principal investigator at the Oncode Institute, an independent research center in the Netherlands.
The researchers tested Sturgeon during 25 live brain surgeries and compared the results to an anatomic pathologist’s standard method of microscope tissue examination. “The new approach delivered 18 correct diagnoses and failed to reach the needed confidence threshold in the other seven cases. It turned around its diagnoses in less than 90 minutes, the study reported—short enough for it to inform decisions during an operation,” The New York Times reported.
But there were issues. Where the minute samples contain healthy brain tissue, identifying an adequate number of tumor markers could become problematic. Under those conditions, surgeons can ask an anatomic pathologist to “flag the [tissue samples] with the most tumor for sequencing, said PhD candidate Marc Pagès-Gallego, a bioinformatician at UMC Utrecht and a co-author of the study,” The New York Times noted.
“Implementation itself is less straightforward than often suggested,” Sebastian Brandner, MD, a professor of neuropathology at University College London, told The Times. “Sequencing and classifying tumor cells often still required significant expertise in bioinformatics as well as workers who are able to run, troubleshoot, and repair the technology,” he added.
“Brain tumors are also the most well-suited to being classified by the chemical modifications that the new method analyzes; not all cancers can be diagnosed that way,” The Times pointed out.
Thus, the research continues. The new method is being applied to other surgical samples as well. The study authors said other facilities are utilizing the method on their own surgical tissue samples, “suggesting that it can work in other people’s hands.” But more work is needed, The Times reported.
UMC Utrecht Researchers Receive Hanarth Grant
To expand their research into the Sturgeon’s capabilities, the UMC Utrecht research team recently received funds from the Hanarth Fonds, which was founded in 2018 to “promote and enhance the use of artificial intelligence and machine learning to improve the diagnosis, treatment, and outcome of patients with cancer,” according to the organization’s website.
The researchers will investigate ways the Sturgeon AI algorithm can be used to identify tumors of the central nervous system during surgery, a UMC Utrecht news release states. These type of tumors, according to the researchers, are difficult to examine without surgery.
“This poses a challenge for neurosurgeons. They have to operate on a tumor without knowing what type of tumor it is. As a result, there is a chance that the patient will need another operation,” said de Ridder in the news release.
The Sturgeon application solves this problem. It identifies the “exact type of tumor during surgery. This allows the appropriate surgical strategy to be applied immediately,” the news release notes.
The Hanarth funds will enable Jeroen and his team to develop a variant of the Sturgeon that uses “cerebrospinal fluid instead of (part of) the tumor. This will allow the type of tumor to be determined already before surgery. The main challenge is that cerebrospinal fluid contains a mixture of tumor and normal DNA. AI models will be trained to take this into account.”
The UMC Utrecht scientists’ breakthrough is another example of how organizations and research groups are working to shorten time to answer, compared to standard anatomic pathology methods. They are combining developing technologies in ways that achieve these goals.
