Dettwyler is set to retire at age 92 after a long career helping clinical laboratories with their coding and billing systems
When William Dettwyler, MT, began working in a clinical laboratory, Harry Truman was president of the United States and scientists had not yet discovered the structure of DNA. Now, as he approaches his 92nd birthday in March, he is finally ready to retire from a career that has spanned more than seven decades, from bench work as a medical laboratory technician (MLT) to assisting labs with their medical coding and medical billing challenges.
Along the way, one of his coding innovations helped the State of Oregon save substantial sums in its Medicaid program. He also helped many medical laboratories increase reimbursement by correcting their coding mistakes. This from someone who left school after eighth grade to help on his family’s farm in rural Oregon.
In an exclusive interview with Dark Daily, Dettwyler discusses his long career and offered pointers for labs on improving their coding and reimbursement procedures.
Back in the 1980s, when he began his consulting work for labs, “they were very poor at billing,” he recalled. “Hospital billing staff didn’t understand lab coding. Reference laboratories didn’t do a good job of picking the right codes or even billing all the codes. Up until around the 1970s, hospitals didn’t even have to bill individual lab procedures with CPT codes. They billed with a revenue center code for all their lab services.”
These days “people are much more sophisticated,” he notes. “There are fewer coding problems compared to what it was in the 1980s and 1990s up to the 2010s.” However, he says he still has a handful of clients who call on his expertise.
“It was not unusual to go to a large university medical center and in three days tell the CFO on my exit review that the following year their lab would bring in about a half million more in revenue, just from my coding review. But I did not reveal to them that I had only gone to the eighth grade in a little one room school and was the lone graduate in my eighth-grade class,” wrote William Dettwyler, MT (above), owner of Codus Medicus in Salem, Ore., in an article he penned for Medical Laboratory Observer. For 75 years Dettwyler worked in the clinical laboratory industry. For much of that time he helped labs all over America improve their coding and reimbursement systems. (Photo copyright: LinkedIn.)
How It All Began
Dettwyler got his first taste of lab work in the early 1950s as a teenager washing glassware for a medical laboratory technician at a local medical practice. A few years later he completed an MLT program at Oregon Institute of Technology in Klamath Falls and landed his first lab tech job at a clinic in Portland.
His entry to consulting came in the early 1970s while he was working for a medical group in Salem. “I was helping the accounting personnel with their billing and noticed that Medicaid was not paying for a common test for syphilis that I was performing,” he recalled. “I contacted Medicaid, and they told me they didn’t understand laboratory procedures.”
After that, “they started to call me frequently with laboratory questions,” he said. “It wasn’t long before they asked me to help them on a part-time basis.” He also assisted with questions related to radiology.
By 1976, Dettwyler was devoting 35 hours a week to assisting the state Medicaid agency while still working as a lab tech.
Simple Hack Ends Overpayments
One of his career highlights came around 1981, when he discovered that the agency was overpaying for some pathology and radiology procedures by as much as 200%.
“Pathologists and radiologists are paid based on whether they are performing the complete procedure—the technical component and the professional component—or just the professional component, where they interpret the results,” he explained.
When billing for just the professional component, the physicians would add two digits to the standard code, so it might come in as 88305-26. However, the state’s computer system could only accommodate a five-digit code, so the state was paying as if the providers had done everything.
“The computer techs said the software couldn’t handle a seven-digit number in a five-digit box, so I devised a way for the computer to read the equivalent of seven digits,” he recalled.
His solution was to modify the codes so that the last digit was an alphabetic character. Instead of billing for code 88305-26, the physicians would bill for 8830F, and the state would pay them correctly.
Around that time, Dettwyler also began assisting a Medicare office in Portland. This forced him to cut back on his work as a lab tech. But he still worked around 60 hours a week.
“For most of my life, I’ve worked three jobs,” he said. “Work is my hobby.” He also had a large family to support—by 1976, he and his wife had 10 kids.
Transition to Lab Consulting
In 1986, the state was facing a budget shortfall and cut its Medicaid consultants, so Dettwyler decided to seek consulting work with labs while continuing to work at the bench.
“I really liked the coding because I had very little competition,” he said. “But I wanted to keep working in the laboratory mainly to understand the problems.”
While working for the state, Dettwyler attended coding seminars and workshops. He noticed that labs were losing revenue due to poor billing practices. “They didn’t understand all the coding complexities, so they really hungered for this kind of assistance.”
But first, he had to find clients. So he partnered with another lab tech who was offering similar consulting services.
Business picked up after Dettwyler contributed an article to the trade publication Medical Laboratory Observer about his process, which he calls “procedure code verification and post payment analysis.”
“That went like gangbusters,” he said. “We started getting calls from all over the country.”
Dettwyler later split from his partner and went to work on his own.
“I would sit down with the person who was responsible for coding, usually the lab or radiology manager,” he explained. “We would go over the chargemaster and cover every procedure to make sure the code and units were correct. When I was done, I would give them a report of what codes we changed and why we changed them.”
Beginning in 1989, he signed on as a contractor for another consultancy, Health Systems Concepts on the East Coast, where he remained until 2019.
Advice to the Current Generation
What is Dettwyler’s advice for someone who wants to follow in his footsteps and assist labs with their coding? “I wouldn’t recommend it now,” he said. “There’s less need for that kind of assistance than in the past.”
However, he does find that labs still run into problems. The greatest need, he says, is in molecular diagnostics, due to the complexity of the procedures.
In addition, labs are sometimes confused by coding for therapeutic drug monitoring, in which a doctor is gauging a patient’s reaction to a therapy versus screening for substance abuse. “Those issues are often misunderstood,” he said.
Microbiology also poses coding challenges, he noted, because of the steps required to identify the pathogen and determine antibiotic susceptibility. “It requires quite a bit of additional coding,” he said. “Some labs don’t understand that they can’t just bill a code for culture and sensitivity. They have to bill for the individual portions.”
Labs that work with reference labs also have to be careful to verify codes for specific procedures. “I’ll review the codes used by reference labs and, surprisingly, they’re not always correct. Reference labs sometimes get it wrong.”
If someone does want to become a coding expert, Dettwyler suggests that “they should first have experience as a lab tech, especially in microbiology, because of the additional coding. And they should try to work with somebody who is already doing it. Then, they should work with the billing department to learn how it operates.”
He also advises clinical laboratory managers to follow the latest developments in the field by reading lab publications such as The Dark Report. “You have to do that to keep current,” he said.
Despite never completing high school, Dettwyler eventually received his GED and an associate degree. “But the degrees didn’t really help me,” he said. “Much of it was on-the-job training and keeping my eyes open and listening.”
Findings could lead to new clinical laboratory tests to screen for individuals with increased risk of blood transfusion complications
Pathologists and clinical laboratory scientists who understand the complexities of blood typing from one human to another will be interested to learn that a 50 year-old mystery has brought about an exciting new discovery—a new human blood group.
British and Israeli scientists led by the UK’s NHS Blood and Transplant (NHSBT) and the University of Bristol discovered the meaning behind a missing protein molecule found in a pregnant woman five decades ago. This anomaly has now been given its own blood group identification called MAL, according to a University of Bristol new release.
“Some people can lack this blood group due to the effect of illness, but the rare inherited form of the AnWj-negative phenotype has only been found in a handful of individuals—though due to this discovery it will now be easier to find others in the future,” the news release notes.
This is important because receiving mismatched blood can be fatal.
“AnWj is a high-prevalence red blood cell (RBC) antigen in the ISBT 901 series. Only nine reports of anti-AnWj have been published since it was first documented in 1972,” according to a 2012 article published by the American Association of Blood Banks, now known as the Association for the Advancement of Blood and Biotherapies (AABB).
For even the small proportion of the population with this new blood group, diagnosing its presence can have a major impact while preventing unwanted harm.
“The work was difficult because the genetic cases are very rare. We would not have achieved this without exome sequencing, as the gene we identified wasn’t an obvious candidate and little is known about Mal protein in red cells,” said Louise Tilley, PhD, Senior Research Scientist, IBGRL Red Cell Reference at NHS Blood and Transplant, in the news release.
“The genetic background of AnWj has been a mystery for more than 50 years, and one which I personally have been trying to resolve for almost 20 years of my career,” said Louise Tilley, PhD (above), Senior Research Scientist, IBGRL Red Cell Reference at NHS Blood and Transplant, in the news release. “It represents a huge achievement, and the culmination of a long term effort, to finally establish this new blood group system and be able to offer the best care to rare, but important, patients,” she added. Clinical laboratory scientists involved in blood banking will want to keep updated as further research into this new blood group is published. (Photo copyright: NHS Blood and Transplant.)
Unraveling the Mystery
In 1972, scientists were stumped by a pregnant woman with a blood sample that was “mysteriously missing a surface molecule found on all other known red blood cells at the time,” Science Alert reported. The AnWj antigen that was missing in that patient’s blood is present in 99.9% of human blood samples.
“Researchers found that the AnWj antigen is carried on the Mal protein. While illness can cause some people to lose the AnWj antigen, inherited cases of the AnWj-negative phenotype are extremely rare. Using whole exome sequencing on five genetically AnWj-negative individuals, researchers confirmed that, in these cases, the participants lacked the antigen due to homozygous deletions in the MAL gene,” an AABB news release stated.
The researchers named the group with the missing antigen the MAL blood group (short for Myelin and Lymphocyte Protein) which is where the antigen resides.
Genetic sequencing enabled the scientists to locate the gene when they “inserted the normal MAL gene into blood cells that were AnWj-negative. This effectively delivered the AnWj antigen to those cells,” Science Alert noted.
Mutated MAL genes result in the AnWj-negative blood type. The team discovered three patients with the blood type and no mutation, “Suggesting that sometimes blood disorders can also cause the antigen to be suppressed,” Science Alert added. The researchers also discovered that AnWj isn’t present in newborns but arrives sometime after they are born.
“Interestingly, all the AnWj-negative patients included in the study shared the same mutation. However, no other cell abnormalities or diseases were found to be associated with this mutation,” Science Alert said.
The discovery that “the Mal protein is responsible for binding AnWj antibodies” could lead to new clinical laboratory tests to screen for patients at risk from blood transfusions, AABB noted in its news release.
Facing the Challenge
Scientists had to overcome many challenges to uncover the details of this blood type. The complexity of the protein further hindered their efforts.
“MAL is a very small protein with some interesting properties which made it difficult to identify, and this meant we needed to pursue multiple lines of investigation to accumulate the proof we needed to establish this blood group system,” said Tim Satchwell, PhD, senior lecturer and cell biologist at the University of the West of England, in the University of Bristol news release.
“Resolving the genetic basis for AnWj has been one of our most challenging projects,” Nicole Thornton, head of IBGRL Red Cell Reference at NHSBT told the AABB. “There is so much work that goes into proving that a gene does actually encode a blood group antigen, but it is what we are passionate about, making these discoveries for the benefit of rare patients around the world.”
It’s hard to pinpoint how many individuals will benefit by testing for the blood group, Tilley told the BBC. Nevertheless, “the NHSBT is the last resort for about 400 patients across the world each year,” the BBC reported.
While more research needs to be done, the initial discovery is promising and may lead to new clinical laboratory tests to identify individuals who could be severely harmed should they receive the wrong blood type during a transfusion.
New guidelines come on the heels of recommendations covering post-market modifications to AI products, including those incorporated into systems used by clinical laboratories
Artificial intelligence (AI) is booming in healthcare, and as the technology finds its way into more medical devices and clinical laboratory diagnostic test technologies the US Food and Drug Administration (FDA) has stepped up its efforts to provide regulatory guidance for developers of these products. This guidance will have an impact on the development of new lab test technology that uses AI going forward.
In December, the FDA issued finalized recommendations for submitting information about planned modifications to AI-enabled healthcare products. Then, in January, the federal agency issued draft guidance that covers product management and marketing submission more broadly. It is seeking public comments on the latter document through April 7.
“The FDA has authorized more than 1,000 AI-enabled devices through established premarket pathways,” said Troy Tazbaz, director of the Digital Health Center of Excellence at the FDA’s Center for Devices and Radiological Health, in a press release announcing the draft guidance.
This guidance “would be the first to provide total product life cycle recommendations for AI-enabled devices, tying together all design, development, maintenance and documentation recommendations, if and when finalized,” Healthcare IT News reported.
“Today’s draft guidance brings together relevant information for developers, shares learnings from authorized AI-enabled devices, and provides a first point-of-reference for specific recommendations that apply to these devices, from the earliest stages of development through the device’s entire life cycle,” said Troy Tazbaz (above), director of the Digital Health Center of Excellence at the FDA Center for Devices and Radiological Health, in a press release. The new guidance will likely affect the development of new clinical laboratory diagnostic technologies that use AI. (Photo copyright: LinkedIn.)
Engaging with FDA
One key takeaway from the guidance is that manufacturers “should engage with the FDA early to ensure that the testing to support the marketing submission for an AI-enabled device reflects the agency’s total product lifecycle, risk-based approach,” states an analysis from consulting firm Orrick, Herrington and Sutcliffe LLP.
Another key point is transparency, Orrick noted. For example, manufacturers should be prepared to offer details about the inputs and outputs of their AI models and demonstrate “how AI helps achieve a device’s intended use.”
Manufacturers should also take steps to avoid bias in data collection for these models. For example, they should gather evidence to determine “whether a device benefits all relevant demographic groups similarly to help ensure that such devices are safe and effective for their intended use,” Orrick said.
New Framework for AI in Drug Development
On the same day that FDA announced the device guidelines, the agency also proposed a framework for regulating use of AI models in developing drugs and biologics.
“AI can be used in various ways to produce data or information regarding the safety, effectiveness, or quality of a drug or biological product,” the federal agency stated in a press release. “For example, AI approaches can be used to predict patient outcomes, improve understanding of predictors of disease progression and process, and analyze large datasets.”
The press release noted that this is the first time the agency has proposed guidance on use of AI in drug development.
These include “bias and reliability problems due to variability in the quality, size, and representativeness of training datasets; the black-box nature of AI models in their development and decision-making; the difficulty of ascertaining the accuracy of a model’s output; and the dangers of data drift and a model’s performance changing over time or across environments. Any of these factors, in FDA’s thinking, could negatively impact the reliability and relevancy of the data sponsors provide FDA.”
The FDA also plans to participate in direct testing of AI-enabled healthcare tools. In October, the FDA and the Department of Veterans Affairs (VA) announced that they will launch “a joint health AI lab to evaluate promising emerging technologies,” according to Nextgov/FCW.
Elnahal said the facility will allow federal agencies and private entities “to test applications of AI in a virtual lab environment.” The goal is to ensure that the tools are safe and effective while adhering to “trustworthy AI principles,” he said.
“It’s essentially a place where you get rapid but effective evaluation—from FDA’s standpoint and from VA’s standpoint—on a potential new application of generative AI to, number one, make sure it works,” he told Nextgov/FCW.
He added that the lab will be set up with safeguards to ensure that the technologies can be tested safely.
“As long as they go through the right security protocols, we’d essentially be inviting parties to test their technology with a fenced off set of VA data that doesn’t have any risk of contagion into our actual live systems, but it’s still informative and simulated,” he told Nextgov/FCW.
There has been an explosion in the use of AI, machine learning, deep learning, and natural language processing in clinical laboratory diagnostic technologies. This is equally true of anatomic pathology, where AI-powered image analysis solutions are coming to market. That two federal agencies are motivated to establish guidelines on working relationships for evaluating the development and use of AI in healthcare settings tells you where the industry is headed.
The CDC suggests that hospitals treating patients for flu symptoms perform clinical laboratory tests for avian influenza A within 24 hours. This additional testing will pinpoint the specific type of flu infecting an individual patient and help prevent further spread of the bird flu virus.
“It’s the subtyping that takes us from knowing that a virus is in the general bucket of ‘influenza A’ to knowing more specifically whether it’s a garden-variety seasonal version of influenza A or, more rarely, a novel version of influenza A like H5N1,” CDC Principal Deputy Director Nirav Shah, MD, JD, told CNN.
According to the CDC, a panzootic of pathogenic avian H5N1 flu virus is currently affecting wild birds, poultry, dairy cows, and other animals throughout the country. There have been 67 total cases of bird flu identified in humans in the US since 2022, with 66 of those cases occurring in 2024.
The risk of humans contracting bird flu are low but is elevated among those who work closely with wild birds, poultry, and dairy cattle. The incidences of the flu virus in animals continues to increase, so CDC says it is important to identify potential bird flu cases in humans in a timely manner.
This demonstrates recognition by the CDC and the clinical laboratory profession that advances in molecular diagnostics and genetic testing now make it feasible for many hospital labs to perform these tests in-house on relevant patients. Such molecular testing is less expensive and produces a faster answer today, compared to just a few years ago.
This call for more lab tests in hospitals is also recognition of the value near-patient testing has from a public health perspective. Historically, it was regional and local public health labs that were sent specimens for testing from patients identified as having an infection that were a public health concern.
The good news is that this expands the role of hospital laboratories for all the right reasons. The downside is that hospital labs will probably see many test claims for these assays not be paid promptly by payers—or paid after unnecessary delays.
“The system right now tells us what has already happened. What we need is to shift to a system that tells us what’s happening in the moment. That is what we are doing today,” Nirav Shah, MD, JD (above), CDC principal deputy told CNN. Hospital and clinical laboratories will likely see an increase in orders for molecular and genetic testing for influenza A. (Photo copyright: Centers for Disease Control and Prevention.)
CDC Recommendations to Clinical Laboratories
The CDC alert also acknowledges that most individuals infected with avian flu were exposed to the virus via the handling of infected dairy cows or poultry in unprotected workplaces. There are no known cases of human-to-human transmission of the disease.
Most cases of avian flu in humans have been clinically mild and the patients quickly recover. However, on January 6, the CDC announced that an elderly patient with underlying health conditions in Louisiana who was previously hospitalized with severe avian influenza A illness had passed away. This case was the first confirmed death in the US attributed to the illness.
The CDC’s Health Advisory makes the following recommendations to clinical laboratories:
Subtype respiratory specimens that are positive for influenza A, but negative for seasonal influenza A virus subtypes, and forward those specimens to a public health laboratory within 24 hours.
Refrain from batching specimens for consolidated or bulk shipment to public health laboratories if that process could result in shipping delays.
Notify public health officials if a hospital or clinical lab does not have access to influenza A virus subtyping and arrange for a public health or commercial lab with this testing capability to perform the analysis.
Clearly link specimens to clinical information from the patient to ensure the prioritization of severely ill and ICU patients.
Immediately contact local public health authority if a positive result for influenza A (H5) virus is obtained using a laboratory developed test (LDT) or another A (H5) subtyping test to initiate time-critical actions.
The CDC’s Health Advisory also states public health laboratories should complete influenza A subtyping assays within 24 hours of receipt and report those results to the CDC, as required.
“One of the motivators of accelerating testing [is] so that we are, again, able to faster see difference between signal and noise, given that the volume of hospitalizations is going up as expected in a rather routine flu season,” Demetre Daskalakis, MD, MPH, director of the CDC’s National Center for Immunization and Respiratory Diseases (NCIRD), told CNN.
Preparing for more Bird Flu in Humans
According to the CDC, approximately 100,000 Americans have been hospitalized with type-A flu this season. The agency expects another 100,000 hospitalizations due to the virus before the end of this year. CDC is tracking flu infections on a weekly basis. Data can be reviewed on its website.
Other government organizations also are developing methods intended to curb the spread of the influenza virus. The federal Department of Agriculture recently launched a national program to test for bird flu in untreated milk. And the US Department of Health and Human Services (HHS) allocated $211 million in new funding to address emerging infectious diseases.
On January 17, the HHS announced it would give $590 million to Moderna to “accelerate the development of mRNA-based pandemic influenza vaccines and enhance mRNA platform capabilities so that the US is better prepared to respond to other emerging infectious diseases.”
“The funding will allow us to bring the benefits of mRNA vaccine technology to bear against a wider array of emerging threats,” said HHS Assistant Secretary for Preparedness and Response Dawn O’Connell, JD, in the announcement. “mRNA technology can be faster to develop and easier to update than other vaccines making it a helpful tool to have against viruses that move fast and mutate quickly.
Hospital laboratories and public health labs should prepare for a spike in test orders for avian influenza A as this year’s flu season progresses. As bird flu increases in animals, it increases the possibility that the disease might infect humans.
Nearly 100,000 patients submitted saliva samples to a genetic testing laboratory, providing insights into their disease risk
Researchers at Mayo Clinic have employed next-generation sequencing technology to produce a massive collection of exome data from more than 100,000 patients, offering a detailed look at genetic variants that predispose people to certain diseases. The study, known as Tapestry, was administered by doctors and scientists from the clinic’s Center for Individualized Medicine and produced the “largest-ever collection of exome data, which include genes that code for proteins—key to understanding health and disease,” according to a Mayo Clinic news release.
For our clinical laboratory professionals, this shows the keen interest that a substantial portion of the population has in using their personal genetic data to help physicians identify their risk for many diseases and types of cancer. This support by healthcare consumers is a sign that labs should be devoting attention and resources to providing these types of gene sequencing services.
As Mayo explained in the news release, the exome includes nearly 20,000 genes that code for proteins. The researchers used the dataset to analyze genes associated with higher risk of heart disease and stroke along with several types of cancer. They noted that the data, which is now available to other researchers, will likely provide insights into other diseases as well, the news release notes.
“What we’ve accomplished with the Tapestry study is a blueprint for future endeavors in medical science,” said gastroenterologist and lead researcher Konstantinos Lazaridis, MD (above), in the news story. “It demonstrates that through innovation, determination and collaboration, we can deeply advance our understanding of DNA function and eventually other bio-molecules like RNA, proteins and metabolites, turning them into novel diagnostic tools to improve health, prevent illness, and even treat disease.” Some of these newly identified genetic markers may be incorporated into new clinical laboratory assays. (Photo copyright: Mayo Clinic.)
How Mayo Conducted the Tapestry Study
One notable aspect of the study was its methodology. The study launched in July 2020 during the COVID-19 pandemic. Since many patients were quarantined, researchers conducted the study remotely, without the need for the patients to visit a Mayo facility. It ran for five years through May 31, 2024. The news release notes that it’s the largest decentralized clinical trial ever conducted by the Mayo Clinic.
The researchers identified 1.3 million patients from the main Mayo Clinic campuses in Minnesota, Arizona, and Florida who met the following eligibility criteria:
Participants had to be 18 or older,
they had to have internet and email access, and
be sufficiently proficient in speaking and reading English.
More than 114,000 patients consented to participate, but some later withdrew, resulting in a final sample of 98,222 individuals. Approximately two-thirds were women. Mean age was 57 (61.9 for men and 54.3 for women).
“It was a tremendous effort,” said Mayo Clinic gastroenterologist and lead researcher Konstantinos Lazaridis, MD, in the news release. “The engagement of such a number of participants in a relatively short time and during a pandemic showcased the trust and the dedication not only of our team but also of our patients.”
He added that the researchers “learned valuable lessons about some patients’ decisions not to participate in Tapestry, which will be the focus of future publications.”
Three Specific Genes
Enrolled patients were invited to visit a website, where they could view a video and submit an eligibility form. Once approved, they completed a digital consent agreement and received a saliva collection kit. Participants were also invited to provide information about their family history.
Helix, a clinical laboratory company headquartered in San Mateo, Calif., performed the exome sequencing.
Though Helix performed whole exome sequencing, the researchers were most interested in three specific sets of genes:
Patients received clinical results directly from Helix along with information about their ancestry. Clinical results were also transmitted to Mayo Clinic for inclusion in patients’ electronic health records (EHRs).
Among the participants, approximately 1,800 (1.9%) had what the researchers described as “actionable pathogenic or likely pathogenic variants.” About half of these were BRCA1/2.
These patients were invited to speak with a genetic counselor and encouraged to undergo additional testing to confirm the variants.
Tapestry Genomic Registry
In addition to the impact on the participants, Mayo Clinic’s now has an enormous amount of raw sequencing data stored in the Tapestry Genomic Registry, where it will be available for future research.
The database “has become a valuable resource for Mayo’s scientific community, with 118 research requests submitted,” the researchers wrote in the news release. Mayo has distribution more than a million exome datasets to other genetic researchers.
“What we’ve accomplished with the Tapestry study is a blueprint for future endeavors in medical science,” Lazaridis noted. “It demonstrates that through innovation, determination, and collaboration, we can deeply advance our understanding of DNA function and eventually other bio-molecules like RNA, proteins and metabolites, turning them into novel diagnostic tools to improve health, prevent illness, and even treat disease.”
Everything about this project is consistent with precision medicine, and the number of individuals discovered to have risk of cancers is relevant. Clinical laboratory professionals understand these ratios and the importance of early detection and early intervention.
What researchers call “the largest proteomic study in the world” could lead to new clinical laboratory assays for determining genetic risk for multiple cancers
Examining blood proteins may be superior to clinical information in determining an individual’s risk for developing multiple diseases. That’s according to a new study conducted by researchers from the UK, America, and Germany who determined that measuring thousands of proteins from a single drop of blood can predict the onset of several illnesses.
The findings may provide clinical laboratories and physicians with new assays to more accurately predict an individual’s risk for more than 60 diseases.
“With data on genetic, imaging, lifestyle factors and health outcomes over many years, this will be the largest proteomic study in the world to be shared as a global scientific resource,” said Naomi Allen, MSc, DPhil, chief scientist at UK Biobank and professor of epidemiology, University of Oxford, in a UK Biobank news release. “These combined data could enable researchers to make novel scientific discoveries about how circulating proteins influence our health, and to better understand the link between genetics and human disease.”
“Measuring protein levels in the blood is crucial to understanding the link between genetic factors and the development of common life-threatening diseases,” said Naomi Allen, MSc, DPhil (above), chief scientist at UK Biobank and professor of epidemiology, University of Oxford, in a news release. With further study, this research could lead to new clinical laboratory assays that help physicians predict an individual’s risk for certain diseases including many forms of cancer. (Photo copyright: UK Biobank.)
Protein Signatures Outperform PSA Testing
To conduct their research, the team collected data from the UK Biobank Pharma Proteomics Project (UKB-PPP). This initiative is “one of the world’s largest studies of blood protein concentrations” and “aims to significantly enhance the field of ‘proteomics,’ enabling better understanding of disease processes and supporting innovative drug development,” according to the Biobank’s website.
The scientists analyzed the values of approximately 3,000 plasma proteins among 41,931 participants in the UKB-PPP. They examined the 10-year potential of developing certain diseases by measuring the plasma proteome and linking those observations to incident cases noted in electronic health records (EHRs).
The team specifically looked at the pathology types for several illnesses and utilized advanced techniques to identify a signature of proteins associated with those various diseases. They found their protein-based model exceeded traditional prediction methods when comparing the models with polygenic risk scores.
“We are therefore extremely excited about the opportunities that our protein signatures may have for earlier detection and ultimately improved prognosis for many diseases, including severe conditions such as Multiple myeloma and idiopathic pulmonary fibrosis,” she added. “We identified so many promising examples; the next step is to select high priority diseases and evaluate their proteomic prediction in a clinical setting.”
Identifying Individuals at High Risk for Certain Diseases
Of the thousands of known proteins in humans, the team focused on about 20 proteins found in blood. With as few as five proteins and as many as 20, they were able to do a risk assessment on 67 diseases, including:
The model could prove to be beneficial in the development of new therapies for certain diseases.
“A key challenge in drug development is the identification of patients most likely to benefit from new medicines. This work demonstrates the promise in the use of large-scale proteomic technologies to identify individuals at high risk across a wide range of diseases, and aligns with our approach to use tech to deepen our understanding of human biology and disease,” said Robert Scott, vice president and head of human genetics and genomics, GSK, and co-lead author of the study in the UCL news release.
“Further work will extend these insights and improve our understanding of how they are best applied to support improved success rates and increased efficiency in drug discovery and development,” he added.
“We are extremely excited about the opportunity to identify new markers for screening and diagnosis from the thousands of proteins circulating and now measurable in human blood,” said Claudia Langenberg, PhD, director of the Precision Healthcare University Research Institute (PHURI) at Queen Mary University of London and professor of computational medicine at the Berlin Institute of Health, in the UCL news release. “What we urgently need are proteomic studies of different populations to validate our findings, and effective tests that can measure disease relevant proteins according to clinical standards with affordable methods.”
More research and studies are needed before the protein-based model can be used to predict disease in clinical settings. However, the model could someday provide clinical laboratories, pathologists, and physicians with new assays that more accurately forecast an individual’s risk for certain illnesses.
