Regulatory agencies in UK and US have yet to address dangers inherent in customer misunderstanding of DTC medical laboratory genetic test results
Direct-to-consumer (DTC) medical laboratory genetic tests are gaining popularity across the globe. But recent research out of the United Kingdom questions the reliability of these tests. The study, according to The Guardian, found that “Over the counter genetic tests in the UK that assess the risk of cancer or heart problems fail to identify 89% of those in danger of getting killer diseases.”
According the PGS website, “each PGS in the catalog is consistently annotated with relevant metadata; including scoring files (variants, effect alleles/weights), annotations of how the PGS was developed and applied, and evaluations of their predictive performance.”
However, the researchers told The Guardian, “Polygenic risk scores performed poorly in population screening, individual risk prediction, and population risk stratification. Strong claims about the effect of polygenic risk scores on healthcare seem to be disproportionate to their performance.”
“Strong claims have been made about the potential of polygenic risk scores in medicine, but our study shows that this is not justified,” Aroon Hingorani, PhD (above), Professor of Genetic Epidemiology at UCL and lead author of the study, told The Guardian. “We found that, when held to the same standards as employed for other tests in medicine, polygenic risk scores performed poorly for prediction and screening across a range of common diseases.” Consumer misunderstanding of DTC medical laboratory genetic tests is a real danger. (Photo copyright: University College London.)
Polygenic Scores Not Beneficial to Cancer Screening
To complete their study, the UCL researchers compared PGS genetic risk data to conventional clinical laboratory testing methods and discovered some troubling results. They include:
On average, only 11% of individuals who developed a disease had been identified by the tests.
A 5% false positive rate where people were informed that they would get a disease within 10 years but did not.
PGS only identified 10% of people who later developed breast cancer.
The researchers state in their BMJ Medicine paper that polygenic risk scores are not the same as testing for certain gene mutations, which could be critical in screening for some cancers. They also wrote that discovering genetic variants associated with the risk for disease is still crucial for drug development.
“It has been suggested that polygenic risk scores could be introduced early on to help prevent breast cancer and heart disease but, in the examples we looked at, we found that the scores contributed little, if any, health benefit while adding cost and complexity,” research physician and epidemiologist Sir Nicholas Wald, FRS, FRCP, FMedSci, Professor of Preventive Medicine at UCL Institute of Health Informatics and co-author of the study, told the Jersey Evening Post.
“Our results build on evidence that indicates that polygenic risk scores do not have a role in public health screening programs,” Wald added.
“This research study rightly highlights that for many health conditions genetic risk scores alone may have limited usefulness, because other factors such as deprivation, lifestyles, and environment are also important,” clinical epidemiologist Raghib Ali, MD, CEO, Chief Investigator and Chief Medical Officer, Our Future Health UK, told The Guardian.
Our Future Health is a collaboration between public, non-profit, and private sectors to create the UK’s largest health research program. The researchers in this endeavor intend to recruit over five million volunteers and use polygenic risk scores to develop innovative ways to prevent, detect, and treat disease. This program is funded by the UK’s National Health System (NHS).
“[Our] research program will be developing integrated risk scores that will take in all the important risk factors,” Ali explained. “We hope these integrated risk scores can identify people more likely to develop diseases, but this is a relatively new area of science and there are still unanswered questions around it.”
Danger of Misunderstanding DTC Genetic Tests
Here in the US, there have been news stories in recent years about the unreliability of certain genetic tests. Dark Daily covered these stories in previous ebriefs. News stories about the unreliability of genetic tests, particularly those marketed directly to consumers, reveal the problems that existing regulatory schemes have yet to address.
In “Consumer Reports Identifies ‘Potential Pitfalls’ of Direct-to-Consumer Genetic Tests,” we covered CR’s findings that though clinical laboratory and pathology professionals understand the difference between a doctor-ordered genetic health risk (GHR) test and a direct-to-consumer (DTC) genetic test, the typical genetic test customer may not. And that, misunderstanding the results of a DTC at-home genetic test can lead to confusion, loss of privacy, and potential harm.
Scientific American also covered the dangers of DTC testing in “The Problem with Direct-to-Consumer Genetic Tests,” in which the author notes that “despite caveats in ads and on packages, users can fail to understand their limitations,” and that “consumer-grade products are easily misconstrued as appropriate medical tests and create false reassurances in patients who could be at legitimate risk.”
Most clinical laboratory managers and pathologists are probably not surprised that the research performed at UCL shows that there are still issues surrounding genetic tests, particularly those marketed directly to consumers. While direct-to-consumer DNA tests can have some benefits, at this time, they are not always the best option for individuals seeking information about their personal risk for hereditary diseases.
Clinical studies show that new ‘cell-free’ test can predict cardiovascular disease risk better than standard HDL cholesterol test
Researchers from the National Institutes of Health (NIH) have developed a diagnostic assay that measures how well high-density lipoprotein (HDL)—the so-called “good” cholesterol—is working in the body. And their findings could lead to new clinical laboratory tests that supplement standard HDL level testing to better determine a person’s risk for heart disease.
Cholesterol tests are among the most commonly performed assays by clinical laboratories. A new test that reveals how well HDL is working in the body would certainly boost a medical laboratory’s test requisition volume.
“Measuring HDL function is limited to research labs and isn’t conducive to large-scale testing by routine clinical laboratories. To try to solve that problem, researchers from NHLBI’s Lipoprotein Metabolism Laboratory created a new diagnostic test,” noted an NHLBI news release.
“This is going to quicken the pace of basic research,” said Edward B. Neufeld, PhD, who along with guest researcher Masaki Sato, PhD, developed the test. “It increases the number of samples that you can study. It increases the number of experiments you can do.”
Such a new cholesterol test would quickly become one of the most commonly performed clinical lab tests because just about every American who has a physical gets cholesterol tests as part of that process.
“Other people may modify this or come up with better versions, which is fine with us,” Edward Neufeld, PhD (above), NHLBI Staff Scientist, said in a news release. “We just really wanted to tackle this problem of evaluating HDL function.” Clinical laboratories may soon have a new cholesterol test to supplement standard HDL level testing. (Photo copyright: ResearchGate.)
Faster Answers Needed about HDL
According to the NIH, the goal should go beyond measuring level of HDL as part of a person’s annual physical. What is also needed is finding out whether HDL cholesterol is effectively doing certain tasks, such as removing extra cholesterol from arteries and transporting it to the liver.
The NHLBI’s new cell-free test may make it possible to step up large-scale clinical testing of HDL function, according to the news release. As it stands now, HDL function study has been limited to research labs where testing involves “harvesting cells in the lab [which] can take days to process,” according to NIH Record.
“Most studies to date that have assessed CAD (coronary artery disease) risk by HDL functionality still use the CEC (cellular cholesterol efflux capacity) in vitro assay and are based on the use of radioisotopes (3H-cholesterol) and cultured cells, which is very labor intensive and impractical to do in a clinical laboratory,” the researchers wrote in The Journal of Clinical Investigation. They also pointed out that CEC batch-to-batch variability does not fit clinical laboratories’ need for standardization.
Advantages of NHLBI’s Test
To overcome these barriers, the NHLBI researchers created an HDL-specific phospholipid efflux (HDL-SPE) assay that has certain advantages over current HDL function assessments done in research labs.
According to the NIH, the HDP-SPE assay:
Is easy to replicate in clinical labs.
Is more suited to automation and large samples.
Offers up results in about an hour.
Is a better predictor of cardiovascular disease risk than HDL cholesterol testing for CAD risk.
“We developed a cell-free, HDL-specific phospholipid efflux assay for the assessment of CAD risk on the basis of HDL functionality in whole plasma or serum. One of the main advantages of the HDL-SPE assay is that it can be readily automated, unlike the various CEC assays currently in use,” the authors noted in their paper.
Here is how the test is performed, according to the NIH:
Plasma with HDL is separated from the patient’s blood.
“Plasma is added to donor particles coated with a lipid mixture resembling plaque and a fluorescent-tagged phospholipid” that only HDL can remove.
The fluorescent signal by HDL is then measured.
A bright signal suggests optimal HDL lipid removal function, while a dim light means reduced function.
The test builds on the scientists’ previous findings and data. In creating the new assay they drew on data from:
A study of 50 severe CAD and 50 non-CAD people.
A Japanese study of 70 CAD and 154 non-CAD participants.
Examined association of HDL-SPE with cardiovascular disease in a study of 340 patients and 340 controls.
“We have established the HDL-SPE assay for assessment of the functional ability of HDL to efflux phospholipids. Our combined data consistently show that our relatively simple HDL-SPE assay captures a pathophysiologically relevant parameter of HDL function that is at least equivalent to the CEC assay in its association with prevalent and incident CAD,” the researchers concluded in The Journal of Clinical Investigation.
Test May Be Subject to New FDA Rule
While HDL cardiovascular-related research is moving forward, studies aimed at the therapeutic side need to pick up, NIH noted.
“Someday we may have a drug that modulates HDL and turns out to be beneficial, but right now we don’t have that,” said Alan Remaley MD, PhD, NHLBI Senior Investigator and Head of the Lipoprotein Metabolism Laboratory, in the news release.
It may be years before the HDL-SPE test is used in medical settings, the researchers acknowledged, adding that more studies are needed with inclusion of different ethnicities.
Additionally, in light of the recently released US Food and Drug Administration (FDA) final rule on regulation of laboratory developed tests (LDT), the company licensed to bring the test to market may need to submit the HDL-SPE assay to the FDA for premarket review and clearance. That could lengthen the time required for the developers to comply with the FDA before the test is used by doctors and clinical laboratories in patient care.
The focus of the ongoing GenoVA study is to “determine the clinical effectiveness of polygenic risk score testing among patients at high genetic risk for at least one of six diseases measured by time-to-diagnosis of prevalent or incident disease over 24 months,” according to the National Institutes of Health.
The scientists used data obtained from 36,423 patients enrolled in the Mass General Brigham Biobank. The six diseases they researched were:
The polygenic scores were then tested among 227 healthy adult patients to determine their risk for the six diseases. The researchers found that:
11% of the patients had a high-risk score for atrial fibrillation,
7% for coronary artery disease,
8% for diabetes, and
6% for colorectal cancer.
Among the subjects used for the study:
15% of the men in the study had a high-risk score for prostate cancer, and
13% of the women in the study had a high score for breast cancer.
The researchers concluded that the implementation of PRS may help improve disease prevention and management and give doctor’s a way to assess a patient’s risk for these conditions. They published their findings in the journal Nature Medicine, titled, “Development of a Clinical Polygenic Risk Score Assay and Reporting Workflow.”
“We have shown that [medical] laboratory assay development and PRS reporting to patients and physicians are feasible … As the performance of PRS continues to improve—particularly for individuals of underrepresented ancestry groups—the implementation processes we describe can serve as generalizable models for laboratories and health systems looking to realize the potential of PRS for improved patient health,” the researchers wrote.
Using PRS in Clinical Decision Support
Polygenetic risk scores examine multiple genetic markers for risk of certain diseases. A calculation based on hundreds or thousands of these genetic markers could help doctors and patients make personalized treatment decisions, a core tenet of precision medicine.
“As a primary care physician myself, I knew that busy physicians were not going to have time to take an entire course on polygenic risk scores. Instead, we wanted to design a lab report and informational resources that succinctly told the doctor and patient what they need to know to make a decision about using a polygenic risk score result in their healthcare,” epidemiologist Jason Vassy, MD, told The Harvard Gazette. Vassy is Associate Professor, Harvard Medical School at VA Boston Healthcare System and one of the authors of the research.
“This is another great example of precision medicine,” Jason Vassy, MD (above), Adjunct Assistant Professor, General Internal Medicine at Boston University School of Medicine, told WebMD. “There’s always been a tantalizing idea that someone’s genetic makeup might help tailor preventative medicine and treatment.” Personalized clinical laboratory testing is increasingly becoming based on an individual’s genetics. (Photo copyright: Harvard Medical School.)
Increasing Diversity of Patients in Genomic Research
The team did encounter some challenges during their analysis. Because most existing genomic research was performed on persons of European descent, the risk scores are less accurate among non-European populations. The researchers for this study addressed this limitation by applying additional statistical methods to qualify accurate PRS calculations across multiple racial groups.
“Researchers must continue working to increase the diversity of patients participating in genomics research,” said Matthew Lebo, PhD, Chief Laboratory Director, Laboratory Molecular Medicine, at Mass General Brigham and one of the authors of the study. “In the meantime, we were heartened to see that we could generate and implement valid genetic scores for patients of diverse backgrounds,” he told The Harvard Gazette.
The team hopes the scores may be utilized in the future to help doctors and patients make better decisions regarding preventative care and screenings.
“It’s easy to say that everyone needs a colonoscopy at age 45,” Vassy told WebMD. “But what if you’re such a low risk that you could put it off for longer? We may get to the point where we understand risk so much that someone may not need one at all.”
Future of PRS in Clinical Decision Making
The scientists plan to enroll more than 1,000 patients in a new program and track them for two years to assess how medical professionals use PRS in clinical care. It is feasible that patients who are at high risk for certain diseases may opt for more frequent screenings or take preventative medicines to mitigate their risk.
“Getting to that point will take time,” Vassy added. “But I can see this type of information playing a role in shared decision making between doctor and patient in the near future.”
The team also established resources and educational materials to assist both doctors and patients in using the scores.
“It’s still very early days for precision prevention,” Vassy noted, “but we have shown it is feasible to overcome some of the first barriers to bringing polygenic risk scores into the clinic.”
More research and studies are needed to prove the effectiveness of using PRS tests in clinical care and determine its role in customized treatment plans based on personal genetics. Nevertheless, pathologists and medical scientists will want to follow the GenoVA study.
“It is probably most helpful to think of polygenic risk scores as a risk factor for disease, not a diagnostic test or an indication that an individual will certainly develop the disease,” Vassy said. “Most diseases have complex, multifactorial etiologies, and a high polygenic risk score is just one piece of the puzzle.”
Pathologists and clinical laboratory managers may want to stay informed as researchers in the GenoVA study tease new useful diagnostic insights from their ongoing study of the whole human genome. Meanwhile, the GenoVA team is moving forward with the 1,000-patient study with the expectation that this new knowledge may enable earlier and more accurate diagnoses of the health conditions that were the focus of the GenoVA study.
WASE-COVID Study also found that use of artificial intelligence technology minimized variability among echocardiogram scan results
Many physicians—including anatomic pathologists—are watching the development of artificial intelligence (AI)-powered diagnostic tools that are intended to analyze images and analyze the data with accuracy comparable to trained doctors. Now comes news of a recent study that demonstrated the ability of an AI tool to analyze echocardiograph images and deliver analyses equal to or better than trained physicians.
Conducted by researchers from the World Alliance Societies of Echocardiography and presented at the latest annual sessions of the American College of Cardiology (ACC), the WASE-COVID Study involved assessing the ability of the AI platform to analyze digital echocardiograph images with the goal of predicting mortality in patients with severe cases of COVID-19.
To complete their research, the WASE-COVID Study scientists examined 870 patients with acute COVID-19 infection from 13 medical centers in nine countries throughout Asia, Europe, United States, and Latin America.
Human versus Artificial Intelligence Analysis
Echocardiograms were analyzed with automated, machine learning-derived algorithms to calculate various data points and identify echocardiographic parameters that would be prognostic of clinical outcomes in hospitalized patients. The results were then compared to human analysis.
All patients in the study had previously tested positive for COVID-19 infection using a polymerase chain reaction (PCR) or rapid antigen test (RAT) and received a clinically-indicated echocardiogram upon admission. For those patients ultimately discharged from the hospital, a follow-up echocardiogram was performed after three months.
“What we learned was that the manual tracings were not able to predict mortality,” Federico Asch, MD, FACC, FASE, Director of the Echocardiography Core Lab at MedStar Health Research Institute in Washington, DC, told US Cardiology Review in a video interview describing the WASE-COVID Study findings.
Asch is also Associate Professor of Medicine (Cardiology) at Georgetown University. He added, “But on the same echoes, if the analysis was done by machine—Ultromics EchoGo Core, a software that is commercially available—when we used the measurements obtained through this platform, we were able to predict in-hospital and out-of-hospital mortality both with ejection fraction and left ventricular longitudinal strain.”
“When compared to the manual reads, the AI algorithms had a much higher predictive value for mortality,” Federico Asch, MD (above), told US Cardiology Review. “Indeed, they were predictive where the manual ones were not.” These findings may have implications in the development and adoption of artificial intelligence driven clinical laboratory diagnostics and for predicting risk of COVID-19 deaths in hospitalized heart patients. Click here to review the entire video interview. (Photo copyright: US Cardiology Review.)
Nearly half of the 870 hospitalized patients were admitted to intensive care units, 27% were placed on ventilators, 188 patients died in the hospital, and 50 additional patients died within three to six months after being released from the hospital.
10 of 13 medical centers performed limited cardiac exams as their primary COVID in-patient practice and three out of the 13 centers performed comprehensive exams.
In-hospital mortality rates ranged from 11% in Asia, 19% in Europe, 26% in the US, to 27% in Latin America.
Left ventricular longitudinal strain (LVLS), right ventricle free wall strain (RVFWS), as well as a patient’s age, lactic dehydrogenase levels and history of lung disease, were independently associated with mortality. Left ventricle ejection fraction (LVEF) was not.
Fully automated quantification of LVEF and LVLS using AI minimized variability.
AI-based left ventricular analyses, but not manual, were significant predictors of in-hospital and follow-up mortality.
The WASE-COVID Study also revealed the varying international use of cardiac ultrasound (echocardiography) on COVID-19 patients.
“By using machines, we reduce variability. By reducing variability, we have a better capacity to compare our results with other outcomes, whether that outcome in this case is mortality or it could be changes over time,” Asch stated in the US Cardiology Review video. “What this really means is that we may be able to show associations and comparisons by using AI that we cannot do with manual [readings] because manual has more variation and is less reliable.”
He said the next steps will be to see if the findings hold true when AI is used in other populations of cardiac patients.
COVID-19 Pandemic Increased Need for Swift Analyses
An earlier WASE Study in 2016 set out to answer whether normal left ventricular heart chamber quantifications vary across countries, geographical regions, and cultures. However, the data produced by that study took years to review. Asch said the COVID-19 pandemic created a need for such analysis to be done more quickly.
“When the pandemic began, we knew that the clinical urgency to learn as much as possible about the cardiovascular connection to COVID-19 was incredibly high, and that we had to find a better way of securely and consistently reviewing all of this information in a timely manner,” he said in the Ultromics new release.
Coronary artery disease (CAD) is the most common form of heart disease and affects more than 16.5 million people over the age of 20. By 2035, the economic burden of CAD will reach an estimated $749 billion in the US alone, according to the Ultromics website.
“COVID-19 has placed an even greater pressure on cardiac care and looks likely to have lasting implications in terms of its impact on the heart,” said Ross Upton, PhD, Founder and CEO of Oxford, UK-based Ultromics, in a news release announcing the US Food and Drug Administration’s 510(k) clearance for the EchoGo Pro, which supports clinicians’ diagnosing of CAD. “The healthcare industry needs to quickly pivot towards AI-powered automation to reduce the time to diagnosis and improve patient care.”
Use of AI to analyze digital pathology images is expected to be a fast-growing element in the anatomic pathology profession, particularly in the diagnosis of cancer. As Dark Daily outlined in this free white Paper, “Anatomic Pathology at the Tipping Point? The Economic Case for Adopting Digital Technology and AI Applications Now,” anatomic pathology laboratories can expect adoption of AI and digital technology to gain in popularity among pathologists in coming years.
