News, Analysis, Trends, Management Innovations for
Clinical Laboratories and Pathology Groups

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News, Analysis, Trends, Management Innovations for
Clinical Laboratories and Pathology Groups

Hosted by Robert Michel
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Google’s Calico Start-up to Sequence Whole Human Genomes of Healthy 100-Year-Olds in Project to Solve Puzzle of Human Aging

If successful, the knowledge gained from this research may provide new tools and medical laboratory tests that pathologists can use in the management of geriatric patients

Google’s founders believe that analysis of the genomes of people who live to be 100 years old and are relatively healthy will allow them to solve the puzzle of human aging. They have funded a new company specifically to pursue this goal.

In the near future, it is unlikely that any of the science developed by this venture will lead to a diagnostic profile or clinical laboratory tests that pathologists can use to help clinicians who deal with the diseases associated with aging. But should the research team at Calico develop a better understanding of the dynamics of human aging, it would certainly be expected that this knowledge would be used to develop appropriate medical laboratory tests. (more…)

Google DeepMind’s AlphaFold Wins CASP14 Competition, Helps Solve Mystery of Protein Folding in a Discovery That Might be Used in New Medical Laboratory Tests

The AI protein-structure-prediction system may ‘revolutionize life sciences by enabling researchers to better understand disease,’ researchers say

Genomics leaders watched with enthusiasm as artificial intelligence (AI) accelerated discoveries that led to new clinical laboratory diagnostic tests and advanced the evolution of personalized medicine. Now Google’s London-based DeepMind has taken that a quantum step further by demonstrating its AI can predict the shape of proteins to within the width of one atom and model three-dimensional (3D) structures of proteins that scientist have been trying to map accurately for 50 years.

Pathologists and clinical laboratory professionals know that it is estimated that there are around 30,000 human genes. But the human proteome has a much larger number of unique proteins. The total number is still uncertain because scientists continue to identify new human proteins. For this reason, more knowledge of the human protein is expected to trigger an expanding number of new assays that can be used by medical laboratories for diagnostic, therapeutic, and patient-monitoring purposes.

DeepMind’s AI tool is called AlphaFold and the protein-structure-prediction system will enable scientists to quickly move from knowing a protein’s DNA sequence to determining its 3D shape without time-consuming experimentation. It “is expected to accelerate research into a host of illnesses, including COVID-19,” BBC News reported.

This protein-folding breakthrough not only answers one of biology’s biggest mysteries, but also has the potential to revolutionize life sciences by enabling researchers to better understand disease processes and design personalized therapies that target specific proteins.

“It’s a game changer,” Andrei Lupas, PhD, Director at the Max Planck Institute for Developmental Biology in Tübingen, Germany, told the journal Nature. “This will change medicine. It will change research. It will change bioengineering. It will change everything.”

AlphaFold Wins Prestigious CASP14 Competition

In November, DeepMind’s AlphaFold won the 14th Community Wide Experiment on Critical Assessment of Techniques for Protein Structure Prediction (CASP14), a biennial competition in which entrants receive amino acid sequences for about 100 proteins whose 3D structures are unknown. By comparing the computational predictions with the lab results, each CASP14 competitor received a global distance test (GDT) score. Scores above 90 out of 100 are considered equal to experimental methods. AlphaFold produced models for about two-thirds of the CASP14 target proteins with GDT scores above 90, a CASP14 press release states.

According to MIT Technology Review, DeepMind’s discovery is significant. That’s because its speed at predicting the structure of proteins is unprecedented and it matched the accuracy of several techniques used in clinical laboratories, including:

Unlike the laboratory techniques, which, MIT noted, are “expensive and slow” and “can take hundreds of thousands of dollars and years of trial and error for each protein,” AlphaFold can predict a protein’s shape in a few days.

“AlphaFold is a once in a generation advance, predicting protein structures with incredible speed and precision,” Arthur D. Levinson, PhD, Founder and CEO of Calico Life Sciences, said in a DeepMind blogpost. “This leap forward demonstrates how computational methods are poised to transform research in biology and hold much promise for accelerating the drug discovery process.”

AlphaFold graph chart
Science reported that AlphaFold, which scored a median of 87—25 points above the next best predictions—did so well that CASP14 organizers worried DeepMind may have been somehow cheated. To validate the results, they asked AlphaFold to complete a “special challenge”—modeling a membrane protein from an ancient species of microbes called archaea, which they had been unable to model satisfactorily using X-ray crystallography. AlphaFold returned a detailed image of a three-part protein with two long helical arms in the middle. “It’s almost perfect,” Andrei Lupas, PhD, Director at the Max Planck Institute for Developmental Biology, told Science. “They could not possibly have cheated on this. I don’t know how they do it.”  (Graphic copyright: DeepMind/Nature.)

Revolutionizing Life Sciences

John Moult, PhD, Professor, University of Maryland Department of Cell Biology and Molecular Genetics, who cofounded CASP in 1994 and chairs the panel, pointed out that scientists have been attempting to solve the riddle of protein folding since Christian Anfinsen, PhD, was awarded the 1972 Nobel Prize in Chemistry for showing it should be possible to determine the shape of proteins based on their amino acid sequence.

“Even tiny rearrangements of these vital molecules can have catastrophic effects on our health, so one of the most efficient ways to understand disease and find new treatments is to study the proteins involved,” Moult said in the CASP14 press release. “There are tens of thousands of human proteins and many billions in other species, including bacteria and viruses, but working out the shape of just one requires expensive equipment and can take years.”

Science reported that the 3D structures of only 170,000 proteins have been solved, leaving roughly 200 million proteins that have yet to be modeled. Therefore, AlphaFold will help researchers in the fields of genomics, microbiomics, proteomics, and other omics understand the structure of protein complexes.

“Being able to investigate the shape of proteins quickly and accurately has the potential to revolutionize life sciences,” Andriy Kryshtafovych, PhD, Project Scientist at University of California, Davis, Genome Center, said in the press release. “Now that the problem has been largely solved for single proteins, the way is open for development of new methods for determining the shape of protein complexes—collections of proteins that work together to form much of the machinery of life, and for other applications.”

Clinical laboratories play a major role in the study of human biology. This breakthrough in genomics research and new insights into proteomics may provide opportunities for medical labs to develop new diagnostic tools and assays that better identify proteins of interest for diagnostic and therapeutic purposes.

—Andrea Downing Peck

Related Information:

AI Solution to a 50-Year-Old Science Challenge Could ‘Revolutionize’ Medical Research

‘It Will Change Everything’: DeepMind’s AI Makes Gigantic Leap in Solving Protein Structures

Protein Structure Prediction Using Multiple Deep Neural Networks in the 13th Critical Assessment of Protein Structure Prediction (CASP13)

AlphaFold: A Solution to a 50-Year-Old Grand Challenge in Biology

DeepMind’s Protein-Folding AI Has Solved A 50-Year-Old Grand Challenge of Biology

‘The Game Has Changed.’ AI Triumphs at Solving Protein Structures

One of Biology’s Biggest Mysteries ‘Largely Solved’ by AI

Sales of Direct-to-Consumer Clinical Laboratory Genetic Tests Soar, as Members of Congress Debate How Patient Data Should be Handled, Secured, and Kept Private

Direct-to-consumer (DTC) genetic testing has been much in the news of late and clinical laboratories, anatomic pathology groups, and biomedical researchers have a stake in how the controversy plays out.

While healthcare consumers seem enamored with the idea of investigating their genomic ancestry in growing numbers, the question of how the data is collected, secured, and distributed when and to whom, is under increased scrutiny by federal lawmakers, bioethicists, and research scientists.

However, should public demand for DTC testing find support in Congress, some lab companies offering direct-to-consumer genetic tests could find their primary source of revenue curtailed.

DTC Sales Skyrocket as FDA Authorizes Genetic Tests for Certain Chronic Diseases

Dark Daily reported last fall on one company that had its plans to distribute thousands of free genetic tests at a football game suspended due to privacy concerns. (See, “State and Federal Agencies Throw Yellow Flag Delaying Free Genetic Tests at NFL Games in Baltimore—Are Clinical Laboratories on Notice about Free Testing?” October 13, 2017.)

Nevertheless, consumer demand for DTC tests continues to rise. In a press release, Ancestry, a family genetic history and consumer genomics company, reported:

  • Record sales of AncestryDNA kits during the 2017 four-day Black Friday to Cyber Monday weekend, selling more than 1.5 million kits; and,
  • The 2017 sales were triple the amount of kits sold during the same period in 2016.

Possibly helping the sale of DTC genetic tests may be the US Food and Drug Administration (FDA) authorization last year of 23andMe’s Personal Genome Service Genetic Health Risk tests for 10 diseases or conditions, including:

Senator Calls for Investigation of DTC Genetic Test Company Use of Patient Data

These are impressive sales. However, medical professionals may wonder how so much genetic data can be kept private by the testing companies. And medical laboratory leaders are not the only ones asking about privacy and the use of genetic test results.

In a November press conference, Senate Minority Leader Chuck Schumer called on the Federal Trade Commission (FTC) to look into genetic testing companies’ privacy and disclosure practices, noted NBC News.

“What those companies can do with all that data—your most sensitive and deepest info, your genetics—is not clear, and in some cases not fair and not right,” stated Schumer.

Congress took action in 2008 by passing the Genetic Information and Nondiscrimination Act (GINA), which bans employers and insurers from making decisions about people based on genetic predispositions to disease.

However, lawmakers also recently introduced House Bill 1313, the Preserving Employee Wellness Programs Act. It reads, in part, “… the collection of information about the manifested disease or disorder of a family member shall not be considered an unlawful acquisition of genetic information with respect to another family as part of a workplace wellness program offered by an employer ….”

“We’re injecting terrible opportunities for discrimination in the workplace,” Robert Green, MD, Professor of Medicine (Genetics) at Harvard Medical School, told Gizmodo.

Robert C. Green, MD, MPH

Robert C. Green, MD, MPH (above), Professor of Medicine, Harvard Medical School; Associate Physician, Brigham and Women’s Hospital; Geneticist, Brigham and Women’s Hospital; and Director, Genomes2People Research Program at Brigham and Women’s Hospital, believes weak genetic privacy laws are inhibiting research and clinical care. “People decline genetic tests because of concerns over privacy and genetic discrimination, especially insurance discrimination,” he told Gizmodo. “This is stymying biomedical research and people’s access to healthcare.” (Photo copyright: Harvard Medical School.)

HIPAA Enables Selling of Anonymized Patient Genetic Data

Peter Pitts, former FDA Associate Commissioner, and President and Co-founder of the Center for Medicine in the Public Interest, a non-profit medical issues research group, blames the release of data by DTC genetic test companies on the Health Insurance Portability and Accountability Act (HIPAA), a law he says makes way for “anonymized” sale of patient data.

“The Portability Act was passed when genetic testing was just a distant dream on the horizon of personalized medicine,” Pitts wrote in a Forbes commentary. “But today that loophole has proven to be a cash cow. 23andMe has sold access to its database to at least 13 outside pharmaceutical firms … AncestryDNA recently announced a lucrative data-sharing partnership with the biotech company Calico.”

For its part, in an online privacy statement, 23andMe noted, “We will use your genetic information or self-reported information and share it with third parties for scientific research purposes only if you sign the appropriate consent document.”

Similarly, Ancestry points out in its posted privacy statement, “We share your genetic information with research partners only when you provide us with your express consent to do so through our informed consent to research.

Consumers Speak Out on Privacy; States Study Laws and Genetic Testing by Research Hospitals

How do consumers feel about the privacy of their genetic test data?  According to a news release, a survey by 23andMe found the following:

  • 80% of Americans are concerned about DNA testing privacy; however,
  • 88% have no awareness or understanding of what testing companies do to protect information; and,
  • 74% of people are, nonetheless, interested in genetic testing.

Meanwhile, as states promulgate various genetic privacy laws, a paper published at SSRN by researchers at the Massachusetts Institute of Technology (MIT) and the University of Virginia (UV) examined how different state laws affect patients’ decisions about having genetic testing performed at various research hospitals.

The MIT/UV study focused on genetic testing by research hospitals as opposed to the DTC genetic testing by private companies. The paper explained that states have one of three types of laws to protect patients’ privacy in genetic testing:

  • “Require the provider to notify the individual about potential privacy risks;
  • “Restrict discriminatory use of genetic data by employers or insurance companies; and,
  • “Limit redisclosure without consent.”

Findings, netted from more than 81,000 respondents, suggest:

  • When genetic data are explained in state laws as patient property, more tests are performed;
  • Conversely, state laws that focus on risk, and ask patients to consent to risk, lead to less people giving the go-ahead for genetic testing.

“We found a positive effect [on the number of tests] was an approach where you gave patients the potential to actually control their own data,” Catherine Tucker, PhD,  Distinguished Professor of Management at MIT and one of the study researchers, told MIT News.

Whether the provider of genetic tests is a private testing company or a research hospital’s clinical laboratory, privacy continues to be a concern, not just to physicians but to federal lawmakers as well. Nevertheless, healthcare consumers and patients who receive comprehensible information about how their genetic data may be used seem to be agreeable to it. At least for now, that is.

—Donna Marie Pocius

Related Information:

AncestryDNA Breaks Holiday Sales Record Black Friday to Cyber Monday

Senator Calls for More Scrutiny of Home DNA Test Industry

The Present and Future Asymmetry of Consumer Genetic Testing

Are Our Terrible Genetic Privacy Laws Hurting Science?

The Privacy Delusions of Genetic Testing

National Survey Shows Strong Interest in DNA Testing

Privacy Protection, Personalized Medicine, and Genetic Testing

How Privacy Policies Affect Genetic Testing

State and Federal Agencies Throw Yellow Flag Delaying Free Genetic Tests at NFL Games in Baltimore—Are Clinical Laboratories on Notice about Free Testing?

Human Longevity Inc. Unleashes Power of Whole-Genome Sequencing to Unlock Keys to Healthy Aging; Research May Lead to New Clinical Laboratory Tests

Human genome pioneer J. Craig Venter’s newest project seeks to ‘change the way medicine is practiced’ by creating genomic-based medicine model

With little fanfare or public notice, a start-up company in San Diego is busy sequencing the largest number of whole human genome sequences in the world. The knowledge expected to result from this effort promises to revolutionize healthcare, as well as clinical laboratory testing.

Human Longevity Inc. (HLI) is a genomics and cell therapy company that has assembled the largest human genome sequencing operation in the world. It’s goal is to use whole genome sequencing and cell-based therapeutics to redefine aging and “meaningfully extend the human lifespan.”

“HLI’s mission is to identify the therapeutically targetable mechanisms responsible for age-related human biological decline, and to apply this intelligence to develop innovative solutions to interrupt or block these processes, meaningfully extending the human lifespan,” HLI states on its website. “We are trying to tackle some of the most vexing diseases like cancer, heart disease, and diabetes … we are working to change the way medicine is practiced through our genomic-focused, preventive model.” (more…)

Google Files Patent for Needle-free Blood Draw System That Could Eventually Remove Clinical Laboratories and Pathology Groups from the Process

Patent filing describes a device that is intended to allow patients to collect their own blood specimens without the need for needles

Google, (now known as Alphabet, Inc.; NASDAQ:GOOG) recently filed an application for another patent that deals with medical laboratory test technology. This patent application is for a needle-free blood draw system that enables patients to perform diagnostic testing on themselves.

The new system is designed to replace painful finger pricks and deliver diagnostic test results digitally to providers’ electronic health record (EHR) systems. Should the technology make it through clinical trials, widespread adoption of such a device could have sweeping implications for pathologists and clinical laboratories across America. (more…)

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