Understanding why some mutations impair normal bodily functions and contribute to cancer may lead to new clinical laboratory diagnostics
New insight into the human genome may help explain the ageing process and provide clues to improving human longevity that can be useful to clinical laboratories and researchers developing cancer diagnostics. A recent study conducted at the Wellcome Sanger Institute in Cambridge, United Kingdom, suggests that the speed of DNA errors in genetic mutations may play a critical role in the lifespan and survival of a species.
To perform their research, the scientists analyzed genomes from the intestines of 16 mammalian species looking for genetic changes. Known as somatic mutations, these mutations are a natural process that occur in all cells during the life of an organism and are typically harmless. However, some somatic mutations can impair the normal function of a cell and even play a role in causing cancer.
“Aging is a complex process, the result of multiple forms of molecular damage in our cells and tissues. Somatic mutations have been speculated to contribute to ageing since the 1950s, but studying them had remained difficult,” said Inigo Martincorena, PhD (above), Group Leader, Sanger Institute and one of the authors of the study. Greater understanding of the role DNA mutations play in cancer could lead to new clinical laboratory tools and diagnostics. (Photo copyright: Wellcome Sanger Institute.)
Lifespans versus Body Mass
The mammalian subjects examined in the study incorporated a wide range of lifespans and body masses and included humans, giraffes, tigers, mice, and the highly cancer-resistant naked mole-rat. The average number of somatic mutations at the end of a lifespan was around 3,200 for all the species studied, despite vast differences in age and body mass. It appears that species with longer lifespans can slow down their rate of genetic mutations.
The average lifespan of the humans used for the study was 83.6 years and they had a somatic mutation rate of 47 per year. Mice examined for the research endured 796 of the mutations annually and only lived for 3.7 years.
Species with similar amounts of the mutations had comparable lifespans. For example, the small, naked mole-rats analyzed experienced 93 mutations per year and lived to be 25 years of age. On the other hand, much larger giraffes encountered 99 mutations each year and had a lifespan of 24 years.
“With the recent advances in DNA sequencing technologies, we can finally investigate the roles that somatic mutations play in ageing and in multiple diseases,” said Inigo Martincorena, PhD, Group Leader, Sanger Institute, one of the authors of the study in a press release. He added, “That this diverse range of mammals end their lives with a similar number of mutations in their cells is an exciting and intriguing discovery.”
The scientists analyzed the patterns of the mutations and found that the somatic mutations accumulated linearly over time. They also discovered that the mutations were caused by similar mechanisms and the number acquired were relatively similar across all the species, despite a difference in diet and life histories. For example, a giraffe is typically 40,000 times larger than a mouse, but both species accumulate a similar number of somatic mutations during their lifetimes.
“The fact that differences in somatic mutation rate seem to be explained by differences in lifespan, rather than body size, suggests that although adjusting the mutation rate sounds like an elegant way of controlling the incidence of cancer across species, evolution has not actually chosen this path,” said Adrian Baez-Ortega, PhD, postdoctoral researcher at the Sanger Institute and one of the paper’s authors, in the press release.
“It is quite possible that every time a species evolves a larger size than its ancestors—as in giraffes, elephants, and whales—evolution might come up with a different solution to this problem. We will need to study these species in greater detail to find out,” he speculated.
Why Some Species Live Longer than Others
The researchers also found that the rate of somatic mutations decreased as the lifespan of each species increased which suggests the mutations have a likely role in ageing. It appears that humans and animals perish after accumulating a similar number of these genetic mutations which implies that the speed of the mutations is vital in ascertaining lifespan and could explain why some species live substantially longer than others.
“To find a similar pattern of genetic changes in animals as different from one another as a mouse and a tiger was surprising. But the most exciting aspect of the study has to be finding that lifespan is inversely proportional to the somatic mutation rate,” said Alex Cagan, PhD, Postdoctoral Fellow at the Sanger Institute and one of the authors of the study in the press release.
“This suggests that somatic mutations may play a role in ageing, although alternative explanations may be possible. Over the next few years, it will be fascinating to extend these studies into even more diverse species, such as insects or plants,” he noted.
Benefit of Understanding Ageing and Death
The scientists believe this study may provide insight to understanding the ageing process and the inevitability and timing of death. They surmise that ageing is likely to be caused by the aggregation of multiple types of damage to the cells and tissues suffered throughout a lifetime, including somatic mutations.
Some companies that offer genetic tests claim their products can predict longevity, despite the lack of widely accepted evidence that such tests are accurate within an acceptable range. Further research is needed to confirm that the findings of the Wellcome Sanger Institute study are relevant to understand the ageing process.
If the results are validated, though, it is probable that new direct-to-consumer (DTC) genetic tests will be developed, which could be a new revenue source for clinical laboratories.
DeepMind hopes its unrivaled collection of data, enabled by artificial intelligence, may advance development of precision medicines, new medical laboratory tests, and therapeutic treatments
‘Tis the season for giving, and one United Kingdom-based artificial intelligence (AI) research laboratory is making a sizeable gift. After using AI and machine learning to create “the most comprehensive map of human proteins,” in existence, DeepMind, a subsidiary of Alphabet Inc. (NASDAQ:GOOGL), parent company of Google, plans to give away for free its database of millions of protein structure predictions to the global scientific community and to all of humanity, The Verge reported.
Pathologists and clinical laboratory scientists developing proteomic assays understand the significance of this gesture. They know how difficult and expensive it is to determine protein structures using sequencing of amino acids. That’s because the various types of amino acids in use cause the [DNA] string to “fold.” Thus, the availability of this data may accelerate the development of more diagnostic tests based on proteomics.
“For decades, scientists have been trying to find a method to reliably determine a protein’s structure just from its sequence of amino acids. Attraction and repulsion between the 20 different types of amino acids cause the string to fold in a feat of ‘spontaneous origami,’ forming the intricate curls, loops, and pleats of a protein’s 3D structure. This grand scientific challenge is known as the protein-folding problem,” a DeepMind statement noted.
Enter DeepMind’s AlphaFold AI platform to help iron things out. “Experimental techniques for determining structures are painstakingly laborious and time consuming (sometimes taking years and millions of dollars). Our latest version [of AlphaFold] can now predict the shape of a protein, at scale and in minutes, down to atomic accuracy. This is a significant breakthrough and highlights the impact AI can have on science,” DeepMind stated.
Release of Data Will Be ‘Transformative’
In July, DeepMind announced it would begin releasing data from its AlphaFold Protein Structure Database which contains “predictions for the structure of some 350,000 proteins across 20 different organisms,” The Verge reported, adding, “Most significantly, the release includes predictions for 98% of all human proteins, around 20,000 different structures, which are collectively known as the human proteome. By the end of the year, DeepMind hopes to release predictions for 100 million protein structures.”
According to Edith Heard, PhD, Director General of the European Molecular Biology Laboratory (EMBL), the open release of such a dataset will be “transformative for our understanding of how life works,” The Verge reported.
“I see this as the culmination of the entire 10-year-plus lifetime of DeepMind,” company CEO and co-founder Demis Hassabis (above), told The Verge. “From the beginning, this is what we set out to do: to make breakthroughs in AI, test that on games like Go and Atari, [and] apply that to real-world problems, to see if we can accelerate scientific breakthroughs and use those to benefit humanity.” The release of DeepMind’s entire protein prediction database will certainly do that. Clinical laboratory scientists worldwide will have free access to use it in developing new precision medicine treatments based on proteomics. (Photo copyright: BBC.)
Free Data about Proteins Will Accelerate Research on Diseases, Treatments
Research into how protein folds and, thereby, functions could have implications to fighting diseases and developing new medicines, according to DeepMind.
“This will be one of the most important datasets since the mapping of the human genome,” said Ewan Birney, PhD, Deputy Director General of the EMBL, in the DeepMind statement. EMBL worked with DeepMind on the dataset.
DeepMind protein prediction data are already being used by scientists in medical research. “Anyone can use it for anything. They just need to credit the people involved in the citation,” said Demis Hassabis, DeepMind CEO and Co-founder, in The Verge.
In a blog article, Hassabis listed several projects and organizations already using AlphaFold. They include:
“As researchers seek cures for diseases and pursue solutions to other big problems facing humankind—including antibiotic resistance, microplastic pollution, and climate change—they will benefit from fresh insights in the structure of proteins,” Hassabis wrote.
Because of the deep financial backing that Alphabet/Google can offer, it is reasonable to predict that DeepMind will make progress with its AI technology that regularly adds capabilities and accuracy, allowing AlphaFold to be effective for many uses.
This will be particularly true for the development of new diagnostic assays that will give clinical laboratories better tools for diagnosing disease earlier and more accurately.
All-of-Us program is free to participants and provides data to more than 800 research studies for cancer, COVID-19, Alzheimer’s, and other diseases; findings will lead to new biomarkers for clinical laboratory tests
It is hard to say no to free. At least that is what the National Institutes of Health (NIH) is counting on to help increase the size and diversity of its database of genetic sequences. The NIH’s All-of-Us Research Program is offering free genetic testing for all participants in the program, as well as free wearable Fitbits for those selected to provide lifestyle and behavior data.
Many pathologists and clinical laboratory managers know that this group of researchers hope to build a database of more than one million genetic sequences to better understand “how certain genetic traits affect underrepresented communities, which could greatly affect the future of customized healthcare,” CBS affiliate 8 News Now reported.
“Customized healthcare” is a euphemism for precision medicine, and genetic sequencing is increasingly playing a key role in the development of personalized diagnostics and therapeutics for cancer and other deadly diseases.
In “VA’s ‘Million Veterans Program’ Research Study Receives Its 100,000th Human Genome Sequence,” Dark Daily described how the NIH’s All-of-Us program was launched in 2018 to aid research into health outcomes influenced by genetics, environments, and lifestyle. At that time, the program had biological samples from more than 270,000 people with a goal of one million participants.
Matthew Thombs, Senior Project Manager of Digital Health Technology at Scripps Research in La Jolla, Calif., joined the All-of-Us program after losing a family member “to a condition I believe could have been managed with changes to their lifestyle,” he told 8 News Now.
“What we are building will empower researchers with the information needed to make such conclusions (about possible need to change lifestyles) and forever alter how diseases are treated,” he added. “I hope that what we are doing here will help my son grow up in a world where healthcare is more of a priority, and many of the ailments we see today are things of the past.”
Such genetic testing could discover biomarkers for future personalized clinical laboratory diagnostics and drug therapies, a key aspect of precision medicine.
The photo above shows an All-of-Us participant being prepped to provide a biological sample for genetic testing. According to Matthew Thombs, Senior Project Manager of Digital Health Technology at Scripps Research, “participants can provide as much or as little information as they like, every single data point matters.” The collected data is shared anonymously with more than 800 research studies for COVID-19, Alzheimer’s, cancer, and other diseases, 8 News Now reported. (Photo copyright: KLAS-TV.)
Scripps Research Integrates Mobile Health Technology into All-of-Us Program
A critical aspect of the NIH’s research is determining how people’s behavior combined with their genetics may predispose them to certain diseases. Nonprofit research institution Scripps Research is working with the NIH’s All of Us Research Program to enroll and collect biological samples from one million US residents.
In addition, Scripps is fitting study participants with wearable mobile health devices to capture data on their habits and lifestyles.
“Until now, the treatment and prevention of disease has been based on a ‘one-size-fits-all’ approach, with most therapeutics tailored for the ‘average patient’. However, advances in genomic sequencing, mobile health technologies, and increasingly sophisticated informatics are ushering in a new era of precision medicine. This new approach takes into account differences in people’s genes, environment, and lifestyles giving medical professionals resources to design targeted treatments and prevention strategies for the individual,” Scripps states on its website.
Can wearable fitness devices and related data contribute to research on genetics and healthcare outcomes? Scripps aims to find out. It has fitted 10,000 people in the All-of-Us program with Fitbit devices (Fitbit Charge 4 tracker or Fitbit Versa 3 smartwatch) at no cost. Since February, Scripps has distributed 10,000 Fitbit wearable devices through the All-of-Us program.
“By sharing information about their health, habits, and environment, participants will help researchers understand why people get sick or stay healthy,” the Scripps website adds.
The Scripps researchers plan to analyze how the people use the wearable devices. They are also accumulating data about participants’ physical activity, heart rate, sleep, and other health metrics and outcomes “as part of the broader All of Us program,” a Scripps news release explained.
“This is the first time All of Us is distributing devices to participants. Our goal is to better understand how participants engage during research studies in order to continually improve user experience and participation. We also expect to learn more about how wearable data may inform the personalization of healthcare,” said Julia Moore Vogel, PhD, Director of The Participant Center at the All of Us Research Program at Scripps Research, in the news release.
All-of-Us Program Records ‘Significant Progress in Participant Diversity’
As of June, the NIH has enrolled 386,000 participants into the All-of-Us program, with 278,000 consenting to all of the program’s steps. Eighty percent of biological samples in the collection are from people in communities that have been under-represented in previous biomedical research an NIH new release noted. According to the NIH, that gives the All-of-Us research program “the most diverse dataset.”
What will all this research ultimately bring to clinical laboratories? Who knows? Nevertheless, if federal institutions like the NIH and non-profit research companies like Scripps believe precision medicine is worth investing in, then the All-of-Us program is worth watching.
A diverse database of a million genetic sequences combined with lifestyle and behavioral data may lead to new and improved personalized diagnostics and drug therapies.
The scientist also employed machine learning “to gauge how easily accessible genes are for transcription” in research that could lead to new clinical laboratory diagnostic tests
Anatomic pathologists and clinical laboratories are of course familiar with the biological science of genomics, which, among other things, has been used to map the human genome. But did you know that a three-dimensional (3D) map of a genome has been created and that it is helping scientists understand how DNA regulates its organization—and why?
The achievement took place at St. Jude Children’s Research Hospital (St. Jude) in Memphis, Tenn. Scientists there created “the first 3D map of a mouse genome” to study “the way cells organize their genomes during development,” a St. Jude news release noted.
Some experts predict that this new approach to understanding how changes happen in a genome could eventually provide new insights that anatomic pathologists and clinical laboratory scientists could find useful when working with physicians to diagnose patients and using the test results to identify the most appropriate therapy for those patients.
In addition to 3D modeling, the researchers applied machine learning to data from multiple sources to see how the organization of the genome changed at different times during development. “The changes are not random, but part of the developmental program of cells,” Dyer said in the news release.
The St. Jude study focused on the rod cells in a mouse retina. That may seem like a narrow scope, but there are more than 8,000 genes involved in retinal development in mice, during which those genes are either turned on or off.
To see what was happening among the cells, the researchers used HI-C analysis, an aspect of ultra-deep chromosome conformation capture, in situ. They found that the loops in the DNA bring together regions of the genome, allowing them to interact in specific ways.
Until this study, how those interactions took place was a
mystery.
“Understanding the way cells organize their genomes during development will help us to understand their ability to respond to stress, injury and disease,”Michael Dyer, PhD (above), Chair of St. Jude’s Developmental Neurobiology Department, co-leader of the Developmental Biology and Solid Tumor Program, and Investigator at Howard Hughes Medical Institute (HHMI), said in the news release. (Photo copyright: St. Jude Children’s Research Hospital.)
The scientists also discovered there were DNA promoters, which encourage gene expression, and also DNA enhancers that increase the likelihood gene expression will occur.
“The research also included the first report of a powerful regulator of gene expression, a super enhancer, that worked in a specific cell at a specific stage of development,” the news release states. “The finding is important because the super enhancers can be hijacked in developmental cancers of the brain and other organs.”
St. Jude goes on to state, “In this study, the scientists determined that when a core regulatory circuit super-enhancer for the VSX2 gene was deleted, an entire class of neurons (bipolar neurons) was eliminated. No other defects were identified. Deletion of the VSX2 gene causes many more defects in retinal development, so the super-enhancer is highly specific to bipolar neurons.”
The St. Jude researchers developed a genetic mouse model of
the defect that scientists are using to study neural circuits in the retina,
the news release states.
Research Technologist Victoria Honnell (left); Developmental Neurobiologist Jackie Norrie, PhD (center); and Postdoctoral Researcher Marybeth Lupo, PhD (right), work in the St. Jude clinical laboratory of Michael Dyer, PhD, using 3D genomic mapping to study gene regulation during development and disease. (Photo copyright: St. Jude Children’s Research Hospital.)
DNA Loops May Matter to Pathology Sooner Rather than
Later
Previous researcher studies primarily used genomic sequencing technology to locate and investigate alterations in genes that lead to disease. In the St. Jude study, the researchers examined how DNA is packaged. If the DNA of a single cell could be stretched out, it would be more than six feet long. To fit into the nucleus of a cell, DNA is looped and bundled into a microscopic package. The St. Jude scientists determined that how these loops are organized regulates how the cell functions and develops.
Scientists around the world will continue studying how the loops in DNA impact gene regulation and how that affects the gene’s response to disease. At St. Jude Children’s Research Hospital, Dyer and his colleagues “used the same approach to create a 3D genomic map of the mouse cerebellum, a brain structure where medulloblastoma can develop. Medulloblastoma is the most common malignant pediatric brain tumor,” noted the St. Jude’s news release.
In addition to providing an understanding of how genes
function, these 3D studies are providing valuable insight into how some
diseases develop and mature. While nascent research such as this may not impact
pathologists and clinical laboratories at the moment, it’s not a stretch to
think that this work may lead to greater understanding of the pathology of
diseases in the near future.
Researchers are discovering it’s possible to determine a person’s age based on the amount of protein in the blood, but the technology isn’t always correct
Mass spectrometry is increasingly finding its way into clinical laboratories and with it—proteomics—the study of proteins in the human body. And like the human genome, scientists are discovering that protein plays an integral part in the aging process.
This is a most interesting research finding. Might medical laboratories someday use proteomic biomarkers to help physicians gauge the aging progression in patients? Might this diagnostic capability give pathologists and laboratory leaders a new product line for direct-to-consumer testing that would be a cash-paying, fast-growing, profitable clinical laboratory testing service? If so, proteomics could be a boon to clinical laboratories worldwide.
When research into genomics was brand-new, virtually no one imagined that someday the direct-to-consumer lab testing model would offer genetic testing to the public and create a huge stream of revenue for clinical laboratories that process genetic tests. Now, research into protein and aging might point to a similar possibility for proteomics.
For example, through proteomics, researchers led by Benoit Lehallier, PhD, Biostatistician, Instructor of Neurology and Neurological Sciences, and senior author Tony Wyss-Coray, PhD, Professor of Neurology and Neurological Sciences and co-director of the Stanford Alzheimer’s Disease Research Center at Stanford University in California, gained an understanding of aging that suggest intriguing possibilities for clinical laboratories.
In their study, published in Nature, titled, “Undulating Changes in Human Plasma Proteome Profiles Across the Lifespan,” the scientists stated that aging doesn’t happen in a consistent process over time, reported Science Alert.
The Stanford researchers also found that they can accurately
determine a person’s age based on the levels of certain proteins in his or her
blood.
Additionally, the study of proteomics may finally explain why blood from young people can have a rejuvenating effect on elderly people’s brains, noted Scientific American.
Each of these findings is important on its own, but taken
together, they may have interesting implications for pathologists who follow
the research. And medical laboratory leaders may find opportunities in mass
spectrometry in the near future, rather than decades from now.
Three Distinct Stages in Aging and Other Findings
The Stanford study found that aging appears to happen at
three distinct points in a person’s life—around the ages 34, 60, and 78—rather
than being a slow, steady process.
The researchers measured and compared levels of nearly 3,000
specific proteins in blood plasma taken from healthy people between the ages of
18 and 95 years. In the published study, the authors wrote, “This new approach
to the study of aging led to the identification of unexpected signatures and
pathways that might offer potential targets for age-related diseases.”
Along with the findings regarding the timeline for aging, the researchers found that about two-thirds of the proteins that change with age differ significantly between men and women. “This supports the idea that men and women age differently and highlights the need to include both sexes in clinical studies for a wide range of diseases,” noted a National Institutes of Health (NIH) report.
“We’ve known for a long time that measuring certain proteins in the blood can give you information about a person’s health status—lipoproteins for cardiovascular health, for example,” stated Wyss-Coray in the NIH report. “But it hasn’t been appreciated that so many different proteins’ levels—roughly a third of all the ones we looked at—change markedly with advancing age.”
Tony Wyss-Coray, PhD (above), Professor of Neurology and Neurological Sciences at Stanford University, was senior author of the proteomics study that analyzed blood plasma from 4,263 people between the ages 18-95. “Proteins are the workhorses of the body’s constituent cells, and when their relative levels undergo substantial changes, it means you’ve changed, too,” he said in a Stanford Medicine news article. “Looking at thousands of them in plasma gives you a snapshot of what’s going on throughout the body.” (Photo copyright: Stanford University.)
Differentiating Aging from Disease
Previous research studies also found it is indeed possible
to measure a person’s age from his or her “proteomic signature.”
The researchers published their findings in Aging Cell, a peer-reviewed open-access journal of the Anatomical Society in the UK, titled, “Plasma Proteomic Signature of Age in Healthy Humans.” In it, the authors wrote, “Our results suggest that there are stereotypical biological changes that occur with aging that are reflected by circulating proteins.”
The fact that chronological age can be determined through a
person’s proteomic signature suggests researchers could separate aging from
various diseases. “Older age is the main risk factor for a myriad of chronic
diseases, and it is invariably associated with progressive loss of function in
multiple physiological systems,” wrote the researchers, adding, “A challenge in
the field is the need to differentiate between aging and diseases.”
Can Proteins Cause Aging?
Additionally, the Stanford study found that changes in protein levels might not simply be a characteristic of aging, but may actually cause it, a Stanford Medicine news article notes.
“Changes in the levels of numerous proteins that migrate
from the body’s tissues into circulating blood not only characterize, but quite
possibly cause, the phenomenon of aging,” Wyss-Coray said.
Can Proteins Accurately Predict Age? Not Always
There were, however, some instances where the protein levels inaccurately predicted a person’s age. Some of the samples the Stanford researchers used were from the LonGenity research study conducted by the Albert Einstein College of Medicine, which investigated “why some people enjoy extremely long life spans, with physical health and brain function far better than expected in the 9th and 10th decades of life,” the study’s website notes.
That study included a group of exceptionally long-lived Ashkenazi Jews, who have a “genetic proclivity toward exceptionally good health in what for most of us is advanced old age,” according to the Stanford Medicine news article.
“We had data on hand-grip strength and cognitive function
for that group of people. Those with stronger hand grips and better measured
cognition were estimated by our plasma-protein clock to be younger than they
actually were,” said Wyss-Coray. So, physical condition is a factor in
proteomics’ ability to accurately prediction age.
Although understanding the connections between protein in
the blood, aging, and disease is in early stages, it is clear additional
research is warranted. Not too long ago the idea of consumers having their DNA
sequenced from a home kit for fun seemed like fantasy.
However, after multiple FDA approvals, and the success of
companies like Ancestry, 23andMe, and the clinical laboratories that serve them,
the possibility that proteomics might go the same route does not seem so
far-fetched.
