Who Qualifies as an “Expert” And How Can We Decide Who Is Trustworthy?
This article is part of the magazine, "The Future of Science In America: The Election Issue," co-published by LeapsMag, the Aspen Institute Science & Society Program, and GOOD.
Expertise is a slippery concept. Who has it, who claims it, and who attributes or yields it to whom is a culturally specific, sociological process. During the COVID-19 pandemic, we have witnessed a remarkable emergence of legitimate and not-so-legitimate scientists publicly claiming or being attributed to have academic expertise in precisely my field: infectious disease epidemiology. From any vantage point, it is clear that charlatans abound out there, garnering TV coverage and hundreds of thousands of Twitter followers based on loud opinions despite flimsy credentials. What is more interesting as an insider is the gradient of expertise beyond these obvious fakers.
A person's expertise is not a fixed attribute; it is a hierarchical trait defined relative to others. Despite my protestations, I am the go-to expert on every aspect of the pandemic to my family. To a reporter, I might do my best to answer a question about the immune response to SARS-CoV-2, noting that I'm not an immunologist. Among other academic scientists, my expertise is more well-defined as a subfield of epidemiology, and within that as a particular area within infectious disease epidemiology. There's a fractal quality to it; as you zoom in on a particular subject, a differentiation of expertise emerges among scientists who, from farther out, appear to be interchangeable.
We all have our scientific domain and are less knowledgeable outside it, of course, and we are often asked to comment on a broad range of topics. But many scientists without a track record in the field have become favorites among university administrators, senior faculty in unrelated fields, policymakers, and science journalists, using institutional prestige or social connections to promote themselves. This phenomenon leads to a distorted representation of science—and of academic scientists—in the public realm.
Trustworthy experts will direct you to others in their field who know more about particular topics, and will tend to be honest about what is and what isn't "in their lane."
Predictably, white male voices have been disproportionately amplified, and men are certainly over-represented in the category of those who use their connections to inappropriately claim expertise. Generally speaking, we are missing women, racial minorities, and global perspectives. This is not only important because it misrepresents who scientists are and reinforces outdated stereotypes that place white men in the Global North at the top of a credibility hierarchy. It also matters because it can promote bad science, and it passes over scientists who can lend nuance to the scientific discourse and give global perspectives on this quintessentially global crisis.
Also at work, in my opinion, are two biases within academia: the conflation of institutional prestige with individual expertise, and the bizarre hierarchy among scientists that attributes greater credibility to those in quantitative fields like physics. Regardless of mathematical expertise or institutional affiliation, lack of experience working with epidemiological data can lead to over-confidence in the deceptively simple mathematical models that we use to understand epidemics, as well as the inappropriate use of uncertain data to inform them. Prominent and vocal scientists from different quantitative fields have misapplied the methods of infectious disease epidemiology during the COVID-19 pandemic so far, creating enormous confusion among policymakers and the public. Early forecasts that predicted the epidemic would be over by now, for example, led to a sense that epidemiological models were all unreliable.
Meanwhile, legitimate scientific uncertainties and differences of opinion, as well as fundamentally different epidemic dynamics arising in diverse global contexts and in different demographic groups, appear in the press as an indistinguishable part of this general chaos. This leads many people to question whether the field has anything worthwhile to contribute, and muddies the facts about COVID-19 policies for reducing transmission that most experts agree on, like wearing masks and avoiding large indoor gatherings.
So how do we distinguish an expert from a charlatan? I believe a willingness to say "I don't know" and to openly describe uncertainties, nuances, and limitations of science are all good signs. Thoughtful engagement with questions and new ideas is also an indication of expertise, as opposed to arrogant bluster or a bullish insistence on a particular policy strategy regardless of context (which is almost always an attempt to hide a lack of depth of understanding). Trustworthy experts will direct you to others in their field who know more about particular topics, and will tend to be honest about what is and what isn't "in their lane." For example, some expertise is quite specific to a given subfield: epidemiologists who study non-infectious conditions or nutrition, for example, use different methods from those of infectious disease experts, because they generally don't need to account for the exponential growth that is inherent to a contagion process.
Academic scientists have a specific, technical contribution to make in containing the COVID-19 pandemic and in communicating research findings as they emerge. But the liminal space between scientists and the public is subject to the same undercurrents of sexism, racism, and opportunism that society and the academy have always suffered from. Although none of the proxies for expertise described above are fool-proof, they are at least indicative of integrity and humility—two traits the world is in dire need of at this moment in history.
[Editor's Note: To read other articles in this special magazine issue, visit the beautifully designed e-reader version.]
This Brain Doc Has a “Repulsive” Idea to Make Football Safer
What do football superstars Tom Brady, Drew Brees, Philip Rivers, and Adrian Peterson all have in common? Last year they wore helmets that provided the poorest protection against concussions in all the NFL.
"You're only as protected as well as the worst helmet that's out there."
A Dangerous Policy
Football helmets are rated on a one-star to five-star system based on how well they do the job of protecting the player. The league has allowed players to use their favorites, regardless of the star rating.
The Oxford-trained neuroscientist Ray Colello conducted a serious analysis of just how much the protection can vary between each level of star rating. Colello and his team of graduate students sifted through two seasons of game video to identify which players were wearing what helmets. There was "a really good correlation with position, but the correlation is much more significant based on age."
"The average player in the NFL is 26.6 years old, but the average age of a player wearing a one-star helmet is 34. And for anyone who knows football, that's ancient," the brain doc says. "Then for our two-star helmet, it's 32; and for a three-star helmet it's 29." Players were sticking with the helmets they were familiar with in college, despite the fact that equipment had improved considerably in recent years.
"You're only as protected as well as the worst helmet that's out there," Colello explains. Offering an auto analogy, he says, "It's like, if you run into the back of a Pinto, even if you are in a five-star Mercedes, that gas tank may still explode and you are still going to die."
It's one thing for a player to take a risk at scrambling his own brain; it's another matter to put a teammate or opponent at needless risk. Colello published his analysis early last year and the NFL moved quickly to ban the worst performing helmets, starting next season.
Some of the 14 players using the soon-to-be-banned helmets, like Drew Brees and Philip Rivers, made the switch to a five-star helmet at the start of training camp and stayed with it. Adrian Peterson wore a one-star helmet throughout the season.
Tom Brady tried but just couldn't get comfortable with a new bonnet and, after losing a few games, switched back to his old one in the middle of the season; he says he's going to ask the league to "grandfather in" his old helmet so he can continue to use it.
As for Colello, he's only just getting started. The brain doc has a much bigger vision for the future of football safety. He wants to prevent concussions from even occurring in the first place by creating an innovative new helmet that's unlike anything the league has ever seen.
Oxford-trained neuroscientist Ray Colello is on a mission to make football safer.
(Photo credit: VCU public affairs)
"A Force Field" of Protection
His inspiration was serendipitous; he was at home watching a football game on TV when Denver Bronco's receiver Wes Welker was hit, lay flat on the field with a concussion, and was carted off. As a commercial flickered on the screen, he ambled into the kitchen for another beer. "What those guys need is a force field protecting them," he thought to himself.
Like so many households, the refrigerator door was festooned with magnets holding his kids' school work in place. And in that eureka moment the idea popped into his head: "Maybe the repulsive force of magnets can put a break on an impact before it even occurs." Colello has spent the last few years trying to turn his concept into reality.
Newton's laws of physics – mass and speed – play out graphically in a concussion. The sudden stop of a helmet-to-helmet collision can shake the brain back and forth inside the skull like beans in a maraca. Dried beans stand up to the impact, making their distinctive musical sound; living brain tissue is much softer and not nearly so percussive. The resulting damage is a concussion.
The risk of that occurring is greater than you might think. Researchers using accelerometers inside helmets have determined that a typical college football player experiences about 600 helmet-to-helmet contacts during a season of practice and games. Each hit generates a split second peak g-force of 20 to 150 within the helmet and the odds of one causing a concussion increase sharply over 100 gs of force.
By comparison, astronauts typically experience a maximum sustained 3gs during lift off and most humans will black out around 9gs, which is why fighter pilots wear special pressure suits to counter the effects.
"It stretches the time line of impact quite dramatically. In fact in most instances, it doesn't even hit."
The NFL's fastest player, Chris Johnson, can run 19.3 mph. A collision at that speed "produces 120gs worth of force," Colello explains. "But if you can extend that time of impact by just 5 milliseconds (from 12 to 17msec) you'll shift that g-force down to 84. There is a very good chance that he won't suffer a concussion."
The neuroscientist dived into learning all he could about the physics magnets. It turns out that the most powerful commercially available magnet is an alloy made of neodymium, iron, and boron. The elements can be mixed and glued together in any shape and then an electric current is run through to make it magnetic; the direction of the current establishes the north-south poles.
A 1-pound neodymium magnet can repulse 600 times its own weight, even though the magnetic field extends less than an inch. That means it can push back a magnet inside another helmet but not affect the brain.
Crash Testing the Magnets
Colello couldn't wait to see if his idea panned out. With blessing from his wife to use their credit card, he purchased some neodymium magnets and jury-rigged experiments at home.
The reinforced plastics used in football helmets don't affect the magnetic field. And the small magnets stopped weights on gym equipment that were dropped from various heights. "It stretches the time line of impact quite dramatically. In fact in most instances, it doesn't even hit," says Colello. "We are dramatically shifting the curve" of impact.
Virginia Commonwealth University stepped in with a $50,000 innovation grant to support the next research steps. The professor ordered magnets custom-designed to fit the curvature of space inside the front and sides of existing football helmets. That makes it impossible to install them the wrong way, and ensures the magnets' poles will always repel and not attract. It adds about a pound and a half to the weight of the helmet.
a) The brain in a helmet. b) Placing the magnet. c) Measuring the impact of a helmet-to-helmet collision. d) How magnets reduce the force of impact.
(Courtesy Ray Colello)
Colello rented crash test dummy heads crammed with accelerometers and found that the magnets performed equally well at slowing collisions when fixed to a pendulum in a test that approximated a helmet and head hitting a similarly equipped helmet. It impressively reduced the force of contact.
The NFL was looking for outside-the-box thinking to prevent concussions. It was intrigued by Colello's approach and two years ago invited him to submit materials for review. To be fair to all entrants, the league proposed to subject all entries to the same standard crush test to see how well each performed in lessening impact. The only trouble was, Colello's approach was designed to avoid collisions, not lessen their impact. The test wouldn't have been a valid evaluation and he withdrew from consideration.
But Colello's work caught the attention of Stefan Duma, an engineering professor at Virginia Tech who developed the five-star rating system for football helmets.
"In theory it makes sense to use [the magnets] to slow down or reduce acceleration, that's logical," says Duma. He believes current helmet technology is nearing "the end of the physics barrier; you can only absorb so much energy in so much space," so the field is ripe for new approaches to improve helmet technology.
However, one of Duma's concerns is whether magnets "are feasible from a weight standpoint." Most helmets today weigh between two and four pounds, and a sufficiently powerful magnet might add too much weight. One possibility is using an electromagnet, which potentially could be lighter and more powerful, particularly if the power supply could be carried lower in the body, say in the shoulder pads.
Colello says his lab tests are promising enough that the concept needs to be tried out on the playing field. "We need to make enough helmets for two teams to play each other in a regulation-style game and measure the impact forces that are generated on each, and see if there is a significant reduction." He is waiting to hear from the National Institutes of Health on a grant proposal to take that next step toward dramatically reducing the risk of concussions in the NFL.
Just five milliseconds could do it.
Genetically Sequencing Healthy Babies Yielded Surprising Results
Today in Melrose, Massachusetts, Cora Stetson is the picture of good health, a bubbly precocious 2-year-old. But Cora has two separate mutations in the gene that produces a critical enzyme called biotinidase and her body produces only 40 percent of the normal levels of that enzyme.
In the last few years, the dream of predicting and preventing diseases through genomics, starting in childhood, is finally within reach.
That's enough to pass conventional newborn (heelstick) screening, but may not be enough for normal brain development, putting baby Cora at risk for seizures and cognitive impairment. But thanks to an experimental study in which Cora's DNA was sequenced after birth, this condition was discovered and she is being treated with a safe and inexpensive vitamin supplement.
Stories like these are beginning to emerge from the BabySeq Project, the first clinical trial in the world to systematically sequence healthy newborn infants. This trial was led by my research group with funding from the National Institutes of Health. While still controversial, it is pointing the way to a future in which adults, or even newborns, can receive comprehensive genetic analysis in order to determine their risk of future disease and enable opportunities to prevent them.
Some believe that medicine is still not ready for genomic population screening, but others feel it is long overdue. After all, the sequencing of the Human Genome Project was completed in 2003, and with this milestone, it became feasible to sequence and interpret the genome of any human being. The costs have come down dramatically since then; an entire human genome can now be sequenced for about $800, although the costs of bioinformatic and medical interpretation can add another $200 to $2000 more, depending upon the number of genes interrogated and the sophistication of the interpretive effort.
Two-year-old Cora Stetson, whose DNA sequencing after birth identified a potentially dangerous genetic mutation in time for her to receive preventive treatment.
(Photo courtesy of Robert Green)
The ability to sequence the human genome yielded extraordinary benefits in scientific discovery, disease diagnosis, and targeted cancer treatment. But the ability of genomes to detect health risks in advance, to actually predict the medical future of an individual, has been mired in controversy and slow to manifest. In particular, the oft-cited vision that healthy infants could be genetically tested at birth in order to predict and prevent the diseases they would encounter, has proven to be far tougher to implement than anyone anticipated.
But in the last few years, the dream of predicting and preventing diseases through genomics, starting in childhood, is finally within reach. Why did it take so long? And what remains to be done?
Great Expectations
Part of the problem was the unrealistic expectations that had been building for years in advance of the genomic science itself. For example, the 1997 film Gattaca portrayed a near future in which the lifetime risk of disease was readily predicted the moment an infant is born. In the fanfare that accompanied the completion of the Human Genome Project, the notion of predicting and preventing future disease in an individual became a powerful meme that was used to inspire investment and public support for genomic research long before the tools were in place to make it happen.
Another part of the problem was the success of state-mandated newborn screening programs that began in the 1960's with biochemical tests of the "heel-stick" for babies with metabolic disorders. These programs have worked beautifully, costing only a few dollars per baby and saving thousands of infants from death and severe cognitive impairment. It seemed only logical that a new technology like genome sequencing would add power and promise to such programs. But instead of embracing the notion of newborn sequencing, newborn screening laboratories have thus far rejected the entire idea as too expensive, too ambiguous, and too threatening to the comfortable constituency that they had built within the public health framework.
"What can you find when you look as deeply as possible into the medical genomes of healthy individuals?"
Creating the Evidence Base for Preventive Genomics
Despite a number of obstacles, there are researchers who are exploring how to achieve the original vision of genomic testing as a tool for disease prediction and prevention. For example, in our NIH-funded MedSeq Project, we were the first to ask the question: "What can you find when you look as deeply as possible into the medical genomes of healthy individuals?"
Most people do not understand that genetic information comes in four separate categories: 1) dominant mutations putting the individual at risk for rare conditions like familial forms of heart disease or cancer, (2) recessive mutations putting the individual's children at risk for rare conditions like cystic fibrosis or PKU, (3) variants across the genome that can be tallied to construct polygenic risk scores for common conditions like heart disease or type 2 diabetes, and (4) variants that can influence drug metabolism or predict drug side effects such as the muscle pain that occasionally occurs with statin use.
The technological and analytical challenges of our study were formidable, because we decided to systematically interrogate over 5000 disease-associated genes and report results in all four categories of genetic information directly to the primary care physicians for each of our volunteers. We enrolled 200 adults and found that everyone who was sequenced had medically relevant polygenic and pharmacogenomic results, over 90 percent carried recessive mutations that could have been important to reproduction, and an extraordinary 14.5 percent carried dominant mutations for rare genetic conditions.
A few years later we launched the BabySeq Project. In this study, we restricted the number of genes to include only those with child/adolescent onset that could benefit medically from early warning, and even so, we found 9.4 percent carried dominant mutations for rare conditions.
At first, our interpretation around the high proportion of apparently healthy individuals with dominant mutations for rare genetic conditions was simple – that these conditions had lower "penetrance" than anticipated; in other words, only a small proportion of those who carried the dominant mutation would get the disease. If this interpretation were to hold, then genetic risk information might be far less useful than we had hoped.
Suddenly the information available in the genome of even an apparently healthy individual is looking more robust, and the prospect of preventive genomics is looking feasible.
But then we circled back with each adult or infant in order to examine and test them for any possible features of the rare disease in question. When we did this, we were surprised to see that in over a quarter of those carrying such mutations, there were already subtle signs of the disease in question that had not even been suspected! Now our interpretation was different. We now believe that genetic risk may be responsible for subclinical disease in a much higher proportion of people than has ever been suspected!
Meanwhile, colleagues of ours have been demonstrating that detailed analysis of polygenic risk scores can identify individuals at high risk for common conditions like heart disease. So adding up the medically relevant results in any given genome, we start to see that you can learn your risks for a rare monogenic condition, a common polygenic condition, a bad effect from a drug you might take in the future, or for having a child with a devastating recessive condition. Suddenly the information available in the genome of even an apparently healthy individual is looking more robust, and the prospect of preventive genomics is looking feasible.
Preventive Genomics Arrives in Clinical Medicine
There is still considerable evidence to gather before we can recommend genomic screening for the entire population. For example, it is important to make sure that families who learn about such risks do not suffer harms or waste resources from excessive medical attention. And many doctors don't yet have guidance on how to use such information with their patients. But our research is convincing many people that preventive genomics is coming and that it will save lives.
In fact, we recently launched a Preventive Genomics Clinic at Brigham and Women's Hospital where information-seeking adults can obtain predictive genomic testing with the highest quality interpretation and medical context, and be coached over time in light of their disease risks toward a healthier outcome. Insurance doesn't yet cover such testing, so patients must pay out of pocket for now, but they can choose from a menu of genetic screening tests, all of which are more comprehensive than consumer-facing products. Genetic counseling is available but optional. So far, this service is for adults only, but sequencing for children will surely follow soon.
As the costs of sequencing and other Omics technologies continue to decline, we will see both responsible and irresponsible marketing of genetic testing, and we will need to guard against unscientific claims. But at the same time, we must be far more imaginative and fast moving in mainstream medicine than we have been to date in order to claim the emerging benefits of preventive genomics where it is now clear that suffering can be averted, and lives can be saved. The future has arrived if we are bold enough to grasp it.
Funding and Disclosures:
Dr. Green's research is supported by the National Institutes of Health, the Department of Defense and through donations to The Franca Sozzani Fund for Preventive Genomics. Dr. Green receives compensation for advising the following companies: AIA, Applied Therapeutics, Helix, Ohana, OptraHealth, Prudential, Verily and Veritas; and is co-founder and advisor to Genome Medical, Inc, a technology and services company providing genetics expertise to patients, providers, employers and care systems.