The Shiny–and Potentially Dangerous—New Tool for Predicting Human Behavior
[Editor's Note: This essay is in response to our current Big Question, which we posed to experts with different perspectives: "How should DNA tests for intelligence be used, if at all, by parents and educators?"]
Imagine a world in which pregnant women could go to the doctor and obtain a simple inexpensive genetic test of their unborn child that would allow them to predict how tall he or she would eventually be. The test might also tell them the child's risk for high blood pressure or heart disease.
Can we use DNA not to understand, but to predict who is going to be intelligent or extraverted or mentally ill?
Even more remarkable -- and more dangerous -- the test might predict how intelligent the child would be, or how far he or she could be expected to go in school. Or heading further out, it might predict whether he or she will be an alcoholic or a teetotaler, or straight or gay, or… you get the idea. Is this really possible? If it is, would it be a good idea? Answering these questions requires some background in a scientific field called behavior genetics.
Differences in human behavior -- intelligence, personality, mental illness, pretty much everything -- are related to genetic differences among people. Scientists have known this for 150 years, ever since Darwin's half-cousin Francis Galton first applied Shakespeare's phrase, "Nature and Nurture" to the scientific investigation of human differences. We knew about the heritability of behavior before Mendel's laws of genetics had been re-discovered at the end of the last century, and long before the structure of DNA was discovered in the 1950s. How could discoveries about genetics be made before a science of genetics even existed?
The answer is that scientists developed clever research designs that allowed them to make inferences about genetics in the absence of biological knowledge about DNA. The best-known is the twin study: identical twins are essentially clones, sharing 100 percent of their DNA, while fraternal twins are essentially siblings, sharing half. To the extent that identical twins are more similar for some trait than fraternal twins, one can infer that heredity is playing a role. Adoption studies are even more straightforward. Is the personality of an adopted child more like the biological parents she has never seen, or the adoptive parents who raised her?
Twin and adoption studies played an important role in establishing beyond any reasonable doubt that genetic differences play a role in the development of differences in behavior, but they told us very little about how the genetics of behavior actually worked. When the human genome was finally sequenced in the early 2000s, and it became easier and cheaper to obtain actual DNA from large samples of people, scientists anticipated that we would soon find the genes for intelligence, mental illness, and all the other behaviors that were known to be "heritable" in a general way.
But to everyone's amazement, the genes weren't there. It turned out that there are thousands of genes related to any given behavior, so many that they can't be counted, and each one of them has such a tiny effect that it can't be tied to meaningful biological processes. The whole scientific enterprise of understanding the genetics of behavior seemed ready to collapse, until it was rescued -- sort of -- by a new method called polygenic scores, PGS for short. Polygenic scores abandon the old task of finding the genes for complex human behavior, replacing it with black-box prediction: can we use DNA not to understand, but to predict who is going to be intelligent or extraverted or mentally ill?
Prediction from observing parents works better, and is far easier and cheaper, than anything we can do with DNA.
PGS are the shiny new toy of human genetics. From a technological standpoint they are truly amazing, and they are useful for some scientific applications that don't involve making decisions about individual people. We can obtain DNA from thousands of people, estimate the tiny relationships between individual bits of DNA and any outcome we want — height or weight or cardiac disease or IQ — and then add all those tiny effects together into a single bell-shaped score that can predict the outcome of interest. In theory, we could do this from the moment of conception.
Polygenic scores for height already work pretty well. Physicians are debating whether the PGS for heart disease are robust enough to be used in the clinic. For some behavioral traits-- the most data exist for educational attainment -- they work well enough to be scientifically interesting, if not practically useful. For traits like personality or sexual orientation, the prediction is statistically significant but nowhere close to practically meaningful. No one knows how much better any of these predictions are likely to get.
Without a doubt, PGS are an amazing feat of genomic technology, but the task they accomplish is something scientists have been able to do for a long time, and in fact it is something that our grandparents could have done pretty well. PGS are basically a new way to predict a trait in an individual by using the same trait in the individual's parents — a way of observing that the acorn doesn't fall far from the tree.
The children of tall people tend to be tall. Children of excellent athletes are athletic; children of smart people are smart; children of people with heart disease are at risk, themselves. Not every time, of course, but that is how imperfect prediction works: children of tall parents vary in their height like anyone else, but on average they are taller than the rest of us. Prediction from observing parents works better, and is far easier and cheaper, than anything we can do with DNA.
But wait a minute. Prediction from parents isn't strictly genetic. Smart parents not only pass on their genes to their kids, but they also raise them. Smart families are privileged in thousands of ways — they make more money and can send their kids to better schools. The same is true for PGS.
The ability of a genetic score to predict educational attainment depends not only on examining the relationship between certain genes and how far people go in school, but also on every personal and social characteristic that helps or hinders education: wealth, status, discrimination, you name it. The bottom line is that for any kind of prediction of human behavior, separation of genetic from environmental prediction is very difficult; ultimately it isn't possible.
Still, experts are already discussing how to use PGS to make predictions for children, and even for embryos.
This is a reminder that we really have no idea why either parents or PGS predict as well or as poorly as they do. It is easy to imagine that a PGS for educational attainment works because it is summarizing genes that code for efficient neurological development, bigger brains, and swifter problem solving, but we really don't know that. PGS could work because they are associated with being rich, or being motivated, or having light skin. It's the same for predicting from parents. We just don't know.
Still, experts are already discussing how to use PGS to make predictions for children, and even for embryos.
For example, maybe couples could fertilize multiple embryos in vitro, test their DNA, and select the one with the "best" PGS on some trait. This would be a bad idea for a lot of reasons. Such scores aren't effective enough to be very useful to parents, and to the extent they are effective, it is very difficult to know what other traits might be selected for when parents try to prioritize intelligence or attractiveness. People will no doubt try it anyway, and as a matter of reproductive freedom I can't think of any way to stop them. Fortunately, the practice probably won't have any great impact one way or another.
That brings us to the ethics of PGS, particularly in the schools. Imagine that when a child enrolls in a public school, an IQ test is given to her biological parents. Children with low-IQ parents are statistically more likely to have low IQs themselves, so they could be assigned to less demanding classrooms or vocational programs. Hopefully we agree that this would be unethical, but let's think through why.
First of all, it would be unethical because we don't know why the parents have low IQs, or why their IQs predict their children's. The parents could be from a marginalized ethnic group, recognizable by their skin color and passed on genetically to their children, so discriminating based on a parent's IQ would just be a proxy for discriminating based on skin color. Such a system would be no more than a social scientific gloss on an old-fashioned program for perpetuating economic and cognitive privilege via the educational system.
People deserve to be judged on the basis of their own behavior, not a genetic test.
Assigning children to classrooms based on genetic testing would be no different, although it would have the slight ethical advantage of being less effective. The PGS for educational attainment could reflect brain-efficiency, but it could also depend on skin color, or economic advantage, or personality, or literally anything that is related in any way to economic success. Privileging kids with higher genetic scores would be no different than privileging children with smart parents. If schools really believe that a psychological trait like IQ is important for school placement, the sensible thing is to administer the children an actual IQ test – not a genetic test.
IQ testing has its own issues, of course, but at least it involves making decisions about individuals based on their own observable characteristics, rather than on characteristics of their parents or their genome. If decisions must be made, if resources must be apportioned, people deserve to be judged on the basis of their own behavior, the content of their character. Since it can't be denied that people differ in all sorts of relevant ways, this is what it means for all people to be created equal.
[Editor's Note: Read another perspective in the series here.]
Stronger psychedelics that rewire the brain, with Doug Drysdale
A promising development in science in recent years has been the use technology to optimize something natural. One-upping nature's wisdom isn't easy. In many cases, we haven't - and maybe we can't - figure it out. But today's episode features a fascinating example: using tech to optimize psychedelic mushrooms.
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These mushrooms have been used for religious, spiritual and medicinal purposes for thousands of years, but only in the past several decades have scientists brought psychedelics into the lab to enhance them and maximize their therapeutic value.
Today’s podcast guest, Doug Drysdale, is doing important work to lead this effort. Drysdale is the CEO of a company called Cybin that has figured out how to make psilocybin more potent, so it can be administered in smaller doses without side effects.
The natural form of psilocybin has been studied increasingly in the realm of mental health. Taking doses of these mushrooms appears to help people with anxiety and depression by spurring the development of connections in the brain, an example of neuroplasticity. The process basically shifts the adult brain from being fairly rigid like dried clay into a malleable substance like warm wax - the state of change that's constantly underway in the developing brains of children.
Neuroplasticity in adults seems to unlock some of our default ways of of thinking, the habitual thought patterns that’ve been associated with various mental health problems. Some promising research suggests that psilocybin causes a reset of sorts. It makes way for new, healthier thought patterns.
So what is Drysdale’s secret weapon to bring even more therapeutic value to psilocybin? It’s a process called deuteration. It focuses on the hydrogen atoms in psilocybin. These atoms are very light and don’t stick very well to carbon, which is another atom in psilocybin. As a result, our bodies can easily breaks down the bonds between the hydrogen and carbon atoms. For many people, that means psilocybin gets cleared from the body too quickly, before it can have a therapeutic benefit.
In deuteration, scientists do something simple but ingenious: they replace the hydrogen atoms with a molecule called deuterium. It’s twice as heavy as hydrogen and forms tighter bonds with the carbon. Because these pairs are so rock-steady, they slow down the rate at which psilocybin is metabolized, so it has more sustained effects on our brains.
Cybin isn’t Drysdale’s first go around at this - far from it. He has over 30 years of experience in the healthcare sector. During this time he’s raised around $4 billion of both public and private capital, and has been named Ernst and Young Entrepreneur of the Year. Before Cybin, he was the founding CEO of a pharmaceutical company called Alvogen, leading it from inception to around $500 million in revenues, across 35 countries. Drysdale has also been the head of mergers and acquisitions at Actavis Group, leading 15 corporate acquisitions across three continents.
In this episode, Drysdale walks us through the promising research of his current company, Cybin, and the different therapies he’s developing for anxiety and depression based not just on psilocybin but another psychedelic compound found in plants called DMT. He explains how they seem to have such powerful effects on the brain, as well as the potential for psychedelics to eventually support other use cases, including helping us strive toward higher levels of well-being. He goes on to discuss his views on mindfulness and lifestyle factors - such as optimal nutrition - that could help bring out hte best in psychedelics.
Show links:
Doug Drysdale full bio
Doug Drysdale twitter
Cybin website
Cybin development pipeline
Cybin's promising phase 2 research on depression
Johns Hopkins psychedelics research and psilocybin research
Mets owner Steve Cohen invests in psychedelic therapies
Doug Drysdale, CEO of Cybin
How the body's immune resilience affects our health and lifespan
Story by Big Think
It is a mystery why humans manifest vast differences in lifespan, health, and susceptibility to infectious diseases. However, a team of international scientists has revealed that the capacity to resist or recover from infections and inflammation (a trait they call “immune resilience”) is one of the major contributors to these differences.
Immune resilience involves controlling inflammation and preserving or rapidly restoring immune activity at any age, explained Weijing He, a study co-author. He and his colleagues discovered that people with the highest level of immune resilience were more likely to live longer, resist infection and recurrence of skin cancer, and survive COVID and sepsis.
Measuring immune resilience
The researchers measured immune resilience in two ways. The first is based on the relative quantities of two types of immune cells, CD4+ T cells and CD8+ T cells. CD4+ T cells coordinate the immune system’s response to pathogens and are often used to measure immune health (with higher levels typically suggesting a stronger immune system). However, in 2021, the researchers found that a low level of CD8+ T cells (which are responsible for killing damaged or infected cells) is also an important indicator of immune health. In fact, patients with high levels of CD4+ T cells and low levels of CD8+ T cells during SARS-CoV-2 and HIV infection were the least likely to develop severe COVID and AIDS.
Individuals with optimal levels of immune resilience were more likely to live longer.
In the same 2021 study, the researchers identified a second measure of immune resilience that involves two gene expression signatures correlated with an infected person’s risk of death. One of the signatures was linked to a higher risk of death; it includes genes related to inflammation — an essential process for jumpstarting the immune system but one that can cause considerable damage if left unbridled. The other signature was linked to a greater chance of survival; it includes genes related to keeping inflammation in check. These genes help the immune system mount a balanced immune response during infection and taper down the response after the threat is gone. The researchers found that participants who expressed the optimal combination of genes lived longer.
Immune resilience and longevity
The researchers assessed levels of immune resilience in nearly 50,000 participants of different ages and with various types of challenges to their immune systems, including acute infections, chronic diseases, and cancers. Their evaluation demonstrated that individuals with optimal levels of immune resilience were more likely to live longer, resist HIV and influenza infections, resist recurrence of skin cancer after kidney transplant, survive COVID infection, and survive sepsis.
However, a person’s immune resilience fluctuates all the time. Study participants who had optimal immune resilience before common symptomatic viral infections like a cold or the flu experienced a shift in their gene expression to poor immune resilience within 48 hours of symptom onset. As these people recovered from their infection, many gradually returned to the more favorable gene expression levels they had before. However, nearly 30% who once had optimal immune resilience did not fully regain that survival-associated profile by the end of the cold and flu season, even though they had recovered from their illness.
Intriguingly, some people who are 90+ years old still have optimal immune resilience, suggesting that these individuals’ immune systems have an exceptional capacity to control inflammation and rapidly restore proper immune balance.
This could suggest that the recovery phase varies among people and diseases. For example, young female sex workers who had many clients and did not use condoms — and thus were repeatedly exposed to sexually transmitted pathogens — had very low immune resilience. However, most of the sex workers who began reducing their exposure to sexually transmitted pathogens by using condoms and decreasing their number of sex partners experienced an improvement in immune resilience over the next 10 years.
Immune resilience and aging
The researchers found that the proportion of people with optimal immune resilience tended to be highest among the young and lowest among the elderly. The researchers suggest that, as people age, they are exposed to increasingly more health conditions (acute infections, chronic diseases, cancers, etc.) which challenge their immune systems to undergo a “respond-and-recover” cycle. During the response phase, CD8+ T cells and inflammatory gene expression increase, and during the recovery phase, they go back down.
However, over a lifetime of repeated challenges, the immune system is slower to recover, altering a person’s immune resilience. Intriguingly, some people who are 90+ years old still have optimal immune resilience, suggesting that these individuals’ immune systems have an exceptional capacity to control inflammation and rapidly restore proper immune balance despite the many respond-and-recover cycles that their immune systems have faced.
Public health ramifications could be significant. Immune cell and gene expression profile assessments are relatively simple to conduct, and being able to determine a person’s immune resilience can help identify whether someone is at greater risk for developing diseases, how they will respond to treatment, and whether, as well as to what extent, they will recover.