Episode Transcript
[00:00:00] Speaker A: Foreign.
[00:00:14] Speaker B: Welcome to Base by Bass, the papercast that brings genomics to you wherever you are. Thanks for listening and don't forget to follow and rate us in your podcast app.
[00:00:24] Speaker C: Okay, so I want you to picture something. A hospital delivery room. You know, it's loud, it's chaotic, the lights are way too bright. Two babies are born, same second, same city. And let's just say for the sake of argument, it's a total miracle of biology. These two kids have the exact same genetic potential for learning.
[00:00:43] Speaker B: Okay, so their, their brains are wired with the same capacity, the same raw hard code.
[00:00:47] Speaker C: Exactly the same. To be brilliant, to solve problems, anything. Now, fast forward 30 years. Do they have the same life?
[00:00:54] Speaker B: That is. I mean, that is the ultimate question, isn't it?
[00:00:57] Speaker C: Right? Does the kid with the PhD genes actually get the PhD?
[00:01:00] Speaker B: And we, we like to tell ourselves that talent wins out. You know, we have this cultural belief that that DNA is this unstoppable blueprint. If you have the code for high intelligence, it's just going to manifest. It'll find a way out.
[00:01:11] Speaker C: Like a flower growing through concrete. Meritocracy. Yeah, the cream rises to the top. But the deep dive we're doing today, it really throws a bucket of cold water on that whole idea.
[00:01:22] Speaker B: How so?
[00:01:23] Speaker C: The data we're looking at suggests that your DNA doesn't just act on its own. It. It sort of asks permission from your parents bank account first.
We're finding that for some children, their genetic potential is a rocket ship. For others, it's a car with no engine. And the difference isn't biology, it's money.
[00:01:42] Speaker B: That is a staggering thought. That you could have all the biological tools to be the next Einstein, but the environment just neutralizes them.
[00:01:49] Speaker C: Exactly.
[00:01:50] Speaker B: Makes you ask, are we actually measuring ability in our society? Are we just measuring opportunity?
[00:01:56] Speaker C: And to help us answer that, we really need to acknowledge the team who crunched all these numbers. I mean, this isn't just speculation. This is hard data.
[00:02:02] Speaker B: Right. This comes from the center for Longitudinal Studies at University College London.
[00:02:06] Speaker C: Yes. So huge credit to Tim T. Morris, Liam Wright, Jimmy Sharby and David Ban. They're the heavy hitters behind this work.
[00:02:15] Speaker B: And what they've done is just so ambitious. They didn't just look at a survey from last year or something?
[00:02:19] Speaker C: No, no. They used these massive data sets to look at how genetics and socioeconomic context have intertwined over nearly a century of British history.
[00:02:29] Speaker B: So let's unpack the context a bit. Why is this specific intersection, genes versus money, so incredibly difficult to study?
[00:02:36] Speaker C: Well, social Scientists have debated the drivers of what they call educational attainment, or ea, for I mean, forever.
We know that educated people tend to be healthier, wealthier. We also know it runs in families.
[00:02:50] Speaker B: Right? The classic chicken and egg problem. Is it because the parents passed down smart genes, or is it because they had a house full of books and paid for tutors?
[00:02:57] Speaker C: It's nearly impossible to separate them. Parents provide both the nature and the nurture. You get their DNA and you get their dining room table conversation.
[00:03:04] Speaker B: So you can't untangle it.
[00:03:06] Speaker C: Not easily. And historically, we've seen some gaps close. The gender gap in education, for example, has largely reversed. In many places, women now outperform men. But the class gap, the socioeconomic gap, is stubborn.
In many places, it's either stable or it's actually getting wider.
[00:03:24] Speaker B: So how does this study tackle that differently? How do they slice that knot?
[00:03:28] Speaker C: By using DNA as a control variable.
See, surveys can be biased. People misremember things. The way we measure class changes over decades.
[00:03:37] Speaker B: But your DNA, your DNA is a constant.
[00:03:40] Speaker C: Baseline, it's a constant. It doesn't change when you lose your job or move house. It acts as this fixed anchor point to measure everything else against.
[00:03:48] Speaker B: It's the one variable that's constant from conception to death.
[00:03:52] Speaker C: Precisely. And the global relevance here is huge. This isn't just about biology.
It's really a checkup on the promise of social mobility.
[00:04:00] Speaker B: You mean on equality of opportunity?
[00:04:02] Speaker C: Yes. If society is truly fair, then your genetic potential should predict your success equally, whether you're born in a mansion or, you know, a council estate. This study really investigates if we're living up to that.
[00:04:13] Speaker B: Okay, let's get into the time machine aspect. You said this covers nearly a century. How on earth do they have genetic data going back that far?
[00:04:20] Speaker C: This is where the UK is just a phenomenal resource for science.
They used three legendary birth cohorts.
First, the 1946 National Survey of Health and Development.
[00:04:30] Speaker B: So these are kids born right after World War II. We're talking ration books. Rebuilding London. A completely different world.
[00:04:37] Speaker C: A different world. Then they used the 1958 National Child Development Study. Post war boom, the Beatles are about to happen. And finally, the 1970 British Cohort Study, the disco era Modernization.
[00:04:51] Speaker B: And they have genetic data on thousands of these people?
[00:04:54] Speaker C: They do. Which lets them track how the link between genes and success changed as the entire world around them was changing.
[00:05:01] Speaker B: Okay, so let's define the tool they're using here. We're going to hear the term PGI a lot. I know it stands for polygenic index. But can you break that down for us?
[00:05:08] Speaker C: Think of it like a credit score, but for your genome, it's absolutely not one single smart gene. There's no gene for getting a PhD. BGI is a score that aggregates thousands, sometimes millions of tiny genetic variants.
[00:05:22] Speaker B: These are the SMPs, right? Little spelling differences in our DNA code?
[00:05:25] Speaker C: Yes.
And individually, one of these variants does almost nothing. It's like a single drop of rain. But when you add up thousands of them that statistically correlate with, say, staying in school longer, you get a score.
A pgi.
[00:05:40] Speaker B: So a high PGI for education doesn't mean you will get a degree. It just means you have a kind of genetic tailwind pushing you that way.
[00:05:48] Speaker C: A probability, not a destiny. Exactly. But here is the really innovative step the UCL team took. And this is crucial. They didn't just use one pgi, they used two.
[00:05:57] Speaker B: Two.
[00:05:58] Speaker C: Two. They created one PGI for educational attainment. Let's call it the School Success Score. And a totally separate one specifically for cognition.
[00:06:07] Speaker B: Wait, I assume those would be the same thing. Doesn't school success just come from cognitive abilities?
[00:06:11] Speaker C: You would think so, but they're distinct. The cognition PGI is strictly linked to things like intelligence tests, processing speed, memory, raw brain power. And the other one, the education PGI, captures that. Yes, but it also captures everything else associated with staying in school. Motivation, patience, conscientiousness, you know, the ability to tolerate boredom, the ability to organize your time.
It's a mix of brains and behavior.
[00:06:34] Speaker B: Okay, that distinction feels like it's going to be really important later. But first, there is one more technical thing. They did this. Inverse probability weighting.
[00:06:43] Speaker C: Yes, and I know that sounds super dry, but it's actually really clever.
Imagine you're trying to predict an election you call a thousand people, but young people never answer their phones.
[00:06:54] Speaker B: But older people always do.
[00:06:56] Speaker C: Right. So if you just tally the votes from who answered, you'll get the wrong winner.
Because your sample is skewed.
[00:07:02] Speaker B: It's skewed toward the people who are easy to reach.
[00:07:05] Speaker C: Exactly. And the same thing happens in these long term studies. Who drops out over 50 years? People with chaotic lives, people with lower incomes. The survivors in the data set tend to be wealthier and more stable than the real population.
[00:07:17] Speaker B: So if you don't fix that, your study on inequality is biased because you've lost the most unequal people from your data.
[00:07:23] Speaker C: Precisely. So inverse probability weighting is like a megaphone. The researchers find the few people from those disadvantaged backgrounds who did stay in the Study and they mathematically turn up the volume on their data to kind.
[00:07:35] Speaker B: Of ghost the missing population back in.
[00:07:38] Speaker C: That's a great way to put it. It ensures we're not just looking at the lucky ones.
[00:07:42] Speaker B: Okay, let's get to the findings. You mentioned that genetic influence is actually increasing.
[00:07:46] Speaker C: Yes. This is finding number one. The timeline shift. They looked at how well that education pgi, the school success score, predicted how many years people actually stayed in school.
For the 1946 cohort, the genetics explained about 3 1/2% of the variance.
[00:08:04] Speaker B: 3.5% feels pretty small.
[00:08:06] Speaker C: It is. But look at the trend. By the time you get to the 1970 cohort, that number jumped to 5.1%.
[00:08:13] Speaker B: So the link is getting stronger.
[00:08:15] Speaker C: The link between your genes and how long you stay in school is getting stronger over time.
[00:08:20] Speaker B: Why? I would have thought as education became more accessible, you know, free universities and so on, that genetics would matter less.
[00:08:28] Speaker C: It's actually the opposite logic.
Think about it. If the environment is terrible for everyone, if school costs a fortune, it doesn't matter how smart you are. No one goes heritability is zero because the environment crushes everyone equally.
[00:08:44] Speaker B: Ah, I see. But as you remove the barriers, the the money excuse goes away. The only thing left to differentiate people is their natural aptitude.
[00:08:51] Speaker C: Exactly. In a perfectly fair society, genetics would explain 100% of the variance. So seeing this number go up suggests the UK was becoming more of a meritocracy.
[00:09:00] Speaker B: Okay, that makes sense. A fair society means higher genetic influence. But. I have a feeling there's a but. Come in.
[00:09:07] Speaker C: There is. This is finding number two. The tognition. Surprise. Remember how we separated the school success score from the raw brain power score?
[00:09:15] Speaker B: Yes.
[00:09:15] Speaker C: Well, the school success score became more predictive, but the cognition score, it stayed flat. It predicted the same amount of variance in 1946 as it did in 1970.
[00:09:24] Speaker B: Wait a minute. So genes are becoming more important for educational success, but the genes for intelligence aren't? What does that even mean? That implies the extra genetic factor that's becoming so important isn't how smart you are. It's those other traits. The grit, the conformity.
[00:09:39] Speaker C: It suggests that as the education system expanded, it didn't necessarily start rewarding the most brilliant minds. It started rewarding the most compliant and organized minds.
[00:09:48] Speaker B: Right.
[00:09:49] Speaker C: The non cognitive skills are what's driving this new genetic advantage.
[00:09:53] Speaker B: That's kind of unsettling. It makes you wonder if we're building a system that filters for obedience rather than innovation.
[00:09:59] Speaker C: It's a valid concern. We might be selecting for people who are good at school, not necessarily people who are good at thinking.
[00:10:05] Speaker B: But even that feels small compared to finding number three. This is a big one. The interaction between genes and money, the.
[00:10:12] Speaker C: Gene by environment interaction. This is the core of the whole paper and the visual is just striking.
[00:10:17] Speaker B: Describe it for us, what does it look like?
[00:10:19] Speaker C: Imagine a fan opening up for children from wealthy educated backgrounds, the high SES group. The line is steep. It's a rocket ship. If you have high genetic potential and rich parents, your education just skyrockets. The environment amplifies the genetics.
[00:10:34] Speaker B: Okay. And for the kids from the poorest.
[00:10:36] Speaker C: Backgrounds, the line is flat.
[00:10:38] Speaker B: Flat.
[00:10:39] Speaker C: Effectively flat. It means that for children born into the lowest occupational class, having a high genetic potential resulted in barely any more education than having a low genetic potential.
[00:10:50] Speaker B: So if you're poor, having the smart genes doesn't actually help you.
[00:10:54] Speaker C: It's suppressed. The environment acts as a hard ceiling. It doesn't matter how powerful the engine is if the garage door is locked.
[00:11:01] Speaker B: There was that specific comparison in the data that just floored me. The one about the high potential poor kid.
[00:11:07] Speaker C: Yes. The study predicted that the educational outcome for a person with very high genetic potential, top 1%, but born into a disadvantaged background was roughly equal to a person with very low genetic potential, bottom 1%, born into a privileged background.
[00:11:23] Speaker B: That just completely dismantles the idea of a level playing field. It suggests that money can override a lack of aptitude and poverty can completely suppress high aptitude.
[00:11:33] Speaker C: It suggests potential is a luxury good. If you're wealthy, your potential determines your outcome. If you're poor, your environment does.
[00:11:42] Speaker B: So let's talk about the implications. We started this asking if society is a meritocracy, and this data suggests, at least for the lower classes, it absolutely was not.
[00:11:53] Speaker C: It really validates what sociologists call resource capture. Wealthy families use their resources to maximize their kids advantages and buffer their disadvantages.
[00:12:03] Speaker B: It's the safety net versus the long.
The wealthy kid gets a launch pad if they're smart and a safety net if they aren't.
[00:12:09] Speaker C: And the poor kid gets neither. Yeah, and this has huge policy implications. We often hear politicians say the solution is just better schools.
[00:12:17] Speaker B: Right. Fix the schools, fix the outcome.
[00:12:19] Speaker C: But this research suggests that's not enough.
If the home environment is acting as a hard ceiling for talented kids before they even walk into a classroom, we have to look there. We have to look at poverty itself.
[00:12:31] Speaker B: We're talking about the lost Einsteins.
[00:12:33] Speaker C: That's the term. How many brilliant minds are we missing out on simply because the high potential kids were born into low opportunity zip codes.
[00:12:40] Speaker B: And because the environment suppressed their genes, we never even knew they had the potential. We just looked at their dropout rate and said, oh, they're not academic material.
[00:12:48] Speaker C: Exactly. While the C student from the wealthy family gets the tutor, the internship, the second chance, and eventually graduates and takes a high paying job.
[00:12:56] Speaker B: I want to circle back to that cognition versus education thing. If the education PGI is what's changing and that includes personality, does that mean we need to rethink how we teach?
[00:13:08] Speaker C: It might. It raises the possibility that the modern education system is structurally biased toward a specific personality type. You know, if you are smart but restless, or smart but disorganized, traits that might be more common in chaotic high stress environments, the system just filters you out.
[00:13:27] Speaker B: Right. It's a lot easier to be motivated and calm when you aren't worrying about where your next meal is coming from.
[00:13:32] Speaker C: Exactly. The environment isn't just the bank balance. It's the cognitive load. It's the stress that consumes the bandwidth. You need to demonstrate those soft skills.
[00:13:42] Speaker B: No, we have to be responsible here. We can't just generalize these results to the whole world, can we?
[00:13:47] Speaker C: No. And the authors are very clear about this limitation. This study is limited to white individuals of European ancestry.
[00:13:54] Speaker B: And why is that?
[00:13:55] Speaker C: It's a limitation of the current genomic data itself.
Most large scale genetic studies have historically been done on European populations. And these polygenic scores don't transfer well across different ancestries.
[00:14:08] Speaker B: So we have to be very careful not to assume this applies everywhere or to other groups.
[00:14:13] Speaker C: Right. And we always have to remember, heritability describes a population, not a person.
A PGI is a probability, not a diagnosis.
[00:14:23] Speaker B: So, bringing it all home, what's the big take home message from this deep dive?
[00:14:26] Speaker C: I think the summary is genetic influence on education isn't static. It changes. But biological potential requires sociological opportunity to flourish.
[00:14:36] Speaker B: So it's not nature versus nurture, it's nature multiplied by nurture.
[00:14:39] Speaker C: That's the perfect way to put it. Genetic liability and social background are two forms of inherited advantage and they work together. If you have both, you win big. If you have neither, you struggle. But the tragedy is when you have the genes but not the background, in that case, the background wins.
[00:14:54] Speaker B: That is a sobering thought. It makes you realize that talent is a fragile thing. It really needs the right soil to grow.
[00:15:00] Speaker C: It does.
[00:15:01] Speaker B: So I want to leave you with a provocative thought to mull over.
We've been talking about this in terms of fairness, but think about it in terms of pure economics. If genetic potential is being wasted, flatlined in disadvantaged environments, what is the cost to our civilization?
[00:15:17] Speaker C: We are leaving a huge amount of human capital on the table.
[00:15:20] Speaker B: Exactly. If our scholarship systems and our job markets are designed to reward the outcome, the grades, the degree rather than the raw potential, are we just rewarding the rich for being rich? And if we fixed that, what problems could those lost Einsteins solve for us?
[00:15:37] Speaker C: That is the question we should all.
[00:15:38] Speaker B: Be asking this episode was based on an Open Access article under the CCBY 4.0 license. You can find a direct link to the paper and the license in our episode description. If you enjoyed this, follow or subscribe in your podcast app and leave a five star rating. If you'd like to support our work, use the donation link in the description. Now. Stay with us for an original track created especially for this episode and inspired by the article you've just heard about. Thanks for listening and join us next time as we explore more science. Bass by bass.
[00:16:31] Speaker A: Three birthdays on.
Same small signal Paper thin But the rules keep shifting where you begin Some doors learn your name too fast Some make you prove your lies Not a prophecy, not a fate It's a key and a changing game the code stays calm the world decides how loud it lands, how far and right why Inheritance louder returns Same spot, different times.
[00:17:15] Speaker C: Not.
[00:17:16] Speaker A: A verdict, not a change, just context on the frame Quiet inheritance louder return when the hallway favors you the volume.
Cognition steady metronome but schooling isn't skill on a policy shift A borrowed book, a mentor's time, a second look the ladder leans on where you stand and who can hold your hand.
Not a prophecy, not a fate It's a key and a changing gate the coast stays calm, the world decides how loud it lands, how far it rides.
Two kinds of inheritance in one what you're born where what you're born from make the doors wider Watch it prove the same code learns a different mood.
Quiet inheritance louder return Same spark, different turn Not a verdict, not a change Just context I'm afraid Quiet inheritance louder return Give it a brim so the heritage what you born with, what you born from make the doors wider what you prove the same quote learns a different mood Quiet inheritance louder.
Quiet inheritance loud release.
