Science

No, Scientists Haven’t Found “the Gay Gene”

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Sorta transcript:

This just in, “researchers say gene changes show who’s gay!” What a great technically accurate but absolutely incorrect headline, NBC!

It’s accurate because some researchers did say that. It’s incorrect because it implies that they said that with any sort of scientific backing, which they did not. It would be like a headline saying “Neil Degrasse Tyson says that Jupiter is made of orange marmalade”. Yes, he did say that, but he was tripping balls at the time and followed it up with “Naaaaaaah.”

The news came not from a published, peer-reviewed study, but from a conference where the researchers talked about their results. That right there should be the end of the story. Until the data has been vetted, there’s just no point in even talking about it. But the conference organizers sent out a press release about it, which was picked up in various places and then eventually landed in the mainstream news. That’s how science news happens these days, unfortunately.

So what does the data look like? Well, it involved 47 pairs of male twins, 37 of whom had one gay brother and one straight brother. The other ten were all gay. So already, we have a really, really small sample size, but not necessarily too small to do a preliminary study. Unfortunately, the researchers then had to split the twins into two groups: a training set to create an algorithm and a testing set to test that algorithm. That means that they were now looking at a sad group of only 23 sets.

23 data points would be bad for most studies, but for this one it’s particularly egregious considering that they were looking at literally thousands of possible characteristics that might correlate. Thousands! And in the end, the model the researchers landed on only managed to predict whether the person was gay 67% of the time.

If those 23 data points were people hanging out at a party, there’s a 50% chance that two of them would share a birthday, and there are only 365 possibilities there. So what do you think the chances are that 67% of them would share one of thousands of possible epigenetic markers?

If you guessed “pretty god damn good,” congratulations! You could be a science writer for NBC News.

Rebecca Watson

Rebecca is a writer, speaker, YouTube personality, and unrepentant science nerd. In addition to founding and continuing to run Skepchick, she hosts Quiz-o-Tron, a monthly science-themed quiz show and podcast that pits comedians against nerds. There is an asteroid named in her honor. Twitter @rebeccawatson Mastodon mstdn.social/@rebeccawatson Instagram @actuallyrebeccawatson TikTok @actuallyrebeccawatson YouTube @rebeccawatson BlueSky @rebeccawatson.bsky.social

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5 Comments

  1. The interaction between phenotype and genotype, people still seem to think genetics is so simple. Like, if I were to inject myself with spider DNA, I’d shoot silk out of my butt and develop a hankering for insects.

    Note that ‘not 100% genetic’ doesn’t mean the same thing as ‘a choice’. And even if it were a choice, that wouldn’t make being gay bad. There’s a vast field between ‘gay gene’ and, um, Republican.

  2. This pre-publication talk is little better than ‘anecdata’, to borrow a useful term, so here goes with another tidbit of ‘anecdata’ – from a conversation with my psychiatrist who occasionally writes in the transgender literature: I asked him whether, seeing as he knows the case histories of hundreds of his patients seeking treatment for gender dysphoria, whether he knew of trans or gender variance being a recurring trait within families, or being often found in families where there were also a number of close gay/lesbian/bi relatives. To paraphrase his answer, he said that there was enough anecdotally to suggest there might be something inheritable going on with gender variance in families – something that might even stand out statistically if you look at enough cases – and after we talked about possibilities of etiology for a bit, pointed me to one researcher investigating slightly larger cohorts (n in the hundreds rather than the dozens) looking for possible influencing factors (the androgen receptor gene of the X chromosome being one, along with other genes involved in sex steroidogenesis). That’s where we’re at with that – potentially exciting but very, very preliminary.

    Yes, statistics may tell you if something is obeying a pattern, provided you haven’t compromised your data collection somehow, so assuming you’re past that hurdle, are you looking for something genetic? Or epigenetic? Or an environmental factor? Or nurture? Or some combination of these? And even then, the mechanism may not always be causative, but is instead a small factor or a cluster of factors that predisposes someone to exhibit the trait. Basically science is hard work to nail down hypotheses, and glib headlines summarising not-even-published-yet research do more damage then they’re worth.

    1. I guess my concern with the science you describe is always the question of what exactly is being measured? Is “gender variance” discrete enough that it can be pinpointed to a gene or a genetic etiology? To me, that just seems entirely too nebulous a concept to use in a meaningful way in these kinds of research. What do you compare it against? What is “gender non-variance” in this schema, how do you figure that out? This sounds like we’re heading into essentialism territory to me.

      Every person varies in some way from the idealized socioculturally imagined gender norms of their society, and those gender norms are not static. This is the problem with these kinds of studies, they take things like “gender variance” or “homosexuality” for granted as self-evident categories and fail to operationalize them, and if they do operationalize them then you can only compare them with studies that have operationalized them in the same way, otherwise you’re not comparing the same things.

      1. Hi Will,
        I cited it as ‘anecdata’, and as far as I can tell this sort of research utilising a self-selected sample of transgender people is idiographic; it’s far too weak to suggest anything causative, and as far as I can tell it certainly couldn’t be used to generalise the result to any other sample of trans people used for other research studies (which are vanishingly far and few between, anyway!); likewise it couldn’t be used to say anything about non-transgender people. (I can dig up a link to the research team’s page if you’re interested.)
        Looking back at what I wrote, I neglected to say that in my opinion this sort of research would have radically less weight than the science that is dubiously summarised by the science media as supportive of a ‘male brain’ or a ‘female brain’ – which has been attacked much more successfully (for example, by meta-studies which aggregated data sets and found results from individual studies no longer held). My bad for omitting to say that.

        1. Yep, agreed. I wasn’t trying to criticize your comment, more to make a broader comment about how the kind of science you described (in addition to the work that inspired Rebecca’s video) has some major conceptual problems that need to be solved–if indeed they can be solved at all–before they can tell us anything meaningful that’s not totally laden with bias. Sorry if my comment came across as criticism. We are definitely in agreement. ;)

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