@ScienceVet2 explains intersex variations on twitter.
ScienceVet is a Ph.D in Biochemistry and has published in the fields of endocrinology and sexual differentiation. His Ph.D. is in Biomedical Sciences - Biochemistry and Molecular Pharmocology.
Transcript of this thread for easier reading:
So. Hi new people! Apparently, weâre gonna talk about sex. Like physical sex! Because⊠thereâs some confusion.
First, sex defined: Weâre talking physical sex here, not gender. Body parts, hormones, and genetics (and more).
BLUF: BIOLOGICAL sex is a spectrum.
Ok, everyoneâs super familiar with the XX/XY dichotomy, right? Yeah, what we all learned in like⊠4th grade? And thatâs great, it gives you a starting point. But itâs⊠well itâs only the very starting point.Â
The IDEA is, XX is girl, XY is boy, right? Welllll⊠thatâs not totally right. There are XY people, who have ovaries! And give birth! AH! And XX people who have male bodies and functional sperm! Double AH!
These are usually written off as âabnormalitiesâ and indeed, some cases have medical issues. But many donât (like the XY woman giving birth). And this is really only the very very tip of the iceberg of âwait, that doesnât fit into our M or F box unless we make it bigger.â Thereâs a WHOLE HOST of things that can cause all sorts of âweirdâ things to happen, ranging from genetic (XXY, XYY, Y, X, XX with translocation, XY with deletion) to hormonal (Androgen Insensitivity, Estradiol failure), and disruptors like dioxins.
So, youâre a scientist, and you want to research stuff, right? Which means you have to categorize stuff. Without categories, data is hard! So you take allll these people, including the âweirdâ ones and you plot them on a graph. Logical!
You use all the differences there are, different genetics, different responses to hormones, different effectiveness in signalling pathways, different sizes in anteroventral periventricular nucleus (AVPV) (yeah thatâs a thing) and give everything numbers, add them up.
You get whatâs called a bimodal distribution (mostly, weâll get to that later) which looks like this. Those two big peaks are what we call âmaleâ and âfemaleâ (even conveniently colored pink for boys and blue for girls - we are using victorian gender colors right?)Â
[Image Description: A graph showing a smooth line that goes up from approximately zero, forms two âhumps,â and then returns to zero. The area under the curve is colored in with a left-to-right gradient that goes from light blue to light pink.]
Now, when youâre trying to look at data, we often group stuff. When we do that with a plot like this, itâs called a âhistogram.â Basically weâre breaking down a curved line into discrete âbins.â Like this (image stolen from the web).
[Image Description: A bar graph showing the distribution of test scores. Each bar represents the number of students who got a score between 0 and 10 percent, 11 and 20 percent, etc. The data is approximately bimodal, like the graph of sex characteristics, and is divided between students who didnât study and students who did study.]
Traditionally, weâve used REALLY BIG bins for this when talking about sex. Basically you either group everything vaguely near a peak into the peak, or you just pretend thereâs nothing else but the biggest peaks. This makes it super easy, because 2 is simple to do data with.
However, as weâve gotten to know more and more about signaling and brains and hormones and started to pay more attention to the outliers where standard stuff just didnât seem to work, we discovered that this isnât a great model to use.
Now Iâm not talking feelings here. Iâm talking about data. As you start to look at anything interesting, like say the effects of 2,3,7,8-Tetrachlorodibenzo-P-dioxin on animals, you start to realize that a 2 bin model doesnât predict your results well.
At first you say, âWell it was just weird.â So you redo it, and it still doesnât work. So you look at your model and you say, âWell ok, what if the modelâs wrong?â
But the model sort of⊠almost predicts a lot of things, and it worked for years, soâŠ
Some enterprising soul says, âHey, remember that histogram where we said weâll just model using the peaks?â And everyone goes, âUh, yeah?â And they say, âWhat if we⊠USED that data?â And everyone groans, because complicated data is hard.
But someone sits down and does the work, and lo, wow the model starts to work again. Where TCDD was ârandomlyâ turning some boys into girls but then some girls into boys, now you can see thereâs a subgroup of what youâd called âfemaleâ that responds like the âmale.â
Whatâs important here is that you havenât MISLABELED males as females. These are functional âfemalesâ who can do all the usual âfemaleâ things like gestate babies. But they respond to this one endocrine disruptor in a âmaleâ way.
So you add another two categories, call them âMale2â and âFemale2â and go on, happy that your model works! Youâve got 4 sexes now, but you donât really have to tell anyone that, right?
Exceeeept then you remember youâve got those XY people that gestate babies. So you add âIntersex1â And then the XX people with penes⊠and ovaries? Ok, âIntersex2â because all these groups respond differently with signalling and brains when you get into the weeds.
And the more you look, the more we LEARN, the more weâre able to separate out those fine differences. Depending on what weâre doing, we may not care. If a doc is giving you aspirin, it probably isnât a big deal. But if theyâre using a steroid on you? Or treating dioxin poisoning? THAT SHIT COULD BE IMPORTANT. Itâs like saying, âthe lightâs off so the power must not be flowing.â It really matters if the lightâs off because the bulb blew.
If we go back to that histogram plot, we can keep breaking down your biological sex into smaller and smaller differences in brain areas, hormone levels, signalling differences, genetic variances. Thereâs nothing stopping us from binning EVERY INDIVIDUAL into their own bin.
Technically, this wouldnât be âinfinite sexesâ but 7.4 billion sexes is functionally close for our brains. Now, our medicine isnât advanced enough for THAT level of detail to make any difference. BUT IT MIGHT BE in the future. Individualized medicine!
The thing to remember is that this isnât ânew.â Weâre not âinventing sexesâ here. Sex has ALWAYS been this curve. We were just using REALLY BIG bins. And now weâre realizing that thatâs not representative of biology, itâs inhibiting understanding of medicine and biology
In case anyoneâs curious, this isnât ideology. This is because I had to figure out why my data didnât match the prediction. Those rats I mentioned? Yeah, my lab. And lab rats are a really pure genetic monoculture, and they STILL donât fit the two peak model well.
So, since itâs come up, an addendum!
Yes, we looked at other things we could do to make our data fit the existing model, thatâs how science works! The ONLY way the data fit was if we let âsexâ be more than just those two narrow peaks.
Modelsâ purpose in science is to predict. If they donât predict correctly, first we check if weâve measured the data correctly, and repeat the experiment a couple more times. If it still doesnât fit, we have to look at the model.
Intersex! Because I didnât specifically mention this above.
âIntersexâ is a term used to collectively speak of the âmiddle groundâ of biology where people canât easily be binned into those two big âmaleâ and âfemaleâ peaks. It can include a large range of biology.
It is worth noting that I never talk about transgender in this thread. Intersex is not the same as transgender. You can be one without the other, or be both.
For people who think this is just âoutliersâ:
Current estimates are that the intersex population is at least 2%. We know thatâs low because there are a lot of âinvisibly intersexâ people. That means AT LEAST 150 million people in the world.
I apologize for the failure to use the word âintersexâ higher up in the discussion. Many people in the middle ground (including the XY person who can carry a child, for example) use this term. I cannot go back and edit the thread, and apologize for my overly clinical description.
Part of the purpose of the thread, which may have failed, was to point out that âintersexâ is not a condition, it is not a disease. Itâs natural with a bimodal distribution. Science not only supports this, it suggests that ignoring intersex people makes your conclusions wrong.
If youâd like additional reading on this topic, the authorâs original thread contains links to resources if you scroll to the bottom. [link]
The Science Vet Explains Biological Sex and Gender
Thanks for the transcription, sapphicscience!
See also:Â What scientists really say about biological sex and gender and Y does not necessarily equal M: On what intersex people can tell us about gender identity
*shoves it in my biology teachersâ faces*
