To prepare for a book I intend to write on the science of gender identity, I drafted the following three blog posts to collect my thoughts. They are highly technical; I need to recast the content for the layperson. I also assembled some of my own biological data to analyze.
The first blog post, http://badassdatascience.com/2015/06/06/sci-gender-identity-01/, covers the very little we know about the genetics involved. It specifically examines polymorphisms in particular genes and tests their correlation to transsexualism.
The second post, http://badassdatascience.com/2015/06/16/sci-gender-identity-02/, I think is the most compelling. And it has the best pictures! It investigates brain anatomy in transsexuals and how it differs from that of cisgendered individuals.
Finally, the third post, http://badassdatascience.com/2015/08/02/sci-gender-identity-03/ covers some of the most recent psychological information I could get my hands on. There were two problems here: Since I’m not a psychologist I only understood the statistical arguments in the papers, and have very little access to psychological literature. Nonetheless I did my best. The most notable discussion in this post is the description of a study examining the stability of gender identity in very young children.
My Own Data
While no correlation between testosterone level and the male-to-female transgender experience has ever been established, it is interesting that my natural testosterone level is extremely low. (This was measured before I started blocking my testosterone with Spironolactone). Here is where I sit on the curve for natal males my age:
The “normal boundaries” are those that my HMO says are healthy. To produce the curve I extracted the mean and standard deviation from . I asked this source for the raw data so I could produce the actual data distribution, rather than the normal approximation, but they did not respond.
I have a brain MRI recorded before I started taking hormones. This is important because hormones can alter brain anatomy. I’m attempting to use the 3DSlicer program  to measure the sizes of my various brain regions using image recognition. My intent is to compare the measurements to a body of (sort of) age-matched female and male brain MRIs I downloaded from .
Right now I’m struggling with the image recognition for my particular MRI, but I’ll figure it out and report the results on this blog.
An example of what this effort looks like in 3DSlicer is:
- http://www.ncbi.nlm.nih.gov/pubmed/21697255 (supplemental data)