Since I moved to the University of Colorado Boulder in the Summer of 2016, I have added social science genetics to my research portfolio. Recently I was made a Faculty Fellow at the Institute for Behavioral Genetics at the University of Colorado Boulder. In the last three years, I have been impressed with the quality of the research being done in this area. Social science genetics suffered its replication crisis early compared to other areas of social science—the era of the “candidate gene study” in which testing out many genes led to de facto p-hacking. Since then, sample sizes for human genetics data have become large enough that one can get significant results even after careful correction for multiple hypothesis testing across a huge number of genetic variants.

The basic finding for most traits of interest to social scientists is that a large number of genes each has a tiny effect. So there typically isn’t a gene for anything but a few diseases. In the absence of a single determinative gene, there are two key things that can be done: (a) look at what kinds of genes are related to a particular trait, how they compare to the genes for other traits, and how great an R-squared genes could in principle get to and (b) construct linear combinations of genes (called “polygenic scores”) that can predict the trait—always with a lower R-squared than is possible in principle because the weights in the linear combination have estimation error.

The August 30, 2019 issue of Science includes an article “Large-scale GWAS reveals insights into the genetic architecture of same-sex sexual behavior” looking at the genetics of homosexuality in this careful way. The authors were able to use data on almost half a million individuals. Here is their “Structured Abstract”:

INTRODUCTION

Across human societies and in both sexes, some 2 to 10% of individuals report engaging in sex with same-sex partners, either exclusively or in addition to sex with opposite-sex partners. Twin and family studies have shown that same-sex sexual behavior is partly genetically influenced, but previous searches for the specific genes involved have been underpowered to detect effect sizes realistic for complex traits.

RATIONALE

For the first time, new large-scale datasets afford sufficient statistical power to identify genetic variants associated with same-sex sexual behavior (ever versus never had a same-sex partner), estimate the proportion of variation in the trait accounted for by all variants in aggregate, estimate the genetic correlation of same-sex sexual behavior with other traits, and probe the biology and complexity of the trait. To these ends, we performed genome-wide association discovery analyses on 477,522 individuals from the United Kingdom and United States, replication analyses in 15,142 individuals from the United States and Sweden, and follow-up analyses using different aspects of sexual preference.

All quotations in this post are from “Large-scale GWAS reveals insights into the genetic architecture of same-sex sexual behavior.

Unsurprisingly, there is no “gay gene,” but instead many, many genes that each has a small effect on the likelihood of having had at least one same-sex sex partner:

The SNPs that reached genome-wide significance had very small effects (odds ratios ~1.1) (table S7). For example, in the UK Biobank, males with a GT genotype at the rs34730029 locus had 0.4% higher prevalence of same-sex sexual behavior than those with a TT genotype (4.0 versus 3.6%). Nevertheless, the contribution of all measured common SNPs in aggregate (SNP-based heritability) was estimated to be 8 to 25% (95% CIs [Confidence Intervals], 5 to 30%) of variation in female and male same-sex sexual behavior, in which the range reflects differing estimates by using different analysis methods or prevalence assumptions … same-sex sexual behavior, like most complex human traits, is influenced by the small, additive effects of very many genetic variants, most of which cannot be detected at the current sample size (22). Consistent with this interpretation, we show that the contribution of each chromosome to heritability is broadly proportional to its size (fig. S3) (14). In contrast to linkage studies that found substantial association of sexual orientation with variants on the X-chromosome (8, 23), we found no excess of signal (and no individual genome-wide significant loci) on the X-chromosome (fig. S4).

Homosexuality is still rare enough that a sample of half a million or so is still not enough to get precise estimates of just what fraction of the variation in homosexual behavior could in principle be predicted by genes. For linear combinations of common genes, the key quotation from above is:

… the contribution of all measured common SNPs [single nucleotide polymorphisms] in aggregate (SNP-based heritability) was estimated to be 8 to 25% (95% CIs, 5 to 30%) of variation.

Based on a wider ranges of genetic variation, the key quotation is as follows:

By modeling the correspondence of relatedness among individuals and the similarity of their sexual behavior, we estimated broad-sense heritability—the percentage of variation in a trait attributable to genetic variation—at 32.4% [95% confidence intervals (CIs), 10.6 to 54.3] (table S4). This estimate is consistent with previous estimates from smaller twin studies (7).

In any case, don’t fall into the fallacy that “genetic” means “unmodifiable” and “environmental” means “modifiable.” Many things that are environmental are hard to modify because it is hard to modify the environment, while many things that are genetic are easy to modify. For example, nearsightedness can easily be corrected by eyeglasses and contact lenses. In the case of homosexuality, there have been, in effect many messily conducted experiments in modifying homosexuality that directly show that in many, many cases it is essentially impossible to modify. Genetic evidence does not speak directly to “modifiability.” In other words, you can’t use genetic evidence to say whether something is a “choice” or not.

The notion that genetic effects are hardwired physical effects is not always on track. Genetics for complex traits often operate through an effect on people’s preferences. That doesn’t mean those preferences are a small thing. Except to protect other people, it is cruel to block the expression of people’s preferences. For example, whether to be an economist or not is clearly a choice, but it would both make some of us miserable and get in the way of important contributions to the world if it were made illegal or socially disfavored to be an economist. Inhibitions to freedom, whether legal or social, need strong justification in reducing harm to others.

Also, there can be physical effects that are not genetic that are at least as hardwired as physical effects. Men who have more older brothers are more likely to be gay. (See the Wikipedia article “Fraternal birth order and male sexual orientation.”) People theorize this might be due to maternal immune-system reactions to previous male fetuses.

Surprises in the Genetic Data

There are several important findings in the genetic data that will surprise some and confirm the prior beliefs of others. First, having had at least one same-sex sexual partner seems to be a different thing for men than for women:

To assess differences in effects between females and males, we also performed sex-specific analyses. These results suggested only a partially shared genetic architecture across the sexes; the across-sex genetic correlation was 0.63 (95% CIs, 0.48 to 0.78) (table S9). This is noteworthy given that most other studied traits show much higher across-sex genetic correlations, often close to 1 (18–21).

A 63% correlation between the genetic predictor for men having had a same-sex sexual partner and for women having had a same-sex sexual partner is still a substantial correlation, but that means there are important differences.

Second, having had at least one as opposed to no same-sex sexual partners is not the same thing as having predominantly same-sex partners:

To maximize our sample size and increase the power to detect SNP associations, we defined our primary phenotype as ever or never having had a same sex partner. … the genetic effects that differentiate heterosexual from same-sex sexual behavior are not the same as those that differ among nonheterosexuals with lower versus higher proportions of same-sex partners. This finding suggests that on the genetic level, there is no single dimension from opposite-sex to same-sex preference. The existence of such a dimension, in which the more someone is attracted to the same-sex the less they are attracted to the opposite-sex, is the premise of the Kinsey scale (39), a research tool ubiquitously used to measure sexual orientation. Another measure, the Klein Grid (40), retains the same premise but separately measures sexual attraction, behavior, fantasies, and identification (as well as nonsexual preferences); however, we found that these sexual measures are influenced by similar genetic factors. Overall, our findings suggest that the most popular measures are based on a misconception of the underlying structure of sexual orientation and may need to be rethought. In particular, using separate measures of attraction to the opposite sex and attraction to the same sex, such as in the Sell Assessment of Sexual Orientation (41), would remove the assumption that these variables are perfectly inversely related and would enable more nuanced exploration of the full diversity of sexual orientation, including bisexuality and asexuality.’’

In other words, the authors suggest a model with two parameters: attraction to men and attraction to women, with some people attracted to both, some people only attracted to men or only to women, and some people attracted to neither.

Scientifically, one of the interesting questions is how genes that increase the probability of homosexual behavior have survived in the gene pool. The authors mention this issue and its importance, but do not suggest any resolution:

We observed in the UK Biobank that individuals who reported same-sex sexual behavior had on average fewer offspring than those of individuals who engaged exclusively in heterosexual behavior, even for individuals reporting only a minority of same-sex partners (Fig. 1B). This reduction in number of children is comparable with or greater than for other traits that have been linked to lower fertility rates (fig. S1) (14). This reproductive deficit raises questions about the evolutionary maintenance of the trait, but we do not address these here.

Conclusion

Before solid evidence about the genetics of homosexuality was available, many people talked as if the genetics of homosexuality could usefully inform how gays should be treated. But it doesn’t. What the genetics of homosexuality does do is help us to appreciate the complexity of sexual attraction.