~1% of people never have sex. While some people simply don’t want sex, for others, no partner can mean loneliness, lower wellbeing, or even economic disadvantage.
No sex is also interesting for genetics as it is an evolutionary “dead end”.
Sexless individuals reported:
- More loneliness, nervousness, unhappiness
- Fewer close relationships & social connections
- Less alcohol & drug use
Patterns differed by sex: for men, physical strength, income, and social connection mattered more.
Where you live matters too.
Men in regions with fewer women were more likely to be sexless.
Sexlessness was also more common in regions with higher income inequality.
Thousands of genetic variants with very tiny effects together explain ~15% of variation. The genetic correlation between men and women is .56.
Ancient DNA shows an allele significantly associated with sexlessness declined over 12,000 years, consistent with natural selection.
Genes linked to sexlessness overlap with genes associated with:
- Higher education & IQ
- Less substance use
- Higher autism & anorexia risk
- Lower ADHD, anxiety, depression & PTSD risk
Sexlessness is relevant to wellbeing and evolution. But it’s also a complex behavioral trait: its genetic associations trace back to many other traits and environments.
The associations we find are correlational and likely to be culture-specific, so more research is needed.
Many thanks to my co–first author @laurawesseldijk (🥰), co–last authors Brendan Zietsch & Karin Verweij, and all other co-authors ❤️
For additional context, we’ve written a lay summary and FAQ that explain the study and how the results can and can’t be used or interpreted: medrxiv.org/content/medrxi…
~40% of UK Biobank participants (N~170k) never completed the fluid intelligence test, limiting power of previous GWASs and introducing bias. We addressed this by imputing missing scores using a wide range of correlated measurements, including health, behavior, and SES outcomes.
In every civilization, people end up sorted into levels of socio-economic status (SES). We explore the history, present, and future of scientific research on the complicated relationship between SES and DNA in @NatureHumBehav 💰🧬🎓
This thread summarizes our key findings, but Twitter's format necessitates some simplification and jargon. For a more comprehensive and nuanced understanding of this complex topic, I encourage reading the full paper, which we've written to be accessible to a wider audience.
We begin with a historical overview of SES itself. Most hunter-gatherers were relatively egalitarian. With the Neolithic shift ~12,000 years ago, societies grew larger and more stratified—SES began shaping lives, and over time, potentially genomes.
We tend to reward people with certain genetic propensities with better environments (higher SES 💰). This results in gene-environment correlations that make society more unequal and further complicate studying human genetics.
Genes associated with complex traits are not distributed randomly across geographic regions. Especially genes associated with education show regional differences in line with SES, at least in part due to migration. More on that in this older thread:
Here, we first showed in ~43k adult siblings that polygenic scores for educational attainment capture gene-environment correlations (rGE) on both a family-level and a regional level. We saw evidence for passive rGE (family you're born into) and active rGE (region you migrate to).
And a thread explaining the main findings below 👇🏾
@NatureHumBehav We looked at the geographic clustering of ancestry differences and complex trait variation. As expected, ancestry differences show very strong geographic clustering and very nice geographic patterns, many roughly separating Wales, England, and Scotland. 2/15
@NatureHumBehav Then we looked at geographic clustering of polygenic scores, measures that are predictive for complex traits and based on measured DNA. Below a figure of how we construct polygenic scores for UK Biobank subjects using genetic effects estimated from external studies. 3/15