Are you mostly noise? This week Born and Raised went to talk to @eivindy.bsky.social about the genetics of personality, the "gloomy prospect", and about Eivind's possible weird mutation!

Illustration of two people standing in front of a large pair of open scissors, symbolizing a separation, accompanied by text about the Max Planck Institute’s study on the risk of divorce.

💔People with a similar risk of divorce are more likely to marry: Hans F. Sunde & Philipp Dierker found that spouses tend to be similar in terms of their risk of separation. Marriage is shaped not only by a person's own background, but also by that of their partner. www.demogr.mpg.de/go/divorce_risk

Nature recently published massive studies on the credibility of social science. We — the Norwegian co-authors on the robustness-paper, Gerit Pfuhl, @oysteinhernaes.bsky.social, @maxkorbmacher.bsky.social, and me — wrote an opinion piece about it (in Norwegian): www.forskersonen.no/forskning-kr...

This is cool work on a methodological level, but I also really like how “assortative mating on liability to divorce” is essentially a six-word relationship drama.

Here is the link to the study: doi.org/10.1017/thg....

Finally, we hope similar models or lines of thinking can be applied to other couple-shared outcomes, such as fertility outcomes or joint health behaviors, to separate sex-specific sources of variation and account for their correlation.

To conclude, we found:
- Partners are similar in their liability to divorce
- Accounting for this reduces estimates of individual-level effects
- Partner similarity itself increases variation in couples' divorce liability
- Female factors were more important than male factors

We also found, regardless of specification, that female familial factors were more important than male familial factors (18% versus 10% variance explained, respectively).

The specific decomposition into additive and non-additive genetic components (or shared-environmental components) are sensitive to assumptions about type and history of assortative mating, but the overall contribution of familial factors remained stable.

A substantial portion of variance (16%) in couple's divorce liability could be attributed to the correlation between male and female liabilities. If partners mated randomly, the divorce rate would drop by 8% (all else equal obviously!).

We find that familial factors (e.g., additive heritability) are estimated to be higher in the classic twin model compared to the extended twin model.

We therefore estimate a classic twin model that treats divorce as an individual-level outcome, along with an extended twin model that accounts for assortative mating and treats divorce as a couple-shared outcome.

One motivation for the study was to show how traditional behavioral genetic methods that have treated divorce as an individual-level outcome may have overestimated the effects of family history because they do not account for the effect of the (correlated) spouse.

We also find that sisters are more highly correlated than brothers (.18 vs .14, respectively), which implies that female familial factors are slightly more important for a couple's divorce risk than the male familial factors.

The high estimated correlation is not surprising. The affine correlations are very high relative to the sibling correlations, implying that partners must be very similar too.

The correlations between affines provide sufficient information to estimate the implied correlation between the two spouses' familial liabilites. We find that partners are highly correlated for liability to divorce (r = .60).

Even individuals who are socially very distant are correlated for divorce. The tetrachoric correlation between one marriage and the husband's brothers' wife's sister's husband's brother's marriage was about .04.

And we find that even distant affines (another word for in-laws) are correlated. And while the correlations between affines are not large (~.06), they are relatively large compared to siblings (~.15).

How can we estimate correlations between partners for an outcome that they share? One solution is to chain-link pairs of spouses and siblings into extended family units. This allows us to quantify similarity between in-laws (and in-laws of in-laws), indirectly quantifying partner similarity.

Can we estimate assortative mating for outcomes shared by partners? Yes we can! In a new paper together with @philippdierker.bsky.social, I find that individuals with similar liabilities to divorce are more likely to get married in the first place!

SCORE | Center for Open Science SCORE shows that there is no shortcut to producing credible research findings, and there is no single indicator of trustworthiness. Research progress depends on transparency, rigor, and establishing r...

SCORE, a collaboration of 865 researchers, is now released as three papers in Nature, six preprints, and a lot of data (cos.io/score/). SCORE examined repeatability of findings from the social-behavioral sciences and tested whether human and automated methods could predict replicability.

Check email :)

Check out this French popular science article on partner similarity and assortative mating, featuring yours truly:

Always energising to engage with cutting-edge work on assortative mating, cross-ancestry prediction, and rare variants at @ESSGN — especially with such a strong cohort of doctoral researchers at Vrije Universiteit Amsterdam.

#Sociogenomics #GeneticPrediction #ESSGN

Me & @aysuo.bsky.social are hiring a postdoc to study gene–environment interplay in health & social inequalities 🧬

You'll analyze genomic data as part of a collaboration with Uppsala & Oslo at @amsterdamumc.bsky.social (NL)

werkenbij.amsterdamumc.org/en/vacatures...

Please RT for karma points ♥️

While this is amazing, I do think people may underestimate the work going into writing good and precise prompts (although major hack: Making codex write the prompt...)

Engaging and clear podcast from @hfsunde.bsky.social on what is assortative mating and why it matters 🎧

Me and @aysuo.bsky.social went to Oslo a couple of weeks ago. This conversation with @hfsunde.bsky.social was really, really exciting!

I was on a podcast! I had great fun talking about my favorite social science genetics topic (partner similarity!) with @aysuo.bsky.social and @rafaelahlskog.bsky.social. If you want to learn more about assortative mating and why it is so interesting, give it a listen 🎧!

If you're looking to build or deepen your knowledge in statistical genetics, the ISG Workshop (June 1–11) covers the full range: biometrics, GWAS, polygenic scores, causal inference, and more. Open to all levels, virtual, and international: www.colorado.edu/ibg/workshop...

Retweets appreciated 🙏