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Sjoerd van Alten

@sjoerdalten.bsky.social
381 followers 172 following 61 posts

Postdoctoral Fellow Economics at Erasmus University Rotterdam. Interested in labor/health, and its intersection with behavioral genetics Find out about my work: sites.google.com/view/sjoerd-van-al…

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Sjoerd van Alten @sjoerdalten.bsky.social · 06/10/2026
12/12 Joint work with @leandroscarvalho.bsky.social, @silviabarcelos.bsky.social, Stephen Dorn, Titus Galama, Catharina Hartman, Qiongshi Lu, and Dilnoza Muslimova Read the paper: arxiv.org/abs/2610.06088
arxiv.org
Random Genetic Variation Links Personality to Earnings and Wealth
Personality is associated with economic outcomes, but whether these relationships are causal remains unclear. We exploit within-family variation in genetic propensity toward the Big Five generated by ...
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Sjoerd van Alten @sjoerdalten.bsky.social · 06/10/2026
11/12 Genetic effects depend on context and may operate through behavioral and environmental pathways. Results do not imply that economic outcomes are predetermined.
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Sjoerd van Alten @sjoerdalten.bsky.social · 06/10/2026
10/12 One implication for hiring: emotional stability gets considerably less attention than the other Big Five traits in interviews and job ads. Yet it is the trait that emerges most clearly for earnings in our analysis.
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Sjoerd van Alten @sjoerdalten.bsky.social · 06/10/2026
9/12 The emotional stability effect on earnings shrinks but stays positive. The conscientiousness effect on wealth is stable. The emotional stability effect on wealth is sensitive to the depression PGI. We cannot rule out all pleiotropy, but this strengthens the causal evidence.
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Sjoerd van Alten @sjoerdalten.bsky.social · 06/10/2026
8/12 A challenge to reading these effects as operating through personality: the same genes can affect several traits (pleiotropy). To assess robustness, we re-estimate the effects of the Big Five PGIs controlling for PGIs for education, cognitive performance and depression
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Sjoerd van Alten @sjoerdalten.bsky.social · 06/10/2026
7/12 Result 2: greater genetic propensity toward emotional stability and conscientiousness raises household wealth. A 1-SD higher PGI increases net wealth by about €6,300 and €4,300, respectively. Openness, extraversion and agreeableness show no consistent pattern.
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Sjoerd van Alten @sjoerdalten.bsky.social · 06/10/2026
6/12 Result 1: greater genetic propensity toward emotional stability raises earnings. A 1-SD higher PGI increases annual earnings by €1,420, or 3.3% of the sample average. The effects of the other four traits are smaller and not statistically significant
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Sjoerd van Alten @sjoerdalten.bsky.social · 06/10/2026
5/12 Does random variation in these genetic propensities generate individual differences in measured personality? Yes. A 1-SD higher PGI raises the corresponding survey-measured trait by 0.09 to 0.14 SD. In each panel, the tallest bar is the PGI for that trait.
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Sjoerd van Alten @sjoerdalten.bsky.social · 06/10/2026
4/12 Illustrating our design: people with a higher emotional stability PGI tend to have wealthier parents (solid bars), so a naive comparison mixes genetics with family background. Once we condition on parental PGIs (patterned bars), we no longer detect this relationship.
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Sjoerd van Alten @sjoerdalten.bsky.social · 06/10/2026
3/12 We measure genetic propensity toward each Big Five trait with polygenic indexes (PGIs) and link them to 19 years of tax records for ~39,000 Dutch Lifelines participants. In practice, we regress earnings and wealth on all five PGIs jointly, controlling for the parents' PGIs.
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Sjoerd van Alten @sjoerdalten.bsky.social · 06/10/2026
2/12 Our design exploits chance: which genetic variants parents pass on is random. Given the parents' genetics, remaining genetic differences across people are random: unrelated to family background and other factors determined before conception.
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Sjoerd van Alten @sjoerdalten.bsky.social · 06/10/2026
1/12 Personality predicts earnings and wealth. But does it cause them? That is hard to answer: personality is correlated with family background and much else. In our new working paper, we use the randomness of genetic inheritance to get closer to a causal answer.
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ESSGN @essgn.bsky.social · 21/05/2026
@sjoerdalten.bsky.social on Parent's externalizing behavior and children's human capital
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Genetics Network Amsterdam @geneamsterdam.bsky.social · 31/03/2026
💼 Job opening for a postdoctoral researcher specialising in gene-environment interplay at Amsterdam UMC to work with @aysuo.bsky.social and @dr-appie.bsky.social werkenbij.amsterdamumc.org/en/vacatures...
werkenbij.amsterdamumc.org
Vacatures - Postdoctoral researcher specialising in gene–environment interplay - Amsterdam UMC
Ready to unravel the complex interplay between genes and environment shaping health and society? Join our interdisciplinary team analyzing large-scale genomic data across Europe. Are you eager to contribute to groundbreaking research on health and social inequalities?
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Rafael Ahlskog @rafaelahlskog.bsky.social · 25/03/2026
We're hiring! Are you a social scientist with experience working with genetic data? Join us as a postdoc and work on gene-environment interplay - with amazing data - in a collaborative project between Uppsala, Oslo and Amsterdam!
uu.se
Postdoctoral Position, Political Science - Uppsala University
Postdoctoral Position, Political Science , Department of Government, Uppsala University
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Rafael Ahlskog @rafaelahlskog.bsky.social · 06/02/2026
Me and @aysuo.bsky.social talk to @sjoerdalten.bsky.social about economics and genetics. And we get some book recommendations. Neat!
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Sjoerd van Alten @sjoerdalten.bsky.social · 04/11/2025
Check out our new study in Nature Genetics! In this paper we study the genetic factors that are associated with field of study.
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Laurel Raffington @laraffington.bsky.social · 28/10/2025
We have an open postdoc position in Social Science Genomics in Berlin! Includes gene-environment interplay within German population cohorts & experimental online survey studies to probe public perceptions of potential DNA biomarker applications 🔗 www.mpib-berlin.mpg.de/2196134/2025...
mpib-berlin.mpg.de
Postdoctoral Position in Social Science Genomics | Max Planck Research Group Biosocial
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Sjoerd van Alten @sjoerdalten.bsky.social · 15/09/2025
Thrilled to see this joint work out! Big thanks to my amazing coauthors: Silvia Barcellos, Leandro Carvalho, Titus Galama, and Marina Aguiar Palma. (8/8)
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Sjoerd van Alten @sjoerdalten.bsky.social · 15/09/2025
Key takeaway: Even variation rooted in nature—our genes—exerts much of its influence through nurture. (7/8)
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Sjoerd van Alten @sjoerdalten.bsky.social · 15/09/2025
We quantify these three channels and find: - Direct genetic transmission and genetic nurture both play substantial roles - Assortative mating is comparatively minor - For wealth outcomes, genetic nurture > direct transmission (6/8)
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Sjoerd van Alten @sjoerdalten.bsky.social · 15/09/2025
This shows parental genes matter not only through direct inheritance but also via: - Genetic nurture – how parental genes shape the child’s environment - Assortative mating – non-random partnering patterns (5/8)
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Sjoerd van Alten @sjoerdalten.bsky.social · 15/09/2025
Our findings: "next-generation" effects of parental PGI on children's outcomes are surprisingly large, as compared to "same-generation" effects (the effects of the parent's PGI on their own socioeconomic status). (4/8)
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Sjoerd van Alten @sjoerdalten.bsky.social · 15/09/2025
To isolate causality, we exploit the natural randomization of genes at conception, conditioning on grandparents’ PGIs. This lets us separate pure genetic transmission from environmental effects. (3/8)
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Sjoerd van Alten @sjoerdalten.bsky.social · 15/09/2025
Using a unique linkage of genetic data from Lifelines_NL and administrative records from Centraal Bureau voor de Statistiek (CBS), we ask: How do a parent’s genes associated with educational attainment—measured by a polygenic index (PGI)—affect their children’s socioeconomic outcomes? (2/8)
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Sjoerd van Alten @sjoerdalten.bsky.social · 15/09/2025
Proud to share our new @nber working paper on how genetics shape the intergenerational transmission of socioeconomic status in the Netherlands. 🧵(1/8) www.nber.org/papers/w34208
nber.org
A Chip Off the Old Block? Genetics and the Intergenerational Transmission of Socioeconomic Status
Founded in 1920, the NBER is a private, non-profit, non-partisan organization dedicated to conducting economic research and to disseminating research findings among academics, public policy makers, an...
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NBER @nber.org · 11/09/2025
Genetics play a role on the persistence of socioeconomic across generations: one generation's genetics significantly impacts the education, income, and wealth of the next, from Sjoerd van Alten, Silvia H. Barcellos, Leandro Carvalho, Titus J. Galama, and Marina ... www.nber.org/papers/w34208
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Tim Morris @timtmorris.bsky.social · 13/08/2025
Call for abstracts: genetics, economic & social issues. We're hosting a 1-day workshop on using genetic data to examine economic & social issues on 12th December at UCL’s Social Research Institute. More info & submission at link below #genetics #socialscience #economics #cohort bit.ly/41EnPmu
bit.ly
Microsoft Forms
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Sjoerd van Alten @sjoerdalten.bsky.social · 17/06/2025
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Sjoerd van Alten @sjoerdalten.bsky.social · 12/06/2025
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Sjoerd van Alten @sjoerdalten.bsky.social · 05/06/2025
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Ted Schwaba @tedmond.bsky.social · 20/05/2025
Extremely excited to share the first effort of the Revived Genomics of Personality Consortium: A highly-powered, comprehensive GWAS of the Big Five personality traits in 1.14 million participants from 46 cohorts. www.biorxiv.org/content/10.1...
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Sjoerd van Alten @sjoerdalten.bsky.social · 01/06/2025
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Sjoerd van Alten @sjoerdalten.bsky.social · 22/05/2025
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Sjoerd van Alten @sjoerdalten.bsky.social · 20/05/2025
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Sjoerd van Alten @sjoerdalten.bsky.social · 18/05/2025
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Gabriella Conti @gabriconti.bsky.social · 10/05/2025
📣 I’m delighted to share a new working paper that’s been years in the making: 🧬 “ #Gene × #Environment Interactions: Polygenic Scores and the Impact of an Early Childhood Intervention in Colombia” 👉🏻 Available here as @hceconomics.bsky.social WP: humcap.uchicago.edu/RePEc/hka/wp...
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Sjoerd van Alten @sjoerdalten.bsky.social · 12/05/2025
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Sjoerd van Alten @sjoerdalten.bsky.social · 02/05/2025
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Alex Strudwick Young @alextisyoung.bsky.social · 28/04/2025
I am recruiting a quantitative/computational postdoc to my group at UCLA. This is a great opportunity to work on foundational theory, methods, and software in statistical genetics. Link to apply: recruit.apo.ucla.edu/JPF10275. Please repost!
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Sjoerd van Alten @sjoerdalten.bsky.social · 16/04/2025
Agreed! The opportunity for follow-up analyses is endless. One thing I forgot to mention here is that these weights are available in the Returns Catalogue to any researchers who use the UKB, under application# 55154: biobank.ndph.ox.ac.uk/ukb/app.cgi?...
biobank.ndph.ox.ac.uk
: Application
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Sjoerd van Alten @sjoerdalten.bsky.social · 16/04/2025
Many thanks to my amazing co-authors: Ben Domingue, Jessica Faul, Titus Galama, and Andries Marees. This paper has been a 4-year long journey and I am so happy to finally see it out!
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Sjoerd van Alten @sjoerdalten.bsky.social · 16/04/2025
Overall, the message is clear: volunteer bias matters to GWAS results and downstream analyses. The extent to which it matters is phenotype-specific. The community should work on creating population-representative weights for various cohorts and incorporate these in GWAS.
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Sjoerd van Alten @sjoerdalten.bsky.social · 16/04/2025
WGWAS may also result in different bio annotations (as estimated in MAGMA). For example, the GWAS results for breast cancer show no enriched pathways. The WGWAS results are expressed in the fallopian tube, uterus, ovary, and Artery Tibial (Figure 3).
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Sjoerd van Alten @sjoerdalten.bsky.social · 16/04/2025
Furthermore, we find evidence that weighting GWAS results pushes the intercept of LD-score regression closer to 1, which indicates that weighting might also shield against bias due to population stratification.
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Sjoerd van Alten @sjoerdalten.bsky.social · 16/04/2025
WGWAS also resulted in larger SNP-based heritabilities for 7 out of the 10 phenotypes (Table 3). For example, Years of education shows a SNP-based heritability of 14.8% in GWAS, and 17.8% in WGWAS.
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Sjoerd van Alten @sjoerdalten.bsky.social · 16/04/2025
Note also that the effective sample size shrinks from 376,900 in GWAS to 143,222 in WGWAS averaged over all phenotypes, a shrinkage of 62%. Hence, representative samples would increase the power of GWAS, as power reduces when taking volunteer bias into account.
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Sjoerd van Alten @sjoerdalten.bsky.social · 16/04/2025
Next, we compare GWAS and WGWAS associations genomewide. The genetic correlation between GWAS and WGWAS results is lower than one for 6 out of 10 phenotypes. The lowest congruence between GWAS and WGWAS is found for Type 1 Diabetes (rG=0.66) and Breast Cancer (rG = 0.80). (Table 2)
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Sjoerd van Alten @sjoerdalten.bsky.social · 16/04/2025
For 5 out of 6 phenotypes we find underestimation: correcting these associations for volunteer bias makes SNP effects more pronounced. For breast cancer we find evidence that previously found top hits are overestimated or even false positives (table 1)
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Sjoerd van Alten @sjoerdalten.bsky.social · 16/04/2025
Next, we compare GWAS and WGWAS for previously known top hits for 6 out of our 10 phenotypes. Regressing WGWAS effects on GWAS effects, a coefficient > 1 implies that volunteer bias leads to an underestimation of effect sizes for these top hits, whereas < 1 implies overestimation
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