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Emneord:
PROMENTA
Publikasjoner
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Porneso, Ralph; Havdahl, Alexandra; Eilertsen, Espen Moen & Ystrom, Eivind
(2026).
Longitudinal genome-wide analysis reveals putative non-additive loci in trait development.
Cell reports.
45(8).
doi:
10.1016/j.celrep.2026.117840.
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Complex traits emerge from reciprocal interactions among genotype, environment, and developmental processes. Yet, standard genetic models assume purely additive effects, potentially obscuring non-additive effects. Here, we introduce a longitudinal log-linear variance and genotype-by-time model to detect associations from within-individual variation departing from additivity, i.e., putative non-additive effects. Applied to early growth (infant length and BMI) and cognitive traits (math and reading) of 45,000 to 65,000 individuals, we report 76 lead putative non-additive loci that are enriched 16-fold for cis-regulatory interactions. Of the 76, 6 overlap prior interaction studies (anthropometric) and only 3 loci overlap prior genome-wide association study (GWAS) (cognitive). Accounting for scale effects and linkage disequilibrium (LD), we observe that additive effects are correlated with putative non-additive effects, i.e., “effect pleiotropy.” These results are consistent with non-additive genetic contribution to trait development, which may partly be absorbed by effects estimated under standard GWAS parameterization that assumes strict additivity.
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Cheesman, Rosa Catherine Gillespie; Anapaz, Ville; Alten, Sjoerd van; Abdellaoui, Abdel; Porneso, Ralph Pascual Ortiz & Ebeltoft, Joakim Coleman
[Vis alle 16 forfattere av denne artikkelen]
(2025).
Genetic associations with educational fields.
Nature Genetics.
ISSN 1061-4036.
57,
s. 2997–3006.
doi:
10.1038/s41588-025-02391-z.
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Educational field choices shape careers, wellbeing and the societal skill distribution, yet genetic influences on what people study remain poorly understood. Here we show that genetic factors are associated with educational field specializations using genome-wide association studies (GWASs) across 463,134 individuals from Finland, Norway and the Netherlands (effective n between 40,072 and 317,209). We identified 17 independent genome-wide significant variants linked to 7 of 10 educational fields, with average heritability of 7%. The genetic signal is specific to field choice rather than educational level, persisting after controlling for years of schooling and confounding factors. By examining genetic clustering across specializations, we uncovered two key dimensions: technical versus social and practical versus abstract. We performed GWASs of these components and demonstrated distinct genetic correlations with personality, behavior and socioeconomic status. Our findings demonstrate that genomic research can illuminate ‘horizontal’ stratification, revealing insights into vocational interests and social sorting beyond traditional attainment measures.
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Porneso, Ralph
(2022).
Visuomotor experience induces functional and structural plasticity of chandelier cells.
BioRxiv.
ISSN 0362-4331.
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Porneso, Ralph Pascual Ortiz; Havdahl, Alexandra; Eilertsen, Espen Moen & Ystrøm, Eivind
(2025).
Genetic Non-Additivity Reveals Variants in Complex Traits.
doi:
https:/geneforum.ee/wp-content/uploads/2025/09/Gene-Forum-Poster-Abstract-book.pdf.
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Background: The contribution of non-additive genetic variation in human traits is nil for
dominance, small for epistasis and, theory suggests, minimal for gene-environment
interaction. Evidence from behavioral genetics indicates genetic interactions play a role in
cognitive traits, and recent genome-wide association studies (GWAS) on height and BMI
have identified single nucleotide polymorphisms (SNPs) involved in interactions. This study
is a first step to uncover the molecular mechanisms behind gene-gene and gene-
environment interactions and, in part, bridge the gap in the missing heritability problem.
Study question: Are there SNPs associated with complex traits plasticity?
Methods: We used a non-linear mixed effects framework to concurrently estimate SNPs’
mean (i.e. additive) and within individual variability (i.e. non-additive) effects on height and
BMI at 6, 8 and 12 months (N=~45,000) and Math and Reading scores at grades 5, 8 and
9 (N=~65,000) from the Norwegian Mother Father and Child cohort (MoBa). We compared
our models against a newly developed pipeline, trajGWAS, which restricts discovery to
variants with linear within subject (WS) variance effects. Our approach relaxes this
restriction. In addition, we investigated whether time-varying effects overlap with non-
additive effects.
Main results: We found putative “plasticity” variants with linear and non-linear effects. We
provide within-individual variability summary statistics for height, BMI, Math and Reading.
We found SNP time-varying effects explain ~1% of non-additive effects on average but
found no overlap.
Limitations: At present, our pipeline runs only using multiple cores and takes a
considerable amount of compute hours.
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Porneso, Ralph Pascual Ortiz; Havdahl, Alexandra; Eilertsen, Espen Moen & Ystrøm, Eivind
(2025).
Non-additive genetic effects and complex traits plasticity.
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Genome-wide association studies (GWAS) on educational attainment and related outcomes have succeeded at identifying hundreds to thousands of genetic variants with small additive effects using measures collected at a single time point. Recently, GWAS leveraging measures collected at multiple time points have found novel genetic associations, suggesting the presence of previously undetected time-specific variants. We hypothesized that a subset of these variants may be involved in gene-by-gene or gene-by-environment interaction. In the present study, we expanded the GWAS framework by estimating genetic effects on the residual variance. We used non-linear mixed effects (NLME) and double generalized linear models (DGLM) to concurrently estimate mean and within individual variance effects on academic performance in Math and Reading at grades 5, 8 and 9 in ~65,000 children from the Norwegian Mother Father and Child cohort (MoBa). We compared our models against a newly developed pipeline, trajGWAS, which restricts variant discovery to those with log-linear within subject (WS) variance effects. Our approach does not impose this restriction and found variants with non-linear variance effect. We replicated findings from other variance-based approaches that non-additive effects co-occur with mean effects. We decorrelated these effects and provide summary statistics for Math and Reading. This study is a first step to better understanding gene-by-gene and gene-by-environment interactions and shed light on the genetic correlates and potential mechanisms involved in complex trait plasticity.
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Porneso, Ralph Pascual Ortiz; Havdahl, Alexandra; Eilertsen, Espen Moen & Ystrøm, Eivind
(2025).
Genetic non-additivity reveals variants in complex traits plasticity.
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In human complex traits, the contribution of non-additive relative to additive genetic variation is nil (dominance) to small (genetic interactions) which makes variant discovery difficult to achieve (Hivert, 2018). Even with larger samples, gene-gene and gene-environment interaction studies face several technical challenges (e.g. greater multiple testing burden, collecting and modelling correlated factors, etc) that impede progress in uncovering biological insights behind trait plasticity . We work around these issues by concurrently modelling the effect of single nucleotide polymorphisms (SNPs) on trait level, which shifts the distribution, and variability, which generates heteroscedasticity (unequal variance across genotype levels) resulting in the spreading out of phenotypic values around a mean. This approach does not require explicit interaction terms to be fitted to the data thereby lessening both computational complexity and multiple testing burden encountered by more traditional approaches. We estimate SNP effects on trait level (additive) and variability (non-additive) using a longitudinal heteroscedastic mixed effects model that assume uncorrelated variance components. In total, we found 25 lead putative plasticity SNPs (i.e. 2 for infant length, 11 for BMI, 5 for math and 7 for reading) of which 5 (1 for infant length and 4 for BMI) were previously reported in epistatic or gene-environment interaction in independent studies. We show that non-additive, time-varying and additive effects are correlated with each other across all 4 traits, indicating additive genetic variation captures SNP interaction effects. Our findings provide SNP-based evidence that non-additive genetic variation contributes to complex traits including height.
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Porneso, Ralph Pascual Ortiz; Eilertsen, Espen Moen; Havdahl, Alexandra & Ystrøm, Eivind
(2024).
Non-additive genetic effects in academic performance.
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Porneso, Ralph Pascual Ortiz; Eilertsen, Espen Moen; Havdahl, Alexandra & Ystrøm, Eivind
(2024).
Identifying genetic variants with non-additive and time-varying genetic effects using longitudinal data.
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Porneso, Ralph Pascual Ortiz
(2024).
Converging evidence on the role of education in unequal health.
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Porneso, Ralph Pascual Ortiz; Eilertsen, Espen Moen; Havdahl, Alexandra & Ystrøm, Eivind
(2024).
Non-additive genetic effects in academic performance.
Fulltekst i vitenarkiv
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Porneso, Ralph Pascual Ortiz; Eilertsen, Espen Moen; Havdahl, Alexandra & Ystrøm, Eivind
(2024).
Identifying genetic variants with non-additive and time-varying effects using longitudinal data.
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Publisert
10. juli 2025 10:00
- Sist endret
10. juli 2025 13:15