Human Traits Beyond Inherited Genes

Our parents’ genes, even the ones we didn’t inherit, leave a measurable, lasting imprint on our lives. An international team led by researchers at the Institute of Science and Technology Austria (ISTA) and the Norwegian Institute of Public Health developed a new approach to analyze genetic data from tens of thousands of families. The study, published this Tuesday in Cell Genomics, found that for height, body weight, and school test performance, the environment shaped by our parents’ genes can be nearly as important as the genes we actually inherited from them.

When scientists study the genetics of human characteristics or disease, they typically look at a person’s own DNA. But parents don’t just pass on genes—their genetic makeup may also shape the household environment, parenting behavior, and countless other factors that influence how a child develops. This phenomenon, known as “genetic nurture”, complicates genetic studies because differences among people can mistakenly be attributed entirely to their own DNA when they are, in fact, partially driven by parental traits.

In addition to this, the same gene may behave differently depending on which parent passed it down. This phenomenon is known as the parent-of-origin effect, where some genes are naturally ‘switched off’ in either eggs or sperm, so that certain variants only have an effect if inherited from the parent where the gene is ‘on’. This may explain why some genetic disorders appear differently depending on the transmitting parent, or why identical genetic sequences can result in different physical or metabolic characteristics.

Untangling a child’s ‘own’ genetic contribution from the invisible genetic hand of their parents has been one of the central unsolved problems in human genetics. Now, an international team led by researchers at the Institute of Science and Technology Austria (ISTA) and the Norwegian Institute of Public Health has developed for the first time a method to clearly separate the multiple ways DNA influences a child’s characteristics. “Indirect genetic effects and parent-of-origin effects are distinct phenomena that may explain how genes influence traits beyond the standard model of a person’s direct DNA. However, disentangling them to reveal their individual contributions and interplay has not been done before,” says Matthew Robinson, professor at ISTA. Robinson led the study together with first author Ilse Krätschmer, a postdoctoral researcher in his group, and Alexandra Havdahl, Center Director of the PsychGen Center for Genetic Epidemiology and Mental Health at the Norwegian Institute of Public Health in Oslo.

The long-lasting influence of parental genes

The team analyzed genetic and phenotypic data from over 30,000 families—each consisting of a mother, father, and child—drawn from two large-scale biobank studies: the Norwegian Mother, Father, and Child Cohort and the Estonian Biobank. For each family, they looked at three measurable traits in the children: height, body mass index (BMI, a measure of body weight relative to height), and scores on national school tests taken around age 10. They then asked: for each trait, how much of the differences among children are attributable to the child’s own DNA, to each of the parents’ DNA acting through the environment they each create, and how much depends on whether DNA regions were inherited from the mother or the father. Uniquely, their approach also accounts for the fact that couples often share similar traits, such as the tendency of tall people to partner with tall people, which can distort the modelling.

The team found that, of the variation attributable to genetics, a child’s own DNA is the single largest source for all three traits—but it is not the whole story. Combined, indirect parental effects and parent-of-origin effects are similarly substantial, meaning that ignoring them produces a significantly incomplete picture of how genes influence traits. They also found that similar DNA regions, known to scientists as “loci”, underlie both direct and indirect genetic effects. “This suggests that the same loci shape a child’s traits both through the genes they carry and through the environment their parents create,” says Krätschmer.

Complex molecular mechanisms

The findings have broad implications for understanding how genetic and environmental factors combine to shape human development and also disease risk between generations. Furthermore, environmental factors play the largest role in BMI and education scores, and the team’s results suggest that policies aimed at improving outcomes in health or education need to consider the powerful role of the family environment. “Our findings reinforce that the relationship between genes and traits is genuinely complex, and this has important implications for how we interpret genetic research,” says Robinson.

The framework can, in principle, be extended to many other traits and could help researchers better understand the genetics of conditions ranging from mental health disorders to metabolic disease. “Ultimately, our method allows us to pinpoint if a genetic effect is only associated with the DNA of one of the parents and not the child’s own DNA,” says Krätschmer. As such, the researchers suggest that only regions of direct genetic effect, which tend to have a stronger impact within the person themselves, are likely to be good drug targets in personalized medicine.

Furthermore, this study may help the team better understand the effects of genetic imprinting—the molecular mechanism underlying the parent-of-origin effect. “Interestingly, our results suggest that genetic imprinting may be widespread in humans, which is surprising, since the underlying mechanisms remain poorly understood,” Robinson concludes.

Publication:

Ilse Krätschmer, Laura Hegemann, Robin Hofmeister, Elizabeth C. Corfield, Mahdi Mahmoudi, Olivier Delaneau, Ole A. Andreassen, Archie Campbell, Caroline Hayward, Estonian Biobank Research Team, Riccardo E. Marioni, Eivind Ystrom, Alexandra Havdahl, and Matthew R. Robinson. 2026. Separating direct, indirect and parent-of-origin genetic effects in the human population. Cell Genomics. DOI: 10.1016/j.xgen.2026.101277

Funding information:

This work was funded by an SNSF Eccellenza Grant (PCEGP3-181181) and by core funding from the Institute of Science and Technology Austria. The Norwegian Mother, Father and Child Cohort Study is supported by the Norwegian Ministry of Health and Care Services and the Ministry of Education and Research. The research is part of the HARVEST collaboration, supported by the Research Council of Norway (#229624).

Genomic data from the NORMENT Centre was funded by the Research Council of Norway (#223273), South East Norway Health Authorities, and Stiftelsen Kristian Gerhard Jebsen, in collaboration with deCODE Genetics. Genomic data from the Center for Diabetes Research at the University of Bergen was funded by the ERC AdG project SELECTionPREDISPOSED, Stiftelsen Kristian Gerhard Jebsen, Trond Mohn Foundation, the Research Council of Norway, the Novo Nordisk Foundation, the University of Bergen, and the Western Norway Health Authorities. Further funding sources include the European Union (Grant numbers: 101045526, 101073237) and the Research Council of Norway (Grant numbers: 336078, 288083, 331640).

Generation Scotland received core support from the Chief Scientist Office of the Scottish Government Health Directorates [CZD/16/6] and the Scottish Funding Council [HR03006]. Genotyping and methylation typing of the GS:SFHS samples was carried out by the Genetics Core Laboratory at the Wellcome Trust Clinical Research Facility, Edinburgh, Scotland, and was funded by the Medical Research Council UK and the Wellcome Trust (Wellcome Trust Strategic Award “STratifying Resilience and Depression Longitudinally” (STRADL) Reference 104036/Z/14/Z).

The Estonian Biobank (EstBB) study was conducted using the Estonian Center of Genomics/Roadmap II funded by the Estonian Research Council (project number TT17).

Norwegian analyses were performed on resources provided by Sigma2 – the National Infrastructure for High-Performance Computing and Data Storage in Norway. Estonian Data analysis was carried out in the High-Performance Computing Center cloud provided by the University of Tartu. Analysis of the Generation Scotland data and the summary statistics obtained from the other analyses was conducted at ISTA and is supported by the Scientific Service Units (SSU) of ISTA through resources provided by Scientific Computing (SciComp).