Family genetic designs in MoBa provide insights into health and functioning.

Authors

Elizabeth C Corfield, Alexey A Shadrin, Oleksandr Frei, Zillur Rahman, Bayram Cevdet Akdeniz, Tahir Tekin Filiz, Aihua Lin, Isabella Badini, Laura Hegemann, Lavinia Athanasiu, Robyn E Wootton, Chloe Austerberry, Amanda M Hughes, Martin Tesli, Espen Hagen, Ragnhild E Brandlistuen, Espen Moen Eilertsen, Lars T Westlye, Pål R Njølstad, Per Magnus, Eivind Hovig, Tetyana Zayats, Helga Ask, Ted Reichborn-Kjennerud, Gibran Hemani, Neil M Davies, Laurie J Hannigan, Ole A Andreassen, Alexandra Karoline Havdahl

Published in

Nature. Aug 19, 2026. Epub Aug 19, 2026.

Abstract

Genome-wide association studies using large, population-based samples of unrelated individuals have discovered thousands of genetic associations with health and disease¹. These studies can help explain genetic and environmental risks. However, increasing evidence suggests that population-based estimates, while precise, can also reflect confounding that affects their use and interpretation. This confounding can be overcome using data from genotyped family members, such as nuclear mother-father-child trios^2,3. However, samples of genotyped families are rare^4-11. Here we illustrate some of the advantages of familial data using the Norwegian Mother, Father and Child Cohort Study (MoBa), a population-based cohort of parents and offspring with extensive genotype data (n ≈ 230,000) (ref. ³), along with broad and longitudinal phenotyping of health and functioning. We provide an overview of MoBa and describe the quality control of genotype data tailored to this extensively related sample. We then use trio data to illustrate how family-based genomic designs can identify distinct direct and indirect sources of genetic influence and structural confounding. As examples, we analyse children's height, educational achievement, depressive symptoms and sleep duration. These demonstrations highlight MoBa as a broadly valuable resource for advancing understanding of health and functioning across the lifecourse and generations.

PMID:
42618792
Bibliographic data and abstract were imported from PubMed on 20 Aug 2026.

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