Year: 2026
Type: article
Abstract: Genome-wide association studies using large, population-based samples of unrelated individuals have discovered thousands of genetic associations with health and disease 1 . 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.
Source: Nature
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
Institutions: Norwegian Institute of Public Health, University of Bristol, Lovisenberg Diakonale Sykehus, MRC Integrative Epidemiology Unit, Oslo University Hospital, University of Oslo, University College London, University of Cambridge, Haukeland University Hospital, University of Bergen, Broad Institute, Massachusetts General Hospital, Norwegian University of Science and Technology
Language: English
Subfield: Genetics
Domain: Life Sciences
Open Access status: hybrid
Estimated APC paid: $12,690
Funders: Stiftelsen Kristian Gerhard Jebsen, Wellcome Trust, UK Research and Innovation, Trond Mohn stiftelse, European Commission, University of Bristol, Helse- og Omsorgsdepartementet, Novo Nordisk, NordForsk, Universitetet i Bergen, Universitetet i Oslo, Norges Forskningsråd, National Institutes of Health, Medical Research Council, Economic and Social Research Council, Helse Sør-Øst RHF, National Institute of Mental Health
Awards: G1040317000, G1169676165, G1274085498, G1300865376, G1350562830, G1416717560, G1420817852, G1572642439, Modern Signal Processing Methods for Ultra-realistic Light-Field Displays, The causal map of the human phenome, Post-pandemic mental health: Risk and resilience in young people (covidmentYOUNG), G2004563491, G2187532201, G2230720350, G2250219476, G2332092160, G2342256610, G240382578, G2498202452, G2572253437, Running in the FAMILY - Understanding and predicting the intergenerational transmission of mental illness, G268165469, G2934376606, G2957267872, G3051413233, G3096137445, G3268937696, G3277956970, G3303394891, G339059223, G3433676821, G3458941969, G3691419938, G3723918320, G3742410397, G3761261155, G4019268957, G4142796561, G4235098896, UCL, Bloomsbury and East London Doctoral Training Partnership, G4297682489, G4345613377, G4478860539, G4493028280, G4516452757, G4670997888, G482473366, G4895042318, G4931922774, G5221782703, How do 'effects' differ across time? Understanding health inequalities by triangulating across multiple data sources and empirical strategies, G5351531748, The causal map of the human phenome, G5458267808, G5479941350, G5625758778, G5663989965, G571894948, G5797205723, Mendelian Randomisation, G6036406809, RCN: Identifying Causal Risk Factors and Treatments for Depression, Anxiety, and ADHD in Young People, G6336899014, G6390370581, G6488308326, G6523755375, G6667305214, G67063899, G6711303027, G6758941665, Leveraging Nordic Opportunities to Transform Mental Health Care through Precision Medicine (PreciMENT), G6966598969, G7015893960, Predicting comorbid cardiovascular disease in individuals with mental disorder by decoding disease mechanisms, G7117495091, G720762514, G7384872225, G7689767205, G7702317272, Cytoplasmic terminal polymerases: small molecule opportunities to target the microRNA pathway, G7731712466, G8100857981, Using real-world big data from eHealth, biobanks and national registries, integrated with clinical trial data to improve outcome of severe mental disorders, G8383967617, G8600322300, G8745459150, Behavioural, Social and Environmental Determinants of Physical and Mental Health, G8858095331, Statistical methods to localize disease heritability and identify biological mechanisms, G971472329
OpenAlex ID: W7203752223