Family genetic designs in MoBa provide insights into health and functioning

• 成果类型: Article; Early Access
• 署名作者: Corfield, Elizabeth C.; Shadrin, Alexey A.; Frei, Oleksandr; Rahman, Zillur; Akdeniz, Bayram Cevdet; Filiz, Tahir Tekin; Lin, Aihua; Badini, Isabella; Hegemann, Laura; Athanasiu, Lavinia; Wootton, Robyn E.; Austerberry, Chloe; Hughes, Amanda M.; Tesli, Martin; Hagen, Espen; Brandlistuen, Ragnhild E.; Eilertsen, Espen Moen; Westlye, Lars T.; Njolstad, Pal R.; Magnus, Per; Hovig, Eivind; Zayats, Tetyana; Ask, Helga; Reichborn-Kjennerud, Ted; Hemani, Gibran; Davies, Neil M.; Hannigan, Laurie J.; Andreassen, Ole A.; Havdahl, Alexandra Karoline
• 署名单位: Norwegian Institute of Public Health (NIPH); University of Bristol; University of Bristol; University of Oslo; University of Oslo; University of Oslo; University of Oslo; University of Oslo; National Hospital Norway; University of London; University College London; University of Bristol; University of London; University College London; University of Cambridge; Norwegian Institute of Public Health (NIPH); University of Oslo; University of Oslo; University of Oslo; University of Bergen; University of Bergen; Haukeland University Hospital; Norwegian Institute of Public Health (NIPH); University of Oslo; Harvard University; Harvard University Medical Affiliates; Massachusetts General Hospital; Harvard University; Massachusetts Institute of Technology (MIT); Broad Institute; Norwegian Institute of Public Health (NIPH); University of Oslo; University of London; University College London; Norwegian University of Science & Technology (NTNU)
• 刊物名称: NATURE
• ISSN/ISSBN: 0028-0836; 1476-4687
• DOI: 10.1038/s41586-026-10926-5
• 发表日期: 2026-08-19
• 关键词: mendelian randomization; genome; inference; common; genotype; project; update; sample; cohort; RISK

摘要

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 trios2,3. However, samples of genotyped families are rare4, 5, 6, 7, 8, 9, 10-11. 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 approximate to 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.