The DOI matches its Crossref record; 109 of the 109 references it cites were found in a registry or an index.
Investigating the genetic architecture of noncognitive skills using GWAS-by-subtraction
Open accessAbstract
Little is known about the genetic architecture of traits affecting educational attainment other than cognitive ability. We used genomic structural equation modeling and prior genome-wide association studies (GWASs) of educational attainment (n = 1,131,881) and cognitive test performance (n = 257,841) to estimate SNP associations with educational attainment variation that is independent of cognitive ability. We identified 157 genome-wide-significant loci and a polygenic architecture accounting for 57% of genetic variance in educational attainment. Noncognitive genetics were enriched in the same brain tissues and cell types as cognitive performance, but showed different associations with gray-matter brain volumes. Noncognitive genetics were further distinguished by associations with personality traits, less risky behavior and increased risk for certain psychiatric disorders. For socioeconomic success and longevity, noncognitive and cognitive-performance genetics demonstrated associations of similar magnitude. By conducting a GWAS of a phenotype that was not directly measured, we offer a view of genetic architecture of noncognitive skills influencing educational success. Genomic structural equation modeling of genome-wide association data for educational attainment and cognitive test performance is used to estimate the genetic component of variation in educational attainment that is independent of cognitive ability. The study finds that noncognitive skills account for 57% of genetic variation in educational attainment.
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Cites
Biological insights from 108 schizophrenia-associated genetic loci
Schizophrenia Working Group of the Psychiatric Genomics Consortium (2014) · Nature · doi:10.1038/nature13595 · Cited by 7,577
LD Score regression distinguishes confounding from polygenicity in genome-wide association studies
Schizophrenia Working Group of the Psychiatric Genomics Consortium, Bulik-Sullivan, B. K., Loh, P.-R., Finucane, H. K., Ripke, S., Yang, J., Patterson, N., Daly, M. J., Price, A. L., & Neale, B. M. (2015) · Nature Genetics · doi:10.1038/ng.3211 · Cited by 5,559
METAL: fast and efficient meta-analysis of genomewide association scans
Willer, C. J., Li, Y., & Abecasis, G. R. (2010) · Bioinformatics · doi:10.1093/bioinformatics/btq340 · Cited by 5,205
The Genotype-Tissue Expression (GTEx) pilot analysis: Multitissue gene regulation in humans
The GTEx Consortium, Ardlie, K. G., Deluca, D. S., Segrè, A. V., Sullivan, T. J., Young, T. R., Gelfand, E. T., Trowbridge, C. A., Maller, J. B., Tukiainen, T., et al. (2015) · Science · doi:10.1126/science.1262110 · Cited by 5,062
A gradient of childhood self-control predicts health, wealth, and public safety
Moffitt, T. E., Arseneault, L., Belsky, D., Dickson, N., Hancox, R. J., Harrington, H., Houts, R., Poulton, R., Roberts, B. W., Ross, S., et al. (2011) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1010076108 · Cited by 4,885
Self-citationThe effects of cognitive and noncognitive abilities on labor market outcomes and social behavior
Heckman, J. J., Stixrud, J., & Urzua, S. (2006) · Journal of Labor Economics · doi:10.1086/504455 · Cited by 4,427
An atlas of genetic correlations across human diseases and traits
ReproGen Consortium, Bulik-Sullivan, B., Psychiatric Genomics Consortium, Genetic Consortium for Anorexia Nervosa of the Wellcome Trust Case Control Consortium 3, Finucane, H. K., Anttila, V., Gusev, A., Day, F. R., Loh, P.-R., Duncan, L., et al. (2015) · Nature Genetics · doi:10.1038/ng.3406 · Cited by 4,255
MAGMA: Generalized Gene-Set Analysis of GWAS Data
de Leeuw, C. A., Mooij, J. M., Heskes, T., & Posthuma, D. (2015) · PLOS Computational Biology · doi:10.1371/journal.pcbi.1004219 · Cited by 3,653
Richardson, M., Abraham, C., & Bond, R. (2012) · Psychological Bulletin · doi:10.1037/a0026838 · Cited by 3,646
Skill formation and the economics of investing in disadvantaged children
Heckman, J. J. (2006) · Science · doi:10.1126/science.1128898 · Cited by 3,559
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Self-citationNivard, M. G., Belsky, D. W., Harden, K. P., Baier, T., Andreassen, O. A., Ystrøm, E., van Bergen, E., & Lyngstad, T. H. (2024) · Nature Human Behaviour · doi:10.1038/s41562-023-01796-2 · Cited by 65
Self-citationWu, Y., Sun, Z., Zheng, Q., Miao, J., Dorn, S., Mukherjee, S., Fletcher, J. M., & Lu, Q. (2024) · Nature Genetics · doi:10.1038/s41588-024-01963-9 · Cited by 45
Genetic Risk for Smoking: Disentangling Interplay Between Genes and Socioeconomic Status
Pasman, J. A., Demange, P. A., Guloksuz, S., Willemsen, A. H. M., Abdellaoui, A., ten Have, M., Hottenga, J.-J., Boomsma, D. I., de Geus, E., Bartels, M., et al. (2022) · Behavior Genetics · doi:10.1007/s10519-021-10094-4 · Cited by 41
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Metadata
- Authors
- Demange, P. A., Malanchini, M., Mallard, T. T., Biroli, P., Cox, S. R., Grotzinger, A. D., Tucker-Drob, E. M., Abdellaoui, A., Arseneault, L., van Bergen, E., Boomsma, D. I., Caspi, A., Corcoran, D. L., Domingue, B. W., Harris, K. M., Ip, H. F., Mitchell, C., Moffitt, T. E., Poulton, R., Prinz, J. A., Sugden, K., Wertz, J., Williams, B. S., de Zeeuw, E. L., Belsky, D. W., Harden, K. P., & Nivard, M. G.
- Venue
- Nature Genetics
- Published
- 2021-01
- Volume
- 53
- Issue
- 1
- Pages
- 35-44
- ISSN
- 1061-4036 (ISSN-L)
- 1546-1718
- OpenAlex
- W3118751020
- Cited by
- 298
- References
- 109
- FWCI
- 23.67
- Type
- journal article
- Language
- en
- Open access
- bronze
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- Demange, P. A., Malanchini, M., Mallard, T. T., Biroli, P., Cox, S. R., Grotzinger, A. D., Tucker-Drob, E. M., Abdellaoui, A., Arseneault, L., van Bergen, E., Boomsma, D. I., Caspi, A., Corcoran, D. L., Domingue, B. W., Harris, K. M., Ip, H. F., Mitchell, C., Moffitt, T. E., Poulton, R., . . . Nivard, M. G. (2021). Investigating the genetic architecture of noncognitive skills using GWAS-by-subtraction. Nature Genetics. https://doi.org/10.1038/s41588-020-00754-2
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
