Publications
SSGAC-Led Publications
"Mendelian imputation of parental genotypes improves estimates of direct genetic effects", Young, A.I., Nehzati, S.M., Benonisdottir, S. et al., Nature Genetics, 2022. https://doi.org/10.1038/s41588-022-01085-0
"Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals", Okbay et al., Nature Genetics, 2022. https://doi.org/10.1038/s41588-022-01016-z
--> Publicly available data can be found here: Data
"Resource profile and user guide of the Polygenic Index Repository", Becker et al., Nature Human Behaviour, 2021. https://doi.org/10.1038/s41562-021-01119-3.
--> Details on data and code availability can be found here: PGI Repository
"Genomic analysis of diet composition finds novel loci and associations with health and lifestyle", Meddens et al., Mol Psychiatry, 2020. https://doi.org/10.1038/s41380-020-0697-5
--> Publicly available data can be found here: Data
"Genome-wide association analyses of risk tolerance and risky behaviors in over one million individuals identify hundreds of loci and shared genetic influences", Karlsson Linnér et al., Nature Genetics, 2019.
--> Publicly available data can be found here: Data
"Gene discovery and polygenic prediction from a 1.1-million-person GWAS of educational attainment", Lee et al., Nature Genetics, 2018.
--> Publicly available data can be found here: Data
"Genome-wide association study results for educational attainment aid in identifying genetic heterogeneity of schizophrenia", Bansal et al., Nature Communications, 2018.
--> Publicly available data can be found here: Data
"Multi-trait analysis of genome-wide association summary statistics using MTAG", Turley et al., Nature Genetics, 2018.
--> Publicly available data can be found here: Data
--> MTAG software can be found here: Software
"An epigenome-wide association study meta-analysis of educational attainment", Karlsson Linnér et al., Molecular Psychiatry, 2017.
--> Publicly available data can be found here: Data
"Genome-wide analysis identifies 12 loci influencing human reproductive behavior", Barban et al., Nature Genetics, 2016.
--> Answers to frequently asked questions about this article can be
found here: FAQs
--> Publicly available data can be found here: Data
"Genome-wide association study identifies 74 loci associated with educational attainment", Okbay et al., Nature, 2016.
--> Answers to frequently asked questions about this article can be found here: FAQs
--> Publicly available data can be found here: Data
"Genetic variants associated with subjective well-being, depressive symptoms and neuroticism identified through genome-wide analyses", Okbay et al., Nature Genetics, 2016.
--> Answers to frequently asked questions about this article can be found here: FAQs
--> Publicly available data can be found here: Data
"Common genetic variants associated with cognitive performance identified using proxy-phenotype method", Rietveld et al., Proceedings of the National Academy of Sciences of the United States of America, 2014.
--> Answers to frequently asked questions about this article can be found here: FAQs
--> Publicly available data can be found here: Data
"Replicability and Robustness of GWAS for Behavioral Traits", Rietveld et al., Psychological Science. Published online October 6, 2014. doi:10.1177/0956797614545132.
"GWAS of 126,559 individuals identifies genetic variants associated with educational attainment", Rietveld et al., Science, 340, 1467-1471, 2013. doi: 10.1126/science.1235488
--> Answers to frequently asked questions about this article can be found here: FAQs
--> Publicly available data can be found here: Data
"Molecular genetics and subjective well-being", C.A. Rietveld, D. Cesarini, D.J. Benjamin, P.D. Koellinger, J.-E. de Neve, H.Tiemeier, M. Johannesson, P.K.E. Magnusson, N.L. Pedersen, R.F. Krueger, and M. Bartels, Proceedings of the National Academy of Sciences of the United States of America, 2013. doi:10.1073/pnas.1222171110.
“The promises and pitfalls of genoeconomics”, D.J. Benjamin, D. Cesarini, C.F. Chabris, E.L. Glaeser, D.I. Laibson, V. Guðnason, T.B. Harris, L.J. Launer, S. Purcell, A.V. Smith, M. Johannesson, P.K.E. Magnusson, J.P. Beauchamp, N.A. Christakis, C.S. Atwood, B. Hebert, J. Freese, R.M. Hauser, T.S. Hauser, A. Grankvist, C.M. Hultman, and P. Lichtenstein, Annual Review of Economics, 4, 627-662, 2012. doi:10.1146/annurev-economics-080511-110939
"The genetic architecture of economic and political preferences", D.J. Benjamin, D. Cesarini, M.J.H.M. van der Loos, C. Dawes, P. Koellinger, P. Magnusson, C. Chabris, D. Conley, D. Laibson, M. Johannesson, and P. Visscher, Proceedings of the National Academy of Sciences of the United States of America, 109(21), 8026-8031, 2012. doi:10.1073/pnas.1120666109
Other SSGAC Publications
“Within-sibship genome-wide association analyses decrease bias in estimates of direct genetic effects”, Howe et al., Nature Genetics 54, 581–592 (2022). Published online May 9, 2022.
"Genetic variants linked to education predict longevity", Marioni et al., Proceedings of the National Academy of Sciences of the United States of America, 2016. doi:10.1073/pnas.1605334113.
“The Fourth Law of Behavior Genetics”, C.F. Chabris, J.J. Lee, D. Cesarini, D.J. Benjamin, and D. Laibson, Current Directions in Psychological Science, 24, 304-312, 2015.
"The association between lower educational attainment and depression due to shared genetic effects? Results in ~25,000 subjects", Peyrot et al., Molecular Psychiatry, 20(6): 735-43, 2015.
"Genetic Variation Associated with Differential Educational Attainment in Adults Has Anticipated Associations with School Performance in Children", M.E. Ward et al., PLoS ONE, 9(7), 2014.
"Polygenic Scores Associated With Educational Attainment in Adults Predict Educational Achievement and Attention Problems in Children", E. L. de Zeeuw et al., Am J Med Genet Part B, 9999: 1–11, 2014.
"The molecular genetic architecture of self-employment", M.J.H.M. van der Loos, C.A. Rietveld, N. Eklund, P.D. Koellinger, F. Rivadeneira, et al., PLoS ONE, 8(4):e60542, 2013.
--> Publicly available data can be found here: Data
"Why is it hard to find genes that are associated with social science traits? Theoretical and empirical considerations", C.F. Chabris, J.J. Lee, D.J. Benjamin, J.P. Beauchamp, E.L. Glaeser, G. Borst, S. Pinker, D.I. Laibson, American Journal of Public Health, 103(S1), S152-S166, 2013.
“Distinct Loci in the CHRNA5/CHRNA3/CHRNB4 Gene Cluster Are Associated With Onset of Regular Smoking”, S.H. Stephens et al., Genetic Epidemiology, 37(8), 846–859, 2013.
“Most Reported Genetic Associations with General Intelligence Are Probably False Positives”, C. Chabris, H. Benjamin, D. Benjamin, J. Beauchamp, D. Cesarini, M.J.H.M. van der Loos, M. Johannesson, P.K.E. Magnusson, P. Lichtenstein, C.S. Atwood, J. Freese, T.S. Hauser, R.M. Hauser, N.A. Christakis, and D. Laibson, Psychological Science, 23(11), 1314-1324, 2012. doi:10.1177/0956797611435528.
"Molecular genetics and economics", J. Beauchamp, D. Cesarini, M. Johannesson, M.J.H.M. van der Loos, P. Koellinger, P. Groenen, J. Fowler, N. Rosenquist, R. Thurik, and N. Christakis, Journal of Economic Perspectives, 25(4), 57-82, 2011.
"Genoeconomics", D.J. Benjamin, C.F. Chabris, E.L. Glaeser, V. Gudnason, T.B. Harris, D.I. Laibson, L. Launer, S. Purcell in M. Weinstein, J.W. Vaupel and K.W. Wachter (eds.), Biosocial Surveys.Committee on Population, Division of Behavioral and Social Sciences and Education. Washington, D.C.: The National Academies Press, 2007.