100 Citations On Iq From Nature

(I collect lists of cites and bibliographies.) Gottfredson, L. S. Why g matters: The complexity of everyday life. Intelligence 24, 79–132 (1997). Deary, I. J. et al. Genetic contributions to stability and change in intelligence from childhood to old age. Nature 482, 212–214 (2012). Deary, I. J., Strand, S., Smith, P. & Fernandes, C. Intelligence and educational achievement. Intelligence 35, 13–21 (2007). Schmidt, F. L. & Hunter, J. General mental ability in the world of work: occupational attainment and job performance. J. Pers. Soc. Psychol. 86, 162–173 (2004). Strenze, T. Intelligence and socioeconomic success: a meta-analytic review of longitudinal research. Intelligence 35, 401–426 (2007). Show context Article 6. Calvin, C. M. et al. Childhood intelligence in relation to major causes of death in 68 year follow-up: prospective population study. Brit. Med. J. 357, 2708 (2017). Show context Article 7. Deary, I. J., Pattie, A. & Starr, J. M. The stability of intelligence from age 11 to age 90 years: the Lothian birth cohort of 1921. Psychol. Sci. 24, 2361–2368 (2013). Show context PubMedArticle 8. [No authors listed] Intelligence research should not be held back by its past. Nature 545, 385–386 (2017). This editorial is a landmark in the acceptance of genetic influence on intelligence, concluding, “it’s well established and uncontroversial among geneticists that together, differences in genetics underwrite significant variation in intelligence between people.” Show context 9. Pinker, S. The Blank Slate: The Modern Denial of Human Nature (Penguin, 2003). Show context 10. Block, N. J. & Dworkin, G. E. The IQ Controversy: Critical Readings (Pantheon, 1976). Show context 11. Gould, S. J. The Mismeasure of Man (W.W. Norton, 1982). Show context 12. Kamin, L. J. The Science and Politics of IQ (Routledge, 1974). Show context 13. Bouchard, T. J. & McGue, M. Familial studies of intelligence: a review. Science 212, 1055–1059 (1981). Show context PubMedArticle 14. Knopik, V. S., Neiderheiser, J., DeFries, J. C. & Plomin, R. Behavioral Genetics. 7th edn (Worth, 2017). Show context 15. Haier, R. J. The Neuroscience of Intelligence (Cambridge Univ. Press, 2016). Show context 16. Hare, B. Survival of the friendliest: Homo sapiens evolved via selection for prosociality. Annu. Rev. Psychol. 68, 155–186 (2017). Show context PubMedArticle 17. Sternberg, R. J. & Kaufman, J. C. The Evolution of Intelligence (Psychology Press, 2013). Show context 18. Chabris, C. F. et al. Most reported genetic associations with general intelligence are probably false positives. Psychol. Sci. 23, 1314–1323 (2012). Show context PubMedArticle 19. Benyamin, B. et al. Childhood intelligence is heritable, highly polygenic and associated with FNBP1L. Mol. Psychiatry 19, 253–258 (2014). Show context CASPubMedArticle 20. Butcher, L. M., Davis, O. S., Craig, I. W. & Plomin, R. Genome-wide quantitative trait locus association scan of general cognitive ability using pooled DNA and 500K single nucleotide polymorphism microarrays. Genes Brain Behav. 7, 435–446 (2008). Show context CASPubMedArticle 21. Davies, G. et al. Genome-wide association studies establish that human intelligence is highly heritable and polygenic. Mol. Psychiatry 16, 996–1005 (2011). Show context CASPubMedArticle 22. Davies, G. et al. Genetic contributions to variation in general cognitive function: a meta-analysis of genome-wide association studies in the CHARGE consortium (N = 53 949). Mol. Psychiatry 20, 183–192 (2015). Show context CASPubMedArticle 23. Davies, G. et al. Genome-wide association study of cognitive functions and educational attainment in UK Biobank (N = 112 151). Mol. Psychiatry 21, 758–767 (2016). Show context CASPubMedArticle 24. Plomin, R. et al. A genome-wide scan of 1842 DNA markers for allelic associations with general cognitive ability: a five-stage design using DNA pooling and extreme selected groups. Behav. Genet. 31, 497–509 (2001). Show context CASPubMedArticle 25. Trampush, J. et al. GWAS meta-analysis reveals novel loci and genetic correlates for general cognitive function: a report from the COGENT consortium. Mol. Psychiatry 22, 336 (2017). Show context PubMedArticle 26. Cesarini, D. & Visscher, P. M. Genetics and educational attainment. Sci. Learn. 2, 1–7 (2017). Show context Article 27. Rietveld, C. A. et al. Common genetic variants associated with cognitive performance identified using the proxy-phenotype method. Proc. Natl Acad. Sci. USA 111, 13790–13794 (2014). This study uses EA1 SNPs to predict intelligence, although less than 1% of the variance is predicted. Show context CASPubMedArticle 28. Rietveld, C. A. et al. GWAS of 126,559 individuals identifies genetic variants associated with educational attainment. Science 340, 1467–1471 (2013). This is the GWAS origin of EA1, which yields a GPS that predicts 1% of the variance in years of education. Show context CASPubMedArticle 29. Rietveld, C. A. et al. Replicability and robustness of genome-wide-association studies for behavioral traits. Psychol. Sci. 25, 1975–1986 (2014). Show context PubMedArticle 30. Okbay, A. et al. Genome-wide association study identifies 74 loci associated with educational attainment. Nature 533, 539–542 (2016). This is the GWAS origin of EA2 GPS, which increases the prediction of educational attainment from 1% to 3% of the variance. Show context CASPubMedArticle 31. Behavior Genetics Association 47th Annual Meeting Abstracts. Okbay, A. et al. GWAS of educational attainment – phase 3: main results [abstract]. Behav. Genet. 47, 699 (2017). This study refers to the largest GWAS of educational attainment (n = 1,100,000), which increases the power of its GPS, EA3, to predict more than 10% of the variance in the targeted trait. Show context 32. von Stumm, S. & Plomin, R. Socioeconomic status and the growth of intelligence from infancy through adolescence. Intelligence 48, 30–36 (2015). Show context PubMedArticle 33. Sniekers, S. et al. Genome-wide association meta-analysis of 78,308 individuals identifies new loci and genes influencing human intelligence. Nat. Genet. 49, 1107–1112 (2017). This is the GWAS origin of IQ2 GPS, which increases the prediction of intelligence from 1% to 3%. Show context PubMedArticle 34. Savage, J. E. et al. GWAS meta-analysis (N = 279,930) identifies new genes and functional links to intelligence. Preprint at https://doi.org/10.1101/184853 (2017). This paper describes the largest GWAS of intelligence to date, which yields a GPS (IQ3) that predicts 4% of the variance in intelligence. Show context 35. Davies, G. et al. Ninety-nine independent genetic loci influencing general cognitive function include genes associated with brain health and structure (N = 280,360). Preprint at https://doi.org/10.1101/176511 (2017). Show context 36. Krapohl, E. et al. Multi-polygenic score approach to trait prediction. Mol. Psychiatry http://dx.doi.org/10.1038/mp.2017.163 (2017). This study employs a multiple-GPS approach and finds that 81 GPSs derived from well-powered GWAS predict 5% of the variance in intelligence. Show context 37. Hill, W. D., Davies, G., McIntosh, A. M., Gale, C. R. & Deary, I. J. A combined analysis of genetically correlated traits identifies 107 loci associated with intelligence. Preprint at https://doi.org/10.1101/160291 (2017). This study employs multiple-trait analysis of GWAS for intelligence and finds that educational attainment and income predict 7% of the variance in intelligence in an independent sample. Show context 38. Manolio, T. A. et al. Finding the missing heritability of complex diseases. Nature 461, 747–753 (2009). Show context CASPubMedArticle 39. Plomin, R. et al. Common DNA markers can account for more than half of the genetic influence on cognitive abilities. Psychol. Sci. 24, 562–568 (2013). Show context PubMedArticle 40. Boyle, E. A., Li, Y. I. & Pritchard, J. K. An expanded view of complex traits: from polygenic to omnigenic. Cell 169, 1177–1186 (2017). Show context PubMedArticle 41. Plomin, R. Blueprint: How DNA Makes Us Who We Are (Allen Lane/Penguin, in the press). This book describes genetic research on behaviour from twin studies to the DNA revolution and its implications for science and society. Show context 42. Honzik, M. P., Macfarlane, J. W. & Allen, L. The stability of mental test performance between two and eighteen years. J. Exp. Educ. 17, 309–324 (1948). Show context Article 43. Haworth, C. M. et al. A twin study of the genetics of high cognitive ability selected from 11,000 twin pairs in six studies from four countries. Behav. Genet. 39, 359–370 (2009). Show context PubMedArticle 44. Plomin, R. & Deary, I. J. Genetics and intelligence differences: five special findings. Mol. Psychiatry 20, 98–108 (2015). This article highlights five genetic findings that are special to intelligence differences, including one not mentioned in this Review — assortative mating is much greater for intelligence than for other traits. Show context CASPubMedArticle 45. Briley, D. A. & Tucker-Drob, E. M. Explaining the increasing heritability of cognitive ability across development: a meta-analysis of longitudinal twin and adoption studies. Psychol. Sci. 24, 1704–1713 (2013). Show context PubMedArticle 46. Selzam, S. et al. Predicting educational achievement from DNA. Mol. Psychiatry 22, 267–272 (2017). This study shows that EA2 predicts 9% of the variance in tested educational achievement at age 16, which was the strongest GPS prediction of a behavioural trait at that time. Show context PubMedArticle 47. Plomin, R. & Kovas, Y. Generalist genes and learning disabilities. Psychol. Bull. 131, 592–617 (2005). Show context PubMedArticle 48. Selzam, S. et al. Genome-wide polygenic scores predict reading performance throughout the school years. Sci. Stud. Read. 21, 334–349 (2017). Show context PubMedArticle 49. Carrion-Castillo, A. et al. Evaluation of results from genome-wide studies of language and reading in a novel independent dataset. Genes Brain Behav. 15, 531–541 (2016). Show context PubMedArticle 50. Krapohl, E. et al. Phenome-wide analysis of genome-wide polygenic scores. Mol. Psychiatry 21, 1188–1193 (2015). Show context PubMedArticle 51. Marioni, R. E. et al. Common genetic variants explain the majority of the correlation between height and intelligence: the generation Scotland study. Behav. Genet. 44, 91–96 (2014). Show context PubMedArticle 52. Williams, K. M. et al. Phenotypic and genotypic correlation between myopia and intelligence. Sci. Rep. 7, 45977 (2017). Show context PubMedArticle 53. Hill, W. D. et al. Age-dependent pleiotropy between general cognitive function and major psychiatric disorders. Biol. Psychiatry 80, 266–273 (2016). Show context PubMedArticle 54. Bulik-Sullivan, B. K. et al. LD Score regression distinguishes confounding from polygenicity in genome-wide association studies. Nat. Genet. 47, 291–295 (2015). Show context CASPubMedArticle 55. Plomin, R., Haworth, C. M. & Davis, O. S. Common disorders are quantitative traits. Nat. Rev. Genet. 10, 872–878 (2009). Show context CASPubMedArticle 56. Spain, S. L. et al. A genome-wide analysis of putative functional and exonic variation associated with extremely high intelligence. Mol. Psychiatry 21, 1145–1151 (2016). Show context PubMedArticle 57. Zabaneh, D. et al. A genome-wide association study for extremely high intelligence. Mol. Psychiatry http://dx.doi.org/10.1038/mp.2017.121 (2017). This GWAS of intelligence uses a novel strategy to increase power — a case–control design in which the subjects were individuals with extremely high IQ from the top 0.0003 of the population (mean IQ of 170). Show context 58. Reichenberg, A. et al. Discontinuity in the genetic and environmental causes of the intellectual disability spectrum. Proc. Natl Acad. Sci. USA 113, 1098–1103 (2016). Show context CASPubMedArticle 59. Vissers, L. E., Gilissen, C. & Veltman, J. A. Genetic studies in intellectual disability and related disorders. Nat. Rev. Genet. 17, 9–18 (2016). Show context CASPubMedArticle 60. Plomin, R. & Daniels, D. Why are children in the same family so different from one another? Behav. Brain Sci. 10, 1–16 (1987). Show context Article 61. Tucker-Drob, E. M. & Bates, T. C. Large cross-national differences in gene × socioeconomic status interaction on intelligence. Psychol. Sci. 27, 138–149 (2016). Show context PubMedArticle 62. Hanscombe, K. B. et al. Socioeconomic status (SES) and children’s intelligence (IQ): in a UK-representative sample SES moderates the environmental, not genetic, effect on IQ. PLOS ONE 7, e30320 (2012). Show context PubMedArticle 63. Plomin, R. & Bergeman, C. S. The nature of nurture: genetic influence on “environmental” measures. Behav. Brain Sci. 14, 373–386 (1991). Show context Article 64. Belsky, D. W. et al. The genetics of success. Psychol. Sci. 27, 957–972 (2016). Show context PubMedArticle 65. Krapohl, E. et al. Widespread covariation of early environmental exposures and trait-associated polygenic variation. Proc. Natl Acad. Sci. USA 114, 11727–11732 (2017). Show context PubMedArticle 66. Smith-Woolley, E. et al. Differences in exam performance between pupils attending different school types mirror the genetic differences between them. NPJ Sci. Learn. (in the press). Show context 67. Ayorech, Z., Krapohl, E., Plomin, R. & von Stumm, S. Genetic influence on intergenerational educational attainment. Psychol. Sci. 28, 1302–1310 (2017). This paper describes both twin analyses and EA2 GPSs that show genetic influence on intergenerational EA. Show context PubMedArticle 68. Behavior Genetics Association 46th Annual Meeting Abstracts. Rimfeld, K., Trzaskowski, M., Esko, T., Metspalu, A. & Plomin, R. Genetic influence on educational attainment and occupational status during and after the Soviet era in Estonia [abstract]. Behav. Genet. 46, 803 (2016). Show context 69. Plomin, R. & DeFries, J. C. Genetics and intelligence: recent data. Intelligence 4, 15–24 (1980). Show context Article 70. McEwen, J. E. et al. The ethical, legal, and social implications program of the National Human Genome Research Institute: reflections on an ongoing experiment. Annu. Rev. Genom. Hum. Genet. 15, 481–504 (2014). Show context Article 71. Bouregy, S., Grigorenko, E. L., Latham, S. R. & Tan, M. Genetics, Ethics and Education (Cambridge Univ. Press, 2017). Show context 72. Conley, D. & Fletcher, J. The Genome Factor: What the Social Genomics Revolution Reveals about Ourselves, our History, and the Future (Princeton Univ. Press, 2017). Show context 73. Cohen, J. Statistical Power Analysis for the Behavioral Sciences (Lawrence Erlbaum Associates, 1977). Show context 74. Gottfredson, L. S. Mainstream science on intelligence. Wall Street Journal (13 December 1994). Show context 75. Carroll, J. B. Human Cognitive Abilities: A Survey of Factor-Analytic Studies (Cambridge Univ. Press, 1993). Show context 76. Spearman, C. ‘General Intelligence’ objectively determined and measured. Am. J. Psychol. 15, 201–292 (1904). Show context Article 77. Jensen, A. R. The g Factor: The Science of Mental Ability (Praeger, 1998). Show context 78. Deary, I. J. Intelligence. Annu. Rev. Psychol. 63, 453–482 (2012). This article is an authoritative overview of intelligence research. Show context PubMedArticle 79. Gow, A. J. et al. Stability and change in intelligence from age 11 to ages 70, 79, and 87: the Lothian Birth Cohorts of 1921 and 1936. Psychol. Ageing 26, 232–240 (2011). Show context Article 80. Schaie, K. W. Developmental Influences on Adult Intelligence: The Seattle Longitudinal Study (Oxford Univ. Press, 2005). Show context 81. Brinch, C. N. & Galloway, T. A. Schooling in adolescence raises IQ scores. Proc. Natl Acad. Sci. USA 109, 425–430 (2012). Show context PubMedArticle 82. Protzko, J. Does the raising IQ–raising g distinction explain the fadeout effect? Intelligence 56, 65–71 (2016). Show context Article 83. Duyme, M., Dumaret, A.-C. & Tomkiewicz, S. How can we boost IQs of “dull children”?: a late adoption study. Proc. Natl Acad. Sci. USA 96, 8790–8794 (1999). Show context CASPubMedArticle 84. Melby-Lervåg, M. & Hulme, C. Is working memory training effective? A meta-analytic review. Dev. Psychol. 49, 270–291 (2013). Show context PubMedArticle 85. Puma, M. et al. Head Start Impact Study Final Report. Administration for Children and Families https://www.acf.hhs.gov/sites/default/files/opre/hs_impact_study_final.pdf (2010). Show context 86. Plomin, R. & Simpson, M. A. The future of genomics for developmentalists. Dev. Psychopathol. 25, 1263–1278 (2013). Show context PubMedArticle 87. Pasaniuc, B. & Price, A. L. Dissecting the genetics of complex traits using summary association statistics. Nat. Rev. Genet. 18, 117–127 (2017). Show context PubMedArticle 88. Vilhjálmsson, B. J. et al. Modeling linkage disequilibrium increases accuracy of polygenic risk scores. Am. J. Hum. Genet. 97, 576–592 (2015). Show context CASPubMedArticle 89. Euseden, J. et al. PRSice: polygenic risk score software. Bioinformatics 31, 1466–1468 (2015). Show context CASPubMedArticle 90. Hill, W. D. et al. Molecular genetic contributions to social deprivation and household income in UK Biobank. Curr. Biol. 26, 3083–3089 (2016). Show context PubMedArticle 91. Turley, P. et al. MTAG: Multi-Trait Analysis of GWAS. Preprint at https://doi.org/10.1101/118810 (2017). Show context 92. Zheng, J. et al. LD Hub: a centralized database and web interface to perform LD score regression that maximizes the potential of summary level GWAS data for SNP heritability and genetic correlation analysis. Bioinformatics 33, 272–279 (2017). Show context PubMedArticle 93. Yang, J. et al. Concepts, estimation and interpretation of SNP-based heritability. Nat. Genet. 49, 1304–1310 (2017). Show context PubMedArticle 94. Sullivan, P. F. et al. Psychiatric genomics: an update and an agenda. Am. J. Psychol. http://dx.doi.org/10.1176/appi.ajp.2017.17030283 (2017). Show context 95. Bacanu, S. A. Sharing extended summary data from contemporary genetic studies is unlikely to threaten subject privacy. PLOS ONE 12, e0179504 (2017). Show context PubMedArticle 96. Calvin, C. M. et al. Multivariate genetic analyses of cognition and academic achievement from two population samples of 174,000 and 166,000 school children. Behav. Genet. 42, 699–710 (2012). Show context PubMedArticle 97. Marioni, R. E. et al. Molecular genetic contributions to socioeconomic status and intelligence. Intelligence 44, 26–32 (2014). Show context PubMedArticle 98. Branigan, A. R., McCallum, K. J. & Freese, J. Variation in the heritability of educational attainment: An international meta-analysis. Soc. Forces 92, 109–140 (2013). Show context Article 99. Krapohl, E. et al. The high heritability of educational achievement reflects many genetically influenced traits, not just intelligence. Proc. Natl Acad. Sci. USA 111, 15273–15278 (2014). Show context CASPubMedArticle 100. Haworth, C. M., Davis, O. S. & Plomin, R. Twins Early Development Study (TEDS): a genetically sensitive investigation of cognitive and behavioral development from childhood to young adulthood. Twin Res. Hum. Genet. 16, 117–125 (2013). Show context