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3. Author Correction: Study of 300,486 individuals identifies 148 independent genetic loci influencing general cognitive function.

Author

Davies, Gail, Lam, Max, Harris, Sarah E, Trampush, Joey W, Luciano, Michelle, Hill, W David, Hagenaars, Saskia P, Ritchie, Stuart J, Marioni, Riccardo E, Fawns-Ritchie, Chloe, Liewald, David CM, Okely, Judith A, Ahola-Olli, Ari V, Barnes, Catriona LK, Bertram, Lars, Bis, Joshua C, Burdick, Katherine E, Christoforou, Andrea, DeRosse, Pamela, Djurovic, Srdjan, Espeseth, Thomas, Giakoumaki, Stella, Giddaluru, Sudheer, Gustavson, Daniel E, Hayward, Caroline, Hofer, Edith, Ikram, M Arfan, Karlsson, Robert, Knowles, Emma, Lahti, Jari, Leber, Markus, Li, Shuo, Mather, Karen A, Melle, Ingrid, Morris, Derek, Oldmeadow, Christopher, Palviainen, Teemu, Payton, Antony, Pazoki, Raha, Petrovic, Katja, Reynolds, Chandra A, Sargurupremraj, Muralidharan, Scholz, Markus, Smith, Jennifer A, Smith, Albert V, Terzikhan, Natalie, Thalamuthu, Anbupalam, Trompet, Stella, van der Lee, Sven J, Ware, Erin B, Windham, B Gwen, Wright, Margaret J, Yang, Jingyun, Yu, Jin, Ames, David, Amin, Najaf, Amouyel, Philippe, Andreassen, Ole A, Armstrong, Nicola J, Assareh, Amelia A, Attia, John R, Attix, Deborah, Avramopoulos, Dimitrios, Bennett, David A, Böhmer, Anne C, Boyle, Patricia A, Brodaty, Henry, Campbell, Harry, Cannon, Tyrone D, Cirulli, Elizabeth T, Congdon, Eliza, Conley, Emily Drabant, Corley, Janie, Cox, Simon R, Dale, Anders M, Dehghan, Abbas, Dick, Danielle, Dickinson, Dwight, Eriksson, Johan G, Evangelou, Evangelos, Faul, Jessica D, Ford, Ian, Freimer, Nelson A, Gao, He, Giegling, Ina, Gillespie, Nathan A, Gordon, Scott D, Gottesman, Rebecca F, Griswold, Michael E, Gudnason, Vilmundur, Harris, Tamara B, Hartmann, Annette M, Hatzimanolis, Alex, Heiss, Gerardo, Holliday, Elizabeth G, Joshi, Peter K, Kähönen, Mika, Kardia, Sharon LR, Karlsson, Ida, and Kleineidam, Luca

Abstract

Christina M. Lill, who contributed to analysis of data, was inadvertently omitted from the author list in the originally published version of this article. This has now been corrected in both the PDF and HTML versions of the article.

Published
2019

5. Study of 300,486 individuals identifies 148 independent genetic loci influencing general cognitive function.

Author

Davies, Gail, Lam, Max, Harris, Sarah E, Trampush, Joey W, Luciano, Michelle, Hill, W David, Hagenaars, Saskia P, Ritchie, Stuart J, Marioni, Riccardo E, Fawns-Ritchie, Chloe, Liewald, David CM, Okely, Judith A, Ahola-Olli, Ari V, Barnes, Catriona LK, Bertram, Lars, Bis, Joshua C, Burdick, Katherine E, Christoforou, Andrea, DeRosse, Pamela, Djurovic, Srdjan, Espeseth, Thomas, Giakoumaki, Stella, Giddaluru, Sudheer, Gustavson, Daniel E, Hayward, Caroline, Hofer, Edith, Ikram, M Arfan, Karlsson, Robert, Knowles, Emma, Lahti, Jari, Leber, Markus, Li, Shuo, Mather, Karen A, Melle, Ingrid, Morris, Derek, Oldmeadow, Christopher, Palviainen, Teemu, Payton, Antony, Pazoki, Raha, Petrovic, Katja, Reynolds, Chandra A, Sargurupremraj, Muralidharan, Scholz, Markus, Smith, Jennifer A, Smith, Albert V, Terzikhan, Natalie, Thalamuthu, Anbupalam, Trompet, Stella, van der Lee, Sven J, Ware, Erin B, Windham, B Gwen, Wright, Margaret J, Yang, Jingyun, Yu, Jin, Ames, David, Amin, Najaf, Amouyel, Philippe, Andreassen, Ole A, Armstrong, Nicola J, Assareh, Amelia A, Attia, John R, Attix, Deborah, Avramopoulos, Dimitrios, Bennett, David A, Böhmer, Anne C, Boyle, Patricia A, Brodaty, Henry, Campbell, Harry, Cannon, Tyrone D, Cirulli, Elizabeth T, Congdon, Eliza, Conley, Emily Drabant, Corley, Janie, Cox, Simon R, Dale, Anders M, Dehghan, Abbas, Dick, Danielle, Dickinson, Dwight, Eriksson, Johan G, Evangelou, Evangelos, Faul, Jessica D, Ford, Ian, Freimer, Nelson A, Gao, He, Giegling, Ina, Gillespie, Nathan A, Gordon, Scott D, Gottesman, Rebecca F, Griswold, Michael E, Gudnason, Vilmundur, Harris, Tamara B, Hartmann, Annette M, Hatzimanolis, Alex, Heiss, Gerardo, Holliday, Elizabeth G, Joshi, Peter K, Kähönen, Mika, Kardia, Sharon LR, Karlsson, Ida, and Kleineidam, Luca

Subjects
Humans, Neurodegenerative Diseases, Genetic Predisposition to Disease, Cognition, Reaction Time, Mental Disorders, Multifactorial Inheritance, Polymorphism, Single Nucleotide, Adolescent, Adult, Aged, Aged, 80 and over, Middle Aged, Young Adult, Genetic Loci, Neurodevelopmental Disorders, Prevention, Behavioral and Social Science, Mental Health, Neurosciences, Biotechnology, Genetics, Human Genome, Neurological, Mental health
Abstract

General cognitive function is a prominent and relatively stable human trait that is associated with many important life outcomes. We combine cognitive and genetic data from the CHARGE and COGENT consortia, and UK Biobank (total N = 300,486; age 16-102) and find 148 genome-wide significant independent loci (P

Published
2018

12. The Association between Socioeconomic Status and Cognitive Development in Children Is Partly Mediated by a Chaotic Home Atmosphere

Author

Seidler, Anna Lene and Ritchie, Stuart J.

Abstract

There are socioeconomic-status (SES) differences in cognitive development. Various factors have been proposed that might explain this association, and one of these factors is the home environment. The present study examined a chaotic home atmosphere as a potential mediator of the association between parental SES and cognitive development. A nationally representative sample of children in the United Kingdom was studied when children were 3 years (n = 15,590), 5 years (n = 13,802), and 7 years old (n = 12,661). At each wave, the children completed multiple cognitive tests, and parents provided information on their SES (income, education, and occupation) and the home atmosphere. Mediation effects were tested with longitudinal structural equation modeling. Direct relations between parental SES and cognitive ability were partly mediated by the home atmosphere. The proportion of mediation was 16% for the change in cognitive ability predicted by parental SES. This study suggests that a chaotic home atmosphere might partly explain the association between parental SES and cognitive development.

Published
2018
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18. Brain structural differences between 73- and 92-year olds matched for childhood intelligence, social background, and intracranial volume

Author

Ritchie, Stuart J., Dickie, David Alexander, Cox, Simon R., Valdés Hernández, Maria del C., Sibbett, Ruth, Pattie, Alison, Anblagan, Devasuda, Redmond, Paul, Royle, Natalie A., Corley, Janie, Maniega, Susana Muñoz, Taylor, Adele M., Karama, Sherif, Booth, Tom, Gow, Alan J., Starr, John M., Bastin, Mark E., Wardlaw, Joanna M., and Deary, Ian J.

Published
2018
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28. Genetic variants linked to education predict longevity

Author

Social Science Genetic Association Consortium, Marioni, Riccardo E., Ritchie, Stuart J., Joshi, Peter K., Hagenaars, Saskia P., Okbay, Aysu, Fischer, Krista, Adams, Mark J., Hill, W. David, Davies, Gail, Nagy, Reka, Amador, Carmen, Läll, Kristi, Metspalu, Andres, Liewald, David C., Campbell, Archie, Wilson, James F., Hayward, Caroline, Esko, Tõnu, Porteous, David J., Gale, Catharine R., and Deary, Ian J.

Published
2016

30. Is Education Associated with Improvements in General Cognitive Ability, or in Specific Skills?

Author

Ritchie, Stuart J., Bates, Timothy C., and Deary, Ian J.

Abstract

Previous research has indicated that education influences cognitive development, but it is unclear what, precisely, is being improved. Here, we tested whether education is associated with cognitive test score improvements via domain-general effects on general cognitive ability ("g"), or via domain-specific effects on particular cognitive skills. We conducted structural equation modeling on data from a large (n = 1,091), longitudinal sample, with a measure of intelligence at age 11 years and 10 tests covering a diverse range of cognitive abilities taken at age 70. Results indicated that the association of education with improved cognitive test scores is not mediated by "g," but consists of direct effects on specific cognitive skills. These results suggest a decoupling of educational gains from increases in general intellectual capacity.

Published
2015
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31. Does Learning to Read Improve Intelligence? A Longitudinal Multivariate Analysis in Identical Twins from Age 7 to 16

Author

Ritchie, Stuart J., Bates, Timothy C., and Plomin, Robert

Abstract

Evidence from twin studies points to substantial environmental influences on intelligence, but the specifics of this influence are unclear. This study examined one developmental process that potentially causes intelligence differences: learning to read. In 1,890 twin pairs tested at 7, 9, 10, 12, and 16 years, a cross-lagged monozygotic-differences design was used to test for associations of earlier within-pair reading ability differences with subsequent intelligence differences. The results showed several such associations, which were not explained by differences in reading exposure and were not restricted to verbal cognitive domains. The study highlights the potentially important influence of reading ability, driven by the nonshared environment, on intellectual development and raises theoretical questions about the mechanism of this influence.

Published
2015
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34. Brain cortical characteristics of lifetime cognitive ageing

Author

Cox, Simon R., Bastin, Mark E., Ritchie, Stuart J., Dickie, David Alexander, Liewald, Dave C., Muñoz Maniega, Susana, Redmond, Paul, Royle, Natalie A., Pattie, Alison, Valdés Hernández, Maria, Corley, Janie, Aribisala, Benjamin S., McIntosh, Andrew M., Wardlaw, Joanna M., and Deary, Ian J.

Published
2017
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38. Epigenetic prediction of complex traits and death

Author

McCartney, Daniel L., Hillary, Robert F., Stevenson, Anna J., Ritchie, Stuart J., Walker, Rosie M., Zhang, Qian, Morris, Stewart W., Bermingham, Mairead L., Campbell, Archie, Murray, Alison D., Whalley, Heather C., Gale, Catharine R., Porteous, David J., Haley, Chris S., McRae, Allan F., Wray, Naomi R., Visscher, Peter M., McIntosh, Andrew M., Evans, Kathryn L., Deary, Ian J., and Marioni, Riccardo E.

Published
2018
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40. Irlen Colored Filters in the Classroom: A 1-Year Follow-Up

Author

Ritchie, Stuart J., Della Sala, Sergio, and McIntosh, Robert D.

Abstract

Colored filters are used to treat Irlen syndrome (IS), a controversial disorder posited to be the cause of a substantial proportion of reading difficulties. Previously, we found that Irlen colored filters do not produce any short-term alleviation of reading difficulties in schoolchildren aged 7-12. Here, we tested whether colored filters show benefits with longer-term use, in a subset of the original sample. We measured reading rate with and without filters in 18 children diagnosed with IS, who had been using the filters for 1 year, and compared the progression of their reading ability across the year against 10 poor-reader control children. The Irlen-treatment group did not read any faster when using their colored filter, and showed no disproportionate gain in reading progress across the year compared to controls. We conclude that Irlen filters do not benefit reading, even after 1 year of use.

Published
2012
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41. The Relationship between Intelligence and Multiple Domains of Religious Belief: Evidence from a Large Adult US Sample

Author

Lewis, Gary J., Ritchie, Stuart J., and Bates, Timothy C.

Abstract

High levels of religiosity have been linked to lower levels of intelligence in a number of recent studies. These results have generated both controversy and theoretical interest. Here in a large sample of US adults we address several issues that restricted the generalizability of these previous results. We measured six dimensions of religiosity (rather than just one or two), along with a multi-scale instrument to assess general intelligence. We also controlled for the influence of the personality trait openness on facets of religious belief and practice. The results indicated that lower intelligence is most strongly associated with higher levels of fundamentalism, but also modestly predicts central components of religiosity such as a sense of religious identification and private religious practice. Secondly, we found that a higher level of openness--often assumed to lead to lower religiosity--is weakly associated with reduced fundamentalism but with increased religious mindfulness, private religious practice, religious support, and spirituality. These new results provide a framework for understanding the links between reasoning and faith. (Contains 3 tables.)

Published
2011
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48. Tractable limitations of current polygenic scores do not excuse genetically confounded social science.

Author

Morris, Damien, Ritchie, Stuart J., and Young, Alexander I.

Subjects
*SOCIAL scientists, *EXCUSES
Abstract

Burt's critique of using polygenic scores in social science conflates the "scientific costs" of sociogenomics with "sociopolitical and ethical" concerns. Furthermore, she paradoxically enlists recent advances in controlling for environmental confounding to argue such confounding is scientifically "intractable." Disinterested social scientists should support ongoing efforts to improve this technology rather than obstructing progress and excusing genetically confounded research. [ABSTRACT FROM AUTHOR]

Published
2023
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50. Genomic SEM Provides Insights into the Multivariate Genetic Architecture of Complex Traits

Author

Grotzinger, Andrew D., Rhemtulla, Mijke, de Vlaming, Ronald, Ritchie, Stuart J., Mallard, Travis T., Hill, W. David, Ip, Hill F., Marioni, Riccardo E., McIntosh, Andrew M., Deary, Ian J., Koellinger, Philipp D., Harden, K. Paige, Nivard, Michel G., and Tucker-Drob, Elliot M.

Subjects
Multifactorial Inheritance, Latent Class Analysis, Mental Disorders, Multivariate Analysis, Humans, Genomics, Factor Analysis, Statistical, Polymorphism, Single Nucleotide, Article, Genome-Wide Association Study
Abstract

Genetic correlations estimated from genome-wide association studies (GWASs) reveal pervasive pleiotropy across a wide variety of phenotypes. We introduce genomic structural equation modelling (genomic SEM): a multivariate method for analysing the joint genetic architecture of complex traits. Genomic SEM synthesizes genetic correlations and single-nucleotide polymorphism heritabilities inferred from GWAS summary statistics of individual traits from samples with varying and unknown degrees of overlap. Genomic SEM can be used to model multivariate genetic associations among phenotypes, identify variants with effects on general dimensions of cross-trait liability, calculate more predictive polygenic scores and identify loci that cause divergence between traits. We demonstrate several applications of genomic SEM, including a joint analysis of summary statistics from five psychiatric traits. We identify 27 independent single-nucleotide polymorphisms not previously identified in the contributing univariate GWASs. Polygenic scores from genomic SEM consistently outperform those from univariate GWASs. Genomic SEM is flexible and open ended, and allows for continuous innovation in multivariate genetic analysis.

Published
2019

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