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Lam et al. (2018) respond to a commentary of their paper entitled 'Large-Scale Cognitive GWAS Meta-Analysis Reveals Tissue-Specific Neural Expression and Potential Nootropic Drug Targets' Lam et al. (2017). While Lam et al. (2018) have now provided the recommended quality control metrics for their paper, problems remain. Specifically, Lam et al. (2018) do not dispute that the results of their multi-trait analysis of genome-wide association study (MTAG) analysis has produced a phenotype with a genetic correlation of one with three measures of education, but do claim the associations found are specific to the trait of cognitive ability. In this brief paper, it is empirically demonstrated that the phenotype derived by Lam et al. (2017) is more genetically similar to education than cognitive ability. In addition, it is shown that of the genome-wide significant loci identified by Lam et al. (2017) are loci that are associated with education rather than with cognitive ability.

Acknowledgements We thank the cohort participants who contributed to these studies and the research staff who collected phenotypic data. Genotyping of the CAGES cohorts and the analyses conducted here were supported by the UK's Biotechnology and Biological Sciences Research Council (BBSRC). Phenotype collection in the Lothian Birth Cohort 1921 was supported by the BBSRC, The Royal Society and The Chief Scientist Office of the Scottish Government. Phenotype collection in the Lothian Birth Cohort 1936 was supported by Research Into Ageing (continues as part of Age UK's The Disconnected Mind project). Phenotype collection in the Aberdeen Birth Cohort 1936 was supported by BBSRC, the Wellcome Trust and Alzheimer's Research UK. Phenotype collection in the Manchester and Newcastle Longitudinal Studies of Cognitive Ageing cohorts was supported by Social Science Research Council, Medical Research Council, Economic and Social Research Council, Research Into Ageing, Wellcome Trust and Unilever plc. The work was undertaken in The University of Edinburgh Centre for Cognitive Ageing and Cognitive Epidemiology, part of the cross council Lifelong Health and Wellbeing Initiative (MR/K026992/1). Funding from the BBSRC, EPSRC, ESRC and MRC is gratefully acknowledged. Authors MJ Wright, N K Hansell, SE Medland, NG Martin, and GW Montgomery would like to acknowledge and thank their twin sample for their participation; the Australian Research Council (ARC) for supporting data collection (A7960034, A79906588, A79801419, DP0212016, DP0343921, DP0664638, DP1093900), and the National Health & Medical Research Council (NHMRC) for funding genotyping (Medical Bioinformatics Genomics Proteomics Programme, 389891). SE Medland is supported by an ARC Future Fellowship. Statistical analyses were carried out on the GenEpi Cluster which is financially supported by contributions from grants from the NHMRC (389892;496682;496688;496739;613672) and ARC (FT0991022;FT0991360). ; Peer reviewed ; Publisher PDF