1 × 10−10 are available in this data set) and matched the selected probes with those in the other data sets (the number of matched probes ranged from 4892 to 6561) (Supplementary Table 4). The correlation of cis-mQTL effects between two brain samples (ROSMAP and Jaffe et al.) was very strong (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\hat r_b = 0.92$$\end{document}r^b=0.92 and s.e. = 0.002), similar to that between two blood samples (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\hat r_b = 0.92$$\end{document}r^b=0.92 between BSGS and LBC with s.e. = 0.003) (Fig. 4a). It is of note that both estimates of rb were smaller than unity, reflecting some degree of heterogeneity between studies. The mean brain–blood rb estimate from two samples was 0.78 (s.e. = 0.006) (Fig. 4a), higher than that for cis-eQTLs (mean \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\hat r_b = 0.70$$\end{document}r^b=0.70 and s.e. = 0.015) shown above (Fig. 1). The result remained largely unchanged if the cis-mQTLs were selected at PmQTL < 5 × 10−8 in the LBC data (Supplementary Fig. 15), again showing the robustness of our results to the choice of reference tissue. In addition, of the
