Fig. 4: Effects of distinct risk loci for LOAD converge on the protein TREM2.
From: Coding and regulatory variants are associated with serum protein levels and disease
a The Manhattan plot highlights variants at two distinct chromosomes associated with serum TREM2 levels. Study-wide significant associations (linear regressions) at P < 1.92 × 10−10 (two-sided) are indicated by the horizontal line. The y-axis shows the −(log10) of the P-values for the association of each genetic variant on the exome array present along the x-axis. Variants at both chromosomes 6 and 11 associated with TREM2 have been independently linked to risk of LOAD including the rs75932628 (NP_061838.1: p.R47H) in TREM2 at chromosome 6 and the variant rs610932 at chromosome 11. b The boxplot to the left shows that carriers with the p.R47H mutation, which is linked to LOAD, are associated with low TREM2 levels. The boxplot on the right shows the trans effect of the well-established GWAS risk variant rs610932 for LOAD on TREM2 serum levels, where the LOAD risk allele C (highlighted in bold) is associated with lower levels of TREM2. The x-axis of each box plot shows the genotypes for the corresponding protein-associated SNP, while the y-axis denotes the Box–Cox transformed, age, and sex-adjusted serum protein levels. Box plots indicate median (middle line), 25th, 75th percentile (box), and 5th and 95th percentile (whiskers). The P-values (two-sided) shown at the top of each plot come from linear regression analysis. c TREM2p.R47H carriers demonstrated lower survival probability post-incident LOAD compared to TREM2p.R47R carriers (P = 0.04, two-sided). The vertical ticks correspond to individuals lost to follow-up. d Scatterplot for the TREM2 protein supported as having a causal effect on LOAD in a two-sample MR analysis. The figure demonstrates the estimated effects of the respective cis- and trans-acting genetic instruments on the serum TREM2 levels in AGES-RS (x-axis) and risk of LOAD through a GWAS by Kunkle et al.32 (y-axis), using 21,982 LOAD cases and 41,944 controls. Each data point displays the estimated effect as beta coefficient = log(odds ratio), along with 95% confidence intervals for the SNP effect on disease (vertical lines) or SNP effect on the protein (horizontal lines). The broken line indicates the inverse variance weighted causal estimate (β = −0.240, SE = 0.059, P = 5.3 × 10−5, two-sided), while the dotted line shows the MR-Egger regression (see Supplementary Data 5 for more details).
