Extended Data Fig. 4: Disease stratified analysis on comparing pQTLs effect size.
To investigate of disease status effect on pQTLs, we performed linear regression on the same protein-loci pairs (before conditioning on top variants) identified from above default model using three additional models: a, joint analysis but with disease status as another covariate (CO vs non-CO). Pearson correlation coefficient was 0.999 (p-value < 2.2 × 10-16, 95%CI = 0.999 to 0.999), 0.999 (p-value = 4.3 × 10-202, 95%CI = 0.999 to 0.999), 0.999 (p-value = 9.5 × 10-52, 95%CI = 0.999 to 0.999) for CSF, plasma, and brain respectively. Sample size for this joint analysis was 835, 529, and 380 for CSF, plasma, and brain respectively. b, AD case (CA) only using the same covariates as default model. Pearson correlation coefficient of 0.991 (p-value = 3.9 × 10-160, 95%CI = 0.988 to 0.993), 0.989 (p-value = 1.8 × 10-83, 95%CI = 0.983 to 0.992), 0.998 (p-value = 2.4 × 10-29, 95%CI = 0.995 to 0.999) for CSF, plasma, and brain respectively. Sample size for this AD case (CA) only analysis was 217, 168, and 248 for CSF, plasma, and brain respectively. c, Cognitive unimpaired (CO) only using the same covariates as default model. Pearson correlation coefficient of 0.999 (p-value = 5.2 × 10-234, 95%CI = 0.998 to 0.999), 0.998 (p-value = 1.17 × 10-122, 95%CI = 0.997 to 0.999), 0.602 (p-value = 0.002, 95%CI = 0.262 to 0.809) for CSF, plasma, and brain respectively. Sample size for this cognitive unimpaired (CO) only analysis was 614, 357, and 24 for CSF, plasma, and brain respectively. The relatively low correlation in default model comparison with control only in brain samples was due to much smaller sample size as a control for brain samples. All statistical tests used were two-sided from (a) to (c).
