Statistical analysis was performed using SPSS 26.0 (IBM Corp, Armonk, NY) and Prism v7 and v8 (Graph-Pad Software, La Jolla, CA). The ROUT method [38 (link)] was used to detect outliers by directly controlling for false discoveries, with a maximum False Discovery Rate set to Q=1%. Outliers were removed from each amyloid-beta or p-tau group studied, across pathologic disease groups, but were retained for linear regressions which utilized rank-based normalization.
Relative amounts of Aβ1–38, Aβ1–40, Aβ1–42, p-tau181, p-tau202, p-tau231, p-tau396 were computed by dividing each data point by the mean of the control group. An analysis of covariance (ANCOVA) was used to adjust for age at death and compare differences of each analyte between CTE pathology groups and, separately, AD pathology groups. The p-tau202:p-tau396 ratio was compared between CTE and AD pathology groups. Statistical significance was determined at p<0.05. Tau epitope and Aβ levels, as well as total years of contact sports play underwent rank-based normalization for regression analyses [39 (link)]. Multiple linear regression analyses were used to evaluate associations between p-tau and predictors total years of playing contact sports and Aβ1–42 levels, adjusting for age at death and sex. Two separate regression models were run, in order to separately examine CTE (excluding AD) and AD (excluding CTE).