Table I. List of variables selected in the Elastic net models. All values were standardized and penalized linear regression models were calculated with the E-net method. Response variables: t-tau, p-tau₁₈₁, Aβ42, or the ratios of Aβ42/t-tau, or Aβ42/p-tau₁₈₁. Explanatory variables: CSF or plasma protein levels together with sex and risk factors for AD APOE genotype and age. For each response a separate model was calculated (Model C1–5 in CSF, P6–8 in plasma) and variables that fitted best into the corresponding model are listed in order of decreasing absolute size of the estimated regression coefficient (RC, indicated in parentheses). RC lies between −0.01 and 0 for variables without a coefficient. Since all variables had been standardized, the RC serves as a measure of the strength for the association between an explanatory variable and its corresponding response variable: the larger RC in absolute value, the higher the association to the response. A RC close to 0 points to a low degree of association between the corresponding variable and the response. For protein nomenclature see supplemental Table S2.

^a Based on the CSF set with 43 subjects, AD n = 25, NDC n = 18 subjects.

^b Based on the training set with 131 subjects, AD n = 52, NDC n = 79 subjects.

^c In model C2 the E-net chose 26 predictors for modeling p-tau_181p with CSF proteins and subjects' characteristics. To avoid overfitting for this model we limited the number of selected variables to eight. The additional 18 variables in order of how they were selected by the E-net here in an extended list: CRP, age, VEGF, SCF, CA19–9, IL-10, IL-5, C3, haptoglobin, TBG, calcitonin, GST, CCL2, α-fetoprotein, PAPP-A, ApoA1, CCL3, IgM.