We set out to develop an efficient machine learning pipeline that could harness the potential of a broad panel of fluid AD biomarkers, including Aβ42/Aβ40, different P-tau variants, GFAP and NFL, to predict Aβ-PET standardized uptake volume ratio (SUVR). The gene discussed is GFAP; the disease is Alzheimer disease.