Equity and Transportability of Plasma ATN Phenotypes in a Population-Representative U.S. Aging Cohort

INTRODUCTIONPlasma biomarkers for Alzheimers disease (AD) pathology promise scalable diagnostic access, yet their performance in diverse, population-representative cohorts remains uncharacterized. We evaluated equity and transportability of plasma amyloid-tau-neurodegeneration (ATN) biomarkers in a nationally representative U.S. aging cohort. METHODSCross-sectional analysis of 4,427 adults aged [&ge;]50 years from the 2016 Health and Retirement Study Venous Blood Study. Plasma biomarkers (A{beta}42/40, pTau181, NfL, GFAP) were classified using established ATN criteria. Survey weights produced population-representative estimates. Outcomes included biomarker-cognition associations, fairness metrics (sensitivity, specificity, predictive values) stratified by race/ethnicity and sex, and education-stratified analyses. RESULTSAmong 4,427 participants representing 36.6 million U.S. adults (weighted: 68 years, 55% female, 79% White), survey-weighted analysis revealed tau as the only biomarker maintaining robust cognitive associations ({beta}=-0.74, p<0.001), while amyloid ({beta}=0.11, p=0.43) and neurodegeneration ({beta}=-0.27, p=0.08) lost significance. White participants demonstrated 12-percentage-point higher sensitivity than Black participants (23.4% vs. 11.4%), with Black women showing lowest sensitivity (8.8%). Educational attainment modified biomarker effects: low-education groups showed paradoxical positive amyloid associations ({beta}=0.74, p=0.01) and amplified neurodegeneration effects ({beta}=-1.02, p=0.006). Race-specific optimal cutpoints differed by 40%. Vascular comorbidity burden was higher in Black (82%) and Hispanic (73%) versus White (65%) participants, yet associations persisted after vascular adjustment. DISCUSSIONPlasma ATN biomarkers demonstrate significant equity gaps and differential transportability across demographic subgroups. The 12-percentage-point sensitivity disparity and education-dependent effect modification highlight barriers to equitable implementation. Population-based validation with fairness metrics should be prerequisite for clinical deployment.