Glial and Vascular Plasma Biomarkers Across the Alzheimer's Disease Continuum: An ADNI-Based Longitudinal Study

Alzheimer's disease (AD) is increasingly recognized as a multicellular disorder involving neurovascular unit dysfunction. Investigating glial and vascular biomarkers together may provide a more integrated view of AD biology. This study characterized baseline distributions, interrelationships, and longitudinal trajectories of plasma glial (GFAP, sTREM2) and vascular/endothelial (VEGF, sICAM-1, sVCAM-1) biomarkers across the AD continuum. Using Alzheimer's Disease Neuroimaging Initiative (ADNI) data, this retrospective longitudinal cohort study included a covariate-complete clinical cohort of 2650 participants classified as cognitively unimpaired (CU), mild cognitive impairment (MCI), or AD dementia. Biomarker-specific analytic samples were determined by assay availability and complete-case requirements. Associations were evaluated using covariate-adjusted linear regression and linear mixed-effects models with participant random intercepts, adjusted for baseline age, sex, education, and APOE ε4 status. Vascular models were additionally refitted with body mass index, systolic blood pressure, antihypertensive and antidiabetic medication use, smoking history, and estimated glomerular filtration rate. Baseline GFAP showed a robust stepwise elevation from CU to MCI to AD (56.3% higher in AD than CU, q = 1.7 × 10^-14; area under the curve 0.82), whereas sTREM2 distributions overlapped across groups. VEGF and sVCAM-1 were higher in AD than CU (14.1%, q = 0.014; 14.7%, q = 0.002), with areas under the curve of 0.61 and 0.63 and more than 80% distribution overlap. GFAP increased by 4.50% per year in CU participants and sTREM2 by 2.99% per year, with no significant diagnosis-by-time interactions for either. Over a 12-month interval, sICAM-1 declined in CU participants, and this decline was attenuated in MCI and AD, while sVCAM-1 increased in CU participants and showed negative diagnosis-by-time interactions. The vascular longitudinal findings were unchanged by adjustment for cardiometabolic and renal covariates, by time-varying diagnosis, and by separating stable MCI from MCI-to-AD converters. Correlations among vascular markers were consistent and well estimated, whereas glial-vascular correlations were based on 64 to 94 overlapping participants and were not significant. Glial and vascular plasma biomarkers did not progress synchronously across the AD continuum. GFAP showed the strongest and most discriminating diagnosis-associated elevation. Vascular markers showed statistically robust but small group-level differences with no individual-level discriminative utility, and their divergent 12-month trajectories require replication over longer follow-up before they can be interpreted as stage-dependent regulation.