Paired CSF–Plasma Analyte Signal Contrasts Across Alzheimer’s Disease Clinical Stages and MCI-to-Dementia Conversion
Yuepeng Deng, Dandan Chen, Haolin Yin, Zihao Lu, Xiaohe Tian, Qiyong GongBackground: Cerebrospinal fluid (CSF) and plasma biomarkers provide complementary information about Alzheimer’s disease (AD), but matched analytes are commonly evaluated separately. We investigated whether relative CSF–plasma analyte signals were associated with AD clinical stage and subsequent conversion from mild cognitive impairment (MCI) to AD dementia. Methods: We analyzed paired CSF and plasma NULISAseq data from 1199 Alzheimer’s Disease Neuroimaging Initiative participants. For 125 shared analyte readouts, ΔNPQ was defined as the within-participant difference between CSF and plasma normalized protein quantifications. Clinical-stage associations were evaluated using covariate-adjusted models. In 547 participants with baseline MCI, we examined subsequent dementia conversion and compared matched CSF-only, plasma-only, ΔNPQ, and joint CSF–plasma representations. Results: Fourteen readouts mapping to eight gene-level targets were associated with more advanced clinical stage after false-discovery-rate correction, involving amyloid/tau, synaptic, astroglial, cholinergic, and neuroaxonal processes. During a median follow-up of 3.0 years, 203 participants with MCI converted to AD dementia. A cross-sectionally derived six-analyte ΔNPQ score was associated with subsequent conversion after adjustment for demographic, genetic, and baseline clinical characteristics (hazard ratio per standard deviation, 1.64; 95% confidence interval, 1.38–1.96). The joint CSF–plasma model yielded the largest estimated improvement in discrimination. After additional adjustment for amyloid/tau biomarkers, the association between ΔNPQ and dementia conversion was attenuated. Conclusions: Relative CSF–plasma analyte patterns are associated with AD clinical stage and subsequent dementia conversion in MCI. Paired-biofluid analysis provides a complementary framework for characterizing disease-associated molecular heterogeneity, rather than a demonstrably superior prognostic model.