Cerebrospinal Fluid Over Plasma Links Analytes to Cognitive Decline in Older Adults at Risk for Alzheimer's Disease

ABSTRACT Objective To identify inflammatory analytes in cerebrospinal fluid (CSF) and plasma associated with cognitive decline in cognitively normal (CN) older adults at risk for Alzheimer's disease (AD). Methods In a longitudinal study of 118 CN older adults (65–80 years, 54% APOE ε4, 26% preclinical AD), 1331 CSF and 1501 plasma analytes were quantified at baseline and 2‐year follow‐up using SomaLogic, with key inflammatory findings validated on the Luminex platform. Linear models (Limma), adjusted for age, sex, APOEε4 , and amyloid‐positive status, identified pathology‐associated analytes. Co‐expression network and multivariable modeling defined hub analytes and enriched pathways. To assess robustness, a targeted panel of 94 inflammation‐related analytes was analyzed using best subsets regression to derive parsimonious models based on adjusted R 2 improvement (≥ 0.01) and ≥ 5 observations per predictor. Subgroup analyses by amyloid and APOE ε4 status were performed, and a two‐stage elastic‐net approach additionally validated analyte selection. Results CSF proteomics revealed stronger APOEε4 and amyloid‐associated analyte signatures than plasma. Forty‐four CSF analytes were co‐regulated by APOEε4 and amyloid‐positive status, forming central network hubs (e.g., EFNB2, NPTN, UNC5D) enriched in axon guidance, synaptic signaling, and extracellular matrix pathways. In contrast, inflammatory analytes including eotaxin‐1 and IL‐17 pathway‐related molecules were associated with longitudinal cognitive decline, with stronger effects observed in females. Eotaxin‐1 demonstrated the most consistent predictive performance across analytic methods, subsets, and assay platforms, whereas network hub analytes were not predictive of cognitive outcomes. Interpretation CSF reflects strong APOEε4 /amyloid related proteomic network alterations linked to cognitive decline, while plasma provides weaker but complementary signals. CSF inflammatory signaling, particularly eotaxin‐1, may serve as a correlate of longitudinal cognitive decline in cognitively normal older adults at risk for AD.

Authors

Institutions

Publication Details

Journal
Annals of Clinical and Translational Neurology
Published
2026-09-17
DOI
https://doi.org/10.1002/acn3.70532
Primary Topic
Alzheimer's disease research and treatments
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
article

Cerebrospinal Fluid Over Plasma Links Analytes to Cognitive Decline in Older Adults at Risk for Alzheimer's Disease

Feixiong Cheng, Chunxuan Ma, Frank P. DiFilippo, Stephen M. Rao et al.
Annals of Clinical and Translational Neurology
Alzheimer's disease research and treatments
article

Cerebrospinal Fluid Over Plasma Links Analytes to Cognitive Decline in Older Adults at Risk for Alzheimer's Disease

Feixiong Cheng, Chunxuan Ma, Frank P. DiFilippo, Stephen M. Rao, Aaron Burberry, James B. Leverenz, Jagan A. Pillai, Lynn M. Bekris, Audrey Zhu, Mikhail Nasrallah, Maria Khrestian, Yifan Yang, Yuan Hou, Ming Wang
article en

Abstract

ABSTRACT Objective To identify inflammatory analytes in cerebrospinal fluid (CSF) and plasma associated with cognitive decline in cognitively normal (CN) older adults at risk for Alzheimer's disease (AD). Methods In a longitudinal study of 118 CN older adults (65–80 years, 54% APOE ε4, 26% preclinical AD), 1331 CSF and 1501 plasma analytes were quantified at baseline and 2‐year follow‐up using SomaLogic, with key inflammatory findings validated on the Luminex platform. Linear models (Limma), adjusted for age, sex, APOEε4 , and amyloid‐positive status, identified pathology‐associated analytes. Co‐expression network and multivariable modeling defined hub analytes and enriched pathways. To assess robustness, a targeted panel of 94 inflammation‐related analytes was analyzed using best subsets regression to derive parsimonious models based on adjusted R 2 improvement (≥ 0.01) and ≥ 5 observations per predictor. Subgroup analyses by amyloid and APOE ε4 status were performed, and a two‐stage elastic‐net approach additionally validated analyte selection. Results CSF proteomics revealed stronger APOEε4 and amyloid‐associated analyte signatures than plasma. Forty‐four CSF analytes were co‐regulated by APOEε4 and amyloid‐positive status, forming central network hubs (e.g., EFNB2, NPTN, UNC5D) enriched in axon guidance, synaptic signaling, and extracellular matrix pathways. In contrast, inflammatory analytes including eotaxin‐1 and IL‐17 pathway‐related molecules were associated with longitudinal cognitive decline, with stronger effects observed in females. Eotaxin‐1 demonstrated the most consistent predictive performance across analytic methods, subsets, and assay platforms, whereas network hub analytes were not predictive of cognitive outcomes. Interpretation CSF reflects strong APOEε4 /amyloid related proteomic network alterations linked to cognitive decline, while plasma provides weaker but complementary signals. CSF inflammatory signaling, particularly eotaxin‐1, may serve as a correlate of longitudinal cognitive decline in cognitively normal older adults at risk for AD.

Annals of Clinical and Translational Neurology
Cleveland Clinic (US), University of Washington (US), Lou Ruvo Brain Institute (US), Cleveland Clinic Lerner College of Medicine (US), VA Puget Sound Health Care System (US), Geriatric Research Education and Clinical Center (US), University School (US), The Neurological Institute (US), Case Western Reserve University (US)
Good health and well-being
Openalex Percentile: Top 12%
Alzheimer's disease research and treatments
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.