Combining MRI-Derived Imaging Measures and Peripheral Proteomics to Improve the Mechanistic Understanding of...

Alzheimer's Disease (AD) core pathology involves amyloidβ and ptau, leading to neurodegeneration (ATN model), yet individuals with comparable core pathology show considerable biological and clinical heterogeneity, motivating new models that consider non-specific processes and co-pathology. MRI and peripheral proteomics offer complementary, non-invasive approaches for capturing biological variation beyond core pathology, and many researchers have begun integrating them. However, no systematic overview of this literature exists. This scoping review evaluated studies combining MRI and peripheral plasma proteomics in AD within revised diagnostic frameworks, summarizing strengths and gaps.

Following PRISMA 2020 guidelines, PubMed, Embase, and Scopus were searched through June 14, 2023, yielding 3,185 records; 63 studies met the inclusion criteria. For each study, study design, participant characteristics, proteomic platforms, imaging modalities, statistical approaches, and significant associations between non-core-pathological proteins and MRIderived measures were extracted.

Across studies, methodological variability was high. Grey matter volume was the most commonly examined imaging metric, followed by cerebrovascular dysfunction, cortical thickness, white-matter and whole-brain volume, and connectivity measures. Overall, 127 non-core-pathology proteins, mostly related to inflammation/immune function, were associated with MRI metrics, though only three appeared in five or more studies. Roughly half of the studies incorporated core AD biomarkers.

This scoping review of 63 studies demonstrates that integrating peripheral proteomics with MRI is an increasingly common approach in AD research, with GFAP, CRP, and IL-6 as the most frequently reported proteins, and grey matter volume and vascular dysfunction as the most commonly examined imaging phenotypes. However, effect sizes are generally modest, findings are heterogeneous, and many studies lack core AD biomarkers, highlighting the need for greater methodological consensus and more mechanistic, multimodal, and longitudinal research.

Integrating MRI and peripheral proteomics is increasingly common in AD research, but consensus on analytic and imaging approaches is limited. Heterogeneity in proteomic platforms and statistical methods constrains comparability; most associations are modest, and observational designs limit causal inference. Future work should emphasize methodological harmonization, reproducibility, multivariate and machine-learning approaches, and randomized trials to test mechanistic pathways.