In this exploratory neuroimaging-proteomic study, we aimed to identify CSF
proteins associated with AD and test their prognostic ability for disease classification and MCI to AD conversion prediction. Our study sample consisted of 295 subjects with CSF multi-analyte panel data and MRI at baseline downloaded from ADNI. Firstly, we tested the statistical effects of CSF
proteins (n = 83) to measures of brain
atrophy, CSF
biomarkers,
ApoE genotype and
cognitive decline. We found that several
proteins (primarily CgA and FABP) were related to either brain
atrophy or CSF
biomarkers. In relation to
ApoE genotype, a unique biochemical profile characterised by low CSF levels of
Apo E was evident in ε4 carriers compared to ε3 carriers. In an exploratory analysis, 3/83
proteins (
SGOT, MCP-1, IL6r) were also found to be mildly associated with
cognitive decline in MCI subjects over a 4-year period. Future studies are warranted to establish the validity of these
proteins as prognostic factors for
cognitive decline. For disease classification, a subset of
proteins (n = 24) combined with MRI measurements and CSF
biomarkers achieved an accuracy of 95.1% (Sensitivity 87.7%; Specificity 94.3%; AUC 0.95) and accurately detected 94.1% of MCI subjects progressing to AD at 12 months. The subset of
proteins included FABP, CgA, MMP-2, and PPP as strong predictors in the model. Our findings suggest that the marker of panel of
proteins identified here may be important candidates for improving the earlier detection of AD. Further targeted proteomic and longitudinal studies would be required to validate these findings with more generalisability.