Association and multimodal model of retinal and blood-based biomarkers for detection of preclinical Alzheimer's disease.

BACKGROUND

The potential diagnostic value of plasma amyloidogenic beta residue 42/40 ratio (Aβ42/Aβ40 ratio), neurofilament light (NfL), tau phosphorylated at threonine-181 (p-tau181), and threonine-217 (p-tau217) has been extensively discussed in the literature. We have also previously described the association between retinal biomarkers and preclinical Alzheimer's disease (AD). The goal of this study was to evaluate the association, and a multimodal model of, retinal and plasma biomarkers for detection of preclinical AD.

METHODS

We included 82 cognitively unimpaired (CU) participants (141 eyes; mean age: 67 years; range: 56-80) from the Atlas of Retinal Imaging in Alzheimer's Study (ARIAS). Blood samples were assessed for concentrations of Aβ42/Aβ40 ratio, NfL, p-tau181, and p-tau217 (ALZpath, Inc.) using Single molecule array (SIMOA) technology. The Spectralis II system (Heidelberg Engineering) was used to acquire macular centered Spectral Domain Optical Coherence Tomography (SD-OCT) images for evaluation of putative retinal gliosis surface area and macular retinal nerve fiber layer (mRNFL) thickness. For all participants, correlations (adjusted for age and correlation between eyes) were assessed between retinal and blood-based biomarkers. A subgroup cohort of 57 eyes from 32 participants with recent Aβ positron emission tomography (PET) results, comprising 18 preclinical patients (Aβ PET + ve, 32 eyes) and 14 controls (Aβ PET -ve, 25 eyes) with a mean age of 69 vs. 66, p = 0.06, was included for the assessment of a multimodal model to distinguish between the two groups. For this subgroup cohort, receiver operating characteristic (ROC) analysis was performed to compare the multimodal model of retinal and plasma biomarkers vs. each biomarker alone to distinguish between the two groups.

RESULTS

Significant correlation was found between putative retinal gliosis and p-tau217 in the univariate mixed model (β = 0.48, p = 0.007) but not for the other plasma biomarkers (p > 0.05). This positive correlation was also retained in the multivariate mixed model (β = 0.43, p = 0.022). The multimodal ROC model based on retinal (gliosis area, inner inferior RNFL thickness, inner superior RNFL thickness, and inner nasal RNFL thickness) and plasma biomarkers (p-tau217 and Aβ42/Aβ40 ratio) had an excellent AUC of 0.97 (95% CI = 0.93-1.01; p < 0.001) compared to unimodal models of retinal and plasma biomarkers.

CONCLUSIONS

Our analyses show the potential of integrating retinal and blood-based biomarkers for improved detection and screening of preclinical AD.