Amyloid-β misfolding as a plasma biomarker indicates risk for future clinical Alzheimer's disease in individuals with subjective cognitive decline.

Background: We evaluated Aβ misfolding in combination with Aβ ratio as a prognostic tool for future clinical progression to mild cognitive impairment (MCI) or dementia due to Alzheimer's disease (AD) in individuals with subjective cognitive decline (SCD).

Methods: Baseline plasma samples (n = 203) from SCD subjects in the SCIENCe project and Amsterdam Dementia Cohort (age 61 ± 9 years; 57% male, mean follow-up time 2.7 years) were analyzed using immuno-infrared-sensor technology. Within 6 years of follow-up, 22 (11%) individuals progressed to MCI or dementia due to AD. Sensor readout values > 1646 cm reflected normal Aβ folding; readouts at ≤ 1646 cm reflected low and at < 1644 cm high misfolding. We used Cox proportional hazard models to quantify Aβ misfolding as a prognostic biomarker for progression to MCI and dementia due to AD. The accuracy of the predicted development of MCI/AD was determined by time-dependent receiver operating characteristic (t-ROC) curve analyses that take individual follow-up and conversion times into account. Statistical models were adjusted for age, sex, and APOEε4 status. Additionally, plasma Aβ data measured by SIMOA were statistically analyzed and compared.

Results: All 22 patients who converted to MCI or AD-dementia within 6 years exhibited Aβ misfolding at baseline. Cox analyses revealed a hazard ratio (HR) of 19 (95% confidence interval [CI] 2.2-157.8) for future conversion of SCD subjects with high misfolding and of 11 (95% CI 1.0-110.1) for those with low misfolding. T-ROC curve analyses yielded an area under the curve (AUC) of 0.94 (95% CI 0.86-1.00; 6-year follow-up) for Aβ misfolding in an age, sex, and APOEε4 model. A similar model with plasma Aβ ratio yielded an AUC of 0.92 (95% CI, 0.82-1.00). The AUC increased to 0.99 (95% CI, 0.99-1.00) after inclusion of both Aβ misfolding and the Aβ ratio.

Conclusions: A panel of structure- and concentration-based plasma amyloid biomarkers may predict conversion to clinical MCI and dementia due to AD in cognitively unimpaired subjects. These plasma biomarkers provide a noninvasive and cost-effective alternative for screening early AD pathological changes. Follow-up studies and external validation in larger cohorts are in progress for further validation of our findings.