Investigating the combination of plasma amyloid-beta and geroscience biomarkers on the incidence of clinically meaningful cognitive decline in older adults

Abstract

We investigated combining a core AD neuropathology measure (plasma amyloid-beta [Aβ] _42/40) with five plasma markers of inflammation, cellular stress, and neurodegeneration to predict cognitive decline. Among 401 participants free of dementia (median [IQR] age, 76 [73-80] years) from the Multidomain Alzheimer Preventive Trial (MAPT), 28 (7.0%) participants developed dementia, and 137 (34.2%) had worsening of clinical dementia rating (CDR) scale over 4 years. In the models utilizing plasma Aβ alone, a tenfold increased risk of incident dementia (nonsignificant) and a fivefold increased risk of worsening CDR were observed as each nature log unit increased in plasma Aβ levels. Models incorporating Aβ plus multiple plasma biomarkers performed similarly to models included Aβ alone in predicting dementia and CDR progression. However, improving Aβ model performance for composite cognitive score (CCS) decline, a proxy of dementia, was observed after including plasma monocyte chemoattractant protein 1 (MCP1) and growth differentiation factor 15 (GDF15) as covariates. Participants with abnormal Aβ, GDF15, and MCP1 presented higher CCS decline (worsening cognitive function) compared to their normal-biomarker counterparts (adjusted β [95% CI], - 0.21 [- 0.35 to - 0.06], p = 0.005). In conclusion, our study found limited added values of multi-biomarkers beyond the basic Aβ models for predicting clinically meaningful cognitive decline among non-demented older adults. However, a combined assessment of inflammatory and cellular stress status with Aβ pathology through measuring plasma biomarkers may improve the evaluation of cognitive performance.

Keywords: Aging; Alzheimer’s disease; Amyloid-beta; Cognitive decline; Inflammation; Neurodegeneration.

Fig. 1

Hazard ratios of incident dementia according to the amyloid model (A) and the multi-biomarker model with the highest Harrell’s C index (B). The inverse of the HR point estimate and the 95% confidence interval are presented for plasma Aβ_42/40 (HR per unit decrease in the nature log of Aβ_42/40 ratio)

Fig. 2

Hazard ratios of worsening CDR according to the amyloid model (A) and the multi-biomarker models with the highest Harrell’s C indices (B and C). The inverse of the HR point estimate and the 95% confidence interval are presented for plasma Aβ_42/40 (HR per unit decrease in the nature log of Aβ_42/40 ratio)

Fig. 3

Estimated change of CCS over 1 year (represented by the gray bar) and 4 years (by the orange bar) according to the best-fitting model that included plasma Aβ_42/40, GDF15 and MCP1. The lower quartile was selected as normal (−) and the upper quartile as abnormal (+) for GDF15 and MCP1; for Aβ, the upper quartile was selected as normal (−) and the lower quartile as abnormal (+). *p-value < 0.05. (A) Estimated mean change of CCS over time according to the indicated normal (−) / abnormal (+) biomarker values. (B) Unadjusted difference in CCS change compared to the reference group (Aβ-, GDF15-, MCP1-). (C) Difference in CCS change compared to the reference group with adjustment for age, sex, education, MAPT group, and body mass index