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. 2021 Mar 25;13(1):65.
doi: 10.1186/s13195-021-00805-8.

Plasma neurofilament light and phosphorylated tau 181 as biomarkers of Alzheimer's disease pathology and clinical disease progression

Christopher Clark  1 , Piotr Lewczuk  2   3 , Johannes Kornhuber  2 , Jonas Richiardi  4 , Bénédicte Maréchal  4   5   6 , Thomas K Karikari  7   8 , Kaj Blennow  7   8 , Henrik Zetterberg  7   8   9   10 , Julius Popp  11   12
Affiliations

Plasma neurofilament light and phosphorylated tau 181 as biomarkers of Alzheimer's disease pathology and clinical disease progression

Christopher Clark et al. Alzheimers Res Ther. .

Abstract

Background: To assess the performance of plasma neurofilament light (NfL) and phosphorylated tau 181 (p-tau181) to inform about cerebral Alzheimer's disease (AD) pathology and predict clinical progression in a memory clinic setting.

Methods: Plasma NfL and p-tau181, along with established cerebrospinal fluid (CSF) biomarkers of AD pathology, were measured in participants with normal cognition (CN) and memory clinic patients with cognitive impairment (mild cognitive impairment and dementia, CI). Clinical and neuropsychological assessments were performed at inclusion and follow-up visits at 18 and 36 months. Multivariate analysis assessed associations of plasma NfL and p-tau181 levels with AD, single CSF biomarkers, hippocampal volume, and clinical measures of disease progression.

Results: Plasma NfL levels were higher in CN participants with an AD CSF profile (defined by a CSF p-tau181/Aβ1-42 > 0.0779) as compared with CN non-AD, while p-tau181 plasma levels were higher in CI patients with AD. Plasma NfL levels correlated with CSF tau and p-tau181 in CN, and with CSF tau in CI patients. Plasma p-tau181 correlated with CSF p-tau181 in CN and with CSF tau, p-tau181, Aβ1-42, and Aβ1-42/Aβ1-40 in CI participants. Compared with a reference model, adding plasma p-tau181 improved the prediction of AD in CI patients while adding NfL did not. Adding p-tau181, but not NfL levels, to a reference model improved prediction of cognitive decline in CI participants.

Conclusion: Plasma NfL indicates neurodegeneration while plasma p-tau181 levels can serve as a biomarker of cerebral AD pathology and cognitive decline. Their predictive performance depends on the presence of cognitive impairment.

Keywords: Alzheimer’s; Biomarkers; Neurofilament light; Plasma; p-tau181.

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Conflict of interest statement

PL received consultation and/or lecture honoraria from IBL International, Fujirebio Europe, AJ Roboscreen, and Roche. KB has served as a consultant, at advisory boards, or at data monitoring committees for Abcam, Axon, Biogen, JOMDD/Shimadzu. Julius Clinical, Lilly, MagQu, Novartis, Roche Diagnostics, and Siemens Healthineers, and is a co-founder of Brain Biomarker Solutions in Gothenburg AB (BBS), which is a part of the GU Ventures Incubator Program. HZ has served at scientific advisory boards for Denali, Roche Diagnostics, Wave, Samumed, Siemens Healthineers, Pinteon Therapeutics and CogRx, has given lectures in symposia sponsored by Fujirebio, Alzecure and Biogen, and is a co-founder of Brain Biomarker Solutions in Gothenburg AB (BBS), which is a part of the GU Ventures Incubator Program (outside submitted work). JR owns shares in Siemens healthcare. JP received consultation and speaker honoraria from Nestle Institute of Health Sciences, Innovation Campus, EPFL, Lausanne, Switzerland, Ono Pharma, OM Pharma Suisse and from Fujirebio Europe. The other authors declare no potential conflicts of interest.

Figures

Fig. 1
Fig. 1
Plasma NfL and p-tau181 levels in the cohort. Boxplots of plasma NfL (a) and p-tau181 (b) concentrations in cognitively healthy participants (CN) and patients with cognitive impairment (CI). Both groups were further stratified according to AD CSF biomarker profile. Mean concentrations between pairs of groups were compared using T-tests. *, p-value < 0.05; ***, p-value < 0.001
Fig. 2
Fig. 2
Models for the prediction of AD. a-b Binomial logistic regression models with the presence of AD pathology as dependent variable along with sex, age, years of education, APOE ε4 carrier status, plasma NfL and plasma p-tau181 levels, with no variable selection (a) or backwards variable selection (b). Coefficients (B) and odds-ratio (Exp(B)) are shown. c ROC curves from predictive models of the presence of AD in CI participants. The reference model (blue) and the reference model with p-tau-181 levels (red) are shown. The 0.5 AUC reference line is shown in green. ROC curves for CN participants for either models are not shown. d AUC of ROC curves obtained by the reference model (Reference) and after adding plasma NfL (+NFL) or p-tau181 levels (+PTAU) in both the CN and CI groups. *, p-value < 0.05
Fig. 3
Fig. 3
Models for the prediction of cognitive change. a-b Linear regression models with changes in cognition at last follow-up as a dependent variable along with sex, age, years of education, APOE ε4 carrier status, Baseline cognitive score, time to follow-up plasma NfL and plasma p-tau181 levels, with no variable selection (a) or backwards variable selection (b). Standardized coefficients, where the variances of dependent and independent variables are equal to 1 (Coeff.) and p-values are shown. c ROC curves from predictive models of the presence of MMSE change in CI participants. The reference model (blue) and the reference model with p-tau181 levels (red) are shown. The 0.5 AUC reference line is shown in green. ROC curves for CN participants for either models are not shown. d AUC of ROC curves obtained by the reference model (Reference) and after adding plasma NfL (+NFL) or plasma p-tau181 levels (+PTAU) in both the CN and CI groups. *, p-value < 0.05
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