Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2019 Dec 13;9(1):19024.
doi: 10.1038/s41598-019-54204-z.

Predicting clinical decline and conversion to Alzheimer's disease or dementia using novel Elecsys Aβ(1-42), pTau and tTau CSF immunoassays

Kaj Blennow  1   2 , Leslie M Shaw  3 , Erik Stomrud  4   5 , Niklas Mattsson  4   6 , Jon B Toledo  3   7 , Katharina Buck  8 , Simone Wahl  8 , Udo Eichenlaub  8 , Valeria Lifke  8 , Maryline Simon  9 , John Q Trojanowski  3 , Oskar Hansson  10   11
Affiliations

Predicting clinical decline and conversion to Alzheimer's disease or dementia using novel Elecsys Aβ(1-42), pTau and tTau CSF immunoassays

Kaj Blennow et al. Sci Rep. .

Abstract

We evaluated the performance of CSF biomarkers for predicting risk of clinical decline and conversion to dementia in non-demented patients with cognitive symptoms. CSF samples from patients in two multicentre longitudinal studies (ADNI, n = 619; BioFINDER, n = 431) were analysed. Aβ(1-42), tTau and pTau CSF concentrations were measured using Elecsys CSF immunoassays, and tTau/Aβ(1-42) and pTau/Aβ(1-42) ratios calculated. Patients were classified as biomarker (BM)-positive or BM-negative at baseline. Ability of biomarkers to predict risk of clinical decline and conversion to AD/dementia was assessed using pre-established cut-offs for Aβ(1-42) and ratios; tTau and pTau cut-offs were determined. BM-positive patients showed greater clinical decline than BM-negative patients, demonstrated by greater decreases in MMSE scores (all biomarkers: -2.10 to -0.70). Risk of conversion to AD/dementia was higher in BM-positive patients (HR: 1.67 to 11.48). Performance of Tau/Aβ(1-42) ratios was superior to single biomarkers, and consistent even when using cut-offs derived in a different cohort. Optimal pTau and tTau cut-offs were approximately 27 pg/mL and 300 pg/mL in both BioFINDER and ADNI. Elecsys pTau/Aβ(1-42) and tTau/Aβ(1-42) are robust biomarkers for predicting risk of clinical decline and conversion to dementia in non-demented patients, and may support AD diagnosis in clinical practice.

PubMed Disclaimer

Conflict of interest statement

K.B. served as a consultant or at advisory boards for Alzheon, BioArctic, Roche Diagnostics, Eli Lilly, Fujirebio Europe, Merck, Novartis and IBL International. His research team has received funds for research from Roche Diagnostics. He is the co-founder of Brain Biomarker Solutions in Gothenburg AB, a GU Venture-based platform company at the University of Gothenburg. L.M.S. received research support from NIH/NIA, ADNI (AG024904) and UPenn ADCC Biomarker Core (AG010124), MJFox Foundation for PD research, Roche, Lilly; provides QC oversight for Roche Elecsys CSF AD biomarker immunoassays for ADNI; and is a consultant for Roche, Lilly, Novartis. E.S., N.M., J.B.T. and J.Q.T. declare that they have no conflict of interest. S.W., U.E., V.L., M.S., and K.Bu. are Roche employees. O.H. acquired research support (for the institution) from Roche, GE Healthcare, Biogen, AVID Radiopharmaceuticals, Fujirebio and Euroimmun. In the past 2 years, he has received consultancy/speaker fees (paid to the institution) from Lilly, Roche and Fujirebio.

Figures

Figure 1
Figure 1
Model-derived time-course plots of MMSE score (24 months) according to CSF biomarker status. Least square-means with SEs are presented for the ADNI MCI and BioFINDER MCS populations. ADNI (upper panel) cut-offs: pTau/Aβ(1–42), 0.025; tTau/Aβ(1–42), 0.27; Aβ(1–42), 977 pg/mL. BioFINDER (lower panel) cut-offs: pTau/Aβ(1–42), 0.022; tTau/Aβ(1–42), 0.26; Aβ(1–42), 1,100 pg/mL. pTau and tTau cut-offs of 27 pg/mL and 300 pg/mL, respectively, were used in both cohorts. Analyses shown with adjustment for age, sex, years of education but without adjustment for APOEε4 status; number of patients in each biomarker group at baseline is presented. MMSE, Mini-Mental State Examination; CSF, cerebrospinal fluid; pTau, phosphorylated Tau; tTau, total Tau; ADNI, Alzheimer’s Disease Neuroimaging Initiative; BM–, biomarker-negative; BM + , biomarker-positive; SE, standard error; MCI, mild cognitive impairment; MCS, mild cognitive symptoms.
Figure 2
Figure 2
Kaplan-Meier curves for outcome all-cause dementia diagnosis within 6 years, according to CSF biomarker status. Data are presented for the ADNI MCI and BioFINDER MCS populations; number of patients in each biomarker group at each time point is presented. ADNI (upper panel) cut-offs: pTau/Aβ(1–42), 0.025; tTau/Aβ(1–42), 0.27; Aβ(1–42), 977 pg/mL. BioFINDER (lower panel) cut-offs: pTau/Aβ(1–42), 0.022; tTau/Aβ(1–42), 0.26; Aβ(1–42), 1,100 pg/mL. pTau and tTau cut-offs of 27 pg/mL and 300 pg/mL, respectively, were used in both cohorts. CSF, cerebrospinal fluid; ADNI, Alzheimer’s Disease Neuroimaging Initiative; pTau, phosphorylated Tau; tTau, total Tau; BM–, biomarker-negative; BM + , biomarker-positive; MCI, mild cognitive impairment; MCS, mild cognitive symptoms.
Figure 3
Figure 3
Evaluation of pTau and Aβ(1–42) for predicting clinical decline and conversion to all-cause dementia. Model-derived time-course plot (least square-means with SE) of clinical decline assessed by change in MMSE score from baseline to 24 months in the (A) ADNI MCI and (c) BioFINDER MCS populations; adjustment for age, sex, years of education but without adjustment for APOEε4 status; number of patients in each biomarker group at baseline is presented. Kaplan-Meier curves of outcome dementia diagnosis within 6 years in the (B) ADNI MCI and (D) BioFINDER MCS populations; number of patients in each biomarker group at each time point is presented. pTau, phosphorylated Tau; MMSE, Mini-Mental State Examination; ADNI, Alzheimer’s Disease Neuroimaging Initiative; SE, standard error; MCI, mild cognitive impairment; MCS, mild cognitive symptoms.
See this image and copyright information in PMC

References

    1. Sperling RA, et al. Toward defining the preclinical stages of Alzheimer’s disease: recommendations from the National Institute on Aging-Alzheimer’s Association workgroups on diagnostic guidelines for Alzheimer’s disease. Alzheimers Dement. 2011;7:280–292. doi: 10.1016/j.jalz.2011.03.003. - DOI - PMC - PubMed
    1. Albert MS, et al. The diagnosis of mild cognitive impairment due to Alzheimer’s disease: recommendations from the National Institute on Aging-Alzheimer’s Association workgroups on diagnostic guidelines for Alzheimer’s disease. Alzheimers Dement. 2011;7:270–279. doi: 10.1016/j.jalz.2011.03.008. - DOI - PMC - PubMed
    1. Petersen RC. Mild cognitive impairment as a diagnostic entity. J. Intern. Med. 2004;256:183–194. doi: 10.1111/j.1365-2796.2004.01388.x. - DOI - PubMed
    1. Apostolova LG, et al. Critical review of the appropriate use criteria for amyloid imaging: effect on diagnosis and patient care. Alzheimers Dement. 2016;5:15–22. - PMC - PubMed
    1. Doraiswamy PM, et al. Florbetapir F 18 amyloid PET and 36-month cognitive decline: a prospective multicenter study. Mol. Psychiatry. 2014;19:1044–1051. doi: 10.1038/mp.2014.9. - DOI - PMC - PubMed

Publication types