Evidence map›Paper›PMID 36745413›Full record

ArticleJAMA neurology2023

Prediction of Longitudinal Cognitive Decline in Preclinical Alzheimer Disease Using Plasma Biomarkers.

Niklas Mattsson-Carlgren, Gemma Salvadó, Nicholas J Ashton, Pontus Tideman, Erik Stomrud, Henrik Zetterberg, Rik Ossenkoppele, Tobey J Betthauser, Karly Alex Cody, Erin M Jonaitis and 6 more

Open access · hybridAbstract read
In one paragraph

Article in JAMA neurology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 214 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
214citing papers in PubMed, 4 pooled it
59.7field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

214 citing papers in PubMed, 4 syntheses or guidelines pooled it, 268 citations in OpenAlex.

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  7. Dulaglutide and neurodegeneration biomarkers: REWIND post hoc analysis.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026
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154 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

16 authors at 6 institutions in 5 countries.

Niklas Mattsson-CarlgrenClinical Memory Research Unit, Faculty of Medicine, Lund University, Lund, Sweden.
Gemma SalvadóClinical Memory Research Unit, Faculty of Medicine, Lund University, Lund, Sweden.
Nicholas J AshtonDepartment of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden.
Pontus TidemanClinical Memory Research Unit, Faculty of Medicine, Lund University, Lund, Sweden.
Erik StomrudClinical Memory Research Unit, Faculty of Medicine, Lund University, Lund, Sweden.
Henrik ZetterbergDepartment of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden.
Rik OssenkoppeleClinical Memory Research Unit, Faculty of Medicine, Lund University, Lund, Sweden.
Tobey J BetthauserWisconsin Alzheimer's Institute, School of Medicine and Public Health, University of Wisconsin-Madison, Madison.
Karly Alex CodyWisconsin Alzheimer's Institute, School of Medicine and Public Health, University of Wisconsin-Madison, Madison.
Erin M JonaitisWisconsin Alzheimer's Institute, School of Medicine and Public Health, University of Wisconsin-Madison, Madison.
Rebecca LanghoughWisconsin Alzheimer's Institute, School of Medicine and Public Health, University of Wisconsin-Madison, Madison.
Sebastian PalmqvistClinical Memory Research Unit, Faculty of Medicine, Lund University, Lund, Sweden.
Kaj BlennowDepartment of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden.
Shorena JanelidzeClinical Memory Research Unit, Faculty of Medicine, Lund University, Lund, Sweden.
Sterling C JohnsonWisconsin Alzheimer's Institute, School of Medicine and Public Health, University of Wisconsin-Madison, Madison.
Oskar HanssonClinical Memory Research Unit, Faculty of Medicine, Lund University, Lund, Sweden.
Lund University · SEUniversity of Wisconsin–Madison · USSkåne University Hospital · SESahlgrenska University Hospital · SEStavanger University Hospital · NOUK Dementia Research Institute · GB

Funding

Wisconsin Registry for Alzheimer's Prevention: Sex Differences in DNA MethylationR01AG027161 · NIA · UNIVERSITY OF WISCONSIN-MADISON · PI Nathaniel Ark Chin, Sterling C Johnson · 2007 to 2026
$35.6M
The Longitudinal Course of Neural Function and Amyloid in People At Risk for ADR01AG021155 · NIA · UNIVERSITY OF WISCONSIN-MADISON · PI Sterling C Johnson · 2004 to 2026
$27.0M
The effects of iron on oxidative stress and Alzheimer's biomarkers in amyloid-positive and negative elderly normalR01AG068398 · NIA · WEILL MEDICAL COLL OF CORNELL UNIV · PI CHIANG, GLORIA CHIA-YI · 2020 to 2024
$2.8M
NIA NIH HHS R01 AG021155NIA NIH HHS R01 AG027161NIA NIH HHS R01 AG068398
6 · The paper itself

Abstract

Importance: Alzheimer disease (AD) pathology starts with a prolonged phase of β-amyloid (Aβ) accumulation without symptoms. The duration of this phase differs greatly among individuals. While this disease phase has high relevance for clinical trial designs, it is currently unclear how to best predict the onset of clinical progression. Objective: To evaluate combinations of different plasma biomarkers for predicting cognitive decline in Aβ-positive cognitively unimpaired (CU) individuals. Design, Setting, and Participants: This prospective population-based prognostic study evaluated data from 2 prospective longitudinal cohort studies (the Swedish BioFINDER-1 and the Wisconsin Registry for Alzheimer Prevention [WRAP]), with data collected from February 8, 2010, to October 21, 2020, for the BioFINDER-1 cohort and from August 11, 2011, to June 27, 2021, for the WRAP cohort. Participants were CU individuals recruited from memory clinics who had brain Aβ pathology defined by cerebrospinal fluid (CSF) Aβ42/40 in the BioFINDER-1 study and by Pittsburgh Compound B (PiB) positron emission tomography (PET) in the WRAP study. A total of 564 eligible Aβ-positive and Aβ-negative CU participants with available relevant data from the BioFINDER-1 and WRAP cohorts were included in the study; of those, 171 Aβ-positive participants were included in the main analyses. Exposures: Baseline P-tau181, P-tau217, P-tau231, glial fibrillary filament protein, and neurofilament light measured in plasma; CSF biomarkers in the BioFINDER-1 cohort, and PiB PET uptake in the WRAP cohort. Main Outcomes and Measures: The primary outcome was longitudinal measures of cognition (using the Mini-Mental State Examination [MMSE] and the modified Preclinical Alzheimer Cognitive Composite [mPACC]) over a median of 6 years (range, 2-10 years). The secondary outcome was conversion to AD dementia. Baseline biomarkers were used in linear regression models to predict rates of longitudinal cognitive change (calculated separately). Models were adjusted for age, sex, years of education, apolipoprotein E ε4 allele status, and baseline cognition. Multivariable models were compared based on model R2 coefficients and corrected Akaike information criterion. Results: Among 171 Aβ-positive CU participants included in the main analyses, 119 (mean [SD] age, 73.0 [5.4] years; 60.5% female) were from the BioFINDER-1 study, and 52 (mean [SD] age, 64.4 [4.6] years; 65.4% female) were from the WRAP study. In the BioFINDER-1 cohort, plasma P-tau217 was the best marker to predict cognitive decline in the mPACC (model R2 = 0.41) and the MMSE (model R2 = 0.34) and was superior to the covariates-only models (mPACC: R2 = 0.23; MMSE: R2 = 0.04; P < .001 for both comparisons). Results were validated in the WRAP cohort; for example, plasma P-tau217 was associated with mPACC slopes (R2 = 0.13 vs 0.01 in the covariates-only model; P = .01) and MMSE slopes (R2 = 0.29 vs 0.24 in the covariates-only model; P = .046). Sparse models were identified with plasma P-tau217 as a predictor of cognitive decline. Power calculations for enrichment in hypothetical clinical trials revealed large relative reductions in sample sizes when using plasma P-tau217 to enrich for CU individuals likely to experience cognitive decline over time. Conclusions and Relevance: In this study, plasma P-tau217 predicted cognitive decline in patients with preclinical AD. These findings suggest that plasma P-tau217 may be used as a complement to CSF or PET for participant selection in clinical trials of novel disease-modifying treatments.

Indexed as

Alzheimer DiseaseCognitive DysfunctionAgedAmyloid beta-PeptidesBiomarkersFemaleHumansLongitudinal StudiesMaleMiddle AgedPositron-Emission TomographyProspective Studiestau ProteinsAmyloid beta-PeptidesBiomarkerstau Proteins

Identifiers

PMID36745413
PMCPMC10087054
OpenAlexW4319294776

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.