Evidence map›Paper›PMID 32643852›Full record

ArticleHuman brain mapping2020

Nonlinear biomarker interactions in conversion from mild cognitive impairment to Alzheimer's disease.

Sebastian G Popescu, Alex Whittington, Roger N Gunn, Paul M Matthews, Ben Glocker, David J Sharp, James H Cole, Alzheimer's Disease Neuroimaging Initiative

Abstract read
In one paragraph

Article in Human brain mapping, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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

18 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. When Age Is More Than a Number: Acceleration of Brain Aging in Neurodegenerative Diseases.Journal of nuclear medicine : official publication, Society of Nuclear Medicine · 2025
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  14. Local Brain-Age: A U-Net Model.Frontiers in aging neuroscience · 2021
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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

8 authors.

Sebastian G PopescuComputational, Cognitive & Clinical Neuroimaging Laboratory, Department of Brain Sciences, Imperial College London, London, UK.
Alex WhittingtonComputational, Cognitive & Clinical Neuroimaging Laboratory, Department of Brain Sciences, Imperial College London, London, UK.
Roger N GunnInvicro Ltd, London, UK.
Paul M MatthewsDepartment of Brain Sciences, Imperial College London, London, UK.
Ben GlockerBiomedical Image Analysis Group, Department of Computing, Imperial College London, London, UK.
David J SharpComputational, Cognitive & Clinical Neuroimaging Laboratory, Department of Brain Sciences, Imperial College London, London, UK.
James H ColeComputational, Cognitive & Clinical Neuroimaging Laboratory, Department of Brain Sciences, Imperial College London, London, UK.ORCID 0000-0003-1908-5588
Alzheimer's Disease Neuroimaging Initiative

Funding

Alzheimer's Disease Neuroimaging Initiative - SupplementU01AG024904 · NIA · NORTHERN CALIFORNIA INSTITUTE RES &EDUC · PI WEINER, MICHAEL W · 2004 to 2015
$121.0M
Alzheimer's Disease Neuroimaging InitiativeBristol-Myers Squibb CompanyCIHRDepartment of Health II-LB-0715-20006Department of Health NIHR-RP-011-048Eli Lilly and CompanyEngineering and Physical Sciences Research CouncilF. Hoffmann-La Roche LtdFoundation for the National Institutes of HealthGE HealthcareImperial College LondonJohnson & JohnsonMeso Scale DiagnosticsNational Institute for Health ResearchNational Institute on AgeingNIA NIH HHS U01 AG024904NIBIB NIH HHSNIH HHS U01 AG024904Northern California Institute for Research and EducationNovartis Pharmaceuticals CorporationTakeda Pharmaceutical CompanyUniversity of Southern CaliforniaUS Department of Defence W81XWH-12-2-0012
6 · The paper itself

Abstract

Multiple biomarkers can capture different facets of Alzheimer's disease. However, statistical models of biomarkers to predict outcomes in Alzheimer's rarely model nonlinear interactions between these measures. Here, we used Gaussian Processes to address this, modelling nonlinear interactions to predict progression from mild cognitive impairment (MCI) to Alzheimer's over 3 years, using Alzheimer's Disease Neuroimaging Initiative (ADNI) data. Measures included: demographics, APOE4 genotype, CSF (amyloid-β42, total tau, phosphorylated tau), [18

Indexed as

Disease ProgressionModels, TheoreticalAgedAged, 80 and overAlzheimer DiseaseBiomarkersCognitive DysfunctionFemaleFollow-Up StudiesHumansMagnetic Resonance ImagingMalePositron-Emission TomographySensitivity and SpecificityBiomarkersAlzheimer's diseasedementia biomarkersGaussian processesmild cognitive impairment

Identifiers

PMID32643852
PMCPMC7502835

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.