Evidence map›Paper›PMID 41157910›Full record

ArticleAlzheimer's & dementia : the journal of the Alzheimer's Association2025

Plasma proteomic Alzheimer's risk score: Biological age clock and pseudotime trajectory.

Shiwei Liu, Yen-Ning Huang, Tamina Park, Eun Hye Lee, Soumilee Chaudhuri, Nicholas Adzibolosu, Paula J Bice, Jeffrey L Dage, Jared R Brosch, Sujuan Gao and 5 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Alzheimer's & dementia : the journal of the Alzheimer's Association, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–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

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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

6 citing papers in PubMed.

  1. Review
  2. Article
  3. Review
  4. Article
  5. Plasma proteomic Alzheimer's risk score: Biological age clock and pseudotime trajectory.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2025
    Article
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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

15 authors.

Shiwei LiuCenter for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, Indiana, USA.
Yen-Ning HuangCenter for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, Indiana, USA.
Tamina ParkCenter for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, Indiana, USA.
Eun Hye LeeCenter for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, Indiana, USA.
Soumilee ChaudhuriCenter for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, Indiana, USA.
Nicholas AdzibolosuCenter for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, Indiana, USA.
Paula J BiceCenter for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, Indiana, USA.
Jeffrey L DageIndiana Alzheimer's Disease Research Center, Indiana University School of Medicine, Indianapolis, Indiana, USA.
Jared R BroschCenter for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, Indiana, USA.
Sujuan GaoIndiana Alzheimer's Disease Research Center, Indiana University School of Medicine, Indianapolis, Indiana, USA.
Liana G ApostolovaCenter for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, Indiana, USA.
Donna M WilcockStark Neurosciences Research Institute, Indiana University School of Medicine, Indianapolis, Indiana, USA.
Shannon L RisacherCenter for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, Indiana, USA.
Andrew J SaykinCenter for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, Indiana, USA.
Kwangsik NhoCenter for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, Indiana, USA.

Funding

Project 1U19AG024904 · NIA · NORTHERN CALIFORNIA INSTITUTE/RES/EDU · PI MICHAEL W WEINER · 2016 to 2026
$226.7M
Alzheimer's Disease Neuroimaging Initiative - SupplementU01AG024904 · NIA · NORTHERN CALIFORNIA INSTITUTE RES &EDUC · PI WEINER, MICHAEL W · 2004 to 2015
$121.0M
National Centralized Repository for Alzheimer's Disease and Related Dementias (NCRAD)U24AG021886 · NIA · INDIANA UNIV-PURDUE UNIV AT INDIANAPOLIS · PI TATIANA M. FOROUD · 2002 to 2026
$119.8M
The Neighborhoods Study: Contextual Disadvantage and Alzheimer’s Disease and Related Dementias (ADRD)R01AG070883 · NIA · UNIVERSITY OF WISCONSIN-MADISON · PI AMY J. KIND · 2021 to 2026
$42.1M
Peripheral and Central Biomarkers of Alzheimer's Disease in Diverse CohortsU19AG074879 · NIA · MAYO CLINIC JACKSONVILLE · PI Minerva Maria Carrasquillo, NILUFER ERTEKIN-TANER · 2023 to 2026
$42.0M
MVP Data Integration into the ADSP Phenotype Harmonization ConsortiumU24AG074855 · NIA · VANDERBILT UNIVERSITY MEDICAL CENTER · PI CUCCARO, MICHAEL L, HOHMAN, TIMOTHY J · 2021 to 2025
$37.5M
Research Education ComponentP30AG010133 · NIA · INDIANA UNIV-PURDUE UNIV AT INDIANAPOLIS · PI SAYKIN, ANDREW J · 1991 to 2020
$37.3M
Research Education ComponentP30AG072976 · NIA · INDIANA UNIVERSITY INDIANAPOLIS · PI ANDREW J SAYKIN · 2021 to 2026
$24.1M
Ultrascale Machine Learning to Empower Discovery in Alzheimers Disease BiobanksU01AG068057 · NIA · UNIVERSITY OF SOUTHERN CALIFORNIA · PI Christos Davatzikos, Heng Huang · 2020 to 2026
$20.7M
KBASE2: Korean Brain Aging Study, Longitudinal Endophenotypes and Systems BiologyU01AG072177 · NIA · INDIANA UNIVERSITY INDIANAPOLIS · PI LEE, DONG YOUNG, NHO, KWANGSIK TIMOTHY · 2021 to 2025
$11.2M
Alzheimer Diagnosis in older Adults with Chronic Conditions ADACC NetworkU24AG082930 · NIA · WAKE FOREST UNIVERSITY HEALTH SCIENCES · PI Nicole R. Fowler, Thomas K Karikari · 2023 to 2026
$7.3M
Memory Circuitry in MCI and Early Alzheimer’s Disease Prodrome: Molecular DriversR01AG019771 · NIA · INDIANA UNIV-PURDUE UNIV AT INDIANAPOLIS · PI SAYKIN, ANDREW J · 2001 to 2021
$6.9M
ADNI Health Enhancement Scientific ProgramNIA NIH HHS K07 AG076659NIA NIH HHS P30 AG010133NIA NIH HHS P30 AG072976NIA NIH HHS R01 AG019771NIA NIH HHS R01 AG057739NIA NIH HHS R01 AG068193NIA NIH HHS R01 AG070883NIA NIH HHS R01 AG075959NIA NIH HHS R01 AG081951NIA NIH HHS R01 AG082348NIA NIH HHS T32 AG071444NIA NIH HHS U01 AG024904NIA NIH HHS U01 AG068057NIA NIH HHS U01 AG072177NIA NIH HHS U19 AG024904NIA NIH HHS U19 AG074879NIA NIH HHS U24 AG021886NIA NIH HHS U24 AG074855NIA NIH HHS U24 AG082930NIH HHS P30 AG010133NIH HHS P30 AG072976NIH HHS R01 AG019771NIH HHS R01 AG057739NIH HHS R01 AG068193NIH HHS R01 AG070883NIH HHS R01 AG075959NIH HHS R01 AG081951NIH HHS R01 AG082348NIH HHS R01 LM012535NIH HHS R01 LM013463NIH HHS T32 AG071444NIH HHS U01 AG024904NIH HHS U01 AG068057NIH HHS U01 AG072177NIH HHS U01 AG24904NIH HHS U19 AG024904NIH HHS U19 AG074879NIH HHS U24 AG074855NLM NIH HHS R01 LM012535NLM NIH HHS R01 LM013463
6 · The paper itself

Abstract

introductionAlzheimer's disease (AD) involves progressive cognitive decline. Plasma proteomics data may provide insights into disease risk and mechanisms.

methodsPlasma proteomics data (N = 498) by the SomaScan 7k platform from the Indiana AD Research Center was used to calculate proteomics-based Alzheimer's risk scores: organ-specific aging clocks and pseudotime trajectory. The Alzheimer's risk scores were investigated for associations with plasma- and imaging-based biomarkers for AD and diagnosis and evaluated for classification performance for diagnosis and biomarker positivity status.

resultsCognition-optimized brain and liver age acceleration showed significant associations with AD diagnosis and biomarkers. Pseudotime showed a molecular trajectory from cognitively normal to AD individuals, in association with plasma and imaging biomarkers. Previously known plasma biomarkers yielded better classification performance with inclusion of proteomics-based Alzheimer's risk scores. DISCUSSION: The findings highlight proteomics-derived biological aging clocks and pseudotime trajectory as potential biomarkers to complement current biomarker frameworks and identify disease mechanisms. HIGHLIGHTS: Plasma proteomic aging clocks and pseudotime provide potential markers for Alzheimer's disease (AD) risk. Cognition-optimized brain aging and pseudotime link to diagnosis and AD biomarkers. Brain aging clock and pseudotime improve the diagnosis classification performance. Pseudotime outperformed established plasma biomarkers for diagnosis classification.

Indexed as

AgingAlzheimer DiseaseProteomicsAgedAged, 80 and overBiomarkersBrainFemaleHumansMaleBiomarkersaging clockAlzheimer's diseasebiomarkersorganplasmaproteomicspseudotime

Identifiers

PMID41157910
PMCPMC12568774

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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.