Evidence map›Paper›PMID 37082508›Full record

ArticleBrain communications2023

Multi-omic integration via similarity network fusion to detect molecular subtypes of ageing.

Mu Yang, Stuart Matan-Lithwick, Yanling Wang, Philip L De Jager, David A Bennett, Daniel Felsky

Open access · goldAbstract read
In one paragraph

Article in Brain communications, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed, 2 pooled it
4.6field-weighted citation impact, top 5% 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

22 citing papers in PubMed, 2 syntheses or guidelines pooled it, 31 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Review
  4. Article
  5. Review
  6. Article
  7. Article
  8. Review
  9. Article
  10. Genetic Burden andJournal of personalized medicine · 2026
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  11. Review
  12. Article
  13. Inflammatory Biomarkers of Asymptomatic and Symptomatic Tuberculosis.bioRxiv : the preprint server for biology · 2025
    Article
  14. Review
  15. Review
  16. Article
  17. Article
  18. Review
  19. Multiomics of Aging and Aging-Related Diseases.International journal of molecular sciences · 2024
    Review
  20. Review
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

6 authors at 3 institutions in 2 countries.

Mu YangDivision of Biostatistics, Dalla Lana School of Public Health, University of Toronto, Toronto, ON M5T 3M7, Canada.ORCID https://orcid.org/0000-0001-7084-029X
Stuart Matan-LithwickThe Krembil Centre for Neuroinformatics, Centre for Addiction and Mental Health, Toronto, ON M5T 1R8, Canada.
Yanling WangRush Alzheimer's Disease Center, Rush University, Chicago, IL 60612, USA.
Philip L De JagerThe Center for Translational and Computational Neuroimmunology, Columbia University Medical Center, New York, NY 10033, USA.
David A BennettRush Alzheimer's Disease Center, Rush University, Chicago, IL 60612, USA.ORCID https://orcid.org/0000-0003-3689-554X
Daniel FelskyDivision of Biostatistics, Dalla Lana School of Public Health, University of Toronto, Toronto, ON M5T 3M7, Canada.
Centre for Addiction and Mental Health · CARush University · USColumbia University Irving Medical Center · US

Funding

EPIDEMIOLOGY OF NEURAL RESERVE AND NEUROBIOLOGY IN AGINGR01AG017917 · NIA · RUSH UNIVERSITY MEDICAL CENTER · PI BENNETT, DAVID ALAN · 2001 to 2023
$43.3M
Rush Alzheimer's Disease Research CenterP30AG072975 · NIA · RUSH UNIVERSITY MEDICAL CENTER · PI Lisa L Barnes, Julie A. Schneider · 2021 to 2026
$24.7M
RISK FACTORS, PATHOLOGY, AND CLINICAL EXPRESSIONS OF ADR01AG015819 · NIA · RUSH UNIVERSITY MEDICAL CENTER · PI BENNETT, DAVID ALAN · 1998 to 2024
$21.4M
Multi-omic network-directed proteoform discovery, dissection and functional validation to prioritize novel AD therapeutic targetsU01AG061356 · NIA · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI BENNETT, DAVID ALAN, DE JAGER, PHILIP L · 2018 to 2022
$13.7M
Metabolomic Signatures for Disease Sub-classification and Target Prioritization in AMP-ADU01AG061359 · NIA · DUKE UNIVERSITY · PI KADDURAH-DAOUK, RIMA F, KASTENMULLER, GABI · 2018 to 2022
$10.0M
Metabolic Signatures Underlying Vascular Risk Factors for Alzheimer-type DementiasRF1AG051550 · NIA · DUKE UNIVERSITY · PI KADDURAH-DAOUK, RIMA F, KLING, MITCHEL ALLAN · 2015 to 2016
$6.3M
Metabolic Networks and Pathways Predictive of Sex Differences in AD Risk and Responsiveness to TreatmentRF1AG059093 · NIA · DUKE UNIVERSITY · PI BRINTON, ROBERTA EILEEN, CHANG, RUI · 2018 to 2018
$5.9M
Metabolic Networks and Pathways in Alzheimer's DiseaseR01AG046171 · NIA · DUKE UNIVERSITY · PI KADDURAH-DAOUK, RIMA F · 2014 to 2017
$4.4M
Metabolic Network Analysis of Biochemical Trajectories in Alzheimer's DiseaseRF1AG057452 · NIA · DUKE UNIVERSITY · PI KADDURAH-DAOUK, RIMA F, KASTENMULLER, GABI · 2017 to 2017
$3.5M
Gut Liver Brain Biochemical Axis in Alzheimer's DiseaseRF1AG058942 · NIA · DUKE UNIVERSITY · PI KADDURAH-DAOUK, RIMA F, VAN DUIJN, CORNELIA MARJA · 2018 to 2018
$3.4M
NIA NIH HHS P30 AG072975NIA NIH HHS R01 AG015819NIA NIH HHS R01 AG017917NIA NIH HHS R01 AG046171NIA NIH HHS RF1 AG051550NIA NIH HHS RF1 AG057452NIA NIH HHS RF1 AG058942NIA NIH HHS RF1 AG059093NIA NIH HHS U01 AG061356NIA NIH HHS U01 AG061359
6 · The paper itself

Abstract

Molecular subtyping of brain tissue provides insights into the heterogeneity of common neurodegenerative conditions, such as Alzheimer's disease. However, existing subtyping studies have mostly focused on single data modalities and only those individuals with severe cognitive impairment. To address these gaps, we applied similarity network fusion, a method capable of integrating multiple high-dimensional multi-omic data modalities simultaneously, to an elderly sample spanning the full spectrum of cognitive ageing trajectories. We analyzed human frontal cortex brain samples characterized by five omic modalities: bulk RNA sequencing (18 629 genes), DNA methylation (53 932 CpG sites), histone acetylation (26 384 peaks), proteomics (7737 proteins) and metabolomics (654 metabolites). Similarity network fusion followed by spectral clustering was used for subtype detection, and subtype numbers were determined by Eigen-gap and rotation cost statistics. Normalized mutual information determined the relative contribution of each modality to the fused network. Subtypes were characterized by associations with 13 age-related neuropathologies and cognitive decline. Fusion of all five data modalities (

Indexed as

Alzheimer’s diseaseclustering analysiscognitive ageingmolecular subtypingmulti-omic integration

Identifiers

PMID37082508
PMCPMC10110975
OpenAlexW4362596377

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.