Evidence map›Paper›PMID 32951606›Full record

ArticleTranslational neurodegeneration2020

Integrated lipidomics and proteomics network analysis highlights lipid and immunity pathways associated with Alzheimer's disease.

Jin Xu, Giulia Bankov, Min Kim, Asger Wretlind, Jodie Lord, Rebecca Green, Angela Hodges, Abdul Hye, Dag Aarsland, Latha Velayudhan and 4 more

Open access · goldAbstract read
In one paragraph

Article in Translational neurodegeneration, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 44 papers.

0numbers the graph read from it
0cells of the map it votes in
44citing papers in PubMed
4.1field-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

44 citing papers in PubMed, 64 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Eigenlipids for exploring lipid biology.Journal of lipid research · 2026
    Review
  6. Article
  7. Article
  8. Review
  9. Article
  10. Review
  11. Review
  12. Article
  13. Lipid profiling reveals unsaturated lipid reduction in women with Alzheimer's disease.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2025
    Article
  14. Article
  15. Review
  16. Article
  17. Review
  18. Integrating causal human genetics andFrontiers in molecular biosciences · 2025
    Article
  19. Review
  20. Article
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

14 authors at 2 institutions in 3 countries.

Jin XuInstitute of Pharmaceutical Science, King's College London, London, UK.
Giulia BankovInstitute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK.
Min KimSteno Diabetes Center Copenhagen, Gentofte, Denmark.
Asger WretlindSteno Diabetes Center Copenhagen, Gentofte, Denmark.
Jodie LordInstitute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK.
Rebecca GreenInstitute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK.
Angela HodgesInstitute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK.
Abdul HyeInstitute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK.
Dag AarslandInstitute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK.
Latha VelayudhanInstitute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK.
Richard J B DobsonInstitute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK. richard.j.dobson@kcl.ac.uk.
Petroula ProitsiInstitute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK. petroula.proitsi@kcl.ac.uk.
Cristina Legido-QuigleyInstitute of Pharmaceutical Science, King's College London, London, UK. cristina.legido.quigley@regionh.dk.
AddNeuroMed Consortium
King's College London · GBSteno Diabetes Center · DK

Funding

Medical Research Council MC_PC_17214
6 · The paper itself

Abstract

backgroundThere is an urgent need to understand the pathways and processes underlying Alzheimer's disease (AD) for early diagnosis and development of effective treatments. This study was aimed to investigate Alzheimer's dementia using an unsupervised lipid, protein and gene multi-omics integrative approach.

methodsA lipidomics dataset comprising 185 AD patients, 40 mild cognitive impairment (MCI) individuals and 185 controls, and two proteomics datasets (295 AD, 159 MCI and 197 controls) were used for weighted gene co-expression network analyses (WGCNA). Correlations of modules created within each modality with clinical AD diagnosis, brain atrophy measures and disease progression, as well as their correlations with each other, were analyzed. Gene ontology enrichment analysis was employed to examine the biological processes and molecular and cellular functions of protein modules associated with AD phenotypes. Lipid species were annotated in the lipid modules associated with AD phenotypes. The associations between established AD risk loci and the lipid/protein modules that showed high correlation with AD phenotypes were also explored.

resultsFive of the 20 identified lipid modules and five of the 17 identified protein modules were correlated with clinical AD diagnosis, brain atrophy measures and disease progression. The lipid modules comprising phospholipids, triglycerides, sphingolipids and cholesterol esters were correlated with AD risk loci involved in immune response and lipid metabolism. The five protein modules involved in positive regulation of cytokine production, neutrophil-mediated immunity, and humoral immune responses were correlated with AD risk loci involved in immune and complement systems and in lipid metabolism (the APOE ε4 genotype).

conclusionsModules of tightly regulated lipids and proteins, drivers in lipid homeostasis and innate immunity, are strongly associated with AD phenotypes.

Indexed as

AgedAged, 80 and overAlzheimer DiseaseCohort StudiesDatabases, GeneticFemaleFollow-Up StudiesGene Regulatory NetworksHumansImmunity, HumoralLipidomicsLongitudinal StudiesMaleProteomicsAD risk lociAlzheimer’s diseaseBrain atrophyDementiaLipidomicsProteomicsRate of cognitive declinesMRIWGCNA

Identifiers

PMID32951606
PMCPMC7504646
OpenAlexW3087103326

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.