Evidence map›Paper›PMID 32112059›Full record

ReviewNature neuroscience2020

The multiplex model of the genetics of Alzheimer's disease.

Rebecca Sims, Matthew Hill, Julie Williams

Registry-linked trialAbstract readReview
PubMed Publisher
In one paragraph

Review in Nature neuroscience, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06529744 (Improving Prognostic Confidence in Neurodegenerative Diseases Causing Dementia Using Peripheral Biomarkers and Integrative Modeling), which is not on this map. Cited by 284 papers, 7 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
284citing papers in PubMed, 7 pooled it
40.2field-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.

NCT06529744 recruitingnot on this mapstarted 2023, after this paper: background citation

Improving Prognostic Confidence in Neurodegenerative Diseases Causing Dementia Using Peripheral Biomarkers and Integrative Modeling

Typeobservational_patient_registrySponsorUniversity Health Network, TorontoRan2023 to 2027Enrolled500ConditionsDementia, Alzheimer Disease, Dementia With Lewy Bodies, Vascular Dementia
3 · Its place in the literature

Who cites it

284 citing papers in PubMed, 7 syntheses or guidelines pooled it, 496 citations in OpenAlex.

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  15. Are we fully exploiting genetic discoveries to understand and treat Alzheimer's disease?Mammalian genome : official journal of the International Mammalian Genome Society · 2026
    Article
  16. Article
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  20. Genetic risk in Alzheimer's disease.NPJ systems biology and applications · 2026
    Review

224 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

3 authors at 2 institutions in 1 country.

Rebecca SimsDivision of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, UK.
Matthew HillDivision of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, UK.
Julie WilliamsDivision of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, UK. williamsj@cardiff.ac.uk.ORCID http://orcid.org/0000-0002-4069-0259
UK Dementia Research Institute · GBCardiff University · GB

Funding

Medical Research Council G0300429Medical Research Council G0600237Medical Research Council G0902227Medical Research Council MC_PC_17112Medical Research Council MR/K013041/1Medical Research Council MR/L023784/1Medical Research Council MR/L023784/2Medical Research Council MR/L501517/1Medical Research Council MR/M009076/1Medical Research Council MR/N029402/1
6 · The paper itself

Abstract

Genes play a strong role in Alzheimer's disease (AD), with late-onset AD showing heritability of 58-79% and early-onset AD showing over 90%. Genetic association provides a robust platform to build our understanding of the etiology of this complex disease. Over 50 loci are now implicated for AD, suggesting that AD is a disease of multiple components, as supported by pathway analyses (immunity, endocytosis, cholesterol transport, ubiquitination, amyloid-β and tau processing). Over 50% of late-onset AD heritability has been captured, allowing researchers to calculate the accumulation of AD genetic risk through polygenic risk scores. A polygenic risk score predicts disease with up to 90% accuracy and is an exciting tool in our research armory that could allow selection of those with high polygenic risk scores for clinical trials and precision medicine. It could also allow cellular modelling of the combined risk. Here we propose the multiplex model as a new perspective from which to understand AD. The multiplex model reflects the combination of some, or all, of these model components (genetic and environmental), in a tissue-specific manner, to trigger or sustain a disease cascade, which ultimately results in the cell and synaptic loss observed in AD.

Indexed as

Models, GeneticAlzheimer DiseaseAnimalsHumansSignal Transduction

Identifiers

PMID32112059
OpenAlexW3007931728

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

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.