Evidence map›Paper›PMID 25723573›Full record

ArticlePloS one2015

Pathway-based analysis of genome-wide siRNA screens reveals the regulatory landscape of APP processing.

Luiz Miguel Camargo, Xiaohua Douglas Zhang, Patrick Loerch, Ramon Miguel Caceres, Shane D Marine, Paolo Uva, Marc Ferrer, Emanuele de Rinaldis, David J Stone, John Majercak and 4 more

Erratum issuedOpen access · goldAbstract read
In one paragraph

Article in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 19 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed, 1 pooled it
2.6field-weighted citation impact, top 10% 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

19 citing papers in PubMed, 1 synthesis or guideline pooled it, 26 citations in OpenAlex.

  1. Pooled it
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  10. Host directed therapies: COVID-19 and beyond.Current research in pharmacology and drug discovery · 2021
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  14. TREM2 in Neurodegenerative Diseases.Molecular neurodegeneration · 2017
    Review
  15. Article
  16. Review
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

14 authors at 4 institutions in 2 countries.

Luiz Miguel CamargoMerck Research Laboratories, Merck & Co, Boston, United States of America.
Xiaohua Douglas ZhangMerck Research Laboratories, Merck & Co, Beijing, China.
Patrick LoerchMerck Research Laboratories, Merck & Co, Boston, United States of America.
Ramon Miguel CaceresMerck Research Laboratories, Merck & Co, Boston, United States of America.
Shane D MarineMerck Research Laboratories, Merck & Co, North Wales, United States of America.
Paolo UvaMerck Research Laboratories, Instituto di Recerca di Biologia Molecolare, Pomezia, Italy.
Marc FerrerMerck Research Laboratories, Merck & Co, North Wales, United States of America.
Emanuele de RinaldisMerck Research Laboratories, Instituto di Recerca di Biologia Molecolare, Pomezia, Italy.
David J StoneMerck Research Laboratories, Merck & Co, West Point, United States of America.
John MajercakMerck Research Laboratories, Merck & Co, West Point, United States of America.
William J RayMerck Research Laboratories, Merck & Co, West Point, United States of America.
Chen Yi-AnNational Institute of Biomedical Innovation, Osaka, Japan.
Mark S ShearmanMerck Research Laboratories, Merck & Co, Boston, United States of America.
Kenji MizuguchiNational Institute of Biomedical Innovation, Osaka, Japan.
Merck & Co., Inc., Rahway, NJ, USA (United States) · USUnited States Military Academy · USNational Institute of Biomedical Innovation, Health and Nutrition · JPOsaka University · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The progressive aggregation of Amyloid-β (Aβ) in the brain is a major trait of Alzheimer's Disease (AD). Aβ is produced as a result of proteolytic processing of the β-amyloid precursor protein (APP). Processing of APP is mediated by multiple enzymes, resulting in the production of distinct peptide products: the non-amyloidogenic peptide sAPPα and the amyloidogenic peptides sAPPβ, Aβ40, and Aβ42. Using a pathway-based approach, we analyzed a large-scale siRNA screen that measured the production of different APP proteolytic products. Our analysis identified many of the biological processes/pathways that are known to regulate APP processing and have been implicated in AD pathogenesis, as well as revealing novel regulatory mechanisms. Furthermore, we also demonstrate that some of these processes differentially regulate APP processing, with some mechanisms favouring production of certain peptide species over others. For example, synaptic transmission having a bias towards regulating Aβ40 production over Aβ42 as well as processes involved in insulin and pancreatic biology having a bias for sAPPβ production over sAPPα. In addition, some of the pathways identified as regulators of APP processing contain genes (CLU, BIN1, CR1, PICALM, TREM2, SORL1, MEF2C, DSG2, EPH1A) recently implicated with AD through genome wide association studies (GWAS) and associated meta-analysis. In addition, we provide supporting evidence and a deeper mechanistic understanding of the role of diabetes in AD. The identification of these processes/pathways, their differential impact on APP processing, and their relationships to each other, provide a comprehensive systems biology view of the "regulatory landscape" of APP.

Indexed as

Genetic TechniquesMetabolic Networks and PathwaysAlzheimer DiseaseAmyloid beta-PeptidesAmyloid beta-Protein PrecursorCell SurvivalDiabetes Mellitus, Type 2Genome-Wide Association StudyHumansPeptide FragmentsProtein Processing, Post-TranslationalProteolysisRNA, Small InterferingSerum Amyloid A ProteinAmyloid beta-Peptidesamyloid beta-protein (1-40)amyloid beta-protein (1-42)Amyloid beta-Protein PrecursorPeptide FragmentsRNA, Small InterferingSerum Amyloid A Protein

Identifiers

PMID25723573
PMCPMC4344212
OpenAlexW2083362242

What OpenQuestion holds

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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.