Evidence map›Paper›PMID 25880661›Full record

ArticleBMC neurology2015

Decision tree analysis of genetic risk for clinically heterogeneous Alzheimer's disease.

Jennifer S Yokoyama, Luke W Bonham, Renee L Sears, Eric Klein, Anna Karydas, Joel H Kramer, Bruce L Miller, Giovanni Coppola

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in BMC neurology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed, 3 pooled it
1.7field-weighted citation impact, top 16% 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

18 citing papers in PubMed, 3 syntheses or guidelines pooled it, 31 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. HFE Mutations in Neurodegenerative Disease as a Model of Hormesis.International journal of molecular sciences · 2024
    Review
  5. Article
  6. Article
  7. Article
  8. Article
  9. Review
  10. Article
  11. Genetic architecture of Alzheimer's disease.Neurobiology of disease · 2020
    Review
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. 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

8 authors at 3 institutions in 1 country.

Jennifer S YokoyamaMemory and Aging Center, Department of Neurology, University of California, San Francisco, CA, 94158, USA. Jennifer.Yokoyama@ucsf.edu.
Luke W BonhamMemory and Aging Center, Department of Neurology, University of California, San Francisco, CA, 94158, USA. Luke.Bonham@ucsf.edu.
Renee L SearsSemel Institute for Neuroscience and Human Behavior, Departments of Neurology and Psychiatry, The David Geffen School of Medicine at University of California Los Angeles, Los Angeles, CA, 90095, USA. r.sears@go.wustl.edu.
Eric KleinSemel Institute for Neuroscience and Human Behavior, Departments of Neurology and Psychiatry, The David Geffen School of Medicine at University of California Los Angeles, Los Angeles, CA, 90095, USA. eklein828@gmail.com.
Anna KarydasMemory and Aging Center, Department of Neurology, University of California, San Francisco, CA, 94158, USA. Anna.Karydas@ucsf.edu.
Joel H KramerMemory and Aging Center, Department of Neurology, University of California, San Francisco, CA, 94158, USA. Joel.Kramer@ucsf.edu.
Bruce L MillerMemory and Aging Center, Department of Neurology, University of California, San Francisco, CA, 94158, USA. Bruce.Miller@ucsf.edu.
Giovanni CoppolaSemel Institute for Neuroscience and Human Behavior, Departments of Neurology and Psychiatry, The David Geffen School of Medicine at University of California Los Angeles, Los Angeles, CA, 90095, USA. gcoppola@ucla.edu.
University Memory and Aging Center · USUniversity of California, Los Angeles · USUniversity of California, San Francisco · US

Funding

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
TDP-43 Loss-of-Function: Biology to BiomarkersP01AG019724 · NIA · UNIVERSITY OF PENNSYLVANIA · PI Jennifer Merrilees · 2002 to 2026
$67.2M
PrPSc SPECIFIC INTERACTION WITH NOVEL PrP-Fc FUSION PROTEINSP50AG023501 · NIA · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI MILLER, BRUCE L · 2004 to 2018
$27.1M
Integrative Center for Neurogenetics and Neurogenomics - OverallP30NS062691 · NINDS · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI COPPOLA, GIOVANNI · 2009 to 2018
$7.4M
Novel Genetic Risk Factors for Alzheimer's Disease (AD) & Frontotemporal DementiaR01AG026938 · NIA · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI GESCHWIND, DANIEL H · 2005 to 2009
$2.5M
Genetic, Genomic, and Imaging Biomarkers in Degenerative DementiaRC1AG035610 · NIA · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI COPPOLA, GIOVANNI · 2009 to 2010
$910k
RNA signatures of frontotemporal dementia and ALS due to C9ORF72 expansionK01AG049152 · NIA · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI YOKOYAMA, JENNIFER S · 2015 to 2019
$648k
NIA NIH HHS K01 AG049152NIA NIH HHS P01 AG019724NIA NIH HHS P50 AG023501NIA NIH HHS P50-AG023501NIA NIH HHS P50-AG023501-08S1NIA NIH HHS R01 AG026938NIA NIH HHS R01 AG26938NIA NIH HHS RC1 AG035610NIA NIH HHS U24 AG021886NIA NIH HHS U24 AG21886NINDS NIH HHS P30 NS062691
6 · The paper itself

Abstract

backgroundHeritability of Alzheimer's disease (AD) is estimated at 74% and genetic contributors have been widely sought. The ε4 allele of apolipoprotein E (APOE) remains the strongest common risk factor for AD, with numerous other common variants contributing only modest risk for disease. Variability in clinical presentation of AD, which is typically amnestic (AmnAD) but can less commonly involve visuospatial, language and/or dysexecutive syndromes (atypical or AtAD), further complicates genetic analyses. Taking a multi-locus approach may increase the ability to identify individuals at highest risk for any AD syndrome. In this study, we sought to develop and investigate the utility of a multi-variant genetic risk assessment on a cohort of phenotypically heterogeneous patients with sporadic AD clinical diagnoses.

methodsWe genotyped 75 variants in our cohort and, using a two-staged study design, we developed a 17-marker AD risk score in a Discovery cohort (n = 59 cases, n = 133 controls) then assessed its utility in a second Validation cohort (n = 126 cases, n = 150 controls). We also performed a data-driven decision tree analysis to identify genetic and/or demographic criteria that are most useful for accurately differentiating all AD cases from controls.

resultsWe confirmed APOE ε4 as a strong risk factor for AD. A 17-marker risk panel predicted AD significantly better than APOE genotype alone (P < 0.00001) in the Discovery cohort, but not in the Validation cohort. In decision tree analyses, we found that APOE best differentiated cases from controls only in AmnAD but not AtAD. In AtAD, HFE SNP rs1799945 was the strongest predictor of disease; variation in HFE has previously been implicated in AD risk in non-ε4 carriers.

conclusionsOur study suggests that APOE ε4 remains the best predictor of broad AD risk when compared to multiple other genetic factors with modest effects, that phenotypic heterogeneity in broad AD can complicate simple polygenic risk modeling, and supports the association between HFE and AD risk in individuals without APOE ε4.

Indexed as

Decision TreesAgedAged, 80 and overAlgorithmsAllelesAlzheimer DiseaseApolipoprotein E4Cohort StudiesFemaleGenetic MarkersGenotypeHumansMaleNeurologic ExaminationPhenotypeRisk AssessmentApolipoprotein E4Genetic Markers

Identifiers

PMID25880661
PMCPMC4459447
OpenAlexW2032447992

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

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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.