Evidence map›Paper›PMID 29860282›Full record

ArticleBrain : a journal of neurology2018

Genetic study of multimodal imaging Alzheimer's disease progression score implicates novel loci.

Marzia A Scelsi, Raiyan R Khan, Marco Lorenzi, Leigh Christopher, Michael D Greicius, Jonathan M Schott, Sebastien Ourselin, Andre Altmann

Open access · hybridAbstract read
In one paragraph

Article in Brain : a journal of neurology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
38citing papers in PubMed, 2 pooled it
6.7field-weighted citation impact, top 3% 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

38 citing papers in PubMed, 2 syntheses or guidelines pooled it, 77 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
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  6. The Effects of SNPs in theVeterinary medicine international · 2026
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  8. IL-1β and CXCR4 as Potential Therapeutic Targets for Alzheimer's Disease.Combinatorial chemistry & high throughput screening · 2025
    Article
  9. Towards cascading genetic risk in Alzheimer's disease.Brain : a journal of neurology · 2024
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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 5 institutions in 3 countries.

Marzia A ScelsiCentre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, University College London, Gower Street NW1 2HE, London, UK.
Raiyan R KhanFunctional Imaging in Neuropsychiatric Disorders (FIND) Lab, Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA 94304-5777, USA.
Marco LorenziCentre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, University College London, Gower Street NW1 2HE, London, UK.
Leigh ChristopherFunctional Imaging in Neuropsychiatric Disorders (FIND) Lab, Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA 94304-5777, USA.
Michael D GreiciusFunctional Imaging in Neuropsychiatric Disorders (FIND) Lab, Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA 94304-5777, USA.
Jonathan M SchottFunctional Imaging in Neuropsychiatric Disorders (FIND) Lab, Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA 94304-5777, USA.
Sebastien OurselinCentre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, University College London, Gower Street NW1 2HE, London, UK.
Andre AltmannCentre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, University College London, Gower Street NW1 2HE, London, UK.
Stanford University · USUniversity College London · GBInstitut national de recherche en sciences et technologies du numérique · FRNational Hospital for Neurology and Neurosurgery · GBUK Dementia Research Institute · GB

Funding

NATIONAL ALZHEIMERS COORDINATING CENTER (NACC)U01AG016976 · NIA · UNIVERSITY OF WASHINGTON · PI KUKULL, WALTER ANTHONY · 1999 to 2020
$72.8M
Working Memory in Parkinson Disease: A Cognitive & Systems Neuroscience ApproachP50AG047366 · NIA · STANFORD UNIVERSITY · PI HENDERSON, VICTOR · 2015 to 2019
$7.9M
Medical Research Council CSUB19166Medical Research Council MR/J01107X/1Medical Research Council MR/L016311/1NIA NIH HHS P50 AG047366NIA NIH HHS U01 AG016976
6 · The paper itself

Abstract

Identifying genetic risk factors underpinning different aspects of Alzheimer's disease has the potential to provide important insights into pathogenesis. Moving away from simple case-control definitions, there is considerable interest in using quantitative endophenotypes, such as those derived from imaging as outcome measures. Previous genome-wide association studies of imaging-derived biomarkers in sporadic late-onset Alzheimer's disease focused only on phenotypes derived from single imaging modalities. In contrast, we computed a novel multi-modal neuroimaging phenotype comprising cortical amyloid burden and bilateral hippocampal volume. Both imaging biomarkers were used as input to a disease progression modelling algorithm, which estimates the biomarkers' long-term evolution curves from population-based longitudinal data. Among other parameters, the algorithm computes the shift in time required to optimally align a subjects' biomarker trajectories with these population curves. This time shift serves as a disease progression score and it was used as a quantitative trait in a discovery genome-wide association study with n = 944 subjects from the Alzheimer's Disease Neuroimaging Initiative database diagnosed as Alzheimer's disease, mild cognitive impairment or healthy at the time of imaging. We identified a genome-wide significant locus implicating LCORL (rs6850306, chromosome 4; P = 1.03 × 10-8). The top variant rs6850306 was found to act as an expression quantitative trait locus for LCORL in brain tissue. The clinical role of rs6850306 in conversion from healthy ageing to mild cognitive impairment or Alzheimer's disease was further validated in an independent cohort comprising healthy, older subjects from the National Alzheimer's Coordinating Center database. Specifically, possession of a minor allele at rs6850306 was protective against conversion from mild cognitive impairment to Alzheimer's disease in the National Alzheimer's Coordinating Center cohort (hazard ratio = 0.593, 95% confidence interval = 0.387-0.907, n = 911, PBonf = 0.032), in keeping with the negative direction of effect reported in the genome-wide association study (βdisease progression score = -0.07 ± 0.01). The implicated locus is linked to genes with known connections to Alzheimer's disease pathophysiology and other neurodegenerative diseases. Using multimodal imaging phenotypes in association studies may assist in unveiling the genetic drivers of the onset and progression of complex diseases.

Indexed as

AgedAlzheimer DiseaseBiomarkersBrainCase-Control StudiesCognitive DysfunctionCohort StudiesDisease ProgressionEndophenotypesFemaleGenetic Predisposition to DiseaseGenome-Wide Association StudyHippocampusHumansMaleMultimodal ImagingBiomarkersLCOR protein, humanRepressor Proteins

Identifiers

PMID29860282
PMCPMC6022660
OpenAlexW2802278070

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.