Evidence map›Paper›PMID 24959311›Full record

ArticleInternational journal of molecular epidemiology and genetics2014

Practical detection of a definitive biomarker panel for Alzheimer's disease; comparisons between matched plasma and cerebrospinal fluid.

Joanna L Richens, Kelly-Ann Vere, Roger A Light, Daniele Soria, Jonathan Garibaldi, A David Smith, Donald Warden, Gordon Wilcock, Nin Bajaj, Kevin Morgan and 1 more

Open access · greenAbstract read
In one paragraph

Article in International journal of molecular epidemiology and genetics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed, 2 pooled it
1.6field-weighted citation impact, top 18% 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, 2 syntheses or guidelines pooled it, 23 citations in OpenAlex.

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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

11 authors at 5 institutions in 1 country.

Joanna L RichensCell Biophysics Group, Institute of Biophysics, Imaging and Optical Science, School of Life Sciences, University of Nottingham, University Park Nottingham, United Kingdom.
Kelly-Ann VereCell Biophysics Group, Institute of Biophysics, Imaging and Optical Science, School of Life Sciences, University of Nottingham, University Park Nottingham, United Kingdom.
Roger A LightInstitute of Biophysics, Imaging and Optical Science, University of Nottingham, University Park Nottingham, United Kingdom.
Daniele SoriaSchool of Computer Science, University of Nottingham, Jubilee Campus Nottingham, United Kingdom ; Advanced Data Analysis Centre, University of Nottingham Nottingham, United Kingdom.
Jonathan GaribaldiSchool of Computer Science, University of Nottingham, Jubilee Campus Nottingham, United Kingdom ; Advanced Data Analysis Centre, University of Nottingham Nottingham, United Kingdom.
A David SmithOxford Project to Investigate Memory and Ageing (OPTIMA), University Department of Physiology, Anatomy and Genetics, University of Oxford Oxford, United Kingdom.
Donald WardenOxford Project to Investigate Memory and Ageing (OPTIMA), University Department of Physiology, Anatomy and Genetics, University of Oxford Oxford, United Kingdom.
Gordon WilcockOxford Project to Investigate Memory and Ageing, Nuffield Department of Clinical Medicine, John Radcliffe Hospital Oxford, United Kingdom.
Nin BajajDepartment of Neurology, Nottingham University Hospitals NHS Trust, Queen's Medical Centre Nottingham, United Kingdom.
Kevin MorganSchool of Life Sciences, Translational Cell Sciences - Human Genetics Group, University of Nottingham, Queen's Medical Centre Nottingham, United Kingdom.
Paul O'SheaCell Biophysics Group, Institute of Biophysics, Imaging and Optical Science, School of Life Sciences, University of Nottingham, University Park Nottingham, United Kingdom.
University of Nottingham · GBUniversity of Oxford · GBJohn Radcliffe Hospital · GBNottingham University Hospitals NHS Trust · GBQueen's Medical Centre · GB

Funding

Medical Research Council G1001500
6 · The paper itself

Abstract

Previous mass spectrometry analysis of cerebrospinal fluid (CSF) has allowed the identification of a panel of molecular markers that are associated with Alzheimer's disease (AD). The panel comprises Amyloid beta, Apolipoprotein E, Fibrinogen alpha chain precursor, Keratin type I cytoskeletal 9, Serum albumin precursor, SPARC-like 1 protein and Tetranectin. Here we report the development and implementation of immunoassays to measure the abundance and diagnostic capacity of these putative biomarkers in matched lumbar CSF and blood plasma samples taken in life from individuals confirmed at post-mortem as suffering from AD (n = 10) and from screened 'cognitively healthy' subjects (n = 18). The inflammatory components of Alzheimer's disease were also investigated. Employment of supervised learning techniques permitted examination of the interrelated expression patterns of the putative biomarkers and identified inflammatory components, resulting in biomarker panels with a diagnostic accuracy of 87.5% and 86.7% for the plasma and CSF datasets respectively. This is extremely important as it offers an ideal high-throughput and relatively inexpensive population screening approach. It appears possible to determine the presence or absence of AD based on our biomarker panel and it seems likely that a cheap and rapid blood test for AD is feasible.

Indexed as

Alzheimer’s diseasebiomarkerblood plasmacerebrospinal fluid

Identifiers

PMID24959311
PMCPMC4065395
OpenAlexW1566803361

What OpenQuestion holds

Textmetadata
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.