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Multivariate analyses of peripheral blood leukocyte transcripts distinguish Alzheimer's, Parkinson's, control, and those at risk for developing Alzheimer's

Overview of attention for article published in Neurobiology of Aging, June 2017
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82

About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (96th percentile)
  • High Attention Score compared to outputs of the same age and source (93rd percentile)

Mentioned by

news
10 news outlets
blogs
1 blog
twitter
4 X users
reddit
1 Redditor

Citations

dimensions_citation
13 Dimensions

Readers on

mendeley
77 Mendeley
citeulike
1 CiteULike
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Title
Multivariate analyses of peripheral blood leukocyte transcripts distinguish Alzheimer's, Parkinson's, control, and those at risk for developing Alzheimer's
Published in
Neurobiology of Aging, June 2017
DOI 10.1016/j.neurobiolaging.2017.05.012
Pubmed ID
Authors

Elaine Delvaux, Diego Mastroeni, Jennifer Nolz, Nienwen Chow, Marwan Sabbagh, Richard J. Caselli, Eric M. Reiman, Frederick J. Marshall, Paul D. Coleman

Abstract

The need for a reliable, simple, and inexpensive blood test for Alzheimer's disease (AD) suitable for use in a primary care setting is widely recognized. This has led to a large number of publications describing blood tests for AD, which have, for the most part, not been replicable. We have chosen to examine transcripts expressed by the cellular, leukocyte compartment of blood. We have used hypothesis-based cDNA arrays and quantitative PCR to quantify the expression of selected sets of genes followed by multivariate analyses in multiple independent samples. Rather than a single study with no replicates, we chose an experimental design in which there were multiple replicates using different platforms and different sample populations. We have divided 177 blood samples and 27 brain samples into multiple replicates to demonstrate the ability to distinguish early clinical AD (Clinical Dementia Rating scale 0.5), Parkinson's disease (PD), and cognitively unimpaired APOE4 homozygotes, as well as to determine persons at risk for future cognitive impairment with significant accuracy. We assess our methods in a training/test set and also show that the variables we use distinguish AD, PD, and control brain. Importantly, we describe the variability of the weights assigned to individual transcripts in multivariate analyses in repeated studies and suggest that the variability we describe may be the cause of inability to repeat many earlier studies. Our data constitute a proof of principle that multivariate analysis of the transcriptome related to cell stress and inflammation of peripheral blood leukocytes has significant potential as a minimally invasive and inexpensive diagnostic tool for diagnosis and early detection of risk for AD.

X Demographics

X Demographics

The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 77 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 77 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 12 16%
Student > Ph. D. Student 9 12%
Student > Bachelor 9 12%
Other 7 9%
Student > Master 5 6%
Other 10 13%
Unknown 25 32%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 9 12%
Neuroscience 9 12%
Medicine and Dentistry 8 10%
Psychology 7 9%
Agricultural and Biological Sciences 4 5%
Other 11 14%
Unknown 29 38%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 82. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 07 September 2017.
All research outputs
#517,437
of 25,382,440 outputs
Outputs from Neurobiology of Aging
#67
of 4,418 outputs
Outputs of similar age
#11,047
of 330,053 outputs
Outputs of similar age from Neurobiology of Aging
#5
of 74 outputs
Altmetric has tracked 25,382,440 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 97th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,418 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.6. This one has done particularly well, scoring higher than 98% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 330,053 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 96% of its contemporaries.
We're also able to compare this research output to 74 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 93% of its contemporaries.