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Network-driven plasma proteomics expose molecular changes in the Alzheimer’s brain

Overview of attention for article published in Molecular Neurodegeneration, April 2016
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  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (78th percentile)

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13 X users
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1 Facebook page

Citations

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27 Dimensions

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131 Mendeley
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Title
Network-driven plasma proteomics expose molecular changes in the Alzheimer’s brain
Published in
Molecular Neurodegeneration, April 2016
DOI 10.1186/s13024-016-0095-2
Pubmed ID
Authors

Philipp A. Jaeger, Kurt M. Lucin, Markus Britschgi, Badri Vardarajan, Ruo-Pan Huang, Elizabeth D. Kirby, Rachelle Abbey, Bradley F. Boeve, Adam L. Boxer, Lindsay A. Farrer, NiCole Finch, Neill R. Graff-Radford, Elizabeth Head, Matan Hofree, Ruochun Huang, Hudson Johns, Anna Karydas, David S. Knopman, Andrey Loboda, Eliezer Masliah, Ramya Narasimhan, Ronald C. Petersen, Alexei Podtelezhnikov, Suraj Pradhan, Rosa Rademakers, Chung-Huan Sun, Steven G. Younkin, Bruce L. Miller, Trey Ideker, Tony Wyss-Coray

Abstract

Biological pathways that significantly contribute to sporadic Alzheimer's disease are largely unknown and cannot be observed directly. Cognitive symptoms appear only decades after the molecular disease onset, further complicating analyses. As a consequence, molecular research is often restricted to late-stage post-mortem studies of brain tissue. However, the disease process is expected to trigger numerous cellular signaling pathways and modulate the local and systemic environment, and resulting changes in secreted signaling molecules carry information about otherwise inaccessible pathological processes. To access this information we probed relative levels of close to 600 secreted signaling proteins from patients' blood samples using antibody microarrays and mapped disease-specific molecular networks. Using these networks as seeds we then employed independent genome and transcriptome data sets to corroborate potential pathogenic pathways. We identified Growth-Differentiation Factor (GDF) signaling as a novel Alzheimer's disease-relevant pathway supported by in vivo and in vitro follow-up experiments, demonstrating the existence of a highly informative link between cellular pathology and changes in circulatory signaling proteins.

X Demographics

X Demographics

The data shown below were collected from the profiles of 13 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 131 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 131 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 28 21%
Researcher 28 21%
Student > Bachelor 14 11%
Student > Master 12 9%
Other 6 5%
Other 20 15%
Unknown 23 18%
Readers by discipline Count As %
Agricultural and Biological Sciences 27 21%
Neuroscience 23 18%
Biochemistry, Genetics and Molecular Biology 14 11%
Medicine and Dentistry 14 11%
Engineering 5 4%
Other 23 18%
Unknown 25 19%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 8. 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 27 June 2020.
All research outputs
#4,421,870
of 24,417,958 outputs
Outputs from Molecular Neurodegeneration
#559
of 910 outputs
Outputs of similar age
#64,772
of 303,517 outputs
Outputs of similar age from Molecular Neurodegeneration
#16
of 18 outputs
Altmetric has tracked 24,417,958 research outputs across all sources so far. Compared to these this one has done well and is in the 81st percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 910 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 15.6. This one is in the 38th percentile – i.e., 38% of its peers scored the same or lower than it.
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 303,517 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 78% of its contemporaries.
We're also able to compare this research output to 18 others from the same source and published within six weeks on either side of this one. This one is in the 16th percentile – i.e., 16% of its contemporaries scored the same or lower than it.