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Integrative network analysis of nineteen brain regions identifies molecular signatures and networks underlying selective regional vulnerability to Alzheimer’s disease

Overview of attention for article published in Genome Medicine, November 2016
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (87th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (62nd percentile)

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1 news outlet
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9 X users
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1 Facebook page

Citations

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236 Dimensions

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285 Mendeley
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Title
Integrative network analysis of nineteen brain regions identifies molecular signatures and networks underlying selective regional vulnerability to Alzheimer’s disease
Published in
Genome Medicine, November 2016
DOI 10.1186/s13073-016-0355-3
Pubmed ID
Authors

Minghui Wang, Panos Roussos, Andrew McKenzie, Xianxiao Zhou, Yuji Kajiwara, Kristen J. Brennand, Gabriele C. De Luca, John F. Crary, Patrizia Casaccia, Joseph D. Buxbaum, Michelle Ehrlich, Sam Gandy, Alison Goate, Pavel Katsel, Eric Schadt, Vahram Haroutunian, Bin Zhang

Abstract

Alzheimer's disease (AD) is the most common form of dementia, characterized by progressive cognitive impairment and neurodegeneration. However, despite extensive clinical and genomic studies, the molecular basis of AD development and progression remains elusive. To elucidate molecular systems associated with AD, we developed a large scale gene expression dataset from 1053 postmortem brain samples across 19 cortical regions of 125 individuals with a severity spectrum of dementia and neuropathology of AD. We excluded brain specimens that evidenced neuropathology other than that characteristic of AD. For the first time, we performed a pan-cortical brain region genomic analysis, characterizing the gene expression changes associated with a measure of dementia severity and multiple measures of the severity of neuropathological lesions associated with AD (neuritic plaques and neurofibrillary tangles) and constructing region-specific co-expression networks. We rank-ordered 44,692 gene probesets, 1558 co-expressed gene modules and 19 brain regions based upon their association with the disease traits. The neurobiological pathways identified through these analyses included actin cytoskeleton, axon guidance, and nervous system development. Using public human brain single-cell RNA-sequencing data, we computed brain cell type-specific marker genes for human and determined that many of the abnormally expressed gene signatures and network modules were specific to oligodendrocytes, astrocytes, and neurons. Analysis based on disease severity suggested that: many of the gene expression changes, including those of oligodendrocytes, occurred early in the progression of disease, making them potential translational/treatment development targets and unlikely to be mere bystander result of degeneration; several modules were closely linked to cognitive compromise with lesser association with traditional measures of neuropathology. The brain regional analyses identified temporal lobe gyri as sites associated with the greatest and earliest gene expression abnormalities. This transcriptomic network analysis of 19 brain regions provides a comprehensive assessment of the critical molecular pathways associated with AD pathology and offers new insights into molecular mechanisms underlying selective regional vulnerability to AD at different stages of the progression of cognitive compromise and development of the canonical neuropathological lesions of AD.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 285 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 3 1%
Unknown 282 99%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 59 21%
Researcher 58 20%
Student > Bachelor 28 10%
Student > Master 22 8%
Professor 18 6%
Other 43 15%
Unknown 57 20%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 55 19%
Neuroscience 45 16%
Agricultural and Biological Sciences 44 15%
Computer Science 17 6%
Medicine and Dentistry 16 6%
Other 35 12%
Unknown 73 26%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 15. 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 23 July 2021.
All research outputs
#2,166,190
of 23,318,744 outputs
Outputs from Genome Medicine
#495
of 1,457 outputs
Outputs of similar age
#39,354
of 313,105 outputs
Outputs of similar age from Genome Medicine
#13
of 35 outputs
Altmetric has tracked 23,318,744 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 90th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,457 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 25.9. This one has gotten more attention than average, scoring higher than 65% 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 313,105 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 87% of its contemporaries.
We're also able to compare this research output to 35 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 62% of its contemporaries.