| Title |
Analyzing the genes related to Alzheimer’s disease via a network and pathway-based approach
|
|---|---|
| Published in |
Alzheimer's Research & Therapy, April 2017
|
| DOI | 10.1186/s13195-017-0252-z |
| Pubmed ID | |
| Authors |
Yan-Shi Hu, Juncai Xin, Ying Hu, Lei Zhang, Ju Wang |
| Abstract |
Our understanding of the molecular mechanisms underlying Alzheimer's disease (AD) remains incomplete. Previous studies have revealed that genetic factors provide a significant contribution to the pathogenesis and development of AD. In the past years, numerous genes implicated in this disease have been identified via genetic association studies on candidate genes or at the genome-wide level. However, in many cases, the roles of these genes and their interactions in AD are still unclear. A comprehensive and systematic analysis focusing on the biological function and interactions of these genes in the context of AD will therefore provide valuable insights to understand the molecular features of the disease. In this study, we collected genes potentially associated with AD by screening publications on genetic association studies deposited in PubMed. The major biological themes linked with these genes were then revealed by function and biochemical pathway enrichment analysis, and the relation between the pathways was explored by pathway crosstalk analysis. Furthermore, the network features of these AD-related genes were analyzed in the context of human interactome and an AD-specific network was inferred using the Steiner minimal tree algorithm. We compiled 430 human genes reported to be associated with AD from 823 publications. Biological theme analysis indicated that the biological processes and biochemical pathways related to neurodevelopment, metabolism, cell growth and/or survival, and immunology were enriched in these genes. Pathway crosstalk analysis then revealed that the significantly enriched pathways could be grouped into three interlinked modules-neuronal and metabolic module, cell growth/survival and neuroendocrine pathway module, and immune response-related module-indicating an AD-specific immune-endocrine-neuronal regulatory network. Furthermore, an AD-specific protein network was inferred and novel genes potentially associated with AD were identified. By means of network and pathway-based methodology, we explored the pathogenetic mechanism underlying AD at a systems biology level. Results from our work could provide valuable clues for understanding the molecular mechanism underlying AD. In addition, the framework proposed in this study could be used to investigate the pathological molecular network and genes relevant to other complex diseases or phenotypes. |
X Demographics
The data shown below were collected from the profiles of 7 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 2 | 29% |
| United States | 2 | 29% |
| Germany | 1 | 14% |
| Unknown | 2 | 29% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 4 | 57% |
| Scientists | 2 | 29% |
| Science communicators (journalists, bloggers, editors) | 1 | 14% |
Mendeley readers
The data shown below were compiled from readership statistics for 172 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Germany | 1 | <1% |
| Unknown | 171 | 99% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 26 | 15% |
| Student > Ph. D. Student | 22 | 13% |
| Student > Bachelor | 18 | 10% |
| Student > Master | 16 | 9% |
| Other | 12 | 7% |
| Other | 26 | 15% |
| Unknown | 52 | 30% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 40 | 23% |
| Neuroscience | 27 | 16% |
| Agricultural and Biological Sciences | 14 | 8% |
| Medicine and Dentistry | 6 | 3% |
| Computer Science | 5 | 3% |
| Other | 21 | 12% |
| Unknown | 59 | 34% |
Attention Score in Context
This research output has an Altmetric Attention Score of 14. 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 13 January 2021.
All research outputs
#2,546,666
of 25,402,889 outputs
Outputs from Alzheimer's Research & Therapy
#568
of 1,469 outputs
Outputs of similar age
#45,798
of 323,467 outputs
Outputs of similar age from Alzheimer's Research & Therapy
#8
of 24 outputs
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We're also able to compare this research output to 24 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 70% of its contemporaries.