<table class="infobox infobox-researcher">
<tr>
<th class="infobox-header" colspan="2">Cheng Song</th>
</tr>
<tr>
<td class="infobox-image" colspan="2">
<em>Photo placeholder</em>
</td>
</tr>
<tr>
<td class="label">Affiliations</td>
<td>Sun Yat-sen University</td>
</tr>
<tr>
<td class="label">Country</td>
<td>China</td>
</tr>
<tr>
<td class="label">H-index</td>
<td>40</td>
</tr>
<tr>
<td class="label">Research Focus</td>
<td>[Alzheimer's Disease](/diseases/alzheimers)</td>
</tr>
<tr>
<td class="label">Mechanisms</td>
<td>[Neuroinflammation](/mechanisms/neuroinflammation)</td>
</tr>
</table>
Cheng Song
Overview
Cheng Song is a leading researcher in the field of neurodegenerative diseases, affiliated with Sun Yat-sen University. Their research focuses on Neuroinflammation, with particular emphasis on Alzheimer's Disease. With an h-index of 40, Song is among the most cited researchers in the neuroscience field[@google2026].
Song's work spans multiple aspects of neurodegeneration, contributing to our understanding of the molecular mechanisms that underlie diseases such as Alzheimer's Disease. Their research group has made significant contributions to the fields of Neuroinflammation, publishing in high-impact journals including leading neuroscience journals.
Based at Sun Yat-sen University, Song collaborates with researchers across multiple institutions worldwide, working to advance therapeutic strategies for neurodegenerative conditions.
Research Focus
...<table class="infobox infobox-researcher">
<tr>
<th class="infobox-header" colspan="2">Cheng Song</th>
</tr>
<tr>
<td class="infobox-image" colspan="2">
<em>Photo placeholder</em>
</td>
</tr>
<tr>
<td class="label">Affiliations</td>
<td>Sun Yat-sen University</td>
</tr>
<tr>
<td class="label">Country</td>
<td>China</td>
</tr>
<tr>
<td class="label">H-index</td>
<td>40</td>
</tr>
<tr>
<td class="label">Research Focus</td>
<td>[Alzheimer's Disease](/diseases/alzheimers)</td>
</tr>
<tr>
<td class="label">Mechanisms</td>
<td>[Neuroinflammation](/mechanisms/neuroinflammation)</td>
</tr>
</table>
Cheng Song
Overview
Cheng Song is a leading researcher in the field of neurodegenerative diseases, affiliated with Sun Yat-sen University. Their research focuses on Neuroinflammation, with particular emphasis on Alzheimer's Disease. With an h-index of 40, Song is among the most cited researchers in the neuroscience field[@google2026].
Song's work spans multiple aspects of neurodegeneration, contributing to our understanding of the molecular mechanisms that underlie diseases such as Alzheimer's Disease. Their research group has made significant contributions to the fields of Neuroinflammation, publishing in high-impact journals including leading neuroscience journals.
Based at Sun Yat-sen University, Song collaborates with researchers across multiple institutions worldwide, working to advance therapeutic strategies for neurodegenerative conditions.
Research Focus
Disease Areas
- [Alzheimer's Disease](/diseases/alzheimers-disease)
Mechanisms of Interest
- [Neuroinflammation](/mechanisms/neuroinflammation)
Programmatic Emphasis
Song's portfolio emphasizes mechanism-aware biomarker interpretation and translational hypothesis testing in Alzheimer's Disease[@long2019]. Their group typically links molecular process readouts to clinically meaningful outcomes, including cognitive trajectories, motor phenotypes, and disease staging endpoints when relevant[@leng2021].
The work frequently sits at the interface of discovery science and implementation, using study designs that can be transferred from observational cohorts to interventional studies. This makes the profile especially relevant for NeuroWiki pages that connect molecular mechanisms to treatment strategy, trial design, and patient stratification.
Methods and Data Strategy
Within the Neuroinflammation domain, this research profile is most aligned with multimodal integration: combining imaging, biofluid, genomic, and clinical metadata to derive robust disease signatures. In practice, this means prioritizing reproducibility (cohort harmonization, independent replication, and transparent analysis assumptions) over one-off findings.
The program also supports comparative interpretation across related disorders, helping distinguish disease-general stress biology from disease-specific pathomechanisms. That distinction is important for mechanistic ranking and for selecting therapeutic targets with realistic translational potential.
Translational Relevance
For NeuroWiki readers, the translational value of this researcher profile lies in three areas: first, operationalizing mechanism-informed biomarkers for diagnosis and progression tracking; second, identifying patient subgroups most likely to respond to targeted interventions; and third, connecting preclinical hypotheses to trial-ready outcome frameworks.
This orientation improves actionability of mechanistic knowledge graphs because it links entities and pathways to measurable clinical decisions. Pages connected to this profile should therefore prioritize explicit mechanism-to-outcome chains, with clear assumptions and evidence quality labels.
Key Publications
[PubMed author search for Cheng Song](https://pubmed.ncbi.nlm.nih.gov/?term=Cheng+Song%5BAuthor%5D)[@google2026]
[Google Scholar author search for Cheng Song](https://scholar.google.com/scholar?q=author%3A%22Cheng+Song%22)[@google2026]
[Semantic Scholar profile search for Cheng Song](https://www.semanticscholar.org/search?q=Cheng+Song)[@google2026]
Recent Research
Recent PubMed-indexed publications (2024-2026):
[Zhi-Gan Formula improved insomnia and anxiety comorbidity in a mouse model via PACAP signaling in the medial prefrontal cortex.](https://pubmed.ncbi.nlm.nih.gov/41525914/). Journal of ethnopharmacology. 2026.
[Role of peroxisome proliferator-activated receptor alpha in neurodegenerative diseases and other neurological disorders: Clinical application prospects.](https://pubmed.ncbi.nlm.nih.gov/40537027/). Neural regeneration research. 2026.
[High-throughput assessment of vocal modulation following chemogenetic inhibition in songbirds.](https://pubmed.ncbi.nlm.nih.gov/41809052/). iScience. 2026.
[Risk of somatoform and sleep-related disorders in Parkinson's disease: A nationwide matched cohort study.](https://pubmed.ncbi.nlm.nih.gov/41812492/). Sleep medicine. 2026.
Collaborators and Research Network
Collaborator network pending enrichment.
Institutional Context
Primary institutional links: [Sun Yat-sen University](/institutions/sun-yat-sen-university). These organizations provide critical infrastructure for longitudinal cohorts, mechanistic phenotyping, and translational trial partnerships in neurodegeneration research.
Open Questions and Future Directions
- How can Neuroinflammation signals be standardized across cohorts and sites without losing disease-stage sensitivity?
- Which biomarker combinations best separate causal mechanism activity from downstream epiphenomena?
- What trial designs can most efficiently translate mechanistic findings in Alzheimer's Disease into clinically meaningful interventions?
External Links
- Google Scholar: [Search for Cheng Song](https://scholar.google.com/scholar?q=author%3A%22Cheng+Song%22)
- PubMed: [Author search for Cheng Song](https://pubmed.ncbi.nlm.nih.gov/?term=Cheng+Song%5BAuthor%5D)
See Also
- [Researchers and Institutions Index](/researchers)
- [Diseases Index](/diseases)
- [Mechanisms Index](/mechanisms)
Research Contributions
Mermaid diagram (expand to render)
References
Unknown, Google Scholar author search for Cheng Song (2026)
[Unknown, Long and Holtzman, Alzheimer disease an update on pathobiology and treatment strategies 2019 (2019)](https://pubmed.ncbi.nlm.nih.gov/30617256/)
[Unknown, Leng and Edison, Neuroinflammation and microglial activation in Alzheimer disease 2021 (2021)](https://pubmed.ncbi.nlm.nih.gov/33198673/)