Overview
flowchart TD
AD["AD"] -->|"causes"| neurodegeneration["neurodegeneration"]
AD["AD"] -->|"causes"| memory_loss["memory_loss"]
AD["AD"] -->|"associated with"| TAU["TAU"]
AD["AD"] -->|"causes"| IMMUNE_TOL["IMMUNE_TOL"]
AD["AD"] -->|"causes"| DEMENTIA["DEMENTIA"]
AD["AD"] -->|"inhibits"| cholinergic_transmission["cholinergic_transmission"]
AD["AD"] -->|"regulates"| PROTEOME["PROTEOME"]
AD["AD"] -->|"associated with"| CHOLINERGIC_TRANSMISSION["CHOLINERGIC_TRANSMISSION"]
AD["AD"] -->|"associated with"| GLYCOLYTIC_PATHWAY["GLYCOLYTIC_PATHWAY"]
TDP_43["TDP-43"] -->|"associated with"| Ad["Ad"]
TAU["TAU"] -->|"implicated in"| AD["AD"]
TAU["TAU"] -->|"associated with"| AD["AD"]
APOE["APOE"] -->|"associated with"| AD["AD"]
MIR_146A["MIR-146A"] -->|"associated with"| AD["AD"]
style AD fill:#4fc3f7,stroke:#333,color:#000
The AT(N) classification system is a research framework established by the National Institute on Aging and Alzheimer's Association (NIA-AA) to categorize Alzheimer's disease biomarkers based on three core pathological processes: Amyloid (A), Tau (T), and Neurodegeneration (N). This framework provides a standardized approach for biomarker-based diagnosis and staging of AD. [@hansson2019]
Core Biomarker Categories
A: Amyloid Biomarkers
These biomarkers detect the presence of amyloid-beta (Aβ) plaque pathology in the brain. [@palmqvist2020]
...Overview
Mermaid diagram (expand to render)
The AT(N) classification system is a research framework established by the National Institute on Aging and Alzheimer's Association (NIA-AA) to categorize Alzheimer's disease biomarkers based on three core pathological processes: Amyloid (A), Tau (T), and Neurodegeneration (N). This framework provides a standardized approach for biomarker-based diagnosis and staging of AD. [@hansson2019]
Core Biomarker Categories
A: Amyloid Biomarkers
These biomarkers detect the presence of amyloid-beta (Aβ) plaque pathology in the brain. [@palmqvist2020]
| Biomarker | Fluid | Imaging | Key Features | [@zetterberg2019]
|-----------|-------|---------|--------------| [@khalil2018]
| Aβ42/40 ratio | CSF, Plasma | - | Decreased in AD; ratio more specific than Aβ42 alone | [@fleisher2020]
| Aβ42 | CSF | - | Decreased due to plaque deposition | [@kanemaru2020]
| Amyloid PET | - | PET (PiB, Florbetapir, Florbetaben) | Visualizes cortical amyloid binding | [@park2021]
Diagnostic Performance: [@li2022]
- CSF Aβ42/40 ratio: Sensitivity 85-95%, Specificity 85-90% for detecting cerebral amyloid
- Amyloid PET: Sensitivity 90-95%, Specificity 90-95% for neuritic plaques
References:
[Jack et al., NIA-AA Framework (2018)](https://doi.org/10.1016/j.jalz.2018.02.013)
[Hansson et al., CSF Aβ42/40 for AD diagnosis (2019)](https://doi.org/10.1002/alz.12008)
T: Tau Biomarkers
These biomarkers detect tau pathology, including neurofibrillary tangles (NFTs) and tau positivities.
T (Tau) Subcategories
| Subcategory | Biomarker | Fluid | Imaging | Key Features |
|-------------|-----------|-------|---------|--------------|
| T-tau (total) | t-Tau | CSF | - | Non-specific neuronal damage marker |
| T-tau (phosphorylated) | p-Tau181, p-Tau217, p-Tau231 | CSF, Plasma | - | AD-specific, correlates with NFT burden |
| Tau PET | - | - | PET (Flortaucipir, MK-6240, PI-2620) | Visualizes tau neurofibrillary tangles |
Diagnostic Performance:
- CSF p-Tau181: Sensitivity 80-90%, Specificity 85-95% for AD
- Plasma p-Tau217: Sensitivity 85-95%, Specificity 85-90% for AD, emerging as optimal blood biomarker
- Tau PET: Sensitivity 85-95%, Specificity 85-90% for detecting tau pathology
References:
[Palmqvist et al., Plasma p-Tau217 for AD (2020)](https://doi.org/10.1001/jamaneurol.2020.0981)
[Fleisher et al., Tau PET imaging (2020)](https://doi.org/10.1016/j.jalz.2020.01.013)
N: Neurodegeneration Biomarkers
These biomarkers indicate neuronal injury, synaptic loss, and brain atrophy.
| Biomarker | Fluid | Imaging | Key Features |
|-----------|-------|---------|--------------|
| Total tau (t-Tau) | CSF | - | Non-specific, elevated in various dementias |
| Neurofilament Light (NfL) | CSF, Blood | - | Axonal injury marker, non-specific |
| Neurogranin | CSF | - | Synaptic marker, AD-specific |
| VILIP-1 | CSF | - | Neuronal injury marker |
| FDG-PET | - | PET | Hypometabolism in AD-vulnerable regions |
| MRI atrophy | - | MRI | Hippocampal, entorhinal cortical atrophy |
Diagnostic Performance:
- CSF t-Tau: Sensitivity 70-85%, Specificity 60-75% (less specific than p-Tau)
- CSF Neurogranin: Sensitivity 75-85%, Specificity 75-85% for AD
- Blood NfL: Sensitivity 70-85%, Specificity 65-80%, useful for disease progression
References:
[Zetterberg et al., Neurofilament light chain (2019)](https://doi.org/10.1001/jamaneurol.2019.0765)
[Khalil et al., Neurogranin as AD biomarker (2018)](https://doi.org/10.1016/j.jalz.2017.09.014)
AT(N) Profiles in Clinical Practice
Normal Biomarker Profile
- A-/T-(N)-: Cognitively normal, no significant AD pathology
Alzheimer's Disease Continuum
| Stage | A | T | N | Clinical Status |
|-------|---|---|---|-----------------|
| Preclinical AD | + | - | - | Cognitively normal |
| Preclinical AD | + | + | - | Cognitively normal, downstream tau |
| MCI due to AD | + | + | -/+ | Mild cognitive impairment |
| Dementia due to AD | + | + | + | Dementia with AD pathology |
Biomarker Combinations and Clinical Utility
AT(N) Combinations for Differential Diagnosis
| Clinical Syndrome | A | T | N | Interpretation |
|------------------|---|---|---|----------------|
| Typical AD | + | + | + | AD dementia |
| AD with Lewy bodies | + | + | + | + α-synuclein markers |
| FTLD | - | + (4R) | + | Tau PET negative, no amyloid |
| Vascular dementia | - | - | + | Neurodegeneration without AD |
Blood-Based Biomarker Panels
Emerging blood-based biomarker panels are simplifying AT(N) profiling:
| Panel Components | Detection |
|-----------------|-----------|
| Aβ42/40 + p-Tau217 | A+T profile |
| p-Tau181/NfL | T+N profile |
| p-Tau217 + NfL + GFAP | Full AT(N) approximation |
Cost Comparison:
- CSF biomarker panel: $500-1000
- Amyloid PET: $3000-5000
- Tau PET: $3000-7000
- Blood biomarkers: $200-500
Accessibility: Blood-based biomarkers offer the highest accessibility, particularly in primary care settings.
Non-Western Population Data
Asian Population Studies
Japanese Cohorts:
- J-ADNI studies show similar CSF Aβ42/40 ratio performance in Japanese populations
- Plasma p-Tau181 shows comparable diagnostic accuracy in Japanese cohorts
Korean Cohorts:
- Korean AD research network has validated amyloid PET criteria in Korean populations
- CSF p-Tau231 shows promise for early detection in Korean cohorts
Chinese Cohorts:
- Chinese Biomarker Consortium demonstrates Aβ42/40 ratio utility
- Plasma NfL reference ranges established for Chinese populations
References:
[Kanemaru et al., Japanese AD biomarkers (2020)](https://pubmed.ncbi.nlm.nih.gov/32156283/)
[Park et al., Korean AD biomarker validation (2021)](https://pubmed.ncbi.nlm.nih.gov/33856345/)
[Li et al., Chinese AD biomarker studies (2022)](https://pubmed.ncbi.nlm.nih/35058321/)
Regulatory Status
| Biomarker | FDA Status | CE Mark |
|-----------|------------|---------|
| Amyloid PET (Florbetapir) | Approved | Yes |
| CSF Aβ42, t-Tau, p-Tau181 | Research use only | Yes (some) |
| Plasma p-Tau (Elecsys) | FDA breakthrough device | Under review |
| Blood NfL | Research use only | Yes (some) |
Clinical Recommendations
Recommended Biomarker Panel by Setting
| Setting | First-line | Confirmatory |
|---------|-----------|--------------|
| Memory clinic | Blood Aβ42/40 + p-Tau | CSF biomarkers or PET |
| Primary care | Blood p-Tau217 | Referral for confirmation |
| Research | Full AT(N) panel | N/A |
- [Alzheimer's Disease](/diseases/alzheimers-disease)
- [Parkinson's Disease](/diseases/parkinsons-disease)
External Links
- [PubMed](https://pubmed.ncbi.nlm.nih.gov/)
- [KEGG Pathways](https://www.genome.jp/kegg/pathway.html)
Allen Brain Atlas Resources
- [Allen Brain Atlas - Gene Expression](https://human.brain-map.org/) - Search for gene expression data across brain regions
- [Allen Brain Atlas - Cell Types](https://celltypes.brain-map.org/) - Explore neuronal cell type taxonomy
References
[DOI:10.1016/j.jalz.2018.02.013](https://doi.org/10.1002/alz.12008)
[DOI:10.1001/jamaneurol.2020.0981](https://doi.org/10.1001/jamaneurol.2019.0765)
[Khalil et al., Neurogranin as AD biomarker (2018) (2018)](/[DOI:10.1016/j.jalz.2017.09.014](https://pubmed.ncbi.nlm.nih.gov/32156283/)
[Park et al., Korean AD biomarker validation (2021) (2021)](https://pubmed.ncbi.nlm.nih.gov/33856345/)
[Li et al., Chinese AD biomarker studies (2022) (2022)](https://pubmed.ncbi.nlm.nih.gov/35058321/)Pathway Diagram
The following diagram shows the key molecular relationships involving AT(N) Biomarker Classification for Alzheimer's Disease discovered through SciDEX knowledge graph analysis:
Mermaid diagram (expand to render)