Biomarker Rankings

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Biomarker Rankings

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Overview

Biomarker Rankings provides a systematic comparison of neurodegenerative disease biomarkers across multiple dimensions — clinical utility, validation status, research activity, diagnostic accuracy, and cost-effectiveness. This page helps researchers and clinicians identify the most promising and well-established biomarkers for [Alzheimer's disease](/diseases/alzheimers-disease), [Parkinson's disease](/diseases/parkinsons-disease), [ALS](/diseases/amyotrophic-lateral-sclerosis), and related disorders.

Biomarkers are ranked using a multi-criteria framework that integrates performance data from peer-reviewed literature, regulatory status across major jurisdictions (US FDA, EU CE, Asia PMDA/NMPA/KFDA), population-specific validation (Western, Japanese, Korean, Chinese cohorts), and clinical adoption metrics[@blennow2019][@hansson2022].

Rankings by Clinical Utility

The following rankings reflect practical usefulness in clinical settings — diagnosis, disease staging, prognosis, and treatment monitoring.

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Overview

Biomarker Rankings provides a systematic comparison of neurodegenerative disease biomarkers across multiple dimensions — clinical utility, validation status, research activity, diagnostic accuracy, and cost-effectiveness. This page helps researchers and clinicians identify the most promising and well-established biomarkers for [Alzheimer's disease](/diseases/alzheimers-disease), [Parkinson's disease](/diseases/parkinsons-disease), [ALS](/diseases/amyotrophic-lateral-sclerosis), and related disorders.

Biomarkers are ranked using a multi-criteria framework that integrates performance data from peer-reviewed literature, regulatory status across major jurisdictions (US FDA, EU CE, Asia PMDA/NMPA/KFDA), population-specific validation (Western, Japanese, Korean, Chinese cohorts), and clinical adoption metrics[@blennow2019][@hansson2022].

Rankings by Clinical Utility

The following rankings reflect practical usefulness in clinical settings — diagnosis, disease staging, prognosis, and treatment monitoring.

| Rank | Biomarker | Primary Use | Disease | Clinical Status | T-Score | D-Score |
|------|-----------|-------------|---------|----------------|---------|---------|
| 1 | Amyloid PET (Florbetapir) | Diagnosis | AD | FDA Approved, CE Marked | Gold | High |
| 2 | CSF p-Tau181 | Diagnosis/Staging | AD | Clinical Use | Gold | High |
| 3 | Plasma p-Tau217 | Diagnosis/Screening | AD | FDA Breakthrough Device | Gold | High |
| 4 | Alpha-synuclein SAA (RT-QuIC) | Diagnosis | PD/DLB | Clinical Use | Silver | Moderate |
| 5 | CSF Aβ42/40 ratio | Diagnosis | AD | Clinical Use | Gold | Moderate |
| 6 | NfL (plasma/CSF) | Prognosis | ALS/AD/PD | Clinical Use | Silver | High |
| 7 | Tau PET (Flortaucipir) | Staging | AD | FDA Approved | Gold | High |
| 8 | DaT-SPECT (Ioflupane) | Diagnosis | PD | FDA Approved | Gold | High |
| 9 | CSF total tau | Diagnostic/Auxiliary | AD | Clinical Use | Silver | Moderate |
| 10 | GFAP (plasma) | Diagnosis/Auxiliary | AD | Research Use | Silver | Moderate |
| 11 | Skin biopsy (p-α-syn) | Diagnosis | PD | Emerging | Silver | Emerging |
| 12 | FDG-PET | Differential Diagnosis | AD/FTD/DLB | Clinical Use | Silver | High |

T-Score: Gold = established standard, Silver = established but non-standard. D-Score: High = high diagnostic certainty, Moderate = moderate, Emerging = needs further validation.

Key insights: Amyloid PET and CSF p-Tau181 remain the gold standard for AD diagnosis. Plasma p-Tau217 has rapidly ascended due to its non-invasive nature and high accuracy[@leuzy2024]. For PD, alpha-synuclein seed amplification assays (SAA) have replaced DaT-SPECT as the top diagnostic tool in research settings, though DaT-SPECT remains clinically established.

Rankings by Validation Status

Biomarker validation follows a structured pathway from analytical validation to clinical validation to clinical utility. Higher validation = more ready for clinical deployment.

| Rank | Biomarker | Validation Level | Evidence Strength | Clinical Readiness | Major Gaps |
|------|-----------|-----------------|-------------------|-------------------|------------|
| 1 | Amyloid PET | Level 1 (Clinical) | AT(N) confirmed | Fully deployed | Cost, access |
| 2 | Tau PET (Flortaucipir) | Level 1 (Clinical) | T-N confirmed | Fully deployed | Off-target binding |
| 3 | CSF Aβ42/40 | Level 1 (Clinical) | A confirmed | Widely available | Lumbar puncture |
| 4 | CSF p-Tau181 | Level 1 (Clinical) | T confirmed | Widely available | Assay harmonization |
| 5 | CSF t-Tau | Level 2 (Evidence) | N confirmed | Available | Non-specific |
| 6 | Plasma NfL | Level 2 (Evidence) | N confirmed | Available | Disease-specificity |
| 7 | Alpha-syn SAA (RT-QuIC) | Level 2 (Evidence) | α-syn confirmed | Emerging | Standardization |
| 8 | Plasma p-Tau217 | Level 2 (Evidence) | T confirmed | Early adoption | Cutoff standardization |
| 9 | GFAP (plasma) | Level 2 (Evidence) | A+N context | Research use | Age effects |
| 10 | Plasma p-Tau231 | Level 3 (Promising) | Early evidence | Research use | Large-cohort validation |

Clinical Readiness Scale: Level 1 = Standard of care, routinely used in clinical trials and specialized memory clinics. Level 2 = Established in research, transitioning to clinical use. Level 3 = Promising early data, requires further validation.

Rankings by Research Activity

Publication counts and clinical trial activity reflect scientific investment and momentum. Metrics from PubMed (2024-2025) and ClinicalTrials.gov.

| Rank | Biomarker | PubMed Count (2024) | Clinical Trials | Research Trend | Hot Topics |
|------|-----------|---------------------|-----------------|----------------|------------|
| 1 | Amyloid-beta (Aβ) | 6,500+ | 200+ | Stable/Growing | Anti-amyloid therapies |
| 2 | p-Tau (all isoforms) | 4,200+ | 150+ | Rapid Growth | p-Tau217 blood tests |
| 3 | NfL (neurofilament) | 3,800+ | 120+ | Rapid Growth | Blood-based monitoring |
| 4 | Alpha-synuclein | 3,500+ | 80+ | Growing | Seed amplification |
| 5 | GFAP (glial) | 1,800+ | 60+ | Rapid Growth | Astroglial activation |
| 6 | TDP-43 | 1,400+ | 40+ | Rapid Growth | LATE-NC, ALS-FTD |
| 7 | sTREM2 | 800+ | 25+ | Growing | Microglial biology |
| 8 | Neurogranin | 750+ | 20+ | Growing | Synaptic dysfunction |
| 9 | YKL-40 (CHI3L1) | 500+ | 15+ | Stable | Neuroinflammation |
| 10 | VILIP-1 | 250+ | 8+ | Stable | Neuronal injury |
| 11 | NPTX2/NPTXR | 200+ | 10+ | Growing | Synaptic integrity |

Research Activity Insights: p-Tau biomarkers show the fastest growth rate, driven by the development of plasma-based tests that enable large-scale screening. NfL research activity is expanding beyond AD into PD, ALS, MS, and traumatic brain injury. GFAP has emerged as a major research focus following its identification as an early marker of astroglial dysfunction.

Rankings by Diagnostic Accuracy

Sensitivity, specificity, and AUC values represent peak performance across all published studies. Ranges reflect variability by cohort, assay platform, and disease stage.

Alzheimer's Disease Biomarkers

| Rank | Biomarker | Sensitivity | Specificity | AUC | Sample Type | AT(N) Category |
|------|-----------|-------------|-------------|-----|-------------|----------------|
| 1 | Amyloid PET | 90-95% | 90-95% | 0.94-0.97 | Imaging | A |
| 2 | Plasma p-Tau217 | 87-95% | 85-93% | 0.93-0.97 | Blood | T |
| 3 | CSF p-Tau181 | 82-92% | 87-95% | 0.90-0.95 | CSF | T |
| 4 | Tau PET (Flortaucipir) | 85-95% | 85-92% | 0.88-0.94 | Imaging | T |
| 5 | CSF Aβ42/40 | 78-88% | 80-88% | 0.84-0.90 | CSF | A |
| 6 | Plasma p-Tau181 | 78-88% | 80-90% | 0.84-0.92 | Blood | T |
| 7 | Plasma GFAP | 70-85% | 72-85% | 0.78-0.86 | Blood | A/N |
| 8 | CSF t-Tau | 72-85% | 68-80% | 0.74-0.84 | CSF | (N) |
| 9 | Plasma NfL | 68-82% | 65-78% | 0.70-0.82 | Blood | (N) |
| 10 | FDG-PET | 75-88% | 70-82% | 0.76-0.85 | Imaging | (N) |

Parkinson's Disease and Synucleinopathies

| Rank | Biomarker | Sensitivity | Specificity | AUC | Sample Type |
|------|-----------|-------------|-------------|-----|-------------|
| 1 | α-Syn SAA (CSF, RT-QuIC) | 82-92% | 88-95% | 0.89-0.95 | CSF |
| 2 | Skin biopsy (p-α-syn) | 78-90% | 85-95% | 0.85-0.93 | Tissue |
| 3 | DaT-SPECT | 82-88% | 78-88% | 0.82-0.90 | Imaging |
| 4 | MIBG cardiac scintigraphy | 75-85% | 75-90% | 0.78-0.88 | Imaging |
| 5 | FDG-PET (PDRP pattern) | 78-88% | 78-88% | 0.80-0.88 | Imaging |
| 6 | Plasma NfL | 68-80% | 70-82% | 0.72-0.82 | Blood |
| 7 | Olfactory testing (UPSIT) | 65-80% | 60-75% | 0.65-0.78 | Behavioral |

ALS Biomarkers

| Rank | Biomarker | Sensitivity | Specificity | AUC | Sample Type |
|------|-----------|-------------|-------------|-----|-------------|
| 1 | Plasma NfL | 82-95% | 78-90% | 0.88-0.95 | Blood |
| 2 | CSF NfL | 85-95% | 80-90% | 0.88-0.95 | CSF |
| 3 | Urine p-Tau181 | 70-85% | 72-88% | 0.76-0.88 | Urine |
| 4 | CSF p-Tau231 | 65-80% | 68-82% | 0.72-0.83 | CSF |
| 5 | Progranulin (plasma) | 75-85% | 85-95% | 0.82-0.90 | Blood |

Rankings by Cost-Effectiveness

Cost-effectiveness considers both direct costs and diagnostic yield per patient. Rankings integrate cost per test, clinical impact, and downstream savings from early diagnosis.

| Rank | Biomarker | Cost Per Test | Setting | Yield | Cost-Effectiveness |
|------|-----------|---------------|---------|-------|-------------------|
| 1 | Plasma p-Tau181/217 | $200-500 | Primary care | High | Excellent |
| 2 | Blood NfL | $150-400 | Primary care | Moderate | Excellent |
| 3 | Olfactory testing | $20-80 | Primary care | Moderate | Good |
| 4 | Plasma GFAP | $180-400 | Specialty care | Moderate | Good |
| 5 | CSF p-Tau181 | $400-800 | Specialty care | High | Good |
| 6 | Gait/digital biomarkers | $50-200 | Home/Clinic | Moderate | Good |
| 7 | FDG-PET | $1,500-3,000 | Imaging center | High | Moderate |
| 8 | Amyloid PET | $3,000-5,000 | Imaging center | Very High | Moderate |
| 9 | Tau PET | $3,000-7,000 | Imaging center | High | Limited |
| 10 | DaT-SPECT | $2,000-4,000 | Imaging center | High | Limited |

Interpretation: Blood-based biomarkers (p-Tau, NfL, GFAP) dominate cost-effectiveness rankings, making them ideal for population screening. Imaging modalities remain essential for confirmatory diagnosis but are constrained by cost and accessibility.

Rankings by Regulatory Status

Regulatory approval varies significantly across jurisdictions. Rankings reflect the broadest clinical deployment potential.

| Rank | Biomarker | US FDA | EU CE-IVDR | Japan PMDA | China NMPA | Korea KFDA |
|------|-----------|--------|-----------|-----------|-----------|------------|
| 1 | Florbetapir (Amyvid) PET | Approved | Yes | Yes | Yes | Yes |
| 2 | Florbetaben (Neuraceq) PET | Approved | Yes | Yes | Yes | Yes |
| 3 | Flutemetamol (Vizamyl) PET | Approved | Yes | Yes | Yes | Yes |
| 4 | Flortaucipir (Tauvid) PET | Approved | Yes | Yes | Yes | Yes |
| 5 | DaT-SPECT (DaTscan) | Approved | Yes | Yes | Yes | Yes |
| 6 | CSF Aβ42, t-Tau, p-Tau181 | LDT | IVD-R | LDT | LDT | LDT |
| 7 | Plasma NfL (Quanterix) | LDT | IVD-R | LDT | LDT | LDT |
| 8 | Plasma p-Tau217 (ALZpath) | Breakthrough Device | Under review | LDT | LDT | LDT |
| 9 | Lumipulse p-Tau181 | FDA cleared | Yes | Yes | Yes | Yes |
| 10 | Skin biopsy p-α-syn | LDT | IVD-R | Research | Research | Research |

Note: "LDT" = laboratory-developed test (not FDA-cleared but used in CLIA-certified labs). "IVD-R" = under EU In Vitro Diagnostic Regulation. Asian regulatory approval varies by country, with PMDA (Japan) and NMPA (China) increasingly harmonizing with Western standards.

Rankings by Non-Western Population Validation

Population-specific validation is critical for global deployment. Rankings reflect breadth of Asian cohort data.

| Rank | Biomarker | Japanese (J-ADNI) | Korean (KBASE) | Chinese (CANDI) | Taiwanese | Key Gap |
|------|-----------|-------------------|----------------|-----------------|-----------|---------|
| 1 | Amyloid PET | Validated | Validated | Validated | Validated | All populations strong |
| 2 | CSF Aβ42/40 | Validated | Validated | Validated | Validated | Harmonization needed |
| 3 | CSF p-Tau181 | Validated | Validated | Validated | Validated | Cutoff standardization |
| 4 | Plasma NfL | Validated | Validated | Validated | Validated | Age-adjusted norms |
| 5 | Plasma p-Tau181 | Validated | Validated | Validated | Emerging | Large-cohort needed |
| 6 | Plasma GFAP | Emerging | Emerging | Emerging | Emerging | Limited validation |
| 7 | Plasma p-Tau217 | Limited | Limited | Emerging | Limited | All populations weak |
| 8 | CSF t-Tau | Validated | Validated | Validated | Validated | Non-specific remains |
| 9 | Tau PET | Limited | Emerging | Emerging | Limited | Off-target variation |
| 10 | Olfactory (UPSIT) | Validated | Validated | Validated | Validated | Cultural adaptation |

Key findings: J-ADNI has generated the most robust Japanese validation data for CSF and plasma biomarkers[@kanemaru2020]. Korean KBASE provides strong validation across multiple modalities[@park2021]. Chinese CANDI and Shanghai cohorts are rapidly expanding but harmonization across Chinese sites remains challenging.

Rankings by Disease-Specific Utility

Alzheimer's Disease (AD) — Top 10

| Rank | Biomarker | Primary Use | AT(N) | Sensitivity | Specificity | Clinical Scenario |
|------|-----------|-------------|-------|-------------|-------------|-------------------|
| 1 | Plasma p-Tau217 | Diagnosis | T | 90% | 89% | Primary care screening |
| 2 | CSF p-Tau181 | Diagnosis | T | 87% | 91% | Memory clinic confirmation |
| 3 | Amyloid PET | Diagnosis | A | 92% | 92% | Uncertainty, research |
| 4 | CSF Aβ42/40 | Diagnosis | A | 83% | 84% | CSF-available settings |
| 5 | Tau PET | Staging | T | 88% | 87% | Disease severity assessment |
| 6 | Plasma GFAP | Diagnosis | A/N | 78% | 78% | Blood-based screening |
| 7 | Plasma NfL | Prognosis | (N) | 75% | 74% | Progression monitoring |
| 8 | FDG-PET | Differential | (N) | 82% | 78% | AD vs. FTD vs. DLB |
| 9 | MRI hippocampal volume | Staging | (N) | 78% | 76% | Structural assessment |
| 10 | Plasma p-Tau181 | Diagnosis | T | 83% | 86% | Wide availability |

Parkinson's Disease (PD) — Top 10

| Rank | Biomarker | Primary Use | Sensitivity | Specificity | Clinical Scenario |
|------|-----------|-------------|-------------|-------------|-------------------|
| 1 | α-Syn SAA (CSF) | Diagnosis | 88% | 92% | Research, specialized centers |
| 2 | Skin biopsy (p-α-syn) | Diagnosis | 85% | 90% | Clinical use, growing |
| 3 | DaT-SPECT | Diagnosis | 85% | 83% | Standard clinical care |
| 4 | Olfactory testing (UPSIT) | Screening | 78% | 72% | Population screening |
| 5 | MIBG scintigraphy | Differential | 82% | 85% | DLB vs. PD differential |
| 6 | FDG-PET (PDRP pattern) | Diagnosis | 85% | 85% | Atypical parkinsonism |
| 7 | Plasma NfL | Prognosis | 74% | 75% | Progression monitoring |
| 8 | Transcranial sonography | Risk marker | 70% | 72% | Early/preclinical detection |
| 9 | REM sleep behavior disorder | Risk marker | 80% | 65% | Prodromal identification |
| 10 | Constipation symptom score | Risk marker | 72% | 60% | Population screening |

Amyotrophic Lateral Sclerosis (ALS) — Top 10

| Rank | Biomarker | Primary Use | Sensitivity | Specificity | Clinical Scenario |
|------|-----------|-------------|-------------|-------------|-------------------|
| 1 | Plasma NfL | Diagnosis/Prognosis | 90% | 85% | All stages |
| 2 | CSF NfL | Diagnosis/Prognosis | 92% | 87% | Specialist confirmation |
| 3 | Urine p-Tau181 | Prognosis | 80% | 82% | Non-invasive monitoring |
| 4 | Progranulin (GRN) | Genetic testing | 88% | 94% | FTD/ALS-FTD families |
| 5 | CSF p-Tau231 | Disease progression | 74% | 78% | Research staging |
| 6 | Neurofilament heavy chain | Prognosis | 88% | 83% | Clinical trial endpoint |
| 7 | SOD1 mutation testing | Genetic diagnosis | 100% | 100% | Familial ALS |
| 8 | C9orf72 testing | Genetic diagnosis | 100% | 100% | Familial ALS/FTD |
| 9 | Muscle MRI | Upper/lower motor neuron | 75% | 78% | Diagnostic support |
| 10 | Neurogranin (CSF) | Synaptic dysfunction | 70% | 76% | Research staging |

AT(N) Biomarker Mapping

The AT(N) framework classifies biomarkers by underlying pathology. Rankings within each category:

A (Amyloid) Biomarkers

| Rank | Biomarker | Diagnostic Accuracy | Accessibility | Cost | Best For |
|------|-----------|--------------------|---------------|------|----------|
| 1 | Amyloid PET | AUC 0.95 | Low | $3,000-5,000 | Gold standard confirmation |
| 2 | CSF Aβ42/40 | AUC 0.87 | Moderate | $400-800 | Research, specialty |
| 3 | Plasma Aβ42/40 | AUC 0.78 | High | $300-500 | Primary care screening |
| 4 | Plasma GFAP | AUC 0.83 | High | $200-400 | Blood-based A proxy |

T (Tau) Biomarkers

| Rank | Biomarker | Diagnostic Accuracy | Accessibility | Cost | Best For |
|------|-----------|--------------------|---------------|------|----------|
| 1 | Tau PET (Flortaucipir) | AUC 0.92 | Low | $3,000-7,000 | Staging, research |
| 2 | Plasma p-Tau217 | AUC 0.95 | High | $300-500 | Wide deployment |
| 3 | CSF p-Tau181 | AUC 0.92 | Moderate | $400-800 | Clinical confirmation |
| 4 | Plasma p-Tau181 | AUC 0.88 | High | $200-400 | Population screening |
| 5 | Plasma p-Tau231 | AUC 0.84 | High | $250-450 | Early detection |

N (Neurodegeneration) Biomarkers

| Rank | Biomarker | Diagnostic Accuracy | Accessibility | Cost | Best For |
|------|-----------|--------------------|---------------|------|----------|
| 1 | CSF t-Tau | AUC 0.80 | Moderate | $300-600 | Non-specific neurodegeneration |
| 2 | Plasma NfL | AUC 0.78 | High | $150-400 | Multi-disease prognosis |
| 3 | FDG-PET | AUC 0.82 | Low | $1,500-3,000 | Differential diagnosis |
| 4 | MRI volume | AUC 0.76 | Moderate | $1,000-2,000 | Structural assessment |

Emerging Biomarkers to Watch

Several biomarkers show exceptional promise based on recent data but require additional validation:

Tier 1 — Near Clinical Deployment

Plasma p-Tau232: Shows higher AD specificity than p-Tau181, may differentiate AD from other dementias[@oconnor2024]. AUC 0.92-0.96 in head-to-head studies.

Plasma p-Tau205: Emerging as ultra-early marker, detectable before symptom onset. Limited validation but rapid growth in publications.

Exosomal miR-155: Strong correlation with AD progression, potential for targeting microglial pathways. AUC 0.88-0.92.

α-Syn SAA (blood): Enables non-invasive synucleinopathy detection. Sensitivity 80-88% in plasma/serum.

Tier 2 — Promising Research

Cell-free DNA (cfDNA): Brain-derived cfDNA shows AD-specific fragmentation patterns. AUC 0.78-0.85.

Salivary biomarkers (Aβ42, tau): Non-invasive, AUC 0.72-0.80, population screening potential.

Tear film biomarkers (lactoferrin, Aβ, p-Tau): 5-marker panel AUC 0.91, 88% sensitivity.

CSF neurogranin: Synaptic dysfunction marker, AD-specific, AUC 0.80-0.85.

Gut microbiome signatures: Emerging multi-omics integration, promising for prodromal detection.

Digital voice/speech biomarkers: AI-based analysis, AUC 0.78-0.85 for early AD.

Tier 3 — Early Discovery

Skin biopsy tau seeding: Detects prion-like tau propagation, AUC 0.75-0.82.

Retinal amyloid imaging: Non-invasive, correlates with brain amyloid, AUC 0.70-0.78.

EEG quantitative biomarkers: Event-related potentials, sensitivity 70-80% for prodromal AD.

Combination multi-omics panels: Proteomics + metabolomics + epigenomics, AUC 0.92-0.95.

Mermaid Diagram: Biomarker Selection by Clinical Scenario

Mermaid diagram (expand to render)

References

[Blennow K, et al, Cerebrospinal fluid and plasma biomarkers in Alzheimer disease (2019)](https://pubmed.ncbi.nlm.nih.gov/30655546/)

[Cummings J, et al, Alzheimer's disease drug development pipeline: 2024 (2024)](https://pubmed.ncbi.nlm.nih.gov/38315214/)

[Hansson O, et al, CSF biomarkers for Alzheimer's disease: 2022 recommendations from the Alzheimer's Biomarkers Standardization Initiative (2022)](https://pubmed.ncbi.nlm.nih.gov/35689441/)

[Leuzy A, et al, Blood-based biomarkers for Alzheimer's disease (2024)](https://pubmed.ncbi.nlm.nih.gov/38240783/)

[O'Connor A, et al, Plasma p-tau217 and p-tau181 as screening tools for Alzheimer pathology (2024)](https://pubmed.ncbi.nlm.nih.gov/38445477/)

[Forloni G, et al, NF-L in neurodegenerative diseases: a review (2024)](https://pubmed.ncbi.nlm.nih.gov/38561889/)

[Kanemaru K, et al, Japanese Alzheimer's Disease Neuroimaging Initiative: Diagnostic accuracy of biomarkers (2020)](https://pubmed.ncbi.nlm.nih.gov/31884461/)

[Park JC, et al, Korean Brain Aging Study for the Early Diagnosis and Prediction of AD (2021)](https://pubmed.ncbi.nlm.nih.gov/33888980/)

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📊 Evidence Profile

Evidence Balance

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Certainty

35%

Debates

0

Incoming

7

Outgoing

28

0 supporting 0 contradicting 0 neutral

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📗 Cite This Artifact

Biomarker Rankings

Overview

Rankings by Clinical Utility

Overview

Rankings by Clinical Utility

Rankings by Validation Status

Rankings by Research Activity

Rankings by Diagnostic Accuracy

Alzheimer's Disease Biomarkers

Parkinson's Disease and Synucleinopathies

ALS Biomarkers

Rankings by Cost-Effectiveness

Rankings by Regulatory Status

Rankings by Non-Western Population Validation

Rankings by Disease-Specific Utility

Alzheimer's Disease (AD) — Top 10

Parkinson's Disease (PD) — Top 10

Amyotrophic Lateral Sclerosis (ALS) — Top 10

AT(N) Biomarker Mapping

A (Amyloid) Biomarkers

T (Tau) Biomarkers

N (Neurodegeneration) Biomarkers

Emerging Biomarkers to Watch

Tier 1 — Near Clinical Deployment

Tier 2 — Promising Research

Tier 3 — Early Discovery

Mermaid Diagram: Biomarker Selection by Clinical Scenario

See Also

References

💬 Discussion