Early Risk Assessment for AMD

Why Early Risk Assessment Matters

Age-Related Macular Degeneration (AMD) is the leading cause of severe, irreversible vision loss in adults over 35. Yet in its early stages, AMD has no noticeable symptoms. Most people are unaware they have the disease until significant damage has already occurred.

Early risk assessment aims to change this by identifying individuals at elevated risk before symptoms develop—allowing for earlier monitoring, lifestyle interventions, and treatments that can slow or prevent disease progression.

“Early detection and treatment can help protect vision and prevent vision loss. Many eye diseases have no early symptoms. But regular comprehensive dilated eye exams can help adults protect their vision by catching eye diseases and conditions early, when they’re easier to treat.”

— National Eye Institute (NEI)

20M+

Americans living with AMD

Zero

Symptoms in early AMD

10–20%

Progress to legally blind in <5 years

~25%

Risk reduction with early intervention

Three Approaches to AMD Risk Assessment

According to NIH and NEI research, there are three complementary approaches to assessing AMD risk:

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Blood-Based Biomarkers

Measuring proteins, metabolites, and molecular signals in a blood sample that correlate with AMD risk and progression

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Structural Imaging

OCT scans, fundus photography, and adaptive optics to detect drusen, pigment changes, and retinal thinning

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AI-Powered Screening

Machine learning models that analyze retinal images and patient data to predict who is at highest risk of rapid progression

NIH researchers conclude that a multimodal approach—combining structural, functional, and systemic biomarker measurements—provides superior prognostic accuracy compared to any single method alone. — PMC

Blood-Based Biomarkers for AMD

Research published through the National Institutes of Health has identified several blood-based biomarkers associated with AMD risk and progression. While evidence is still developing, these markers represent a promising frontier for non-invasive early screening:

Biomarker	Finding	Significance
Apolipoprotein M (ApoM)	Reduced levels in AMD patients vs. healthy controls	Links AMD to cholesterol metabolism dysfunction; potential therapeutic target
C-Reactive Protein (CRP)	Elevated levels associated with late AMD progression	Systemic inflammation marker; increased risk indicator
HDL Cholesterol	Elevated HDL-C predicts AMD progression	Lipid metabolism involvement in retinal disease
Homocysteine	Elevated serum levels correlate with wet and dry AMD severity	Established biomarker for AMD; measurable in routine blood tests
Interleukin-6 (IL-6)	Associated with advanced AMD	Inflammatory pathway involvement in disease progression
Interleukin-8 (IL-8)	Associated with advanced AMD	Immune-mediated retinal damage marker
8 Metabolite Panel	Significant association with 3-year AMD progression	Multi-metabolite approach improves predictive accuracy

“Patients with macular degeneration have reduced levels of ApoM circulating in the blood compared with healthy controls. Various methods of dialing up ApoM could serve as new treatment strategies for AMD.”

— National Eye Institute, 2025

Genetic Risk Factors

Research has identified significant genetic components to AMD risk. According to NIH studies, 52 common and rare single nucleotide polymorphisms (SNPs) across 34 genetic loci are associated with AMD:

Key Genetic Variants

Complement Factor H (CFH) — Captures a substantial fraction of AMD risk
PLEKHA1/ARMS2/HtrA1 — Among the strongest genetic predictors
VEGF SNPs — Vascular endothelial growth factor variants linked to wet AMD
Complement Factor B and C2 — Promising markers in the complement pathway

NEI Position on Genetic Testing

The National Eye Institute currently does not recommend genetic testing for AMD in clinical practice because:

Results cannot reliably guide prevention or treatment decisions
AMD involves many known and yet-undiscovered genetic factors
Even when weighted with other risk factors, genetic status fails to reliably predict individual risk

Genetic markers remain valuable for research purposes and stratifying patients into risk categories in clinical trials.

While genetic testing alone is insufficient, combining genetic data with blood-based biomarkers and clinical assessments may provide a more complete picture of individual AMD risk in the future. — PMC

AI-Powered Screening for AMD

The National Eye Institute highlights artificial intelligence as a transformative tool for early AMD detection and risk prediction:

How AI Screening Works

Deep convolutional neural networks are trained on large datasets of patients with known outcomes. The network extracts features from retinal images—such as drusen size, type, and pigment abnormalities—and combines them with patient data including age, smoking status, and genetic profile.

With enough data, the network detects patterns that enable both screening and prediction of progression.

Why It Matters

For 10–20% of AMD patients, disease progresses from diagnosis to late-stage and legally blind in under 5 years. The NEI notes that identifying who falls into this high-risk group “often isn’t easy” with traditional methods.

AI systems like iPredict enable non-eye-care specialists to screen patients and predict which individuals with early AMD are at risk for accelerated vision loss.

“Emerging AI methods may be used to automatically detect and quantify AMD biomarkers in a cost-effective, rapid throughput manner. This will expedite screening and assist in the selection of appropriate patients for clinical trials.”

— National Institutes of Health, PMC

NEI Advanced AMD Risk Calculator

The National Eye Institute provides an Advanced AMD Risk Calculator for eye care professionals that predicts the likelihood of developing advanced AMD (geographic atrophy or neovascular AMD) over a period of 2 to 10 years.

Who It Applies To

Individuals aged 55–80 without advanced AMD in either eye, or with advanced AMD in only one eye. People older than 80 may use the calculator by entering 80 as their age.

How It Works

The calculator generates group-based risk estimates based on patient characteristics. It predicts the proportion of patients sharing those characteristics who are likely to develop advanced AMD within a specified time interval.

Important Limitation

Risk estimates apply to patient populations with similar characteristics—they cannot determine if or when a specific individual will develop advanced AMD. The calculator is intended for eye care professionals, not direct patient use.

Source: NEI Advanced AMD Risk Calculator — National Eye Institute

Understanding AMD Progression Risk

Not all AMD progresses at the same rate. NIH research reveals important differences in progression risk depending on which eyes are affected:

Early AMD in One Eye Only

For people with early AMD in one eye and no signs in the other, approximately 5% will develop advanced AMD after 10 years.

Early AMD in Both Eyes

For people with early AMD in both eyes, approximately 14% will develop late AMD in at least one eye after 10 years.

Research from PMC identifies that demographic, environmental, genetic, and molecular risk factors are most valuable at earlier disease stages, while phenotypic risk factors such as drusen and pigment abnormalities become more important for predicting progression during later stages of the disease.

Critical window: For 10–20% of patients, AMD progresses from diagnosis to late-stage and legally blind in under 5 years. Identifying this high-risk group early is essential for timely intervention.

The Future of Early Risk Assessment

According to NIH research, the next generation of risk assessment tools will integrate multiple data sources for significantly improved predictive accuracy:

Blood-based biomarker panels — Multi-marker assays measuring inflammation, cholesterol metabolism, and complement activation from a simple blood draw
AI-integrated retinal imaging — Machine learning analysis of OCT and fundus images to detect subtle early changes invisible to the human eye
Genetic risk scoring — Polygenic risk scores combined with clinical data for improved stratification
Metabolomic profiling — Comprehensive analysis of blood metabolites to identify unique AMD risk signatures
Wearable monitoring — At-home vision monitoring devices and apps that detect early functional changes between office visits

“Biomarker-based predictive models represent a paradigm shift from reactive medicine to proactive prevention. These systems enable early disease detection, risk stratification, and personalized interventions—foundational elements for evidence-based health management.”