GrimAge Risk Score

Score a caller-calibrated methylation mortality-risk composite; no built-in clinical coefficients.

Description

A log-linear biomarker score requires supplied coefficients.

A log-linear biomarker score requires supplied coefficients. Published GrimAge models need trained components absent from this generic calculator.^{[1, 2]}

Score a caller-calibrated methylation mortality-risk composite; no built-in clinical coefficients.

When to use GrimAge Risk Score

Use this tool to score a caller-calibrated methylation mortality-risk composite; no built-in clinical coefficients.

Prepare the already measured signals, counts, coordinates, fitted coefficients or sequence strings requested. Keep assay definitions, units, aligned lists and caller-selected thresholds consistent.

How to use GrimAge Risk Score and understand its results

Prepare the already measured signals, counts, coordinates, fitted coefficients or sequence strings requested. Keep assay definitions, units, aligned lists and caller-selected thresholds consistent.
Enter biomarkerValues, biomarkerWeights, intercept, decisionThreshold using the field table and calculation rules, then run the tool.
Read linearPredictor, relativeRisk, flagged. The explanation below defines the units, signs, ordering and any flags or placeholder values.
If the tool reports an input issue, correct the values and run it again. Apply the stated assumptions when interpreting a successfully returned result.

Input field	Meaning	Value type; see rules below	Requirement
biomarkerValues	Biomarker values	list of number	Required
biomarkerWeights	Biomarker weights	list of number	Required
intercept	Intercept	number	Required
decisionThreshold	Decision threshold	number	Required

Enter nonempty aligned finite weights/biomarkers, intercept and positive risk threshold. Return linear score, relative risk and inclusive flag.

linear=intercept+Σ(weight×biomarker); relativeRisk=exp(linear)

Units, indexing, boundary conditions and exceptional cases are defined in the calculation rules above.

Output field	Meaning	Value type
linearPredictor	Linear predictor	number
relativeRisk	Relative risk	number
flagged	Flagged	boolean

json

{
  "input": {
    "biomarkerValues": [
      2,
      3
    ],
    "biomarkerWeights": [
      0.5,
      1
    ],
    "intercept": -2,
    "decisionThreshold": 0.7
  },
  "output": {
    "linearPredictor": 2,
    "relativeRisk": 7.38905609893065,
    "flagged": true
  }
}

Limitations and assumptions

No GrimAge coefficients, methylation-clock fit, baseline risk or clinical prediction is supplied. Extreme scores can fail finite-output validation.

Numeric inputs, where present, must be finite. Follow the calculation-specific rules for overflow, underflow and exceptional cases. Lists are limited to 100,000 entries; the rules above may require smaller limits. Missing required fields, extra fields, wrong value types and violations of the calculation rules are input errors. A successfully returned false flag is an evaluated outcome; its meaning is explained above.

Alternative or Complementary methods

Use Epigenetic Age Residual: Calculate and classify epigenetic age acceleration. For a complementary task, use DunedinPACE Ratio: Compare a measured epigenetic pace of aging to an injected reference pace.

Further background: DNA methylation GrimAge strongly predicts lifespan and healthspan.

References

GrimAge Risk Score — tool.io
DNA methylation GrimAge strongly predicts lifespan and healthspan — Lu and colleagues

Similar or alternative tools

Epigenetic Age Residual
Calculate and classify epigenetic age acceleration.
DunedinPACE Ratio
Compare a measured epigenetic pace of aging to an injected reference pace.