Analyte Degradation Risk Assessment

analyte-degradation-risk-assessment

Summary

Assess whether blood-derived metabolite and lipid analytes have degraded or remain stable under known pre-analytical conditions (time delay, temperature, matrix type). This skill enables retrospective evaluation of measurement reliability in metabolomics and lipidomics datasets by querying experimental stability data.

When to use

You have measured metabolites or lipids from biobanked or processed blood samples (EDTA plasma or serum) and know the pre-analytical conditions (time delay before/after centrifugation in hours, processing temperature in °C, sample matrix). You need to flag which analytes may have degraded beyond a stability threshold (default 20–30% fold-change) and thus require cautious interpretation or exclusion from downstream analysis.

When NOT to use

• Sample matrix is not EDTA plasma or serum (e.g., whole blood, urine, cerebrospinal fluid); ALISTER currently only covers these two matrices.
• Pre-analytical conditions are completely unknown or poorly documented; the skill requires explicit numeric input for time delays and temperatures to query the database.
• The analyte names do not conform to lipid shorthand nomenclature or RefMet nomenclature; automatic matching will fail and manual curation is required.

Inputs

• pre-analytical sample metadata (time delay hours before centrifugation, time delay hours after centrifugation, temperature °C before centrifugation, temperature °C after centrifugation, matrix type: EDTA plasma or serum)
• analyte name list (lipid shorthand nomenclature or RefMet nomenclature for polar metabolites)
• optional: measured analyte abundance table (rows=samples, columns=analytes; .csv format)

Outputs

• analyte stability assessment table (analyte name, stability flag: stable/degraded, fold-change estimate, confidence/generalization metrics, literature citations)
• aggregated stability summary (pie chart or percentage breakdown of stable vs. degraded analytes under input conditions)
• annotated dataset (input analyte table with instability flags appended; for data filtering mode)
• downloadable .csv or PDF report containing query parameters, stability results, and reference metadata

How to apply

Parse the known pre-analytical parameters (time delay before centrifugation, time delay after centrifugation, temperature pre- and post-centrifugation, matrix type) into a structured query. Submit this query against ALISTER's underlying stability database, which returns literature-derived stability assessments for each analyte under the matched or generalized conditions. Stability is assessed as a binary flag (stable/degraded) and a fold-change metric. Apply the default 20% threshold for single pre-analytical conditions or 30% for combined conditions; adjust thresholds if stricter or more permissive criteria are needed. Return a structured output (CSV or JSON) annotating each analyte with its stability status, fold-change estimate, confidence metadata, and supporting literature citations. Use the confidence or generalization metrics to assess how closely the database matched your exact input conditions.

Related tools

• ALISTER (web app) (Query interface and stability database engine for retrospective and prospective pre-analytical stability assessment) — https://github.com/Fraunhofer-ITMP/alister
• Shiny (User interface framework for the web app)
• RStudio (Development and deployment environment)

Evaluation signals

• Stability status (stable/degraded) aligns with literature-reported fold-change thresholds: ≤20% fold-change under single condition = stable; >20% or combined conditions >30% = degraded.
• Analyte names are successfully matched against ALISTER's database; unmatched analytes are logged or flagged for manual review.
• Confidence/generalization metrics indicate how closely the queried conditions matched available experimental data; high confidence suggests direct literature support, low confidence indicates interpolation or extrapolation.
• Output structure is valid (JSON schema or CSV headers) and includes mandatory fields: analyte identity, stability flag, fold-change estimate, and at least one citation.
• When data filtering mode is used, unstable analytes are consistently flagged in the output and can be filtered from downstream analysis; filtering produces a subset table with reduced analyte count and matched sample rows.

Limitations

• Database coverage is limited to influences of time delay and temperature; other pre-analytical variables (e.g., pH, anticoagulant batch, centrifuge speed) are not currently modeled.
• Only EDTA plasma and serum matrices are supported; other blood fractionation methods or tissues are out of scope.
• When exact experimental conditions are not in the database, ALISTER performs generalization (interpolation or nearest-neighbor matching); the degree and direction of generalization is reported but may reduce confidence in edge cases.
• Analytes must be named in lipid shorthand nomenclature or RefMet nomenclature; common names or non-standard identifiers will not match and require manual curation.
• Stability assessment is based on aggregate literature data and does not account for sample-specific factors (e.g., individual variation in enzyme activity, hemolysis, lipemia) that may affect real-world degradation kinetics.

Evidence

• [readme] In retrospective assessment of samples, that ALISTER assesses analytes stability based on pre-analytical sample information provided by the user: "In retrospective assessment of samples, that ALISTER assesses analytes stability based on pre-analytical sample information provided by the user"
• [other] Parse user-provided pre-analytical parameters (time delay in hours, temperature in °C, matrix type: EDTA plasma or serum) into a structured query object. Query the ALISTER stability database with the parsed parameters to retrieve matching analyte-stability records (analyte name, stability flag, confidence metrics).: "Parse user-provided pre-analytical parameters (time delay in hours, temperature in °C, matrix type: EDTA plasma or serum) into a structured query object. Query the ALISTER stability database with the"
• [readme] By default the critical threshold for assessing instability is set to 20% fold change due to specific pre-analytical conditions. When conditions are combined (e.g. added change due to delay before and after centrifugation) the threshold is expanded to 30%.: "By default the critical threshold for assessing instability is set to 20% fold change due to specific pre-analytical conditions. When conditions are combined (e.g. added change due to delay before"
• [intro] Time delay and temperature during processing are among the major pre-analytical pitfalls affecting (EDTA) plasma and serum samples: "Time delay and temperature during processing are among the major pre-analytical pitfalls affecting (EDTA) plasma and serum samples"
• [readme] Lipids are named after the lipid shorthand nomenclature, while polar metabolites are named after their RefMet nomenclature.: "Lipids are named after the lipid shorthand nomenclature, while polar metabolites are named after their RefMet nomenclature."