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MediBalans › Diagnostics › Biological Age Panel
MediBalans · RNA Transcriptomics · Proteomics

How does your
biological age profile look?

Chronological age is the number of years you have lived. BioAge compares measured RNA and protein patterns with age-associated reference data and provides a model-based estimate of your biological profile. It is not a direct measurement of your cells' actual age or a prediction of how long you will live.

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RNATranscriptomic Analysis
Multi-System Assessment
LongitudinalComparison
ClinicalInterpretation
What the panel measures and estimates

Measures molecular patterns.
Estimates an age-associated profile.

RNA transcriptomics measures gene expression in the sample. Proteomics measures the levels of proteins included in the panel. These are the direct laboratory measurements at the time of sampling.

The MediBalans analysis model compares these patterns with age-associated reference data and calculates a model-based biological age estimate and domain profile. The model does not directly measure the functional age of cells, organs or the whole body.

When retesting is performed under comparable conditions, a change can show that the model value and its underlying markers have changed. It cannot by itself show why the change occurred, prove that a particular intervention caused it or establish that an equivalent number of healthy life-years has been gained.

Biological age is one of several possible inputs within the broader concept of healthspan. See how MediBalans separates molecular markers from measurable health and function →

Global Constraint Rule · The aging context

The BioAge result is used within GCR as one of several inputs for identifying biological domains that may warrant further evaluation. The model identifies patterns and associations; it does not independently establish a root cause, diagnosis or treatment sequence.

Test Facts — Biological Age Panel

What the assessment includes

MethodsRNA transcriptomics + protein biomarker panel
OutputModel-based age estimate · Domain profile · Longitudinal comparison
PatternsRNA and protein patterns associated with inflammation · senescence · mitochondrial processes · proteostasis · DNA repair
Sample typeBlood draw — coordinated at MediBalans or local laboratory
RetestingWhen clinically justified and under comparable sampling and analytical conditions
InterpretationAlongside history, symptoms, function, routine tests and established risk markers; treatment is not guided by the model score alone
Molecular domains

Six domains, examined through RNA and protein patterns

Transcriptomic age model

RNA-related age profile

The model compares measured gene-expression patterns with age-associated reference data. It estimates a molecular age profile; it does not measure DNA methylation unless a separate methylation assay has been performed.

Senescence

Senescent Cell Burden

The panel can measure selected RNA and protein markers associated with senescence and SASP. It does not count senescent cells or establish their total burden.

Mitochondrial Function

Mitochondrial processes

The panel analyses RNA and protein patterns associated with mitochondrial processes. It is not a direct functional test of ATP production or mitochondrial capacity.

Inflammation

Inflammation-related patterns

The panel measures selected cytokines and RNA or protein patterns associated with inflammation. The result describes the marker profile at sampling and is not itself a diagnosis or a direct measure of the body's total inflammatory burden.

Proteostasis

Proteostasis-related patterns

The panel analyses patterns associated with proteostasis. It does not directly measure the cells' overall ability to fold, repair or degrade proteins.

DNA Repair

DNA repair-related patterns

The panel analyses expression of genes and proteins associated with DNA damage response and repair. Expression patterns are not a direct measurement of DNA damage, genomic stability or repair capacity.

Why it matters now

A summary measure — not a medical verdict.

A molecular age profile can complement, but does not replace, established risk assessment, diagnostics, functional measures or recommended screening. The result needs to be interpreted within the full clinical picture.

A change on serial testing can indicate that the model profile has changed, particularly when it exceeds method variation and aligns with symptoms, function and other markers. It does not itself prove treatment benefit, rejuvenation or extended lifespan.

GCR is MediBalans' framework for structuring clinical interpretation. Systems-biology studies in other organisms or biological systems do not by themselves validate the BioAge model or its clinical use in humans.

For a clinical question

Post-viral & Chronic Illness

Research has reported age-associated molecular differences in some patient groups. An individual BioAge result is not diagnostic and cannot establish that a condition has accelerated that person's aging.

For proactive optimisation

Longitudinal baseline

The panel can provide a baseline for longitudinal comparison. The model value is considered alongside established risk markers, symptoms and functional measures — not as a standalone optimisation target.

Longitudinal follow-up

Change over time

Retesting with the same method under comparable conditions can show a change in the model value. It cannot by itself establish cause, confirm treatment benefit or show that healthspan or lifespan has increased.

Questions

Biological Age Panel explained

The panel measures RNA gene expression and levels of selected proteins in the sample. A model compares these patterns with age-associated reference data and estimates a biological age profile. The result is complementary information, not a direct measurement of your cells' actual age.

Chronological age is the time since birth. Here, biological age is a model-based estimate derived from selected molecular markers. Different models, sample types and reference populations can therefore produce different results.

RNA transcriptomics measures which genes are expressed in the sample and at what levels. The model can identify age-associated patterns, but these are not direct measures of organ function, causality or remaining lifespan.

Yes, the model value can change between samples. Under comparable conditions, this can show that the measured patterns have changed, but it does not by itself prove why, that a particular treatment caused the change or that an equivalent number of healthy life-years has been gained.

Retesting should be considered when there is a clear clinical question, ideally using the same method and comparable sampling conditions. An interval of 6–12 months may be reasonable in some follow-ups, but its value is assessed individually.

The panel may be relevant for adults seeking a deeper, research-adjacent molecular profile who understand the method's limitations. It complements history, clinical findings, function and established risk markers — it is not a standalone diagnosis or lifespan prediction.

Next Step

Understand your biological profile.
Follow it in context.

BioAge provides a model-based baseline from RNA and protein patterns. Dr Mario Anthis interprets the result alongside history, clinical findings, function and established markers. Any action is based on the overall assessment — not the age value alone.

Book Also: ALCAT →
Related inputs

Related clinical inputs

Immune Response · Cell Science Systems

ALCAT — Food Intolerance

ALCAT is a separate clinical input concerning immune reactivity to tested substances. It should not be described as a general measure of what drives biological aging.
Intracellular · Cell Science Systems

CMA — Cellular Micronutrient Analysis

CMA provides information on cellular micronutrient-related markers. The result is interpreted alongside dietary history, routine tests and other clinical information.
Genetics · Proprietary

MethylDetox — 38 Genes

MethylDetox describes inherited variants in selected genes. It does not measure current methylation capacity or aging rate and does not guide treatment on its own.

Research & sources

Published transcriptomic and proteomic models can estimate chronological age and have, in some cohorts, been associated with disease outcomes or mortality. Results depend on sample type, platform, model and population. Accuracy for chronological age is not the same as validation as a surrogate for healthspan or treatment benefit.

[1]
Sood S et al. A whole-blood gene-expression meta-analysis identified a transcriptomic age signature associated with several age-related clinical traits. The associations do not establish individual causation or treatment benefit. Nature Communications. 2015;6:8570 ↗
[2]
Jung T et al. MultiTIMER is an interpretable, multi-tissue RNA model of chronological age and biological processes in research data. It is not clinical validation of MediBalans BioAge. Aging Cell. 2023;22:e13799 ↗
[3]
Modeling transcriptomic age using knowledge-primed artificial neural networks. The model was developed using skin RNA sequencing and illustrates that transcriptomic age models are tissue- and platform-specific. It does not validate a blood-based clinical test. npj Aging and Mechanisms of Disease. 2021;7:15 ↗
[4]
Argentieri MA et al. A plasma-proteomic age model was developed and validated across cohorts in the UK, China and Finland; its age gap was associated with disease and mortality at cohort level. Nature Medicine. 2024;30:2450–2460 ↗
[5]
Moqri M et al. A consensus framework for validating biomarkers of aging emphasises predictive validity, generalisability and requirements for clinical translation. Nature Medicine. 2024;30:360–372 ↗
[6]
Horvath S. The foundational epigenetic clock study uses DNA methylation. It provides research background but is not evidence that the current RNA and protein panel measures DNA methylation. Genome Biology. 2013;14:R115 ↗
Evidence context: The literature supports the concept of molecular age models but does not automatically validate the specific combined MediBalans model or a change in its value as a surrogate for healthspan or lifespan. BioAge is used as complementary, research-adjacent information.

Keep reading. Explore symptom guides, clinical notes, assessments and diagnostics in our knowledge base.

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