Can Routine Clinical Tests Be Used to Estimate Biological Age?

1. Biological aging can be quantified using routinely collected clinical data. Blood chemistry, complete blood counts, blood pressure and organ-function measurements can be combined into quantitative measures of biological aging. The algorithms can be adapted to the biomarkers available rather than requiring one fixed laboratory panel.

2. BioAge is a toolkit, not another biological-age test. It provides a framework for implementing and comparing KDM Biological Age, PhenoAge and Homeostatic Dysregulation. KDM produces an age-related estimate, PhenoAge incorporates mortality-related information, and Homeostatic Dysregulation measures deviation from a healthy physiological reference state.

3. Biomarker selection affected algorithm performance. The researchers constructed versions using different combinations of clinical biomarkers. A combined V2 set performed better in validation analyses and was selected for the CALERIE analysis, while performance varied by algorithm and biomarker set.

4. The effect of calorie restriction differed between biological-aging measures. KDM Biological Age increased by approximately 0.69 biological years per year in controls and changed by an estimated −0.20 years per year in the calorie-restriction group. PhenoAge increased by approximately 0.83 versus 0.17 years per year. Homeostatic Dysregulation showed no statistically significant group difference.

5. The reference population used to construct an algorithm can influence the result. An earlier CALERIE analysis using Homeostatic Dysregulation trained on different NHANES reference data had detected slower aging, illustrating the sensitivity of biological-aging algorithms to their development data.

Biological age is often associated with specialized molecular tests such as DNA methylation. This study demonstrates that biological aging can also be quantified from clinical measurements already collected in routine medical assessment.

The measurements themselves do not constitute a biological age. They must first be selected and interpreted through a defined algorithm.

A clinical biological-aging assessment therefore includes several distinct components: clinical biomarkers, a biological-aging algorithm, a reference population, validation and the resulting measure. Changing one component can influence the estimate.

The CALERIE analysis adds a longitudinal dimension because repeated measurements allowed researchers to examine whether an intervention changed the trajectory of biological-aging measures over two years.

The fact that calorie restriction affected KDM Biological Age and PhenoAge but not Homeostatic Dysregulation demonstrates why a statement such as “biological aging slowed” needs context.

For longevity research, routinely collected clinical data may provide more than a snapshot of current health. When incorporated into appropriately developed and validated algorithms, they can be used to study differences between individuals and changes in aging-related physiology over time.

Clinical biological-age algorithms are particularly interesting because they can use measurements already widely available in medical practice, potentially allowing assessment without a separate molecular aging test.

The paper does not establish a ready-to-use diagnostic test for an individual patient. BioAge is a research toolkit for constructing, applying and evaluating biological-aging algorithms.

KDM Biological Age, PhenoAge and Homeostatic Dysregulation should not be regarded as interchangeable versions of the same test. They represent different approaches and may respond differently even when applied to the same intervention data.

Meaningful interpretation requires knowing which biomarkers and algorithm were used, which reference population supported development, which health outcomes were used for validation, and whether change on repeated testing can be distinguished from measurement variability.

For clinical application, the relevant question is not simply “What is the patient's biological age?” but also “What exactly does this measure quantify, and what evidence supports its interpretation?”