Science & Research

Biological age is measurable, modifiable, and shows up early — in the mouth, in the blood, and in daily function. Praxiom Life translates the latest aging-clock and biomarker research into a single, clinically usable score for patients and clinicians.

1. Multi‑System View of Biological Age

Modern aging science has moved beyond single markers to composite “clocks” that integrate information across many systems. Large plasma proteomics studies have created organ‑specific and whole‑body aging clocks that outperform traditional risk factors in predicting mortality and disease. Next‑generation DNA methylation clocks do the same at the epigenetic level, capturing cell‑level aging processes across 11 physiological systems from a single blood test.​

Key references (examples):

Proteomic aging clocks and organ‑specific aging models (Cell Metabolism 2025, PLoS Medicine 2024, npj Aging 2025).​

Systems‑level epigenetic clocks such as Systems Age and DunedinPACE (Sehgal et al., Nature Aging 2025; Belsky et al., eLife 2022, PubMed 35029144).​

Telomere length and epigenetic age acceleration as independent predictors of mortality and stroke risk (Aging Cell 2025, Journal of Stroke & Cerebrovascular Diseases 2026).​

2. Biomarkers That Matter for Longevity

Praxiom Life’s framework is anchored in biomarker domains repeatedly linked to healthspan, frailty, and mortality.​

  • Inflammation & “inflammageing”
    IL‑6, hs‑CRP, GDF‑15, CXCL9 and composite inflammation scores robustly predict frailty, cognitive decline, and mortality (CXCL9 as the lead marker of the iAge inflammatory clock: Sayed et al., Nature Aging 2021, PubMed 34888528). Systematic reviews confirm IL‑6 as a core inflammaging biomarker in community‑dwelling adults.​
  • Metabolic and glycemic health
    HbA1c alone misses key aging signals; continuous glucose metrics like Time‑in‑Range and glycemic variability correlate with cellular senescence and inflammation (La Grotta et al., Cardiovascular Diabetology 2025, PubMed 41239371). Metabolomic age scores (e.g., MileAge) further capture aging‑related metabolic patterns beyond single markers (Mutz et al., Science Advances 2024, PubMed 39693428).​
  • Proteins and hormones of aging
    GDF‑15, FGF‑21, NAD‑related pathways, IGF‑1, and plasma proteomic indices track systemic stress, metabolic flexibility, and longevity across large cohorts. Human GDF‑15 “knockout” data refine what truly healthy ranges look like for long‑term health (Gurtan et al., Nature Metabolism 2024, PubMed 39327531).​
  • Telomeres and epigenetic clocks
    Telomere length and advanced DNA‑methylation clocks provide complementary views of biological aging and are consistently associated with mortality and age‑related disease.​

3. Oral and Microbiome Signals

Praxiom Life adds something traditional longevity platforms miss: an explicit oral and microbiome dimension.​

  • Chronic periodontitis drives systemic inflammation and is linked to neurodegeneration, cognitive decline, and frailty in older adults.​
  • Oral and salivary microbiome diversity changes with age and correlates with systemic cytokines and aging phenotypes, making it a practical early biomarker of biological aging.​
  • Gut microbiome diversity and composition are repeatedly associated with healthy longevity, metabolic health, and inflammaging.​

Recent work in elderly cohorts shows that shifts in oral and gut microbial diversity track with systemic fatty acids, inflammatory markers, and age‑related disease risk.​

4. Function and “Real‑World” Aging

Biological age is not only molecular—it is visible in how people move and function.​

  • Handgrip strength and gait speed are among the most robust predictors of mortality, frailty, heart failure outcomes, and “exceptional ager” phenotypes.​
  • Allostatic load indices and sleep‑inflammation studies show that chronic stress and poor sleep translate into accelerated brain and white‑matter aging.​

Praxiom incorporates these functional and stress‑load concepts as part of a practical, clinic‑friendly view of aging rather than treating them as separate from lab values.​

5. How Praxiom Uses This Science

Praxiom does not simply copy a single academic clock; it integrates these validated domains into a pragmatic scoring model.​

  • We start from high‑grade evidence (systematic reviews, large cohorts, Mendelian randomization) to assign weights to biomarker families—oral inflammation, systemic inflammation, glucose dynamics, proteomics, epigenetics, functional status, and stress load.​
  • The algorithm favors multi‑marker patterns (e.g., IL‑6 + CRP + GDF‑15; HbA1c + CGM variability; periodontal status + pathogen load + oral microbiome diversity) rather than single cut‑offs, reflecting how modern clocks work.​
  • Over time, longitudinal data (how your profile changes) is treated as more important than any single snapshot.​

Praxiom Life’s Bio‑Age score is therefore best thought of as a translational layer: it brings state‑of‑the‑art aging science into a form that dentists, physicians, and patients can understand and act on visit by visit.

PubMed links that inform the Praxiom model:

Individual biomarker domains are supported by published evidence. The composite Praxiom Bio-Age score is in active development and has not yet been externally validated.

Healthy longevity, as the field now defines it, is about extending the years a person stays capable, not the years they stay alive. The Biomarkers of Aging Consortium classifies biomarkers of ageing as molecular, physiological, histologic or radiographic, with digital biomarkers emerging, and asks that they be minimally invasive and repeatable so they can be followed over time (Moqri et al., Cell 2023, PubMed 37657418). Abu Dhabi’s Healthy Longevity Medicine Clinic Standard (Department of Health, issued October 2024, in force April 2025) uses three categories, molecular, physiological and digital, and provides for repeat testing to check that a plan is working. Praxiom Life is built to fit that model from the patient side: molecular markers from saliva and blood, physiological measures from fitness tests, digital data from wearables, read against a personal baseline, with the oral cavity added as a domain the standard does not yet name.

The app’s own reference library holds over a hundred peer-reviewed studies, one set per biomarker, and grows through a monthly literature review. Each addition is read and approved before it reaches the app. The library is open from the Settings screen; no account is needed to read it.

Clinicians and researchers: the framework, the evidence by domain and the pre-specified validation protocol are on the Clinicians and Research Partners page.

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