A decade of pioneering proteomics research.

Teal's analytics framework is informed by foundational research from the Wyss-Coray lab at Stanford — independently validated across four peer-reviewed publications and a global proteomics data challenge.

Tony Wyss-Coray

Co-Founder

D.H. Chen Distinguished Professor of Neurology and Neurological Sciences at Stanford. Director of the Knight Initiative for Brain Resilience. 200+ publications. TIME “Health Care 50,” 2020.

2019
Identified nonlinear plasma proteome changes across the lifespan.
Nature Medicine
Undulating changes in human plasma proteome profiles across the lifespan
December 2019Lifespan proteomics
2020
Showed that tissue-specific gene expression patterns are reflected in circulating proteins.
Nature
Ageing hallmarks exhibit organ-specific temporal signatures
July 2020Tabula Muris Senis
2023
Introduced organ-specific aging clocks using plasma proteomics.
Nature
Organ aging signatures in the plasma proteome track health and disease
December 2023Cover paper
2025
Proteomic organ-specific ageing signatures and 20-year risk of age-related diseases (Whitehall II).
Lancet Digital Health
Proteomic organ-specific ageing signatures and 20-year risk of age-related diseases
March 2025Whitehall II
2025
Validated and expanded organ aging models in 50k UK Biobank cohort.
Nature Medicine
Plasma proteomics links brain and immune system aging with healthspan and longevity
August 202544k+ UK Biobank
2026
Developed cell aging clocks across 40+ cell types and general outlier models.
bioRxiv
Preprint visualizationTeal Rise
Cell-level aging signatures across 40+ cell types in 60,000 individuals
February 2026Pre-print

Work in practice — Organ aging and dementia risk.

A national research institute partnered with Teal Rise to study how plasma proteomics and organ-specific biological aging relate to dementia risk from midlife to late life. Combining proteomics, genetics, MRI imaging, and adjudicated clinical outcomes, we quantified aging trajectories and identified candidate causal proteomic drivers of neurodegeneration.

~5,000

Plasma proteins

20yr

Follow-up window

Publication figures

Statistical tables

Organ-specific aging signatures

Cohort study

Organ age gap × small vessel disease

Standardized association (β) between each organ's age gap and four MRI-derived measures. Brain and vasculature show the strongest links.

n = 50,000 · UK Biobank · Olink Explore 3072 · illustrative values

Methods

Plasma proteomics (~5,000 proteins) + adjudicated dementia outcomes
MRI imaging + TOPMed genotyping + curated GWAS summary stats
Cox proportional hazards, mixed-effects longitudinal models
PWAS + Mendelian Randomization for causal inference
Pathway enrichment via Reactome, KEGG, GO, MSigDB

Deliverables

28 publication-ready figures
42 statistical tables (HRs, PWAS, MR results)
Processed organ age gaps, pace metrics, GWAS summary stats
Detailed methods documentation

Key insights

Organ aging predicts dementia risk

Each additional year of organ age gap — particularly in brain, heart, liver, and pancreas — was associated with substantially elevated dementia risk.

Midlife pace anticipates late-life decline

Accelerated aging trajectories correlated with cortical thinning and white-matter hyperintensity burden on MRI decades later.

Multi-organ aging is supra-additive

Brains aging in synchrony with heart or muscle exhibited compounding risk, pointing to network-level biological aging.

Causal evidence from PWAS + MR

Integrating proteomics with genetics provided causal evidence for specific proteins directly modulating aging and dementia risk.