Decode Aging
Research & Development
Building a longitudinal clinical cohort for normative aging research.
A deeply phenotyped, biobanked, FAIR-structured dataset designed to support personalized preventive medicine, translational aging research, and technology validation.
Explore the DatasetClinical Infrastructure
A research-ready clinical infrastructure
Own Clinics
Standardized data acquisition, direct QM
Scientific Partnerships
Universities, research institutes, methodological development
Clinical Partnerships
Hospital cooperations, disease cohort enrichment
Clinically embedded
Data collected directly in clinical operations – under real-world conditions, not artificial research settings.
Longitudinal by design
Every patient is re-examined regularly. This creates individual health trajectories over time.
Built for reuse
FAIR data structure, biobanking, and platform access make the dataset usable for external collaborations.
There is no such dataset. We have screened them all.
Systematic screening of 633 publicly available datasets. Not a single one met all criteria.
Eight dataset requirements
From symptoms to multimodal understanding
What the YEARS dataset contains
Multimodal data collection across all relevant dimensions of human health.
Omics
- ·Genetics
- ·Epigenetics
- ·Metagenomics
- ·Proteomics
- ·Transcriptomics
- ·Metabolomics
- ·Microbiome
- ·Immunophenotyping
- ·Immunosequencing
Clinical Labs
- ·Cardiovascular
- ·Inflammation
- ·Hematology/Coagulation
- ·Metabolic/Lipid
- ·Hormone
- ·Kidney/Liver
- ·Autoimmunity
- ·Vitamins
- ·Blood gas
Imaging
- ·Resting ECG
- ·Stress ECG
- ·Resting echo
- ·Brain MRI*
- ·Liver MRI*
- ·Whole body MRI*
- ·Facial/skin imaging†
- ·Thyroid/vessel US
- ·Fundus photography
Medical History
- ·Family history
- ·Previous conditions
- ·Medications
- ·Surgeries
- ·Allergies
- ·Symptom diary
Physical Function
- ·Grip strength
- ·Gait speed
- ·Balance
- ·VO₂max
- ·Body composition
- ·Bone density
Lifestyle & Mental
- ·Sleep quality
- ·Physical activity
- ·Nutrition
- ·Stress
- ·Mental health
- ·Social factors
Data Quality SOP Pipeline
Scientific operations and governance
Ethics approval, data governance and clinical quality systems form the foundation of our research infrastructure.
Ethics
Ethics committee approval and study registration in accordance with international standards.
Data governance
GDPR-compliant data processing, pseudonymized storage, clear IP agreements before data access.
Quality systems
SOP-supported acquisition protocols, internal quality controls, external auditability.
Anonymised case reports
Examples of clinical discoveries from YEARS operations.
Patient 1
40y male, unexplained fatigue
Patient 2
81y female, severe exercise intolerance + urticaria
Patient 3
45y male, no findings
Collaboration models
We offer three collaboration pathways – for research institutions, industry partners, and clinical expansion.
Academic
Biomarker discovery & publications
- ·Biomarker discovery
- ·Cohort analyses
- ·Joint publications
- ·Methodological development
Industry (Translational)
Diagnostic validation & IP-protected
- ·Diagnostic validation
- ·Digital biomarker testing
- ·Wearable validation
- ·Biomarker qualification
Clinical implementation
Protocolised assessments & cohort expansion
- ·Protocolised assessments
- ·Cohort expansion
- ·Structured data
- ·Diseased cohort enrichment
Building the YEARS dataset
Timeline and milestones
Proof of Concept
- ·Berlin center opened Q3/2024
- ·Start of recruitment
- ·SOPs established
Longitudinal build-out
- ·400–600 subjects/physician/year
- ·Annual follow-ups
- ·Wearable integration
First integrated analyses
- ·PoC study
- ·Recallable subjects
- ·First longitudinal multi-omics
Scaled infrastructure
- ·10–25k deeply phenotyped
- ·50k total with partners
- ·50,000+ patient years
Explore collaboration
For academic collaborations and industry partnerships, contact our research team directly.
Dr. Jan K. Hennigs · YEARS Medical Center · Joachimsthaler Straße 34 · 10719 Berlin