Scientists Identify Three Genes That Control How Fast Your Body Ages at Protein Level
UK Biobank study of 44,435 people reveals genetic variants in BRCA1, POLR2A, and TET2 that accelerate biological aging measured through blood proteins.
Summary
Researchers analyzed blood proteins from 44,435 UK Biobank participants to create a 'proteomic aging clock' that predicts biological age with 94% accuracy. The study identified three key genes—BRCA1, POLR2A, and TET2—that influence how fast people age at the protein level. Each year of accelerated proteomic aging increased death risk by 13%. Higher BMI and type 2 diabetes causally accelerated this aging process, supporting the idea that metabolic health directly impacts biological aging speed.
Detailed Summary
A groundbreaking study of 44,435 UK Biobank participants has revealed how genetics control the rate of biological aging at the protein level, offering new insights into why some people age faster than others. Researchers created a highly accurate 'proteomic aging clock' by analyzing 1,459 blood proteins, achieving 94% correlation with chronological age.
The team identified 16 genetic variants associated with accelerated proteomic aging, but found that most were driven by effects on single proteins. After removing these single-protein effects, three genes emerged with widespread impacts on aging: BRCA1 (known for breast cancer risk), POLR2A (involved in gene transcription), and TET2 (regulates DNA methylation). These genes appear to influence aging through broad effects across multiple protein pathways.
The proteomic aging clock proved remarkably predictive of health outcomes. Each year of accelerated proteomic aging increased all-cause mortality risk by 13%, even after accounting for chronological age. The clock strongly predicted cancer, type 2 diabetes, and heart disease, often completely replacing chronological age as a predictor.
Using Mendelian randomization, researchers demonstrated that higher BMI and type 2 diabetes causally accelerate proteomic aging, providing strong evidence that metabolic dysfunction directly speeds biological aging processes. This supports interventions targeting weight management and metabolic health for longevity.
The study represents a major advance in aging research by moving beyond DNA methylation clocks to protein-based measures that may be more biologically interpretable and actionable for clinical applications.
Key Findings
- Proteomic aging clock predicts mortality with 13% increased risk per year of acceleration
- Three genes (BRCA1, POLR2A, TET2) control widespread protein aging effects
- Higher BMI and type 2 diabetes causally accelerate biological aging
- Protein age completely replaces chronological age for predicting major diseases
- GDF15 and SCARF2 emerge as top aging-associated proteins
Methodology
Elastic net machine learning model trained on 1,459 plasma proteins from UK Biobank participants. Genome-wide association study identified genetic variants, with follow-up analysis removing single-protein effects to find broad aging signals.
Study Limitations
Study limited to UK Biobank participants of primarily European ancestry. Protein measurements from single time point may not capture aging dynamics over time.
Enjoyed this summary?
Get the latest longevity research delivered to your inbox every week.
