An Open Competition for Biomarkers of Aging

Abstract

Open scientific competitions have successfully driven biomedical advances but remain underutilized in aging research, where biological complexity and heterogeneity require methodological innovations. Here, we present the results from Phase I of the Biomarkers of Aging Challenge, an open competition designed to drive innovation in aging biomarker development and validation. The challenge leverages a unique DNA methylation dataset and aging outcomes from 500 individuals, aged 18 to 99. Participants are asked to develop novel models to predict chronological age, mortality, and multi-morbidity. Results from the chronological age prediction phase show important advances in biomarker accuracy and innovation compared to existing models. The winning models feature improved predictive power and employ advanced machine learning techniques, innovative data preprocessing, and the integration of biological knowledge. These approaches have led to the identification of novel age-associated methylation sites and patterns. This challenge establishes a paradigm for collaborative aging biomarker development, potentially accelerating the discovery of clinically relevant predictors of aging-related outcomes. This supports personalized medicine, clinical trial design, and the broader field of geroscience, paving the way for more targeted and effective longevity interventions.

Figure 1.. Overview of the Biomarkers of Aging Challenge.

a. Timeline of the challenge showing the three phases: Chronological Age Prediction (March-July 2024), Mortality Prediction (July-November 2024), and Multi-morbidity Prediction (planned for 2025). Key dates for each phase, including announcements, deadlines, and result releases, are indicated. b. Illustration of the MGB cohort (n = 500) used in the challenge, showing blood samples, DNA extraction, and methylation array analysis. c. Age distribution of the challenge cohort, with density plots colored for males and females. d. Bar chart showing the race distribution of the challenge cohort, including White, Black, Asian, and other categories.

Figure 2.. Phase 1 of the Biomarkers of Aging Challenge.

a. Bar plot showing the mean absolute error (MAE) for different models, including competition submissions (blue) and published biomarkers (red). The x-axis lists the models, and the y-axis shows the MAE in years. The plot indicates that 37 teams submitted a total of 551 entries. b. Scatter plot comparing predicted vs. actual age for the top 3 winning teams. Each point represents an individual, with different colors for each team’s model. The diagonal line represents perfect prediction.