To better understand aging in Indians, the Indian Institute of Science (IISc) started a large research project called BHARAT as part of its Longevity India Program.

About the BHARAT Study

• BHARAT stands for ‘Biomarkers of Healthy Aging, Resilience, Adversity, and Transitions’.
• Objective: To map physiological, molecular, and environmental indicators that influence aging in the Indian population.
• It aims to build the Bharat Baseline – a reliable reference for what is normal in Indians.

What BHARAT aims to Capture?

• Genomic biomarkers (e.g., mutations linked to disease susceptibility).
• Proteomic and metabolic indicators (reflecting biological functions and pathways).
• Environmental and lifestyle data (to understand contextual influences).
• Seeks to identify early markers of sub-optimal organ functioning, even before disease manifests.
  • Example: When “liver age” is biologically older than chronological age.

Why is Study Needed?

• Western Benchmarks: Most existing ageing and disease-related biomarkers are based on Western populations, which may not apply accurately to Indians.
  • Western benchmarks for cholesterol, Vitamin D, or B12 may mislabel Indians as deficient.
• Predictive models for diseases may be misleading without population-specific baselines.
• Age-related diseases are rising:
  • India faces a 168% rise in Parkinson’s and 200% increase in dementia cases in low- and middle-income countries by 2050.
• Gaps in Current Healthcare Understanding
  • Diagnostic cut-offs often don’t reflect population-specific disease progression in the Global South.
    • For example, C-reactive protein (CRP) is naturally elevated in many Indians due to early-life infections, toxins, or metabolic issues, not necessarily acute illness.
    • Using Western CRP thresholds can miss early signs of cardiovascular/metabolic diseases in Indians.

Challenges 

• India’s vast diversity — genetic, environmental, and socioeconomic — makes comprehensive sampling difficult.
  • Training datasets must reflect India’s diversity to avoid reinforcing existing health inequities.
• Other Challenges include:
  • Gathering samples from healthy adults.
  • Securing long-term government and philanthropic funding.
  • Nationwide expansion of sample collection.

Role of AI and Computational Tools

• AI and machine learning will be used to:
  • Integrate and analyze multi-dimensional data.
  • Simulate intervention outcomes.
  • Improve signal detection in high-dimensional, small-sample studies.

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