Transforming Indian Healthcare: The Impact of Multi-Omics on Disease Management

Introduction

India is leveraging multi-omics approaches, combining genomics, proteomics, transcriptomics, and epigenomics, to revolutionize the diagnosis and treatment of diseases such as tuberculosis (TB), cancers, and rare genetic disorders.

Genome India Project

• Objective: Develop a reference genome for Indian people.
• Achievements: Sequenced 10,000 genomes from 99 ethnic groups by January 2024.
• Impact: Helps design low-cost diagnostic tools and enhance disease research.

IndiGen Mission

• Objective: Create a dataset representing India’s diverse ethnic groups.
• Achievements: Sequenced genomes of 1,008 individuals in six months.
• Impact: Aids in understanding genetic diseases, developing affordable screenings, and optimizing treatments.

Indian Tuberculosis Genomic Surveillance Consortium (InTGS)

• Objective: Sequence 32,000 TB strains and create a repository of Mycobacterium tuberculosis strains.
• Goals:
  • Map genetic diversity and drug resistance patterns of TB bacteria.
  • Develop sequence-based methods for determining drug resistance.
• Impact: Improve TB diagnosis and treatment strategies.

Paediatric Rare Genetic Disorders (PRaGeD) Mission

• Objective: Address rare genetic disorders in children.
• Activities:
  • Create awareness and perform genetic diagnoses.
  • Discover and characterize new genes or variants.
  • Provide counseling and develop new therapies.
• Impact: Enhance management and prenatal diagnosis of rare genetic diseases.

Indian Cancer Genome Consortium (ICGC-India)

• Objective: Characterize genomic abnormalities in Indian cancer patients.
• Activities:
  • Identify population-specific genetic variations linked to cancer.
  • Facilitate personalized treatment strategies.
• Impact: Improve cancer diagnosis, identify biomarkers, and develop targeted therapies.

Antimicrobial Resistance Research

• Objective: Analyze antimicrobial resistance using genomics and metagenomics.
• Impact: Help clinicians prescribe antibiotics more effectively by understanding resistance profiles without growing microbes in labs.

Role of AI and ML

• Applications:
  • Analyze extensive genomic datasets.
  • Predict disease risks and develop diagnostic tools.
  • Classify cancers and develop treatment strategies.
  • Identify disease-causing variants in genetic disorders.
• Impact: Enhance the speed and accuracy of data analysis and healthcare solutions.

Key Points

• Multi-omics approaches are transforming the diagnosis and treatment of TB, cancers, and rare genetic disorders in India.
• National initiatives like Genome India, IndiGen, InTGS, PRaGeD, and ICGC-India are at the forefront of this revolution.
• AI and ML are crucial in managing and analyzing large datasets to develop effective healthcare strategies.