MULTI-OMICS

Source: Hindu

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Context

• India is leveraging advanced genomics and multi-omics technologies to revolutionize the diagnosis and treatment of diseases like tuberculosis (TB), cancers, and those caused by antimicrobial resistance.
• Multi-omics integrates genomics, proteomics, transcriptomics, and epigenomics to provide comprehensive insights into disease mechanisms and treatment responses.

Details

Genomics Initiatives in India

• Genome India Project
  • Objective: Develop a reference genome for Indian people.
  • Milestone: Sequencing 10,000 genomes from 99 ethnic groups.
  • Applications: Design low-cost diagnostics and disease-specific genetic chips.
• IndiGen Project
  • Objective: Create a pilot dataset for analyzing genetic diseases.
  • Milestone: Sequencing genomes of 1,008 individuals from diverse ethnic groups.
  • Applications: Develop affordable screening approaches, optimize treatment, and minimize adverse events.
• Disease-Specific Consortia
  • Focus Areas: TB, cancers, rare genetic disorders, and antimicrobial resistance.
  • Approach: Use AI and machine learning to combine data from various omics to develop comprehensive disease management strategies.

Tuberculosis (TB)

• Indian Tuberculosis Genomic Surveillance Consortium (InTGS)
  • Objective: Sequence 32,000 TB clinical strains and develop a repository of Mycobacterium tuberculosis strains.
  • Goals: Map genetic diversity, correlate mutations with drug resistance, and develop sequence-based drug resistance determination methods.

Rare Genetic Disorders

• Paediatric Rare Genetic Disorders (PRaGeD) Mission
  • Objective: Create awareness, perform genetic diagnoses, discover new genes, provide counseling, and develop therapies.
  • Approach: Use IndiGen data in bioinformatic pipelines and next-generation sequencing for diagnosis and disease management.

Cancers

• Indian Cancer Genome Consortium (ICGC-India)
  • Objective: Characterize genomic abnormalities in various cancers and identify population-specific genetic variations.
  • Applications: Discover biomarkers, new treatment targets, and develop personalized treatment strategies.
• Indian Cancer Genome Atlas Project
  • Objective: Create a comprehensive catalogue of genomic alterations in Indian cancers.
  • Applications: Facilitate cancer research and precision medicine initiatives.

Antimicrobial Resistance

• Role of Genomics and Metagenomics
  • Objective: Analyze antimicrobial resistance and identify resistance profiles without lab cultures.
  • Applications: Inform antibiotic use and select appropriate drug combinations.

AI, ML, and Multi-omics

• AI and ML in Genomics
  • Applications: Predict cancer risk, develop diagnostic tools, classify cancers, and develop treatment strategies.
  • Data Analysis: AI and ML facilitate the analysis of large genomic datasets, identifying disease-causing variants.
• Multi-omics Integration
  • Applications: Combine genomics, proteomics, transcriptomics, and epigenomics to provide holistic insights into disease mechanisms and treatment responses.
  • Technological Advancements: Standard computational facilities can now handle multi-omics Big Data products rapidly.

Conclusion

By integrating AI and machine learning, researchers are able to extract valuable insights from extensive datasets, paving the way for personalized medicine and improved patient outcomes.

Sources:

Hindu

PRACTICE QUESTION Q. India's adoption of multi-omics and advanced genomics is transforming the healthcare landscape, offering new possibilities for the diagnosis and treatment of complex diseases. Discuss. (10 marks)