‘Genome-wide Disease Association Studies (GWAS) advanced our understanding of health and disease.’ Discuss. (Answer in 250 words)

- ‘Genome-wide Disease Association Studies (GWAS) advanced our understanding of health and disease.’ Discuss. (Answer in 250 words)
Introduction
The claim is true but narrower than it sounds. The genome-wide scan replaced guesswork about candidate genes with an unbiased search, and established that common disease is highly polygenic — a real advance whose clinical returns remain modest.

Body
1. The design: several hundred thousand to several million single nucleotide polymorphisms are typed on arrays and imputed against a reference panel, in large case-control or cohort samples. Each variant is tested singly for association with the trait; the significance threshold is set near five in a hundred million to survive a million effectively independent tests, population stratification is controlled by principal components, and a finding counts only when it replicates in an independent sample.
2. What it has delivered: many tens of thousands of robust variant-trait associations, a figure large but only approximate. Complement factor H in age-related macular degeneration, TCF7L2 in type 2 diabetes, FTO in obesity, NOD2 and IL23R in Crohn's disease, the 9p21 locus in coronary artery disease, and a Neanderthal-derived haplotype on chromosome 3 in severe COVID-19. It has yielded polygenic risk scores, implicated new pathways such as autophagy in Crohn's, and strengthened drug-target selection and Mendelian randomisation.
3. Its limits: effect sizes are tiny, odds ratios commonly between 1.1 and 1.3, so much heritability remains unexplained. Most hits are non-coding, and the causal variant, gene and tissue usually stay unknown, so association is not mechanism. Participants are overwhelmingly of European ancestry, so risk scores transfer poorly to South Asian and African populations, the gap the GenomeIndia programme is meant to narrow.
4. The judgment: an advance in understanding genetic architecture rather than in prediction.

Conclusion
Such studies ended the candidate-gene era and demonstrated polygenicity. Their promise of personalised medicine still awaits functional follow-up and genuinely diverse samples.