The first genome-wide association study

What the study found

In this 2007 Nature study, the Wellcome Trust Case Control Consortium ran a joint genome-wide association (GWA) study in the British population, examining about 2,000 individuals for each of seven major diseases against a shared set of roughly 3,000 controls, using a 500,000-marker genotyping array. Comparing cases with controls, they identified 24 independent association signals at stringent significance (P < 5 x 10^-7): one in bipolar disorder, one in coronary artery disease, nine in Crohn's disease, three in rheumatoid arthritis, seven in type 1 diabetes, and three in type 2 diabetes.

Why it matters

Common diseases are shaped by many genes of small effect, which older methods struggled to find. Scanning hundreds of thousands of markers across thousands of people at once — a GWAS — made it possible to locate regions of the genome statistically linked to disease, and to do so across several diseases in one design.

Analysis — the pattern

This was a template (analysis, not a single-study claim): large shared control sets, dense genotyping arrays, and strict significance thresholds became the standard, and GWAS grew into a major engine of human genetics. A recurring lesson is that most hits fall in non-coding, regulatory regions — which later maps like ENCODE helped interpret.

What is still uncertain

An association signal marks a region, not a mechanism, and the effect of any single common variant is usually small. Translating GWAS hits into biology and clinical use remains slow, case-by-case work, and early studies were weighted toward European-ancestry populations.