"Here, we demonstrate that large language models (LLMs) can accurately identify genes likely to be causal at loci from GWAS. By evaluating the performance of GPT-3.5 and GPT-4 on datasets of GWAS loci with high-confidence causal gene annotations, we show that these models outperform state-of-the-art methods in identifying putative causal genes."