eng International Academy of Ecology and Environmental Sciences Network Pharmacology 2415-1084 2026-12-1 11 3-4 62 89 1 article WenJun Zhang 1 2 School of Life Sciences, Sun Yat-sen University, Guangzhou 510275, China In present study, a GWAS (Genome-Wide Association Study) data fetcher with AI was developed. It is a web-based tool that generates genetic variant data for Mendelian Randomization (MR) analysis using AI language models. It supports several AI services as DeepSeek, Google Gemini, and OpenAI GPT, etc. The fetcher supports both univariate and multivariate MR analyses. In the fetcher, the input are exposure variable(s) and outcome variable, the output are GWAS exposure and outcome data files. By leveraging AI to generate realistic data, users can practice MR analysis without accessing restricted genetic databases, test analysis pipelines safely, learn GWAS data structure and format, experiment with different exposure-outcome combinations, and develop and validate bioinformatics tools. http://www.iaees.org/publications/journals/np/articles/2026-11(3-4)/a-GWAS-data-fetcher-with-AI.pdf GWAS data fetcher Artificial Intelligence (AI) Large Model (LM) web-based tool Mendelian Randomization (MR)