The paper discusses the detection of pleiotropy in Mendelian randomization (MR) studies using summary data and a continuous outcome. Pleiotropy, the influence of a genetic variant on multiple phenotypes, can lead to biased estimates in MR studies. The authors propose an alternative approach to the Sargan test, which is used when individual phenotype, outcome, and genotype data are measured in the same subjects. Their method, the between-instrument heterogeneity Q test, is evaluated through simulations and applied to published data. The Q test is found to be conservative in small samples but has increasing power with the degree of pleiotropy and sample size. The I² index, which measures the percentage of total variation in estimates explained by heterogeneity, is also evaluated and shown to have similar properties to the Q test. The authors conclude that the between-instrument Q test is a useful tool for detecting heterogeneity due to pleiotropy or other causes in large MR studies based on summary data.The paper discusses the detection of pleiotropy in Mendelian randomization (MR) studies using summary data and a continuous outcome. Pleiotropy, the influence of a genetic variant on multiple phenotypes, can lead to biased estimates in MR studies. The authors propose an alternative approach to the Sargan test, which is used when individual phenotype, outcome, and genotype data are measured in the same subjects. Their method, the between-instrument heterogeneity Q test, is evaluated through simulations and applied to published data. The Q test is found to be conservative in small samples but has increasing power with the degree of pleiotropy and sample size. The I² index, which measures the percentage of total variation in estimates explained by heterogeneity, is also evaluated and shown to have similar properties to the Q test. The authors conclude that the between-instrument Q test is a useful tool for detecting heterogeneity due to pleiotropy or other causes in large MR studies based on summary data.