This review discusses the evidence for pleiotropy in contemporary genetic mapping studies, focusing on the challenges and strategies for detecting and interpreting cross-phenotype (CP) associations. CP associations, where a genetic variant affects multiple traits, are common in genome-wide association studies (GWASs) across autoimmune diseases, cancers, and neuropsychiatric disorders. The review highlights the distinction between biological pleiotropy, mediated pleiotropy, and spurious pleiotropy, and outlines analytical approaches to identify and characterize these effects. It emphasizes the importance of careful study design to minimize spurious associations and the need for fine mapping to distinguish biological from spurious pleiotropy. The clinical implications of CP effects are also discussed, including their impact on disease classification, genetic testing, and drug development. The review concludes by outlining future directions, such as the use of sequencing-based studies and phenome-wide association studies (PheWASs) to further our understanding of shared genetic architecture and complex traits.This review discusses the evidence for pleiotropy in contemporary genetic mapping studies, focusing on the challenges and strategies for detecting and interpreting cross-phenotype (CP) associations. CP associations, where a genetic variant affects multiple traits, are common in genome-wide association studies (GWASs) across autoimmune diseases, cancers, and neuropsychiatric disorders. The review highlights the distinction between biological pleiotropy, mediated pleiotropy, and spurious pleiotropy, and outlines analytical approaches to identify and characterize these effects. It emphasizes the importance of careful study design to minimize spurious associations and the need for fine mapping to distinguish biological from spurious pleiotropy. The clinical implications of CP effects are also discussed, including their impact on disease classification, genetic testing, and drug development. The review concludes by outlining future directions, such as the use of sequencing-based studies and phenome-wide association studies (PheWASs) to further our understanding of shared genetic architecture and complex traits.