Big data in sarcoidosis

• Published in: Current opinion in pulmonary medicine Vol. 30; no. 5; p. 561
• Main Author: Rivera, Natalia V
• Format: Journal Article
• Language: English
• Published: United States 01.09.2024
• Subjects: Big Data; Biomarkers - metabolism; Humans; Phenotype; Precision Medicine; Sarcoidosis - diagnosis; Sarcoidosis - physiopathology; Sarcoidosis - therapy
• ISSN: 1531-6971
• DOI: 10.1097/MCP.0000000000001102

This review provides an overview of recent advancements in sarcoidosis research, focusing on collaborative networks, phenotype characterization, and molecular studies. It highlights the importance of collaborative efforts, phenotype characterization, and the integration of multilevel molecular data for advancing sarcoidosis research and paving the way toward personalized medicine. Sarcoidosis exhibits heterogeneous clinical manifestations influenced by various factors. Efforts to define sarcoidosis endophenotypes show promise, while technological advancements enable extensive molecular data generation. Collaborative networks and biobanks facilitate large-scale studies, enhancing biomarker discovery and therapeutic protocols. Sarcoidosis presents a complex challenge due to its unknown cause and heterogeneous clinical manifestations. Collaborative networks, comprehensive phenotype delineation, and the utilization of cutting-edge technologies are essential for advancing our understanding of sarcoidosis biology and developing personalized medicine approaches. Leveraging large-scale epidemiological resources and biobanks and integrating multilevel molecular data offer promising avenues for unraveling the disease's heterogeneity and improving patient outcomes.