{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,16]],"date-time":"2026-10-16T18:49:55Z","timestamp":1792176595744,"version":"4.4.0"},"reference-count":26,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2024,8,20]],"date-time":"2024-08-20T00:00:00Z","timestamp":1724112000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Immunol."],"abstract":"<jats:sec><jats:title>Background<\/jats:title><jats:p>Inflammaging, an immune status characterized by a sustained increase in pro-inflammatory markers and a decline in anti-inflammatory mechanisms, is a critical risk factor in the development of sarcopenia. Landscapes of the causal relationships between immunity and sarcopenia are needed to understand the mechanism of sarcopenia and provide novel treatments comprehensively.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>We used Mendelian Randomization (MR) as the basic method in this study. By setting immune proteins, immune cells, and sarcopenia as exposures and outcomes alternatively, and then combining them in different directions, we potentially estimated their causal relationships and directions and subsequently mapped the comprehensive causal landscape based on this information efficiently. To further understand the network, we developed a method based on rank-sums to integrate multiple algorithms and identify the key immune cells and proteins.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>More than 1,000 causal relationships were identified between immune cell phenotypes, proteins, and sarcopenia traits (p &amp;lt; 0.05), and the causal maps of these linkages were established. In the threshold of FDR &amp;lt; 0.05, hundreds of causal linkages were still significant. The final comprehensive map included 13 immune cell phenotypes and 8 immune proteins. The star factors in the final map included EM CD8br %CD8br, EM DN (CD4- CD8-) %DN, SIRT2, and so on.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusion<\/jats:title><jats:p>By reading the landscapes in this study, we may not only find the factors and the pathways that have been reported and proven but also identify multiple novel immunity cell phenotypes and proteins with enriched upstream and downstream pathways.<\/jats:p><\/jats:sec>","DOI":"10.3389\/fimmu.2024.1443885","type":"journal-article","created":{"date-parts":[[2024,8,20]],"date-time":"2024-08-20T04:44:32Z","timestamp":1724129072000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":9,"title":["Comprehensive landscapes of the causal network between immunity and 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