Volumetric body composition analysis of the Cancer Genome Atlas reveals novel body composition traits and molecular markers Associated with Renal Carcinoma outcomes

• Published in: Scientific reports Vol. 14; no. 1; pp. 27022 - 15
• Main Authors: Mironchuk, Olesya, Chang, Andrew L., Rahmani, Farzaneh, Portell, Kaitlyn, Nunez, Elena, Nigogosyan, Zack, Ma, Da, Popuri, Karteek, Chow, Vincent Tze Yang, Beg, Mirza Faisal, Luo, Jingqin, Ippolito, Joseph E.
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 06-11-2024; Nature Publishing Group; Nature Portfolio
• Subjects: 631/67/2321; 692/4028/67/589/1588/1351; Abdomen; Archives & records; Body composition; Body fat; Body mass index; Computed tomography; Datasets; Females; Gene expression; Genomes; Genomic analysis; Humanities and Social Sciences; Kidney cancer; Magnetic resonance imaging; Medicine; Mortality; multidisciplinary; Musculoskeletal system; Obesity; Patients; Qualitative research; Renal cell carcinoma; Sarcopenia; Science; Science (multidisciplinary); Software; Tomography; Vertebrae
• ISSN: 2045-2322; 2045-2322
• DOI: 10.1038/s41598-024-76280-6

Clinically, the body mass index remains the most frequently used metric of overall obesity, although it is flawed by its inability to account for different adipose (i.e., visceral, subcutaneous, and inter/intramuscular) compartments, as well as muscle mass. Numerous prior studies have demonstrated linkages between specific adipose or muscle compartments to outcomes of multiple diseases. Although there are no universally accepted standards for body composition measurement, many studies use a single slice at the L3 vertebral level. In this study, we use computed tomography (CT) studies from patients in The Cancer Genome Atlas (TCGA) to compare current L3-based techniques with volumetric techniques, demonstrating potential limitations with level-based approaches for assessing outcomes. In addition, we identify gene expression signatures in normal kidney that correlate with fat and muscle body composition traits that can be used to predict sex-specific outcomes in renal cell carcinoma.