When engaging in hypothesis generating research, it is important to summarize the relationships of interest in a meaningful way. Correlation coefficients are a common summary statistic that describe the strength and direction of relationships. Simple summary methods use unadjusted correlation coefficients such as Pearson or Spearman's; however, failing to adjust for covariates may result in misleading conclusions. Partial correlations allow for adjustment variables, but traditional approaches for measuring partial rank correlations lack a theoretical foundation. Liu et al (Biometrics, in press) proposed an alternative estimator for covariate-adjusted partial Spearman's rank correlations using probability-scale residuals (PSRs). We apply this method to explore the relationships between body composition and markers of innate and adaptive immune status in HIV+ subjects. Three measures of adiposity were considered - body mass index, fat mass index, and plasma leptin. Immunologic markers included soluble cytokines and other biomarkers, CD4+ and CD8+ T cell subsets.