Fig 2: Immune profile of cis women with PBC.(A and B) Serum cytokine levels determined by flow cytometry–based LEGENDplex analysis from cis women with PBC (n = 24) compared with age- and sex-matched healthy controls (n = 23). (C) Frequencies of CD3+, CD4+ CD8+, Th2, Th1, Th17, and Treg from cis women with PBC (n = 17–21) compared with age- and sex-matched healthy controls (n = 21–22) were analyzed by flow cytometry. (D) Th1 differentiation rate was increased in CD4+ T cells derived from cis women with PBC (n = 16) compared with age- and sex-matched healthy controls (n = 21). (E) Serum testosterone levels of cis women with PBC (n = 27) compared with age- and sex-matched healthy controls (n = 23) determined by LC-MS/MS analysis. (F) Correlation analysis of serum testosterone levels and serum cytokine profiles determined using flow cytometry–based LEGENDplex analysis from cis women with PBC (n = 27). (G) Decreased concentrations of IFN-γ and TNF in supernatant of T cell receptor–stimulated T cells derived from healthy cis women in the presence of testosterone. Cytokine secretion was analyzed in supernatants using ELISA, and statistical significance was determined via 1-way ANOVA (G). Statistical analysis was performed using Mann-Whitney U test (B–E). *P ≤ 0.05; **P ≤ 0.01; ***P ≤ 0.001, ****P ≤ 0.0001.

Fig 3: Shift toward antiinflammatory immune cell subsets in trans men receiving GAHT.(A) Heatmap of intraindividual serum cytokine changes in trans men (n = 25) 6M after GAHT normalized to baseline before therapy start. Serum cytokine levels were determined by flow cytometry–based LEGENDplex analysis. (B) Heatmap of T cell populations identified as significantly different by flow cytometry–based immunophenotyping 6M after therapy start (n = 22). Red indicates an increase and blue indicates a decrease compared with baseline samples. (C) Frequencies of CD3+, CD4+, CD8+, Th17, Th1, Th2, and Treg from trans men at BL, 3M, and 6M time points analyzed by flow cytometry. (D) Shift in T cell phenotypes toward antiinflammatory immune cell subsets. Data are shown as mean ± SD. Statistical analysis was performed using a 1-way ANOVA with correction for multiple comparisons. *P ≤ 0.05; **P ≤ 0.01.

Fig 4: Increased circulating mucosal-associated invariant T (MAIT) cells related to poor collateralization formation. A and B, Flow cytometry analysis of CD3+CD4+ cells among live cells from patients with good collateralization (GC; n=59) and poor (PC; n=45) collateralization. Statistical significance for paired comparisons was performed by Student t test. C and D, Flow cytometry analysis of CD3+CD8+ cells among live cells from patients with GC and PC. Statistical significance for paired comparisons was performed by Student t test. E and F, Flow cytometry analysis of MAIT cells among CD3+ cells from patients with GC and PC. Statistical significance for paired comparisons was performed by Student t test. G, The proportion of poor collateralization increased stepwise with the increase of that of MAIT cells. H, Restricted cubic splines plot detecting the association between the proportion of MAIT cells and poor collateralization. I, Receiver operating characteristic curve analysis of the proportion of MAIT cells for diagnosing poor collateralization. J, Subgroup analyses of the proportion of MAIT cells for diagnosing poor collateralization. Statistical significance for paired comparisons was performed by Student t test. Data are presented as mean±SD. See also Figures S9 and S10. AUC indicates area under the curve; BMI, body mass index; GFR, glomerular filtration rate; HbA1c, glycated hemoglobin A1c; and OR, odds ratio.