Decoding sex differences in human immunity through systems immunology

Abstract

Immune function varies widely across humans. Biological sex is a key factor underlying human immune variability, with men presenting with more severe infections and increased cancer rates, while women exhibit higher vaccine responses and prevalence of autoimmunity. Intrinsic biological sex differences arise from varying contributions of chromosomal sex, and sex hormone sensing and downstream signaling to different cell types. This complex regulation presents a unique opportunity for the exploration of human immune sex differences using systems-level methods of investigation. Here we analyze the current literature and the applications of systems immunology in elucidating the immune sex differences in humans. We examine mechanisms of biological sex modulation of human immunity via sex chromosomes, and particularly emphasize the role of sex hormones. We then focus on how systems immunology has been advancing our understanding of how sex impacts the healthy immune system at steady state, ranging from cell composition, transcriptomics, epigenomics, metabolomics, spatial and cell-cell interactions, to plasma proteomics. We also examine systems-level applications to investigating sex differences upon immune perturbations and give an overview of key future directions for the field. Systems immunology provides a powerful framework to decode biological sex-regulated pathways in immunity, paving the way for more precise, sex-informed therapeutic interventions to address sex differences in immune-related conditions.

Keywords: biological sex; sex differences in human immunity; sex hormones; systems immunology.

Figure 1.

Overview of signaling pathways for sex hormones and upstream regulators. Interaction of hypothalamic–pituitary–gonadal axis protein hormones and steroid hormones with their receptors, highlighting their tissue sources, cognate receptors, downstream non-genomic and genomic signaling cascades. The hypothalamus-derived GnRH acts via the GPCR GnRHR triggering non-genomic signaling pathways. Pituitary-derived LH and FSH bind to their respective GPCRs, LHCGR and FSHR, activating similar non-genomic signaling cascades. Androgens, such as testosterone, DHT, and androstenedione, act through both membrane androgen receptors (mAR) and androgen receptors (AR). mAR is a GPCR that mediates non-genomic signaling, while the nuclear receptor AR initiates both non-genomic signaling, and genomic signaling by binding AREs in the nucleus. Estrogens, including estradiol, estrone, and estriol, act through both membrane estrogen receptors (mER) and nuclear ERα and ERβ. mER mediates non-genomic signaling, while nuclear receptors ERα/ERβ activate both non-genomic signaling, and genomic signaling by binding EREs. Progestins, like progesterone, act through membrane progesterone receptors (mPR), which induce non-genomic signaling, and nuclear PR, which initiates both non-genomic signaling, and genomic signaling pathways by PRE binding. Androgen, estrogen, and progestin signaling exhibit significant crosstalk. Sex hormones bind at low affinity to non-cognate sex hormone receptors, and sex hormone nuclear receptors can interact with various hormone response elements and cooperate or antagonize each other to activate or repress gene expression. Light-colored arrows indicate lower binding affinity. Intracellular signaling cascades depicted are derived from immune cells (GnRH, mER) [48, 49, 50], testicular Sertoli cells and ovarian granulosa (FSHR) [51], or cell lines derived from ovarian and testicular (LHCGR) [52], prostate (mAR) [53], breast (mPR) [54] or diverse types of cancer (AR, ERα/β, PR) [55]. AR: androgen receptor, ARE: androgen response element, ER: estrogen receptor, ERE: estrogen response element, ERK/MAPK: extracellular signal-regulated kinase/mitogen-activated protein kinase, FSH: follicle-stimulating hormone, FSHR: FSH receptor, GnRH: gonadotropin-releasing hormone, GnRHR: GnRH receptor, LH: luteinizing hormone, LHCGR: LH/choriogonadotropin receptor, mAR: membrane-bound AR, mER: membrane-bound ER, mPR: membrane-bound PR, Pi3K/Akt: phosphoinositide 3-kinase/protein kinase B, PKA: protein kinase A, PKC: protein kinase C, PR: progesterone receptor, PRE: progesterone response element. Created in BioRender. Escrivà Font, J. (2025) https://BioRender.com/ejhfg27.

Figure 2.

Sex hormones across lifespan in humans. A. Estradiol, progesterone, and testosterone levels across different endocrinological phases of life for individuals with XX and XY chromosomal sex. In utero levels are inferred from maternal serum and amniotic fluid levels (dashed curves), whereas post-natal values are derived from blood measurements (solid curves). Dashed vertical lines indicate notable hormone transitions, including birth, puberty onset, embryo implantation, and menopause. Short, dotted lines delineate each menstrual cycle. Ref [47, 86, 87, 298–300]. B. Trajectories over the course of life for testosterone and estradiol blood concentrations in individuals with XX and XY chromosomal sex. Both sexes start at low circulating sex hormone concentrations at birth and diverge during puberty. Males show a steady testosterone decline during andropause, while female menopause shows faster kinetics in estradiol concentration reduction. Variability in hormone concentrations is depicted with dotted circles. Ref [47]. C. Landscape of testosterone and estrogen signaling for different human cohorts across life stages, sex-hormone altering conditions, and pharmacological modulations. Comparison of immune measurements among these groups can enable investigation of sex chromosomes and sex hormone modulation of human immune function. PCOS: Polycystic ovarian syndrome. MHT: Masculinizing hormone therapy. FHT: Feminizing hormone therapy. Orange denotes individuals with XX chromosomal sex, and purple denotes individuals with XY chromosomal sex.

Figure 3.

Multiscale immunology investigation via system immunology approaches. A. Scales of human immune investigation, ranging from molecular- to cohort-level investigation via immunology studies, and population-based investigation via epidemiology studies. B. Experimental immunology approaches: Experimental techniques are plotted based on the knowledge depth and breadth they can provide, and colored based on their category: systems immunology (blue) versus classical immunology (green). Generally, systems immunology provides a broader understanding due to high-throughput techniques. Some methods can be regarded as systems-level or classical approaches, depending on the experimental design, and are colored half blue and half green. C. Computational immunology approaches: Single-cell transcriptomics data illustrates how computational approaches enable the investigation of sex differences in immunity at multiple biological scales. DEGs, differentially expressed genes; PPI databases, protein-protein interaction databases, e.g. STRING [139]; TFBS databases, transcriptional factor binding site databases, e.g. JASPAR [140]; LRI databases, ligand-receptor interaction databases, e.g. CellPhoneDB [141], CellChatDB [142], and OmniPath [143]; GEMs, genome-scale metabolic models [144]. Created in BioRender. Cao, T. (2025) https://BioRender.com/7er4sm8.