Immune-aging is linked to clinical malignancy and vaccine responses in myeloma

Several single-cell transcriptomic approaches have been applied to study immune system in MM, and previously implied “T-cell exhaustion” largely based on comparison with signatures derived in murine chronic viral infection models. However functional validation of such “signatures” has been lacking. In this paper, we have studied nearly 300+ racially diverse MM/MGUS patients/healthy controls. Initial functional studies did not support global T cell exhaustion, but instead illustrated paradoxically enhanced inflammatory cytokine production and proliferation in MM T cells, even in phenotypes previously thought to be “exhausted”. We therefore hypothesized that altered states of T cell differentiation (e.g. increased terminal effectors) may instead be related to immune aging. In order to quantify this, we first studied a cohort of 100+ healthy donors across 7 decades of life to quantify age-associated immune changes, and then applied findings to MM/MGUS cohorts. This led to the discovery that in chronologically age-matched cohorts, MM is associated with greater immune aging compared to MGUS. These findings were also supported by transcriptomic and phospho-proteomic analyses. Interestingly, MGUS patients with Black ancestry exhibited enhanced aging. These data therefore support potential contribution of immune aging in malignant transformation, as well as racial predisposition with earlier onset of MM in Blacks. Finally, to evaluate the impact of immune aging on immune function in vivo, we analyzed yet another cohort of patients undergoing SARSCov2 vaccination. Immune but not chronologic aging was associated with responses to vaccination. Overall design: Peripheral blood and bone marrow specimens were obtained from patients with myeloma and MGUS following informed consent approved by Emory Institutional Review Board. BMMCs (n=23) were thawed, incubated at 37°C for 1 hour to rest. Cells were stained using a TotalSeq-C antibody cocktail following the 10X Genomics protocol for Chromium Single-Cell Immune Profiling with Feature Barcoding Technology (ver. 1.0). Single cells were isolated using the Chromium Controller (10X Genomics). Gene expression and CITE-seq libraries were prepared using the following kits from 10× Genomics: Chromium Next GEM Single Cell 5' Kit v2 (PN-1000263), Chromium 5' Feature Barcode Kit (PN-1000541), Chromium Single-Cell 5' Library Construction Kit (PN-1000190), Chromium Next GEM Chip K Single Cell Kit (PN-1000287), Dual Index Kit TT Set A (PN-1000215) and Dual Index Kit TN Set A (PN-1000250). Sequencing was conducted on an Illumina NovaSeq 6000 at a targeted depth of 50,000 reads/cell for GEX libraries and 5000 reads/cell for CITE-seq libraries.