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Immune responses generally decline with age. However, the dynamics of this process at the individual level have not been characterized, hindering quantification of an individual’s immune age. Here, we use multiple ‘omics’ technologies to capture population- and individual-level changes in the human immune system of 135 healthy adult individuals of different ages sampled longitudinally over a nine-year period. We observed high inter-individual variability in the rates of change of cellular frequencies that was dictated by their baseline values, allowing identification of steady-state levels toward which a cell subset converged and the ordered convergence of multiple cell subsets toward an older adult homeostasis. These data form a high-dimensional trajectory of immune aging (IMM-AGE) that describes a person’s immune status better than chronological age. We show that the IMM-AGE score predicted all-cause mortality beyond well-established risk factors in the Framingham Heart Study, establishing its potential use in clinics for identification of patients at risk. An integrated high-dimensional measurement of immune age describes a person’s immune status better than chronological age and predicts all-cause mortality.

Lupus nephritis is a potentially fatal autoimmune disease for which the current treatment is ineffective and often toxic. To develop mechanistic hypotheses of disease, we analyzed kidney samples from patients with lupus nephritis and from healthy control subjects using single-cell RNA sequencing. Our analysis revealed 21 subsets of leukocytes active in disease, including multiple populations of myeloid cells, T cells, natural killer cells and B cells that demonstrated both pro-inflammatory responses and inflammation-resolving responses. We found evidence of local activation of B cells correlated with an age-associated B-cell signature and evidence of progressive stages of monocyte differentiation within the kidney. A clear interferon response was observed in most cells. Two chemokine receptors, CXCR4 and CX3CR1 , were broadly expressed, implying a potentially central role in cell trafficking. Gene expression of immune cells in urine and kidney was highly correlated, which would suggest that urine might serve as a surrogate for kidney biopsies. Much about the kidney-resident immune populations is a black box. Hacohen and colleagues use single cell RNA sequencing of kidney, skin and urine from lupus nephritis patients to describe the transcriptional state of the immune cells present in each compartment.

The MYC oncogene drives T- and B- lymphoid malignancies, including Burkitt’s lymphoma (BL) and Acute Lymphoblastic Leukemia (ALL). Here, we demonstrate a systemic reduction in natural killer (NK) cell numbers in SRα-tTA/Tet-O-MYC ON mice bearing MYC-driven T-lymphomas. Residual mNK cells in spleens of MYC ON T-lymphoma-bearing mice exhibit perturbations in the terminal NK effector differentiation pathway. Lymphoma-intrinsic MYC arrests NK maturation by transcriptionally repressing STAT1/2 and secretion of Type I Interferons (IFNs). Treating T-lymphoma-bearing mice with Type I IFN improves survival by rescuing NK cell maturation. Adoptive transfer of mature NK cells is sufficient to delay both T-lymphoma growth and recurrence post MYC inactivation. In MYC-driven BL patients, low expression of both STAT1 and STAT2 correlates significantly with the absence of activated NK cells and predicts unfavorable clinical outcomes. Our studies thus provide a rationale for developing NK cell-based therapies to effectively treat MYC-driven lymphomas in the future. Oncogene addiction is considered as a cancer cell-autonomous phenomenon, but can also influence the host immune system. Here the authors show that MYC-driven lymphomagenesis is associated with a block in the maturation and effector functions of natural killer cells as a mechanism of tumor escape from immunosurveillance.

While many diseases of aging have been linked to the immunological system, immune metrics capable of identifying the most at-risk individuals are lacking. From the blood immunome of 1,001 individuals aged 8-96 years, we developed a deep-learning method based on patterns of systemic age-related inflammation. The resulting inflammatory clock of aging (iAge) tracked with multimorbidity, immunosenescence, frailty and cardiovascular aging, and is also associated with exceptional longevity in centenarians. The strongest contributor to iAge was the chemokine CXCL9, which was involved in cardiac aging, adverse cardiac remodeling and poor vascular function. Furthermore, aging endothelial cells in human and mice show loss of function, cellular senescence and hallmark phenotypes of arterial stiffness, all of which are reversed by silencing CXCL9. In conclusion, we identify a key role of CXCL9 in age-related chronic inflammation and derive a metric for multimorbidity that can be utilized for the early detection of age-related clinical phenotypes.

SARS-CoV-2 infection can have widely diverse clinical outcomes, from asymptomatic infection to death, with many possible clinical symptoms and syndromes. It is thus essential to understand how the virus interacts with the host immune system to bring about these varied outcomes and to inform vaccine development. We now know that both antibody and T cell responses are induced in the majority of infected individuals, and that cross-reactive responses from other coronaviruses also exist in the uninfected population. Innate immune responses are a key focus of research and may influence the course of disease and the character of subsequent adaptive responses. Finally, baseline immune profiles and changes during early acute infection may be key to predicting the course of disease. Understanding all these aspects can help to create better immune monitoring tools for COVID-19, including tools for predicting disease severity or specific sequelae, perhaps even prior to infection.

BACKGROUNDElevated levels of inflammatory cytokines have been associated with poor outcomes among COVID-19 patients. It is unknown, however, how these levels compare with those observed in critically ill patients with acute respiratory distress syndrome (ARDS) or sepsis due to other causes.METHODSWe used a Luminex assay to determine expression of 76 cytokines from plasma of hospitalized COVID-19 patients and banked plasma samples from ARDS and sepsis patients. Our analysis focused on detecting statistical differences in levels of 6 cytokines associated with cytokine storm (IL-1β, IL-1RA, IL-6, IL-8, IL-18, and TNF-α) between patients with moderate COVID-19, severe COVID-19, and ARDS or sepsis.RESULTSFifteen hospitalized COVID-19 patients, 9 of whom were critically ill, were compared with critically ill patients with ARDS (n = 12) or sepsis (n = 16). There were no statistically significant differences in baseline levels of IL-1β, IL-1RA, IL-6, IL-8, IL-18, and TNF-α between patients with COVID-19 and critically ill controls with ARDS or sepsis.CONCLUSIONLevels of inflammatory cytokines were not higher in severe COVID-19 patients than in moderate COVID-19 or critically ill patients with ARDS or sepsis in this small cohort. Broad use of immunosuppressive therapies in ARDS has failed in numerous Phase 3 studies; use of these therapies in unselected patients with COVID-19 may be unwarranted.FUNDINGFunding was received from NHLBI K23 HL125663 (AJR); The Bill and Melinda Gates Foundation OPP1113682 (AJR and CAB); Burroughs Wellcome Fund Investigators in the Pathogenesis of Infectious Diseases #1016687 NIH/NIAID U19AI057229-16; Stanford Maternal Child Health Research Institute; and Chan Zuckerberg Biohub (CAB).

Multiplexed fluorescence or electrochemiluminescence immunoassays of soluble cytokines are commonly performed in the context of human serum or plasma, to look for disease biomarkers and to monitor the immune system in a simple and minimally invasive way. These assays provide challenges due to the complexities of the matrix (serum or plasma) and the presence of many cytokines near the limit of detection of the assay. Here, we compare the readout of matched serum and plasma samples, which are generally correlated. However, a subset of cytokines usually have higher levels in serum, and the non-specific background is significantly increased in serum versus plasma. Presumably as a result of this non-specific background, disease-related decreases in low-abundance cytokines can sometimes be detected in plasma but not in serum. We further show, through spike recovery experiments, that both serum and plasma inhibit the readout of many cytokines, with some variability between donors, but with serum causing greater inhibition than plasma in many cases. Standard diluents from different vendors can partially reverse this inhibition to varying degrees. Dilution of samples can also partly overcome the inhibitory effect of the matrix. We also show that dilution is nonlinear and differentially affects various cytokines. Together, these data argue that (1) plasma is a more sensitive matrix for detecting changes in certain low-abundance cytokines; (2) calculation of concentrations in serum or plasma matrices is inherently inaccurate; and (3) dilution of samples should not be assumed to be linear, i.e., all comparisons need to be made among similarly diluted samples.

Background While immune checkpoint blockade has greatly improved clinical outcomes in diseases such as melanoma, there remains a need for predictive biomarkers to determine who will likely benefit most from which therapy. To date, most biomarkers of response have been identified in the tumors themselves. Biomarkers that could be assessed from peripheral blood would be even more desirable, because of ease of access and reproducibility of sampling. Methods We used mass cytometry (CyTOF) to comprehensively profile peripheral blood of melanoma patients, in order to find predictive biomarkers of response to anti-CTLA-4 or anti-PD-1 therapy. Using a panel of ~ 40 surface and intracellular markers, we performed in-depth phenotypic and functional immune profiling to identify potential predictive biomarker candidates. Results Immune profiling of baseline peripheral blood samples using CyTOF revealed that anti-CTLA-4 and anti-PD-1 therapies have distinct sets of candidate biomarkers. The distribution of CD4 + and CD8 + memory/non-memory cells and other memory subsets was different between responders and non-responders to anti-CTLA-4 therapy. In anti-PD-1 (but not anti-CTLA-4) treated patients, we discovered differences in CD69 and MIP-1β expressing NK cells between responders and non-responders. Finally, multivariate analysis was used to develop a model for the prediction of response. Conclusions Our results indicate that anti-CTLA-4 and anti-PD-1 have distinct predictive biomarker candidates. CD4 + and CD8 + memory T cell subsets play an important role in response to anti-CTLA-4, and are potential biomarker candidates. For anti-PD-1 therapy, NK cell subsets (but not memory T cell subsets) correlated with clinical response to therapy. These functionally active NK cell subsets likely play a critical role in the anti-tumor response triggered by anti-PD-1.

Precision medicine requires highly scalable methods of multiplexed biomarker quantification that can accurately describe patient physiology. Unfortunately, contemporary molecular detection methods are generally limited to a dynamic range of sensitivity spanning just 3–4 orders of magnitude, whereas the actual physiological dynamic range of the human plasma proteome spans more than 10 orders of magnitude. Current methods rely on sample splitting and differential dilution to compensate for this mismatch, but such measures greatly limit the reproducibility and scalability that can be achieved—in particular, the effects of non-linear dilution can greatly confound the analysis of multiplexed assays. We describe here a two-pronged strategy for equalizing the signal generated by each analyte in a multiplexed panel, thereby enabling simultaneous quantification of targets spanning a wide range of concentrations. We apply our ‘EVROS’ strategy to a proximity ligation assay and demonstrate simultaneous quantification of four analytes present at concentrations spanning from low femtomolar to mid-nanomolar levels. In this initial demonstration, we achieve a dynamic range spanning seven orders of magnitude in a single 5 µl sample of undiluted human serum, highlighting the opportunity to achieve sensitive, accurate detection of diverse analytes in a highly multiplexed fashion. The human plasma proteome spans over 10 orders of magnitude, but current quantification methods cover only 3-4 orders. Here, authors propose a tuning approach for proximity-based assays, enabling simultaneous quantification of four analytes across a wide concentration range (low fM to mid-nM).

While many age-associated immune changes have been reported, a comprehensive set of metrics of immune aging is lacking. Here we report data from 243 healthy adults aged 40-97, for whom we measured clinical and functional parameters, serum cytokines, cytokines and gene expression in stimulated and unstimulated PBMC, PBMC phenotypes, and cytokine-stimulated pSTAT signaling in whole blood. Although highly heterogeneous across individuals, many of these assays revealed trends by age, sex, and CMV status, to greater or lesser degrees. Age, then sex and CMV status, showed the greatest impact on the immune system, as measured by the percentage of assay readouts with significant differences. An elastic net regression model could optimally predict age with 14 analytes from different assays. This reinforces the importance of multivariate analysis for defining a healthy immune system. These data provide a reference for others measuring immune parameters in older people.