Edward A. Ganio

Clinical recovery from surgery correlates with single-cell immune signatures

Single-cell mass cytometry revealed immune correlates of patient-associated variability in surgical recovery. Signaling Surgical Recovery The speed and ease of recovery after surgery differ for every patient, and determining the mechanisms that drive recovery could lead to patient-specific recovery protocols. Gaudilliere et al. used mass cytometry to characterize postsurgical immunological insult at a single-cell level and found a surgical immune signature that correlated with clinical recovery across patients. Specifically, cell signaling responses, but not cell frequency, were linked to recovery. Moreover, the correlated signaling responses occurred most notably in CD14+ monocytes, suggesting that these cells may play a predominant role in surgical recovery. The consistency of this signature across patients suggests a tightly regulated immune response to surgical trauma, which, if validated, may form the basis of a diagnostic guideline for personalized postsurgical care. Delayed recovery from surgery causes personal suffering and substantial societal and economic costs. Whether immune mechanisms determine recovery after surgical trauma remains ill-defined. Single-cell mass cytometry was applied to serial whole-blood samples from 32 patients undergoing hip replacement to comprehensively characterize the phenotypic and functional immune response to surgical trauma. The simultaneous analysis of 14,000 phosphorylation events in precisely phenotyped immune cell subsets revealed uniform signaling responses among patients, demarcating a surgical immune signature. When regressed against clinical parameters of surgical recovery, including functional impairment and pain, strong correlations were found with STAT3 (signal transducer and activator of transcription), CREB (adenosine 3′,5′-monophosphate response element–binding protein), and NF-κB (nuclear factor κB) signaling responses in subsets of CD14+ monocytes (R = 0.7 to 0.8, false discovery rate <0.01). These sentinel results demonstrate the capacity of mass cytometry to survey the human immune system in a relevant clinical context. The mechanistically derived immune correlates point to diagnostic signatures, and potential therapeutic targets, that could postoperatively improve patient recovery.

Expression of specific inflammasome gene modules stratifies older individuals into two extreme clinical and immunological states

Low-grade, chronic inflammation has been associated with many diseases of aging, but the mechanisms responsible for producing this inflammation remain unclear. Inflammasomes can drive chronic inflammation in the context of an infectious disease or cellular stress, and they trigger the maturation of interleukin-1β (IL-1β). Here we find that the expression of specific inflammasome gene modules stratifies older individuals into two extremes: those with constitutive expression of IL-1β, nucleotide metabolism dysfunction, elevated oxidative stress, high rates of hypertension and arterial stiffness; and those without constitutive expression of IL-1β, who lack these characteristics. Adenine and N4-acetylcytidine, nucleotide-derived metabolites that are detectable in the blood of the former group, prime and activate the NLRC4 inflammasome, induce the production of IL-1β, activate platelets and neutrophils and elevate blood pressure in mice. In individuals over 85 years of age, the elevated expression of inflammasome gene modules was associated with all-cause mortality. Thus, targeting inflammasome components may ameliorate chronic inflammation and various other age-associated conditions.

Patient-specific Immune States before Surgery Are Strong Correlates of Surgical Recovery.

Background:Recovery after surgery is highly variable. Risk-stratifying patients based on their predicted recovery profile will afford individualized perioperative management strategies. Recently, application of mass cytometry in patients undergoing hip arthroplasty revealed strong immune correlates of surgical recovery in blood samples collected shortly after surgery. However, the ability to interrogate a patient’s immune state before surgery and predict recovery is highly desirable in perioperative medicine. Methods:To evaluate a patient’s presurgical immune state, cell-type–specific intracellular signaling responses to ex vivo ligands (lipopolysaccharide, interleukin [IL]-6, IL-10, and IL-2/granulocyte macrophage colony-stimulating factor) were quantified by mass cytometry in presurgical blood samples. Selected ligands modulate signaling processes perturbed by surgery. Twenty-three cell surface and 11 intracellular markers were used for the phenotypic and functional characterization of major immune cell subsets. Evoked immune responses were regressed against patient-centered outcomes, contributing to protracted recovery including functional impairment, postoperative pain, and fatigue. Results:Evoked signaling responses varied significantly and defined patient-specific presurgical immune states. Eighteen signaling responses correlated significantly with surgical recovery parameters (|R| = 0.37 to 0.70; false discovery rate < 0.01). Signaling responses downstream of the toll-like receptor 4 in cluster of differentiation (CD) 14+ monocytes were particularly strong correlates, accounting for 50% of observed variance. Immune correlates identified in presurgical blood samples mirrored correlates identified in postsurgical blood samples. Conclusions:Convergent findings in pre- and postsurgical analyses provide validation of reported immune correlates and suggest a critical role of the toll-like receptor 4 signaling pathway in monocytes for the clinical recovery process. The comprehensive assessment of patients’ preoperative immune state is promising for predicting important recovery parameters and may lead to clinical tests using standard flow cytometry.

Implementing Mass Cytometry at the Bedside to Study the Immunological Basis of Human Diseases: Distinctive Immune Features in Patients with a History of Term or Preterm Birth

Single‐cell technologies have immense potential to shed light on molecular and biological processes that drive human diseases. Mass cytometry (or Cytometry by Time Of Flight mass spectrometry, CyTOF) has already been employed in clinical studies to comprehensively survey patients’ circulating immune system. As interest in the “bedside” application of mass cytometry is growing, the delineation of relevant methodological issues is called for. This report uses a newly generated dataset to discuss important methodological considerations when mass cytometry is implemented in a clinical study. Specifically, the use of whole blood samples versus peripheral blood mononuclear cells (PBMCs), design of mass‐tagged antibody panels, technical and analytical implications of sample barcoding, and application of traditional and unsupervised approaches to analyze high‐dimensional mass cytometry datasets are discussed. A mass cytometry assay was implemented in a cross‐sectional study of 19 women with a history of term or preterm birth to determine whether immune traits in peripheral blood differentiate the two groups in the absence of pregnancy. Twenty‐seven phenotypic and 11 intracellular markers were simultaneously analyzed in whole blood samples stimulated with lipopolysaccharide (LPS at 0, 0.1, 1, 10, and 100 ng mL−1) to examine dose‐dependent signaling responses within the toll‐like receptor 4 (TLR4) pathway. Complementary analyses, grounded in traditional or unsupervised gating strategies of immune cell subsets, indicated that the prpS6 and pMAPKAPK2 responses in classical monocytes are accentuated in women with a history of preterm birth (FDR<1%). The results suggest that women predisposed to preterm birth may be prone to mount an exacerbated TLR4 response during the course of pregnancy. This important hypothesis‐generating finding points to the power of single‐cell mass cytometry to detect biologically important differences in a relatively small patient cohort.

An immune clock of human pregnancy

High-dimensional analysis reveals the chronology of immunological adaptations during the course of human pregnancies. Following the hand of the immunological clock Immune function is altered during pregnancy to protect the fetus from an immunological attack without disrupting protection against infection. Now, Aghaeepour et al. use mass cytometry to examine the precise timing of these pregnancy-induced changes in immune function and regulation. They developed an algorithm that captures the immunological timeline during pregnancy that both validates previous findings and sheds new light on immune cell interaction during gestation. By defining this immunological chronology during normal term pregnancy, they can now begin to determine which alterations associate with pregnancy-related pathologies. The maintenance of pregnancy relies on finely tuned immune adaptations. We demonstrate that these adaptations are precisely timed, reflecting an immune clock of pregnancy in women delivering at term. Using mass cytometry, the abundance and functional responses of all major immune cell subsets were quantified in serial blood samples collected throughout pregnancy. Cell signaling–based Elastic Net, a regularized regression method adapted from the elastic net algorithm, was developed to infer and prospectively validate a predictive model of interrelated immune events that accurately captures the chronology of pregnancy. Model components highlighted existing knowledge and revealed previously unreported biology, including a critical role for the interleukin-2–dependent STAT5ab signaling pathway in modulating T cell function during pregnancy. These findings unravel the precise timing of immunological events occurring during a term pregnancy and provide the analytical framework to identify immunological deviations implicated in pregnancy-related pathologies.

Mapping the Fetomaternal Peripheral Immune System at Term Pregnancy.

Preterm labor and infections are the leading causes of neonatal deaths worldwide. During pregnancy, immunological cross talk between the mother and her fetus is critical for the maintenance of pregnancy and the delivery of an immunocompetent neonate. A precise understanding of healthy fetomaternal immunity is the important first step to identifying dysregulated immune mechanisms driving adverse maternal or neonatal outcomes. This study combined single-cell mass cytometry of paired peripheral and umbilical cord blood samples from mothers and their neonates with a graphical approach developed for the visualization of high-dimensional data to provide a high-resolution reference map of the cellular composition and functional organization of the healthy fetal and maternal immune systems at birth. The approach enabled mapping of known phenotypical and functional characteristics of fetal immunity (including the functional hyperresponsiveness of CD4+ and CD8+ T cells and the global blunting of innate immune responses). It also allowed discovery of new properties that distinguish the fetal and maternal immune systems. For example, examination of paired samples revealed differences in endogenous signaling tone that are unique to a mother and her offspring, including increased ERK1/2, MAPK-activated protein kinase 2, rpS6, and CREB phosphorylation in fetal Tbet+CD4+ T cells, CD8+ T cells, B cells, and CD56loCD16+ NK cells and decreased ERK1/2, MAPK-activated protein kinase 2, and STAT1 phosphorylation in fetal intermediate and nonclassical monocytes. This highly interactive functional map of healthy fetomaternal immunity builds the core reference for a growing data repository that will allow inferring deviations from normal associated with adverse maternal and neonatal outcomes.

Multicenter Systems Analysis of Human Blood Reveals Immature Neutrophils in Males and During Pregnancy.

Despite clear differences in immune system responses and in the prevalence of autoimmune diseases between males and females, there is little understanding of the processes involved. In this study, we identified a gene signature of immature-like neutrophils, characterized by the overexpression of genes encoding for several granule-containing proteins, which was found at higher levels (up to 3-fold) in young (20–30 y old) but not older (60 to >89 y old) males compared with females. Functional and phenotypic characterization of peripheral blood neutrophils revealed more mature and responsive neutrophils in young females, which also exhibited an elevated capacity in neutrophil extracellular trap formation at baseline and upon microbial or sterile autoimmune stimuli. The expression levels of the immature-like neutrophil signature increased linearly with pregnancy, an immune state of increased susceptibility to certain infections. Using mass cytometry, we also find increased frequencies of immature forms of neutrophils in the blood of women during late pregnancy. Thus, our findings show novel sex differences in innate immunity and identify a common neutrophil signature in males and in pregnant women.

Multiomics modeling of the immunome, transcriptome, microbiome, proteome and metabolome adaptations during human pregnancy

Motivation: Multiple biological clocks govern a healthy pregnancy. These biological mechanisms produce immunologic, metabolomic, proteomic, genomic and microbiomic adaptations during the course of pregnancy. Modeling the chronology of these adaptations during full‐term pregnancy provides the frameworks for future studies examining deviations implicated in pregnancy‐related pathologies including preterm birth and preeclampsia. Results: We performed a multiomics analysis of 51 samples from 17 pregnant women, delivering at term. The datasets included measurements from the immunome, transcriptome, microbiome, proteome and metabolome of samples obtained simultaneously from the same patients. Multivariate predictive modeling using the Elastic Net (EN) algorithm was used to measure the ability of each dataset to predict gestational age. Using stacked generalization, these datasets were combined into a single model. This model not only significantly increased predictive power by combining all datasets, but also revealed novel interactions between different biological modalities. Future work includes expansion of the cohort to preterm‐enriched populations and in vivo analysis of immune‐modulating interventions based on the mechanisms identified. Availability and implementation: Datasets and scripts for reproduction of results are available through: https://nalab.stanford.edu/multiomics‐pregnancy/. Supplementary information: Supplementary data are available at Bioinformatics online.

Deep Immune Profiling of an Arginine-Enriched Nutritional Intervention in Patients Undergoing Surgery

Application of high-content immune profiling technologies has enormous potential to advance medicine. Whether these technologies reveal pertinent biology when implemented in interventional clinical trials is an important question. The beneficial effects of preoperative arginine-enriched dietary supplements (AES) are highly context specific, as they reduce infection rates in elective surgery, but possibly increase morbidity in critically ill patients. This study combined single-cell mass cytometry with the multiplex analysis of relevant plasma cytokines to comprehensively profile the immune-modifying effects of this much-debated intervention in patients undergoing surgery. An elastic net algorithm applied to the high-dimensional mass cytometry dataset identified a cross-validated model consisting of 20 interrelated immune features that separated patients assigned to AES from controls. The model revealed wide-ranging effects of AES on innate and adaptive immune compartments. Notably, AES increased STAT1 and STAT3 signaling responses in lymphoid cell subsets after surgery, consistent with enhanced adaptive mechanisms that may protect against postsurgical infection. Unexpectedly, AES also increased ERK and P38 MAPK signaling responses in monocytic myeloid-derived suppressor cells, which was paired with their pronounced expansion. These results provide novel mechanistic arguments as to why AES may exert context-specific beneficial or adverse effects in patients with critical illness. This study lays out an analytical framework to distill high-dimensional datasets gathered in an interventional clinical trial into a fairly simple model that converges with known biology and provides insight into novel and clinically relevant cellular mechanisms.