Jakob Franz Einhaus

All Publications

• Immune Modulation by Personalized vs Standard Prehabilitation Before Major Surgery: A Randomized Clinical Trial. JAMA surgery Cambriel, A., Tsai, A., Choisy, B., Sabayev, M., Hedou, J., Shelton, E., Singh, K., Amar, J., Badea, V., Bruckman, S., Ganio, E., Einhaus, J., Feyaerts, D., Stelzer, I., Sato, M., Langeron, O., Bonham, T. A., Gaudillière, D., Shelton, A., Kin, C., Gaudillière, B., Verdonk, F. 2025

  Abstract

  Prehabilitation programs are increasingly recognized for their potential to improve surgical outcomes. However, their efficacy remains debated, largely due to a lack of pathophysiologically driven implementation and limited personalization.To determine the impact of personalized vs standard prehabilitation on preoperative physical, cognitive, and immune function and postoperative outcomes.In this prospective, single-blinded, randomized interventional trial conducted from June 2020 to September 2022 in a single academic medical center, 58 patients undergoing major elective surgery were randomized to standard (n = 30) or personalized prehabilitation (n = 28) using block randomization. Those with contraindication to exercise, an American Society of Anesthesiologists score 4 or higher, in palliative care, less than 14 days between screening and surgery were excluded. Data were analyzed from April 2023 to May 2025.The personalized group received 2 weekly one-on-one remote coaching sessions tailored to individual progress in 4 domains (physical activity, nutrition, cognitive training, and mindfulness), whereas the standard group followed a paper-based program, including the same domains, without individualized support.Primary clinical outcomes included cognitive assessments and physical performance measures, including the wall squat test, timed-up-and-go test, and 6-minute walk test (6MWT). The primary immunological outcomes included major innate and adaptive immune cell frequencies and intracellular signaling responses measured using a 47-plex mass cytometry immunoassay.Of 58 patients (median [IQR] age, 57 [45-67] years; 31 [57%] female) enrolled, 54 completed the study (n = 27 per group). The personalized group exhibited significant improvements in physical measures (eg, median [IQR] 6MWT: 496 [340-619] minutes before prehab versus 546 [350-728] minutes after; P = .03) and fewer moderate-to-severe postoperative complications (4 vs 11 Clavien-Dindo grade >1; P = .04). Multivariable modeling identified profound and cell-type specific immune alterations postprehabilitation compared to baseline (area under the receiver operating characteristic curve [AUROC], 0.88; 0.79-0.97; P < .001; leave-one-out cross-validation), including dampened phosphorylated protein kinase R-like endoplasmic reticulum kinase 1/2 signaling in classical monocytes and myeloid-derived suppressor cells after interleukin 2, 4, and 6 stimulation, and reduced phosphorylated cyclic adenosine monophosphate response-element binding protein signaling in Th1 cells. In contrast, the standard group showed only moderate clinical improvements and no immune changes (AUROC = 0.63; 95% CI, 0.48-0.78; P = .12).In this study, personalized prehabilitation significantly altered the immunome before surgery, dampening inflammatory signaling responses previously implicated in the pathophysiology of key surgical outcomes, including surgical site infections and postoperative neurocognitive decline. These changes were accompanied by improved physical and cognitive function before surgery and decreased postoperative complications. These findings support the use of personalized prehabilitation and provide an avenue for biologically driven monitoring of prehabilitation efficacy, and individual tailoring of programs to optimize surgical readiness and recovery.ClinicalTrials.gov Identifier: NCT04498208.

  View details for DOI 10.1001/jamasurg.2025.4917

  View details for PubMedID 41222945

• MULTIOMIC APPROACH TO STUDY THE IMMUNOLOGIC PROFILE PRECEDING PRETERM BIRTH Urbschat, C., Stelzer, I., Gillard, J., Thiele, K., Feyearts, D., Pagenkemper, M., Tallarek, A., Hollwitz, B., Sato, M., Ganio, E., Diop, M., Ando, K., Einhaus, J., Aghaeepour, N., Stevenson, D., Gagliani, N., Wostemeier, A., Bonn, S., Diemert, A., Gaudilliere, B., Arck, P. W B SAUNDERS CO LTD. 2025

  View details for Web of Science ID 001632327700087

• Single-cell-level digital twins for preterm birth prevention strategies. bioRxiv : the preprint server for biology Einhaus, J., Neidlinger, P., Fondeur, O., Sato, M., Anronikov, A., Miyazaki, K., Amar, J. N., Ando, K., Badea, V., Gaudilliere, D. K., Sabayev, M., Feyaerts, D., Diop, M., Tsai, A. S., Cambriel, A., Ganio, E. A., Lagarde, R., O'Kelly, E., Stelzer, I. A., Hedou, J., Wong, R. J., Blumenfeld, Y. J., Lyell, D. J., Shaw, G. M., Oskotsky, T. T., Sirota, M., Giudice, L., Stevenson, D. K., Aghaeepour, N., Gaudilliere, B. 2025

  Abstract

  Digital twin models can accelerate therapeutic development by enabling low-risk testing of candidate interventions. In preterm labor (PTL), a major pregnancy complication where clinical trials face unique ethical and financial barriers, digital twins are especially valuable for evaluating new therapies targeting immune dysfunctions driving PTL. Yet, current models lack single-cell resolution, limiting detection of cell-type-specific mechanisms, off-target effects, and the design of personalized interventions. We present Simulated Immunome Modeling of Clinical Outcomes (SIMCO), a single-cell-level digital twin framework that models immunomodulatory treatment effects on the timing of labor using immunome-wide, single-cell simulations. SIMCO's digital twins are trained and validated on a newly generated mass cytometry atlas of the pregnant immunome exposed to nine candidate drugs preselected for PTL prevention. Applying SIMCO to an independent cohort of pregnant individuals, we simulate treatment effects on gestational length, screening for candidate drugs that delay labor timing and providing system-level mechanistic insight for each drug candidate. Tetrahydrofolate, maprotiline, and the combination of aspirin and lansoprazole emerged as top candidates for PTL prevention, delaying labor onset primarily through enhanced mTOR signaling in innate immune cells and attenuated JAK/STAT signaling in naïve CD4+ T cells. The codebase is available at https://github.com/ofondeur/SIMCO/.

  View details for DOI 10.1101/2025.09.29.679252

  View details for PubMedID 41256687

  View details for PubMedCentralID PMC12621756

• A Transcriptomics-Based Computational Drug Repositioning Pipeline Identifies Simvastatin And Primaquine As Novel Therapeutics For Endometriosis Pain. bioRxiv : the preprint server for biology Oskotsky, T. T., Tang, X., Arthurs, E., Govil, A., Abbasi, F., Bhoja, A., Bunis, D. J., Lau, A., Einhaus, J., Diop, M., Irwin, J. C., Gaudilliere, B., Stevenson, D. K., Giudice, L. C., McAllister, S. L., Sirota, M. 2025

  Abstract

  Introduction and Methods: Endometriosis has limited treatment options, prompting the search for novel therapeutics. We previously used a transcriptomics-based computational drug repositioning pipeline to analyze public bulk transcriptomic data and identified several drug candidates. Fenoprofen, our top in silico candidate, was validated in a rat model. Building on this, we now evaluate two additional candidates, simvastatin (a cholesterol-lowering drug) and primaquine (an antimalarial), based on strong gene expression reversal scores and favorable safety profiles. Using a validated rat model of endometriosis and pain, we conducted behavioral testing, bulk RNA sequencing, and differential expression analysis to assess their therapeutic potential.Results: Of 299 drugs identified computationally, simvastatin and primaquine ranked highly for reversing gene expression signatures associated with endometriosis. In vivo validation using a rat model of endometriosis demonstrated that both drugs significantly reduced vaginal hyperalgesia, a surrogate marker of endometriosis-associated pain. RNA-seq of uteri and lesions confirmed reversal of disease-associated gene expression signatures following treatment.Conclusion: Simvastatin and primaquine attenuated pain behaviors and reversed endometriosis-related gene expression changes in an animal model. These findings highlight their potential as repurposed therapeutics for endometriosis-related pain and support the effectiveness of computational drug repositioning strategies in identifying new treatment strategies.

  View details for DOI 10.1101/2025.05.28.656743

  View details for PubMedID 40502156

• Single-Cell Epigenetic Dynamics and Determinants of Surgical Outcomes Cambriel, A., Sabayev, M., Ganio, E., Angst, M., Bonham, T., Anronikov, A., Tsai, A., Diop, M., Einhaus, J., Feyaerts, D., Goodman, S., Drover, D., Verdonk, F., Gaudilliere, B. LIPPINCOTT WILLIAMS & WILKINS. 2025: 496

  View details for Web of Science ID 001551889100194

• Immune Modulation by Personalized vs Standard Prehabilitation Program Before Major Surgery Cambriel, A., Tsai, A., Sabayev, M., Choisy, B., Hedou, J., Shelton, E., Singh, K., Amar, J., Badea, V., Bruckman, S., Ganio, E., Einhaus, J., Feyaerts, D., Stelzer, I., Bonham, T., Sato, M., Gaudilliere, D., Shelton, A., Gaudilliere, B., Kin, C., Verdonk, F. LIPPINCOTT WILLIAMS & WILKINS. 2025: 959

  View details for Web of Science ID 001551889100367

• Immune Profile of Palmar Cooling on Delayed Onset of Muscle Soreness Tsai, A., Vinh Cao, Anronikov, S., Miyazaki, K., Liu, C., Darracott, C., Einhaus, J., Gaudilliere, D., Gaudilliere, B., Heller, H. LIPPINCOTT WILLIAMS & WILKINS. 2025: 700-701

  View details for Web of Science ID 001551889100272

• Immune Profiling of Post-COVID Condition in Adults Living in Mexico: A Longitudinal Analysis of Immune and Proteomic Markers Anronikov, S., Meikle, C., Saavedra, S., Gallegos, A., Islas, L., Nunez, I., Chen, H., Feyaerts, D., Gillard, J., Tsai, A., Bonham, T., Genic, E., Nolan, G., Meyerowitz, J., Stelzer, I., Ando, K., Han, X., Gaudilliere, D., Einhaus, J., Sato, M., Flores, J., Valdes-Ferrer, S., McIlwain, D., Gaudilliere, B. LIPPINCOTT WILLIAMS & WILKINS. 2025: 230-231

  View details for Web of Science ID 001551889100090

• The single-cell immune profile throughout gestation and its potential value for identifying women at risk for spontaneous preterm birth EUROPEAN JOURNAL OF OBSTETRICS & GYNECOLOGY AND REPRODUCTIVE BIOLOGY-X Feyaerts, D., Diop, M., Galaz, J., Einhaus, J. F., Arck, P. C., Diemert, A., Winn, V. D., Parast, M., Gyamfi-Bannerman, C., Prins, J. R., Gomez-Lopez, N., Stelzer, I. A. 2025; 25

  View details for DOI 10.1016/j.eurox.2025.100371

  View details for Web of Science ID 001429255200001

• High-Dimensional Imaging Reveals Eutopic Endometrial Cell Frequency and Functional Shifts in Endometriosis Diop, M. G., Feyaerts, D., Einhaus, J., Irwin, J., Bonham, A., Stelzer, I., Stevenson, D., Sirota, M., Blish, C., Giudice, L., Gaudilliere, B. SPRINGER HEIDELBERG. 2025: 48A

  View details for Web of Science ID 001609923000003

• An immune signature of postoperative cognitive decline: A prospective cohort study. International journal of surgery (London, England) Verdonk, F., Cambriel, A., Hedou, J., Ganio, E., Bellan, G., Gaudilliere, D., Einhaus, J., Sabayev, M., Stelzer, I. A., Feyaerts, D., Bonham, A. T., Ando, K., Choisy, B., Drover, D., Heifets, B., Chretien, F., Aghaeepour, N., Angst, M. S., Molliex, S., Sharshar, T., Gaillard, R., Gaudilliere, B. 2024

  Abstract

  Postoperative cognitive decline (POCD) is the predominant complication affecting patients over 60 years old following major surgery, yet its prediction and prevention remain challenging. Understanding the biological processes underlying the pathogenesis of POCD is essential for identifying mechanistic biomarkers to advance diagnostics and therapeutics. This study aimed to provide a comprehensive analysis of immune cell trajectories differentiating patients with and without POCD and to derive a predictive score enabling the identification of high-risk patients during the preoperative period.Twenty-six patients aged 60 years old and older undergoing elective major orthopedic surgery were enrolled in a prospective longitudinal study, and the occurrence of POCD was assessed seven days after surgery. Serial samples collected before surgery, and one, seven, and 90 days after surgery were analyzed using a combined single-cell mass cytometry and plasma proteomic approach. Unsupervised clustering of the high-dimensional mass cytometry data was employed to characterize time-dependent trajectories of all major innate and adaptive immune cell frequencies and signaling responses. Sparse machine learning coupled with data-driven feature selection was applied to the pre-surgery immunological dataset to classify patients at risk for POCD.The analysis identified cell-type and signaling-specific immune trajectories differentiating patients with and without POCD. The most prominent trajectory features revealed early exacerbation of JAK/STAT and dampening of inhibitory κB and nuclear factor-κB immune signaling responses in patients with POCD. Further analyses integrating immunological and clinical data collected before surgery identified a preoperative predictive model comprising one plasma protein and ten immune cell features that classified patients at risk for POCD with excellent accuracy (AUC=0.80, P=2.21e-02 U-test).Immune system-wide monitoring of patients over 60 years old undergoing surgery unveiled a peripheral immune signature of POCD. A predictive model built on immunological data collected before surgery demonstrated greater accuracy in predicting POCD compared to known clinical preoperative risk factors, offering a concise list of biomarker candidates to personalize perioperative management.

  View details for DOI 10.1097/JS9.0000000000002118

  View details for PubMedID 39411891

• Discovery of sparse, reliable omic biomarkers with Stabl. Nature biotechnology Hédou, J., Marić, I., Bellan, G., Einhaus, J., Gaudillière, D. K., Ladant, F. X., Verdonk, F., Stelzer, I. A., Feyaerts, D., Tsai, A. S., Ganio, E. A., Sabayev, M., Gillard, J., Amar, J., Cambriel, A., Oskotsky, T. T., Roldan, A., Golob, J. L., Sirota, M., Bonham, T. A., Sato, M., Diop, M., Durand, X., Angst, M. S., Stevenson, D. K., Aghaeepour, N., Montanari, A., Gaudillière, B. 2024

  Abstract

  Adoption of high-content omic technologies in clinical studies, coupled with computational methods, has yielded an abundance of candidate biomarkers. However, translating such findings into bona fide clinical biomarkers remains challenging. To facilitate this process, we introduce Stabl, a general machine learning method that identifies a sparse, reliable set of biomarkers by integrating noise injection and a data-driven signal-to-noise threshold into multivariable predictive modeling. Evaluation of Stabl on synthetic datasets and five independent clinical studies demonstrates improved biomarker sparsity and reliability compared to commonly used sparsity-promoting regularization methods while maintaining predictive performance; it distills datasets containing 1,400-35,000 features down to 4-34 candidate biomarkers. Stabl extends to multi-omic integration tasks, enabling biological interpretation of complex predictive models, as it hones in on a shortlist of proteomic, metabolomic and cytometric events predicting labor onset, microbial biomarkers of pre-term birth and a pre-operative immune signature of post-surgical infections. Stabl is available at https://github.com/gregbellan/Stabl .

  View details for DOI 10.1038/s41587-023-02033-x

  View details for PubMedID 38168992

  View details for PubMedCentralID 7003173

• Stabl: sparse and reliable biomarker discovery in predictive modeling of high-dimensional omic data. Research square Hédou, J., Marić, I., Bellan, G., Einhaus, J., Gaudillière, D. K., Ladant, F. X., Verdonk, F., Stelzer, I. A., Feyaerts, D., Tsai, A. S., Ganio, E. A., Sabayev, M., Gillard, J., Bonham, T. A., Sato, M., Diop, M., Angst, M. S., Stevenson, D., Aghaeepour, N., Montanari, A., Gaudillière, B. 2023

  Abstract

  High-content omic technologies coupled with sparsity-promoting regularization methods (SRM) have transformed the biomarker discovery process. However, the translation of computational results into a clinical use-case scenario remains challenging. A rate-limiting step is the rigorous selection of reliable biomarker candidates among a host of biological features included in multivariate models. We propose Stabl, a machine learning framework that unifies the biomarker discovery process with multivariate predictive modeling of clinical outcomes by selecting a sparse and reliable set of biomarkers. Evaluation of Stabl on synthetic datasets and four independent clinical studies demonstrates improved biomarker sparsity and reliability compared to commonly used SRMs at similar predictive performance. Stabl readily extends to double- and triple-omics integration tasks and identifies a sparser and more reliable set of biomarkers than those selected by state-of-the-art early- and late-fusion SRMs, thereby facilitating the biological interpretation and clinical translation of complex multi-omic predictive models. The complete package for Stabl is available online at https://github.com/gregbellan/Stabl.

  View details for DOI 10.21203/rs.3.rs-2609859/v1

  View details for PubMedID 36909508

  View details for PubMedCentralID PMC10002850

• Towards multiomic analysis of oral mucosal pathologies. Seminars in immunopathology Einhaus, J., Han, X., Feyaerts, D., Sunwoo, J., Gaudilliere, B., Ahmad, S. H., Aghaeepour, N., Bruckman, K., Ojcius, D., Schurch, C. M., Gaudilliere, D. K. 2023

  Abstract

  Oral mucosal pathologies comprise an array of diseases with worldwide prevalence and medical relevance. Affecting a confined space with crucial physiological and social functions, oral pathologies can be mutilating and drastically reduce quality of life. Despite their relevance, treatment for these diseases is often far from curative and remains vastly understudied. While multiple factors are involved in the pathogenesis of oral mucosal pathologies, the host's immune system plays a major role in the development, maintenance, and resolution of these diseases. Consequently, a precise understanding of immunological mechanisms implicated in oral mucosal pathologies is critical (1) to identify accurate, mechanistic biomarkers of clinical outcomes; (2) to develop targeted immunotherapeutic strategies; and (3) to individualize prevention and treatment approaches. Here, we review key elements of the immune system's role in oral mucosal pathologies that hold promise to overcome limitations in current diagnostic and therapeutic approaches. We emphasize recent and ongoing multiomic and single-cell approaches that enable an integrative view of these pathophysiological processes and thereby provide unifying and clinically relevant biological signatures.

  View details for DOI 10.1007/s00281-022-00982-0

  View details for PubMedID 36790488

• Neuroimaging is the new "spatial omic": multi-omic approaches to neuro-inflammation and immuno-thrombosis in acute ischemic stroke. Seminars in immunopathology Maier, B., Tsai, A. S., Einhaus, J. F., Desilles, J., Ho-Tin-Noe, B., Gory, B., Sirota, M., Leigh, R., Lemmens, R., Albers, G., Olivot, J., Mazighi, M., Gaudilliere, B. 2023

  Abstract

  Ischemic stroke (IS) is the leading cause of acquired disability and the second leading cause of dementia and mortality. Current treatments for IS are primarily focused on revascularization of the occluded artery. However, only 10% of patients are eligible for revascularization and 50% of revascularized patients remain disabled at 3 months. Accumulating evidence highlight the prognostic significance of the neuro- and thrombo-inflammatory response after IS. However, several randomized trials of promising immunosuppressive or immunomodulatory drugs failed to show positive results. Insufficient understanding of inter-patient variability in the cellular, functional, and spatial organization of the inflammatory response to IS likely contributed to the failure to translate preclinical findings into successful clinical trials. The inflammatory response to IS involves complex interactions between neuronal, glial, and immune cell subsets across multiple immunological compartments, including the blood-brain barrier, the meningeal lymphatic vessels, the choroid plexus, and the skull bone marrow. Here, we review the neuro- and thrombo-inflammatory responses to IS. We discuss how clinical imaging and single-cell omic technologies have refined our understanding of the spatial organization of pathobiological processes driving clinical outcomes in patients with an IS. We also introduce recent developments in machine learning statistical methods for the integration of multi-omic data (biological and radiological) to identify patient-specific inflammatory states predictive of IS clinical outcomes.

  View details for DOI 10.1007/s00281-023-00984-6

  View details for PubMedID 36786929

• High-multiplex tissue imaging in routine pathology-are we there yet? Virchows Archiv : an international journal of pathology Einhaus, J., Rochwarger, A., Mattern, S., Gaudillière, B., Schürch, C. M. 2023

  Abstract

  High-multiplex tissue imaging (HMTI) approaches comprise several novel immunohistological methods that enable in-depth, spatial single-cell analysis. Over recent years, studies in tumor biology, infectious diseases, and autoimmune conditions have demonstrated the information gain accessible when mapping complex tissues with HMTI. Tumor biology has been a focus of innovative multiparametric approaches, as the tumor microenvironment (TME) contains great informative value for accurate diagnosis and targeted therapeutic approaches: unraveling the cellular composition and structural organization of the TME using sophisticated computational tools for spatial analysis has produced histopathologic biomarkers for outcomes in breast cancer, predictors of positive immunotherapy response in melanoma, and histological subgroups of colorectal carcinoma. Integration of HMTI technologies into existing clinical workflows such as molecular tumor boards will contribute to improve patient outcomes through personalized treatments tailored to the specific heterogeneous pathological fingerprint of cancer, autoimmunity, or infection. Here, we review the advantages and limitations of existing HMTI technologies and outline how spatial single-cell data can improve our understanding of pathological disease mechanisms and determinants of treatment success. We provide an overview of the analytic processing and interpretation and discuss how HMTI can improve future routine clinical diagnostic and therapeutic processes.

  View details for DOI 10.1007/s00428-023-03509-6

  View details for PubMedID 36757500

• Integrated single-cell and plasma proteomic modeling to predict surgical site complications, a prospective cohort study Tsai, A. S., Hedou, J., Einhaus, J., Rumer, K., Verdonk, F., Stanley, N., Choisy, B., Ganio, E. A., Bonham, A., Jacobsen, D., Warrington, B., Gao, X., Tingle, M., McAllister, T., Fallahzadeh, R., Feyaerts, D., Stelzer, I., Gaudilliere, D., Ando, K., Shelton, A., Morris, A., Kebebew, E., Aghaeepour, N., Kin, C., Angst, M. S., Gaudilliere, B. LIPPINCOTT WILLIAMS & WILKINS. 2022: 1204-1205

  View details for Web of Science ID 000840283001162

• iNKT cells can effectively inhibit IL-6 production by B cells in systemic sclerosis. Cytotherapy Einhaus, J., Asteriti, E., Pecher, A., Keppeler, H., Klein, R., Schneidawind, C., Henes, J., Schneidawind, D. 2022; 24 (5): 482-488

  Abstract

  OBJECTIVE: Systemic sclerosis (SSc) is a connective tissue disease with poorly understood pathogenesis and limited treatment options. Patient mortality is rooted predominantly in the development of pulmonary and cardiac complications. The overactivated immune system is assumed to sustain the inflammatory signature of this autoimmune disease. Here, we investigate the potential of immunoregulatory invariant natural killer T (iNKT) cells to inhibit proinflammatory B cell responses in an in vitro model of inflammation.METHODS: B cells from healthy volunteers (n = 17) and patients with SSc (n=15) were used for functional testing upon lipopolysaccharide (LPS) stimulation in a co-culture system with third-party iNKT cells. Cytokine production was measured with antibody-based immunoassays (ELISA) and intracellular cytokine staining.RESULTS: iNKT cells strongly inhibited the production of proinflammatory interleukin-6 by B cells upon stimulation with LPS in both healthy volunteers and patients with SSc. In a Transwell assay, cell contact between B cells and iNKT cells proved necessary for this inhibitory effect. Similarly, blocking of CD1d on the surface of B cells abolished the immunoregulatory effect of iNKT cells on B cells. B cell subsets with higher expression of CD1d, namely unswitched memory B cells, were more susceptible to iNKT cell inhibition.CONCLUSION: Our in vitro data underline the potential of iNKT cells in the control of SSc and provide a rationale for the use of novel iNKT cell-based therapeutic strategies in the context of autoimmune diseases.

  View details for DOI 10.1016/j.jcyt.2021.12.002

  View details for PubMedID 35181242

• Integrated Single-Cell and Plasma Proteomic Modeling to Predict Surgical Site Complications: A Prospective Cohort Study. Annals of surgery Rumer, K. K., Hedou, J., Tsai, A., Einhaus, J., Verdonk, F., Stanley, N., Choisy, B., Ganio, E., Bonham, A., Jacobsen, D., Warrington, B., Gao, X., Tingle, M., McAllister, T. N., Fallahzadeh, R., Feyaerts, D., Stelzer, I., Gaudilliere, D., Ando, K., Shelton, A., Morris, A., Kebebew, E., Aghaeepour, N., Kin, C., Angst, M. S., Gaudilliere, B. 1800

  Abstract

  OBJECTIVE: The aim of this study was to determine whether single-cell and plasma proteomic elements of the host's immune response to surgery accurately identify patients who develop a surgical site complication (SSC) after major abdominal surgery.SUMMARY BACKGROUND DATA: SSCs may occur in up to 25% of patients undergoing bowel resection, resulting in significant morbidity and economic burden. However, the accurate prediction of SSCs remains clinically challenging. Leveraging high-content proteomic technologies to comprehensively profile patients' immune response to surgery is a promising approach to identify predictive biological factors of SSCs.METHODS: Forty-one patients undergoing non-cancer bowel resection were prospectively enrolled. Blood samples collected before surgery and on postoperative day one (POD1) were analyzed using a combination of single-cell mass cytometry and plasma proteomics. The primary outcome was the occurrence of an SSC, including surgical site infection, anastomotic leak, or wound dehiscence within 30 days of surgery.RESULTS: A multiomic model integrating the single-cell and plasma proteomic data collected on POD1 accurately differentiated patients with (n = 11) and without (n = 30) an SSC [area under the curve (AUC) = 0.86]. Model features included coregulated proinflammatory (eg, IL-6- and MyD88- signaling responses in myeloid cells) and immunosuppressive (eg, JAK/STAT signaling responses in M-MDSCs and Tregs) events preceding an SSC. Importantly, analysis of the immunological data obtained before surgery also yielded a model accurately predicting SSCs (AUC = 0.82).CONCLUSIONS: The multiomic analysis of patients' immune response after surgery and immune state before surgery revealed systemic immune signatures preceding the development of SSCs. Our results suggest that integrating immunological data in perioperative risk assessment paradigms is a plausible strategy to guide individualized clinical care.

  View details for DOI 10.1097/SLA.0000000000005348

  View details for PubMedID 34954754

• Measuring the human immune response to surgery: multiomics for the prediction of postoperative outcomes. Current opinion in critical care Verdonk, F., Einhaus, J., Tsai, A. S., Hedou, J., Choisy, B., Gaudilliere, D., Kin, C., Aghaeepour, N., Angst, M. S., Gaudilliere, B. 2021

  Abstract

  Postoperative complications including infections, cognitive impairment, and protracted recovery occur in one-third of the 300 million surgeries performed annually worldwide. Complications cause personal suffering along with a significant economic burden on our healthcare system. However, the accurate prediction of postoperative complications and patient-targeted interventions for their prevention remain as major clinical challenges.Although multifactorial in origin, the dysregulation of immunological mechanisms that occur in response to surgical trauma is a key determinant of postoperative complications. Prior research, primarily focusing on inflammatory plasma markers, has provided important clues regarding their pathogenesis. However, the recent advent of high-content, single-cell transcriptomic, and proteomic technologies has considerably improved our ability to characterize the immune response to surgery, thereby providing new means to understand the immunological basis of postoperative complications and to identify prognostic biological signatures.The comprehensive and single-cell characterization of the human immune response to surgery has significantly advanced our ability to predict the risk of postoperative complications. Multiomic modeling of patients' immune states holds promise for the discovery of preoperative predictive biomarkers, ultimately providing patients and surgeons with actionable information to improve surgical outcomes. Although recent studies have generated a wealth of knowledge, laying the foundation for a single-cell atlas of the human immune response to surgery, larger-scale multiomic studies are required to derive robust, scalable, and sufficiently powerful models to accurately predict the risk of postoperative complications in individual patients.

  View details for DOI 10.1097/MCC.0000000000000883

  View details for PubMedID 34545029

• VoPo leverages cellular heterogeneity for predictive modeling of single-cell data. Nature communications Stanley, N. n., Stelzer, I. A., Tsai, A. S., Fallahzadeh, R. n., Ganio, E. n., Becker, M. n., Phongpreecha, T. n., Nassar, H. n., Ghaemi, S. n., Maric, I. n., Culos, A. n., Chang, A. L., Xenochristou, M. n., Han, X. n., Espinosa, C. n., Rumer, K. n., Peterson, L. n., Verdonk, F. n., Gaudilliere, D. n., Tsai, E. n., Feyaerts, D. n., Einhaus, J. n., Ando, K. n., Wong, R. J., Obermoser, G. n., Shaw, G. M., Stevenson, D. K., Angst, M. S., Gaudilliere, B. n., Aghaeepour, N. n. 2020; 11 (1): 3738

  Abstract

  High-throughput single-cell analysis technologies produce an abundance of data that is critical for profiling the heterogeneity of cellular systems. We introduce VoPo (https://github.com/stanleyn/VoPo), a machine learning algorithm for predictive modeling and comprehensive visualization of the heterogeneity captured in large single-cell datasets. In three mass cytometry datasets, with the largest measuring hundreds of millions of cells over hundreds of samples, VoPo defines phenotypically and functionally homogeneous cell populations. VoPo further outperforms state-of-the-art machine learning algorithms in classification tasks, and identified immune-correlates of clinically-relevant parameters.

  View details for DOI 10.1038/s41467-020-17569-8

  View details for PubMedID 32719375

• Preferential inhibition of adaptive immune system dynamics by glucocorticoids in patients after acute surgical trauma. Nature communications Ganio, E. A., Stanley, N. n., Lindberg-Larsen, V. n., Einhaus, J. n., Tsai, A. S., Verdonk, F. n., Culos, A. n., Gahemi, S. n., Rumer, K. K., Stelzer, I. A., Gaudilliere, D. n., Tsai, E. n., Fallahzadeh, R. n., Choisy, B. n., Kehlet, H. n., Aghaeepour, N. n., Angst, M. S., Gaudilliere, B. n. 2020; 11 (1): 3737

  Abstract

  Glucocorticoids (GC) are a controversial yet commonly used intervention in the clinical management of acute inflammatory conditions, including sepsis or traumatic injury. In the context of major trauma such as surgery, concerns have been raised regarding adverse effects from GC, thereby necessitating a better understanding of how GCs modulate the immune response. Here we report the results of a randomized controlled trial (NCT02542592) in which we employ a high-dimensional mass cytometry approach to characterize innate and adaptive cell signaling dynamics after a major surgery (primary outcome) in patients treated with placebo or methylprednisolone (MP). A robust, unsupervised bootstrap clustering of immune cell subsets coupled with random forest analysis shows profound (AUC = 0.92, p-value = 3.16E-8) MP-induced alterations of immune cell signaling trajectories, particularly in the adaptive compartments. By contrast, key innate signaling responses previously associated with pain and functional recovery after surgery, including STAT3 and CREB phosphorylation, are not affected by MP. These results imply cell-specific and pathway-specific effects of GCs, and also prompt future studies to examine GCs' effects on clinical outcomes likely dependent on functional adaptive immune responses.

  View details for DOI 10.1038/s41467-020-17565-y

  View details for PubMedID 32719355

• Author Correction: Preferential inhibition of adaptive immune system dynamics by glucocorticoids in patients after acute surgical trauma. Nature communications Ganio, E. A., Stanley, N. n., Lindberg-Larsen, V. n., Einhaus, J. n., Tsai, A. S., Verdonk, F. n., Culos, A. n., Ghaemi, S. n., Rumer, K. K., Stelzer, I. A., Gaudilliere, D. n., Tsai, E. n., Fallahzadeh, R. n., Choisy, B. n., Kehlet, H. n., Aghaeepour, N. n., Angst, M. S., Gaudilliere, B. n. 2020; 11 (1): 4495

  Abstract

  An amendment to this paper has been published and can be accessed via a link at the top of the paper.

  View details for DOI 10.1038/s41467-020-18410-y

  View details for PubMedID 32883978

• Differential Dynamics of the Maternal Immune System in Healthy Pregnancy and Preeclampsia FRONTIERS IN IMMUNOLOGY Han, X., Ghaemi, M. S., Ando, K., Peterson, L. S., Ganio, E. A., Tsai, A. S., Gaudilliere, D. K., Stelzer, I. A., Einhaus, J., Bertrand, B., Stanley, N., Culos, A., Tanada, A., Hedou, J., Tsai, E. S., Fallahzadeh, R., Wong, R. J., Judy, A. E., Winn, V. D., Druzins, M. L., Blumenfeld, Y. J., Hlatky, M. A., Quaintance, C. C., Gibbs, R. S., Carvalho, B., Shaw, G. M., Stevenson, D. K., Angst, M. S., Aghaeepour, N., Gaudilliere, B. 2019; 10

  View details for DOI 10.3389/fimmu.2019.01305

  View details for Web of Science ID 000470999000001

• Differential Dynamics of the Maternal Immune System in Healthy Pregnancy and Preeclampsia. Frontiers in immunology Han, X., Ghaemi, M. S., Ando, K., Peterson, L. S., Ganio, E. A., Tsai, A. S., Gaudilliere, D. K., Stelzer, I. A., Einhaus, J., Bertrand, B., Stanley, N., Culos, A., Tanada, A., Hedou, J., Tsai, E. S., Fallahzadeh, R., Wong, R. J., Judy, A. E., Winn, V. D., Druzin, M. L., Blumenfeld, Y. J., Hlatky, M. A., Quaintance, C. C., Gibbs, R. S., Carvalho, B., Shaw, G. M., Stevenson, D. K., Angst, M. S., Aghaeepour, N., Gaudilliere, B. 2019; 10: 1305

  Abstract

  Preeclampsia is one of the most severe pregnancy complications and a leading cause of maternal death. However, early diagnosis of preeclampsia remains a clinical challenge. Alterations in the normal immune adaptations necessary for the maintenance of a healthy pregnancy are central features of preeclampsia. However, prior analyses primarily focused on the static assessment of select immune cell subsets have provided limited information for the prediction of preeclampsia. Here, we used a high-dimensional mass cytometry immunoassay to characterize the dynamic changes of over 370 immune cell features (including cell distribution and functional responses) in maternal blood during healthy and preeclamptic pregnancies. We found a set of eight cell-specific immune features that accurately identified patients well before the clinical diagnosis of preeclampsia (median area under the curve (AUC) 0.91, interquartile range [0.82-0.92]). Several features recapitulated previously known immune dysfunctions in preeclampsia, such as elevated pro-inflammatory innate immune responses early in pregnancy and impaired regulatory T (Treg) cell signaling. The analysis revealed additional novel immune responses that were strongly associated with, and preceded the onset of preeclampsia, notably abnormal STAT5ab signaling dynamics in CD4+T cell subsets (AUC 0.92, p = 8.0E-5). These results provide a global readout of the dynamics of the maternal immune system early in pregnancy and lay the groundwork for identifying clinically-relevant immune dysfunctions for the prediction and prevention of preeclampsia.

  View details for DOI 10.3389/fimmu.2019.01305

  View details for PubMedID 31263463

  View details for PubMedCentralID PMC6584811

• A YEAR-LONG IMMUNE PROFILE OF THE SYSTEMIC RESPONSE IN ACUTE STROKE SURVIVORS Tsai, A., Berry, K., Beneyto, M. M., Gaudilliere, D., Ganio, E. A., Culos, A., Ghaemi, M. S., Choisy, B., Djebali, K., Einhaus, J. F., Bertrand, B., Tanada, A., Stanley, N., Fallahzadeh, R., Baca, Q., Quach, L. N., Osborn, E., Drag, L., Lansberg, M., Angst, M., Gaudilliere, B., Buckwalter, M. S., Aghaeepour, N. LIPPINCOTT WILLIAMS & WILKINS. 2019: 155

  View details for Web of Science ID 000480793600335

• DEEP IMMUNE PROFILE OF PREOPERATIVE GLUCOCORTICOID ADMINISTRATION IN PATIENTS UNDERGOING SURGERY Rumer, K., Ganio, E. A., Stanley, N., Einhaus, J., Tsai, A. S., Culos, A., Fallazadeh, R., Lindberg-Larsen, V., Kehlet, H., Angst, M., Aghaeepour, N., Gaudilliere, B. LIPPINCOTT WILLIAMS & WILKINS. 2019: 140

  View details for Web of Science ID 000480793600305

• DEEP IMMUNE PROFILE OF PREOPERATIVE GLUCOCORTICOID ADMINISTRATION IN PATIENTS UNDERGOING SURGERY Gaudilliere, B., Ganio, E. A., Stanley, N., Einhaus, J., Tsai, A. S., Culos, A., Rumer, K., Fallahzadeh, R., Lindberg-Larsen, V., Kehlet, H., Angst, M. S., Aghaeepour, N. LIPPINCOTT WILLIAMS & WILKINS. 2019: 733

  View details for Web of Science ID 000619263200339

• A year-long immune profile of the systemic response in acute stroke survivors. Brain : a journal of neurology Tsai, A. S., Berry, K., Beneyto, M. M., Gaudilliere, D., Ganio, E. A., Culos, A., Ghaemi, M. S., Choisy, B., Djebali, K., Einhaus, J. F., Bertrand, B., Tanada, A., Stanley, N., Fallahzadeh, R., Baca, Q., Quach, L. N., Osborn, E., Drag, L., Lansberg, M. G., Angst, M. S., Gaudilliere, B., Buckwalter, M. S., Aghaeepour, N. 2019

  Abstract

  Stroke is a leading cause of cognitive impairment and dementia, but the mechanisms that underlie post-stroke cognitive decline are not well understood. Stroke produces profound local and systemic immune responses that engage all major innate and adaptive immune compartments. However, whether the systemic immune response to stroke contributes to long-term disability remains ill-defined. We used a single-cell mass cytometry approach to comprehensively and functionally characterize the systemic immune response to stroke in longitudinal blood samples from 24 patients over the course of 1 year and correlated the immune response with changes in cognitive functioning between 90 and 365 days post-stroke. Using elastic net regularized regression modelling, we identified key elements of a robust and prolonged systemic immune response to ischaemic stroke that occurs in three phases: an acute phase (Day 2) characterized by increased signal transducer and activator of transcription 3 (STAT3) signalling responses in innate immune cell types, an intermediate phase (Day 5) characterized by increased cAMP response element-binding protein (CREB) signalling responses in adaptive immune cell types, and a late phase (Day 90) by persistent elevation of neutrophils, and immunoglobulin M+ (IgM+) B cells. By Day 365 there was no detectable difference between these samples and those from an age- and gender-matched patient cohort without stroke. When regressed against the change in the Montreal Cognitive Assessment scores between Days 90 and 365 after stroke, the acute inflammatory phase Elastic Net model correlated with post-stroke cognitive trajectories (r = -0.692, Bonferroni-corrected P = 0.039). The results demonstrate the utility of a deep immune profiling approach with mass cytometry for the identification of clinically relevant immune correlates of long-term cognitive trajectories.

  View details for DOI 10.1093/brain/awz022

  View details for PubMedID 30860258

• Differential Dynamics of the Maternal Immune System in Healthy Pregnancy and Preeclampsia. Han, X., Ghaemi, M. S., Ando, K., Peterson, L., Ganio, E. A., Tsai, A. S., Gaudilliere, D., Einhaus, J., Tsai, E. S., Stanley, N. M., Culos, A., Taneda, A. H., Fallahzadeh, R., Wong, R. J., Winn, V. D., Stevenson, D. K., Angst, M. S., Aghaeepour, N., Gaudilliere, B. SAGE PUBLICATIONS INC. 2019: 271A

  View details for Web of Science ID 000459610400616