Systems Medicine in Chronic Inflammatory Diseases

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Systems Medicine in Chronic Inflammatory Diseases

Joachim L. Schultze,1,2,* The SYSCID consortium, and Philip Rosenstiel3,4,5,* 1Genomics and Immunoregulation, Life and Medical Sciences (LIMES) Institute, University of Bonn, 53115 Bonn, Germany 2Molecular Immunology in Neurodegeneration, German Center for Neurodegenerative Diseases (DZNE), 53127 Bonn, Germany 3Institute of Clinical Molecular Biology, Christian-Albrechts-University Kiel and University Hospital Schleswig-Holstein, Campus Kiel, 24105 Kiel, Germany 4Department of MedicineI, Christian-Albrechts-University and University Hospital Schleswig-Holstein, Kiel, 24105 Kiel, Germany 5Lead Contact *Correspondence: j.schultze@uni-bonn.de (J.L.S.), p.rosenstiel@mucosa.de (P.R.)

Chronic inflammatory diseases represent an increasing medical burden, yet neither tools to predict the individual disease course nor causal cures are at hand. We discuss opportunities for systems medicine to derive precise, individualized disease models and outline the European consortium SYSCID as part of the roadmap to clinical practice.

Inflammation is a principle ``life insurance'' mechanism of multicellular organisms. While phylogenetically designed to protect the body from invasion by other organisms or from events of cellular danger, chronic inflammatory reactions are often detrimental and have been recognized to play a role in the pathophysiology of numerous socio-economically relevant disorders, including atherosclerosis, metabolic syndrome, neurodegeneration, and cancer. Chronic inflammatory disease (CID) is used here as a term to characterize a group of chronic disorders of the immune system of unknown etiology with a continuously rising incidence in Western countries over the past 70 years (Bach, 2002). In this sense, CIDs comprise a spectrum of non-communicable immune-mediated diseases with a polygenic mode of inheritance, which may affect almost all organ systems: gut (e.g., inflammatory bowel disease [IBD]), vessels and kidney (e.g., systemic lupus erythematosus [SLE] or other vasculitis forms), pancreas (type I diabetes), skin (e.g., psoriasis), and joints (e.g., rheumatoid arthritis [RA]). Canonical immune taxonomy would classify CIDs as a spectrum of disorders ranging from classical autoimmune diseases like SLE or Sjo? gren's Syndrome (with a clear contribution of pathogenic antibodies recognizing autoantigens) to chronic destructive disease, such as IBD or psoriasis mainly involving T cell-mediated responses and barrier dysfunction. Allergies and atopic disease (e.g., asthma and atopic dermatitis) can be included into CIDs in a wider sense, in which responses to non-self antigens and IgE-mediated

reactions are key elements of the immune pathology.

The diseases usually manifest at a specific time window during adult life and are associated with a significant degree of long-term disability. Beyond local manifestations, CIDs are characterized by increased mortality due to chronic involvement of other organs, such as the lung or the cardiovascular system as is evident in SLE or psoriasis. A significant social burden results from stigmatization as the diseases may negatively affect the individual's appearance (e.g., body size and weight) or primary body functions, such as defecation, mobility, and sex life.

Diagnosis of many of these CIDs is still based on morphological characteristics (inspection or endoscopy) and disease behavior criteria, such as inspection, endoscopy, disease activity indices (e.g., CDAI, Harvey Bradshaw Index), general blood tests (C-reactive protein, leukocyte count), and stool tests (fecal calprotectin level). Only in some of the diseases have more indicative biomarkers been identified (e.g., citrullinated protein antibodies in RA). All these CIDs are incurable diseases and current therapy aims to dampen systemic immune responses and gain control of the disease. Therapeutic approaches vary depending on disease type and severity, and they range from local immunomodulation (aminosalicylate, disease-modifying antirheumatic drugs) to systemic immunosuppression (azathioprine, glucocorticoids, cytotoxic agents). Novel approaches in therapy of CIDs include targeted inhibition of proinflammatory cytokines (e.g., anti-TNF-a,

anti-IL23 and/or anti-IL12, anti-BLys, anti-IL1 or inhibition of pro-inflammatory leukocytes), either by inhibition of homing (e.g., anti-a4b7 integrin antibodies) or direct cytotoxicity (anti-CD20). It remains to be shown whether the increasing notion that such compounds might be effective in other diseases involving chronic inflammatory reactions (e.g., anti-IL1 in cardiovascular disease) will lead to a shift in clinical recognition and, ultimately a potential clinical reclassification, as defined by the broad adoption of immunosuppressive therapies.

Interestingly, although these diseases have a strong genetic background, most of them have been almost unknown to clinical medicine until the beginning of the 20th century, indicating an interplay between long-standing genetic variation in the population and changing environmental conditions as a cause of epidemiologically new inflammatory disease entities. It is important to note that many CIDs affect barrier organs sensu strictu, which may be directly influenced by environmental changes, yet recent evidence clearly has indicated that such immunologically active interfaces like the gut or lung are important instruction sites for systemic immunity as well. Recent advances have been made in the description of genetic risk factors, and the dissection of the pathophysiology (e.g., the description of aberrant inflammatory signal transduction), both of which have been shown to overlap significantly between CIDs (Zhernakova et al., 2009; Ellinghaus et al., 2016)

However, complex questions such as why a specific disease manifests in a

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Figure 1. Schematic View on Systems Immunology of CID The figure depicts two important layers of a systems-oriented understanding of inflammatory disorders. Systems medicine access defines the clinical accessibility of relevant tissue types, while the analysis layers dissect each tissue type into multi-dimensional molecular data spaces. The scheme depicts two access layers important for SYSCID: peripheral blood and intestinal biopsies and highlights main analysis layers.

given individual, and how the disease becomes overt in a specific time window during adulthood, remain unresolved. Here, we delineate why systems medicine and, particularly, systems immunology are key for a new understanding of the etiology of CIDs and we define areas of medical need where such approaches may be translatable to clinical care.

Systems Medicine: Why in CIDs and Why Now? Technological and computational advances in the past 10 years have revolutionized our ability to acquire high-dimensional medically-relevant data on almost all molecular levels including genome, transcriptome, proteome, and glycome. Molecular imaging and rapid analysis of large nucleotide sequences (e.g., exome and genome sequencing) have already become part of the clinical reality, yet only for very few conditions such as cancer and some monogenic diseases including rare immune deficiencies. Other disciplines, including rheumatology, the classical CID discipline, are lagging far behind. This is due to several issues, which currently hamper introduction into clinical algorithms: (1) Although CIDs (RA, SLE, and IBD in particular) have been a successful showcase of the recent wave of genetic studies with over 200 validated and replicated polygenic

risk loci, the most common genetic variants only confer a small absolute risk and they do not suffice for making an accurate diagnosis. Overall, more than 60% of the heritable risk of all CID types remains unexplained by genetic variation. Moreover, only a fraction of the many individuals carrying genetic risk variants will develop CIDs, indirectly showing that other mechanisms (such as gender, epigenetics, microbiome, protein glycosylation, and environmental factors) critically affect the expressivity of individual genetic traits. Without a holistic understanding of diverse molecular information layers, accurate prediction will stay out of reach. This is different from the oncology field, as the mutational landscape of an individual tumor (as a single molecular layer) is often strongly related to its biological behavior. (2) Diagnostic information in the current medical setting is obtained as a series of independent diagnostic observations, often driven by organ-based specialists (e.g., gastroenterologist for IBD). Genetics and pathophysiology research, however, have demonstrated a vast overlap of molecular risk maps between individual CIDs, but also for their significant co-morbidities, e.g., cardiovascular disease and cancer, suggesting that medicine will likely fail to truly predict disease affection if it remains bound to such historical categories. Inter-

disciplinary inflammation medicine, as an accepted part of medical education and practice, will be seminal for any innovative, systems-based medical care scenario. The successful implementation of comprehensive cancer centers was driven by the same spirit. (3) A major obstacle to translation of medical knowledge driven by multi-dimensional molecular data to the clinics is the level of prior understanding and education needed to interpret the findings. In contrast, medical phenotyping still uses macromorphological manifestations and indirect symptoms for defining the disease and its activity. The enormous complexity of Omics-datasets and often the prolonged time from initial analysis to final conclusions, currently limit the value of the data for the attending physician. Accordingly, approaches using multi-dimensional data must face the overt challenge that ultimately it must be translated into simple scores/algorithms which must be clinically meaningful and actionable, and easily understandable, also for the patient.

Why will a systems-oriented approach in CIDs help to overcome these challenges of molecular diagnostics and why is CID the right indication at the right time for such an approach? Similar to any other new discipline, the term systems medicine lacks a universally accepted definition. Pragmatically, it has been proposed (Wolkenhauer and Green, 2013) that systems medicine should be understood as an application of systems biology analysis principles to diseasefocused or clinically-relevant problems. The statement refers to the systems biology concept of iterative perturbation, measurement and development of (mathematical) models for predicting the behavior of a complex biological system. Importantly, the concept is usually linked to an integrative analysis of high-dimensional molecular data (transcriptome, epigenome, glycome, microbiome) to describe and monitor important system components in a hypothesis-free manner. In principle, these system components are determined by an access layer (tissue and/or material type) and an analysis layer (e.g., transcriptome, DNA methylome, glycome, tissue-resident microbiome), which must be integrated to reconstruct functional disease networks (Figure 1). In a wider sense, systems medicine can

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Figure 2. Patient Life History and Disease Course in CIDs The timeline graph depicts an individual disease course and describes the march from sub-clinical molecular alterations to disease in the three diseases under study in SYSCID: inflammatory bowel disease (IBD), rheumatoid arthritis (RA), and systemic lupus erythematosus (SLE). In this concept, clinically overt disease manifestation can be understood as a threshold and rather late event in the etiology, a ``point of no return.'' Importantly, the disorders display molecular cross-disease signatures of behavior, which might be important to predict disease course and select the appropriate therapies.

also be understood as the application of pre-existing systems biology methods and models to predict future behavior of individual disease (Aronson and Rehm, 2015). Except for controlled medical approaches to the immune system, e.g., vaccinations or targeted antibody therapies, perturbations in immunology can frequently only be defined post hoc, and the proposed concept ignores that it is often neither feasible nor ethically appropriate to directly and repeatedly measure network states in human disease (e.g., due to inaccessibility of the affected tissue). Significant exceptions are barrier organs, like the intestinal mucosa, as well as migrating immune cells (blood), which can be subjected to repeated examinations, e.g., after a defined therapeutic intervention, and are thus a particularly feasible target to systems medicine.

Based on these developments we define here the major unmet clinical needs in CIDs that clearly require systems-oriented approaches (Figure 2):

d Disease manifestation: Current diagnostic methods are not sufficient to accurately predict early dis-

ease manifestation. It is clear, that in all CID entities the disease process starts long before diagnosis. Time from first symptoms to diagnosis of CIDs even in Western Europe still suffers from a diagnostic delay of 12?24 months. Also, interfering with early stages of this ``march towards disease'' is more likely to result in a cure than treating overt disease. Diagnostic algorithms employing multimodal marker sets for early and unequivocal detection of disease are thus a major unmet need in CIDs. d Disease progression and comorbidities: Another important need results from the fact that long-term disease progression and occurrence of complications are not yet predictable in CIDs. Early identification of patients with aggressive disease behavior (e.g., joint destruction in RA or stenosis and fistula in Crohns disease) or prediction of associated complications such as cardiovascular events, malignancies, or metabolic disorders are decisive elements for a future individualized

clinical treatment. First promising results have demonstrated that functional exhaustion signatures of CD8+ T cell are a common element of complicated disease behavior across several CIDs (McKinney et al., 2015). In a similar way, due to alterations in IgG glycosylation, different CIDs are associated with the loss of immunosuppressive potential of circulating IgG, e.g., affecting disease progression. d Therapy Response: In CIDs, several different targeted therapies neutralizing specific factors of the immune system (so called ``biologicals,'' e.g., antibodies to TNF or IL-6) have been approved. Such therapies are cost-intensive and suffer from significant primary and secondary nonresponse rates. So far on the individual patient level, a molecular rationale (biomarker) for employing a specific compound in an indication situation is missing. It is highly attractive to use the antagonization of key cytokines as a perturbation to study human disease pathophysiology in a systems biology paradigm. To understand kinetics of immunological network changes associated with response and nonresponse to different biologicals (e.g., inhibitors of TNF-a, IL-6, IL-1 or adhesion molecules) by multimodal clinical diagnostics and multi-Omics (transcriptome (mRNA, sncRNA), DNA methylome, glycome, microbiome) in longitudinal studies will be an important element to develop a systems-based decision support to select the right therapy at the right time. An interesting problem is whether we will be able to identify those states a priori, i.e., before the onset of therapy or whether therapeutic outcome can only be predicted from early shifts of the network after a first probatory administration of the drug.

Creating Systems Immunology as a Discipline--from General Concepts to Individuality Most of basic immunology has been based on hypothesis-driven research with the assumption that there is an underlying concept of a ``prototypic immune system.'' This view has been fostered by

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all seminal findings on immune system functioning over the last decades that have been mainly made in model systems, particularly in mice. Many of these studies have focused on single molecules, single genes, single pathways, or single cell types only. However, understanding a complex disease phenotype such as CIDs requires the integration of different information layers across multiple scales from molecules to cells and organs and ultimately to the whole human organism (Wolkenhauer and Green, 2013). By definition, a single dimension does not carry enough information to understand a systemic disease.

Large consortial efforts generating comprehensive catalogs in a standardized fashion form the framework for further systematic exploration of all the components of the immune system. Prominent examples of influential consortia dealing with large genomic datasets for a deeper understanding of the molecular identity of immune cells include ImmGen, ImmVar, gTEX (Mele et al., 2015) and the IHEC-based consortia BluePrint, DEEP (Durek et al., 2016) as well as ENCODE.

Despite aiming for reference catalogs, all Omics technologies have strongly emphasized interindividual variation. In fact, the identification and characterization of cell-type specific molecular quantitative trait loci QTLs (Fairfax et al., 2014; Lappalainen et al., 2013) explaining epigenetic and transcriptional variation in human immune cells (Astle et al., 2016) are an important step forward in linking the multifaceted contribution of genetic and epigenetic factors to immune phenotypes.

The importance of individuality is now emerging not only between but also within an individual. We are now at the point to define the genomes, transcriptomes, and epigenomes of single immune cells, which will give us completely new opportunities to define immune cell populations by functional units rather than preselected cell surface markers (Jaitin et al., 2014; Mass et al., 2016). Deconstructing responses at the single cell level may thus lead to a radical change of our functional understanding of the immune system by dissecting cellular heterogeneity and hierarchy in an unbiased manner. We are convinced that a complete understanding of complex diseases such as CIDs will not be possible without under-

standing the impact of these individual components.

International Efforts to Foster Systems Immunology and Systems Medicine in Chronic Immune Disorders If patients should benefit from these exciting developments in genomic and immunological research, we need to develop and implement the necessary infrastructures, technologies, interdisciplinary teams and career tracks that foster a successful link from basic to translational and even clinical sciences. Cancer centers and international cancer consortia might be a good blueprint for these endeavors. The task ahead for CIDs is large requiring multi-national efforts along the European idea of collaborative nations. Within the European research eco-system (H2020), one such example has recently been funded and initiated and will be presented here as a new example.

SYSCID: An Example of a MultiNational Effort to Tackle CIDs by Systems Medicine Approaches SYSCID (A Systems medicine approach to chronic inflammatory diseases, syscid.eu) is an EU-based interdisciplinary consortium of researchers with expertise ranging from medical sciences, immunology, genomics, epigenomics, glycomics, molecular biology, bioinformatics, and even to computer sciences. The consortium has set its primary focus on the exploration of cross-sectional and longitudinal molecular and clinical datasets to investigate the course of disease with a view to a patient's lifetime. SYSCID has therefore selected three CID entities as its major focus: RA, SLE, and IBD. The diseases share a significant amount of genetic disease risk loci and formal immunological features (e.g., IL-17). Importantly, the disorders display a cross-disease signatures of behavior (severe course versus mild course), which are distinct from the disease-related signals. A signature is present on the genetic level for IBD (CD) and RA (SNP in FOXO3A, Lee et al., 2013). On the transcriptomal level in whole blood, a CD8+ T cell exhaustion signature is linked to severe future disease behavior in IBD and SLE (McKinney et al., 2015). We thus hypothesize that the three diseases are an interesting starting point for a sys-

tems medicine approach, in order to further develop molecular tool sets to predict clinical severity and/or providing a rationale for therapy decision-making. As such, SYSCID aims to deliver molecular subphenotypes, which can be employed as stratification measures in future clinical trials. To integrate prior knowledge in systems biology, SYSCID is strongly linked to large consortia such as the International Human Epigenome Consortium (IHEC), International Cancer Genome Consortium ICGC, TwinsUK, or Metagenomics of the Human Intestinal Tract (Meta-HIT).

In total, the consortium will have access to clinical, genomics, immunological, and molecular data of close to 50,000 individuals from several CID cohorts throughout Europe. Within these cohorts, 2,500 individuals will be subjected to an Omicsbased analysis, for which longitudinal clinical datasets are at hand. Data will be generated on different scales ranging from whole blood signatures, signatures to purified immune cell types. Clinical samples have been selected on the basis of available longitudinal clinical activity data (harmonized clinical scores) and sampling protocols for blood, purified cell types, and stool. SYSCID will also comprise a prospective longitudinal single cell analysis study following patients during first time biological therapy. We have selected blood as a major biospecimen as (1) the tissue is readily available also for repeated-measurement, thus any finding in this tissue compartment will be more easily adopted in future clinical trial designs and (2) our seminal prior observations regarding a cross-disease severity signature have also been made in blood (McKinney et al., 2015). We will aim to verify signatures in affected tissue specimen.

The five dimensions of generated systems level data will include the SNP variome, DNA methylome, transcriptome, immunoglobulin glycome, and gut microbiome. With such unique longitudinal datasets at hand, SYSCID aims to (1) identify a ``core disease signature'' of CIDs based on multimodal biomarkers from blood and novel mechanistic insights into CIDs, (2) define ``predictive models of disease outcome'' allowing patient tailored therapy decisions, and (3) develop novel ``reprogramming strategies'' for CIDs based on genomic, epigenomic, and transcriptional programs identified in CID patients.

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Accepting a ``systems'' network setup of immunological reactions implicates that disease is a fixed imbalance of a topology of multilayer information and can be causally altered, e.g., by editing the epigenome and transcriptionally reprogram states of specific cell types, such as macrophage polarization defects. A major aim of SYSCID is to explore new bioinformatics algorithms and models which integrate multidimensional molecular and clinical data using statistical (non) linear modeling and feature selection techniques. Validation on independent cohorts will be used to assess model predictive power. A further focus is on the exploitation of single cell genomic techniques as innovative diagnostic toolbox to simultaneously identify the immune cell subsets and determine their activation status. SYSCID follows other model solutions (e.g., data use and access committees of the UK Twin cohort and the IIBD Genetics consortium) to allow access to its data including clinical information for community research, while at the same time protecting the right of the participating patients.

Other Endeavors Utilizing Systems Immunology Approaches in a Clinical Setting Apart from this example, the systems immunology field joining genomic and cutting-edge computational approaches currently gives rise to many large-scale research consortia. A very prominent and successful European consortium is the Human Functional Genomics Projects (HFGP, humanfunctionalgenomics. org) led by M. Netea, which links deep immunological phenotyping with genetic, epigenetic, transcriptomic, and microbiomic information. Starting initially with two cohorts of 200 respectively 500 healthy individuals, HFGP is now extending its efforts toward cohorts of cardiovascular diseases, HIV, diabetes type 2, and candidiasis.

As early as 2007 the collaborative research program Systems Approach to Immunology (systemsimmunology. org), was initiated as an international consortium to study the mechanisms by which the immune system responds to infectious diseases. This program was continued in 2012 and now focuses on the dissection of the immune response to infectious diseases through the

application of systems-guided forward genetics.

Beyond these large-scale international systems immunology projects, there are also national activities. One such very successful systems immunology consortium is the US-based Human Immunology Project Consortium (HIPC, ), funded by the NIH in 2010 and renewed in 2015 with differing member institutions. This consortium is mainly focusing on systems vaccinology, a term introduced by Pulendran and Chaussabel (Li et al., 2014) and the definition of signatures of components of the human immune system in steady-state and activated by vaccination. In Europe, Germany has been a major supporter of systems immunology approaches through, e.g., the e:med German National initiative on systems medicine (), which has been funded since 2013, several larger consortia focus on immunological diseases (CapSys, SYSIMIT, SysINFLAME). In addition to national and international consortia, human systems immunology has also been introduced at single institutions. Excellent examples are the Human Immune Monitoring Center (HIMC) at Stanford University, the Emory Vaccine Center at Emory University, or the Milieu Inte? rieur Consortium at the Pasteur Institute in Paris, the German Excellence Clusters ImmunoSensation in Bonn and Inflammation at Interfaces in Kiel to name a few examples.

Conclusion and Outlook Since the ``wake-up call'' by Mark Davis in 2008 (Davis, 2008), human immunology has made tremendous progress. Systems immunology as a part of systems medicine is transforming human immunology. Now, we face the challenge to fully integrate large-scale molecular technologies and computational sciences into our way of thinking. This interdisciplinary approach directly links basic to clinical research in human immunology and will likely transform clinical paradigms in immune system-related disorders including CIDs. We believe that SYSCID is a corner stone for a European systems medicine strategy as it analyzes unique clinically well-controlled longitudinal sample sets on several Omics-data layers and employs whole blood, as well as purified immune cell subsets. Hence, our approach

will enable to relate dynamic changes of cellular markers to the individual disease course and therapy response. SYSCID makes a first step toward integrating systems medicine into a more individualized clinical care in CIDs. However, we are aware that this challenge will require large scientific, structural, and educational changes in order to become clinical reality:

1. There is no single country that can tackle the task; human systems medicine of immune-system-mediated disorders will only be successful as a truly international endeavor.

2. We are about to make the critical step from the tissue or cell population level to the single cell information layer.

3. Complexity and costs are enormous even when only addressing a single disease and, like for cancer, a Pan-Immune disease consortium may be an important step.

4. Immunologists and clinicians need to reach out to other research areas such as computational sciences, crossing borders of disciplines.

5. Systems approaches seem to be inherently complicated, thus we need to educate and interact with the public. It must be conveyed that translational research with large personal health datasets is an important opportunity rather than a risk of losing privacy. Informed acceptance of the public as an important stakeholder is key to bringing this into reality. Ultimately, patients need to understand diagnostic and therapeutic options arising from these methods, so like any new method in medicine we should avoid hiding it in a black box.

6. As exciting as the novel options of systems-based medicine in CID are, there is a particular requirement to keep costs of novel approaches as low as possible. Currently, unit prices of many of the genome-wide approaches (e.g., methylome, single cell transcriptome) are far beyond reach of clinical practice. This is not only true because of the mere production costs, but also because of the time-consuming and still

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individualized bioinformatics pipelines. We must keep in mind to simplify and standardize systemsbased diagnostic approaches. This can be achieved both by extracting informative biomarkers from different data layers (thus reducing complexity and costs per test) or developing standard tools for large scale analysis of data (thus reducing costs of analysis). When you think of the algorithms behind magnetic resonance imaging machines, this does not seem out of reach. In the end, the only measures, which will count in clinical practice are reasonable turnaround time and cost-tobenefit ratio. 7. Young clinician scientists must be trained in systems-oriented medicine in medical school, and it needs to become mainstream for them. Moreover, we need curricular postgraduate programs, specialty training, and faculty programs that allow protected research time for clinician scientists at all levels, as they are an endangered species in the face of economic pressure. 8. Ultimately, large patient numbers will be needed in long-term clinical trials. Some of the trials are likely not in the main interest of the large pharmaceutical companies. Stratification may not be achieved with a simple companion diagnostic test and head-to-head comparator trials might cut down market sizes for individual compounds. We thus must convince funding agencies to invest in roadmaps, which bring systems medicine into clinical practice, e.g., by funding clinical trials where systems-instructed therapy decisions in CIDs are compared against a standard of care.

Systems Medicine may change the life of patients with CIDs and other immunemediated diseases in a foreseeable time frame. Using this toolbox, cancer has been a forerunner, but molecular diagnostics and treatment options in CIDs are getting similarly targeted and diverse. It is time that we leave our comforting disciplinary boundaries to translate this potential into clinical medicine.

SUPPLEMENTAL INFORMATION

Supplemental Information includes a list of The SYSCID consortium members and affiliations and can be found with this article online at . org/10.1016/j.immuni.2018.03.022.

CONSORTIUM

Joachim L. Schultze, Konrad Aden, Vibeke Andersen, Aggelos Banos, Signe Bek, Marc Beyer, Johanna Blase, Dimitrios Boumpas, Paraskevi Christofidou, Emmanouil Dermitzakis, Andre Franke, Gilles Gasparoni, Michel Georges, Wei Gu, Robert Hasler, Stefanie Herresthal, Stephan Huthmacher, Mohamad Jawhara, Amy Kenyon, Gordan Lauc, Paul A Lyons, Massimo Mangino, Eoin F. McKinney, Neha Mishra, Gioacchino Natoli, Karl Nordstro? m, Nikolaos Panousis, Marija Pezer, Marilou RamosPamplona, Jeroen Raes, Elisa Rosati, Reinhard Schneider, Stefan Schreiber, Jonas SchulteSchrepping, Timothy Spector, Kenneth G.C. Smith, Doris Vandeputte, Aleksandar Vojta, Jo? rn Walter, Vlatka Zoldos, and Philip Rosenstiel.

ACKNOWLEDGMENTS

We thank Renate Nikolaus for her help with graphic design. The work of the authors receives funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 733100 (SYSCID), the e:Med program SYSINFLAME, the DFG EXC Immunosensation, and the EXC Inflammation at Interfaces.

AUTHOR CONTRIBUTIONS

J.L.S. and P.R. conceived, guided, and wrote the article, and all members of the SYSCID consortium discussed and conceived content of this article and contributed to its writing.

DECLARATION OF INTERESTS

G.L. declares he is owner and CEO of Genos, a biotech company that specializes in highthroughput glycomic analysis and has several patents in the field. None of the other authors state a relevant financial interest with regard to the content of the work.

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