INFECT Final Report Appendices

Appendices INFECT Final Report

1. Figures & Tables

Page 1 of 1

Figure 1.

The INFECT-project: A systems medicine approach to advance our understanding of necrotizing soft tissue infections (NSTI) Clinical challenges in focus: NSTIs are rapidly progressing severe infections associated with substantial risk of loss of lives and limbs. Prompt diagnosis is key!

Infectious NSTI patient cohort & biobank: Disease Hyperbaric - Prospective Intensive Oxygen - > 400 patients Care Surgery - > 6000 samples Clinicians

Identified disease traits Host & pathogen specific Microbiology Immunology Patient samples Infected tissue models Cell biology

Experimentalists Multi omics Pathway analyses

IL1b Systems Mathematical biology modelling

Multiplex diagnostics Small & Medium Enterprises

Outcome: Advanced understanding of the disease & associated pathogenesis Improved diagnostics & therapeutics Implemented systems medicine in infectious diseases Scientific foundation for personalized medicine in NSTI

2013 – 2018 www.fp7infect.eu

Figure 2.1

Figure 2.2

Data from retrospective analysis of patient Expected and ongoing INFECT study inclusion from clinical partners in WP2 sampling from clinical partners in WP2 sampling from clinical partners in WP2

Region Data No. of patients Estimated INFECT INFECT STUDY INFECT STUDY INFECT STUDY INFECT STUDY collection INFECT STUDY Mean per year STUDY ENROLMENTS ENROLMENTS ENROLMENTS ENROLMENTS years enrolments ENROLMENTS 2014 2015 2016 2017/18 Per Year 2013

Denmark 277 Partner 2 RH 2005- Per year: 55 50-60 48 72 61 55 31 2009

Sweden 006- 109 Partner 3 2010 SLL Per year: 21 20 4 17 22 11 9

Sweden 2006- 27 Partner 4 2011 BLS Per year: 3 5 1 4 3 1 1

Sweden 2008- 28 Partner 5 2010 SU Per year: 9 10 6 11 9 9 3

Norway 2000- 100 Partner 6 2009 UiB Per year: 10 10-15 14 19 11 10 0

Figure 2.3

Figure 2.4

Figure 7.1

Figure 7.2

Figure 7.3

Family / Classification Genus Species Family / Classification Genus Species

Burkholderiaceae Burkholderia Burkholderia cepacia complex Ajellomycetaceae Blastomyces Blastomyces dermatitidis Burkholderia pseudomallei Histoplasma Histoplasma capsulatum Neisseriaceae Neisseria Neisseria meningitidis Campylobacteraceae Campylobacter Arthrodermataceae Arthroderma Heliobacteraceae Helicobacter Helicobacter pylori Arthroderma benhamiae Enterobacteriaceae Citrobacter Citrobacter koseri Arthroderma otae Citrobacter freundii complex Epidermophyton Epidermophyton floccosum Enterobacter Enterobacter aerogenes Microsporum Microsporum gypseum Enterobacter cloacae complex Escherichia Escherichia coli Microsporum audouinii Klebsiella Klebsiella oxytoca Trichophyton Trichophyton interdigitale /mentagrophytes Klebsiella pneumoniae Trichophyton rubrum / violaceum Morganella Morganella morganii Trichophyton verrucosum Proteus Proteus mirabilis Trichophyton tonsurans Salmonella Salmonella enterica Serratia Serratia marcescens Trichophyton soudanense Yersinia Yersinia enterocolitica Onygenales incertae sedis Coccidioides Yersinia pseudotuberculosis complex Aspergillaceae Aspergillus Legionellaceae Legionella Legionella pneumophila Aspergillus clavatus Pasteurellaceae Actinobacillus Actinobacillus pleuropneumoniae Aspergillus flavus Haemophilus Haemophilus haemolyticus Haemophilus influenzae Aspergillus fumigatus Aspergillus niger

Moraxellaceae Acinetobacter Acinetobacter calcoaceticus / baumannii complex Fungi Penicillium Penicillium digitatum Moraxella Moraxella catarrhalis Debaryomycetaceae Debaryomyces Debaryomyces hansenii Pseudomonaceae Pseudomonas Pseudomonas aeruginosa Candida

Pseudomonas syringae Bacteria Xanthomonadaceae Stenotrophomonas Stenotrophomonas maltophilia group Candida albicans Fusobacteriaceae Fusobacterium Candida dubliniensis Fusobacterium nucleatum Candida parapsilosis Fusobacterium necrophorum Candida tropicalis Corynebacteriaceae Corynebacterium Corynebacterium diphtheriae Saccharomycetaceae Nakaseomyces Candida glabrata Corynebacterium jeikeium Corynebacterium ulcerans Saccharomyces Propionibacteriaceae Propionibacterium Saccharomyces cerevisiae Bacillaceae Bacillus Bacillus subtilis Zygosaccharomyces Zygosaccharomyces rouxii Listeriaceae Listeria Pichiaceae Pichia Pichia kudriavzevii Staphylococcaceae Staphylococcus Microascaceae Scedosporium Staphylococcus aureus Staphylococcus epidermidis Nectriaceae Fusarium Fusarium oxysporum species complex Staphylococcus haemolyticus Fusarium solani species complex Enterococcaceae Enterococcus Enterococcus faecalis Pneumocystidaceae Pneumocystis Pneumocystis jirovecii Enterococcus faecium Pneumocystis murina Streptococcaceae Streptococcus Cladosporiaceae Cladosporium Streptococcus pneumoniae Streptococcus pyogenes Tremellaceae Filobasidiella Cryptococcus neoformans Streptococcus anginosus group Cryptococcus gattii Streptococcus dysgalactiae Streptococcus agalactiae Peptoniphilaceae Finegoldia Finegoldia magna Prevotellaceae Prevotella Prevotella intermedia Borreliaceae Borreliella Borreliella burgdorferi Resistance Resistance marker genes Vancomycin resistances vanA vanB Methicillin resistances mecA

Resistance mecC

Figure 7.4

Figure 7.5

Correlation Performance CRP 47% Acceptable Cystatin C 53% Acceptable Myoglobin 84% Good NGAL 60% Good PCT 75% Good

Figure 9.

Report by Prof. Matthias Reuss:

Tabel 1. Novel insights into the pathophysiology of NSTIs

Results* Exploitation End users Beneficiary Host trait: IL1 Potential target for: SMEs Patients Diagnostics Clinicians Health care Intervention Researchers Industry Patient stratification

Future clinical trials Host-dependent Potential target for: SMEs Patients pathophysiology Diagnostics Clinicians Health care Intervention Researchers Industry Patient stratification

Future clinical trials Host antibody deficiency Potential target for: SMEs Patients Intervention Clinicians Health care Patient stratification Researchers Industry Future clinical trials

Different bacterial traits Potential target for: SMEs Patients influence tissue pathology Diagnosis Clinicians Health care Intervention Researchers Industry Patient stratification

Future clinical trials Aetiology-dependent Potential target for: SMEs Patients pathophysiology Diagnosis Clinicians Health care Intervention Researchers Industry Patient stratification

Future clinical trials Bacterial biofilm Diagnosis Clinicians Patients Health Antibiotic use Researchers care

Table 2. Patient benefit: superior diagnosis

Results* Exploitation End users Beneficiary Hyborg for patient monitoring Diagnostics SMEs Patients Clinicians Health care Industry

Hyborg pathogen ID and Diagnostics (blood, tissue) SMEs Patients enrichment Clinicians Health care Industry

Table 3. Patient benefit: advanced understanding of the clinical aspects of NSTI and preparation of guidelines for management and care.

Results* Exploitation End users Beneficiary Advanced understanding of Diagnostics Clinicians Researchers NSTI patients Treatment strategies Students Health care Identification of at risk Researchers Industry patients SMEs Patients Education Students

Table 4. Patient benefit: novel therapeutic strategies

Results* Exploitation End users Beneficiary IVIG should not be used for all Patient stratification and Clinicians Patients NSTI. Results support the use of tailored therapy Health care IVIG in S. pyogenes NSTI.

Biofilm Appropriate antibiotic use Clinicians Patients Microbial aetiology is closely Researchers Health care linked to body area affected Industry Industry

Table 5. Design/optimization of future clinical trials

Results* Exploitation End users Beneficiary IL1b for patient stratification and Exploratory clinical trials Clinicians Researchers intervention Researchers Health care Industry Patients

Table 6. Reduction on health care costs

Results* Exploitation End users Beneficiary IVIG should not be used for all Patient stratification and Clinicians Health care NSTI. Results support the use of tailored therapy IVIG in S. pyogenes NSTI.

Biofilm Appropriate antibiotic use Clinicians Health care Microbial aetiology is closely linked to body area affected

Table 7. Establishment of the value of systems medicine in solving complex human diseases

Results* Exploitation End users Beneficiary Patient outcome prediction model Clinical decision support Clinicians Health care Patients

Pathophysiology-dependent patient Tailored treatment Clinicians Health care stratification SME Patients

Multiplex diagnostic tool based on Superior diagnostics Clinicians Health care patient biomarkers Patient stratification SME Patients

Dedicated Semantic Resource for Clinical decision support Clinicians Health care Data Storage and Management Superior diagnostics Academic Patients Patient stratification Institutions SME Patient organisations

Table 8. Fostering the competitiveness of SMEs and European innovation

Results* Exploitation End users Beneficiary New computational models and Clinical decision support Clinicians Health care bioinformatic tools for: Tailored treatment SME Patients Superior diagnostics Patient stratification Simple method to enrich pathogens Kit to enrich bacteria and Laboratories Patients in whole blood samples fungi in blood samples Highly sensitive molecular Diagnostic tests to identify Laboratories Patients pathogen diagnostics bacteria and fungi from whole blood

Table 9. Training of early stage and experienced researchers

Results/Activity Author/Responsible, Title, University, Year Field PhD thesis Anna Linnér, Clinical and Pathophysiological aspects of sepsis, Infectious Karolinska Institutet, 2014 Diseases

PhD thesis Trond Bruun, Clincial and bacterial diversity in streptococcal skin Infectious and soft tissue disease, University of Bergen, 2016 Diseases

PhD thesis Oddvar Oppegaard, Trends of Streptococcus dysgalactiae Infectious subspecies equisimilis infections in western Norway – Insight into Diseases clinical and microbial aspects. University of Bergen, 2017

PhD thesis Marco Bo Hansen; Biomarkers of NSTI. Aspects of the innate Intensive care immune response. medicine University of Copenhagen, 2016. PhD thesis Martin Bruun Madsen, “Necrotising Soft Tissue Infections in the Intensive care ICU to be defended August 30, 2018, University of Copenhagen, medicine 2018

PhD thesis Peter Polzik: Biomarkers reflecting endothelial dysfunction and Intensive Care prognosis in NSTI. Medicine University of Copenhagen 2018. PhD thesis Jasper Koehorst “FAIR FUNCTIONAL GENOMICS” to be Systems medicine defended on January 25, 2019 at Wageningen University, the Netherlands

PhD thesis Jesse van Dam “Semantic Technologies for Systems Medicine” to Systems medicine be defended on January 23, 2019 at Wageningen University, the Netherlands

PhD thesis Chella Krishnan, K, Host-Pathogen Interactions Promoting Molecular Pathogen Survival and Potentiating Disease Severity & Morbidity Genetics, in Invasive Group A Streptococcal Necrotizing Soft Tissue Biochemistry, & Infections, University of Cincinnati, 2015 Microbiology PhD thesis Srikanth Mairpady Shambat, Host-pathogen interactions in Infection Biology invasive staphylococcal infections, Karolinska Institutet, 2016

PhD thesis Julia Uhlmann, Neutrophil interactions with Streptococcus Infection Biology pyogenes and Staphylococcus aureus, Karolinska Institutet, 2017

PhD thesis Johanna Snäll, Phagocytic cells and Streptococcus pyogenes in Infection Biology invasive infections: an inflammatory relationship, Karolinska Institutet, 2017

Table 9. Training of early stage and experienced researchers

PhD thesis Puran Chen, Human organotypic models in biomedical research to Infection Biology be defended in January 2019, Karolinska Institutet

Postgraduate Mattias Svensson, Exploring mechanisms of tissue infection and Infection Biology course pathology using innovative human organotypic models, Karolinska Institutet, 2014 Training at Training course in systems analyses approaches and computational Systems Medicine advanced level modelling, organised by WUR and LG teams, for clinicians and experimentalists in the INFECT consortium, March 2018