ReviewCurrent opinion in systems biology2017
Treatable traits and therapeutic targets: Goals for systems biology in infectious disease.
Review in Current opinion in systems biology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers, 2 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
26 citing papers in PubMed, 2 syntheses or guidelines pooled it, 59 citations in OpenAlex.
- Heterogeneity in Staphylococcus aureus Bacteraemia Clinical Trials Complicates Interpretation of Findings.The Journal of infectious diseases · 2022Pooled it
- The utility of peripheral blood leucocyte ratios as biomarkers in infectious diseases: A systematic review and meta-analysis.The Journal of infection · 2019Pooled it
- Trial
- Functional immune changes are conserved in COVID-19 and trauma patients receiving intensive care.Nature communications · 2026Article
- Corticosteroids in sepsis.Journal of intensive medicine · 2025Review
- Thromboelastometry-Based Profiling of Haemostatic Alterations in Neonatal Sepsis by Causative Pathogens.Antibiotics (Basel, Switzerland) · 2025Article
- Causal inference can lead us to modifiable mechanisms and informative archetypes in sepsis.Intensive care medicine · 2024Review
- Clinical Subphenotypes of Staphylococcus aureus Bacteremia.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2024Observational
- Distinct Clinical Endpoints of Staphylococcus aureus Bacteraemia Complicate Assessment of Outcome.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2024Observational
- Extending the 'host response' paradigm from sepsis to cardiogenic shock: evidence, limitations and opportunities.Critical care (London, England) · 2023Review
- Towards systems immunology of critical illness at scale: from single cell 'omics to digital twins.Trends in immunology · 2023Review
- Circulating N-formylmethionine and metabolic shift in critical illness: a multicohort metabolomics study.Critical care (London, England) · 2022Article
- Defining resistance and tolerance traits in Covid-19: towards a stratified medicine approach.QJM : monthly journal of the Association of Physicians · 2022Article
- ATRPred: A machine learning based tool for clinical decision making of anti-TNF treatment in rheumatoid arthritis patients.PLoS computational biology · 2022Article
- Redefining critical illness.Nature medicine · 2022Review
- Distinct clinical symptom patterns in patients hospitalised with COVID-19 in an analysis of 59,011 patients in the ISARIC-4C study.Scientific reports · 2022Article
- Multidimensional inflammatory and immunological endotypes of idiopathic focal segmental glomerulosclerosis and their association with treatment outcomes.Clinical kidney journal · 2021Article
- A metabolomic endotype of bioenergetic dysfunction predicts mortality in critically ill patients with acute respiratory failure.Scientific reports · 2021Article
- Inflammatory profiles across the spectrum of disease reveal a distinct role for GM-CSF in severe COVID-19.Science immunology · 2021Article
- Histological Evidence of Pulmonary Microthrombosis and Vasculitis in Life-Threatening Respiratory Virus Diseases.Open forum infectious diseases · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Among the many medical applications of systems biology, we contend that infectious disease is one of the most important and tractable targets. We take the view that the complexity of the immune system is an inevitable consequence of its evolution, and this complexity has frustrated reductionist efforts to develop host-directed therapies for infection. However, since hosts vary widely in susceptibility and tolerance to infection, host-directed therapies are likely to be effective, by altering the biology of a susceptible host to induce a response more similar to a host who survives. Such therapies should exert minimal selection pressure on organisms, thus greatly decreasing the probability of pathogen resistance developing. A systems medicine approach to infection has the potential to provide new solutions to old problems: to identify host traits that are potentially amenable to therapeutic intervention, and the host immune factors that could be targeted by host-directed therapies. Furthermore, undiscovered sub-groups with different responses to treatment are almost certain to exist among patients presenting with life-threatening infection, since this population is markedly clinically heterogeneous. A major driving force behind high-throughput clinical phenotyping studies is the aspiration that these subgroups, hitherto opaque to observation, may be observed in the data generated by new technologies. Subgroups of patients are unlikely to be static - serial clinical and biological phenotyping may reveal different trajectories through the pathophysiology of disease, in which different therapeutic approaches are required. We suggest there are two major goals for systems biology in infection medicine: (1) to identify subgroups of patients that share treatable features; and, (2) to integrate high-throughput data from clinical and
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.