Molecular Patterns in Acute Pancreatitis Reflect Generalizable Endotypes of the Host Response to Systemic Injury in Humans

Neyton, Lucile; Zheng, Xiaozhong; Skouras, Christos; Doeschl‐Wilson, Andrea; Gutmann, Michael U.; Uings, Iain; Rao, Francesco; Nicolas, Armel; Marshall, Craig; Wilson, Lisa-Marie; Baillie, J Kenneth; Mole, Damian J.

doi:10.1097/sla.0000000000003974

Cited by 23 publications

(18 citation statements)

References 58 publications

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“…This supports the notion that there are distinct host responses to critical illness or "treatable traits" that are independent of syndromic diagnoses such as ARDS or sepsis (35). This concept is also supported by recent work demonstrating that inflammatory sub-phenotypes can be identified in ventilated patients without ARDS (36) and in pancreatitis (37). The fact that HCA of inflammatory mediators alone provides very similar patient grouping to LCA of clinical and inflammatory data suggests that most group separation derives from inflammatory mediators that are not routinely measured in clinical practice and provides evidence that these groups are robust to the choice of clustering approach, enhancing their validity.…”

Section: Discussionsupporting

confidence: 78%

Inflammatory sub-phenotypes in sepsis: relationship to outcomes, treatment effect and transcriptomic sub-phenotypes

Antcliffe

Santhakumaran

et al. 2022

Preprint

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Rationale: Heterogeneity of sepsis limits discovery and targeting of treatments. Clustering approaches in critical illness have identified patient groups who may respond differently to therapies. These include in acute respiratory distress syndrome (ARDS) two inflammatory sub-phenotypes, using latent class analysis (LCA), and in sepsis two Sepsis Response Signatures (SRS), based on transcriptome profiling. It is unknown if inflammatory sub-phenotypes such as those identified in ARDS are present in sepsis and how sub-phenotypes defined with different techniques compare. Objectives: To identify inflammatory sub-phenotypes in sepsis using LCA and assess if these show differential treatment responses. These sub-phenotypes were compared to hierarchical clusters based on inflammatory mediators and to SRS sub-phenotypes. Methods: LCA was applied to clinical and biomarker data from two septic shock randomized trials. VANISH compared norepinephrine to vasopressin and hydrocortisone to placebo and LeoPARDS compared levosimendan to placebo. Hierarchical cluster analysis (HCA) was applied to 65, 21 and 11 inflammatory mediators measured in patients from the GAinS (n=124), VANISH (n=155) and LeoPARDS (n=484) studies. Measurements and Main Results: LCA and HCA identified a sub-phenotype of patients with high cytokine levels and worse organ dysfunction and survival, with no interaction between LCA classes and trial treatment responses. Comparison of inflammatory and transcriptomic sub-phenotypes revealed some similarities but without sufficient overlap that they are interchangeable. Conclusions: A sub-phenotype with high levels of inflammation and increased disease severity is consistently identifiable in sepsis, with similarities to that described in ARDS. There was limited overlap with the transcriptomic sub-phenotypes.

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Section: Discussionsupporting

confidence: 78%

Inflammatory sub-phenotypes in sepsis: relationship to outcomes, treatment effect and transcriptomic sub-phenotypes

Antcliffe

Santhakumaran

et al. 2022

Preprint

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“…However it is clear that COVID-19 is not a homogeneous clinical entity. Important biological differences are likely to exist between patient subgroups, as is seen in other forms of critical illness including sepsis, 1 pancreatitis, 2 , and dengue. 3 Remarkably, this is already evident for COVID-19: highly significant sub-group effects were seen in the first drug trial to demonstrate an improvement in mortality, dexamethasone.…”

Section: Introductionmentioning

confidence: 99%

Robust, reproducible clinical patterns in hospitalised patients with COVID-19

Millar

Neyton

Seth

et al. 2020

Preprint

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Severe COVID-19 is characterised by fever, cough, and dyspnoea. Symptoms affecting other organ systems have been reported. The clinical associations of different patterns of symptoms can influence diagnostic and therapeutic decision-making: for example, significant differential therapeutic effects in sub-groups of patients with different severities of respiratory failure have already been reported for the only treatment so far shown to reduce mortality in COVID-19, dexamethasone. We obtained structured clinical data on 68914 patients in the UK (the ISARIC Coronavirus Clinical Characterisation Consortium, 4C) and used a principled, unsupervised clustering approach to partition the first 33468 cases according to symptoms reported at recruitment. We validated our findings in a second group of 35446 cases recruited to ISARIC-4C, and in separate cohort of community cases. A core symptom set of fever, cough, and dyspnoea co-occurred with additional symptoms in three patterns: fatigue and confusion, diarrhoea and vomiting, or productive cough. Presentations with a single reported symptom of dyspnoea or confusion were common, and a subgroup of patients reported few or no symptoms. Patients presenting with gastrointestinal symptoms were more commonly female, had a longer duration of symptoms before presentation, and had lower 30-day mortality. Patients presenting with confusion, with or without core symptoms, were older and had a higher unadjusted mortality. Symptom clusters were highly consistent in replication analysis using a further 35446 individuals subsequently recruited to ISARIC-4C. Similar patterns were externally verified in 4445 patients from a study of self-reported symptoms of mild disease. The large scale of ISARIC-4C study enabled robust, granular discovery and replication of patient clusters. Clinical interpretation is necessary to determine which of these observations have practical utility. We propose that four patterns are usefully distinct from the core symptom groups: gastro-intestinal disease, productive cough, confusion, and pauci-symptomatic presentations. Importantly, each is associated with an in-hospital mortality which differs from that of patients with core symptoms. These observations deepen our understanding of COVID-19 and will influence clinical diagnosis, risk prediction, and future mechanistic and clinical studies.

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“…Fourth, the extent and clinical relevance of subphenotypes beyond ARDS has to be determined. The results by Kitsios et al [44] are promising as we start to suspect that the true extent of subphenotypes is much larger than assumed and not only related to hypo-or hyperinflammatory states and maybe not even limited to lung failure [51,52]. Validation in a larger cohort of patients with heterogenous risk factors for ARDS and a model to predicate its stability is needed.…”

Section: The Gaps In the Current Knowledgementioning

confidence: 95%

The discovery of biological subphenotypes in ARDS: a novel approach to targeted medicine?

et al. 2021

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The acute respiratory distress syndrome (ARDS) is a severe lung disorder with a high morbidity and mortality which affects all age groups. Despite active research with intense, ongoing attempts in developing pharmacological agents to treat ARDS, its mortality rate remains unaltered high and treatment is still only supportive. Over the years, there have been many attempts to identify meaningful subgroups likely to react differently to treatment among the heterogenous ARDS population, most of them unsuccessful. Only recently, analysis of large ARDS cohorts from randomized controlled trials have identified the presence of distinct biological subphenotypes among ARDS patients: a hypoinflammatory (or uninflamed; named P1) and a hyperinflammatory (or reactive; named P2) subphenotype have been proposed and corroborated with existing retrospective data. The hyperinflammatory subphenotyope was clearly associated with shock state, metabolic acidosis, and worse clinical outcomes. Core features of the respective subphenotypes were identified consistently in all assessed cohorts, independently of the studied population, the geographical location, the study design, or the analysis method. Additionally and clinically even more relevant treatment efficacies, as assessed retrospectively, appeared to be highly dependent on the respective subphenotype. This discovery launches a promising new approach to targeted medicine in ARDS. Even though it is now widely accepted that each ARDS subphenotype has distinct functional, biological, and mechanistic differences, there are crucial gaps in our knowledge, hindering the translation to bedside application. First of all, the underlying driving biological factors are still largely unknown, and secondly, there is currently no option for fast and easy identification of ARDS subphenotypes. This narrative review aims to summarize the evidence in biological subphenotyping in ARDS and tries to point out the current issues that will need addressing before translation of biological subohenotypes into clinical practice will be possible.

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Molecular Patterns in Acute Pancreatitis Reflect Generalizable Endotypes of the Host Response to Systemic Injury in Humans

Cited by 23 publications

References 58 publications

Inflammatory sub-phenotypes in sepsis: relationship to outcomes, treatment effect and transcriptomic sub-phenotypes

Inflammatory sub-phenotypes in sepsis: relationship to outcomes, treatment effect and transcriptomic sub-phenotypes

Robust, reproducible clinical patterns in hospitalised patients with COVID-19

The discovery of biological subphenotypes in ARDS: a novel approach to targeted medicine?

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