Complementary approaches of molecular methods for the diagnosis of suspected sepsis
Abstract/Contents
- Abstract
- Many infectious diseases begin with a constellation of non-specific signs and symptoms, defying both clinical diagnosis and conventional diagnostic tests. In sepsis, which is a severe inflammatory response to infection, over 40% of patients will not have microbial diagnoses due in part to limitations in conventional diagnostic tests, and 30-50% of patients will not survive. We aimed to incorporate the complementary approaches of directly detecting microbial sequences as well as profiling the human host response to improve the diagnosis of patients with sepsis. Metagenomic shotgun Next Generation Sequencing (NGS) has the potential to detect thousands of microbial organisms. Without understanding what microbial sequences circulate in healthy individuals, however, clinicians risk misinterpreting microbial sequences in patients with infection. Our first aim was to characterize the "microbial background" in the plasma of 10 healthy volunteers using NGS with a depth of 100M reads per plasma sample and rigorous negative controls. Microbial read abundances of all bacterial species identified in healthy plasma were indistinguishable from that of negative controls. To understand if there really are microbial sequences in healthy human blood, we introduced a deliberate mucosal disturbance in healthy adults using a normal aspect of daily life: flossing. In five of ten additional healthy volunteers, we found a spike in oral-related bacterial species in plasma immediately following flossing that diminished within minutes. With rigorous negative controls and the introduction of a deliberate mucosal disturbance, we were able to observe and characterize credible microbial sequences in healthy human blood using NGS. Next, we executed a collaborative effort to integrate three complementary diagnostic approaches to specimens from 200 consecutive, unselected patients who presented to the Stanford Hospital Emergency Department with suspected sepsis: 1) direct bacterial DNA detection with NGS on plasma, 2) direct viral DNA and RNA enrichment and detection with Viral Capture Sequencing (VirCapSeq) on plasma, and 3) profiling the human host response using an 18-gene qRT-PCR assay that classifies bacterial infection, viral infection, and noninfectious causes of inflammation. Additionally, we developed a statistical model for distinguishing true signals from contamination in plasma NGS data. Assay results were reviewed for clinical relevance in a retrospective chart review by physicians with specialty training in infectious diseases. After chart review, we showed that NGS and VirCapSeq discovered clinically relevant organisms that were not detected by conventional hospital diagnostic tests in over 20 patients. Cases of interest included patients with B. hermsii, Coxsackievirus A6, and L. interrogans. Additionally, we demonstrated the potential for host response to influence diagnosis decisions, including in patients with NGS and VirCapSeq results that were difficult to interpret for clinical relevance. When utilized separately, microbial sequencing is often limited by a lack of understanding of clinical relevance, and our host response profiling is limited by a resolution that does not extend to the species level. We have shown that integrating host response profiling and microbial sequencing may synergistically enhance the utility of each assay, and ultimately, the diagnosis of patients with suspected sepsis. To advance our integrated diagnostics approach into the clinic, future studies will need to develop microbial sequence enrichment methods and curated databases for NGS, update host response signatures as new data from additional patient populations are generated and perform prospective randomized clinical trials to measure changes in diagnoses, treatment decisions, and patient outcomes.
Description
| Type of resource | text |
|---|---|
| Form | electronic resource; remote; computer; online resource |
| Extent | 1 online resource. |
| Place | California |
| Place | [Stanford, California] |
| Publisher | [Stanford University] |
| Copyright date | 2018; ©2018 |
| Publication date | 2018; 2018 |
| Issuance | monographic |
| Language | English |
Creators/Contributors
| Author | Cheng, Henry Kim |
|---|---|
| Degree supervisor | Relman, David A |
| Thesis advisor | Relman, David A |
| Thesis advisor | Altman, Russ |
| Thesis advisor | Bhatt, Ami (Ami Siddharth) |
| Degree committee member | Altman, Russ |
| Degree committee member | Bhatt, Ami (Ami Siddharth) |
| Associated with | Stanford University, Department of Bioengineering. |
Subjects
| Genre | Theses |
|---|---|
| Genre | Text |
Bibliographic information
| Statement of responsibility | Henry Kim Cheng. |
|---|---|
| Note | Submitted to the Department of Bioengineering. |
| Thesis | Thesis Ph.D. Stanford University 2018. |
| Location | electronic resource |
Access conditions
- Copyright
- © 2018 by Henry Kim Cheng
- License
- This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).
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