A novel host-proteome signature for distinguishing between acute bacterial and viral infections

Abstract

Bacterial and viral infections are often clinically indistinguishable, leading to inappropriate patient management and antibiotic misuse. Bacterial-induced host proteins such as procalcitonin, C-reactive protein (CRP), and Interleukin-6, are routinely used to support diagnosis of infection. However, their performance is negatively affected by inter-patient variability, including time from symptom onset, clinical syndrome, and pathogens. Our aim was to identify novel viral-induced host proteins that can complement bacterial-induced proteins to increase diagnostic accuracy. Initially, we conducted a bioinformatic screen to identify putative circulating host immune response proteins. The resulting 600 candidates were then quantitatively screened for diagnostic potential using blood samples from 1002 prospectively recruited patients with suspected acute infectious disease and controls with no apparent infection. For each patient, three independent physicians assigned a diagnosis based on comprehensive clinical and laboratory investigation including PCR for 21 pathogens yielding 319 bacterial, 334 viral, 112 control and 98 indeterminate diagnoses; 139 patients were excluded based on predetermined criteria. The best performing host-protein was TNF-related apoptosis-inducing ligand (TRAIL) (area under the curve [AUC] of 0.89; 95% confidence interval [CI], 0.86 to 0.91), which was consistently up-regulated in viral infected patients. We further developed a multi-protein signature using logistic-regression on half of the patients and validated it on the remaining half. The signature with the highest precision included both viral- and bacterial-induced proteins: TRAIL, Interferon gamma-induced protein-10, and CRP (AUC of 0.94; 95% CI, 0.92 to 0.96). The signature was superior to any of the individual proteins (P<0.001), as well as routinely used clinical parameters and their combinations (P<0.001). It remained robust across different physiological systems, times from symptom onset, and pathogens (AUCs 0.87-1.0). The accurate differential diagnosis provided by this novel combination of viral- and bacterial-induced proteins has the potential to improve management of patients with acute infections and reduce antibiotic misuse.

Conflict of interest statement

Competing Interests: This study was funded by MeMed. KO, AC, OB, RN, TF, LE, EB and EE are employed by MeMed. TF and KO were previously employed by MeMed. Professors PF, IP, and YR report holding equity ownership or stock-options in MeMed. Drs. IC, YD, MG, and AH were part of the clinical expert panel and received hourly fees from MeMed. Prof. RD received consulting fees from MeMed. All MeMed affiliated authors hold stock options. GD is employed by Applied Immune Technologies. Dr. GD contributed to this work in her free time without any compensation from MeMed or Applied Immune Technologies. Drs. EE and KO have two related patents: WO 2011/132086 (Signatures and determinants for distinguishing between a bacterial and viral infection and methods of use thereof) and WO 2013/117746 (Signatures and determinants for diagnosing infections and methods of use thereof). MeMed has the following related products: ImmunoXpert™ and ImmunoPoC™ (in development). This does not alter the authors’ adherence to PLOS ONE policies on sharing data and materials.

Figures

Fig 1. Study workflow.

(A) An overview of the study workflow. nBacterial, nViral and nControl represent the number of bacterial (including mixed bacterial plus viral co-infections), viral and control (with no apparent infectious disease) cases, respectively. CBC—complete blood count. (B) An overview of protein screening, model construction and validation process.

Fig 2. The proteins TRAIL, IP-10 and CRP are differentially expressed in bacterial, viral and non-infectious patients.

Box plots for TRAIL (A), IP-10 (B), and CRP (C), measured over the entire study cohort (n = 765) are presented. Red line and circle correspond to group median and average respectively; t-test p-values between bacterial and viral groups and between infectious (bacterial and viral) vs non-infectious (including healthy subjects) are depicted.

Fig 3. Signature performance is robust across different patient subgroups and outperforms lab parameters and protein biomarkers.

(A) Signature AUCs in subgroups of the study cohort (bacterial and viral) are depicted. Square size is proportional to number of patients and error bars represent 95% CI. In the Pathogens analysis, each virus was compared to bacteria affecting the same physiological system, indicated in brackets. R-respiratory, C-central nervous system, G-gastrointestinal, U-urinary, K-skin, S-systemic (i.e. non-localized). Only pathogens detected in more than 5 patients are presented. PED—pediatric emergency departments, ED—emergency departments. For subgroup definitions see Table 1 legend. (B) Performance of clinical and lab parameters as well as the best performing pair (ANC and Lym %), triplet (ANC, Lym % and Pulse), and quadruplets (ANC, Lym %, Pulse, Mono %) of parameters, the values of which were combined using a logistic regression. Comparison was done on the entire study cohort (n = 653), apart from pulse (recorded in 292 bacterial and 326 viral patients), and respiratory rate (recorded in 292 bacterial and 326 viral patients). The signature performed significantly better (P<10–15) than the optimal quadruplet. (C) The signature performed significantly better (P<10–8) than biomarkers with a well-established role in the host response to infections. For each of the select biomarkers, analysis was performed in a subgroup of the study cohort (43≤n≤154 for each analysis, a convenience sample, n depended on the strength of the signal). Error bars represent 95% CI.

Fig 4. TRAIL, IP-10 and CRP participate in different signaling pathways and exhibit complementary dynamics in response to bacterial (B) and viral (V) infections.

PAMPs—pathogen-associated molecular patterns; PGN—peptidoglycan; LPS—lipopolysaccharide.