key: cord-0036177-6xxc135t
authors: Gao, Catherine A.; Huston, John C.; Toro, Patricia Valda; Gautam, Samir; Dela Cruz, Charles S.
title: Molecular Diagnostics in Pulmonary Infections
date: 2019-09-28
journal: Precision in Pulmonary, Critical Care, and Sleep Medicine
DOI: 10.1007/978-3-030-31507-8_12
sha: 3bebe57f48489b8f15941e1fd1d7686f508ae1e8
doc_id: 36177
cord_uid: 6xxc135t

Infection of the lung parenchyma, or pneumonia, accounts for over four million deaths per year worldwide (Ferkol and Schraufnagel, Ann Am Thorac Soc 11:404–406, 2014). The condition is common, but also over-diagnosed, in part due to relatively poor laboratory and radiographic diagnostics. Indeed, we continue to rely on antiquated tools such as sputum culture and chest X-ray – the former of which lacks speed and sensitivity, and the latter specificity (Albaum et al. Chest 110:343–50, 1996). The resulting presumptive diagnoses of pneumonia lead to excessive use of empiric broad spectrum antibiotics; indeed, by some estimates, 30–70% of antibiotic prescriptions for lower respiratory tract infection are inappropriate (Kraus, PLoS One 12(3): e0174584, 2017). This approach begets microbial resistance, exposes patients to medication side effects, and puts patients at risk of potentially life-threatening complications including Clostridium difficile colitis. To improve diagnostic certainty in patients with suspected pneumonia, we must begin to consider and implement emerging technologies for efficient and accurate characterization of host responses to infection and identification of pathogens. In this chapter, we will discuss precision diagnostics already in common practice and those poised to be, and how these tools may ultimately enable personalization in the diagnosis of pneumonia.

and basic radiologic studies including chest X-ray. A dichotomous approach aimed at defining both host and pathogen is generally taken. Important host-defining historical features include any degree of immunosuppression (e.g., neutropenia, chronic corticosteroid use, malignancy, liver or kidney disease, diabetes mellitus, immunosenescence), underlying structural lung disease (e.g., obstructive lung diseases, bronchiectasis), risk of aspiration (due to altered sensorium, bulbar muscle weakness, dysphagia, esophageal disorders), and relevant exposures (i.e., travel, sick contacts, animals). Regarding the pathogen, one probes the clinical history for susceptibilities and characteristic syndromesfor example, a background of chronic alcoholism or poorly treated HIV will point to aspiration pneumonia and opportunistic infections, respectively. The patient's clinical course is also closely observed in-house for clues to an etiology, for example, rapid response to empiric antibiotics indicating infection.

While these historical subtleties will provide important guidance for the seasoned, sophisticated clinician, simpler heuristics more often determine diagnostic decision-making. In the case of pneumonia, the basic defining features include a radiographic infiltrate, systemic signs of infection (e.g., fever), and pulmonary symptoms of infection (e.g., productive cough, SOB, and occasionally pleuritic chest pain) [4] . Unfortunately, in practice, these historical features may be insufficient and potentially misleading as they may manifest in completely different disease processes, many of which do not require antibiotics. These include decompensated heart failure (SOB), pulmonary embolism (pleuritic chest pain), COPD exacerbation (SOB and cough), and even allergic rhinitis (fatigue, malaise, productive cough). Furthermore, studies have shown that history has poor interobserver reliability in the ability to record symptoms in patients with suspected pneumonia. For instance, the classic amalgam of fever, cough, tachycardia, and crackles has a sensitivity of less than 50% for the diagnosis of acute pneumonia, and no other constellation of historical and physical findings has performed better [5] .

For the most part, microbiological diagnosis of bacterial pneumonia has remained unchanged since the 1800s, as we continue to rely on traditional sputum gram stain and culture. Its longev- 1 Current approach to the workup of suspected pneumonia. This approach includes obtaining a careful clinical history and physical exam, sputum and blood cultures, and chest X-ray ity, however, belies its relatively dismal diagnostic performance. This was starkly illustrated by a landmark study in 2015, which showed that in more than 60% of the cases, no bacterial or viral organism could be identified [6] . Equally poor results are seen in patients with ventilatorassociated pneumonia, in whom only 50% of pathogens are identified [7] . In addition to poor sensitivity, traditional culture suffers from slow turn-around time, as they take on average 36-48 hours to result [8] .

Chest radiography has long been considered essential in the diagnosis of pneumonia. However, the sensitivity of chest radiography for pneumonia is less than 50%, and the positive predictive value is only 30% [9] . Furthermore, chest X-rays are of variable quality and often difficult to interpret due to underlying cardiopulmonary disease, obesity, etc. Finally, initial studies may be falsely negative, due to a phenomenon known as "blos-soming infiltrate," which has been observed in up to 7% of patients in one study [10] .

Given these many shortcomings of traditional diagnostics for pneumonia, the development of advanced tools is clearly needed. Excitingly, novel ways to diagnose pneumonia are rapidly emerging, with some already folded into practice. This section will cover these newer techniques, which run the technological gamut from protein biomarkers to whole genome sequencing and proteomic profiling. Table 12 .1 for Summary) An important component of the diagnostic armamentarium in pneumonia is a family of assays aimed at detecting bacterial antigens in bodily fluids (e.g., serum and urine). This approach is Commercially available [13, 15, 19, 27] Mass spectrometry for proteomic profiling (continued) already in widespread practice given its relatively low cost, high specificity, rapid processing times, and ready accessibility to samples. The principal disadvantage derives from the indirect detection of pathogen through an antigen rather than isolation of the organism, which is necessary for assessing antibiotic susceptibility [11, 12] . A common example is the assay for S. pneumoniae urinary antigen (the C-polysaccharide), which has a sensitivity and specificity of 72% and 96%, respectively, in patients with non-bacteremic pneumonia. Importantly, initiation of antibiotics does not impair test characteristics, as antigens remaining positive for at least 3 days after receiving appropriate therapy [13] . Another example is the urine immunoassay for detecting Legionella pneu-mophilia serogroup 1, which causes between 50% and 70% of Legionella infections. This test has 80% sensitivity and greater than 99% specificity [14] .

Polymerase Chain Reaction (RT-PCR) is a simple and rapid means of identifying bacterial and viral pathogens in the blood, sputum, and bronchoalveolar lavage (BAL) fluid in order identify causative organisms of pneumonia. Turnaround is typically on the scale of just a few hours.

Multiplex PCR allows for amplification of many nucleic acid targets within one reaction [40] [41] [42] [43] [44] [45] [46] [15], potentially enabling diagnosis of multiple pathogens simultaneously. There are numerous commercial multiplex PCR systems currently in use to diagnose pneumonia-mostly viral infection from nasopharyngeal sampling, but some bacterial pathogens as well. A downside to multiplex PCR is the potential for primer-primer interactions, which can interfere with amplification and decrease the sensitivity of the test; bead-array and microarrays are used to combat this issue [15] . A second issue is the risk of false positivity, which can stem either from the exquisite sensitivity of the test or from coincidental detection of organisms that are potentially pathogenic, but not producing disease in a given patient. Multiplex PCR has changed our basic understanding of what causes pneumonia; in a landmark trial by the EPIC team, among more than 2000 patients with radiographic evidence of pneumonia, the majority of cases with a confirmed microbiological etiology were viral, and the most frequent pathogen was rhinovirus, accounting for 9% of cases [6, 16] . It should be noted, however, that the sampling site in this study was the nasopharynx, and therefore the recovered virus may simply represent a bystander and not the pathogen responsible for the lower respiratory tract infection (LRTI). Further complicating the interpretation of viral studies is that 15% of healthy individuals carry a respiratory tract pathogen at any given time [16] .

Recent studies have highlighted the prognostic importance of assessing pathogen load, which is enabled by real-time PCR (RT-PCR). For example, confirming an elevated S. pneumoniae DNA in the serum of patients with confirmed CAP was associated with a higher mortality, need for mechanical ventilation, and risk of shock [17] . Other studies have demonstrated a dose-dependent relationship, with higher bacterial DNA loads correlating with more severe disease [18] .

In addition to defining the presence and quantity of pathogen, PCR can be used to identify genetic resistance determinants. The quintessential exam-ple is identification of the mecA gene, which confers methicillin resistance to Staphylococcus aureus species, that is, methicillin-resistant S. aureus (MRSA). Specifically, the gene encodes for penicillin-binding protein 2a, which has a decreased affinity for beta-lactam antibiotics that renders almost the entire drug class obsolete, with the exception of late-generation cephalosporins [19, 20] . Multiple iterations of tests aimed at identifying MRSA have culminated in an effective multiplex assay that recognizes four pertinent genes in only 2-6 hours [21] . These include the SCCmec-orfX junction (which indicates the Staphylococcus genus), spa (which specifies S. aureus), mecA (the resistance gene), and mecC (a mecA homolog). Additional MRSA assays have been developed; as a class, they perform well with sensitivities greater than 90% and specificities approaching 100% [19] .

PCR tests for virulence factors in common bacterial LRTI pathogens such as S. pneumoniae and Moraxella catarrhalis have been tested, but with mixed success, mainly due to the frequent colonization of these organisms in the upper respiratory tract [22] . For example, tests for the pneumolysin gene (a highly cytotoxic and inflammatory virulence factor for S. pneumoniae) in lower respiratory samples have shown inadequate sensitivity and specificity, and therefore have not been adopted into clinical practice [23] .

An area of increasing interest is the rapid diagnosis of active Mycobacterium tuberculosis (MTb) infection. For decades, clinicians have relied on sputum acid-fast bacilli smears and culture, which have numerous drawbacks. First, the turnaround time is quite long-often taking months to result, resulting in delayed initiation of antimicrobials, and prolonged isolation of suspected patients. Second, sensitivity is quite poor, with detection rates estimated at 45-80% [24, 25] . Consequently, invasive testing may be necessary to make the diagnosis, including bronchoscopy and biopsy.

To address these issues, PCR assays are now being used in clinical practice. This technology can help diagnose pulmonary TB in 24-48 hours [26] , and it has further utility in distinguishing between MTb and non-tuberculous mycobacteria on positive AFB smears, with a positive predictive value of over 95%. Although still less sensitive than culture, the PCR test can detect MTb at a concentration of 1-10 organisms per milliliter [27] [28] [29] . This feature enables detection of MTb in patients with a negative AFB smear, with approximate 50-80% accuracy [30] . PCR tests can also detect resistance against drugs including rifampin or isoniazid with high sensitivity and specificity, can be completed in only 2 hours, and are highly sensitive and specific [31] .

Matrix-assisted laser desorption ionization time of flight mass spectrometry (MALDI-TOF MS) is a technique with the capacity to identify pathogens through recognition of unique proteomic profiles [32] . In contrast to traditional cultures, which take 36-48 hours to result, MALDI-TOF MS takes minutes, with a relatively low cost per sample [33] . In addition to pathogen identification, this methodology can also detect antibiotic resistance, for instance through recognition of specific proteins such as PBP2a in S. aureus, which indicates MRSA [34] .

Another use of mass spectrometry is in the characterization of volatile organic compounds (VOCs)so-called "breathomics," which has been hailed as a promising noninvasive method of sampling the respiratory tract [35] . Exhaled air contains numerous VOCs, including metabolites related to both host and pathogen. Select VOCs have been shown to be associated with pneumonia. As an example, one study identified 12 compounds that could correctly diagnose VAP with a sensitivity and specificity of 75% and 73% respectively [36] , but concerns have been raised regarding the risk of bias in this and other early investigations.

Whole genome sequencing (WGS) and 16S rRNA gene sequencing are high-output tech-niques that aim to comprehensively characterize the respiratory microbiome in a high-throughput manner.

16S rRNA sequencing depends on the use of nucleic acid primers against highly conserved sequences of ribosomal RNA. This allows identification of a bacterial species and some quantitative data on the relative abundance of the pathogen. Although rapid and relatively low in cost (per sample), it lacks the ability to detect genetic material outside of the ribosome, leaving resistance and virulence genes unrecognized.

A study using 16S rRNA sequencing on bronchial aspirates of mechanically ventilated patients with suspected VAP showed promising results. Compared to traditional bronchial aspirate cultures, 16S rRNA sequencing matched the culture result in 85% of cases, but time to identification was significantly shorter in the 16S group [37, 38] , which is meaningful since early antibiotics (within 48 hours) are known to reduce mortality in patients with VAP [39] .

Contrary to 16S, WGS fully sequences the respiratory microbiome, and as such can report on the presence of resistance and virulence genes [40, 41] . As discussed above, PCR-based assays have the capability to identify MTb and rifampin resistance in just 2 hours, but mutations outside of the probed sequence are not identified. WGS allows recognition of these, although the relative significance of such mutations may not be known [42, 43] . With time, this issue should be addressed with genome-wide association studies (GWAS), which aim to delineate a catalog of resistance loci [48] [49] [50] . This will serve as a reference for clinical samples and may help in creating models that predict future resistance to antimicrobials.

The granularity that WGS provides can also be used to trace transmission patterns of infection. This idea was exploited to track an outbreak of Human Adenovirus-7 (HAdV-7) causing ARDS at military training bases in Hubei Province, China. WGS helped identify a "super-spreader" who was not quarantined and had prolonged viral shedding [46] . Additionally, WGS can offer basic insight into the dysbiosis that often accompanies lung diseases such as chronic obstructive pulmonary disease (COPD). This is exemplified by a study examining rhinovirus-induced exacerbation, which demonstrated a significant rise in the overall bacterial burden [47] .

One of the recognized weaknesses of WGS is target specificity. Though advanced post hoc processing methods allow for elimination of host genetic signal, there is no way to identify colonizing nonpathogenic or commensal organisms [44] . Additional disadvantages of meta-omics in general include the risk of contamination, inability to discriminate live from dead microbial DNA, and cost.

Host Response Biomarkers (See Table 12 .

In general, clinicians are alerted to infection by the host's inflammatory response to the pathogen. Observable manifestations of lung inflammation include classic systemic signs such as fever, local symptoms such as cough and purulent sputum, and radiographic evidence of neu- [71] [72] [73] [74] (continued) trophilic infiltrates. Inflammatory diagnostics have progressed immensely from simple leukocyte counts to serum biomarkers, such as C-reactive protein and procalcitonin, and more recently a wave of new biomarkers and genomic techniques. The sensitivity and specificity of these newer techniques vastly outstrips that of traditional pneumonia diagnostics; their implementation in clinical practice promises to improve not only diagnosis of infection, but also prediction of deterioration and tapering of therapy. These improvements should help to limit antibiotic overuse-one of the major unsolved problems in pneumonia.

C-reactive protein (CRP) is an early acute phase reactant that is synthesized in the liver in response to IL-6 secreted by monocytes and macrophages. The "C" in its name derives from its reaction with the C-polysaccharide of S. pneumoniae as the first biomarker for pneumococcal pneumonia [51, 52] . It is highly sensitive, but rather nonspecific as the level rises in most inflammatory conditions, and therefore must be used judiciously in the context of bacterial pneumonia. Interestingly, it is especially elevated in cases of Legionella infection compared with other biomarkers [53] . Given its widespread availability, it has been validated as a point-of-care (POC) lab test to guide antibiotic use in primary care [54] , and levels have been correlated to disease severity and complications in community-acquired pneumonia [55] . Used with other inflammatory marker profiles, CRP may be used to pinpoint the time of infection: In patients who present within 3 days of disease onset, CRP was low, but in patients who present after more than 3 days of symptom onset, CRP levels rose significantly [56] .

Procalcitonin is the prohormone of calcitonin, which is expressed mostly in the C-cells of the thyroid during health. In response to pathogenassociated molecular patterns (PAMPs), damageassociated molecular patterns (DAMPs), and inflammatory cytokines during infection, however, the expression of procalcitonin is upregulated in virtually every tissue and cell type [57] . Importantly, its expression is suppressed by type I interferons generated during viral infection, improving its specificity for bacterial etiologies. Serum levels elevate rapidly (within ~4 hours) and peak around 24-48 hours, making it an excellent early marker for infection [58] . Compared with CRP, it has been shown to be more sensitive and specific in identifying bacterial infections [59] . Also, unlike other infectious markers, its level is neither decreased (as is CRP) nor increased (as is white blood cell count) by the use of steroids [60] . An important drawback, however, is its lack of sensitivity for atypical infections such as Legionella, Mycoplasma, and Chlamydophilia [61] .

First described as a biomarker for sepsis in 1993 [62] , procalcitonin has since been validated repeatedly as not only a marker of bacterial infection, but also a correlate of severity in sepsis and septic shock [63] . A meta-analysis of 21 studies including over 6000 patients showed that an elevated procalcitonin level was a risk factor for mortality (RR 4.38) [64] . A review of 1770 patients with CAP showed that procalcitonin levels had an approximately linear association with the need for invasive respiratory or vasopressor support; at levels >10 ng/mL, the risk was 22.4% compared to 4% in patients with procalcitonin <0.05 ng/mL [65] .

Procalcitonin also serves as an important component of antimicrobial stewardship algorithms, helping to guide the decision to withhold antibiotics from low-risk patients and to abbreviate treatment courses in high-risk patients [66] [67] [68] . The latter is enabled by the progressive reduction in procalcitonin that accompanies successful treatment of infection; when its value drops to 80-90% (depending on the study) antibiotics can be stopped. Although numerous reports have shown the efficacy of procalcitonin-guided prescribing strategies in decreasing antibiotic usage, questions have lingered regarding safety. To address these questions, Schuetz et al. conducted a comprehensive meta-analysis, including studies across a variety of clinical settings including primary care, emergency departments, and the ICU. The study not only confirmed dramatic reductions in antibiotic exposure and safety, but in fact showed that procalcitonin-guided strategies improve clinical outcomes in terms of mortality and treatment failure [69] .

Conflicting data, however, have been presented. Most prominently, a study in 1656 patients randomized to procalcitonin-guided versus usual antibiotic care in the emergency department failed to demonstrate even a reduction in antibiotic exposure [70] . These differences may have arisen due to heightened awareness of proper antibiotic prescribing practices and/or the relatively low acuity of the patients in the trial. Further studies will be necessary to clarify these issues.

Overall, procalcitonin has clear potential to aid in the diagnosis and management of pneumonia, but, like any biomarker, it has important limitations. These include its elevation in renal failure and relative nonspecificity for acute inflamma-tion, including that related to cancer and tissue necrosis. Consequently, its usefulness will depend largely on the clinical setting (e.g., primary care vs. ICU) as well as the provider's knowledge of its biology and ability to integrate its significance within the larger clinical picture.

Inflammatory cytokines (IL-1, IL-6, IL-8, TNFα, among others) are significantly higher in patients with severe pneumonia than in those with milder disease, and can predict mortality in hospitalized patients with CAP [71] . For example, a 27-component panel was followed in 247 patients, with IL-6, IL-8, and MIP-1β showing a strong association with disease severity and adverse short-term outcome [72] . The levels rise and fall rapidly though, on the order of hours, and are usually highest at presentation [73] . A study of 1886 patients with CAP demonstrated an elevation of cytokine levels in 82% of patients, but the overall response was heterogeneous and no pattern clearly identified severe sepsis [74] . Though scientifically sensical, the optimal implementation of these cytokine panels in clinical practice remains unclear.

An array of novel biomarkers for CAP are now emerging, including pro-atrial natriuretic peptide (pro-ANP), C-terminal pro-vasopressin (copeptin or pro-VNP), mid-regional pro-adrenomedullin (MR-proADM), and others. These have shown advantages compared to CRP and PCT but have not yet been introduced into widespread clinical practice.

Pro-ANP is elevated in lower respiratory tract infections during CAP [75] , and has the potential to predict both 30-day and 180-day mortality [76] . A study of 549 patients with mild CAP showed that a single pro-ANP measurement was more accurate than CRP and PCT in predicting need for admission [77] . Exciting data from the CAPNETZ network indicate that pro-ANP and pro-VNP are significantly higher in fatal CAP and possess superior AUCs to those of WBC, CURB-65, CRP, and procalcitonin [78] .

Copeptin has been shown likewise to be higher in patients with pneumonia before antibiotic treatment [79] ; it also has been shown in a study of pediatric CAP to be significantly higher in pneumonia cases and non-survivors [80] .

MR-proADM has been shown to be predictive of complications and mortality in patients with CAP in a meta-analysis of eight studies with 4119 patients [81] . A systematic review of 12 studies similarly found that elevated MR-proADM was highly associated with an increase in short term mortality (OR 6.8) and complications (OR 5.0) [82] .

Alveolar pentraxin 3 (PTX3), an acute-phase mediator produced by lung cells, represents another promising biomarker for pneumonia. An examination of 82 intubated patients' BAL fluid showed that elevated PTX3 levels were able to identify bacterial pneumonia [83] . A subsequent nested case-control study found that a 2.56 ng/ mL breakpoint had superb sensitivity and specificity for the diagnosis of VAP: 85% and 86%, respectively [84] . Finally, kallistatin, an antiinflammatory kallikrein inhibitor, has been reported to be significantly consumed in severe CAP patients, and low levels early in admission are associated with increased mortality [85] .

It would be of great clinical value to have methods for predicting which patients will develop severe respiratory disease in response to a given pathogen and who will have milder courses, as at-risk patients can be given more prompt and aggressive care. A number of genetic analyses have been undertaken to address this need. Notable associations have been made with polymorphisms in pro-inflammatory factors such as TNF-α, IL-6, and lymphotoxin alpha (LTA) [86] . Additionally, several single nucleotide polymorphisms (SNPs) in immune-related genes have been shown to confer either resistance or susceptibility to Streptococcal infection; for instance, mutations in the toll-interleukin 1 receptor domain-containing adaptor protein (TIRAP) and the NF-kappaB pathway have been identified as protective [87] .

Rautanen and the ESICM/ECCRN group evaluated over 2500 patients and found 11 loci that correlated significantly with 28-day survival in ICU patients with severe CAP [88] . They further found a SNP in the FER gene to be highly correlated with survival; mortality was 9.5% in patients with the CC genotype, 15.2% in the TC genotype patients, and 25.3% in the TT genotype patients [88] . A follow-up study looked at the FER polymorphism status in 441 patients with ARDS in the ICU, and again found that the TT genotype patients had higher mortality, with a 90-day hazard ratio of 4.62 [89] .

In the past decade, significant efforts have been made to identify gene expression signatures that accurately identify host response to infection. With the increasing availability of transcriptomic analysis, it may soon be feasible to obtain expression profiles in high-risk patients to aid in the diagnosis and management of pneumonia.

Several groups have assembled gene expression microarrays to diagnose acute infections, with the specific goal of distinguishing viral versus bacterial pneumonia [90, 91] . In 2007, Ramilo and colleagues examined 131 peripheral blood samples and characterized 35 genes able to discriminate bacterial versus viral pneumonia with 95% accuracy [92] . Suarez et al. analyzed whole blood transcriptional data from 118 patients with lower respiratory tract infections and identified 3376 genes associated with bacterial infection and 2391 with viral infections. Using the K-nearest neighbors' algorithm, they identified a parsimonious ten-gene classifier that could distinguish between the two with 95% sensitivity and 92% specificity, greatly outperforming procalcitonin [93] . Scicluna's team looked at blood microarray analysis of critically ill patients with and without CAP and defined a 78-gene signature for CAP [94] . They narrowed this down to a ratio of the FAIM3 (fas apoptotic inhibitory molecule 3) and PLAC8 (placenta specific 8) gene expression, leading to area under curve of 0.845, again outperforming procalcitonin [94] .

Sweeney and Khatri have derived a set of seven genes that discriminate bacterial versus viral infections, which they validated in 30 independent cohorts [95] . Tsalik and his group looked at peripheral whole blood gene expression in 273 subjects with community onset respiratory infections, and used sparse logistic regression to develop classifiers for bacterial infections (71 probes) versus viral infections (33 probes) and noninfectious causes (26 probes); the overall accuracy was higher than that of procalcitonin and also three other published classifiers of bacterial versus viral infections [96] .

While the foregoing studies require the use of multi-gene assays, Tang and colleagues recently used genomic analysis of 1071 patients to find a single gene capable of identifying viral infection, interferon alpha inducible protein 27 (IFI27) [97] . They demonstrated a considerable upregulation at the transcript level in patients with influenza as opposed to bacterial pneumonia, likely due to the specific activation of interferon signaling pathways downstream of pathogen recognition receptors selective for virus.

With regards to predicting host response to lung infections, there have been a number of recent advances. Meijas et al. looked at a cohort of infants hospitalized with RSV, HRV, and influenza and identified a score calculated from RSV transcriptional profiles that correlated with outcomes including length of hospitalization, duration of supplementation oxygen, and clinical disease severity score-an important example of the potential utility of transcriptomics in predicting the need for intensive care [98] . Banchereau et al. characterized whole blood transcriptional profiles of patients hospitalized with community-acquired Staphylococcus aureus infection and were able to generate a score they called molecular distance to health (MDTH), which correlated with elevated inflammatory markers, longer duration of hospitalization, and more severe disease [99] .

A transcriptomic analysis of peripheral leukocytes from 265 ICU patients with sepsis from CAP found two distinct sepsis response signa-tures "SRS", which they categorized as "SRS1" and "SRS2". Over 3000 genes were noted to be differentially expressed between the groups, with 2260 downregulated in the SRS1 group. SRS1, which had lower expression of Toll-like receptor (TLR) signals, downregulation of human leukocyte antigen (HLA) class II genes, and decreased T-cell activation, was associated with a higher 14-day mortality than SRS2. They distilled out a set of just seven genes to classify patients into SRS1 or SRS2 [100] . Schaack et al. drew from over 900 microarray samples from public repositories from patients with sepsis and identified two clusters of patients according to global blood transcriptomes; these clusters exhibited expression of genes demonstrating a loss of monocyte and T-cell function, indicating a group of patients with higher immunosuppression that may need more aggressive care [101] .

Metabolomics is an emerging area of investigation aimed at characterizing the cellular metabolic changes during infection [102] . Groups have found metabolic patterns specific to sepsis, some metabolites that potentially can identify severe versus less severe pneumonia, and certain metabolites that may predict poorer outcomes. For instance, To's group found that 13 lipid metabolites could discriminate between CAP and non-CAP cases with an AUC of >0.8, and that trihexosylceramide levels were higher in fatal cases [103] . A separate group used 1D 1H nuclear magnetic resonance (NMR) spectra to generate metabolic profiles from 15 patients with pneumonia; comparing the metabolic profiles using Orthogonal Partial Least Squares Discriminant Analysis (OPLS-DA) they were able to differentiate cases of VAP from those without [104] . Finally, Ning et al. analyzed 119 patients with CAP and found markedly different metabolic patterns as assessed by liquid chromatographymass spectrometry (LC-MS) compared with control patients [105] . Sphinganine, p-Cresol sulfate, and DHEA-S were significantly lower, and in combination with lactate, this panel could dis-criminate severe CAP from non-severe CAP with an impressive AUC of 0.911, better than the CURB-65, PSI, and APACHE II scores [105] .

Numerous studies have shown that the location of specimen sampling importantly influences diagnostic yield. While the most common tests are those tested in the serum, sputum and airway fluid (BAL, non-bronchoscopic BAL, tracheal aspirates) should also be evaluated. A study of BAL fluid from 47 patients found that median WBC count and neutrophil percentages were significantly higher in bacterial than viral pneumonia. Furthermore, BAL WBC count was an independent predictor of bacterial pneumonia, and when combined with procalcitonin or CRP, the composite reached a sensitivity of 95.8% and a specificity of 95.7% [106] . Importantly, the utility of BAL leukocytosis extends to immunocompromised patients as well, as demonstrated by a study of 107 patients with either hematological malignancy or solid organ transplant. This showed that BAL fluid neutrophil percentage had the highest AUC to predict bacterial infection; in contrast, neither the presence of infiltrates nor leukocyte count was helpful in diagnosing bacterial infection [107] .

Interestingly, a discordant inflammatory response has been demonstrated in blood versus sputum in patients with severe CAP. Neutrophil respiratory burst was increased as expected in the blood, but significantly diminished in the lung, indicating either a local failure of inflammatory response or possibly an adaptive immunosuppression to protect lung tissue from immunopathology [108] .

As discussed above, breathomics, or measurement of (VOCs) in exhaled breath, is a noninvasive means of sampling host metabolites. Promising early studies have shown discernable metabolomic changes in pneumonia due inflammation and oxidative stress [109] ; further work will be necessary to understand the potential clinical utility of such methods.

With ongoing advances in molecular and biochemical methods, we aim for an ever-greater level of diagnostic detail, with the ultimate goal of reliably diagnosing causative pathogens in pneumonia, as well as predicting decompensations, complications, and resolution. In addition to traditional clinical evaluation, we now employ powerful diagnostic tools to evaluate both host and pathogen including biomarkers and PCR; the advent of technologies such as mass spectroscopy and WGS promises further improvements in diagnostic clarity. In addition, the impressive (but potentially overwhelming) amount of data available through electronic medical records and multi-omics modalities including sequencing data may necessitate machine learning algo-rithms to further optimize pneumonia diagnosis and management.

Incorporating these techniques, we can reenvision the case presented at the outset of this chapter (see Fig. 12 .2). The same 45-year-old patient presents with fever and cough. WGS is performed on a sputum sample and reveals influenza B infection with no bacterial superinfection. Antibiotics are withheld, and he initially improves on neuraminidase inhibitor therapy. However, 5 days later he has recurring fevers and worsening hypoxia. Analysis of his exhaled volatile compounds reveals a profile consistent with S. aureus pneumonia; mass spectrometry analysis of a sputum sample rapidly confirms S. aureus infection and further identifies mecA, indicating MRSA. Vancomycin is promptly added, and the team considers transferring him to a higher level Using bacterial pneumonia as an example, pathogens access alveoli and trigger immune responses through the elaboration of pathogen associated molecular patterns (PAMPs), which activate pathogen recognition receptors (PRRs) and production of inflammatory cytokines. Pathogens also damage lung tissue directly, in some cases leading to acute respiratory distress syndrome (ARDS). In general, procalcitonin is secreted during bacterial and not viral infections. Bacterial lung infections can also result in systemic inflammation characterized by acute phase response and production of C-reactive protein (CRP), fever, multiorgan failure, vasoplegia, and vascular permeability that presents as sepsis of care for closer monitoring. However, his pro-ANP and MR-pro-ADM are not elevated, and onsite transcriptomic analysis of peripheral leukocytes does not show an SRS1 pattern, reassuring the team that he is not a high risk for decompensating. He is safely sent to the general medicine floor, continues to improve, and is discharged home after his short hospitalization.

Several obstacles stand in the way of realizing this level of diagnostic precision and therapeutic sophistication, however. For instance, the costs associated with many of these tests are prohibitive, especially in smaller medical centers. Therefore, technological improvements will be necessary to decrease operating costs while clinical studies must be performed to identify those patients best suited for such advanced and more expensive diagnostics. Basic and translational studies are also needed to more fully elucidate the pathophysiology and natural history of pneumonia to inform future clinical studies and further explain existing data. Ultimately, a multidisciplinary approach involving clinical research, basic biology, chemical analysis, assay optimization, and computational science are needed to usher in an era where the potentially transformative technologies described above are used routinely in the diagnosis and management of pneumonia.

• Traditional methods for the diagnosis and characterization of pulmonary infections are inadequate. • The use of advanced molecular diagnostics such as newer biomarkers, multiplex PCR, mass spectrometry, metagenomics, and metataxonomics can improve clinical precision in the diagnosis of pneumonia. • More studies involving biomarkers and multi-omics approaches are needed to help better characterize the host response to pulmonary infections.

• Incorporation of advanced tools for diagnostics and host response measurements will likely enable personalization of our management of pneumonia and improve outcomes.

The global burden of respiratory disease

Interobserver reliability of the chest radiograph in community-acquired pneumonia

Antibiotic prescribing for acute lower respiratory tract infections (LRTI) -guideline adherence in the German primary care setting: an analysis of routine data

Infectious Diseases Society of America/American Thoracic Society consensus guidelines on the management of community-acquired pneumonia in adults

Does this patient have community-acquired pneumonia? Diagnosing pneumonia by history and physical examination

Community-acquired pneumonia requiring hospitalization among U.S. adults

A 2015 update on ventilatorassociated pneumonia: new insights on its prevention, diagnosis, and treatment

A systematic review of matrix-assisted laser desorption/ionisation time-of-flight mass spectrometry compared to routine microbiological methods for the time taken to identify microbial organisms from positive blood cultures

High discordance of chest x-ray and computed tomography for detection of pulmonary opacities in ED patients: implications for diagnosing pneumonia

Patients admitted to hospital with suspected pneumonia and normal chest radiographs: epidemiology, microbiology, and outcomes

Impact of rapid urine antigen tests to determine the etiology of community-acquired pneumonia in adults

Current and potential usefulness of pneumococcal urinary antigen detection in hospitalized patients with community-acquired pneumonia to guide antimicrobial therapy

Influence of Antibiotics on the Detection of Bacteria by Culture-Based and Culture-Independent Diagnostic Tests in Patients Hospitalized With Community-Acquired Pneumonia

Clinical utility of a Legionella pneumophila urinary antigen test in a large university teaching hospital

an automated nested multiplex PCR system for multi-pathogen detection: development and application to respiratory tract infection

Identification of respiratory viruses in asymptomatic subjects: asymptomatic respiratory viral infections

Severity of pneumococcal pneumonia associated with genomic bacterial load

Association between pneumococcal load and disease severity in adults with pneumonia

Evaluation of multiple real-time PCR tests on nasal samples in a large MRSA surveillance program

Mechanisms of methicillin resistance in Staphylococcus aureus

Rapid diagnostics for methicillinresistant Staphylococcus aureus

Quantitative detection of Streptococcus pneumoniae, Haemophilus influenzae, and Moraxella catarrhalis in lower respiratory tract samples by real-time PCR

Is quantitative PCR for the pneumolysin (ply) gene useful for detection of pneumococcal lower respiratory tract infection?

Sputum processing methods to improve the sensitivity of smear microscopy for tuberculosis: a systematic review

This statement was endorsed by the Council of the Infectious Disease Society of America

The health-system benefits and costeffectiveness of using Mycobacterium tuberculosis direct nucleic acid amplification testing to diagnose tuberculosis disease in the United States

Role of clinical judgment in the application of a nucleic acid amplification test for the rapid diagnosis of pulmonary tuberculosis

The interpretation of nucleic acid amplification tests for tuberculosis: do rapid tests change treatment decisions?

The role of clinical suspicion in evaluating a new diagnostic test for active tuberculosis: results of a multicenter prospective trial

Updated guidelines for the use of nucleic acid amplification tests in the diagnosis of tuberculosis

Availability of an assay for detecting Mycobacterium tuberculosis, including rifampin-resistant strains, and considerations for its use -United States

MALDI-TOF mass spectrometry technology for detecting biomarkers of antimicrobial resistance: current achievements and future perspectives

Matrix assisted laser desorption time of flight mass spectrometry (MALDI-TOF MS) in clinical microbiology

Rapid detection of antibiotic resistance based on mass spectrometry and stable isotopes

The potential role of exhaled breath analysis in the diagnostic process of pneumonia-a systematic review

Analysis of volatile organic compounds in exhaled breath to diagnose ventilatorassociated pneumonia

Single-molecule long-read 16S sequencing to characterize the lung microbiome from mechanically ventilated patients with suspected pneumonia

16S pan-bacterial PCR can accurately identify patients with ventilator-associated pneumonia

Impact of appropriateness of initial antibiotic therapy on the outcome of ventilatorassociated pneumonia

Whole-genome sequencing for surveillance of invasive pneumococcal diseases in Ontario, Canada: rapid prediction of genotype, antibiotic resistance and characterization of emerging serotype 22F

The role of whole genome sequencing in antimicrobial susceptibility testing of bacteria: report from the EUCAST Subcommittee

False-positive rifampin resistant results with Xpert MTB/RIF version 4 assay in clinical samples with a low bacterial load

Direct whole-genome sequencing of sputum accurately identifies drug-resistant mycobacterium tuberculosis faster than MGIT culture sequencing

Same-day diagnostic and surveillance data for tuberculosis via whole-genome sequencing of direct respiratory samples

Mixed-strain mycobacterium tuberculosis infections and the implications for tuberculosis treatment and control

Whole-genome sequencing for tracing the transmission link between two ARD outbreaks caused by a novel HAdV serotype 7 variant

Outgrowth of the bacterial airway microbiome after rhinovirus exacerbation of chronic obstructive pulmonary disease

Genome-wide analysis of multi-and extensively drug-resistant Mycobacterium tuberculosis

Validation of β-lactam minimum inhibitory concentration predictions for pneumococcal isolates with newly encountered penicillin binding protein (PBP) sequences

Developing an in silico minimum inhibitory concentration panel test for Klebsiella pneumoniae

The occurrence during acute infections of a protein not normally present in the blood : i. Distribution of the reactive protein in patients' sera and the effect of calcium on the flocculation reaction with c polysaccharide of pneumococcus

Serological reactions in pneumonia with a non-protein somatic fraction of pneumococcus

C-reactive protein levels in community-acquired pneumonia

Biomarkers as point-of-care tests to guide prescription of antibiotics in patients with acute respiratory infections in primary care

Utility of C-reactive protein in assessing the disease severity and complications of community-acquired pneumonia

Initial inflammatory profile in community-acquired pneumonia depends on time since onset of symptoms

Ubiquitous expression of the calcitonin-I gene in multiple tissues in response to Sepsis1

Update on procalcitonin measurements

Procalcitonin as a biomarker of infectious diseases

New approaches to sepsis: molecular diagnostics and biomarkers

Usefulness of procalcitonin to differentiate typical from atypical communityacquired pneumonia

High serum procalcitonin concentrations in patients with sepsis and infection

Biomarkers in the critically ill patient: procalcitonin

Prognostic value of procalcitonin in pneumonia: a systematic review and meta-analysis

Procalcitonin as an early marker of the need for invasive respiratory or vasopressor support in adults with community-acquired pneumonia

Meta-analysis and systematic review of procalcitonin-guided therapy in respiratory tract infections

Procalcitonin-guided antibiotic therapy and hospitalisation in patients with lower respiratory tract infections: the prohosp study

Use of procalcitonin to reduce patients' exposure to antibiotics in intensive care units (PRORATA trial): a multicentre randomised controlled trial

Effect of procalcitonin-guided antibiotic treatment on mortality in acute respiratory infections: a patient level meta-analysis

Procalcitonin-guided use of antibiotics for lower respiratory tract infection

Biomarkers improve mortality prediction by prognostic scales in community-acquired pneumonia

Cytokine responses, microbial aetiology and short-term outcome in communityacquired pneumonia

Systemic cytokine response in patients with community-acquired pneumonia

Understanding the inflammatory cytokine response in pneumonia and sepsis: results of the Genetic and Inflammatory Markers of Sepsis (GenIMS) Study

Circulating levels of pro-atrial natriuretic peptide in lower respiratory tract infections

MR-pro-atrial natriuretic peptide (MR-proANP) predicts short-and long-term outcomes in respiratory tract infections: a prospective validation study

Accuracy of C-reactive protein, procalcitonin, and mid-regional pro-atrial natriuretic peptide to guide site of care of community-acquired pneumonia

CAPNETZ-communityacquired pneumonia competence network

C-terminal provasopressin (copeptin) in patients with community-acquired pneumoniainfluence of antibiotic pre-treatment: results from the German competence network CAPNETZ

Predictive value of copeptin as a severity marker of community-acquired pneumonia

Prognostic value of mid-regional proadrenomedullin (MR-proADM) in patients with community-acquired pneumonia: a systematic review and meta-analysis

Midregional proadrenomedullin for prognosis in community-acquired pneumonia: a systematic review

Alveolar pentraxin 3 as an early marker of microbiologically confirmed pneumonia: a threshold-finding prospective observational study

Sequential Measurements of Pentraxin 3 Serum Levels in Patients with Ventilator-Associated Pneumonia: A Nested Case-Control Study

Plasma kallistatin levels in patients with severe community-acquired pneumonia

Genetic predisposition to respiratory infection and sepsis

A Mal functional variant is associated with protection against invasive pneumococcal disease, bacteremia, malaria and tuberculosis

Genome-wide association study of survival from sepsis due to pneumonia: an observational cohort study

The FER rs4957796 TT genotype is associated with unfavorable 90-day survival in Caucasian patients with severe ARDS due to pneumonia

Unbiased detection of respiratory viruses by use of RNA sequencing-based metagenomics: a systematic comparison to a commercial PCR panel

Viral pathogen detection by metagenomics and pan-viral group polymerase chain reaction in children with pneumonia lacking identifiable etiology

Gene expression patterns in blood leukocytes discriminate patients with acute infections

Superiority of transcriptional profiling over procalcitonin for distinguishing bacterial from viral lower respiratory tract infections in hospitalized adults

A molecular biomarker to diagnose community-acquired pneumonia on intensive care unit admission

Robust classification of bacterial and viral infections via integrated host gene expression diagnostics

Host gene expression classifiers diagnose acute respiratory illness etiology

A novel immune biomarker discriminates between influenza and bacteria in patients with suspected respiratory infection

Whole blood gene expression profiles to assess pathogenesis and disease severity in infants with respiratory syncytial virus infection

Host immune transcriptional profiles reflect the variability in clinical disease manifestations in patients with Staphylococcus aureus infections

Genomic landscape of the individual host response and outcomes in sepsis: a prospective cohort study

The immunosuppressive face of sepsis early on intensive care unit-a large-scale microarray meta-analysis

Severe community-acquired pneumonia: optimal management

Lipid metabolites as potential diagnostic and prognostic biomarkers for acute community acquired pneumonia

Metabolic profiling in patients with pneumonia on intensive care

Metabolic profiles in communityacquired pneumonia: developing assessment tools for disease severity

Usefulness of cellular analysis of bronchoalveolar lavage fluid for predicting the etiology of pneumonia in critically ill patients

BAL neutrophils, serum procalcitonin, and C-reactive protein to predict bacterial infection in the immunocompromised host

Contrasting inflammatory responses in severe and non-severe community-acquired pneumonia

The versatile use of exhaled volatile organic compounds in human health and disease