Tropheryma whipplei in Pulmonary Infections: Microbial Competition with Streptococcus pneumoniae and Pseudomonas aeruginosa, Association with Anemia, and Lack of Benefit from Targeted Therapy - A Retrospective Cohort Study

Tropheryma whipplei in Pulmonary Infections: Microbial Competition with Streptococcus pneumoniae and Pseudomonas aeruginosa, Association with Anemia, and Lack of Benefit from Targeted Therapy - A Retrospective Cohort Study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Tropheryma whipplei in Pulmonary Infections: Microbial Competition with Streptococcus pneumoniae and Pseudomonas aeruginosa, Association with Anemia, and Lack of Benefit from Targeted Therapy - A Retrospective Cohort Study Zhili Wu, Xiaoli Luo, Cailin Zhao, Jing Xu, Mingdong HU, Xiaolong Chen This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9406285/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 7 You are reading this latest preprint version Abstract Objective Tropheryma whipplei (TW), the pathogen of Whipple's disease, has recently been identified as potentially pathogenic in respiratory infections through metagenomic next-generation sequencing (mNGS) technology. However, its clinical significance in lung infections is still unclear due to its frequent co-detection with other pathogens and the lack of diagnostic standards. Methods We retrospectively analyzed 74 patients with TW-positive bronchoalveolar lavage fluid (BALF) detected by mNGS from January 2018 to December 2022. Over the study period, a total of 1,543 BALF samples were subjected to mNGS analysis, resulting in a detection rate of 4.79% for TW. Clinical manifestations, imaging features, and microbiological data (including TW sequence quantification and co-pathogen profiles) were systematically evaluated. Treatment efficacy was assessed via follow-up CT in 41 patients. Results The cohort (mean age 55 years, 47.3% male) predominantly presented with cough (71.6%), expectoration (59.5%), and dyspnea (31.1%). Characteristic CT findings included patchy opacities (74.3%) and multiple nodules (71.6%). Laboratory abnormalities included anemia (58.1%), hypoalbuminemia (51.4%), and elevated inflammatory markers (CRP 53.2%, ESR 62.5%). TW was the sole pathogen in only 23.0% of cases, with common bacterial (64.9%) and fungal (25.7%) co-infections. Notably, TW sequence counts were significantly lower when co-infected with Streptococcus pneumoniae or Pseudomonas aeruginosa (P = 0.038) and were significantly higher in anemic patients (P = 0.045). Targeted anti-TW therapy did not significantly improve radiographic outcomes in this cohort (P = 0.295). Conclusion This study suggests that respiratory TW often represents co-infection rather than primary pathogenicity. The bacterium exhibits complex ecological interactions within the lung microbiota and is associated with specific hematological abnormalities. These findings challenge the necessity of routine TW-targeted therapy in mixed infections and emphasize the need for diagnostic procedures integrating sequence quantification and clinical parameters. Tropheryma whipplei pulmonary infection metagenomic next-generation sequencing microbiome antimicrobial therapy co-infection anemia Figures Figure 1 Figure 2 Introduction Tropheryma whipplei (TW) is a Gram-positive, partially acid-fast actinobacterium. It is an obligate intracellular bacterium that is notoriously difficult to culture and is commonly found in the environment. Globally, Whipple's disease is rare, with an estimated annual incidence of less than 1 per million [ 1 ]. However, TW DNA has been detected in the stool samples of 4–12% of healthy individuals in certain regions, suggesting asymptomatic carriage [ 2 ]. Regarding respiratory specimens, specifically BALF, the reported positivity rate for TW via mNGS ranges from 0.5% to 2% [ 6 ]. TW has a relatively small genome, reflecting its host-dependent parasitic lifestyle. Historically, TW has been established as the etiological agent of Whipple's disease, typically manifesting with gastrointestinal clinical features [ 3 ]. The increasing use of metagenomic next-generation sequencing (mNGS) has gradually increased the detection of TW in respiratory infections, suggesting that it may play a pathogenic role in pulmonary diseases [ 4 ]. With the widespread adoption of mNGS in clinical practice, two important clinical pitfalls have emerged: overdiagnosis of TW as a primary pathogen leading to unnecessary anti-TW therapy, and underrecognition of true Whipple's disease when extrapulmonary manifestations are subtle. Moreover, diagnostic errors often occur because TW is frequently co-detected with other conventional pathogens, thereby obscuring its pathogenic contribution. Most existing studies on TW pulmonary infection are case reports or small-sample studies, while its clinical features, diagnostic criteria, and treatment strategies are not fully defined [ 5 – 7 ]. The diagnosis of TW pulmonary infection currently relies mainly on mNGS, but the clinical significance of a positive result remains controversial. First, TW is often co-detected with other definite pathogens, making its role as a primary pathogen or commensal unclear [ 7 ]. Second, the bacterium is frequently detected in immunocompromised individuals or those with underlying lung diseases, suggesting possible opportunistic pathogenic characteristics [ 8 , 9 ]. Third, there is a lack of standards for a pathogenic threshold for TW sequence counts and their correlation with disease severity [ 5 , 10 ]. This retrospective investigation of 74 patients with mNGS-detectable TW in BALF was conducted with three primary objectives: (1) to characterize the clinical, imaging, and serological features of TW-associated lung conditions; (2) to analyze the impact of co-infection patterns on TW sequence counts and to evaluate treatment outcomes. This study presents the first systematic analysis of the correlation between TW sequence counts and co-infecting pathogens, anemia, and other clinical parameters, offering a pragmatic approach to interpreting TW detection in respiratory samples. Materials and methods Study Design and Patients This retrospective cohort study included 74 individuals with BALF specimens testing positive for Tropheryma whipplei via mNGS. Cases were ascertained by reviewing electronic medical records from the Second Affiliated Hospital of Army Medical University spanning January 2018 to December 2022. During this period, a total of 1,543 BALF samples from unique patients underwent mNGS testing. The overall detection rate for TW was 4.79% (74/1,543). Ethical approval for this study was granted by the Institutional Review Board (Approval No. : 2025-Yan Di-369-01), which also waived the requirement for individual informed consent given the study's retrospective design. BALF was collected during bronchoscopy by instilling 20–50 mL of sterile saline into the diseased bronchial segments, followed by immediate aspiration. A minimum 5 mL aliquot from each sample was preserved at -20°C and dispatched to the BGI clinical laboratory (Chongqing, China) for mNGS processing. We retrieved a comprehensive dataset encompassing demographics, clinical presentation, radiological findings, laboratory parameters, mNGS results, final diagnoses, therapeutic interventions, and patient outcomes. BALF Processing and DNA Extraction BALF samples (1.5-3 mL per patient) were processed using a standardized protocol. To deplete human DNA, 450 µL of BALF was treated with 11.5 µL of 1.0% saponin (final concentration 0.025%), agitated vigorously for 15 seconds, and allowed to stand at ambient temperature for 5 minutes.Then, 75 µL of a host depletion reaction mix was added, followed by another vortexing step and incubation at 37°C for 10 minutes. The mixture was centrifuged at 18,000g for 5 minutes. Roughly 450 µL of supernatant was carefully removed and discarded, leaving approximately 70–80 µL of residual liquid. The pellet was resuspended in 800 µL of PBS and centrifuged again under identical conditions. After discarding another 800 µL of supernatant, the pellet was resuspended in 370 µL of TE buffer. Cellular lysis was accomplished by introducing 7.2 µL of Lyticase (RT410-TA, TIANGEN BIOTECH, Beijing, China) for enzymatic digestion, succeeded by mechanical disruption using 250 µL of 0.5 mm glass beads via vortex agitation. DNA was finally extracted from 300 µL of the lysate using the TIANMicrobe Magnetic Bead Pathogen DNA Extraction Kit (TIANGEN, NG550-01, Beijing, China) in accordance with the manufacturer's instructions. Library Construction and Sequencing Sequencing libraries were prepared from the isolated DNA through a series of steps: enzymatic fragmentation, end-repair, adapter ligation, and PCR amplification. The Agilent 2100 Bioanalyzer was employed to assess library quality and confirm the fragment size distribution (approximately 300 bp). Quantification of library concentration was performed with the Qubit dsDNA HS Assay Kit (Thermo Fisher Scientific, Waltham, MA, USA). Libraries meeting quality thresholds were pooled in equimolar amounts and circularized to form single-stranded DNA circles. These templates subsequently underwent rolling circle amplification (RCA) to produce DNA nanoballs (DNBs), which were then arrayed onto patterned nanoarray chips. Sequencing was executed on either the BGISEQ-50 or MGISEQ-2000 platforms (BGI, Shenzhen, China). Bioinformatic Analysis Raw sequencing data underwent initial processing to eliminate low-quality reads, yielding high-quality datasets. To reduce host-originating sequences, reads aligning to the human reference genome were removed utilizing the BWA software ( http://bio-bwa.sourceforge.net/ ). Subsequent filtering steps discarded low-complexity sequences. Subsequently, the remaining high-quality, non-human reads were mapped against the BGI Pathogen Metagenomics Database (PMDB), which contains complete genomes of over 12,000 bacterial, viral, fungal, and parasitic species. A species was considered detected if at least 2 unique reads mapped with an identity of ≥ 97% and coverage of ≥ 50% of the reference sequence. The read count for each identified pathogen, including T. whipplei, was documented. Statistical Analysis Analyses were conducted using SPSS Statistics version 29.0.2.0(20) (IBM Corp., USA) and GraphPad Prism version 8.0.1 (GraphPad Software, USA). The distribution of continuous variables was evaluated using the Shapiro-Wilk test. Data conforming to a normal distribution are summarized as mean ± standard deviation (SD) and compared via the independent-samples t-test; non-normally distributed data are reported as median with interquartile range (IQR) and analyzed employing the Mann-Whitney U test. Categorical variables are expressed as counts and percentages and compared using Pearson's chi-square test or Fisher's exact test, as warranted. The Mann-Whitney U test was also utilized to examine relationships between TW sequence counts and clinical parameters (including anemia, hypoalbuminemia, and co‑infection status). Radiographic improvement was contrasted between treatment cohorts using chi-square analysis. A two-sided P-value < 0.05 was deemed statistically significant for all tests. Results Demographics, clinical features, imaging, and laboratory findings TW was identified in the BALF of seventy-four patients via mNGS. The average age was 55 years (spanning 18–83 years), and 47.3% (35/74) were male. The main clinical manifestations were cough (71.6%), expectoration (59.5%), dyspnea (31.1%), and hemoptysis (24.3%). Chest CT showed patchy opacities (74.3%), multiple nodules (71.6%), mediastinal lymphadenopathy (47.3%), and pleural effusion (10.8%) as the main features, with a small proportion showing interstitial changes. Most patients underwent serological testing before BALF sampling. 79.7% of patients had normal white blood cell (WBC) counts, only 10 (13.5%) had elevated WBC, but 53.2% had elevated C-reactive protein (CRP) levels and 62.5% had an elevated erythrocyte sedimentation rate (ESR). Notably, 58.1% of patients had hemoglobin levels below the normal reference range, and 51.4% showed decreased serum albumin. In addition, 25.7% (19/74) exhibited platelet counts above the normal reference range (Table 1 ). Table 1 Demographic, clinical, and serological characteristics Characteristics T. whipplei positive Age, years (mean, SD) 55 (12.9) Male 39 (47.3%) Clinical symptoms Cough 53 (71.6%) Expectoration 44 (59.5%) Hemoptysis 18 (24.3%) Dyspnea 23 (31.1%) CT imaging features Patchy opacities 55(74.3%) Multiple nodules 53(71.6%) Mediastinal lymphadenopathy 35(47.3%) Pleural effusion 8(10.8%) Interstitial changes 3(4.1%) Blood test WBC (×10⁹/L) (mean, SD) 6.86 (2.80) Low (WBC < 3.5) 5/74 (6.8%) Normal (3.5 ≤ WBC < 9.5) 59/74 (79.7%) High (WBC ≥ 9.5) 10/74 (13.5%) CRP (mg/L) (median, IQR) 9.5 (3.6-30.28) Normal (CRP < 8) 29/62 (46.8%) High (CRP ≥ 8) 33/62 (53.2%) ESR (mm/h) (median, IQR) 20.75 (9.43-49) Normal (ESR < 15) 24/64 (37.5%) High (ESR ≥ 15) 40/64 (62.5%) Hb (g/L) 124.86 (22.11) Low (Hb < 130) 43/73 (58.9%) Normal (130 ≤ Hb < 175) 29/73 (39.7%) High (Hb ≥ 175) 1/73 (1.4%) Plt (10^9/L) (median, IQR) 225 (182.5-306.25) Low (Plt < 100) 5/74 (6.8%) Normal (100 ≤ Plt < 300) 50/74 (67.6%) High (Plt ≥ 300) 19/74 (25.7%) Alb (g/L) 39.21 (5.79) Low (Alb < 40) 38/64 (59.4%) Normal (40 ≤ Alb < 55) 25/64 (39.1%) High (Alb ≥ 55) 1/64 (1.6%) Comorbidities Among the 89.2% of patients with underlying lung diseases, secondary tuberculosis and lung cancer were equally the most common (each 27%), followed by COPD (13.5%) and fungal infections (10.8%).Additionally, 4 patients had other malignancies, including lymphoma (n = 2), colon cancer (n = 1), and rectal cancer (n = 1). Twelve patients (16.2%) had diabetes, 22 (29.7%) had hypoalbuminemia, and 10 (13.5%) had anemia(Table 2 ). Table 2 Comorbidities Comorbidity n (%) or count Pulmonary diseases 66(89.2%) Secondary tuberculosis 20(27%) Lung cancer 20(27%) COPD 10(13.5%) Fungal infection 8(10.8%) Aspergillus pneumonia 4 Pneumocystis jirovecii pneumonia 3 Pulmonary cryptococcosis 1 Paragonimiasis 1 Chlamydia psittaci infection 1 ARDS 3 Bronchiectasis 3 Old tuberculosis 4 Interstitial pneumonia 2 Pulmonary epithelioid hemangioma 1 Inflammatory pseudotumor of the lung 1 Mediastinal lymphadenitis 1 Diabetes mellitus 12(16.2%) Other malignancies 4(5.4%) Lymphoma 2 Postoperative colon cancer 1 Rectal cancer 1 Antisynthetase syndrome 1 Hypoalbuminemia 22(29.7%) Anemia 10(13.5%) Microbiological characteristics TW was the sole pathogen detected by mNGS in only 17 patients (23.0%). Approximately two-thirds (64.9%) showed co-detection with other bacteria; the most common were Mycobacterium tuberculosis complex (18.9%), Haemophilus influenzae (17.6%), Streptococcus pneumoniae (14.9%), Klebsiella pneumoniae (13.5%), and Pseudomonas aeruginosa (12.2%). Nineteen patients (25.7%) had co-detection with fungi, including Pneumocystis jirovecii , Aspergillus , Candida , and Cryptococcus . Twenty-five patients (33.8%) had DNA virus sequences detected, predominantly human herpesviruses (Table 3 ). Table 3 Common pathogens co-detected by mNGS Co-detected pathogen n (%) Bacteria 48(64.9%) Mycobacterium tuberculosis complex 14(18.9%) Haemophilus influenzae 13(17.6%) Streptococcus pneumoniae 11(14.9%) Klebsiella pneumoniae 10(13.5%) Pseudomonas aeruginosa 9(12.2%) Moraxella catarrhalis 3(4.1%) Staphylococcus aureus 2(2.7%) Acinetobacter baumannii 5(6.8%) Fungi 19(25.7%) Aspergillus spp. 5(6.8%) Candida spp. 5(6.8%) Pneumocystis jirovecii 8(10.8%) Cryptococcus neoformans 1(1.3%) DNA Viruses 25(33.8%) Human herpesviruses 23(31.1%) The TW sequence counts in these patients ranged from a few to over ten thousand (Fig. 1 ). Further analysis revealed that TW sequence counts were significantly lower in patients co-infected with S. pneumoniae or P. aeruginosa (P = 0.038) (Fig. 2 ). In contrast, co-infection with M. tuberculosis complex, H. influenzae, or other pathogens did not significantly alter TW sequence counts (P > 0.05). Concurrently, patients with decreased hemoglobin had significantly higher TW sequence counts compared to the normal group (P = 0.045). TW sequence counts were not influenced by decreased serum albumin (P > 0.05). Treatment efficacy Forty-one patients underwent chest CT re-examination one month later to evaluate treatment response, and 22 (53.7%) showed radiographic improvement. Among these 41 patients, 23 received anti-TW treatment, including: 10 with sulfonamides alone; 4 with ceftriaxone combined with sulfonamides; 3 with carbapenems; 2 with ceftriaxone; 2 with ceftriaxone combined with tetracycline; 1 with tetracycline; and 1 with tetracycline combined with sulfonamides. Univariate analysis found no significant difference in treatment efficacy between the anti-TW treatment group and the untreated group (P = 0.295) (Table 4 ). Table 4 Comparison of treatment efficacy against T. whipplei No anti-TW treatment Anti-TW treatment Total χ 2 p No improvement 10(55.6%) 9(39.1%) 19(46.3%) 1.096 0.295 Improvement 8(44.4%) 14(60.9%) 22(53.7%) Total 18 23 41 Discussion Co-detection Patterns and Microbial Competition This study comprehensively analyzed the clinical, imaging, and microbiological characteristics of Tropheryma whipplei (TW) pulmonary infection using mNGS of BALF. The findings indicate that TW often coexists with other respiratory pathogens, being the sole detected pathogen in only 23% of cases, which is close to the 29.8% reported by Lin M et al. [ 4 ] and the 24.1% reported by Shen et al. [ 5 ]. This raises important questions about the pathogenic role of TW in pulmonary infections, especially considering that 89.2% of the patients in this cohort had chronic underlying lung diseases. The detection of high TW sequence counts (exceeding 10,000 reads in some patients), coupled with systemic inflammatory responses (elevated CRP in 53.2%, elevated ESR in 62.5%) [ 5 , 11 ], suggesting that TW may act as an active pathogen rather than mere colonization in certain clinical contexts. TW was frequently co-detected with other pathogens ( S. pneumoniae , M. tuberculosis , Candida , etc.) [ 12 – 14 ]. Notably, this study found that TW sequence counts decreased when co-detected with S. pneumoniae or P. aeruginosa (P = 0.038), suggesting potential microbial competition within the respiratory microenvironment. These results are consistent with a recent report by Lai et al. [ 6 ], who also observed lower TW reads in patients with bacterial co‑infections, although they did not distinguish between specific pathogens. Our finding that TW sequence counts were significantly lower in the presence of S. pneumoniae or P. aeruginosa suggests a complex ecological interaction within the lung microbiome, potentially indicative of direct microbial competition. As fast-growing, highly virulent pathogens, S. pneumoniae and P. aeruginosa may outcompete TW for nutritional resources or ecological niches within the respiratory tract. Furthermore, these common bacteria can induce a robust, acute inflammatory response and antimicrobial peptide production, potentially creating an inhospitable microenvironment for the slower-growing, intracellular TW. This suppressive effect was not observed with M. tuberculosis or H. influenzae, hinting that the nature of pathogen interaction is specific and not merely a consequence of any co-infection. Clinical and Systemic Correlates The clinical manifestations of TW-associated lung disease are non-specific [ 4 , 5 ]. The most common symptoms in this cohort were cough (71.6%), expectoration (59.5%), and dyspnea (31.1%), overlapping with those of the underlying lung diseases. Radiologically, features such as patchy opacities (74.3%), multiple nodules (71.6%), and mediastinal lymphadenopathy (47.3%) might be more suggestive, consistent with previous studies [ 15 – 17 ], though these findings also overlap with other pulmonary diseases. Laboratory abnormalities including anemia (58.1%), hypoalbuminemia (51.4%), and thrombocytosis (25.7%) reflect processes of chronic inflammation or malabsorption. We report a positive correlation between elevated TW sequence counts and the presence of anemia (P = 0.045), representing a novel finding that has not been previously documented in prior investigations regarding pulmonary TW [ 4 – 7 ]. Anemia in these patients is unlikely to be coincidental; rather, it may reflect a state of chronic disease, similar to classic Whipple's disease[ 11 , 18 , 19 ]. Chronic inflammation, driven by TW infection, can lead to elevated hepcidin, resulting in iron sequestration and anemia of inflammation. Concurrently, the observed hypoalbuminemia suggests possible malabsorption or a nutritional deficiency state, which could be exacerbated by a chronic infectious process. This hematological abnormality could thus serve as a valuable clinical clue, pointing towards a more significant and active TW involvement rather than mere colonization. Treatment Efficacy and Underlying Reasons The most noteworthy finding of this study is that targeted anti-TW treatment did not significantly improve clinical outcomes (P = 0.295). This result provides direct support for the clinical decision framework we propose. Table 4 shows that among 41 patients with follow‑up CT, radiographic improvement occurred in 60.9% (14/23) of the anti‑TW group and 44.4% (8/18) of the untreated group, with no statistically significant difference observed between the groups. Thus, routine anti‑TW therapy is not supported by the current evidence. This result may be influenced by several factors. First, high prevalence of co-infections: 64.9% of patients had bacterial co-infections and 25.7% had fungal co-infections, the dominant clinical picture and radiographic findings were likely driven by these conventional pathogens. Treatment directed at these co-pathogens would resolve the primary infection, obscuring any incremental benefit from anti-TW agents. Second, host factors: the cohort predominantly included patients with significant underlying pulmonary comorbidities (89.2%) and immunocompromised conditions, which could confound the assessment of treatment response and contribute to overall slower recovery. Third, heterogeneity of treatment regimens: the lack of a standardized protocol led to varied antibiotic choices (sulfonamides, cephalosporins, carbapenems, tetracyclines) and durations, making it difficult to draw definitive conclusions about the efficacy of any specific regimen against pulmonary TW. Finally, colonization vs. true infection: it is plausible that in a substantial proportion of patients, especially those with low sequence counts and clear alternative pathogens, TW represented colonization or a bystander organism rather than a true pathogen necessitating treatment. Shen Y et al. documented a case of acute TW pneumonia where symptoms and imaging improved after ceftriaxone treatment [ 20 ]. Similarly, Huo Y et al. found that 7 patients with TW detected in BALF responded well to a combined imipenem-cilastatin and sulfamethoxazole regimen [ 17 ]. Conversely, Sun, L., etc. reported that TW in BALF frequently indicated oropharyngeal contamination rather than a true infection [ 7 ]. These contrasting findings suggest the need for differentiated clinical management strategies: considering anti-TW treatment for cases with high TW sequence counts and no other definite pathogens detected, while prioritizing treatment for the main co-infecting pathogens in most cases with mixed infections. Clinical Implications and a Proposed Framework Several limitations of this study must be acknowledged. These include its retrospective design, a limited sample size (n = 74), and the lack of standardized treatment protocols. Future larger prospective studies with systematic follow-up mechanisms are needed to better define diagnostic criteria for TW pulmonary infection, elucidate its pathophysiological mechanisms, and develop evidence-based treatment guidelines. Particularly important is investigating TW's potential role as an opportunistic pathogen in immunocompromised hosts and its interaction mechanisms with the lung microbiome. Despite these limitations, this study provides an important basis for the clinical interpretation of TW detection in respiratory specimens and lays the groundwork for further research on this emerging pulmonary pathogen. Our study challenges the routine treatment of TW upon its detection by mNGS. More specifically, we propose a pragmatic framework for clinical decision-making: Consider Treatment when: (1) TW is the sole detected pathogen with high sequence counts; (2) Patients have persistent or progressive symptoms and radiographic infiltrates despite broad-spectrum antibiotics covering common pathogens; (3) There is supporting evidence of systemic involvement (e.g., unexplained anemia, hypoalbuminemia, arthralgia); and (4) In immunocompromised hosts with a high index of suspicion. Withhold or Defer Treatment when: (1) A classic primary pathogen (e.g., S. pneumoniae , M. tuberculosis ) is identified and aligns with the clinical presentation; (2) TW sequence counts are low and the patient is improving with standard therapy; (3) The patient is asymptomatic with incidental findings, suggesting colonization. Conclusions In conclusion, the pathogenic role of TW in pulmonary infections requires further validation. Clinicians need to interpret mNGS results comprehensively along with clinical symptoms, imaging findings, and laboratory tests.For cases suspected of TW pathogenicity, multidisciplinary discussion is recommended to develop individualized treatment plans after weighing the pros and cons. As detection technology improves and clinical understanding grows, the exact role of TW in respiratory infections will become clearer. Abbreviations BALF: Bronchoalveolar lavage fluid CRP: C‑reactive protein CT: Computed tomography ESR: Erythrocyte sedimentation rate mNGS: Metagenomic next‑generation sequencing TW: Tropheryma whipplei WBC: White blood cell Declarations Ethics approval and consent to participate This retrospective study was conducted in accordance with the Declaration of Helsinki. The study was approved by the Institutional Review Board of Xinqiao Hospital, Army Medical University (Approval No.: 2025‑Yan Di‑369‑01). The requirement for informed consent was waived by the committee as the study involved minimal risk and utilized de‑identified data from routine clinical practice. Clinical trial number Not applicable. Consent for publication We requested an exemption from informed consent and provided the reasons in the ethical application. The documents listed in the original ethical approval file have been approved by the Ethical committee. Ethical committee approved our research, including the research plan, the format for releasing research results, and the informed consent form (exemption application). Availability of data and materials Data generated and/or analyzed in this study are not publicly available due to patient privacy regulations and institutional policies, but are available from the corresponding author upon reasonable request. Competing interests The authors declare that they have no competing interests. Funding This study received no specific grant from any funding agency in the public, commercial, or not‑for‑profit sectors. Authors ’ contributions ZW and XL (Xiaoli Luo) made equal contributions to this work. ZW and XL (Xiaoli Luo): data collection, data analysis, and manuscript drafting. CZ and JX: data curation and statistical support. MH and XC (Xiaolong Chen): conceptualization, design, supervision, and critical revision of the manuscript. All authors reviewed and approved the final manuscript. 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Clinical and laboratory predictors and prevalence of immune reconstitution inflammatory syndrome in patients with Whipple's disease. J Dig Dis. 2023;24(10):516–21. 10.1111/1751-2980.13223 . Gomez-Casado C, Villaseñor A, Rodriguez-Nogales A, et al. Understanding Platelets in Infectious and Allergic Lung Diseases. Int J Mol Sci. 2019;20(7). 10.3390/ijms20071730 . Shen Y, Cui SS, Teng XB, et al. Acute pneumonia due to Tropheryma whipplei diagnosed by metagenomic next-generation sequencing and pathology: A case report. Heliyon. 2024;10(4):e26747. 10.1016/j.heliyon.2024.e26747 . Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 17 May, 2026 Reviewers agreed at journal 12 May, 2026 Reviewers invited by journal 06 May, 2026 Editor invited by journal 04 May, 2026 Editor assigned by journal 22 Apr, 2026 Submission checks completed at journal 22 Apr, 2026 First submitted to journal 13 Apr, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9406285","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":639875191,"identity":"578e1444-e7a4-414c-a3a4-5dcd5c9d490a","order_by":0,"name":"Zhili Wu","email":"","orcid":"","institution":"Army Medical University","correspondingAuthor":false,"prefix":"","firstName":"Zhili","middleName":"","lastName":"Wu","suffix":""},{"id":639875192,"identity":"d3775b24-e352-4058-be9c-c59eea136b00","order_by":1,"name":"Xiaoli Luo","email":"","orcid":"","institution":"Army Medical University","correspondingAuthor":false,"prefix":"","firstName":"Xiaoli","middleName":"","lastName":"Luo","suffix":""},{"id":639875193,"identity":"b5cd8c51-2ebb-4f15-bed4-724b237973f4","order_by":2,"name":"Cailin Zhao","email":"","orcid":"","institution":"Army Medical University","correspondingAuthor":false,"prefix":"","firstName":"Cailin","middleName":"","lastName":"Zhao","suffix":""},{"id":639875194,"identity":"4a9fe882-5620-4766-8e26-a1651735d78f","order_by":3,"name":"Jing Xu","email":"","orcid":"","institution":"Army Medical University","correspondingAuthor":false,"prefix":"","firstName":"Jing","middleName":"","lastName":"Xu","suffix":""},{"id":639875196,"identity":"a69a9fd8-bed4-4b06-84ed-62168bb39dc2","order_by":4,"name":"Mingdong HU","email":"","orcid":"","institution":"Army Medical University","correspondingAuthor":false,"prefix":"","firstName":"Mingdong","middleName":"","lastName":"HU","suffix":""},{"id":639875197,"identity":"a3ef1e4d-7955-45c9-be31-f09c4645a646","order_by":5,"name":"Xiaolong Chen","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABIElEQVRIiWNgGAWjYDACCRBhwMDAB6ITKmqY+aESjA2EtLCB6AdnjrFLthGlhQGihfFhGzO/wTECWvhnNx97zFNgJ8fG3nv4RQIbm7Tx/e7UzTwMNrIbDjA/e4DNkjvH0g1nGCQbs/GcS7NI4JExNjvGu+02D0Oa8YYDbOYGWLQYSOSYSXwwYE5sAzIMEiTYkqFaDiduOMDDJoFVS/43iQSDeqgWA+b6zW1gLf/xaMlhA9pyGKTF+EFCAjOzARtYywGcWiRupJlJzjA4DvTLGTOGhAPHmCWO5W67OQfou5mH2cywaeGfkfxMmudPtRw/e4/xx5//gFHZfHbbjTcVdrJ9x5ufYdOCDJCdAQoqZgLqQUo+EFYzCkbBKBgFIxEAADBrXmczxz0KAAAAAElFTkSuQmCC","orcid":"","institution":"Army Medical University","correspondingAuthor":true,"prefix":"","firstName":"Xiaolong","middleName":"","lastName":"Chen","suffix":""}],"badges":[],"createdAt":"2026-04-13 15:53:17","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9406285/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9406285/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":109286595,"identity":"cee42132-b12d-499b-a563-51b521e3852c","added_by":"auto","created_at":"2026-05-15 02:35:43","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":15425,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDistribution of \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eT. whipplei\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e sequence counts.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-9406285/v1/8333100493ad2e3d8482e9d5.png"},{"id":109296498,"identity":"cd329958-07af-446d-af84-52dfeac194e7","added_by":"auto","created_at":"2026-05-15 08:47:34","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":50910,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSubgroup analysis of \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eT. whipplei\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e sequence counts.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eLegend: TW, \u003cem\u003eTropheryma whipplei\u003c/em\u003e; S. p., \u003cem\u003eStreptococcus pneumoniae\u003c/em\u003e; P. a., \u003cem\u003ePseudomonas aeruginosa\u003c/em\u003e; Hb, hemoglobin. Boxes represent the median and the IQR; whiskers indicate the 5th–95th percentiles. \u003cem\u003eP\u003c/em\u003e values were calculated using the Mann‑Whitney U test.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-9406285/v1/748af9a3027c7435ba94273a.png"},{"id":109297326,"identity":"536e0eb1-c58a-4c03-808f-0433cf036e72","added_by":"auto","created_at":"2026-05-15 08:56:36","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":329272,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9406285/v1/401629aa-3af2-4d91-9cc6-34f886c4a751.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Tropheryma whipplei in Pulmonary Infections: Microbial Competition with Streptococcus pneumoniae and Pseudomonas aeruginosa, Association with Anemia, and Lack of Benefit from Targeted Therapy - A Retrospective Cohort Study","fulltext":[{"header":"Introduction","content":"\u003cp\u003e \u003cem\u003eTropheryma whipplei\u003c/em\u003e (TW) is a Gram-positive, partially acid-fast actinobacterium. It is an obligate intracellular bacterium that is notoriously difficult to culture and is commonly found in the environment. Globally, Whipple's disease is rare, with an estimated annual incidence of less than 1 per million [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. However, TW DNA has been detected in the stool samples of 4\u0026ndash;12% of healthy individuals in certain regions, suggesting asymptomatic carriage [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Regarding respiratory specimens, specifically BALF, the reported positivity rate for TW via mNGS ranges from 0.5% to 2% [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. TW has a relatively small genome, reflecting its host-dependent parasitic lifestyle. Historically, TW has been established as the etiological agent of Whipple's disease, typically manifesting with gastrointestinal clinical features [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. The increasing use of metagenomic next-generation sequencing (mNGS) has gradually increased the detection of TW in respiratory infections, suggesting that it may play a pathogenic role in pulmonary diseases [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eWith the widespread adoption of mNGS in clinical practice, two important clinical pitfalls have emerged: overdiagnosis of TW as a primary pathogen leading to unnecessary anti-TW therapy, and underrecognition of true Whipple's disease when extrapulmonary manifestations are subtle. Moreover, diagnostic errors often occur because TW is frequently co-detected with other conventional pathogens, thereby obscuring its pathogenic contribution. Most existing studies on TW pulmonary infection are case reports or small-sample studies, while its clinical features, diagnostic criteria, and treatment strategies are not fully defined [\u003cspan additionalcitationids=\"CR6\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. The diagnosis of TW pulmonary infection currently relies mainly on mNGS, but the clinical significance of a positive result remains controversial. First, TW is often co-detected with other definite pathogens, making its role as a primary pathogen or commensal unclear [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Second, the bacterium is frequently detected in immunocompromised individuals or those with underlying lung diseases, suggesting possible opportunistic pathogenic characteristics [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Third, there is a lack of standards for a pathogenic threshold for TW sequence counts and their correlation with disease severity [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThis retrospective investigation of 74 patients with mNGS-detectable TW in BALF was conducted with three primary objectives: (1) to characterize the clinical, imaging, and serological features of TW-associated lung conditions; (2) to analyze the impact of co-infection patterns on TW sequence counts and to evaluate treatment outcomes. This study presents the first systematic analysis of the correlation between TW sequence counts and co-infecting pathogens, anemia, and other clinical parameters, offering a pragmatic approach to interpreting TW detection in respiratory samples.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy Design and Patients\u003c/h2\u003e \u003cp\u003eThis retrospective cohort study included 74 individuals with BALF specimens testing positive for Tropheryma whipplei via mNGS. Cases were ascertained by reviewing electronic medical records from the Second Affiliated Hospital of Army Medical University spanning January 2018 to December 2022. During this period, a total of 1,543 BALF samples from unique patients underwent mNGS testing. The overall detection rate for TW was 4.79% (74/1,543). Ethical approval for this study was granted by the Institutional Review Board (Approval No. : 2025-Yan Di-369-01), which also waived the requirement for individual informed consent given the study's retrospective design. BALF was collected during bronchoscopy by instilling 20\u0026ndash;50 mL of sterile saline into the diseased bronchial segments, followed by immediate aspiration. A minimum 5 mL aliquot from each sample was preserved at -20\u0026deg;C and dispatched to the BGI clinical laboratory (Chongqing, China) for mNGS processing. We retrieved a comprehensive dataset encompassing demographics, clinical presentation, radiological findings, laboratory parameters, mNGS results, final diagnoses, therapeutic interventions, and patient outcomes.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eBALF Processing and DNA Extraction\u003c/h3\u003e\n\u003cp\u003eBALF samples (1.5-3 mL per patient) were processed using a standardized protocol. To deplete human DNA, 450 \u0026micro;L of BALF was treated with 11.5 \u0026micro;L of 1.0% saponin (final concentration 0.025%), agitated vigorously for 15 seconds, and allowed to stand at ambient temperature for 5 minutes.Then, 75 \u0026micro;L of a host depletion reaction mix was added, followed by another vortexing step and incubation at 37\u0026deg;C for 10 minutes. The mixture was centrifuged at 18,000g for 5 minutes. Roughly 450 \u0026micro;L of supernatant was carefully removed and discarded, leaving approximately 70\u0026ndash;80 \u0026micro;L of residual liquid. The pellet was resuspended in 800 \u0026micro;L of PBS and centrifuged again under identical conditions. After discarding another 800 \u0026micro;L of supernatant, the pellet was resuspended in 370 \u0026micro;L of TE buffer. Cellular lysis was accomplished by introducing 7.2 \u0026micro;L of Lyticase (RT410-TA, TIANGEN BIOTECH, Beijing, China) for enzymatic digestion, succeeded by mechanical disruption using 250 \u0026micro;L of 0.5 mm glass beads via vortex agitation. DNA was finally extracted from 300 \u0026micro;L of the lysate using the TIANMicrobe Magnetic Bead Pathogen DNA Extraction Kit (TIANGEN, NG550-01, Beijing, China) in accordance with the manufacturer's instructions.\u003c/p\u003e\n\u003ch3\u003eLibrary Construction and Sequencing\u003c/h3\u003e\n\u003cp\u003eSequencing libraries were prepared from the isolated DNA through a series of steps: enzymatic fragmentation, end-repair, adapter ligation, and PCR amplification. The Agilent 2100 Bioanalyzer was employed to assess library quality and confirm the fragment size distribution (approximately 300 bp). Quantification of library concentration was performed with the Qubit dsDNA HS Assay Kit (Thermo Fisher Scientific, Waltham, MA, USA). Libraries meeting quality thresholds were pooled in equimolar amounts and circularized to form single-stranded DNA circles. These templates subsequently underwent rolling circle amplification (RCA) to produce DNA nanoballs (DNBs), which were then arrayed onto patterned nanoarray chips. Sequencing was executed on either the BGISEQ-50 or MGISEQ-2000 platforms (BGI, Shenzhen, China).\u003c/p\u003e\n\u003ch3\u003eBioinformatic Analysis\u003c/h3\u003e\n\u003cp\u003eRaw sequencing data underwent initial processing to eliminate low-quality reads, yielding high-quality datasets. To reduce host-originating sequences, reads aligning to the human reference genome were removed utilizing the BWA software (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://bio-bwa.sourceforge.net/\u003c/span\u003e\u003cspan address=\"http://bio-bwa.sourceforge.net/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). Subsequent filtering steps discarded low-complexity sequences.\u003c/p\u003e \u003cp\u003eSubsequently, the remaining high-quality, non-human reads were mapped against the BGI Pathogen Metagenomics Database (PMDB), which contains complete genomes of over 12,000 bacterial, viral, fungal, and parasitic species. A species was considered detected if at least 2 unique reads mapped with an identity of \u0026ge;\u0026thinsp;97% and coverage of \u0026ge;\u0026thinsp;50% of the reference sequence. The read count for each identified pathogen, including T. whipplei, was documented.\u003c/p\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eAnalyses were conducted using SPSS Statistics version 29.0.2.0(20) (IBM Corp., USA) and GraphPad Prism version 8.0.1 (GraphPad Software, USA). The distribution of continuous variables was evaluated using the Shapiro-Wilk test. Data conforming to a normal distribution are summarized as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (SD) and compared via the independent-samples t-test; non-normally distributed data are reported as median with interquartile range (IQR) and analyzed employing the Mann-Whitney U test. Categorical variables are expressed as counts and percentages and compared using Pearson's chi-square test or Fisher's exact test, as warranted. The Mann-Whitney U test was also utilized to examine relationships between TW sequence counts and clinical parameters (including anemia, hypoalbuminemia, and co‑infection status). Radiographic improvement was contrasted between treatment cohorts using chi-square analysis. A two-sided P-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was deemed statistically significant for all tests.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eDemographics, clinical features, imaging, and laboratory findings\u003c/h2\u003e \u003cp\u003eTW was identified in the BALF of seventy-four patients via mNGS. The average age was 55 years (spanning 18\u0026ndash;83 years), and 47.3% (35/74) were male. The main clinical manifestations were cough (71.6%), expectoration (59.5%), dyspnea (31.1%), and hemoptysis (24.3%).\u003c/p\u003e \u003cp\u003eChest CT showed patchy opacities (74.3%), multiple nodules (71.6%), mediastinal lymphadenopathy (47.3%), and pleural effusion (10.8%) as the main features, with a small proportion showing interstitial changes. Most patients underwent serological testing before BALF sampling. 79.7% of patients had normal white blood cell (WBC) counts, only 10 (13.5%) had elevated WBC, but 53.2% had elevated C-reactive protein (CRP) levels and 62.5% had an elevated erythrocyte sedimentation rate (ESR). Notably, 58.1% of patients had hemoglobin levels below the normal reference range, and 51.4% showed decreased serum albumin. In addition, 25.7% (19/74) exhibited platelet counts above the normal reference range (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDemographic, clinical, and serological characteristics\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eT. whipplei\u003c/em\u003e positive\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge, years (mean, SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e55 (12.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e39 (47.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eClinical symptoms\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCough\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e53 (71.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eExpectoration\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e44 (59.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHemoptysis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18 (24.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDyspnea\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e23 (31.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCT imaging features\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePatchy opacities\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e55(74.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMultiple nodules\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e53(71.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMediastinal lymphadenopathy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e35(47.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePleural effusion\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8(10.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInterstitial changes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3(4.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBlood test\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWBC (\u0026times;10⁹/L) (mean, SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.86 (2.80)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow (WBC \u0026lt; 3.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5/74 (6.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNormal (3.5\u0026thinsp;\u0026le;\u0026thinsp;WBC \u0026lt; 9.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e59/74 (79.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh (WBC\u0026thinsp;\u0026ge;\u0026thinsp;9.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e10/74 (13.5%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCRP (mg/L) (median, IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9.5 (3.6-30.28)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNormal (CRP \u0026lt; 8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e29/62 (46.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh (CRP\u0026thinsp;\u0026ge;\u0026thinsp;8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e33/62 (53.2%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eESR (mm/h) (median, IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20.75 (9.43-49)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNormal (ESR \u0026lt; 15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24/64 (37.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh (ESR\u0026thinsp;\u0026ge;\u0026thinsp;15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e40/64 (62.5%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHb (g/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e124.86 (22.11)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow (Hb \u0026lt; 130)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e43/73 (58.9%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNormal (130\u0026thinsp;\u0026le;\u0026thinsp;Hb \u0026lt; 175)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e29/73 (39.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh (Hb\u0026thinsp;\u0026ge;\u0026thinsp;175)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1/73 (1.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePlt (10^9/L) (median, IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e225 (182.5-306.25)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow (Plt \u0026lt; 100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5/74 (6.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNormal (100\u0026thinsp;\u0026le;\u0026thinsp;Plt \u0026lt; 300)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e50/74 (67.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh (Plt\u0026thinsp;\u0026ge;\u0026thinsp;300)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e19/74 (25.7%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAlb (g/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e39.21 (5.79)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow (Alb \u0026lt; 40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e38/64 (59.4%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNormal (40\u0026thinsp;\u0026le;\u0026thinsp;Alb \u0026lt; 55)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25/64 (39.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh (Alb\u0026thinsp;\u0026ge;\u0026thinsp;55)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1/64 (1.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eComorbidities\u003c/h3\u003e\n\u003cp\u003eAmong the 89.2% of patients with underlying lung diseases, secondary tuberculosis and lung cancer were equally the most common (each 27%), followed by COPD (13.5%) and fungal infections (10.8%).Additionally, 4 patients had other malignancies, including lymphoma (n\u0026thinsp;=\u0026thinsp;2), colon cancer (n\u0026thinsp;=\u0026thinsp;1), and rectal cancer (n\u0026thinsp;=\u0026thinsp;1). Twelve patients (16.2%) had diabetes, 22 (29.7%) had hypoalbuminemia, and 10 (13.5%) had anemia(Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComorbidities\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eComorbidity\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003en (%) or count\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePulmonary diseases\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e66(89.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSecondary tuberculosis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20(27%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLung cancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20(27%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCOPD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10(13.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFungal infection\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8(10.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eAspergillus\u003c/em\u003e\u0026nbsp;pneumonia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003ePneumocystis jirovecii\u003c/em\u003e\u0026nbsp;pneumonia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePulmonary cryptococcosis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParagonimiasis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eChlamydia psittaci\u003c/em\u003e\u0026nbsp;infection\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eARDS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBronchiectasis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOld tuberculosis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInterstitial pneumonia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePulmonary epithelioid hemangioma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInflammatory pseudotumor of the lung\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMediastinal lymphadenitis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiabetes mellitus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12(16.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther malignancies\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4(5.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLymphoma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePostoperative colon cancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRectal cancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAntisynthetase syndrome\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHypoalbuminemia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e22(29.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnemia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10(13.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eMicrobiological characteristics\u003c/h2\u003e \u003cp\u003eTW was the sole pathogen detected by mNGS in only 17 patients (23.0%). Approximately two-thirds (64.9%) showed co-detection with other bacteria; the most common were Mycobacterium tuberculosis complex (18.9%), Haemophilus influenzae (17.6%), \u003cem\u003eStreptococcus pneumoniae\u003c/em\u003e (14.9%), \u003cem\u003eKlebsiella pneumoniae\u003c/em\u003e (13.5%), and \u003cem\u003ePseudomonas aeruginosa\u003c/em\u003e (12.2%). Nineteen patients (25.7%) had co-detection with fungi, including \u003cem\u003ePneumocystis jirovecii\u003c/em\u003e, \u003cem\u003eAspergillus\u003c/em\u003e, \u003cem\u003eCandida\u003c/em\u003e, and \u003cem\u003eCryptococcus\u003c/em\u003e. Twenty-five patients (33.8%) had DNA virus sequences detected, predominantly human herpesviruses (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCommon pathogens co-detected by mNGS\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCo-detected pathogen\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003en (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBacteria\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e48(64.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eMycobacterium tuberculosis\u003c/em\u003e\u0026nbsp;complex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e14(18.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eHaemophilus influenzae\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e13(17.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eStreptococcus pneumoniae\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e11(14.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eKlebsiella pneumoniae\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10(13.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003ePseudomonas aeruginosa\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e9(12.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eMoraxella catarrhalis\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3(4.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eStaphylococcus aureus\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2(2.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eAcinetobacter baumannii\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5(6.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFungi\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e19(25.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eAspergillus\u003c/em\u003e\u0026nbsp;spp.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5(6.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eCandida\u003c/em\u003e\u0026nbsp;spp.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5(6.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003ePneumocystis jirovecii\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8(10.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eCryptococcus neoformans\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1(1.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDNA Viruses\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e25(33.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHuman herpesviruses\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e23(31.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe TW sequence counts in these patients ranged from a few to over ten thousand (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Further analysis revealed that TW sequence counts were significantly lower in patients co-infected with \u003cem\u003eS. pneumoniae\u003c/em\u003e or \u003cem\u003eP. aeruginosa\u003c/em\u003e (P\u0026thinsp;=\u0026thinsp;0.038) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). In contrast, co-infection with M. tuberculosis complex, H. influenzae, or other pathogens did not significantly alter TW sequence counts (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05). Concurrently, patients with decreased hemoglobin had significantly higher TW sequence counts compared to the normal group (P\u0026thinsp;=\u0026thinsp;0.045). TW sequence counts were not influenced by decreased serum albumin (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eTreatment efficacy\u003c/h2\u003e \u003cp\u003eForty-one patients underwent chest CT re-examination one month later to evaluate treatment response, and 22 (53.7%) showed radiographic improvement. Among these 41 patients, 23 received anti-TW treatment, including: 10 with sulfonamides alone; 4 with ceftriaxone combined with sulfonamides; 3 with carbapenems; 2 with ceftriaxone; 2 with ceftriaxone combined with tetracycline; 1 with tetracycline; and 1 with tetracycline combined with sulfonamides. Univariate analysis found no significant difference in treatment efficacy between the anti-TW treatment group and the untreated group (P\u0026thinsp;=\u0026thinsp;0.295) (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparison of treatment efficacy against \u003cem\u003eT. whipplei\u003c/em\u003e\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo anti-TW treatment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAnti-TW treatment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eχ\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo improvement\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10(55.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9(39.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19(46.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e1.096\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.295\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eImprovement\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8(44.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14(60.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e22(53.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e41\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eCo-detection Patterns and Microbial Competition\u003c/h2\u003e \u003cp\u003eThis study comprehensively analyzed the clinical, imaging, and microbiological characteristics of \u003cem\u003eTropheryma whipplei\u003c/em\u003e (TW) pulmonary infection using mNGS of BALF. The findings indicate that TW often coexists with other respiratory pathogens, being the sole detected pathogen in only 23% of cases, which is close to the 29.8% reported by Lin M et al. [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e] and the 24.1% reported by Shen et al. [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. This raises important questions about the pathogenic role of TW in pulmonary infections, especially considering that 89.2% of the patients in this cohort had chronic underlying lung diseases. The detection of high TW sequence counts (exceeding 10,000 reads in some patients), coupled with systemic inflammatory responses (elevated CRP in 53.2%, elevated ESR in 62.5%) [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e], suggesting that TW may act as an active pathogen rather than mere colonization in certain clinical contexts. TW was frequently co-detected with other pathogens (\u003cem\u003eS. pneumoniae\u003c/em\u003e, \u003cem\u003eM. tuberculosis\u003c/em\u003e, \u003cem\u003eCandida\u003c/em\u003e, etc.) [\u003cspan additionalcitationids=\"CR13\" citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Notably, this study found that TW sequence counts decreased when co-detected with \u003cem\u003eS. pneumoniae\u003c/em\u003e or \u003cem\u003eP. aeruginosa\u003c/em\u003e (P\u0026thinsp;=\u0026thinsp;0.038), suggesting potential microbial competition within the respiratory microenvironment. These results are consistent with a recent report by Lai et al. [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e], who also observed lower TW reads in patients with bacterial co‑infections, although they did not distinguish between specific pathogens. Our finding that TW sequence counts were significantly lower in the presence of S. pneumoniae or P. aeruginosa suggests a complex ecological interaction within the lung microbiome, potentially indicative of direct microbial competition. As fast-growing, highly virulent pathogens, \u003cem\u003eS. pneumoniae\u003c/em\u003e and \u003cem\u003eP. aeruginosa\u003c/em\u003e may outcompete TW for nutritional resources or ecological niches within the respiratory tract. Furthermore, these common bacteria can induce a robust, acute inflammatory response and antimicrobial peptide production, potentially creating an inhospitable microenvironment for the slower-growing, intracellular TW. This suppressive effect was not observed with M. tuberculosis or H. influenzae, hinting that the nature of pathogen interaction is specific and not merely a consequence of any co-infection.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eClinical and Systemic Correlates\u003c/h2\u003e \u003cp\u003eThe clinical manifestations of TW-associated lung disease are non-specific [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. The most common symptoms in this cohort were cough (71.6%), expectoration (59.5%), and dyspnea (31.1%), overlapping with those of the underlying lung diseases. Radiologically, features such as patchy opacities (74.3%), multiple nodules (71.6%), and mediastinal lymphadenopathy (47.3%) might be more suggestive, consistent with previous studies [\u003cspan additionalcitationids=\"CR16\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e], though these findings also overlap with other pulmonary diseases. Laboratory abnormalities including anemia (58.1%), hypoalbuminemia (51.4%), and thrombocytosis (25.7%) reflect processes of chronic inflammation or malabsorption. We report a positive correlation between elevated TW sequence counts and the presence of anemia (P\u0026thinsp;=\u0026thinsp;0.045), representing a novel finding that has not been previously documented in prior investigations regarding pulmonary TW [\u003cspan additionalcitationids=\"CR5 CR6\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Anemia in these patients is unlikely to be coincidental; rather, it may reflect a state of chronic disease, similar to classic Whipple's disease[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Chronic inflammation, driven by TW infection, can lead to elevated hepcidin, resulting in iron sequestration and anemia of inflammation. Concurrently, the observed hypoalbuminemia suggests possible malabsorption or a nutritional deficiency state, which could be exacerbated by a chronic infectious process. This hematological abnormality could thus serve as a valuable clinical clue, pointing towards a more significant and active TW involvement rather than mere colonization.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eTreatment Efficacy and Underlying Reasons\u003c/h2\u003e \u003cp\u003eThe most noteworthy finding of this study is that targeted anti-TW treatment did not significantly improve clinical outcomes (P\u0026thinsp;=\u0026thinsp;0.295). This result provides direct support for the clinical decision framework we propose. Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e shows that among 41 patients with follow‑up CT, radiographic improvement occurred in 60.9% (14/23) of the anti‑TW group and 44.4% (8/18) of the untreated group, with no statistically significant difference observed between the groups. Thus, routine anti‑TW therapy is not supported by the current evidence. This result may be influenced by several factors. First, high prevalence of co-infections: 64.9% of patients had bacterial co-infections and 25.7% had fungal co-infections, the dominant clinical picture and radiographic findings were likely driven by these conventional pathogens. Treatment directed at these co-pathogens would resolve the primary infection, obscuring any incremental benefit from anti-TW agents. Second, host factors: the cohort predominantly included patients with significant underlying pulmonary comorbidities (89.2%) and immunocompromised conditions, which could confound the assessment of treatment response and contribute to overall slower recovery. Third, heterogeneity of treatment regimens: the lack of a standardized protocol led to varied antibiotic choices (sulfonamides, cephalosporins, carbapenems, tetracyclines) and durations, making it difficult to draw definitive conclusions about the efficacy of any specific regimen against pulmonary TW. Finally, colonization vs. true infection: it is plausible that in a substantial proportion of patients, especially those with low sequence counts and clear alternative pathogens, TW represented colonization or a bystander organism rather than a true pathogen necessitating treatment. Shen Y et al. documented a case of acute TW pneumonia where symptoms and imaging improved after ceftriaxone treatment [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Similarly, Huo Y et al. found that 7 patients with TW detected in BALF responded well to a combined imipenem-cilastatin and sulfamethoxazole regimen [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Conversely, Sun, L., etc. reported that TW in BALF frequently indicated oropharyngeal contamination rather than a true infection [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. These contrasting findings suggest the need for differentiated clinical management strategies: considering anti-TW treatment for cases with high TW sequence counts and no other definite pathogens detected, while prioritizing treatment for the main co-infecting pathogens in most cases with mixed infections.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eClinical Implications and a Proposed Framework\u003c/h2\u003e \u003cp\u003eSeveral limitations of this study must be acknowledged. These include its retrospective design, a limited sample size (n\u0026thinsp;=\u0026thinsp;74), and the lack of standardized treatment protocols. Future larger prospective studies with systematic follow-up mechanisms are needed to better define diagnostic criteria for TW pulmonary infection, elucidate its pathophysiological mechanisms, and develop evidence-based treatment guidelines. Particularly important is investigating TW's potential role as an opportunistic pathogen in immunocompromised hosts and its interaction mechanisms with the lung microbiome. Despite these limitations, this study provides an important basis for the clinical interpretation of TW detection in respiratory specimens and lays the groundwork for further research on this emerging pulmonary pathogen. Our study challenges the routine treatment of TW upon its detection by mNGS. More specifically, we propose a pragmatic framework for clinical decision-making: Consider Treatment when: (1) TW is the sole detected pathogen with high sequence counts; (2) Patients have persistent or progressive symptoms and radiographic infiltrates despite broad-spectrum antibiotics covering common pathogens; (3) There is supporting evidence of systemic involvement (e.g., unexplained anemia, hypoalbuminemia, arthralgia); and (4) In immunocompromised hosts with a high index of suspicion. Withhold or Defer Treatment when: (1) A classic primary pathogen (e.g., \u003cem\u003eS. pneumoniae\u003c/em\u003e, \u003cem\u003eM. tuberculosis\u003c/em\u003e) is identified and aligns with the clinical presentation; (2) TW sequence counts are low and the patient is improving with standard therapy; (3) The patient is asymptomatic with incidental findings, suggesting colonization.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusions","content":"\u003cp\u003eIn conclusion, the pathogenic role of TW in pulmonary infections requires further validation. Clinicians need to interpret mNGS results comprehensively along with clinical symptoms, imaging findings, and laboratory tests.For cases suspected of TW pathogenicity, multidisciplinary discussion is recommended to develop individualized treatment plans after weighing the pros and cons. As detection technology improves and clinical understanding grows, the exact role of TW in respiratory infections will become clearer.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eBALF: Bronchoalveolar lavage fluid\u003c/p\u003e\n\u003cp\u003eCRP: C‑reactive protein\u003c/p\u003e\n\u003cp\u003eCT: Computed tomography\u003c/p\u003e\n\u003cp\u003eESR: Erythrocyte sedimentation rate\u003c/p\u003e\n\u003cp\u003emNGS: Metagenomic next‑generation sequencing\u003c/p\u003e\n\u003cp\u003eTW: Tropheryma whipplei\u003c/p\u003e\n\u003cp\u003eWBC: White blood cell\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis retrospective study was conducted in accordance with the Declaration of Helsinki. The study was approved by the Institutional Review Board of Xinqiao Hospital, Army Medical University (Approval No.: 2025‑Yan Di‑369‑01). The requirement for informed consent was waived by the committee as the study involved minimal risk and utilized de‑identified data from routine clinical practice.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical trial number\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe requested an exemption from informed consent and provided the reasons in the ethical application. The documents listed in the original ethical approval file have been approved by the Ethical committee. Ethical committee approved our research, including the research plan, the format for releasing research results, and the informed consent form (exemption application).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData generated and/or analyzed in this study are not publicly available due to patient privacy regulations and institutional policies, but are available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study received no specific grant from any funding agency in the public, commercial, or not‑for‑profit sectors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u003c/strong\u003e\u003cstrong\u003e’\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eZW and XL (Xiaoli Luo) made equal contributions to this work. ZW and XL (Xiaoli Luo): data collection, data analysis, and manuscript drafting. CZ and JX: data curation and statistical support. MH and XC (Xiaolong Chen): conceptualization, design, supervision, and critical revision of the manuscript. All authors reviewed and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors thank BGI for providing technical support with sample processing. The use of professional writing services was not involved in the preparation of this manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u003c/strong\u003e\u003cstrong\u003e’\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;information\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eKorybski J, Zelig J, Narayanan S, et al. Deciphering whipple's disease complexity. 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Heliyon. 2024;10(4):e26747. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.heliyon.2024.e26747\u003c/span\u003e\u003cspan address=\"10.1016/j.heliyon.2024.e26747\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-infectious-diseases","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"infd","sideBox":"Learn more about [BMC Infectious Diseases](http://bmcinfectdis.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/infd","title":"BMC Infectious Diseases","twitterHandle":"#bmcinfectdis","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Tropheryma whipplei, pulmonary infection, metagenomic next-generation sequencing, microbiome, antimicrobial therapy, co-infection, anemia","lastPublishedDoi":"10.21203/rs.3.rs-9406285/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9406285/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eObjective\u003c/h2\u003e \u003cp\u003e \u003cem\u003eTropheryma whipplei\u003c/em\u003e (TW), the pathogen of Whipple's disease, has recently been identified as potentially pathogenic in respiratory infections through metagenomic next-generation sequencing (mNGS) technology. However, its clinical significance in lung infections is still unclear due to its frequent co-detection with other pathogens and the lack of diagnostic standards.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eWe retrospectively analyzed 74 patients with TW-positive bronchoalveolar lavage fluid (BALF) detected by mNGS from January 2018 to December 2022. Over the study period, a total of 1,543 BALF samples were subjected to mNGS analysis, resulting in a detection rate of 4.79% for TW. Clinical manifestations, imaging features, and microbiological data (including TW sequence quantification and co-pathogen profiles) were systematically evaluated. Treatment efficacy was assessed via follow-up CT in 41 patients.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThe cohort (mean age 55 years, 47.3% male) predominantly presented with cough (71.6%), expectoration (59.5%), and dyspnea (31.1%). Characteristic CT findings included patchy opacities (74.3%) and multiple nodules (71.6%). Laboratory abnormalities included anemia (58.1%), hypoalbuminemia (51.4%), and elevated inflammatory markers (CRP 53.2%, ESR 62.5%). TW was the sole pathogen in only 23.0% of cases, with common bacterial (64.9%) and fungal (25.7%) co-infections. Notably, TW sequence counts were significantly lower when co-infected with \u003cem\u003eStreptococcus pneumoniae\u003c/em\u003e or \u003cem\u003ePseudomonas aeruginosa\u003c/em\u003e (P\u0026thinsp;=\u0026thinsp;0.038) and were significantly higher in anemic patients (P\u0026thinsp;=\u0026thinsp;0.045). Targeted anti-TW therapy did not significantly improve radiographic outcomes in this cohort (P\u0026thinsp;=\u0026thinsp;0.295).\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eThis study suggests that respiratory TW often represents co-infection rather than primary pathogenicity. The bacterium exhibits complex ecological interactions within the lung microbiota and is associated with specific hematological abnormalities. These findings challenge the necessity of routine TW-targeted therapy in mixed infections and emphasize the need for diagnostic procedures integrating sequence quantification and clinical parameters.\u003c/p\u003e","manuscriptTitle":"Tropheryma whipplei in Pulmonary Infections: Microbial Competition with Streptococcus pneumoniae and Pseudomonas aeruginosa, Association with Anemia, and Lack of Benefit from Targeted Therapy - A Retrospective Cohort Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-05-15 02:35:40","doi":"10.21203/rs.3.rs-9406285/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2026-05-17T21:27:47+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"199218116803968518368245105532244648332","date":"2026-05-12T08:02:38+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-05-06T05:46:28+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-05-04T13:35:02+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-04-22T09:51:29+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-04-22T09:51:22+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Infectious Diseases","date":"2026-04-13T15:37:48+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-infectious-diseases","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"infd","sideBox":"Learn more about [BMC Infectious Diseases](http://bmcinfectdis.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/infd","title":"BMC Infectious Diseases","twitterHandle":"#bmcinfectdis","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"9f9598f7-c507-422c-acb3-fe33f53a8ecd","owner":[],"postedDate":"May 15th, 2026","published":true,"recentEditorialEvents":[{"type":"editorInvitedReview","content":"","date":"2026-05-17T21:27:47+00:00","index":88,"fulltext":""},{"type":"reviewerAgreed","content":"199218116803968518368245105532244648332","date":"2026-05-12T08:02:38+00:00","index":75,"fulltext":""},{"type":"reviewersInvited","content":"38","date":"2026-05-06T05:46:28+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-05-04T13:35:02+00:00","index":"","fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-15T02:35:40+00:00","versionOfRecord":[],"versionCreatedAt":"2026-05-15 02:35:40","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9406285","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9406285","identity":"rs-9406285","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}