Torquetenovirus from bronchoalveolar lavage fluid as a biomarker for lung infection among immunocompromised hosts

Abstract

Aim: Torquetenovirus (TTV) was a promising biomarker for immunity, while lung regional TTV for evaluating the opportunistic infection among immunocompromised hosts (ICH) was unclear.

Materials & methods: In the ICH and non-ICH populations, we compared the susceptibility to opportunistic infections, clinical severity and the prognosis between subgroups, respectively.

Results: ICH with detectable bronchoalveolar lavage fluid (BALF)-TTV were more susceptible to lung aspergillosis and Mycobacterium infections. Furthermore, our data demonstrated that the ICH cohort with detectable BALF-TTV represented a higher clinical severity and a worse prognosis, while the above findings were not found in the non-ICH population.

Conclusion: Our findings demonstrated that the BALF-TTV could act as an effective predictor for opportunistic infection for ICH that complemented the CD4⁺ T cell counts.

Plain language summary

Article highlights.

Background

• In clinical practice, the population base of immunocompromised host (ICH) and the incidence of severe infection complications are increasing.

• Torquetenovirus (TTV) was demonstrated to be associated with the immune constitution and immune-related adverse outcomes in post-transplant recipients independent of the CD4⁺ T cell count.

Methods

• The potential of lung regional TTV as a risk biomarker for ICH was investigated according to its relationship with lung opportunistic infections, clinical severity and clinical outcomes.

Results

• We found that the detectable TTV from bronchoalveolar lavage fluid (BALF) could act as an immune predictive biomarker for the susceptibility to opportunistic pathogens and prognosis for immunocompromised hosts independent of CD4⁺ T cell counts, while the above findings were not shown in the non-ICH population.

Conclusion

• We established a novel lung regional biomarker for predicting lung opportunistic infection.

• Furthermore, this study was likely to guide further studies to investigate the specific connection between TTV included lung microbial diversity and host immunity.

1. Background

Immunocompromised hosts (ICH) have an increased susceptibility to severe infection and higher immune-related mortality [1,2]. Due to the long-term steroid usage for the treatment of autoimmune diseases, longer duration of cancer chemotherapy and overuse of immunosuppressive drugs in organ transplant recipients, the severe infection complications and adverse clinical outcomes of ICH are increasing [3,4]. Notably, severe respiratory infections are the main reason for intensive care unit admission in immunocompromised patients and these patients are more likely to develop acute respiratory failure and sepsis, inducing a poor prognosis [5,6].

In clinical practice, timely life-supporting interventions as well as the early recognition of responsible pathogens are important among ICH [7,8]. Failure to identify the etiology of acute respiratory failure is associated with a higher mortality rate, making it a clinical crisis [5,9]. To date, there is still no consensual predictive biomarker for the susceptibility to opportunistic pathogenic infections and prognosis among ICH. The search for effective predictors of susceptibility to opportunistic pathogens and predictors of prognosis for ICH to enhance their therapeutic guidance is becoming increasingly important and urgent.

The value of CD4⁺ T cell count as a biomarker for ICH is highly controversial. Some studies demonstrated the correlation between immune deficiency and the lower CD4⁺ T lymphocyte level [10,11]. However, due to the finding from other studies that T lymphocyte levels could normalize without full functional recovery, the performance of CD4⁺ T lymphocyte level as a biomarker for systemic immunity is inevitably limited [12–14]. Therefore, there is an urgent need to find complementary predictive biomarkers for ICH.

Torquetenovirus (TTV), as a promising biomarker for immunity, was demonstrated to be associated with the immune constitution and immune-related adverse outcomes in post-transplant recipients [15–17]. TTV is a ubiquitous, nonenveloped DNA virus from the Anelloviridae family with no known pathogenicity [15]. Notably, recent studies have shown that TTV could be a potential predictive biomarker for the severity of lung infections, and some studies indicated lung microbiomes would become one of the useful biomarkers for respiratory diseases and host immunity [18,19]. Therefore, exploration of the value of TTV in lung regional immunity is of great value, for it might predict the deterioration in critical events of severe lung infection. However, previous studies mainly focused on the correlation between peripheral blood TTV deoxyribonucleic acid (DNA) and the intensity of host immunosuppression in post-transplant patients [15,16,20,21], and the predictive value of lung regional TTV for ICH has not yet been evaluated.

In this study, we aimed to investigate the potential of detective TTV DNA from bronchoalveolar lavage fluid (BALF) as a predictive biomarker for the susceptibility to opportunistic pathogenic infections and prognosis among ICH, thus complementing CD4⁺ T cell counts as an immune predictive biomarker.

2. Materials & methods

2.1. Patients

This study protocol was approved by the Ethics Committee of The First Affiliated Hospital of Soochow University (Ic 317 in 2022). We retrospectively analyzed the data of 98 patients with suspected pneumonia who have received metagenomic next-generation sequencing (mNGS) of BALF at The First Affiliated Hospital of Soochow University between January 2020 and May 2022. The First Affiliated Hospital of Suzhou University is located in Suzhou, a city with more than 10 million permanent residents in southeastern China. The patients enrolled in this study were all permanent residents of Suzhou. BALF samples for mNGS were collected from all enrolled patients within 48 h after admission. Suspected pneumonia must fulfill all the following criteria: there are related clinical symptoms, such as new-onset fever, cough or dyspnoea; new-onset radiological findings on chest images; the above manifestations were considered highly suspicious for lung infection by two or more specialists.

2.2. mNGS of BALF samples

Samples of 1.5–3 ml BALF were collected from all enrolled patients according to standard procedures and mNGS was performed less than 30 min after each sample was collected. DNA sequencing libraries were constructed for each patient through DNA fragmentation, end-repair, adapter ligation and polymerase chain reaction amplification.

The laboratory operation includes pretreatment of the sample to be tested, nucleic acid extraction, library construction and high-throughput sequencing to obtain nucleic acid sequencing data. First, the specimen should be preprocessed. In order to improve the sensitivity of mNGS detection, the pathogens or their nucleic acids were selected for enrichment during the sample pretreatment process, and the forward enrichment method and the reverse enrichment method were selected. The forward enrichment method refers to the enrichment of pathogens (nucleic acids) after nucleic acid extraction, represented by polymerase chain reaction enrichment and probe capture; the reverse enrichment method is the de-host technology, including differential centrifugation, differential cleavage, methylation antibody treatment and other processes. Second, nucleic acid extraction is required, which includes nucleic acid release and nucleic acid purification. Following that, the DNA library was constructed. Then, high-throughput sequencing was performed. In order to reduce the false positives caused by label hopping, this process uses a dual-label sequencing mode.

Agilent 2100 was used for quality control of the libraries. Qualified libraries were then sequenced on the BGISEQ-50/MGISEQ-2000 platform. The nucleic acid sequence of microorganisms in the sample was analyzed by a dehumanized host nucleic acid technology-HUGO (Humanized Genomic Ortholog). HUGO is a de-humanized host nucleic acid technology that can increase the microbial genome sequence in the total sequence percentage of the sample DNA by 10–100-times, achieving DNA enrichment of pathogenic microorganisms and dramatically increasing the sensitivity of detection. After the removal of non-compliant reads, the remaining data were classified by simultaneous alignment with five microbial genome databases, including viruses, bacteria, fungi, mycobacteria and parasites. RefSeq includes 9233 whole-genome sequences of viral taxa, 7044 bacterial genomes or scaffolds, 2890 fungi related to human infection, 635 sequences of mycobacteria and 172 parasites associated with human diseases. Generally, the presence of the TTV is defined when the number of detected TTV sequences or normalized sequences of TTV is ≥ 3 and the genomic coverage of these sequences is ≥ 10% in the sample reads.

2.3. Data collection

For every enrolled patient, demographic data, underlying diseases, imaging information, the results of laboratory tests including microbiological testing and quantitative plasma CD4⁺ T cell immunoassays, illness severity information and clinical outcomes data were collected from the electronic medical record.

2.4. Definitions

ICH was defined as any of the following: patients with autoimmune diseases requiring long-term (>3 months) steroids (>0.3 mg/Kg/day) or other cytotoxic drugs; with hematological malignancy or with solid tumor requiring chemotherapy over the past year; or Patients receiving transplantation within 1 year [22]. The Sequential Organ Failure Assessment (SOFA) score is based on the 1994 proposal of the European Society of Intensive Care Medicine [23]. Septic shock was defined according to the third international consensus definition for septic shock (sepsis-3) criteria [24]. The diagnosis of aspergillosis is based on the 2016 proposal by the Infectious Diseases Society of America and should meet all the following criteria: imaging abnormalities, such as cavitation and fungal spheres; elevated Aspergillus IgG antibodies or other microbiological evidence such as positive Aspergillus cultures from sputum, BALF or lung tissue, positive serum galactomannan (GM) test or pathological evidence of aspergillosis [25]. The GM test for Aspergillus is one of the classical serologic methods for the detection of Aspergillus infections, and its main test substance is the GM antigen. Mycobacterium infection includes tuberculosis and nontuberculous mycobacteria. Tuberculosis was diagnosed by the previous history of environmental exposure to Tuberculosis, clinical findings, lung involvement on chest radiograph or positron emission tomography/computed tomography (PET/CT) scan, microbiological testing and strain identification [26]. The diagnosis of nontuberculous mycobacteria is based on the criteria issued by The American Thoracic Society and Infectious Diseases Society of America in 2007 [27].

2.5. Statistical analysis

Continuous variables were described by mean values (standard deviations), and categorical variables were described by numbers (percentages). Student t-test was used to compare continuous variables and the Chi-square test or Fisher’s exact test was for categorical group comparisons. Kaplan–Meier’s estimates were employed to determine the probability of 28-day survival and differences were determined using the Log-rank test. Statistical analysis was performed using SPSS (ver.23, Armonk, US) and Graphpad Prism (ver. 8, La Jolla, US). For all analyses, a two-tailed p-value < 0.05 was considered significant.

3.1. Demographics

A total of 98 patients were enrolled in this study. Patients were divided into the BALF-TTV-positive (n = 24) and negative (n = 74) groups according to the mNGS testing results. Meanwhile, patients were also grouped as ICH (n = 35) and non-ICH (n = 63) according to their immune status and diagnostic criteria. Actually, there were 22 TTV-negative patients in the ICH group and 11 TTV-positive patients in the non-ICH group.

As shown in Table 1, the median age of the TTV-positive subjects was 62.3 years, which is comparable to that of the TTV-negative group. The majority gender in both groups were males and there was no significant difference between the two groups (79.2 vs 66.2%, p = 0.200). As for the underlying diseases, no significant differences were found in the proportion of diabetes, chronic obstructive pulmonary disease, asthma and malignant disease between the two groups (p < 0.05 for each).

Table 1.

Baseline characteristics of the study subjects.

Variates	TTV (n = 24)	Non-TTV (n = 74)	p-value
Age (years)	62.3 (57.5 – 67.0)	57.4 (53.3 – 61.4)	0.232
Gender (male)	19 (79.2%)	49 (66.2%)	0.200
Diabetes	5 (20.8%)	12 (16.2%)	0.604
COPD	3 (12.5%)	10 (13.5%)	0.603
Asthma	2 (8.3%)	3 (4.1%)	0.356
Malignance	7 (29.2%)	12 (16.2%)	0.137

COPD: Chronic obstructive pulmonary disease; TTV: Torquetenovirus.

3.2. BALF-TTV was more commonly detectable in subjects with ICH

Consistent with a previous observation [10], our data showed the absolute plasma CD4⁺ T cell count of the ICH group was lower than that of the non-ICH group (272 vs 433/μl, p = 0.027), and a higher proportion of patients with CD4⁺ <200/μl was depicted in the ICH group (38.1 vs 23.3%, p = 0.049) (Figure 1A & B), while it was noticed that a decreased absolute CD4⁺ T cell count was not found in all of our ICH subjects. Possibly, additional biomarkers other than the CD4⁺ T cell count would be responsible for the immunocompromised status. Considering the significance of TTV detection in the immune monitoring of post-transplant recipients, then we investigate the predictive potential of detectable TTV from BALF for ICH.

Figure 1.

Bronchoalveolar lavage fluid-torquetenovirus was more commonly detectable in immunocompromised hosts. (A) The absolute CD4⁺ T cell number of the ICH cohort was significantly lower than that of the non-ICH cohort (272 vs 433 /μl, p = 0.027). (B) The ICH cohort has a higher proportion of subjects with CD4⁺ <200/μl compared with the non-ICH cohort (38.1 vs 23.3%, p = 0.049). (C) BALF-TTV was more commonly detectable in the ICH cohort (37.1 vs 17.5%, p = 0.030). (D) In ICH cohort, the absolute CD4⁺ T cell count was comparable in subjects with or without detectable BALF-TTV (p > 0.05 for each).

BALF: Bronchoalveolar lavage fluid; ICH: Immunocompromised hosts; TTV: Torquetenovirus.

Accordingly, a higher proportion of detectable BALF-TTV was found in ICH relative to the non-ICH cohort (37.1 vs 17.5%, p = 0.030). We then tried to explore the relationship between the CD4⁺ T cell count and the detectable BALF-TTV. Interestingly, the plasma CD4⁺ T cell counts were comparable between the BALF-TTV positive and negative subgroups from the ICH cohort (235 vs 316/μl, p = 0.148), implying the possibility of detectable TTV in BALF as an additional biomarker for ICH irrespective of CD4⁺ T cell count.

3.3. ICH with detectable BALF-TTV were more susceptible to aspergillosis or Mycobacterium infection

Aspergillus and mycobacteria are common opportunistic pathogens of lung infection in ICH. First, we investigated the association between absolute CD4⁺ T cell number and prevalence of lung Aspergillus and Mycobacterium infections. By establishing the CD4⁺ T cell count of 200/μl as the cutoff value, the proportion of lower CD4⁺ T cell count was comparable between the Aspergillus(+) and the Aspergillus(-) group in either ICH as well as the non-ICH population (36.4 vs 16.7%, p = 0.198; 14.3 vs 10.7%, p = 0.777; respectively) (Figure 2A & B). Similarly, the proportion of lower CD4⁺ T cell count was comparable between the mycobacteria(+) and the mycobacterium (-) group in either ICH as well as the non-ICH population (42.9 vs 17.9%, p = 0.159; 40.0 vs 10.4%, p = 0.124) (Figure 2C & D). The above data indicated that the lower CD4⁺ T cell count in the prediction of opportunistic infections was unsatisfactory in people with different immune status.

Figure 2.

Association between absolute CD4⁺ T cell number and the incidence of lung Aspergillus and Mycobacterium infections. (A & B) The proportion of lower CD4⁺ T cell count was comparable between the Aspergillus(+) and the Aspergillus(-) group in either ICH as well as the non-ICH population (36.4 vs 16.7%, p = 0.198; 14.3 vs 10.7%, p = 0.777; respectively). (C & D) The proportion of lower CD4⁺ T cell count was comparable between the Mycobacterium(+) and the Mycobacterium(-) group in either ICH as well as the non-ICH population (42.9 vs 17.9%, p = 0.159; 40.0 vs 10.4%, p = 0.124).

ICH: Immunocompromised hosts.

Following that, we investigated the prevalence of lung Aspergillus and Mycobacterium infection in subjects with detectable BALF-TTV (Figure 3). Notably, our data showed that in ICH, a higher proportion of BALF-TTV(+) was found in the Aspergillus(+) group compared with the Aspergillus (-) group (54.6 vs 29.2%, p = 0.035) (Figure 3A). Similarly, in ICH, a higher proportion of BALF-TTV(+) was found in the Mycobacteri (+) group (85.7 vs 25.0%, p = 0.006) (Figure 3C), while the above finding was not shown in the non-ICH population (p > 0.05 for each) (Figure 3B & D). The odds ratio (OR) of BALF-TTV(+) for the Aspergillus infection was 5.25 (95% CI: 1.23–24.42) and the OR of BALF-TTV(+) for the Mycobacterium infection was 18.00 (95% CI: 1.84–176.56).

Figure 3.

Association between bronchoalveolar lavage fluid-torquetenovirus(+) and the incidence of lung Aspergillus and Mycobacterium infections. (A) In ICH, a higher proportion of BALF-TTV(+) was found in the Aspergillus(+) group compared with the Aspergillus (-) group (54.6 vs 29.2%, p = 0.035). (B) In non-ICH, the proportion of BALF-TTV(+) was comparable between the Aspergillus(+) and the Aspergillus(-) group. (C) In ICH, a higher proportion of BALF-TTV(+) was found in the Mycobacteri(+) group (85.7 vs 25.0%, p = 0.006). (D) In non-ICH, the proportion of BALF-TTV(+) was comparable between the Mycobacteri(+) and the Mycobacteri(-) group.

BALF: Bronchoalveolar lavage fluid; ICH: Immunocompromised hosts; TTV: Torquetenovirus.

We then further explored the predictive ability of BALF-TTV and lower CD4⁺ T cell count (<200/μl) for the occurrence of opportunistic pathogens in the ICH population. The sensitivity, specificity and Youden index of the biomarkers were calculated. The data showed that in the ICH population, the Youden index of BALF-TTV(+) for opportunistic infection prediction was 0.52, with a predictive sensitivity of 72.73% and a specificity of 79.17%. The Youden index of lower CD4⁺ T cell count (<200/μl) for opportunistic infection prediction was 0.18, with a predictive sensitivity of 42.86% and a specificity of 75.00%.

The data above together suggested that detectable BALF-TTV might be a better predictive biomarker for opportunistic pathogenic infections in ICH than the absolute CD4⁺ T cell number.

3.4. Detectable TTV in BALF in subjects with ICH represented increased clinical severity

We also hypothesized that detectable TTV in BALF could more accurately reflect increased clinical severity compared with CD4⁺ T cell count. Considering that all enrolled patients received mNGS testing of the BALF and were at risk for disease progression, including non-ICH patients, this study applied the SOFA score in both the ICH group and the non-ICH group to assess the clinical severity. Furthermore, the incidence of septic shock was also selected as a comparative indicator of disease severity between subgroups.

As expected, we found the clinical severity was comparable regardless of the CD4⁺ T cell count in ICH (p > 0.05) (Table 2). In contrast with the above finding, our data showed in the ICH cohort, a higher SOFA score and incidence of septic shock were shown in the TTV-positive group than that in the TTV-negative group (6 vs 3, p = 0.043; 29.2 vs 9.5%, p = 0.017; respectively). These results indicated that detectable TTV in BALF represented an increased clinical severity in ICH subjects.

Table 2.

Association between clinical severity and torquetenovirusdetection results or CD4⁺ T cell count.

Variates	CD4+<200/μl (n=15)	CD4+≥200/μl (n = 36)	p-value	TTV (+) (n = 24)	TTV (–) (n = 74)	p-value
SOFA score	4 (3 – 7)	3 (2 – 4)	0.104	4 (2 – 5)	2 (1 – 3)	0.011
ICH	5 (4 – 8)	3 (2 – 4)	0.064	6 (4 – 8)	3 (2 – 5)	0.043
Non-ICH	3 (1 – 4)	2 (1 – 3)	0.786	2 (0 – 4)	2 (1 – 2)	0.786
Septic shock	7 (46.7%)	9 (25.0%)	0.118	10 (41.7%)	13 (17.6%)	0.015
ICH	6 (40.0%)	5 (13.9%)	0.119	7 (29.2%)	7 (9.5%)	0.017
Non-ICH	1 (6.7%)	4 (11.1%)	0.384	3 (12.5%)	6 (8.1%)	0.384

p-values less than 0.05 are highlighted in bold.

ICH: Immunocompromised hosts; SOFA score: Sequential organ failure assessment score; TTV: Torquetenovirus.

3.5. Detectable TTV in BALF from ICH exhibited a higher mortality risk in ICH subjects

Finally, based on the Kaplan–Meier analysis, the predictive value of lower CD4⁺ T cell count, as well as detectable TTV in BALF on mortality risk, were investigated (Figure 4). Our data showed that between the higher and lower CD4⁺ T cell count group, the mortality risk was comparable in both ICH and non-ICH cohort (p > 0.05 for each). In contrast to the above finding, it was noticed that in the ICH cohort, higher mortality risk was found in the TTV-positive group compared with the TTV-negative group (~lc ratio: 2.79; 95% CI: 0.89–7.93; p = 0.029), while in the non-ICH cohort, the 28-day mortality risk was found comparable between the subgroups (p = 0.188). The above findings indicated that detectable TTV in BALF might be a prognostic biomarker for ICH.

Figure 4.

Kaplan–Meier survival analysis for estimating the 28-day survival. (A & B) In both ICH and non-ICH cohort, the absolute CD4⁺ T cell numbers were not related to the mortality risk; (C & D) In the ICH cohort, higher mortality risk was found in the TTV-positive group compared with the TTV-negative group (HR: 2.79; 95% CI: 0.89– 7.93; p = 0.029). In the non-ICH cohort, the 28-day mortality risk was found comparable between the BALF-TTV positive and negative subgroups.

BALF: Bronchoalveolar lavage fluid; HR: Hazard ratio; ICH: Immunocompromised hosts; TTV: Torquetenovirus.

4. Discussion

The easier access to mNGS in recent years has revolutionized our understanding of lung mycobiome, not only enabling us to find pathogens comprehensively but also facilitating our exploration of regional immune biomarkers [22,28,29]. To our knowledge, previous studies mainly focused on the correlation between the intensity of host immunosuppression and CD4⁺ T cell count [30–32] as well as the peripheral blood TTV load, and little of them focused on the predictive value of TTV as a microorganism in the lung region [14,21,33–35]. Additionally, though lung infections are a major contributor to mortality in ICH, the predictive and prognostic potential of TTV in regional immunity has not yet been well explored [2,18,36]. Under these circumstances, the investigation of detectable TTV in BALF as a biomarker for ICH was technically realizable and clinically meaningful.

The potential of CD4⁺ T lymphocyte level as a predictive biomarker for ICH in our study was unsatisfying. Though our data showed a lower CD4⁺ T cell count in the ICH group, no association was found between CD4⁺ T cell count and susceptibility to lung immune-related pathogens infection or clinical severity in ICH. This finding is consistent with reports of the deficiency of CD4⁺ T cell count for the immunological function prediction [11,13]. Interestingly, as for the relationship between positive TTV in BALF and the CD4⁺ T cell count, our data indicated detectable TTV in BALF was irrespective of CD4⁺ T cell count. This finding further suggested that pulmonary regional TTV might be a complementary biomarker for ICH to be explored.

The mNGS enabled us to better discover the spectrum of the microbiome in the lung region, including TTV and explore their potential effects on the lung [37,38]. Previous studies demonstrated that interactions between the lung mycobiome were influenced by host immunity, and the microbiomes are likely to be further important factors in shaping lung inflammatory response [39–41]. In addition, some studies have reported the significant value of mNGS in the diagnosis of suspected infections in ICH [42–44].

In this study, we observed 37.1% ICH of the study subjects with detectable TTV DNA in BALF, relatively higher than the 20.9% that Lingai Pan et al. [45] found in a study of a smaller size. In addition to previous findings demonstrating the potential of plasma TTV load as a biomarker for ICH [20,21], some research has shown that the lung microbiomes might be important factors in shaping lung inflammatory response, and it was expected that the lung microbiomes would become one of the useful biomarkers for respiratory diseases and clinical settings [39–41]. The present study showed that compared with the non-ICH group, the proportion of detectable TTV was higher in the ICH, confirming the possible predictive potential of detectable TTV of BALF for systemic immunity of the host. Moreover, given the fact that TTV is a part of the environment of lung microorganisms, the detectable TTV in BALF made our study more convincing in further exploring its role in regional immunity.

Recent studies showed that lung Aspergillus or Mycobacterium infection was susceptible to relative and/or absolute immune dysregulation in ICH, which could induce adverse manifestations from colonization and sensitization to more invasive diseases [26,46,47]. As expected, our data also showed a higher prevalence of lung aspergillosis and Mycobacterium infection in the TTV-positive group of ICH. This finding suggested that detectable TTV in BALF could reflect the susceptibility of pathogenic bacteria infections in the lung of ICH, which indirectly indicated the predictive potential of pulmonary regional TTV on lung regional immunity for ICH.

Several studies also have shown that in non-ICH, the plasma TTV load was associated with adverse implications in patients with lung infection, implicating that in non-ICH, TTV might associated with regional immunity regardless of the systemic immunity of the host [18,48]. However, the above findings were not implied in the non-ICH in our data. Given the different baseline characteristics and different types of pathogenic lung infections in the study population among these studies, more exploration is needed to obtain a relatively consistent conclusion.

Many recent studies have established a critical role TTV plays in reflecting disease severity and poor prognosis [20,49]. It was noticed that TTV was demonstrated to be a potentially useful biomarker to assess the immune constitution and clinical outcomes in hematopoietic stem cell transplant recipients [11,50,51]. Consistent with the above findings, in the present study, the higher SOFA score and higher incidence of septic shock in the TTV-positive group in ICH implied the presence of lung regional TTV might be used to evaluate the severity of ICH. Moreover, our data also showed a higher mortality risk of ICH when TTV was detectable in BALF, suggesting the prognostic predictive value of lung regional TTV for ICH.

Though we have tried to minimize the occurrence of relevant bias by including more samples and relatively sufficient analysis, there are still some limitations of the research. This study is a single-center study. A relatively small sample size may lead to selection bias and more research is needed to verify the accuracy of the results in the future. In addition, this study may exist confounding variables that are unevenly distributed between groups, resulting in potential confounding bias. At present, the sequence numbers mNGS do not represent the nucleic acid copy number of pathogens, but they can reflect the presence/absence as well as the relative quantification of both background and pathogenic microorganisms. Since we mainly explore the predictive value of the detective lung regional TTV for ICH, the investigation of the kinetics of the TTV sequences in the BALF was not conducted in this study. Even so, the relationship of lung regional TTV with the prediction and prognosis of ICH depicted in this study was likely to guide further studies investigating the specific connection between TTV-included lung microbial diversity and host immunity. Additionally, the cytokine and metabolites from BALF samples were not available in the present study. Further studies on the functional effects of key structural ligands and microbial metabolites on lung immunity are still needed.

5. Conclusion

With the help of mNGS, we detected the TTV DNA in the BALF of the study subjects and studied the potential of lung regional TTV as a predictive marker for ICH. Our findings indicated that the detectable TTV from BALF could be a complementary predictive and prognostic biomarker for ICH. Furthermore, the relationship of lung regional TTV with the prediction of ICH found in this study was likely to guide further studies investigating the specific connection between TTV-included lung microbial diversity and host immunity.

Funding Statement

The project was supported by grant of Suzhou City (grant number SYS2021034) and Jiangsu Provincial Medical Key Discipline (grant number ZDXK202201).

Author contributions

C Chen conceived the idea, designed it and supervised the study. ZW Zhu and Y Wang designed and performed the statistical analysis. WW Ning and C Liu participated in clinical care and data collection. All authors wrote, reviewed, and approved the final version of the manuscript.

Financial disclosure

The project was supported by grant of Suzhou City (grant number SYS2021034) and Jiangsu Provincial Medical Key Discipline (grant number ZDXK202201). The funders had no role in the study design, data collection and analysis, decision to publish or preparation of the manuscript. This study also supported by group of the wild goose formation leading flight plan and author Cheng Chen is one of the team members. The funders had no role in the study design, data collection and analysis, decision to publish or preparation of the manuscript. The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed.

Competing interests disclosure

The authors have no competing interests or relevant affiliations with any organization or entity with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, stock ownership or options and expert testimony.

Writing disclosure

No writing assistance was utilized in the production of this manuscript.

Ethical conduct of research

The authors state that they have obtained appropriate institutional review board approval (This study was approved by the Institutional Review Boards of The First Affiliated Hospital of Soochow University [Ic. 317 in 2022]) and/or have followed the principles outlined in the Declaration of Helsinki for all human or animal experimental investigations.

In addition, for investigations involving human subjects, informed consent has been obtained from the participants involved.