Clinical usefulness of metagenomic next-generation sequencing for the diagnosis of central nervous system infection in people living with HIV

Microbiomes detected by cerebrospinal fluid metagenomic next-generation sequencing among patients with and without HIV with suspected central nervous system infection

BACKGROUND

Opportunistic infections in the central nervous system (CNS) can be a serious threat to people living with HIV. Early aetiological diagnosis and targeted treatment are crucial but difficult. Metagenomic next-generation sequencing (mNGS) has significant advantages over traditional detection methods. However, differences in the cerebrospinal fluid (CSF) microbiome profiles of patients living with and without HIV with suspected CNS infections using mNGS and conventional testing methods have not yet been adequately evaluated.

METHODS

We conducted a retrospective cohort study in the first hospital of Changsha between January 2019 and June 2022 to investigate the microbiomes detected using mNGS of the CSF of patients living with and without HIV with suspected CNS infections. The pathogens causing CNS infections were concurrently identified using both mNGS and traditional detection methods. The spectrum of pathogens identified was compared between the two groups.

RESULTS

Overall, 173 patients (140 with and 33 without HIV) with suspected CNS infection were enrolled in our study. In total, 106 (75.7%) patients with and 16 (48.5%) patients without HIV tested positive with mNGS (p = 0.002). Among the enrolled patients, 71 (50.7%) with HIV and five (15.2%) without HIV tested positive for two or more pathogens (p < 0.001). Patients with HIV had significantly higher proportions of fungus (20.7% vs. 3.0%, p = 0.016) and DNA virus (59.3% vs. 21.2%, p < 0.001) than those without HIV. Epstein-Barr virus (33.6%) was the most commonly identified potential pathogen in the CSF of patients living with HIV using mNGS, followed by cytomegalovirus (20.7%) and torque teno virus (13.8%). The top three causative pathogens identified in patients without HIV were Streptococcus (18.2%), Epstein-Barr virus (12.1%), and Mycobacterium tuberculosis (9.1%). In total, 113 patients living with HIV were diagnosed as having CNS infections. The rate of pathogen detection in people living with HIV with a CNS infection was significantly higher with mNGS than with conventional methods (93.8% vs. 15.0%, p < 0.001).

CONCLUSION

CSF microbiome profiles differ between patients living with and without HIV with suspected CNS infection. mNGS is a powerful tool for the diagnosis of CNS infection among people living with HIV, especially in those with mixed infections.

Nanopore targeted sequencing-based diagnosis of central nervous system infections in HIV-infected patients

BACKGROUND

Early and accurate etiological diagnosis is very important for improving the prognosis of central nervous system (CNS) infections in human immunodeficiency virus (HIV)-infected patients. The goal is not easily achieved by conventional microbiological tests. We developed a nanopore targeted sequencing (NTS) platform and evaluated the diagnostic performance for CNS infections in HIV-infected patients, with special focus on cryptococcal meningitis (CM). We compared the CM diagnostic performance of NTS with conventional methods and cryptococcal polymerase chain reaction (PCR).

METHODS

This study included 57 hospitalized HIV-infected patients with suspected CNS infections from September 2018 to March 2022. The diagnosis established during hospitalization includes 27 cases of CM, 13 CNS tuberculosis, 5 toxoplasma encephalitis, 2 cytomegalovirus (CMV) encephalitis and 1 Varicella-zoster virus (VZV) encephalitis. The 2 cases of CMV encephalitis also have co-existing CM. Target-specific PCR amplification was used to enrich pathogen sequences before nanopore sequencing. NTS was performed on stored cerebrospinal fluid (CSF) samples and the results were compared with the diagnosis during hospitalization.

RESULTS

53 (93.0%) of the patients were male. The median CD4 cell count was 25.0 (IQR: 14.0-63.0) cells/uL. The sensitivities of CSF culture, India ink staining, cryptococcal PCR and NTS for CM were 70.4% (95%CI: 51.5 - 84.1%), 76.0% (95%CI: 56.6 - 88.5%), 77.8% (59.2 - 89.4%) and 85.2% (95%CI: 67.5 - 94.1%), respectively. All those methods had 100% specificity for CM. Our NTS platform could identify Cryptococcus at species level. Moreover, NTS was also able to identify all the 5 cases of toxoplasma encephalitis, 2 cases of CMV encephalitis and 1 VZV encephalitis. However, only 1 of 13 CNS tuberculosis cases was diagnosed by NTS, and so did Xpert MTB/RIF assay.

CONCLUSIONS

NTS has a good diagnostic performance for CM in HIV-infected patients and may have the ability of simultaneously detecting other pathogens, including mixed infections. With continuing improving of the NTS platform, it may be a promising alterative microbiological test for assisting with the diagnosis of CNS infections.

Metagenomic next-generation sequencing for diagnosis of infectious encephalitis and meningitis: a retrospective study of 90 patients

BACKGROUND

Infections of the central nervous system (CNS) are potentially life-threatening and can cause serious morbidity. We evaluated the clinical value of metagenomic next-generation sequencing (mNGS) in the diagnosis of infectious encephalitis and meningitis and explored the factors affecting the results of mNGS.

METHODS

Patients with suspected cases of encephalitis or meningitis who presented in Northern Jiangsu People's Hospital from 1 March 2018 to 30 September 2022 were collected. Demographic, historical, and clinical information were obtained, and cerebrospinal fluid (CSF) samples were treated with mNGS. The pathogen was identified using National Center for Biotechnology Information (NCBI) GenBank sequence data.

RESULTS

Ninety-six patients were screened and finally 90 subjects enrolled. Of the 90 enrolled cases, 67 (74.4%) were diagnosed with central nervous system infections, which included 48 cases (71.6%) of viral infection, 11 (12.2%) of bacterial infection, 5 (7.5%) of mycobacterium tuberculosis, 2 (3.0%) of fungal infection, and 1 (1.5%) of rickettsia infection. From these cases, mNGS identified 40 (44.4%) true-positive cases, 3 (3.3%) false-positive case, 22 (24.4%) true-negative cases, and 25 (27.8%) false-negative cases. The sensitivity and specificity of mNGS were 61.5% and 88%, respectively. mNGS of CSF could show a higher positive rate in patients with marked CSF abnormalities, including elevated protein concentrations and monocyte counts.

CONCLUSION

mNGS of CSF is an effective method for detecting infectious encephalitis and meningitis, and the results should be analyzed combined with conventional microbiological testing results.

Economic impact of metagenomic next-generation sequencing versus traditional bacterial culture for postoperative central nervous system infections using a decision analysis mode: study protocol for a randomized controlled trial

IMPORTANCE

Diagnosing and treating postoperative central nervous system infections (PCNSIs) remains challenging due to the low detection rate and time-consuming nature of traditional methods for identifying microorganisms in cerebrospinal fluid. Metagenomic next-generation sequencing (mNGS) technology provides a rapid and comprehensive understanding of microbial composition in PCNSIs by swiftly sequencing and analyzing the microbial genome. The current study aimed to assess the economic impact of using mNGS versus traditional bacterial culture-directed PCNSIs diagnosis and therapy in post-neurosurgical patients from Beijing Tiantan Hospital. mNGS is a relatively expensive test item, and whether it has the corresponding health-economic significance in the clinical application of diagnosing intracranial infection has not been studied clearly. Therefore, the investigators hope to explore the clinical application value of mNGS detection in PCNSIs after neurosurgery.

Coinfection of SARS-CoV-2 and influenza A (H3N2) detected in bronchoalveolar lavage fluid of a patient with long COVID using metagenomic next-generation sequencing: a case report

The growing number of long COVID cases has drawn clinical attention to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which has been spreading worldwide since winter 2019. Its symptoms are not limited to fatigue and shortness of breath but also affect daily life. We report the use of metagenomic next-generation sequencing (mNGS) to detect coinfection with SARS-CoV-2 and influenza A virus in a patient with long COVID. The patient was admitted with fever, expectoration, fatigue, and shortness of breath. The PCR test was negative due to possible clearance of SARS-Cov-2 in the upper respiratory tract of patients with long COVID. Other routine microbiological tests were also negative, making the clinical diagnosis difficult. Bronchoalveolar lavage fluid (BALF) samples were tested using mNGS. The patient was diagnosed and treated promptly, recovered quickly, and continued taking azvudine after discharge; his condition was stable. This study illustrates that mNGS may be valuable for the timely diagnosis of patients with long COVID and their mixed infections.

The application of metagenomic next-generation sequencing in pathogen diagnosis: a bibliometric analysis based on Web of Science

Background

Infectious disease is a large burden on public health globally. Metagenomic next-generation sequencing (mNGS) has become popular as a new tool for pathogen diagnosis with numerous advantages compared to conventional methods. Recently, research on mNGS increases yearly. However, no bibliometric analysis has systematically presented the full spectrum of this research field. Therefore, we reviewed all the publications associated with this topic and performed this study to analyze the comprehensive status and future hotspots of mNGS for infectious disease diagnosis.

Methods

The literature was searched in the Web of Science Core Collection and screened without year or language restrictions, and the characteristics of the studies were also identified. The outcomes included publication years, study types, journals, countries, authorship, institutions, frontiers, and hotspots with trends. Statistical analysis and visualization were conducted using VOSviewer (version 1.6.16) and CiteSpace (version 6.1. R3).

Results

In total, 325 studies were included in the analysis after screening. Studies were published between 2009 and 2022 with a significantly increasing number from 1 to 118. Most of the studies were original articles and case reports. Frontiers in Cellular and Infection Microbiology and Clinical Infectious Disease were the most commonly cited and co-cited journals. Institutions and researchers from China contributed the most to this field, followed by those from the USA. The hotspots and frontiers of these studies are pneumonia, tuberculosis, and central nervous system infections.

Conclusion

This study determined that mNGS is a hot topic in the diagnosis of infectious diseases with development trends and provides insights into researchers, institutions, hotspots and frontiers in mNGS, which can offer references to related researchers and future research.

Clinical metagenomics-challenges and future prospects

Infections lacking precise diagnosis are often caused by a rare or uncharacterized pathogen, a combination of pathogens, or a known pathogen carrying undocumented or newly acquired genes. Despite medical advances in infectious disease diagnostics, many patients still experience mortality or long-term consequences due to undiagnosed or misdiagnosed infections. Thus, there is a need for an exhaustive and universal diagnostic strategy to reduce the fraction of undocumented infections. Compared to conventional diagnostics, metagenomic next-generation sequencing (mNGS) is a promising, culture-independent sequencing technology that is sensitive to detecting rare, novel, and unexpected pathogens with no preconception. Despite the fact that several studies and case reports have identified the effectiveness of mNGS in improving clinical diagnosis, there are obvious shortcomings in terms of sensitivity, specificity, costs, standardization of bioinformatic pipelines, and interpretation of findings that limit the integration of mNGS into clinical practice. Therefore, physicians must understand the potential benefits and drawbacks of mNGS when applying it to clinical practice. In this review, we will examine the current accomplishments, efficacy, and restrictions of mNGS in relation to conventional diagnostic methods. Furthermore, we will suggest potential approaches to enhance mNGS to its maximum capacity as a clinical diagnostic tool for identifying severe infections.

Metagenomic next-generation sequencing versus traditional laboratory methods for the diagnosis of central nervous system opportunistic infections in HIV-infected Chinese adults

To evaluate clinical value of metagenomic next-generation sequencing (mNGS) in people living with HIV/AIDS (PLWHA) who had CNS disorders. Cerebrospinal fluid (CSF) samples from 48 PLWHA presenting with CNS disorders were sequenced using mNGS and compared with clinical conventional diagnostic methods. In total, 36/48 ss(75%) patients were diagnosed with pathogen(s) infection by mNGS, and the positive detection proportion by mNGS was higher than that by clinical conventional diagnostic methods (75% vs 52.1%, X² = 5.441, P = 0.020). Thirteen out of 48 patients (27.1%) were detected with 3-7 pathogens by mNGS. Moreover, 77 pathogen strains were detected, of which 94.8% (73/77) by mNGS and 37.0% (30/77) by clinical conventional methods (X² = 54.206, P < 0.001). The sensitivity and specificity of pathogens detection by mNGS were 63.9% (23/36) and 66.7% (8/12), respectively, which were superior to that by clinical conventional methods (23/36 vs 9/25, X² = 4.601, P = 0.032; 8/12 vs 5/23, X² = 5.029, P = 0.009). The application of mNGS was superior for its ability to detect a variety of unknown pathogens and multiple pathogens infection, and relatively higher sensitivity and specificity in diagnosis of CNS disorders in PLWHA.

Clinical application value of metagenomic next-generation sequencing in the diagnosis of central nervous system infections

Objectives: The purpose of this study is to evaluate the clinical application value of metagenomic next-generation sequencing (mNGS) in central nervous system (CNS) infections. Methods: Both mNGS and routine examination of cerebrospinal fluid (CSF) samples from patients with CNS infections retrospectively analyzed the efficacy of mNGS in this cohort and were ultimately compared with a clinical diagnosis. Results: A total of 94 cases consistent with CNS infections were included in the analysis. The positive rate for mNGS is 60.6% (57/94), which is significantly higher than 20.2% (19/94; p < 0.01) detected using conventional methods. mNGS detected 21 pathogenic strains that could not be detected by routine testing. Routine tests were positive for two pathogens but negative for mNGS. The sensitivity and specificity of mNGS in the diagnosis of central nervous system infections were 89.5% and 44%, respectively, when compared with traditional tests. At discharge, 20 (21.3%) patients were cured, 55 (58.5%) patients showed improvements, five (5.3%) patients did not recover, and two (2.1%) patients died. Conclusion: mNGS has unique advantages in the diagnosis of central nervous system infections. mNGS tests can be performed when patients are clinically suspected of having a central nervous system infection but no pathogenic evidence.

Metagenomic next-generation sequencing for identification of central nervous system pathogens in HIV-infected patients

Although considerable interest in metagenomic next-generation sequencing (mNGS) has been attracted in recent years, limited data are available regarding the performance of mNGS in HIV-associated central nervous system (CNS) infection. Here, we conducted a retrospectively analyzing of the cerebrospinal fluid (CSF) mNGS reports and other clinical data from 80 HIV-infected patients admitted to the Second Hospital of Nanjing, China from March, 2018 to March, 2022. In our study, CSF mNGS reported negative result, mono-infection, and mixed infection in 8.8, 36.2, and 55% of the patients, respectively. Epstein-Barr virus (EBV), positive in 52.5% of samples, was the most commonly reported pathogen, followed by cytomegalovirus (CMV), John Cunningham virus (JCV), torque teno virus (TTV), cryptococcus neoformans (CN), toxoplasma Gondii (TE), and mycobacterium tuberculosis (MTB). 76.2% of the EBV identification and 54.2% of the CMV identification were not considered clinically important, and relative less sequence reads were reported in the clinical unimportant identifications. The clinical importance of the presence of TTV in CSF was not clear. Detection of JCV, CN, or TE was 100% suggestive of specific CNS infection, however, 60% of the MTB reports were considered contamination. Moreover, of the 44 (55%) mixed infections reported by mNGS, only 4 (5%) were considered clinical important, and mNGS failed to identify one mixed infection. Additionally, except for MTB, CSF mNGS tended to have high sensitivity to identify the above-mentioned pathogens (almost with 100% sensitivity). Even all the diagnostic strategies were evaluated, the cause of neurological symptoms remained undetermined in 6 (7.5%) patients. Overall, our results suggest that mNGS is a very sensitive tool for detecting common opportunistic CNS pathogen in HIV-infected patients, although its performance in CNS tuberculosis is unsatisfactory. EBV and CMV are commonly detected by CSF mNGS, however, the threshold of a clinical important detection remains to be defined.

Application of metagenomic next-generation sequencing in the diagnosis of infectious diseases of the central nervous system after empirical treatment

BACKGROUND

The diagnostic value of metagenomic next-generation sequencing (mNGS) in central nervous system (CNS) infectious diseases after empirical treatment has not been reported.

AIM

To investigate the diagnostic value of mNGS of cerebrospinal fluid (CSF) in the empirically treated CNS infectious diseases.

METHODS

A total of 262 CSF samples from patients with suspected CNS infections were collected between August 2020 and December 2021. Both mNGS and conventional methods were used for testing. The conventional methods included microbial culture, smear, polymerase chain reaction, etc.

RESULTS

Among 262 suspected cases, 183 cases (69.84%) were diagnosed as CNS infection, including 86 cases of virus infection (47.00%), 70 cases of bacterial infection (38.25%) and 27 cases of fungal infection (14.76%). The sensitivity and specificity of mNGS were 65.6% (95%CI: 58.2%-72.3%) and 89.6% (95%CI: 79.1%-95.3%), respectively. The PPV of mNGS was 94.5% (95%CI: 88.6%-97.6%), and the NPV was 48.8% (95%CI: 39.7%–57.9%). The pathogen detective sensitivity and accuracy of mNGS were higher than those of conventional methods (Sensitivity: 65.6% vs 37.2%; P < 0.001; Accuracy: 72.0% vs 50%, P < 0.001). The results showed that compared with conventional methods, mNGS technology was a more sensitive method for the diagnosis of CNS infection after empirical treatment.

CONCLUSION

mNGS can be a better method applied in the diagnosis of CNS infection after empirical treatment.

Metagenomic Next-Generation Sequencing for the Diagnosis of Suspected Opportunistic Infections in People Living with HIV

Objective

The diagnosis of suspected opportunistic infections in HIV patients is challenging due to the wide range of potential causes. This study used mNGS to analyse specimens of suspected opportunistic infections in HIV patients from a single centre to explore this method’s applicability as a diagnostic tool compared to that of CMTs.

Methods

We retrospectively investigated 46 suspected opportunistic infections in people living with HIV(PLWH) Hospitalized at Hangzhou Xixi hospital from January 2020 to August 2021. In total, we collected 49 samples (3 patients provided 2 samples) and sent them out for mNGS.

Results

mNGS had a better detection rate for fungi and nontuberculous mycobacteria than that of CMTs. Specifically, the diagnostic detection rate of fungi (11 vs 19, P<0.05) and nontuberculous mycobacteria (1 vs 6, p<0.05) was significantly higher; there was no difference in detection rate for other pathogens (bacteria, Mycobacterium tuberculosis, or viruses). The sensitivity of mNGS was 90.91%, 50%, 0%, 100%, and 100% for detecting fungi, bacteria, Mycobacterium tuberculosis, nontuberculous mycobacteria, and viruses, respectively; the corresponding specificities were 74.29%, 97.73%, 86.36%, 86.67%, and 91.11%.

Conclusion

mNGS technology provides an alternative and promising method of identifying suspected opportunistic infections in PLWH. Thus, the best diagnosis strategy may be using a combination of mNGS and CMTs.

Case Report: Streptococcus Suis Meningitis Diagnosed in a HIV-Infected Patient With Cryptococcal Meningitis Using Next-Generation Sequencing

Background: Streptococcus suis has been recognized as a zoonotic pathogen that may cause infections in humans. Although rarely described, it is not surprising that both cryptococcal and streptococcus suis meningitis infections can co-exist in a HIV-infected patient with a low CD4 count. However, a fast and accurate diagnose of meningitis of multipathogenic infections is challenging. In this report, we describe such a case of a HIV-infected patient with meningitis of multipathogenic infections.

Case Presentation: The patient was a 34-year-old Chinese male who was diagnosed with cryptococcal meningitis and HIV at the same time about 1 year ago. During the same time period, he had received (with good compliance) fluconazole and tenofovir-lamivudine- dolutegravir based antiretroviral therapy (ART). However, symptom of progressively worsening occipital headache appeared after he was exposed to a truck which was used for transporting pigs. Initial workup indicated an increase of the cerebrospinal fluid (CSF) opening pressure (OP) and an increase in the number of lymphocytes and proteins in CSF. A magnetic resonance imaging (MRI) scan revealed that partial cerebellar surface enhancement. The cryptococcus capsular antigen test of CSF was positive. The results of the India Ink microscopy for cryptococcus, nucleic acid of CMV and EBV and mycobacterium tuberculosis (MTB) tests of CSF were negative. The results of the bacteria and fungi smear and culture of CSF were also negative. Eventually, streptococcus suis was detected using next-generation sequencing (NGS) in CSF. The diagnosis of Streptococcus suis meningitis was made based on the patient's contact history with carrier pigs and the clinical findings addressed above. The treatment of 2 weeks of intravenous ceftriaxone and 1 week of oral moxifloxacin resulted in improvement of the condition of CSF. The anti-fungal treatment using fluconazole continued until the CFS OP went down to a normal level and the cryptococcus capsular antigen test of CSF was negative 6 months later.

Conclusion: This case highlights that NGS might be beneficial to HIV-infected patients who have meningitis with negative CSF culture results. Multiple etiologies for such condition in the immunocompromised patients must be taken into consideration and early stage NGS is recommended.