Combining Metagenomic Sequencing With Whole Exome Sequencing to Optimize Clinical Strategies in Neonates With a Suspected Central Nervous System Infection

The diagnostic value of bronchoalveolar lavage fluid metagenomic next-generation sequencing in critically ill patients with respiratory tract infections

Metagenomic next-generation sequencing (mNGS) is an unbiased and rapid method for detecting pathogens. This study enrolled 145 suspected severe pneumonia patients who were admitted to the Affiliated Hospital of Jining Medical University. This study primarily aimed to determine the diagnostic performance of mNGS and conventional microbiological tests (CMTs) using bronchoalveolar lavage fluid samples for detecting pathogens. Our findings indicated that mNGS performed significantly higher sensitivity (97.54% vs 28.68%, P < 0.001), coincidence (90.34% vs 35.17%, P < 0.001), and negative predictive value (80.00% vs 13.21%, P < 0.001) but performed lower specificity than CMTs (52.17% vs 87.5%, P < 0.001). Streptococcus pneumoniae as the most common bacterial pathogen had the largest proportion (22.90%, 30/131) in this study. In addition to bacteria, fungi, and virus, mNGS can detect a variety of atypical pathogens such as Mycobacterium tuberculosis and non-tuberculous. Mixed infections were common in patients with severe pneumonia, and bacterial-fungal-viral-atypical pathogens were the most complicated infection. After adjustments of antibiotics based on mNGS and CMTs, the clinical manifestation improved in 139 (95.86%, 139/145) patients. Our data demonstrated that mNGS had significant advantage in diagnosing respiratory tract infections, especially atypical pathogens and fungal infections. Pathogens were detected timely and comprehensively, contributing to the adjustments of antibiotic treatments timely and accurately, improving patient prognosis and decreasing mortality potentially.IMPORTANCEMetagenomic next-generation sequencing using bronchoalveolar lavage fluid can provide more comprehensive and accurate pathogens for respiratory tract infections, especially when considering the previous usage of empirical antibiotics before admission or complicated clinical presentation. This technology is expected to play an important role in the precise application of antimicrobial drugs in the future.

Case Report: Taking action or standing by: managing a preterm neonate at the risk of neonatal varicella by metagenomic next-generation sequencing

Neonatal varicella is indeed a rare condition, and most infants born to mothers with varicella have a good prognosis. However, in exceptional cases, neonatal varicella can be life-threatening, particularly for preterm infants. Therefore, it is vital to make an early diagnosis or predict the risk of neonatal varicella to ensure prompt treatment and improve prognosis. This report made an effort to early predict neonatal vericalla by using metagenomic next-generation sequencing (mNGS) in a preterm infant who was at risk for vericalla infection. A preterm infant born from a mother with varicella with symptom onset at 8 days before delivery, putting the infant at risk for varicella infection. Importantly, the patient develop pneumonia and pneumothorax, and neonatal vericella was suspected. Fortunately, the use of mNGS for testing the varicella gene in the serum promptly ruled out varicella zoster virus (VZV) infection in the patient, as indicated by a negative mNGS result. Subsequent follow-up, which included a 14-day stay in the hospital followed by an additional 7 days at home, confirmed this finding. Throughout this period, the patient did not exhibit any rash or other symptoms associated with varicella. Therefore, the novel approach of using mNGS allows neonatologists to predict and promptly address potential neonatal infections. This early detection is crucial, as delayed diagnosis or treatment could pose life-threatening risks, as exemplified by the case of neonatal varicella. In such cases, neonatologists can take proactive measures instead of standing by for at-risk neonates. Furthermore, given the severity of neonatal varicella as a life-threatening condition, the early exclusion of subsequent varicella infection by mNGS can offer reassurance to both family members and healthcare professionals.

Clinical Metagenomic Next-Generation Sequencing for Diagnosis of Central Nervous System Infections: Advances and Challenges

Central nervous system (CNS) infections carry a substantial burden of morbidity and mortality worldwide, and accurate and timely diagnosis is required to optimize management. Metagenomic next-generation sequencing (mNGS) has proven to be a valuable tool in detecting pathogens in patients with suspected CNS infection. By sequencing microbial nucleic acids present in a patient's cerebrospinal fluid, brain tissue, or samples collected outside of the CNS, such as plasma, mNGS can detect a wide range of pathogens, including rare, unexpected, and/or fastidious organisms. Furthermore, its target-agnostic approach allows for the identification of both known and novel pathogens. This is particularly useful in cases where conventional diagnostic methods fail to provide an answer. In addition, mNGS can detect multiple microorganisms simultaneously, which is crucial in cases of mixed infections without a clear predominant pathogen. Overall, clinical mNGS testing can help expedite the diagnostic process for CNS infections, guide appropriate management decisions, and ultimately improve clinical outcomes. However, there are key challenges surrounding its use that need to be considered to fully leverage its clinical impact. For example, only a few specialized laboratories offer clinical mNGS due to the complexity of both the laboratory methods and analysis pipelines. Clinicians interpreting mNGS results must be aware of both false negatives-as mNGS is a direct detection modality and requires a sufficient amount of microbial nucleic acid to be present in the sample tested-and false positives-as mNGS detects environmental microbes and their nucleic acids, despite best practices to minimize contamination. Additionally, current costs and turnaround times limit broader implementation of clinical mNGS. Finally, there is uncertainty regarding the best practices for clinical utilization of mNGS, and further work is needed to define the optimal patient population(s), syndrome(s), and time of testing to implement clinical mNGS.

Case report: Acute severe hyponatremia-induced seizures in a newborn: a community-acquired case and literature review

Severe neonatal hyponatremia represents a critical electrolyte imbalance with potentially severe neurological outcomes, a condition rarely documented in community-acquired, full-term newborns. This report underscores a unique case of a 23-day-old, previously healthy, full-term male neonate experiencing severe hyponatremia that precipitated seizures, underscoring the urgency of prompt recognition and intervention. The neonate presented with symptoms including vomiting, groaning, chills, fixed staring, and limb tremors. Critical findings upon admission encompassed hypothermia, hypotension, tachycardia, and tachypnea accompanied by significant weight loss. The clinical presentation was marked by dehydration, lethargy, weak crying, a fixed gaze, irregular breathing, and coarse lung sounds, yet a distended abdomen, hypertonic limb movements, and recurrent seizures were observed. Immediate interventions included establishing IV access, rewarming, mechanical ventilation, seizure management, volume expansion, dopamine for circulatory support, and initiation of empirical antibiotics. Diagnostic evaluations revealed a sodium ion concentration of 105.9 mmol/L, while amplitude-integrated electroencephalography (aEEG) detected pronounced seizure activity characterized by a lack of sleep-wake rhythmicity, noticeable elevation in both the lower and upper amplitude margins, and a sustained decrease in the lower margin voltage dropping below 5 μV, presenting as sharp or serrated waveforms. The management strategy entailed rapid electrolyte normalization using hypertonic saline and sodium bicarbonate, anticonvulsant therapy, and comprehensive supportive care, with continuous aEEG monitoring until the cessation of seizures. Remarkably, by the third day, the neonate's condition had stabilized, allowing for discharge in good health 10 days post-admission. At a 16-month follow-up, the child exhibited no adverse neurological outcomes and demonstrated favorable growth and development. Our extensive review on the etiology, clinical manifestations, aEEG monitoring, characteristics of seizures induced by severe neonatal hyponatremia, treatment approaches, and the prognosis for seizures triggered by severe hyponatremia aims to deepen the understanding and enhance clinical management of this complex condition. It stresses the importance of early detection, accurate diagnosis, and customized treatment protocols to improve outcomes for affected neonates. Additionally, this review accentuates the indispensable role of aEEG monitoring in managing neonates at elevated risk for seizures. Yet, the safety and efficacy of swiftly administering hypertonic saline for correcting severe hyponatremia-induced seizures necessitate further investigation through medical research.

The application value of metagenomic next-generation sequencing technology in the diagnosis and treatment of neonatal infectious meningitis - a single center retrospective case-control study

OBJECTIVE

This retrospective study was conducted to investigate the application value of metagenomics next generation sequencing (mNGS) technology in the diagnosis and treatment of neonatal infectious meningitis.

METHODS

From 1 January 2020 to 31 December 2022, 73 newborns suspected of infectious meningitis were hospitalized. After screening by inclusion and exclusion criteria, 69 newborns were subsequently included in the study, containing 27 cases with positive mNGS result and 42 cases with negative mNGS result. Furthermore, according to the diagnosis of meningitis, mNGS positive group and mNGS negative group were further divided into infectious meningitis with mNGS (+) group (n = 27) and infectious meningitis with mNGS (-) group (n = 26), respectively.

RESULTS

(1) Compared with cerebrospinal fluid (CSF) culture, mNGS has better diagnostic value [positive predictive value (PPV) = 100.00% (27/27), negative predictive value (NPV) = 38.10% (16/42), agreement rate = 62.32% (43/69), area under the curve (AUC) = 0.750, 95% confidence interval (CI): 0.636-0.864]. (2) There were significant differences in the onset age, age at first CSF test, CSF leukocyte count, CSF glucose, positive rate of CSF culture, blood leukocyte count, procalcitonin (PCT), C-reaction protein (CRP), age at first mNGS test and adjusting anti-infective medication in the comparison between infectious meningitis with mNGS (+) group and infectious meningitis with mNGS (-) group (p < 0.05). (3) mNGS could help improve the cure rate [crude odds ratio (OR) = 3.393, 95%CI: 1.072-10.737; adjusted OR = 15.580, 95%CI: 2.114-114.798].

CONCLUSION

Compared with classic meningitis detection methods, mNGS has better PPV, NPV, agreement rate, and AUC. mNGS could help improve the cure rate.

Higher diagnostic value of next-generation sequencing versus culture in periprosthetic joint infection: A systematic review and meta-analysis

BACKGROUND

The next-generation sequencing (NGS) has developed rapidly in the past decade and is becoming a promising diagnostic tool for periprosthetic infection (PJI). However, its diagnostic value for PJI is still uncertain. The purpose of this systematic review and meta-analysis was to evaluate the diagnostic value of NGS compared to culture.

METHODS

In this systematic review and meta-analysis, electronic databases including PubMed, Embase, Cochrane Central Register of Controlled Trials, Web of Science and clinicaltrials.gov were searched for studies from inception to 12 November 2023. Diagnostic parameters, such as sensitivity, specificity, diagnostic odds ratio and area under the summary receiver-operating characteristic (SROC) curve (AUC), were calculated for the included studies. A systematic review and meta-analysis was performed.

RESULTS

A total of 22 studies with 2461 patients were included in our study. The pooled sensitivity, specificity and diagnostic odds ratio of NGS were 87% (95% confidence interval [CI]: 83-90), 94% (95% CI: 91-96) and 111 (95% CI: 70-177), respectively. On the other hand, the pooled sensitivity, specificity and diagnostic odds ratio of culture were 63% (95% CI: 58-67), 98% (95% CI: 96-99) and 93 (95% CI: 40-212), respectively. The SROC curve for NGS and culture showed that the AUCs are 0.96 (95% CI: 0.94-0.98) and 0.82 (95% CI: 0.79-0.86), respectively.

CONCLUSION

This systematic review and meta-analysis found NGS had higher sensitivity and diagnostic accuracy but slightly lower specificity than culture. Based on the pooled results, we suggested NGS may have the potential to be a new tool for the diagnosis of PJI.

LEVEL OF EVIDENCE

Level IV.

Utilizing metagenomic next-generation sequencing for pathogen detection and diagnosis in lower respiratory tract infections in real-world clinical practice

BACKGROUND

Infectious etiologies of lower respiratory tract infections (LRTIs) by the conventional microbiology tests (CMTs) can be challenging. Metagenomic next-generation sequencing (mNGS) has great potential in clinical use for its comprehensiveness in identifying pathogens, particularly those difficult-to-culture organisms.

METHODS

We analyzed a total of 205 clinical samples from 201 patients with suspected LRTIs using mNGS in parallel with CMTs. mNGS results were used to guide treatment adjustments for patients who had negative CMT results. The efficacy of treatment was subsequently evaluated in these patients.

RESULTS

mNGS-detected microorganisms in 91.7% (188/205) of the clinical samples, whereas CMTs demonstrated a lower detection rate, identifying microorganisms in only 37.6% (77/205) of samples. Compared to CMT results, mNGS exhibited a detection sensitivity of 93.5% and 95.4% in all 205 clinical samples and 180 bronchoalveolar lavage fluid (BALF) samples, respectively. A total of 114 patients (114/201; 56.7%) showed negative CMT results, among which 92 received treatment adjustments guided by their positive mNGS results. Notably, 67.4% (62/92) of patients demonstrated effective treatment, while 25% (23/92) experienced a stabilized condition. Subgroup analysis of cancer patients revealed that 41.9% (13/31) exhibited an effective response to treatment, and 35.5% (11/31) maintained a stable condition following medication adjustments guided by mNGS.

CONCLUSION

mNGS demonstrated great potential in identifying microorganisms of clinical significance in LRTIs. The rapid turnaround time and reduced susceptibility to the impact of antimicrobial administration make mNGS a valuable supplementary tool for diagnosis and treatment decision-making for suspected LRTIs in clinical practice.

Combination of metagenomic next-generation sequencing and conventional tests unraveled pathogen profiles in infected patients undergoing allogeneic hematopoietic stem cell transplantation in Jilin Province of China

Background

Infection is the main cause of death for patients after allogeneic hematopoietic stem cell transplantation (HSCT). However, pathogen profiles still have not been reported in detail due to their heterogeneity caused by geographic region.

Objective

To evaluate the performance of metagenomic next-generation sequencing (mNGS) and summarize regional pathogen profiles of infected patients after HSCT.

Methods

From February 2021 to August 2022, 64 patients, admitted to the Department of Hematology of The First Hospital of Jilin University for HSCT and diagnosed as suspected infections, were retrospectively enrolled.

Results

A total of 38 patients were diagnosed as having infections, including bloodstream (n =17), pulmonary (n =16), central nervous system (CNS) (n =4), and chest (n =1) infections. Human betaherpesvirus 5 (CMV) was the most common pathogen in both bloodstream (n =10) and pulmonary (n =8) infections, while CNS (n =2) and chest (n =1) infections were mainly caused by Human gammaherpesvirus 4 (EBV). For bloodstream infection, Mycobacterium tuberculosis complex (n =3), Staphylococcus epidermidis (n =1), and Candida tropicalis (n =1) were also diagnosed as causative pathogens. Furthermore, mNGS combined with conventional tests can identify more causative pathogens with high sensitivity of 82.9% (95% CI 70.4-95.3%), and the total coincidence rate can reach up to 76.7% (95% CI 64.1-89.4%).

Conclusions

Our findings emphasized the importance of mNGS in diagnosing, managing, and ruling out infections, and an era of more rapid, independent, and impartial diagnosis of infections after HSCT can be expected.

Metagenomic next-generation sequencing in detecting pathogens in pediatric oncology patients with suspected bloodstream infections

BACKGROUND

Studies on mNGS application in pediatric oncology patients, who are at high risk of infection, are quite limited.

METHODS

From March 2020 to June 2022, a total of 224 blood samples from 195 pediatric oncology patients who were suspected as bloodstream infections were enrolled in this study. Their clinical and laboratory data were retrospectively reviewed, and the diagnostic performance of mNGS was assessed.

RESULTS

Compared to the reference tests, mNGS showed significantly higher sensitivity (89.8% vs 32.5%, P < 0.001) and clinical agreement (76.3% vs 51.3%, P < 0.001) in detecting potential pathogens and distinguishing BSI from non-BSI. Especially, mNGS had an outstanding performance for virus detection, contributing to 100% clinical diagnosed virus. Samples from patients with neutropenia showed higher incidence of bacterial infections (P = 0.035). The most identified bacteria were Escherichia coli, and the overall infections by gram-negative bacteria were significantly more prevalent than those by gram-positive ones (90% vs 10%, P < 0.001). Overall, mNGS had an impact on the antimicrobial regimens' usage in 54.3% of the samples in this study.

CONCLUSIONS

mNGS has the advantage of rapid and effective pathogen diagnosis in pediatric oncology patients with suspected BSI, especially for virus.

IMPACT

Compared with reference tests, mNGS showed significantly higher sensitivity and clinical agreement in detecting potential pathogens and distinguishing bloodstream infections (BSI) from non-BSI. mNGS is particularly prominent in clinical diagnosed virus detection. The incidence of bacterial infection was higher in patients with neutropenia, and the overall infection rate of Gram-negative bacteria was significantly higher than that of Gram-positive bacteria. mNGS affects the antimicrobial regimens' usage in more than half of patients.

Diagnostic performance of metagenomic next-generation sequencing for the detection of pathogens in cerebrospinal fluid in pediatric patients with central nervous system infection: a systematic review and meta-analysis

BACKGROUND

Detecting pathogens in pediatric central nervous system infection (CNSI) is still a major challenge in medicine. In addition to conventional diagnostic patterns, metagenomic next-generation sequencing (mNGS) shows great potential in pathogen detection. Therefore, we systematically evaluated the diagnostic performance of mNGS in cerebrospinal fluid (CSF) in pediatric patients with CNSI.

METHODS

Related literature was searched in the Web of Science, PubMed, Embase, and Cochrane Library. We screened the literature and extracted the data according to the selection criteria. The quality of included studies was assessed by the Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) tool and the certainty of the evidence was measured by the Grading of Recommendations, Assessment, Development, and Evaluations (GRADE) score system. Then, the pooled sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odd's ratio (DOR), and area under the curve (AUC) of the summary receiver operating characteristic curve (sROC) were estimated in Stata Software and MetaDisc. Subgroup analyses were performed to investigate the potential factors that influence the diagnostic performance.

RESULTS

A total of 10 studies were included in the meta-analysis. The combined sensitivity was 0.68 (95% confidence interval [CI]: 0.59 to 0.76, I2 = 66.77%, p < 0.001), and the combined specificity was 0.89 (95% CI: 0.80 to 0.95, I2 = 83.37%, p < 0.001). The AUC of sROC was 0.85 (95% CI, 0.81 to 0.87). The quality level of evidence elevated by the GRADE score system was low.

CONCLUSIONS

Current evidence shows that mNGS presents a good diagnostic performance in pediatric CNSI. Due to the limited quality and quantity of the included studies, more high-quality studies are needed to verify the above conclusion.

Decoding human cytomegalovirus for the development of innovative diagnostics to detect congenital infection

Cytomegalovirus is the most common cause of congenital infectious disease and the leading nongenetic etiology of sensorineural hearing loss. Although most infected neonates are asymptomatic at birth, congenital cytomegalovirus infection is responsible for nearly 400 infant deaths annually in the United States and may lead to significant long-term neurodevelopmental impairments in survivors. The resulting financial and social burdens of congenital cytomegalovirus infection have led many medical centers to initiate targeted testing after birth, with a growing advocacy to advance universal newborn screening. While no cures or vaccines are currently available to eliminate or prevent cytomegalovirus infection, much has been learned over the last five years regarding disease pathophysiology and viral replication cycles that may enable the development of innovative diagnostics and therapeutics. This Review will detail our current understanding of congenital cytomegalovirus infection, while focusing our discussion on routine and emerging diagnostics for viral detection, quantification, and long-term prognostication. IMPACT: This review highlights our current understanding of the fetal transmission of human cytomegalovirus. It details clinical signs and physical findings of congenital cytomegalovirus infection. This submission discusses currently available cytomegalovirus diagnostics and introduces emerging platforms that promise improved sensitivity, specificity, limit of detection, viral quantification, detection of genomic antiviral resistance, and infection staging (primary, latency, reactivation, reinfection).

Genetic counselling considerations with genetic/genomic testing in Neonatal and Pediatric Intensive Care Units: A scoping review

Genetic and genomic technologies can effectively diagnose numerous genetic disorders. Patients benefit when genetic counselling accompanies genetic testing and international guidelines recommend pre- and post-test genetic counselling with genome-wide sequencing. However, there is a gap in knowledge regarding the unique genetic counselling considerations with different types of genetic testing in the Neonatal Intensive Care Unit (NICU) and the Pediatric Intensive Care Unit (PICU). This scoping review was conducted to identify the gaps in care with respect to genetic counselling for infants/pediatric patients undergoing genetic and genomic testing in NICUs and PICUs and understand areas in need of improvement in order to optimize clinical care for patients, caregivers, and healthcare providers. Five databases (MEDLINE [Ovid], Embase [Ovid], PsycINFO [Ebsco], CENTRAL [Ovid], and CINHAL [Ebsco]) and grey literature were searched. A total of 170 studies were included and used for data extraction and analysis. This scoping review includes descriptive analysis, followed by a narrative account of the extracted data. Results were divided into three groups: pre-test, post-test, and comprehensive (both pre- and post-test) genetic counselling considerations based on indication for testing. More studies were conducted in the NICU than the PICU. Comprehensive genetic counselling was discussed in only 31% of all the included studies demonstrating the need for both pre-test and post-test genetic counselling for different clinical indications in addition to the need to account for different cultural aspects based on ethnicity and geographic factors.

Development of novel parameters for pathogen identification in clinical metagenomic next-generation sequencing

Introduction: Metagenomic next-generation sequencing (mNGS) has emerged as a powerful tool for rapid pathogen identification in clinical practice. However, the parameters used to interpret mNGS data, such as read count, genus rank, and coverage, lack explicit performance evaluation. In this study, the developed indicators as well as novel parameters were assessed for their performance in bacterium detection. Methods: We developed several relevant parameters, including 10M normalized reads, double-discard reads, Genus Rank Ratio, King Genus Rank Ratio, Genus Rank Ratio*Genus Rank, and King Genus Rank Ratio*Genus Rank. These parameters, together with frequently used read indicators including raw reads, reads per million mapped reads (RPM), transcript per kilobase per million mapped reads (TPM), Genus Rank, and coverage were analyzed for their diagnostic efficiency in bronchoalveolar lavage fluid (BALF), a common source for detecting eight bacterium pathogens: Acinetobacter baumannii, Klebsiella pneumoniae, Streptococcus pneumoniae, Staphylococcus aureus, Hemophilus influenzae, Stenotrophomonas maltophilia, Pseudomonas aeruginosa, and Aspergillus fumigatus. Results: The results demonstrated that these indicators exhibited good diagnostic efficacy for the eight pathogens. The AUC values of all indicators were almost greater than 0.9, and the corresponding sensitivity and specificity values were almost greater than 0.8, excepted coverage. The negative predictive value of all indicators was greater than 0.9. The results showed that the use of double-discarded reads, Genus Rank Ratio*Genus Rank, and King Genus Rank Ratio*Genus Rank exhibited better diagnostic efficiency than that of raw reads, RPM, TPM, and in Genus Rank. These parameters can serve as a reference for interpreting mNGS data of BALF. Moreover, precision filters integrating our novel parameters were built to detect the eight bacterium pathogens in BALF samples through machine learning. Summary: In this study, we developed a set of novel parameters for pathogen identification in clinical mNGS based on reads and ranking. These parameters were found to be more effective in diagnosing pathogens than traditional approaches. The findings provide valuable insights for improving the interpretation of mNGS reports in clinical settings, specifically in BALF analysis.

High specificity of metagenomic next-generation sequencing using protected bronchial brushing sample in diagnosing pneumonia in children

Background

Lower respiratory tract infections are the leading cause of morbidity and mortality in children worldwide. Timely and accurate pathogen detection is crucial for proper clinical diagnosis and therapeutic strategies. The low detection efficiency of conventional methods and low specificity using respiratory samples seriously hindered the accurate detection of pathogens.

Methods

In this study, we retrospectively enrolled 1,032 children to evaluate the performance of metagenomics next-generation sequencing (mNGS) using bronchoalveolar lavage fluid (BALF) sample and protected bronchial brushing (BB) sample in diagnosing pneumonia in children. In addition, conventional tests (CTs) were also performed.

Results

The specificity of BB mNGS [67.3% (95% CI 58.6%-75.9%)] was significantly higher than that of BALF mNGS [38.5% (95% CI 12.0%-64.9%)]. The total coincidence rate of BB mNGS [77.6% (95% CI 74.8%-80.5%)] was slightly higher than that of BALF mNGS [76.5% (95% CI 68.8%-84.1%)] and CTs [38.5% (95% CI 35.2%-41.9%)]. During the epidemics of Mycoplasma pneumoniae, the detection rate of M. pneumoniae in the >6-year group (81.8%) was higher than that in the 3-6-year (78.9%) and <3-year groups (21.5%). The highest detection rates of bacteria, fungi, and viruses were found in the <3-year, >6-year, and 3-6-year groups, respectively. mNGS detection should be performed at the duration of 5-7 days after the start of continuous anti-microbial therapy or at the duration of 6-9 days from onset to mNGS test.

Conclusions

This is the first report to evaluate the performance of BB mNGS in diagnosing pulmonary infections in children on a large scale. Based on our findings, extensive application of BB mNGS could be expected.

The Utility of Metagenomic Next-Generation Sequencing (mNGS) in the Management of Patients With Bronchiectasis: A Single-Center Retrospective Study of 93 Cases

Background

Bronchiectasis is a chronic inflammatory respiratory disease mainly caused by pathogenic infections. However, standard methods of pathogen detection show prolonged cycle durations and unsatisfactory sensitivity and detection rates. Macrogenomic next-generation sequencing (mNGS) emerges as a promising technique for swift, effective, and unbiased pathogen detection and subsequent data interpretation.

Methods

Here, a retrospective analysis of 93 patients with suspected bronchiectasis was performed to assess the clinical applicability of mNGS. Bronchoalveolar alveolar lavage fluid (BALF) samples were collected from these subjects, followed by standard assays and mNGS separately. The turnaround time, detection rate, and pathogen identification using mNGS were compared with those of standard methods.

Results

mNGS identified a greater number of bacteria (72 vs 16), fungi (26 vs 19), and viruses (14 vs 0) than standard methods. Specifically, the commonly identified bacteria were Haemophilus, Mycobacterium intracellulare, Pseudomonas, and Streptococcus pneumoniae, while the most detected fungi were Aspergillus and the most prevalent viruses were human herpesviruses. Of note, 29 out of 30 patients (96.67%) who received optimized treatment strategies based on mNGS results experienced recovery.

Conclusions

Collectively, these findings suggest that mNGS has the potential to improve the diagnosis and treatment of bronchiectasis patients by enabling rapid and precise pathogen detection, which can lead to timely and effective treatment strategies.

Diagnostic Performance and Clinical Impact of Metagenomic Next-Generation Sequencing for Pediatric Infectious Diseases

Metagenomic next-generation sequencing (mNGS) has shown promise in the diagnosis of infectious diseases in adults, while its efficacy in pediatric infections remains uncertain. We performed a retrospective analysis of 1,493 mNGS samples from pediatric patients with blood, central nervous system, and lower respiratory tract infections. The positive percent agreement (PPA) and the negative percent agreement (NPA) of mNGS were compared to conventional microbiological tests (CMT) based on clinical diagnosis. The agreement of mNGS compared to CMT, as well as the clinical impact of mNGS, were valuated. Using the clinical diagnosis as a reference, mNGS demonstrated a significantly higher overall PPA compared to CMT (53.1% [95% CI = 49.7 to 56.6%] versus 25.8% [95% CI = 22.8 to 28.9%]), while maintaining a comparable overall NPA (93.2% [95% CI = 91.3 to 95.1%] versus 97.2% [95% CI = 95.9 to 98.4%]). In septic patients under 6 years of age or with immunosuppressive status, mNGS showed a higher PPA and a comparable NPA compared to CMT. The overall PPA and NPA of mNGS compared to CMT were 75.3 and 75.0%, respectively. The majority of cases of Streptococcus pneumoniae, Streptococcus agalactiae, Mycobacterium tuberculosis complex, and Pneumocystis jirovecii infections were identified by mNGS. A positive clinical impact of 14.0% (206/1,473), a negative impact of 0.8% (11/1,473), a nonimpact of 84.7% (1,248/1,473), and an unknown impact of 0.5% (8/1,473) were observed in the mNGS results. Notably, the positive impact was greater among immunosuppressed patients than among nonimmunosuppressed individuals (67/247, 27.1% versus 139/1,226, 11.3%; P < 0.001). mNGS is valuable for pathogen detection, diagnosis, and clinical management of infections among pediatric patients. mNGS was thus effective for the diagnosis of pediatric infections, which may guide clinical management. Patients with immunosuppressive conditions benefited more from mNGS testing.

Diagnosis of Neurological Infections in Pediatric Patients from Cell-Free DNA Specimens by Using Metagenomic Next-Generation Sequencing

Central nervous system (CNS) infections can cause significant morbidity and mortality, especially in children. Rapid and accurate pathogenic detection in suspected CNS infections is essential for disease control at the early stage of infection. To evaluate the performance of metagenomic next-generation sequencing (mNGS) of cell-free DNA (cfDNA) in cerebrospinal fluid (CSF) in pediatric patients, we retrospectively analyzed the efficiency of cfDNA mNGS in children with CNS infections (n = 257) or noninfectious neurological disorders (n = 81). The CSF samples of 124 random subjects were used to evaluate the accuracy between mNGS of cfDNA and whole-cell DNA (wcDNA). In total, cfDNA mNGS detected a wide range of microbes with a detection rate of 71.0%, and the sensitivity and total coincidence rate with clinical diagnosis reached 68.9% and 67.5%, respectively. Compared with wcDNA mNGS, cfDNA mNGS had a higher efficacy in detecting viruses (66 versus 13) and Mycobacterium (7 versus 1), with significantly higher reads per million. The dominant causative pathogens were bacteria and viruses in CNS infections, but these presented with different pathogen spectra in different age categories. The best timing for the mNGS test ranged from 1 to 6 days after the start of anti-infection therapy, and the earlier mNGS started, the better was identification of bacterial CNS infections. This study emphasized that cfDNA mNGS had overall superiority to conventional methods on causative pathogen detection in pediatric CNS infections, and it was even better than wcDNA mNGS. Furthermore, research needs to be better validated in large-scale clinical trials to improve the clinical applications of cfDNA mNGS. IMPORTANCE Our study emphasized that cfDNA mNGS had overall superiority to conventional methods on causative pathogen detection in CNS-infected children, and it was even better than wcDNA mNGS. cfDNA mNGS detected a wide range of pathogens with a high total coincidence rate (67.5%) against clinical diagnosis. The best timing for cfDNA mNGS detection ranged from 1 to 6 days, rather than 0 days, after the start of empirical anti-infection therapy. The earlier mNGS started, the better the identifications of bacterial CNS infections. To the best of our knowledge, this research is the first report evaluating the clinical utility of mNGS with different methods (cfDNA versus wcDNA) of extracting DNA from CSF specimens in diagnosing pediatric CNS infections. Meanwhile, this is the largest cohort study that has evaluated the performance of mNGS using cfDNA from CSF specimens in pediatric patients with CNS infections.

Metagenomic Next-Generation Sequencing for the Diagnosis of Neonatal Infectious Diseases

Infectious diseases pose a fatal risk to neonates. Timely and accurate pathogen detection is crucial for proper clinical diagnosis and therapeutic strategies. Limited sample volumes from neonatal patients seriously hindered the accurate detection of pathogens. Here, we unravel that metagenomic next-generation sequencing (mNGS) of cell-free DNA (cfDNA) and RNA can achieve unbiased detection of trace pathogens from different kinds of body fluid samples and blood samples. We enrolled 168 neonatal patients with suspected infections from whom blood samples (n = 153), cerebrospinal fluid samples (n = 127), and respiratory tract samples (RTSs) (including bronchoalveolar lavage fluids, sputa, and respiratory secretions) (n = 51) were collected and analyzed using mNGS. High rates of positivity (70.2%; 118/168) of mNGS were observed, and the coincidence rate against the final clinical diagnosis in positive mNGS cases reached 68.6% (81/118). The most common causative pathogens were Klebsiella pneumoniae (n = 12), Escherichia coli (n = 12), and Streptococcus pneumoniae (n = 8). mNGS using cfDNA and RNA can identify microbes that cannot be detected by conventional methods in different body fluid and blood samples, and more than 50% of these microbes were identified as causative pathogens. Further local polynomial regression fitting analysis revealed that the best timing for mNGS detection ranged from 1 to 3 days after the start of continuous antimicrobial therapy. Diagnosed and guided by mNGS results, the therapeutic regimens for 86 out of 117 neonatal patients were changed, most of whom (80/86) completely recovered and were discharged, while 44 out of 86 patients completely or partially stopped unnecessary medication. Our findings highlight the importance of mNGS in detecting causative DNA and RNA pathogens in infected neonatal patients. IMPORTANCE To the best of our knowledge, this is the first report on evaluating the performance of mNGS using cfDNA and RNA from body fluid and blood samples for diagnosing neonatal infections. mNGS of RNA and cfDNA can achieve the unbiased detection and identification of trace pathogens from different kinds of neonatal body fluid and blood samples with a high total coincidence rate (226/331; 68.3%) against final clinical diagnoses by sample. The best timing for mNGS detection in neonatal infections ranged from 1 to 3 days, rather than 0 days, after the start of continuous antimicrobial therapy. Our findings highlight the importance of mNGS in detecting causative DNA and RNA pathogens, and the extensive application of mNGS for the diagnosis of neonatal infections can be expected.

Metagenomic next-generation sequencing of cell-free and whole-cell DNA in diagnosing central nervous system infections

Background

Central nervous system (CNS) infections pose a fatal risk to patients. However, the limited sample volumes of cerebrospinal fluid (CSF) and low detection efficiency seriously hinder the accurate detection of pathogens using conventional methods.

Methods

We evaluated the performance of metagenomics next-generation sequencing (mNGS) in diagnosing CNS infections. CSF samples from 390 patients clinically diagnosed with CNS infections were used for the mNGS of cell-free DNA (cfDNA) (n =394) and whole-cell DNA (wcDNA) (n =150).

Results

The sensitivity of mNGS using cfDNA was 60.2% (237/394, 95% confidence interval [CI] 55.1%–65.0%), higher than that of mNGS using wcDNA (32.0%, 95% [CI] 24.8%–40.2%, 48/150) and conventional methods (20.9%, 95% [CI] 16.2%–26.5%, 54/258) (P < 0.01, respectively). The accuracy of mNGS using cfDNA in positive samples was 82.6%. Most of viral (72.6%) and mycobacterial (68.8%) pathogens were only detected by the mNGS of cfDNA. Meningitis and encephalitis with Streptococcus pneumoniae infection might be more likely to result in critically ill diseases, while Human alphaherpesvirus 3 was prone to cause non-critically ill diseases.

Conclusions

This is the first report on evaluating and emphasizing the importance of mNGS using CSF cfDNA in diagnosing CNS infections, and its extensive application in diagnosing CNS infections could be expected, especially for viral and mycobacterial CNS infections.

Metagenomics next-generation sequencing for the diagnosis of central nervous system infection: A systematic review and meta-analysis

Objective

It is widely acknowledged that central nervous system (CNS) infection is a serious infectious disease accompanied by various complications. However, the accuracy of current detection methods is limited, leading to delayed diagnosis and treatment. In recent years, metagenomic next-generation sequencing (mNGS) has been increasingly adopted to improve the diagnostic yield. The present study sought to evaluate the value of mNGS in CNS infection diagnosis.

Methods

Following the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) 2022 guidelines, we searched relevant articles published in seven databases, including PubMed, Web of Science, and Cochrane Library, published from January 2014 to January 2022. High-quality articles related to mNGS applications in the CNS infection diagnosis were included. The comparison between mNGS and the gold standard of CNS infection, such as culture, PCR or serology, and microscopy, was conducted to obtain true positive (TP), true negative (TN), false positive (FP), and false negative (FN) values, which were extracted for sensitivity and specificity calculation.

Results

A total of 272 related studies were retrieved and strictly selected according to the inclusion and exclusion criteria. Finally, 12 studies were included for meta-analysis and the pooled sensitivity was 77% (95% CI: 70–82%, I² = 39.69%) and specificity was 96% (95% CI: 93–98%, I² = 72.07%). Although no significant heterogeneity in sensitivity was observed, a sub-group analysis was conducted based on the pathogen, region, age, and sample pretreatment method to ascertain potential confounders. The area under the curve (AUC) of the summary receiver operating characteristic curve (SROC) of mNGS for CNS infection was 0.91 (95% CI: 0.88–0.93). Besides, Deek's Funnel Plot Asymmetry Test indicated no publication bias in the included studies (Figure 3, p > 0.05).

Conclusion

Overall, mNGS exhibits good sensitivity and specificity for diagnosing CNS infection and diagnostic performance during clinical application by assisting in identifying the pathogen. However, the efficacy remains inconsistent, warranting subsequent studies for further performance improvement during its clinical application.

Study registration number

INPLASY202120002

Progress in the application of metagenomic next-generation sequencing in pediatric infectious diseases

Infectious diseases are the major cause of children's deaths all over the world. With the development of evidence-based medicine, etiological diagnosis becomes more and more important. Since traditional methods have been unable to meet the needs of diagnosis and treatment, metagenomic next-generation sequencing (mNGS) gradually shows its unique advantages for pathogen diagnosis. This article aimed to introduce the application of mNGS technology in the diagnosis and treatment of neonatal and puerile infectious diseases by providing some examples.

Diagnostic performance of metagenomic next-generation sequencing for the detection of pathogens in bronchoalveolar lavage fluid in patients with pulmonary infections: Systematic review and meta-analysis

BACKGROUND

The identification of pathogens in patients with pulmonary infection has always been a major challenge in medicine. Compared with sputum and throat swabs, bronchoalveolar lavage fluid (BALF) can better reflect the actual state in the lungs. However, there has not been a meta-analysis of the diagnostic efficacy of metagenomic next-generation sequencing (mNGS) in detecting pathogens in BALF from patients with pulmonary infections.

METHODS

Data sources were PubMed, Web of Science, Embase, and the China National Knowledge Infrastructure. The pooled sensitivity and specificity were estimated by using random-effects or fixed-effect models. Subgroup analysis was performed to reveal the effect of potential explanatory factors on the diagnostic performance measures.

RESULTS

The pooled sensitivity was 78% (95% confidence interval: 67-87%; I² = 92%) and the pooled specificity was 77% (95% confidence interval: 64-94%; I² = 74%) for mNGS. Subgroup analyses for the sensitivity of mNGS revealed that patients with pulmonary infections who were severely ill or immunocompromised significantly affected heterogeneity (P < 0.001). The positive detection rate of mNGS for pathogens in BALF of severely or immunocompromised pulmonary-infected patients was 92% (95% confidence interval: 78-100%).

CONCLUSION

mNGS has high diagnostic performance for BALF pathogens in patients with pulmonary infections, especially in critically ill or immunocompromised patients.

Diagnostic accuracy of the metagenomic next-generation sequencing (mNGS) for detection of bacterial meningoencephalitis: a systematic review and meta-analysis

The early diagnosis of bacterial meningoencephalitis (BM/E) is difficult, and delay in diagnosis can cause complications leading to neurological impairment/death. In cases of unexplained BM/E, the metagenomic NGS (mNGS) offers an advantage over conventional methods, especially when a rare pathogen is implicated or the patient is on antibiotics. This study aims to evaluate and compare the diagnostic efficacy of mNGS for the diagnosis of BM/E using cerebrospinal fluid (CSF) specimens versus a composite reference standard (CRS). The electronic databases (Embase, PubMed, and Web of Science) were searched up to 15 June 2021. Studies such as cohort, case-control, prospective, or retrospective studies that assessed the diagnostic efficacy of mNGS in suspected bacterial meningitis/encephalitis cases were included. Ten studies met the inclusion criteria, including three retrospective and seven prospective studies. The sensitivity of mNGS for diagnosis of BM/E from CSF samples ranged from 33 (95% CI: 13-62) to 98% (95% CI: 76-99). The specificity of mNGS ranged from 67 (95% CI: 55-78) to 98% (95% CI: 95-99). The estimated AUC (area under curve) by hierarchical summary receiver operating characteristic (HSROC) of the studies being analyzed was 0.912. The meta-regression analysis demonstrated that the different types of studies (single-center vs. multi-center) had an effect on the specificity of mNGS for BM/E compared with CRS (90% vs. 96%, meta-regression P < 0.05). The current analysis revealed moderate diagnostic accuracy of mNGS. This approach can be helpful, especially in cases of undiagnosed BM/E by identification of organism and subsequently accelerating the patient management.