Browse
Submit Data
Databases
API
Help

Dataset Information

27 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Metagenomic Next-Generation Sequencing Reveals the Profile of Viral Infections in Kidney Transplant Recipients During the COVID-19 Pandemic

ABSTRACT:

Background

To study the clinical application of metagenomic next-generation sequencing (mNGS) in the detection of viral infections in kidney transplant recipients (KTRs) during the COVID-19 pandemic.

Methods

Using mNGS technology, 50 human fluid samples of KTRs were detected, including 20 bronchoalveolar lavage fluid (BALF) samples, 21 urine samples and 9 blood samples. The detected nucleic acid sequences were compared and analyzed with the existing viral nucleic acid sequences in the database, and the virus infection spectrum of KTRs was drawn.

Results

The viral nucleic acids of 15 types of viruses were detected in 96.00% (48/50) of the samples, of which 11 types of viruses were in BALF (95.00%, 19/20), and the dominant viruses were torque teno virus (TTV) (65.00%; 13/20), cytomegalovirus (CMV) (45.00%; 9/20) and human alphaherpesvirus 1 (25.00%; 5/20). 12 viruses (95.24%, 20/21) were detected in the urine, and the dominant viruses were TTV (52.38%; 11/21), JC polyomavirus (52.38%; 11/21), BK polyomavirus (42.86%; 9/21), CMV (33.33%; 7/21) and human betaherpesvirus 6B (28.57%; 6/21). 7 viruses were detected in the blood (100.00%, 9/9), and the dominant virus was TTV (100.00%; 9/9). Four rare viruses were detected in BALF and urine, including WU polyomavirus, primate bocaparvovirus 1, simian virus 12, and volepox virus. Further analysis showed that TTV infection with high reads indicated a higher risk of acute rejection (P < 0.05).

Conclusions

mNGS detection reveals the rich virus spectrum of infected KTRs, and improves the detection rate of rare viruses. TTV may be a new biomarker for predicting rejection.

SUBMITTER: Tian X

PROVIDER: S-EPMC9309489 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Similar Datasets

Metagenomic Next-Generation Sequencing for Diagnosing Infections in Lung Transplant Recipients: A Retrospective Study.

Project description:Background: Accurate identification of pathogens is essential for the diagnosis and control of infections. We aimed to compare the diagnostic performance of metagenomic next-generation sequencing (mNGS) and conventional detection methods (CDM) in lung transplant recipients (LTRs). Methods: We retrospectively analyzed 107 LTRs with suspected infection of pulmonary, blood, central nervous system or chest wall between March 2018 and November 2020. Bronchoalveolar lavage fluid and other body fluids were subject to pathogen detection by both mNGS and CDM. Results: Of the 163 specimens, 84 (51.5%) tested positive for both mNGS and culture, 19 (11.7%) of which were completely consistent, 44 (27.0%) were partially congruent, and 21 (12.9%) were discordant (kappa = .215; p = .001). Compared with CDM, mNGS detected a higher diversity of pathogens. Moreover, the turn-around time was significantly shorter for mNGS compared with culture (2.7 ± .4 vs. 5.5 ± 1.6 days, p < .001). As an auxiliary method, treatment strategies were adjusted according to mNGS findings in 31 cases (29.0%), including eight patients with non-infectious diseases, who were finally cured. Conclusion: mNGS can identify pathogens with a shorter turn-around time and therefore provide a more accurate and timely diagnostic information to ascertaining pulmonary infections. mNGS might have a role in differentiating infectious from non-infectious lung diseases in LTRs.

| S-EPMC8866178 | biostudies-literature

Application of metagenomic next-generation sequencing in the diagnosis and treatment of recurrent urinary tract infection in kidney transplant recipients.

Project description:BackgroundRapid and accurate pathogen diagnosis is an urgent unmet clinical need for recurrent urinary tract infection (RUTI) in kidney transplant recipients (KTRs). Metagenomic next-generation sequencing (mNGS) may offer another strategy for diagnosing uropathogens but remains to be studied.MethodsNineteen KTRs with RUTI were collected in this study. The uropathogens were detected and compared by mNGS and urine culture, respectively. Modifications of the anti-infection strategy were also assessed.ResultsRich and diverse pathogens were revealed by mNGS. mNGS was significantly higher than culture in total positive rate (100.0% vs. 31.6%; p < 0.01) and in identification rates for bacteria (89.5% vs. 31.6%; p < 0.01), for viruses (57.9% vs. 0; p < 0.01), and for fungi (42.1% vs. 0; p < 0.01), respectively. mNGS identified a significantly higher proportion of mixed infections than culture (89.5% vs. 10.5%; p < 0.01). The anti-infection therapies were adjusted in two (33.3%) and 12 (76.9%) cases guided by culture and mNGS, respectively.ConclusionmNGS has more remarkable etiological diagnostic performance compared with urine culture for KTRs with RUTI to guide anti-infection strategies and, in turn, protect the graft.

| S-EPMC9441654 | biostudies-literature

Longitudinal Monitoring of DNA Viral Loads in Transplant Patients Using Quantitative Metagenomic Next-Generation Sequencing.

Project description:Immunocompromised patients are prone to reactivations and (re-)infections of multiple DNA viruses. Viral load monitoring by single-target quantitative PCRs (qPCR) is the current cornerstone for virus quantification. In this study, a metagenomic next-generation sequencing (mNGS) approach was used for the identification and load monitoring of transplantation-related DNA viruses. Longitudinal plasma samples from six patients that were qPCR-positive for cytomegalovirus (CMV), Epstein-Barr virus (EBV), BK polyomavirus (BKV), adenovirus (ADV), parvovirus B19 (B19V), and torque teno-virus (TTV) were sequenced using the quantitative metagenomic Galileo Viral Panel Solution (Arc Bio, LLC, Cambridge, MA, USA) reagents and bioinformatics pipeline combination. Qualitative and quantitative performance was analysed with a focus on viral load ranges relevant for clinical decision making. All pathogens identified by qPCR were also identified by mNGS. BKV, CMV, and HHV6B were additionally detected by mNGS, and could be confirmed by qPCR or auxiliary bioinformatic analysis. Viral loads determined by mNGS correlated with the qPCR results, with inter-method differences in viral load per virus ranging from 0.19 log10 IU/mL for EBV to 0.90 log10 copies/mL for ADV. TTV, analysed by mNGS in a semi-quantitative way, demonstrated a mean difference of 3.0 log10 copies/mL. Trends over time in viral load determined by mNGS and qPCR were comparable, and clinical thresholds for initiation of treatment were equally identified by mNGS. The Galileo Viral Panel for quantitative mNGS performed comparably to qPCR concerning detection and viral load determination, within clinically relevant ranges of patient management algorithms.

| S-EPMC8874692 | biostudies-literature

Metagenomic next-generation sequencing aids the diagnosis of viral infections in febrile returning travellers.

Project description:ObjectivesTravel-associated infections are challenging to diagnose because of the broad spectrum of potential aetiologies. As a proof-of-principle study, we used MNGS to identify viral pathogens in clinical samples from returning travellers in a single center to explore its suitability as a diagnostic tool.MethodsPlasma samples from 40 returning travellers presenting with a fever of ≥38°C were sequenced using MNGS on the Illumina MiSeq platform and compared with standard-of-care diagnostic assays.ResultsIn total, 11/40 patients were diagnosed with a viral infection. Standard of care diagnostics revealed 5 viral infections using plasma samples; dengue virus 1 (n = 2), hepatitis E (n = 1), Ebola virus (n = 1) and hepatitis A (n = 1), all of which were detected by MNGS. Three additional patients with Chikungunya virus (n = 2) and mumps virus were diagnosed by MNGS only. Respiratory infections detected by nasal/throat swabs only were not detected by MNGS of plasma. One patient had infection with malaria and mumps virus during the same admission.ConclusionsMNGS analysis of plasma samples improves the sensitivity of diagnosis of viral infections and has potential as an all-in-one diagnostic test. It can be used to identify infections that have not been considered by the treating physician, co-infections and new or emerging pathogens.SummaryNext generation sequencing (NGS) has potential as an all-in-one diagnostic test. In this study we used NGS to diagnose returning travellers with acute febrile illness in the UK, highlighting cases where the diagnosis was missed using standard methods.

| S-EPMC6859916 | biostudies-literature

Emerging viral diseases in kidney transplant recipients.

Project description:Viruses are the most important cause of infections and a major source of mortality in Kidney Transplant Recipients (KTRs). These patients may acquire viral infections through exogenous routes including community exposure, donor organs, and blood products or by endogenous reactivation of latent viruses. Beside major opportunistic infections due to CMV and EBV and viral hepatitis B and C, several viral diseases have recently emerged in KTRs. New medical practices or technologies, implementation of new diagnostic tools, and improved medical information have contributed to the emergence of these viral diseases in this special population. The purpose of this review is to summarize the current knowledge on emerging viral diseases and newly discovered viruses in KTRs over the last two decades. We identified viruses in the field of KT that had shown the greatest increase in numbers of citations in the NCBI PubMed database. BKV was the most cited in the literature and linked to an emerging disease that represents a great clinical concern in KTRs. HHV-8, PVB19, WNV, JCV, H1N1 influenza virus A, HEV, and GB virus were the main other emerging viruses. Excluding HHV8, newly discovered viruses have been infrequently linked to clinical diseases in KTRs. Nonetheless, pathogenicity can emerge long after the discovery of the causative agent, as has been the case for BKV. Overall, antiviral treatments are very limited, and reducing immunosuppressive therapy remains the cornerstone of management.

| S-EPMC7169126 | biostudies-literature

Butyrate-producing gut bacteria and viral infections in kidney transplant recipients: A pilot study.

Project description:BackgroundThe gut microbiome is being associated increasingly with development of infections besides Clostridium difficile infection. A recent study found an association between butyrate-producing gut (BPG) bacteria and less frequent development of lower respiratory viral infections in allogeneic hematopoietic stem cell transplant recipients (Haak et al, Blood 131(26): 2978, 2018). In this investigation, we examine the relationship between the abundance of BPG bacteria and the development of viral infections in a cohort of kidney transplant recipients.MethodsWe recruited 168 kidney transplant recipients who provided 510 fecal specimens in the first 3 months after transplantation and profiled the gut microbiota using 16S rRNA gene sequencing of the V4-V5 hypervariable region. We classified the kidney transplant recipients into higher BPG Bacteria Group and lower BPG Bacteria Group using the same criteria of 1% relative gut abundance of BPG bacteria as the Haak et al study.ResultsAdministration of antibiotics against anaerobes was associated with a significant decrease in the relative gut abundance of BPG bacteria. The higher BPG Bacteria Group was associated with less development of respiratory viral infections (Hazard Ratio [HR]: 0.28, P = .01) but not with less development of CMV viremia (HR: 0.38, P = .13) or BK viremia (HR: 1.02, P = .98) at 2 years post transplantation.ConclusionOur pilot investigation supports future validation of the relationship between high relative gut abundance of BPG bacteria and decreased risk for development of respiratory viral infections.

| S-EPMC6917841 | biostudies-literature

Kidney transplant recipients

Project description:Kidney transplant recipients

| PRJNA1054489 | ENA

Kidney transplant recipients

Project description:This SuperSeries is composed of the SubSeries listed below.

2024-10-15 | GSE250536 | GEO

COVID-19 Breakthrough Infections in Vaccinated Kidney Transplant Recipients.

Project description:Coronavirus disease 2019 (COVID-19) is associated with increased morbidity and mortality among kidney transplant recipients (KTRs). The administration of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccination is the only reliable strategy to prevent COVID-19 and alleviate the severity of COVID-19 in this particular population. The aim of this article was to evaluate the clinical protection by vaccines (breakthrough infections, deaths, and hospitalizations) in KTRs. There were 135 KTRs with COVID-19 breakthrough infections for whom patient-level data were available in PubMed and Web of Science. There was a male predominance (61.4%), 97 were given the standard vaccination regimen, and 38 received three or four doses of the vaccine. The median age was 59.0 (IQR: 49.0-69.0) years. A total of 67 patients were hospitalized, and 10 patients died. In 72.6% of cases, triple-maintenance immunosuppression was employed. The deceased patients were older than the survivors (p < 0.05); an age over 60 years was a risk factor for death (p < 0.05). The KTRs with booster vaccines had a longer time interval from the last vaccine to COVID-19 infection and lower hospitalization rates than the individuals who received the standard vaccination regimen (33.3% vs. 54.8%, p < 0.05). The hospitalized patients were older than the outpatients (p < 0.05). Among 16,820 fully vaccinated or boosted KTRs from 14 centers, there were 633 breakthrough infections (3.58%) and 73 associated deaths (0.41%). The center-level breakthrough infection rates varied from 0.21% to 9.29%. These findings highlight the need for booster doses for KTRs. However, more research is needed to define the long-term effectiveness and immunogenicity of booster doses and to identify methods to boost the protective response to vaccination in these immunocompromised patients.

| S-EPMC9696595 | biostudies-literature

Pathogenic Detection by Metagenomic Next-Generation Sequencing in Osteoarticular Infections.

Project description:Objectives: To evaluate metagenomic next-generation sequencing (mNGS) as a diagnostic tool in detecting pathogens from osteoarticular infection (OAI) samples. Methods: 130 samples of joint fluid, sonicate fluid, and tissue were prospectively collected from 92 patients with OAI. The performance of mNGS and microbiology culture was compared pairwise. Results: The overall sensitivity of mNGS was 88.5% (115/130), significantly higher than that of microbiological culture, which had a sensitivity of 69.2% (90/130, p < 0.01). Sensitivity was significantly higher for joint fluid (mNGS: 86.7% vs. microbiology culture: 68.7%, p < 0.01) and sonicate fluid (mNGS: 100% vs. microbiology culture: 66.7%, p < 0.05) samples. mNGS detected 12 pathogenic strains undetected by microbiological culture. Additional pathogens detected by mNGS were Coagulase-negative Staphylococci, Gram-negative Bacillus, Streptococci, Anaerobe, non-tuberculosis mycobacterium, MTCP (p > 0.05), and Mycoplasma (OR = ∞, 95% confidence interval, 5.12-∞, p < 0.001). Additionally, sensitivity by mNGS was higher in antibiotic-treated samples compared to microbiological culture (89.7 vs. 61.5%, p < 0.01). Conclusions: mNGS is a robust diagnostic tool for pathogenic detection in samples from OAI patients, compared to routine cultures. The mNGS technique is particularly valuable to diagnose pathogens that are difficult to be cultured, or to test samples from patients previously treated with antibiotics.

| S-EPMC7527540 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data