Dataset Information

Next-generation sequencing for diagnosis of rare diseases in the neonatal intensive care unit.

ABSTRACT:

Background

Rare diseases often present in the first days and weeks of life and may require complex management in the setting of a neonatal intensive care unit (NICU). Exhaustive consultations and traditional genetic or metabolic investigations are costly and often fail to arrive at a final diagnosis when no recognizable syndrome is suspected. For this pilot project, we assessed the feasibility of next-generation sequencing as a tool to improve the diagnosis of rare diseases in newborns in the NICU.

Methods

We retrospectively identified and prospectively recruited newborns and infants admitted to the NICU of the Children's Hospital of Eastern Ontario and the Ottawa Hospital, General Campus, who had been referred to the medical genetics or metabolics inpatient consult service and had features suggesting an underlying genetic or metabolic condition. DNA from the newborns and parents was enriched for a panel of clinically relevant genes and sequenced on a MiSeq sequencing platform (Illumina Inc.). The data were interpreted with a standard informatics pipeline and reported to care providers, who assessed the importance of genotype-phenotype correlations.

Results

Of 20 newborns studied, 8 received a diagnosis on the basis of next-generation sequencing (diagnostic rate 40%). The diagnoses were renal tubular dysgenesis, SCN1A-related encephalopathy syndrome, myotubular myopathy, FTO deficiency syndrome, cranioectodermal dysplasia, congenital myasthenic syndrome, autosomal dominant intellectual disability syndrome type 7 and Denys-Drash syndrome.

Interpretation

This pilot study highlighted the potential of next-generation sequencing to deliver molecular diagnoses rapidly with a high success rate. With broader use, this approach has the potential to alter health care delivery in the NICU.

SUBMITTER: Daoud H

PROVIDER: S-EPMC4978597 | biostudies-literature | 2016 Aug

REPOSITORIES: biostudies-literature

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Publications

Next-generation sequencing for diagnosis of rare diseases in the neonatal intensive care unit.

Daoud Hussein H Luco Stephanie M SM Li Rui R Bareke Eric E Beaulieu Chandree C Jarinova Olga O Carson Nancy N Nikkel Sarah M SM Graham Gail E GE Richer Julie J Armour Christine C Bulman Dennis E DE Chakraborty Pranesh P Geraghty Michael M Lines Matthew A MA Lacaze-Masmonteil Thierry T Majewski Jacek J Boycott Kym M KM Dyment David A DA

CMAJ : Canadian Medical Association journal = journal de l'Association medicale canadienne 20160530 11

<h4>Background</h4>Rare diseases often present in the first days and weeks of life and may require complex management in the setting of a neonatal intensive care unit (NICU). Exhaustive consultations and traditional genetic or metabolic investigations are costly and often fail to arrive at a final diagnosis when no recognizable syndrome is suspected. For this pilot project, we assessed the feasibility of next-generation sequencing as a tool to improve the diagnosis of rare diseases in newborns i ...[more]

PMID: 27241786

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Project description:IntroductionThe Enterobacter cloacae complex (ECC) species are potential neonatal pathogens, and ECC strains are among the most commonly encountered Enterobacter spp. associated with nosocomial bloodstream infections. Outbreaks caused by ECC can lead to significant morbidity and mortality in susceptible neonates. At the molecular level, ECC exhibits genomic heterogeneity, with six closely related species and subspecies. Genetic variability poses a challenge in accurately identifying outbreaks by determining the clonality of ECC isolates. This difficulty is further compounded by the limitations of the commonly used molecular typing methods, such as pulsed field gel electrophoresis, which do not provide reliable accuracy in distinguishing between ECC strains and can lead to incorrect conclusions. Next-generation sequencing (NGS) offers superior resolution in determining strain relatedness. Therefore, we investigated the clinical pertinence of incorporating NGS into existing bundle measures to enhance patient management during an outbreak of ECC in a level-3 neonatal intensive care unit (NICU) in Germany.MethodsAs the standard of care, all neonates on the NICU received weekly microbiological swabs (nasopharyngeal and rectal) and analysis of endotracheal secretion, where feasible. During the 2.5-month outbreak, colonisation with ECC was detected in n = 10 neonates. The phylogenetic relationship and potential antimicrobial resistance genes as well as mobile genetic elements were identified via bacterial whole-genome sequencing (WGS) using Illumina MiSeq followed by in silico data analysis.ResultsAlthough all ECC isolates exhibited almost identical antimicrobial susceptibility patterns, the WGS data revealed the involvement of four different ECC clones. The isolates could be characterised as Enterobacter hormaechei subspecies steigerwaltii (n = 6, clonal), subsp. hoffmannii (n = 3, two clones) and subsp. oharae (n = 1). Despite the collection of environmental samples, no source of this diffuse outbreak could be identified. A new standardised operating procedure was implemented to enhance the management of neonates colonised with MRGN. This collaborative approach involved both parents and medical professionals and successfully prevented further transmission of ECC.ConclusionsInitially, it was believed that the NICU outbreak was caused by a single ECC clone due to the similarity in antibiotic resistance. However, our findings show that antibiotic susceptibility patterns can be misleading in investigating outbreaks of multi-drug-resistant ECC. In contrast, bacterial WGS accurately identified ECC at the clonal level, which significantly helped to delineate the nature of the observed outbreak.

Project description:ObjectiveTo evaluate the diagnostic performance of metagenomic next-generation sequencing (mNGS) and culture in pathogen detection among intensive care unit (ICU) and non-ICU patients with suspected pulmonary infection.MethodsIn this prospective study, sputum samples were collected from patients with suspected pulmonary infection for 2 consecutive days and then subjected to DNA or RNA sequencing by mNGS or culture; 62 ICU patients and 60 non-ICU patients were admitted. In the end, comparisons were made on the pathogen species identified by mNGS and culture, the overall performance of these two methods in pathogen detection, and the most common pathogens detected by mNGS between the ICU and non-ICU groups.ResultsIn DNA and RNA sequencing, the positive rate of pathogen detection reached 96.69% (117/121) and 96.43% (108/112), respectively. In culture tests, the positive rate of the pathogen was 39.34% (48/122), much lower than that of DNA and RNA sequencing. In general, the positive rate of pathogen detection by sputum mNGS was significantly higher than that of sputum culture in the total and non-ICU groups (p < 0.001) but did not show a significant difference when compared to the result of sputum culture in the ICU group (p = 0.08). Haemophilus spp., Candida albicans, Enterococcus spp., and viruses from the mNGS results were excluded before comparing the overall performance of these two methods in pathogen detection. Specifically, among the 10 most common bacteria implied from the mNGS results, significant differences were observed in the number of cases of Haemophilus parainfluenzae, Acinetobacter baumannii, Klebsiella pneumoniae, Pseudomonas aeruginosa, Stenotrophomonas maltophilia, Staphylococcus aureus, and Enterococcus faecalis between the ICU and non-ICU groups (p < 0.05).ConclusionsThis study demonstrated the superiority of mNGS over culture in detecting all kinds of pathogen species in sputum samples. These results indicate that mNGS may serve as a valuable tool to identify pathogens, especially for ICU patients who are more susceptible to mixed infections.

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Dataset Information

Next-generation sequencing for diagnosis of rare diseases in the neonatal intensive care unit.

Background

Methods

Results

Interpretation

Publications

Next-generation sequencing for diagnosis of rare diseases in the neonatal intensive care unit.

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