scholarly journals Application of combined genomic and transfer analyses to identify factors mediating regional spread of antibiotic resistant bacterial lineages

2020 ◽  
Author(s):  
Joyce Wang ◽  
Betsy Foxman ◽  
Ali Pirani ◽  
Zena Lapp ◽  
Lona Mody ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Genomic Analysis ◽  
Patient Characteristics ◽  
Patient Transfer ◽  
Whole Genome ◽  
Nursing Facilities ◽  
Antibiotic Resistant ◽  
Patient Level ◽  
Healthcare Associated

ABSTRACTBackgroundPatients entering nursing facilities (NFs) are frequently colonized with antibiotic resistant organisms (AROs). To understand the determinants of ARO colonization on NF admission we applied whole-genome sequencing to track the spread of four ARO species across regional NFs and evaluated patient-level characteristics and transfer acute-care hospitals (ACHs) as risk factors for colonization.Methods584 patients from six NFs were surveyed for methicillin-resistant Staphylococcus aureus (MRSA), vancomycin-resistant Enterococcus faecalis/faecium (VREfc/VREfm) and ciprofloxacin-resistant Escherichia coli (CipREc) colonization. Genomic analysis was performed to quantify ARO spread between NFs and compared to patient-transfer networks. The association between admission colonization and patient-level variables and recent ACH exposures was examined using multivariable regression models.ResultsThe majority of ARO isolates across study sites belonged to major healthcare-associated lineages: MRSA (ST5;N=89/117); VREfc (ST6;N=68/75); CipREc (ST131; N=58/64), and VREfm (clade A; N=129/129). While the genomic similarity of strains between NF pairs was associated with overlap in their feeder ACHs (Spearman’s rho=0.44-0.75, p<0.05 for MRSA, VREfc and CipREc), limited phylogenetic clustering by either ACH or NF supported regional endemicity. Significant predictors for ARO colonization on NF admission included lower functional status (adjusted odds ratio [aOR]>1 for all four AROs) and recent exposure to glycopeptides (aOR>2 for VREfm, VREfc and MRSA) or 3rd/4th-generation cephalosporins (aOR>2 for MRSA and VREfm). Transfer from specific ACHs was an independent risk factor for only one ARO/ACH pair (VREfm/ACH19, aOR=2.48[1.06-5.83]).ConclusionIn this region, healthcare-associated ARO lineages are endemic among connected NFs and ACHs, making patient characteristics more informative of NF admission colonization risk than exposure to specific ACHs.SummaryUsing a combination of whole-genome sequencing, patient transfer and clinical data, we discerned the dissemination of four high-priority antibiotic-resistant organisms (ARO) in the regional healthcare network, and epidemiolocal drivers underlying the high ARO importation rate into regional nursing facilities.

scholarly journals Application of Combined Genomic and Transfer Analyses to Identify Factors Mediating Regional Spread of Antibiotic-resistant Bacterial Lineages

2020 ◽  
Vol 71 (10) ◽  
pp. e642-e649
Author(s):  
Joyce Wang ◽  
Betsy Foxman ◽  
Ali Pirani ◽  
Zena Lapp ◽  
Lona Mody ◽  
...  
Keyword(s):  
Methicillin Resistant Staphylococcus Aureus ◽  
Genomic Analysis ◽  
Patient Characteristics ◽  
Fourth Generation ◽  
Nursing Facilities ◽  
Antibiotic Resistant ◽  
Patient Level ◽  
Vancomycin Resistant ◽  
Healthcare Associated ◽  
Genomic Similarity

Abstract Background Patients entering nursing facilities (NFs) are frequently colonized with antibiotic-resistant organisms (AROs). To understand the determinants of ARO colonization on NF admission, we applied whole-genome sequencing to track the spread of 4 ARO species across regional NFs and evaluated patient-level characteristics and transfer acute care hospitals (ACHs) as risk factors for colonization. Methods Patients from 6 NFs (n = 584) were surveyed for methicillin-resistant Staphylococcus aureus (MRSA), vancomycin-resistant Enterococcus faecalis/faecium (VREfc/VREfm), and ciprofloxacin-resistant Escherichia coli (CipREc) colonization. Genomic analysis was performed to quantify ARO spread between NFs and compared to patient-transfer networks. The association between admission colonization and patient-level variables and recent ACH exposures was examined. Results The majority of ARO isolates belonged to major healthcare-associated lineages: MRSA (sequence type [ST] 5); VREfc (ST6); CipREc (ST131), and VREfm (clade A). While the genomic similarity of strains between NF pairs was positively associated with overlap in their feeder ACHs (P &lt; .05 for MRSA, VREfc, and CipREc), limited phylogenetic clustering by either ACH or NF supported regional endemicity. Significant predictors for ARO colonization on NF admission included lower functional status and recent exposure to glycopeptides (adjusted odds ratio [aOR], &gt; 2 for MRSA and VREfc/VREfm) or third-/fourth-generation cephalosporins (aOR, &gt; 2 for MRSA and VREfm). Transfer from specific ACHs was an independent risk factor for only 1 ARO/ACH pair (VREfm/ACH19: aOR, 2.48). Conclusions In this region, healthcare-associated ARO lineages are endemic among connected NFs and ACHs, making patient characteristics more informative of NF admission colonization risk than exposure to specific ACHs.

scholarly journals Are Many Patients Diagnosed With Healthcare-associated Clostridioides difficile Infections Colonized With the Infecting Strain on Admission?

2019 ◽  
Vol 69 (10) ◽  
pp. 1801-1804 ◽  
Author(s):  
Melany Gonzalez-Orta ◽  
Carlos Saldana ◽  
Yilen Ng-Wong ◽  
Jennifer Cadnum ◽  
Annette Jencson ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Acute Care ◽  
Genome Sequencing ◽  
Acute Care Hospital ◽  
Whole Genome ◽  
Care Hospital ◽  
Clostridioides Difficile ◽  
Healthcare Associated

Abstract In a cohort of 480 patients admitted to an acute care hospital, 68 (14%) had positive perirectal cultures for toxigenic Clostridioides difficile on admission. Of the 11 patients (2%) diagnosed with healthcare-associated C. difficile infections, 3 (27%) had genetically related admission and infection isolates, based on whole-genome sequencing.

scholarly journals Identification of Pathogenic Structural Variants in Rare Disease Patients through Genome Sequencing

2019 ◽  
Author(s):  
James M. Holt ◽  
Camille L. Birch ◽  
Donna M. Brown ◽  
Manavalan Gajapathy ◽  
Nadiya Sosonkina ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Rare Disease ◽  
Genome Sequencing ◽  
Genomic Analysis ◽  
Whole Genome ◽  
Structural Variants ◽  
Single Nucleotide Variants ◽  
Standard Clinical Practice ◽  
Wide Range ◽  
Genetic Features

AbstractPurposeClinical whole genome sequencing is becoming more common for determining the molecular diagnosis of rare disease. However, standard clinical practice often focuses on small variants such as single nucleotide variants and small insertions/deletions. This leaves a wide range of larger “structural variants” that are not commonly analyzed in patients.MethodsWe developed a pipeline for processing structural variants for patients who received whole genome sequencing through the Undiagnosed Diseases Network (UDN). This pipeline called structural variants, stored them in an internal database, and filtered the variants based on internal frequencies and external annotations. The remaining variants were manually inspected and then interesting findings were reported as research variants to clinical sites in the UDN.ResultsOf 477 analyzed UDN cases, 286 cases (≈ 60%) received at least one structural variant as a research finding. The variants in 16 cases (≈ 4%) are considered “Certain” or “Highly likely” molecularly diagnosed and another 4 cases are currently in review. Of those 20 cases, at least 13 were identified originally through our pipeline with one finding leading to identification of a new disease. As part of this paper, we have also released the collection of variant calls identified in our cohort along with heterozygous and homozygous call counts. This data is available at https://github.com/HudsonAlpha/UDN_SV_export.ConclusionStructural variants are key genetic features that should be analyzed during routine clinical genomic analysis. For our UDN patients, structural variants helped solve ≈ 4% of the total number of cases (≈ 13% of all genome sequencing solves), a success rate we expect to improve with better tools and greater understanding of the human genome.

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