Balancing precision versus cohort transcriptomic analysis of acute and recovery phase of viral bronchiolitis

Abstract

Viral infections affecting the lower respiratory tract place enormous burdens on hospitals. As neither vaccines nor anti-viral agents exist for many viruses, understanding risk factors and outcomes in each patient using minimally invasive analysis, such as blood, can lead to improved healthcare delivery. A cohort of PAXGene RNAseq of infants admitted with moderate or severe acute bronchiolitis and respiratory syncytial virus (RSV) were compared with case-control statistical analysis and cohort-based outlier mapping for precision transcriptomics. Severe bronchiolitis patients had signatures connected to the immune system, interferon signaling, and cytokine signaling, with marked sex differences in XIST, RPS4Y1, KDM5D, and LINC00278 for severity. Several patients had unique secondary infections, cytokine activation, immune responses, biological pathways, and immune cell activation, highlighting the need for defining patient-level transcriptomic signatures. Balancing relative contributions of cohort-based biomarker discoveries with patient's biological responses is needed to understand totality of mechanisms of adverse outcomes in viral bronchiolitis.

CCR5 and Biological Complexity: The Need for Data Integration and Educational Materials to Address Genetic/Biological Reductionism at the Interface of Ethical, Legal, and Social Implications

“…The phenotypes seen in the Geno2MP data suggested a broader analysis of CCR5 in disease pathologies. With the robust expression of CCR5 in blood and our history in studying the blood of immune challenged individuals, we selected to process CCR5 biology for blood-based RNAseq of 7,280 samples from 62 different BioProjects and three of our studies where we have patient-to-transcriptome insights ( 74 – 76 ) ( Figure 7 ). All these samples were blood collected into RNA PAXgene tubes to standardize sample collection.…”

“…The lowest CCR5 levels in the MODS cohort were observed in sepsis patients, one of which (patient 27) was lethal. The RSV study’s top three outliers for CCR5 expression were all hospitalized RSV cases (patient 1, 4, 19) ( 76 ). Patient 1 had high levels of Agromyces aureus and Caulobacter vibrioides like reads in the blood in addition to clinically confirmed RSV, while also having multiple levels of elevated RNA associated with lung hyperinflammation.…”

“…Open Targets Genetics ( 73 ) was used for the understanding of GWAS and pheWAS associations. Samples from our previous RNAseq work and details of methods used can be found in the three publications for MODS, RSV, or COVID-19 ( 74 – 76 ). All PAXgene tube blood RNAseq datasets within the NCBI SRA were downloaded with the SRA toolkit ( ) and processed for abundance using Salmon_0.14.1 ( 77 ) and the Gencode38 transcriptome ( 78 ).…”

“…All PAXgene tube blood RNAseq datasets within the NCBI SRA were downloaded with the SRA toolkit ( ) and processed for abundance using Salmon_0.14.1 ( 77 ) and the Gencode38 transcriptome ( 78 ). Microglia datasets were extracted from BioProjects PRJNA649597, PRJNA662330, PRJNA665286, PRJNA667596, PRJNA688478, PRJNA689841, PRJNA387182, PRJNA483247 and the blood RNAseq datasets from BioProjects PRJEB14743, PRJEB20731, PRJEB23048, PRJEB27958, PRJEB27965, PRJEB33892, PRJEB36928, PRJEB41073, PRJEB44660, PRJNA201433, PRJNA230906, PRJNA232593, PRJNA251404, PRJNA277352, PRJNA305001, PRJNA315611, PRJNA327986, PRJNA329148, PRJNA352062, PRJNA354367, PRJNA357628, PRJNA358580, PRJNA369684, PRJNA378794, PRJNA380820, PRJNA384259, PRJNA390289, PRJNA397222, PRJNA398240, PRJNA401870, PRJNA427575, PRJNA437114, PRJNA454694, PRJNA476781, PRJNA493832, PRJNA494155, PRJNA504827, PRJNA511891, PRJNA526259, PRJNA526839, PRJNA533086, PRJNA552286, PRJNA562305, PRJNA588242, PRJNA591657, PRJNA600846, PRJNA601661, PRJNA607120, PRJNA630674, PRJNA632871, PRJNA634938, PRJNA638653, PRJNA639278, PRJNA647880, PRJNA664368, PRJNA679264, PRJNA679331, PRJNA680771, PRJNA683803, PRJNA686397, PRJNA702558, PRJNA728070 in addition to our groups studies on MODS, RSV, and COVID-19 ( 74 – 76 ). All Gencode38 mapped reads for these samples can be found at .…”

Loss of Health Promoting Bacteria in the Gastrointestinal Microbiome of PICU Infants with Bronchiolitis: A Single-Center Feasibility Study

“…There is currently little understanding of the gut microbiota composition of infants with RSV in the PICU. Through the use of blood transcriptomics, we have previously shown that members of this RSV cohort presented experienced an extensive inflammatory response [ 11 ]. Our focus here was to determine how severely RSV in hospitalized infants impacts the gut microbiota and how various exposures (antibiotics, diet) modulate the GI microbiota.…”