Biology subjects

Knight, J. C.

Publications and source records attributed to Knight, J. C..

3 recordsLinked to original sources

bioRxiv2018

Joint sequencing of human and pathogen genomes reveals the genetics of pneumococcal meningitis

Streptococcus pneumoniae is a common nasopharyngeal colonizer, but can also cause life-threatening invasive diseases such as empyema, bacteremia and meningitis. Genetic variation of host and pathogen is known to play a role in invasive pneumococcal disease, though to what extent is unknown. In a genome-wide association study of human and pathogen we show that human variation explains almost half of variation in susceptibility to pneumococcal meningitis and one-third of variation in severity, and identified variants in CCDC33 associated with susceptibility. Pneumococcal variation explained a large amount of invasive potential, but serotype explained only half of this variation. Newly developed methods identified pneumococcal genes involved in invasiveness including pspC and zmpD, and allowed a human-bacteria interaction analysis, finding associations between pneumococcal lineage and STK32C.

genomics↗

bioRxiv2018

The Autoimmune Disease Risk Allele rs6897932 Modulates Monocyte IL7R Surface and Soluble Receptor Levels in a Context-Specific Manner

IL-7 is a key factor in T-cell immunity and IL7R polymorphisms are implicated in autoimmune pathogenesis. IL7R mRNA is induced in stimulated monocytes in a genetically determined manner, yet a role for IL7R in monocyte biology remains unexplored. Here we characterize genetic regulation of IL7R at the protein level across multiple cell subsets and conditions in healthy individuals. We find monocyte surface and soluble IL7R (sIL7R) protein are markedly expressed in response to lipopolysaccharide (LPS). We further demonstrate alleles of rs6897932, a non-synonymous IL7R polymorphism associated with susceptibility to Multiple Sclerosis, Ankylosing Spondylitis and Primary Biliary Cirrhosis, form the key determinant of both surface IL7R and sIL7R in the context of inflammation. No effect of this allele was observed in unstimulated monocytes or across lymphoid subsets. Production of sIL7R by monocytes greatly exceeded that of CD4+ T-cells, and was strongly associated with both rs6897932 genotype and expression of the splicing factor gene DDX39A. Stimulated monocytes were sensitive to exogenous IL-7, which elicits a defined transcriptional signature. Flow cytometry and single-cell sequencing of synovial fluid derived monocytes from patients with spondyloarthritis showed an enlarged subset of IL7R+ monocytes with a unique transcriptional profile that markedly overlaps that induced by IL-7 in-vitro and shows similarity to the previously described Mono4 subset. These data demonstrate disease-associated genetic variants at IL7R specifically impact monocyte surface IL7R and sIL7R following innate immune stimulation, suggesting a previously unappreciated key role for monocytes in IL-7 pathway biology and IL7R-associated diseases.

immunology↗

bioRxiv2016

Mortality prediction in sepsis via gene expression analysis: a community approach

Improved risk stratification and prognosis in sepsis is a critical unmet need. Clinical severity scores and available assays such as blood lactate reflect global illness severity with suboptimal performance, and do not specifically reveal the underlying dysregulation of sepsis. Here three scientific groups were invited to independently generate prognostic models for 30-day mortality using 12 discovery cohorts (N=650) containing transcriptomic data collected from primarily community-onset sepsis patients. Predictive performance was validated in 5 cohorts of community-onset sepsis patients (N=189) in which the models showed summary AUROCs ranging from 0.765-0.89. Similar performance was observed in 4 cohorts of hospital-acquired sepsis (N=282). Combining the new gene-expression-based prognostic models with prior clinical severity scores led to significant improvement in prediction of 30-day mortality (p<0.01). These models provide an opportunity to develop molecular bedside tests that may improve risk stratification and mortality prediction in patients with sepsis, improving both resource allocation and prognostic enrichment in clinical trials.

bioinformatics↗