Bernard H. Brownstein

Genomic responses in mouse models poorly mimic human inflammatory diseases

A cornerstone of modern biomedical research is the use of mouse models to explore basic pathophysiological mechanisms, evaluate new therapeutic approaches, and make go or no-go decisions to carry new drug candidates forward into clinical trials. Systematic studies evaluating how well murine models mimic human inflammatory diseases are nonexistent. Here, we show that, although acute inflammatory stresses from different etiologies result in highly similar genomic responses in humans, the responses in corresponding mouse models correlate poorly with the human conditions and also, one another. Among genes changed significantly in humans, the murine orthologs are close to random in matching their human counterparts (e.g., R2 between 0.0 and 0.1). In addition to improvements in the current animal model systems, our study supports higher priority for translational medical research to focus on the more complex human conditions rather than relying on mouse models to study human inflammatory diseases.

A network-based analysis of systemic inflammation in humans

Oligonucleotide and complementary DNA microarrays are being used to subclassify histologically similar tumours, monitor disease progress, and individualize treatment regimens. However, extracting new biological insight from high-throughput genomic studies of human diseases is a challenge, limited by difficulties in recognizing and evaluating relevant biological processes from huge quantities of experimental data. Here we present a structured network knowledge-base approach to analyse genome-wide transcriptional responses in the context of known functional interrelationships among proteins, small molecules and phenotypes. This approach was used to analyse changes in blood leukocyte gene expression patterns in human subjects receiving an inflammatory stimulus (bacterial endotoxin). We explore the known genome-wide interaction network to identify significant functional modules perturbed in response to this stimulus. Our analysis reveals that the human blood leukocyte response to acute systemic inflammation includes the transient dysregulation of leukocyte bioenergetics and modulation of translational machinery. These findings provide insight into the regulation of global leukocyte activities as they relate to innate immune system tolerance and increased susceptibility to infection in humans.

A genomic storm in critically injured humans

Critical injury in humans induces a genomic storm with simultaneous changes in expression of innate and adaptive immunity genes.

Co-ordinated programme of gene expression during asexual intraerythrocytic development of the human malaria parasite Plasmodium falciparum revealed by microarray analysis.

Plasmodium falciparum is a protozoan parasite responsible for the most severe forms of human malaria. All the clinical symptoms and pathological changes seen during human infection are caused by the asexual blood stages of Plasmodium. Within host red blood cells, the parasite undergoes enormous developmental changes during its maturation. In order to analyse the expression of genes during intraerythrocytic development, DNA microarrays were constructed and probed with stage‐specific cDNA. Developmental upregulation of specific mRNAs was found to cluster into functional groups and revealed a co‐ordinated programme of gene expression. Those involved in protein synthesis (ribosomal proteins, translation factors) peaked early in development, followed by those involved in metabolism, most dramatically glycolysis genes. Adhesion/invasion genes were turned on later in the maturation process. At the end of intraerythrocytic development (late schizogony), there was a general shut‐off of gene expression, although a small set of genes, including a number of protein kinases, were turned on at this stage. Nearly all genes showed some regulation over the course of development. A handful of genes remained constant and should be useful for normalizing mRNA levels between stages. These data will facilitate functional analysis of the P. falciparum genome and will help to identify genes with a critical role in parasite progression and multiplication in the human host.

Quantitative proteome analysis of human plasma following in vivo lypopolysaccharide administration using 16O/18O labeling and the accurate mass and time tag approach

Identification of novel diagnostic or therapeutic biomarkers from human blood plasma would benefit significantly from quantitative measurements of the proteome constituents over a range of physiological conditions. Herein we describe an initial demonstration of proteome-wide quantitative analysis of human plasma. The approach utilizes postdigestion trypsin-catalyzed 16O/18O peptide labeling, two-dimensional LC-FTICR mass spectrometry, and the accurate mass and time (AMT) tag strategy to identify and quantify peptides/proteins from complex samples. A peptide accurate mass and LC elution time AMT tag data base was initially generated using MS/MS following extensive multidimensional LC separations to provide the basis for subsequent peptide identifications. The AMT tag data base contains >8,000 putative identified peptides, providing 938 confident plasma protein identifications. The quantitative approach was applied without depletion of high abundance proteins for comparative analyses of plasma samples from an individual prior to and 9 h after lipopolysaccharide (LPS) administration. Accurate quantification of changes in protein abundance was demonstrated by both 1:1 labeling of control plasma and the comparison between the plasma samples following LPS administration. A total of 429 distinct plasma proteins were quantified from the comparative analyses, and the protein abundances for 25 proteins, including several known inflammatory response mediators, were observed to change significantly following LPS administration.

High Dynamic Range Characterization of the Trauma Patient Plasma Proteome

Although human plasma represents an attractive sample for disease biomarker discovery, the extreme complexity and large dynamic range in protein concentrations present significant challenges for characterization, candidate biomarker discovery, and validation. Herein we describe a strategy that combines immunoaffinity subtraction and subsequent chemical fractionation based on cysteinyl peptide and N-glycopeptide captures with two-dimensional LC-MS/MS to increase the dynamic range of analysis for plasma. Application of this “divide-and-conquer” strategy to trauma patient plasma significantly improved the overall dynamic range of detection and resulted in confident identification of 22,267 unique peptides from four different peptide populations (cysteinyl peptides, non-cysteinyl peptides, N-glycopeptides, and non-glycopeptides) that covered 3654 different proteins with 1494 proteins identified by multiple peptides. Numerous low abundance proteins were identified, exemplified by 78 “classic” cytokines and cytokine receptors and by 136 human cell differentiation molecules. Additionally a total of 2910 different N-glycopeptides that correspond to 662 N-glycoproteins and 1553 N-glycosylation sites were identified. A panel of the proteins identified in this study is known to be involved in inflammation and immune responses. This study established an extensive reference protein database for trauma patients that provides a foundation for future high throughput quantitative plasma proteomic studies designed to elucidate the mechanisms that underlie systemic inflammatory responses.

Reactivation of Multiple Viruses in Patients with Sepsis

A current controversy is whether patients with sepsis progress to an immunosuppressed state. We hypothesized that reactivation of latent viruses occurred with prolonged sepsis thereby providing evidence of clinically-relevant immunosuppression and potentially providing a means to serially-monitor patients immune status. Secondly, if viral loads are markedly elevated, they may contribute to morbidity and mortality. This study determined if reactivation of herpesviruses, polyomaviruses, and the anellovirus TTV occurred in sepsis and correlated with severity. Serial whole blood and plasma samples from 560 critically-ill septic, 161 critically-ill non-septic, and 164 healthy age-matched patients were analyzed by quantitative-polymerase-chain-reaction for cytomegalovirus (CMV), Epstein-Barr (EBV), herpes-simplex (HSV), human herpes virus-6 (HHV-6), and TTV. Polyomaviruses BK and JC were quantitated in urine. Detectable virus was analyzed with respect to secondary fungal and opportunistic bacterial infections, ICU duration, severity of illness, and survival. Patients with protracted sepsis had markedly increased frequency of detectable virus. Cumulative viral DNA detection rates in blood were: CMV (24.2%), EBV (53.2%), HSV (14.1%), HHV-6 (10.4%), and TTV (77.5%). 42.7% of septic patients had presence of two or more viruses. The 50% detection rate for herpesviruses was 5–8 days after sepsis onset. A small subgroup of septic patients had markedly elevated viral loads (>104–106 DNA copies/ml blood) for CMV, EBV, and HSV. Excluding TTV, DNAemia was uncommon in critically-ill non-septic patients and in age-matched healthy controls. Compared to septic patients without DNAemia, septic patients with viremia had increased fungal and opportunistic bacterial infections. Patients with detectable CMV in plasma had higher 90-day mortality compared to CMV-negative patients; p<0.05. Reactivation of latent viruses is common with prolonged sepsis, with frequencies similar to those occurring in transplant patients on immunosuppressive therapy and consistent with development of an immunosuppressive state. Whether reactivated latent viruses contribute to morbidity and mortality in sepsis remains unknown.

Clinical microfluidics for neutrophil genomics and proteomics

Neutrophils have key roles in modulating the immune response. We present a robust methodology for rapidly isolating neutrophils directly from whole blood with on-chip processing for mRNA and protein isolation for genomics and proteomics. We validate this device with an ex vivo stimulation experiment and by comparison with standard bulk isolation methodologies. Last, we implement this tool as part of a near-patient blood processing system within a multi-center clinical study of the immune response to severe trauma and burn injury. The preliminary results from a small cohort of subjects in our study and healthy controls show a unique time-dependent gene expression pattern clearly demonstrating the ability of this tool to discriminate temporal transcriptional events of neutrophils within a clinical setting.

Cell-specific expression and pathway analyses reveal alterations in trauma-related human T cell and monocyte pathways.

Monitoring genome-wide, cell-specific responses to human disease, although challenging, holds great promise for the future of medicine. Patients with injuries severe enough to develop multiple organ dysfunction syndrome have multiple immune derangements, including T cell apoptosis and anergy combined with depressed monocyte antigen presentation. Genome-wide expression analysis of highly enriched circulating leukocyte subpopulations, combined with cell-specific pathway analyses, offers an opportunity to discover leukocyte regulatory networks in critically injured patients. Severe injury induced significant changes in T cell (5,693 genes), monocyte (2,801 genes), and total leukocyte (3,437 genes) transcriptomes, with only 911 of these genes common to all three cell populations (12%). T cell-specific pathway analyses identified increased gene expression of several inhibitory receptors (PD-1, CD152, NRP-1, and Lag3) and concomitant decreases in stimulatory receptors (CD28, CD4, and IL-2Rα). Functional analysis of T cells and monocytes confirmed reduced T cell proliferation and increased cell surface expression of negative signaling receptors paired with decreased monocyte costimulation ligands. Thus, genome-wide expression from highly enriched cell populations combined with knowledge-based pathway analyses leads to the identification of regulatory networks differentially expressed in injured patients. Importantly, application of cell separation, genome-wide expression, and cell-specific pathway analyses can be used to discover pathway alterations in human disease.

A genomic score prognostic of outcome in trauma patients

Traumatic injuries frequently lead to infection, organ failure, and death. Health care providers rely on several Injury scoring systems to quantify the extent of injury and to help predict clinical outcome. Physiological, anatomical, and clinical laboratory analytic scoring systems (Acute Physiology and Chronic Health Evaluation [APACHE], Injury Severity Score [ISS]) are utilized, with limited success, to predict outcome following injury. The recent development of techniques for measuring the expression level of all of a person’s genes simultaneously may make it possible to develop an injury scoring system based on the degree of gene activation. We hypothesized that a peripheral blood leukocyte gene expression score could predict outcome, including multiple organ failure, following severe blunt trauma. To test such a scoring system, we measured gene expression of peripheral blood leukocytes from patients within 12 h of traumatic injury. cRNA derived from whole blood leukocytes obtained within 12 h of injury provided gene expression data for the entire genome that were used to create a composite gene expression score for each patient. Total blood leukocytes were chosen because they are active during inflammation, which is reflective of poor outcome. The gene expression score combines the activation levels of all the genes into a single number which compares the patient’s gene expression to the average gene expression in uninjured volunteers. Expression profiles from healthy volunteers were averaged to create a reference gene expression profile which was used to compute a difference from reference (DFR) score for each patient. This score described the overall genomic response of patients within the first 12 h following severe blunt trauma. Regression models were used to compare the association of the DFR, APACHE, and ISS scores with outcome. We hypothesized that patients with a total gene response more different from uninjured volunteers would tend to have poorer outcome than those more similar. Our data show that for measures of poor outcome, such as infections, organ failures, and length of hospital stay this is correct. DFR scores were associated significantly with adverse outcome, including multiple organ failure, duration of ventilation, length of hospital stay, and infection rate. The association remained significant after adjustment for injury severity as measured by APACHE or ISS. A single score representing changes in gene expression in peripheral blood leukocytes within hours of severe blunt injury is associated with adverse clinical outcomes that develop later in the hospital course. Assessment of genome-wide gene expression provides useful clinical information that is different from that provided by currently utilized anatomic or physiologic scores.