Predictive signature of murine and human host response to typical and atypical pneumonia.

BACKGROUND: Pneumonia due to typical bacterial, atypical bacterial and viral pathogens can be difficult to clinically differentiate. Host response-based diagnostics are emerging as a complementary diagnostic strategy to pathogen detection. METHODS: We used murine models of typical bacterial, atypical bacterial and viral pneumonia to develop diagnostic signatures and understand the host's response to these types of infections. Mice were intranasally inoculated with Streptococcus pneumoniae, Mycoplasma pneumoniae, influenza or saline as a control. Peripheral blood gene expression analysis was performed at multiple time points. Differentially expressed genes were used to perform gene set enrichment analysis and generate diagnostic signatures. These murine-derived signatures were externally validated in silico using human gene expression data. The response to S. pneumoniae was the most rapid and robust. RESULTS: Mice infected with M. pneumoniae had a delayed response more similar to influenza-infected animals. Diagnostic signatures for the three types of infection had 0.94-1.00 area under the receiver operator curve (auROC). Validation in five human gene expression datasets revealed auROC of 0.82-0.96. DISCUSSION: This study identified discrete host responses to typical bacterial, atypical bacterial and viral aetiologies of pneumonia in mice. These signatures validated well in humans, highlighting the conserved nature of the host response to these pathogen classes.

Implementation of a Prospective Index-Cluster Sampling Strategy for the Detection of Presymptomatic Viral Respiratory Infection in Undergraduate Students.

Background: Index-cluster studies may help characterize the spread of communicable infections in the presymptomatic state. We describe a prospective index-cluster sampling strategy (ICSS) to detect presymptomatic respiratory viral illness and its implementation in a college population. Methods: We enrolled an annual cohort of first-year undergraduates who completed daily electronic symptom diaries to identify index cases (ICs) with respiratory illness. Investigators then selected 5-10 potentially exposed, asymptomatic close contacts (CCs) who were geographically co-located to follow for infections. Symptoms and nasopharyngeal samples were collected for 5 days. Logistic regression model-based predictions for proportions of self-reported illness were compared graphically for the whole cohort sampling group and the CC group. Results: We enrolled 1379 participants between 2009 and 2015, including 288 ICs and 882 CCs. The median number of CCs per IC was 6 (interquartile range, 3-8). Among the 882 CCs, 111 (13%) developed acute respiratory illnesses. Viral etiology testing in 246 ICs (85%) and 719 CCs (82%) identified a pathogen in 57% of ICs and 15% of CCs. Among those with detectable virus, rhinovirus was the most common (IC: 18%; CC: 6%) followed by coxsackievirus/echovirus (IC: 11%; CC: 4%). Among 106 CCs with a detected virus, only 18% had the same virus as their associated IC. Graphically, CCs did not have a higher frequency of self-reported illness relative to the whole cohort sampling group. Conclusions: Establishing clusters by geographic proximity did not enrich for cases of viral transmission, suggesting that ICSS may be a less effective strategy to detect spread of respiratory infection.

Host-response transcriptional biomarkers accurately discriminate bacterial and viral infections of global relevance.

Diagnostic limitations challenge management of clinically indistinguishable acute infectious illness globally. Gene expression classification models show great promise distinguishing causes of fever. We generated transcriptional data for a 294-participant (USA, Sri Lanka) discovery cohort with adjudicated viral or bacterial infections of diverse etiology or non-infectious disease mimics. We then derived and cross-validated gene expression classifiers including: 1) a single model to distinguish bacterial vs. viral (Global Fever-Bacterial/Viral [GF-B/V]) and 2) a two-model system to discriminate bacterial and viral in the context of noninfection (Global Fever-Bacterial/Viral/Non-infectious [GF-B/V/N]). We then translated to a multiplex RT-PCR assay and independent validation involved 101 participants (USA, Sri Lanka, Australia, Cambodia, Tanzania). The GF-B/V model discriminated bacterial from viral infection in the discovery cohort an area under the receiver operator curve (AUROC) of 0.93. Validation in an independent cohort demonstrated the GF-B/V model had an AUROC of 0.84 (95% CI 0.76-0.90) with overall accuracy of 81.6% (95% CI 72.7-88.5). Performance did not vary with age, demographics, or site. Host transcriptional response diagnostics distinguish bacterial and viral illness across global sites with diverse endemic pathogens.

Safety and efficacy of letetresgene autoleucel alone or with pembrolizumab for relapsed/refractory multiple myeloma.

This pilot study assessed the safety and efficacy of letetresgene autoleucel (lete-cel; GSK3377794), a genetically modified autologous T-cell therapy targeting New York esophageal squamous cell carcinoma-1 (NY-ESO-1)/L antigen family member 1 isoform A (LAGE-1a)-positive myeloma cells, alone or in combination with pembrolizumab in patients with relapsed/refractory multiple myeloma. Eligible patients expressed NY-ESO-1 and/or LAGE-1a and either HLA-A∗02:01, ∗02:05, or ∗02:06. Patients received lete-cel single infusion alone (arm 1) or with pembrolizumab (arm 2). 127 patients were screened, and 6 patients (3 per arm) were enrolled; patients in arm 1 and 2 received lete-cel alone, or with pembrolizumab, respectively. All patients exhibited grade 3/4 cytopenias, which resolved or improved to grade 1. One patient (arm 1) had grade 3/4 lete-cel-related adverse events (AEs); 2 patients (arm 2) had grade 3/4 AEs related to lete-cel and lymphodepletion. Three patients with grade 1/2 cytokine release syndrome (CRS) exhibited elevated post-lete-cel interleukin-6 levels versus those without CRS. Pooled overall response rate was 50% including 1 patient each with confirmed clinical response, very good clinical response, and partial response, and progression-free survival ranged from 1.3 to 5.2 months. Responders (arm 1: n = 1; arm 2: n = 2) had a time-to-response of 3 weeks, duration of response of 2.1 months. Two responders, but no nonresponders, exhibited elevated cytokine levels after lete-cel infusion. Lete-cel had a manageable safety profile and demonstrated clear but transient antitumor activity in patients with relapsed/refractory multiple myeloma. This trial was registered at www.clinicaltrials.gov as #NCT03168438.

Validation of a Host Gene Expression Test for Bacterial/Viral Discrimination in Immunocompromised Hosts.

BACKGROUND: Host gene expression has emerged as a complementary strategy to pathogen detection tests for the discrimination of bacterial and viral infection. The impact of immunocompromise on host-response tests remains unknown. We evaluated a host-response test discriminating bacterial, viral, and noninfectious conditions in immunocompromised subjects. METHODS: An 81-gene signature was measured using real-time-polymerase chain reaction in subjects with immunocompromise (chemotherapy, solid-organ transplant, immunomodulatory agents, AIDS) with bacterial infection, viral infection, or noninfectious illness. A regularized logistic regression model trained in immunocompetent subjects was used to estimate the likelihood of each class in immunocompromised subjects. RESULTS: Accuracy in the 136-subject immunocompetent training cohort was 84.6% for bacterial versus nonbacterial discrimination and 80.8% for viral versus nonviral discrimination. Model validation in 134 immunocompromised subjects showed overall accuracy of 73.9% for bacterial infection (P = .04 relative to immunocompetent subjects) and 75.4% for viral infection (P = .30). A scheme reporting results by quartile improved test utility. The highest probability quartile ruled-in bacterial and viral infection with 91.4% and 84.0% specificity, respectively. The lowest probability quartile ruled-out infection with 90.1% and 96.4% sensitivity for bacterial and viral infection, respectively. Performance was independent of the type or number of immunocompromising conditions. CONCLUSIONS: A host gene expression test discriminated bacterial, viral, and noninfectious etiologies at a lower overall accuracy in immunocompromised patients compared with immunocompetent patients, although this difference was only significant for bacterial infection classification. With modified interpretive criteria, a host-response strategy may offer clinically useful diagnostic information for patients with immunocompromise.

A blood-based host gene expression assay for early detection of respiratory viral infection: an index-cluster prospective cohort study.

BACKGROUND: Early and accurate identification of individuals with viral infections is crucial for clinical management and public health interventions. We aimed to assess the ability of transcriptomic biomarkers to identify naturally acquired respiratory viral infection before typical symptoms are present. METHODS: In this index-cluster study, we prospectively recruited a cohort of undergraduate students (aged 18-25 years) at Duke University (Durham, NC, USA) over a period of 5 academic years. To identify index cases, we monitored students for the entire academic year, for the presence and severity of eight symptoms of respiratory tract infection using a daily web-based survey, with symptoms rated on a scale of 0-4. Index cases were defined as individuals who reported a 6-point increase in cumulative daily symptom score. Suspected index cases were visited by study staff to confirm the presence of reported symptoms of illness and to collect biospecimen samples. We then identified clusters of close contacts of index cases (ie, individuals who lived in close proximity to index cases, close friends, and partners) who were presumed to be at increased risk of developing symptomatic respiratory tract infection while under observation. We monitored each close contact for 5 days for symptoms and viral shedding and measured transcriptomic responses at each timepoint each day using a blood-based 36-gene RT-PCR assay. FINDINGS: Between Sept 1, 2009, and April 10, 2015, we enrolled 1465 participants. Of 264 index cases with respiratory tract infection symptoms, 150 (57%) had a viral cause confirmed by RT-PCR. Of their 555 close contacts, 106 (19%) developed symptomatic respiratory tract infection with a proven viral cause during the observation window, of whom 60 (57%) had the same virus as their associated index case. Nine viruses were detected in total. The transcriptomic assay accurately predicted viral infection at the time of maximum symptom severity (mean area under the receiver operating characteristic curve [AUROC] 0·94 [95% CI 0·92-0·96]), as well as at 1 day (0·87 [95% CI 0·84-0·90]), 2 days (0·85 [0·82-0·88]), and 3 days (0·74 [0·71-0·77]) before peak illness, when symptoms were minimal or absent and 22 (62%) of 35 individuals, 25 (69%) of 36 individuals, and 24 (82%) of 29 individuals, respectively, had no detectable viral shedding. INTERPRETATION: Transcriptional biomarkers accurately predict and diagnose infection across diverse viral causes and stages of disease and thus might prove useful for guiding the administration of early effective therapy, quarantine decisions, and other clinical and public health interventions in the setting of endemic and pandemic infectious diseases. FUNDING: US Defense Advanced Research Projects Agency.

Previously Derived Host Gene Expression Classifiers Identify Bacterial and Viral Etiologies of Acute Febrile Respiratory Illness in a South Asian Population.

BACKGROUND: Pathogen-based diagnostics for acute respiratory infection (ARI) have limited ability to detect etiology of illness. We previously showed that peripheral blood-based host gene expression classifiers accurately identify bacterial and viral ARI in cohorts of European and African descent. We determined classifier performance in a South Asian cohort. METHODS: Patients ≥15 years with fever and respiratory symptoms were enrolled in Sri Lanka. Comprehensive pathogen-based testing was performed. Peripheral blood ribonucleic acid was sequenced and previously developed signatures were applied: a pan-viral classifier (viral vs nonviral) and an ARI classifier (bacterial vs viral vs noninfectious). RESULTS: Ribonucleic acid sequencing was performed in 79 subjects: 58 viral infections (36 influenza, 22 dengue) and 21 bacterial infections (10 leptospirosis, 11 scrub typhus). The pan-viral classifier had an overall classification accuracy of 95%. The ARI classifier had an overall classification accuracy of 94%, with sensitivity and specificity of 91% and 95%, respectively, for bacterial infection. The sensitivity and specificity of C-reactive protein (>10 mg/L) and procalcitonin (>0.25 ng/mL) for bacterial infection were 100% and 34%, and 100% and 41%, respectively. CONCLUSIONS: Previously derived gene expression classifiers had high predictive accuracy at distinguishing viral and bacterial infection in South Asian patients with ARI caused by typical and atypical pathogens.

Utility of predictive tools for risk stratification of elderly individuals with all-cause acute respiratory infection.

PURPOSE: A number of scoring tools have been developed to predict illness severity and patient outcome for proven pneumonia, however, less is known about the utility of clinical prediction scores for all-cause acute respiratory infection (ARI), especially in elderly subjects who are at increased risk of poor outcomes. METHODS: We retrospectively analyzed risk factors and outcomes of individuals ≥ 60 years of age presenting to the emergency department with a clinical diagnosis of ARI. RESULTS: Of 276 individuals in the study, 40 had proven viral infection and 52 proven bacterial infection, but 184 patients with clinically adjudicated ARI (67%) remained without a proven microbial etiology despite extensive clinical (and expanded research) workup. Patients who were older, had multiple comorbidities, or who had proven bacterial infection were more likely to require hospital and ICU admission. We identified a novel model based on 11 demographic and clinical variables that were significant risk factors for ICU admission or mortality in elderly subjects with all-cause ARI. As comparators, a modified PORT score was found to correlate more closely with all-cause ARI severity than a modified CURB-65 score (r, 0.54, 0.39). Interestingly, modified Jackson symptom scores were found to inversely correlate with severity (r, - 0.34) but show potential for differentiating viral and bacterial etiologies. CONCLUSIONS: Modified PORT, CURB-65, Jackson symptom scores, and a novel ARI scoring tool presented herein all offer predictive ability for all-cause ARI in elderly subjects. Such broadly applicable scoring metrics have the potential to assist in treatment and triage decisions at the point of care.

Single-Molecule hsTnI and Short-Term Risk in Stable Patients With Chest Pain.

BACKGROUND: Evaluation of stable symptomatic outpatients with suspected coronary artery disease (CAD) may be challenging because they have a wide range of cardiovascular risk. The role of troponin testing to assist clinical decision making in this setting is unexplored. OBJECTIVES: This study sought to evaluate the prognostic meaning of single-molecule counting high-sensitivity troponin I (hsTnI) (normal range <6 ng/l) among outpatients with stable chest symptoms and suspected CAD. METHODS: Participants with available blood samples in PROMISE (Prospective Multicenter Imaging Study for Evaluation of Chest Pain) were studied, and hsTnI results were analyzed relative to the primary outcome of death, acute myocardial infarction (MI), or hospitalization for unstable angina by 1 year. The secondary outcome was the composite of cardiovascular death or acute MI. RESULTS: The study sample consisted of 4,021 participants; 98.6% had measurable hsTnI concentrations. The median hsTnI value was 1.6 ng/l. In upper hsTnI quartiles, patients had higher-risk clinical profiles. Higher hsTnI concentrations were associated with greater event probabilities for death, acute MI, or hospitalization for unstable angina. In multivariable models, hsTnI concentrations independently predicted death, acute MI, or hospitalization for unstable angina (hazard ratio: 1.54 per increase in log-hsTnI interquartile range; p < 0.001) and cardiovascular death or acute MI (hazard ratio: 1.52 per increase in log-hsTnI interquartile range; p < 0.001) and were particularly associated with near-term events, compared with longer follow-up. CONCLUSIONS: In symptomatic outpatients with suspected CAD, higher concentrations of hsTnI within the normal range were associated with heightened near-term risk for death, acute MI, or hospitalization. (Prospective Multicenter Imaging Study for Evaluation of Chest Pain [PROMISE]; NCT01174550).

High-Sensitivity Troponin I and Coronary Computed Tomography in Symptomatic Outpatients With Suspected CAD: Insights From the PROMISE Trial.

OBJECTIVES: The goal of this study was to examine associations between concentrations of high-sensitivity troponin I (hsTnI) (measured by using a single-molecule counting method) and obstructive coronary artery disease (CAD) in 1,844 stable, symptomatic outpatients with suspected CAD randomized to undergo coronary computed tomography angiography (CTA) in the PROMISE (Prospective Multicenter Imaging Study for Evaluation of Chest Pain) trial. BACKGROUND: Elevated concentrations of hsTnI are associated with CAD in patients with myocardial infarction. The meaning of hsTnI concentrations in stable symptomatic outpatients is not well understood. METHODS: Clinical characteristics and CTA results (including coronary artery calcium [CAC] scores) were expressed across hsTnI quartiles. Determinants of hsTnI concentration were identified. Multivariable logistic regression identified independent predictors of obstructive CAD50 (≥50% stenosis in any vessel) and CAD70 (≥70% stenosis or ≥50% left main). RESULTS: The median hsTnI concentration was 1.5 ng/l; nearly all (98.5%) subjects had measurable hsTnI, and 6.1% had concentrations ≥99th percentile concentration for this assay (6 ng/l). Higher CAC scores, as well as more prevalent and diffuse CAD, was seen in upper hsTnI quartiles (all p < 0.001). Independent predictors of hsTnI concentrations included age, sex, and CAC score (all p < 0.05). After adjusting for demographic and clinical characteristics, log-transformed hsTnI concentrations were associated with obstructive CAD50 (odds ratio: 1.15 per interquartile range; p = 0.02) and CAD70 (odds ratio: 1.25 per interquartile range; p = 0.001). CONCLUSIONS: In stable symptomatic outpatients undergoing nonemergent coronary CTA for the diagnosis of suspected CAD, higher concentrations of hsTnI were associated with increasing presence and severity of coronary atherosclerosis. (Prospective Multicenter Imaging Study for Evaluation of Chest Pain [PROMISE]; NCT01174550).

Sex-Based Differences in Outcomes With Transcatheter Aortic Valve Therapy: TVT Registry From 2011 to 2014.

BACKGROUND: A differential impact of sex has been observed in transcatheter aortic valve replacement (TAVR) outcomes from small observational studies and subgroup analyses of randomized trials. OBJECTIVES: The goal of this study was to compare the in-hospital and 1-year outcomes in male and female subjects from the U.S. nationwide TAVR registry. METHODS: National data from the Society of Thoracic Surgeons/American College of Cardiology Transcatheter Valve Therapy Registry were used for in-hospital outcomes, and data linked from the Centers for Medicare & Medicaid Services were used to provide 1-year events. Multivariable logistic regression adjustment was performed for in-hospital outcomes. Fine-Gray models were used for nonfatal 1-year outcomes to account for the competing risk of death. RESULTS: From 2011 to 2014, a total of 11,808 (49.9%) women and 11,844 (51.1%) men underwent TAVR. Compared with male patients, female patients were older, with a lower prevalence of coronary artery disease, atrial fibrillation, and diabetes but a higher rate of porcelain aorta, lower glomerular filtration rate, and higher mean Society of Thoracic Surgeons score (9.0% vs. 8.0%; all p < 0.001). Women were treated more often by using nontransfemoral access than men (45.0% vs. 34.0%). Despite using smaller device sizes, women achieved valve cover index ≥8% more often than men (66% vs. 54%). In-hospital vascular complications were higher in women (8.27% vs. 4.39%; adjusted hazard ratio [HR]: 1.70; 95% CI: 1.34 to 2.14; p < 0.001) and a trend toward higher bleeding (8.01% vs 5.96%; adjusted HR: 1.19; 95% CI: 0.99 to 1.44; p = 0.06) was observed; however, 1-year mortality was lower (21.3% vs. 24.5%; adjusted HR: 0.73; 95% CI: 0.63 to 0.85; p < 0.001) in women than in men. CONCLUSIONS: Female patients undergoing TAVR had a different risk profile compared with male patients. Notwithstanding a greater adjusted risk for in-hospital vascular complications, 1-year adjusted survival was superior in female patients.

Transcriptomic Analysis of the Host Response and Innate Resilience to Enterotoxigenic Escherichia coli Infection in Humans.

BACKGROUND: Enterotoxigenic Escherichia coli (ETEC) is a globally prevalent cause of diarrhea. Though usually self-limited, it can be severe and debilitating. Little is known about the host transcriptional response to infection. We report the first gene expression analysis of the human host response to experimental challenge with ETEC. METHODS: We challenged 30 healthy adults with an unattenuated ETEC strain, and collected serial blood samples shortly after inoculation and daily for 8 days. We performed gene expression analysis on whole peripheral blood RNA samples from subjects in whom severe symptoms developed (n = 6) and a subset of those who remained asymptomatic (n = 6) despite shedding. RESULTS: Compared with baseline, symptomatic subjects demonstrated significantly different expression of 406 genes highlighting increased immune response and decreased protein synthesis. Compared with asymptomatic subjects, symptomatic subjects differentially expressed 254 genes primarily associated with immune response. This comparison also revealed 29 genes differentially expressed between groups at baseline, suggesting innate resilience to infection. Drug repositioning analysis identified several drug classes with potential utility in augmenting immune response or mitigating symptoms. CONCLUSIONS: There are statistically significant and biologically plausible differences in host gene expression induced by ETEC infection. Differential baseline expression of some genes may indicate resilience to infection.

SLCO1B1 genetic variants, long-term low-density lipoprotein cholesterol levels and clinical events in patients following cardiac catheterization.

AIM: SLCO1B1 variants are associated with intermediate outcomes that may increase risk of death/myocardial infarction (MI) in statin-treated patients. PATIENTS & METHODS: In high-risk Caucasians undergoing cardiac catheterization, we tested the association between rs4149056/625T>C and rs2306283/492A>G with low-density lipoprotein cholesterol (LDL-c) over 3 years (n = 1402) and death/MI over 6 years (n = 2994), accounting for statin use or type during follow-up. RESULTS: Carriers of the rs4149056 C allele had 6.2 ± 1.7 mg/dl higher LDL-c per C allele (p < 0.001) but were not at higher risk for death/MI (p = 0.9). We found no associations between rs2306283 and LDL-c or death/MI (p > 0.6). CONCLUSION: Functional SLCO1B1 variants are not associated with death/MI in patients commonly treated with statins, despite higher LDL-c in carriers of the rs4149056 C allele.

Whole blood gene expression profiles distinguish clinical phenotypes of venous thromboembolism.

INTRODUCTION: Recurrent venous thromboembolism (VTE) occurs infrequently following a provoked event but occurs in up to 30% of individuals following an initial unprovoked event. There is limited understanding of the biological mechanisms that predispose patients to recurrent VTE. OBJECTIVES: To identify whole blood gene expression profiles that distinguished patients with clinically distinct patterns of VTE. PATIENTS/METHODS: We studied 107 patients with VTE separated into 3 groups: (1) 'low-risk' patients had one or more provoked VTE; (2) 'moderate-risk' patients had a single unprovoked VTE; (3) 'high-risk' patients had ≥2 unprovoked VTE. Each patient group was also compared to twenty-five individuals with no personal history of VTE. Total RNA from whole blood was isolated and hybridized to Illumina HT-12V4 Beadchips to assay whole genome expression. RESULTS: Using class prediction analysis, we distinguished high-risk patients from low-risk patients and healthy controls with good receiver operating curve characteristics (AUC=0.81 and 0.84, respectively). We also distinguished moderate-risk individuals and low-risk individuals from healthy controls with AUC's of 0.69 and 0.80, respectively. Using differential expression analysis, we identified several genes previously implicated in thrombotic disorders by genetic analyses, including SELP, KLKB1, ANXA5, and CD46. Protein levels for several of the identified genes were not significantly different between the different groups. CONCLUSION: Gene expression profiles are capable of distinguishing patients with different clinical presentations of VTE, and genes relevant to VTE risk are frequently differentially expressed in these comparisons.

A translatable predictor of human radiation exposure.

Terrorism using radiological dirty bombs or improvised nuclear devices is recognized as a major threat to both public health and national security. In the event of a radiological or nuclear disaster, rapid and accurate biodosimetry of thousands of potentially affected individuals will be essential for effective medical management to occur. Currently, health care providers lack an accurate, high-throughput biodosimetric assay which is suitable for the triage of large numbers of radiation injury victims. Here, we describe the development of a biodosimetric assay based on the analysis of irradiated mice, ex vivo-irradiated human peripheral blood (PB) and humans treated with total body irradiation (TBI). Interestingly, a gene expression profile developed via analysis of murine PB radiation response alone was inaccurate in predicting human radiation injury. In contrast, generation of a gene expression profile which incorporated data from ex vivo irradiated human PB and human TBI patients yielded an 18-gene radiation classifier which was highly accurate at predicting human radiation status and discriminating medically relevant radiation dose levels in human samples. Although the patient population was relatively small, the accuracy of this classifier in discriminating radiation dose levels in human TBI patients was not substantially confounded by gender, diagnosis or prior exposure to chemotherapy. We have further incorporated genes from this human radiation signature into a rapid and high-throughput chemical ligation-dependent probe amplification assay (CLPA) which was able to discriminate radiation dose levels in a pilot study of ex vivo irradiated human blood and samples from human TBI patients. Our results illustrate the potential for translation of a human genetic signature for the diagnosis of human radiation exposure and suggest the basis for further testing of CLPA as a candidate biodosimetric assay.

Biological pathway selection through Bayesian integrative modeling.

Pathway analysis has become a central approach to understanding the underlying biology of differentially expressed genes. As large amounts of microarray data have been accumulated in public repositories, flexible methodologies are needed to extend the analysis of simple case-control studies in order to place them in context with the vast quantities of available and highly heterogeneous data sets. To address this challenge, we have developed a two-level model, consisting of 1) a joint Bayesian factor model that integrates multiple microarray experiments and ties each factor to a predefined pathway and 2) a point mass mixture distribution that infers which factors are relevant/irrelevant to each dataset. Our method can identify pathways specific to a particular experimental trait which are concurrently induced/repressed under a variety of interventions. In this paper, we describe the model in depth and provide examples of its utility in simulations as well as real data from a study of radiation exposure. Our analysis of the radiation study leads to novel insights into the molecular basis of time- and dose- dependent response to ionizing radiation in mice peripheral blood. This broadly applicable model provides a starting point for generating specific and testable hypotheses in a pathway-centric manner.

27-Hydroxycholesterol links hypercholesterolemia and breast cancer pathophysiology.

Hypercholesterolemia is a risk factor for estrogen receptor (ER)-positive breast cancers and is associated with a decreased response of tumors to endocrine therapies. Here, we show that 27-hydroxycholesterol (27HC), a primary metabolite of cholesterol and an ER and liver X receptor (LXR) ligand, increases ER-dependent growth and LXR-dependent metastasis in mouse models of breast cancer. The effects of cholesterol on tumor pathology required its conversion to 27HC by the cytochrome P450 oxidase CYP27A1 and were attenuated by treatment with CYP27A1 inhibitors. In human breast cancer specimens, CYP27A1 expression levels correlated with tumor grade. In high-grade tumors, both tumor cells and tumor-associated macrophages exhibited high expression levels of the enzyme. Thus, lowering circulating cholesterol levels or interfering with its conversion to 27HC may be a useful strategy to prevent and/or treat breast cancer.

Gene by sex interaction for measures of obesity in the framingham heart study.

Obesity is an increasingly prevalent and severe health concern with a substantial heritable component and marked sex differences. We sought to determine if the effect of genetic variants also differed by sex by performing a genome-wide association study modeling the effect of genotype-by-sex interaction on obesity phenotypes. Genotype data from individuals in the Framingham Heart Study Offspring cohort were analyzed across five exams. Although no variants showed genome-wide significant gene-by-sex interaction in any individual exam, four polymorphisms displayed a consistent BMI association (P-values .00186 to .00010) across all five exams. These variants were clustered downstream of LYPLAL1, which encodes a lipase/esterase expressed in adipose tissue, a locus previously identified as having sex-specific effects on central obesity. Primary effects in males were in the opposite direction from females and were replicated in Framingham Generation 3. Our data support a sex-influenced association between genetic variation at the LYPLAL1 locus and obesity-related traits.

Genome-wide association study of Lp-PLA(2) activity and mass in the Framingham Heart Study.

Lipoprotein-associated phospholipase A(2) (Lp-PLA(2)) is an emerging risk factor and therapeutic target for cardiovascular disease. The activity and mass of this enzyme are heritable traits, but major genetic determinants have not been explored in a systematic, genome-wide fashion. We carried out a genome-wide association study of Lp-PLA(2) activity and mass in 6,668 Caucasian subjects from the population-based Framingham Heart Study. Clinical data and genotypes from the Affymetrix 550K SNP array were obtained from the open-access Framingham SHARe project. Each polymorphism that passed quality control was tested for associations with Lp-PLA(2) activity and mass using linear mixed models implemented in the R statistical package, accounting for familial correlations, and controlling for age, sex, smoking, lipid-lowering-medication use, and cohort. For Lp-PLA(2) activity, polymorphisms at four independent loci reached genome-wide significance, including the APOE/APOC1 region on chromosome 19 (p = 6 x 10(-24)); CELSR2/PSRC1 on chromosome 1 (p = 3 x 10(-15)); SCARB1 on chromosome 12 (p = 1x10(-8)) and ZNF259/BUD13 in the APOA5/APOA1 gene region on chromosome 11 (p = 4 x 10(-8)). All of these remained significant after accounting for associations with LDL cholesterol, HDL cholesterol, or triglycerides. For Lp-PLA(2) mass, 12 SNPs achieved genome-wide significance, all clustering in a region on chromosome 6p12.3 near the PLA2G7 gene. Our analyses demonstrate that genetic polymorphisms may contribute to inter-individual variation in Lp-PLA(2) activity and mass.