Longitudinal Pilot Evaluation of the Gut Microbiota Comparing Patients With and Without Chronic Kidney Disease.

OBJECTIVE: The gut microbiota contributes to metabolic diseases, such as diabetes and hypertension, but is poorly characterized in chronic kidney disease (CKD). DESIGN AND METHODS: We enrolled 24 adults within household pairs, in which at least one member had self-reported kidney disease, diabetes, or hypertension. CKD was classified based on estimated glomerular filtration rate < 60 mL/min/1.73 m2 or urine-albumin-to-creatinine ratio of ≥ 30 mg/g. Participants collected stool and dietary recalls seasonally over a year. Gut microbiota was characterized using 16s rRNA and metagenomic sequencing. RESULTS: Ten participants had CKD (42%) with a median (interquartile range) estimated glomerular filtration rate of 49 (44, 54) mL/min/1.73 m2. By 16s rRNA sequencing, there was moderate to high intraclass correlation (ICC = 0.63) for seasonal alpha diversity (Shannon index) within individuals and modest differences by season (P < .01). ICC was lower with metagenomics, which has resolution at the species level (ICC = 0.26). There were no differences in alpha or beta diversity by CKD with either method. Among 79 genera, Frisingicoccus, Tuzzerella, Faecalitalea, and Lachnoclostridium had lower abundance in CKD, while Collinsella, Lachnospiraceae_ND3007, Veillonella, and Erysipelotrichaceae_UCG_003 were more abundant in CKD (each nominal P < .05) using 16s rRNA sequencing. Higher Collinsella and Veillonella and lower Lachnoclostridium in CKD were also identified by metagenomics. By metagenomics, Coprococcus catus and Bacteroides stercoris were more and less abundant in CKD, respectively, at false discovery rate corrected P = .02. CONCLUSIONS: We identified candidate taxa in the gut microbiota associated with CKD. High ICC in individuals with modest seasonal impacts implies that follow-up studies may use less frequent sampling.

Diversity of plant DNA in stool is linked to dietary quality, age, and household income.

Eating a varied diet is a central tenet of good nutrition. Here, we develop a molecular tool to quantify human dietary plant diversity by applying DNA metabarcoding with the chloroplast trnL-P6 marker to 1,029 fecal samples from 324 participants across two interventional feeding studies and three observational cohorts. The number of plant taxa per sample (plant metabarcoding richness or pMR) correlated with recorded intakes in interventional diets and with indices calculated from a food frequency questionnaire in typical diets (ρ = 0.40 to 0.63). In adolescents unable to collect validated dietary survey data, trnL metabarcoding detected 111 plant taxa, with 86 consumed by more than one individual and four (wheat, chocolate, corn, and potato family) consumed by >70% of individuals. Adolescent pMR was associated with age and household income, replicating prior epidemiologic findings. Overall, trnL metabarcoding promises an objective and accurate measure of the number and types of plants consumed that is applicable to diverse human populations.

A Multidimensional Bioinformatic Platform for the Study of Human Response to Surgery.

OBJECTIVE: To design and establish a prospective biospecimen repository that integrates multi-omics assays with clinical data to study mechanisms of controlled injury and healing. BACKGROUND: Elective surgery is an opportunity to understand both the systemic and focal responses accompanying controlled and well-characterized injury to the human body. The overarching goal of this ongoing project is to define stereotypical responses to surgical injury, with the translational purpose of identifying targetable pathways involved in healing and resilience, and variations indicative of aberrant peri-operative outcomes. METHODS: Clinical data from the electronic medical record combined with large-scale biological data sets derived from blood, urine, fecal matter, and tissue samples are collected prospectively through the peri-operative period on patients undergoing 14 surgeries chosen to represent a range of injury locations and intensities. Specimens are subjected to genomic, transcriptomic, proteomic, and metabolomic assays to describe their genetic, metabolic, immunologic, and microbiome profiles, providing a multidimensional landscape of the human response to injury. RESULTS: The highly multiplexed data generated includes changes in over 28,000 mRNA transcripts, 100 plasma metabolites, 200 urine metabolites, and 400 proteins over the longitudinal course of surgery and recovery. In our initial pilot dataset, we demonstrate the feasibility of collecting high quality multi-omic data at pre- and postoperative time points and are already seeing evidence of physiologic perturbation between timepoints. CONCLUSIONS: This repository allows for longitudinal, state-of-the-art geno-mic, transcriptomic, proteomic, metabolomic, immunologic, and clinical data collection and provides a rich and stable infrastructure on which to fuel further biomedical discovery.

The Pediatric Obesity Microbiome and Metabolism Study (POMMS): Methods, Baseline Data, and Early Insights.

OBJECTIVE: The purpose of this study was to establish a biorepository of clinical, metabolomic, and microbiome samples from adolescents with obesity as they undergo lifestyle modification. METHODS: A total of 223 adolescents aged 10 to 18 years with BMI ≥95th percentile were enrolled, along with 71 healthy weight participants. Clinical data, fasting serum, and fecal samples were collected at repeated intervals over 6 months. Herein, the study design, data collection methods, and interim analysis-including targeted serum metabolite measurements and fecal 16S ribosomal RNA gene amplicon sequencing among adolescents with obesity (n = 27) and healthy weight controls (n = 27)-are presented. RESULTS: Adolescents with obesity have higher serum alanine aminotransferase, C-reactive protein, and glycated hemoglobin, and they have lower high-density lipoprotein cholesterol when compared with healthy weight controls. Metabolomics revealed differences in branched-chain amino acid-related metabolites. Also observed was a differential abundance of specific microbial taxa and lower species diversity among adolescents with obesity when compared with the healthy weight group. CONCLUSIONS: The Pediatric Metabolism and Microbiome Study (POMMS) biorepository is available as a shared resource. Early findings suggest evidence of a metabolic signature of obesity unique to adolescents, along with confirmation of previously reported findings that describe metabolic and microbiome markers of obesity.

RNA splicing and aggregate gene expression differences in lung squamous cell carcinoma between patients of West African and European ancestry.

OBJECTIVES: Despite disparities in lung cancer incidence and mortality, the molecular landscape of lung cancer in patients of African ancestry remains underexplored, and race-related differences in RNA splicing remain unexplored. MATERIALS AND METHODS: We identified differentially spliced genes (DSGs) and differentially expressed genes (DEGs) in biobanked lung squamous cell carcinoma (LUSC) between patients of West African and European ancestry, using ancestral genotyping and Affymetrix Clariom D array. DSGs and DEGs were validated independently using the National Cancer Institute Genomic Data Commons. Associated biological processes, overlapping canonical pathways, enriched gene sets, and cancer relevance were identified using Gene Ontology Consortium, Ingenuity Pathway Analysis, Gene Set Enrichment Analysis, and CancerMine, respectively. Association with LUSC survival was conducted using The Cancer Genome Atlas. RESULTS: 4,829 DSGs and 267 DEGs were identified, including novel targets in NSCLC as well as genes identified previously to have relevance to NSCLC. RNA splicing events within 3 DSGs as well as 1 DEG were validated in the independent cohort. 853 DSGs and 29 DEGs have been implicated as potential drivers, oncogenes and/or tumor suppressor genes. Biological processes enriched among DSGs and DEGs included metabolic process, biological regulation, and multicellular organismal process and, among DSGs, ion transport. Overlapping canonical pathways among DSGs included neuronal signaling pathways and, among DEGs, cell metabolism involving biosynthesis. Gene sets enriched among DSGs included KRAS Signaling, UV Response, E2 F Targets, Glycolysis, and Coagulation. 355 RNA splicing events within DSGs and 18 DEGs show potential association with LUSC patient survival. CONCLUSION: These DSGs and DEGs, which show potential biological and clinical relevance, could have the ability to drive novel biomarker and therapeutic development to mitigate LUSC disparities.

The cancer microbiome atlas: a pan-cancer comparative analysis to distinguish tissue-resident microbiota from contaminants.

Studying the microbial composition of internal organs and their associations with disease remains challenging due to the difficulty of acquiring clinical biopsies. We designed a statistical model to analyze the prevalence of species across sample types from The Cancer Genome Atlas (TCGA), revealing that species equiprevalent across sample types are predominantly contaminants, bearing unique signatures from each TCGA-designated sequencing center. Removing such species mitigated batch effects and isolated the tissue-resident microbiome, which was validated by original matched TCGA samples. Gene copies and nucleotide variants can further distinguish mixed-evidence species. We, thus, present The Cancer Microbiome Atlas (TCMA), a collection of curated, decontaminated microbial compositions of oropharyngeal, esophageal, gastrointestinal, and colorectal tissues. This led to the discovery of prognostic species and blood signatures of mucosal barrier injuries and enabled systematic matched microbe-host multi-omic analyses, which will help guide future studies of the microbiome's role in human health and disease.

Short-Chain Fatty Acid Production by Gut Microbiota from Children with Obesity Differs According to Prebiotic Choice and Bacterial Community Composition.

Pediatric obesity remains a public health burden and continues to increase in prevalence. The gut microbiota plays a causal role in obesity and is a promising therapeutic target. Specifically, the microbial production of short-chain fatty acids (SCFA) from the fermentation of otherwise indigestible dietary carbohydrates may protect against pediatric obesity and metabolic syndrome. Still, it has not been demonstrated that therapies involving microbiota-targeting carbohydrates, known as prebiotics, will enhance gut bacterial SCFA production in children and adolescents with obesity (age, 10 to 18 years old). Here, we used an in vitro system to examine the SCFA production by fecal microbiota from 17 children with obesity when exposed to five different commercially available over-the-counter (OTC) prebiotic supplements. We found microbiota from all 17 patients actively metabolized most prebiotics. Still, supplements varied in their acidogenic potential. Significant interdonor variation also existed in SCFA production, which 16S rRNA sequencing supported as being associated with differences in the host microbiota composition. Last, we found that neither fecal SCFA concentration, microbiota SCFA production capacity, nor markers of obesity positively correlated with one another. Together, these in vitro findings suggest the hypothesis that OTC prebiotic supplements may be unequal in their ability to stimulate SCFA production in children and adolescents with obesity and that the most acidogenic prebiotic may differ across individuals.IMPORTANCE Pediatric obesity remains a major public health problem in the United States, where 17% of children and adolescents are obese, and rates of pediatric "severe obesity" are increasing. Children and adolescents with obesity face higher health risks, and noninvasive therapies for pediatric obesity often have limited success. The human gut microbiome has been implicated in adult obesity, and microbiota-directed therapies can aid weight loss in adults with obesity. However, less is known about the microbiome in pediatric obesity, and microbiota-directed therapies are understudied in children and adolescents. Our research has two important findings: (i) dietary prebiotics (fiber) result in the microbiota from adolescents with obesity producing more SCFA, and (ii) the effectiveness of each prebiotic is donor dependent. Together, these findings suggest that prebiotic supplements could help children and adolescents with obesity, but that these therapies may not be "one size fits all."

Rationale and design of "Hearts & Parks": study protocol for a pragmatic randomized clinical trial of an integrated clinic-community intervention to treat pediatric obesity.

BACKGROUND: The prevalence of child and adolescent obesity and severe obesity continues to increase despite decades of policy and research aimed at prevention. Obesity strongly predicts cardiovascular and metabolic disease risk; both begin in childhood. Children who receive intensive behavioral interventions can reduce body mass index (BMI) and reverse disease risk. However, delivering these interventions with fidelity at scale remains a challenge. Clinic-community partnerships offer a promising strategy to provide high-quality clinical care and deliver behavioral treatment in local park and recreation settings. The Hearts & Parks study has three broad objectives: (1) evaluate the effectiveness of the clinic-community model for the treatment of child obesity, (2) define microbiome and metabolomic signatures of obesity and response to lifestyle change, and (3) inform the implementation of similar models in clinical systems. METHODS: Methods are designed for a pragmatic randomized, controlled clinical trial (n = 270) to test the effectiveness of an integrated clinic-community child obesity intervention as compared with usual care. We are powered to detect a difference in body mass index (BMI) between groups at 6 months, with follow up to 12 months. Secondary outcomes include changes in biomarkers for cardiovascular disease, psychosocial risk, and quality of life. Through collection of biospecimens (serum and stool), additional exploratory outcomes include microbiome and metabolomics biomarkers of response to lifestyle modification. DISCUSSION: We present the study design, enrollment strategy, and intervention details for a randomized clinical trial to measure the effectiveness of a clinic-community child obesity treatment intervention. This study will inform a critical area in child obesity and cardiovascular risk research-defining outcomes, implementation feasibility, and identifying potential molecular mechanisms of treatment response. CLINICAL TRIAL REGISTRATION: NCT03339440 .

Bridging the gaps: using an NHP model to predict single dose radiation absorption in humans.

Purpose: Design and characterization of a radiation biodosimetry device are complicated by the fact that the requisite data are not available in the intended use population, namely humans exposed to a single, whole-body radiation dose. Instead, one must turn to model systems. We discuss our studies utilizing healthy, unexposed humans, human bone marrow transplant patients undergoing total body irradiation (TBI), non-human primates subjected to the same irradiation regimen received by the human TBI patients and NHPs given a single, whole-body dose of ionizing radiation.Materials and Methods: We use Bayesian linear mixed models to characterize the association between NHP and human expression patterns in radiation response genes when exposed to a common exposure regimen and across exposure regimens within the same species.Results: We show that population average differences in expression of our radiation response genes from one to another model system are comparable to typical differences between two randomly sampled members of a given model system and that these differences are smaller, on average, for linear combinations of the probe data and for the model-based combinations employed for dose prediction as part of a radiation biodosimetry device.Conclusions: Our analysis suggests that dose estimates based on our gene list will be accurate when applied to humans who have received a single, whole-body exposure to ionizing radiation.

Orphan Adhesion GPCR GPR64/ADGRG2 Is Overexpressed in Parathyroid Tumors and Attenuates Calcium-Sensing Receptor-Mediated Signaling.

Abnormal feedback of serum calcium to parathyroid hormone (PTH) secretion is the hallmark of primary hyperparathyroidism (PHPT). Although the molecular pathogenesis of parathyroid neoplasia in PHPT has been linked to abnormal expression of genes involved in cell growth (e.g., cyclin D1, retinoblastoma, and ß-catenin), the molecular basis of abnormal calcium sensing by calcium-sensing receptor (CaSR) and PTH hypersecretion in PHPT are incompletely understood. Through gene expression profiling, we discovered that an orphan adhesion G protein-coupled receptor (GPCR), GPR64/ADGRG2, is expressed in human normal parathyroid glands and is overexpressed in parathyroid tumors from patients with PHPT. Using immunohistochemistry, Western blotting, and coimmunoprecipitation, we found that GPR64 is expressed on the cell surface of parathyroid cells, is overexpressed in parathyroid tumors, and physically interacts with the CaSR. By using reporter gene assay and GPCR second messenger readouts we identified Gαs, 3',5'-cyclic adenosine monophosphate (cAMP), protein kinase A, and cAMP response element binding protein (CREB) as the signaling cascade downstream of GPR64. Furthermore, we found that an N-terminally truncated human GPR64 is constitutively active and a 15-amino acid-long peptide C-terminal to the GPCR proteolysis site (GPS) of GPR64 activates this receptor. Functional characterization of GPR64 demonstrated its ability to increase PTH release from human parathyroid cells at a range of calcium concentrations. We discovered that the truncated constitutively active, but not the full-length GPR64 physically interacts with CaSR and attenuates the CaSR-mediated intracellular Ca2+ signaling and cAMP suppression in HEK293 cells. Our results indicate that GPR64 may be a physiologic regulator of PTH release that is dysregulated in parathyroid tumors, and suggest a role for GPR64 in pathologic calcium sensing in PHPT. © 2016 American Society for Bone and Mineral Research.

A Molecular Profile of the Endothelial Cell Response to Ionizing Radiation.

Ionizing radiation exposure can cause acute radiation sickness (ARS) by damaging the hematopoietic compartment. Radiation damages quiescent hematopoietic stem cells (HSCs) and proliferating hematopoietic cells, resulting in neutropenia, thrombocytopenia and increased risk for long-term hematopoietic dysfunction and myelodysplasia. While some aspects of the hematopoietic response to radiation injury are intrinsic to hematopoietic cells, the recovery of the HSC pool and overall hematopoiesis is also dependent on signals from bone marrow endothelial cells (BM ECs) within the HSC vascular niche. The precise mechanisms through which BM ECs regulate HSC regeneration remain unclear. Characterization of the altered EC gene expression that occurs in response to radiation could provide a roadmap to the discovery of EC-derived mechanisms that regulate hematopoietic regeneration. Here, we show that 5 Gy total-body irradiation substantially alters the expression of numerous genes in BM ECs within 24 h and this molecular response largely resolves by day 14 postirradiation. Several unique and nonannotated genes, which encode secreted proteins were upregulated and downregulated in ECs in response to radiation. These results highlight the complexity of the molecular response of BM ECs to ionizing radiation and identify several candidate mechanisms that should be prioritized for functional analysis in models of hematopoietic injury and regeneration.

Genomic profiling in locally advanced and inflammatory breast cancer and its link to DCE-MRI and overall survival.

PURPOSE: We have previously reported that dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) perfusion patterns obtained from locally advanced breast cancer (LABC) patients prior to neoadjuvant therapy predicted pathologic clinical response. Genomic analyses were also independently conducted on the same patient population. This retrospective study was performed to test two hypotheses: (1) gene expression profiles are associated with DCE-MRI perfusion patterns, and (2) association between long-term overall survival data and gene expression profiles can lead to the identification of novel predictive biomarkers. METHODS: We utilised RNA microarray and DCE-MRI data from 47 LABC patients, including 13 inflammatory breast cancer (IBC) patients. Association between gene expression profile and DCE-MRI perfusion patterns (centrifugal and centripetal) was determined by Wilcoxon rank sum test. Association between gene expression level and survival was assessed using a Cox rank score test. Additional genomic analysis of the IBC subset was conducted, with a period of follow-up of up to 11 years. Associations between gene expression and overall survival were further assessed in The Cancer Genome Atlas Data Portal. RESULTS: Differences in gene expression profiles were seen between centrifugal and centripetal perfusion patterns in the sulphotransferase family, cytosolic, 1 A, phenol-preferring, members 1 and 2 (SULT1A1, SULT1A2), poly (ADP-ribose) polymerase, member 6 (PARP6), and metastasis tumour antigen1 (MTA1). In the IBC subset our analyses demonstrated that differential expression of 45 genes was associated with long-term survival. CONCLUSIONS: Here we have demonstrated an association between DCE-MRI perfusion patterns and gene expression profiles. In addition we have reported on candidate prognostic biomarkers in IBC patients, with some of the genes being significantly associated with survival in IBC and LABC.

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.

A methodology for utilization of predictive genomic signatures in FFPE samples.

BACKGROUND: Gene expression signatures developed to measure the activity of oncogenic signaling pathways have been used to dissect the heterogeneity of tumor samples and to predict sensitivity to various cancer drugs that target components of the relevant pathways, thus potentially identifying therapeutic options for subgroups of patients. To facilitate broad use, including in a clinical setting, the ability to generate data from formalin-fixed, paraffin-embedded (FFPE) tissues is essential. METHODS: Patterns of pathway activity in matched fresh-frozen and FFPE xenograft tumor samples were generated using the MessageAmp Premier methodology in combination with assays using Affymetrix arrays. Results generated were compared with those obtained from fresh-frozen samples using a standard Affymetrix assay. In addition, gene expression data from patient matched fresh-frozen and FFPE melanomas were also utilized to evaluate the consistency of predictions of oncogenic signaling pathway status. RESULTS: Significant correlation was observed between pathway activity predictions from paired fresh-frozen and FFPE xenograft tumor samples. In addition, significant concordance of pathway activity predictions was also observed between patient matched fresh-frozen and FFPE melanomas. CONCLUSIONS: Reliable and consistent predictions of oncogenic pathway activities can be obtained from FFPE tumor tissue samples. The ability to reliably utilize FFPE patient tumor tissue samples for genomic analyses will lead to a better understanding of the biology of disease progression and, in the clinical setting, will provide tools to guide the choice of therapeutics to those most likely to be effective in treating a patient's disease.

Retraction: A genomic strategy to refine prognosis in early-stage non-small-cell lung cancer. N Engl J Med 2006;355:570-80.

To the Editor: We would like to retract our article, "A Genomic Strategy to Refine Prognosis in Early-Stage Non-Small-Cell Lung Cancer,"(1) which was published in the Journal on August 10, 2006. Using a sample set from a study by the American College of Surgeons Oncology Group (ACOSOG) and a collection of samples from a study by the Cancer and Leukemia Group B (CALGB), we have tried and failed to reproduce results supporting the validation of the lung metagene model described in the article. We deeply regret the effect of this action on the work of other investigators.

Regulator of G protein signaling 5 is highly expressed in parathyroid tumors and inhibits signaling by the calcium-sensing receptor.

The molecular mechanisms responsible for aberrant calcium signaling in parathyroid disease are poorly understood. The loss of appropriate calcium-responsive modulation of PTH secretion observed in parathyroid disease is commonly attributed to decreased expression of the calcium-sensing receptor (CaSR), a G protein-coupled receptor. However, CaSR expression is highly variable in parathyroid adenomas, and the lack of correlation between CaSR abundance and calcium-responsive PTH kinetics indicates that mechanisms independent of CaSR expression may contribute to aberrant calcium sensing in parathyroid disease. To gain a better understanding of parathyroid tumors and the molecular determinants that drive parathyroid adenoma development, we performed gene expression profiling on a panel of 64 normal and neoplastic parathyroid tissues. The microarray data revealed high-level expression of genes known to be involved in parathyroid biology (PTH, VDR, CGA, CaSR, and GCM2). Moreover, our screen identified regulator of G protein signaling 5 (RGS5) as a candidate inhibitor of CaSR signaling. We confirmed RGS5 to be highly expressed in parathyroid adenomas relative to matched-pair normal glands. Transient expression of RGS5 in cells stably expressing CaSR resulted in dose-dependent abrogation of calcium-stimulated inositol trisphosphate production and ERK1/2 phosphorylation. Furthermore, we found that RGS5-nullizygous mice display reduced plasma PTH levels, an outcome consistent with attenuated opposition to CaSR activity. Collectively, these data suggest that RGS5 can act as a physiological regulator of calcium sensing by CaSR in the parathyroid gland. The abnormally elevated expression of RGS5 observed in parathyroid adenomas could thus represent a novel mechanism of CaSR desensitization in patients with primary hyperparathyroidism.

Diagnosis of partial body radiation exposure in mice using peripheral blood gene expression profiles.

In the event of a terrorist-mediated attack in the United States using radiological or improvised nuclear weapons, it is expected that hundreds of thousands of people could be exposed to life-threatening levels of ionizing radiation. We have recently shown that genome-wide expression analysis of the peripheral blood (PB) can generate gene expression profiles that can predict radiation exposure and distinguish the dose level of exposure following total body irradiation (TBI). However, in the event a radiation-mass casualty scenario, many victims will have heterogeneous exposure due to partial shielding and it is unknown whether PB gene expression profiles would be useful in predicting the status of partially irradiated individuals. Here, we identified gene expression profiles in the PB that were characteristic of anterior hemibody-, posterior hemibody- and single limb-irradiation at 0.5 Gy, 2 Gy and 10 Gy in C57Bl6 mice. These PB signatures predicted the radiation status of partially irradiated mice with a high level of accuracy (range 79-100%) compared to non-irradiated mice. Interestingly, PB signatures of partial body irradiation were poorly predictive of radiation status by site of injury (range 16-43%), suggesting that the PB molecular response to partial body irradiation was anatomic site specific. Importantly, PB gene signatures generated from TBI-treated mice failed completely to predict the radiation status of partially irradiated animals or non-irradiated controls. These data demonstrate that partial body irradiation, even to a single limb, generates a characteristic PB signature of radiation injury and thus may necessitate the use of multiple signatures, both partial body and total body, to accurately assess the status of an individual exposed to radiation.