Flexible copula model for integrating correlated multi-omics data from single-cell experiments.

With recent advances in technologies to profile multi-omics data at the single-cell level, integrative multi-omics data analysis has been increasingly popular. It is increasingly common that information such as methylation changes, chromatin accessibility, and gene expression are jointly collected in a single-cell experiment. In biomedical studies, it is often of interest to study the associations between various data types and to examine how these associations might change according to other factors such as cell types and gene regulatory components. However, since each data type usually has a distinct marginal distribution, joint analysis of these changes of associations using multi-omics data is statistically challenging. In this paper, we propose a flexible copula-based framework to model covariate-dependent correlation structures independent of their marginals. In addition, the proposed approach could jointly combine a wide variety of univariate marginal distributions, either discrete or continuous, including the class of zero-inflated distributions. The performance of the proposed framework is demonstrated through a series of simulation studies. Finally, it is applied to a set of experimental data to investigate the dynamic relationship between single-cell RNA sequencing, chromatin accessibility, and DNA methylation at different germ layers during mouse gastrulation.

Genome-wide search algorithms for identifying dynamic gene co-expression via Bayesian variable selection.

A wealth of gene expression data generated by high-throughput techniques provides exciting opportunities for studying gene-gene interactions systematically. Gene-gene interactions in a biological system are tightly regulated and are often highly dynamic. The interactions can change flexibly under various internal cellular signals or external stimuli. Previous studies have developed statistical methods to examine these dynamic changes in gene-gene interactions. However, due to the massive number of possible gene combinations that need to be considered in a typical genomic dataset, intensive computation is a common challenge for exploring gene-gene interactions. On the other hand, oftentimes only a small proportion of gene combinations exhibit dynamic co-expression changes. To solve this problem, we propose Bayesian variable selection approaches based on spike-and-slab priors. The proposed algorithms reduce the computational intensity by focusing on identifying subsets of promising gene combinations in the search space. We also adopt a Bayesian multiple hypothesis testing procedure to identify strong dynamic gene co-expression changes. Simulation studies are performed to compare the proposed approaches with existing exhaustive search heuristics. We demonstrate the implementation of our proposed approach to study the association between gene co-expression patterns and overall survival using the RNA-sequencing dataset from The Cancer Genome Atlas breast cancer BRCA-US project.

Modeling dynamic correlation in zero-inflated bivariate count data with applications to single-cell RNA sequencing data.

Interactions between biological molecules in a cell are tightly coordinated and often highly dynamic. As a result of these varying signaling activities, changes in gene coexpression patterns could often be observed. The advancements in next-generation sequencing technologies bring new statistical challenges for studying these dynamic changes of gene coexpression. In recent years, methods have been developed to examine genomic information from individual cells. Single-cell RNA sequencing (scRNA-seq) data are count-based, and often exhibit characteristics such as overdispersion and zero inflation. To explore the dynamic dependence structure in scRNA-seq data and other zero-inflated count data, new approaches are needed. In this paper, we consider overdispersion and zero inflation in count outcomes and propose a ZEro-inflated negative binomial dynamic COrrelation model (ZENCO). The observed count data are modeled as a mixture of two components: success amplifications and dropout events in ZENCO. A latent variable is incorporated into ZENCO to model the covariate-dependent correlation structure. We conduct simulation studies to evaluate the performance of our proposed method and to compare it with existing approaches. We also illustrate the implementation of our proposed approach using scRNA-seq data from a study of minimal residual disease in melanoma.

The Arabidopsis transcription factor AINTEGUMENTA orchestrates patterning genes and auxin signaling in the establishment of floral growth and form.

Understanding how flowers form is an important problem in plant biology, as human food supply depends on flower and seed production. Flower development also provides an excellent model for understanding how cell division, expansion and differentiation are coordinated during organogenesis. In the model plant Arabidopsis thaliana, floral organogenesis requires AINTEGUMENTA (ANT) and AINTEGUMENTA-LIKE 6 (AIL6)/PLETHORA 3 (PLT3), two members of the Arabidopsis AINTEGUMENTA-LIKE/PLETHORA (AIL/PLT) transcription factor family. Together, ANT and AIL6/PLT3 regulate aspects of floral organogenesis, including floral organ initiation, growth, identity specification and patterning. Previously, we used RNA-Seq to identify thousands of genes with disrupted expression in ant ail6 mutant flowers, indicating that ANT and AIL6/PLT3 influence a vast transcriptional network. The immediate downstream targets of ANT and AIL6/PLT3 in flowers are unknown, however. To identify direct targets of ANT regulation, we performed an RNA-Seq time-course experiment in which we induced ANT activity in transgenic plants bearing an ANT-glucocorticoid receptor fusion construct. In addition, we performed a ChIP-Seq experiment that identified ANT binding sites in developing flowers. These experiments identified 200 potential ANT target genes based on their proximity to ANT binding sites and differential expression in response to ANT. These 200 candidate target genes were involved in functions such as polarity specification, floral organ development, meristem development and auxin signaling. In addition, we identified several genes associated with lateral organ growth that may mediate the role of ANT in organ size control. These results reveal new features of the ANT transcriptional network by linking ANT to previously unknown regulatory targets.

Coexposure to Inhaled Aldehydes or Carbon Dioxide Enhances the Carcinogenic Properties of the Tobacco-Specific Nitrosamine 4-Methylnitrosamino-1-(3-pyridyl)-1-butanone in the A/J Mouse Lung.

Tobacco smoke is a complex mixture of chemicals, many of which are toxic and carcinogenic. Hazard assessments of tobacco smoke exposure have predominantly focused on either single chemical exposures or the more complex mixtures of tobacco smoke or its fractions. There are fewer studies exploring interactions between specific tobacco smoke chemicals. Aldehydes such as formaldehyde and acetaldehyde were hypothesized to enhance the carcinogenic properties of the human carcinogen, 4-methylnitrosamino-1-(3-pyridyl)-1-butanone (NNK) through a variety of mechanisms. This hypothesis was tested in the established NNK-induced A/J mouse lung tumor model. A/J mice were exposed to NNK (intraperitoneal injection, 0, 2.5, or 7.5 µmol in saline) in the presence or absence of acetaldehyde (0 or 360 ppmv) or formaldehyde (0 or 17 ppmv) for 3 h in a nose-only inhalation chamber, and lung tumors were counted 16 weeks later. Neither aldehyde by itself induced lung tumors. However, mice receiving both NNK and acetaldehyde or formaldehyde had more adenomas with dysplasia or progression than those receiving only NNK, suggesting that aldehydes may increase the severity of NNK-induced lung adenomas. The aldehyde coexposure did not affect the levels of NNK-derived DNA adduct levels. Similar studies tested the ability of a 3 h nose-only carbon dioxide (0, 5, 10, or 15%) coexposure to influence lung adenoma formation by NNK. While carbon dioxide alone was not carcinogenic, it significantly increased the number of NNK-derived lung adenomas without affecting NNK-derived DNA damage. These studies indicate that the chemicals in tobacco smoke work together to form a potent lung carcinogenic mixture.

Bisphosphonate-Related Osteonecrosis of the Jaw.

OBJECTIVES: Antiresorptive agents for bone pain were widely used to treat patients with advanced osteoporosis, multiple myeloma, and bone metastatic cancer. In recent years, however, bisphosphonate-related osteonecrosis of the jaw (BRONJ) has been a rare but major complication of this therapy. Most patients with BRONJ undergo dental procedures during treatment with antiresorptive agents. However, BRONJ may also occur spontaneously. This study reports 13 BRONJ patient cases at Kaohsiung Veterans General Hospital, Taiwan, and their related treatments. We also compare patients with cancer with patients with osteoporosis in treatment outcomes. METHODS: Thirteen symptomatic patients with BRONJ were reviewed between 1985 and 2018 at Kaohsiung Veterans General Hospital. We included patients at advanced stage who were hospitalized for infection control of osteonecrosis of the jaw and excluded asymptomatic patients at stage 0 and stage 1. Four multiple myeloma, 3 patients with bone metastatic breast cancer and 6 patients with advanced osteoporosis (average ages, 63.57 ± 14.54 years in cancer patients and 79.5 ± 9.31 years in osteoporosis patients; average drug durations, 25.86 ± 27.23 months in cancer patients and 58.33 ± 23.87 months in osteoporosis patients; average follow-up times, 22.71 ± 14.46 months in cancer patients and 28.08 ± 36.35 months in osteoporosis patients) were included. RESULTS: Seven patients were defined as having stage 3 (53.8%) and 6 as having stage 2 (46.2%) medication-related osteonecrosis of the jaw, according to the American Association of Oral and Maxillofacial Surgeons classification. The complete response rate with totally healed mucosa was 61.5%. Four cancer patients received free fibular flap (FFF) reconstruction with a high complete response rate (100%). All of them had a relatively better performance status, and the average age was also younger than osteoporosis patients. CONCLUSION: Free fibular flap with a high complete response rate may improve pain relief and infection control for patients with BRONJ. Younger age is seemed to be a great indicator for FFF, but poor self-care ability (Eastern Cooperative Oncology Group status >3) is not suitable for these surgical treatments.

Haematogenous Klebsiella pneumoniae osteomyelitis.

OBJECTIVES: Klebsiella pneumoniae infection has been associated with alcoholic and diabetic patient populations, especially in Asian populations. K. pneumonia wound infection is common, but K. pneumonia without wound osteomyelitis (OM) is relatively rare. However, the pathogenesis of haematogenous K. pneumonia without open wound OM still unclear until now. In our research, we are trying to collect patients with haematogenous K. pneumonia osteomyelitis (K.p OM) at our hospital and to evaluate their contributing factors. METHODS: We compiled a retrospective database of haematogenous K. pneumonia osteomyelitis (K.p OM) from 1990 to 2019 at our hospital. Patients' bone cultures without K. pneumonia infection were excluded. Sixteen patients with haematogenous K.p OM were recruited. Patients' basic information, comorbidities, wound history, the biochemical examination of the blood, bacterial blood, bone, urine, and liver abscess cultures, the location of OM, corresponding treatments, and post operation K.p wound infection history were reviewed retrospectively. The collected data were analyzed using SPSS software. RESULTS: Unwounded haematogenous K.p OM had a statistically significant and positive correlation with liver insufficiency (P = .037; OR = 2.200), advanced age (≥ 65 years) (P = .037; OR = 2.200) and male gender (P = .03; OR = 1.833). DM, hypertension, steroid usage, GI or GU tract K.p infection, post operation K.p wound infection, hypoalbuminemia, and the location of K.p OM had no significant relationship to outcomes. CONCLUSION: Male patients of advanced age (> 65 years) and patients with liver insufficiency, including liver cirrhosis and hepatitis, have a strong correlation with unwounded haematogenous K.p OM.

Using sufficient direction factor model to analyze latent activities associated with breast cancer survival.

High-dimensional gene expression data often exhibit intricate correlation patterns as the result of coordinated genetic regulation. In practice, however, it is difficult to directly measure these coordinated underlying activities. Analysis of breast cancer survival data with gene expressions motivates us to use a two-stage latent factor approach to estimate these unobserved coordinated biological processes. Compared to existing approaches, our proposed procedure has several unique characteristics. In the first stage, an important distinction is that our procedure incorporates prior biological knowledge about gene-pathway membership into the analysis and explicitly model the effects of genetic pathways on the latent factors. Second, to characterize the molecular heterogeneity of breast cancer, our approach provides estimates specific to each cancer subtype. Finally, our proposed framework incorporates sparsity condition due to the fact that genetic networks are often sparse. In the second stage, we investigate the relationship between latent factor activity levels and survival time with censoring using a general dimension reduction model in the survival analysis context. Combining the factor model and sufficient direction model provides an efficient way of analyzing high-dimensional data and reveals some interesting relations in the breast cancer gene expression data.

Flexible bivariate correlated count data regression.

Multivariate count data are common in many disciplines. The variables in such data often exhibit complex positive or negative dependency structures. We propose three Bayesian approaches to modeling bivariate count data by simultaneously considering covariate-dependent means and correlation. A direct approach utilizes a bivariate negative binomial probability mass function developed in Famoye (2010, Journal of Applied Statistics). The second approach fits bivariate count data indirectly using a bivariate Poisson-gamma mixture model. The third approach is a bivariate Gaussian copula model. Based on the results from simulation analyses, the indirect and copula approaches perform better overall than the direct approach in terms of model fitting and identifying covariate-dependent association. The proposed approaches are applied to two RNA-sequencing data sets for studying breast cancer and melanoma (BRCA-US and SKCM-US), respectively, obtained through the International Cancer Genome Consortium.

Meta-analytic framework for modeling genetic coexpression dynamics.

Methods for exploring genetic interactions have been developed in an attempt to move beyond single gene analyses. Because biological molecules frequently participate in different processes under various cellular conditions, investigating the changes in gene coexpression patterns under various biological conditions could reveal important regulatory mechanisms. One of the methods for capturing gene coexpression dynamics, named liquid association (LA), quantifies the relationship where the coexpression between two genes is modulated by a third "coordinator" gene. This LA measure offers a natural framework for studying gene coexpression changes and has been applied increasingly to study regulatory networks among genes. With a wealth of publicly available gene expression data, there is a need to develop a meta-analytic framework for LA analysis. In this paper, we incorporated mixed effects when modeling correlation to account for between-studies heterogeneity. For statistical inference about LA, we developed a Markov chain Monte Carlo (MCMC) estimation procedure through a Bayesian hierarchical framework. We evaluated the proposed methods in a set of simulations and illustrated their use in two collections of experimental data sets. The first data set combined 10 pancreatic ductal adenocarcinoma gene expression studies to determine the role of possible coordinator gene USP9X in the Hippo pathway. The second experimental data set consisted of 907 gene expression microarray Escherichia coli experiments from multiple studies publicly available through the Many Microbe Microarray Database website (http://m3d.bu.edu/) and examined genes that coexpress with serA in the presence of coordinator gene Lrp.

Clinical Importance and Risk Factors for Postoperative Late-Onset Pneumonia After Major Oral Cancer Surgery With Microvascular Reconstruction.

BACKGROUND: Pulmonary complications are common among patients who have undergone major oral cancer surgery with microvascular reconstruction. Current literatures focused on early-onset pneumonia in the postoperative acute stage. In contrast, we are aiming to identify the clinical importance and the risk factors associated with late-onset pneumonia in oral cancer patients after acute stage. METHODS: In total, 195 patients were included from May 2014 to December 2016 and followed up for up to 1 year after surgery. Their medical histories were reviewed to identify the risk factors of late-onset pneumonia and outcome. Primary outcome was late-onset pneumonia. Other outcome measures included early-onset pneumonia, tumor recurrence, and death within 1 year after surgery. RESULTS: Patients with late-onset pneumonia have demonstrated a significantly higher rate of tumor recurrence (P < 0.001) and death within 1 year (P < 0.001). Independent risk factors of late-onset pneumonia identified were age (P = 0.031), previous radiotherapy (P = 0.017), postoperative radiotherapy (P = 0.002), flap size (P = 0.001), flap type other than osteocutaneous fibula flap (P = 0.009), and tumor recurrence (P < 0.001). CONCLUSIONS: Late-onset pneumonia can act as a warning sign for oral cancer patients who have received microsurgical reconstruction, for its high correlation with tumor recurrence and mortality rate.

Whole-Blood Transcriptional Signatures Composed of Erythropoietic and NRF2-Regulated Genes Differ Between Cerebral Malaria and Severe Malarial Anemia.

Background: Among the severe malaria syndromes, severe malarial anemia (SMA) is the most common, whereas cerebral malaria (CM) is the most lethal. However, the mechanisms that lead to CM and SMA are unclear. Methods: We compared transcriptomic profiles of whole blood obtained from Ugandan children with acute CM (n = 17) or SMA (n = 17) and community children without Plasmodium falciparum infection (n = 12) and determined the relationships among gene expression, hematological indices, and relevant plasma biomarkers. Results: Both CM and SMA demonstrated predominantly upregulated enrichment of dendritic cell activation, inflammatory/Toll-like receptor/chemokines, and monocyte modules, but downregulated enrichment of lymphocyte modules. Nuclear factor, erythroid 2 like 2 (Nrf2)-regulated genes were overexpressed in children with SMA relative to CM, with the highest expression in children with both SMA and sickle cell disease (HbSS), corresponding with elevated plasma heme oxygenase-1 in this group. Erythroid and reticulocyte-specific signatures were markedly decreased in CM relative to SMA despite higher hemoglobin levels and appropriate increases in erythropoietin. Viral sensing/interferon-regulatory factor 2 module expression and plasma interferon-inducible protein-10/CXCL10 negatively correlated with reticulocyte-specific signatures. Conclusions: Compared with SMA, CM is associated with downregulation of Nrf2-related and erythropoiesis signatures by whole-blood transcriptomics. Future studies are needed to confirm these findings and assess pathways that may be amenable to interventions to ameliorate CM and SMA.

Individual Differences in the Response of Human ß-Lymphoblastoid Cells to the Cytotoxic, Mutagenic, and DNA-Damaging Effects of a DNA Methylating Agent, N-Methylnitrosourethane.

Metabolic activation of many carcinogens leads to formation of reactive intermediates that form DNA adducts. These adducts are cytotoxic when they interfere with cell division. They can also cause mutations by miscoding during DNA replication. Therefore, an individual's risk of developing cancer will depend on the balance between these processes as well as their ability to repair the DNA damage. Our hypothesis is that variations of genes participating in DNA damage repair and response pathways play significant roles in an individual's risk of developing tobacco-related cancers. To test this hypothesis, 61 human B-lymphocyte cell lines from the International HapMap project were phenotyped for their sensitivity to the cytotoxic and genotoxic properties of a model methylating agent, N-nitroso-N-methylurethane (NMUr). Cell viability was measured using a luciferase-based assay. Repair of the mutagenic and toxic DNA adduct, O6-methylguanine (O6-mG), was monitored by LC-MS/MS analysis. Genotoxic potential of NMUr was assessed employing a flow-cytometry based in vitro mutagenesis assay in the phosphatidylinositol-glycan biosynthesis class-A (PIG-A) gene. A wide distribution of responses to NMUr was observed with no correlation to gender or ethnicity. While the rate of O6-mG repair partially influenced the toxicity of NMUr, it did not appear to be the major factor affecting individual susceptibility to the mutagenic effects of NMUr. Genome-wide analysis identified several novel single nucleotide polymorphisms to be explored in future functional validation studies for a number of the toxicological end points.

Meta-analytic framework for liquid association.

MOTIVATION: Although coexpression analysis via pair-wise expression correlation is popularly used to elucidate gene-gene interactions at the whole-genome scale, many complicated multi-gene regulations require more advanced detection methods. Liquid association (LA) is a powerful tool to detect the dynamic correlation of two gene variables depending on the expression level of a third variable (LA scouting gene). LA detection from single transcriptomic study, however, is often unstable and not generalizable due to cohort bias, biological variation and limited sample size. With the rapid development of microarray and NGS technology, LA analysis combining multiple gene expression studies can provide more accurate and stable results. RESULTS: In this article, we proposed two meta-analytic approaches for LA analysis (MetaLA and MetaMLA) to combine multiple transcriptomic studies. To compensate demanding computing, we also proposed a two-step fast screening algorithm for more efficient genome-wide screening: bootstrap filtering and sign filtering. We applied the methods to five Saccharomyces cerevisiae datasets related to environmental changes. The fast screening algorithm reduced 98% of running time. When compared with single study analysis, MetaLA and MetaMLA provided stronger detection signal and more consistent and stable results. The top triplets are highly enriched in fundamental biological processes related to environmental changes. Our method can help biologists understand underlying regulatory mechanisms under different environmental exposure or disease states. AVAILABILITY AND IMPLEMENTATION: A MetaLA R package, data and code for this article are available at http://tsenglab.biostat.pitt.edu/software.htm. CONTACT: ctseng@pitt.edu. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Daily and Nondaily Smoking Varies by Acculturation among English-Speaking, US Latino Men and Women.

Background: Higher smoking prevalence and quantity (cigarettes per day) has been linked to acculturation in the United States among Latinas, but not Latino men. Our study examines variation between a different and increasingly important target behavior, smoking level (nondaily vs daily) and acculturation by sex. Methods: An online English-language survey was administered to 786 Latino smokers during July through August 2012. The Brief Acculturation Rating Scale for Mexican Americans-II (ARSMA-II) and other acculturation markers were used. Multinomial logistic regression models were implemented to assess the association between smoking levels (nondaily, light daily, and moderate/heavy daily) with acculturation markers. Results: Greater ARMSA-II scores (relative risk ratio, RRR=.81, 95% CI: .72-.91) and being born inside the United States (RRR=.42, 95% CI: .24-.74) were associated with lower relative risk of nondaily smoking. Greater Latino orientation (RRR=1.29, 95% CI: 1.11-1.48) and preference for Spanish language (RRR=1.06, 95% CI: 1.02-1.10) and media (RRR=1.12, 95% CI: 1.05-1.20) were associated with higher relative risk of nondaily smoking. The relationship between acculturation and smoking level did not differ by sex. Conclusion: This study found that among both male and female, English-speaking Latino smokers, nondaily smoking was associated with lower acculturation, while daily smoking was linked with higher acculturation.

The Candidate Cancer Gene Database: a database of cancer driver genes from forward genetic screens in mice.

Identification of cancer driver gene mutations is crucial for advancing cancer therapeutics. Due to the overwhelming number of passenger mutations in the human tumor genome, it is difficult to pinpoint causative driver genes. Using transposon mutagenesis in mice many laboratories have conducted forward genetic screens and identified thousands of candidate driver genes that are highly relevant to human cancer. Unfortunately, this information is difficult to access and utilize because it is scattered across multiple publications using different mouse genome builds and strength metrics. To improve access to these findings and facilitate meta-analyses, we developed the Candidate Cancer Gene Database (CCGD, http://ccgd-starrlab.oit.umn.edu/). The CCGD is a manually curated database containing a unified description of all identified candidate driver genes and the genomic location of transposon common insertion sites (CISs) from all currently published transposon-based screens. To demonstrate relevance to human cancer, we performed a modified gene set enrichment analysis using KEGG pathways and show that human cancer pathways are highly enriched in the database. We also used hierarchical clustering to identify pathways enriched in blood cancers compared to solid cancers. The CCGD is a novel resource available to scientists interested in the identification of genetic drivers of cancer.

Contributing Factors for Complications and Outcomes in Patients With Snakebite: Experience in a Medical Center in Southern Taiwan.

OBJECTIVES: Snakebite usually results in various complications, such as significant soft tissue damage, infection, hematological, and neurological deficit. Surgical intervention, usually, is indicated in patients with tissue necrosis, infection, and compartment syndrome. To identify the contributing factors for complications and outcomes in different patients with snakebite so that outcomes can be evaluated and treatment of such patients can be initiated at the earliest. METHODS: Information was collected regarding age, sex, underlying disease, species of snake, and the course of treatment of the victims of snakebite who visited the emergency department of a medical center in southern Taiwan between 2004 and 2014. The data obtained were analyzed using SPSS 20.0. RESULTS: The bites from Taiwan cobra (Naja naja atra) significantly resulted in more complications than those from other snakes and required surgical intervention. The use of antivenin and antibiotics, immediate presentation to the hospital, and the location of the bite also were significant contributing factors. CONCLUSIONS: Taiwan cobra significantly results in higher possibility of prolonged hospitalization, operation, tissue necrosis, infection, and necrotizing fasciitis. Location of the bite, immediate presentation to the hospital, and use of antivenin and antibiotics affect the outcome of snakebite. Knowledge of these factors will help in a better management of patients with snakebite.

Clinical practice guidelines on prostate cancer: a critical appraisal.

PURPOSE: Clinical practice guidelines are increasingly being used by leading organizations to promote high quality evidence-based patient care. However, the methodological quality of clinical practice guidelines developed by different organizations varies considerably. We assessed published clinical practice guidelines on the treatment of localized prostate cancer to evaluate the rigor, applicability and transparency of their recommendations. MATERIALS AND METHODS: We searched for English based clinical practice guidelines on treatment of localized prostate cancer from leading organizations in the 15-year period from 1999 to 2014. Clinical practice guidelines limited to early detection, screening, staging and/or diagnosis of prostate cancer were excluded from analysis. Four independent reviewers used the validated AGREE II instrument to assess the quality of clinical practice guidelines in 6 domains, including 1) scope and purpose, 2) stakeholder involvement, 3) rigor of development, 4) clarity of presentation, 5) applicability and 6) editorial independence. RESULTS: A total of 13 clinical practice guidelines met inclusion criteria. Overall the highest median scores were in the AGREE II domains of clarity of presentation, editorial independence, and scope and purpose. The lowest median score was for applicability (28.1%). Although the median score of editorial independence was high (85.4%), variability was also substantial (IQR 12.5-100). NICE and AUA clinical practice guidelines consistently scored well in most domains. CONCLUSIONS: Clinical practice guidelines from different organizations on treatment of localized prostate cancer are of variable quality and fall short of current standards in certain areas, especially in applicability and stakeholder involvement. Improvements in these key domains can enhance the impact and implementation of clinical practice guidelines.

Using gene expression to improve the power of genome-wide association analysis.

BACKGROUND/AIMS: Genome-wide association (GWA) studies have reported susceptible regions in the human genome for many common diseases and traits; however, these loci only explain a minority of trait heritability. To boost the power of a GWA study, substantial research endeavors have been focused on integrating other available genomic information in the analysis. Advances in high through-put technologies have generated a wealth of genomic data and made combining SNP and gene expression data become feasible. RESULTS: In this paper, we propose a novel procedure to incorporate gene expression information into GWA analysis. This procedure utilizes weights constructed by gene expression measurements to adjust p values from a GWA analysis. RESULTS from simulation analyses indicate that the proposed procedures may achieve substantial power gains, while controlling family-wise type I error rates at the nominal level. To demonstrate the implementation of our proposed approach, we apply the weight adjustment procedure to a GWA study on serum interferon-regulated chemokine levels in systemic lupus erythematosus patients. The study results can provide valuable insights for the functional interpretation of GWA signals. AVAILABILITY: The R source code for implementing the proposed weighting procedure is available at http://www.biostat.umn.edu/∼yho/research.html.

High risk of rhabdomyolysis and acute kidney injury after traumatic limb compartment syndrome.

PURPOSE: Rhabdomyolysis often occurs after traumatic compartment syndrome, and high morbidity and mortality have been reported with the acute kidney injury that develops subsequently. We focused on the risk factors for rhabdomyolysis and acute kidney injury in patients with traumatic compartment syndrome. We also analyzed the relation between renal function and rhabdomyolysis in these patients. MATERIALS AND METHODS: A retrospective chart review was conducted from January 2006 to March 2012. Inpatients with traumatic compartment syndrome were included. We evaluated patients' demographics, history of illicit drugs use or alcohol consumption, mechanism of injury, symptoms, serum creatine kinase levels, and kidney function. RESULTS: A total of 52 patients with a mean age of 40.9 years were included; 23 patients had rhabdomyolysis (44.2%), of which 9 patients developed acute kidney injury (39.1%). Significant predictive factors for rhabdomyolysis were history of illicit drugs or alcohol use (P=0.039; odds ratio, 5.91) and ischemic injury (P=0.005). We found a moderate correlation between serum creatine kinase levels and serum creatinine levels (R=0.57; P<0.0001). The correlation coefficient (R) between serum creatine kinase levels and the estimated creatinine clearance rate was -0.45. Rhabdomyolysis was a predisposing factor for acute kidney injury (P=0.011; odds ratio, 8.68). Four patients with rhabdomyolysis required a short period of renal replacement therapy. CONCLUSION: A high percentage of patients with traumatic compartment syndrome developed rhabdomyolysis (44.2%). Patients with rhabdomyolysis had a higher possibility of developing acute kidney injury (39.1%), and rhabdomyolysis was correlated to renal function. Early diagnosis, frequent monitoring, and aggressive treatment are suggested once compartment syndrome is suspected. The overall prognosis is good with early diagnosis and proper treatment.