The impact of hyperkalemia on ICU admission and mortality: a retrospective study of Chinese emergency department data.

OBJECTIVE: This study assesses the influence of hyperkalemia on both disease severity and the risk of mortality among patients admitted to the emergency room. METHODS: This retrospective observational study utilized data from the Chinese Emergency Triage Assessment and Treatment database (CETAT, version 2.0), which was designed to evaluate and optimize management strategies for emergency room (ER) patients. Patients were systematically categorized based on serum potassium levels. Relationships between serum potassium levels, risk of mortality, and the severity of illness were then analyzed using multifactorial logistic regression and through Receiver Operating Characteristic (ROC) analysis. The effectiveness of various treatments at lowering potassium levels was also investigated. RESULTS: 12,799 emergency patients were enrolled, of whom 20.1% (n = 2,577) were hypokalemic and 2.98% (n = 381) were hyperkalemic. Among hyperkalemic patients, the leading reasons for visiting the ER were altered consciousness 23.88% (n = 91), cardiovascular symptoms 22.31% (n = 85), and gastrointestinal symptoms 20.47% (n = 78). Comparative analysis with patients exhibiting normal potassium levels revealed hyperkalemia as an independent factor associated with mortality in the ER. Mortality risk appears to positively correlate with increasing potassium levels, reaching peaks when blood potassium levels ranged between 6.5 and 7.0. Hyperkalemia emerged as a strong predictor of death in the ER, with an Area Under the Curve (AUC) of 0.89. The most frequently prescribed treatment for hyperkalemia patients was diuretics (57.32%, n = 188), followed by intravenous sodium bicarbonate (50.91%, n = 167), IV calcium (37.2%, n = 122), insulin combined with high glucose (27.74%, n = 91), and Continuous Renal Replacement Therapy (CRRT) for 19.82% (n = 65). Among these, CRRT appeared to be the most efficacious at reducing potassium levels. Diuretics appeared relatively ineffective, while high-glucose insulin, sodium bicarbonate, and calcium preparations having no significant effect on the rate of potassium decline. CONCLUSION: Hyperkalemia is common in emergency situations, especially among patients with altered consciousness. There is a strong positive correlation between the severity of hyperkalemia and mortality risk. CRRT appears to be the most effective potassium reducting strategy, while the use of diuretics should be approached with caution.

Modeling the XBB strain of SARS-CoV-2: Competition between variants and impact of reinfection.

XBB, an Omicron subvariant of SARS-CoV-2 that began to circulate in late 2022, has been dominant in the US since early 2023. To quantify the impact of XBB on the progression of COVID-19, we propose a new mathematical model which describes the interplay between XBB and other SARS-CoV-2 variants at the population level and which incorporates the effects of reinfection. We apply the model to COVID-19 data in the US that include surveillance data on the cases and variant proportions from the New York City, the State of New York, and the State of Washington. Our fitting and simulation results show that the transmission rate of XBB is significantly higher than that of other variants and the reinfection from XBB may play an important role in shaping the pandemic/epidemic pattern in the US.

Elevated exposures to persistent endocrine disrupting compounds impact the sperm methylome in regions associated with autism spectrum disorder.

Environmental exposures to endocrine disrupting compounds (EDCs) such as the organochlorines have been linked with various diseases including neurodevelopmental disorders. Autism spectrum disorder (ASD) is a highly complex neurodevelopmental disorder that is considered strongly genetic in origin due to its high heritability. However, the rapidly rising prevalence of ASD suggests that environmental factors may also influence risk for ASD. In the present study, whole genome bisulfite sequencing was used to identify genome-wide differentially methylated regions (DMRs) in a total of 52 sperm samples from a cohort of men from the Faroe Islands (Denmark) who were equally divided into high and low exposure groups based on their serum levels of the long-lived organochlorine 1,1-dichloro-2,2-bis(p-chlorophenyl)ethylene (DDE), a primary breakdown product of the now banned insecticide dichlorodiphenyltrichloroethane (DDT). Aside from being considered a genetic isolate, inhabitants of the Faroe Islands have a native diet that potentially exposes them to a wide range of seafood neurotoxicants in the form of persistent organic pollutants (POPs). The DMRs were mapped to the human genome using Bismark, a 3-letter aligner used for methyl-seq analyses. Gene ontology, functional, and pathway analyses of the DMR-associated genes showed significant enrichment for genes involved in neurological functions and neurodevelopmental processes frequently impacted by ASD. Notably, these genes also significantly overlap with autism risk genes as well as those previously identified in sperm from fathers of children with ASD in comparison to that of fathers of neurotypical children. These results collectively suggest a possible mechanism involving altered methylation of a significant number of neurologically relevant ASD risk genes for introducing epigenetic changes associated with environmental exposures into the sperm methylome. Such changes may provide the potential for transgenerational inheritance of ASD as well as other disorders.

Improvements Achieved by Multiple Imputation for Single-Cell RNA-Seq Data in Clustering Analysis and Differential Expression Analysis.

In a single-cell RNA-seq (scRNA-seq) data set, a high proportion of missing values (or an excessive number of zeroes) are frequently observed. For the related follow-up tasks, such as clustering analysis and differential expression analysis, a data set without missing values is generally required. Many imputation approaches have been proposed for this purpose. Multiple imputation (MI) is a well-established approach to address possible biases in a follow-up analysis result based on one-time imputed data. There is a lack of investigation on this in the analysis of scRNA-seq data. In this study, we have investigated how to efficiently apply the MI approach to the clustering analysis and the differential expression analysis of scRNA-seq data. We proposed an MI procedure for clustering analysis and an MI procedure for differential expression analysis. To demonstrate the improvements achieved by MI in clustering analysis and differential expression analysis of scRNA-seq data, we analyzed three well-known scRNA-seq data sets. scIGANs, an scRNA-seq imputation method based on the generative adversarial networks (GANs), has been recently proposed for scRNA-seq data imputation. Multiple randomly imputed data sets can be conveniently generated by this method. We implemented our MI procedures based on scIGANs. We demonstrated that MI yielded improved performances on the clustering analysis and differential expression analysis results. Our applications to experimental scRNA-seq data illustrated the advantages of MI over one-time imputation of missing values in scRNA-seq data.

A model-based approach to assess reproducibility for large-scale high-throughput MRI-based studies.

Magnetic Resonance Imaging (MRI) technology has been increasingly used in neuroscience studies. Reproducibility of statistically significant findings generated by MRI-based studies, especially association studies (phenotype vs. MRI metric) and task-induced brain activation, has been recently heavily debated. However, most currently available reproducibility measures depend on thresholds for the test statistics and cannot be use to evaluate overall study reproducibility. It is also crucial to elucidate the relationship between overall study reproducibility and sample size in an experimental design. In this study, we proposed a model-based reproducibility index to quantify reproducibility which could be used in large-scale high-throughput MRI-based studies including both association studies and task-induced brain activation. We performed the model-based reproducibility assessments for a few association studies and task-induced brain activation by using several recent large sMRI/fMRI databases. For large sample size association studies between brain structure/function features and some basic physiological phenotypes (i.e. Sex, BMI), we demonstrated that the model-based reproducibility of these studies is more than 0.99. For MID task activation, similar results could be observed. Furthermore, we proposed a model-based analytical tool to evaluate minimal sample size for the purpose of achieving a desirable model-based reproducibility. Additionally, we evaluated the model-based reproducibility of gray matter volume (GMV) changes for UK Biobank (UKB) vs. Parkinson Progression Marker Initiative (PPMI) and UK Biobank (UKB) vs. Human Connectome Project (HCP). We demonstrated that both sample size and study-specific experimental factors play important roles in the model-based reproducibility assessments for different experiments. In summary, a systematic assessment of reproducibility is fundamental and important in the current large-scale high-throughput MRI-based studies.

RNA sequencing of blood in coronary artery disease: involvement of regulatory T cell imbalance.

BACKGROUND: Cardiovascular disease had a global prevalence of 523 million cases and 18.6 million deaths in 2019. The current standard for diagnosing coronary artery disease (CAD) is coronary angiography. Surprisingly, despite well-established clinical indications, up to 40% of the one million invasive cardiac catheterizations return a result of 'no blockage'. The present studies employed RNA sequencing of whole blood to identify an RNA signature in patients with angiographically confirmed CAD. METHODS: Whole blood RNA was depleted of ribosomal RNA (rRNA) and analyzed by single-molecule sequencing of RNA (RNAseq) to identify transcripts associated with CAD (TRACs) in a discovery group of 96 patients presenting for elective coronary catheterization. The resulting transcript counts were compared between groups to identify differentially expressed genes (DEGs). RESULTS: Surprisingly, 98% of DEGs/TRACs were down-regulated ~ 1.7-fold in patients with mild to severe CAD (> 20% stenosis). The TRACs were independent of comorbid risk factors for CAD, such as sex, hypertension, and smoking. Bioinformatic analysis identified an enrichment in transcripts such as FoxP1, ICOSLG, IKZF4/Eos, SMYD3, TRIM28, and TCF3/E2A that are likely markers of regulatory T cells (Treg), consistent with known reductions in Tregs in CAD. A validation cohort of 80 patients confirmed the overall pattern (92% down-regulation) and supported many of the Treg-related changes. TRACs were enriched for transcripts associated with stress granules, which sequester RNAs, and ciliary and synaptic transcripts, possibly consistent with changes in the immune synapse of developing T cells. CONCLUSIONS: These studies identify a novel mRNA signature of a Treg-like defect in CAD patients and provides a blueprint for a diagnostic test for CAD. The pattern of changes is consistent with stress-related changes in the maturation of T and Treg cells, possibly due to changes in the immune synapse.

Association Between Time of Day and the Decision for an Intrapartum Cesarean Delivery.

OBJECTIVE: To examine whether the decision and indications for performing intrapartum cesarean delivery vary by time of day. METHODS: We conducted a secondary analysis of a multicenter observational cohort of 115,502 deliveries (2008-2011), including nulliparous women with term, singleton, nonanomalous live gestations in vertex presentation who were attempting labor. Those who attempted home birth, or underwent cesarean delivery scheduled or decided less than 30 minutes after admission were excluded. Time of day was defined as cesarean delivery decision time among those who delivered by cesarean and delivery time among those who delivered vaginally, categorized by each hour of a 24-hour day. Primary outcomes were decision to perform cesarean delivery and the indications for cesarean delivery (labor dystocia, nonreassuring fetal status, or other indications). Secondary outcomes included whether a dystocia indication adhered to standards promoted to reduce cesarean delivery rates. Bivariate analyses were performed using χ and Kruskal-Wallis tests for categorical and continuous outcomes, respectively, and generalized additive models with smoothing splines explored nonlinear associations without adjustment for other factors. RESULTS: Seven thousand nine hundred fifty-six (22.1%) of 36,014 eligible women underwent cesarean delivery. Decision for cesarean delivery (P<.001) decreased from midnight (21.2%) to morning, reaching a nadir at 10:00 (17.9%) and subsequently rising to peak at 21:00 (26.2%). The frequency of cesarean delivery for dystocia also was significantly associated with time of day (P<.001) in a pattern mirroring overall cesarean delivery. Among cesarean deliveries for dystocia (n=5,274), decision for cesarean delivery at less than 5 cm dilation (P<.001), median duration from 5 cm dilation to cesarean delivery decision (P=.003), and median duration from complete dilation to cesarean delivery decision (P=.014) all significantly differed with time of day. The frequency of nonreassuring fetal status and "other" indications were not significantly associated with time of day (P>.05). CONCLUSION: Among nulliparous women who were attempting labor at term, the decision to perform cesarean delivery, particularly for dystocia, varied with time of day. Some of these differences correlate with labor management differences, given the changing frequency of latent phase cesarean delivery and median time in active phase.

Duration of Operative Vaginal Delivery and Adverse Obstetric Outcomes.

OBJECTIVE: This study aimed to evaluate whether the number of vacuum pop-offs, the number of forceps pulls, or the duration of operative vaginal delivery (OVD) is associated with adverse maternal and perinatal outcomes. STUDY DESIGN: This is a secondary analysis of a multicenter observational cohort of women who underwent an attempted OVD. Women were stratified by the duration of OVD and the number of pop-offs (vacuum) or pulls (forceps) attempted. Severe perineal lacerations, failed OVD, and a composite adverse neonatal outcome were compared by the duration of OVD and number of pop-offs or pulls. RESULTS: Of the 115,502 women in the primary cohort, 5,325 (4.6%) underwent an attempt at OVD: 3,594 (67.5%) with vacuum and 1,731 (32.5%) with forceps. After adjusting for potential confounders, an increasing number of pop-offs was associated with an increased odds of the composite adverse neonatal outcome. However, an increasing duration of vacuum exhibited a stronger association with the composite adverse neonatal outcome. Similarly, the number of forceps pulls was less strongly associated with the composite adverse neonatal outcome compared with the duration of forceps application. CONCLUSION: The duration of OVD may be more associated with adverse neonatal outcomes than the number of pop-offs or pulls.

A distance-type measure approach to the analysis of copy number variation in DNA sequencing data.

BACKGROUND: The next generation sequencing technology allows us to obtain a large amount of short DNA sequence (DNA-seq) reads at a genome-wide level. DNA-seq data have been increasingly collected during the recent years. Count-type data analysis is a widely used approach for DNA-seq data. However, the related data pre-processing is based on the moving window method, in which a window size need to be defined in order to obtain count-type data. Furthermore, useful information can be reduced after data pre-processing for count-type data. RESULTS: In this study, we propose to analyze DNA-seq data based on the related distance-type measure. Distances are measured in base pairs (bps) between two adjacent alignments of short reads mapped to a reference genome. Our experimental data based simulation study confirms the advantages of distance-type measure approach in both detection power and detection accuracy. Furthermore, we propose artificial censoring for the distance data so that distances larger than a given value are considered potential outliers. Our purpose is to simplify the pre-processing of DNA-seq data. Statistically, we consider a mixture of right censored geometric distributions to model the distance data. Additionally, to reduce the GC-content bias, we extend the mixture model to a mixture of generalized linear models (GLMs). The estimation of model can be achieved by the Newton-Raphson algorithm as well as the Expectation-Maximization (E-M) algorithm. We have conducted simulations to evaluate the performance of our approach. Based on the rank based inverse normal transformation of distance data, we can obtain the related z-values for a follow-up analysis. For an illustration, an application to the DNA-seq data from a pair of normal and tumor cell lines is presented with a change-point analysis of z-values to detect DNA copy number alterations. CONCLUSION: Our distance-type measure approach is novel. It does not require either a fixed or a sliding window procedure for generating count-type data. Its advantages have been demonstrated by our simulation studies and its practical usefulness has been illustrated by an experimental data application.

Defining failed induction of labor.

BACKGROUND: While there are well-accepted standards for the diagnosis of arrested active-phase labor, the definition of a "failed" induction of labor remains less certain. One approach to diagnosing a failed induction is based on the duration of the latent phase. However, a standard for the minimum duration that the latent phase of a labor induction should continue, absent acute maternal or fetal indications for cesarean delivery, remains lacking. OBJECTIVE: The objective of this study was to determine the frequency of adverse maternal and perinatal outcomes as a function of the duration of the latent phase among nulliparous women undergoing labor induction. STUDY DESIGN: This study is based on data from an obstetric cohort of women delivering at 25 US hospitals from 2008 through 2011. Nulliparous women who had a term singleton gestation in the cephalic presentation were eligible for this analysis if they underwent a labor induction. Consistent with prior studies, the latent phase was determined to begin once cervical ripening had ended, oxytocin was initiated, and rupture of membranes had occurred, and was determined to end once 5-cm dilation was achieved. The frequencies of cesarean delivery, as well as of adverse maternal (eg, postpartum hemorrhage, chorioamnionitis) and perinatal (eg, a composite frequency of seizures, sepsis, bone or nerve injury, encephalopathy, or death) outcomes, were compared as a function of the duration of the latent phase (analyzed with time both as a continuous measure and categorized in 3-hour increments). RESULTS: A total of 10,677 women were available for analysis. In the vast majority (96.4%) of women, the active phase had been reached by 15 hours. The longer the duration of a woman's latent phase, the greater her chance of ultimately undergoing a cesarean delivery (P < .001, for time both as a continuous and categorical independent variable), although >40% of women whose latent phase lasted ≥18 hours still had a vaginal delivery. Several maternal morbidities, such as postpartum hemorrhage (P < .001) and chorioamnionitis (P < .001), increased in frequency as the length of latent phase increased. Conversely, the frequencies of most adverse perinatal outcomes were statistically stable over time. CONCLUSION: The large majority of women undergoing labor induction will have entered the active phase by 15 hours after oxytocin has started and rupture of membranes has occurred. Maternal adverse outcomes become statistically more frequent with greater time in the latent phase, although the absolute increase in frequency is relatively small. These data suggest that cesarean delivery should not be undertaken during the latent phase prior to at least 15 hours after oxytocin and rupture of membranes have occurred. The decision to continue labor beyond this point should be individualized, and may take into account factors such as other evidence of labor progress.

A statistical method for the conservative adjustment of false discovery rate (q-value).

BACKGROUND: q-value is a widely used statistical method for estimating false discovery rate (FDR), which is a conventional significance measure in the analysis of genome-wide expression data. q-value is a random variable and it may underestimate FDR in practice. An underestimated FDR can lead to unexpected false discoveries in the follow-up validation experiments. This issue has not been well addressed in literature, especially in the situation when the permutation procedure is necessary for p-value calculation. RESULTS: We proposed a statistical method for the conservative adjustment of q-value. In practice, it is usually necessary to calculate p-value by a permutation procedure. This was also considered in our adjustment method. We used simulation data as well as experimental microarray or sequencing data to illustrate the usefulness of our method. CONCLUSIONS: The conservativeness of our approach has been mathematically confirmed in this study. We have demonstrated the importance of conservative adjustment of q-value, particularly in the situation that the proportion of differentially expressed genes is small or the overall differential expression signal is weak.

An efficient concordant integrative analysis of multiple large-scale two-sample expression data sets.

MOTIVATION: We have proposed a mixture model based approach to the concordant integrative analysis of multiple large-scale two-sample expression datasets. Since the mixture model is based on the transformed differential expression test P-values (z-scores), it is generally applicable to the expression data generated by either microarray or RNA-seq platforms. The mixture model is simple with three normal distribution components for each dataset to represent down-regulation, up-regulation and no differential expression. However, when the number of datasets increases, the model parameter space increases exponentially due to the component combination from different datasets. RESULTS: In this study, motivated by the well-known generalized estimating equations (GEEs) for longitudinal data analysis, we focus on the concordant components and assume that the proportions of non-concordant components follow a special structure. We discuss the exchangeable, multiset coefficient and autoregressive structures for model reduction, and their related expectation-maximization (EM) algorithms. Then, the parameter space is linear with the number of datasets. In our previous study, we have applied the general mixture model to three microarray datasets for lung cancer studies. We show that more gene sets (or pathways) can be detected by the reduced mixture model with the exchangeable structure. Furthermore, we show that more genes can also be detected by the reduced model. The Cancer Genome Atlas (TCGA) data have been increasingly collected. The advantage of incorporating the concordance feature has also been clearly demonstrated based on TCGA RNA sequencing data for studying two closely related types of cancer. AVAILABILITY AND IMPLEMENTATION: Additional results are included in a supplemental file. Computer program R-functions are freely available at http://home.gwu.edu/∼ylai/research/Concordance. CONTACT: ylai@gwu.edu. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Detecting discordance enrichment among a series of two-sample genome-wide expression data sets.

BACKGROUND: With the current microarray and RNA-seq technologies, two-sample genome-wide expression data have been widely collected in biological and medical studies. The related differential expression analysis and gene set enrichment analysis have been frequently conducted. Integrative analysis can be conducted when multiple data sets are available. In practice, discordant molecular behaviors among a series of data sets can be of biological and clinical interest. METHODS: In this study, a statistical method is proposed for detecting discordance gene set enrichment. Our method is based on a two-level multivariate normal mixture model. It is statistically efficient with linearly increased parameter space when the number of data sets is increased. The model-based probability of discordance enrichment can be calculated for gene set detection. RESULTS: We apply our method to a microarray expression data set collected from forty-five matched tumor/non-tumor pairs of tissues for studying pancreatic cancer. We divided the data set into a series of non-overlapping subsets according to the tumor/non-tumor paired expression ratio of gene PNLIP (pancreatic lipase, recently shown it association with pancreatic cancer). The log-ratio ranges from a negative value (e.g. more expressed in non-tumor tissue) to a positive value (e.g. more expressed in tumor tissue). Our purpose is to understand whether any gene sets are enriched in discordant behaviors among these subsets (when the log-ratio is increased from negative to positive). We focus on KEGG pathways. The detected pathways will be useful for our further understanding of the role of gene PNLIP in pancreatic cancer research. Among the top list of detected pathways, the neuroactive ligand receptor interaction and olfactory transduction pathways are the most significant two. Then, we consider gene TP53 that is well-known for its role as tumor suppressor in cancer research. The log-ratio also ranges from a negative value (e.g. more expressed in non-tumor tissue) to a positive value (e.g. more expressed in tumor tissue). We divided the microarray data set again according to the expression ratio of gene TP53. After the discordance enrichment analysis, we observed overall similar results and the above two pathways are still the most significant detections. More interestingly, only these two pathways have been identified for their association with pancreatic cancer in a pathway analysis of genome-wide association study (GWAS) data. CONCLUSIONS: This study illustrates that some disease-related pathways can be enriched in discordant molecular behaviors when an important disease-related gene changes its expression. Our proposed statistical method is useful in the detection of these pathways. Furthermore, our method can also be applied to genome-wide expression data collected by the recent RNA-seq technology.

Prediction of Spontaneous Preterm Birth Among Nulliparous Women With a Short Cervix.

OBJECTIVES: The purpose of this study was to evaluate whether demographic and sonographic factors associated with spontaneous preterm birth among nulliparous women with a cervical length of less than 30 mm could be combined into an accurate prediction model for spontaneous preterm birth. METHODS: We conducted a secondary analysis of a trial of nulliparous women with a singleton gestation and a cervical length of less than 30 mm on transvaginal sonography between 16 and 22 weeks who lacked other risk factors for spontaneous (eg, prior cervical excisional procedure) or medically indicated (eg, chronic hypertension) preterm birth, who were randomized to either 17α-hydroxyprogesterone caproate treatment or a placebo. Risk factors associated with spontaneous preterm birth within the entire cohort were identified by univariable analysis. Factors significantly associated (P < .05) with spontaneous preterm birth were included in a multivariable logistic regression analysis to determine whether an accurate prediction model could be developed. RESULTS: Of the 657 randomized patients, 109 (16.6%) had spontaneous preterm birth before 37 weeks' gestation. Logistic regression analysis revealed only cervical length (odds ratio, 1.06 per 1-mm decrease; 95% confidence interval, 1.02-1.10) to be associated with spontaneous preterm birth. The area under the receiver operating characteristic curve based on this regression was low (0.63; 95% confidence interval, 0.58-0.69). Results were similar for the outcome of spontaneous preterm birth before 34 weeks. CONCLUSIONS: An accurate prediction model for spontaneous preterm birth among nulliparous women with a short cervix could not be developed.

Association of the Duration of Active Pushing With Obstetric Outcomes.

OBJECTIVE: To estimate the associations between the duration of active pushing during the second stage of labor and maternal and neonatal outcomes. METHODS: We performed an observational study in which data were obtained by trained abstractors from maternal and neonatal charts of deliveries at 25 hospitals over a 3-year period. In this secondary analysis, women with no prior cesarean delivery who had a term, singleton, cephalic gestation and reached complete dilation were analyzed. The duration of pushing, defined as the time from initiation of pushing to either vaginal delivery or the decision to proceed with a cesarean delivery, was determined. The primary maternal outcome was cesarean delivery and the primary neonatal outcome was a composite that included: mechanical ventilation, proven sepsis, brachial plexus palsy, clavicular fracture, skull fracture, other fracture, seizures, hypoxic-ischemic encephalopathy, or death. Nulliparous and parous women were analyzed separately in univariable and then multivariable analyses. RESULTS: A total of 53,285 women were analyzed. In both nulliparous and parous women, longer duration of pushing was associated with increased odds of both cesarean delivery and the neonatal adverse outcome composite. Nevertheless, even after 4 hours of pushing, approximately 78% of nulliparous women who continued with active pushing had a vaginal delivery and more than 97% did not have the composite adverse neonatal outcome. Similarly, after more than 2 hours of pushing, approximately 82% of parous women who continued active pushing delivered vaginally and more than 97% did not have the adverse neonatal outcome. CONCLUSION: A longer duration of pushing is associated with an increased relative risk, but small absolute difference in risk, of neonatal complications. Approximately 78% of nulliparous women delivered vaginally even after 4 hours of pushing.

miR-671-5p inhibits epithelial-to-mesenchymal transition by downregulating FOXM1 expression in breast cancer.

MicroRNA (miRNA) dysfunction is associated with a variety of human diseases, including cancer. Our previous study showed that miR-671-5p was deregulated throughout breast cancer progression. Here, we report for the first time that miR-671-5p is a tumor-suppressor miRNA in breast tumorigenesis. We found that expression of miR-671-5p was decreased significantly in invasive ductal carcinoma (IDC) compared to normal in microdissected formalin-fixed, paraffin-embedded (FFPE) tissues. Forkhead Box M1 (FOXM1), an oncogenic transcription factor, was predicted as one of the direct targets of miR-671-5p, which was subsequently confirmed by luciferase assays. Forced expression of miR-671-5p in breast cancer cell lines downregulated FOXM1 expression, and attenuated the proliferation and invasion in breast cancer cell lines. Notably, overexpression of miR-671-5p resulted in a shift from epithelial-to-mesenchymal transition (EMT) to mesenchymal-to-epithelial transition (MET) phenotypes in MDA-MB-231 breast cancer cells and induced S-phase arrest. Moreover, miR-671-5p sensitized breast cancer cells to cisplatin, 5-fluorouracil (5-FU) and epirubicin exposure. Host cell reactivation (HCR) assays showed that miR-671-5p reduces DNA repair capability in post-drug exposed breast cancer cells. cDNA microarray data revealed that differentially expressed genes when miR-671-5p was transfected are associated with cell proliferation, invasion, cell cycle, and EMT. These data indicate that miR-671-5p functions as a tumor suppressor miRNA in breast cancer by directly targeting FOXM1. Hence, miR-671-5p may serve as a novel therapeutic target for breast cancer management.

Identification and Functional Validation of Reciprocal microRNA-mRNA Pairings in African American Prostate Cancer Disparities.

PURPOSE: African Americans (AA) exhibit higher rates of prostate cancer incidence and mortality compared with European American (EA) men. In addition to socioeconomic influences, biologic factors are believed to play a critical role in prostate cancer disparities. We investigated whether population-specific and -enriched miRNA-mRNA interactions might contribute to prostate cancer disparities. EXPERIMENTAL DESIGN: Integrative genomics was used, combining miRNA and mRNA profiling, miRNA target prediction, pathway analysis, and functional validation, to map miRNA-mRNA interactions associated with prostate cancer disparities. RESULTS: We identified 22 AA-specific and 18 EA-specific miRNAs in prostate cancer versus patient-matched normal prostate, and 10 "AA-enriched/-depleted" miRNAs in AA prostate cancer versus EA prostate cancer comparisons. Many of these population-specific/-enriched miRNAs could be paired with target mRNAs that exhibited an inverse pattern of differential expression. Pathway analysis revealed EGFR (or ERBB) signaling as a critical pathway significantly regulated by AA-specific/-enriched mRNAs and miRNA-mRNA pairings. Novel miRNA-mRNA pairings were validated by qRT-PCR, Western blot, and/or IHC analyses in prostate cancer specimens. Loss/gain of function assays performed in population-specific prostate cancer cell lines confirmed miR-133a/MCL1, miR-513c/STAT1, miR-96/FOXO3A, miR-145/ITPR2, and miR-34a/PPP2R2A as critical miRNA-mRNA pairings driving oncogenesis. Manipulating the balance of these pairings resulted in decreased proliferation and invasion, and enhanced sensitization to docetaxel-induced cytotoxicity in AA prostate cancer cells. CONCLUSIONS: Our data suggest that AA-specific/-enriched miRNA-mRNA pairings may play a critical role in the activation of oncogenic pathways in AA prostate cancer. Our findings also suggest that miR-133a/MCL1, miR-513c/STAT1, and miR-96/FOXO3A may have clinical significance in the development of novel strategies for treating aggressive prostate cancer.

Outlier reset CUSUM for the exploration of copy number alteration data.

Copy number alteration (CNA) data have been collected to study disease related chromosomal amplifications and deletions. The CUSUM procedure and related plots have been used to explore CNA data. In practice, it is possible to observe outliers. Then, modifications of the CUSUM procedure may be required. An outlier reset modification of the CUSUM (ORCUSUM) procedure is developed in this paper. The threshold value for detecting outliers or significant CUSUMs can be derived using results for sums of independent truncated normal random variables. Bartel's non-parametric test for autocorrelation is also introduced to the analysis of copy number variation data. Our simulation results indicate that the ORCUSUM procedure can still be used even in the situation where the degree of autocorrelation level is low. Furthermore, the results show the outlier's impact on the traditional CUSUM's performance and illustrate the advantage of the ORCUSUM's outlier reset feature. Additionally, we discuss how the ORCUSUM can be applied to examine CNA data with a simulated data set. To illustrate the procedure, recently collected single nucleotide polymorphism (SNP) based CNA data from The Cancer Genome Atlas (TCGA) Research Network is analyzed. The method is applied to a data set collected in an ovarian cancer study. Three cytogenetic bands (cytobands) are considered to illustrate the method. The cytobands 11q13 and 9p21 have been shown to be related to ovarian cancer. They are presented as positive examples. The cytoband 3q22, which is less likely to be disease related, is presented as a negative example. These results illustrate the usefulness of the ORCUSUM procedure as an exploratory tool for the analysis of SNP based CNA data.

Is There a Threshold Oral Glucose Tolerance Test Value for Predicting Adverse Pregnancy Outcome?

OBJECTIVE: This study aims to determine whether there is a threshold 3-hour oral glucose tolerance test (OGTT) value associated with accelerated risk of adverse pregnancy outcomes. STUDY DESIGN: In a secondary analysis of a cohort of women with untreated mild gestational glucose intolerance, we used generalized additive models with smoothing splines to explore nonlinear associations between each of the 3-hour OGTT values (fasting, 1-hour, 2-hour, and 3-hour) and adverse pregnancy outcomes, including the study's composite outcome (perinatal mortality, hypoglycemia, hyperbilirubinemia, neonatal hyperinsulinemia, and/or birth trauma), large for gestational age birth weight, small for gestational age birth weight, shoulder dystocia, neonatal hypoglycemia, gestational hypertension (gHTN), and preeclampsia. RESULTS: Among the 1,360 eligible women, each timed OGTT value was linearly associated with increased odds of composite adverse outcome. We found evidence of a departure from linearity only for the association between fasting glucose and gHTN/preeclampsia, with a stronger association for values of 85 to 94 mg/dL (p = 0.03). We found no evidence of departure from linearity for any other OGTT values and measured outcomes (all chi-square test p-values ≥ 0.05). CONCLUSION: In a population of untreated women with mild gestational glucose intolerance and fasting OGTT < 95 mg/dL, we found an increasing risk of gHTN with a fasting glucose between 85 and 94 mg/dL.