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Children admitted to the pediatric intensive care unit (PICU) often require multiple medications to achieve comfort and sedation. Although starting doses are available, these medications are typically titrated to the desired effect. Both oversedation and undersedation are associated with adverse events. The aim of this retrospective study was to evaluate cumulative medication burden necessary to achieve comfort in patients in the PICU and determine relevant predictors of medication needs. In order to account for all of the sedative medications, z-scores were used to assess the population average dose of each medication and compare each patient day to this population average. Sedation regimens for 130 patients in the PICU were evaluated. Mean overall infusion rates of fentanyl, morphine, and hydromorphone were 1.67 ± 0.81 µg/kg/hour, 0.12 ± 0.08 mg/kg/hour, and 17.84 ± 13.4 µg/kg/hour, respectively. The mean infusion rate of dexmedetomidine was 0.59 ± 0.28 µg/kg/hour, and midazolam was 0.14 ± 0.1 mg/kg/hour. Summation z-sores were used to rank the amount of sedation medication needed to achieve comfort for each individual patient for his/her PICU stay in relation to the entire sample. Patient age, weight, and length of mechanical ventilation were all significant predictors of sedation requirement. This study will provide data necessary to develop a model of cumulative medication burden needed to achieve appropriate sedation in this population. This descriptive model in appropriately ranking patients based on sedative needs is the first step in exploring potential genetic factors that may provide an insight into homing in on the appropriate sedation regimen.

The CYP2B6 gene is highly polymorphic and its activity shows wide interindividual variability. However, substantial variability in CYP2B6 activity remains unexplained by the known CYP2B6 genetic variations. Circulating, cell-free micro RNAs (miRNAs) may serve as biomarkers of hepatic enzyme activity. CYP2B6 activity in 72 healthy volunteers was determined using the disposition of efavirenz as a probe drug. Circulating miRNA expression was quantified from baseline plasma samples. A linear model consisting of the effects of miRNA expression, genotype-determined metabolizer status, and demographic information was developed to predict CYP2B6 activity. Expression of 2,510 miRNAs were quantified out of which 7 miRNAs, together with the CYP2B6-genotypic metabolizer status and demographics, was shown to be predictive markers for CYP2B6 activity. The reproducibility of the model was evaluated by cross-validation. The average Pearson's correlation (R) between the predicted and observed maximum plasma concentration (Cmax ) ratios of efavirenz and its metabolite-8-OH efavirenz using the linear model with all features (7 miRNA + metabolizer status + age + sex + race) was 0.6702. Similar results were also observed using area under the curve (AUC) ratios (Pearson correlation's R = 0.6035). Thus, at least 36% (R2 ) of the variability of in vivo CYP2B6 activity was explained using this model. This is a significant improvement over the models using only the genotype-based metabolizer status or the demographic information, which explained only 6% or less of the variability of in vivo CYP2B6 activity. Our results, therefore, demonstrate that circulating plasma miRNAs can be valuable biomarkers for in vivo CYP2B6 activity.

Single nucleotide variants (SNVs) in intronic regions have yet to be systematically investigated for their disease-causing potential. Using known pathogenic and neutral intronic SNVs (iSNVs) as training data, we develop the RegSNPs-intron algorithm based on a random forest classifier that integrates RNA splicing, protein structure, and evolutionary conservation features. RegSNPs-intron showed excellent performance in evaluating the pathogenic impacts of iSNVs. Using a high-throughput functional reporter assay called ASSET-seq (ASsay for Splicing using ExonTrap and sequencing), we evaluate the impact of RegSNPs-intron predictions on splicing outcome. Together, RegSNPs-intron and ASSET-seq enable effective prioritization of iSNVs for disease pathogenesis.

Genome-wide association studies (GWAS) of complex traits, such as alcohol use disorders (AUD), usually identify variants in non-coding regions and cannot by themselves distinguish whether the associated variants are functional or in linkage disequilibrium with the functional variants. Transcriptome studies can identify genes whose expression differs between alcoholics and controls. To test which variants associated with AUD may cause expression differences, we integrated data from deep RNA-seq and GWAS of four postmortem brain regions from 30 subjects with AUD and 30 controls to analyze allele-specific expression (ASE). We identified 88 genes with differential ASE in subjects with AUD compared to controls. Next, to test one potential mechanism contributing to the differential ASE, we analyzed single nucleotide polymorphisms (SNPs) in the 3′ untranslated regions (3′UTR) of these genes. Of the 88 genes with differential ASE, 61 genes contained 437 SNPs in the 3′UTR with at least one heterozygote among the subjects studied. Using a modified PASSPORT-seq (parallel assessment of polymorphisms in miRNA target-sites by sequencing) assay, we identified 25 SNPs that affected RNA levels in a consistent manner in two neuroblastoma cell lines, SH-SY5Y and SK-N-BE(2). Many of these SNPs are in binding sites of miRNAs and RNA-binding proteins, indicating that these SNPs are likely causal variants of AUD-associated differential ASE. In sum, we demonstrate that a combination of computational and experimental approaches provides a powerful strategy to uncover functionally relevant variants associated with the risk for AUD.

BACKGROUND AND AIMS: Variation in micro-RNA (miRNA) levels in blood has been associated with alterations of physiological functions of the cardiovascular system. Circulating miRNA have the potential to become reliable biomarkers for risk stratification and early detection of cardiovascular events. Recurrent thrombotic events in patients with established coronary artery disease (CAD) demonstrate the need for personalized approaches to secondary prevention, especially in light of recent novel treatment approaches. METHODS: In a single center cohort study, whole blood samples were collected from 437 subjects undergoing cardiac catheterization, who were followed for recurrent cardiovascular events during a mean follow up of 1.5 years. We selected a case cohort (n = 22) with recurrent thrombotic events on standard medical therapy (stent thrombosis (n = 6) or spontaneous myocardial infarction (MI) (n = 16)) and a matched cohort with CAD, but uneventful clinical follow up (n = 26), as well as a control group with cardiovascular risk factors, but without angiographic CAD (n = 24). We performed complete miRNA next generation sequencing of RNA extracted from whole blood samples (including leukocytes and platelets). RESULTS: A differential pattern of miRNA expression was found among controls, CAD patients with no events, and CAD patients with recurrent events. MiRNA previously associated with MI, CAD, endothelial function, vascular smooth muscle cells, platelets, angiogenesis, heart failure, cardiac hypertrophy, arrhythmia, and stroke were found variably expressed in our case-control cohorts. Seventy miRNA (FDR < 0.05) were linked to the risk of recurrent myocardial infarction and future stent thrombosis, as compared to CAD patients with subsequently uneventful follow up. CONCLUSIONS: MiRNA next generation sequencing demonstrates altered fingerprint profile of whole blood miRNA expression among subjects with subsequent recurrent thrombotic events on standard medical therapy (‘non-responders’), as compared to subjects with no recurrent cardiovascular events. MiRNA profiling may be useful to identify high risk subjects and provide additional insights into disease mechanisms not currently attenuated with standard medical therapy used in CAD treatment.

siRNA stabilized for in vivo applications is filtered and reabsorbed in the renal proximal tubule (PT), reducing mRNA expression transiently. Prior siRNA efforts have successfully prevented upregulation of mRNA in response to injury. We proposed reducing constitutive gene and protein expression of LRP2 (megalin) in order to understand its molecular regulation in mice. Using siRNA targeting mouse LRP2 (siLRP2), reduction of LRP2 mRNA expression was compared to scrambled siRNA (siSCR) in mouse PT cells. Mice received siLRP2 administration optimized for dose, administration site, carrier solution, administration frequency, and administration duration. Kidney cortex was collected upon sacrifice. Renal gene and protein expression were compared by qRT-PCR, immunoblot, and immunohistochemistry (IHC). Compared to siSCR, siLRP2 reduced mRNA expression in PT cells to 16.6%±0.6%. In mouse kidney cortex, siLRP2 reduced mRNA expression to 74.8 ± 6.3% 3 h and 70.1 ± 6.3% 6 h after administration. mRNA expression rebounded at 12 h (160.6 ± 11.2%). No megalin renal protein expression reduction was observed by immunoblot or IHC, even after serial twice daily dosing for 3.5 days. Megalin is a constitutively expressed protein. Although LRP2 renal mRNA expression reduction was achieved, siRNA remains a costly and inefficient intervention to reduce in vivo megalin protein expression.

A large number of single nucleotide variants (SNVs) in the human genome are known to be responsible for inherited disease. An even larger number of SNVs, particularly those located in introns, have yet to be investigated for their pathogenic potential. Using known pathogenic and neutral intronic SNVs (iSNVs), we developed the regSNPs-intron algorithm based on a random forest classifier that integrates RNA splicing, protein structure and evolutionary conservation features. regSNPs-intron showed high accuracy in computing disease-causing probabilities of iSNVs. Using a high-throughput functional reporter assay called ASSET-seq (ASsay for Splicing using ExonTrap and sequencing), we validated regSNPs-intron predictions by measuring the impact of iSNVs on splicing outcome. Together, regSNPs-intron and ASSET-seq enable effective prioritization of iSNVs for disease pathogenesis. regSNPs-intron is available at https://regsnps-intron.ccbb.iupui.edu.

Transcriptome studies can identify genes whose expression differs between alcoholics and controls. To test which variants associated with alcohol use disorder (AUDs) may cause expression differences, we integrated deep RNA-seq and genome-wide association studies (GWAS) data from four postmortem brain regions of 30 AUDs subjects and 30 controls (social/non-drinkers) and analyzed allele-specific expression (ASE). We identified 90 genes with differential ASE in subjects with AUDs compared to controls. Of these, 61 genes contained 437 single nucleotide polymorphisms (SNPs) in the 3’ untranslated regions (3’UTR) with at least one heterozygote among the subjects studied. Using a modified PASSPORT-seq (parallel assessment of polymorphisms in miRNA target-sites by sequencing) assay, we identified 25 SNPs that showed affected RNA levels in a consistent manner in two neuroblastoma cell lines, SH-SY5Y and SK-N-BE(2). Many of these are in binding sites of miRNAs and RNA binding proteins, indicating that these SNPs are likely causal variants of AUD-associated differential ASE.

Next-generation sequencing (NGS) studies have identified large numbers of genetic variants that are predicted to alter miRNA–mRNA interactions. We developed a novel high-throughput bioassay, PASSPORT-seq, that can functionally test in parallel 100s of these variants in miRNA binding sites (mirSNPs). The results are highly reproducible across both technical and biological replicates. The utility of the bioassay was demonstrated by testing 100 mirSNPs in HEK293, HepG2, and HeLa cells. The results of several of the variants were validated in all three cell lines using traditional individual luciferase assays. Fifty-five mirSNPs were functional in at least one of three cell lines (FDR ≤ 0.05); 11, 36, and 27 of them were functional in HEK293, HepG2, and HeLa cells, respectively. Only four of the variants were functional in all three cell lines, which demonstrates the cell-type specific effects of mirSNPs and the importance of testing the mirSNPs in multiple cell lines. Using PASSPORT-seq, we functionally tested 111 variants in the 3′ UTR of 17 pharmacogenes that are predicted to alter miRNA regulation. Thirty-three of the variants tested were functional in at least one cell line.

CYP2B6*6 and CYP2B6*18 are the most clinically important variants causing reduced CYP2B6 protein expression and activity. However, these variants do not account for all variability in CYP2B6 activity. Emerging evidence has shown that genetic variants in the 3'UTR may explain variable drug response by altering microRNA regulation. Five 3'UTR variants were associated with significantly altered efavirenz AUC0-48 (8-OH-EFV/EFV) ratios in healthy human volunteers. The rs70950385 (AG>CA) variant, predicted to create a microRNA binding site for miR-1275, was associated with 33% decreased CYP2B6 activity among normal metabolizers (AG/AG vs. CA/CA [p

The design and synthesis of dual aromatase inhibitors/selective estrogen receptor modulators (AI/SERMs) is an attractive strategy for the discovery of new breast cancer therapeutic agents. Previous efforts led to the preparation of norendoxifen (4) derivatives with dual aromatase inhibitory activity and estrogen receptor binding activity. In the present study, some of the structural features of the potent AI letrozole were incorporated into the lead compound (norendoxifen) to afford a series of new dual AI/SERM agents based on a symmetrical diphenylmethylene substructure that eliminates the problem of E,Z isomerization encountered with norendoxifen-based AI/SERMs. Compound 12d had good aromatase inhibitory activity (IC50 = 62.2 nM) while also exhibiting good binding activity to both ER-α (EC50 = 72.1 nM) and ER-β (EC50 = 70.8 nM). In addition, a new synthesis was devised for the preparation of norendoxifen and its analogues through a bis-Suzuki coupling strategy.