In this work, tannic acid (TA) was employed to modify the surface of multiwall carbon nanotubes (CNTs) to form TCNTs hybrids via noncovalent functionalization to enhance its dispersibility in water. ...Then, the TCNTs enhanced epoxy coatings were applied on sintered NdFeB magnets by cathodic electrophoretic deposition method for corrosion test. The corrosion resistance of prepared specimens was assessed by electrochemical experiments. The results show that TCNTs hybrids present a more homogeneous distribution in epoxy resin than pristine CNTs and could obviously promote anticorrosion properties of prepared specimens. Within 36-day soaking in 3.5 wt.% NaCl solution, the specimens maintain a high value of |
Z
|
0.01Hz
(10
8
Ω cm
2
) when the concentration of TCNTs is 2 g/L. When immersed in 3.5 wt.% NaCl solution for 40 days, the
E
corr
of specimens shifts to − 0.207 V and
J
corr
is about 5.281 × 10
−11
A cm
−2
, which demonstrates superior corrosion resistance.
Germline disease-causing variants are generally more spatially clustered in protein 3-dimensional structures than benign variants. Motivated by this tendency, we develop a fast and powerful ...protein-structure-based scan (PSCAN) approach for evaluating gene-level associations with complex disease and detecting signal variants. We validate PSCAN's performance on synthetic data and two real data sets for lipid traits and Alzheimer's disease. Our results demonstrate that PSCAN performs competitively with existing gene-level tests while increasing power and identifying more specific signal variant sets. Furthermore, PSCAN enables generation of hypotheses about the molecular basis for the associations in the context of protein structures and functional domains.
Previous genome‐wide association studies (GWASs) have been largely focused on European (EUR) populations. However, polygenic risk scores (PRSs) derived from EUR have been shown to perform worse in ...non‐EURs compared with EURs. In this study, we aim to improve PRS prediction in East Asians (EASs). We introduce a rescaled meta‐analysis framework to combine both EUR (N = 122,175) and EAS (N = 30,801) GWAS summary statistics. To improve PRS prediction in EASs, we use a scaling factor to up‐weight the EAS data, such that the resulting effect size estimates are more relevant to EASs. We then derive PRSs for EAS from the rescaled meta‐analysis results of EAS and EUR data. Evaluated in an independent EAS validation data set, this approach increases the prediction liability‐adjusted Nagelkerke's pseudo R2 by 40%, 41%, and 5%, respectively, compared with PRSs derived from an EAS GWAS only, EUR GWAS only, and conventional fixed‐effects meta‐analysis of EAS and EUR data. The PRS derived from the rescaled meta‐analysis approach achieved an area under the receiver operating characteristic curve (AUC) of 0.6059, higher than AUC = 0.5782, 0.5809, 0.6008 for EAS, EUR, and conventional meta‐analysis of EAS and EUR. We further compare PRSs constructed by single‐nucleotide polymorphisms that have different linkage disequilibrium (LD) scores and minor allele frequencies (MAFs) between EUR and EAS, and observe that lower LD scores or MAF in EAS correspond to poorer PRS performance (AUC = 0.5677, 0.5530, respectively) than higher LD scores or MAF (AUC = 0.589, 0.5993, respectively). We finally build a PRS stratified by LD score differences in EUR and EAS using rescaled meta‐analysis, and obtain an AUC of 0.6096, with improvement over other strategies investigated.
The increasing use of electronic health records (EHRs) and biobanks offers unique opportunities to study Mendelian diseases. We described a novel approach to summarize clinical manifestations from ...patient EHRs into phenotypic evidence for cystic fibrosis (CF) with potential to alert unrecognized patients of the disease.
We estimated genetically predicted expression (GReX) of cystic fibrosis transmembrane conductance regulator (CFTR) and tested for association with clinical diagnoses in the Vanderbilt University biobank (N = 9142 persons of European descent with 71 cases of CF). The top associated EHR phenotypes were assessed in combination as a phenotype risk score (PheRS) for discriminating CF case status in an additional 2.8 million patients from Vanderbilt University Medical Center (VUMC) and 125,305 adult patients including 25,314 CF cases from MarketScan, an independent external cohort.
GReX of CFTR was associated with EHR phenotypes consistent with CF. PheRS constructed using the EHR phenotypes and weights discovered by the genetic associations improved discriminative power for CF over the initially proposed PheRS in both VUMC and MarketScan.
Our study demonstrates the power of EHRs for clinical description of CF and the benefits of using a genetics-informed weighing scheme in construction of a phenotype risk score. This research may find broad applications for phenomic studies of Mendelian disease genes.
Inflammatory breast cancer (IBC) is the most aggressive form of breast cancer. Although it is a rare subtype, IBC is responsible for roughly 10% of breast cancer deaths. In order to obtain a better ...understanding of the genomic landscape and intratumor heterogeneity (ITH) in IBC, we conducted whole-exome sequencing of 16 tissue samples (12 tumor and four normal samples) from six hormone-receptor-positive IBC patients, analyzed somatic mutations and copy number aberrations, and inferred subclonal structures to demonstrate ITH. Our results showed that KMT2C was the most frequently mutated gene (42%, 5/12 samples), followed by HECTD1, LAMA3, FLG2, UGT2B4, STK33, BRCA2, ACP4, PIK3CA, and DNAH8 (all nine genes tied at 33% frequency, 4/12 samples). Our data indicated that PTEN and FBXW7 mutations may be considered driver gene mutations for IBC. We identified various subclonal structures and different levels of ITH between IBC patients, and mutations in the genes EIF4G3, IL12RB2, and PDE4B may potentially generate ITH in IBC.
Family samples, which can be enriched for rare causal variants by focusing on families with multiple extreme individuals and which facilitate detection of de novo mutation events, provide an ...attractive resource for next-generation sequencing studies. Here, we describe, implement, and evaluate a likelihood-based framework for analysis of next generation sequence data in family samples. Our framework is able to identify variant sites accurately and to assign individual genotypes, and can handle de novo mutation events, increasing the sensitivity and specificity of variant calling and de novo mutation detection. Through simulations we show explicit modeling of family relationships is especially useful for analyses of low-frequency variants and that genotype accuracy increases with the number of individuals sequenced per family. Compared with the standard approach of ignoring relatedness, our methods identify and accurately genotype more variants, and have high specificity for detecting de novo mutation events. The improvement in accuracy using our methods over the standard approach is particularly pronounced for low-frequency variants. Furthermore the family-aware calling framework dramatically reduces Mendelian inconsistencies and is beneficial for family-based analysis. We hope our framework and software will facilitate continuing efforts to identify genetic factors underlying human diseases.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Gene-based rare variant association studies (RVASs) have low power due to the infrequency of rare variants and the large multiple testing burden. To correct for multiple testing, traditional false ...discovery rate (FDR) procedures which depend solely on P-values are often used. Recently, Independent Hypothesis Weighting (IHW) was developed to improve the detection power while maintaining FDR control by leveraging prior information for each hypothesis. Here, we present a framework to increase power of gene-based RVASs by incorporating prior information using IHW. We first build supervised machine learning models to assign each gene a prediction score that measures its disease risk, using the input of multiple biological features, fed with high-confidence risk genes and local background genes selected near GWAS significant loci as the training set. Then we use the prediction scores as covariates to prioritize RVAS results via IHW. We demonstrate the effectiveness of this framework through applications to RVASs in schizophrenia and autism spectrum disorder. We found sizeable improvements in the number of significant associations compared to traditional FDR approaches, and independent evidence supporting the relevance of the genes identified by our framework but not traditional FDR, demonstrating the potential of our framework to improve power of gene-based RVASs.
Cumulative data have shown that microRNAs (miRNA) are involved in the etiology and prognosis of colorectal cancer (CRC). Genetic polymorphisms in pre-miRNA genes may influence the biogenesis and ...functions of their host miRNAs. However, whether these polymorphisms are associated with CRC prognosis remains unknown.
We analyzed the effects of seven single-nucleotide polymorphisms (SNP) in pre-miRNA genes on the prognosis of a Chinese population with 408 CRC patients with surgically-resected adenocarcinoma.
Two SNPs were identified to be significantly associated with recurrence-free survival and overall survival of the patients. The most significant SNP was rs6505162 in pre-miR-423. Compared with the homozygous wild-type genotype, the variant-containing genotypes of this SNP were significantly associated with both the overall survival (HR = 2.12, 95% CI = 1.34-3.34, P = 0.001) and the recurrence-free survival (HR = 1.59, 95% CI = 1.08-2.36, P = 0.019). Another SNP, rs4919510 in pre-miR-608, was also associated with altered recurrence-free survival (HR = 0.61, 95% CI = 0.41-0.92, P = 0.017). These effects were evident only in patients receiving chemotherapy but not in those without chemotherapy. In addition, the combined analysis of the two SNPs conferred a 2.84-fold (95% CI = 1.50-5.37, P = 0.001) increased risk of recurrence and/or death. Similarly, this effect was only prominent in those receiving chemotherapy (P < 0.001) but not in those without chemotherapy (P = 0.999).
Our data suggest that genetic polymorphisms in pre-miRNA genes may impact CRC prognosis especially in patients receiving chemotherapy, a finding that warrants further independent validation.
This is one of the first studies showing a prognostic role of pre-miRNA gene SNPs in CRC.
Studies of complex disorders benefit from integrative analyses of multiple omics data. Yet, sample mix-ups frequently occur in multi-omics studies, weakening statistical power and risking false ...findings. Accurately aligning sample information, genotype, and corresponding omics data is critical for integrative analyses. We developed DRAMS (https://github.com/Yi-Jiang/DRAMS) to Detect and Re-Align Mixed-up Samples to address the sample mix-up problem. It uses a logistic regression model followed by a modified topological sorting algorithm to identify the potential true IDs based on data relationships of multi-omics. According to tests using simulated data, the more types of omics data used or the smaller the proportion of mix-ups, the better that DRAMS performs. Applying DRAMS to real data from the PsychENCODE BrainGVEX project, we detected and corrected 201 (12.5% of total data generated) mix-ups. Of the 21 mix-ups involving errors of racial identity, DRAMS re-assigned all data to the correct racial group in the 1000 Genomes project. In doing so, quantitative trait loci (QTL) (FDR<0.01) increased by an average of 1.62-fold. The use of DRAMS in multi-omics studies will strengthen statistical power of the study and improve quality of the results. Even though very limited studies have multi-omics data in place, we expect such data will increase quickly with the needs of DRAMS.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
The liver is one of the few organs that have the capacity to regenerate in response to injury. We carried out genomewide microRNA (miRNA) microarray studies during liver regeneration in rats after ...70% partial hepatectomy (PH) at early and mid time points to more thoroughly understand their role. At 3, 12, and 18 hours post‐PH ∼40% of the miRNAs tested were up‐regulated. Conversely, at 24 hours post‐PH, ∼70% of miRNAs were down‐regulated. Furthermore, we established that the genomewide down‐regulation of miRNA expression at 24 hours was also correlated with decreased expression of genes, such as Rnasen, Dgcr8, Dicer, Tarbp2, and Prkra, associated with miRNA biogenesis. To determine whether a potential negative feedback loop between miRNAs and their regulatory genes exists, 11 candidate miRNAs predicted to target the above‐mentioned genes were examined and found to be up‐regulated at 3 hours post‐PH. Using reporter and functional assays, we determined that expression of these miRNA‐processing genes could be regulated by a subset of miRNAs and that some miRNAs could target multiple miRNA biogenesis genes simultaneously. We also demonstrated that overexpression of these miRNAs inhibited cell proliferation and modulated cell cycle in both Huh‐7 human hepatoma cells and primary rat hepatocytes. From these observations, we postulated that selective up‐regulation of miRNAs in the early phase after PH was involved in the priming and commitment to liver regeneration, whereas the subsequent genomewide down‐regulation of miRNAs was required for efficient recovery of liver cell mass. Conclusion: Our data suggest that miRNA changes are regulated by negative feedback loops between miRNAs and their regulatory genes that may play an important role in the steady‐state regulation of liver regeneration. (HEPATOLOGY 2011;)
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