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BACKGROUND Hereditary spastic paraplegia presents spasticity as the main clinical manifestation, reducing gait quality and producing incapacity. Management with botulinum toxin type A (BoNT-A) is not well elucidated. The objective of the current study was to evaluate the efficacy and safety of BoNT-A in patients with hereditary spastic paraplegias. METHODS This was a double-blind, randomized, placebo-controlled crossover trial. Each participant was randomly assigned to receive 1 injection session of either BoNT-A (100 IU/2 mL of Prosigne in each adductor magnus and each triceps surae) or saline 0.9% (2 mL). The primary outcome measure was change from baseline in maximal gait velocity, and secondary outcome measures included changes in gait at self-selected velocity, spasticity, muscle strength, Spastic Paraplegia Rating Scale, pain, fatigue, and subjective perception of improvement. We also looked at adverse events reported by the patients. RESULTS We enrolled 55 patients, 36 of whom were men and 41 with the pure phenotype. Mean age was 43 ± 13.4 years (range, 19-72 years), mean age of onset waws 27 ± 13.1 years (range

Mesial temporal lobe epilepsy (MTLE) is a chronic neurological disorder characterized by the occurrence of seizures, and histopathological abnormalities in the mesial temporal lobe structures, mainly hippocampal sclerosis (HS). We used a multi-omics approach to determine the profile of transcript and protein expression in the dorsal and ventral hippocampal dentate gyrus (DG) and Cornu Ammonis 3 (CA3) in an animal model of MTLE induced by pilocarpine. We performed label-free proteomics and RNAseq from laser-microdissected tissue isolated from pilocarpine-induced Wistar rats. We divided the DG and CA3 into dorsal and ventral areas and analyzed them separately. We performed a data integration analysis and evaluated enriched signaling pathways, as well as the integrated networks generated based on the gene ontology processes. Our results indicate differences in the transcriptomic and proteomic profiles among the DG and the CA3 subfields of the hippocampus. Moreover, our data suggest that epileptogenesis is enhanced in the CA3 region when compared to the DG, with most abnormalities in transcript and protein levels occurring in the CA3. Furthermore, our results show that the epileptogenesis in the pilocarpine model involves predominantly abnormal regulation of excitatory neuronal mechanisms mediated by N-methyl D-aspartate (NMDA) receptors, changes in the serotonin signaling, and neuronal activity controlled by calcium/calmodulin-dependent protein kinase (CaMK) regulation and leucine-rich repeat kinase 2 (LRRK2)/WNT signaling pathways.

Made available in DSpace on 2020-12-12T02:06:26Z (GMT). No. of bitstreams: 0 Previous issue date: 2020-12-01 Type 2 diabetes mellitus (T2DM), dyslipidemia and periodontitis are frequently associated pathologies; however, there are no studies showing the peripheral blood transcript profile of these combined diseases. Here we identified the differentially expressed genes (DEGs) of circulating lymphocytes and monocytes to reveal potential biomarkers that may be used as molecular targets for future diagnosis of each combination of these pathologies (compared to healthy patients) and give insights into the underlying molecular mechanisms of these diseases. Study participants (n = 150) were divided into groups: (H) systemically and periodontal healthy (control group); (P) with periodontitis, but systemically healthy; (DL-P) with dyslipidemia and periodontitis; (T2DMwell-DL-P) well-controlled type 2 diabetes mellitus with dyslipidemia and periodontitis; and (T2DMpoorly-DL-P) poorly-controlled type 2 diabetes mellitus with dyslipidemia and periodontitis. We preprocessed the microarray data using the Robust Multichip Average (RMA) strategy, followed by the RankProd method to identify candidates for DEGs. Furthermore, we performed functional enrichment analysis using Ingenuity Pathway Analysis and Gene Set Enrichment Analysis. DEGs were submitted to pairwise comparisons, and selected DEGs were validated by quantitative polymerase chain reaction. Validated DEGs verified from T2DMpoorly-DL-P versus H were: TGFB1I1, VNN1, HLADRB4 and CXCL8; T2DMwell-DL-P versus H: FN1, BPTF and PDE3B; DL-P versus H: DAB2, CD47 and HLADRB4; P versus H: IGHDL-P, ITGB2 and HLADRB4. In conclusion, we identified that circulating lymphocytes and monocytes of individuals simultaneously affected by T2DM, dyslipidemia and periodontitis, showed an altered molecular profile mainly associated to inflammatory response, immune cell trafficking, and infectious disease pathways. Altogether, these results shed light on novel potential targets for future diagnosis, monitoring or development of targeted therapies for patients sharing these conditions. Department of Diagnosis and Surgery School of Dentistry at Araraquara UNESP- São Paulo State University Department of Morphology Genetics Orthodontics and Pediatric Dentistry School of Dentistry at Araraquara UNESP- São Paulo State University Molecular Genomics and Therapeutics Section Genetics of Development and Disease Branch National Institute of Diabetes and Digestive and Kidney Diseases National Institutes of Health 10 Center Drive Building 10 Room 9D11 Department of Surgery Uniformed Services University of the Health Sciences and Henry Jackson Foundation for the Advancement of Military Medicine Postgraduate Program in Sciences of the University of Franca Department of Genetics Faculty of Medicine of Ribeirão Preto USP – University of São Paulo Department of Biology Faculty of Philosophy Sciences and Letters of Ribeirão Preto USP –University of São Paulo Department of Medical Genetics and Medicine Genomics University of Campinas – UNICAMP Department of Statistics Institute of Mathematics Statistics and Scientific Computing University of Campinas Department of Periodontology University of North Carolina at Chapel Hill – UNC School of Dentistry Advanced Research Center in Medicine Union of the Colleges of the Great Lakes (UNILAGO) Department of Diagnosis and Surgery School of Dentistry at Araraquara UNESP- São Paulo State University Department of Morphology Genetics Orthodontics and Pediatric Dentistry School of Dentistry at Araraquara UNESP- São Paulo State University

Molecular diagnosis is important to provide accurate genetic counseling of skeletal dysplasias (SD). Although next-generation sequencing (NGS) techniques are currently the preferred methods for analyzing these conditions, some of the published results have not shown a detection rate as high as it would be expected. The present study aimed to assess the diagnostic yield of targeted NGS combined with Sanger sequencing (SS) for low-coverage exons of genes of interest and exome sequencing (ES) in a series of patients with rare SD and use two patients as an example of our strategy. This study used two different in-house panels. Of 93 variants found in 88/114 (77%) patients, 57 are novel. The pathogenic variants found in the following genes: B3GALT6, PCYT1A, INPPL1, LIFR, of four patients were only detected by SS. In conclusion, the high diagnostic yield reached in the present study can be attributed to both a good selection of patients and the utilization of the SS for the insufficiently covered regions. Additionally, the two case reports-a patient with acrodysostosis related to PRKAR1A and another with ciliopathy associated with KIAA0753, add new and relevant clinical information to the current knowledge.

Depression is a complex and multifactorial disease, affecting about 6.5% of the elderly population in what is referred to as late-life depression (LLD). Despite its public health relevance, there is still limited information about the molecular mechanisms of LLD. We analyzed the blood plasma of 50 older adults, 19 with LLD and 31 controls, through untargeted mass spectrometry, and used systems biology tools to identify biochemical pathways and biological processes dysregulated in the disease. We found 96 differentially expressed proteins between LLD patients and control individuals. Using elastic-net regression, we generated a panel of 75 proteins that comprises a potential model for determining the molecular signature of LLD. We also showed that biological pathways related to vesicle-mediated transport and voltage-dependent calcium channels may be dysregulated in LLD. These data can help to build an understanding of the molecular basis of LLD, offering an integrated view of the biomolecular alterations that occur in this disorder. SIGNIFICANCE: Major depressive disorder in the elderly, called late-life depression (LLD), is a common and disabling disorder, with recent prevalence estimates of 6.5% in the general population. Despite the public health relevance, there is still limited information about the molecular mechanisms of LLD. The findings in this paper shed light on LLD heterogeneous biological mechanisms. We uncovered a potential novel biomolecular signature for LLD and biological pathways related to this condition which can be targets for the development of novel interventions for prevention, early diagnosis, and treatment of LLD.

Evolving in sync with the computation revolution over the past 30 years, computational biology has emerged as a mature scientific field. While the field has made major contributions toward improving scientific knowledge and human health, individual computational biology practitioners at various institutions often languish in career development. As optimistic biologists passionate about the future of our field, we propose solutions for both eager and reluctant individual scientists, institutions, publishers, funding agencies, and educators to fully embrace computational biology. We believe that in order to pave the way for the next generation of discoveries, we need to improve recognition for computational biologists and better align pathways of career success with pathways of scientific progress. With 10 outlined steps, we call on all adjacent fields to move away from the traditional individual, single-discipline investigator research model and embrace multidisciplinary, data-driven, team science., Do you want to attract computational biologists to your project or to your department? Despite the major contributions of computational biology, those attempting to bridge the interdisciplinary gap often languish in career advancement, publication, and grant review. Here, sixteen computational biologists around the globe present "A field guide to cultivating computational biology," focusing on solutions.

The development of precision medicine strategies requires prior knowledge of the genetic background of the target population. However, despite the availability of data from admixed Americans within large reference population databases, we cannot use these data as a surrogate for that of the Brazilian population. This lack of transferability is mainly due to differences between ancestry proportions of Brazilian and other admixed American populations. To address the issue, a coalition of research centres created the Brazilian Initiative on Precision Medicine (BIPMed). In this study, we aim to characterise two datasets obtained from 358 individuals from the BIPMed using two different platforms: whole-exome sequencing (WES) and a single nucleotide polymorphism (SNP) array. We estimated allele frequencies and variant pathogenicity values from the two datasets and compared our results using the BIPMed dataset with other public databases. Here, we show that the BIPMed WES dataset contains variants not included in dbSNP, including 6480 variants that have alternative allele frequencies (AAFs) >1%. Furthermore, after merging BIPMed WES and SNP array data, we identified 809,589 variants (47.5%) not present within the 1000 Genomes dataset. Our results demonstrate that, through the incorporation of Brazilian individuals into public genomic databases, BIPMed not only was able to provide valuable knowledge needed for the implementation of precision medicine but may also enhance our understanding of human genome variability and the relationship between genetic variation and disease predisposition.

We conducted a two-stage association study on patients with oropharynx (OP) squamous cell carcinoma (SCC) and healthy controls to identify single nucleotide variants (SNVs) located at the microRNA (miR)-binding sites of carcinogenesis genes associated with risk and prognosis of the disease. In stage 1, 49 patients and 49 controls were analyzed using Genome-Wide Human SNV Arrays to identify variants in the 3′-untranslated region (3′-UTR) of carcinogenesis-related genes, and one SNV was selected for data validation in stage 2 by TaqMan assays in 250 OPSCC patients and 250 controls. The ERP29 c.*293A > G (rs7114) SNV located at miR-4421 binding site was selected for data validation among 46 SNVs. The ERp29 and miR-4421 levels were evaluated by quantitative-PCR and Western blotting. Interaction between miR-4421 with 3′-UTR of ERP29 was evaluated by luciferase reporter assay. Event-free survival (EFS) was calculated by Kaplan–Meier and Cox methods. ERP29 GG variant genotype was more common in OPSCC patients than in controls (6.4% vs 3.6%, p = 0.02; odds ratio: 5.67; 95% confidence interval (CI) 1.27–25.26). Shorter EFS were seen in the base of tongue (BT) SCC patients with GG genotype (0.0% vs 36.2%, p = 0.01; hazard ratio: 2.31; 95% CI: 1.03–5.15). Individuals with ERP29 AG or GG genotypes featured lower levels of ERP29 mRNA (p = 0.005), ERp29 protein (p p = 0.02). The miR-4421 showed more efficient binding with 3′-UTR of the variant G allele when compared with wild-type allele A (p = 0.001). Our data suggest that ERP29 rs7114 SNV may alter the risk and prognosis of OPSCC due to variation in the ERp29 production possibly modulated by miR-4421.

Ultraviolet light exposure and cutaneous pigmentation are important host risk factors for cutaneous melanoma (CM), and it is well known that inherited ability to produce melanin varies in humans. The study aimed to identify single-nucleotide variants (SNVs) on pigmentation-related genes with importance in risk and clinicopathological aspects of CM. The study was conducted in two stages. In stage 1, 103 CM patients and 103 controls were analyzed using Genome-Wide Human SNV Arrays in order to identify SNVs in pigmentation-related genes, and the most important SNVs were selected for data validation in stage 2 by real-time polymerase-chain reaction in 247 CM patients and 280 controls. ADCY3 c.675+9196T>G, CREB1 c.303+373G>A, and MITF c.938-325G>A were selected for data validation among 74 SNVs. Individuals with CREB1 GA or AA genotype and allele “A” were under 1.79 and 1.47-fold increased risks of CM than others, respectively. Excesses of CREB1 AA and MITF AA genotype were seen in patients with tumors at Clark levels III to V (27.8% versus 13.7%) and at III or IV stages (46.1% versus 24.9%) compared to others, respectively. When compared to others, patients with ADCY3 TT had 1.89 more chances of presenting CM progression, and those with MITF GA or AA had 2.20 more chances of evolving to death by CM. Our data provide, for the first time, preliminary evidence that inherited abnormalities in ADCY3, CREB1, and MITF pigmentation-related genes, not only can increase the risk to CM, but also influence CM patients’ clinicopathological features.

OBJECTIVE Focal cortical dysplasias (FCDs) are an important cause of drug-resistant epilepsy. In this work, we aimed to investigate whether abnormal gene regulation, mediated by microRNA, could be involved in FCD type II. METHODS We used total RNA from the brain tissue of 16 patients with FCD type II and 28 controls. MicroRNA expression was initially assessed by microarray. Quantitative polymerase chain reaction, in situ hybridization, luciferase reporter assays, and deep sequencing for genes in the mTOR pathway were performed to validate and further explore our initial study. RESULTS hsa-let-7f (p = 0.039), hsa-miR-31 (p = 0.0078), and hsa-miR34a (p = 0.021) were downregulated in FCD type II, whereas a transcription factor involved in neuronal and glial fate specification, NEUROG2 (p

In this paper, we combine polynomial functions, Generalized Estimating Equations, and bootstrap-based model selection to test for signatures of linear or nonlinear relationships between body surface temperature and ambient temperature in endotherms. Linearity or nonlinearity is associated with the absence or presence of cutaneous vasodilation and vasoconstriction, respectively. We obtained experimental data on body surface temperature variation from a mammalian model organism as a function of ambient temperature using infrared thermal imaging. The statistical framework of model estimation and selection successfully detected linear and nonlinear relationships between body surface temperature and ambient temperature for different body regions of the model organism. These results demonstrate that our statistical approach is instrumental to assess the complexity of thermoregulation in endotherms.

Cardiovascular disease (CVD) and venous thromboembolism (VTE) figure among the main causes of morbidity and mortality in modern societies. Although associated with distinct pathogenic mechanisms, epidemiological, experimental and clinical trial data suggest that the mechanisms responsible for arterial and venous thrombosis are at least partially overlapped. Herein we aimed to explore shared and discordant pathways involved in the pathogenesis of VTE and CVD at the transcriptomic level and to validate the results in independent cohorts. Five public datasets of gene expression data from VTE and CVD (myocardial infarction, peripheral arterial occlusive disease and stroke) patients were analyzed using an integrative bioinformatic strategy. A machine/statistical learning method was used to derive classifiers for the discrimination of VTE and CVD, and tested in independent datasets. Two sets of genes that were commonly (n = 472) or divergently (n = 124) expressed in CVD and VTE were identified. Genes and pathways associated with innate immune function were over-represented in both conditions, along with pathways associated with complement and hemostasis. Pathways associated with neutrophil activation and with IL-1 signaling were also enriched in CVD compared to VTE. The gene expression signature of VTE more closely resembled the pattern of cardioembolic stroke than the patterns of acute myocardial infarction, ischemic stroke and peripheral arterial occlusive disease. Classifiers derived from these gene lists accurately discriminated patients with VTE and CVD from independent cohorts. In conclusion, our results add a new set of data at the transcriptomic level for future studies between arterial and venous thrombosis. Strengths and limitations of this study Our results represent the first comparison of venous and arterial thrombosis at the transcriptomic level. Our main result was the demonstration that immunothrombosis pathways are important to the pathophysiology of these conditions, also at the transcriptomic level. A specific signature for venous and arterial thrombosis was described, and validated in independent cohorts. The limited number of public repositories with gene expression data from patients with venous thromboembolism limits the representation of these patients in our analyses. In order to gather a meaningful number of studies with gene expression data we had to include patients in different time-points since the index thrombotic event, which might have increased the heterogeneity of our population.

For a better interpretation of variants, evidence-based databases, such as ClinVar, compile data on the presumed relationships between variants and phenotypes. In this study, we aimed to analyze the pattern of sequencing depth in variants from whole-exome sequencing data in the 1000 Genomes project phase 3, focusing on the variants present in the ClinVar database that were predicted to affect protein-coding regions. We demonstrate that the distribution of the sequencing depth varies across different sequencing centers (pair-wise comparison, p < 0.001). Most importantly, we found that the distribution pattern of sequencing depth is specific to each facility, making it possible to correctly assign 96.9% of the samples to their sequencing center. Thus, indicating the presence of a systematic bias, related to the methods used in the different facilities, which generates significant variations in breadth and depth in whole-exome sequencing data in clinically relevant regions. Our results show that methodological differences, leading to significant heterogeneity in sequencing depth, may potentially influence the accuracy of genetic diagnosis. Furthermore, our findings highlight how it is still challenging to integrate results from different sequencing centers, which may also have an impact on genomic research.

Admixed American populations have different global proportions of European, Sub-Saharan African, and Native-American ancestry. However, individuals who display the same global ancestry could exhibit remarkable differences in the distribution of local ancestry blocks. We studied for the first time the distribution of local ancestry across the genome of 264 Brazilian admixed individuals, ascertained within the scope of the Brazilian Initiative on Precision Medicine. We found a decreased proportion of European ancestry together with an excess of Native-American ancestry on chromosome 8p23.1 and showed that this is due to haplotypes created by chromosomal inversion events. Furthermore, Brazilian non-inverted haplotypes were more similar to Native-American haplotypes than to European haplotypes, in contrast to what was found in other American admixed populations. We also identified signals of recent positive selection on chromosome 8p23.1, and one gene within this locus, PPP1R3B, is related to glycogenesis and has been associated with an increased risk of type 2 diabetes and obesity. These findings point to a selection event after admixture, which is still not entirely understood in recent admixture events., This study was supported by FAPESP (Fundação de Amparo à Pesquisa do Estado de São Paulo, Brazil) grants BEPE-PD #2016/14423-9, and CEPID-BRAINN #2013/07559-3 IL-C and F.C. were also supported by grants from CNPq (Conselho Nacional de Pesquisa, Brazil). A.M.S., L.R.A. and D.C. were also supported by the Agència de Gestió d’Ajuts Universitaris i de la Recerca (Generalitat de Catalunya) grant 2014SGR866 and ‘Unidad de Excelencia María de Maeztu’ funded by MINECO (MDM-2014-0370).

Background As the most incident tumor among women worldwide, breast cancer is a heterogeneous disease. Tremendous efforts have been made to understand how tumor characteristics as histological type, molecular subtype, and tumor microenvironment collectively influence disease diagnosis to treatment, which impact outcomes. Differences between populations and environmental and cultural factors have impacts on the origin and evolution of the disease, as well as the therapeutic challenges that arise due to these factors. We, then, compared copy number variations (CNVs) in mucinous and nonmucinous luminal breast tumors from a Brazilian cohort to investigate major CNV imbalances in mucinous tumors versus non‐mucinous luminal tumors, taking into account their clinical and pathological features. Methods 48 breast tumor samples and 48 matched control blood samples from Brazilian women were assessed for CNVs by chromosome microarray. Logistic regression and random forest models were used in order to assess CNVs in chromosomal regions from tumors. Results CNVs that were identified in chromosomes 1, 5, 8, 17, 19, and 21 classify tumors according to their histological type, ethnicity, disease stage, and familial history. Conclusion Copy number alterations described in this study provide a better understanding of the landscape of genomic aberrations in mucinous breast cancers that are associated with clinical features.

Objective: We aimed to improve the classification of SCN1A missense variants in patients with Dravet syndrome (DS) by combining and modifying the current variants classification criteria to minimize inconclusive test results. Methods: We established a score classification workflow based on evidence of pathogenicity to adapt the classification of DS-related SCN1A missense variants. In addition, we compiled the variants reported in the literature and our cohort and assessed the proposed pathogenic classification criteria. We combined information regarding previously established pathogenic amino acid changes, mode of inheritance, population-specific allele frequencies, localization within protein domains, and deleterious effect prediction analysis. Results: Our meta-analysis showed that 46% (506/1,101) of DS-associated SCN1A variants are missense. We applied the score classification workflow and 56.5% (286/506) of the variants had their classification changed from VUS: 17.8% (90/506) into “pathogenic” and 38.7% (196/506) as “likely pathogenic.” Conclusion: Our results indicate that using multimodal analysis seems to be the best approach to interpret the pathogenic impact of SCN1A missense changes for the molecular diagnosis of patients with DS. By applying the proposed workflow, most DS related SCN1A variants had their classification improved.

Antipsychotics are the main line of treatment for schizophrenia. Even though there are significant rates of medication drop out due to side effects and limited response of approximately 50% of patients. This is likely due to incomplete knowledge in how these drugs act at the molecular level. To improve treatment efficacy during the critical early stages of schizophrenia, we aimed to identify molecular signatures at baseline (T0) for prediction of a positive response to the atypical antipsychotics olanzapine and risperidone after 6 weeks (T6) treatment. Blood plasma samples were processed and analyzed by label-free quantitative shotgun proteomics using two-dimensional nano-liquid chromatography, coupled online to a Synapt G2-Si mass spectrometer. Data were obtained in MSE mode (data-independent acquisition) in combination with ion-mobility (HDMSE). We were able to identify a potential panel of proteins that might predict a positive outcome to olanzapine and risperidone treatment. The proteins found to be differentially abundant between T0 and T6 in good responders compared to poor responders were analyzed in silico for enrichment pathways and found to be mostly involved with immune system functions. This data can contribute to better understand the biochemical signaling mechanisms peripherally triggered by antipsychotic medication and eventually used to develop surrogate biomarker tests to help improve treatment outcomes and guide development of new treatment approaches. Significance The application of proteomics to the study of the atypical antipsychotic effects on the blood plasma proteome from schizophrenia patients could help in the search for new targets to improve the current therapies, as well as in the development of new therapeutic strategies. In this original article, we provided clues that atypical antipsychotics might be associated with good response by modulating proteins that play a role in inflammation and/or immune system pathways. In addition, the proteins with differential abundance found in the comparison between good and poor responders at the baseline might compose a signature for prediction of response effectiveness.

Mesial temporal lobe epilepsy (MTLE) is a chronic neurological disorder affecting almost 40% of adult patients with epilepsy. Hippocampal sclerosis (HS) is a common histopathological abnormality found in patients with MTLE. HS is characterised by extensive neuronal loss in different hippocampus sub-regions. In this study, we used laser microdissection-based microproteomics to determine the protein abundances in different regions and layers of the hippocampus dentate gyrus (DG) in an electric stimulation rodent model which displays classical HS damage similar to that found in patients with MTLE. Our results indicate that there are differences in the proteomic profiles of different layers (granule cell and molecular), as well as different regions, of the DG (ventral and dorsal). We have identified new signalling pathways and proteins present in specific layers and regions of the DG, such as PARK7, RACK1, and connexin 31/gap junction. We also found two major signalling pathways that are common to all layers and regions: inflammation and energy metabolism. Finally, our results highlight the utility of high-throughput microproteomics and spatial-limited isolation of tissues in the study of complex disorders to fully appreciate the large biological heterogeneity present in different cell populations within the central nervous system.

Mesial temporal lobe epilepsy (MTLE) is the most frequent type of epilepsy in adults and it is usually refractory to clinical treatments. In most patients with MTLE a characteristic histopathological lesion is observed, including hippocampal sclerosis (HS). The subiculum is an important area which connects the hippocampus with the enthorrinal cortex. In this study aims to understand the molecular role of the subiculum in MTLE in the classical model of pilocarpine using RNA-seq (RNA sequencing)

As sequencing costs drop with the constant improvements in the field, next-generation sequencing becomes one of the most used technologies in biological research. Sequencing technology allows the detailed characterization of events at the molecular level, including gene expression, genomic sequence and structural variants. Such experiments result in billions of sequenced nucleotides and each one of them is associated to a quality score. Several software tools allow the quality assessment of whole experiments. However, users need to switch between software environments to perform all steps of data analysis, adding an extra layer of complexity to the data analysis workflow. We developed Rqc, a Bioconductor package designed to assist the analyst during assessment of high-throughput sequencing data quality. The package uses parallel computing strategies to optimize large data sets processing, regardless of the sequencing platform. We created new data quality visualization strategies by using established analytical procedures. That improves the ability of identifying patterns that may affect downstream procedures, including undesired sources technical variability. The software provides a framework for writing customized reports that integrates seamlessly to the R/Bioconductor environment, including publication-ready images. The package also offers an interactive tool to generate quality reports dynamically. Rqc is implemented in R and it is freely available through the Bioconductor project (https://bioconductor.org/packages/Rqc/) for Windows, Linux and Mac OS X operating systems.

Bioconductor is an open-source, open-development software project for the analysis and comprehension of high-throughput data in genomics and molecular biology. The project aims to enable interdisciplinary research, collaboration and rapid development of scientific software. Based on the statistical programming language R, Bioconductor comprises 934 interoperable packages contributed by a large, diverse community of scientists. Packages cover a range of bioinformatic and statistical applications. They undergo formal initial review and continuous automated testing. We present an overview for prospective users and contributors.

We report a comprehensive analysis of 412 muscle-invasive bladder cancers characterized by multiple TCGA analytical platforms. Fifty-eight genes were significantly mutated, and the overall mutational load was associated with APOBEC-signature mutagenesis. Clustering by mutation signature identified a high-mutation subset with 75% 5-year survival. mRNA expression clustering refined prior clustering analyses and identified a poor-survival "neuronal" subtype in which the majority of tumors lacked small cell or neuroendocrine histology. Clustering by mRNA, long non-coding RNA (lncRNA), and miRNA expression converged to identify subsets with differential epithelial-mesenchymal transition status, carcinoma in situ scores, histologic features, and survival. Our analyses identified 5 expression subtypes that may stratify response to different treatments.

Objectives The objective of this study was to investigate the relationship between baseline resting heart rate and incidence of heart failure (HF) and global and regional left ventricular (LV) dysfunction. Background The association of resting heart rate to HF and LV function has not been well described in an asymptomatic multi-ethnic population. Methods Resting heart rate was measured in participants in the MESA (Multi-Ethnic Study of Atherosclerosis) trial at inclusion. Incident HF was registered (n = 176) during follow-up (median 7 years) in those who underwent cardiac magnetic resonance imaging (n = 5,000). Changes in ejection fraction (ΔEF) and peak circumferential strain (Δecc) were measured as markers of developing global and regional LV dysfunction in 1,056 participants imaged at baseline and 5 years later. Time to HF (Cox model) and Δecc and ΔEF (multiple linear regression models) were adjusted for demographics, traditional cardiovascular risk factors, calcium score, LV end-diastolic volume, and mass in addition to resting heart rate. Results Cox analysis demonstrated that for 1 beat/min increase in resting heart rate, there was a 4% greater adjusted relative risk for incident HF (hazard ratio: 1.04; 95% CI: 1.02 to 1.06; p Conclusions Elevated resting heart rate was associated with increased risk for incident HF in asymptomatic participants in the MESA trial. Higher heart rate was related to development of regional and global LV dysfunction independent of subclinical atherosclerosis and coronary heart disease. (Multi-Ethnic Study of Atherosclerosis [MESA]; NCT00005487 )

Lung cancer is one of the most frequent types of cancer worldwide. Most patients are diagnosed at advanced stage and thus have poor prognosis. Smoking is a risk factor for lung cancer, however most smokers do not develop lung cancer while 20% of women with lung adenocarcinoma are non-smokers. Therefore, it is possible that these two groups present differences besides the smoking status, including differences in their gene expression signature. The altered expression patterns of non-coding RNAs in complex diseases make them potential biomarkers for diagnosis and treatment. We analyzed data from differentially and constitutively expressed PIWI-interacting RNAs and small nucleolar RNAs from publicly available small RNA high-throughput sequencing data in search of an expression pattern of non-coding RNA that could differentiate these two groups. Here, we report two sets of differentially expressed small non-coding RNAs identified in normal and tumoral tissues of women with lung adenocarcinoma, that discriminate between smokers and non-smokers. Our findings may offer new insights on metabolic alterations caused by tobacco and may be used for early diagnosis of lung cancer.

Epilepsy is misdiagnosed in up to 25% of patients, leading to serious and long-lasting consequences. Recently, circulating microRNAs have emerged as potential biomarkers in a number of clinical scenarios. The purpose of this study was to identify and to validate circulating microRNAs that could be used as biomarkers in the diagnosis of epilepsy. Quantitative real-time PCR was used to measure plasma levels of three candidate microRNAs in two phases of study: an initial discovery phase with 14 patients with mesial temporal lobe epilepsy (MTLE), 13 with focal cortical dysplasia (FCD) and 16 controls; and a validation cohort constituted of an independent cohort of 65 patients with MTLE and 83 controls. We found hsa-miR-134 downregulated in patients with MTLE (p = 0.018) but not in patients with FCD, when compared to controls. Furthermore, hsa-miR-134 expression could be used to discriminate MTLE patients with an area under the curve (AUC) of 0.75. To further assess the robustness of hsa-miR-134 as a biomarker for MTLE, we studied an independent cohort of 65 patients with MTLE, 27 of whom MTLE patients were responsive to pharmacotherapy, and 38 patients were pharmacoresistant and 83 controls. We confirmed that hsa-miR-134 was significantly downregulated in the plasma of patients with MTLE when compared with controls (p < 0.001). In addition, hsa-miR-134 identified patients with MTLE regardless of their response to pharmacotherapy or the presence of MRI signs of hippocampal sclerosis. We revealed that decreased expression of hsa-miR-134 could be a potential non-invasive biomarker to support the diagnosis of patients with MTLE.

Preprocessing microarray data consists of a number of statistical procedures that convert the observed intensities into quantities that represent biological events of interest, like gene expression and allele-specific abundances. Here, we present a summary of the theory behind microarray data preprocessing for expression, whole transcriptome and SNP designs and focus on the computational protocol used to obtain processed data that will be used on downstream analyses. We describe the main features of the oligo Bioconductor package, an application designed to support oligonucleotide microarrays using the R statistical environment and the infrastructure provided by Bioconductor, allowing the researcher to handle probe-level data and interface with advanced statistical tools under a simplified framework. We demonstrate the use of the package by preprocessing data originated from three different designs.

Introduction Skeletal muscle microRNAs (miRNAs) are potential candidate biomarkers for amyotrophic lateral sclerosis (ALS) that deserve further investigation. Objectives To identify miRNAs abnormally expressed in the skeletal muscle and plasma of patients with ALS, and to correlate them with parameters of disease progression. Methods Expression profile of miRNAs in muscle was evaluated using an array platform. Subsequently we assessed the plasmatic expression of candidate miRNAs in a set of 39 patients/39 controls. We employed generalized estimating equations to investigate correlations with clinical data. Results We identified 11 miRNAs differentially expressed in the muscle of ALS patients; of these, miR424, miR-214 and miR-206 were validated by qPCR in muscle samples. In plasma, we found only miR-424 and miR 206 to be overexpressed. Baseline expression of miR-424 and 206 correlated with clinical deterioration over time. Conclusion MiR-424 and miR-206 are potential prognostic markers for ALS.

We report here the first complete transcriptome analysis of the dorsal (dDG) and ventral dentate gyrus (vDG) of a rat epilepsy model presenting a hippocampal lesion with a strict resemblance to classical hippocampal sclerosis (HS). We collected the dDG and vDG by laser microdissection 15 days after electrical stimulation and performed high-throughput RNA-sequencing. There were many differentially regulated genes, some of which were specific to either of the two sub-regions in stimulated animals. Gene ontology analysis indicated an enrichment of inflammation-related processes in both sub-regions and of axonal guidance and calcium signaling processes exclusively in the vDG. There was also a differential regulation of genes encoding molecules involved in synaptic function, neural electrical activity and neuropeptides in stimulated rats. The data presented here suggests, in the time point analyzed, a remarkable interaction among several molecular components which takes place in the damaged hippocampi. Furthermore, even though similar mechanisms may function in different regions of the DG, the molecular components involved seem to be region specific.

Background: The formation of thrombi inside arteries and veins is a process that underlies the pathogenesis of the most important causes of morbidity and mortality in the modern world: namely cardiovascular diseases (CVD), a term encompassing acute myocardial infarction (AMI), ischemic stroke (IS) and peripheral arterial occlusive disease (PAOD); and venous thromboembolism (VTE). So far, the discussion on how much CVD and VTE share and differ in terms of pathological mechanisms has been based on morphological studies about the composition of venous and arterial thrombi, epidemiological studies about the association and common risk factors of CVD and VTE, and inferences upon the cellular and molecular mechanisms of each of these conditions. Objective: Here we introduce a new strategy to obtain insights on the association of CVD and VTE based on the comparison of transcriptomic signatures associated with these conditions. Methods: publicly available datasets (from Gene Expression Omnibus Database) of gene expression data from patients with AMI, IS, PAOD, cardioembolic stroke (CS), and VTE were identified and retrieved. Stringent selection criteria regarding patient selection, microarray methods and RNA sources were applied to limit heterogeneity as much as possible. A meta-analysis was performed using a robust statistical method, allowing the identification of genes that are commonly expressed in the same direction in all five conditions. We also identified a list of genes that were divergently expressed between VTE and CVD. Both lists were then used for functional and correlation analyses aimed to gain additional insights on the molecular pathogenesis of arterial and venous thrombosis. Results: Five datasets fulfilled the inclusion criteria and were included in our analyses: the dataset of VTE patients originally compared gene expression levels in patients with single or recurrent VTE with healthy controls (GSE19151); three datasets involving CVD compared gene expression levels of patients with PAOD (GSE 27034), AMI (GSE 48060) and IS (GSE 22255) with study-specific healthy controls. A dataset comparing patients with CS (GSE58294) and healthy controls was also included. In total, data from 163 adult patients and 145 healthy controls were analyzed. The meta-analysis generated a list of 473 genes whose expression was changed in the same direction in all five conditions (168 up-regulated and 305 down-regulated). The top 20 up- and down-regulated genes are shown in figure 1a. The functional analysis of the 168 up-regulated genes identified pathways associated with hemostasis, innate immunity and neutrophil activation and degranulation as overrepresented in patients compared to controls. When gene expression fold-change levels were analyzed across all five diseases, a lower correlation coefficient was observed between VTE and CVD, when compared to correlations observed within CVD such as AMI and PAOD (fig.1b). Moreover, an unsupervised cluster analysis showed that the expression pattern of these 473 genes in AMI, PAOD and IS are more closely related to each other than to VTE and CS (fig. 1a). When the 124 genes that were divergently expressed between VTE and CVD were functionally analyzed, genes that were upregulated only in CVD were associated with activation of innate immunity, whereas genes that were upregulated in VTE were associated with cell maintenance pathways. Discussion and conclusion: our comparative analyses provide new data on how venous and arterial thrombosis differ at a transcriptional level. Specifically, we identified a set of 473 genes whose expression levels were consistently changed in both CVD and VTE, and 124 genes with divergent expression levels between these conditions. The prominence of pathways associated with hemostasis, innate immunity and neutrophil function in both CVD and VTE are in line with the concept of immunothrombosis in the pathogenesis of thrombotic disorders. The clustering of MI, IS and PAOD compared to VTE and CS is coherent with the concept that CS is caused by thrombi formed in a different microenvironment than IS. Additional studies are warranted on the role of these genes and pathways in the pathogenesis of CVD and VTE, as well as on the biological relevance of these thrombosis-specific gene expression signatures in other thrombotic disorders. Disclosures De Paula: Hematology and Transfusion Medicine Center, University of Campinas: Employment.

We briefly review some principles of the Bioconductor project for statistical analysis of genome scale data and show in detail how these are deployed to analyze high-density genotyping arrays manufactured by Affymetrix, Inc. (Genome-wide SNP 6.0). Issues addressed include probe design and verification of probe address assertions, preprocessing of scanned intensities via SNPRMA, genotype calling via CRLMM, and downstream analysis of genotype-expression associations.

SNP arrays offer the opportunity to get a genome-wide view on copy number alterations and are increasingly used in oncology. DNA from formalin-fixed paraffin-embedded material (FFPE) is partially degraded which limits the application of those technologies for retrospective studies. We present the use of Affymetrix GeneChip SNP6.0 for identification of copy number alterations in fresh frozen (FF) and matched FFPE samples. Fifteen pairs of adenocarcinomas with both frozen and FFPE embedded material were analyzed. We present an optimization of the sample preparation and show the importance of correcting the measured intensities for fragment length and GC-content when using FFPE samples. The absence of GC content correction results in a chromosome specific "wave pattern" which may lead to the misclassification of genomic regions as being altered. The highest concordance between FFPE and matched FF were found in samples with the highest call rates. Nineteen of the 23 high level amplifications (83%) seen using FF samples were also detected in the corresponding FFPE material. For limiting the rate of "false positive" alterations, we have chosen a conservative False Discovery Rate (FDR). We observed better results using SNP probes than CNV probes for copy number analysis of FFPE material. This is the first report on the detection of copy number alterations in FFPE samples using Affymetrix GeneChip SNP6.0.

This study was originally conceived to test in a rigorous way the specificity of three major approaches to high-throughput array-based DNA methylation analysis: (1) MeDIP, or methylated DNA immunoprecipitation, an example of antibody-mediated methyl-specific fractionation; (2) HELP, or HpaII tiny fragment enrichment by ligation-mediated PCR, an example of differential amplification of methylated DNA; and (3) fractionation by McrBC, an enzyme that cuts most methylated DNA. These results were validated using 1466 Illumina methylation probes on the GoldenGate methylation assay and further resolved discrepancies among the methods through quantitative methylation pyrosequencing analysis. While all three methods provide useful information, there were significant limitations to each, specifically bias toward CpG islands in MeDIP, relatively incomplete coverage in HELP, and location imprecision in McrBC. However, we found that with an original array design strategy using tiling arrays and statistical procedures that average information from neighboring genomic locations, much improved specificity and sensitivity could be achieved, e.g., ∼100% sensitivity at 90% specificity with McrBC. We term this approach “comprehensive high-throughput arrays for relative methylation” (CHARM). While this approach was applied to McrBC analysis, the array design and computational algorithms are fractionation method-independent and make this a simple, general, relatively inexpensive tool suitable for genome-wide analysis, and in which individual samples can be assayed reliably at very high density, allowing locus-level genome-wide epigenetic discrimination of individuals, not just groups of samples. Furthermore, unlike the other approaches, CHARM is highly quantitative, a substantial advantage in application to the study of human disease.

Preprocessing microarray data consists of a number of statistical procedures that convert the observed intensities into quantities that represent biological events of interest, like gene expression and allele-specific abundances. Here, we present a summary of the theory behind microarray data preprocessing for expression, whole transcriptome and SNP designs and focus on the computational protocol used to obtain processed data that will be used on downstream analyses. We describe the main features of the oligo Bioconductor package, an application designed to support oligonucleotide microarrays using the R statistical environment and the infrastructure provided by Bioconductor, allowing the researcher to handle probe-level data and interface with advanced statistical tools under a simplified framework. We demonstrate the use of the package by preprocessing data originated from three different designs.

Ce rapport presente les resultats d’une etude approfondie consacree a la reussite des etudiants de premier cycle admis a l’Universite d’Etat de Campinas (Unicamp), au Bresil, de 1994 a 1997, au regard de leur milieu socio-economique d’origine et de leur parcours scolaire. Cette etude repose sur la modelisation hierarchique des differentes variables a l’œuvre. Il ressort principalement de cette analyse que les etudiants issus de milieux defavorises, tant sur le plan educatif que socio-economique, affichent une meilleure performance relative que les autres. Nous analysons par ailleurs la politique de discrimination positive mise en œuvre a Unicamp dans le cadre des admissions en premier cycle – sous l’impulsion de cette decouverte, notamment – et presentons ensuite certaines donnees probantes issues d’une premiere evaluation de l’impact de cette politique. Nous formulons enfin une serie de remarques concernant les repercussions de l’etude, et du programme mis en œuvre par la suite a Unicamp, sur le debat actuel entourant le bien-fonde des politiques de discrimination positive facilitant l’acces aux etablissements d’enseignement superieur bresiliens.