Search

Human variant databases could be better exploited if the variant data available in multiple resources is integrated in a single comprehensive resource along with sequence and structural features. Such integration would improve the analyses of variants for disease prediction, prevention or treatment. The HuVarBase (HUmanVARiantdataBASE) assimilates publicly available human variant data at protein level and gene level into a comprehensive resource. Protein level data such as amino acid sequence, secondary structure of the mutant residue, domain, function, subcellular location and post-translational modification are integrated with gene level data such as gene name, chromosome number & genome position, DNA mutation, mutation type origin and rs ID number. Disease class has been added for the disease causing variants. The database is publicly available at https://www.iitm.ac.in/bioinfo/huvarbase. A total of 774,863 variant records, integrated in the HuVarBase, can be searched with options to display, visualize and download the results.

PURPOSE: As atherosclerotic plaque ruptures are the primary cause of ischaemic events, their preventive identification by imaging remains a clinical challenge. Matrix metalloproteinases (MMP) are involved in plaque progression and destabilisation and are therefore promising targets to characterize rupture-prone unstable plaques. This study aims at evaluating MMP imaging to discriminate unstable from stable plaque phenotypes. METHODS: ApoE deficient mice (ApoE-/-) on a high cholesterol diet underwent implantation of a tapered cuff around the right common carotid artery (CCA) inducing a highly inflamed atherosclerotic plaque upstream (US) and a more stable plaque phenotype downstream (DS) of the cuff. 8 weeks after surgery, the MMP inhibitor-based photoprobe Cy5.5-AF443 was administered i.v. 3h prior to in situ and ex vivo fluorescence reflectance imaging of the CCAs. Thereafter, CCAs were analysed regarding plaque size, presence of macrophages, and MMP-2 and MMP-9 concentrations by immunohistochemistry and ELISA. RESULTS: We found a significantly higher uptake of Cy5.5-AF443 in US as compared to DS plaques in situ (1.29 vs. 1.06 plaque-to-background ratio; p

Objectives Sleep-wake disturbances (SWD) are frequent in Parkinson’s disease (PD). The effect of deep brain stimulation (DBS) on SWD is poorly known. In this study we examined the subjective and objective sleep-wake profile and the quality of life (QoL) of PD patients in the context of subthalamic DBS. Patients and methods We retrospectively analyzed data from PD patients and candidates for DBS in the nucleus suthalamicus (STN). Pre-DBS, sleep-wake assessments included subjective and objective (polysomnography, vigilance tests and actigraphy) measures. Post-DBS, subjective measures were collected. QoL was assessed using the Parkinson’s Disease Questionnaire (PDQ-39) and the RAND SF-36-item Health Survey (RAND SF-36). Results Data from 74 PD patients (62% male, mean age 62.2 years, SD = 8.9) with a mean UPDRS-III (OFF) of 34.2 (SD = 14.8) and 11.8 (SD = 4.5) years under PD treatment were analyzed. Pre-DBS, daytime sleepiness, apathy, fatigue and depressive symptoms were present in 49%, 34%, 38% and 25% of patients respectively but not always as co-occurring symptoms. Sleep-wake disturbances were significantly correlated with QoL scores. One year after STN DBS, motor signs, QoL and sleepiness improved but apathy worsened. Changes in QoL were associated with changes in sleepiness and apathy but baseline sleep-wake functions were not predictive of STN DBS outcome. Conclusion In PD patients presenting for STN DBS, subjective and objective sleep-wake disturbances are common and have a negative impact on QoL before and after neurosurgery. Given the current preliminary evidence, prospective observational studies assessing subjective and objective sleep-wake variables prior to and after DBS are needed.

Endothelial barriers have a central role in inflammation as they allow or deny the passage of leukocytes from the vasculature into the tissue. To bind leukocytes, endothelial cells form adhesive clusters containing tetraspanins and ICAM-1, so-called endothelial adhesive platforms (EAPs). Upon leukocyte binding, EAPs evolve into docking structures that emanate from the endothelial surface while engulfing the leukocyte. Here, we show that TNF-α is sufficient to induce apical protrusions in the absence of leukocytes. Using advanced quantitation of atomic force microscopy (AFM) recordings, we found these structures to protrude by 160 ± 80 nm above endothelial surface level. Confocal immunofluorescence microscopy proved them positive for ICAM-1, JAM-A, tetraspanin CD9 and f-actin. Microvilli formation was inhibited in the absence of CD9. Our findings indicate that stimulation with TNF-α induces nanoscale changes in endothelial surface architecture and that--via a tetraspanin CD9 depending mechanism--the EAPs rise above the surface to facilitate leukocyte capture.

Background The Cancer Genome Atlas Project (TCGA) is a National Cancer Institute effort to profile at least 500 cases of 20 different tumor types using genomic platforms and to make these data, both raw and processed, available to all researchers. TCGA data are currently over 1.2 Petabyte in size and include whole genome sequence (WGS), whole exome sequence, methylation, RNA expression, proteomic, and clinical datasets. Publicly accessible TCGA data are released through public portals, but many challenges exist in navigating and using data obtained from these sites. We developed TCGA Expedition to support the research community focused on computational methods for cancer research. Data obtained, versioned, and archived using TCGA Expedition supports command line access at high-performance computing facilities as well as some functionality with third party tools. For a subset of TCGA data collected at University of Pittsburgh, we also re-associate TCGA data with de-identified data from the electronic health records. Here we describe the software as well as the architecture of our repository, methods for loading of TCGA data to multiple platforms, and security and regulatory controls that conform to federal best practices. Results TCGA Expedition software consists of a set of scripts written in Bash, Python and Java that download, extract, harmonize, version and store all TCGA data and metadata. The software generates a versioned, participant- and sample-centered, local TCGA data directory with metadata structures that directly reference the local data files as well as the original data files. The software supports flexible searches of the data via a web portal, user-centric data tracking tools, and data provenance tools. Using this software, we created a collaborative repository, the Pittsburgh Genome Resource Repository (PGRR) that enabled investigators at our institution to work with all TCGA data formats, and to interrogate these data with analysis pipelines, and associated tools. WGS data are especially challenging for individual investigators to use, due to issues with downloading, storage, and processing; having locally accessible WGS BAM files has proven invaluable. Conclusion Our open-source, freely available TCGA Expedition software can be used to create a local collaborative infrastructure for acquiring, managing, and analyzing TCGA data and other large public datasets.

Late onset Alzheimer's disease (LOAD) is a genetically complex and clinically heterogeneous disease. Recent large-scale genome wide association studies (GWAS) have identified more than twenty loci that modify risk for AD. Despite the identification of these loci, little progress has been made in identifying the functional variants that explain the association with AD risk. Thus, we sought to determine whether the novel LOAD GWAS single nucleotide polymorphisms (SNPs) alter expression of LOAD GWAS genes and whether expression of these genes is altered in AD brains. The majority of LOAD GWAS SNPs occur in gene dense regions under large linkage disequilibrium (LD) blocks, making it unclear which gene(s) are modified by the SNP. Thus, we tested for brain expression quantitative trait loci (eQTLs) between LOAD GWAS SNPs and SNPs in high LD with the LOAD GWAS SNPs in all of the genes within the GWAS loci. We found a significant eQTL between rs1476679 and PILRB and GATS, which occurs within the ZCWPW1 locus. PILRB and GATS expression levels, within the ZCWPW1 locus, were also associated with AD status. Rs7120548 was associated with MTCH2 expression, which occurs within the CELF1 locus. Additionally, expression of several genes within the CELF1 locus, including MTCH2, were highly correlated with one another and were associated with AD status. We further demonstrate that PILRB, as well as other genes within the GWAS loci, are most highly expressed in microglia. These findings together with the function of PILRB as a DAP12 receptor supports the critical role of microglia and neuroinflammation in AD risk.

During apoptosis the pro-death Bcl-2 family members Bax and Bak induce mitochondrial outer membrane permeabilization (MOMP) to mediate cell death. Recently, it was shown that Bax and Bak are also required for mitochondrial permeability transition pore (MPTP)-dependent necrosis, where, in their non-oligomeric state, they enhance permeability characteristics of the outer mitochondrial membrane. Necroptosis is another form of regulated necrosis involving the death receptors and receptor interacting protein kinases (RIP proteins, by Ripk genes). Here, we show cells or mice deficient for Bax/Bak or cyclophilin D, a protein that regulates MPTP opening, are resistant to cell death induced by necroptotic mediators. We show that Bax/Bak oligomerization is required for necroptotic cell death and that this oligomerization reinforces MPTP opening. Mechanistically, we observe mixed lineage kinase domain-like (MLKL) protein and cofilin-1 translocation to the mitochondria following necroptosis induction, while expression of the mitochondrial matrix isoform of the antiapoptotic Bcl-2 family member, myeloid cell leukemia 1 (Mcl-1), is significantly reduced. Some of these effects are lost with necroptosis inhibition in Bax/Bak1 double null, Ppif-/-, or Ripk3-/- fibroblasts. Hence, downstream mechanisms of cell death induced by necroptotic stimuli utilize both Bax/Bak to generate apoptotic pores in the outer mitochondrial membrane as well as MPTP opening in association with known mitochondrial death modifying proteins.

Epidemiological and genetic studies suggest that schizophrenia and autism may share genetic links. Besides common single nucleotide polymorphisms, recent data suggest that some rare copy number variants (CNVs) are risk factors for both disorders. Because we have previously found that schizophrenia and psychosis in Alzheimer's disease (AD+P) share some genetic risk, we investigated whether CNVs reported in schizophrenia and autism are also linked to AD+P. We searched for CNVs associated with AD+P in 7 recurrent CNV regions that have been previously identified across autism and schizophrenia, using the Illumina HumanOmni1-Quad BeadChip. A chromosome 16p11.2 duplication CNV (chr16: 29,554,843-30,105,652) was identified in 2 of 440 AD+P subjects, but not in 136 AD subjects without psychosis, or in 593 AD subjects with intermediate psychosis status, or in 855 non-AD individuals. The frequency of this duplication CNV in AD+P (0.46%) was similar to that reported previously in schizophrenia (0.46%). This duplication CNV was further validated using the NanoString nCounter CNV Custom CodeSets. The 16p11.2 duplication has been associated with developmental delay, intellectual disability, behavioral problems, autism, schizophrenia (SCZ), and bipolar disorder. These two AD+P patients had no personal of, nor any identified family history of, SCZ, bipolar disorder and autism. To the best of our knowledge, our case report is the first suggestion that 16p11.2 duplication is also linked to AD+P. Although rare, this CNV may have an important role in the development of psychosis.

Late-onset Alzheimer's disease (LOAD) is a multifactorial disorder with over twenty loci associated with disease risk. Given the number of genome-wide significant variants that fall outside of coding regions, it is possible that some of these variants alter some function of gene expression rather than tagging coding variants that alter protein structure and/or function. RegulomeDB is a database that annotates regulatory functions of genetic variants. In this study, we utilized RegulomeDB to investigate potential regulatory functions of lead single nucleotide polymorphisms (SNPs) identified in five genome-wide association studies (GWAS) of risk and age-at onset (AAO) of LOAD, as well as SNPs in LD (r2≥0.80) with the lead GWAS SNPs. Of a total 614 SNPs examined, 394 returned RegulomeDB scores of 1–6. Of those 394 variants, 34 showed strong evidence of regulatory function (RegulomeDB score

Protein-RNA complexes play key roles in several cellular processes by the interactions of amino acids with RNA. To understand the recognition mechanism, it is important to identify the specific amino acids involved in RNA binding. Various computational methods have been developed for predicting RNA binding residues from protein sequence. However, their performances mainly depend on the training dataset, feature selection for developing a model and learning capacity of the model. Hence, it is important to reveal the correspondence between the performance of methods and properties of RNA-binding proteins (RBPs). In this work, we have collected all available RNA binding residues prediction methods and revealed their performances on unbiased, stringent and diverse datasets for RBPs with less than 25% sequence identity based on structural class, fold, superfamily, family, protein function, RNA type, RNA strand and RNA conformation. The best methods for each type of RBPs and the type of RBPs, which require further refinement in prediction, have been brought out. We also analyzed the performance of these methods for the disordered regions, structures which are not included in the training dataset and recently solved structures. The reliability of prediction is better than randomly choosing any method or combination of methods. This approach would be a valuable resource for biologists to choose the best method based on the type of RBPs for designing their experiments and the tool is freely accessible online at www.iitm.ac.in/bioinfo/RNA-protein/.

Accurate distinction between peptide sequences that can form amyloid-fibrils or amorphous β-aggregates, identification of potential aggregation prone regions in proteins, and prediction of change in aggregation rate of a protein upon mutation(s) are critical to research on protein misfolding diseases, such as Alzheimer's and Parkinson's, as well as biotechnological production of protein based therapeutics. We have developed a Curated Protein Aggregation Database (CPAD), which has collected results from experimental studies performed by scientific community aimed at understanding protein/peptide aggregation. CPAD contains more than 2300 experimentally observed aggregation rates upon mutations in known amyloidogenic proteins. Each entry includes numerical values for the following parameters: change in rate of aggregation as measured by fluorescence intensity or turbidity, name and source of the protein, Uniprot and Protein Data Bank codes, single point as well as multiple mutations, and literature citation. The data in CPAD has been supplemented with five different types of additional information: (i) Amyloid fibril forming hexa-peptides, (ii) Amorphous β-aggregating hexa-peptides, (iii) Amyloid fibril forming peptides of different lengths, (iv) Amyloid fibril forming hexa-peptides whose crystal structures are available in the Protein Data Bank (PDB) and (v) Experimentally validated aggregation prone regions found in amyloidogenic proteins. Furthermore, CPAD is linked to other related databases and resources, such as Uniprot, Protein Data Bank, PUBMED, GAP, TANGO, WALTZ etc. We have set up a web interface with different search and display options so that users have the ability to get the data in multiple ways. CPAD is freely available at http://www.iitm.ac.in/bioinfo/CPAD/. The potential applications of CPAD have also been discussed.

Background: A genome-wide association study (GWAS) typically involves examining representative SNPs in individuals from some population. A GWAS data set can concern a million SNPs and may soon concern billions. Researchers investigate the association of each SNP individually with a disease, and it is becoming increasingly commonplace to also analyze multi-SNP associations. Techniques for handling so many hypotheses include the Bonferroni correction and recently developed Bayesian methods. These methods can encounter problems. Most importantly, they are not applicable to a complex multilocus hypothesis which has several competing hypotheses rather than only a null hypothesis. A method that computes the posterior probability of complex hypotheses is a pressing need. Methodology/Findings: We introduce the Bayesian network posterior probability (BNPP) method which addresses the difficulties. The method represents the relationship between a disease and SNPs using a directed acyclic graph (DAG) model, and computes the likelihood of such models using a Bayesian network scoring criterion. The posterior probability of a hypothesis is computed based on the likelihoods of all competing hypotheses. The BNPP can not only be used to evaluate a hypothesis that has previously been discovered or suspected, but also to discover new disease loci associations. The results of experiments using simulated and real data sets are presented. Our results concerning simulated data sets indicate that the BNPP exhibits both better evaluation and discovery performance than does a p-value based method. For the real data sets, previous findings in the literature are confirmed and additional findings are found. Conclusions/Significance: We conclude that the BNPP resolves a pressing problem by providing a way to compute the posterior probability of complex multi-locus hypotheses. A researcher can use the BNPP to determine the expected utility of investigating a hypothesis further. Furthermore, we conclude that the BNPP is a promising method for discovering disease loci associations.

Next Generation Sequencing (NGS) methods are driving profound changes in biomedical research, with a growing impact on patient care. Many academic medical centers are evaluating potential models to prepare for the rapid increase in NGS information needs. This study sought to investigate (1) how and where sequencing data is generated and analyzed, (2) research objectives and goals for NGS, (3) workforce capacity and unmet needs, (4) storage capacity and unmet needs, (5) available and anticipated funding resources, and (6) future challenges. As a precursor to informed decision making at our institution, we undertook a systematic needs assessment of investigators using survey methods. We recruited 331 investigators from over 60 departments and divisions at the University of Pittsburgh Schools of Health Sciences and had 140 respondents, or a 42% response rate. Results suggest that both sequencing and analysis bottlenecks currently exist. Significant educational needs were identified, including both investigator-focused needs, such as selection of NGS methods suitable for specific research objectives, and program-focused needs, such as support for training an analytic workforce. The absence of centralized infrastructure was identified as an important institutional gap. Key principles for organizations managing this change were formulated based on the survey responses. This needs assessment provides an in-depth case study which may be useful to other academic medical centers as they identify and plan for future needs.

Although common APOE genetic variation has a major influence on plasma LDL-cholesterol, its role in affecting HDL-cholesterol and triglycerides is not well established. Recent genome-wide association studies suggest that APOE also affects plasma variation in HDL-cholesterol and triglycerides. It is thus important to resequence the APOE gene to identify both common and uncommon variants that affect plasma lipid profile. Here, we have sequenced the APOE gene in 190 subjects with extreme HDL-cholesterol levels selected from two well-defined epidemiological samples of U.S. non-Hispanic Whites (NHWs) and African Blacks followed by genotyping of identified variants in the entire datasets (623 NHWs, 788 African Blacks) and association analyses with major lipid traits. We identified a total of 40 sequence variants, of which 10 are novel. A total of 32 variants, including common tagSNPs (≥5% frequency) and all uncommon variants (

Escherichia coli and other enteric bacteria survive exposure to extreme acid (pH 2 or lower) in gastric fluid. Aerated cultures survive via regulons expressing glutamate decarboxylase (Gad, activated by RpoS), cyclopropane fatty acid synthase (Cfa) and others. But extreme-acid survival is rarely tested under low oxygen, a condition found in the stomach and the intestinal tract. We observed survival of E. coli K-12 W3110 at pH 1.2-pH 2.0, conducting all manipulations (overnight culture at pH 5.5, extreme-acid exposure, dilution and plating) in a glove box excluding oxygen (10% H2, 5% CO2, balance N2). With dissolved O2 concentrations maintained below 6 µM, survival at pH 2 required Cfa but did not require GadC, RpoS, or hydrogenases. Extreme-acid survival in broth (containing tryptone and yeast extract) was diminished in media that had been autoclaved compared to media that had been filtered. The effect of autoclaved media on extreme-acid survival was most pronounced when oxygen was excluded. Exposure to H2O2 during extreme-acid treatment increased the death rate slightly for W3110 and to a greater extent for the rpoS deletion strain. Survival at pH 2 was increased in strains lacking the anaerobic regulator fnr. During anaerobic growth at pH 5.5, strains deleted for fnr showed enhanced transcription of acid-survival genes gadB, cfa, and hdeA, as well as catalase (katE). We show that E. coli cultured under oxygen exclusion (

Background: The complex interactions between recurrent trypsin-mediated pancreatic injury, alcohol-associated pancreatic injury and SPINK1 polymorphisms in chronic pancreatitis (CP) are undefined. We hypothesize that CP occurs as a result of multiple pathological mechanisms (pathways) that are initiated by different metabolic or environmental factors (etiologies) and may be influenced differentially by downstream genetic risk factors. We tested this hypothesis by evaluating the differences in effect size of the high risk SPINK1 N34S haplotype on CP from multiple etiologies after combining clinical reports of SPINK1 N34S frequency using meta-analysis. Methods and Findings: The Pubmed and the Embase databases were reviewed. We studied 24 reports of SPINK1 N34S in CP (2,421 cases, 4,857 controls) using reported etiological factors as surrogates for pathways and multiple meta-analyses to determine the differential effects of SPINK1 N34S between alcoholic and non-alcoholic etiologies. Using estimates of between-study heterogeneity, we sub-classified our 24 studies into four specific clusters. We found that SPINK1 N34S is strongly associated with CP overall (OR 11.00; 95% CI: 7.59-15.93), but the effect of SPINK1 N34S in alcoholic CP (OR 4.98, 95% CI: 3.16-7.85) was significantly smaller than in idiopathic CP (OR 14.97, 95% C.I. = 9.09-24.67) or tropical CP (OR 19.15, 95% C.I. = 8.83-41.56). Studies analyzing familial CP showed very high heterogeneity suggestive of a complex etiology with an I2 = 80.95%. Conclusion: The small effect of SPINK1 N34S in alcoholic subjects suggests that CP is driven through a different pathway that is largely trypsin-independent. The results also suggest that large effect sizes of SPINK1 N34S in small candidate gene studies in CP may be related to a mixture of multiple etiologic pathways leading to the same clinical endpoint. © 2008 Aoun MD et al.

Low success (