While indicated for schizophrenia and acute mania, ziprasidone’s evidence base and use in clinical practice extends beyond these regulatory approvals. We, an invited panel of experts led by a working group of 3, critically examined the evidence and our collective experience regarding the effectiveness, tolerability and safety of ziprasidone across its clinical uses. There was no opportunity for manufacturer input into the content of the review. As anticipated, ziprasidone was found to be effective for its indicated uses, although its utility in mania and mixed states lacked comparative data. Beyond these uses, the available data were either unimpressive or were lacking. An attractive characteristic is its neutral effect on weight thereby providing patients with a non-obesogenic long-term treatment option. Key challenges in practice include the need for dosing on a full stomach and managing its early onset adverse effect of restlessness. Addressing these issues are critical to its long-term success

The Gene Ontology (GO) is the de facto standard for the functional description of gene products, providing a consistent, information-rich terminology applicable across species and information repositories. The UniProt Consortium uses both manual and automatic GO annotation approaches to curate UniProt Knowledgebase (UniProtKB) entries. The selection of a protein set prioritized for manual annotation has implications for the characteristics of the information provided to users working in a specific field or interested in particular pathways or processes. In this article, we describe an organelle-focused, manual curation initiative targeting proteins from the human peroxisome. We discuss the steps taken to define the peroxisome proteome and the challenges encountered in defining the boundaries of this protein set. We illustrate with the use of examples how GO annotations now capture cell and tissue type information and the advantages that such an annotation approach provides to users.

Database URL: http://www.ebi.ac.uk/GOA/ and http://www.uniprot.org

Objective

Several studies have reported higher prevalence of obesity in patients suffering from bipolar disorder (BD). To study the relation of elevated body mass index (BMI) in patients with BD more closely, we investigated differences in sociodemographic, clinical, and medical characteristics with respect to BMI, with the hypothesis that BMI is related to prognosis and outcome.

Methods

We measured the BMI of 276 subjects of a tertiary care sample from the Maritime Bipolar Registry. Subjects were 16 to 83 years old, with psychiatric diagnoses of bipolar I disorder (n = 186), bipolar II disorder (n = 85), and BD not otherwise specified (n = 5). The registry included basic demographic data and details of the clinical presentation. We first examined the variables showing a significant association with BMI; subsequently, we modeled the relationship between BMI and psychiatric outcome using structural equation analysis.

Results

The prevalence of obesity in our sample was 39.1%. We found higher BMI in subjects with a chronic course (p < 0.001) and longer duration of illness (p = 0.02), lower scores on the Global Assessment of Functioning Scale (p = 0.02), and on disability (p = 0.002). Overweight patients had more frequent comorbid subthreshold social (p = 0.02) and generalized anxiety disorders (p = 0.05), diabetes mellitus type II (p < 0.001), and hypertension (p = 0.001). Subjects who achieved complete remission of symptoms on lithium showed significantly lower BMI (p = 0.01).

Conclusions

Our findings suggest that BMI is associated with the prognosis and outcome of BD. Whether this association is causal remains to be determined.

Objective

Hippocampal volume decrease associated with illness burden is among the most replicated findings in unipolar depression. The absence of hippocampal volume changes in most studies of individuals with bipolar disorder (BD) may reflect neuroprotective effects of lithium (Li).

Methods

We recruited 17 BD patients from specialized Li clinics, with at least two years of regularly monitored Li treatment (Li group), and compared them to 12 BD participants with < 3 months of lifetime Li exposure and no Li treatment within two years prior to the scanning (non-Li group) and 11 healthy controls. All BD patients had at least 10 years of illness and five episodes. We also recruited 13 Li-naïve, young BD participants (15–30 years of age) and 18 sex- and age-matched healthy controls. We compared hippocampal volumes obtained from 1.5-T magnetic resonance imaging (MRI) scans using optimized voxel-based morphometry with small volume correction.

Results

The non-Li group had smaller left hippocampal volumes than controls (corrected p < 0.05), with a trend for lower volumes than the Li group (corrected p < 0.1), which did not differ from controls. Young, Li-naïve BD patients close to the typical age of onset had comparable hippocampal volumes to controls.

Conclusions

Whereas patients with limited lifetime Li exposure had significantly lower hippocampal volumes than controls, patients with comparable illness burden, but with over two years of Li treatment, or young Li-naïve BD patients without Li exposure, showed hippocampal volumes comparable to controls. These results provide indirect support for neuroprotective effects of Li and negative effects of illness burden on hippocampal volumes in bipolar disorders.

Objective

Although bipolar disorder has high heritability, the onset occurs during several decades of life, suggesting that social and environmental factors may have considerable influence on disease onset. This study examined the association between the age of onset and sunlight at the location of onset.

Method

Data were obtained from 2414 patients with a diagnosis of bipolar I disorder, according to DSM-IV criteria. Data were collected at 24 sites in 13 countries spanning latitudes 6.3 to 63.4 degrees from the equator, including data from both hemispheres. The age of onset and location of onset were obtained retrospectively, from patient records and/or direct interviews. Solar insolation data, or the amount of electromagnetic energy striking the surface of the earth, were obtained from the NASA Surface Meteorology and Solar Energy (SSE) database for each location of onset.

Results

The larger the maximum monthly increase in solar insolation at the location of onset, the younger the age of onset (coefficient= −4.724, 95% CI: −8.124 to −1.323, p = 0.006), controlling for each country’s median age. The maximum monthly increase in solar insolation occurred in springtime. No relationships were found between the age of onset and latitude, yearly total solar insolation, and the maximum monthly decrease in solar insolation. The largest maximum monthly increases in solar insolation occurred in diverse environments, including Norway, arid areas in California, and Chile.

Conclusion

The large maximum monthly increase in sunlight in springtime may have an important influence on the onset of bipolar disorder.

The Structure Integration with Function, Taxonomy and Sequences resource (SIFTS; http://pdbe.org/sifts) is a close collaboration between the Protein Data Bank in Europe (PDBe) and UniProt. The two teams have developed a semi-automated process for maintaining up-to-date cross-reference information to UniProt entries, for all protein chains in the PDB entries present in the UniProt database. This process is carried out for every weekly PDB release and the information is stored in the SIFTS database. The SIFTS process includes cross-references to other biological resources such as Pfam, SCOP, CATH, GO, InterPro and the NCBI taxonomy database. The information is exported in XML format, one file for each PDB entry, and is made available by FTP. Many bioinformatics resources use SIFTS data to obtain cross-references between the PDB and other biological databases so as to provide their users with up-to-date information.

The availability of comprehensive information about enzymes plays an important role in answering questions relevant to interdisciplinary fields such as biochemistry, enzymology, biofuels, bioengineering and drug discovery. At the EMBL European Bioinformatics Institute, we have developed an enzyme portal (http://www.ebi.ac.uk/enzymeportal) to provide this wealth of information on enzymes from multiple in-house resources addressing particular data classes: protein sequence and structure, reactions, pathways and small molecules. The fact that these data reside in separate databases makes information discovery cumbersome. The main goal of the portal is to simplify this process for end users.

The 5th International Biocuration Conference brought together over 300 scientists to exchange on their work, as well as discuss issues relevant to the International Society for Biocuration’s (ISB) mission. Recurring themes this year included the creation and promotion of gold standards, the need for more ontologies, and more formal interactions with journals. The conference is an essential part of the ISB's goal to support exchanges among members of the biocuration community. Next year's conference will be held in Cambridge, UK, from 7 to 10 April 2013. In the meanwhile, the ISB website provides information about the society's activities (http://biocurator.org), as well as related events of interest.

Background

Neuroprotective effects of lithium (Li) have been well documented in tissue cultures and animal models, whereas human data continue to be limited. Previous studies investigating the association between Li treatment and brain N-acetylaspartate (NAA), a putative neuronal marker, showed mixed results because of methodological heterogeneity.

Methods

To investigate the effects of Li on prefrontal cortex NAA levels, we compared patients with bipolar disorder from specialized Li clinics in Berlin and Halifax with at least 2 years of ongoing Li treatment (Li group), patients with lifetime Li exposure of less than 3 months more than 2 years ago (non-Li group) and healthy controls. Participants in both patient groups had at least 10 years of illness and 5 episodes. We measured left prefrontal NAA levels using 1.5-T magnetic resonance spectroscopy.

Results

We enrolled 27 participants in the Li, 16 in the non-Li and 21 in the healthy control groups. The non-Li group had lower prefrontal NAA levels than the Li group (t41 = −3.44, corrected p < 0.01) or control participants (t35 = −2.91, corrected p < 0.05), who did not differ from the Li group (t46 = −0.14, p = 0.89). The same pattern of prefrontal NAA differences was replicated in both sites. In addition, there was a negative correlation between prefrontal NAA and duration of illness in the non-Li group (r = −0.60, p = 0.019) but not in the Li group (r = 0.07, p = 0.74).

Limitations

Study limitations include the cross-sectional design and exposure to other medications.

Conclusion

Whereas patients with bipolar disorder, substantial illness burden and limited lifetime Li exposure had significantly lower prefrontal NAA levels than controls, Li-treated patients with similar illness burden showed prefrontal NAA levels comparable to those of healthy controls. These findings provide indirect support for neuroprotective effects of Li and for negative effects of illness burden on prefrontal NAA levels in patients with bipolar disorder.

As the deluge of genomic DNA sequence grows the fraction of protein sequences that have been manually curated falls. In turn, as the number of laboratories with the ability to sequence genomes in a high-throughput manner grows, the informatics capability of those labs to accurately identify and annotate all genes within a genome may often be lacking. These issues have led to fears about transitive annotation errors making sequence databases less reliable. During the lifetime of the Pfam protein families database a number of protein families have been built, which were later identified as composed solely of spurious open reading frames (ORFs) either on the opposite strand or in a different, overlapping reading frame with respect to the true protein-coding or non-coding RNA gene. These families were deleted and are no longer available in Pfam. However, we realized that these may perform a useful function to identify new spurious ORFs. We have collected these families together in AntiFam along with additional custom-made families of spurious ORFs. This resource currently contains 23 families that identified 1310 spurious proteins in UniProtKB and a further 4119 spurious proteins in a collection of metagenomic sequences. UniProt has adopted AntiFam as a part of the UniProtKB quality control process and will investigate these spurious proteins for exclusion.

Curated databases are an integral part of the tool set that researchers use on a daily basis for their work. For most users, however, how databases are maintained, and by whom, is rather obscure. The International Society for Biocuration (ISB) represents biocurators, software engineers, developers and researchers with an interest in biocuration. Its goals include fostering communication between biocurators, promoting and describing their work, and highlighting the added value of biocuration to the world. The ISB recently conducted a survey of biocurators to better understand their educational and scientific backgrounds, their motivations for choosing a curatorial job and their career goals. The results are reported here. From the responses received, it is evident that biocuration is performed by highly trained scientists and perceived to be a stimulating career, offering both intellectual challenges and the satisfaction of performing work essential to the modern scientific community. It is also apparent that the ISB has at least a dual role to play to facilitate biocurators’ work: (i) to promote biocuration as a career within the greater scientific community; (ii) to aid the development of resources for biomedical research through promotion of nomenclature and data-sharing standards that will allow interconnection of biological databases and better exploit the pivotal contributions that biocurators are making.

Database URL: http://biocurator.org

The Gene Ontology (GO) resource provides dynamic controlled vocabularies to provide an information-rich resource to aid in the consistent description of the functional attributes and subcellular locations of gene products from all taxonomic groups (www.geneontology.org). System-focused projects, such as the Renal and Cardiovascular GO Annotation Initiatives, aim to provide detailed GO data for proteins implicated in specific organ development and function. Such projects support the rapid evaluation of new experimental data and aid in the generation of novel biological insights to help alleviate human disease. This paper describes the improvement of GO data for renal and cardiovascular research communities and demonstrates that the cardiovascular-focused GO annotations, created over the past three years, have led to an evident improvement of microarray interpretation. The reanalysis of cardiovascular microarray datasets confirms the need to continue to improve the annotation of the human proteome.

Availability

GO annotation data is freely available from: ftp://ftp.geneontology.org/pub/go/gene-associations/

The GO annotation dataset provided by the UniProt Consortium (GOA: http://www.ebi.ac.uk/GOA) is a comprehensive set of evidenced-based associations between terms from the Gene Ontology resource and UniProtKB proteins. Currently supplying over 100 million annotations to 11 million proteins in more than 360 000 taxa, this resource has increased 2-fold over the last 2 years and has benefited from a wealth of checks to improve annotation correctness and consistency as well as now supplying a greater information content enabled by GO Consortium annotation format developments. Detailed, manual GO annotations obtained from the curation of peer-reviewed papers are directly contributed by all UniProt curators and supplemented with manual and electronic annotations from 36 model organism and domain-focused scientific resources. The inclusion of high-quality, automatic annotation predictions ensures the UniProt GO annotation dataset supplies functional information to a wide range of proteins, including those from poorly characterized, non-model organism species. UniProt GO annotations are freely available in a range of formats accessible by both file downloads and web-based views. In addition, the introduction of a new, normalized file format in 2010 has made for easier handling of the complete UniProt-GOA data set.

The promise of genome sequencing was that the vast undiscovered country would be mapped out by comparison of the multitude of sequences available and would aid researchers in deciphering the role of each gene in every organism. Researchers recognize that there is a need for high quality data. However, different annotation procedures, numerous databases, and a diminishing percentage of experimentally determined gene functions have resulted in a spectrum of annotation quality. NCBI in collaboration with sequencing centers, archival databases, and researchers, has developed the first international annotation standards, a fundamental step in ensuring that high quality complete prokaryotic genomes are available as gold standard references. Highlights include the development of annotation assessment tools, community acceptance of protein naming standards, comparison of annotation resources to provide consistent annotation, and improved tracking of the evidence used to generate a particular annotation. The development of a set of minimal standards, including the requirement for annotated complete prokaryotic genomes to contain a full set of ribosomal RNAs, transfer RNAs, and proteins encoding core conserved functions, is an historic milestone. The use of these standards in existing genomes and future submissions will increase the quality of databases, enabling researchers to make accurate biological discoveries.

The gene ontology (go) resource provides dynamic controlled vocabularies to aid in the description of the functional attributes and subcellular locations of gene products from all taxonomic groups (www.geneontology.org). A renal-focused curation initiative, funded by Kidney Research UK and supported by the GO Consortium, has started at the European Bioinformatics Institute and aims to provide a detailed GO resource for mammalian proteins implicated in renal development and function. This report outlines the aims of this initiative and explains how the renal community can become involved to help improve the availability, quality and quantity of GO terms and their association to specific proteins.

The advent of sequencing and structural genomics projects has provided a dramatic boost in the number of protein structures and sequences. Due to the high-throughput nature of these projects, many of the molecules are uncharacterised and their functions unknown. This, in turn, has led to the need for a greater number and diversity of tools and databases providing annotation through transfer based on homology and prediction methods. Though many such tools to annotate protein sequence and structure exist, they are spread throughout the world, often with dedicated individual web pages. This situation does not provide a consensus view of the data and hinders comparison between methods. Integration of these methods is needed. So far this has not been possible since there was no common vocabulary available that could be used as a standard language. A variety of terms could be used to describe any particular feature ranging from different spellings to completely different terms. The Protein Feature Ontology (http://www.ebi.ac.uk/ontology-lookup/browse.do?ontName=BS) is a structured controlled vocabulary for features of a protein sequence or structure. It provides a common language for tools and methods to use, so that integration and comparison of their annotations is possible. The Protein Feature Ontology comprises approximately 100 positional terms (located in a particular region of the sequence), which have been integrated into the Sequence Ontology (SO). 40 non-positional terms which describe general protein properties have also been defined and, in addition, post-translational modifications are described by using an already existing ontology, the Protein Modification Ontology (MOD). The Protein Feature Ontology has been used by the BioSapiens Network of Excellence, a consortium comprising 19 partner sites in 14 European countries generating over 150 distinct annotation types for protein sequences and structures.

The Gene Ontology (GO) has proven to be a valuable resource for functional annotation of gene products. At well over 27 000 terms, the descriptiveness of GO has increased rapidly in line with the biological data it represents. Therefore, it is vital to be able to easily and quickly mine the functional information that has been made available through these GO terms being associated with gene products. QuickGO is a fast, web-based tool for browsing the GO and all associated GO annotations provided by the GOA group. After undergoing a redevelopment, QuickGO is now able to offer many more features beyond simple browsing. Users have responded well to the new tool and given very positive feedback about its usefulness. This tutorial will demonstrate how some of these features could be useful to the researcher wanting to discover more about their dataset, particular areas of biology or to find new ways of directing their research.

Database URL: http://www.ebi.ac.uk/QuickGO

Summary: QuickGO is a web-based tool that allows easy browsing of the Gene Ontology (GO) and all associated electronic and manual GO annotations provided by the GO Consortium annotation groups QuickGO has been a popular GO browser for many years, but after a recent redevelopment it is now able to offer a greater range of facilities including bulk downloads of GO annotation data which can be extensively filtered by a range of different parameters and GO slim set generation.

Availability and Implementation: QuickGO has implemented in JavaScript, Ajax and HTML, with all major browsers supported. It can be queried online at http://www.ebi.ac.uk/QuickGO. The software for QuickGO is freely available under the Apache 2 licence and can be downloaded from http://www.ebi.ac.uk/QuickGO/installation.html

Contact: goa@ebi.ac.uk; dbinns@ebi.ac.uk

The Gene Ontology Annotation (GOA) project at the EBI (http://www.ebi.ac.uk/goa) provides high-quality electronic and manual associations (annotations) of Gene Ontology (GO) terms to UniProt Knowledgebase (UniProtKB) entries. Annotations created by the project are collated with annotations from external databases to provide an extensive, publicly available GO annotation resource. Currently covering over 160 000 taxa, with greater than 32 million annotations, GOA remains the largest and most comprehensive open-source contributor to the GO Consortium (GOC) project. Over the last five years, the group has augmented the number and coverage of their electronic pipelines and a number of new manual annotation projects and collaborations now further enhance this resource. A range of files facilitate the download of annotations for particular species, and GO term information and associated annotations can also be viewed and downloaded from the newly developed GOA QuickGO tool (http://www.ebi.ac.uk/QuickGO), which allows users to precisely tailor their annotation set.

The Universal Protein Resource (UniProt) provides a central resource on protein sequences and functional annotation with three database components, each addressing a key need in protein bioinformatics. The UniProt Knowledgebase (UniProtKB), comprising the manually annotated UniProtKB/Swiss-Prot section and the automatically annotated UniProtKB/TrEMBL section, is the preeminent storehouse of protein annotation. The extensive cross-references, functional and feature annotations and literature-based evidence attribution enable scientists to analyse proteins and query across databases. The UniProt Reference Clusters (UniRef) speed similarity searches via sequence space compression by merging sequences that are 100% (UniRef100), 90% (UniRef90) or 50% (UniRef50) identical. Finally, the UniProt Archive (UniParc) stores all publicly available protein sequences, containing the history of sequence data with links to the source databases. UniProt databases continue to grow in size and in availability of information. Recent and upcoming changes to database contents, formats, controlled vocabularies and services are described. New download availability includes all major releases of UniProtKB, sequence collections by taxonomic division and complete proteomes. A bibliography mapping service has been added, and an ID mapping service will be available soon. UniProt databases can be accessed online at or downloaded at .

The Universal Protein Resource (UniProt) provides the scientific community with a single, centralized, authoritative resource for protein sequences and functional information. Formed by uniting the Swiss-Prot, TrEMBL and PIR protein database activities, the UniProt consortium produces three layers of protein sequence databases: the UniProt Archive (UniParc), the UniProt Knowledgebase (UniProt) and the UniProt Reference (UniRef) databases. The UniProt Knowledgebase is a comprehensive, fully classified, richly and accurately annotated protein sequence knowledgebase with extensive cross-references. This centrepiece consists of two sections: UniProt/Swiss-Prot, with fully, manually curated entries; and UniProt/TrEMBL, enriched with automated classification and annotation. During 2004, tens of thousands of Knowledgebase records got manually annotated or updated; we introduced a new comment line topic: TOXIC DOSE to store information on the acute toxicity of a toxin; the UniProt keyword list got augmented by additional keywords; we improved the documentation of the keywords and are continuously overhauling and standardizing the annotation of post-translational modifications. Furthermore, we introduced a new documentation file of the strains and their synonyms. Many new database cross-references were introduced and we started to make use of Digital Object Identifiers. We also achieved in collaboration with the Macromolecular Structure Database group at EBI an improved integration with structural databases by residue level mapping of sequences from the Protein Data Bank entries onto corresponding UniProt entries. For convenient sequence searches we provide the UniRef non-redundant sequence databases. The comprehensive UniParc database stores the complete body of publicly available protein sequence data. The UniProt databases can be accessed online (http://www.uniprot.org) or downloaded in several formats (ftp://ftp.uniprot.org/pub). New releases are published every two weeks.

To provide the scientific community with a single, centralized, authoritative resource for protein sequences and functional information, the Swiss-Prot, TrEMBL and PIR protein database activities have united to form the Universal Protein Knowledgebase (UniProt) consortium. Our mission is to provide a comprehensive, fully classified, richly and accurately annotated protein sequence knowledgebase, with extensive cross-references and query interfaces. The central database will have two sections, corresponding to the familiar Swiss-Prot (fully manually curated entries) and TrEMBL (enriched with automated classification, annotation and extensive cross-references). For convenient sequence searches, UniProt also provides several non-redundant sequence databases. The UniProt NREF (UniRef) databases provide representative subsets of the knowledgebase suitable for efficient searching. The comprehensive UniProt Archive (UniParc) is updated daily from many public source databases. The UniProt databases can be accessed online (http://www.uniprot.org) or downloaded in several formats (ftp://ftp.uniprot.org/pub). The scientific community is encouraged to submit data for inclusion in UniProt.

The SWISS-PROT protein knowledgebase (http://www.expasy.org/sprot/ and http://www.ebi.ac.uk/swissprot/) connects amino acid sequences with the current knowledge in the Life Sciences. Each protein entry provides an interdisciplinary overview of relevant information by bringing together experimental results, computed features and sometimes even contradictory conclusions. Detailed expertise that goes beyond the scope of SWISS-PROT is made available via direct links to specialised databases. SWISS-PROT provides annotated entries for all species, but concentrates on the annotation of entries from human (the HPI project) and other model organisms to ensure the presence of high quality annotation for representative members of all protein families. Part of the annotation can be transferred to other family members, as is already done for microbes by the High-quality Automated and Manual Annotation of microbial Proteomes (HAMAP) project. Protein families and groups of proteins are regularly reviewed to keep up with current scientific findings. Complementarily, TrEMBL strives to comprise all protein sequences that are not yet represented in SWISS-PROT, by incorporating a perpetually increasing level of mostly automated annotation. Researchers are welcome to contribute their knowledge to the scientific community by submitting relevant findings to SWISS-PROT at swiss-prot@expasy.org.

As the amount of biological data grows, so does the need for biologists to store and access this information in central repositories in a free and unambiguous manner. The European Bioinformatics Institute (EBI) hosts six core databases, which store information on DNA sequences (EMBL-Bank), protein sequences (SWISS-PROT and TrEMBL), protein structure (MSD), whole genomes (Ensembl) and gene expression (ArrayExpress). But just as a cell would be useless if it couldn't transcribe DNA or translate RNA, our resources would be compromised if each existed in isolation. We have therefore developed a range of tools that not only facilitate the deposition and retrieval of biological information, but also allow users to carry out searches that reflect the interconnectedness of biological information. The EBI's databases and tools are all available on our website at www.ebi.ac.uk.

The goal of treatment of major depression should be full remission. Many patients, however, fail to achieve or maintain symptom-free status. Residual depressive symptoms are common, even where there has been a robust response to antidepressant therapy. In clinical studies, approximately one-third of patients achieve a full remission, one-third experience a response and one-third are nonresponders. Partial remission is characterized by the presence of poorly defined residual symptoms. These symptoms typically include depressed mood, psychic anxiety, sleep disturbance, fatigue and diminished interest or pleasure. It is currently unclear which factors predict partial remission. However, it is clear that residual symptoms are powerful predictors of relapse, with relapse rates 3–6 times higher in patients with residual symptoms than in those who experience full remission. Residual symptoms are also associated with more medical and psychiatric visits, increased public assistance, disability benefits, thoughts of and attempts at suicide and chronicity. The risk of stroke and coronary events is also higher in patients with residual depressive symptoms. The substantial proportion of patients who achieve only partial remission has traditionally been neglected in antidepressant trials. Given that residual symptoms may relate, in part, to an incompatibility between patient and treatment, further research is needed to predict a better match. These symptoms are a clinically relevant state of illness, and the correct choice of initial antidepressant treatment should offer the greatest chance of achieving full remission.