Guiding the choice of informatics software and tools for lipidomics research applications.

Progress in mass spectrometry lipidomics has led to a rapid proliferation of studies across biology and biomedicine. These generate extremely large raw datasets requiring sophisticated solutions to support automated data processing. To address this, numerous software tools have been developed and tailored for specific tasks. However, for researchers, deciding which approach best suits their application relies on ad hoc testing, which is inefficient and time consuming. Here we first review the data processing pipeline, summarizing the scope of available tools. Next, to support researchers, LIPID MAPS provides an interactive online portal listing open-access tools with a graphical user interface. This guides users towards appropriate solutions within major areas in data processing, including (1) lipid-oriented databases, (2) mass spectrometry data repositories, (3) analysis of targeted lipidomics datasets, (4) lipid identification and (5) quantification from untargeted lipidomics datasets, (6) statistical analysis and visualization, and (7) data integration solutions. Detailed descriptions of functions and requirements are provided to guide customized data analysis workflows.

MetaboLights: open data repository for metabolomics.

MetaboLights is a global database for metabolomics studies including the raw experimental data and the associated metadata. The database is cross-species and cross-technique and covers metabolite structures and their reference spectra as well as their biological roles and locations where available. MetaboLights is the recommended metabolomics repository for a number of leading journals and ELIXIR, the European infrastructure for life science information. In this article, we describe the continued growth and diversity of submissions and the significant developments in recent years. In particular, we highlight MetaboLights Labs, our new Galaxy Project instance with repository-scale standardized workflows, and how data public on MetaboLights are being reused by the community. Metabolomics resources and data are available under the EMBL-EBI's Terms of Use at https://www.ebi.ac.uk/metabolights and under Apache 2.0 at https://github.com/EBI-Metabolights.

Phenotypic clustering of bipolar disorder supports stratification by lithium responsiveness over diagnostic subtypes.

INTRODUCTION: The aim of this study was to determine whether the clinical profiles of bipolar disorder (BD) patients could be differentiated more clearly using the existing classification by diagnostic subtype or by lithium treatment responsiveness. METHODS: We included adult patients with BD-I or II (N = 477 across four sites) who were treated with lithium as their principal mood stabilizer for at least 1 year. Treatment responsiveness was defined using the dichotomized Alda score. We performed hierarchical clustering on phenotypes defined by 40 features, covering demographics, clinical course, family history, suicide behaviour, and comorbid conditions. We then measured the amount of information that inferred clusters carried about (A) BD subtype and (B) lithium responsiveness using adjusted mutual information (AMI) scores. Detailed phenotypic profiles across clusters were then evaluated with univariate comparisons. RESULTS: Two clusters were identified (n = 56 and n = 421), which captured significantly more information about lithium responsiveness (AMI range: 0.033 to 0.133) than BD subtype (AMI: 0.004 to 0.011). The smaller cluster had disproportionately more lithium responders (n = 47 [83.8%]) when compared to the larger cluster (103 [24.4%]; p = 0.006). CONCLUSIONS: Phenotypes derived from detailed clinical data may carry more information about lithium responsiveness than the current classification of diagnostic subtype. These findings support lithium responsiveness as a valid approach to stratification in clinical samples.

MetaboLights: a resource evolving in response to the needs of its scientific community.

MetaboLights is a database for metabolomics studies, their raw experimental data and associated metadata. The database is cross-species and cross-technique and it covers metabolite structures and their reference spectra as well as their biological roles and locations. MetaboLights is the recommended metabolomics repository for a number of leading journals and ELIXIR, the European infrastructure for life science information. In this article, we describe the significant updates that we have made over the last two years to the resource to respond to the increasing amount and diversity of data being submitted by the metabolomics community. We refreshed the website and most importantly, our submission process was completely overhauled to enable us to deliver a far more user-friendly submission process and to facilitate the growing demand for reproducibility and integration with other 'omics. Metabolomics resources and data are available under the EMBL-EBI's Terms of Use via the web at https://www.ebi.ac.uk/metabolights and under Apache 2.0 at Github (https://github.com/EBI-Metabolights/).

Cultural Differences in Psychological Distress and Illness Perceptions Amongst People Living With Cardiac Inherited Diseases.

Cardiac Inherited diseases (CID) and minority ethnic status are both associated with anxiety and depression. This study aimed to investigate differences in patient experiences of CID between ethnic groups in New Zealand (NZ) in order to inform psychosocial interventions and promote health equity. A cross-sectional survey was administered to a NZ CID database. One-hundred and fifty-two (152) NZ Europeans, 19 Maori, and two Pasifika participated. Maori and Pasifika peoples reported significantly greater symptom perceptions, shorter timeline perceptions, higher perceived risk of severe symptoms, and were less likely to attribute the cause of their CID to hereditary factors than NZ Europeans. Maori and Pasifika also reported more anxiety and distress, although both groups reported beneficial medication perceptions and high medication adherence. Differences could not be attributed to clinical or other demographic variables. The use of screening tools and development of culturally appropriate interventions may help reduce both distress and health inequities.

UniRule: a unified rule resource for automatic annotation in the UniProt Knowledgebase.

MOTIVATION: The number of protein records in the UniProt Knowledgebase (UniProtKB: https://www.uniprot.org) continues to grow rapidly as a result of genome sequencing and the prediction of protein-coding genes. Providing functional annotation for these proteins presents a significant and continuing challenge. RESULTS: In response to this challenge, UniProt has developed a method of annotation, known as UniRule, based on expertly curated rules, which integrates related systems (RuleBase, HAMAP, PIRSR, PIRNR) developed by the members of the UniProt consortium. UniRule uses protein family signatures from InterPro, combined with taxonomic and other constraints, to select sets of reviewed proteins which have common functional properties supported by experimental evidence. This annotation is propagated to unreviewed records in UniProtKB that meet the same selection criteria, most of which do not have (and are never likely to have) experimentally verified functional annotation. Release 2020_01 of UniProtKB contains 6496 UniRule rules which provide annotation for 53 million proteins, accounting for 30% of the 178 million records in UniProtKB. UniRule provides scalable enrichment of annotation in UniProtKB. AVAILABILITY AND IMPLEMENTATION: UniRule rules are integrated into UniProtKB and can be viewed at https://www.uniprot.org/unirule/. UniRule rules and the code required to run the rules, are publicly available for researchers who wish to annotate their own sequences. The implementation used to run the rules is known as UniFIRE and is available at https://gitlab.ebi.ac.uk/uniprot-public/unifire.

A systematic review of illness perception interventions in type 2 diabetes: Effects on glycaemic control and illness perceptions.

AIMS: This systematic review sought to synthesize the evidence regarding the effectiveness of illness perception interventions compared with control conditions at changing illness perceptions and improving glycaemic control in individuals with type 2 diabetes. METHODS: Seven electronic databases were searched between October 2018 and May 2020. Randomized controlled trials that tested interventions informed by the Common-Sense Model in adults with type 2 diabetes, and measured illness perceptions and glycaemic control at pre- and post-intervention were included. The Cochrane risk of bias tool was used to assess risk of bias. RESULTS: A total of 4095 articles were identified, of which nine randomized control trials (2561 participants) across 12 publications were included in this review. Findings showed that all the illness perception domains were modified in at least one trial, with the exception of cyclical timeline perceptions. Coherence, personal control, treatment control and chronic timeline perceptions were the most frequently modified perceptions. Glycaemic control demonstrated an improvement in the intervention group compared to the control group at 3 and 6 months post-intervention in two trials. Risk of bias assessment showed high risk of bias especially for the blinding of participants and the personnel domain. CONCLUSIONS: There is limited evidence that interventions informed by the Common-Sense Model can improve glycaemic control in individuals with type 2 diabetes through changing inaccurate illness perceptions. Recommendations for future research are to tailor intervention content based on baseline perceptions, measure the emotional and causal domains, and involve family members in the intervention. (PROSPERO registration: CRD42019114532).

Canadian Network for Mood and Anxiety Treatments (CANMAT) and International Society for Bipolar Disorders (ISBD) recommendations for the management of patients with bipolar disorder with mixed presentations.

OBJECTIVES: The 2018 Canadian Network for Mood and Anxiety Treatments (CANMAT) and International Society for Bipolar Disorders (ISBD) guidelines provided clinicians with pragmatic treatment recommendations for bipolar disorder (BD). While these guidelines included commentary on how mixed features may direct treatment selection, specific recommendations were not provided-a critical gap which the current update aims to address. METHOD: Overview of research regarding mixed presentations in BD, with treatment recommendations developed using a modified CANMAT/ISBD rating methodology. Limitations are discussed, including the dearth of high-quality data and reliance on expert opinion. RESULTS: No agents met threshold for first-line treatment of DSM-5 manic or depressive episodes with mixed features. For mania + mixed features second-line treatment options include asenapine, cariprazine, divalproex, and aripiprazole. In depression + mixed features, cariprazine and lurasidone are recommended as second-line options. For DSM-IV defined mixed episodes, with a longer history of research, asenapine and aripiprazole are first-line, and olanzapine (monotherapy or combination), carbamazepine, and divalproex are second-line. Research on maintenance treatments following a DSM-5 mixed presentation is extremely limited, with third-line recommendations based on expert opinion. For maintenance treatment following a DSM-IV mixed episode, quetiapine (monotherapy or combination) is first-line, and lithium and olanzapine identified as second-line options. CONCLUSION: The CANMAT and ISBD groups hope these guidelines provide valuable support for clinicians providing care to patients experiencing mixed presentations, as well as further influence investment in research to improve diagnosis and treatment of this common and complex clinical state.

SIFTS: updated Structure Integration with Function, Taxonomy and Sequences resource allows 40-fold increase in coverage of structure-based annotations for proteins.

The Structure Integration with Function, Taxonomy and Sequences resource (SIFTS; http://pdbe.org/sifts/) was established in 2002 and continues to operate as a collaboration between the Protein Data Bank in Europe (PDBe; http://pdbe.org) and the UniProt Knowledgebase (UniProtKB; http://uniprot.org). The resource is instrumental in the transfer of annotations between protein structure and protein sequence resources through provision of up-to-date residue-level mappings between entries from the PDB and from UniProtKB. SIFTS also incorporates residue-level annotations from other biological resources, currently comprising the NCBI taxonomy database, IntEnz, GO, Pfam, InterPro, SCOP, CATH, PubMed, Ensembl, Homologene and automatic Pfam domain assignments based on HMM profiles. The recently released implementation of SIFTS includes support for multiple cross-references for proteins in the PDB, allowing mappings to UniProtKB isoforms and UniRef90 cluster members. This development makes structure data in the PDB readily available to over 1.8 million UniProtKB accessions.

Progress towards an OECD reporting framework for transcriptomics and metabolomics in regulatory toxicology.

Omics methodologies are widely used in toxicological research to understand modes and mechanisms of toxicity. Increasingly, these methodologies are being applied to questions of regulatory interest such as molecular point-of-departure derivation and chemical grouping/read-across. Despite its value, widespread regulatory acceptance of omics data has not yet occurred. Barriers to the routine application of omics data in regulatory decision making have been: 1) lack of transparency for data processing methods used to convert raw data into an interpretable list of observations; and 2) lack of standardization in reporting to ensure that omics data, associated metadata and the methodologies used to generate results are available for review by stakeholders, including regulators. Thus, in 2017, the Organisation for Economic Co-operation and Development (OECD) Extended Advisory Group on Molecular Screening and Toxicogenomics (EAGMST) launched a project to develop guidance for the reporting of omics data aimed at fostering further regulatory use. Here, we report on the ongoing development of the first formal reporting framework describing the processing and analysis of both transcriptomic and metabolomic data for regulatory toxicology. We introduce the modular structure, content, harmonization and strategy for trialling this reporting framework prior to its publication by the OECD.

Metabolomics: The Stethoscope for the Twenty-First Century.

Metabolomics encompasses the systematic identification and quantification of all metabolic products in the human body. This field could provide clinicians with novel sets of diagnostic biomarkers for disease states in addition to quantifying treatment response to medications at an individualized level. This literature review aims to highlight the technology underpinning metabolic profiling, identify potential applications of metabolomics in clinical practice, and discuss the translational challenges that the field faces. We searched PubMed, MEDLINE, and EMBASE for primary and secondary research articles regarding clinical applications of metabolomics. Metabolic profiling can be performed using mass spectrometry and nuclear magnetic resonance-based techniques using a variety of biological samples. This is carried out in vivo or in vitro following careful sample collection, preparation, and analysis. The potential clinical applications constitute disruptive innovations in their respective specialities, particularly oncology and metabolic medicine. Outstanding issues currently preventing widespread clinical use are scalability of data interpretation, standardization of sample handling practice, and e-infrastructure. Routine utilization of metabolomics at a patient and population level will constitute an integral part of future healthcare provision.

Dissemination and analysis of the quality assurance (QA) and quality control (QC) practices of LC-MS based untargeted metabolomics practitioners.

INTRODUCTION: The metabolomics quality assurance and quality control consortium (mQACC) evolved from the recognized need for a community-wide consensus on improving and systematizing quality assurance (QA) and quality control (QC) practices for untargeted metabolomics. OBJECTIVES: In this work, we sought to identify and share the common and divergent QA and QC practices amongst mQACC members and collaborators who use liquid chromatography-mass spectrometry (LC-MS) in untargeted metabolomics. METHODS: All authors voluntarily participated in this collaborative research project by providing the details of and insights into the QA and QC practices used in their laboratories. This sharing was enabled via a six-page questionnaire composed of over 120 questions and comment fields which was developed as part of this work and has proved the basis for ongoing mQACC outreach. RESULTS: For QA, many laboratories reported documenting maintenance, calibration and tuning (82%); having established data storage and archival processes (71%); depositing data in public repositories (55%); having standard operating procedures (SOPs) in place for all laboratory processes (68%) and training staff on laboratory processes (55%). For QC, universal practices included using system suitability procedures (100%) and using a robust system of identification (Metabolomics Standards Initiative level 1 identification standards) for at least some of the detected compounds. Most laboratories used QC samples (>86%); used internal standards (91%); used a designated analytical acquisition template with randomized experimental samples (91%); and manually reviewed peak integration following data acquisition (86%). A minority of laboratories included technical replicates of experimental samples in their workflows (36%). CONCLUSIONS: Although the 23 contributors were researchers with diverse and international backgrounds from academia, industry and government, they are not necessarily representative of the worldwide pool of practitioners due to the recruitment method for participants and its voluntary nature. However, both questionnaire and the findings presented here have already informed and led other data gathering efforts by mQACC at conferences and other outreach activities and will continue to evolve in order to guide discussions for recommendations of best practices within the community and to establish internationally agreed upon reporting standards. We very much welcome further feedback from readers of this article.

Perceptions of Risk of Cardiac Arrest in Individuals Living With a Cardiac Inherited Disease: Are the Doctor and the Patient on the Same Page?

BACKGROUND: Risk perceptions influence patient engagement with treatment recommendations, yet it is unknown whether patients with a cardiac inherited disease (CID) hold accurate risk perceptions. The study aimed to examine whether CID patients' and clinician's risk perceptions correlate and factors associated with patient perceptions. METHODS: 202 CID patients (of 618 [36%]) participated in a postal survey assessing perceived risk of aborted cardiac arrest or sudden cardiac death (ACA/SCD). Median age was 53 (16 to 83 years); 86 had Long QT Syndrome (LQTS), 69 had hypertrophic cardiomyopathy, 12 had dilated cardiomyopathy, and 27 had 'other'. Clinical and genetic characteristics were collected from the CID registry; clinical estimate of 5-year risk was determined for LQTS participants (n = 77) using a combination of cardiac arrest or syncope history, maximal QTc length, age, sex and genotype. RESULTS: Patients' risk perceptions of ACA/SCD ranged from 0 to 100%, (median 20%). Greater risk perceptions were associated with: non-New Zealand (NZ) Europeans (p < 0.01), probands (p < 0.05), reporting more physical symptoms (including those unrelated to CID) (p < 0.01), and more symptoms of anxiety (p < 0.05). Median risk assessment by LQTS patients was 15%, and by the clinician was 4.5%. No association was found between patient and clinician assessments of risk (rs = 0.13, ns), 56% of LQTS patients overestimated their risk, 14% underestimated and 30% were accurate. CONCLUSION: Cardiac inherited disease patients' risk perceptions correlate poorly with those of the clinician. Patients overestimating risk tend to have physical symptoms usually unrelated to their CID, and underlying anxiety. Techniques to better communicate risk are needed.

How Patient Perceptions Shape Responses and Outcomes in Inherited Cardiac Conditions.

At least one-third of adults living with an inherited cardiac condition report clinically-significant levels of psychological distress. Poorer health-related quality of life compared with population norms is also consistently reported. These outcomes are associated with younger patient age, having an implantable cardioverter defibrillator, and receipt of uncertain clinical test results, and can influence self-management behaviours, such as adherence to potentially critical life-preserving medications. According to the Common Sense Model of Illness, people use information from multiple sources to 'make sense' of their health condition, and how they conceptualise the condition can strongly influence adaptation and coping responses. Previous studies with people with inherited cardiac conditions show that illness perceptions, such as greater perceived consequences and a poorer understanding of the condition, are associated with greater psychological distress and poorer adherence to medication. The Common Sense Model provides one potential framework for identifying patients who may be more vulnerable to adverse health outcomes, and for developing early interventions to reduce the physical and psychosocial burden of these conditions. Interventions based on the Common Sense Model have successfully improved physical and psychosocial outcomes associated with other cardiac conditions, and could be tailored for use with patients with an inherited cardiac condition (ICC).

Towards quality assurance and quality control in untargeted metabolomics studies.

We describe here the agreed upon first development steps and priority objectives of a community engagement effort to address current challenges in quality assurance (QA) and quality control (QC) in untargeted metabolomic studies. This has included (1) a QA and QC questionnaire responded to by the metabolomics community in 2015 which recommended education of the metabolomics community, development of appropriate standard reference materials and providing incentives for laboratories to apply QA and QC; (2) a 2-day 'Think Tank on Quality Assurance and Quality Control for Untargeted Metabolomic Studies' held at the National Cancer Institute's Shady Grove Campus and (3) establishment of the Metabolomics Quality Assurance and Quality Control Consortium (mQACC) to drive forward developments in a coordinated manner.

Open Targets: a platform for therapeutic target identification and validation.

We have designed and developed a data integration and visualization platform that provides evidence about the association of known and potential drug targets with diseases. The platform is designed to support identification and prioritization of biological targets for follow-up. Each drug target is linked to a disease using integrated genome-wide data from a broad range of data sources. The platform provides either a target-centric workflow to identify diseases that may be associated with a specific target, or a disease-centric workflow to identify targets that may be associated with a specific disease. Users can easily transition between these target- and disease-centric workflows. The Open Targets Validation Platform is accessible at https://www.targetvalidation.org.

Canadian Network for Mood and Anxiety Treatments (CANMAT) and International Society for Bipolar Disorders (ISBD) 2018 guidelines for the management of patients with bipolar disorder.

The Canadian Network for Mood and Anxiety Treatments (CANMAT) previously published treatment guidelines for bipolar disorder in 2005, along with international commentaries and subsequent updates in 2007, 2009, and 2013. The last two updates were published in collaboration with the International Society for Bipolar Disorders (ISBD). These 2018 CANMAT and ISBD Bipolar Treatment Guidelines represent the significant advances in the field since the last full edition was published in 2005, including updates to diagnosis and management as well as new research into pharmacological and psychological treatments. These advances have been translated into clear and easy to use recommendations for first, second, and third- line treatments, with consideration given to levels of evidence for efficacy, clinical support based on experience, and consensus ratings of safety, tolerability, and treatment-emergent switch risk. New to these guidelines, hierarchical rankings were created for first and second- line treatments recommended for acute mania, acute depression, and maintenance treatment in bipolar I disorder. Created by considering the impact of each treatment across all phases of illness, this hierarchy will further assist clinicians in making evidence-based treatment decisions. Lithium, quetiapine, divalproex, asenapine, aripiprazole, paliperidone, risperidone, and cariprazine alone or in combination are recommended as first-line treatments for acute mania. First-line options for bipolar I depression include quetiapine, lurasidone plus lithium or divalproex, lithium, lamotrigine, lurasidone, or adjunctive lamotrigine. While medications that have been shown to be effective for the acute phase should generally be continued for the maintenance phase in bipolar I disorder, there are some exceptions (such as with antidepressants); and available data suggest that lithium, quetiapine, divalproex, lamotrigine, asenapine, and aripiprazole monotherapy or combination treatments should be considered first-line for those initiating or switching treatment during the maintenance phase. In addition to addressing issues in bipolar I disorder, these guidelines also provide an overview of, and recommendations for, clinical management of bipolar II disorder, as well as advice on specific populations, such as women at various stages of the reproductive cycle, children and adolescents, and older adults. There are also discussions on the impact of specific psychiatric and medical comorbidities such as substance use, anxiety, and metabolic disorders. Finally, an overview of issues related to safety and monitoring is provided. The CANMAT and ISBD groups hope that these guidelines become a valuable tool for practitioners across the globe.

From the research laboratory to the database: the Caenorhabditis elegans kinome in UniProtKB.

Protein kinases form one of the largest protein families and are found in all species, from viruses to humans. They catalyze the reversible phosphorylation of proteins, often modifying their activity and localization. They are implicated in virtually all cellular processes and are one of the most intensively studied protein families. In recent years, they have become key therapeutic targets in drug development as natural mutations affecting kinase genes are the cause of many diseases. The vast amount of data contained in the primary literature and across a variety of biological data collections highlights the need for a repository where this information is stored in a concise and easily accessible manner. The UniProt Knowledgebase meets this need by providing the scientific community with a comprehensive, high-quality and freely accessible resource of protein sequence and functional information. Here, we describe the expert curation process for kinases, focusing on the Caenorhabditis elegans kinome. The C. elegans kinome is composed of 438 kinases and almost half of them have been functionally characterized, highlighting that C. elegans is a valuable and versatile model organism to understand the role of kinases in biological processes.

Revising Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition, criteria for the bipolar disorders: Phase I of the AREDOC project.

OBJECTIVE: To derive new criteria sets for defining manic and hypomanic episodes (and thus for defining the bipolar I and II disorders), an international Task Force was assembled and termed AREDOC reflecting its role of Assessment, Revision and Evaluation of DSM and other Operational Criteria. This paper reports on the first phase of its deliberations and interim criteria recommendations. METHOD: The first stage of the process consisted of reviewing Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition, and recent International Classification of Diseases criteria, identifying their limitations and generating modified criteria sets for further in-depth consideration. Task Force members responded to recommendations for modifying criteria and from these the most problematic issues were identified. RESULTS: Principal issues focussed on by Task Force members were how best to differentiate mania and hypomania, how to judge 'impairment' (both in and of itself and allowing that functioning may sometimes improve during hypomanic episodes) and concern that rejecting some criteria (e.g. an imposed duration period) might risk false-positive diagnoses of the bipolar disorders. CONCLUSION: This first-stage report summarises the clinical opinions of international experts in the diagnosis and management of the bipolar disorders, allowing readers to contemplate diagnostic parameters that may influence their clinical decisions. The findings meaningfully inform subsequent Task Force stages (involving a further commentary stage followed by an empirical study) that are expected to generate improved symptom criteria for diagnosing the bipolar I and II disorders with greater precision and to clarify whether they differ dimensionally or categorically.

UniProt-DAAC: domain architecture alignment and classification, a new method for automatic functional annotation in UniProtKB.

MOTIVATION: Similarity-based methods have been widely used in order to infer the properties of genes and gene products containing little or no experimental annotation. New approaches that overcome the limitations of methods that rely solely upon sequence similarity are attracting increased attention. One of these novel approaches is to use the organization of the structural domains in proteins. RESULTS: We propose a method for the automatic annotation of protein sequences in the UniProt Knowledgebase (UniProtKB) by comparing their domain architectures, classifying proteins based on the similarities and propagating functional annotation. The performance of this method was measured through a cross-validation analysis using the Gene Ontology (GO) annotation of a sub-set of UniProtKB/Swiss-Prot. The results demonstrate the effectiveness of this approach in detecting functional similarity with an average F-score: 0.85. We applied the method on nearly 55.3 million uncharacterized proteins in UniProtKB/TrEMBL resulted in 44 818 178 GO term predictions for 12 172 114 proteins. 22% of these predictions were for 2 812 016 previously non-annotated protein entries indicating the significance of the value added by this approach. AVAILABILITY AND IMPLEMENTATION: The results of the method are available at: ftp://ftp.ebi.ac.uk/pub/contrib/martin/DAAC/ CONTACT: tdogan@ebi.ac.uk SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.