A Collaborative Effort to Establish Common Metrics for Use in Mental Health.

This Viewpoint provides a summary of a new project launched by a coalition of research funders and journals to improve the measures used in mental health research.

Common measures in mental health: a joint initiative by funders and journals.

There is notable heterogeneity in how clinical and phenotypic data are measured by mental health researchers. There is a proliferation of self-report measures (eg, over 280 for depression alone), meaning it is challenging for researchers to compare findings across different studies from different laboratories. To begin to address this issue, a consortium of mental health research funders and journals has launched the Common Measures in Mental Health Science Initiative. The purpose of this endeavour is to identify common measures for mental health conditions that funders and journals can require all researchers to collect, in addition to any other measures they require for their specific study. These measures would not necessarily capture the full range of experiences of a given condition but could be used to link and compare across studies with different designs in different contexts. This Health Policy outlines the rationale, objectives, and potential challenges of this initiative, which aims to enhance the rigour and comparability of mental health research by promoting the adoption of standardised measures.

Accounting for mental health research funding: developing a quantitative baseline of global investments.

High-quality data on funding for mental health research are essential to mapping funding levels, identifying gaps in the funding landscape, and tracking the impact of research funding. To date, quantitative analyses of research funding in mental health have been restricted in scope. In this Health Policy paper, we present a comprehensive analysis of grant funding for mental health research as a starting point for discussion among stakeholders globally. We drew on a major international research database and used existing definitions and automated classification tools for mental health research. Our analysis shows a flat and stable trend over the years 2015-19 and highly unequal geographical distribution of funding, and reveals patterns of funding across different conditions and across the research spectrum. Improvements in data availability and quality, in the definitions delineating mental health research from other areas, and in automated classification tools are needed to ensure funders and policy makers can fully rely on the data and generate bespoke analyses as needed. We argue that collaborative reporting of funding for mental health research globally could help to inform and evaluate efforts to increase investments, to improve strategic dialogue, and to achieve the best possible allocation of finite resources.

Combining chemical genomics screens in yeast to reveal spectrum of effects of chemical inhibition of sphingolipid biosynthesis.

BACKGROUND: Single genome-wide screens for the effect of altered gene dosage on drug sensitivity in the model organism Saccharomyces cerevisiae provide only a partial picture of the mechanism of action of a drug. RESULTS: Using the example of the tumor cell invasion inhibitor dihydromotuporamine C, we show that a more complete picture of drug action can be obtained by combining different chemical genomics approaches--analysis of the sensitivity of rho0 cells lacking mitochondrial DNA, drug-induced haploinsufficiency, suppression of drug sensitivity by gene overexpression and chemical-genetic synthetic lethality screening using strains deleted of nonessential genes. Killing of yeast by this chemical requires a functional mitochondrial electron-transport chain and cytochrome c heme lyase function. However, we find that it does not require genes associated with programmed cell death in yeast. The chemical also inhibits endocytosis and intracellular vesicle trafficking and interferes with vacuolar acidification in yeast and in human cancer cells. These effects can all be ascribed to inhibition of sphingolipid biosynthesis by dihydromotuporamine C. CONCLUSION: Despite their similar conceptual basis, namely altering drug sensitivity by modifying gene dosage, each of the screening approaches provided a distinct set of information that, when integrated, revealed a more complete picture of the mechanism of action of a drug on cells.

Design of phenotypic screens for bioactive chemicals and identification of their targets by genetic and proteomic approaches.

Cell-based screening using phenotypic assays is a useful means of identifying bioactive chemicals for use as tools to elucidate complex cellular processes. However, the chemicals must display sufficient selectivity and their targets have to be identified. We describe how cell-based screening assays can be designed to maximize the likelihood of discovering selective compounds through the choice of positive readouts, low chemical concentrations and long incubation periods. Examining the potency, efficacy and activity range of chemicals can further help set apart those likely to act more specifically. Identifying the cellular targets of active chemicals can be especially demanding. Secondary screens and the cautious use of the candidate approach can help narrow down their mechanisms of action, but biased approaches may lead to the identification of secondary or even irrelevant targets. We discuss strategies for unbiased target identification by sampling potential targets at the genome-wide and proteome-wide levels.

Gene characterization index: assessing the depth of gene annotation.

BACKGROUND: We introduce the Gene Characterization Index, a bioinformatics method for scoring the extent to which a protein-encoding gene is functionally described. Inherently a reflection of human perception, the Gene Characterization Index is applied for assessing the characterization status of individual genes, thus serving the advancement of both genome annotation and applied genomics research by rapid and unbiased identification of groups of uncharacterized genes for diverse applications such as directed functional studies and delineation of novel drug targets. METHODOLOGY/PRINCIPAL FINDINGS: The scoring procedure is based on a global survey of researchers, who assigned characterization scores from 1 (poor) to 10 (extensive) for a sample of genes based on major online resources. By evaluating the survey as training data, we developed a bioinformatics procedure to assign gene characterization scores to all genes in the human genome. We analyzed snapshots of functional genome annotation over a period of 6 years to assess temporal changes reflected by the increase of the average Gene Characterization Index. Applying the Gene Characterization Index to genes within pharmaceutically relevant classes, we confirmed known drug targets as high-scoring genes and revealed potentially interesting novel targets with low characterization indexes. Removing known drug targets and genes linked to sequence-related patent filings from the entirety of indexed genes, we identified sets of low-scoring genes particularly suited for further experimental investigation. CONCLUSIONS/SIGNIFICANCE: The Gene Characterization Index is intended to serve as a tool to the scientific community and granting agencies for focusing resources and efforts on unexplored areas of the genome. The Gene Characterization Index is available from http://cisreg.ca/gci/.

Yeast as a tool to uncover the cellular targets of drugs.

Knowledge of the spectrum of cellular proteins targeted by experimental therapeutic agents would greatly facilitate drug development. However, identifying the targets of drugs is a daunting challenge. The yeast Saccharomyces cerevisiae is a valuable model organism for human diseases and pathways because it is genetically tractable and shares many functional homolog with humans. In yeast, it is possible to increase or decrease the expression level of essentially every gene and measure changes in drug sensitivity to uncover potential targets. It is also possible to infer mechanism of action from comparing the changes in mRNA expression elicited by drug treatment with those induced by gene deletions or by other drugs. Proteins that bind drugs directly can be identified using yeast protein chips. This review of the use of yeast for discovering targets of drugs discusses the advantages and drawbacks of each approach and how combining methods may reveal targets more efficiently.

NovelFam3000--uncharacterized human protein domains conserved across model organisms.

BACKGROUND: Despite significant efforts from the research community, an extensive portion of the proteins encoded by human genes lack an assigned cellular function. Most metazoan proteins are composed of structural and/or functional domains, of which many appear in multiple proteins. Once a domain is characterized in one protein, the presence of a similar sequence in an uncharacterized protein serves as a basis for inference of function. Thus knowledge of a domain's function, or the protein within which it arises, can facilitate the analysis of an entire set of proteins. DESCRIPTION: From the Pfam domain database, we extracted uncharacterized protein domains represented in proteins from humans, worms, and flies. A data centre was created to facilitate the analysis of the uncharacterized domain-containing proteins. The centre both provides researchers with links to dispersed internet resources containing gene-specific experimental data and enables them to post relevant experimental results or comments. For each human gene in the system, a characterization score is posted, allowing users to track the progress of characterization over time or to identify for study uncharacterized domains in well-characterized genes. As a test of the system, a subset of 39 domains was selected for analysis and the experimental results posted to the NovelFam3000 system. For 25 human protein members of these 39 domain families, detailed sub-cellular localizations were determined. Specific observations are presented based on the analysis of the integrated information provided through the online NovelFam3000 system. CONCLUSION: Consistent experimental results between multiple members of a domain family allow for inferences of the domain's functional role. We unite bioinformatics resources and experimental data in order to accelerate the functional characterization of scarcely annotated domain families.

Ulysses - an application for the projection of molecular interactions across species.

We developed Ulysses as a user-oriented system that uses a process called Interolog Analysis for the parallel analysis and display of protein interactions detected in various species. Ulysses was designed to perform such Interolog Analysis by the projection of model organism interaction data onto homologous human proteins, and thus serves as an accelerator for the analysis of uncharacterized human proteins. The relevance of projections was assessed and validated against published reference collections. All source code is freely available, and the Ulysses system can be accessed via a web interface http://www.cisreg.ca/ulysses.

Exploring the foundation of genomics: a northern blot reference set for the comparative analysis of transcript profiling technologies.

In this paper we aim to create a reference data collection of Northern blot results and demonstrate how such a collection can enable a quantitative comparison of modern expression profiling techniques, a central component of functional genomics studies. Historically, Northern blots were the de facto standard for determining RNA transcript levels. However, driven by the demand for analysis of large sets of genes in parallel, high-throughput methods, such as microarrays, dominate modern profiling efforts. To facilitate assessment of these methods, in comparison to Northern blots, we created a database of published Northern results obtained with a standardized commercial multiple tissue blot (dbMTN). In order to demonstrate the utility of the dbMTN collection for technology comparison, we also generated expression profiles for genes across a set of human tissues, using multiple profiling techniques. No method produced profiles that were strongly correlated with the Northern blot data. The highest correlations to the Northern blot data were determined with microarrays for the subset of genes observed to be specifically expressed in a single tissue in the Northern analyses. The database and expression profiling data are available via the project website (http://www.cisreg.ca). We believe that emphasis on multitechnique validation of expression profiles is justified, as the correlation results between platforms are not encouraging on the whole. Supplementary material for this article can be found at: http://www.interscience.wiley.com/jpages/1531-6912/suppmat.