78 research outputs found
QuickGO: a user tutorial for the web-based Gene Ontology browser
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
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
Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/142934/1/bdi12609.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/142934/2/bdi12609_am.pd
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The anti-epileptic drug Valproic Acid (VPA) inhibits steroidogenesis in bovine theca and granulosa cells in vitro
Valproic acid (VPA) is used widely to treat epilepsy and bipolar disorder. Women undergoing VPA treatment reportedly have an increased incidence of polycystic ovarian syndrome (PCOS)-like symptoms including hyperandrogenism and oligo- or amenorrhoea. To investigate potential direct effects of VPA on ovarian steroidogenesis we used primary bovine theca (TC) and granulosa (GC) cells maintained under conditions that preserve their 'follicular' phenotype. Effects of VPA (7.8-500 ”g/ml) on TC were tested with/without LH. Effects of VPA on GC were tested with/without FSH or IGF analogue. VPA reduced (P99% decrease; P<0.0001) with lesser effects on LHR, STAR, CYP11A1 and HSD3B1 mRNA (<90% decrease; P<0.05). VPA only reduced TC progesterone secretion induced by the highest (luteinizing) LH dose tested; TC number was unaffected by VPA. At higher concentrations (125-500 ”g/ml) VPA inhibited basal, FSH- and IGF-stimulated estradiol secretion (P<0.0001) by GC without affecting progesterone secretion or cell number. VPA reversed FSH-induced upregulation of CYP19A1 and HSD17B1 mRNA abundance (P<0.001). The potent histone deacetylase (HDAC) inhibitors trichostatin A and scriptaid also suppressed TC androstenedione secretion and granulosal cell oestrogen secretion suggesting that the action of VPA reflects its HDAC inhibitory properties. In conclusion, these findings refute the hypothesis that VPA has a direct stimulatory action on TC androgen output. On the contrary, VPA inhibits both LH-dependent androgen production and FSH/IGF-dependent estradiol production in this in vitro bovine model, likely by inhibition of HDAC
Internet use by older adults with bipolar disorder: international survey results
Background: The world population is aging and the number of older adults with bipolar disorder is increasing. Digital technologies are viewed as a framework to improve care of older adults with bipolar disorder. This analysis quantifies Internet use by older adults with bipolar disorder as part of a larger survey project about information seeking.
Methods: A paper-based survey about information seeking by patients with bipolar disorder was developed and translated into 12 languages. The survey was anonymous and completed between March 2014 and January 2016 by 1222 patients in 17 countries. All patients were diagnosed by a psychiatrist. General estimating equations were used to account for correlated data.
Results: Overall, 47% of older adults (age 60 years or older) used the Internet versus 87% of younger adults (less than 60 years). More education and having symptoms that interfered with regular activities increased the odds of using the Internet, while being age 60 years or older decreased the odds. Data from 187 older adults and 1021 younger adults were included in the analysis excluding missing values.
Conclusions: Older adults with bipolar disorder use the Internet much less frequently than younger adults. Many older adults do not use the Internet, and technology tools are suitable for some but not all older adults. As more health services are only available online, and more digital tools are developed, there is concern about growing health disparities based on age. Mental health experts should participate in determining the appropriate role for digital tools for older adults with bipolar disorder.We acknowledge support by the Open Access Publication Funds of the SLUB/TU Dresden (Grant No. IN-1502335)
International multi-site survey on the use of online support groups in bipolar disorder
Background: Peer support is an established component of recovery from bipolar disorder, and online support groups may offer opportunities to expand the use of peer support at the patientâs convenience. Prior research in bipolar disorder has reported value from online support groups. Aims: To understand the use of online support groups by patients with bipolar disorder as part of a larger project about information seeking. Methods: The results are based on a one-time, paper-based anonymous survey about information seeking by patients with bipolar disorder, which was translated into 12 languages. The survey was completed between March 2014 and January 2016 and included questions on the use of online support groups. All patients were diagnosed by a psychiatrist. Analysis included descriptive statistics and general estimating equations to account for correlated data. Results and conclusions: The survey was completed by 1222 patients in 17 countries. The patients used the Internet at a percentage similar to the general public. Of the Internet users who looked online for information about bipolar disorder, only 21.0% read or participated in support groups, chats, or forums for bipolar disorder (12.8% of the total sample). Given the benefits reported in prior research, clarification of the role of online support groups in bipolar disorder is needed. With only a minority of patients using online support groups, there are analytical challenges for future studies
Exome sequencing in bipolar disorder identifies AKAP11 as a risk gene shared with schizophrenia
The COMBREX Project: Design, Methodology, and Initial Results
© 2013 Brian P. et al.Prior to the âgenomic era,â when the acquisition of DNA sequence involved significant labor and expense, the sequencing of genes was strongly linked to the experimental characterization of their products. Sequencing at that time directly resulted from the need to understand an experimentally determined phenotype or biochemical activity. Now that DNA sequencing has become orders of magnitude faster and less expensive, focus has shifted to sequencing entire genomes. Since biochemistry and genetics have not, by and large, enjoyed the same improvement of scale, public sequence repositories now predominantly contain putative protein sequences for which there is no direct experimental evidence of function. Computational approaches attempt to leverage evidence associated with the ever-smaller fraction of experimentally analyzed proteins to predict function for these putative proteins. Maximizing our understanding of function over the universe of proteins in toto requires not only robust computational methods of inference but also a judicious allocation of experimental resources, focusing on proteins whose experimental characterization will maximize the number and accuracy of follow-on predictions.COMBREX is funded by a GO grant from the National Institute of General Medical Sciences (NIGMS) (1RC2GM092602-01).Peer Reviewe
Association of Attention-Deficit/Hyperactivity Disorder and Depression Polygenic Scores with Lithium Response: A Consortium for Lithium Genetics Study
Response to lithium varies widely between individuals with bipolar disorder (BD). Polygenic risk scores (PRSs) can uncover pharmacogenomics effects and may help predict drug response. Patients (N = 2,510) with BD were assessed for long-term lithium response in the Consortium on Lithium Genetics using the Retrospective Criteria of Long-Term Treatment Response in Research Subjects with Bipolar Disorder score. PRSs for attention-deficit/hyperactivity disorder (ADHD), major depressive disorder (MDD), and schizophrenia (SCZ) were computed using lassosum and in a model including all three PRSs and other covariates, and the PRS of ADHD (ÎČ = â0.14; 95% confidence interval [CI]: â0.24 to â0.03; p value = 0.010) and MDD (ÎČ = â0.16; 95% CI: â0.27 to â0.04; p value = 0.005) predicted worse quantitative lithium response. A higher SCZ PRS was associated with higher rates of medication nonadherence (OR = 1.61; 95% CI: 1.34â1.93; p value = 2eâ7). This study indicates that genetic risk for ADHD and depression may influence lithium treatment response. Interestingly, a higher SCZ PRS was associated with poor adherence, which can negatively impact treatment response. Incorporating genetic risk of ADHD, depression, and SCZ in combination with clinical risk may lead to better clinical care for patients with BD
Localization of type 1 diabetes susceptibility to the MHC class I genes HLA-B and HLA-A
The major histocompatibility complex (MHC) on chromosome 6 is associated with susceptibility to more common diseases than any other region of the human genome, including almost all disorders classified as autoimmune. In type 1 diabetes the major genetic susceptibility determinants have been mapped to the MHC class II genes HLA-DQB1 and HLA-DRB1 (refs 1-3), but these genes cannot completely explain the association between type 1 diabetes and the MHC region. Owing to the region's extreme gene density, the multiplicity of disease-associated alleles, strong associations between alleles, limited genotyping capability, and inadequate statistical approaches and sample sizes, which, and how many, loci within the MHC determine susceptibility remains unclear. Here, in several large type 1 diabetes data sets, we analyse a combined total of 1,729 polymorphisms, and apply statistical methods - recursive partitioning and regression - to pinpoint disease susceptibility to the MHC class I genes HLA-B and HLA-A (risk ratios >1.5; Pcombined = 2.01 à 10-19 and 2.35 à 10-13, respectively) in addition to the established associations of the MHC class II genes. Other loci with smaller and/or rarer effects might also be involved, but to find these, future searches must take into account both the HLA class II and class I genes and use even larger samples. Taken together with previous studies, we conclude that MHC-class-I-mediated events, principally involving HLA-B*39, contribute to the aetiology of type 1 diabetes. ©2007 Nature Publishing Group
The CAFA challenge reports improved protein function prediction and new functional annotations for hundreds of genes through experimental screens
Background The Critical Assessment of Functional Annotation (CAFA) is an ongoing, global, community-driven effort to evaluate and improve the computational annotation of protein function. Results Here, we report on the results of the third CAFA challenge, CAFA3, that featured an expanded analysis over the previous CAFA rounds, both in terms of volume of data analyzed and the types of analysis performed. In a novel and major new development, computational predictions and assessment goals drove some of the experimental assays, resulting in new functional annotations for more than 1000 genes. Specifically, we performed experimental whole-genome mutation screening in Candida albicans and Pseudomonas aureginosa genomes, which provided us with genome-wide experimental data for genes associated with biofilm formation and motility. We further performed targeted assays on selected genes in Drosophila melanogaster, which we suspected of being involved in long-term memory. Conclusion We conclude that while predictions of the molecular function and biological process annotations have slightly improved over time, those of the cellular component have not. Term-centric prediction of experimental annotations remains equally challenging; although the performance of the top methods is significantly better than the expectations set by baseline methods in C. albicans and D. melanogaster, it leaves considerable room and need for improvement. Finally, we report that the CAFA community now involves a broad range of participants with expertise in bioinformatics, biological experimentation, biocuration, and bio-ontologies, working together to improve functional annotation, computational function prediction, and our ability to manage big data in the era of large experimental screens.Peer reviewe
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