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Lee B, Yu MS, Song JG, Lee HM, Kim HW, Na D. Corydalis ternata Nakai Alleviates Cognitive Decline in Alzheimer's Disease by Reducing β-Amyloid and Neuroinflammation. Rejuvenation Res 2024; 27:87-101. [PMID: 38545769 DOI: 10.1089/rej.2023.0069] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/25/2024] Open
Abstract
Recently, natural herbs have gained increasing attention owing to their comparatively low toxicity levels and the abundance of historical medical documentation regarding their use. Nevertheless, owing to a lack of knowledge regarding these herbs and their compounds, attempts to find those that could be beneficial for treating diseases have often been ad hoc; thus, there is now a growing demand for an in silico method to identify beneficial herbs. In this study, we present a computational approach for identifying natural herbs specifically effective in treating cognitive decline in Alzheimer's disease (AD) sufferers, which analyzes the similarities between herbal compounds and known drugs targeting AD-related proteins. Our in silico method suggests that Corydalis ternata can improve cognitive decline in AD sufferers. Behavioral tests with an AD mouse model for the confirmation of the in silico prediction reveals that C. ternata significantly alleviated the cognitive decline (memory and motor functions) caused by neurodegeneration. Further pathology analyses reveal that C. ternata decreases the level of Aβ plaques, reduces neuroinflammation, and promotes autophagy flux, and thus C. ternata can be clinically effective for preventing mild cognitive impairment during the early stages of AD. These findings highlight the potential utility of our in silico method and the potential clinical application of the identified natural herb in treating and preventing AD.
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Affiliation(s)
- Bomi Lee
- Department of Bio-Integrated Science and Technology, College of Life Sciences, Sejong University, Seoul, Republic of Korea
| | - Myeong-Sang Yu
- Department of Biomedical Engineering, Chung-Ang University, Seoul, Republic of Korea
| | - Jae Gwang Song
- Department of Bio-Integrated Science and Technology, College of Life Sciences, Sejong University, Seoul, Republic of Korea
| | - Hyang-Mi Lee
- Department of Biomedical Engineering, Chung-Ang University, Seoul, Republic of Korea
| | - Hyung Wook Kim
- Department of Bio-Integrated Science and Technology, College of Life Sciences, Sejong University, Seoul, Republic of Korea
| | - Dokyun Na
- Department of Biomedical Engineering, Chung-Ang University, Seoul, Republic of Korea
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Na D, Lim DH, Hong JS, Lee HM, Cho D, Yu MS, Shaker B, Ren J, Lee B, Song JG, Oh Y, Lee K, Oh KS, Lee MY, Choi MS, Choi HS, Kim YH, Bui JM, Lee K, Kim HW, Lee YS, Gsponer J. A multi-layered network model identifies Akt1 as a common modulator of neurodegeneration. Mol Syst Biol 2023; 19:e11801. [PMID: 37984409 DOI: 10.15252/msb.202311801] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2023] [Revised: 10/25/2023] [Accepted: 10/27/2023] [Indexed: 11/22/2023] Open
Abstract
The accumulation of misfolded and aggregated proteins is a hallmark of neurodegenerative proteinopathies. Although multiple genetic loci have been associated with specific neurodegenerative diseases (NDs), molecular mechanisms that may have a broader relevance for most or all proteinopathies remain poorly resolved. In this study, we developed a multi-layered network expansion (MLnet) model to predict protein modifiers that are common to a group of diseases and, therefore, may have broader pathophysiological relevance for that group. When applied to the four NDs Alzheimer's disease (AD), Huntington's disease, and spinocerebellar ataxia types 1 and 3, we predicted multiple members of the insulin pathway, including PDK1, Akt1, InR, and sgg (GSK-3β), as common modifiers. We validated these modifiers with the help of four Drosophila ND models. Further evaluation of Akt1 in human cell-based ND models revealed that activation of Akt1 signaling by the small molecule SC79 increased cell viability in all models. Moreover, treatment of AD model mice with SC79 enhanced their long-term memory and ameliorated dysregulated anxiety levels, which are commonly affected in AD patients. These findings validate MLnet as a valuable tool to uncover molecular pathways and proteins involved in the pathophysiology of entire disease groups and identify potential therapeutic targets that have relevance across disease boundaries. MLnet can be used for any group of diseases and is available as a web tool at http://ssbio.cau.ac.kr/software/mlnet.
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Affiliation(s)
- Dokyun Na
- Department of Biomedical Engineering, Chung-Ang University, Seoul, Republic of Korea
| | - Do-Hwan Lim
- College of Life Sciences and Biotechnology, Korea University, Seoul, Republic of Korea
- School of Systems Biomedical Science, Soongsil University, Seoul, Republic of Korea
| | - Jae-Sang Hong
- College of Life Sciences and Biotechnology, Korea University, Seoul, Republic of Korea
- Center for Systems Biology, Massachusetts General Hospital, Boston, MA, USA
| | - Hyang-Mi Lee
- Department of Biomedical Engineering, Chung-Ang University, Seoul, Republic of Korea
| | - Daeahn Cho
- Department of Biomedical Engineering, Chung-Ang University, Seoul, Republic of Korea
| | - Myeong-Sang Yu
- Department of Biomedical Engineering, Chung-Ang University, Seoul, Republic of Korea
| | - Bilal Shaker
- Department of Biomedical Engineering, Chung-Ang University, Seoul, Republic of Korea
| | - Jun Ren
- Department of Biomedical Engineering, Chung-Ang University, Seoul, Republic of Korea
| | - Bomi Lee
- College of Life Sciences, Sejong University, Seoul, Republic of Korea
| | - Jae Gwang Song
- College of Life Sciences, Sejong University, Seoul, Republic of Korea
| | - Yuna Oh
- Korea Institute of Science and Technology, Seoul, Republic of Korea
| | - Kyungeun Lee
- Korea Institute of Science and Technology, Seoul, Republic of Korea
| | - Kwang-Seok Oh
- Information-based Drug Research Center, Korea Research Institute of Chemical Technology, Deajeon, Republic of Korea
| | - Mi Young Lee
- Information-based Drug Research Center, Korea Research Institute of Chemical Technology, Deajeon, Republic of Korea
| | - Min-Seok Choi
- College of Life Sciences and Biotechnology, Korea University, Seoul, Republic of Korea
| | - Han Saem Choi
- College of Life Sciences, Sejong University, Seoul, Republic of Korea
| | - Yang-Hee Kim
- College of Life Sciences, Sejong University, Seoul, Republic of Korea
| | - Jennifer M Bui
- Department of Biochemistry and Molecular Biology, Michael Smith Laboratories, University of British Columbia, Vancouver, BC, Canada
| | - Kangseok Lee
- Department of Life Science, Chung-Ang University, Seoul, Republic of Korea
| | - Hyung Wook Kim
- College of Life Sciences, Sejong University, Seoul, Republic of Korea
| | - Young Sik Lee
- College of Life Sciences and Biotechnology, Korea University, Seoul, Republic of Korea
| | - Jörg Gsponer
- Department of Biochemistry and Molecular Biology, Michael Smith Laboratories, University of British Columbia, Vancouver, BC, Canada
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Ballouz S, Pavlidis P, Gillis J. Using predictive specificity to determine when gene set analysis is biologically meaningful. Nucleic Acids Res 2018; 45:e20. [PMID: 28204549 PMCID: PMC5389513 DOI: 10.1093/nar/gkw957] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2016] [Revised: 10/04/2016] [Accepted: 10/10/2016] [Indexed: 11/14/2022] Open
Abstract
Gene set analysis, which translates gene lists into enriched functions, is among the most common bioinformatic methods. Yet few would advocate taking the results at face value. Not only is there no agreement on the algorithms themselves, there is no agreement on how to benchmark them. In this paper, we evaluate the robustness and uniqueness of enrichment results as a means of assessing methods even where correctness is unknown. We show that heavily annotated (‘multifunctional’) genes are likely to appear in genomics study results and drive the generation of biologically non-specific enrichment results as well as highly fragile significances. By providing a means of determining where enrichment analyses report non-specific and non-robust findings, we are able to assess where we can be confident in their use. We find significant progress in recent bias correction methods for enrichment and provide our own software implementation. Our approach can be readily adapted to any pre-existing package.
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Affiliation(s)
- Sara Ballouz
- Stanley Institute for Cognitive Genomics, Cold Spring Harbor Laboratory, Woodbury, NY 11797, USA
| | - Paul Pavlidis
- Department of Psychiatry and Michael Smith Laboratories, University of British Columbia, Vancouver, BC, V6T 1Z4, Canada
| | - Jesse Gillis
- Stanley Institute for Cognitive Genomics, Cold Spring Harbor Laboratory, Woodbury, NY 11797, USA
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Transcriptomic characterization of MRI contrast with focus on the T1-w/T2-w ratio in the cerebral cortex. Neuroimage 2018; 174:504-517. [PMID: 29567503 PMCID: PMC6450807 DOI: 10.1016/j.neuroimage.2018.03.027] [Citation(s) in RCA: 44] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2018] [Revised: 03/12/2018] [Accepted: 03/14/2018] [Indexed: 01/24/2023] Open
Abstract
Magnetic resonance (MR) images of the brain are of immense clinical and research utility. At the atomic and subatomic levels, the sources of MR signals are well understood. However, we lack a comprehensive understanding of the macromolecular correlates of MR signal contrast. To address this gap, we used genome-wide measurements to correlate gene expression with MR signal intensity across the cerebral cortex in the Allen Human Brain Atlas (AHBA). We focused on the ratio of T1-weighted and T2-weighted intensities (T1-w/T2-w ratio image), which is considered to be a useful proxy for myelin content. As expected, we found enrichment of positive correlations between myelin-associated genes and the ratio image, supporting its use as a myelin marker. Genome-wide, there was an association with protein mass, with genes coding for heavier proteins expressed in regions with high T1-w/T2-w values. Oligodendrocyte gene markers were strongly correlated with the T1-w/T2-w ratio, but this was not driven by myelin-associated genes. Mitochondrial genes exhibit the strongest relationship, showing higher expression in regions with low T1-w/T2-w ratio. This may be due to the pH gradient in mitochondria as genes up-regulated by pH in the brain were also highly correlated with the ratio. While we corroborate associations with myelin and synaptic plasticity, differences in the T1-w/T2-w ratio across the cortex are more strongly linked to molecule size, oligodendrocyte markers, mitochondria, and pH. We evaluate correlations between AHBA transcriptomic measurements and a group averaged T1-w/T2-w ratio image, showing agreement with in-sample results. Expanding our analysis to the whole brain results in strong positive T1-w/T2-w correlations for immune system, inflammatory disease, and microglia marker genes. Genes with negative correlations were enriched for neuron markers and synaptic plasticity genes. Lastly, our findings are similar when performed on T1-w or inverted T2-w intensities alone. These results provide a molecular characterization of MR contrast that will aid interpretation of future MR studies of the brain.
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Ballouz S, Gillis J. Strength of functional signature correlates with effect size in autism. Genome Med 2017; 9:64. [PMID: 28687074 PMCID: PMC5501949 DOI: 10.1186/s13073-017-0455-8] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2017] [Accepted: 06/23/2017] [Indexed: 01/03/2023] Open
Abstract
BACKGROUND Disagreements over genetic signatures associated with disease have been particularly prominent in the field of psychiatric genetics, creating a sharp divide between disease burdens attributed to common and rare variation, with study designs independently targeting each. Meta-analysis within each of these study designs is routine, whether using raw data or summary statistics, but combining results across study designs is atypical. However, tests of functional convergence are used across all study designs, where candidate gene sets are assessed for overlaps with previously known properties. This suggests one possible avenue for combining not study data, but the functional conclusions that they reach. METHOD In this work, we test for functional convergence in autism spectrum disorder (ASD) across different study types, and specifically whether the degree to which a gene is implicated in autism is correlated with the degree to which it drives functional convergence. Because different study designs are distinguishable by their differences in effect size, this also provides a unified means of incorporating the impact of study design into the analysis of convergence. RESULTS We detected remarkably significant positive trends in aggregate (p < 2.2e-16) with 14 individually significant properties (false discovery rate <0.01), many in areas researchers have targeted based on different reasoning, such as the fragile X mental retardation protein (FMRP) interactor enrichment (false discovery rate 0.003). We are also able to detect novel technical effects and we see that network enrichment from protein-protein interaction data is heavily confounded with study design, arising readily in control data. CONCLUSIONS We see a convergent functional signal for a subset of known and novel functions in ASD from all sources of genetic variation. Meta-analytic approaches explicitly accounting for different study designs can be adapted to other diseases to discover novel functional associations and increase statistical power.
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Affiliation(s)
- Sara Ballouz
- The Stanley Institute for Cognitive Genomics, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724 USA
| | - Jesse Gillis
- The Stanley Institute for Cognitive Genomics, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724 USA
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Tan PPC, Rogic S, Zoubarev A, McDonald C, Lui F, Charathsandran G, Jacobson M, Belmadani M, Leong J, Van Rossum T, Portales-Casamar E, Qiao Y, Calli K, Liu X, Hudson M, Rajcan-Separovic E, Lewis MES, Pavlidis P. Interactive Exploration, Analysis, and Visualization of Complex Phenome-Genome Datasets with ASPIREdb. Hum Mutat 2016; 37:719-26. [PMID: 27158917 PMCID: PMC4940263 DOI: 10.1002/humu.23011] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2015] [Accepted: 04/28/2016] [Indexed: 11/10/2022]
Abstract
Identifying variants causal for complex genetic disorders is challenging. With the advent of whole-exome and whole-genome sequencing, computational tools are needed to explore and analyze the list of variants for further validation. Correlating genetic variants with subject phenotype is crucial for the interpretation of the disease-causing mutations. Often such work is done by teams of researchers who need to share information and coordinate activities. To this end, we have developed a powerful, easy to use Web application, ASPIREdb, which allows researchers to search, organize, analyze, and visualize variants and phenotypes associated with a set of human subjects. Investigators can annotate variants using publicly available reference databases and build powerful queries to identify subjects or variants of interest. Functional information and phenotypic associations of these genes are made accessible as well. Burden analysis and additional reporting tools allow investigation of variant properties and phenotype characteristics. Projects can be shared, allowing researchers to work collaboratively to build queries and annotate the data. We demonstrate ASPIREdb's functionality using publicly available data sets, showing how the software can be used to accomplish goals that might otherwise require specialized bioinformatics expertise. ASPIREdb is available at http://aspiredb.chibi.ubc.ca.
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Affiliation(s)
- Powell Patrick Cheng Tan
- Michael Smith Laboratories and Department of Psychiatry, University of British Columbia, Vancouver, BC, Canada
| | - Sanja Rogic
- Michael Smith Laboratories and Department of Psychiatry, University of British Columbia, Vancouver, BC, Canada
| | - Anton Zoubarev
- Michael Smith Laboratories and Department of Psychiatry, University of British Columbia, Vancouver, BC, Canada
| | - Cameron McDonald
- Michael Smith Laboratories and Department of Psychiatry, University of British Columbia, Vancouver, BC, Canada
| | - Frances Lui
- Michael Smith Laboratories and Department of Psychiatry, University of British Columbia, Vancouver, BC, Canada
| | - Gayathiri Charathsandran
- Michael Smith Laboratories and Department of Psychiatry, University of British Columbia, Vancouver, BC, Canada
| | - Matthew Jacobson
- Michael Smith Laboratories and Department of Psychiatry, University of British Columbia, Vancouver, BC, Canada
| | - Manuel Belmadani
- Michael Smith Laboratories and Department of Psychiatry, University of British Columbia, Vancouver, BC, Canada
| | - Justin Leong
- Michael Smith Laboratories and Department of Psychiatry, University of British Columbia, Vancouver, BC, Canada
| | - Thea Van Rossum
- Michael Smith Laboratories and Department of Psychiatry, University of British Columbia, Vancouver, BC, Canada
| | - Elodie Portales-Casamar
- Michael Smith Laboratories and Department of Psychiatry, University of British Columbia, Vancouver, BC, Canada
| | - Ying Qiao
- Department of Pathology, BC Child and Family Research Institute, University of British Columbia (UBC), 950 West 28th, Room 3060, Vancouver, BC V5Z 4H4, Canada
- Department of Medical Genetics, BC Child and Family Research Institute, UBC, Vancouver, BC V6H 3N1, Canada
| | - Kristina Calli
- Department of Medical Genetics, BC Child and Family Research Institute, UBC, Vancouver, BC V6H 3N1, Canada
| | - Xudong Liu
- Department of Psychiatry, Queen's University, Kingston, Ontario K7L 3N6 Canada
- Ongwanada Resource Cente, Kingston, Ontario K7L 3N6 Canada
| | - Melissa Hudson
- Department of Psychiatry, Queen's University, Kingston, Ontario K7L 3N6 Canada
| | - Evica Rajcan-Separovic
- Department of Pathology, BC Child and Family Research Institute, University of British Columbia (UBC), 950 West 28th, Room 3060, Vancouver, BC V5Z 4H4, Canada
| | - ME Suzanne Lewis
- Department of Medical Genetics, BC Child and Family Research Institute, UBC, Vancouver, BC V6H 3N1, Canada
| | - Paul Pavlidis
- Michael Smith Laboratories and Department of Psychiatry, University of British Columbia, Vancouver, BC, Canada
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Portales-Casamar E, Lussier AA, Jones MJ, MacIsaac JL, Edgar RD, Mah SM, Barhdadi A, Provost S, Lemieux-Perreault LP, Cynader MS, Chudley AE, Dubé MP, Reynolds JN, Pavlidis P, Kobor MS. DNA methylation signature of human fetal alcohol spectrum disorder. Epigenetics Chromatin 2016; 9:25. [PMID: 27358653 PMCID: PMC4926300 DOI: 10.1186/s13072-016-0074-4] [Citation(s) in RCA: 91] [Impact Index Per Article: 11.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2016] [Accepted: 06/17/2016] [Indexed: 02/06/2023] Open
Abstract
Background Prenatal alcohol exposure is the leading preventable cause of behavioral and cognitive deficits, which may affect between 2 and 5 % of children in North America. While the underlying mechanisms of alcohol’s effects on development remain relatively unknown, emerging evidence implicates epigenetic mechanisms in mediating the range of symptoms observed in children with fetal alcohol spectrum disorder (FASD). Thus, we investigated the effects of prenatal alcohol exposure on genome-wide DNA methylation in the NeuroDevNet FASD cohort, the largest cohort of human FASD samples to date. Methods Genome-wide DNA methylation patterns of buccal epithelial cells (BECs) were analyzed using the Illumina HumanMethylation450 array in a Canadian cohort of 206 children (110 FASD and 96 controls). Genotyping was performed in parallel using the Infinium HumanOmni2.5-Quad v1.0 BeadChip. Results After correcting for the effects of genetic background, we found 658 significantly differentially methylated sites between FASD cases and controls, with 41 displaying differences in percent methylation change >5 %. Furthermore, 101 differentially methylated regions containing two or more CpGs were also identified, overlapping with 95 different genes. The majority of differentially methylated genes were highly expressed at the level of mRNA in brain samples from the Allen Brain Atlas, and independent DNA methylation data from cortical brain samples showed high correlations with BEC DNA methylation patterns. Finally, overrepresentation analysis of genes with up-methylated CpGs revealed a significant enrichment for neurodevelopmental processes and diseases, such as anxiety, epilepsy, and autism spectrum disorders. Conclusions These findings suggested that prenatal alcohol exposure is associated with distinct DNA methylation patterns in children and adolescents, raising the possibility of an epigenetic biomarker of FASD. Electronic supplementary material The online version of this article (doi:10.1186/s13072-016-0074-4) contains supplementary material, which is available to authorized users.
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Affiliation(s)
| | - Alexandre A Lussier
- Department of Medical Genetics, Centre for Molecular Medicine and Therapeutics, Child and Family Research Institute, University of British Columbia, Vancouver, BC Canada
| | - Meaghan J Jones
- Department of Medical Genetics, Centre for Molecular Medicine and Therapeutics, Child and Family Research Institute, University of British Columbia, Vancouver, BC Canada
| | - Julia L MacIsaac
- Department of Medical Genetics, Centre for Molecular Medicine and Therapeutics, Child and Family Research Institute, University of British Columbia, Vancouver, BC Canada
| | - Rachel D Edgar
- Department of Medical Genetics, Centre for Molecular Medicine and Therapeutics, Child and Family Research Institute, University of British Columbia, Vancouver, BC Canada
| | - Sarah M Mah
- Department of Medical Genetics, Centre for Molecular Medicine and Therapeutics, Child and Family Research Institute, University of British Columbia, Vancouver, BC Canada
| | - Amina Barhdadi
- Beaulieu-Saucier Pharmacogenomics Centre, Montreal Heart Institute, Université de Montréal, Montreal, QC Canada
| | - Sylvie Provost
- Beaulieu-Saucier Pharmacogenomics Centre, Montreal Heart Institute, Université de Montréal, Montreal, QC Canada
| | | | - Max S Cynader
- Brain Research Centre, University of British Columbia, Vancouver, BC Canada
| | - Albert E Chudley
- Department of Pediatrics and Child Health, Faculty of Medicine, University of Manitoba, Winnipeg, MB Canada.,Department of Biochemistry and Medical Genetics, Faculty of Medicine, University of Manitoba, Winnipeg, MB Canada
| | - Marie-Pierre Dubé
- Beaulieu-Saucier Pharmacogenomics Centre, Montreal Heart Institute, Université de Montréal, Montreal, QC Canada.,Faculty of Medicine, Université de Montréal, Montreal, QC Canada
| | - James N Reynolds
- Centre for Neuroscience Studies, Queen's University, Kingston, ON Canada
| | - Paul Pavlidis
- Centre for High-Throughput Biology, University of British Columbia, Vancouver, BC Canada
| | - Michael S Kobor
- Department of Medical Genetics, Centre for Molecular Medicine and Therapeutics, Child and Family Research Institute, University of British Columbia, Vancouver, BC Canada.,Human Early Learning Partnership, School of Population and Public Health, University of British Columbia, Vancouver, British Columbia Canada
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Rogic S, Wong A, Pavlidis P. Meta-Analysis of Gene Expression Patterns in Animal Models of Prenatal Alcohol Exposure Suggests Role for Protein Synthesis Inhibition and Chromatin Remodeling. Alcohol Clin Exp Res 2016; 40:717-27. [PMID: 26996386 PMCID: PMC5310543 DOI: 10.1111/acer.13007] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2015] [Accepted: 01/11/2016] [Indexed: 12/23/2022]
Abstract
BACKGROUND Prenatal alcohol exposure (PAE) can result in an array of morphological, behavioral, and neurobiological deficits that can range in their severity. Despite extensive research in the field and a significant progress made, especially in understanding the range of possible malformations and neurobehavioral abnormalities, the molecular mechanisms of alcohol responses in development are still not well understood. There have been multiple transcriptomic studies looking at the changes in gene expression after PAE in animal models; however, there is a limited apparent consensus among the reported findings. In an effort to address this issue, we performed a comprehensive re-analysis and meta-analysis of all suitable, publically available expression data sets. METHODS We assembled 10 microarray data sets of gene expression after PAE in mouse and rat models consisting of samples from a total of 63 ethanol (EtOH)-exposed and 80 control animals. We re-analyzed each data set for differential expression and then used the results to perform meta-analyses considering all data sets together or grouping them by time or duration of exposure (pre- and postnatal, acute and chronic, respectively). We performed network and Gene Ontology enrichment analysis to further characterize the identified signatures. RESULTS For each subanalysis, we identified signatures of differential expressed genes that show support from multiple studies. Overall, the changes in gene expression were more extensive after acute EtOH treatment during prenatal development than in other models. Considering the analysis of all the data together, we identified a robust core signature of 104 genes down-regulated after PAE, with no up-regulated genes. Functional analysis reveals over representation of genes involved in protein synthesis, mRNA splicing, and chromatin organization. CONCLUSIONS Our meta-analysis shows that existing studies, despite superficial dissimilarity in findings, share features that allow us to identify a common core signature set of transcriptome changes in PAE. This is an important step to identifying the biological processes that underlie the etiology of fetal alcohol spectrum disorders.
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Affiliation(s)
- Sanja Rogic
- Department of Psychiatry and Michael Smith Laboratories, University of British Columbia, Vancouver, BC, Canada
| | - Albertina Wong
- Department of Psychiatry and Michael Smith Laboratories, University of British Columbia, Vancouver, BC, Canada
| | - Paul Pavlidis
- Department of Psychiatry and Michael Smith Laboratories, University of British Columbia, Vancouver, BC, Canada
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Verleyen W, Ballouz S, Gillis J. Positive and negative forms of replicability in gene network analysis. Bioinformatics 2015; 32:1065-73. [PMID: 26668004 DOI: 10.1093/bioinformatics/btv734] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2015] [Accepted: 12/09/2015] [Indexed: 02/07/2023] Open
Abstract
MOTIVATION Gene networks have become a central tool in the analysis of genomic data but are widely regarded as hard to interpret. This has motivated a great deal of comparative evaluation and research into best practices. We explore the possibility that this may lead to overfitting in the field as a whole. RESULTS We construct a model of 'research communities' sampling from real gene network data and machine learning methods to characterize performance trends. Our analysis reveals an important principle limiting the value of replication, namely that targeting it directly causes 'easy' or uninformative replication to dominate analyses. We find that when sampling across network data and algorithms with similar variability, the relationship between replicability and accuracy is positive (Spearman's correlation, rs ∼0.33) but where no such constraint is imposed, the relationship becomes negative for a given gene function (rs ∼ -0.13). We predict factors driving replicability in some prior analyses of gene networks and show that they are unconnected with the correctness of the original result, instead reflecting replicable biases. Without these biases, the original results also vanish replicably. We show these effects can occur quite far upstream in network data and that there is a strong tendency within protein-protein interaction data for highly replicable interactions to be associated with poor quality control. AVAILABILITY AND IMPLEMENTATION Algorithms, network data and a guide to the code available at: https://github.com/wimverleyen/AggregateGeneFunctionPrediction CONTACT jgillis@cshl.edu SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- W Verleyen
- Stanley Institute for Cognitive Genomics, Cold Spring Harbor Laboratory, 500 Sunnyside Boulevard Woodbury, NY 11797, USA
| | - S Ballouz
- Stanley Institute for Cognitive Genomics, Cold Spring Harbor Laboratory, 500 Sunnyside Boulevard Woodbury, NY 11797, USA
| | - J Gillis
- Stanley Institute for Cognitive Genomics, Cold Spring Harbor Laboratory, 500 Sunnyside Boulevard Woodbury, NY 11797, USA
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Lussier AA, Stepien KA, Neumann SM, Pavlidis P, Kobor MS, Weinberg J. Prenatal alcohol exposure alters steady-state and activated gene expression in the adult rat brain. Alcohol Clin Exp Res 2015; 39:251-61. [PMID: 25684047 DOI: 10.1111/acer.12622] [Citation(s) in RCA: 29] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2014] [Accepted: 10/28/2014] [Indexed: 12/15/2022]
Abstract
BACKGROUND Prenatal alcohol exposure (PAE) is associated with alterations in numerous physiological systems, including the stress and immune systems. We have previously shown that PAE increases the course and severity of arthritis in an adjuvant-induced arthritis (AA) model. While the molecular mechanisms underlying these effects are not fully known, changes in neural gene expression are emerging as important factors in the etiology of PAE effects. As the prefrontal cortex (PFC) and hippocampus (HPC) play key roles in neuroimmune function, PAE-induced alterations to their transcriptome may underlie abnormal steady-state functions and responses to immune challenge. This study examined brains from adult PAE and control females from our recent AA study to determine whether PAE causes long-term alterations in gene expression and whether these mediate the altered severity and course of arthritis in PAE females. METHODS Adult females from PAE, pair-fed (PF), and ad libitum-fed control (C) groups were injected with either saline or complete Freund's adjuvant. Animals were terminated at the peak of inflammation or during resolution (Days 16 and 39 postinjection, respectively); cohorts of saline-injected PAE, PF, and C females were terminated in parallel. Gene expression was analyzed in the PFC and HPC using whole-genome mRNA expression microarrays. RESULTS Significant changes in gene expression in both the PFC and HPC were found in PAE compared to controls in response to ethanol exposure alone (saline-injected females), including genes involved in neurodevelopment, apoptosis, and energy metabolism. Moreover, in response to inflammation (adjuvant-injected females), PAE animals showed unique expression patterns, while failing to exhibit the activation of genes and regulators involved in the immune response observed in control and pair-fed animals. CONCLUSIONS These results support the hypothesis that PAE affects neuroimmune function at the level of gene expression, demonstrating long-term effects of PAE on the central nervous system response under steady-state conditions and following an inflammatory insult.
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Affiliation(s)
- Alexandre A Lussier
- Department of Medical Genetics, University of British Columbia, Vancouver, British Columbia, Canada
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Schriml LM, Mitraka E. The Disease Ontology: fostering interoperability between biological and clinical human disease-related data. Mamm Genome 2015; 26:584-9. [PMID: 26093607 PMCID: PMC4602048 DOI: 10.1007/s00335-015-9576-9] [Citation(s) in RCA: 50] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2015] [Accepted: 06/08/2015] [Indexed: 12/15/2022]
Abstract
The Disease Ontology (DO) enables cross-domain data integration through a common standard of human disease terms and their etiological descriptions. Standardized disease descriptors that are integrated across mammalian genomic resources provide a human-readable, machine-interpretable, community-driven disease corpus that unifies the representation of human common and rare diseases. The DO is populated by consensus-driven disease data descriptors that incorporate disease terms utilized by genomic and genetic projects and resources engaged in studies to understand the genetics of human disease through the study of model organisms. The DO project serves multiple roles for the model organism community by providing: (1) a structured "backbone" of disease concepts represented among the model organism databases; (2) authoritative disease curation services to researchers and resource providers; and (3) development of subsets of the DO representative of human diseases annotated to animal models curated within the model organism databases.
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Affiliation(s)
- Lynn M Schriml
- Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD, 21201, USA.
| | - Elvira Mitraka
- Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD, 21201, USA
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Ch'ng C, Kwok W, Rogic S, Pavlidis P. Meta-Analysis of Gene Expression in Autism Spectrum Disorder. Autism Res 2015; 8:593-608. [PMID: 25720351 DOI: 10.1002/aur.1475] [Citation(s) in RCA: 37] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2013] [Accepted: 02/04/2015] [Indexed: 02/04/2023]
Abstract
Autism spectrum disorders (ASD) are clinically heterogeneous and biologically complex. In general it remains unclear, what biological factors lead to changes in the brains of autistic individuals. A considerable number of transcriptome analyses have been performed in attempts to address this question, but their findings lack a clear consensus. As a result, each of these individual studies has not led to any significant advance in understanding the autistic phenotype as a whole. Here, we report a meta-analysis of more than 1000 microarrays across twelve independent studies on expression changes in ASD compared to unaffected individuals, in both blood and brain tissues. We identified a number of known and novel genes that are consistently differentially expressed across three studies of the brain (71 samples in total). A subset of the highly ranked genes is suggestive of effects on mitochondrial function. In blood, consistent changes were more difficult to identify, despite individual studies tending to exhibit larger effects than the brain studies. Our results are the strongest evidence to date of a common transcriptome signature in the brains of individuals with ASD.
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Affiliation(s)
- Carolyn Ch'ng
- Graduate Program in Bioinformatics, University of British Columbia, Vancouver, Canada, V6T 1Z4 (C.C.).,Center for High Throughput Biology, University of British Columbia, Vancouver, Canada, V6T 1Z4 (C.C., W.K., S.R., P.P.)
| | - Willie Kwok
- Center for High Throughput Biology, University of British Columbia, Vancouver, Canada, V6T 1Z4 (C.C., W.K., S.R., P.P.).,Department of Psychiatry, University of British Columbia, Vancouver, Canada, V6T 1Z4 (W.K., S.R., P.P.)
| | - Sanja Rogic
- Center for High Throughput Biology, University of British Columbia, Vancouver, Canada, V6T 1Z4 (C.C., W.K., S.R., P.P.).,Department of Psychiatry, University of British Columbia, Vancouver, Canada, V6T 1Z4 (W.K., S.R., P.P.)
| | - Paul Pavlidis
- Center for High Throughput Biology, University of British Columbia, Vancouver, Canada, V6T 1Z4 (C.C., W.K., S.R., P.P.).,Department of Psychiatry, University of British Columbia, Vancouver, Canada, V6T 1Z4 (W.K., S.R., P.P.)
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Kibbe WA, Arze C, Felix V, Mitraka E, Bolton E, Fu G, Mungall CJ, Binder JX, Malone J, Vasant D, Parkinson H, Schriml LM. Disease Ontology 2015 update: an expanded and updated database of human diseases for linking biomedical knowledge through disease data. Nucleic Acids Res 2014; 43:D1071-8. [PMID: 25348409 PMCID: PMC4383880 DOI: 10.1093/nar/gku1011] [Citation(s) in RCA: 372] [Impact Index Per Article: 37.2] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/02/2023] Open
Abstract
The current version of the Human Disease Ontology (DO) (http://www.disease-ontology.org) database expands the utility of the ontology for the examination and comparison of genetic variation, phenotype, protein, drug and epitope data through the lens of human disease. DO is a biomedical resource of standardized common and rare disease concepts with stable identifiers organized by disease etiology. The content of DO has had 192 revisions since 2012, including the addition of 760 terms. Thirty-two percent of all terms now include definitions. DO has expanded the number and diversity of research communities and community members by 50+ during the past two years. These community members actively submit term requests, coordinate biomedical resource disease representation and provide expert curation guidance. Since the DO 2012 NAR paper, there have been hundreds of term requests and a steady increase in the number of DO listserv members, twitter followers and DO website usage. DO is moving to a multi-editor model utilizing Protégé to curate DO in web ontology language. This will enable closer collaboration with the Human Phenotype Ontology, EBI's Ontology Working Group, Mouse Genome Informatics and the Monarch Initiative among others, and enhance DO's current asserted view and multiple inferred views through reasoning.
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Affiliation(s)
- Warren A Kibbe
- Center for Biomedical Informatics and Information Technology, National Cancer Institute, 9609 Medical Center Drive, Rockville, MD 20850, USA
| | - Cesar Arze
- Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD 21201, USA
| | - Victor Felix
- Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD 21201, USA
| | - Elvira Mitraka
- Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD 21201, USA
| | - Evan Bolton
- PubChem, National Center for Biotechnology Information, National Library of Medicine National Institutes of Health Department of Health and Human Services 8600 Rockville Pike, Bethesda, MD 20894, USA
| | - Gang Fu
- PubChem, National Center for Biotechnology Information, National Library of Medicine National Institutes of Health Department of Health and Human Services 8600 Rockville Pike, Bethesda, MD 20894, USA
| | | | - Janos X Binder
- Structural and Computational Biology Unit, European Molecular Biology Laboratory (EMBL), Heidelberg, 69117, Germany Bioinformatics Core Facility, Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, Esch-sur-Alzette, 4362, Luxembourg
| | - James Malone
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Drashtti Vasant
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Helen Parkinson
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Lynn M Schriml
- Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD 21201, USA Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, MD 21201, USA
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Meta-analysis of human methylomes reveals stably methylated sequences surrounding CpG islands associated with high gene expression. Epigenetics Chromatin 2014; 7:28. [PMID: 25493099 PMCID: PMC4260796 DOI: 10.1186/1756-8935-7-28] [Citation(s) in RCA: 62] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2014] [Accepted: 10/06/2014] [Indexed: 02/03/2023] Open
Abstract
BACKGROUND DNA methylation is thought to play an important role in the regulation of mammalian gene expression, partly based on the observation that a lack of CpG island methylation in gene promoters is associated with high transcriptional activity. However, the CpG island methylation level only accounts for a fraction of the variance in gene expression, and methylation in other domains is hypothesized to play a role. We hypothesized that regions of very high stability in methylation would exist and provide biological insight into the role of methylation both within and outside CpG islands. RESULTS We set out to identify highly stable regions in the human methylome, based on the subset of CpGs assayed with an Illumina Infinium 450 K array. Using 1,737 samples from 30 publically available studies, we identified 15,224 CpGs that are 'ultrastable' in their state across tissues and developmental stages (974 always methylated; 14,250 always unmethylated). Further analysis of ultrastable CpGs led us to identify a novel subset of CpG islands, 'ravines', which exhibit a markedly consistent pattern of low methylation with highly methylated flanking shores and shelves. We distinguish ravines from other CpG islands characterized by a broader flanking region of low methylation. Interestingly, ravines are associated with higher gene expression compared to typical unmethylated CpG islands, and are more often found near housekeeping genes. CONCLUSIONS The identification of ultrastable sites in the human methylome led us to identify a subclass of CpG islands characterized by a very stable pattern of methylation encompassing the island and flanking regions, established early in development and maintained through differentiation. This pattern is associated with particularly high levels of gene expression, providing new evidence that methylation beyond the CpG island could play a role in gene expression.
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McCarthy SE, Gillis J, Kramer M, Lihm J, Yoon S, Berstein Y, Mistry M, Pavlidis P, Solomon R, Ghiban E, Antoniou E, Kelleher E, O’Brien C, Donohoe G, Gill M, Morris DW, McCombie WR, Corvin A. De novo mutations in schizophrenia implicate chromatin remodeling and support a genetic overlap with autism and intellectual disability. Mol Psychiatry 2014; 19:652-8. [PMID: 24776741 PMCID: PMC4031262 DOI: 10.1038/mp.2014.29] [Citation(s) in RCA: 265] [Impact Index Per Article: 26.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/06/2013] [Revised: 01/21/2014] [Accepted: 02/24/2014] [Indexed: 02/07/2023]
Abstract
Schizophrenia is a serious psychiatric disorder with a broadly undiscovered genetic etiology. Recent studies of de novo mutations (DNMs) in schizophrenia and autism have reinforced the hypothesis that rare genetic variation contributes to risk. We carried out exome sequencing on 57 trios with sporadic or familial schizophrenia. In sporadic trios, we observed a ~3.5-fold increase in the proportion of nonsense DNMs (0.101 vs 0.031, empirical P=0.01, Benjamini-Hochberg-corrected P=0.044). These mutations were significantly more likely to occur in genes with highly ranked probabilities of haploinsufficiency (P=0.0029, corrected P=0.006). DNMs of potential functional consequence were also found to occur in genes predicted to be less tolerant to rare variation (P=2.01 × 10(-)(5), corrected P=2.1 × 10(-)(3)). Genes with DNMs overlapped with genes implicated in autism (for example, AUTS2, CHD8 and MECP2) and intellectual disability (for example, HUWE1 and TRAPPC9), supporting a shared genetic etiology between these disorders. Functionally CHD8, MECP2 and HUWE1 converge on epigenetic regulation of transcription suggesting that this may be an important risk mechanism. Our results were consistent in an analysis of additional exome-based sequencing studies of other neurodevelopmental disorders. These findings suggest that perturbations in genes, which function in the epigenetic regulation of brain development and cognition, could have a central role in the susceptibility to, pathogenesis and treatment of mental disorders.
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Affiliation(s)
- Shane E. McCarthy
- The Stanley Institute for Cognitive Genomics, Cold Spring Harbor Laboratory, Cold Spring Harbor, 11724, USA
| | - Jesse Gillis
- The Stanley Institute for Cognitive Genomics, Cold Spring Harbor Laboratory, Cold Spring Harbor, 11724, USA
| | - Melissa Kramer
- The Stanley Institute for Cognitive Genomics, Cold Spring Harbor Laboratory, Cold Spring Harbor, 11724, USA
| | - Jayon Lihm
- The Stanley Institute for Cognitive Genomics, Cold Spring Harbor Laboratory, Cold Spring Harbor, 11724, USA
| | - Seungtai Yoon
- The Stanley Institute for Cognitive Genomics, Cold Spring Harbor Laboratory, Cold Spring Harbor, 11724, USA
| | - Yael Berstein
- The Stanley Institute for Cognitive Genomics, Cold Spring Harbor Laboratory, Cold Spring Harbor, 11724, USA
| | - Meeta Mistry
- Department of Psychiatry and Centre for High-throughput Biology, The University of British Columbia, Vancouver, Canada
| | - Paul Pavlidis
- Department of Psychiatry and Centre for High-throughput Biology, The University of British Columbia, Vancouver, Canada
| | - Rebecca Solomon
- The Stanley Institute for Cognitive Genomics, Cold Spring Harbor Laboratory, Cold Spring Harbor, 11724, USA
| | - Elena Ghiban
- The Stanley Institute for Cognitive Genomics, Cold Spring Harbor Laboratory, Cold Spring Harbor, 11724, USA
| | - Eric Antoniou
- The Stanley Institute for Cognitive Genomics, Cold Spring Harbor Laboratory, Cold Spring Harbor, 11724, USA
| | - Eric Kelleher
- Department of Psychiatry, School of Medicine, Trinity College Dublin, Dublin 2, Ireland
| | - Carol O’Brien
- Department of Psychiatry, School of Medicine, Trinity College Dublin, Dublin 2, Ireland
| | - Gary Donohoe
- Department of Psychiatry, School of Medicine, Trinity College Dublin, Dublin 2, Ireland
| | - Michael Gill
- Department of Psychiatry, School of Medicine, Trinity College Dublin, Dublin 2, Ireland
| | - Derek W. Morris
- Department of Psychiatry, School of Medicine, Trinity College Dublin, Dublin 2, Ireland
| | - W. Richard. McCombie
- The Stanley Institute for Cognitive Genomics, Cold Spring Harbor Laboratory, Cold Spring Harbor, 11724, USA
- The Watson School of Biological Sciences, Cold Spring Harbor Laboratory, Cold Spring Harbor, 11724, USA
| | - Aiden Corvin
- Department of Psychiatry, School of Medicine, Trinity College Dublin, Dublin 2, Ireland
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Herrera-Galeano JE, Hirschberg DL, Mokashi V, Solka J. OGA: an ontological tool of human phenotypes with genetic associations. BMC Res Notes 2013; 6:511. [PMID: 24308566 PMCID: PMC4234991 DOI: 10.1186/1756-0500-6-511] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2013] [Accepted: 11/28/2013] [Indexed: 11/29/2022] Open
Abstract
Background The availability of genetic data has increased dramatically in recent years. The greatest value of this data is its potential for personalized medicine. Many new associations are reported every day from Genome Wide Association Studies (GWAS). However, robust, reproducible associations are elusive for some complex diseases. Ontologies present a potential way to distinguish between spurious associations and those with a potential influence on the phenotype. Such an approach would be based on finding associations of the same genetic variant with closely related, but distinct, phenotypes. This approach can be accomplished with a phenotype ontology that also holds genetic association data. Results Here, we report a structured knowledge application to navigate and to facilitate the discovery of relationships between different phenotypes and their genetic associations. Conclusions OGA allows users to (1) find the intersecting set of genes for phenotypes of interest, (2) find empirical p values for such observations and (3) OGA outperforms similar applications in number of total concepts and genes mapped.
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Rouchka EC, Flight RM. Proceedings of the 12th Annual UT-ORNL-KBRIN Bioinformatics Summit 2013. BMC Bioinformatics 2013; 14 Suppl 17:A1. [PMID: 24625056 PMCID: PMC3853103 DOI: 10.1186/1471-2105-14-s17-a1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
Affiliation(s)
- Eric C Rouchka
- Department of Computer Engineering and Computer Science, University of Louisville, Duthie Center for Engineering, Louisville, KY 40292, USA
| | - Robert M Flight
- Department of Chemistry, University of Louisville, Louisville, KY 40292, USA
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