ABSTRACT
While many transcriptional profiling experiments measure dynamic processes that change over time, few include enough time points to adequately capture temporal changes in expression. This is especially true for data from human subjects, for which relevant samples may be hard to obtain, and for developmental processes where dynamics are critically important. Although most expression data sets sample at a single time point, it is possible to use accompanying temporal information to create a virtual time series by combining data from different individuals. We introduce TEMPO, a pathway-based outlier detection approach for finding pathways showing significant temporal changes in expression patterns from such combined data. We present findings from applications to existing microarray and RNA-seq data sets. TEMPO identifies temporal dysregulation of biologically relevant pathways in patients with autism spectrum disorders, Huntington's disease, Alzheimer's disease, and COPD. Its findings are distinct from those of standard temporal or gene set analysis methodologies. Overall, our experiments demonstrate that there is enough signal to overcome the noise inherent in such virtual time series, and that a temporal pathway approach can identify new functional, temporal, or developmental processes associated with specific phenotypes. Availability: An R package implementing this method and full results tables are available at bcb.cs.tufts.edu/tempo/.
- Mark D Alter, Rutwik Kharkar, Keri E Ramsey, David W Craig, Raun D Melmed, Theresa A Grebe, R Curtis Bay, Sharman Ober-Reynolds, Janet Kirwan, Josh J Jones, et almbox. . 2011. Autism and increased paternal age related changes in global levels of gene expression regulation. PloS one, Vol. 6, 2 (2011), e16715.Google ScholarCross Ref
- IP Androulakis, E Yang, and RR Almon . 2007. Analysis of time-series gene expression data: methods, challenges, and opportunities. Annual review of biomedical engineering Vol. 9 (2007), 205.Google Scholar
- Michael Ashburner, Catherine A Ball, Judith A Blake, David Botstein, Heather Butler, J Michael Cherry, Allan P Davis, Kara Dolinski, Selina S Dwight, Janan T Eppig, et almbox. . 2000. Gene Ontology: tool for the unification of biology. Nature genetics, Vol. 25, 1 (2000), 25--29.Google Scholar
- E.C. Azmitia, Z.T. Saccomano, M.F. Alzoobaee, M. Boldrini, and P.M. Whitaker-Azmitia . 2016. Persistent Angiogenesis in the Autism Brain: An Immunocytochemical Study of Postmortem Cortex, Brainstem and Cerebellum. J Autism Dev Disord., Vol. 46, 4 (2016), 1307--18.Google ScholarCross Ref
- Z. Bar-Joseph . 2004. Analyzing time series gene expression data. Bioinformatics, Vol. 20, 16 (Nov . 2004), 2493--2503. Google ScholarDigital Library
- Ziv Bar-Joseph, Georg Gerber, Itamar Simon, David K Gifford, and Tommi S Jaakkola . 2003. Comparing the continuous representation of time-series expression profiles to identify differentially expressed genes. Proceedings of the National Academy of Sciences, Vol. 100, 18 (2003), 10146--10151.Google ScholarCross Ref
- Ziv Bar-Joseph, Anthony Gitter, and Itamar Simon . 2012. Studying and modelling dynamic biological processes using time-series gene expression data. Nature Reviews Genetics Vol. 13, 8 (2012), 552--564.Google ScholarCross Ref
- M. G. Bartley, K. Marquardt, D. Kirchhof, H. M. Wilkins, D. Patterson, and D. A. Linseman . 2012. Overexpression of amyloid-β protein precursor induces mitochondrial oxidative stress and activates the intrinsic apoptotic cascade. J. Alzheimers Dis., Vol. 28, 4 (2012), 855--868.Google ScholarCross Ref
- Y. Benjamini and Y. Hochberg . 1995. Controlling the false discovery rate: a practical and powerful approach to multiple hypothesis testing. J R Stat Soc B Vol. 57 (1995), 289--300.Google ScholarCross Ref
- I. Blockx, N. Van Camp, M. Verhoye, R. Boisgard, A. Dubois, B. Jego, E. Jonckers, K. Raber, K. Siquier, B. Kuhnast, F. Dollé, H.P. Nguyen, S. Von Hörsten, B. Tavitian, and A. Van der Linden . 2011. Genotype specific age related changes in a transgenic rat model of Huntington's disease. Neuroimage, Vol. 58, 4 (15 Oct . 2011), 1006--16.Google Scholar
- M. Bothwell and E. Giniger . 2000. Alzheimer's disease: neurodevelopment converges with neurodegeneration. Cell, Vol. 102, 3 (Aug . 2000), 271--273.Google ScholarCross Ref
- E. Breece, B. Paciotti, C. W. Nordahl, S. Ozonoff, J. A. Van de Water, S. J. Rogers, D. Amaral, and P. Ashwood . 2013. Myeloid dendritic cells frequencies are increased in children with autism spectrum disorder and associated with amygdala volume and repetitive behaviors. Brain Behav. Immun. Vol. 31 (Jul . 2013), 69--75.Google Scholar
- E. M. Bublil and Y. Yarden . 2007. The EGF receptor family: spearheading a merger of signaling and therapeutics. Curr. Opin. Cell Biol. Vol. 19, 2 (Apr . 2007), 124--134.Google ScholarCross Ref
- Brendan J Carolan, Adriana Heguy, Ben-Gary Harvey, Philip L Leopold, Barbara Ferris, and Ronald G Crystal . 2006. Up-regulation of expression of the ubiquitin carboxyl-terminal hydrolase L1 gene in human airway epithelium of cigarette smokers. Cancer research, Vol. 66, 22 (2006), 10729--10740.Google Scholar
- K. H. Chang, Y. C. Chen, Y. R. Wu, W. F. Lee, and C. M. Chen . 2012. Downregulation of genes involved in metabolism and oxidative stress in the peripheral leukocytes of Huntington's disease patients. PLoS ONE, Vol. 7, 9 (2012), e46492.Google ScholarCross Ref
- S. Choorapoikayil, B. Weijts, R. Kers, A. de Bruin, and J. den Hertog . 2013. Loss of Pten promotes angiogenesis and enhanced VEGFA expression in zebrafish. Dis Model Mech., Vol. 6, 5 (2013), 1159--66.Google ScholarCross Ref
- Ana Conesa, Mar'ıa José Nueda, Alberto Ferrer, and Manuel Talón . 2006. maSigPro: a method to identify significantly differential expression profiles in time-course microarray experiments. Bioinformatics, Vol. 22, 9 (2006), 1096--1102. Google ScholarDigital Library
- EH Cook, Rachel Courchesne, Catherine Lord, Nancy J Cox, Shuya Yan, Alan Lincoln, Richard Haas, Eric Courchesne, and Bennett L Leventhal . 1997. Evidence of linkage between the serotonin transporter and autistic disorder. Molecular psychiatry Vol. 2 (1997), 247--250.Google Scholar
- F. Crews, J. He, and C. Hodge . 2007. Adolescent cortical development: a critical period of vulnerability for addiction. Pharmacol. Biochem. Behav. Vol. 86, 2 (Feb . 2007), 189--199.Google ScholarCross Ref
- Jan Croonenberghs, Eugene Bosmans, Dirk Deboutte, Gunter Kenis, and Michael Maes . 2002. Activation of the inflammatory response system in autism. Neuropsychobiology (2002).Google Scholar
- Harris Drucker, Chris JC Burges, Linda Kaufman, Alex Smola, Vladimir Vapnik, et almbox. . 1997. Support vector regression machines. Advances in neural information processing systems Vol. 9 (1997), 155--161. Google ScholarDigital Library
- Ron Edgar, Michael Domrachev, and Alex E Lash . 2002. Gene Expression Omnibus: NCBI gene expression and hybridization array data repository. Nucleic acids research Vol. 30, 1 (2002), 207--210.Google Scholar
- L. Enriquez-Barreto and M. Morales . 2016. The PI3K signaling pathway as a pharmacological target in Autism related disorders and Schizophrenia. Mol Cell Ther Vol. 4 (2016), 2.Google ScholarCross Ref
- Jason Ernst and Ziv Bar-Joseph . 2006. STEM: a tool for the analysis of short time series gene expression data. BMC bioinformatics, Vol. 7, 1 (2006), 191.Google Scholar
- H.A. Farahani, A. Rahiminezhad, L. Same, and K. Immannezhad . 2010. A Comparison of Partial Least Squares (PLS) and Ordinary Least Squares (OLS) regressions in predicting of couples mental health based on their communicational patterns. Procedia Social and Behavioral Sciences Vol. 5 (2010), 1459--63.Google ScholarCross Ref
- A. Felipe, O. Vinas, and X. Remesar . 1992. Changes in alanine and glutamine transport during rat red blood cell maturation. Biosci. Rep., Vol. 12, 1 (Feb . 1992), 47--56.Google ScholarCross Ref
- S. K. Garg, C. Delaney, H. Shi, and R. Yung . 2014. Changes in adipose tissue macrophages and T cells during aging. Crit. Rev. Immunol., Vol. 34, 1 (2014), 1--14.Google ScholarCross Ref
- S. Ghavami, S. Shojaei, B. Yeganeh, S. R. Ande, J. R. Jangamreddy, M. Mehrpour, J. Christoffersson, W. Chaabane, A. R. Moghadam, H. H. Kashani, M. Hashemi, A. A. Owji, and M. J. os . 2014. Autophagy and apoptosis dysfunction in neurodegenerative disorders. Prog. Neurobiol. Vol. 112 (Jan . 2014), 24--49.Google Scholar
- M. Grilli, G. Ferrari Toninelli, D. Uberti, P. Spano, and M. Memo . 2003. Alzheimer's disease linking neurodegeneration with neurodevelopment. Funct. Neurol., Vol. 18, 3 (2003), 145--148.Google Scholar
- S. S. Hacievliyagil, L. C. Mutlu, and I. Temel . 2013. Airway inflammatory markers in chronic obstructive pulmonary disease patients and healthy smokers. Niger J Clin Pract, Vol. 16, 1 (2013), 76--81.Google ScholarCross Ref
- Ravi Kiran Reddy Kalathur, Miguel A Hernández-Prieto, and Matthias E Futschik . 2012. Huntington's Disease and its therapeutic target genes: a global functional profile based on the HD Research Crossroads database. BMC neurology, Vol. 12, 1 (2012), 1.Google Scholar
- A. Kolevzon, K. A. Mathewson, and E. Hollander . 2006. Selective serotonin reuptake inhibitors in autism: a review of efficacy and tolerability. J Clin Psychiatry, Vol. 67, 3 (Mar . 2006), 407--414.Google ScholarCross Ref
- L.N. Kota, S. Bharath, M. Purushottam, N.S. Moily, P.T. Sivakumar, M. Varghese, P.K. Pal, and S. Jain . 2015. Reduced telomere length in neurodegenerative disorders may suggest shared biology. J Neuropsychiatry Clin Neurosci. Vol. 27, 2 (2015), e92--6.Google ScholarCross Ref
- S. Kyrylenko, M. Roschier, P. Korhonen, and A. Salminen . 1999. Regulation of PTEN expression in neuronal apoptosis. Brain Res. Mol. Brain Res. Vol. 73, 1--2 (Nov . 1999), 198--202.Google ScholarCross Ref
- T. Lawrence . 2009. The nuclear factor NF-kappaB pathway in inflammation. Cold Spring Harb Perspect Biol Vol. 1, 6 (Dec . 2009), a001651.Google ScholarCross Ref
- Devys D Liu YF, Deth RC . 1997. SH3 domain-dependent association of huntingtin with epidermal growth factor receptor signaling complexes. J Biol Chem., Vol. 272, 13 (1997), 8121--4.Google ScholarCross Ref
- Simon Lovestone, Paul Francis, Iwona Kloszewska, Patrizia Mecocci, Andrew Simmons, Hilkka Soininen, Christian Spenger, Magda Tsolaki, Bruno Vellas, Lars-Olof Wahlund, et almbox. . 2009. AddNeuroMed-the European collaboration for the discovery of novel biomarkers for Alzheimer's disease. Annals of the New York Academy of Sciences Vol. 1180, 1 (2009), 36--46.Google ScholarCross Ref
- R. L. Margolis, D. M. Chuang, and R. M. Post . 1994. Programmed cell death: implications for neuropsychiatric disorders. Biol. Psychiatry, Vol. 35, 12 (Jun . 1994), 946--956.Google ScholarCross Ref
- L. Martin, X. Latypova, C. M. Wilson, A. Magnaudeix, M. L. Perrin, C. Yardin, and F. Terro . 2013. Tau protein kinases: involvement in Alzheimer's disease. Ageing Res. Rev., Vol. 12, 1 (Jan . 2013), 289--309.Google Scholar
- Anastasios Mastrokolias, Yavuz Ariyurek, Jelle J Goeman, Erik van Duijn, Raymund AC Roos, Roos C van der Mast, GertJan B van Ommen, Johan T den Dunnen, Peter AC't Hoen, and Willeke MC van Roon-Mom . 2015. Huntington's disease biomarker progression profile identified by transcriptome sequencing in peripheral blood. European Journal of Human Genetics Vol. 23, 10 (2015), 1349--1356.Google ScholarCross Ref
- A. Monsonego, A. Nemirovsky, and I. Harpaz . 2013. CD4 T cells in immunity and immunotherapy of Alzheimer's disease. Immunology, Vol. 139, 4 (Aug . 2013), 438--446.Google ScholarCross Ref
- I. Munoz-Sanjuan and G. P. Bates . 2011. The importance of integrating basic and clinical research toward the development of new therapies for Huntington disease. J. Clin. Invest., Vol. 121, 2 (Feb . 2011), 476--483.Google ScholarCross Ref
- L. C. Murrin, J. D. Sanders, and D. B. Bylund . 2007. Comparison of the maturation of the adrenergic and serotonergic neurotransmitter systems in the brain: implications for differential drug effects on juveniles and adults. Biochem. Pharmacol., Vol. 73, 8 (Apr . 2007), 1225--1236.Google ScholarCross Ref
- K. Noto, C. Brodley, and D. Slonim . 2010. Anomaly Detection Using an Ensemble of Feature Models. Proc IEEE Int Conf Data Min (Dec . 2010), 953--958. Google ScholarDigital Library
- K. Noto, C. Brodley, and D. Slonim . 2012. FRaC: a feature-modeling approach for semi-supervised and unsupervised anomaly detection. Data Min Knowl Discov Vol. 25, 1 (2012), 109--133. Google ScholarDigital Library
- T. M. Przytycka, M. Singh, and D. K. Slonim . 2010. Toward the dynamic interactome: it's about time. Brief. Bioinformatics Vol. 11, 1 (Jan . 2010), 15--29.Google ScholarCross Ref
- M. F. Ramoni, P. Sebastiani, and I. S. Kohane . 2002. Cluster analysis of gene expression dynamics. Proc. Natl. Acad. Sci. U.S.A. Vol. 99, 14 (Jul . 2002), 9121--9126.Google ScholarCross Ref
- P. Resnik . 1999. Semantic similarity in a taxonomy: an information-based measure and its application to problems of ambiguity in natural language. Journal of Artificial Intelligence Research (JAIR) Vol. 11 (1999), 95--130. Google ScholarDigital Library
- E. R. Ritvo, A. Yuwiler, E. Geller, E. M. Ornitz, K. Saeger, and S. Plotkin . 1970. Increased blood serotonin and platelets in early infantile autism. Arch. Gen. Psychiatry Vol. 23, 6 (Dec . 1970), 566--572.Google ScholarCross Ref
- J. M. Rubio-Perez and J. M. Morillas-Ruiz . 2012. A review: inflammatory process in Alzheimer's disease, role of cytokines. ScientificWorldJournal Vol. 2012 (2012), 756357.Google ScholarCross Ref
- E. Sefer, M. Kleyman, and Z. Bar-Joseph . 2016. Tradeoffs between Dense and Replicate Sampling Strategies for High-Throughput Time Series Experiments. Cell Syst, Vol. 3, 1 (Jul . 2016), 35--42.Google Scholar
- C.E. Shannon . 1948. A mathematical theory of communication (Part I). Bell Syst Tech J Vol. 27 (1948), 379--423.Google ScholarCross Ref
- Alex J Smola and Bernhard Schölkopf . 2004. A tutorial on support vector regression. Statistics and computing Vol. 14, 3 (2004), 199--222. Google ScholarDigital Library
- Sanjana Sood, Iain J Gallagher, Katie Lunnon, Eric Rullman, Aoife Keohane, Hannah Crossland, Bethan E Phillips, Tommy Cederholm, Thomas Jensen, Luc JC van Loon, et almbox. . 2015. A novel multi-tissue RNA diagnostic of healthy ageing relates to cognitive health status. Genome biology, Vol. 16, 1 (2015), 185.Google Scholar
- D. Spies and C. Ciaudo . 2015. Dynamics in Transcriptomics: Advancements in RNA-seq Time Course and Downstream Analysis. Comput Struct Biotechnol J Vol. 13 (2015), 469--477.Google ScholarCross Ref
- Oliver Stegle, Katherine J Denby, Emma J Cooke, David L Wild, Zoubin Ghahramani, and Karsten M Borgwardt . 2010. A robust Bayesian two-sample test for detecting intervals of differential gene expression in microarray time series. Journal of Computational Biology Vol. 17, 3 (2010), 355--367.Google ScholarCross Ref
- Aravind Subramanian, Pablo Tamayo, Vamsi K Mootha, Sayan Mukherjee, Benjamin L Ebert, Michael A Gillette, Amanda Paulovich, Scott L Pomeroy, Todd R Golub, Eric S Lander, et almbox. . 2005. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proceedings of the National Academy of Sciences of the United States of America, Vol. 102, 43 (2005), 15545--15550.Google ScholarCross Ref
- Ann E Tilley, Ben-Gary Harvey, Adriana Heguy, Neil R Hackett, Rui Wang, Timothy P O'connor, and Ronald G Crystal . 2009. Down-regulation of the notch pathway in human airway epithelium in association with smoking and chronic obstructive pulmonary disease. American journal of respiratory and critical care medicine, Vol. 179, 6 (2009), 457--466.Google Scholar
- Randall D. Tobias . 1995. An introduction to partial least squares regression SUGI: Proceedings of the 20th Annual SAS User's Group International meeting. Orlando, Florida, 1250--7.Google Scholar
- M. Trindade, W. Oigman, and M. Fritsch Neves . 2017. Potential Role of Endothelin in Early Vascular Aging. Curr Hypertens Rev, Vol. 13, 1 (2017), 33--40.Google ScholarCross Ref
- K. S. van der Geest, W. H. Abdulahad, S. M. Tete, P. G. Lorencetti, G. Horst, N. A. Bos, B. J. Kroesen, E. Brouwer, and A. M. Boots . 2014. Aging disturbs the balance between effector and regulatory CD4Google Scholar
- T cells. Exp. Gerontol. Vol. 60 (Dec . 2014), 190--196.Google Scholar
- Erik van Duijn, Elisabeth M Kingma, Reinier Timman, Frans G Zitman, Aad Tibben, Raymund AC Roos, and Rose C van der Mast . 2008. Cross-sectional study on prevalences of psychiatric disorders in mutation carriers of Huntington's disease compared with mutation-negative first-degree relatives. The Journal of clinical psychiatry Vol. 69, 11 (2008), 1--478.Google ScholarCross Ref
- A. L. Varigonda, E. Jakubovski, M. J. Taylor, N. Freemantle, C. Coughlin, and M. H. Bloch . 2015. Systematic Review and Meta-Analysis: Early Treatment Responses of Selective Serotonin Reuptake Inhibitors in Pediatric Major Depressive Disorder. J Am Acad Child Adolesc Psychiatry Vol. 54, 7 (Jul . 2015), 557--564.Google ScholarCross Ref
- Hongen Wei, Ian Alberts, and Xiaohong Li . 2014. The apoptotic perspective of autism. International Journal of Developmental Neuroscience Vol. 36 (2014), 13--18.Google ScholarCross Ref
- Heather C Wick, Harold Drabkin, Huy Ngu, Michael Sackman, Craig Fournier, Jessica Haggett, Judith A Blake, Diana W Bianchi, and Donna K Slonim . 2014. DFLAT: functional annotation for human development. BMC bioinformatics, Vol. 15, 1 (2014), 45.Google Scholar
- Herman Wold . 1985. Partial least squares. Encyclopedia of statistical sciences (1985).Google Scholar
- W. Yeo and J. Gautier . 2004. Early neural cell death: dying to become neurons. Dev. Biol., Vol. 274, 2 (Oct . 2004), 233--244.Google ScholarCross Ref
- N. Yosef and A. Regev . 2011. Impulse control: temporal dynamics in gene transcription. Cell, Vol. 144, 6 (Mar . 2011), 886--896.Google ScholarCross Ref
- Guangchuang Yu, Fei Li, Yide Qin, Xiaochen Bo, Yibo Wu, and Shengqi Wang . 2010. GOSemSim: an R package for measuring semantic similarity among GO terms and gene products. Bioinformatics, Vol. 26, 7 (2010), 976--978. Google ScholarDigital Library
- A. Zeidel, B. Beilin, I. Yardeni, E. Mayburd, G. Smirnov, and H. Bessler . 2002. Immune response in asymptomatic smokers. Acta Anaesthesiol Scand Vol. 46, 8 (Sep . 2002), 959--964.Google ScholarCross Ref
- J. Zhou and L. F. Parada . 2012. PTEN signaling in autism spectrum disorders. Curr. Opin. Neurobiol. Vol. 22, 5 (Oct . 2012), 873--879.Google ScholarCross Ref
- M. N. Ziats and O. M. Rennert . 2011. Expression profiling of autism candidate genes during human brain development implicates central immune signaling pathways. PLoS ONE, Vol. 6, 9 (2011), e24691.Google ScholarCross Ref
- G. E. Zinman, S. Naiman, Y. Kanfi, H. Cohen, and Z. Bar-Joseph . 2013. ExpressionBlast: mining large, unstructured expression databases. Nat. Methods, Vol. 10, 10 (Oct . 2013), 925--926.Google ScholarCross Ref
Index Terms
- TEMPO: Detecting Pathway-Specific Temporal Dysregulation of Gene Expression in Disease
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