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Network- and attribute-based classifiers can prioritize genes and pathways for autism spectrum disorders and intellectual disability†‡

  1. Yan Kou§,
  2. Catalina Betancur,
  3. Huilei Xu‖,
  4. Joseph D Buxbaum††,*,
  5. Avi Ma'ayan‡‡,*

Article first published online: 12 APR 2012

DOI: 10.1002/ajmg.c.31330

Issue

American Journal of Medical Genetics Part C: Seminars in Medical Genetics

American Journal of Medical Genetics Part C: Seminars in Medical Genetics

Special Issue: Autism and Intellectual Disability: Two Sides of the Same Coin

Volume 160C, Issue 2, pages 130–142, 15 May 2012

Additional Information

How to Cite

Kou, Y., Betancur, C., Xu, H., Buxbaum, J. D. and Ma'ayan, A. (2012), Network- and attribute-based classifiers can prioritize genes and pathways for autism spectrum disorders and intellectual disability. Am. J. Med. Genet., 160C: 130–142. doi: 10.1002/ajmg.c.31330

Author Information

  1. §

    Yan Kou, M.Sc., is a graduate student at Mount Sinai School of Medicine, New York, working under the supervision of Drs. Ma'ayan and Buxbaum. She is interested in developing and applying systems biological methods to complex human disorders. Yan Kou is a Seaver Graduate Fellow.

  2. Catalina Betancur, M.D., Ph.D., is director of research at the INSERM U952, CNRS UMR 7224, Université Pierre et Marie Curie, in Paris, France. Her work is focused on the elucidation of the genetic bases of autism spectrum disorders.

  3. ‖

    Huilei Xu, B.Sc., is a graduate student at Mount Sinai School of Medicine, New York, working under the supervision of Drs. Ma'ayan and Ihor Lemischka. Huilei Xu is interested in developing and applying data mining methods in computational systems biology with the focus on understanding embryonic stem cell pluripotency and early differentiation.

  4. ††

    Joseph D Buxbaum, M.Sc., Ph.D., is a Professor in the Departments of Psychiatry, Neuroscience, and Genetics and Genomic Sciences, at the Mount Sinai School of Medicine in New York. His interests are in understanding the causes of, and developing targeted treatment for, neuropsychiatric disorders. Dr. Buxbaum is the Director of the Seaver Autism Center for Research and Treatment as well as Chief for the Center of Excellence in Neurodevelopmental Disorders of the Friedman Brain Institute, both at Mount Sinai.

  5. ‡‡

    Avi Ma'ayan, M.Sc., Ph.D., is an Assistant professor in the Department of Pharmacology and Systems Therapeutics. His interests are in applying graph theory, machine learning and dimensionality reduction methods for integrating omics datasets collected from mammalian sources to better understand biological regulation on a global scale. Dr. Ma'ayan is the Director of the Bioinformatics and Network Analysis Core of the Systems Biology Center New York.

*Department of Psychiatry, Mount Sinai School of Medicine, One Gustave L Levy Place, Box 1668, New York, NY 10029.

  1. †

    Yan Kou, Catalina Betancur, and Huilei Xu contributed equally to this study.

  2. ‡

    How to Cite this Article: Kou Y, Betancur C, Xu H, Buxbaum JD, Ma'ayan A. 2012. Network- and attribute-based classifiers can prioritize genes and pathways for autism spectrum disorders and intellectual disability. Am J Med Genet Part C Semin Med Genet 160C:130–142.

  3. §

    Yan Kou, M.Sc., is a graduate student at Mount Sinai School of Medicine, New York, working under the supervision of Drs. Ma'ayan and Buxbaum. She is interested in developing and applying systems biological methods to complex human disorders. Yan Kou is a Seaver Graduate Fellow.

  4. Catalina Betancur, M.D., Ph.D., is director of research at the INSERM U952, CNRS UMR 7224, Université Pierre et Marie Curie, in Paris, France. Her work is focused on the elucidation of the genetic bases of autism spectrum disorders.

  5. ‖

    Huilei Xu, B.Sc., is a graduate student at Mount Sinai School of Medicine, New York, working under the supervision of Drs. Ma'ayan and Ihor Lemischka. Huilei Xu is interested in developing and applying data mining methods in computational systems biology with the focus on understanding embryonic stem cell pluripotency and early differentiation.

  6. ††

    Joseph D Buxbaum, M.Sc., Ph.D., is a Professor in the Departments of Psychiatry, Neuroscience, and Genetics and Genomic Sciences, at the Mount Sinai School of Medicine in New York. His interests are in understanding the causes of, and developing targeted treatment for, neuropsychiatric disorders. Dr. Buxbaum is the Director of the Seaver Autism Center for Research and Treatment as well as Chief for the Center of Excellence in Neurodevelopmental Disorders of the Friedman Brain Institute, both at Mount Sinai.

  7. ‡‡

    Avi Ma'ayan, M.Sc., Ph.D., is an Assistant professor in the Department of Pharmacology and Systems Therapeutics. His interests are in applying graph theory, machine learning and dimensionality reduction methods for integrating omics datasets collected from mammalian sources to better understand biological regulation on a global scale. Dr. Ma'ayan is the Director of the Bioinformatics and Network Analysis Core of the Systems Biology Center New York.

Publication History

  1. Issue published online: 19 APR 2012
  2. Article first published online: 12 APR 2012

Funded by

  • NIH. Grant Numbers: P50GM071558-03, R01DK088541-01A1, RC2LM010994-01, R01MH089025-02

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REFERENCES

  • Bader GD, Betel D, Hogue CWV. 2003. BIND: The Biomolecular Interaction Network Database. Nucleic Acids Res 31: 248– 250.
  • Berger S, Posner J, Ma'ayan A. 2007. Genes2Networks: Connecting lists of gene symbols using mammalian protein interactions databases. BMC Bioinformatics 8: 372.
  • Berger SI, Ma'ayan A, Iyengar R. 2010. Systems pharmacology of arrhythmias. Sci Signal 3: ra30.
  • Betancur C. 2011. Etiological heterogeneity in autism spectrum disorders: More than 100 genetic and genomic disorders and still counting. Brain Res 1380: 42– 477.
  • Beuming T, Skrabanek L, Niv MY, Mukherjee P, Weinstein H. 2005. PDZBase: A protein–protein interaction database for PDZ-domains. Bioinformatics 21: 827– 828.
  • Byvatov E, Schneider G. 2003. Support vector machine applications in bioinformatics. Appl Bioinformatics 2: 67– 77.
  • Chatr-aryamontri A, Ceol A, Palazzi LM, Nardelli G, Schneider MV, Castagnoli L, Cesareni G. 2007. MINT: The Molecular INTeraction database. Nucleic Acids Res 35: D572– 574.
  • Chen J, Aronow B, Jegga A. 2009. Disease candidate gene identification and prioritization using protein interaction networks. BMC Bioinformatics 10: 73.
  • Culhane AC, Schwarzl T, Sultana R, Picard KC, Picard SC, Lu TH, Franklin KR, French SJ, Papenhausen G, Correll M, Quackenbush J. 2010. GeneSigDB a curated database of gene expression signatures. Nucleic Acids Res 38: D716– D725.
  • El-Fishawy P, State MW. 2009. The genetics of autism: Key issues, recent findings, and clinical implications. Psychiatr Clin North Am 33: 83– 105.
  • Ewing RM, Chu P, Elisma F, Li H, Taylor P, Climie S, McBroom-Cerajewski L, Robinson MD, O'Connor L, Li M, Taylor R, Dharsee M, Ho Y, Heilbut A, Moore L, Zhang S, Ornatsky O, Bukhman YV, Ethier M, Sheng Y, Vasilescu J, Abu-Farha M, Lambert JP, Duewel HS, Stewart II, Kuehl B, Hogue K, Colwill K, Gladwish K, Muskat B, Kinach R, Adams SL, Moran MF, Morin GB, Topaloglou T, Figeys D. 2007. Large-scale mapping of human protein–protein interactions by mass spectrometry. Mol Syst Biol 3: 89.
  • Gilman SR, Iossifov I, Levy D, Ronemus M, Wigler M, Vitkup D. 2011. Rare de novo variants associated with autism implicate a large functional network of genes involved in formation and function of synapses. Neuron 70: 898– 907.
  • Gkoutos G, Green E, Mallon A-M, Hancock J, Davidson D. 2004. Using ontologies to describe mouse phenotypes. Genome Biol 6: R8.
  • Hermjakob H, Montecchi-Palazzi L, Lewington C, Mudali S, Kerrien S, Orchard S, Vingron M, Roechert B, Roepstorff P, Valencia A, Margalit H, Armstrong J, Bairoch A, Cesareni G, Sherman D, Apweiler R. 2004. IntAct: An open source molecular interaction database. Nucl Acids Res 32: D452– D455.
  • Jiang H, Ching WK. 2011. Classifying DNA repair genes by kernel-based support vector machines. Bioinformation 7: 257– 263.
  • Kanehisa M, Araki M, Goto S, Hattori M, Hirakawa M, Itoh M, Katayama T, Kawashima S, Okuda S, Tokimatsu T, Yamanishi Yl. 2008. KEGG for linking genomes to life and the environment. Nucleic Acids Res 36: D480– D484.
  • Kang HJ, Kawasawa YI, Cheng F, Zhu Y, Xu X, Li M, Sousa AMM, Pletikos M, Meyer KA, Sedmak G, Guennel T, Shin Y, Johnson MB, Krsnik Z, Mayer S, Fertuzinhos S, Umlauf S, Lisgo SN, Vortmeyer A, Weinberger DR, Mane S, Hyde TM, Huttner A, Reimers M, Kleinman JE, Sestan N. 2011. Spatio-temporal transcriptome of the human brain. Nature 478: 483– 489.
  • Kann MG. 2009. Advances in translational bioinformatics: Computational approaches for the hunting of disease genes. Brief Bioinformatics 11: 96– 110.
  • Lachmann A, Ma'ayan A. 2009. KEA: Kinase enrichment analysis. Bioinformatics 25: 684– 686.
  • Lachmann A, Ma'ayan A. 2010. Lists2Networks: Integrated analysis of gene/protein lists. BMC Bioinformatics 11: 87.
  • Lachmann A, Xu H, Krishnan J, Berger SI, Mazloom AR, Ma'ayan A. 2010. ChEA: Transcription factor regulation inferred from integrating genome-wide ChIP-X experiments. Bioinformatics 26: 2438– 2444.
  • Li L, Zhang K, Lee J, Cordes S, Davis DP, Tang Z. 2009. Discovering cancer genes by integrating network and functional properties. BMC Med Genomics 2: 61.
  • Lynn DJ, Winsor GL, Chan C, Richard N, Laird MR, Barsky A, Gardy JL, Roche FM, Chan THW, Shah N, Lo R, Naseer M, Que J, Yau M, Acab M, Tulpan D, Whiteside MD, Chikatamarla A, Mah B, Munzner T, Hokamp K, Hancock RE, Brinkman FS. 2008. InnateDB: Facilitating systems-level analyses of the mammalian innate immune response. Mol Syst Biol 4: 218.
  • Ma'ayan A, Jenkins SL, Neves S, Hasseldine A, Grace E, Dubin-Thaler B, Eungdamrong NJ, Weng G, Ram PT, Rice JJ, Kershenbaum A, Stolovitzky GA, Blitzer RD, Iyengar R. 2005. Formation of regulatory patterns during signal propagation in a mammalian cellular network. Science 309: 1078– 1083.
  • Matys V, Fricke E, Geffers R, Gling E, Haubrock M, Hehl R, Hornischer K, Karas D, Kel AE, Kel-Margoulis OV, Kloos DU, Land S, Lewicki-Potapov B, Michael H, Münch R, Reuter I, Rotert S, Saxel H, Scheer M, Thiele S, Wingender E. 2003. TRANSFAC: Transcriptional regulation, from patterns to profiles. Nucleic Acids Res 31: 374– 378.
  • Mewes H, Amid C, Arnold R, Frishman D, Guldener U, Mannhaupt G, Munsterkotter M, Pagel P, Strack N, Stumpflen V, Warfsmann J, Ruepp A. 2004. MIPS: Analysis and annotation of proteins from whole genomes. Nucleic Acids Res 32: D41– D44.
  • Navlakha S, Kingsford C. 2010. The power of protein interaction networks for associating genes with diseases. Bioinformatics 26: 1057– 1063.
  • Oti M, Snel B, Huynen MA, Brunner HG. 2006. Predicting disease genes using protein–protein interactions. J Med Genet 43: 691– 698.
  • Peri S, Navarro JD, Kristiansen TZ, Amanchy R, Surendranath V, Muthusamy B, Gandhi TKB, Chandrika KN, Deshpande N, Suresh S, Rashmi BP, Shanker K, Padma N, Niranjan V, Harsha HC, Talreja N, Vrushabendra BM, Ramya MA, Yatish AJ, Joy M, Shivashankar HN, Kavitha MP, Menezes M, Choudhury DR, Ghosh N, Saravana R, Chandran S, Mohan S, Jonnalagadda CK, Prasad CK, Kumar-Sinha C, Deshpande KS, Pandey A. 2004. Human protein reference database as a discovery resource for proteomics. Nucleic Acids Res 32: D497– 501.
  • Rual J-F, Venkatesan K, Hao T, Hirozane-Kishikawa T, Dricot A, Li N, Berriz GF, Gibbons FD, Dreze M, Ayivi-Guedehoussou N, Klitgord N, Simon C, Boxem M, Milstein S, Rosenberg J, Goldberg DS, Zhang LV, Wong SL, Franklin G, Li S, Albala JS, Lim J, Fraughton C, Llamosas E, Cevik S, Bex C, Lamesch P, Sikorski RS, Vandenhaute J, Zoghbi HY, Smolyar A, Bosak S, Sequerra R, Doucette-Stamm L, Cusick ME, Hill DE, Roth FP, Vidal M. 2005. Towards a proteome-scale map of the human protein–protein interaction network. Nature 437: 1173– 1178.
  • Sakai Y, Shaw CA, Dawson BC, Dugas DV, Al-Mohtaseb Z, Hill DE, Zoghbi HY. 2011. Protein interactome reveals converging molecular pathways among autism disorders. Sci Transl Med 3: 86ra49.
  • Sanders SJ, Ercan-Sencicek AG, Hus V, Luo R, Murtha MT, Moreno-De-Luca D, Chu SH, Moreau MP, Gupta AR, Thomson SA, Mason CE, Bilguvar K, Celestino-Soper PB, Choi M, Crawford EL, Davis L, Wright NR, Dhodapkar RM, DiCola M, DiLullo NM, Fernandez TV, Fielding-Singh V, Fishman DO, Frahm S, Garagaloyan R, Goh GS, Kammela S, Klei L, Lowe JK, Lund SC, McGrew AD, Meyer KA, Moffat WJ, Murdoch JD, O'Roak BJ, Ober GT, Pottenger RS, Raubeson MJ, Song Y, Wang Q, Yaspan BL, Yu TW, Yurkiewicz IR, Beaudet AL, Cantor RM, Curland M, Grice DE, Günel M, Lifton RP, Mane SM, Martin DM, Shaw CA, Sheldon M, Tischfield JA, Walsh CA, Morrow EM, Ledbetter DH, Fombonne E, Lord C, Martin CL, Brooks AI, Sutcliffe JS, Cook EH Jr, Geschwind D, Roeder K, Devlin B, State MW. 2011. Multiple recurrent de novo CNVs, including duplications of the 7q11.23 Williams syndrome region, are strongly associated with autism. Neuron 70: 863– 885.
  • Stark C, Breitkreutz B-J, Reguly T, Boucher L, Breitkreutz A, Tyers M. 2006. BioGRID: A general repository for interaction datasets. Nucleic Acids Res 34: D535– 539.
  • Stelzl U, Worm U, Lalowski M, Haenig C, Brembeck FH, Goehler H, Stroedicke M, Zenkner M, Schoenherr A, Koeppen S, Timm J, Mintzlaff S, Abraham C, Bock N, Kietzmann S, Goedde A, Toksöz E, Droege A, Krobitsch S, Korn B, Birchmeier W, Lehrach H, Wanker EE. 2005. A human protein–protein interaction network: A resource for annotating the proteome. Cell 122: 957– 968.
  • Topper S, Ober C, Das S. 2011. Exome sequencing and the genetics of intellectual disability. Clin Genet 80: 117– 126.
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  • Voineagu I, Wang X, Johnston P, Lowe JK, Tian Y, Horvath S, Mill J, Cantor RM, Blencowe BJ, Geschwind DH. 2011. Transcriptomic analysis of autistic brain reveals convergent molecular pathology. Nature 474: 380– 384.
  • Xenarios I, Rice DW, Salwinski L, Baron MK, Marcotte EM, Eisenberg D. 2000. DIP: The Database of Interacting Proteins. Nucleic Acids Res 28: 289– 291.
  • Xu H, Lemischka IR, Ma'ayan A. 2010. SVM classifier to predict genes important for self-renewal and pluripotency of mouse embryonic stem cells. BMC Syst Biol 4: 173.
  • Yu H, Tardivo L, Tam S, Weiner E, Gebreab F, Fan C, Svrzikapa N, Hirozane-Kishikawa T, Rietman E, Yang X, Sahalie J, Salehi-Ashtiani K, Hao T, Cusick ME, Hill DE, Roth FP, Braun P, Vidal M. 2011. Next-generation sequencing to generate interactome datasets. Nat Methods 8: 478– 480.
  • Zhang W, Sun F, Jiang R. 2011. Integrating multiple protein–protein interaction networks to prioritize disease genes: A Bayesian regression approach. BMC Bioinformatics 12: S11.
  • Ziats MN, Rennert OM. 2011. Expression profiling of autism candidate genes during human brain development implicates central immune signaling pathways. PLoS One 6: e24691.
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