Isfahan University of Medical Sciences

Science Communicator Platform

Stay connected! Follow us on X network (Twitter):
Share this content! On (X network) By
A Crowdsourced Analysis to Identify Ab Initio Molecular Signatures Predictive of Susceptibility to Viral Infection Publisher Pubmed



Fourati S1 ; Talla A1 ; Mahmoudian M2, 3 ; Burkhart JG4, 5 ; Klen R2 ; Henao R6, 7 ; Yu T8 ; Aydin Z9 ; Yeung KY10 ; Ahsen ME11 ; Almugbel R10 ; Jahandideh S12 ; Liang X10 ; Nordling TEM13 Show All Authors
Authors
  1. Fourati S1
  2. Talla A1
  3. Mahmoudian M2, 3
  4. Burkhart JG4, 5
  5. Klen R2
  6. Henao R6, 7
  7. Yu T8
  8. Aydin Z9
  9. Yeung KY10
  10. Ahsen ME11
  11. Almugbel R10
  12. Jahandideh S12
  13. Liang X10
  14. Nordling TEM13
  15. Shiga M14
  16. Stanescu A11, 15
  17. Vogel R11, 16
  18. Abdallah EB21, 22
  19. Aghababazadeh FA23
  20. Amadoz A24
  21. Bhalla S25
  22. Bleakley K26, 27
  23. Bongen E28
  24. Borzacchielo D22, 29
  25. Bucher P30, 31
  26. Carbonellcaballero J32
  27. Chaudhary K33
  28. Chinesta F34
  29. Chodavarapu P35
  30. Chow RD36
  31. Cokelaer T37
  32. Cubuk C38
  33. Dhanda SK39
  34. Dopazo J38
  35. Faux T2
  36. Feng Y40
  37. Flinta C41
  38. Guziolowski C21, 22
  39. He D42
  40. Hidalgo MR38
  41. Hou J43
  42. Inoue K44, 45
  43. Jaakkola MK2, 46
  44. Ji J47
  45. Kumar R48
  46. Kumar S30, 31
  47. Kursa MB49
  48. Li Q50, 51
  49. Lopuszynski M49
  50. Lu P51
  51. Magnin M21, 22, 44
  52. Mao W52, 53
  53. Miannay B21
  54. Nikolayeva I54, 55, 56
  55. Obradovic Z57
  56. Pak C58
  57. Rahman MM10
  58. Razzaq M21, 22
  59. Ribeiro T21, 22, 44
  60. Roux O21, 22
  61. Saghapour E59
  62. Saini H60
  63. Sarhadi S61
  64. Sato H62
  65. Schwikowski B54
  66. Sharma A63, 64, 65
  67. Sharma R65, 66
  68. Singla D67
  69. Stojkovic I57, 68
  70. Suomi T2
  71. Suprun M69
  72. Tian C70, 71
  73. Tomalin LE72
  74. Xie L73
  75. Yu X74
  76. Pandey G11
  77. Chiu C17
  78. Mcclain MT6, 18, 19
  79. Woods CW6, 18, 19
  80. Ginsburg GS6, 19
  81. Elo LL2
  82. Tsalik EL6, 19, 20
  83. Mangravite LM8
  84. Sieberts SK8
Show Affiliations
Authors Affiliations
  1. 1. Department of Pathology, School of Medicine, Case Western Reserve University, Cleveland, 44106, OH, United States
  2. 2. Turku Centre for Biotechnology, University of Turku and Abo Akademi University, Turku, FI-20520, Finland
  3. 3. Department of Future Technologies, University of Turku, Turku, FI-20014, Finland
  4. 4. Department of Medical Informatics and Clinical Epidemiology, School of Medicine, Oregon Health & Science University, Portland, 97239, OR, United States
  5. 5. Laboratory of Evolutionary Genetics, Institute of Ecology and Evolution, University of Oregon, Eugene, 97403, OR, United States
  6. 6. Duke Center for Applied Genomics and Precision Medicine, Duke University School of Medicine, Durham, 27710, NC, United States
  7. 7. Department of Electrical and Computer Engineering, Duke University, Durham, 27708, NC, United States
  8. 8. Sage Bionetworks, Seattle, 98121, WA, United States
  9. 9. Department of Computer Engineering, Abdullah Gul University, Kayseri, 38080, Turkey
  10. 10. School of Engineering and Technology, University of Washington Tacoma, Tacoma, 98402, WA, United States
  11. 11. Department of Genetics and Genomic Sciences and Icahn Institute for Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, 10029, NY, United States
  12. 12. Origent Data Sciences, Inc., Vienna, 22182, VA, United States
  13. 13. Department of Mechanical Engineering, National Cheng Kung University, Tainan, 70101, Taiwan
  14. 14. Department of Electrical, Electronic and Computer Engineering, Faculty of Engineering, Gifu University, Gifu, 501-1193, Japan
  15. 15. Department of Computer Science, University of West Georgia, Carrolton, 30116, GA, United States
  16. 16. IBM T.J. Watson Research Center, Yorktown Heights, 10598, NY, United States
  17. 17. Section of Infectious Diseases and Immunity, Imperial College London, London, W12 0NN, United Kingdom
  18. 18. Medical Service, Durham VA Health Care System, Durham, 27705, NC, United States
  19. 19. Department of Medicine, Duke University School of Medicine, Durham, 27710, NC, United States
  20. 20. Emergency Medicine Service, Durham VA Health Care System, Durham, 27705, NC, United States
  21. 21. Laboratoire des Sciences du Numerique de Nantes, Nantes, 44321, France
  22. 22. Ecole Centrale de Nantes, Nantes, 44321, France
  23. 23. Department of Biostatistics and Bioinformatics, Moffitt Cancer Center, Tampa, 33612, FL, United States
  24. 24. Department of Bioinformatics, Igenomix SL, Paterna, 46980, Spain
  25. 25. CSIR-Institute of Microbial Technology, Chandigarh, 160036, India
  26. 26. Inria Saclay, Palaiseau, 91120, France
  27. 27. Departement de Mathematiques d’Orsay, Orsay, 91405, France
  28. 28. Stanford Immunology, Stanford, 94305, CA, United States
  29. 29. Institut de Calcul Intensif, Nantes, 44321, France
  30. 30. Swiss Institute for Experimental Cancer Research, Swiss Federal Institute of Technology Lausanne (EPFL), Lausanne, 1015, Switzerland
  31. 31. Swiss Institute of Bioinformatics, Lausanne, 1015, Switzerland
  32. 32. Centre de Regulacio Genomica (CRG), Barcelona Institute for Science and Technology, Barcelona, 09003, Spain
  33. 33. Epidemiology Program, University of Hawaii Cancer Center, Honolulu, 96813, HI, United States
  34. 34. PIMM, ENSAM ParisTech, Paris, 75013, France
  35. 35. Aganitha Cognitive Solutions, S.R. Shetty Nagar, Bangalore, 560 076, India
  36. 36. Department of Genetics, Yale School of Medicine, New Haven, 06510, CT, United States
  37. 37. Institut Pasteur—Bioinformatics and Biostatistics Hub—C3BI, USR3756 IP CNRS, Paris, 75015, France
  38. 38. Clinical Bioinformatic Area, Fundacion Progreso y Salud, Sevilla, 41012, Spain
  39. 39. Division of Vaccine Discovery, La Jolla Institute for Allergy and Immunology, La Jolla, 92037, CA, United States
  40. 40. Department of Statistics, Columbia University, New York, 10027, NY, United States
  41. 41. Ericsson Research, Machine Intelligence and Automation, Stockholm, 164 83, Sweden
  42. 42. Department of Computer Science, Graduate Center, The City University of New York, New York, 10016, NY, United States
  43. 43. Altman Translational and Clinical Research Institute, University of California, San Diego, La Jolla, 92037, CA, United States
  44. 44. National Institute of Informatics, Chiyoda-ku, Tokyo, 101-8430, Japan
  45. 45. Tokyo Institute of Technology, Meguro-ku, Tokyo, 152-8550, Japan
  46. 46. Department of Mathematics and Statistics, University of Turku, Turku, FI-20014, Finland
  47. 47. Department of Mathematical Statistics, School of Statistics, Shandong University of Finance and Economics, Jinan, 250014, Shandong, China
  48. 48. CSIR-Central Scientific Instruments Organization, Chandigarh, 160030, India
  49. 49. Interdisciplinary Centre for Mathematical and Computational Modelling, University of Warsaw, Warsaw, 02-106, Poland
  50. 50. Health Informatics Institute, Morsani College of Medicine, University of South Florida, Tampa, 33620, FL, United States
  51. 51. Department of Biostatistics, University of Kansas Medical Center, Kansas City, 66160, KS, United States
  52. 52. Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, 15260, PA, United States
  53. 53. Carnegie Mellon-University of Pittsburgh, Pittsburgh, 15260, PA, United States
  54. 54. Systems Biology Laboratory, Center for Bioinformatics, Biostatistics, and Integrative Biology (C3BI) and USR 3756, Institut Pasteur, Paris, 75015, France
  55. 55. Unite de Genetique fonctionnelle des maladies infectieuses, Institut Pasteur, Paris, 75015, France
  56. 56. Universite Paris-Descartes, Sorbonne Paris Cite, Paris, 75014, France
  57. 57. Center for Data Analytics and Biomedical Informatics, College of Science and Technology, Temple University, Philadelphia, 19122, PA, United States
  58. 58. UT Southwestern Medical Center at Dallas, Dallas, 75390, TX, United States
  59. 59. Department of Biomedical Engineering, School of Advanced Technologies in Medicine, Isfahan University of Medical Sciences, Isfahan, 8174673461, Iran
  60. 60. Research Innovation and International, University of the South Pacific, Suva, Fiji
  61. 61. Department of Medical Biotechnology, Faculty of Advanced Medical Sciences, Tabriz University of Medical Sciences, Tabriz, 51368, Iran
  62. 62. Graduate School of Natural Science and Technology, Gifu University, Gifu, 501-1193, Japan
  63. 63. Laboratory of Medical Science Mathematics, RIKEN Center for Integrative Medical Science, Yokohama, 230-0045, Japan
  64. 64. Institute for Integrated and Intelligent Systems, Griffith University, Brisbane, 4111, QLD, Australia
  65. 65. School of Engineering and Physics, Faculty of Science Technology and Environment, University of the South Pacific, Suva, Fiji
  66. 66. School of Electrical and Electronics Engineering, Fiji National University, Suva, Fiji
  67. 67. Host−Parasite Interaction Biology Group, National Institute of Malaria Research, New Delhi, 110077, India
  68. 68. Signals and Systems Department, School of Electrical Engineering, University of Belgrade, Belgrade, 11120, Serbia
  69. 69. Department of Pediatrics, Allergy and Immunology, Icahn School of Medicine at Mount Sinai, New York, 10029, NY, United States
  70. 70. Niels Bohr Institute, University of Copenhagen, Copenhagen, 2100, Denmark
  71. 71. Department of Chemistry and Biochemistry, University of Colorado, Boulder, Boulder, 80303, CO, United States
  72. 72. Icahn School of Medicine at Mount Sinai, New York, 10029, NY, United States
  73. 73. Department of Computer Science, The City University of New York, New York, 10065, NY, United States
  74. 74. Department of Biology, University of Pennsylvania, Philadelphia, 19104, PA, United States

Source: Nature Communications Published:2018


Abstract

The response to respiratory viruses varies substantially between individuals, and there are currently no known molecular predictors from the early stages of infection. Here we conduct a community-based analysis to determine whether pre- or early post-exposure molecular factors could predict physiologic responses to viral exposure. Using peripheral blood gene expression profiles collected from healthy subjects prior to exposure to one of four respiratory viruses (H1N1, H3N2, Rhinovirus, and RSV), as well as up to 24 h following exposure, we find that it is possible to construct models predictive of symptomatic response using profiles even prior to viral exposure. Analysis of predictive gene features reveal little overlap among models; however, in aggregate, these genes are enriched for common pathways. Heme metabolism, the most significantly enriched pathway, is associated with a higher risk of developing symptoms following viral exposure. This study demonstrates that pre-exposure molecular predictors can be identified and improves our understanding of the mechanisms of response to respiratory viruses. © 2018, The Author(s).