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2. Multi-omic longitudinal study reveals immune correlates of clinical course among hospitalized COVID-19 patients

Author

Abraham, James, Adkisson, Michael, Albert, Marisa, Altamirano, Luz Torres, Alvarenga, Bonny, Anderson, Matthew L., Anderson, Evan J., Arnett, Azlann, Asashima, Hiromitsu, Atkinson, Mark A., Baden, Lindsey R., Barton, Brenda, Beach, Katherine, Beagle, Elizabeth, Becker, Patrice M., Bell, Matthew R., Bernui, Mariana, Bime, Christian, Boddapati, Arun Kumar, Booth, J. Leland, Borresen, Brittney, Brakenridge, Scott C., Bristow, Laurel, Bryant, Robert, Calfee, Carolyn S., Carreño, Juan Manuel, Carrillo, Sidney, Chak, Suzanna, Chang, Iris, Connors, Jennifer, Conway, Michelle, Corry, David B., Cowan, David, Croen, Brett, Dela Cruz, Charles S., Cusimano, Gina, Eaker, Lily, Edwards, Carolyn, Ehrlich, Lauren I.R., Elashoff, David, Erickson, Heidi, Erle, David J., Farhadian, Shelli, Farrugia, Keith, Fatou, Benoit, Fernandes, Andrea, Fernandez-Sesma, Ana, Fragiadakis, Gabriela K., Furukawa, Sara, Geltman, Janelle N., Ghale, Rajani, Bermúdez González, Maria Carolina, Goonewardene, I. Michael, Guerrero, Estella Sanchez, Guirgis, Faheem W., Hafler, David A., Hamilton, Sydney, Harris, Paul, Hayati, Arash Nemati, Hendrickson, Carolyn M., Agudelo Higuita, Nelson I., Hodder, Thomas, Holland, Steven M., Hough, Catherine L., Huerta, Christopher, Hurley, Kerin C., Hutton, Scott R., Iwasaki, Akiko, Jauregui, Alejandra, Jha, Meenakshi, Johnson, Brandi, Joyner, David, Kangelaris, Kirsten N., Kelly, Geoffrey, Khalil, Zain, Khan, Zenab, Kheradmand, Farrah, Kim, James N., Kimura, Hiroki, Ko, Albert I., Kohr, Bernard, Kraft, Monica, Krummel, Matthew, Kutzler, Michele A., Lasky-Su, Jessica, Lee, Serena, Lee, Deanna, Leipold, Michael, Lentucci, Claudia, Leroux, Carolyn, Lin, Edward, Liu, Shanshan, Love, Christina, Lu, Zhengchun, Maliskova, Lenka, Manning, Brittany Roth, Manohar, Monali, Martens, Mark, McComsey, Grace A., McEnaney, Kerry, McLin, Renee, Melamed, Esther, Melnyk, Nataliya, Mendez, Kevin, Messer, William B., Metcalf, Jordan P., Michelotti, Gregory, Mick, Eran, Mohanty, Subhasis, Mosier, Jarrod, Mulder, Lubbertus C.F., Murphy, Maimouna, Nadeau, Kari R.C., Nelson, Ebony, Nelson, Allison, Nguyen, Viet, Oberhaus, Jordan, Panganiban, Bernadine, Pellegrini, Kathryn L., Pickering, Harry C., Powell, Debra L., Presnell, Scott, Pulendran, Bali, Rahman, Adeeb H., Rashid, Ahmad Sadeed, Raskin, Ariel, Reed, Elaine F., Ribeiro, Susan Pereira, Rivera, Adreanne M., Rogers, Jacob E., Rogers, Angela, Rogowski, Brandon, Rooks, Rebecca, Rosenberg-Hasson, Yael, Rothman, Jessica, Rousseau, Justin F., Salehi-Rad, Ramin, Saluvan, Mehmet, Samaha, Hady, Schaenman, Joanna, Schunk, Ron, Semenza, Nicholas C., Sen, Subha, Sevransky, Jonathan, Seyfert-Margolis, Vicki, Shaheen, Tanzia, Shaw, Albert C., Sieg, Scott, Siegel, Sarah A.R., Sigal, Natalia, Siles, Nadia, Simmons, Brent, Simon, Viviana, Singh, Gagandeep, Sinko, Lauren, Smith, Cecilia M., Smolen, Kinga K., Song, Li-Zhen, Srivastava, Komal, Sullivan, Peter, Syphurs, Caitlin, Tcheou, Johnstone, Tegos, George P., Tharp, Greg K., Tong, Alexandra, Tsitsiklis, Alexandra, Ungaro, Ricardo F., Vaysman, Tatyana, Viode, Arthur, Vita, Randi, Wang, Xiaomei, Ward, Alyssa, Ward, Dawn C., Willmore, Andrew, Woloszczuk, Kyra, Wong, Kari, Woodruff, Prescott G., Xu, Leqi, van Haren, Simon, van de Guchte, Adriana, Zhao, Yujiao, Diray-Arce, Joann, Fourati, Slim, Doni Jayavelu, Naresh, Patel, Ravi, Maguire, Cole, Chang, Ana C., Dandekar, Ravi, Qi, Jingjing, Lee, Brian H., van Zalm, Patrick, Schroeder, Andrew, Chen, Ernie, Konstorum, Anna, Brito, Anderson, Gygi, Jeremy P., Kho, Alvin, Chen, Jing, Pawar, Shrikant, Gonzalez-Reiche, Ana Silvia, Hoch, Annmarie, Milliren, Carly E., Overton, James A., Westendorf, Kerstin, Cairns, Charles B., Rouphael, Nadine, Bosinger, Steven E., Kim-Schulze, Seunghee, Krammer, Florian, Rosen, Lindsey, Grubaugh, Nathan D., van Bakel, Harm, Wilson, Michael, Rajan, Jayant, Steen, Hanno, Eckalbar, Walter, Cotsapas, Chris, Langelier, Charles R., Levy, Ofer, Altman, Matthew C., Maecker, Holden, Montgomery, Ruth R., Haddad, Elias K., Sekaly, Rafick P., Esserman, Denise, Ozonoff, Al, Augustine, Alison D., Guan, Leying, Peters, Bjoern, and Kleinstein, Steven H.

Published
2023
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5. Multi-omic longitudinal study reveals immune correlates of clinical course among hospitalized COVID-19 patients.

Author

Diray-Arce, Joann, Diray-Arce, Joann, Fourati, Slim, Doni Jayavelu, Naresh, Patel, Ravi, Maguire, Cole, Chang, Ana C, Dandekar, Ravi, Qi, Jingjing, Lee, Brian H, van Zalm, Patrick, Schroeder, Andrew, Chen, Ernie, Konstorum, Anna, Brito, Anderson, Gygi, Jeremy P, Kho, Alvin, Chen, Jing, Pawar, Shrikant, Gonzalez-Reiche, Ana Silvia, Hoch, Annmarie, Milliren, Carly E, Overton, James A, Westendorf, Kerstin, IMPACC Network, Cairns, Charles B, Rouphael, Nadine, Bosinger, Steven E, Kim-Schulze, Seunghee, Krammer, Florian, Rosen, Lindsey, Grubaugh, Nathan D, van Bakel, Harm, Wilson, Michael, Rajan, Jayant, Steen, Hanno, Eckalbar, Walter, Cotsapas, Chris, Langelier, Charles R, Levy, Ofer, Altman, Matthew C, Maecker, Holden, Montgomery, Ruth R, Haddad, Elias K, Sekaly, Rafick P, Esserman, Denise, Ozonoff, Al, Becker, Patrice M, Augustine, Alison D, Guan, Leying, Peters, Bjoern, Kleinstein, Steven H, Diray-Arce, Joann, Diray-Arce, Joann, Fourati, Slim, Doni Jayavelu, Naresh, Patel, Ravi, Maguire, Cole, Chang, Ana C, Dandekar, Ravi, Qi, Jingjing, Lee, Brian H, van Zalm, Patrick, Schroeder, Andrew, Chen, Ernie, Konstorum, Anna, Brito, Anderson, Gygi, Jeremy P, Kho, Alvin, Chen, Jing, Pawar, Shrikant, Gonzalez-Reiche, Ana Silvia, Hoch, Annmarie, Milliren, Carly E, Overton, James A, Westendorf, Kerstin, IMPACC Network, Cairns, Charles B, Rouphael, Nadine, Bosinger, Steven E, Kim-Schulze, Seunghee, Krammer, Florian, Rosen, Lindsey, Grubaugh, Nathan D, van Bakel, Harm, Wilson, Michael, Rajan, Jayant, Steen, Hanno, Eckalbar, Walter, Cotsapas, Chris, Langelier, Charles R, Levy, Ofer, Altman, Matthew C, Maecker, Holden, Montgomery, Ruth R, Haddad, Elias K, Sekaly, Rafick P, Esserman, Denise, Ozonoff, Al, Becker, Patrice M, Augustine, Alison D, Guan, Leying, Peters, Bjoern, and Kleinstein, Steven H

Abstract

The IMPACC cohort, composed of >1,000 hospitalized COVID-19 participants, contains five illness trajectory groups (TGs) during acute infection (first 28 days), ranging from milder (TG1-3) to more severe disease course (TG4) and death (TG5). Here, we report deep immunophenotyping, profiling of >15,000 longitudinal blood and nasal samples from 540 participants of the IMPACC cohort, using 14 distinct assays. These unbiased analyses identify cellular and molecular signatures present within 72 h of hospital admission that distinguish moderate from severe and fatal COVID-19 disease. Importantly, cellular and molecular states also distinguish participants with more severe disease that recover or stabilize within 28 days from those that progress to fatal outcomes (TG4 vs. TG5). Furthermore, our longitudinal design reveals that these biologic states display distinct temporal patterns associated with clinical outcomes. Characterizing host immune responses in relation to heterogeneity in disease course may inform clinical prognosis and opportunities for intervention.

Published
2023

6. A Noise Removal Algorithm for Time Series Microarray Data

Author

Doni Jayavelu, Naresh, Bar, Nadav, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Goebel, Randy, editor, Siekmann, Jörg, editor, Wahlster, Wolfgang, editor, Correia, Luís, editor, Reis, Luís Paulo, editor, and Cascalho, José, editor

Published
2013
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10. Erratum: A Noise Removal Algorithm for Time Series Microarray Data

Author

Doni Jayavelu, Naresh, Bar, Nadav, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Goebel, Randy, editor, Siekmann, Jörg, editor, Wahlster, Wolfgang, editor, Correia, Luís, editor, Reis, Luís Paulo, editor, and Cascalho, José, editor

Published
2013
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12. Enhancer Chromatin and 3D Genome Architecture Changes from Naive to Primed Human Embryonic Stem Cell States

Author

Battle, Stephanie L., primary, Doni Jayavelu, Naresh, additional, Azad, Robert N., additional, Hesson, Jennifer, additional, Ahmed, Faria N., additional, Overbey, Eliah G., additional, Zoller, Joseph A., additional, Mathieu, Julie, additional, Ruohola-Baker, Hannele, additional, Ware, Carol B., additional, and Hawkins, R. David, additional

Published
2019
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13. DNA methylation dynamics during embryonic development and postnatal maturation of the mouse auditory organ of Corti

Author

Yizhar-Barnea, Ofer, primary, Valensisi, Cristina, additional, Kishore, Kamal, additional, Doni Jayavelu, Naresh, additional, Andrus, Colin, additional, Koffler-Brill, Tal, additional, Ushakov, Kathy, additional, Perl, Kobi, additional, Noy, Yael, additional, Bhonker, Yoni, additional, Pelizzola, Mattia, additional, Hawkins, R. David, additional, and Avraham, Karen B., additional

Published
2018
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17. Reconstruction of temporal activity of microRNAs from gene expression data in breast cancer cell line

Author

Doni Jayavelu, Naresh and Bar, Nadav

Subjects
Network component analysis – microRNAs – Breast cancer – Activity – Data decomposition – Cancer markers – EGFR signaling – Survival analysis – Kaplan-Meier plots
Abstract

Background MicroRNAs (miRNAs) are small non-coding RNAs that regulate genes at the post-transcriptional level in spatiotemporal manner. Several miRNAs are identified as prognostic and diagnostic markers in many human cancers. Estimation of the temporal activities of the miRNAs is an important step in the way to understand the complex interactions of these important regulatory elements with transcription factors (TFs) and target genes (TGs). However, current research on miRNA activities excludes network dynamics from the studies, disregarding the important element of time in the regulatory network analysis. Results In the current study, we combined experimentally verified miRNA-TG interactions with breast cancer microarray TG expression data to identify key miRNAs and compute their temporal activity using network component analysis (NCA). The computed activities showed that miRNAs were regulated in a time dependent manner. Our results allowed constructing a synergistic network of miRNAs using the computed miRNA activities and their shared regulation of TGs. We further extended this network by incorporating miRNA-TG, miRNA-TF, TF-miRNA and TF-TG regulations in the context of breast cancer. Our integrated network identified several miRNAs known to be involved in breast cancer regulation and revealed several novel miRNAs. Our further analysis detected substantial involvement of the miRNAs miR-324, miR-93, miR-615 and miR-1 in breast cancer, which was not known previously. Next, combining our integrated networks with functional annotation of differentially expressed genes resulted in new sub-networks. These sub-networks allowed us to identify the key miRNAs and their interactions with TFs and TGs of several biological processes involved in breast cancer. The identified markers are validated for their potential as prognostic markers for breast cancer through survival analysis. Conclusions Our dynamical analysis of the miRNA interactions greatly helps to discover new network based markers, and is highly applicable (but not limited) to cancer research. © 2016 Jayavelu and Bar. Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Published
2015

19. Multi-omic longitudinal study reveals immune correlates of clinical course among hospitalized COVID-19 patients.

Author

Diray-Arce J, Fourati S, Doni Jayavelu N, Patel R, Maguire C, Chang AC, Dandekar R, Qi J, Lee BH, van Zalm P, Schroeder A, Chen E, Konstorum A, Brito A, Gygi JP, Kho A, Chen J, Pawar S, Gonzalez-Reiche AS, Hoch A, Milliren CE, Overton JA, Westendorf K, Cairns CB, Rouphael N, Bosinger SE, Kim-Schulze S, Krammer F, Rosen L, Grubaugh ND, van Bakel H, Wilson M, Rajan J, Steen H, Eckalbar W, Cotsapas C, Langelier CR, Levy O, Altman MC, Maecker H, Montgomery RR, Haddad EK, Sekaly RP, Esserman D, Ozonoff A, Becker PM, Augustine AD, Guan L, Peters B, and Kleinstein SH

Subjects
Humans, SARS-CoV-2, Longitudinal Studies, Multiomics, Disease Progression, COVID-19
Abstract

The IMPACC cohort, composed of >1,000 hospitalized COVID-19 participants, contains five illness trajectory groups (TGs) during acute infection (first 28 days), ranging from milder (TG1-3) to more severe disease course (TG4) and death (TG5). Here, we report deep immunophenotyping, profiling of >15,000 longitudinal blood and nasal samples from 540 participants of the IMPACC cohort, using 14 distinct assays. These unbiased analyses identify cellular and molecular signatures present within 72 h of hospital admission that distinguish moderate from severe and fatal COVID-19 disease. Importantly, cellular and molecular states also distinguish participants with more severe disease that recover or stabilize within 28 days from those that progress to fatal outcomes (TG4 vs. TG5). Furthermore, our longitudinal design reveals that these biologic states display distinct temporal patterns associated with clinical outcomes. Characterizing host immune responses in relation to heterogeneity in disease course may inform clinical prognosis and opportunities for intervention., Competing Interests: Declaration of interests The Icahn School of Medicine at Mount Sinai has filed patent applications relating to SARS-CoV-2 serological assays and NDV-based SARS-CoV-2 vaccines, which list F.K. as co-inventor. Mount Sinai has spun out a company, Kantaro, to market serological tests for SARS-CoV-2. F.K. has consulted for Merck and Pfizer (before 2020) and is currently consulting for Pfizer, Seqirus, Third Rock Ventures, Merck, and Avimex. The Krammer laboratory is also collaborating with Pfizer on animal models of SARS-CoV-2. Viviana Simon is a co-inventor on a patent filed relating to SARS-CoV-2 serological assays (the “Serology Assays”). O.L. is a named inventor on patents held by Boston Children’s Hospital relating to vaccine adjuvants and human in vitro platforms that model vaccine action. His laboratory has received research support from GlaxoSmithKline (GSK). C.B.C. serves as a consultant to bioMerieux and is funded for a grant from the Bill & Melinda Gates Foundation. J.A.O. is a consultant at Knocean, Inc. J.L.-S. serves as a scientific advisor of Precion, Inc. S.R.H., G.M., and K.W. are employees of Metabolon, Inc. V.S.-M. is a current employee of MyOwnMed. N.R. reports contracts with Lilly and Sanofi for COVID-19 clinical trials and serves as a consultant for ICON EMMES for consulting on safety for COVID19 clinical trials. A. Rahman is a current employee of Immunai, Inc. S.H.K. is a consultant related to ImmPort data repository for Peraton. N.D.G. is a consultant for Tempus Labs and the National Basketball Association. Akiko Iwasaki is a consultant for 4BIO, Blue Willow Biologics, Revelar Biotherapeutics, RIGImmune, Xanadu Bio, and Paratus Sciences. M. Kraft receives research funds paid to her institution from NIH and ALA and from Sanofi and Astra-Zeneca for work in asthma; serves as a consultant for Astra-Zeneca, Sanofi, Chiesi, and GSK for severe asthma; and is a co-founder and CMO for RaeSedo, Inc., a company created to develop peptidomimetics for treatment of inflammatory lung disease. E. Melamed received research funding from Babson Diagnostics and honorarium from Multiple Sclerosis Association of America and has served on the advisory boards of Genentech, Horizon, Teva, and Viela Bio., (Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.)

Published
2023
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