Institute Affiliations


All Publications


  • NASA GeneLab RNA-seq consensus pipeline: standardized processing of short-read RNA-seq data. iScience Overbey, E. G., Saravia-Butler, A. M., Zhang, Z., Rathi, K. S., Fogle, H., da Silveira, W. A., Barker, R. J., Bass, J. J., Beheshti, A., Berrios, D. C., Blaber, E. A., Cekanaviciute, E., Costa, H. A., Davin, L. B., Fisch, K. M., Gebre, S. G., Geniza, M., Gilbert, R., Gilroy, S., Hardiman, G., Herranz, R., Kidane, Y. H., Kruse, C. P., Lee, M. D., Liefeld, T., Lewis, N. G., McDonald, J. T., Meller, R., Mishra, T., Perera, I. Y., Ray, S., Reinsch, S. S., Rosenthal, S. B., Strong, M., Szewczyk, N. J., Tahimic, C. G., Taylor, D. M., Vandenbrink, J. P., Villacampa, A., Weging, S., Wolverton, C., Wyatt, S. E., Zea, L., Costes, S. V., Galazka, J. M. 2021; 24 (4): 102361

    Abstract

    With the development of transcriptomic technologies, we are able to quantify precise changes in gene expression profiles from astronauts and other organisms exposed to spaceflight. Members of NASA GeneLab and GeneLab-associated analysis working groups (AWGs) have developed a consensus pipeline for analyzing short-read RNA-sequencing data from spaceflight-associated experiments. The pipeline includes quality control, read trimming, mapping, and gene quantification steps, culminating in the detection of differentially expressed genes. This data analysis pipeline and the results of its execution using data submitted to GeneLab are now all publicly available through the GeneLab database. We present here the full details and rationale for the construction of this pipeline in order to promote transparency, reproducibility, and reusability of pipeline data; to provide a template for data processing of future spaceflight-relevant datasets; and to encourage cross-analysis of data from other databases with the data available in GeneLab.

    View details for DOI 10.1016/j.isci.2021.102361

    View details for PubMedID 33870146

  • Cell-free DNA (cfDNA) and Exosome Profiling from a Year-Long Human Spaceflight Reveals Circulating Biomarkers. iScience Bezdan, D., Grigorev, K., Meydan, C., Pelissier Vatter, F. A., Cioffi, M., Rao, V., MacKay, M., Nakahira, K., Burnham, P., Afshinnekoo, E., Westover, C., Butler, D., Mozsary, C., Donahoe, T., Foox, J., Mishra, T., Lucotti, S., Rana, B. K., Melnick, A. M., Zhang, H., Matei, I., Kelsen, D., Yu, K., Lyden, D. C., Taylor, L., Bailey, S. M., Snyder, M. P., Garrett-Bakelman, F. E., Ossowski, S., De Vlaminck, I., Mason, C. E. 2020; 23 (12): 101844

    Abstract

    Liquid biopsies based on cell-free DNA (cfDNA) or exosomes provide a noninvasive approach to monitor human health and disease but have not been utilized for astronauts. Here, we profile cfDNA characteristics, including fragment size, cellular deconvolution, and nucleosome positioning, in an astronaut during a year-long mission on the International Space Station, compared to his identical twin on Earth and healthy donors. We observed a significant increase in the proportion of cell-free mitochondrial DNA (cf-mtDNA) inflight, and analysis of post-flight exosomes in plasma revealed a 30-fold increase in circulating exosomes and patient-specific protein cargo (including brain-derived peptides) after the year-long mission. This longitudinal analysis of astronaut cfDNA during spaceflight and the exosome profiles highlights their utility for astronaut health monitoring, as well as cf-mtDNA levels as a potential biomarker for physiological stress or immune system responses related to microgravity, radiation exposure, and the other unique environmental conditions of spaceflight.

    View details for DOI 10.1016/j.isci.2020.101844

    View details for PubMedID 33376973

  • Pre-symptomatic detection of COVID-19 from smartwatch data. Nature biomedical engineering Mishra, T., Wang, M., Metwally, A. A., Bogu, G. K., Brooks, A. W., Bahmani, A., Alavi, A., Celli, A., Higgs, E., Dagan-Rosenfeld, O., Fay, B., Kirkpatrick, S., Kellogg, R., Gibson, M., Wang, T., Hunting, E. M., Mamic, P., Ganz, A. B., Rolnik, B., Li, X., Snyder, M. P. 2020

    Abstract

    Consumer wearable devices that continuously measure vital signs have been used to monitor the onset of infectious disease. Here, we show that data from consumer smartwatches can be used for the pre-symptomatic detection of coronavirus disease 2019 (COVID-19). We analysed physiological and activity data from 32 individuals infected with COVID-19, identified from a cohort of nearly 5,300 participants, and found that 26 of them (81%) had alterations in their heart rate, number of daily steps or time asleep. Of the 25 cases of COVID-19 with detected physiological alterations for which we had symptom information, 22 were detected before (or at) symptom onset, with four cases detected at least nine days earlier. Using retrospective smartwatch data, we show that 63% of the COVID-19 cases could have been detected before symptom onset in real time via a two-tiered warning system based on the occurrence of extreme elevations in resting heart rate relative to the individual baseline. Our findings suggest that activity tracking and health monitoring via consumer wearable devices may be used for the large-scale, real-time detection of respiratory infections, often pre-symptomatically.

    View details for DOI 10.1038/s41551-020-00640-6

    View details for PubMedID 33208926

  • Perspectives on ENCODE. Nature ENCODE Project Consortium, Snyder, M. P., Gingeras, T. R., Moore, J. E., Weng, Z., Gerstein, M. B., Ren, B., Hardison, R. C., Stamatoyannopoulos, J. A., Graveley, B. R., Feingold, E. A., Pazin, M. J., Pagan, M., Gilchrist, D. A., Hitz, B. C., Cherry, J. M., Bernstein, B. E., Mendenhall, E. M., Zerbino, D. R., Frankish, A., Flicek, P., Myers, R. M., Abascal, F., Acosta, R., Addleman, N. J., Adrian, J., Afzal, V., Aken, B., Akiyama, J. A., Jammal, O. A., Amrhein, H., Anderson, S. M., Andrews, G. R., Antoshechkin, I., Ardlie, K. G., Armstrong, J., Astley, M., Banerjee, B., Barkal, A. A., Barnes, I. H., Barozzi, I., Barrell, D., Barson, G., Bates, D., Baymuradov, U. K., Bazile, C., Beer, M. A., Beik, S., Bender, M. A., Bennett, R., Bouvrette, L. P., Bernstein, B. E., Berry, A., Bhaskar, A., Bignell, A., Blue, S. M., Bodine, D. M., Boix, C., Boley, N., Borrman, T., Borsari, B., Boyle, A. P., Brandsmeier, L. A., Breschi, A., Bresnick, E. H., Brooks, J. A., Buckley, M., Burge, C. B., Byron, R., Cahill, E., Cai, L., Cao, L., Carty, M., Castanon, R. G., Castillo, A., Chaib, H., Chan, E. T., Chee, D. R., Chee, S., Chen, H., Chen, H., Chen, J., Chen, S., Cherry, J. M., Chhetri, S. B., Choudhary, J. S., Chrast, J., Chung, D., Clarke, D., Cody, N. A., Coppola, C. J., Coursen, J., D'Ippolito, A. M., Dalton, S., Danyko, C., Davidson, C., Davila-Velderrain, J., Davis, C. A., Dekker, J., Deran, A., DeSalvo, G., Despacio-Reyes, G., Dewey, C. N., Dickel, D. E., Diegel, M., Diekhans, M., Dileep, V., Ding, B., Djebali, S., Dobin, A., Dominguez, D., Donaldson, S., Drenkow, J., Dreszer, T. R., Drier, Y., Duff, M. O., Dunn, D., Eastman, C., Ecker, J. R., Edwards, M. D., El-Ali, N., Elhajjajy, S. I., Elkins, K., Emili, A., Epstein, C. B., Evans, R. C., Ezkurdia, I., Fan, K., Farnham, P. J., Farrell, N., Feingold, E. A., Ferreira, A., Fisher-Aylor, K., Fitzgerald, S., Flicek, P., Foo, C. S., Fortier, K., Frankish, A., Freese, P., Fu, S., Fu, X., Fu, Y., Fukuda-Yuzawa, Y., Fulciniti, M., Funnell, A. P., Gabdank, I., Galeev, T., Gao, M., Giron, C. G., Garvin, T. H., Gelboin-Burkhart, C. A., Georgolopoulos, G., Gerstein, M. B., Giardine, B. M., Gifford, D. K., Gilbert, D. M., Gilchrist, D. A., Gillespie, S., Gingeras, T. R., Gong, P., Gonzalez, A., Gonzalez, J. M., Good, P., Goren, A., Gorkin, D. U., Graveley, B. R., Gray, M., Greenblatt, J. F., Griffiths, E., Groudine, M. T., Grubert, F., Gu, M., Guigo, R., Guo, H., Guo, Y., Guo, Y., Gursoy, G., Gutierrez-Arcelus, M., Halow, J., Hardison, R. C., Hardy, M., Hariharan, M., Harmanci, A., Harrington, A., Harrow, J. L., Hashimoto, T. B., Hasz, R. D., Hatan, M., Haugen, E., Hayes, J. E., He, P., He, Y., Heidari, N., Hendrickson, D., Heuston, E. F., Hilton, J. A., Hitz, B. C., Hochman, A., Holgren, C., Hou, L., Hou, S., Hsiao, Y. E., Hsu, S., Huang, H., Hubbard, T. J., Huey, J., Hughes, T. R., Hunt, T., Ibarrientos, S., Issner, R., Iwata, M., Izuogu, O., Jaakkola, T., Jameel, N., Jansen, C., Jiang, L., Jiang, P., Johnson, A., Johnson, R., Jungreis, I., Kadaba, M., Kasowski, M., Kasparian, M., Kato, M., Kaul, R., Kawli, T., Kay, M., Keen, J. C., Keles, S., Keller, C. A., Kelley, D., Kellis, M., Kheradpour, P., Kim, D. S., Kirilusha, A., Klein, R. J., Knoechel, B., Kuan, S., Kulik, M. J., Kumar, S., Kundaje, A., Kutyavin, T., Lagarde, J., Lajoie, B. R., Lambert, N. J., Lazar, J., Lee, A. Y., Lee, D., Lee, E., Lee, J. W., Lee, K., Leslie, C. S., Levy, S., Li, B., Li, H., Li, N., Li, X., Li, Y. I., Li, Y., Li, Y., Li, Y., Lian, J., Libbrecht, M. W., Lin, S., Lin, Y., Liu, D., Liu, J., Liu, P., Liu, T., Liu, X. S., Liu, Y., Liu, Y., Long, M., Lou, S., Loveland, J., Lu, A., Lu, Y., Lecuyer, E., Ma, L., Mackiewicz, M., Mannion, B. J., Mannstadt, M., Manthravadi, D., Marinov, G. K., Martin, F. J., Mattei, E., McCue, K., McEown, M., McVicker, G., Meadows, S. K., Meissner, A., Mendenhall, E. M., Messer, C. L., Meuleman, W., Meyer, C., Miller, S., Milton, M. G., Mishra, T., Moore, D. E., Moore, H. M., Moore, J. E., Moore, S. H., Moran, J., Mortazavi, A., Mudge, J. M., Munshi, N., Murad, R., Myers, R. M., Nandakumar, V., Nandi, P., Narasimha, A. M., Narayanan, A. K., Naughton, H., Navarro, F. C., Navas, P., Nazarovs, J., Nelson, J., Neph, S., Neri, F. J., Nery, J. R., Nesmith, A. R., Newberry, J. S., Newberry, K. M., Ngo, V., Nguyen, R., Nguyen, T. B., Nguyen, T., Nishida, A., Noble, W. S., Novak, C. S., Novoa, E. M., Nunez, B., O'Donnell, C. W., Olson, S., Onate, K. C., Otterman, E., Ozadam, H., Pagan, M., Palden, T., Pan, X., Park, Y., Partridge, E. C., Paten, B., Pauli-Behn, F., Pazin, M. J., Pei, B., Pennacchio, L. A., Perez, A. R., Perry, E. H., Pervouchine, D. D., Phalke, N. N., Pham, Q., Phanstiel, D. H., Plajzer-Frick, I., Pratt, G. A., Pratt, H. E., Preissl, S., Pritchard, J. K., Pritykin, Y., Purcaro, M. J., Qin, Q., Quinones-Valdez, G., Rabano, I., Radovani, E., Raj, A., Rajagopal, N., Ram, O., Ramirez, L., Ramirez, R. N., Rausch, D., Raychaudhuri, S., Raymond, J., Razavi, R., Reddy, T. E., Reimonn, T. M., Ren, B., Reymond, A., Reynolds, A., Rhie, S. K., Rinn, J., Rivera, M., Rivera-Mulia, J. C., Roberts, B., Rodriguez, J. M., Rozowsky, J., Ryan, R., Rynes, E., Salins, D. N., Sandstrom, R., Sasaki, T., Sathe, S., Savic, D., Scavelli, A., Scheiman, J., Schlaffner, C., Schloss, J. A., Schmitges, F. W., See, L. H., Sethi, A., Setty, M., Shafer, A., Shan, S., Sharon, E., Shen, Q., Shen, Y., Sherwood, R. I., Shi, M., Shin, S., Shoresh, N., Siebenthall, K., Sisu, C., Slifer, T., Sloan, C. A., Smith, A., Snetkova, V., Snyder, M. P., Spacek, D. V., Srinivasan, S., Srivas, R., Stamatoyannopoulos, G., Stamatoyannopoulos, J. A., Stanton, R., Steffan, D., Stehling-Sun, S., Strattan, J. S., Su, A., Sundararaman, B., Suner, M., Syed, T., Szynkarek, M., Tanaka, F. Y., Tenen, D., Teng, M., Thomas, J. A., Toffey, D., Tress, M. L., Trout, D. E., Trynka, G., Tsuji, J., Upchurch, S. A., Ursu, O., Uszczynska-Ratajczak, B., Uziel, M. C., Valencia, A., Biber, B. V., van der Velde, A. G., Van Nostrand, E. L., Vaydylevich, Y., Vazquez, J., Victorsen, A., Vielmetter, J., Vierstra, J., Visel, A., Vlasova, A., Vockley, C. M., Volpi, S., Vong, S., Wang, H., Wang, M., Wang, Q., Wang, R., Wang, T., Wang, W., Wang, X., Wang, Y., Watson, N. K., Wei, X., Wei, Z., Weisser, H., Weissman, S. M., Welch, R., Welikson, R. E., Weng, Z., Westra, H., Whitaker, J. W., White, C., White, K. P., Wildberg, A., Williams, B. A., Wine, D., Witt, H. N., Wold, B., Wolf, M., Wright, J., Xiao, R., Xiao, X., Xu, J., Xu, J., Yan, K., Yan, Y., Yang, H., Yang, X., Yang, Y., Yardimci, G. G., Yee, B. A., Yeo, G. W., Young, T., Yu, T., Yue, F., Zaleski, C., Zang, C., Zeng, H., Zeng, W., Zerbino, D. R., Zhai, J., Zhan, L., Zhan, Y., Zhang, B., Zhang, J., Zhang, J., Zhang, K., Zhang, L., Zhang, P., Zhang, Q., Zhang, X., Zhang, Y., Zhang, Z., Zhao, Y., Zheng, Y., Zhong, G., Zhou, X., Zhu, Y., Zimmerman, J. 2020; 583 (7818): 693–98

    Abstract

    The Encylopedia of DNA Elements (ENCODE) Project launched in 2003 with the long-term goal of developing a comprehensive map of functional elements in the human genome. These included genes, biochemical regions associated with gene regulation (for example, transcription factor binding sites, open chromatin, and histone marks) and transcript isoforms. The marks serve as sites for candidate cis-regulatory elements (cCREs) that may serve functional roles in regulating gene expression1. The project has been extended to model organisms, particularly the mouse. In the third phase of ENCODE, nearly a million and more than 300,000 cCRE annotations have been generated for human and mouse, respectively, and these have provided a valuable resource for the scientific community.

    View details for DOI 10.1038/s41586-020-2449-8

    View details for PubMedID 32728248

  • Deep longitudinal multiomics profiling reveals two biological seasonal patterns in California. Nature communications Sailani, M. R., Metwally, A. A., Zhou, W. n., Rose, S. M., Ahadi, S. n., Contrepois, K. n., Mishra, T. n., Zhang, M. J., Kidziński, Ł. n., Chu, T. J., Snyder, M. P. 2020; 11 (1): 4933

    Abstract

    The influence of seasons on biological processes is poorly understood. In order to identify biological seasonal patterns based on diverse molecular data, rather than calendar dates, we performed a deep longitudinal multiomics profiling of 105 individuals over 4 years. Here, we report more than 1000 seasonal variations in omics analytes and clinical measures. The different molecules group into two major seasonal patterns which correlate with peaks in late spring and late fall/early winter in California. The two patterns are enriched for molecules involved in human biological processes such as inflammation, immunity, cardiovascular health, as well as neurological and psychiatric conditions. Lastly, we identify molecules and microbes that demonstrate different seasonal patterns in insulin sensitive and insulin resistant individuals. The results of our study have important implications in healthcare and highlight the value of considering seasonality when assessing population wide health risk and management.

    View details for DOI 10.1038/s41467-020-18758-1

    View details for PubMedID 33004787

  • Expanded encyclopaedias of DNA elements in the human and mouse genomes. Nature Moore, J. E., Purcaro, M. J., Pratt, H. E., Epstein, C. B., Shoresh, N. n., Adrian, J. n., Kawli, T. n., Davis, C. A., Dobin, A. n., Kaul, R. n., Halow, J. n., Van Nostrand, E. L., Freese, P. n., Gorkin, D. U., Shen, Y. n., He, Y. n., Mackiewicz, M. n., Pauli-Behn, F. n., Williams, B. A., Mortazavi, A. n., Keller, C. A., Zhang, X. O., Elhajjajy, S. I., Huey, J. n., Dickel, D. E., Snetkova, V. n., Wei, X. n., Wang, X. n., Rivera-Mulia, J. C., Rozowsky, J. n., Zhang, J. n., Chhetri, S. B., Zhang, J. n., Victorsen, A. n., White, K. P., Visel, A. n., Yeo, G. W., Burge, C. B., Lécuyer, E. n., Gilbert, D. M., Dekker, J. n., Rinn, J. n., Mendenhall, E. M., Ecker, J. R., Kellis, M. n., Klein, R. J., Noble, W. S., Kundaje, A. n., Guigó, R. n., Farnham, P. J., Cherry, J. M., Myers, R. M., Ren, B. n., Graveley, B. R., Gerstein, M. B., Pennacchio, L. A., Snyder, M. P., Bernstein, B. E., Wold, B. n., Hardison, R. C., Gingeras, T. R., Stamatoyannopoulos, J. A., Weng, Z. n. 2020; 583 (7818): 699–710

    Abstract

    The human and mouse genomes contain instructions that specify RNAs and proteins and govern the timing, magnitude, and cellular context of their production. To better delineate these elements, phase III of the Encyclopedia of DNA Elements (ENCODE) Project has expanded analysis of the cell and tissue repertoires of RNA transcription, chromatin structure and modification, DNA methylation, chromatin looping, and occupancy by transcription factors and RNA-binding proteins. Here we summarize these efforts, which have produced 5,992 new experimental datasets, including systematic determinations across mouse fetal development. All data are available through the ENCODE data portal (https://www.encodeproject.org), including phase II ENCODE1 and Roadmap Epigenomics2 data. We have developed a registry of 926,535 human and 339,815 mouse candidate cis-regulatory elements, covering 7.9 and 3.4% of their respective genomes, by integrating selected datatypes associated with gene regulation, and constructed a web-based server (SCREEN; http://screen.encodeproject.org) to provide flexible, user-defined access to this resource. Collectively, the ENCODE data and registry provide an expansive resource for the scientific community to build a better understanding of the organization and function of the human and mouse genomes.

    View details for DOI 10.1038/s41586-020-2493-4

    View details for PubMedID 32728249

  • Longitudinal multi-omics of host-microbe dynamics in prediabetes. Nature Zhou, W., Sailani, M. R., Contrepois, K., Zhou, Y., Ahadi, S., Leopold, S. R., Zhang, M. J., Rao, V., Avina, M., Mishra, T., Johnson, J., Lee-McMullen, B., Chen, S., Metwally, A. A., Tran, T. D., Nguyen, H., Zhou, X., Albright, B., Hong, B., Petersen, L., Bautista, E., Hanson, B., Chen, L., Spakowicz, D., Bahmani, A., Salins, D., Leopold, B., Ashland, M., Dagan-Rosenfeld, O., Rego, S., Limcaoco, P., Colbert, E., Allister, C., Perelman, D., Craig, C., Wei, E., Chaib, H., Hornburg, D., Dunn, J., Liang, L., Rose, S. M., Kukurba, K., Piening, B., Rost, H., Tse, D., McLaughlin, T., Sodergren, E., Weinstock, G. M., Snyder, M. 2019; 569 (7758): 663–71

    Abstract

    Type 2 diabetes mellitus (T2D) is a growing health problem, but little is known about its early disease stages, its effects on biological processes or the transition to clinical T2D. To understand the earliest stages of T2Dbetter, we obtained samples from 106 healthy individuals and individuals with prediabetes over approximately four years and performed deep profiling of transcriptomes, metabolomes, cytokines, and proteomes, as well as changes in the microbiome. This rich longitudinal data set revealed many insights: first, healthy profiles are distinct among individuals while displaying diverse patterns of intra- and/or inter-personal variability. Second, extensive host and microbial changes occur during respiratory viral infections and immunization, and immunization triggers potentially protective responses that are distinct from responses to respiratory viral infections. Moreover, during respiratory viral infections, insulin-resistant participants respond differently than insulin-sensitive participants. Third, global co-association analyses among the thousands of profiled molecules reveal specific host-microbe interactions that differ between insulin-resistant and insulin-sensitive individuals. Last, we identified early personal molecular signatures in one individual that preceded the onset of T2D, including the inflammation markers interleukin-1 receptor agonist (IL-1RA) and high-sensitivity C-reactive protein (CRP) paired with xenobiotic-induced immune signalling. Our study reveals insights into pathways and responses that differ between glucose-dysregulated and healthy individuals during health and disease and provides an open-access data resource to enable further research into healthy, prediabetic and T2D states.

    View details for DOI 10.1038/s41586-019-1236-x

    View details for PubMedID 31142858

  • A longitudinal big data approach for precision health NATURE MEDICINE Rose, S., Contrepois, K., Moneghetti, K. J., Zhou, W., Mishra, T., Mataraso, S., Dagan-Rosenfeld, O., Ganz, A. B., Dunn, J., Hornburg, D., Rego, S., Perelman, D., Ahadi, S., Sailani, M., Zhou, Y., Leopold, S. R., Chen, J., Ashland, M., Christle, J. W., Avina, M., Limcaoco, P., Ruiz, C., Tan, M., Butte, A. J., Weinstock, G. M., Slavich, G. M., Sodergren, E., McLaughlin, T. L., Haddad, F., Snyder, M. P. 2019; 25 (5): 792-+
  • The NASA Twins Study: A multidimensional analysis of a year-long human spaceflight SCIENCE Garrett-Bakelman, F. E., Darshi, M., Green, S. J., Gur, R. C., Lin, L., Macias, B. R., McKenna, M. J., Meydan, C., Mishra, T., Nasrini, J., Piening, B. D., Rizzardi, L. F., Sharma, K., Siamwala, J. H., Taylor, L., Vitaterna, M., Afkarian, M., Afshinnekoo, E., Ahadi, S., Ambati, A., Arya, M., Bezdan, D., Callahan, C. M., Chen, S., Choi, A. K., Chlipala, G. E., Contrepois, K., Covington, M., Crucian, B. E., De Vivo, I., Dinges, D. F., Ebert, D. J., Feinberg, J. I., Gandara, J. A., George, K. A., Goutsias, J., Grills, G. S., Hargens, A. R., Heer, M., Hillary, R. P., Hoofnagle, A. N., Hook, V. H., Jenkinson, G., Jiang, P., Keshavarzian, A., Laurie, S. S., Lee-McMullen, B., Lumpkins, S. B., MacKay, M., Maienschein-Cline, M. G., Melnick, A. M., Moore, T. M., Nakahira, K., Patel, H. H., Pietrzyk, R., Rao, V., Saito, R., Salins, D. N., Schilling, J. M., Sears, D. D., Sheridan, C. K., Stenger, M. B., Tryggvadottir, R., Urban, A. E., Vaisar, T., Van Espen, B., Zhang, J., Ziegler, M. G., Zwart, S. R., Charles, J. B., Kundrot, C. E., Scott, G. I., Bailey, S. M., Basner, M., Feinberg, A. P., Lee, S. C., Mason, C. E., Mignot, E., Rana, B. K., Smith, S. M., Snyder, M. P., Turek, F. W. 2019; 364 (6436): 144-+
  • A longitudinal big data approach for precision health. Nature medicine Schüssler-Fiorenza Rose, S. M., Contrepois, K. n., Moneghetti, K. J., Zhou, W. n., Mishra, T. n., Mataraso, S. n., Dagan-Rosenfeld, O. n., Ganz, A. B., Dunn, J. n., Hornburg, D. n., Rego, S. n., Perelman, D. n., Ahadi, S. n., Sailani, M. R., Zhou, Y. n., Leopold, S. R., Chen, J. n., Ashland, M. n., Christle, J. W., Avina, M. n., Limcaoco, P. n., Ruiz, C. n., Tan, M. n., Butte, A. J., Weinstock, G. M., Slavich, G. M., Sodergren, E. n., McLaughlin, T. L., Haddad, F. n., Snyder, M. P. 2019; 25 (5): 792–804

    Abstract

    Precision health relies on the ability to assess disease risk at an individual level, detect early preclinical conditions and initiate preventive strategies. Recent technological advances in omics and wearable monitoring enable deep molecular and physiological profiling and may provide important tools for precision health. We explored the ability of deep longitudinal profiling to make health-related discoveries, identify clinically relevant molecular pathways and affect behavior in a prospective longitudinal cohort (n = 109) enriched for risk of type 2 diabetes mellitus. The cohort underwent integrative personalized omics profiling from samples collected quarterly for up to 8 years (median, 2.8 years) using clinical measures and emerging technologies including genome, immunome, transcriptome, proteome, metabolome, microbiome and wearable monitoring. We discovered more than 67 clinically actionable health discoveries and identified multiple molecular pathways associated with metabolic, cardiovascular and oncologic pathophysiology. We developed prediction models for insulin resistance by using omics measurements, illustrating their potential to replace burdensome tests. Finally, study participation led the majority of participants to implement diet and exercise changes. Altogether, we conclude that deep longitudinal profiling can lead to actionable health discoveries and provide relevant information for precision health.

    View details for PubMedID 31068711

  • The NASA Twins Study: A multidimensional analysis of a year-long human spaceflight. Science (New York, N.Y.) Garrett-Bakelman, F. E., Darshi, M. n., Green, S. J., Gur, R. C., Lin, L. n., Macias, B. R., McKenna, M. J., Meydan, C. n., Mishra, T. n., Nasrini, J. n., Piening, B. D., Rizzardi, L. F., Sharma, K. n., Siamwala, J. H., Taylor, L. n., Vitaterna, M. H., Afkarian, M. n., Afshinnekoo, E. n., Ahadi, S. n., Ambati, A. n., Arya, M. n., Bezdan, D. n., Callahan, C. M., Chen, S. n., Choi, A. M., Chlipala, G. E., Contrepois, K. n., Covington, M. n., Crucian, B. E., De Vivo, I. n., Dinges, D. F., Ebert, D. J., Feinberg, J. I., Gandara, J. A., George, K. A., Goutsias, J. n., Grills, G. S., Hargens, A. R., Heer, M. n., Hillary, R. P., Hoofnagle, A. N., Hook, V. Y., Jenkinson, G. n., Jiang, P. n., Keshavarzian, A. n., Laurie, S. S., Lee-McMullen, B. n., Lumpkins, S. B., MacKay, M. n., Maienschein-Cline, M. G., Melnick, A. M., Moore, T. M., Nakahira, K. n., Patel, H. H., Pietrzyk, R. n., Rao, V. n., Saito, R. n., Salins, D. N., Schilling, J. M., Sears, D. D., Sheridan, C. K., Stenger, M. B., Tryggvadottir, R. n., Urban, A. E., Vaisar, T. n., Van Espen, B. n., Zhang, J. n., Ziegler, M. G., Zwart, S. R., Charles, J. B., Kundrot, C. E., Scott, G. B., Bailey, S. M., Basner, M. n., Feinberg, A. P., Lee, S. M., Mason, C. E., Mignot, E. n., Rana, B. K., Smith, S. M., Snyder, M. P., Turek, F. W. 2019; 364 (6436)

    Abstract

    To understand the health impact of long-duration spaceflight, one identical twin astronaut was monitored before, during, and after a 1-year mission onboard the International Space Station; his twin served as a genetically matched ground control. Longitudinal assessments identified spaceflight-specific changes, including decreased body mass, telomere elongation, genome instability, carotid artery distension and increased intima-media thickness, altered ocular structure, transcriptional and metabolic changes, DNA methylation changes in immune and oxidative stress-related pathways, gastrointestinal microbiota alterations, and some cognitive decline postflight. Although average telomere length, global gene expression, and microbiome changes returned to near preflight levels within 6 months after return to Earth, increased numbers of short telomeres were observed and expression of some genes was still disrupted. These multiomic, molecular, physiological, and behavioral datasets provide a valuable roadmap of the putative health risks for future human spaceflight.

    View details for PubMedID 30975860

  • Distinct transcriptomic and exomic abnormalities within myelodysplastic syndrome marrow cells. Leukemia & lymphoma Im, H., Rao, V., Sridhar, K., Bentley, J., Mishra, T., Chen, R., Hall, J., Graber, A., Zhang, Y., Li, X., Mias, G. I., Snyder, M. P., Greenberg, P. L. 2018: 1-11

    Abstract

    To provide biologic insights into mechanisms underlying myelodysplastic syndromes (MDS) we evaluated the CD34+ marrow cells transcriptome using high-throughput RNA sequencing (RNA-Seq). We demonstrated significant differential gene expression profiles (GEPs) between MDS and normal and identified 41 disease classifier genes. Additionally, two main clusters of GEPs distinguished patients based on their major clinical features, particularly between those whose disease remained stable versus patients who transformed into acute myeloid leukemia within 12 months. The genes whose expression was associated with disease outcome were involved in functional pathways and biologic processes highly relevant for MDS. Combined with exomic analysis we identified differential isoform usage of genes in MDS mutational subgroups, with consequent dysregulation of distinct biologic functions. This combination of clinical, transcriptomic and exomic findings provides valuable understanding of mechanisms underlying MDS and its progression to a more aggressive stage and also facilitates prognostic characterization of MDS patients.

    View details for DOI 10.1080/10428194.2018.1452210

    View details for PubMedID 29616851

  • Integrative Personal Omics Profiles during Periods of Weight Gain and Loss. Cell systems Piening, B. D., Zhou, W. n., Contrepois, K. n., Röst, H. n., Gu Urban, G. J., Mishra, T. n., Hanson, B. M., Bautista, E. J., Leopold, S. n., Yeh, C. Y., Spakowicz, D. n., Banerjee, I. n., Chen, C. n., Kukurba, K. n., Perelman, D. n., Craig, C. n., Colbert, E. n., Salins, D. n., Rego, S. n., Lee, S. n., Zhang, C. n., Wheeler, J. n., Sailani, M. R., Liang, L. n., Abbott, C. n., Gerstein, M. n., Mardinoglu, A. n., Smith, U. n., Rubin, D. L., Pitteri, S. n., Sodergren, E. n., McLaughlin, T. L., Weinstock, G. M., Snyder, M. P. 2018

    Abstract

    Advances in omics technologies now allow an unprecedented level of phenotyping for human diseases, including obesity, in which individual responses to excess weight are heterogeneous and unpredictable. To aid the development of better understanding of these phenotypes, we performed a controlled longitudinal weight perturbation study combining multiple omics strategies (genomics, transcriptomics, multiple proteomics assays, metabolomics, and microbiomics) during periods of weight gain and loss in humans. Results demonstrated that: (1) weight gain is associated with the activation of strong inflammatory and hypertrophic cardiomyopathy signatures in blood; (2) although weight loss reverses some changes, a number of signatures persist, indicative of long-term physiologic changes; (3) we observed omics signatures associated with insulin resistance that may serve as novel diagnostics; (4) specific biomolecules were highly individualized and stable in response to perturbations, potentially representing stable personalized markers. Most data are available open access and serve as a valuable resource for the community.

    View details for PubMedID 29361466

  • Distinct Transcriptomic and Exomic Abnormalities Within Myelodysplastic Syndrome Marrow Cells Leukemia & Lymphoma Im, H., Rao, V., Sridhar, K., Bentley, J., Mishra, T., Chen, R., Hall, J., Graber, A., Zhang, Y., Xiao, L., Mias, G., Snyder, M. P., Greenberg, P. L. 2018: 1-11
  • A comparative encyclopedia of DNA elements in the mouse genome NATURE Yue, F., Cheng, Y., Breschi, A., Vierstra, J., Wu, W., Ryba, T., Sandstrom, R., Ma, Z., Davis, C., Pope, B. D., Shen, Y., Pervouchine, D. D., Djebali, S., Thurman, R. E., Kaul, R., Rynes, E., Kirilusha, A., Marinov, G. K., Williams, B. A., Trout, D., Amrhein, H., Fisher-Aylor, K., Antoshechkin, I., DeSalvo, G., See, L., Fastuca, M., Drenkow, J., Zaleski, C., Dobin, A., Prieto, P., Lagarde, J., Bussotti, G., Tanzer, A., Denas, O., Li, K., Bender, M. A., Zhang, M., Byron, R., Groudine, M. T., McCleary, D., Pham, L., Ye, Z., Kuan, S., Edsall, L., Wu, Y., Rasmussen, M. D., Bansal, M. S., Kellis, M., Keller, C. A., Morrissey, C. S., Mishra, T., Jain, D., Dogan, N., Harris, R. S., Cayting, P., Kawli, T., Boyle, A. P., Euskirchen, G., Kundaje, A., Lin, S., Lin, Y., Jansen, C., Malladi, V. S., Cline, M. S., Erickson, D. T., Kirkup, V. M., Learned, K., Sloan, C. A., Rosenbloom, K. R., De Sousa, B. L., Beal, K., Pignatelli, M., Flicek, P., Lian, J., Kahveci, T., Lee, D., Kent, W. J., Santos, M. R., Herrero, J., Notredame, C., Johnson, A., Vong, S., Lee, K., Bates, D., Neri, F., Diegel, M., Canfield, T., Sabo, P. J., Wilken, M. S., Reh, T. A., Giste, E., Shafer, A., Kutyavin, T., Haugen, E., Dunn, D., Reynolds, A. P., Neph, S., Humbert, R., Hansen, R. S., de Bruijn, M., Selleri, L., Rudensky, A., Josefowicz, S., Samstein, R., Eichler, E. E., Orkin, S. H., Levasseur, D., Papayannopoulou, T., Chang, K., Skoultchi, A., Gosh, S., Disteche, C., Treuting, P., Wang, Y., Weiss, M. J., Blobel, G. A., Cao, X., Zhong, S., Wang, T., Good, P. J., Lowdon, R. F., Adams, L. B., Zhou, X., Pazin, M. J., Feingold, E. A., Wold, B., Taylor, J., Mortazavi, A., Weissman, S. M., Stamatoyannopoulos, J. A., Snyder, M. P., Guigo, R., Gingeras, T. R., Gilbert, D. M., Hardison, R. C., Beer, M. A., Ren, B. 2014; 515 (7527): 355-?

    Abstract

    The laboratory mouse shares the majority of its protein-coding genes with humans, making it the premier model organism in biomedical research, yet the two mammals differ in significant ways. To gain greater insights into both shared and species-specific transcriptional and cellular regulatory programs in the mouse, the Mouse ENCODE Consortium has mapped transcription, DNase I hypersensitivity, transcription factor binding, chromatin modifications and replication domains throughout the mouse genome in diverse cell and tissue types. By comparing with the human genome, we not only confirm substantial conservation in the newly annotated potential functional sequences, but also find a large degree of divergence of sequences involved in transcriptional regulation, chromatin state and higher order chromatin organization. Our results illuminate the wide range of evolutionary forces acting on genes and their regulatory regions, and provide a general resource for research into mammalian biology and mechanisms of human diseases.

    View details for DOI 10.1038/nature13992

    View details for Web of Science ID 000345770600034

  • A comparative encyclopedia of DNA elements in the mouse genome. Nature Yue, F., Cheng, Y., Breschi, A., Vierstra, J., Wu, W., Ryba, T., Sandstrom, R., Ma, Z., Davis, C., Pope, B. D., Shen, Y., Pervouchine, D. D., Djebali, S., Thurman, R. E., Kaul, R., Rynes, E., Kirilusha, A., Marinov, G. K., Williams, B. A., Trout, D., Amrhein, H., Fisher-Aylor, K., Antoshechkin, I., DeSalvo, G., See, L., Fastuca, M., Drenkow, J., Zaleski, C., Dobin, A., Prieto, P., Lagarde, J., Bussotti, G., Tanzer, A., Denas, O., Li, K., Bender, M. A., Zhang, M., Byron, R., Groudine, M. T., McCleary, D., Pham, L., Ye, Z., Kuan, S., Edsall, L., Wu, Y., Rasmussen, M. D., Bansal, M. S., Kellis, M., Keller, C. A., Morrissey, C. S., Mishra, T., Jain, D., Dogan, N., Harris, R. S., Cayting, P., Kawli, T., Boyle, A. P., Euskirchen, G., Kundaje, A., Lin, S., Lin, Y., Jansen, C., Malladi, V. S., Cline, M. S., Erickson, D. T., Kirkup, V. M., Learned, K., Sloan, C. A., Rosenbloom, K. R., Lacerda de Sousa, B., Beal, K., Pignatelli, M., Flicek, P., Lian, J., Kahveci, T., Lee, D., Kent, W. J., Ramalho Santos, M., Herrero, J., Notredame, C., Johnson, A., Vong, S., Lee, K., Bates, D., Neri, F., Diegel, M., Canfield, T., Sabo, P. J., Wilken, M. S., Reh, T. A., Giste, E., Shafer, A., Kutyavin, T., Haugen, E., Dunn, D., Reynolds, A. P., Neph, S., Humbert, R., Hansen, R. S., de Bruijn, M., Selleri, L., Rudensky, A., Josefowicz, S., Samstein, R., Eichler, E. E., Orkin, S. H., Levasseur, D., Papayannopoulou, T., Chang, K., Skoultchi, A., Gosh, S., Disteche, C., Treuting, P., Wang, Y., Weiss, M. J., Blobel, G. A., Cao, X., Zhong, S., Wang, T., Good, P. J., Lowdon, R. F., Adams, L. B., Zhou, X., Pazin, M. J., Feingold, E. A., Wold, B., Taylor, J., Mortazavi, A., Weissman, S. M., Stamatoyannopoulos, J. A., Snyder, M. P., Guigo, R., Gingeras, T. R., Gilbert, D. M., Hardison, R. C., Beer, M. A., Ren, B. 2014; 515 (7527): 355-364

    Abstract

    The laboratory mouse shares the majority of its protein-coding genes with humans, making it the premier model organism in biomedical research, yet the two mammals differ in significant ways. To gain greater insights into both shared and species-specific transcriptional and cellular regulatory programs in the mouse, the Mouse ENCODE Consortium has mapped transcription, DNase I hypersensitivity, transcription factor binding, chromatin modifications and replication domains throughout the mouse genome in diverse cell and tissue types. By comparing with the human genome, we not only confirm substantial conservation in the newly annotated potential functional sequences, but also find a large degree of divergence of sequences involved in transcriptional regulation, chromatin state and higher order chromatin organization. Our results illuminate the wide range of evolutionary forces acting on genes and their regulatory regions, and provide a general resource for research into mammalian biology and mechanisms of human diseases.

    View details for DOI 10.1038/nature13992

    View details for PubMedID 25409824

  • An encyclopedia of mouse DNA elements (Mouse ENCODE) GENOME BIOLOGY Stamatoyannopoulos, J. A., Snyder, M., Hardison, R., Ren, B., Gingeras, T., Gilbert, D. M., Groudine, M., Bender, M., Kaul, R., Canfield, T., Giste, E., Johnson, A., Zhang, M., Balasundaram, G., Byron, R., Roach, V., Sabo, P. J., Sandstrom, R., Stehling, A. S., Thurman, R. E., Weissman, S. M., Cayting, P., Hariharan, M., Lian, J., Cheng, Y., Landt, S. G., Ma, Z., Wold, B. J., Dekker, J., Crawford, G. E., Keller, C. A., Wu, W., Morrissey, C., Kumar, S. A., Mishra, T., Jain, D., Byrska-Bishop, M., Blankenberg, D., Lajoie, B. R., Jain, G., Sanyal, A., Chen, K., Denas, O., Taylor, J., Blobel, G. A., Weiss, M. J., Pimkin, M., Deng, W., Marinov, G. K., Williams, B. A., Fisher-Aylor, K. I., DeSalvo, G., Kiralusha, A., Trout, D., Amrhein, H., Mortazavi, A., Edsall, L., McCleary, D., Kuan, S., Shen, Y., Yue, F., Ye, Z., Davis, C. A., Zaleski, C., Jha, S., Xue, C., Dobin, A., Lin, W., Fastuca, M., Wang, H., Guigo, R., Djebali, S., Lagarde, J., Ryba, T., Sasaki, T., Malladi, V. S., Cline, M. S., Kirkup, V. M., Learned, K., Rosenbloom, K. R., Kent, W. J., Feingold, E. A., Good, P. J., Pazin, M., Lowdon, R. F., Adams, L. B. 2012; 13 (8)