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RESEARCH ARTICLE
◥
HUMAN PHYSIOLOGY
The NASA Twins Study:
A multidimensional analysis of a
year-long human spaceflight
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 intimamedia 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.
H
undreds of humans have flown in space
since 1961, providing insight into the effects of environmental factors—including
weightlessness, unloading, and radiation
exposure—on the physiological responses
of the human body and their functional consequences. Human physiological adaptation to
short-duration (4 months) spaceflight have been described,
particularly for the cardiovascular, musculoskeletal, and sensorimotor systems (1). Some
changes, such as headward fluid shift, are rapid
and reach a new steady state relatively quickly
(within days). By contrast, the nature of change
in cardiovascular and muscular traits during
longer missions is more pronounced, and their
rate of return to baseline after spaceflight is
prolonged (2). The headward fluid shift occurs
immediately upon entry into weightlessness (3),
resulting in a decrease in plasma and blood volume during the first few days of a mission (4)
that plateaus in the first 2 weeks of flight. However, the decrease in plasma volume and red
blood cells is not significantly different for shortor long-duration missions (5). Conversely, cardiovascular adaptations (e.g., left ventricular mass
increase) and resulting downstream outcomes
(e.g., orthostatic tolerance and maximal oxygen
consumption losses) become more pronounced
with longer-duration missions (5–8). Similarly,
loss of muscle mass and strength are greater
after longer-duration spaceflight (9–11). The
Garrett-Bakelman et al., Science 364, eaau8650 (2019)
12 April 2019
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Downloaded from http://science.sciencemag.org/ on April 27, 2019
Francine E. Garrett-Bakelman1,2*, Manjula Darshi3*, Stefan J. Green4*,
Ruben C. Gur5*, Ling Lin6*, Brandon R. Macias7*, Miles J. McKenna8*,
Cem Meydan1,9*, Tejaswini Mishra6*, Jad Nasrini5*, Brian D. Piening6*†,
Lindsay F. Rizzardi10*‡, Kumar Sharma3*, Jamila H. Siamwala11*§, Lynn Taylor8*,
Martha Hotz Vitaterna12*, Maryam Afkarian13, Ebrahim Afshinnekoo1,9, Sara Ahadi6,
Aditya Ambati6, Maneesh Arya7, Daniela Bezdan1,9, Colin M. Callahan10, Songjie Chen6,
Augustine M. K. Choi1, George E. Chlipala4, Kévin Contrepois6, Marisa Covington14,
Brian E. Crucian14, Immaculata De Vivo15, David F. Dinges5, Douglas J. Ebert7,
Jason I. Feinberg10, Jorge A. Gandara1, Kerry A. George7, John Goutsias10,
George S. Grills1¶, Alan R. Hargens11, Martina Heer16#, Ryan P. Hillary6,
Andrew N. Hoofnagle17, Vivian Y. H. Hook11, Garrett Jenkinson10**, Peng Jiang12,
Ali Keshavarzian18, Steven S. Laurie7, Brittany Lee-McMullen6, Sarah B. Lumpkins19,
Matthew MacKay1, Mark G. Maienschein-Cline4, Ari M. Melnick1, Tyler M. Moore5,
Kiichi Nakahira1††, Hemal H. Patel11, Robert Pietrzyk7, Varsha Rao6, Rintaro Saito11‡‡,
Denis N. Salins6, Jan M. Schilling11, Dorothy D. Sears11, Caroline K. Sheridan1,
Michael B. Stenger14, Rakel Tryggvadottir10, Alexander E. Urban6, Tomas Vaisar17,
Benjamin Van Espen11, Jing Zhang6, Michael G. Ziegler11, Sara R. Zwart20,
John B. Charles14§§, Craig E. Kundrot21§§, Graham B. I. Scott22§§, Susan M. Bailey8§§,
Mathias Basner5§§, Andrew P. Feinberg10§§, Stuart M. C. Lee7§§,
Christopher E. Mason1,9,23,24§§, Emmanuel Mignot6§§, Brinda K. Rana11§§,
Scott M. Smith14§§, Michael P. Snyder6§§, Fred W. Turek12§§
adverse effects of these adaptations are especially
clear upon return to Earth. Regular vigorous exercise, combined with adequate nutrition during
spaceflight, mitigate some of the spaceflightinduced muscle (9, 12) and bone loss (13) that
occur during both short- and long-duration
missions. However, recent evidence suggests
that long-duration missions on the International
Space Station (ISS) have resulted in some astronauts developing ocular changes, including optic
disc edema and choroidal folds (14, 15), termed
spaceflight-associated neuro-ocular syndrome
(SANS) (16). The incidence and severity of ocular
symptoms varies, and the exact mechanism for
the development of SANS is not well understood,
which has limited NASA’s ability to develop an
effective countermeasure.
Although our understanding of the physiological and functional consequences of 4- to
6-month missions has increased greatly over
the 18 years of continuous human presence on
the ISS, there is almost no experience with
spaceflight length greater than 6 months. Future
missions, however, could be as long as 3 years,
including transit to and from Mars and possible
exploration of the planet, yet only four individuals have participated in spaceflight missions
lasting 1 year or more. Moreover, investigations
have not consistently implemented an integrated,
cross-discipline study design or utilized multiomic
approaches to biospecimen analyses. Thus, we
have limited knowledge of the full range of the
interactions of molecular, physiological, and cognitive dynamics that occur during long-duration
spaceflight. Given the increasing number of
vehicles providing access to spaceflight (17) and
proposed missions to Mars, studies are needed
to better understand the impact of prolonged
spaceflight on human biology and health. Genetic, immune system, and metabolic functions
are of particular concern given exposure to space
radiations, restricted diet, reduced physical work
requirements, disrupted circadian rhythms, and
weightlessness. Importantly, longitudinal measures of biomarkers (such as genomic, epigenomic,
biochemical, and physiological alterations) can
provide critical metrics for astronaut health that
could aid in assessment of increased risks and
guide potential personalized interventions.
The NASA Twins Study investigators leveraged the opportunity to study identical twin
astronauts, one in space and one on Earth. Data
were generated from specimens collected and
test protocols administered over 25 months,
spanning time points before (preflight), during
(inflight), and after (postflight) spaceflight with
an integrated sampling scheme (Fig. 1A), including a wide variety of biological samples as
well as cognitive and physiological measures
(Fig. 1A and table S1). Our study also provides
an example of inflight data and sample collection strategies used to generate a comprehensive, longitudinal, molecular, physiological, and
cognitive profile, providing a scientific framework and baseline data for future studies. It is
important to note that with a single test subject in the spaceflight environment for this
R ES E A RC H | R E S EA R C H A R T I C LE
particular set of measures, it is impossible to
attribute causality to spaceflight versus a coincidental event. Therefore, our study should
be considered as hypothesis-generating and
framework-defining and must be complemented in the future by studies of additional
astronauts.
Results
Extensive multisystem changes occur
in spaceflight
Data were generated from fresh (FR) and ambient return (AR) whole blood or PBMCs that
were either directly processed and fractionated
into subpopulations (T cells: CD4 and CD8;
B cells: CD19; and lymphocyte depleted: LD)
(fig. S1) or processed directly from frozen PBMCs.
For fractionated subpopulations, the inflight collections were confounded by ambient return
(AR specimens were collected on the ISS and
returned to Earth via Soyuz capsule at room
temperature). To simulate this effect, independent samples were generated to mimic FR and
AR sample collection conditions and used for
correction. Unsupervised analysis of gene expression profiles segregated TW’s inflight from
preflight and postflight samples, as well as from
volved in the tricarboxylic acid (TCA) cycle, glycolysis, and amino acid, fatty acid, ketone body,
and pyrimidine metabolism. Of the 81 targeted
metabolites, 60 and 66 metabolites were detected in plasma and urine, respectively (table
S3). No significant changes were observed in
plasma metabolites, but 32 urinary metabolites
were significantly altered inflight for TW [FDR:
P < 0.05, analysis of variance (ANOVA)]. To assess the epigenetic contribution to the changes observed, whole-genome bisulfite sequencing (WGBS) was performed on a subset of CD4 and CD8 samples from each subject. Global DNA methylation changes in TW were within the range of variation seen in HR throughout the study. However, ontology analysis of genes ranked on the basis of epigenetic discordance, as quantified by average promoter Jensen-Shannon distance (JSD) between samples, revealed distinct pathways enriched in TW when comparing preflight with inflight samples (Fig. 1D and tables S4 and S5). For example, in CD8 cells, enrichment in regulation of neutrophil activation or granulation was observed in TW [q < 0.01, hypergeometric test (HGT)], but not in HR (Fig. 1D). Similarly, in CD4 cells, enrichment in platelet aggregation (q = 0.0002, HGT) was observed only in TW. To identify complex changes spanning diverse analyte classes that occur over time, the different data types were combined and scaled, and c-means clustering analysis was performed. Although this analysis (Fig. 1E) revealed that physiological levels for a large number of analytes were unaffected by spaceflight (Fig. 1E; clusters 1 and 2), several notable patterns were identified. These included a cluster of features, including cognitive performance, that for TW increased inflight and declined sharply upon return before reaching baseline (Fig. 1E, cluster 3; and Fig. 1F); this cluster was enriched for analytes involved in central carbon metabolism [q < 0.0002; integrated molecular pathway level analysis (IMPaLA) combined pathway analysis, Fisher’s method]. Integrating gene expression changes with the other analytes revealed additional complex biochemical trajectories; for example, gene expression changes associated with neutrophil regulation were enriched (q < 1 × 10−12; IMPaLA combined pathway analysis, Fisher’s method) in cluster 25 (fig. S5), illustrating an increase very early inflight followed by a steady decline, until increasing again postflight. 1 Weill Cornell Medicine, New York, NY, USA. 2University of Virginia School of Medicine, Charlottesville, VA, USA. 3Center for Renal Precision Medicine, University of Texas Health, San Antonio, TX, USA. 4University of Illinois at Chicago, Chicago, IL, USA. 5University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA. 6Stanford University School of Medicine, Palo Alto, CA, USA. 7KBRwyle, Houston, TX, USA. 8Colorado State University, Fort Collins, CO, USA. 9The Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, New York, NY, USA. 10Johns Hopkins University, Baltimore, MD, USA. 11University of California, San Diego, La Jolla, CA, USA. 12Northwestern University, Evanston, IL, USA. 13University of California, Davis, Davis, CA, USA. 14 National Aeronautics and Space Administration (NASA), Houston, TX, USA. 15Harvard T.H. Chan School of Public Health, Boston, MA, USA. 16University of Bonn, Bonn, Germany. 17University of Washington, Seattle, WA, USA. 18Rush University Medical Center, Chicago, IL, USA. 19MEI Technologies, Houston, TX, USA. 20University of Texas Medical Branch, Galveston, TX, USA. 21Space Life and Physical Sciences Division, NASA Headquarters, Washington, DC, USA. 22National Space Biomedical Research Institute, Baylor College of Medicine, Houston, TX, USA. 23The Feil Family Brain and Mind Research Institute, New York, NY, USA. 24The WorldQuant Initiative for Quantitative Prediction, New York, NY, USA. *These authors contributed equally to this work. †Present address: Providence Portland Medical Center, Portland, OR, USA. ‡Present address: HudsonAlpha Institute for Biotechnology, Huntsville, AL, USA. §Present address: Brown University, Providence, RI, USA. ¶Present address: Augusta University, Augusta, GA, USA. #Present address: IUBH International University of Applied Sciences, Bad Reichenhall, Germany. **Present address: Mayo Clinic, Rochester, MN, USA. ††Present address: Nara Medical University, Nara, Japan. ‡‡Present address: Institute for Advanced Biosciences, Keio University, Tokyo, Japan. §§Corresponding author. Email: jbcharle@gmail.com (J.B.C); craig.e.kundrot@nasa.gov (C.E.K.); graham_b_scott@yahoo.com (G.B.I.S.); susan.bailey@colostate.edu (S.M.B.); basner@pennmedicine.upenn.edu (M.B.); afeinberg@jhu.edu (A.P.F.); stuart.lee-1@nasa.gov (S.M.C.L.); chm2042@med.cornell.edu (C.E.M.); mignot@stanford.edu (E.M.); bkrana@ucsd.edu (B.K.R.); scott.m.smith@nasa.gov (S.M.S.); mpsnyder@stanford.edu (M.P.S.); fturek@northwestern.edu (F.W.T.) Garrett-Bakelman et al., Science 364, eaau8650 (2019) 12 April 2019 2 of 20 Downloaded from http://science.sciencemag.org/ on April 27, 2019 A pair of male monozygotic twins were studied, one of whom spent 340 days aboard the ISS (flight subject; TW), while his identical twin remained on Earth (ground subject; HR). The subjects were 50 years of age at the time of study initiation and had accumulated different amounts of prior spaceflight exposure (Table 1). TW had, over the course of 12 years, a total of 180 days in space before the 1-year mission; there was a 4-year gap from the end of the previous longduration mission until the start of this study. By contrast, HR had a total of 54 days in space and, at the time of this study, had not flown in space for almost 4 years. Collected samples (n = 317) from both subjects throughout the duration of the study included stool, urine, and whole blood, which was also separated into peripheral blood mononuclear cells (PBMCs), sorted immune cells, and plasma. These samples were assayed for epigenomic, metabolomic, transcriptomic, proteomic, molecular, and microbiome changes (Fig. 1A and table S1). Additionally, subjects participated in physiological and cognitive tests in the laboratory during preflight and postflight ground-based testing and onboard the ISS (inflight). HR specimens, for all cell populations examined (fig. S2, A to E). Similar expression changes were observed for all cell types assessed (Fig. 1B). Differentially expressed genes (DEGs, DESeq2 multivariate negative binomial model, q < 0.01) were identified across all samples and cell types (n = 9317) with HR as the control and a particular focus on the differences that persisted postflight. In the LD cell population, of the 481 DEGs found inflight, compared with preflight, there were 112 (23.2%) that remained differentially expressed postflight (Fig. 1B and table S2). Across all sorted cell types, only 811 of the inflight DEGs remained disrupted postflight. Concomitant with an overall shift in mitochondrial RNA (mtRNA) levels (see below), far more DEGs (n = 8564, DESeq2 multivariate negative binomial model, q < 0.01) were observed in the 6- to 12-month inflight period compared with HR than in the 0- to 6-month inflight period (n = 1447) in PBMCs. This large (6×) shift in overall gene regulation upon exposure in TW to a year-long spaceflight suggests that overall gene regulation may be more affected by longer-duration spaceflight. To assess physiological and immune signaling changes, the metabolome, proteome, and cytokine complement were measured using mass spectrometry and antibody-based methods. Targeted and untargeted metabolomics and proteomics were performed on plasma and urine samples, whereas cytokine profiling was performed only on plasma samples (fig. S3 and table S1). Untargeted analysis was focused on a high-confidence set of 719 metabolites (out of 4162 metabolic features) identified in plasma using a broadspectrum liquid chromatography–mass spectrometry (LC-MS) metabolomics platform (18). Linear models demonstrate significant differences [false discovery rate (FDR) < 0.05] in the abundance of 245 metabolites among pre-, in-, and postflight samples between TW and HR, including those specific to the earlier or later halves of the flight period as well as those associated with time spent on the ISS (Fig. 1C and table S3). Additionally, 39 metabolites were significantly different (FDR < 0.05) between TW and HR at baseline (table S3). Metabolites indicative of genotoxic stress, inflammation, and altered amino acid metabolism were increased in TW inflight (table S3). Targeted metabolomic analysis using gas chromatography–tandem mass spectrometry (GC-MS/MS) was performed in plasma and urine to quantify metabolites in- R ES E A RC H | R E S EA R C H A R T I C LE Downloaded from http://science.sciencemag.org/ on April 27, 2019 Garrett-Bakelman et al., Science 364, eaau8650 (2019) 12 April 2019 3 of 20 R ES E A RC H | R E S EA R C H A R T I C LE Fig. 1. Study design and human spaceflight metrics. The flight subject (TW, blue) and his identical twin (HR, green) were each studied over 25 months using a comprehensive set of health and biological metrics. (A) Earth-based and spaceflight collections include blood, sorted cells (CD4, CD8, CD19, and LD), stool, buccal, saliva, urine, and AR blood. TCR, T cell receptor sequencing; T- and U-Metabolomics, targeted and untargeted metabolomics; OSI, oxidative stress and inflammation; T- and U-Proteomics, targeted and untargeted proteomics; CVU, cardiac and vascular ultrasound; VSF, vascular structure and function. (B) Gene expression changes in TW inflight and postflight compared with the preflight period. All time points of HR were used to account for normal levels of variance and noise in gene expression. Genes that were significantly altered inflight after controlling for subject baselines and AR effect are reported. Gene expression changes were reported for any gene with q < 0.05 in a multivariate model that utilized expression values for polyadenylated [poly (A)+] and ribosomal RNA depleted transcripts. (C) Metabolites present at significantly different levels in HR and TW or between pre-, in-, and postflight periods. Heatmap represents median-normalized log2 intensity for each analyte, scaled across all samples. Red color indicates relative enrichment, whereas blue indicates relative depletion. (D) GO analysis of genes ranked on the basis of epigenetic discordance at their promoters. Comparisons of preflight samples to inflight (early and late, and combined early and late) and postflight samples are shown for both CD4 and CD8 cells. Heatmaps represent transformed enrichment values [square root (sqrt) of enrichment] for GO categories with a raw enrichment value >5. Reg., regulation; neg. reg., negative
regulation. (E) C-means clustering of multiomics data reveals longitudinal
patterns associated with spaceflight. Analyte abundance (scaled) plotted over
time for the identified clusters from the integrated metabolome, proteome,
cytokine, cognition, and microbiome datasets is shown. Median abundance
(bold) per cluster and 5th and 95th percentiles of abundance (shaded)
are indicated. The gray shaded region indicates the inflight period.
n, number of analytes in cluster. (F) Individual plots of the different analyte
types that compose the spaceflight-dependent cluster, cluster 3, from (E).
Telomere levels are plotted adjacent to the cluster members for reference.
Median abundance (bold) per cluster and 5th and 95th percentiles of
abundance (shaded) are indicated. Thin lines show annotated examples of
analytes from cluster 3. For Cognition, accuracy [MP(Acc)] and speed
[MP(Spd)] on the motor praxis task as well as standardized speed across
cognitive domains (speed) are shown. n, number of analytes in cluster;
CAG, coabundance gene groups.
telomere length distributions that confirmed
HR’s relatively stable telomere lengths throughout
the study (Fig. 2C and fig. S6D). Consistent with
TW’s increased average telomere length during
spaceflight, temporal shifts toward increased
numbers of longer telomeres and concurrent
decreases in the numbers of shorter telomeres
were also observed (fig. S6D); for example, there
was a significant shift in TW’s inflight (FD259)
telomere length distribution as compared to his
preflight (L−162; L− days before launch) distribution (P < 2.2 × 10−16; Mann-Whitney U test) (Fig. 2D). After returning to Earth (R+190), TW’s telomere length distribution shifted back toward increased numbers of shorter telomeres, more closely resembling his preflight distribution. However, an increased number of signal-free chromosome ends, indicative of complete loss and/or critically short telomeres (i.e., below our level of resolution), was also apparent (Fig. 2D). Spaceflight-specific shifts in telomere length dynamics were also supported by gene expression results, in that when inflight, TW’s down-regulated DEGs were significantly enriched in packagingof–telomere ends and telomere-maintenance pathways, in both CD4 and CD8 cells [gene set enrichment analysis (GSEA), all q ≤ 0.001] (table S2). Similarly, changes in DNA methylation of the gene promoter for TERT, which encodes the regulatory subunit of telomerase, were observed when comparing preflight with the late inflight time point in both CD4 and CD8 T cells (JSD rank 248 and 32, respectively); by contrast, for HR, TERT was not highly ranked (428 or greater) (table S5). Telomerase is the reverse transcriptase capable of de novo addition of species-specific telomeric repeats onto the ends of newly replicated chromosomes (25). Telomerase activity was evaluated pre-, in-, and postflight (PBMCs, ambient) with the qRT-PCR telomeric repeat amplification protocol (TRAP) (24, 26). In general, TW had lower levels of telomerase activity than HR throughout the study, whereas levels for the two individuals Garrett-Bakelman et al., Science 364, eaau8650 (2019) 12 April 2019 were similar preflight and postflight (fig. S6E). Unfortunately, telomerase activity was lost in all inflight samples collected onboard the ISS. Given the sensitivity of enzymatic activity to sample handling conditions, we speculated that unavoidable transit time and/or temperatures associated with ambient return (via Soyuz) destroyed telomerase activity. To test this hypothesis, we compared ground control samples that had been in transit ≤24 hours with those that had been in transit ≥48 hours, mimicking the transit time from the ISS to Johnson Space Center. Loss of telomerase activity was observed in all blood samples experiencing transit times ≥48 hours (P = 0.002; Student’s t test); however, telomere length and DNA integrity were unaffected (fig. S6, F to H). DNA damage responses during spaceflight Chromosome aberrations were analyzed in the same samples as above to evaluate potential telomere-related instability (e.g., fusions) as well as to assess DDRs to ionizing radiation (IR) exposure during spaceflight (27), specifically galactic cosmic ray (GCR)–induced cytogenetic damage, as has been done previously in blood lymphocytes of astronauts (28). Here, high-resolution directional genomic hybridization (dGH) paints (29) for chromosomes 1, 2, and 3 were used to enable simultaneous detection of interchromosomal translocations and intrachromosomal inversions (Fig. 2E). Baseline frequencies of these structural variants were similar for the two subjects, with inversions being more frequent than translocations (Fig. 2F). TW’s inversion frequencies increased at a greater rate than translocations, consistent with inflight IR exposure, particularly to high linear energy transfer (LET) space radiation (30, 31). Indeed, a physical dosimeter dose of 76.18 milligrays and an effective dose of 146.34 millisieverts were recorded by NASA. Also consistent with IR exposure, genes whose expression was 4 of 20 Downloaded from http://science.sciencemag.org/ on April 27, 2019 Telomeres lengthened during spaceflight Telomeres are repetitive features of chromosomal termini essential for maintaining genomic integrity; they protect physical DNA ends from degradation and prevent them from triggering inappropriate DNA damage responses (DDRs). Telomere length shortens with cell division and thus with age, as well as with a variety of lifestyle factors, such as stress, and environmental exposures, including air pollution and radiation. Here, average telomere length was evaluated pre-, in-, and postflight (DNA; PBMCs) using quantitative real-time polymerase chain reaction (qRT-PCR) (19, 20). Consistent with a strong genetic component (21), HR and TW had similar telomere lengths at baseline (preflight P = 0.942; one-way ANOVA), and telomere lengths for HR remained relatively stable for the duration of the study (Fig. 2A). Most notable was a significant increase in telomere length during flight for TW (14.5%), as compared with his preflight and postflight measures as well as with those of HR (P = 0.048, 0.0003, and 0.0073, respectively; one-way ANOVA). TW’s increased telomere length was observed at all inflight time points assessed [flight day (FD) 14 to FD334; fig. S6A], as well as in sorted CD4, CD8, and LD cells, but not in CD19 cells (Fig. 2B and fig. S6B). These results are consistent with recently reported cell type–specific responses to factors that contribute to telomere length regulation (22). Notably, telomere length shortened rapidly upon TW’s return to Earth, within ~48 hours [FD340 ambient return to R+0 (R+ days post return); fig. S6B] and stabilized to near preflight averages within months. Additionally, metaphase chromosomes were prepared from pre-, in-, and postflight samples (stimulated T cells; ambient whole blood), and thousands of individual telomeres were evaluated with telomere fluorescence in situ hybridization (Telo-FISH) (23, 24), an independent measure that showed the same trends observed with qRT-PCR (fig. S6C). Importantly, Telo-FISH cell-by-cell analyses also enabled generation of R ES E A RC H | R E S EA R C H A R T I C LE altered inflight were significantly enriched in pathways related to DNA damage responses in LD, CD4, CD8, and PBMCs [generalized linear model (GLM), all q ≤ 0.002; table S2]. Furthermore, TW’s inversion frequencies continued to rise postflight, indicative of instability and possibly reflective of IR-induced DNA damage to stem cell compartments. Although TW’s translocation frequencies were variable, translocations were also increased inflight and postflight compared with preflight, additional evidence of inflight radiation exposure and the persistence of GCR-induced cytogenetic damage (32). DNA methylation patterning during spaceflight We also examined DNA methylation in FR and AR specimens (Fig. 1A and table S1). Genomewide DNA methylation levels were measured in CD4 and CD8 lymphocytes isolated from both subjects at four time points throughout the study: one preflight, two inflight (early and late), and one postflight. Principal components analysis (PCA) revealed a distinction in global DNA methylation between the two cell types and between subjects for the CD4 samples (Fig. 3A). Moreover, TW’s inflight samples were distinct from pre- flight and postflight samples for both cell types. Subtle differences in both genome-wide mean methylation levels (MML) and normalized methylation entropy (NME; a measure of methylation stochasticity) were detected inflight for TW, which returned to baseline postflight (Fig. 3B). Although for HR, the direction of these changes was consistent in CD4 and CD8 cells, it was reversed for TW, with a decrease in MML at FD259 for CD4 cells and an increase in CD8 cells. Although MML and NME are not necessarily predictive of one another (33), an inverse relationship between genome-wide medians of MML and Downloaded from http://science.sciencemag.org/ on April 27, 2019 Fig. 2. Telomere length dynamics and DNA damage responses. (A) Relative average telomere length in PBMCs (DNA) pre-, in-, and postflight assessed by qRT-PCR for HR (green) and TW (blue). Significance was tested by one-way ANOVA, and error bars represent SEM. (B) Relative average telomere length for TW in sorted PBMC subpopulations, CD19 B cells, CD4 and CD8 T cells, and LD fractions, pre-, in-, and postflight. Boxplot whiskers show min and max. (C and D) Telo-FISH–generated histograms of individual telomere length distributions [shorter to longer, lower to higher relative fluorescent intensity (RFI)] for HR (C) and TW (D) preflight (blue), inflight (red), and postflight (green). (E) Cytogenetic analysis of DNA damage utilizing dGH paints (pink) for chromosomes 1, 2, and 3 facilitated simultaneous detection of translocations and inversions. Representative image of dGH on a metaphase chromosome spread illustrating an intrachromosomal inversion (yellow arrow) and an interchromosomal reciprocal translocation (white arrows). (F) Quantification of translocation (striped bars) and inversion (solid bars) frequencies for HR and TW pre-, in-, and postflight. Results were not statistically significant (one-way ANOVA). Error bars represent SEM. Garrett-Bakelman et al., Science 364, eaau8650 (2019) 12 April 2019 5 of 20 R ES E A RC H | R E S EA R C H A R T I C LE Downloaded from http://science.sciencemag.org/ on April 27, 2019 Fig. 3. Global changes in DNA methylation during spaceflight. (A) PCA of distances derived from average CpG methylation levels in 1-kb intervals along the chromosomes in each sample (CD4 and CD8 lymphocytes collected from each subject). (B) Genome-wide distributions of MML and NME values in CD4 and CD8 lymphocytes collected from each subject at indicated time points. (C) Genome-wide distributions of JSDs within each subject in comparisons of preflight to the indicated inflight and postflight time points in CD4 and CD8 cells. (D) Heatmaps representing transformed enrichment values (square root of enrichment) for GO categories with a raw enrichment value >5 in TW for comparisons of preflight (L−162) samples to inflight
Garrett-Bakelman et al., Science 364, eaau8650 (2019)
12 April 2019
(early, FD76; late, FD259) and postflight (R+104) samples in CD4 and CD8
cells. (E) University of California, Santa Cruz, Genome Browser images
of NOTCH3 and SLC1A5 with peaks of JSD at their promoters in TW when
comparing inflight (FD259, for NOTCH3, and FD76, for SLC1A5) to preflight
(L−162) samples from CD4 (for NOTCH3) and CD8 (for SLC1A5) cells.
Differential MML (dMML) and differential NME (dNME) values are also plotted,
with negative values indicating reduced MML or NME at the inflight time points
compared with preflight time points. For all boxplots, center lines indicate
median, boxes indicate interquartile range (IQR), and whiskers indicate
1.5 × IQR. CGI, CpG island; chr. 19, chromosome 19.
6 of 20
R ES E A RC H | R E S EA R C H A R T I C LE
global methylation changes in TW were within
the range observed for HR.
Although the observed genome-wide changes
were minimal, we hypothesized that local changes
at promoters of genes involved in environmental
adaptation could be particularly affected in TW
during flight. We therefore ranked genes according to their epigenetic discordance, as quantified
by the JSD, and used these ranked lists for gene
ontology (GO) enrichment analysis (table S4).
When comparing inflight with preflight samples
from TW, we observed enrichments for genes
involved in the response to platelet-derived growth
factor (PDGF) and T cell differentiation and
activation pathways in both CD4 and CD8 cells
(Fig. 3D). Genes involved in platelet aggregation
(q = 0.028, HGT), regulation of ossification (q =
0.009, HGT), and cellular response to ultraviolet-B
(UV-B) (q = 0.039, HGT) were also enriched in
these comparisons, specifically in CD4 cells. By
contrast, analysis of CD8 cells revealed enrichment
in genes involved in the somatostatin signaling
pathway (q = 0.016, HGT) and positive regulation
of superoxide anion generation (q = 0.016, HGT).
Importantly, for all time point comparisons, the
most enriched GO terms for TW preflight versus
inflight were not enriched in HR (Fig. 1D).
Fig. 4. Lipids and vaccine response. (A) Cytokines present at significantly
different levels in HR and TW or between pre-, in-, and postflight periods.
Heatmap represents median-normalized log2 intensity for each analyte,
scaled across all samples. Red color indicates relative enrichment,
whereas blue indicates relative depletion. (B) Relative levels (mediannormalized, scaled log2 intensity) of complex lipids containing w-3 and
w-6 fatty acids in HR and TW, from untargeted plasma metabolomics. Red
Garrett-Bakelman et al., Science 364, eaau8650 (2019)
12 April 2019
Immune response and inflammation
during spaceflight
Differential gene expression analysis indicated
that many immune-related pathways were significantly changed inflight across all cell types
(GLM, q < 0.001), including the adaptive immune system, innate immune response, and natural killer cell–mediated immunity (table S2). Additionally, DNA methylation analysis revealed epigenetic discordance (indicated by JSD peaks) for TW in the promoters of NOTCH3, a wellknown regulator of T cell differentiation (34), and SLC1A5/ASCT2, which promotes T cell activation (35), between preflight (L−162) and inflight samples (FD259 for NOTCH3 and FD76 for SLC1A5) in CD4 and CD8 cells, respectively (Fig. 3E). This epigenetic discordance was associated with a peak of increased promoter methylation (from 10.7 to 20.2%) and entropy (from 41.4 to 71.3%) during flight and was observed in TW, but not in HR nor between HR and TW in preflight samples (fig. S7, B and C), and for SLC1A5, was associated with differential expression (down-regulation) (table S2). To further evaluate T cell and immune functionality in spaceflight, we assessed cytokine data for inflammation signatures. Although none of the cytokines assayed were significantly different at color indicates relative enrichment, whereas blue indicates relative depletion. LysoPC, lysophosphatidylcholine; LysoPE, lysophosphatidylethanolamine. (C) Immunological and postvaccination response to spaceflight. For each subject, the proportion of season 2 clones present in the database of influenza vaccination-responsive CDR3 clones derived from year 1 and 3 vaccinations is shown for each cell type and respective TCR chain (FDR < 0.05). 7 of 20 Downloaded from http://science.sciencemag.org/ on April 27, 2019 NME is evident across all samples. Importantly, the magnitude of changes in both MML and NME was greater for HR and did not fully return to baseline. These data indicate that genome-wide DNA methylation changes detected in CD4 and CD8 cells from TW were within the range of variation seen in HR. These results identify only limited epigenetic discordance in global methylation and entropy levels. Therefore, we quantified both global and local epigenetic discordances between samples by calculating JSDs among all relevant pairwise comparisons within a cell type. Peaks of JSD indicate observable changes in the probability distributions of methylation levels within genomic regions, even if changes in mean methylation levels are small. Genome-wide JSD analysis revealed only subtle changes when comparing preflight with inflight or postflight samples within a subject (Fig. 3C). By contrast, we observed greater JSD changes in comparisons between subjects, particularly in CD4 cells (fig. S7A), consistent with our observation of higher MML and NME changes in that cell type (Fig. 3B). Similar to the results associated with methylation level and entropy, the magnitude of JSD changes was slightly greater for HR than for TW, again indicating that R ES E A RC H | R E S EA R C H A R T I C LE were no significant differences (FDR > 0.05) in
the percentage of unique CD4 or CD8 T cell receptor sequences (vaccination-responsive clones)
that were noted as recruited by vaccination at
6 months inflight from the total PBMC fraction
when compared with preflight and postflight responses in TW (Fig. 4C and fig. S9).
Changes over time in the gastrointestinal (GI)
microbiota were examined with shotgun metagenome sequencing of genomic DNA extracted
from serial fecal swabs of both subjects over the
course of the study (tables S1 and S10). At the
taxonomic level of genus, 1364 to 1641 taxa were
detected in microbiome samples of both subjects.
Although the richness of the fecal microbiome of
HR was consistently higher than that of TW (P < 0.05, paired Wilcoxon signed-rank test, genus level) for the duration of the study, there were no significant differences between subjects in the Shannon index (SI; an index of diversity) (P = 0.82, paired Wilcoxon signed-rank test, genus level). Within TW, there was no decrease in richness or SI in inflight samples relative to preflight and postflight samples [median genera detected 1405.5 versus 1405; median SI (log2), 2.66 versus 2.42; Fig. 5A]. Fecal microbial communities from both subjects were dominated by bacteria from the phyla Firmicutes and Bacteroidetes, together representing >96% of all annotated sequences recovered.
Actinobacterial and Proteobacterial sequences
represented 1.97 and 1.27% of annotated sequences, respectively. The ratio of sequences derived
from Firmicutes to those derived from Bacteroidetes (F/B ratio) ranged from 0.72 to 5.55. The
F/B ratio in TW was higher in inflight samples
relative to combined pre- and postflight samples
(median F/B ratio 3.21 versus 1.45) but returned
to preflight levels postflight (a maximum F/B
ratio of 4.60 was observed in TW inflight; Fig.
5A). Yet, all TW F/B ratios were in the range of
0.01 to 5.96 observed in a healthy human cohort
(39). Although HR had an increased F/B ratio at
the second preflight sampling [ground day (GD)56; GD- days before TW launch; F/B ratio of
5.55], this increased ratio was not sustained
over time and was low throughout the remainder of the analysis period (range of F/B ratios
was 0.72 to 1.76; Fig. 5A). Fecal microbiomes at
all sampling time points from both subjects had
high relative abundance of bacteria from the
genus Bacteroides (ranging from 15.4 to 61.0% of
reads annotated to the taxonomic level of genus).
When examining diversity among samples
(beta diversity), fecal microbial communities of
the subjects were significantly different [analysis
of similarity (ANOSIM) sample statistic R = 0.587,
P = 0.001] and remained distinct over time (Fig.
5B and fig. S10A). The microbial community
structure observed in the four inflight TW samples was significantly different from the pre- and
postflight samples combined (ANOSIM, R = 0.438,
P = 0.016; Fig. 5B). No such effect was observed
in HR samples (ANOSIM, R = −0.05, P = 0.579).
Garrett-Bakelman et al., Science 364, eaau8650 (2019)
12 April 2019
Taxonomic and functional microbial
shifts during spaceflight
Similar flight-associated trends were identified
in targeted analyses of fungal and viral community structures (fig. S10B) and in analyses of functional gene content across all taxa (Fig. 5C). At
the highest resolution of functional gene annotation (SEED function), the subjects had significantly different functional gene content (ANOSIM,
R = 0.456, P = 0.003). For TW, the functional
gene content observed in the four inflight samples was significantly different from the preflight
and postflight samples (ANOSIM, R = 0.55, P =
0.016; Fig. 5C). No such change over time was
observed for HR (ANOSIM, R = −0.094, P = 0.762).
To evaluate the extent of microbial community shifts in flight, we identified specific taxonomic groups and gene function features that
were significantly altered during the inflight
period in both subjects. Specifically, 0.5 to 4.5%
of the detected microbial taxa—including 36 species, 13 genera, 8 families, 4 orders, 3 classes, and
3 phyla—were differentially abundant (FDR < 0.05), when inflight samples were compared with the combined pre- and postflight periods (Fig. 5D). However, we found a smaller number of altered microbial groups at each taxonomic level in HR for the same comparison (Fig. 5D). Similar observations were made when analyzing functional gene content. The spaceflight environment significantly (FDR < 0.05, EdgeR) altered the abundance of a moderate fraction (2 to 23%) of gene functional categories at each level in TW inflight compared with the combined preflight and postflight periods. The number of altered gene functional categories was smaller for HR during the inflight-equivalent period (Fig. 5E). Overall, TW’s inflight samples had high similarity in taxonomic composition and functional gene content, as assessed with Bray-Curtis similarity (Fig. 5F). The level of similarity within TW’s inflight samples was slightly higher than the inflight-equivalent samples from HR for both taxonomic and functional gene annotations (P = 0.03 and 0.31, paired Wilcoxon signed-rank test, respectively). Although TW had more similar preflight and postflight microbial communities than HR, these differences were not significant (P = 0.16 and 0.13, paired Wilcoxon signed-rank test, for taxonomy and functional gene annotations, respectively; Fig. 5F). Finally, we examined metabolomic data for corroboration with the microbiome signatures. We observed several small-molecule markers of microbial metabolism in the untargeted LC-MS metabolomics data, including phenyls, secondary bile acid metabolites, and indole containing compounds, some of which are produced solely by microbial metabolism. Some metabolites, such as 3-indole propionic acid, have anti-inflammatory effects and were observed at lower levels in TW throughout the duration of the study (Fig. 5G and table S3). Mitochondria-related adaptations during spaceflight Our integrated analyses identified a number of mitochondria-related changes at the genomic and functional levels related to the 1-year mission. 8 of 20 Downloaded from http://science.sciencemag.org/ on April 27, 2019 baseline between TW and HR, 50 of the 62 cytokines assayed were differentially abundant between pre-, in-, and postflight in TW. We observed three notable signatures of inflammation. The first signature was composed of cytokines whose levels rose in TW’s plasma in the days after return and continued to be increased 6 months after return. These return-associated cytokines included CSF2 (GM-CSF), HGF, IL10, IL17A, IL18, LEP (leptin), CD40LG (CD40L), LTA (TNFB), VEGFD, NGF, FGF2 (FGFB), IFNA2 (IFNA), IFNB1 (IFNB), IFNG, SERPINE1 (PAI1), RETN, ICAM1, VCAM1, TNFSF10 (TRAIL), and VEGFA (VEGF), among others (Fig. 4A and table S6). The second signature was composed of cytokines that were at relatively high levels in TW preflight, continued to be high inflight, and decreased after return. These cytokines included BDNF, EGF, CXCL5 (ENA78), CXCL1 (GROa), IL2, IL6, LIF, PGDF-BB, TGFA, and TNF (TNFA), with several of them involved in mediating inflammation, cell growth, and cell proliferation, as well as tumor proliferation and vascularization (Fig. 1E and table S6). Of note, IL2 stimulation in CD8 cells activates Hippo signaling (36), and we observed enrichment in this pathway (q = 0.033, HGT) when comparing average promoter JSD (a measure of methylation discordance) from TW’s preflight with postflight samples in both CD4 and CD8 cells (table S4). The third signature of inflammation was seen immediately after landing (R+0 and R+4), with up to eightfold changes for CCL2 (MCP-1), C-reactive protein (CRP), and IL1RN (IL1RA; fig. S8, A to C; ANOVA, q < 0.001; table S8). Notably, CCL2 levels were increased at R+0, whereas CRP levels rose at R+0 and continued to rise at R+4 days. IL1RA levels only peaked at our R+4 data collection point. All three measures returned to baseline levels by the R+36 collection. During both inflight and postflight periods in TW, we detected increased levels of lysophospholipids containing proinflammatory omega-6 20:4 fatty acid (arachidonic acid) (37), together with a decrease in lysophospholipids containing antiinflammatory omega-3 20:5 fatty acid (eicosapentaenoic acid) (38), suggestive of an increased inflammatory status (Fig. 4B and table S3). Finally, we performed a vaccination response experiment to compare the effect of an influenza immunization in the spaceflight environment with that on Earth on the T cell receptor (TCR) repertoires in both subjects with the 2015–2016 trivalent unadjuvanted flu vaccination. Samples were obtained from TW and HR before and ~10 days after a trivalent flu immunization at three time points over the duration of the study. TW was sampled both on Earth (years 1 and 3) and on the ISS (year 2). For samples collected on Earth, repertoires for CD4 and CD8 T cells were separated, whereas frozen PBMCs from the ISS were expected to be a mixture of CD4 and CD8 repertoires. Vaccination-responsive clones were identified by matching complementarity-determining regions (CDR3s) pre- and postvaccination for each subject and cell type, with z scores as measures of change in a one-tailed approach. There R ES E A RC H | R E S EA R C H A R T I C LE Downloaded from http://science.sciencemag.org/ on April 27, 2019 Fig. 5. Effect of spaceflight on the fecal microbial community structure of the flight subject relative to the twin ground subject. Samples are color coded by subject (TW, blue; HR, green), with open symbols representing flight samples from TW or flight-equivalent samples from HR. (A) Taxonomic alpha diversity parameters for HR and TW over nine sampling events, normalized to the value of the first sampling event for each subject. Shown are the normalized genus-level log2 SI values for both subjects and the F/B ratio. SI values at the first sampling event were 4.26 and 3.13 for HR and TW, respectively. F/B ratio values at the first sampling event were 2.18 and 0.87 for HR and TW, respectively. (B and C) Analysis of microbial community taxonomic structure at the genus level (B) and functional gene content (C) using mMDS of annotated shotgun metagenome sequence data. Data were log(x + 1) transformed, and a resemblance matrix, from Bray-Curtis dissimilarity, was generated. MDS axes 1 and 2 are plotted; two-dimensional stress values are 0.19 and 0.13 for taxonomic and functional gene analyses, respectively. Sample names represent dates relative to launch. (D) Number of microbial features at each taxonomic level that were differentially abundant between the inflight samples and the combined pre- and postflight samples of TW Garrett-Bakelman et al., Science 364, eaau8650 (2019) 12 April 2019 or between the equivalent sets of samples from HR. (E) Number of gene functional features at each level (ranged from SEED, that is, the most specific gene functions, to level 1, that is, the most general categories) that were differentially abundant between the inflight samples and the combined pre- and postflight samples of TW or between the equivalent sets of samples from HR. (F) Overall similarity of metagenomic sequence data from sample groups was assessed with Bray-Curtis similarity measurements for untransformed data and presented as boxplots. For each subject, all nine samples are compared and plotted (HR and TW; 36 comparisons), followed by pre- and postflight samples only (HR ground and TW ground; 10 comparisons) and flight samples only (HR flight and TW flight; six comparisons). (G) Metabolic products associated with microbial metabolism in humans. The heatmap shows relative levels of microbial metabolites detected in the metabolomics data (median-normalized, scaled, log2 intensity). Red color indicates relative enrichment, whereas blue indicates relative depletion. Row annotations mark different classes of microbial metabolites, including indoles (violet), phenyls (orange), and bile acids (green). Metabolites that were not significantly altered between HR and TW or between pre-, in-, and postflight periods are marked in black. 9 of 20 R ES E A RC H | R E S EA R C H A R T I C LE Genic annotation of RNA sequencing (RNA-seq) data (40, 41) revealed higher levels of mtRNA inflight as compared with preflight and postflight (Fig. 6A and fig. S11A). The time spent on the ISS was correlated [coefficient of determination (R2) = 0.84] with increased mtRNA inflight (P = 3.6 × 10−6, ANOVA). Mitochondrial genome coverage was consistent across all samples (fig. S11B) and validated by qPCR in DNA from blood plasma and qRT-PCR in RNA from PBMCs, supporting this finding further (fig. S11, C to E). We also conducted an extracellular flux assay that monitors real-time changes in the mito- chondrial oxygen consumption rate (OCR, a measure of mitochondrial oxidative phosphorylation) by treating muscle cells (L6 cell line) with plasma from the astronauts. The results can be characterized as twofold, whereby the plasma can (i) increase basal respiration (Fig. 6B) and (ii) decrease the spare reserve adenosine triphosphate (ATP) capacity (Fig. 6C). These trends show an increase in ATP-linked respiration, decrease in nonmitochondrial respiration, and no change in maximum respiration (Fig. 6, D and E), which may also reflect the changes in mtRNA levels observed during flight. Additionally, a significantly increased level of lactic acid (P = 0.018; ANOVA) was detected in TW’s urine inflight, which returned to baseline postflight. The highest lactic acid levels were observed in TW during the first 15 days and final 14 days of spaceflight (Fig. 6F). GC-MS/MS urine metabolomics data showed an increase in the lactic acid/pyruvic acid ratio (Fig. 6G), indicating a shift from aerobic to anaerobic metabolism. A similar trend in lactic acid levels, as observed in the urine, was also observed in plasma, although only the lactic acid/pyruvic acid ratio was significantly altered in plasma at an FDR of 0.05 (fig. S12, A Downloaded from http://science.sciencemag.org/ on April 27, 2019 Fig. 6. Mitochondrial functions and Seahorse assays. (A) mtRNA content observed in RNA-seq data for the unsorted frozen PBMC (expressed relative to total number of aligned reads). Sequencing results after library preparation with both poly (A)+ selection and ribosomal depletion. (B to E) Mean OCR during pre-, in-, and postflight for basal mitochondrial respiration (B), spare reserve capacity (C), ATP-linked respiration (D), and nonmitochondrial respiration (E). L6 muscle cells were treated with plasma from TW and HR collected pre-, in-, and postflight with six to eight assay replicates per time point. OCR was measured before and after the addition of inhibitors (oligomycin, a complex V inhibitor; FCCP, a protonophore; and antimycin A and rotenone, complex III and I inhibitors, respectively) to derive parameters of mitochondrial respiration. Mean OCR was calculated for each parameter after normalizing for baseline OCR of the L6 cells before the addition of plasma or inhibitors. Error bars represent 95% confidence intervals of the mean OCR of all replicates at each time point for each flight event. (F) Boxplots comparing the concentration of lactic acid in urine normalized to urine creatinines (determined by GC-MS targeted metabolomics) pre-, in-, and postflight in TW and HR. (G) Boxplots representing the ratio of urine lactic acid to pyruvate pre-, in-, and postflight in TW and HR revealing an inflight shift to anaerobic metabolism in the flight twin. Garrett-Bakelman et al., Science 364, eaau8650 (2019) 12 April 2019 10 of 20 R ES E A RC H | R E S EA R C H A R T I C LE to C). Lactic acid production promotes higher extracellular acidification rates (42) that, in turn, are associated with increased expression of glycolysis-related genes. We also observed a trend for increased levels of plasma TCA cycle intermediates in the inflight period, such as citric acid and malic acid (FDR < 0.10), com- pared with preflight and postflight levels (fig. S12, D and E). Given the previously noted changes in mitochondrial respiration, we examined TW’s data for other related signatures. TW exhibited altered gene expression patterns in pathways related to oxygen and reactive species metabolic processes, mitochondrial transport, hypoxia, and apoptotic mitochondrial changes (GSEA, q < 0.0001) (table S2). Although differential expression of these genetic pathways is observed in response to hypoxic stimuli in a rodent model (43), the partial pressure of oxygen levels on ISS were near sea-level values (fig. S13). Cardiovascular changes during spaceflight Fig. 7. Vascular adaptations. (A and B) Carotid artery diameter during diastole (A) and carotid intima-media thickness (cIMT) (B) measured while supine on the ground and during spaceflight in TW and HR. “Pre” indicates the mean of the two preflight measurements. (C and D) IL1B (C) and PGF2a (D) as examples of biomarkers of inflammation and oxidative stress that were measured in these two subjects. (E and F) Boxplots of relative COL3A1 (E) and COL1A1 (F) levels pre-, in-, and postflight for both subjects. (G) Ratio of relative plasma levels of proteins APOB and APOA1 (APOB/APOA1) in both subjects pre-, in-, and postflight, measured using untargeted proteomics (LC-MS). Garrett-Bakelman et al., Science 364, eaau8650 (2019) Body mass, nutrition, and hydration during spaceflight Baseline and inflight values for HR and TW can be found in table S8. Similar to observations in other astronauts (46), TW lost 7% of his body 12 April 2019 11 of 20 Downloaded from http://science.sciencemag.org/ on April 27, 2019 Spaceflight-specific changes in cardiovascular structure and function were observed similar to those previously reported (44, 45) in astronauts during long-duration spaceflight, including a cardiac output increase of 10% (average of spaceflight measurements) (Fig. 7A) and a moderate decrease in systolic and mean arterial pressure (table S7) relative to the upright posture on Earth. Moreover, carotid artery distension developed early in flight during both systole and diastole and persisted throughout the mission (Fig. 7A). Concomitantly, carotid intima-media thickness increased in TW from preflight to inflight and remained thicker 4 days after landing (Fig. 7B). In addition, indices of inflammation, including cytokines [e.g., IL1A, IL1B, IL2, and prostaglandin F2a (PGF2a)] and chemokines, were increased during spaceflight in TW, whereas they remained unchanged in HR across all time points measured (Fig. 7, C and D; fig. S8; and table S6). Biomarkers of oxidative stress were not consistently increased [e.g., oxidized low-density lipoprotein (LDL), myeloperoxidase, and 8-hydroxy-2′-deoxyguanosine (8-OHdG)] in TW during spaceflight (table S8). However, targeted proteomics identified increased levels of two proteins that may be associated with observed changes in vascular wall dimensions. Collagen alpha-1(III) chain (COL3A1) and collagen alpha-1(I) chain (COL1A1) proteins in TW’s inflight urine were increased compared with preflight levels, and these values returned to baseline levels postflight (Fig. 7, E and F). We also observed increased COL1A1, from measurements of two separate COL1A1 peptides, by untargeted proteomic analyses (Fig. 7F). This finding is consistent with enrichment of expression levels of genes in the collagen-related pathways [including but not limited to GO term “collagen trimer” and Reactome pathway “collagen formation” in PBMCs (DESeq2, q < 0.001)] (table S2). We also observed an increase in the ratio of plasma levels of apoliprotein B (APOB; a major constituent of LDL particles) to apolipoprotein A1 [APOA1; a major constituent of high-density lipoprotein (HDL) particles] during the last 6 months inflight (late inflight; after FD180) in TW, compared with preflight and early inflight (ANOVA, P = 0.003, Fig. 7G). These levels decreased postflight and, then, were not significantly different from preflight levels. No significant increase was seen in HR, indicating an association of the APOB/APOA1 ratio with the long duration of the mission. R ES E A RC H | R E S EA R C H A R T I C LE Neuro-ocular changes during spaceflight Spaceflight resulted in a cephalad fluid shift and ocular changes in TW that were not present in HR. Internal jugular vein cross-sectional area, forehead tissue thickness, cardiac filling, stroke volume, and cardiac output increased, despite an average decrease in mean arterial pressure when compared with values associated with the seated position on Earth (Fig. 9, A and B). Increases in subfoveal choroidal thickness (primary vascular supply of the outer retina) and peripapillary total retinal thickness were observed, indicating retinal edema formation (Fig. 9, C and D). Moreover, although TW exhibited choroidal folds during preflight testing before this mission, the severity of the choroidal folds increased during spaceflight, as quantified by number and depth. These ocular structure parameters were unchanged in HR for the duration of the study, and choroidal folds were not present at the initiation of these data collection sessions (Fig. 9, A to D). Of relevance to these ocular changes, untargeted proteomics revealed a decrease in urine leucine-rich alpha-2-glycoprotein (LRG1) levels in TW inflight relative to those pre- and postflight (Fig. 9E). LRG1 has been reported to play a role in retinal vascular pathology (49). The predisposition to develop these ocular changes during spaceflight has also been associated with Bvitamin status and the presence of specific singlenucleotide polymorphisms (SNPs) (50). Risk alleles in five SNPs predict incidence of ophthalmic issues (49), and six of the nine risk alleles are presGarrett-Bakelman et al., Science 364, eaau8650 (2019) Fig. 8. Body weight, bone formation, fluid regulation, and biochemical activity during spaceflight. Biochemical and biophysical measures during the mission. Data are mean ± SD. (A) Body mass expressed as percent change (D) from preflight. (B) Relative urine AQP2 concentration in TW (blue circles) plotted along with serum sodium concentrations (yellow circles). (C) Calculated plasma osmolality for both subjects. (D) Relative urine AQP2 concentrations for both subjects. (E) Untargeted (LC-MS) urine proteomics reveals that relative angiotensinogen (AGT) levels inflight correspond with inflight weight loss. In (B) to (E), the shaded area represents inflight time points. (F and G) Bone breakdown (N-telopeptide) (F) and bone formation [bonespecific alkaline phosphatase (AP)] (G) markers. Data in (F) and (G) are expressed as percent change from preflight. (H) Exercise load using the advanced resistive exercise device (ARED) and bone-specific AP marker. 1 lb = 0.45 kg; U/L, units per liter. ent in the twins (50). Furthermore, serum folate, a B vitamin that is often low in astronauts who experienced ophthalmic changes during flight (51), was also low in both TW and HR (Fig. 9F). Cognitive performance Continuous high levels of astronaut cognitive performance are critical for mission success. Study subjects performed a computerized cognitive test battery (Cognition) (52) throughout all phases of the mission (Fig. 10A). TW’s accuracy and speed scores were measured for the different phases of the mis12 April 2019 sion [preflight, inflight months 1 to 6 (early flight), inflight months 7 to 12 (late flight), and postflight] (Fig. 10B). TW took more risk than HR on the balloon analog risk test (BART) during all phases of the mission, more so inflight compared with preflight and postflight. Compared with HR, TW did not exhibit significant deficits in either speed (−0.7 SD, P = 0.3518; Student’s t test) or accuracy (−0.2 SD, P = 0.6678; Student’s t test) across cognitive domains preflight. TW’s cognitive speed increased across all cognitive domains early inflight relative to preflight. During 12 of 20 Downloaded from http://science.sciencemag.org/ on April 27, 2019 mass during flight, whereas HR gained ~4% of his body mass over the course of the study (Fig. 8A). TW had decreased urine volume (table S8) and increased urinary aquaporin-2 (AQP2) inflight compared with preflight, which both returned to baseline postflight (Fig. 8B). Serum sodium concentrations (Fig. 8B) and osmolality (Fig. 8C) followed urine AQP2 levels (Fig. 8D) for the duration of the study. TW’s energy intake was about 66% of predicted requirements, and beyond the nominal vitamin D supplements provided to all astronauts, he did not report taking vitamin or mineral supplements during the mission. In TW, proteomic analysis revealed a decrease in urine angiotensinogen inflight relative to pre- and postflight that is correlated with the decline of body mass inflight (Fig. 8E). Bone turnover markers for both breakdown (N-telopeptide; Fig. 8F) and formation (bonespecific alkaline phosphatase; Fig. 8G) increased 50 to 60% in TW during the first 6 months, as previously reported during 4- to 6-month spaceflights (13, 47, 48). However, these markers decreased in the last 6 months of the mission until immediately before landing. Similar trends were observed for other resorption (e.g., serum CTX-b) and formation markers (e.g., P1NP and osteocalcin; table S8), supporting these data. Bone formation and volume of resistive exercise before the blood draw followed similar trends (Fig. 8H), that is, when exercise volume was lower in the second half of the mission (due to injury), bone formation was correspondingly lower, as expected. R ES E A RC H | R E S EA R C H A R T I C LE the same period, spatial orientation and motor praxis accuracy increased (>1 SD), whereas accuracy of visual object learning and abstract
matching decreased (>1 SD) relative to HR. There
was no significant decrease in performance from
early to late inflight, with the following exceptions: (i) decline (>1 SD) in emotion recognition
task (ERT) and digit symbol substitution task
(DSST) speed and (ii) decline (>2 SD) in abstract
matching (AM) accuracy (P = 0.0280; Student’s
t test; TW versus HR late flight, Fig. 10C). Per-
formance trends across the study on key accuracy
and speed metrics for all 10 tests in the Cognition
battery are shown in fig. S14.
Most notably, cognitive speed decreased for all
tests except for the DSST, and accuracy decreased
for all domains except for spatial orientation
postflight. TW’s cognitive efficiency (a combination of speed and accuracy across cognitive
domains) was similar pre- and inflight relative
to HR but was significantly lower postflight (P =
0.0016, Student’s t test). This postflight decline
in cognitive performance persisted up to 6 months
postflight in both speed and accuracy domains
(Fig. 10C).
Discussion
The NASA Twins Study represents an integrated,
multiomics, molecular, physiological, and cognitive portrait of an astronaut and reveals the biomedical responses of a human body during a
year-long spaceflight. Our results demonstrate
both transient and persistent changes associated
Downloaded from http://science.sciencemag.org/ on April 27, 2019
Fig. 9. Fluid shifts and ocular changes. (A and B) Internal jugular vein
cross-sectional area (A) and forehead skin thickness (B) measured by
ultrasound as indicators of acute fluid shifting during the transition
from seated to supine during ground-based testing and the chronic fluid
shift in weightlessness in TW. (C and D) Concurrently, ocular measures
of choroid thickness (C) and total retinal thickness (D) measured by
Garrett-Bakelman et al., Science 364, eaau8650 (2019)
12 April 2019
optical coherence tomography under the same conditions. (E) Untargeted
proteomics reveals decreased urine excretion of LRG1 in TW during
flight relative to ground time points. (F) Serum folate is lower in astronauts
who experienced ophthalmic issues and was similarly relatively low in
both twins. TW’s serum folate increased during flight, mirroring the
increase in telomere length.
13 of 20
R ES E A RC H | R E S EA R C H A R T I C LE
with long-duration spaceflight across multiple cell
types, tissues, genotypes, and phenotypes. These
specific data, as well as the broader biomedical
measures and sample collection methods, can
now serve as a foundation for scientific and medical assessments of future astronauts, especially
for those on prolonged, exploration-class missions.
NASA has announced plans for a Mars mission and a cis-lunar station, which will provide
new opportunities for contextualizing human
physiological and molecular dynamics during
extended spaceflight. Data from this study indi-
cate that at least 10 key physiological processes
were influenced by long-duration spaceflight,
which serve as targets for development of countermeasure interventions during future explorationclass human space travel. These include (i) body
mass and nutrition, (ii) telomere length regulation, (iii) maintenance of genome stability, (iv)
vascular health, (v) ocular structural adaptations,
(vi) transcriptional and metabolic changes, (vii)
epigenetic shifts, (viii) lipid level alterations, (ix)
microbiome responses, and (x) cognitive function.
These can further be classified as associations
that are of potentially (i) low risk, (ii) medium or
unknown risk, and (iii) high risk. These risk
classifications are made on the basis of the degree
of potential functional importance during spaceflight and their persistence for at least 6 months
after returning to Earth.
Highly dynamic associations with
potentially low risk
Many rapid physiological and molecular changes
associated with spaceflight returned to near preflight levels, including average telomere length,
Downloaded from http://science.sciencemag.org/ on April 27, 2019
Fig. 10. Cognitive performance results. (A) Representative images of the
Cognition battery (10 tasks). MP, motor praxis; VOLT, visual object learning
test; F2B, fractal 2-back; AM, abstract matching; LOT, line orientation test;
ERT, emotion recognition task; MRT, matrix reasoning test; DSST, digit
symbol substitution task; BART, balloon analog risk test; PVT, psychomotor
vigilance test. (B) Heatmap of cognitive performance scores of TW relative
to HR during preflight (N = 3 tests), the first 6 months inflight (inflight 1 to 6,
N = 6 tests), the second 6 months inflight (inflight 7 to 12, N = 5 tests),
and postflight (N = 3 tests). Test scores were corrected for practice and
stimulus set-difficulty effects. All data were then standardized relative to
preflight ground data of 15 astronauts (including TW and HR). Test scores in
the heatmap reflect TW scores minus HR scores expressed in SD units. The
Garrett-Bakelman et al., Science 364, eaau8650 (2019)
12 April 2019
BART reflects risk-taking behavior and was thus not included in the
accuracy score across cognitive domains (accuracy, ALL). Efficiency was
calculated as the average of the speed score across cognitive domains
(speed, ALL) and the accuracy score across cognitive domains (accuracy,
ALL). (C) Standardized cognition performance scores for individual test
bouts for the AM test (1) and speed (2), accuracy (3), and efficiency
(4) across cognitive domains. The vertical lines indicate launch and landing
dates for TW. The AM plot shows that HR (green) had a major insight
mid-mission relative to the rules that govern the AM that TW (blue) did
not have (50% is performance at chance level on the AM). The speed,
accuracy, and efficiency plots demonstrate that the nature of
the postflight decline in TW’s performance was protracted.
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R ES E A RC H | R E S EA R C H A R T I C LE
body mass, microbiome composition, T cell
function, and most cellular and tissue regulation (transcriptional and metabolic). Owing to
their pronounced responses during spaceflight,
these serve as important potential biomarkers
for adaptation of the human body in space but
likely represent minimal to low risks for longduration missions.
Measures of gene function
Telomere elongation
The spaceflight-specific telomere elongation observed in this study is consistent with similar findings in unrelated astronauts on shorter (~6 month)
duration ISS missions, as well as in Caenorhabditis
elegans flown on the ISS for 11 days (53). Although
the underlying mechanisms and potential consequences of such transient telomere elongation
are currently unknown, healthy lifestyle factors
related to metabolic and nutritional status, physical activity, and weight loss have been associated
with longer telomeres (54–60). Consistent with
these studies, TW’s reduced body mass and increased serum folate levels inflight correlated
with telomere lengthening (fig. S15).
Microbiome changes
The GI microbiome can be expected to respond
dynamically to changes in diet and other factors,
Associations with potential mid-level
or unknown risk
Several features of long-duration spaceflight represent mid-level or unknown long-term risk, including collagen regulation, intravascular fluid
management, and persistent telomere loss and/or
critical shortening.
Collagen regulation
To our knowledge, spaceflight-related changes in
urinary excretion of COL1A1 and COL3A1 have
not previously been observed in astronauts. They
are both more than twice the molecular weight
of albumin, so whole collagen molecules would
filter from blood into the urine poorly (63). They
are present in the kidney in relatively low levels.
Weightlessness alters loading on cartilage, bone,
tendon, skin, vasculature, and the sclera, so these
are other potential sources of increased urinary
COL1A1 and COL3A1. TW had an increased internal jugular diameter and vascular remodeling
of his carotid artery manifested as increased
intima-media thickness. COL3A1 is a functionally important component of the vasculature,
because defects in the COL3A1 gene cause blood
pooling in the legs and impaired blood pressure
responses to standing. Changes in muscle, tendon,
bone, and hydrostatic loading during weightlessness provide numerous sites where the body might
undergo structural remodeling, leading to increased urinary excretion of COL1A1 and COL3A1.
Intravascular fluid management
Astronauts are at risk for dehydration, which
can lead to increased renal stone risk (47). AQP2
controls water transport in the renal collecting
duct epithelial cells and is regulated by vasopressin, which is released when the body is dehydrated. A decrease in both food and water
intake might be linked to a decreased upper and
lower GI motility associated with decreased gravitational force. The return to Earth usually leads
to fluid retention and weight gain, and indeed,
TW exhibited a modest weight gain in the days
after landing. Our study provides evidence that
an increase in urinary AQP2 manifests during
spaceflight rather than being related to readaptation to the Earth environment and also correlates with serum sodium levels. It is thus likely
that increased urine AQP2 was due to high plasma
sodium stimulating vasopressin release. AQP2 is
regulated by vasopressin, which elicits fluid reabsorption from the urine when activated (64).
This renal water reabsorption protein was unable to fully compensate for decreased water
intake, leading to an increased plasma sodium
concentration and oncotic pressure during flight.
TW’s increased urine AQP2 may be the result of
inflight dehydration or hypernatremia, as indicated by increased plasma sodium levels and
measured by osmolality. For future missions,
urine AQP2 levels should be monitored in crewmembers to identify who should be considered
for potential therapeutic interventions to ameliorate the side effects and physiological complications of dehydration.
During spaceflight, 24-hour urine volumes are
generally decreased, secondary to water intake
and the low relative humidity onboard the ISS
(13). Several of our findings may be associated
with the reduced energy intake and weight loss
observed in the flight subject, including telomere
Table 1. Spaceflight experience of study subjects. Summary of spaceflight missions (launch and landing dates) as well as durations for study subjects TW and HR.
Subject
TW
Vehicle
Mission
Launch date
Landing date
Duration (days)
Space shuttle
STS-103
12/19/99
12/27/99
8
………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………….
Space shuttle
STS-118
8/8/07
8/21/07
12.7
………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………….
International
Space Station
Expedition 25/26
10/7/10
3/16/11
159
………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………….
International
Space
Station
Expedition
43/44/45/46
3/27/15
3/1/16
340
……………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………..
Space shuttle
STS-108
12/5/01
12/17/01
11.8
………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………….
HR
Space shuttle
STS-121
7/4/06
7/17/06
12.8
Space
shuttle
STS-124
5/31/14
6/14/14
13.8
………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………….
………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………….
Space shuttle
STS-134
5/16/11
6/1/11
15.7
……………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………..
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The majority (91.3%) of the genes that changed
expression in CD4, CD8, and LD cells during
spaceflight returned to normal ranges within
6 months postflight (Fig. 1B and table S2). In
addition, although some epigenetic loci were
changed, the genome-wide epigenetic variance
was higher in the ground control than in the
flight subject during the 25 months of this study.
Furthermore, the observed changes in metabolic
levels in plasma returned to baseline postflight.
The immune stress indicated by the transcriptional and proteomic data did not seem to impair
recruitment of influenza-specific T cells, as evaluated by the response to the midflight vaccination, suggesting that primary immune functions,
including chemotaxis, antigen distribution and
trafficking, and presentation through the lymphatic system were maintained. Overall, these
data show plasticity and resilience for many core
genetic, epigenetic, transcriptional, cellular, and
biological functions.
and such variability over time was evident in
both subjects. Although each subject maintained
individual microbiome characteristics, more
changes in microbial community composition
and function were found during the flight period
in TW than in the equivalent period in HR (Fig. 5).
Given the number of significantly changed microbiome features inflight, it is likely that some
microbiome changes observed are related to
spaceflight. Inflight changes in small-molecule
microbiome-derived metabolites (Fig. 5G) also
suggest that the microbiome undergoes functional changes in response to spaceflight. Compared with the differences between individuals,
the scale of microbiome changes in microbial
diversity in TW during flight was relatively small
and may be reflective of isolation and dietary
change. This is consistent with ground-based
studies of volunteers undergoing extended isolation (61, 62). The flight subject showed a significant and spaceflight-specific increase in the
F/B ratio; however, this ratio returned to preflight levels within weeks of landing, indicating
a rebounding across the microbial ecosystem
of the GI tract. Furthermore, the diversity of the
microbiome, often considered an indication of
microbiome health, was not decreased inflight.
The health risks associated with these inflight
changes are not known but may be minimal.
R ES E A RC H | R E S EA R C H A R T I C LE
Persistent telomere loss and/or
critical shortening
The rapid (1 year) will be required to determine the manner by which those
risks will change (e.g., linear or exponential) and
to establish appropriate safety thresholds.
These results represent an integrated portrait
of molecular, physiological, and behavioral adaptations and challenges for the human body during
extended spaceflight and are important to individual astronauts and to many groups at NASA
(e.g., ISS Program, Space Medicine, and the
Human Research Program) for planning other
ISS missions. These data can be of immediate
use by investigators and groups around the world
planning future human spaceflight missions.
Moreover, future year-long ISS missions would
provide additional subjects and materials for
subsequent studies and interpretation in support
of future Mars missions. However, the opportunity to have an identical twin as a control for a
spaceflight study is not currently planned nor
expected. Thus, this study and its methodologies
represent a uniquely controlled and integrated
framework for comprehensively quantifying astronaut biology in space.
R ES E A RC H | R E S EA R C H A R T I C LE
fuzzy c-means clustering for longitudinal
trends. All P values were corrected for multiple
testing using a FDR of 0.05 or 0.01, and q values
are reported in all tables.
21.
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