Molecular and physiological changes in the SpaceX Inspiration4 civilian crew

Abstract

Human spaceflight has historically been managed by government agencies, such as in the NASA Twins Study¹, but new commercial spaceflight opportunities have opened spaceflight to a broader population. In 2021, the SpaceX Inspiration4 mission launched the first all-civilian crew to low Earth orbit, which included the youngest American astronaut (aged 29), new in-flight experimental technologies (handheld ultrasound imaging, smartwatch wearables and immune profiling), ocular alignment measurements and new protocols for in-depth, multi-omic molecular and cellular profiling. Here we report the primary findings from the 3-day spaceflight mission, which induced a broad range of physiological and stress responses, neurovestibular changes indexed by ocular misalignment, and altered neurocognitive functioning, some of which match those of long-term spaceflight², but almost all of which did not differ from baseline (pre-flight) after return to Earth. Overall, these preliminary civilian spaceflight data suggest that short-duration missions do not pose a significant health risk, and moreover present a rich opportunity to measure the earliest phases of adaptation to spaceflight in the human body at anatomical, cellular, physiological and cognitive levels. Finally, these methods and results lay the foundation for an open, rapidly expanding biomedical database for astronauts³, which can inform countermeasure development for both private and government-sponsored space missions.

Full text

Nature | Vol 632 | 29 August 2024 | 1155
Article
Molecular and physiological changes in the
SpaceX Inspiration4 civilian crew
Christopher W. Jones1,25, Eliah G. Overbey2,3,4,5,25, Jerome Lacombe6,7,25, Adrian J. Ecker1,
Cem Meydan2,3,4, Krista Ryon2,3,4, Braden Tierney2,3,4, Namita Damle2,3,4, Matthew MacKay2,3,4,
Evan E. Afshin2,3,4, Jonathan Foox2,3,4, Jiwoon Park2,3, Theodore M. Nelson8, Mir Suhail Mohamad9,
Syed Gufran Ahmad Byhaqui9, Burhan Aslam9, Ummer Akbar Tali9, Liaqun Nisa9,
Priya V. Menon9, Chintan O. Patel9, Sharib A. Khan9, Doug J. Ebert10, Aaron Everson10,
Michael C. Schubert11, Nabila N. Ali11, Mallika S. Sarma11, JangKeun Kim2,3, Nadia Houerbi2,3,
Kirill Grigorev2,3, J. Sebastian Garcia Medina2,3, Alexander J. Summers6, Jian Gu6,7,
John A. Altin12, Ali Fattahi6, Mohammad I. Hirzallah13,1 4, Jimmy H. Wu14,15, Alexander C. Stahn1,
Afshin Beheshti16,17, Remi Klotz18, Veronica Ortiz18, Min Yu18, Laura Patras19,20, Irina Matei19,2 1,
David Lyden19,21, Ari Melnick2, Neil Banerjee22, Sean Mullane22, Ashley S. Kleinman2,3,
Michael Loesche22, Anil S. Menon23, Dorit B. Donoviel14,15, Emmanuel Urquieta14,15,
Jaime Mateus22, Ashot E. Sargsyan10, Mark Shelhamer11, Frederic Zenhausern6,7,12, 24 ,
Eric M. Bershad13,1 4, Mathias Basner1,26 ✉ & Christopher E. Mason2,3,4,26 ✉
Human spaceight has historically been managed by government agencies, such
asin the NASA Twins Study1, but new commercial spaceight opportunities have
opened spaceight to a broader population. In 2021, the SpaceX Inspiration4 mission
launched the rst all-civilian crew to low Earth orbit, which included the youngest
American astronaut (aged 29), new in-ight experimental technologies (handheld
ultrasound imaging, smartwatch wearables and immune proling), ocular alignment
measurements and new protocols for in-depth, multi-omic molecular and cellular
proling. Here we report the primary ndings from the 3-day spaceight mission,
which induced a broad range of physiological and stress responses, neurovestibular
changes indexed by ocular misalignment, and altered neurocognitive functioning,
some of which match those oflong-term spaceight2, but almost all of which did
not dier from baseline (pre-ight) after return to Earth. Overall, these preliminary
civilian spaceight data suggest that short-duration missions do not pose a
signicant health risk, and moreover present a rich opportunity to measure the
earliest phases of adaptation to spaceight in the human body at anatomical,
cellular, physiological and cognitive levels. Finally, these methods and results lay
the foundation for an open, rapidly expanding biomedical database for astronauts3,
which can inform countermeasure development for both private and government-
sponsored space missions.
Orbital human spaceflight missions have historically flown highly
screened and extensively trained cohorts of astronauts, with limited
public data available for follow-up analyses. However, with the emer-
gence of private space programmes and broadening access to orbital
missions, new opportunities for research and discovery have emerged
for civilian engagement with spaceflight. Specifically, SpaceX has now
launched or announced several privately supported missions, includ-
ing the all-civilian Inspiration4 missionand the Polaris Dawn series of
missions (including on Starship). These missions enable a broader
representation of astronaut cohorts, spanning a wider range of ages
(for example, the youngest American astronaut, Hayley Arceneaux),
balanced representation of sexes, diverse genetic and medical back-
grounds, as well as opportunities for new science, technology, art and
public engagement during their missions.
Here we present findings from the human research experiments
performed on SpaceX’s first all-civilian private spaceflight, Inspiration4,
which launched from Kennedy Space Center on 15 September 2021, on
the SpaceX Crew Dragon capsule. This orbital class mission reached
590.6 km in altitude; the farthest distance crewed orbital missions have
been into space since the Gemini programme. Although the crew spent
only 3 days in low Earth orbit, they experienced similar hazards of space-
flight as International Space Station (ISS) missions (often 6–12 months
in duration), including radiation exposure, sustained microgravity, the
closed and hostile environment of space, isolation and confinement,
and long distance from Earth resources2. Thus, the Inspiration4 mission,
and similar missions, provide a platform to study these acute exposures
endemic to low Earth orbit, with unique data collection opportunities
in the earliest phase of the human body’s response to spaceflight.
https://doi.org/10.1038/s41586-024-07648-x
Received: 3 February 2023
Accepted: 3 June 2024
Published online: 11 June 2024
Open access
Check for updates
A list of afiliations appears at the end of the paper.
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1156 | Nature | Vol 632 | 29 August 2024
Article
The three main objectives of the research projects deployed on the
Inspiration4 mission were to (1) evaluate the feasibility of collecting
biological and behavioural data in an all-civilian crew throughout
pre-flight, in-flight and post-flight phases of the spaceflight mission,
(2) examine the biological and behavioural responses of the crew to
short-duration orbital spaceflight and (3) build the foundation for a
biomedical database and enable access to these biomedical data from
the crew and mission. The Inspiration4 mission provided a unique
opportunity to test the feasibility of medical research aboard a com-
mercial spaceflight mission crewed by non-professional astronauts, as
well as new clinical and research protocols, which spanned a wide range
of assays and experiments (Extended Data Fig.1 and Supplementary
Table1). Specifically, the Multimodal Evaluation of Spaceflight Health
protocol for the Inspiration4 mission from the Translational Research
Institute for Space Health (TRISH) funded multiple investigators to
conduct separate yet related investigations on the Inspiration4 mis-
sion, and deployed a battery of tests to understand some of the major
effects of short-duration spaceflight on humans, including portable
ultrasound measurements, cognitive and sensorimotor tests, sur-
veys, physiological data collected with a smartwatch and blood/saliva
testing. Moreover, a comprehensive Space Omics and Medical Atlas
(SOMA) protocol, based on the NASA Twins Study1, was used to meas-
ure multi-omic, clinical and immune profiles in whole blood, serum,
plasma, saliva and biopsied skin samples. In this Article, we present and
discuss the key findings from studies evaluating the Inspiration4 crew’s
comprehensive multi-omics analyses of biospecimens, ultrasound
imaging, otolith function, cardiovascular physiology and cognitive
performance, which together enable an in-depth biomedical research
approach for private crews on upcoming missions and unprecedented
access to these data and samples.
Multi-omic profiling of the Inspiration4 crew
Building upon established omics, sample pipelines and analytic meth-
ods from the NASA Twins Study1, we collected samples for an integrative
multi-omics analysis of the Inspiration4 crew (Extended Data Fig.2).
This included biospecimens collected before launch (L) pre-flight
(L − 92, L − 44 and L − 3), in-flight (flight days (FDs) FD1, FD2 and FD3)
and post-flight following return (R) to Earth (R + 1, R + 45, R + 82 and
R + 194). Blood, saliva, skin swabs, skin biopsies and capsule swabs
were collected (Extended Data Fig.2), followed by a battery of assays
to collect multi-omic measurements, including spatially resolved tran
-
scriptomics, whole-genome sequencing (WGS), direct RNA sequenc-
ing, combined single-nuclei RNA sequencing/single-nuclei assay for
transposase-accessible chromatin using sequencing (ATAC-seq), Tcell
receptor immune repertoire sequencing, B cell receptor immune rep-
ertoire sequencing, proteomics (liquid chromatography with tandem
mass spectrometry (LC–MS/MS)), metabolomics (LC–MS/MS), a clonal
haematopoiesis panel, cell-free DNA and cell-free RNA sequencing
from plasma, shotgun metagenomics and shotgun metatranscriptom-
ics (Methods and Extended Data Fig.2). Also, clinical measurements
were obtained and included complete blood count, a comprehensive
metabolic panel, a CLIA-grade (Clinical Laboratory Improvement
Amendments) WGS and pharmacogenomics profile, a cardiovascular
biomarker panel and cytokine/chemokine panel assays (Fig.1, Extended
Data Fig.2 and Supplementary Table2).
These data revealed a broad set of molecular changes across multiple
layers of biology (Fig.1), and each specific omics dataset was examined
in depth across several Inspiration4 companion papers. First, epigenet-
ics data from single-nuclei chromatin (single-nuclei ATAC-seq) profil-
ing showed more than 70,000 peaks per sample, which were enriched
for genes involved in DNA repair, immune activation and nucleosome
organization
4,5
, notably matching results from the NASA Twins Study
1
.
Second, telomere elongation was observed for all crew members,
but all other metrics of genome stability, sequence divergence and
clonal haematopoiesis were unchanged6. Third, we observed an aver-
age of 668 metabolites and more than 4,000 proteins per sample in
plasma, which was smaller than the 637 proteins per sample in the
exosome population, yet the exosome proteomic data revealed unique,
brain-associated peptides7. Fourth, direct RNA nanopore sequencing
showed a mean of 13,022 transcripts per sample, plus a significant spike
in methyl-6-adenine (m6A) levels on the day of landing, R + 1 (ref. 8);
this was complemented with a range of 18,632–29,900 genes detected
across all single-nucleus RNA sequencing data. Fifth, we characterized
the spatial biopsies of the crew samples with GeoMx, which revealed a
mean of 16,433 genes persection, with evidence of disrupted inflamma-
tion in pathways near the surface of the skin
9
. Finally, we examined the
microbiome of the crew, using shotgun metagenomics and metatran-
scriptomics before, during and after spaceflight, and we found a spike
in virus abundance in-flight, as well as 3.6 million non-redundant genes
at 90% identity, 1,287 metagenomic assembled genomes and 1,544
assembled viral genomes10.
Immune reactivity analysis
The primary objective of the virome-wide antibody project was to
assess immunological responses, including those that could be asso-
ciated with viral reactivation, during short-duration spaceflight, as a
multitude of evidence has demonstrated perturbation of the immune
system (for example, decreased cellular immunity, dysregulation of
Tcell function and cytokine production) and reactivation of latent
viruses during both short-duration (for example, space shuttle)
and long-duration ISS missions11–14. Therefore, we generated virome
reactivity profiles of the Inspiration4 crew across mission phases,
leveraging a highly multiplexed assay (‘PepSeq’) that measures
immunoglobulin G (IgG) reactivity to peptides representing the
human virome
15–17
. PepSeq analysis using a previously described
15
15,000-peptide assay covering 80 human-infecting viral species
showed that the reactivity profiles of dried blood spot samples col-
lected in-flight clustered with those of terrestrial samples from the
corresponding astronauts (Fig.2a), indicating that the collection and
storage of samples during flight did not adversely affect their quality.
The time-invariant reactivity profiles of the four astronauts included
reactivity to 45 species (Supplementary Table3) and were dominated
by reactivity to peptides from respiratory viruses and Epstein–Barr
virus13,18, as expected (Fig.2a).
To detect species-specific antibody changes during the sampling
period, we conducted a peptide set enrichment analysis19 to compare
all pairs of consecutive time points for each virus species (Fig.2b). We
detected a total of n = 8 such events (defined as significant reactivity
increases); the largest number corresponded to Epstein–Barr virus
(n = 4), a virus previously reported to be reactive in astronauts during
short-duration spaceflight13,18. The remainder were species associ-
ated with common upper respiratory infections: Rhinoviruses A and C
(n = 2 and n = 1, respectively) and Adenovirus C (n = 1). The Epstein–Barr
virus events included changing reactivity that overlapped with flight
for astronauts C001 and C002 during flight (Fig.2b), although these
specific viruses were not found in the sequence data (Fig.1). These
combined analyses indicate that changing immunity to viruses can
be detected during spaceflight, even under conditions where no viral
symptoms or replication are detected, which has been previously docu-
mented in astronauts during longer missions14.
Point-of-care sampling and analysis
In addition to the viral and immune profiles, the Inspiration4 crew
also tested a paper-based multiplexed microgravity-adapted vertical
flow immunoassay (0g-VFI) (Methods and Extended Data Fig.3a–c) to
detect plasma immunoglobulin M (IgM) and C-reactive protein (CRP)
in-flight via gold nanoparticle-conjugated antibodies. Assessment of
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Nature | Vol 632 | 29 August 2024 | 1157
cross-reactivity and specificity showed no significant non-specific
binding, with a minimal background sometimes visible for IgM
(Extended Data Fig.3d). The limit of detection for CRP and IgM was
0.01 and 0.7 µg ml
−1
, respectively (Extended Data Fig.4a). The intra-
and interassay coefficients of variation were less than 20% (Extended
Data Fig.4b), and the presence of some high-level outliers was the
result of a low spatial distribution homogeneity that was compen-
sated by measurement repeatability (Extended Data Fig.4c). Post-flight
examination of the 0g-VFI showed that absorbing pads displayed a
marked area, suggesting that an average of 80 µl of fluid crossed the
membrane, thus highlighting both that fluid displacement occurred
in the microgravity environment and that it was correctly used by the
Inspiration4 crew (Extended Data Fig.3e). Finally, the analysis of 0g-VFI
membranes showed that no IgM or CRP were detected for the devices
run in space following standard protocol (15 min incubation) by the
crew (Extended Data Fig.3f). Unused kits stored in the Dragon capsule
were run post-flight on Earth and did not display any changes either.
Furthermore, control kits stored on Earth with hygroscopic compounds
for the same period (that is, the duration of the flight experiment) and
run for 15 min also showed strong intensity, suggesting the need to
maintain low humidity levels during storage. Accelerated stability stud-
ies conducted in an environmental chamber at 42 °C and 75% humidity
confirmed the effect of desiccation on VFI performance, with a more
than 8-fold decrease in intensity after storage without a hygroscopic
compound (Extended Data Fig.5).
Ultrasound imaging of the Inspiration4 crew
Traditional imaging equipment and techniques, while established
aboard the ISS, may not be afforded in resource-constrained missions
due to their size and resource dependence. The Inspiration4 mission
featured the first in-flight research use of Butterfly iQ+, a handheld
single-probe ultrasound device for urinary bladder, internal jugular
vein (IJV) and eye imaging in full crew autonomy (Fig.3). Aims for all tar-
gets included both the assessment of physiological changes in response
to spaceflight and evaluation of autonomous procedure efficacy.
Eighty-nine imaging instances (multiframe cine of varied length) were
collected pre-flight, and 108 imaging instances were collected in-flight,
Crew ID
C003
C004
0
10,000
20,000
30,000
No. of genes
detected
0
50,000
0
200
400
600
800
0
200
400
600
No. of metabolites
detected
No. of peaks
detected
• PBMC single-nuclei gene expression
• Single-nuclei chromatin accessibility
• Plasma proteomics
• EVP proteomics
• Plasma metabolomics
Time points
L – 92
L – 44
L – 3
R + 1
R + 45
R + 82
L – 92
L – 44
L – 3
R + 1
R + 45
R + 82
L – 92
L – 44
L – 3
R + 1
R + 45
R + 82
L – 92
L – 44
L – 3
R + 1
R + 45
R + 82
DNA
Protein
• Whole-blood bulk gene expression
• Whole-blood m6A mRNA modications
• Skin spatially-resolved gene expression
No. of proteins
detected
L – 92
L – 44
L – 3
R + 1
R + 45
R + 82
0
10,000
20,000
No. of transcripts
detected
0
500
1,000
1,500
2,000
No. of m6A
sites detected
L – 92
L – 44
L – 3
R + 1
R + 45
R + 82
R + 194
L – 92
L – 44
L – 3
R + 1
R + 45
R + 82
R + 194
0
5,000
10,000
15,000
L – 44
R + 1
Microbial
• Skin and env. swab bacterial specie
s
0
500
1,000
1,500
0
1,000
2,000
3,000
0
10
20
30
No. of species
detected
No. of genera detected
L – 92
L – 44
L – 3
R + 1
R + 45
R + 82
FD2
FD3
L – 92
L – 44
L – 3
R + 1
R + 45
R + 82
FD2
FD3
L – 92
L – 44
L – 3
R + 1
R + 45
R + 82
FD2
FD3
• cfDNA sequencing
• WGS
• Telomere elongation
• Clonal haematopoiesis
Time points
• T cell/B cell immune repertoire proling
0
2,000
4,000
6,000
R + 194
100,000
150,000
No. of proteins
detected
Time points
RNA
Time points
C001
C002
No. of genes
detected
No. of species
detected
• Skin and env. swab fungal species
• Skin and env. swab viral species
Fig. 1 | Mult i-omic chan ges acros s the Inspirat ion4 missi on. Hundred s of
thousand s of multi-omic me asurement s were generated ac ross multiple
sample ty pes. From DNA, s ingle-nuclei ch romatin acces sibility, WGS, cell-fr ee
DNA (cfDN A) sequencin g, telomere len gth and clonal h aematopoies is were
measured. From RNA, whole blood gene expression, whole blood m6A
modifications, periph eral blood mononuclear cell(PBMC) single-nuclei RNA
sequenc ing, skin spati ally resolved gene e xpression and Tcell a nd B cell
immune rep ertoire prof iling were perfor med. For proteins , plasma
proteomics, extracellular vesicles and particles (EVP) proteomics and plasma
metabo lomics were quant ified. Addi tionally, from microbial s kin and
environme ntal (Env.) swabs, bacte rial, fungal and v iral specie s were measured.
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1158 | Nature | Vol 632 | 29 August 2024
Article
yielding an average of 27 instances per astronaut (range = 18–32
instances). Bladder imaging success scores were above the usability
threshold (2.33 ± 0.24 (s.d.); range = 2.0–2.5; Methods), demonstrating
the effectiveness of the imaging system and the instructions for urinary
bladder volume assessments (Fig.3b). However, these image sets did
not reveal significant physiological trends, possibly due to variability
between the small number of astronauts and crew-reported operational
constraints affecting the timing of data acquisition relative to voiding.
The bilateral IJV images were the highest in quality (2.36 ± 0.51 (s.d.);
range = 1.8–2.9) and thus amenable to quantification and analysis. The
in-flight image sets from ocular imaging (the most intricate procedure)
consistently scored below the usability threshold in all four astronauts
(0.76 ± 0.51 (s.d.; range = 0.0–1.1); the mean ocular success score was
lower than both the bladder and IJV success scores, which were of similar
quality. Therefore, ocular imaging data were deemed inadequate for
quantification of microgravity-induced structural changes.
The IJV imaging protocol was similar to the protocol described in
ref. 20, which was designed to measure bilateral IJV cross-sectional areas
(CSAs) and flow velocities, and can be used to identify anomalies, such
as thrombi, loss of flow spontaneity, flow reversal and spontaneous
C004
C001
C002
C003
Terrestrial
Flight
ab
C001
C002
C003
C004
Time relative to ight (days)
Terrestrial Flight
–80 –60 –40 –20 0
HHV-4
(EBV)
HRV-A
HAdV-C
HRV-C
Interval with increasing reactivity
Interval with decreasing reactivity
Collection:
HHV-1
NV
SARS-CoV-2
HRV3
HHV-7
HHV-5
HAdV-B
HAdV-D
HHV-6
HOPV
RV-A
HRV-A
HRV-B
EV-C
EV-A
EV-D
Others
HRV-C
EV-B
HHV-4
HAdV-C
Fig. 2 | Viro me-wide ant ibody analys is of blood sa mples self- collecte d
during short-duration spaceflight. Blood spot samples were collected
longitud inally across all mi ssion phase s from the four Inspir ation4 astron auts
and analyse d for IgG react ivity acro ss a 15,000 -plex peptide li brary repres enting
80 human-infe cting viral sp ecies using th e PepSeq ass ay. a, Reactivity for e ach
sample (column s) is shown across all 1,490 p eptides (rows) react ive in at least
one astron aut, with sampl es clustered by th e similarity of th eir reactiv ity
profile s and peptide s grouped by the vi rus species f rom which they were
designe d. Sample reac tivity pro files clust ered tightly w ithin each ast ronaut,
including those collected in-flight. Reactivity was detected against peptides
from a total of 45 v irus specie s, listed in Supp lemental Table3, includin g full
names. b, Time in tervals wit h signific antly increasi ng (red) or decreasin g (blue)
IgG reac tivity in the fo ur astronauts , detected u sing Peptide Se t Enrichment
Analysis19 (Metho ds). Shown are the four viru s species for whic h at least one
signif icant increa se was detec ted with the six s ampling time po ints indicate d
by vertical t ick marks at the to p of the plot. EBV, Epstein–Bar r virus; EV-A,
Enterovirus A; EV-B, Enterovirus B; EV-C, Enterovirus C; EV-D, Enterovirus D;
HAd V-B, Human mastadenovirus B; HAdV- C, Human mastadenovirus C;
HAd V-D, Human mastadenovirus D; HHV-1, Human alphaherpesvirus 1; H HV-4,
Human gammaherpesvirus 4; HHV-5, Human betaherpesvir us 5; HHV- 6,
Human betaherpesvirus 6; HHV-7, Human betaherpesvirus 7; HOPV, Human
orthopneumovirus; H RV3, Human respirovirus 3; HRV-A, Rhinovirus A; HRV- B,
Rhinovirus B; HRV-C, Rhinovirus C; N V, Norwalk virus; RV-A, Rotavirus;
SARS- CoV-2, Severe a cute respirato ry syndrome c oronavirus 2 .
0
0.5
1.0
1.5
2.0
2.5
3.0
Bladder IJV Eye
Success score (0–3)
Mean
C001
C002
C003
C004
b
0
0.2
0.4
0.6
0.8
1.0
1.2
GND GND
ITD
FLT FLT
ITD
IJV CSA (cm2)
P = 0.13 P = 0.09
d
a c
Instructions:
view 2 acquisition
in color doppler
Hold probe in place,
make two ~6-second
cine-loops
Move color box if
needed to cover the IJV
7
8
Tap Actions
5
Tap Color Doppler
6
Maintain same View 2
Maintain View 2:
IJV across
the screen
Colour box covers
the IJV
Fig. 3 | Imaging-based experiments. a, Payload: Butte rfly iQ + ultrasound
system and Re sQGARD I TD7 used for physiolo gical inter vention. b, Summar y
plot of image qua lity asses sment. For each i mage acquired, ima ging succes s
scores were c alculated bas ed on anatomica l accuracy and te chnical qualit y
(Methods). The m ean success s core for each astr onaut is plotte d as an
individual d ata point, and g rey-dotted bar s represent the g rand mean ± s.d . of
astronaut s uccess score s for each anatomi cal target; n = 4 ast ronauts, n = 14
bladder ima ges, n = 73 IJV image s and n = 19 eye images. Eye imagi ng success
scores were di fferent than bla dder and IJV sco res per one-way AN OVA and post
hoc Tukey’s honest sig nificant di fference. c, A sa mple page from the J IT
instruc tions for fl ow spontaneit y assessm ent. d, CSA of the r ight IJV pre-f light
in the supine p osition (GND) and in-f light (FLT), with and wit hout ITD
breathing . Pre-flig ht data were deri ved from a single ima ging instan ce per
astronaut , while in-flig ht data were averaged a cross in-fli ght instanc es within
each astro naut (range = 1–3 imaging inst ances); mean IJV C SA for each astrona ut
is present ed for each condit ion, along wit h the grand mean ± s .d. The differ ence
betwee n grand means for e ach IJV CSA as sessment pr e-flight (GN D) and in-flight
(FLT) is visualized w ith a black dashe d linear trend lin e; n = 4 astronauts , n = 4
GND images , n = 4 GND ITD images , n = 8 FLT images and n = 7 FLT ITD images.
No differen ces betwee n pre-fligh t (GND) and in-fligh t (FLT) were found
evaluated us ing paired, two-t ailed Student ’s t-tests with a sig nificanc e
threshold of α < 0.05.
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Nature | Vol 632 | 29 August 2024 | 1159
echo contrast development21,22 (Fig.3c). In contrast to long-duration
ISS cohorts20,22 and regardless of flight day (FD1–3), both IJVs were
free from thrombi and flow anomalies in all Inspiration4 astronauts.
Spontaneous antegrade flow was demonstrated in all examined IJVs by
colour and (or) spectral Doppler and no spontaneous echo contrast was
detected. While previous studies of astronauts in both short-duration
(lessthan 7 days) and long-duration spaceflight have demonstrated
a stable increase in IJV CSA
20,23,24
, the absence of flow anomalies and
spontaneous echo contrast in all four astronauts suggests a poten-
tial difference from respective long-duration spaceflight data and
the possibility of lower risk of IJV thrombosis in the early period of
microgravity exposure. The effect of inspiratory resistance breathing
using an impedance threshold device (ITD) on IJV filling (reflected as
CSA) appeared more pronounced on the right side, but varied among
astronauts and did not reach statistical significance (Fig.3d, t-test,
P values > 0.05). Notably, the measurements were concordant among
astronauts pre-flight and in-flight (Fig.3d), indicating reliable data col-
lection and encouraging further inquiries into the potential of ITD-like
interventions as a countermeasure against thrombosis in cases of clini-
cal concern with commensurate flow anomalies.
Otolith asymmetry and motion sickness
The neurovestibular system is adversely affected by the microgravity
environment of space through altered neural processing and transduc-
tion of sensory measurements25,26. The otolith organs are an integral
component of the neurovestibular system that transduce sensory
effects, particularly linear acceleration and gravity. Any normal asym-
metry between otoliths on the two sides of the head is compensated
for by central neural processes on Earth
27
; however, this compensa-
tion is inappropriate in microgravity, which can lead to vertical and
torsional ocular misalignment. This asymmetry (as manifest in ocular
misalignment) has also been associated with increased susceptibility
to space motion sickness (SMS)
25
. Ocular alignment was assessed in
the Inspiration4 crew, as a proximal measure of otolith asymmetry,
during the pre-flight and post-flight phases using a computerized test
that measured vertical (vertical alignment nulling (VAN)) and torsional
(torsional alignment nulling (TAN)) ocular misalignment. VAN and
TAN data collected on the Inspiration4 crew showed no consistent and
systematic effects of spaceflight from pre-flight to post-flight. VAN,
however, exhibited different patterns between astronauts who expe-
rienced SMS in-flight compared to those who did not (Fig.4). Two of
the four Inspiration4 crew (50%) experienced SMS, which is consistent
with earlier reports that 50–67% of astronauts experience SMS during
short-duration spaceflight
28,29
. Astronauts who did not experience SMS
(Fig.4a,c) exhibited consistent vertical misalignment both pre-flight
and post-flight, and that misalignment was different after the flight
than before the flight. This is presumably because post-flight testing
reflects the in-flight adaptive state, and that 0g-adapted state should,
in general, be different from the 1g state (P values < 0.001; Supple-
mentary Table4 and Extended Data Fig.6). A statistical evaluation of
the proposed interpretation of SMS susceptibility was developed to
validate these observations (Supplementary Information).
Cardiovascular responses to spaceflight
While some wearable devices have previously flown in other spaceflight
missions, crew of the Inspiration4 mission used Apple Watches, which
feature a rich set of biometrics that can be collected on astronauts and
have the potential to be useful in future missions. Astronaut cardiovas-
cular physiology was measured with the Series 6 Apple Watch, which
astronauts donned on FD2 and wore for an average of 1.3 ± 0.1 days
in-flight (Extended Data Fig.1). Significant changes across mission
phases were observed for crew heart rate (Extended Data Fig.7a,e)
and heart rate variability (HRV; Fig.5d and Extended Data Fig.7b,f),
and differential heart rate changes between astronauts were also
observed (F = 9.46, P < 0.0001). Studies of heart rate in spaceflight
have yielded mixed findings30, and relative to pre-flight, only C004
exhibited decreased heart rate (Supplementary Table5), as well as
increased HRV (Fig.5d). These cardiovascular changes in C004 were
accompanied by lower blood oxygen saturation in-flight (Extended
Data Fig.7c,g), yet post-flight measures of cardiovascular function
did not differ from baseline (pre-flight) upon return to Earth. Consist-
ent with earlier studies
31
, increased heart rate post-flight, relative to
pre-flight, was observed for two astronauts, C001 and C002; C001 also
exhibited elevated blood oxygen saturation levels post-flight. Further
-
more, the crew exhibited substantially lower overall activity in-flight
relative to pre-flight (F = 6.65, P < 0.0001), which was accompanied by
reduced active energy expenditure (Extended Data Fig.7d,h; F = 9.29,
P = 0.0001); this reduced energy expenditure was driven by C001.
Some of the effects of spaceflight on astronaut physiology and
behaviour can be attributed to the spacecraft environment32. The
cabin environment was measured via sensors in the spacecraft, while
sound pressure levels were measured using the Apple Watch. Environ-
mental variables fluctuated over time in-flight (Extended Data Fig.8
and Supplementary Table5). The Inspiration4 crew were confined to
the Dragon capsule, which has a volume of 9.3 m3, and were free to
move about the cabin. The Dragon cabin environment is nominally
controlled to 14.7 psi and 21% O
2
, in-flight O
2
partial pressures aver-
aged 3.1 psia (range = 3.0–3.3 psia; equivalent to 20.4–22.4%) and
CO
2
averaged 0.8 mmHg (range = 0.4–2.0 mmHg). Temperature and
humidity are controlled to maintain a comfortable short-sleeve envi-
ronment; the crew had the capability to adjust the temperature, which
averaged 25.5 °C (range = 21.8–27.9 °C) in-flight. Relative humidity
Pre 1Pre 2Post 1Post 2
–4
–2
0
2
4
Misalignment (º)
Pre 1Pre 2Post 1Post 2
–4
–2
0
2
4
Misalignment (º)
Pre 1Pre 2Post 1Post 2
–4
–2
0
2
4
Misalignment (º)
Pre 1Pre 2Post 1Post 2
–4
–2
0
2
4
Misalignment (º)
ab
c
d
Fig. 4 | Ocular misalignment before and after short-duration spaceflight.
a–d, The respo nse of the neurove stibular system t o short-duration sp aceflig ht
was indexed by oc ular misalignm ent, as a proximal me asure of otolith
asymme try. The degree o f vertical ocul ar misalignme nt (VAN) is shown for
each of the n = 4 as tronauts as follow s: C001 (a), C002* (b), C003 (c), C004* (d).
An aster isk denotes as tronauts who re ported SMS in -flight; in th ese astronau ts
(C002 and C004), VAN scores we re notsignific antly differen t post-flight
relative to pre-f light. E ach box represen ts one test se ssion (n = 2 pre-f light and
n = 2 post-fligh t, for each astrona ut), in which 11 VAN trials were p erformed.
The horiz ontal bar in each b ox represent s the median of that d ataset, the b ox
encompas ses the cent ral 50% of the data set and the whis kers indicate the
minimum and ma ximum values th at are not outliers (out liers, which are mor e
than three sc aled median ab solute deviat ions from the me dian, are indicate d
by circles). Two-sample two-tailed t-tests wer e performed for e ach astronaut
individually to determine consistency of pre-flight and post-flight measures,
and significant differences (indicating spaceflight adaptation) between
pre-flight and post-flight measures.
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1160 | Nature | Vol 632 | 29 August 2024
Article
could range between 25% and 75% (typically around 50%) and averaged
29.9% (range = 27.3–52.3%). The Dragon environmental conditions were
equivalent to those on the ISS, with O
2
ranging from 2.8 psia to 3.0 psia,
temperature ranging from 18 °C to 25 °C, relative humidity of 25–75%
and a cabin pressure ranging from 3.8 psia to 14.9 psia. Aside from one
period with high sound pressure levels in three astronauts post-flight,
sound pressure levels were similar across mission phases; of note, the
spacecraft produced around 50 dBA of background noise. Noise expo-
sure remained below the occupational 8 h exposure limit of 80 dBA
for all but one data point (Extended Data Fig.8e,g). In-flight, three of
the four astronauts exhibited a significant and positive association
between CO
2
levels and higher HRV (Fig.5f); however, other spacecraft
environmental factors, including cabin pressure and temperature, did
not exhibit consistent relationships with HRV.
The Inspiration4 crew’s neurobehavioural functions
Astronaut neurocognitive functioning and behavioural health are inte-
gral to the success of spaceflight missions. Astronauts performed the
ten cognitive tests of NASA’s Cognition battery
33
multiple times during
each mission phase (Fig.5a–c and Extended Data Fig.1). Across cogni-
tive domains and asconsistent with earlier work
34
, astronaut cognitive
performance was largely unaffected by short-duration spaceflight (Sup-
plementary Table6). Astronauts were, however, significantly slower
on four cognition tests, and on three of them (psychomotor vigilance
test, digit–symbol substitution task and motor praxis task assessing
sustained attention, visual search and working memory and sensori-
motor speed, respectively), astronauts were also less accurate (albeit
statistically significantly so for the motor praxis task only), suggesting
*
**
**
**
*
*
****
*
C001 C003C002 C004
**
*
*
*
**
*
Accuracy Speed Post- versus pre-ight In- versus pre-ight
a
Cognition performance:
change in-ight relative to pre-ight
bc
Alertness and mood survey:
changes relative to pre-ight
d
Heart rate variability (ms)
e
CO2 (mmHg)
f
Heart rate variability (ms)
*
FD1 FD2 FD3
–3 –2 –1 0123
Motor praxis
VOLT accuracy
F2B speed
F2B accuracy
AM speed
AM accuracy
LOT speed
LOT accuracy
ERT speed
ERT accuracy
MRT speed
MRT accuracy
DSST speed
DSST accuracy
BART speed
BART risk taking
PVT speed
PVT accuracy
ALL speed
ALL accuracy
z-score
–5 –3 –1
135
Sleep quality
High workload
Sleepiness
Unhappiness
Sickness
Physical
exhaustion
Stress
Depression
Boredom
Monotony
Points on 11-point scale
0
20
40
60
80
100
120
140
Pre-ight In-ight Post-ight
0
0.5
1.0
1.5
2.0
2.5
00:00
12:00
00:00
12:00
00:00
12:00
00:00
0
20
40
60
80
100
120
0.50 0.75 1.00 1.25 1.50 1.75
2.00
–3 –2 –1 0123
z-score
Accuracy Speed
Cognition performance:
change post-ight relative to pre-ight
Time
CO2 (mmHg)
C001 C003C002 C004
Motor praxis
VOLT accuracy
F2B speed
F2B accuracy
AM speed
AM accuracy
LOT speed
LOT accuracy
ERT speed
ERT accuracy
MRT speed
MRT accuracy
DSST speed
DSST accuracy
BART speed
BART risk taking
PVT speed
PVT accuracy
ALL speed
ALL accuracy
Fig. 5 | Behavioural and physiological responses to short-duration
spaceflight. a,b, The s tandardized di fference in acc uracy (grey) and sp eed
(green) of a stronaut (n = 4) cognit ive performanc e on the ten assays o f the
cognition test battery (n = 26 admini strations) and unad justed 95% conf idence
interval s. Response s peed and accur acy metrics w ere standardize d (z-scored)
before analysis to allow for comparison among cognitive domains. a, Difference
in cogniti on accuracy and s peed in-f light relative to pre -flight. b, Dif ference in
cogniti on accuracy and sp eed post-fli ght relative to pre-f light. c, Chan ge in
astronaut r atings of their b ehavioural st ate in-flig ht (blue) and post-fli ght
(orange) relative to pre-f light and un adjusted 95% con fidence in tervals.
Astronau ts reporte d on their behavi oural state usi ng 11-point Likert s cales
using the ale rtness and m ood survey50. For a, b and c, diffe rences bet ween
mission phases were tested using mixed-effect models contrasting in-flight
and post-flight relative to pre-flight; P values were c orrected for mu ltiple
comparisons using the false discovery rate method51, and adjusted signif icant
associa tions are denote d as: *P < 0.05; **P < 0.01; ** **P < 0.0001. d, Average
HRV, a measure of parasy mpathetic re gulation of card iac function , across 1 h
measurem ent periods (n = 1 27). HRV estima tes were derived f rom heart per iod
data colle cted via the Ap ple Watch using the s .d. of RR inter vals. Signif icant
changes in H RV (F = 5.64, P = 0.0046) and hear t rate (F = 37.10, P < 0.0001) were
observe d in the Inspirati on4 crew across mi ssion phases . e, One-minute
averages of spa cecraft CO2 levels . NASA’s current 1 h standa rd restrict s CO2
levels to less t han 3 mmHg. f, Relatio nship betwee n 1 h average CO2 levels in
the spacec raft and HRV for each a stronaut in-f light (n = 44). AM, abst ract
matching ; BART, balloon analogue r isk test; DSST, digit–symb ol substitut ion
task; ERT, emotion r ecognition t est; F2B, frac tal 2-back; LOT, line orien tation
test; MP, motor praxis t ask; MRT, matrix rea soning test; PV T, psychomotor
vigilanc e test; VOLT, visual object lea rning test.
Content courtesy of Springer Nature, terms of use apply. Rights reserved

Nature | Vol 632 | 29 August 2024 | 1161
lower cognitive efficiency (Fig.5a and Supplementary Note3). These
cognitive deficits were partially driven by one astronaut (C002), who
exhibited a substantial performance deficit early in-flight (Extended
Data Fig.9). Except for the digit–symbol substitution task, cognitive
performance post-flight did not differ from performance pre-flight
(Fig.5b and Supplementary Table6).
Astronauts also completed an alertness and mood survey (AMS)
before performing each Cognition battery. Nightly sleep duration of
6.7 ± 0.7 h in-flight was reported, which is modestly longer than previ-
ous studies
35,36
. Astronauts reported a moderate level of stress and high
workload, similar to astronauts completing 6-month ISS missions
36
,
but reported no other alertness or mood symptoms (Extended Data
Fig.10). In-flight mood and alertness did not differ from pre-flight,
but astronauts reported being significantly happier and less bored
post-flight(Fig.5c and Supplementary Table7). Although astronaut
reports of adverse behavioural states were overall similar across mis-
sion phases, there was substantial variability both within and between
astronauts in their behavioural responses to spaceflight (Extended Data
Fig.10). Furthermore, one astronaut (C003) exhibited a considerable
increase in physical exhaustion upon return to Earth; overall, these
behavioural responses to short-duration spaceflight are consistent
with a previous report of astronauts in long-duration (6-month mis-
sions) spaceflight36.
Discussion
To understand the effects of short-duration spaceflight on the human
body for the all-civilian spaceflight crew, this study performed a suite
of experiments and collected a wide range of biospecimens before,
during and after a 3-day orbital mission. This multidimensional battery
included blood, stool, urine, biopsy and saliva samples, ultrasound
measurements of the eye, jugular vein and bladder, cognitive and
sensorimotor tests, surveys and physiological data collected with an
Apple smartwatch. These data showed some of the same signatures
of long-duration spaceflight, such as inflammatory response, DNA
damage response gene expression (and proteins), telomere elonga-
tion and immune signalling changes (Figs.1 and 2), and demonstrated
that such phenotypes can also be observed in the earliest phases of
spaceflight and across a shorter mission time frame. Moreover, this
mission also enabled new biomedical metrics for spaceflight, such as
RNA methylation, single-nucleus chromatin, single-cell expression
metrics and spatial transcriptomics. Overall, this work demonstrated
that a diverse civilian crew can conduct scientific experiments, process
samples and significantly contribute to spaceflight research with mini-
mal risk. Although two astronauts presented with SMS, most metrics
(for example, IJV size, heart rate, complete blood count metrics, gene
expression and cytokines) were either stable or quickly reverted to
pre-flight levels (baseline) after landing on Earth.
The development of diagnostic, point-of-care devices that can
detect and quantify multiple biomarkers is critical to monitor astro-
nauts’ healthcare for future spaceflight missions and to help guide
medical interventions. This mission showed that a VFI can be used
to detect antigens and, more generally, protein markers
37–39
. Due to
flight certification constraints required for all technologies used in
spaceflight, the desiccant usually placed in the packaging kit to avoid
high humidity exposure during long-term storage had to be removed,
and has been identified as the main cause for the alteration of the assay
efficiency in-flight. For future missions, reagent and system stability
studies will have to determine optimal storage conditions without
the use of hygroscopic compounds. Despite this obstacle, the 0g-VFI
demonstrated its robustness of operation in space, and the simplicity
of its user interface allowed for its use by untrained non-scientists,
supporting the feasibility of such point-of-care diagnostic systems
for several applications on additional specimen types, including for
deep-space missions.
The Inspiration4 ultrasound imaging experiment pursued three
research objectives, which were to examine (1) urinary bladder func-
tion in microgravity, (2) IJV flow with and without intervention by
inspiratory resistance and (3) microgravity-associated changes in ocu-
lar morphology. The choice of targets was motivated by high-priority
concerns and risks reported over the years of ISS missions. For exam-
ple, flow anomalies in the IJV (for example, severe stasis, flow rever-
sal) frequently develop in ISS crew members in the later stages of
long-duration spaceflight20–22; however, such alterations in cardiovas-
cular function have been less studied in the earlier days of spaceflight
when precursors to cardiovascular risks may begin to emerge
23
. In the
Inspiration4 mission, IJV flow anomalies were not observed in any of the
four astronauts, suggesting that flow anomalies develop later in-flight.
The lack of IJV flow anomalies also diverge from Earth-based simula-
tions of microgravity (head-down tilt), which demonstrate IJV and
other vascular alterations after five days of exposure
23
. If corroborated
by future studies in short-duration spaceflight, this finding may further
our understanding of the mechanisms and progression pattern of
flow degradation in the left IJV during sustained microgravity. Inspira-
tory resistance reduced right IJV CSA by an average of 36% pre-flight
(supine) and 29% in-flight but did not reach statistical significance in
this small cohort of astronauts. This trend suggests facilitated IJV drain-
age due to resistance breathing, and the experiment demonstrated
a simplified in-flight screening method, with resistance breathing as
an option to correct anomalous IJV flow. Overall, these findings bode
well for the cardiovascular safety profile of short-duration missions,
although future studies that address other anatomical targets are
needed, as the effects of spaceflight are not uniform throughout the
cardiovascular system23,24. A better understanding of the cardiovas-
cular risks could alleviate some of the spaceflight health concerns
for private citizens with diverse health backgrounds and medical
histories, although notably, no health issues were observed in the
Inspiration4 crew.
The Inspiration4 mission undertook ultrasound imaging-based
human research in full crew autonomy, with minimal pre-flight
familiarization and reliance on experiment-specific just-in-time
( JIT) instruction. Probing the potential limitations of miniaturized
ultrasound technology combined with the rapid deployment and
complete crew autonomy was an inseparable part of the experiment.
This autonomy is in stark contrast to the ISS experience, where all
imaging sessions are conducted with a traditional device and in
real-time interaction with experts in the mission control centre. The
anatomical and technical quality of the images, expressed as overall
success scores, appeared inversely related to the complexity of the
autonomous procedures. Bladder imaging (the simplest procedure)
and IJV imaging (intermediate difficulty and complexity) each had
similar scores, well above the usability threshold. Conversely, the
ocular imaging procedure (most intricate), which required precise
gaze control and accurate probe manipulation by real-time visual
feedback, did not produce image sets of sufficient quality to derive the
intended measures, such as globe axial length or optic nerve sheath
diameter. In this study, all but the most intricate procedures could
be successfully performed by minimally trained users with the aid of
appropriate JIT materials. Based on these findings, as well as those
acquired during similar applications on the ISS, ocular imaging with
JIT instruction in future missions should involve a dedicated ultra-
sound operator; however, other exams can be reliably performed
in self-scanning, autonomous mode, which represents a significant
medical and research capability insituations with degraded communi-
cations (for example, high latency, loss of communication). Payloads
consisting of a miniaturized imaging system with an intuitive interface
can enable future experiments featuring short lead and training times,
rapid deployment, flexible schedules and data collection autonomy,
which will enable scientific research opportunities even on the most
constrained of spaceflight missions.
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1162 | Nature | Vol 632 | 29 August 2024
Article
Studying ocular misalignment and otolith symmetry in short-
duration spaceflight is not without caveats. First, the Inspiration4
results (Fig.4) are based on comparing pre-flight and post-flight tests
and relating that comparison to in-flight SMS. The ultimate goal is to
use pre-flight tests alone to predict in-flight susceptibility, which is
planned for future flights. The incidence of SMS was 50% in the Inspi-
ration4 mission, which is consistent with the reported incidence in
short-duration spaceflight29. Second, there is no relation between
motion sickness susceptibility in parabolic flight and susceptibility
in orbital flight, yet early work on torsional alignment was performed
in parabolic flight to predict susceptibility in orbital flight
40
. Third, our
results with VAN are promising for SMS prediction, while results with
TAN are not (of note, the original work41 relating SMS to ocular skew
was done with torsion). Finally, SMS has multiple contributing factors
and multiple manifestations that vary between individuals, and thus it
may be unrealistic to think that a single measure will continue to have
high predictive power in a larger population.
Consistent with studies of astronauts and cosmonauts completing
both short- and long-duration spaceflight missions
34–36
, collecting
objective measures of astronaut cardiovascular functions and neu-
rocognitive functioning, as well as subjective measures of sleep and
astronaut behavioural states, is feasible in commercial astronaut crews
throughout short-duration orbital missions. The Inspiration4 crew
provided valid and usable data on cardiovascular physiology, cogni-
tive performance and behavioural states across mission phases that
can translate to the general public
3,42
, which is important as trained
astronauts from international space agencies are not necessarily rep-
resentative of the average individual. The effects of short-duration
spaceflight on Inspiration4 crew cardiovascular physiology and cogni-
tive performance were modest, although there was substantial inter-
individual variability in the response to spaceflight, as previously
observed34,43,44.
Studies of cognitive performance have generally found that astro-
nauts maintain relatively high levels of performance in spaceflight,
although this may be a function of the duration of spaceflight missions,
where performance decrements manifest with longer mission dura-
tions
1,34
. In this study, accuracy on eight of the ten (80%) cognition tests
was unaffected by short-duration spaceflight (Fig.5). There was, how-
ever, more variability in astronaut response speed on neurocognitive
tasks, where slower response speeds were observed on four cognition
tests, a finding consistent with earlier reports of astronaut response
slowing during short-duration spaceflight (that is, less than or equal
to 10 days in spaceflight shuttle missions)45,46.
Although previous studies have not found large cognitive perfor-
mance deficits in spaceflight, this may be due to the timing of neuro-
cognitive testing, which often does not occur on the first day in-flight,
but up to four days in-flight, at which point cognitive deficits may have
dissipated. Furthermore, the observed changes in response speed may,
to some extent, be associated with neurovestibular and sensorimotor
alterations induced by spaceflight26,47. While astronaut sleep dura-
tions less than 6 h on the ISS have been associated with psychomo-
tor slowing, Inspiration4 astronauts averaged 6.7 h of sleep per night
in-flight and thus the contribution of sleep loss to slower response
speeds would be modest if present
36
. Astronauts did not report overtly
negative behavioural states in-flight(for example, depression, stress),
butthey reported more happiness and less boredom post-flight rela-
tive to pre-flight (Fig.5).
Significantly, all data from this study are stored in multiple controlled-
access repositories for easy access, including TrialX, NASA’s Open
Science Data Repository and GeneLab, the SOMA data portal and the
Commercial Spaceflight Data Repository, which facilitates the col-
lection of mission-specific research, medical data and biospecimens
to be stored in a permanent electronic data and tissue repository for
future scientific research. These data also include qualitative survey
data received via mobile apps, DICOM-standard images from portable
ultrasound devices, data from wearables (for example, heart rate, elec-
trocardiogram), biospecimen information, cell processing details
48
and the environmental/mission data from the Crew Dragon capsule
(for example, cabin pressure, temperature and humidity, spacecraft
telemetry), which can help guide exploration-class future missions49.
Finally, the repository contains a visualization dashboard for research-
ers to view summary analytics and access individual observations and
data files, which has been added to TRISH’s enhancing exploration
platforms and analogue definition programme.
Although the Inspiration4 mission was the first all-civilian crew to
complete a short-duration, orbital spaceflight mission while collecting
repeated multidimensional measurements of biological and behav-
ioural function relevant to the challenges of spaceflight, the study is
not without limitations. Although the total sample of n = 4 astronauts
is small, it is not inconsistent with previous studies of astronaut cog-
nitive performance in spaceflight. While data collection spaceflight
is challenging and limited by numerous factors (for example, cost,
limited time and access to astronauts), longitudinal sampling of meas-
ures within and across mission phases can promote statistical power
(Supplementary Note1). This study did not have age- and sex-matched
controls on Earth; however, repeated measures within the Inspira-
tion4 crew across mission phases allow for astronauts to serve as their
own controls (within-subjects design) by using their pre-flight (that is,
baseline) levels as a reference. Future studies, or additional studies with
equivalent design, of civilian astronauts in short-duration spaceflight
with larger sample sizes are needed to confirm the findings or to assign
any possible causal links.
Finally, it is worth noting that the Inspiration4 mission was not
designed to address how the biological and behavioural responses
of the Inspiration4 crew relate to those of professional astronauts or
cosmonauts, or those with career-long exposure to spaceflight. Fur-
thermore, the research on the Inspiration4 mission was not designed
to determine the safety of spaceflight for all civilians, or to recommend
spaceflight for future civilian passengers; the Inspiration4 research
projects were also not tasked with making judgements for future crew
selection or fitness for spaceflight. The selection of astronauts for
spaceflight is exclusive to international space agencies (governmen-
tal or commercial). Nonetheless, the Inspiration4 data, along with
data from other civilian spaceflight missions, may contribute to the
development of reference ranges and pre-flight preparatory tasks (for
example, behavioural testing in confined environments) that can help
guide future crew selection and mission planning.
Conclusions
While broad in its research scope, this study represents only the begin-
ning. Anatomical and physiological variability, small sample size, the
operational complexities of a highly constrained mission and lim-
ited skill management capabilities combined to preclude confident
conclusions on many physiological variables. However, as intended
by the TRISH, enhancing exploration platforms and analog defini-
tion, and SOMA programmes, these Inspiration4 data will serve as
a rich foundation for scaling and enhancing the knowledge base on
early phases of space physiology, and expanding our understanding
of spaceflight-associated effects on human health. Future missions
can also include telemedicine, more autonomous data collection,
next-generation sequencing-based in-flight omics assays and related
diagnostics tools. Excitingly, some of these same astronauts will be
present on future missions and/or contribute to long-term studies of
astronaut health, which will help delineate the short- and long-term
impacts of spaceflight and continue to prepare future astronauts for
their missions.
Finally, it is worth noting that collaboration with government, aca-
demia and the private sector at the same time led to lessons learned
that should be useful to investigators embarking on similar endeavours
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Nature | Vol 632 | 29 August 2024 | 1163
in future civilian spaceflight missions. Specifically, co-ordination
among diverse research teams can be enabled by agile funding entities
(for example, TRISH, SpaceX, philanthropy) and a dedicated project
manager. Also, a single institutional review board (IRB) protocol,
such as that put in place by TRISH,can simplify subject consenting,
while a standardized database provider (TrialX, funded by TRISH) was
critical for data ingestion, cross-institute sharing and standardization
for future cross-mission analyses and use of artificial intelligence
and machine learning approaches. Finally, the consent and release
forms of study participants were envisioned for long-term use, with
datasets managed under the oversight of a data release board, and
for these precious samples to be utilized and characterized for many
years to come.
Online content
Any methods, additional references, Nature Portfolio reporting summa-
ries, source data, extended data, supplementary information, acknowl-
edgements, peer review information, details of author contributions
and competing interests, and statements of data and code availability
are available at https://doi.org/10.1038/s41586-024-07648-x.
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1164 | Nature | Vol 632 | 29 August 2024
Article
1Unit for Experimental Psychiatry, Division of Sleep and Chronobiology, Department of
Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA.
2Department of Physiology, Biophysics and Medicine, Weill Cornell Medicine, New York, NY,
USA. 3The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational
Biomedicine, Weill Cornell Medicine, New York, NY, USA. 4The WorldQuant Initiative for
Quantitative Prediction, Weill Cornell Medicine, New York, NY, USA. 5Center for STEM,
University of Austin, Austin, TX, USA. 6Center for Applied Nanobioscience and Medicine,
College of Medicine-Phoenix, University of Arizona, Phoenix, AZ, USA. 7Department of Basic
Medical Sciences, College of Medicine Phoenix, University of Arizona, Phoenix, AZ, USA.
8Department of Microbiology & Immunology, Vagelos College of Physicians & Surgeons,
Columbia University Irving Medical Center, New York, NY, USA. 9TrialX Inc., New York, NY,
USA. 10KBR, Science & Space, Houston, TX, USA. 11Department of Otolaryngology - Head &
Neck Surgery, The Johns Hopkins University School of Medicine, Baltimore, MD, USA.
12The Translational Genomics Research Institute (TGen), Phoenix, AZ, USA. 13Departments of
Neurology and Neurosurgery, Baylor College of Medicine, Houston, TX, USA. 14Center for
Space Medicine, Baylor College of Medicine, Houston, TX, USA. 15The Translational
Research Institute for Space Health (TRISH), Houston, TX, USA. 16Stanley Center
for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
17Blue Marble Space Institute of Science, Space Biosciences Division, NASA Ames Research
Center, Moffett Field, CA, USA. 18Department of Stem Cell Biology and Regenerative
Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA,
USA. 19Children’s Cancer and Blood Foundation Laboratories, Departments of Pediatrics and
Cell and Developmental Biology, Drukier Institute for Children’s Health, Weill Cornell
Medicine, New York, NY, USA. 20Department of Molecular Biology and Biotechnology,
Center of Systems Biology, Biodiversity and Bioresources, Faculty of Biology and Geology,
Babes-Bolyai University, Cluj-Napoca, Romania. 21Meyer Cancer Center, Weill Cornell
Medicine, New York, NY, USA. 22SpaceX, Hawthorne, CA, USA. 23University of Texas,
Department of Emergency Medicine, Houston, TX, USA. 24Department of Biomedical
Engineering, University of Arizona, Tucson, AZ, USA. 25These authors contributed equally:
Christopher W. Jones, Eliah G. Overbey, Jerome Lacombe. 26These authors jointly
supervised this work: M. Basner, C. E. Mason. ✉e-mail: basner@pennmedicine.upenn.edu;
chm2042@med.cornell.edu
Content courtesy of Springer Nature, terms of use apply. Rights reserved

Methods
Subjects and consent
Four adult non-professional astronauts were selected to participate
in the Inspiration4 mission. All subjects provided written informed
consent to participate in the study, which included the collection and
use of their samples and data in research protocols at Weill Cornell
Medicine,Baylor College of Medicine/TRISH and collaborating insti-
tutions; the study was approved by multiple IRBs and included the
following IRB protocols: Weill Cornell Medicine IRB no. 21-05023569,
WCG-IRB 1309934, Multimodal Evaluation of Spaceflight Participants
Health – SpaceX Inspiration-4 Mission; Baylor College of Medicine/
Translational Research Institute for Space Health IRB no. 1316696,
WCG-IRB 20214456, Commercial Spaceflight Data Repository. Sub-
jects consented to the storage of their de-identified, coded research
data in a secure, password-protected database at SpaceX, Weill Cornell
Medicine,Baylor College of Medicine/TRISH, and the institutions of
study co-investigators. Subjects also consented to the publication of
the results of this research while maintaining their confidentiality.
Multi-omics methods
Datasets generated for multi-omics profiling span nine different bio-
specimen sample types: whole blood, serum, plasma, peripheral blood
mononuclear cells (PBMCs), extracellular vesicles and particles, dried
blood spots, skin biopsies, skin swabs and capsule swabs. These sam-
ples were subject to a spectrum of multi-omic assays, including WGS,
clonal haematopoiesis, direct RNA sequencing, single-nuclei RNA
sequencing, single-nuclei ATAC-seq, single-cell B cell repertoire and
Tcell repertoire V(D)J sequencing, proteomics, metabolomics, cell-free
DNA sequencing, metagenomics and metatranscriptomics. Additional
biomarkers were quantified using a CLIA lab for complete blood count,
comprehensive metabolic panel and cytokine panel. These data types
were generated across ten time points in total: three pre-flight (L − 92,
L − 44, L − 3), three in-flight (FD1, FD2, FD3), one post-flight (R + 1) and
three recovery (R + 45, R + 82, R + 194).
Multi-omic feature counts describe the datasets published in refs. 4,5.
Transcripts detected in whole blood RNA sequencing were assembled
using StringTie
52
. m6A modifications were quantified using m6Anet
53
with a probability threshold of 0.9. Genes detected from skin biopsy
had a count of at least five from the normalized count matrix from
the NanoString GeoMx NGS DnD Pipeline. The number of ATAC-seq
peaks and genes detected from the single-nuclei data was quantified
using the cellranger-arc(v2.0.0) count algorithm from 10x Genomics.
We followed the 10x single-cell multi-ome analysis pipeline as previ-
ously reported
48
and adapted for this data as described here.Shotgun
metagenomic and metatranscriptomic sequencing reads were dedu-
plicated, filtered for human sequences via alignment to the human
reference genome (Hg38) and trimmed for adaptor contamination.
Fungal, viral and bacterial taxonomic composition was computed via
masked read alignment to a database containing all complete genomes
in RefSeq using kraken2 (confidence = 0.2)54. For assembly-based
approaches, quality-controlled (unmasked) reads were assembled
with MetaSPAdes55. Bins were generated with MetaBAT2 (ref. 56), and
Open-Reading-Frames were identified with bakta
57
and clustered into
a non-redundant gene catalogue with mmseqs2 (ref. 58). Assembled
viral genomes were identified among contigs with CheckV
59
. Additional
details can be found in ref. 10.
Virome methods
Highly multiplexed, epitope-resolved IgG reactivity analysis across the
human virome was performed on reconstituted dried blood samples
using DNA-barcoded peptide (PepSeq) assays. The HV2 library has been
previously described15 and consists of 15,000 30mer peptides covering
80 viral species and selected based on earlier evidence of reactivity in
other cohorts. PepSeq libraries were synthesized and used to profile
IgG binding, as previously described
16,17
. Briefly, DNA-barcoded peptide
libraries were generated using bulk invitro enzymatic reactions, start-
ing with the PCR amplification of oligonucleotide templates and their
transcription to generate mRNA. The product was ligated to a hairpin
oligonucleotide adaptor bearing a puromycin molecule tethered by a
polyethylene glycol spacer and used as a template in an invitro transla-
tion reaction. Finally, a reverse transcription reaction, primed by the
adaptor hairpin, was used to generate cDNA, and the original mRNA
was removed using RNAse. To perform serological assays, 0.1 pmol of
the resulting DNA-barcoded peptide library (5 µl) was added to 5 µl of
neat, reconstituted blood spot solution and incubated overnight. The
binding reaction was applied to prewashed protein G-bearing beads,
washed, eluted and indexed using barcoded DNA oligos. Following PCR
cleanup, products were pooled, quantified and sequenced using an
Illumina NextSeq instrument yielding a depth of more than 900,000
reads per sample.
Z-score enrichment values for each peptide in each sample were
generated from raw sequence reads in a two-step process using PepSIRF
v.1.4.0, an open-source software package for the analysis of highly mul-
tiplexed serology60 data. First, reads were demultiplexed and mapped to
members of the HV2 library using the demux module to generate inte-
ger count values for each sample peptide. Next, peptides with similar
abundances in the buffer-only negative control samples were grouped
into bins and used to generate z-scores for each data point, representing
the distance (in standard deviations) of each data point from its unen-
riched distribution mean. log
2
-transformed offset-adjusted z-scores
(log
2
(z + 8) − 3) were used for downstream analyses. At an adjusted
z-score threshold of 0.75, we detected 45 virus species (Supplementary
Table3) for which at least 1 peptide was reactive in at least 1 sample.
To identify viral events, we applied peptide set enrichment analysis to
all pairs of consecutive samples as previously described19, and used a
P value threshold of 1 × 10−5.
Membrane printing
0g-VFI membranes were fabricated using nitrocellulose membrane
sheets (9 × 8 cm), which were prepared into target membranes on a
bench-top CO2 laser cutter at 1% power, 100% speed and 3 mm depth.
These target membranes have circular discs (6 mm diameter) cut into
them in a 6 × 5 design with fiducial markers for targeting the dispens-
ing locations during microarray printing. Control antibody reagent
(mouse IgG), rabbit anti-human CRP (11250-R106, SinoBiological) and
goat anti-human IgM (109-005-129, Jackson ImmunoResearch) capture
antibodies were diluted to working concentrations (0.5 mg ml
−1
) using
filtered 1× PBS. In a clean-room environment, a Nano-Plotter NP2.1 was
used for non-contact piezoelectric microarray dispensing of capture
antibodies onto the circular discs of a target nitrocellulose membrane
(0.2 µm pore size). To prevent evaporation of reagents during printing,
an ambient humidity of 55% was maintained using a humidifier. The
nozzle hydrostatic pressure was set with the water level of the pressure
compensation vessel at the pipette tip height. Spot-front-end software
was utilized to co-ordinate a spotting plan for use in the Nano-Plotter
Controller software (NPC16) to dispense a nine-spot pattern (350 µm
period) of the antibody microarray onto the centre of each circular
disc. A 384-well microplate was used to aspirate the antibodies during
dispensing. The test reagents were dispensed in 20 droplets per spot
at their respective working concentrations at the top two rows (three
spots per row for each reagent) of the nine-spot pattern. Ten droplets
of the control reagent were dispensed at the bottom three spots of the
nine-spot pattern. The immunoassay membranes were then stored in
aluminium pouches with silica bead desiccant for later use.
Preparation of conjugation pad
Conjugate pads were fabricated using polyester fibre with binder
(Grade 6614, Ahlstrom Munksjo), which were cut into circular discs
(10.5 mm) on a bench-top CO2 laser cutter. Gold nanoparticles
Content courtesy of Springer Nature, terms of use apply. Rights reserved

Article
conjugated anti-rabbit IgG (kindly provided by DrAuCoin at the Uni-
versity of Nevada-Reno) were incubated with mouse anti-human CRP
(11250-R106, SinoBiological) and IgM (MA5-14729, ThermoFisher) for
10 min. The conjugate mix was then dispensed and dried on the con-
jugate pads at 25 °C for 2 h.
Assembly of vertical flow apparatus
The 0g-VFI consists of a stacked multilayer of pads and membranes
assembled in 3D-printed plastic caps and capsules (Extended Data
Fig.3a). The sandwich immunoassay on the 0g-VFI is performed at the
multiplexed sensing nitrocellulose membrane, which contains the nine
immunoreaction spots. Above the 0g-VFI membrane are functional
paper layers, which decrease flow surface area to achieve uniform verti-
cal flow (flow-directing pad), decrease flow rate to increase intensity
(retarding pad), generate the assay colour (conjugation pad) and col-
lect plasma samples (sample pad). These layers are all contained in
a 3D-printed pad holder, placed in a membrane housing that allows
contact between the 0g-VFI membrane and cotton absorbing pads. The
user-friendly device also contains capsules within which are wet pads
(assay or washing buffer) that trigger fluid transfer once screwed to the
membrane housing and placed in contact with the absorbing pads. In
total, the 0g-VFI contains four modules consisting of the membrane
housing protected with a cap, assay buffer capsule, washing buffer
capsule and magnifier cap, all of which fit in small zip bags (Extended
Data Fig.3b). Overall, the assay takes up to 20 min due to its simple
assembly sequence using the screw cap and reservoir design of the
0g-VFI platform (Extended Data Fig.3c). A user manual and instruction
video were made to detail the workflow procedure to SpaceX personnel
and Inspiration4 crew. The user manual was integrated in the 0g-VFI
kit and was thus available in-flight. The Inspiration4 crew were trained
by SpaceX personnel and were instructed to work in pairs for sample
collection and to self-perform the 0g-VFI procedure.
All plastic components of the 0g-VFI were designed in SolidWorks
and 3D-printed in house at the Center for Applied NanoBioscience and
Medicine using a Surgical Guide Resin material from Formlabs. Using
the Formlabs 3B stereolithography printer, the 0g-VFI was printed and
then washed for 20 min in 99% isopropyl alcohol to clear loose and
uncured resin. Curing was then performed under intense ultraviolet
light at 70 °C for 30 min, followed by trimming of the support scaffolds.
First, the different pad layers were stacked inside of the pad holder as
follows (ordered top to bottom): sample pad (made from chopped
glass with binder (Grade 8950, Ahlstrom Munksjo)), polyethersulfone
filter, conjugate pad, retarding and flow-directing pads both made
of thin glass fibres (Grade 8950, Ahlstrom Munksjo). All layers were
assembled with double-sided, medical-grade pressure-sensitive adhe-
sive (ARcare 90106NB). Second, a 3.5-cm-diameter cotton pad (Grade
320, Ahlstrom Munksjo) was positioned in the membrane housing
with a 6-mm-diameter cotton pad (Grade 222, Ahlstrom Munksjo) on
top, both acting as absorbent pads. The 0g-VFI printed membrane
was then placed on top of the absorbing pads and 400 µl of blocking
buffer (10mM borate buffer (pH 8) with 2.5% Triton X-100, 1% bovine
serum albumin, 0.2% polyvinylpyrrolidone-40 and 0.1% sucrose filtered
through a 0.2 µm polyethersulfone filter membrane) was pipetted
on it and incubated for 30 min. Then, the pad holder was positioned
inside the housing membrane and the device was tightly closed with
a lid. Separately, wet pads saturated with a TritonX100 (0.1%), albu-
min (0.5%), PBS (0.1 M) solution and a 50 mM carbonate/bicarbonate
buffer (washing buffer) were placed in the assay buffer pad capsule
and the washing buffer pad capsule, respectively. Plasma was sepa
-
rated from fingerstick-collected whole blood using a modified A-PON
plasma separator cartridge (GattaCo). As drawing blood using con-
ventional methods is difficult in spaceflight for novice astronauts,
whole blood was collected via fingerstick using a Food and Drug
Administration-approved lancet to promote successful sample col-
lection by the Inspiration4 crew.
Ultrasound methods
All imaging was performed with a Butterfly iQ+ handheld ultrasound
system (Butterfly Network) with the Butterfly mobile app running on
iPhone12 (Apple, Inc.). The device was used in approved preset modes
for each procedure (ophthalmic, vascular and bladder). Eighty-nine
imaging instances (multiframe cine of varied length) were collected
pre-flight and 108 (7.68 GB) images were collected in-flight. All in-flight
data (27 instances per astronaut on average; range = 18–32) were stored
on the local device (iPhone 12) until secure transfer to a DICOM (Digital
Imaging and Communications in Medicine)server upon return to Earth.
Image analysis was performed in Osirix MD DICOM software (Pixmeo).
Of the n = 106 in-flight imaging instances analysed, n = 73 were related
to IJV, n = 14 to urinary bladder and n = 19 were ophthalmic.
All astronauts were self-scanning operators. All pre-flight crew inter-
actions (experiment briefing, familiarization and training, and baseline
data collection) were conducted by SpaceX personnel using limited
time allocations. Using a previously untested approach to experiment
execution, the investigative team relied on experiment-specific JIT
instructions to communicate both conceptual and procedural infor-
mation to SpaceX personnel (for baseline data collection and famil-
iarization) and to the Inspiration4 crew (for autonomous in-flight data
collection). In-flight imaging data were obtained via self-scanning and
used potable water as a coupling medium in lieu of ultrasound gel.
Bladder scans were collected both pre- and post-void, whenever pos-
sible. IJV scans were performed with and without inspiratory resistance
generated by an ITD (ResQGARD ITD7, Zoll).
Given the risks to data quality posed by limitations of imaging exper-
tise, and to evaluate the effectiveness of the JIT tools, a formalized data
quality assessment was conducted in the initial phase of data analysis.
This included the scoring of each imaging instance for anatomical accu-
racy and technical quality on a scale of 0–3 (0 = no useful information,
3 = clinical quality). Anatomical accuracy criteria included whether the
target was clearly and contiguously visible, along with essential ana-
tomical landmarks; technical quality criteria included elements such
as image clarity, gain, acoustical interference, artefact and shadowing.
An overall success score was derived as the mean of these two scores,
with a usability threshold set at 2.0. This quality filter served to reject
anatomically inaccurate or technically flawed images. To determine
whether the success of imaging instances varied by anatomical target,
a one-way ANOVA tested for in-flight differences in imaging success
scores among anatomical targets (that is, bladder, IJV and eye); post hoc
pairwise comparisons between anatomical targets were conducted via
Tukey’s honest significant difference. To evaluate the effect of imped
-
ance breathing on IJV CSA, a series of paired, two-tailed Student’s t-tests
were conducted; differences between normal and impedance breathing
were evaluated by averaging IJV CSA for each condition within each
mission phase (that is, pre-flight and in-flight).
Ocular misalignment methods
The otolith organs of the vestibular system transduce linear accelera-
tion and gravity. The sense organs consist of a mass of calcium carbon-
ate crystals (otoconia) that overlie a membrane that is innervated with
hair cells. Motion of the crystals relative to the hair cells bends the
hair cells, and this bending modifies their firing rates and so provides
information on linear acceleration to the central vestibular system.
While generally symmetric, there is reason to believe that there are
slight asymmetries between the otolith organs on the two sides of
the head, in otoconial mass or synaptic sensitivity. This asymmetry
is compensated by central neural processes27, but this compensa-
tion becomes inappropriate in gravity fields other than 1g, leading to
changes in vertical and torsional ocular alignment
61,62
. In particular,
the magnitude of torsional misalignment in altered g levels has been
associated with susceptibility to SMS40,41,63. G-dependent changes in
vertical alignment have also been demonstrated in parabolic flight
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and laboratory studies
62,64
. Data on SMS in-flight were obtained via
self-report.
A perceptual-nulling technique was used to measure misalignment
between the eyes (skew) in both vertical and torsional directions
65
. For
these tests, the subject views a red line and a blue line on the touch-
screen of a tablet computer, through colour-matched red and blue
filters, one over each eye. This provides independent images to each
eye. Since the test is performed in darkness, there is no visual informa-
tion that is seen by both eyes together, and hence there are no visual
cues to align the eyes (which would fuse the images on the two retinas).
One line remains fixed on the screen, while the other line is positioned
by the subject, either vertically or torsionally. The subject’s goal is to
adjust one line until it appears to be aligned with the other, stationary,
line (that is, to null any apparent vertical or rotational offset between
the lines). The final amount by which the lines are separated from one
another vertically or rotated relative to one another provides a meas-
ure of vertical or torsional ocular misalignment, respectively, which
produces measures of VAN and TAN. Astronauts completed VAN and
TAN measures twice pre-flight and twice post-flight, where each session
consisted of 11 VAN and 11 TAN trials. There was no in-flight testing.
Statistical testing to evaluate associations of torsional (TAN) and ver-
tical (VAN) ocular misalignment with SMS were carried out via a series
of two-sample t-tests within each astronaut individually to provide
information on the following: (1) whether the two pre-flight datasets are
the same or different from each other, (2) whether the two post-flight
datasets are the same or different from each other and (3) whether the
(grouped) pre-flight data are different from the (grouped) post-flight
data. The t-tests were performed after removing outliers, which were
defined as values more than three scaled median absolute deviations
from the median, where median absolute deviation is a measure of the
deviation of the values from the median (analogous to the standard
deviation for data from normal distributions) and can be reduced to a
sequential decision tree for prediction of individual SMS susceptibility
(Supplementary Note2). There are several reasons for this individual
testing as opposed to a pooled analysis across subjects. First, the high
variability across subjects (typical of many neurovestibular assess-
ments), combined with the small subject pool, makes it unlikely that
there would be sufficient statistical power in a pooled analysis. Second,
individual testing permits a stepwise approach in which a series of tests
can lead to a predictive metric. Finally, SMS is notoriously idiosyncratic,
and spaceflight measures are subject to many confounds, which sup-
ports a focused longitudinal examination.
Cardiovascular function
The Apple Watch Series 6 was used to objectively measure cardiovascu-
lar function, which was indexed by blood oxygen saturation levels, heart
rate and HRV, as well as activity and energy consumption. The Apple
Watch also measured sound pressure levels. The crew donned the Apple
Watch for selected periods in all three phases of the mission, including
pre-flight, in-flight and post-flight (Extended Data Fig.1). The crew
donned the Apple Watch from L − 22 to L − 20 and had an average wear
time of 2.7 ± 0.3 (s.d.) days (range = 2.4–3.0 days), in-flight from FD2
to FD3 with an average wear time of 1.2 ± 0.1 (s.d.) days (range = 1.2–1.4
days) and post-flight from R + 0 to R + 10 with an average wear time of
5.8 ± 3.4 (s.d.) days (range = 2.2–9.1 days).
Neurocognitive functioning
Neurocognitive functioning was assessed using NASA’s cognition test
battery
33
, which consists of 10 brief cognitive tests that probe a range of
neurocognitive domains relevant to the challenges of spaceflight and
includes the psychomotor vigilance test, matrix reasoning test, abstract
matching, line orientation test, visual object learning test, motor praxis
task, emotion recognition task, digit–symbol substitution task, fractal
2-back and balloon analogue risk test. Developed for high-performing
astronauts, cognition has been deployed in long-duration spaceflight
studies
1
, as well as in ground-based studies that simulate aspects of
spaceflight in analogue environments
66–68
. Cognition was adminis-
tered with the Joggle Research App (Pulsar Informatics, Inc.) on an
iPad Mini Series 4 twice pre-flight (L − 47 and L − 22), up to three times
in-flight and twice post-flight (R + 0 and R + 1). Cognition data were
corrected for practice and stimulus set effects after applying another
correction for the fact that tests were performed on an iPad instead of
a laptop69,70. After these corrections, the expectation is that test results
do not change with repeated administration.
Alertness and mood survey
Before performing each cognition test battery, astronauts reported
on their behavioural state using the AMS
50
via the Qualtrics applica-
tion on the Apple iPad Mini Series 4. Developed for astronauts, the
18-item AMS measures behavioural responses to the challenges of
both long- and short-duration spaceflight. Fourteen of the 18 AMS
items were surveyed in the Inspiration4 crew to reduce time burden,
and the four items that were removed had significant overlap with
other AMS items. Ten AMS items (monotony, boredom, depression,
stress, physical exhaustion, sickness, unhappiness, sleepiness, work-
load and sleep quality) prompted astronauts to rate each item using
11-point Likert scales (range = 0–10). The remaining AMS items assessed
astronaut sleep timing and duration, crew conflict and medication use
(stimulant/depressant).
Statistical analysis of cognition, AMS and Apple watch data
All statistical analyses were conducted using SAS v.9.4. Before statistical
analysis of cognitive performance, all cognition data were standard-
ized via z-scoring to facilitate comparisons across the different neu-
rocognitive domains, as well as to allow the effects to be interpreted
as effect sizes. Mixed-effects models using PROC MIXED with a ran-
dom subject intercept were used to test astronaut behavioural and
physiological responses to short-duration spaceflight across mission
phases. Repeated measures were nested within subjects and differences
between responses during both the in-flight and post-flight periods were
tested relative to the pre-flight period using change scores generated
for each astronaut from the average of an outcome for each mission
phase. Post hoc analyses that tested differences between astronauts
and mission phases were corrected for multiple comparisons based on
the false discovery rate method with a significance threshold of P < 0.05
(refs. 51); both unadjusted and adjusted P values are reported. For crew-
level differences between mission phases, Type III effects are reported.
Reporting summary
Further information on research design is available in theNature Port-
folio Reporting Summary linked to this article.
Data availability
Datasets have been uploaded to four different data repositories: the
NASA Open Science Data Repositories (osdr.nasa.gov; comprising
GeneLab
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and the Ames Life Sciences Data Archive (ALSDA)
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Acknowledgements C.E.M. thanks I. Tulchinsky and WorldQuant, The GI Research Foundation,
NASA (NNX14AH50G, NNX17AB26G, 80NSSC22K0254, NNH18ZTT001N-FG2, Translational
Research Institute for Space Health (TRISH)/NNX16AO69A), the National Institutes of Health
(R01MH117406, P01CA214274 R01CA249054, R01AI151059, U54AG089334) and the Leukemia
andLymphomaSociety MCL7001-18, 7029-23). E.G.O. thanks Quest Diagnostics and G. Pajot
for logistical support across multiple biospecimen collection locations. We also thank the
Epigenomics and SCU Cores at WCM, the GI Research Foundation (GIRF) and Radvinsky family,
and J.J. Hastings for help in the mission logistics. The NASA Open Science Data Repositories
thanks the NASA Space Biology Program and the NASA Human Research Program. F.Z., J.L.,
J.G., J.A.A., A.F. and A.J.S. were supported under NASA contract NNX 16A069A/CAT0001,
TRISH through NASA Cooperative Agreement NNX16AO69A, and NIAID 1U01AI148307-01 and
U24AI152172. We also thank M. Zubaidi, M. McNeely and P. Luk at GattaCo for providing the
plasma separation cartridges, and G. Nelson and H. Mead for assistance running PepSeq
assays. A.E.S., D.J.E., A.E., M.B., A.J.E., C.E.M, C.W.J., E.M.B., M.I.H., E.U., D.B.D., M.S., M.S.S.,
M.C.S., N.N.A., A.M., J.M. and J.H.W. were supported by the Translational Research Institute for
Space Health (TRISH)through NASA Cooperative Agreement NNX16AO69A.D.B.D.andE.U.
thank John Wright Allen, Amara Azobu andLeanne Scottat Baylor College of Medicine for
helping put in place the Federal Wide Assurance at SpaceX.
Author contributions J.H.W., D.B.D., J.M., A.E.S., M.Shelhamer, F.Z., E.M.B., M.B. and C.E.M.
conceived the study. E.G.O., J.L., A.J.E., M.M., E.E.A., D.J.E., A.E., M.C.S., A.M., J.G., J.A.A., A.F.,
M.I.H., D.L., S.M., M.L., A.S.M., D.B.D., E.U., J.M., A.E.S., M.Shelhamer, F.Z., E.M.B., M.B. and
C.E.M. designed the experiments. C.W.J., E.G.O., J.L., A.J.E., K.R., B.T., N.D., J.K., A.J.S., A.F., N.B.,
S.M., M.L., A.S.M., J.M., M.B. and C.E.M. prepared and/or collected samples. C.W.J., E.G.O., J.L.,
A.J.E., K.R., N.D., J.K., A.J.S., J.A.A., A.F., R.K., V.O., M.Y., L .P., I.M., J.M., M.B. and C.E.M. generated
the data. C.W.J., E.G.O., J.L., A.J.E., C.M., B.T., J.F., J.P., T.N., M.S., S.G.B., B.A., U.A.T., L.N., P.M.,
C.O.P., S.A.K., D.J.E., A.E., N.N.A., M.S.S., J.K., N.H., K.G., S.G.M., J.A.A., A.C.S., J.M., A.E.S.,
M.Shelhamer, M. Suhail,F.Z., M.B. and C.E.M. analysed the data. C.W.J., E.G.O., M.B. and C.E.M.
prepared the manuscript. D.B.D., E.U., J.M., A.E.S., M.Shelhamer, F.Z. and E.M.B. are senior
authors for the Inspiration4 mission. All authors reviewed and approved the manuscript.
Competing interests C.E.M. is a co-founder of BioAstra. The remaining authors declare no
competing interests.
Additional information
Supplementary information The online version contains supplementary material available at
https://doi.org/10.1038/s41586-024-07648-x.
Correspondence and requests for materials should be addressed to Mathias Basner or
Christopher E. Mason.
Peer review information Nature thanks Jochen Schwenk, Balazs Aczel and the other,
anonymous, reviewer(s) for their contribution to the peer review of this work.
Reprints and permissions information is available at http://www.nature.com/reprints.
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Extende d Data Fig. 1 | Th e environmen tal, physiolo gical, cog nitive,
imaging, and omics measures collected across Inspiration4 mission
phases and their sampling frequency. To assess th e effect of shor t-duration
spacef light on an all-c ivilian crew, data were co llected on myr iad domains
using vario us methodolo gies (colors, lef t) before, during, a nd after fl ight
spanning human biometrics, virome, cognition, spacecraft environment,
and multi-o mics assays. G reen circles den ote samples co llected on Ear th
(i.e., pre-flight, post-flight) and blue diamonds denote data collected in-flight,
along with t heir respec tive assays. For th e timing of data co llection, dat a
collecte d during the pre-f light per iod is present ed as the numbe r of days prior
to launch (L) and dat a collecte d in the post-fligh t period is pres ented as the
number of days fol lowing return (R) t o Earth. Dat a with continua l collection
(e.g. cabin m easurement s) are shown as brackete d time period s.
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Article
Extende d Data Fig. 2 | SOM A biosamp le collect ions during t he Inspirat ion4
mission. Sample t ypes and down stream assay s performed for mu lti-omic
and clinical b iomarkers. A vari ety of blood de rivatives were col lected via
venipunct ure. Samples th at have not yet been se quenced are biob anked.
EVP = ex tracellular ves icles and part icles. Env = enviro nment.Created w ith
BioRender.com.
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Extende d Data Fig. 3 | Pap er-based m ultiplexed mi crogravity-a dapted
vertical f low ass ay (0g-VFI). a, Annotated e xploded view of t he 0g-VFI.PES,
polyethersulfone. b, Pictures of t he packaged 0g-VFI k it as stored in th e Dragon
(left) and th e three differen t component s of the 0g-VFI: (1) membran e housing
with the ma gnifier ca p, (2) assay buffer pad ca psule and (3) washing buf fer pad
capsule. c, Schemat ic overview of the co mplete assay op eration as pe rformed
during the mi ssion, from the bl ood collect ion by fingers tick to the visua l
detect ion of the immuno globulin M (IgM) and C-re active protein (CR P) values,
passing by th e plasma separa tion using the Ga ttaco® car tridge and the
different in cubation and wa shing steps. d, Re presentat ive images of 0g-VFI
membrane s showing the mul tiplexing per formance (top) and graphi cal
quantif ication (bo ttom) of the values ob tained when m embranes were e ither
incubate d with no sample s (ø), IgM only, CRP only or in multiplex w ith
IgM + CRP (Da ta presente d are mean ± SEM from th ree independ ent 0g-VFI
(n = 3). e, Graph representi ng the average volume of as say buffer tran sferred to
the absorb ing pad when the 0 g-VFI was used in micro gravity dur ing the I4
mission (Da ta presente d are mean ± SEM; n = 3). Pictur es show absorbi ng pads
from two dif ferent 0g-VFI kit s used in-fli ght with diame ter of wet area (red
circles), which inform s the volume of assay b uffer transfer red from the wet pad
during ope ration. f, Visual c omparison of 0g-VF I membranes fr om kits stored
in the lab and pe rformed followi ng standard proto col with 15 min i ncubation (i)
with kit s stored in the Dra gon capsule and ru n in-flight for 1 5 min (ii) or
post-fligh t for 90 min (iii).
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Article
Extende d Data Fig. 4 | 0g-Verti cal Flow Immun oassay (VF I) analytic al
performance and quality control metrics. a, 0g-VFI intensity for C-rea ctive
protein (CRP) and im munoglobulin M (I gM) spots are a fun ction of CRP a nd
IgM conce ntration on mult iplex membrane s. CRP and Ig M samples were
assayed fro m three indepen dent 0g-VFI (n = 3) and each CR P and IgM data po int
presente d is the mean ± SEM of t he triplicate . For each CRP and I gM plot, a
four-parameter log istic model wa s used to genera te the fitt ed curve and the
limit of dete ction (LOD), represen ted as a dotted l ine, was deter mined using
the following for mula:
xσLOD =+3
negC ne
gC
, where LOD is equ al to the mean of
the negat ive control (negC) + 3 st andard deviatio ns (σ) of the negative cont rol.
b, Intra- and int er-assay coeff icients of var iation (CV) across C RP and IgM
assays are pre sented; CVs were cal culated by CV (%) = (Standar d Deviation/
Mean) x 100. For the in ter-assay CV, each point repre sents the CV of t he control
spots obt ained from thre e independe nt identical re plicates of 7 CR P and IgM
0g-VFI membra nes (n = 14). For the intra-assay CV, each poi nt represent s the
CV of the three c ontrol spots o btained wit hin the same memb ranes from 43
independ ent CRP and Ig M 0g-VFI. c, Representative intensity distribution
across 0g-VFI m embranes. T he plot shows three I gM spots from t hree
independ ent 0g-VFI membra nes (R1, R 2, and R3) expose d to an IgM
concentr ation of 1 µg /mL; the average of the thre e IgM spots is pr esented in
black.
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Extende d Data Fig. 5 | Acce lerated st ability stu dies of 0g-VFI dev ices.
0g-VFI device s were packed: 1) in the pre sence of a hygros copic substa nce
(Desicc ation, D) or 2) no hygroscop ic substance ( No desiccat ion, ø) and stored
in an environm ental chamb er at 42 °C and 75% humidit y. a, Representative
0g-VFI membra nes packed with (D) an d without (ø) desicc ation. b, C-reacti ve
protein (CRP) and im munoglobulin M (I gM) quantif ication aft er a 3-day
incubatio n. Data prese nted are mean ± SEM f rom three indep endent 0g-VFI
(n = 3).
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Article
Extende d Data Fig. 6 | Oc ular misali gnment be fore and after s hort-
duration spaceflight. Data a s presented in F ig.5. Red boxes indicat e the
grouping , for each astronau t, of pre-flig ht and the post-fli ght tests; an as terisk
(*) denotes ast ronauts who exp erienced sp ace motion sick ness (SMS) in-f light.
This shows co nsistency of p re-flight an d post-flight te sts in the non-SM S
astronaut s (C001 and C003). Vertica l offsets of th e boxes in each grap h show
change from pre -flight to p ost-flight, indi cative of adaptive c hange during
fligh t (larger adaptive c hange associa ted with lack of S MS). Boxes are drawn
manually, to enclos e the median in ea ch case.
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Extended Data Fig. 7 | Cardiovascular responses to short-duration
spaceflight. a, One -hour averages of as tronaut hear t rate (HR) measur ed
across all mi ssion phases ( N = 424). b, One-hour averages of astro naut heart
rate variab ility (HRV), a measure o f parasympath etic regulati on of cardiac
functio n, derived from h eart perio d data using the s tandard deviat ion of R-R
interval s across missio n phases (N = 12 7). c, Scatter pl ot of astronaut blo od
oxygen satur ation across mi ssion phase s (N = 177); blood oxyge nation
measurem ents failed in t wo astronauts i n-flight. d, S catter plot o f one-hour
averages of ast ronaut energ y consumptio n across missio n phases (N = 502).
e, Average hourly HR for ea ch mission pha se. f, Average hourly HRV for each
mission phase. g, Average hourly b lood oxygen sat uration for each mi ssion
phase. h, Average hou rly energy con sumption for eac h mission phase . For
panels e-h, mean ± SEM with th e n for each astronau t during that mis sion phase.
Differenc es in cardiome tabolic meas ures in-flig ht and post-flig ht relative to
pre-fli ght were evaluated u sing mixed-ef fect models th at nested rep eated
measures within astronauts contrasting the in-flight and post-flight periods
with pre-f light; P-values we re correcte d for multiple compar isons using th e
false discovery rate method51 and adjusted sign ificant as sociations a re
denoted a s: *P < 0.05; **** P < 0.0001.
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Article
Extende d Data Fig. 8 | Pr ofiles o f the spacecra ft environ ment during
short-duration spaceflight. a, One-minu te averages of cabin p ressure of the
spacecra ft measured t hroughout the In spiration4 mi ssion (FD: fl ight day).
b, One-minute averages of temperature in the spacecraft. c, One-minute
averages of par tial pressure of O xygen (O2) in the space craft. d, One-minute
averages of rela tive humidity in th e spacecraf t. e, Scatter p lot of sound
pressure level s for each astrona ut, measured us ing the Apple Watch, ac ross
mission pha ses; sound pre ssure levels were average d arithmetic ally, and each
point repre sents a one-ho ur average (N = 797). f, Scat ter plot of barome tric
pressure level s for each astrona ut, measured us ing the Apple Watch, ac ross
mission pha ses; each poin t represent s a one-hour average (N = 17 7). g, Average
sound pres sure level for each as tronaut durin g each missio n phase (mea n ± SEM),
which was sa mpled twice p er hour by the Apple Watc h (N = 797). Sound
pressure level s were similar in-f light relative to pre -flight for thr ee of the four
astronaut s; one astronau t was exposed to hi gher sound pre ssure levels (C001;
β = −7.152; P < 0.00 01) in-flight . h, Average barometric pr essure level for each
astronaut d uring each mis sion phase. For pa nels g and h, mean ± SEM w ith
the n for each astro naut during tha t mission phase . Difference s in-flight a nd
post-flight relative to pre-flight were evaluated using mixed-effect models
contrasting the in-flight and post-flight periods with pre-flight; post-hoc
analyses t esting for differ ences betw een astronaut s were correct ed for
multiple comparisons using the false discovery rate method51. Signif icant
associa tions are adjust ed for multiple comp arisons: *P < 0.0 5; **P < 0.01;
****P < 0.0001.
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Extende d Data Fig. 9 | Pr ofiles o f astronaut co gnitive per formance on
Cognition assays across mission phases. Performan ce on each of the 10
Cognition tests is indexe d by response sp eed in the left p anel and accurac y in
the right pa nel for each astro naut across mis sion phases (N = 2 6 Cognition
administrations). For response speed outcomes, higher values represent
slower respo nse speeds; re sponse spe ed on the Psychomo tor Vigilance
Test is inverted to ma tch the direct ion of other Cogn ition speed m etrics. For
accuracy outcomes, higher values represent more accurate performance.
a, Psychomotor V igilance Test (PV T). b, Matrix Reas oning Test (MRT). c, Abstract
Matching (AM). d, Line Orienta tion Test (LOT). e, Visual Obje ct Learning Test
(VOLT). f, Motor Pra xis Task (MP). g, Emotion Recogn ition Test (ERT). h, D ig it-
Symbol Subs titution Task (DSST). i, Frac tal 2-Back (F2B). j, Ball oon Analog R isk
Test (BART). k, Aggr egate Cogni tion speed and a ccuracy acros s tests (data for
each test we re standardize d before averaging ; BART risk tak ing does not
contribu te to the accurac y score across te sts).
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Extende d Data Fig. 10 | As tronaut repo rt of behavi oral states a cross
mission phases. Astro nauts (N = 4) reporte d on their sleep du ration and
behaviora l state using th e Alertne ss and Mood Sur vey (AMS)50. For all 10 AMS
items (panels b-k), astronauts ra ted their behav ioral state usi ng 11-point
Likert-type s cales for each ite m during all three ph ases of the mis sion (N = 26
for each item). AM S items are plot ted on the full rang e of each scale and h igher
numbers re present high er ratings in the d irection of the i tem at the bott om of
each panel (e. g., for Poor Sleep Qu ality, a higher numbe r represents w orse
sleep qualit y). For all AMS items exce pt sleep qualit y and workload, as tronauts
were prompted t o rate “how are you feeli ng right now? ” a, Sleep duratio n
(derived from se lf-reported slee p and wake-up time s). b, Sleep quality
(question: “H ow was the quality o f your sleep?”; anchor s: good—poor). c, High
workload (ques tion: “What w as today’s workload? ”; anchors: very l ow—very
high) . d, Sleepiness (anchor s: not sleepy at all—ver y sleepy). e, Physical
exhaustion (anchors: energetic—physically exhausted). f, Sickness (anch ors:
healthy—sick). g, Depressed (ancho rs: not depress ed at all—very depre ssed).
h, Unhappiness (anchors: happy—unhappy). i, Bored (anchors: go od—poor).
j, Monotonou s (anchors: good—poo r). k, Stressed (anchors: n ot stressed a t all—
very stressed).
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