Longitudinal Immune Profiling in Sepsis Reveals Transient Expansion of a CD14+Monocyte State and Persistent T Cell Suppression Article Swipe
Pierre Ankomah
,
Alyssa DuBois
,
Abraham Sonny
,
Miguel Reyes
,
Paul C. Blainey
,
Marcia B. Goldberg
,
Michael R. Filbin
,
Nir Hacohen
,
Roby P. Bhattacharyya
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1101/2025.05.17.25327533
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1101/2025.05.17.25327533
Sepsis is a dynamic syndrome of immune dysregulation and a leading cause of global mortality. Although immune suppression is recognized as a hallmark of sepsis, the temporal dynamics and mechanistic drivers of immune dysfunction remain incompletely understood. Here, we performed longitudinal single-cell transcriptomic and proteomic profiling of peripheral blood from 98 adults with sepsis or sterile inflammation, alongside 12 healthy controls, capturing immune trajectories from initial clinical presentation through recovery. Integration of RNA and surface protein data revealed an early expansion of a transcriptionally reprogrammed CD14 + monocyte population (MS1) exhibiting features of monocytic myeloid-derived suppressor cells (M-MDSCs), including downregulation of HLA-DR and upregulation of alarmins ( S100A8 , S100A9 ), resistin, and clusterin. M-MDSCs arise from emergency myelopoiesis and contribute to adaptive immune suppression through impaired antigen presentation and T cell inhibition. MS1 abundance peaked at initial presentation and declined progressively during the first week of clinical management in most patients. In contrast, CD8 + naive and CD4 + memory T cells exhibited sustained depletion, with recovery occurring at convalescence in only a subset of patients. Plasma proteomic profiling identified cytokines and growth factors, including IL-6 and resistin, that may contribute to MS1 induction and suppressive activity. IL-6 exhibited a kinetic trajectory that closely paralleled MS1 abundance, peaking early and declining during recovery. Resistin levels were positively correlated with MS1 abundance across all timepoints from acute sepsis through convalescence. These dynamics suggest temporally distinct cytokine roles in initiating and sustaining immunosuppressive myeloid responses in sepsis. Together, these findings define a high-resolution, time-resolved immune atlas of human sepsis, linking emergency myelopoiesis to downstream adaptive immune suppression. Our results suggest that coordinated dynamics between myeloid and lymphoid compartments shape early immune trajectories in sepsis and highlight MDSC-targeting pathways as potential therapeutic avenues.
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Metadata
- Type
- preprint
- Language
- en
- Landing Page
- https://doi.org/10.1101/2025.05.17.25327533
- https://www.medrxiv.org/content/medrxiv/early/2025/05/19/2025.05.17.25327533.full.pdf
- OA Status
- green
- References
- 45
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4410510263
All OpenAlex metadata
Raw OpenAlex JSON
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https://doi.org/10.1101/2025.05.17.25327533Digital Object Identifier
- Title
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Longitudinal Immune Profiling in Sepsis Reveals Transient Expansion of a CD14+Monocyte State and Persistent T Cell SuppressionWork title
- Type
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preprintOpenAlex work type
- Language
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enPrimary language
- Publication year
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2025Year of publication
- Publication date
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2025-05-19Full publication date if available
- Authors
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Pierre Ankomah, Alyssa DuBois, Abraham Sonny, Miguel Reyes, Paul C. Blainey, Marcia B. Goldberg, Michael R. Filbin, Nir Hacohen, Roby P. BhattacharyyaList of authors in order
- Landing page
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https://doi.org/10.1101/2025.05.17.25327533Publisher landing page
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https://www.medrxiv.org/content/medrxiv/early/2025/05/19/2025.05.17.25327533.full.pdfDirect link to full text PDF
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YesWhether a free full text is available
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greenOpen access status per OpenAlex
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https://www.medrxiv.org/content/medrxiv/early/2025/05/19/2025.05.17.25327533.full.pdfDirect OA link when available
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CD14, Monocyte, Immune system, Profiling (computer programming), Sepsis, Immunology, Medicine, Computer science, Operating systemTop concepts (fields/topics) attached by OpenAlex
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0Total citation count in OpenAlex
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45Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.sepsis | 54, 228, 283 |
| abstract_inverted_index.subset | 175 |
| abstract_inverted_index.M-MDSCs | 115 |
| abstract_inverted_index.antigen | 128 |
| abstract_inverted_index.between | 273 |
| abstract_inverted_index.closely | 205 |
| abstract_inverted_index.drivers | 31 |
| abstract_inverted_index.dynamic | 4 |
| abstract_inverted_index.healthy | 60 |
| abstract_inverted_index.initial | 66, 138 |
| abstract_inverted_index.kinetic | 202 |
| abstract_inverted_index.leading | 11 |
| abstract_inverted_index.linking | 259 |
| abstract_inverted_index.myeloid | 243, 274 |
| abstract_inverted_index.peaking | 209 |
| abstract_inverted_index.protein | 76 |
| abstract_inverted_index.results | 268 |
| abstract_inverted_index.sepsis, | 25, 258 |
| abstract_inverted_index.sepsis. | 246 |
| abstract_inverted_index.sterile | 56 |
| abstract_inverted_index.suggest | 233, 269 |
| abstract_inverted_index.surface | 75 |
| abstract_inverted_index.through | 69, 126, 229 |
| abstract_inverted_index.ABSTRACT | 0 |
| abstract_inverted_index.Although | 16 |
| abstract_inverted_index.Resistin | 215 |
| abstract_inverted_index.adaptive | 123, 264 |
| abstract_inverted_index.alarmins | 106 |
| abstract_inverted_index.avenues. | 291 |
| abstract_inverted_index.clinical | 67, 148 |
| abstract_inverted_index.cytokine | 236 |
| abstract_inverted_index.declined | 141 |
| abstract_inverted_index.distinct | 235 |
| abstract_inverted_index.dynamics | 28, 232, 272 |
| abstract_inverted_index.factors, | 185 |
| abstract_inverted_index.features | 92 |
| abstract_inverted_index.findings | 249 |
| abstract_inverted_index.hallmark | 23 |
| abstract_inverted_index.impaired | 127 |
| abstract_inverted_index.lymphoid | 276 |
| abstract_inverted_index.monocyte | 88 |
| abstract_inverted_index.pathways | 287 |
| abstract_inverted_index.recovery | 168 |
| abstract_inverted_index.revealed | 78 |
| abstract_inverted_index.syndrome | 5 |
| abstract_inverted_index.temporal | 27 |
| abstract_inverted_index.Together, | 247 |
| abstract_inverted_index.abundance | 135, 222 |
| abstract_inverted_index.activity. | 198 |
| abstract_inverted_index.alongside | 58 |
| abstract_inverted_index.capturing | 62 |
| abstract_inverted_index.contrast, | 154 |
| abstract_inverted_index.controls, | 61 |
| abstract_inverted_index.cytokines | 182 |
| abstract_inverted_index.declining | 212 |
| abstract_inverted_index.emergency | 118, 260 |
| abstract_inverted_index.exhibited | 164, 200 |
| abstract_inverted_index.expansion | 81 |
| abstract_inverted_index.highlight | 285 |
| abstract_inverted_index.including | 99, 186 |
| abstract_inverted_index.induction | 195 |
| abstract_inverted_index.monocytic | 94 |
| abstract_inverted_index.occurring | 169 |
| abstract_inverted_index.patients. | 152, 177 |
| abstract_inverted_index.performed | 40 |
| abstract_inverted_index.potential | 289 |
| abstract_inverted_index.profiling | 46, 180 |
| abstract_inverted_index.proteomic | 45, 179 |
| abstract_inverted_index.recovery. | 70, 214 |
| abstract_inverted_index.resistin, | 112, 189 |
| abstract_inverted_index.responses | 244 |
| abstract_inverted_index.sustained | 165 |
| abstract_inverted_index.(M-MDSCs), | 98 |
| abstract_inverted_index.abundance, | 208 |
| abstract_inverted_index.clusterin. | 114 |
| abstract_inverted_index.contribute | 121, 192 |
| abstract_inverted_index.correlated | 219 |
| abstract_inverted_index.depletion, | 166 |
| abstract_inverted_index.downstream | 263 |
| abstract_inverted_index.exhibiting | 91 |
| abstract_inverted_index.identified | 181 |
| abstract_inverted_index.initiating | 239 |
| abstract_inverted_index.management | 149 |
| abstract_inverted_index.mortality. | 15 |
| abstract_inverted_index.paralleled | 206 |
| abstract_inverted_index.peripheral | 48 |
| abstract_inverted_index.population | 89 |
| abstract_inverted_index.positively | 218 |
| abstract_inverted_index.recognized | 20 |
| abstract_inverted_index.suppressor | 96 |
| abstract_inverted_index.sustaining | 241 |
| abstract_inverted_index.temporally | 234 |
| abstract_inverted_index.timepoints | 225 |
| abstract_inverted_index.trajectory | 203 |
| abstract_inverted_index.Integration | 71 |
| abstract_inverted_index.coordinated | 271 |
| abstract_inverted_index.dysfunction | 34 |
| abstract_inverted_index.inhibition. | 133 |
| abstract_inverted_index.mechanistic | 30 |
| abstract_inverted_index.single-cell | 42 |
| abstract_inverted_index.suppression | 18, 125 |
| abstract_inverted_index.suppressive | 197 |
| abstract_inverted_index.therapeutic | 290 |
| abstract_inverted_index.understood. | 37 |
| abstract_inverted_index.compartments | 277 |
| abstract_inverted_index.incompletely | 36 |
| abstract_inverted_index.longitudinal | 41 |
| abstract_inverted_index.myelopoiesis | 119, 261 |
| abstract_inverted_index.presentation | 68, 129, 139 |
| abstract_inverted_index.reprogrammed | 85 |
| abstract_inverted_index.suppression. | 266 |
| abstract_inverted_index.trajectories | 64, 281 |
| abstract_inverted_index.upregulation | 104 |
| abstract_inverted_index.convalescence | 171 |
| abstract_inverted_index.dysregulation | 8 |
| abstract_inverted_index.inflammation, | 57 |
| abstract_inverted_index.progressively | 142 |
| abstract_inverted_index.time-resolved | 253 |
| abstract_inverted_index.MDSC-targeting | 286 |
| abstract_inverted_index.convalescence. | 230 |
| abstract_inverted_index.downregulation | 100 |
| abstract_inverted_index.transcriptomic | 43 |
| abstract_inverted_index.myeloid-derived | 95 |
| abstract_inverted_index.high-resolution, | 252 |
| abstract_inverted_index.immunosuppressive | 242 |
| abstract_inverted_index.transcriptionally | 84 |
| cited_by_percentile_year | |
| countries_distinct_count | 0 |
| institutions_distinct_count | 9 |
| citation_normalized_percentile.value | 0.24947411 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |