Evidence map›Paper›PMID 38744274›Full record

ArticleCell reports. Medicine2024

Clinical and CSF single-cell profiling of post-COVID-19 cognitive impairment.

William T Hu, Milota Kaluzova, Alice Dawson, Victor Sotelo, Julia Papas, Alexander Lemenze, Carol Shu, Mini Jomartin, Ashima Nayyar, Sabiha Hussain

Abstract read
In one paragraph

Article in Cell reports. Medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

15 citing papers in PubMed.

  1. Observational
  2. Review
  3. Article
  4. Review
  5. Review
  6. The Central Role of Macrophages in Long COVID Pathophysiology.International journal of molecular sciences · 2025
    Review
  7. Article
  8. Article
  9. Article
  10. Article
  11. Neuroimmune pathophysiology of long COVID.Psychiatry and clinical neurosciences · 2025
    Review
  12. Review
  13. Article
  14. Review
  15. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

William T HuDepartment of Neurology, Rutgers-Robert Wood Johnson Medical School, New Brunswick, NJ, USA; Center for Innovation in Health and Aging Research, Institute for Health, Health Care Policy, and Aging Research, New Brunswick, NJ, USA. Electronic address: william.hu@rutgers.edu.
Milota KaluzovaDepartment of Neurology, Rutgers-Robert Wood Johnson Medical School, New Brunswick, NJ, USA.
Alice DawsonDepartment of Neurology, Rutgers-Robert Wood Johnson Medical School, New Brunswick, NJ, USA; Center for Innovation in Health and Aging Research, Institute for Health, Health Care Policy, and Aging Research, New Brunswick, NJ, USA.
Victor SoteloDepartment of Neurology, Rutgers-Robert Wood Johnson Medical School, New Brunswick, NJ, USA; Center for Innovation in Health and Aging Research, Institute for Health, Health Care Policy, and Aging Research, New Brunswick, NJ, USA.
Julia PapasDepartment of Neurology, Rutgers-Robert Wood Johnson Medical School, New Brunswick, NJ, USA; Center for Innovation in Health and Aging Research, Institute for Health, Health Care Policy, and Aging Research, New Brunswick, NJ, USA.
Alexander LemenzeDepartment of Pathology and Laboratory Medicine, Rutgers-New Jersey Medical School, Newark, NJ, USA.
Carol ShuDepartment of Medicine-Pulmonary and Critical Care, Rutgers-Robert Wood Johnson Medical School, New Brunswick, NJ, USA.
Mini JomartinDepartment of Neurology, Rutgers-Robert Wood Johnson Medical School, New Brunswick, NJ, USA.
Ashima NayyarDepartment of Neurology, Rutgers-Robert Wood Johnson Medical School, New Brunswick, NJ, USA.
Sabiha HussainDepartment of Medicine-Pulmonary and Critical Care, Rutgers-Robert Wood Johnson Medical School, New Brunswick, NJ, USA.

Funding

CSF, MRI, and PET biomarkers of neuroinflammation in Alzheimer's diseaseR01AG054046 · NIA · RBHS-ROBERT WOOD JOHNSON MEDICAL SCHOOL · PI HU, WILLIAM TZU-LUNG · 2016 to 2020
$3.9M
Transfer RF1 AG054991 Beyond Haploinsuffiency- Gain of Function in Prograulin MutationsRF1AG054991 · NIA · RBHS-ROBERT WOOD JOHNSON MEDICAL SCHOOL · PI HU, WILLIAM TZU-LUNG · 2019 to 2019
$3.4M
NIA NIH HHS R01 AG054046NIA NIH HHS RF1 AG054991
6 · The paper itself

Abstract

Natural history and mechanisms for persistent cognitive symptoms ("brain fog") following acute and often mild COVID-19 are unknown. In a large prospective cohort of people who underwent testing a median of 9 months after acute COVID-19 in the New York City/New Jersey area, we found that cognitive dysfunction is common; is not influenced by mood, fatigue, or sleepiness; and is correlated with MRI changes in very few people. In a subgroup that underwent cerebrospinal fluid analysis, there are no changes related to Alzheimer's disease or neurodegeneration. Single-cell gene expression analysis in the cerebrospinal fluid shows findings consistent with monocyte recruitment, chemokine signaling, cellular stress, and suppressed interferon response-especially in myeloid cells. Longitudinal analysis shows slow recovery accompanied by key alterations in inflammatory genes and increased protein levels of CXCL8, CCL3L1, and sTREM2. These findings suggest that the prognosis for brain fog following COVID-19 correlates with myeloid-related chemokine and interferon-responsive genes.

Indexed as

Cognitive DysfunctionCOVID-19SARS-CoV-2Single-Cell AnalysisAdultAgedFemaleHumansInterleukin-8Magnetic Resonance ImagingMaleMembrane GlycoproteinsMiddle AgedProspective StudiesReceptors, ImmunologicCXCL8 protein, humanInterleukin-8Membrane GlycoproteinsReceptors, ImmunologicTREM2 protein, humanAlzheimer’s diseasebrain foginterferonlong COVIDPASCSARS-CoV-2

Identifiers

PMID38744274
PMCPMC11148803

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.