ArticleFrontiers of medicine2020
Single-cell RNA-seq data analysis on the receptor ACE2 expression reveals the potential risk of different human organs vulnerable to 2019-nCoV infection.
Article in Frontiers of medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to 3 registered trials, which are not on this map. Cited by 1,317 papers, 6 of them syntheses that pooled it.
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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.
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.
The Clinical Manifestations of SARS-Cov-2 Disease; Not Only Pulmonary
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Alternative Application Methods of Pre-procedural Povidone Iodine Mouthrinse
Who cites it
1,317 citing papers in PubMed, 6 syntheses or guidelines pooled it.
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- Effects of pulmonary air leak on patients with coronavirus disease 2019 (COVID-19): a systematic review and meta-analysis.BMC pulmonary medicine · 2023Pooled it
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- Association of non-alcoholic fatty liver and metabolic-associated fatty liver with COVID-19 outcomes: A systematic review and meta-analysis.World journal of gastroenterology · 2023Pooled it
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- Identifying direct risk factors in UK Biobank via simultaneous Bayesian-frequentist model-averaged hypothesis testing using Doublethink.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
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- MicroRNAs in Acute COVID-19 and Long COVID: Dysregulation, Pathogenic Roles, and Clinical Implications.Journal of immunology research · 2026Review
- Sex and age are associated with host immune responses and multi-organ dysfunction in hospitalized patients with COVID-19.Frontiers in public health · 2026Article
- Biological Plausibility Between Long-COVID and Periodontal Disease Development or Progression.Biomedicines · 2025Review
- Kidney diseases and single-cell sequencing research: a bibliometric analysis from 2015 to 2024.Renal failure · 2025Review
- A public health perspective of SARS-CoV-2 evolution and surveillance strategies in Germany from 2020 to 2023.Communications medicine · 2025Review
- Angiotensin‑converting enzyme 2 expression in human tumors: Implications for prognosis and therapy (Review).Oncology reports · 2025Review
1,257 more citing papers are in PubMed but not listed here.
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6 authors.
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No grant is acknowledged in the PubMed record.
Abstract
It has been known that, the novel coronavirus, 2019-nCoV, which is considered similar to SARS-CoV, invades human cells via the receptor angiotensin converting enzyme II (ACE2). Moreover, lung cells that have ACE2 expression may be the main target cells during 2019-nCoV infection. However, some patients also exhibit non-respiratory symptoms, such as kidney failure, implying that 2019-nCoV could also invade other organs. To construct a risk map of different human organs, we analyzed the single-cell RNA sequencing (scRNA-seq) datasets derived from major human physiological systems, including the respiratory, cardiovascular, digestive, and urinary systems. Through scRNA-seq data analyses, we identified the organs at risk, such as lung, heart, esophagus, kidney, bladder, and ileum, and located specific cell types (i.e., type II alveolar cells (AT2), myocardial cells, proximal tubule cells of the kidney, ileum and esophagus epithelial cells, and bladder urothelial cells), which are vulnerable to 2019-nCoV infection. Based on the findings, we constructed a risk map indicating the vulnerability of different organs to 2019-nCoV infection. This study may provide potential clues for further investigation of the pathogenesis and route of 2019-nCoV infection.
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Registered trials
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.