Machine learning analysis suggests that there are four sub-phenotypes of long COVID

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Machine learning analysis suggests that there are four sub-phenotypes of long COVID NatureMedicine WeillCornell longCOVID coronavirus covid machinelearning data healthcaredata phenotype

By Pooja Toshniwal PahariaDec 6 2022Reviewed by Danielle Ellis, B.Sc. In a recent study published in Nature Medicine, researchers identified PASC [post-acute sequelae of coronavirus disease 2019 ] sub-phenotypes depending on conditions diagnosed within 1 to 3 months of acute infection by severe acute respiratory syndrome coronavirus 2 .

EHR data of two big CRNs from the nationwide PCORnet , i.e., the INSIGHT CRN and the OneFlorida+ CRN. The INSIGHT CRN comprises 12 million NYC residents, whereas the OneFlorida+ CRN comprises 19 million individuals residing in Georgia, Alabama, and Georgia. The TM approach was used to identify co-incident patterns of the PASC conditions, depending on which PASC sub-phenotypes were determined. After obtaining high-dimensional binary representations of PASC conditions , the algorithm learned PASC topics and inferred the patient representations in the low-dimensional PASC topic space via the topic-modelling approach. PASC sub-phenotypes were determined based on patient clusters representing PASC topics .

The sub-phenotype had the greatest percentage of SARS-CoV-2-positive patients during the initial COVID-19 wave . The sub-phenotype individuals had an elevated burden of comorbidities and were largely prescribed for anemia, circulatory disorders, and endocrine disorders. Sub-phenotype 3 comprised 23% of individuals with disorders of the nervous and musculoskeletal systems , including pain of musculoskeletal origin, sleep disorders, and headaches. The median patient age was 57 years, and 61% of them were female. The sub-phenotype comprised the greatest percentage of individuals with >5.0 outpatient setting visits before COVID-19 . The sub-phenotype individuals were mostly prescribed with analgesic medications .

 

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Epigenetic and transcriptomic reprogramming in monocytes of severe COVID-19 patients reflects alterations in myeloid differentiation and the influence of inflammatory cytokines - Genome MedicineBackground COVID-19 manifests with a wide spectrum of clinical phenotypes, ranging from asymptomatic and mild to severe and critical. Severe and critical COVID-19 patients are characterized by marked changes in the myeloid compartment, especially monocytes. However, little is known about the epigenetic alterations that occur in these cells during hyperinflammatory responses in severe COVID-19 patients. Methods In this study, we obtained the DNA methylome and transcriptome of peripheral blood monocytes from severe COVID-19 patients. DNA samples extracted from CD14 + CD15- monocytes of 48 severe COVID-19 patients and 11 healthy controls were hybridized on MethylationEPIC BeadChip arrays. In parallel, single-cell transcriptomics of 10 severe COVID-19 patients were generated. CellPhoneDB was used to infer changes in the crosstalk between monocytes and other immune cell types. Results We observed DNA methylation changes in CpG sites associated with interferon-related genes and genes associated with antigen presentation, concordant with gene expression changes. These changes significantly overlapped with those occurring in bacterial sepsis, although specific DNA methylation alterations in genes specific to viral infection were also identified. We also found these alterations to comprise some of the DNA methylation changes occurring during myeloid differentiation and under the influence of inflammatory cytokines. A progression of DNA methylation alterations in relation to the Sequential Organ Failure Assessment (SOFA) score was found to be related to interferon-related genes and T-helper 1 cell cytokine production. CellPhoneDB analysis of the single-cell transcriptomes of other immune cell types suggested the existence of altered crosstalk between monocytes and other cell types like NK cells and regulatory T cells. Conclusion Our findings show the occurrence of an epigenetic and transcriptional reprogramming of peripheral blood monocytes, which could be associated with the
Source: BioMedCentral - 🏆 22. / 71 Read more »