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Salivary cytokines may be predictive of severe Covid-19 in children

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Dr Swati Y Bhave, Adjunct Professor in Adolescent Medicine; Dr D Y Patil Medical College, & Dr D Y Patil Vidyapeeth, Pune Senior consultant, Adolescent Pediatrics & Head-In-charge of Adolescent Wellness Clinic, Jehangir Hospital Pune    12 October 2021

Preliminary findings of an ongoing study presented at the American Academy of Pediatrics (AAP) virtual annual meeting suggest that children with severe Covid-19 have significantly elevated levels of salivary cytokines.

The study examined 180 children (mean age 7.1 years) with Covid-19; of these, 60 were admitted to hospital for their illness and 40 had severe disease. Five of the children with severe Covid-19 had cardiac symptoms, 26 children developed severe respiratory symptoms, while most of the remaining children had multisystem inflammatory syndrome in children (MIS-C). Six salivary cytokines (TNF R-1, IL-13, IL-15, CCL-7, CXCL-10, MIG [CXCL9]) were assessed. Micro RNA (miRNA) levels were also measured in 129 saliva samples.

Preliminary analysis of data showed that the levels of CXCL-10, MIG and TNF R-1 were higher in the saliva of children with severe Covid-19 compared to those who had mild disease. All these three cytokines are proinflammatory. An additional finding was the significantly lower levels of 63 microRNAs in the saliva of children with severe infection compared to children who did not have severe disease.

This study has demonstrated raised levels of proinflammatory cytokines in the saliva. But, according to the authors, their small sample size precluded evaluation of any correlation between specific cytokines and various symptoms of Covid-19 infection. The difference in the miRNA levels between the two groups was statistically significant and showed promise as a predictive model.

Drawing blood samples may be a distressing experience for children. Being painless, using saliva as a specimen therefore would particularly be advantageous in children.

Researchers from Central Michigan University, Penn State University and Wayne State University have collaborated on this research, which will continue till June next year. They are hopeful about developing a predictive model based on these biomarkers, social determinants of health and relevant clinical data, which can be used as a bedside tool to identify children at risk for severe disease. Early detection of impending severity will allow timely institution of appropriate treatment and save lives.

(Sources: MedPage Today October 9, 2021, AAP News Release October 8, 2021, PennState News October 9, 2021)

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