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Henders, A.

Publications and source records attributed to Henders, A..

2 recordsLinked to original sources

Cardiovascular symptoms of PASC are associated with trace-level cytokines that affect the function of human pluripotent stem cell derived cardiomyocytes

Globally, over 65 million individuals are estimated to suffer from post-acute sequelae of COVID-19 (PASC). A large number of individuals living with PASC experience cardiovascular symptoms (i.e. chest pain and heart palpitations) (PASC-CVS). The role of chronic inflammation in these symptoms, in particular in individuals with symptoms persisting for >1 year after SARS-CoV-2 infection, remains to be clearly defined. In this cross-sectional study, blood samples were obtained from three different sites in Australia from individuals with i) a resolved SARS-CoV-2 infection (and no persistent symptoms i.e. Recovered), ii) individuals with prolonged PASC-CVS and iii) SARS-CoV-2 negative individuals. Individuals with PASC-CVS, relative to Recovered individuals, had a blood transcriptomic signature associated with inflammation. This was accompanied by elevated levels of pro-inflammatory cytokines (IL-12, IL-1{beta}, MCP-1 and IL-6) at approximately 18 months post-infection. These cytokines were present in trace amounts, such that they could only be detected with the use of novel nanotechnology. Importantly, these trace-level cytokines had a direct effect on the functionality of pluripotent stem cell derived cardiomyocytes in vitro. This effect was not observed in the presence of dexamethasone. Plasma proteomics demonstrated further differences between PASC-CVS and Recovered patients at approximately 18 months post-infection including enrichment of complement and coagulation associated proteins in those with prolonged cardiovascular symptoms. Together, these data provide a new insight into the role of chronic inflammation in PASC-CVS and present nanotechnology as a possible novel diagnostic approach for the condition.

microbiology↗

Improved prediction of chronological age from DNA methylation limits it as a biomarker of ageing

DNA methylation is associated with age. The deviation of age predicted from DNA methylation from actual age has been proposed as a biomarker for ageing. However, a better prediction of chronological age implies less opportunity for biological age. Here we used 13,661 samples (from blood and saliva) in the age range of 2 to 104 years from 14 cohorts measured on Illumina HumanMethylation450/EPIC arrays to perform prediction analyses. We show that increasing the sample size achieves a smaller prediction error and higher correlations in test datasets. We demonstrate that smaller prediction errors provide a limit to how much variation in biological ageing can be captured by methylation and provide evidence that age predictors from small samples are prone to confounding by cell composition. Our predictor shows a similar or better performance in non-blood tissues including saliva, endometrium, breast, liver, adipose and muscle, compared with Horvaths across-tissue age predictor.

bioinformatics↗