The SARS-CoV-2 infection determines the COVID-19 syndrome characterized, in the worst cases, by severe respiratory distress, pulmonary and cardiac fibrosis, inflammatory cytokine release, and immunosuppression. This condition has led to the death of about 2.15% of the total infected world population so far. Among survivors, the presence of the so-called persistent post-COVID-19 syndrome (PPCS) is a common finding. In COVID-19 survivors, PPCS presents one or more symptoms: fatigue, dyspnea, memory loss, sleep disorders, and difficulty concentrating. In this study, a cohort of 117 COVID-19 survivors (post-COVID-19) and 144 non-infected volunteers (COVID-19-free) was analyzed using pyrosequencing of defined CpG islands previously identified as suitable for biological age determination. The results show a consistent biological age increase in the post-COVID-19 population, determining a DeltaAge acceleration of 10.45 ± 7.29 years (+5.25 years above the range of normality) compared with 3.68 ± 8.17 years for the COVID-19-free population (p < 0.0001). A significant telomere shortening parallels this finding in the post-COVID-19 cohort compared with COVID-19-free subjects (p < 0.0001). Additionally, ACE2 expression was decreased in post-COVID-19 patients, compared with the COVID-19-free population, while DPP-4 did not change. In light of these observations, we hypothesize that some epigenetic alterations are associated with the post-COVID-19 condition, particularly in younger patients (< 60 years).

Introduction & Backgroundthe SARS-CoV-2 infection determines the COVID-19 syndrome characterized, in the worst cases, by severe respiratory distress, pulmonary and cardiac fibrosis, inflammatory cytokines release, and immunodepression. This condition has led to the death of about 2.15% of the total infected world population so far. Among survivors, the presence of the so-called post-COVID19 syndrome (PPCS) is a common finding. In patients who survived the SARS-CoV-2 infection, overt PPCS presents one or more symptoms such as fatigue, dyspnea, memory loss, sleep disorders, and difficulty concentrating. The pathophysiology of PPCS is currently poorly understood, and whether epigenetic mechanisms are involved in this process is unexplored.Methods & ResultsIn this study, a cohort of 117 COVID19 survivors (post-COVID19) and 144 non-infected volunteers (COVID19-free) were analyzed using pyrosequencing of defined CpG islands previously identified as suitable for biological age determination. Besides, telomere length (TL) and ACE2 and DPP4 receptor expression were determined. The results show a consistent biological age increase in the post-covid population (58,44 ± 14,66 ChronoAge Vs. 67,18 ± 10,86 BioAge, P<0,0001), determining a DeltaAge acceleration of 10,45 ± 7,29 years (+5.25 years above range of normality) compared to 3,68 ± 8,17 years for the COVID19-free population (P<0,0001). A significant telomere shortening parallels this finding in the post-COVID19 cohort compared to COVID19-free subjects (post-COVID19 TL: 3,03 ± 2,39 Kb vs. COVID19-free: 10,67 ± 11,69 Kb; P<0,0001). Additionally, ACE2 expression was decreased in post-COVID19 patients compare to COVID19-free, while DPP-4 did not change.ConclusionIn light of these observations, we hypothesize that some epigenetic alterations are associated with the post-COVID19 condition, particularly in the younger (<60 years). Although the consequences of such modifications on the long-term clinical outcome remain unclear, they might indicate a direction to investigate the pathophysiological basis of the post-COVID19 syndrome.

Background The present study investigates whether epigenetic differences emerge in the heart of patients undergoing cardiac surgery for an aortic valvular replacement (AVR) or coronary artery bypass graft (CABG). An algorithm is also established to determine how the pathophysiological condition might influence the human biological cardiac age. Results Blood samples and cardiac auricles were collected from patients who underwent cardiac procedures: 94 AVR and 289 CABG. The CpGs from three independent blood-derived biological clocks were selected to design a new blood- and the first cardiac-specific clocks. Specifically, 31 CpGs from six age-related genes, ELOVL2, EDARADD, ITGA2B, ASPA, PDE4C, and FHL2, were used to construct the tissue-tailored clocks. The best-fitting variables were combined to define new cardiac- and blood-tailored clocks validated through neural network analysis and elastic regression. In addition, telomere length (TL) was measured by qPCR. These new methods revealed a similarity between chronological and biological age in the blood and heart; the average TL was significantly higher in the heart than in the blood. In addition, the cardiac clock discriminated well between AVR and CABG and was sensitive to cardiovascular risk factors such as obesity and smoking. Moreover, the cardiac-specific clock identified an AVR patient's subgroup whose accelerated bioage correlated with the altered ventricular parameters, including left ventricular diastolic and systolic volume. Conclusion This study reports on applying a method to evaluate the cardiac biological age revealing epigenetic features that separate subgroups of AVR and CABG.