ROCHESTER, Minn. — Senescence is an aspect of aging that involves a biological dysfunction that occurs in response to repetitive stressors. Biological aging is associated with an increase in the incidence of cardiovascular disease, but whether heart failure is itself a senescent process independent of age is less clear.
Senescent cells acquire a phenotype — characteristics that are genetically related — that may lead to inflammation and induce senescence in neighboring cells, which also can contribute to cardiac deterioration. The increasing sophistication of artificial intelligence (AI) and machine learning have opened new opportunities to study physiologic age, senescence and cardiovascular mortality.
A four-year pilot study by Mayo Clinic researchers, using an AI-enabled ECG algorithm, suggests that the progression of heart failure is a senescent phenomenon associated with indicators of accelerated aging. These indicators include progenitor stem cells with reduced telomerase activity and increased levels of plasma senescence-associated secretory phenotype proteins.
The findings, published in Mayo Clinic Proceedings, suggest stem cell niches may acquire a senescent phenotype in heart failure, which might impact endogenous potential for healing and recovery. With further research, senolytic therapy may be considered for a future role in treatment of heart failure, the study concludes.
“Senescence and aging are well-described components of the pathophysiology of heart failure, and our pilot study aimed to ascertain whether the onset of heart failure is a senescent process independent of age,” says Barry Boilson, M.D., a Mayo Clinic cardiologist and the study’s first author.
“The findings suggest that heart failure may promote a senescent phenotype independent of chronological age, and we also show for the first time that the AI ECG shows a phenotype of cardiac aging in heart failure beyond the patient’s chronological age. This phenotype appears to be associated with cellular and molecular markers of senescence.”
The findings indicate that AI ECG may offer noninvasive opportunities to assess response to senolytic therapy in patients with heart failure, Dr. Boilson says.
The study, conducted from 2016 to 2020, involved the analysis of CD34+ progenitor hematopoietic stem cells. The AI algorithm was used to determine cardiac age and the gap between a patient’s cardiac age and chronological age.
Further investigation in other stem cell populations in cardiac tissue could pave the way for studies to assess the potential benefits of senolytic drug therapy to reduce or reverse the effects of heart failure-related cardiac aging, Dr. Boilson says.
Funding for the study was provided by the Mayo Clinic Department of Cardiovascular Medicine. Co-authors with Dr. Boilson are Dhivya Vadhana Meenakshi-Siddharthan, Ph.D.; Christopher Livia, Ph.D.; Timothy Peterson; Paul Stalboerger; Steven Zincke; Zachi Attia, Ph.D.; Alfredo Clavell, M.D.; Paul Friedman, M.D.; Suraj Kapa, M.D.; Peter Noseworthy, M.D.; Marissa Schafer, Ph.D.; John Stulak, M.D.; and Atta Behfar, M.D., Ph.D.
The post Heart failure induces cardiac and stem cell aging, Mayo Clinic study finds appeared first on Mayo Clinic News Network.
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