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Methylation metrics in patients with severe depression suggest accelerated cell aging




According to an interdisciplinary team at the University of California, San Francisco, cells in individuals with major depressive disorder (MDD) have higher than expected methyl in certain parts of their DNA compared to cells in healthy individuals without MDD. Found to show a rate of conversion (UCSF) in collaboration with scientists and others.

Methylation of specific gene sets (DNA methylation clocks) usually changes in a predictable way with age, but the rate of these changes varies from person to person. Methylation patterns in individuals with MDD suggested that their cell age was accelerated on average compared to matched healthy controls.

MDD is one of the most prevalent health concerns in the world. According to the World Health Organization, about 300 million people (4.4% of the population) suffer from some form of depression.

According to the team survey (“GrimAge, an epigenetic predictor of mortality, is accelerated in major depressive disorder, “) Announced in Translation psychiatryBlood samples from MDD patients were analyzed for methylation patterns using the “GrimAge” clock, a mathematical algorithm designed to predict the remaining lifespan of an individual based on cell methylation patterns. It was.

Individuals with MDD show significantly higher GrimAge scores, suggesting an increased risk of death compared to healthy individuals of the same age. This is an average of about 2 years on the GrimAge clock.

“Major depressive disorder (MDD) is associated with premature death and is an independent risk factor for a wide range of illnesses, especially age-related illnesses such as cardiovascular disease, diabetes and Alzheimer’s disease. The pathophysiology underlying the rate of increase in expressive disorders is unknown. MDD has been proposed to represent a condition in which cell aging is accelerating, and several methods of measuring cell aging have been developed in recent years. It has been done, “the researchers write.

“Among such metrics, an estimator of biological age based on predictable age-related patterns of DNA methylation (DNAm), the so-called” epigenetic clock, “has accelerated mental illness. It has been shown to be particularly promising in its ability to capture aging. The recently developed DNAm metric, known as the “Grim Age,” is unique in that it is trained on time-to-death data and outperforms its predecessor in predicting both morbidity and mortality. Still, GrimAge has not been investigated by MDD.

“Here we measured GrimAge in 49 physically healthy non-medicated individuals with MDD and 60 age-matched healthy controls. Those with MDD measured GrimAge in healthy controls (‘AgeAccelGrim'”. ), It was found that GrimAge was significantly larger than the chronological age (‘AgeAccelGrim’).p= 0.001), median excessive cell senescence for 2 years. This difference remained significant after controlling gender, current smoking status, and body mass index (p= 0.015). “

“These findings are consistent with previous proposals for accelerated cellular senescence in MDD, but are the first to demonstrate this with epigenetic metrics that predict early mortality.”

The title book Great Depressive Disorder.
MDD is one of the most prevalent health concerns in the world. According to the World Health Organization, about 300 million people (4.4% of the population) suffer from some form of depression. [designer491/Getty Images]

Interestingly, individuals with MDD were screened for physical health prior to entering the study and showed no apparent signs of age-related medical conditions. The methylation pattern associated with mortality risk persisted even after considering lifestyle factors such as smoking and BMI.

These findings provide new insights into the increase in condition-related mortality and morbidity, suggesting that there is a fundamental biological mechanism that accelerates cellular senescence in some MDD patients. Researchers say.

“This shifts the way we understand depression from pure or systemic illnesses that are confined to brain processes,” said Katerina Protsenko, a UCSF medical student and lead author of the study. Stated. “This should fundamentally change the way we tackle depression and our way of thinking about it as part of our overall health.”

“One of the notable things about depression is that patients have an unexpectedly high rate of age-related physical illness and premature mortality, even after considering suicide and lifestyle,” said a psychiatrist. Added member Owen Walkowitz, MD. “It has always been a mystery, and it has led us to look for signs of aging at the cellular level,” said Weill Institute for Neurosciences at UCSF, co-lead author of the study.

There are many lifespan algorithms based on methylation, but only GrimAge is based on methylation patterns, especially those related to mortality. Researchers point out that it is not yet clear whether depression causes changes in methylation in certain individuals, or whether both depression and methylation are associated with another underlying factor.

Some individuals may have a genetic predisposition to generate specific methylation patterns in response to stressors, but this has not been well studied. Changes in methylation patterns have previously been observed in individuals with post-traumatic stress disorders.

In the future, researchers hope that pharmacological treatment or treatment will reduce MDD-related methylation changes in the hope that they will normalize the cellular senescence process of affected individuals before MDD progresses. I want to decide if I can do it. Although the GrimAge methylation clock is associated with mortality in other populations, no studies have yet determined whether this methylation pattern also predicts MDD mortality.

“As we continue our research, we would like to see if working with MDD with antidepressants and other therapies alters methylation patterns, which makes these patterns dynamic and altered. We know we can, “says Dr. Synthia Mellon. , Professor of Ob / Gyn & Reproductive Sciences at UCSF, and co-author of the study.

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