Cutting Out Just a Muffin a Day Can Make You Age More Slowly, Study Finds

Death comes for us all. Aging, maybe not.

It sounds preposterous, but plenty of animals—from the lowly jellyfish to naked mole rats and giant tortoises—show negligible signs of aging. Some animals are even “biologically immortal,” escaping the gradual deterioration of physiological functions as the clock ticks on.


One theory, the geroscience hypothesis, proposes that aging is due to a myriad of molecular changes that accumulate over time. Dubbed the hallmarks of aging, these “red flags” range from genetic mutations to chronic inflammation. As we age, the genome gradually breaks down. Telomeres, the DNA “caps” that protect chromosomes, waste away. The cell’s energy factory, the mitochondria, slowly disintegrate.

But it’s not all bad news: by hunting down contributors to aging, we can develop more sophisticated methods to combat these molecular processes. In turn, the treatments can also potentially reverse aging at the molecular level.

This week, a new analysis from one of the largest anti-aging studies to date found that cutting calories by 25 percent for two years slowed the pace of aging. Called CALERIE, or the Comprehensive Assessment of Long-term Effects of Reducing Intake of Energy trial, the study was the first randomized controlled study—a gold standard—to examine one of the most prominent theories in longevity: that cutting calories without sacrificing nutrients promotes healthy longevity.

Initial results from the trial found that the diet rewired multiple metabolic and immune responses to promote health. The new results went further, asking: can a two-year modest cut in calories alter your biological age?

Spoiler alert: yes and no. Although reducing calories didn’t change the volunteers’ biological age compared to people who ate to their hearts’ desire, it slowed the rate of aging—that is, how rapidly a person ages based on biological measures.

Don’t brush those results off. Even slowing aging by just two percent corresponds to a 10-15 percent reduction in mortality risk, which is similar to quitting smoking, the authors said.

“Our study found evidence that calorie restriction slowed the pace of aging in humans” said study author Dr. Calen Ryan at Columbia’s Butler Aging Center.

Tick Tock Goes the Clock

We all know people who look and behave younger—or older—than their age. Scientists have long known that your chronological age—that is, the years you count on your birthday—is often different than your biological age. Recent studies show that peoples’ biological age is more predictive of their chances of getting age-related diseases, such as hypertension, diabetes, heart disease, cancer, and dementia.

The question is, how do you measure your biological age?

One popular solution is using DNA methylation (DNAm) clocks. As we age, parts of our DNA become dotted with a chemical group that silences the gene, in a process called methylation. A decade ago, scientists found that DNA methylation can closely predict a person’s chronological age. These first-generation clocks used machine learning to compare samples spanning from teenagers to the elderly to extract patterns from DNA methylation as a proxy for aging.

But the results weren’t helpful. The clocks struggled to predict age-related diseases or the risk of death, making them inept for early intervention, the authors explained.

Flash forward five years, and second-generation DNAm clocks rocked the geroscience field. Rather than chronological age, these clocks aimed to better quantify biological age by analyzing mortality risk. For example, the PhenoAge clock, developed by a team at the University of California, Los Angeles (UCLA) added clinical biomarkers such as white blood cell counts—a reflection of immune system health—into the DNA methylation aging model.

GrimAge, another DNAm clock developed at UCLA, also honed in on age-related diseases. Using machine learning, the clock was trained on DNA methylation patterns specifically associated with smoking, cardiovascular disease, and cancer—essentially focusing the algorithm on hunting down age-related diseases. Compared to first-generation clocks, both PhenoAge and GrimAge were far more powerful predictors of mortality and age-related diseases.

But they weren’t perfect. Although they had improved potential for testing aging interventions, they struggled with reliability.

Enter the third wave of DNAm clocks. If PhenoAge and GrimAge were odometers—capturing the biological aging already experienced—these clocks are speedometers. DunedinPACE (Pace of Aging Computed from the Epigenome) is a popular one: it captures the pace of aging rather than age itself. Developed in a longitudinal study in New Zealand, the algorithm uses an exceptionally long list of health measures to capture each person’s health deterioration as they age.

CALERIE Conundrum

The new analysis used all three clocks—PhenoAge, GrimAge, and DunedinPACE—to see if reducing calorie intake delayed biological aging.

The data came from blood samples of 200 volunteers in the CALERIE Phase 2 trial. The multi-center randomized controlled study was the largest yet examining caloric restriction as an anti-aging intervention. The volunteers were a diverse bunch, ranging from 21 to 50 years old and comprised of different genders and ethnicities.

The control group had it easy: they could go about their daily eating habits. Those in the restriction arm cut a quarter of their daily calorie intake and attended behavioral counseling sessions to help sustain their diet.

Perhaps unsurprisingly, not everyone stuck to their regime—the average calorie cut was roughly 12 percent, about a muffin every day. Even so, people on the restricted diet decreased their rate of aging by two to three percent as measured with DunedinPACE. It doesn’t sound like much, but according to one estimate it cuts mortality risk up to 15 percent, boosting cardiovascular and metabolic health while slowing age-related bodily changes.

Then came the shocker: restricting calories didn’t impact peoples’ biological age, as measured with both PhenoAge and GrimAge clocks. There were multiple reasons: for one, the trial lasted for only two years, and these clocks measure aging factors up to a specific point in time. In other words, the intervention may be too brief to change a lifetime of dietary habits and history, which are etched into the DNA epigenome. The team was also unable to follow up with the participants beyond the two-year mark, when the study ended, which may have revealed longer-term health benefits.

“This is an interesting study…it suggests that measures of aging from DNA may slow, but does not report on any physical or functional changes in aging,” said Dr. Duane Mellor at Aston Medical School in Birmingham, U.K., who was not involved in the study.

Feast or Fast?

To the authors, the study is just the first step in hunting down why people age—and how we can potentially slow or reverse the process.

“The purpose of DNAm analysis in CALERIE was to evaluate intervention effects at the molecular level, where aging processes are posited to originate,” said the authors.

A follow-up trial is in the works to see if cutting calories has long-term effects on healthy aging. But perhaps more impactful is the use of DNAm clocks to assess aging interventions. Scientists have long identified multiple therapies that could improve healthspan in animal models. But because human aging takes decades to cause diseases, it’s difficult to assess the efficacy of potential treatments.

“Humans live a long time,” said study author Dr. Daniel Belsky, “so it isn’t practical to follow them until we see differences in aging-related disease or survival. Instead, we rely on biomarkers developed to measure the pace and progress of biological aging over the duration of the study.”

For now, the study showed that DNAm clocks can efficiently tag-team with anti-aging interventions to assess their efficacy.

“Our findings are important because they provide evidence from a randomized trial that slowing human aging may be possible. They also give us a sense of the kinds of effects we might look for in trials of interventions that could appeal to more people, like intermittent fasting or time-restricted eating,” said Ryan.

Image Credit: fancycrave1 from Pixabay


* This article was originally published at Singularity Hub

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