How Fast Are You Aging
- 6 days ago
- 17 min read
Why Your Pace of Aging Predicts Cancer Better Than Your Birthday
TL;DR: Why This Matters
The 60-second version: A 2026 Nature Medicine study found that younger generations are biologically aging faster than their birth year predicts — and that gap tracks with real increases in early-onset cancer risk. The tool that captures this, DunedinPACE, doesn't just estimate how old your body looks; it measures how fast you're aging right now, which is a number you can actually move.
What the evidence shows:
People born in the 1990s carry a biological age gap nearly 4x wider than people born in the late 1960s — reached in about 25 fewer years of birth cohorts. [Nature Medicine, 2026]
A wider biological age gap raised early-onset cancer risk by 8–22% per standard deviation, independent of inherited genetic risk. [Nature Medicine, 2026]
Organs age on independent timelines — brain, immune system, liver, and fat tissue each carry their own aging clock and their own disease signature. [npj Digital Medicine, 2026; Nature Aging, 2025]
Pace of aging, not a single biological-age snapshot, is the most actionable number, because it responds to sleep, metabolic health, and lifestyle change within months rather than years. [eLife, 2022; Nature Aging, 2023]
A high pace score is a signal worth investigating, not a diagnosis — on its own, it can't tell you which of three underlying systems (supply, allocation, or alarm) is driving it.
Why it matters: If a rising rate of early-onset cancer is connected to accelerated biological aging — and that pace of aging is measurable and, evidence suggests, modifiable — then waiting for symptoms or a standard screening age to act works against what the research shows. That reframes prevention as something to start measuring in your 30s and 40s, not your 60s.
In my practice, I see two 48-year-olds in the same week who don't belong in the same decade. Same birth certificate. Completely different capacity for repair, recovery, and resilience — one recovers from a hard training week in a day, the other is still flat three days later; one's fasting insulin looks like a 30-year-old's, the other's looks like a pre-diabetic's. For years the only way to describe that gap was clinical instinct: "she's aging well," "he's aging hard." Now there's a number for it, and a growing body of evidence suggests that number matters more than the one on your driver's license.
Cancer diagnosed before age 50 — early-onset cancer — is rising worldwide, and it's climbing even as smoking and heavy drinking fall. That paradox has stumped researchers for years. A June 2026 study in Nature Medicine from Washington University offers an unsettling lead: younger generations are aging faster on the inside, and that accelerated biological aging tracks with their cancer risk. This article walks through what that study found, what "biological age" actually measures, why the pace of aging matters more than a single snapshot, what's driving the acceleration, what the evidence says about slowing it down, and — importantly — what a biological age number can't tell you on its own.
Why Early-Onset Cancer Is Rising
The global rise in early-onset cancer is one of medicine's fastest-growing mysteries. According to a 2023 analysis in BMJ Oncology using Global Burden of Disease data, global incidence of cancer diagnosed before age 50 rose 79% between 1990 and 2019 — from about 1.82 million new cases a year to 3.26 million. The increase is steepest in high-income countries, including Australia, Canada, the United States, and the United Kingdom, and researchers project it will keep climbing: a further 31% rise in cases is projected by 2030.
Genetics alone doesn't explain a shift this fast — the human genome doesn't change meaningfully across two or three generations. For years, researchers have instead catalogued individual behavioral and environmental risk factors: obesity, poor diet, sedentary behavior, metabolic dysregulation, alcohol, and changes in the gut microbiome. Each one shows up in the data, but the contribution of any single factor is modest. That's the puzzle the WashU team set out to solve: what if these factors are all converging on a single, measurable pathway — accelerated biological aging?
The 2026 Study in Plain Terms
Dr. Yin Cao's team at Washington University School of Medicine in St. Louis used the "age gap" — a person's biological age minus their chronological age — as the central measurement. Biological age, in this study, was estimated with PhenoAge, a second-generation epigenetic and biochemical clock built from nine routine, widely available blood markers: albumin, creatinine, glucose, C-reactive protein, lymphocyte percentage, mean cell volume, red blood cell distribution width, alkaline phosphatase, and white blood cell count, combined with chronological age in a validated formula. A positive age gap means your biology looks older than your birth year would predict; a negative age gap means it looks younger.
The researchers asked two questions. First: has the age gap widened across generations? Second: does a wider gap predict cancer?
In the UK Biobank (more than 154,000 adults), people born between 1965 and 1974 carried a 0.23-standard-deviation wider age gap than people born between 1950 and 1954 — a measurable generational shift toward faster biological aging in just 15 years of birth cohorts. That wider gap mattered clinically: each additional standard deviation of biological age raised the risk of early-onset solid cancer by about 8% overall (hazard ratio 1.08), concentrated in lung, gastrointestinal, and uterine cancers. The lung cancer signal was striking — a 57% increase in risk per standard deviation. People in the highest age-gap group carried roughly 15% more early-onset cancer risk than those with the smallest gaps.
In the US All of Us Research Program (more than 10,000 adults), the generational shift was even sharper: people born in the 1990s carried a 0.92-standard-deviation wider age gap than those born in the late 1960s — nearly four times the UK Biobank shift in about 25 fewer years of birth cohorts. Each standard deviation of extra biological age raised cancer risk by 22%.
Two details make this more than a correlation to file away. First, the cancer signal was much weaker for the same cancer types diagnosed after age 55 — suggesting the age gap is capturing something specific to how a body ages early, not just aging in general. Second, the association survived adjustment for inherited risk, including telomere length and polygenic risk scores for both aging and cancer. Whatever the age gap is measuring, it isn't simply a proxy for genetics passed down at birth.
As Dr. Cao put it: "Our ultimate goal is to decode how modern environments become biologically embedded to drive cancer risk, transforming prevention from broad recommendations to personalized interventions."
Organ-Specific Aging: Where You Age Matters
The WashU study went a layer deeper than whole-body aging. By analyzing blood protein levels linked to specific organ systems, the researchers found that organs age on their own individual schedules — and that each organ's aging pattern carries its own disease signature:
An aged immune system tracked strongly with early-onset lung cancer, independent of whole-body aging.
Aged adipose (fat) tissue tracked with early-onset colorectal cancer, again independent of whole-body aging.
This organ-specific picture is being reinforced by parallel research. A February 2026 study in npj Digital Medicine used MRI and imaging data from more than 11,000 UK Biobank participants to build aging clocks for seven distinct organ systems: brain, heart, liver, kidney, pancreas, eye, and body composition. The pattern held: an accelerated age gap in a specific organ strongly predicted disease in that organ. Brain-aging models, for example, achieved an AUC of 0.82 for predicting future dementia — a strong result for a non-invasive biomarker. A separate 2025 proteomic-clock study across UK, US, and Chinese cohorts (more than 43,000 UK Biobank participants) found the same thing using blood protein signatures instead of imaging: the brain age gap alone predicted dementia with an AUC around 0.84, on par with combining several established clinical risk factors.
The clinical implication is straightforward and important: your body isn't aging as a single unit with one dial. It's a collection of systems — immune, metabolic, cardiovascular, neurological — each running its own clock, each capable of aging faster or slower than the others, and each carrying its own downstream disease risk. A single "biological age" number averages all of that together and can hide a fast-aging organ behind a normal-looking whole-body score.
Biological Age vs. the Candles on Your Cake
Chronological age is simply elapsed time — a fact of the calendar, not physiology. Biological age is an estimate of how worn your systems actually are, built from measurable data: blood chemistry, inflammatory markers, or the pattern of chemical tags (methylation) attached to your DNA. Two 48-year-olds can be a decade apart biologically, and that gap is where disease risk concentrates.
Aging clocks have evolved in three generations, each answering a different question:
First-generation clocks (like the original Horvath clock) were built simply to predict chronological age from DNA methylation — useful for forensics, less useful clinically. Second-generation clocks like PhenoAge and GrimAge were trained instead on mortality and disease outcomes, which is why they're better at flagging risk. But both generations share a limitation: they're a snapshot. They tell you where you are on the odometer. They don't tell you whether you're still accelerating, decelerating, or holding steady — and that distinction is exactly what determines whether an intervention is working.
The Number That Matters Most: Your Pace of Aging
DunedinPACE, developed by Dr. Daniel Belsky and colleagues using the Dunedin Study — a New Zealand birth cohort followed for over four decades — does something no earlier clock does: it reports a rate, not a position.
It was built from 20 years of repeated measurement across 19 organ-system biomarkers (cardiovascular, metabolic, renal, hepatic, immune, dental, and pulmonary function) in the same group of people from age 26 to 45. Because the same people were measured repeatedly over two decades, the algorithm could be trained on an actual rate of physiological decline — not just a single time point compared against age.
The values are intuitive:
1.0 means you're aging one biological year per calendar year — the population average.
1.3 means you're aging roughly 30% faster than the clock on the wall.
0.8 means you're aging roughly 20% slower.
DunedinPACE has since been validated in more than 65 cohorts across 17 countries and 6 ethnic ancestry groups, with over 300 peer-reviewed publications reporting its findings. It has several design advantages that matter clinically:
It was derived from longitudinal data in healthy adults, before chronic disease onset — so it captures early physiological drift, not late-stage disease.
It was built in a single birth cohort, avoiding the generational and measurement confounding that can distort clocks trained on data pooled across decades.
It was specifically trained to be responsive to intervention — and in comparative trials, DunedinPACE is consistently the most sensitive aging clock to short-term behavioral or pharmacological change.
What a Pace Score Can — and Can't — Tell You
This is the point where a lot of longevity content oversimplifies, so it's worth being precise. A DunedinPACE reading above 1.0 is not a diagnosis. It is not a prognosis. It doesn't tell you that you will get cancer, and a "good" score doesn't mean you're in the clear. What it tells you is a rate — a scoreboard number.
Think of it as a car's speedometer without a dashboard. It tells you how fast the car is moving. It doesn't tell you whether the engine, the transmission, or the fuel line is the reason. That's the missing piece in most consumer-facing "biological age" marketing: a number alone doesn't identify the driver, and reacting to a number without finding the driver is how people end up buying supplements or protocols that don't address what's actually accelerating their aging.
Clinically useful biological age testing pairs the pace (the scoreboard) with a look at what's allocating the body's resources toward defense instead of repair — chronic inflammation, unresolved stress physiology, metabolic dysfunction, poor sleep architecture, gut dysfunction — and works backward from there. The number is the invitation to look further, not the endpoint of the workup.
For a 45-and-up professional deciding where to put their attention, this distinction matters practically: pace is the better target precisely because it responds to what you do. It moves over months, not years. An odometer-style clock changes slowly and mostly reflects history you can't undo. A speedometer changes with what you do starting this week.
What Is Driving Accelerated Aging in Younger Generations?
If younger generations are aging faster on average, something is pushing the speedometer up across an entire population. The "hallmarks of aging" — the biological processes considered the root drivers of aging, including chronic low-grade inflammation ("inflammaging"), cellular senescence, epigenetic alterations, mitochondrial dysfunction, and immune dysregulation — are heavily influenced by modern environment and behavior. Researchers are actively investigating several converging factors:
Ultra-processed foods (UPFs). Multiple studies published in 2024–2025 link high UPF consumption to accelerated biological aging, independent of overall diet quality or calorie intake. The proposed mechanisms include chronic low-grade inflammation, disruption of the gut microbiome, and direct epigenetic effects from additives, emulsifiers, and processing byproducts. This is an active and evolving area of research; the associations are consistent, but the field is still working out causal mechanisms.
Metabolic dysfunction. Insulin resistance and poor glucose control are among the most consistently identified drivers of systemic inflammation and biological age acceleration. Diabetic and pre-diabetic metabolism accelerates aging through oxidative stress, chronic inflammation, and epigenetic changes in insulin-sensitive tissue.
Sedentary behavior. Objectively measured sedentary time (from wearables, not self-report) correlates with epigenetic age acceleration across multiple studies. The inverse holds too: higher physical activity is consistently associated with slower biological aging across multiple clock measures, independent of body weight.
Sleep disruption. A landmark 2026 study led by researchers at Columbia University, published in Nature, built a "Sleep Chart" relating self-reported sleep duration to 23 biological aging clocks across 17 organ systems in nearly 500,000 UK Biobank participants, using imaging, proteomic, and metabolomic data. The relationship was consistently U-shaped: both short sleep (under 6 hours) and long sleep (over 8 hours) were associated with faster aging across nearly every organ system studied, including the brain, heart, lungs, and immune system. The lowest biological age gaps clustered in a narrow window — between 6.4 and 7.8 hours per night, varying slightly by organ and sex. Short and long sleep were also linked to higher rates of COPD, asthma, gastritis, reflux, depression, and diabetes. The authors are careful to note this is observational: sleep duration doesn't necessarily cause faster organ aging on its own — it may also be a marker of other stressors — but the association is remarkably consistent across three independent measurement technologies.
Environmental exposures. Air pollution, endocrine-disrupting chemicals (found in plastics, personal care products, and food packaging), and other environmental toxins have been associated with a widened gap between chronological and biological age across multiple population studies.
No single factor above explains the generational shift on its own — that's precisely the point. The hallmarks-of-aging framework suggests these pressures converge on a shared set of cellular processes, which is why addressing them individually (one supplement, one diet tweak) tends to underperform addressing the pattern as a whole.
A Systems Problem, Not a Single Number
This is worth stating plainly, because a lot of longevity marketing gets it backwards: reducing longevity to one biological age number is exactly the kind of oversimplification that leads people astray. A pace-of-aging score is useful precisely because it's a signal that something needs investigating — not because it's a complete diagnosis on its own.
At The Johnson Center, we think about this using a four-layer framework:
Supply → Allocation → Alarm → Scoreboard
Supply is what your body has to work with — sleep, nutrients, oxygen delivery, mitochondrial capacity.
Allocation is where that supply gets spent — on repair and growth, or diverted to defense.
Alarm is what's driving that diversion — chronic stress physiology, unresolved inflammation, a gut or immune system perceiving ongoing threat.
Scoreboard is what shows up on a test: your labs, your biological age, your DunedinPACE score.
A biological age or pace-of-aging number lives at the Scoreboard layer. It's a real, useful, evidence-backed signal — but it can't tell you, by itself, whether the driver sits in Supply, Allocation, or Alarm. Two people with the same DunedinPACE reading of 1.2 can have completely different reasons for it: one is under-slept and metabolically dysregulated, the other has an unresolved chronic inflammatory process. The same score, two different treatment plans. That's the piece a standalone biological age test — however well-validated — cannot supply on its own, and it's why pace of aging is best used as the start of a systems-based workup rather than the end of one.
Common Misconceptions About Biological Age
"A high score means I'm going to get cancer or die young."
No. The 2026 Nature Medicine study found an association between a wider age gap and increased risk, not certainty. Risk ratios in the range of 8–22% per standard deviation describe a shifted probability across a population, not a personal prophecy. Population-level risk and individual outcome are different things. And specific interventions can decrease your pace of aging.
"If my labs are normal, my biological age must be fine."
Not necessarily. Standard annual labs check for the presence of diagnosable disease. They weren't designed to detect the rate of underlying physiological change, which is exactly what biological age and pace-of-aging clocks are built to capture. Normal labs mean you don't have the disease they tested for — they don't rule out an accelerated trajectory.
"One test is enough to know my aging story."
A single DunedinPACE or PhenoAge reading is a data point, not a trend line. Because pace of aging is intervention-sensitive, retesting after a meaningful change (typically 6–12 months) is what turns a number into information you can act on.
"Biological age testing is only useful once I'm already sick."
The opposite is closer to true. Because these clocks were validated in largely healthy, disease-free cohorts before chronic disease onset, their most useful window is precisely the one before anything shows up on a conventional scan or blood panel.
Why This Should Change How You Think About Prevention
If accelerated aging is a shared root beneath multiple forms of early disease, the default model of medicine — wait for symptoms, wait until you hit the standard screening age — is working against the evidence. The actionable move is to measure the pace while still healthy, identify which systems are aging fastest, and address the underlying drivers before anything becomes visible on a scan or in a diagnosis.
Bending the Curve: Evidence-Based Interventions
The levers that move pace of aging in controlled studies are unglamorous, mostly free, and consistent with decades of general health guidance. Here is what the evidence actually supports — and, just as important, the evidence's limits.
1. Caloric restriction and fasting. The CALERIE trial (Comprehensive Assessment of Long-Term Effects of Reducing Intake of Energy) is the first randomized controlled trial of long-term caloric restriction in healthy, non-obese humans. Participants who sustained roughly 25% caloric restriction over two years showed a 2–3% slowing in DunedinPACE (effect size d = −0.25 to −0.29). Researchers estimate that magnitude of change corresponds to a 10–15% reduction in mortality risk — comparable to a smoking-cessation intervention, though this projection is extrapolated from other longitudinal data, not measured directly as mortality in the trial itself. Notably, the caloric-restriction effect showed up on DunedinPACE but not on the static PhenoAge or GrimAge clocks, which is itself informative: it suggests pace-of-aging measures pick up a kind of change that snapshot clocks miss.
2. Exercise: resistance and aerobic training. In one controlled study, eight weeks of combined aerobic and resistance training (three sessions a week, 60 minutes) reduced epigenetic age by roughly two years in sedentary women aged 50–70 — but this effect was concentrated entirely in the subgroup whose biological aging was already accelerated at baseline. Women who started with slower-than-average aging showed no significant additional change. This is a meaningful nuance: exercise in this study looks less like a universal rejuvenation and more like a correction for those already running hot. Separately, cardiorespiratory fitness (VO2 max) remains one of the most reproducible predictors of longevity in the broader literature — a meta-analysis pooling more than 100,000 adults found that each 1-MET increase in fitness was associated with a 13% reduction in all-cause mortality and a 15% reduction in cardiovascular events.
3. Metabolic health: glucose and insulin. Keeping fasting insulin low (ideally below 5 μIU/mL), ApoB below 80 mg/dL, and hs-CRP below 1.0 mg/L reflects minimal metabolic risk and correlates with slower biological aging across multiple clocks. Emerging trial data on GLP-1 receptor agonists like semaglutide show a related signal worth watching closely: a 32-week randomized, placebo-controlled trial found semaglutide slowed DunedinPACE by approximately 9% and produced significant improvements across four additional epigenetic clocks (PhenoAge, GrimAge V1, GrimAge V2, and PCGrimAge). The important caveat: that trial was conducted in 84 adults with HIV-associated lipohypertrophy and metabolic dysfunction-associated liver disease — not a general healthy population — so this should be read as an early, promising mechanistic signal rather than established evidence that GLP-1 drugs slow aging broadly. Larger trials in general populations are needed before drawing firmer conclusions.
4. Sleep quality. Protecting sleep in that 6.4–7.8-hour window supports cellular repair, helps clear metabolic waste from the brain via the glymphatic system, and appears to reduce the epigenetic damage associated with both chronic sleep deprivation and chronic oversleeping.
5. Reducing chronic inflammation. Managing chronic stress physiology, eating a whole-food diet, and minimizing ultra-processed food intake helps keep inflammaging — chronic low-grade inflammation — in check, one of the primary proposed drivers of accelerated biological aging.
A faster DunedinPACE is a signal, not a sentence. The entire clinical reason to measure it is that, unlike your birth year, it can be moved — and the interventions with the best evidence behind them are the least exotic ones.
How to Measure It
Epigenetic testing reads patterns of DNA methylation to estimate biological age, pace of aging, and organ-specific ages from a blood sample. TruDiagnostic's TruAge panel, for example, reports DunedinPACE alongside biological age, organ-specific ages, and telomere length in a single test.
On its own, an epigenetic panel is a starting point, not a full picture. Pairing it with the standard-but-underused longevity blood markers — the nine PhenoAge inputs, plus hs-CRP, ApoB, and fasting insulin — builds a more complete view of your health trajectory than a single birthday or a single test ever could. Because pace-of-aging measures are intervention-sensitive, retesting on a 6–12 month cadence after a targeted intervention is what converts a number into a feedback loop rather than a one-time curiosity.
At The Johnson Center, we use TruAge to check your phenoage and pace of aging. Our program using the Cellular Intelligence Protocol™ maps what's actually driving your pace of aging — supply, allocation, or alarm — then sequences interventions in the order your biology needs, rather than treating a pace score as a finish line.
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FAQ
How do I know how fast I'm aging?
A pace-of-aging clock like DunedinPACE, measured from DNA methylation in a blood sample, gives a speed: 1.0 is average, above 1.0 is faster, below 1.0 is slower. It's available through epigenetic panels such as TruDiagnostic's TruAge.
What is DunedinPACE?
DunedinPACE is a third-generation epigenetic biomarker derived from 20 years of longitudinal data tracking 19 organ-system biomarkers in the Dunedin birth cohort. Unlike biological age clocks that act as odometers, DunedinPACE acts as a speedometer — reporting how fast you're aging right now. It's been validated in over 65 cohorts across 17 countries and is the most intervention-sensitive aging clock currently available.
What's the difference between biological and chronological age?
Chronological age is how long you've lived; biological age is how worn your systems are, estimated from blood biomarkers (like PhenoAge) or DNA methylation. The gap between them — and how fast it's growing — is what predicts disease risk.
Why is early-onset cancer rising?
It isn't fully solved, but a 2026 Nature Medicine study links it partly to accelerated biological aging in younger generations: a wider biological-to-chronological age gap predicted more early-onset solid cancer, independent of inherited risk. Global incidence of cancer before age 50 has risen 79% since 1990. Generational shifts toward ultra-processed diets, sedentary lifestyles, metabolic dysfunction, and environmental exposures are suspected contributors.
What drives accelerated aging?
The primary suspected drivers include chronic low-grade inflammation (inflammaging), insulin resistance and metabolic dysfunction, poor sleep quality, sedentary behavior, high consumption of ultra-processed foods, and environmental toxin exposure. These factors are thought to converge on the hallmarks of aging at the cellular and epigenetic level.
Can I lower my biological age or pace of aging?
Yes. DunedinPACE is highly responsive to behavior. The CALERIE trial showed that caloric restriction slowed the pace of aging by 2–3% in a randomized controlled trial. Building muscle and aerobic fitness, improving sleep, stabilizing glucose, reducing inflammation, and losing excess visceral fat are the strongest, best-supported levers.
Does a single biological age test tell me everything I need to know?
No. A pace-of-aging score identifies that something is worth investigating; it doesn't identify what. Two people can share the same score for very different underlying reasons. A meaningful workup pairs the pace score with metabolic, inflammatory, and organ-specific markers to find the actual driver.
How often should I retest?
Because DunedinPACE is sensitive to behavioral and clinical change, a 6–12 month retest after a targeted intervention is a reasonable cadence to see whether the pace is actually moving — rather than testing once and treating the number as fixed.
Sources
• Tian, R., Zong, X., Ren, D., et al. (2026). Biological aging and generational shifts in early-onset cancer risk. Nature Medicine. https://www.nature.com/articles/s41591-026-04448-w
• (2026). Imaging-based organ-specific aging clock predicts human diseases and longevity. npj Digital Medicine. https://www.nature.com/articles/s41746-026-02488-7
• Organ-specific proteomic aging clocks predict disease and longevity across diverse populations. (2025). Nature Aging. https://www.nature.com/articles/s43587-025-01016-8
• Belsky, D.W., et al. (2022). DunedinPACE, a DNA methylation biomarker of the pace of aging. eLife. https://elifesciences.org/articles/73420
• Waziry, R., Belsky, D.W., et al. (2023). Effect of long-term caloric restriction on DNA methylation measures of biological aging in healthy adults from the CALERIE trial. Nature Aging. https://www.nature.com/articles/s43587-022-00357-y
• Levine, M.E., et al. (2018). An epigenetic biomarker of aging for lifespan and healthspan (PhenoAge). Aging (Albany NY).
• Li, X., et al. (2023). Global trends in incidence, death, burden and risk factors of early-onset cancer from 1990 to 2019. BMJ Oncology. https://bmjoncology.bmj.com/content/2/1/e000049
• Corley, M.J., et al. (2026). Epigenetic aging and treatment response to semaglutide in people with HIV. https://pubmed.ncbi.nlm.nih.gov/40791720/
• da Silva Rodrigues, G., et al. (2023/2024). Eight weeks of physical training decreases 2 years of DNA methylation age of sedentary women. Research Quarterly for Exercise and Sport. https://pubmed.ncbi.nlm.nih.gov/37466924/
• Wen, J., et al. (2026). Sleep chart of biological ageing clocks in middle and late life. Nature. https://www.cuimc.columbia.edu/news/too-little-sleep-and-too-much-associated-faster-aging
• Kodama, S., et al. (2009). Cardiorespiratory fitness as a quantitative predictor of all-cause mortality and cardiovascular events. JAMA. https://jamanetwork.com/journals/jama/fullarticle/1108396
• TruDiagnostic — TruAge / DunedinPACE. https://www.trudiagnostic.com/truage
• WashU Medicine Press Release (2026). Faster aging in younger generations linked to rise in early-onset cancer. https://medicine.washu.edu/news/faster-aging-in-younger-generations-linked-to-rise-in-early-onset-cancer/
Barbara Johnson, MD — Founder & Medical Director, The Johnson Center: Functional Health & Longevity. Virginia Beach · Blacksburg · Telemedicine across Virginia.
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