Geroscience has historically focused on extending lifespan and “healthspan”—the years free from debilitating chronic disease. However, a new perspective paper argues this framework is deeply flawed because it overlooks the gradual erosion of capacity that occurs even in ostensibly healthy individuals. The researchers introduce “Peakspan”: the period during which an individual maintains at least 90% of their peak functional performance in a specific physiological or cognitive domain. According to their multi-system analysis, most human biological systems reach maximal capacity in early adulthood, between the 20s and 30s.
Consequently, humans now spend the vast majority of their adult lives in a “healthy but declined” state, carrying a massive functional gap well before clinical disease is diagnosed.
The authors argue that extending Peakspan, rather than just healthspan, is the true functional manifestation of rejuvenative biomedical progress and is strictly necessary for sustained economic growth in aging societies. They advocate for a massive shift in how we measure and intervene in aging, leveraging artificial intelligence (AI) and “Deep Aging Clocks”. Instead of measuring chronological age deviation, these AI models would calculate a “delta-peak age,” estimating an individual’s proximity to their own historical maximum performance rather than a population average. By aggressively targeting the specific moment when function drops below 90% (the “Peakspan exit”), we can theoretically intervene before system-wide decline cascades into overt pathology. The paper essentially demands we stop accepting gradual functional deterioration as “normal” and start utilizing AI to optimize for maximal capacity throughout the life course.
Impact Evaluation: The impact score of this journal is 7.0, evaluated against a typical high-end range of 0–60+ for top general science, therefore this is a Medium impact journal.
While the paper avoids cellular pathway analysis (e.g., mTOR, AMPK), it forcefully reorients aging priorities toward organ-specific functional trajectories:
Cognitive: Fluid intelligence, including processing speed and working memory, peaks between ages 20 and 30. Conversely, crystallized intelligence peaks much later, between ages 45 and 54.
Cardiorespiratory: VO2max and maximum cardiac output peak in the early to mid-20s. Furthermore, gas-exchange efficiency (DLCO) decline accelerates after age 40. [Confidence: High]
Immune: Naïve T-cell export collapses rapidly after puberty, falling to 20% of pre-puberty levels by age 25. This effectively destroys the immune system’s Peakspan exceptionally early. [Confidence: High]
Endocrine: The paper highlights the decline of IGF-1, with serum levels in the late 70s dropping to 30-35% of young adult values.
Novelty
The framework shifts the therapeutic goalpost from “disease-free survival” to “preservation of ≥90% of absolute maximum personal capacity”.
It introduces the conceptual requirement for “delta-peak age” in AI clocks. This anchors biological age to an individual’s historical zenith rather than a generalized population mean. [Confidence: High]
Critical Limitations
Zero Actionable Interventions: As a theoretical framework, this paper completely lacks actionable insights regarding specific compounds, dosages, or lifestyle interventions required to actually extend Peakspan. It tells us what to measure, but not how to physically fix it. [Confidence: High]
The Baseline Data Problem: The entire concept relies on knowing an individual’s specific “peak”. Realistically, almost no one has comprehensive multi-omic, structural, and physiological baselines established during their 20s. Relying on retrospective inference of individual maxima introduces massive measurement error. [Confidence: Medium]
Unproven Reversibility: The paper heavily relies on the premise that identifying the “Peakspan exit” will allow for restorative interventions. However, it provides no empirical data demonstrating that a human who has dropped to 85% of their fluid cognitive peak can be therapeutically restored to ≥90%. [Confidence: High]
Development with Age: Unlike fluid intelligence (fast, novel problem-solving), crystallized intelligence strengthens as people get older, often peaking in middle age and holding steady into the 70s or 80s
“working memory, peaks between ages 20 and 30”
That really sucks folks. Explains why it’s easier for me to remember what happened 50 years ago than what happened 5 minutes ago.
