Blood biomarker profiling will be increasingly important in the coming years

The gap

Evidence profile

Sourced from the future work of the source papers, classified as general, drawn from work published between 2024 and 2026, spanning 3 journals. Those papers have been cited 34 times in total.

Supporting evidence — 3 representative gaps

• Integrative research on technology-assisted physical activity and biological aging: a review of wearable sensors, tele-exercise platforms, and aging biomarkers (2026) · Frontiers in Medicine · doi

  In summary, technology-assisted physical activity represents an important development in aging research and intervention. It may help delay biological aging by improving exercise adherence and enabling more individualized intervention strategies (42, 137). This review systematically summarizes current evidence on the relationship between technology-facilitated exercise and biological age biomarkers (epigenetic clocks, senescence-associated secretory phenotype or SASP, and organ-specific proteomics), which forms a solid scientific basis to review the eectiveness of exercise interventions on the process of aging. The biology of aging is complex and systemic, as reflected by the multiple mechanisms through which exercise exerts anti-aging eects, such as regulating autophagy, mitochondrial functioning, hemodynamics, and immune regulation. By examining these pathways, this review highlights the need for a holistic and mechanistically informed approach to the development of exercise regimens that may positively influence the biology of aging. From multiple research perspectives, it is clear that although conventional exercise interventions are beneficial, technology can enable more precise, adaptive, and scalable physical activity strategies for diverse older populations. Nevertheless, important challenges remain for the clinical translation of these innovations. Major challenges include inequities in technology access among aging populations and the lack of standardized intervention protocols. Addressing these challenges will require the integration of multi-omics data and the development of precision intervention systems that can adapt to individual variability and optimize outcomes. In research settings, Table 1 can be applied by prespecifying sensor-derived adherence/dose metrics and selecting at least one validated aging biomarker class as a key secondary endpoint with standardized baseline and follow-up sampling. A practical implementation example may help clarify this framework. In a research setting, older adults could undergo baseline profiling that includes functional testing (e.g., gait, balance, and mobility), wearable-derived physiological measures (e.g., heart rate, sleep, recovery, and activity dose), and one prespecified molecular aging panel (for example, an epigenetic clock plus selected inflammatory/SASP markers). Participants could then complete a 12-week wearable- and app-supported exercise program with predefined decision rules for progression, supervision, and safety escalation. At follow-up, biomarker changes would be interpreted together with sensor-derived exposure metrics to distinguish inadequate exercise dose delivery from true biological non-response. In a clinical or community setting, a lower-cost version of the same framework could rely on consumer wearables, brief remote coaching, and selective biomarker sampling in higher-risk or poor-response individuals. In both settings, implementation will depend on feasibility considerations such as device validity, assay cost, interoperability between wearable and laboratory data systems, missing-data management, clinician workflow burden, and transparent governance for privacy, bias, and algorithmic accountability. In the future, the integration of artificial intelligence with multimodal intervention strategies may substantially transform technology-assisted exercise paradigms. With AI-based analytics and customizable feedback mechanisms, future interventions may be dynamically optimized to improve eectiveness and adherence. In addition, incorporating these advanced exercise modalities into public health policy may play an important role in achieving large- scale impact and promoting healthy aging at the population level. To our knowledge, this review is among the first to integrate cross-disciplinary evidence on technology-assisted exercise and biological aging signatures while proposing a “precision exercise anti-aging” framework. Besides philosophical development, this theoretical model can also be used in practical terms to guide potential research and practice in the future. Ultimately, a precision-oriented and integrative perspective will be essential for realizing the full potential of technology-assisted physical activity to slow biological aging, extend healthspan, and improve quality of life in older populations.

  generalfuture work
  Keywords: aging exercise technology intervention biological assisted activity development review physical important adherence strategies interventions older
• Exercise as a Systemic Prevention and Management for Alzheimer’s Disease: Restoring Brain–Body Homeostasis Through Metabolic, Neurovascular, Anti-Inflammatory, and Regenerative Mechanisms (2026) · Cells · doi

  Physical exercise exerts broad neuroprotective effects by modulating multiple inter- connected mechanisms implicated in AD. Beyond its direct effects on neuronal function, exercise acts as a systemic intervention that enhances metabolic, cardiovascular, immune, and neuroendocrine homeostasis, thereby preserving both systemic and cerebral resilience during aging. Through these integrated adaptations, exercise may attenuate Aβ and tau pathology, reduce neuroinflammation and oxidative stress, support neurovascular integrity, and promote healthy brain aging. Despite growing evidence supporting the benefits of exercise, several challenges remain. Exercise protocols vary considerably across studies with respect to modality, inten- sity, duration, and frequency, limiting the development of standardized yet individualized recommendations for patients at different stages of cognitive decline [339]. Although dose– response relationships between exercise and cognitive function are increasingly recognized, the optimal exercise dose and modality for individuals at different stages of cognitive decline remain to be established. In addition, the molecular mechanisms underlying exercise-induced neuroprotection and the relative contributions of systemic adaptations remain incompletely understood. It also remains unclear how genetic factors (e.g., APOE ε4), metabolic status, gut microbiome composition, and other individual characteristics influence responsiveness to exercise. Furthermore, validated biomarkers capable of ob- jectively assessing biological responses to exercise or guiding optimal exercise dosing are currently lacking. Although aerobic and resistance exercise appear to differentially influence cognitive domains, the extent to which specific exercise modalities preferen- tially target distinct neural networks and cognitive functions requires further investigation. Large, longitudinal randomized controlled trials incorporating multi-omics and biomarker stratification will be essential to address these knowledge gaps [345,346]. Future research should move beyond general lifestyle advice toward precision, biomarker-guided exercise prescriptions. Resources such as the Molecular Transducers of Physical Activity Consor- tium (MoTrPAC) are providing comprehensive multi-omic maps of systemic responses to exercise that may facilitate the identification of biomarkers for individualized exercise prescription [347]. AI-driven integration of genetic risk factors (e.g., APOE ε4 status), baseline tau burden, physical fitness, exercise-responsive biomarkers (e.g., irisin, CTSB, and EVs), remote diagnostics, wearable biosensors, and virtual reality-based rehabilitation may enable personalized optimization of exercise intensity, duration, and frequency in real time. In parallel, a deeper understanding of exercise-regulated brain–body crosstalk and the development of scalable strategies to improve long-term exercise adherence will be critical for maximizing the clinical translation of exercise-based interventions in AD. Author Contributions: Conceptualization, L.X.; investigation, data analysis, and interpretation, L.X. and J.M.G.; writing—original draft preparation, L.X. and J.M.G.; writing—review and editing, L.X., J.M.G., M.M., and T.N.; visualization, L.X., J.M.G., and M.M.; supervision, L.X. and T.N. All authors have read and agreed to the published version of the manuscript. Funding: This work was supported in part by JSPS KAKENHI Grant-in-Aid for Scientific Re- search (C) (Grant Nos. 26K12666 and 25K13155) and Grant-in-Aid for Scientific Research (B) (Grant No. 23K21496). https://doi.org/10.3390/cells15151368 Cells 2026, 15, 1368 25 of 40 Data Availability Statement: No new data were created or analyzed in this study. Data sharing is not applicable to this article. Acknowledgments: During the preparation of this manuscript, the authors used ChatGPT (OpenAI, GPT-5.5) to assist with figure generation and figure refinement. The authors reviewed and edited all generated outputs and take full responsibility for the content of this publication. Conflicts of Interest: The authors declare no conflicts of interest.

  generalfuture work
  Keywords: exercise cognitive systemic authors grant physical remain biomarkers effects mechanisms beyond function metabolic aging adaptations
• ‘Exerkines’: A Comprehensive Term for the Factors Produced in Response to Exercise (2024) · Biomedicines · cited 34× · doi

  Blood biomarker profiling will be increasingly important in the coming years. Michael Snyder at Stanford [82] recently demonstrated that the analysis of thousands of metabolites, lipids, cytokines, and proteins obtained from 10 µL of blood together with physiological information from wearable sensors is able to provide a real-time dynamic evaluation of reactions to a complex mixture of dietary interventions allowing for the discovery of individualized inflammatory and metabolic responses. The combination of wearable devices and multi-omics microsampling during physical exercise will facilitate the dynamic profiling of sports-related health status. This approach has shown promise in predicting individual responses to exercise with respect to metabolic and cardiorespiratory health [19]. By integrating data from different omics levels, researchers have been able to elucidate the complex interplay between exercise-induced molecules and physiological outcomes, paving the way for personalized exercise interventions and targeted therapies. Author Contributions: Conceptualization, G.N. and G.C.; data curation, G.N., G.C. and F.C.; writing—original draft preparation, G.C., S.P. and J.L.M.; writing—review and editing, G.N. and J.L.M. All authors have read and agreed to the published version of the manuscript. Funding: This research received no external funding. Conflicts of Interest: The authors declare no conflict of interest.

  generalfuture work
  Keywords: exercise blood profiling physiological wearable able dynamic complex interventions metabolic responses omics health writing authors

Questions about this gap