In this episode of the Optisan Podcast, Dr. George Sutphin discusses biological age tests, focusing on epigenetic and glycan age assessments. The conversation explores the accuracy, relevance, and implications of these tests for understanding biological versus chronological age. Key topics include the limitations of current biomarkers, the impact of lifestyle on aging metrics, and the challenges of interpreting results. The discussion emphasizes the need for caution in marketing claims and the importance of scientific validation in biological age testing.

Check out the links below for further information and/or reading about some of the things we discussed in this podcast episode. Note that we do not necessarily endorse or agree with the content of these readings, but present them as supplementary material that may deepen your understanding of the topic after you listen to our podcast. This list is in no way exhaustive, but it’s a good start!

Biomarkers of aging for the identification and evaluation of longevity interventions - ScienceDirect

George talks about his recent experience taking the glycan age biological age assessment, the significance of biological age tests, and their limitations when used to inform the health status of an individual. This seminal paper discusses criteria for assessment of biomarkers of aging, methodologies for their validation, as well as ongoing challenges and future directions. Chronological age is the number of years an individual has lived on earth, the number of candles on their birthday cake. Biological age, on the other hand, is a reflection of the health and functioning of organs and tissues in the body. As such, biological age is the biggest risk factor for age-related disease and disability. Developing tools to track changes to the rate of biological aging forms the foundation of the practice of longevity medicine, particularly for evaluating the clinical effectiveness of longevity interventions in realistic time frames. But lack of standardized protocols and metrics for assessing the properties of biomarkers of aging has hindered progress in elucidating markers that can be reliably used in clinical trials, let alone the commercial space. This paper from the Biomarkers of Aging Consortium proposes a framework consisting of consensus terminology, classification and evaluation criteria for validating biomarkers of aging for clinical applications.

Epigenetic clocks and programmatic aging - ScienceDirect

George and Matt discuss epigenetic age clocks and the relative impact that epigenetic dysfunction has on the biological aging process. Ultimately, they agree that while likely playing a very important role, epigenetic dysfunction only represents one facet of the biological aging process amongst many other hallmarks of aging and other unknown mechanisms of aging. This paper proposes a hypothesis for how epigenetic changes over time may represent an upstream driving force that is determinative of aging. Ultimately, the hypothesis proposes that celsl have high fidelity control over epigenetic modifications and gene expression when an organism is young to ensure tight control of the developmental process. In the adult organism, this control “loosens” to ensure adaptive ability as an organism matures so it can adapt to its changing environment to ensure reproductive fitness. As the forces of natural selection subside in post-reproductive ages, the further loosening of epigenetic control mechanisms ultimately permits age-related damage decline which leads to organismal senescence and age-related decline. Central to this hypothesis is that epigenetic and developmental changes occurring throughout life history are part and parcel of the same process that drives biological aging. Focusing on epigenetic patterns on regions of the chromosome associated with developmental genes and segmenting changes in the clock according to these proposed phases of epigenetic changes may lend further utility to epigenetic clocks as a research tool within the geroscience field.

OMICmAge: An integrative multi-omics approach to quantify biological age with electronic medical records - PMC

Matt mentions his experience with OMICmAge, the latest generation of explainable epigenetic clocks. While epigenetic clocks hold potential to predict aspects of age-related decline and chronic disease, it is still not clear how reliable they are between replicates or whether they are superior to conventional biomarkers for predicting disease in the clinical setting. This paper discusses the development of the OMICmAge clock, constructed with multiple types of omics data (proteomics, epigenomics, metabolomics) and clinical electronic medical health records. The authors go on to validate OMICmAge clock as more predictive for morbidity and mortality than standalone clinical markers in two retrospective longitudinal data cohorts. Whether this predictive validity is preserved in prospective clinical studies is yet to be determined.

IgG glycans in health and disease: Prediction, intervention, prognosis, and therapy - ScienceDirect

Matt and George discuss the GlycanAge biological age assessment, developed as a predictive measure of relative changes to immune health, chronic inflammation, and biological age. GlycanAge measures the spatial arrangement and concentration of glycan molecules placed on top of IgG antibodies, which in turn determines the inflammatory reactivity of the immune system. This paper reviews the current state of knowledge regarding glycosylation in a wide range of disease states and it's potential applications as a diagnostic for disease prevention and the evaluation of various longevity interventions

https://academic.oup.com/eep/article/9/1/dvad005/7224619

The accuracy of biological age clocks heavily depends on the participants (training dataset) utilized to develop the clock. This is typically based on large, longitudinal data banks including biological and demographic information. This review evaluates the data utilized to construct 13 commonly used epigenetic clocks and highlights a potential oversight in the design of clocks as typically little attention has been paid to sociodemographic characteristics of the participants which are known to be associated with both DNA methylation variation and healthy aging. The authors propose that future work should incorporate and report tangible data on sociodemographic and socioeconomic characteristics of its participants to aid interpretation of clock results.