Epigenetic Testing: the Best Measurement for Biological Testing a Change in Philosophy About Longevity and Aging As a Disease

Epigenetic Testing: The Best Measurement for Biological Testing A Change in Philosophy about Longevity and Aging as a Disease

The approach to Preventative Medicine has been limited due to little data and long periods of investigation.

Now, there is a movement in medicine and in the community about longevity and the tools to ﬁx this.

Age now has an ICD-10 extension code! Why Do We Age?

Aging is the time-dependent functional decline at the cellular level

These 9 hallmarks of aging contribute to the aging process and determine one’s aging phenotype

Aging is the loss of physiological integrity, this is the primary risk factor for major human pathologies, like cancer, diabetes, cardiovascular disorders, and neurodegenerative diseases [Lopez-Otin et al 2013] Aging as a Risk Factor

Aging is the greatest risk factor for a majority of chronic diseases. Collectively, chronic diseases comprise the majority of global disease burden and are the most common cause of mortality (kennedy et al. 2014) 80% of adults age 65+ have at least one chronic disease (NCOA) Percent of population 65+ with these common chronic conditions Hypertension (58%) High cholesterol (47%) Arthritis (31%) Coronary Heart Disease (29%) Diabetes (27%) Aging as a Risk Factor

Aging causes the progressive damage of biological structures, contributing to the development of disease and death Members of the current generation of adults aged 45-64 live longer but are experiencing higher rates of chronic conditions By the time you reach 60, your risk of getting cancer doubles from when you were 50 (White et al. 2015) 70% of all cancers occur among adults aged 65 and up 82% of people who die from coronary heart disease are 65+

Aging as a Risk Factor

Age is the predominant risk factor for many diseases, such as: Cardiovascular disease (North and Sinclair, 2012) Dementia (Querfurth and LaFerla, 2010) Osteoporosis (Raisz, 1988) Osteoarthritis (Raisz, 1988) Cancer (de Magalhães, 2013) Type 2 diabetes (Gunasekaran and Gannon, 2011) Unlocking the ways to regulate the rate of aging will help prevent some of the most common morbidities in the world Inﬂammation and Its Link to Health “Inﬂammaging”

Local inflammation is a vital immune response triggered by infection and injury. Inflammatory responses promote the destruction and clearance of viral and bacterial pathogens, and enhance wound healing. Proinflammatory cytokines attract immune cells to sites of infection or injury, activating them to respond to the insult. While acute, local inflammation is beneficial, chronic low grade inflammation may have detrimental health consequences.

Inflammation is a robust and reliable predictor of all-cause mortality in older adults. C-reactive protein (CRP) and proinflammatory cytokines such as interleukin-1 (IL-1), IL-6, and tumor necrosis factor-alpha (TNF-α) are prognostic for cardiovascular disease, type II diabetes, arthritis, osteoporosis, Alzheimer's disease, and periodontal disease (Ershler and Keller, 2000; Kiecolt-Glaser et al., 2002). More globally, chronic inflammation has been suggested as one key biological mechanism that may fuel declines in physical function leading to frailty, disability, and, ultimately, death (Ershler and Keller, 2000). Aging and Senescence: SASP: Functions

Senescence-associated secretory phenotype (SASP) Since aging is the greatest risk factor for every disease, how can we appropriately measure it? Are there better methods than chronological age?

Chronological age (CA) is a commonly used indicator for aging. However, life expectancy shows considerable variation among individuals with equal or similar CAs due to diversity in genotypes and in living habits and environments.

A 50-year-old individual may have 60-year-old body functions, and many people look older or younger compared to others at the same CA (even in twins). Therefore, CA is not an optimal indicator for the aging progress.

The History Of Biological Age Measurements

During the past decades, extensive effort has been made to identify such aging biomarkers that, according to the stage-setting definition (Baker and Sprott, 1988), are “biological parameters of an organism that either alone or in some multivariate composite will, in the absence of disease, better predict functional capability at some late age, than will chronological age”. Later on, the American Federation for Aging Research (AFAR) formulated the criteria for aging biomarkers as follows:

1. It must predict the rate of aging. In other words, it would tell exactly where a person is in their total life span. It must be a better predictor of life span than chronological age.

2. It must monitor a basic process that underlies the aging process, not the effects of disease.

3. It must be able to be tested repeatedly without harming the person. For example, a blood test or an imaging technique.

4. It must be something that works in humans and in laboratory animals, such as mice. This is so that it can be tested in lab animals before being validated in humans.

However, to date, no such marker or marker combination has emerged. What Else Makes a Good Biological Age Clock?

Recently, several new biomarkers for biological aging have come into play. They can be separated into molecular- (based on DNA, proteomics, RNA etc.) or phenotypic biomarkers of aging (clinical measures such as blood pressure, grip strength, lipids etc.).

They should be markers that predict chronological age, or at least can separate “young” from “old”.

They should also be associated with a normal aging phenotype or a non-communicable age-related disease independent of chronological age in humans. What Should Biological Age Be Used For?

A biological age predictor could be defined as a biomarker correlated with chronological age (black line), which brings additive information in the risk assessments for age-related conditions on top of chronological age. Hence, adult individuals of the same chronological age could possess different risks for age-associated diseases as judged from their biological ages (x's in figure).

Usually, the positive predictive value (red line) of a biological age predictor decreases from mid-life and onwards due to the increased biological heterogeneity at old age (confidence interval described by dashed lines increases at old age). Why is Biological Age Testing Important

Individual Precision Medicine - How does ___ intervention affect YOU?

Validating therapies which reduce this can show us in real time what reduces risk.

We can predict disease early (IvyGene and OncoBlot)

We can tease out the reason and links for aging The Most Common Test for Biological Age: Telomeres Telomeres: What does this tell us?

All cells have have a finite replicative potential; it is predictable based on the length of telomere repeat DNA.

Telomeres define the ends of chromosomes and function to preserve genome integrity; they are comprised of TTAGGG sequences that are bound by specialized proteins.

Telomere length (TL) shortens during DNA replication and, at a critical threshold, the shortest telomere(s) activate a DNA damage response that signals cell death or a permanent cell cycle arrest, known as cellular senescence

The observations in cultured cells, and the fact that TL shortens with aging, have led to a hypothesized role for telomere shortening in human aging and age-related disease; however, the short TL threshold that is clinically relevant for disease risk is not known, and whether TL measurement can influence treatment decisions in clinical settings has not been determined. The Most Common Test for Biological Age: Telomeres

Since the number of cell replication in vivo increases with age, telomere length (TL) is negatively correlated with age of proliferating somatic cells. Meta-analysis of 124 cross-sectional studies and 5 longitudinal studies showed that the correlation between leukocyte telomere length (LTL) and age ranges between r=-0.295 and r=-0.338 across adults

Inherited deficiencies where telomere analysis is used in clinical diagnosis and to guide treatment include bone marrow failure, dyskeratosis congenita, aplastic anemia, acute myeloid leukemia, immune deficiencies, and pulmonary fibrosis. What about preventing disease outside of these conditions? Is TL helpful?

What do large-scale and meta-analysis studies say on associations between telomere length and age-associated traits?

Women on average have longer telomeres than men. Hence, women have a lower biological age than men as judged from the telomere lengths.

Although no meta-analysis on mortality has been reported yet, the association between short telomeres and increased mortality risk has been shown repeatedly in many studies (Needham et al., 2015; Bakaysa et al., 2007; Deelen et al., 2014)

However, a meta-analysis on telomere length and overall cancer risk (23,379 cases and 68,792 controls) showed a null result, indicating that telomeres may play different roles for different cancers (Zhu et al., 2016).

Telomeres have also been associated with many age-related traits such as cognition and physical function. However, studies, and even meta-analysis efforts, are often small with limited conclusions (Gardner et al., 2013).

Technical bias in the measurement of telomere lengths may also contribute to the lack of consistent results. What about preventing disease outside of these conditions? Is TL helpful?

Short telomeres were found to be risk factors for gastrointestinal, head and neck cancers only. Furthermore, short telomere length has been described as a risk factor for coronary heart disease as judged from a meta-analysis of 43,725 participants (8400 events) (Haycock et al., 2014), and from a large-scale observational study (Scheller Madrid et al., 2016).

To conclude, the suggestive epidemiological evidence for a causal role of telomeres in aging diseases is challenging current knowledge and needs to be further investigated, preferably in longitudinal studies. The discussion around cause or consequence is valid not only for telomeres, but for all biomarkers of aging and is important for future perspectives of healthy aging. Telomere Summary

“Briefly, telomere length is extensively validated but has low predictive power.” Other Age Predictors: Multi-omics Other Age Predictors: Multi-omics Proteomics Clocks

Over the last two decades, several studies have shown effects of aging on protein glycosylation as measured from human serum or plasma (Pucic et al., 2011; Ruhaak et al., 2010; Parekh et al., 1988; Ruhaak et al., 2011; Knezevic et al., 2010). However, most studies were based on non-targeted approaches in single cohorts, making validation across studies impossible. Recently, Kristic ́ and colleagues made an effort of combining four European cohorts to study IgG glycosylation in aging (Kristic et al., 2014).

A prediction model for age based on three individual glycans, the GlycanAge, was built in one cohort, and replicated well in the others (among which TwinsUK was included). The GlycanAge index was associated with health variables such as fibrinogen, HbA1c, BMI, triglycerides and uric acid after correction for age and sex. Proteomics Clocks

“There were cases of substantial divergence between participants’ chronological and physiological age — for example, among the subjects in the LonGenity study, with their genetic proclivity toward exceptionally good health in what for most of us is advanced old age.

“We had data on hand-grip strength and cognitive function for that group of people,” Wyss-Coray. “Those with stronger hand grips and better measured cognition were estimated by our plasma-protein clock to be younger than they actually were.”

However, the protein-derived age variable itself was not tested for associations with health outcomes. Metabolomic Clocks

What is the metabolome?

Metabolomics is the scientific study of chemical processes involving metabolites, the small molecule substrates, intermediates and products of metabolism. Specifically, metabolomics is the "systematic study of the unique chemical fingerprints that specific cellular processes leave behind", the study of their small-molecule metabolite profiles.

Metabolic profiling can give an instantaneous snapshot of the physiology of that cell, and thus, metabolomics provides a direct "functional readout of the physiological state" of an organism.

Relatively few studies have analyzed associations with age on the metabolome and they were conducted using different measurement techniques. Yu and colleagues used a targeted mass-spectrometry method identifying 131 metabolites in fasting serum, where 11 were independently associated with age in females after BMI adjustments (Yu et al., 2012).

Later, the same groups combined analyses of non-targeted mass-spectrometry and age using the Metabolon platform (Menni et al., 2013). Metabolomic Clocks

In that study, 22 independent age-associated metabolites, mostly lipids and amino acids, were found. One selected metabolite, C-glyTrp, was associated with age-related traits such as lung function and hip bone mineral density after adjustments for age. In a study from 2016 by Hertel and colleagues, a proton nuclear magnetic resonance (H1 NMR) spectroscopy investigation in human urine samples quantified 59 metabolites (Hertel et al., 2016).

Construction of a Metabolic Age Score included all metabolites as predictors and age as the outcome. The metabolic age score was validated and replicated in two independent cohorts, and found to associate with clinical outcomes independent of age, e.g., kidney malfunction, high HbA1c levels, and hyperglyceridemia. Importantly, survival analysis showed that individuals in the first tertile of the score (lower biological age) had higher all-cause survival rates, and that the prediction added value over commonly known risk factors. Composite Biomarker Clocks

Finally, a study using TwinsUK data applied a multi-omics approach to investigate relationships between different biomarkers of aging (Zierer et al., 2016).

Several biological age predictors have been investigated in those data, as discussed above, and here epigenetic, metabolomic, transcriptomic and glycomic measures were combined into graphical models. Unfortunately, instead of using pre-defined age predictors, multiple single markers were inferred in the models, making comparisons to earlier studies and interpretations difficult.

Nevertheless, linking many different data types and disentangling the relationship between different biological age predictors may shed light on the aging process and provide further understanding of what contributes to healthy aging. The Introduction to Epigenetic Clocks

“Steve Horvath from the Department of Human Genetics at the University of California-Los Angeles, says, "When it comes to predicting lifespan, GrimAge is 18 percent more accurate than calendar age, and 14 percent better than previously described epigenetic biomarkers. With regard to predicting time to coronary heart disease, GrimAge is 61 percent more accurate than chronological age and 46 percent better than previously reported epigenetic biomarkers. In spite of this signiﬁcant enhancement, however, it must be noted that neither age nor DNAmGrimAge is particularly good at predicting time to heart disease." My Story: The Introduction to Epigenetic Clocks My Story: The Introduction to Epigenetic Clocks

According to one of the developers, Steve Horvath, the statistical significance provided by the recently developed DNAm ‘GrimAge’ clock is such that ‘[i]t’s really more likely that planet Earth will be hit by an aster- oid tomorrow than that this predictor doesn’t work’ [15]. What Is Epigenetic Biological Age?

Epigenetic biological age is the age estimate in years based on methylated CpGs in the genome

Biological age is how old our cells really are, it is our real age. This is dependent on one’s biological state.

Epigenetic aging can be reversed and is inﬂuenced by lifestyle and environmental factors

DNA methylation age is a promising marker for studying human development, aging, and cancer, and is useful for evaluating rejuvenation therapies. [Horvath 2013] What Is DNA Methylation?

“Environmental inﬂuences on DNA methylation are the center of the developmental origins of health and disease” [Mikeska et al.]

An epigenetic mechanism where methyl groups are added to the DNA

DNA Methylation changes the way DNA is expressed without changing the DNA sequence

It is a promising biomarker for biological aging and various morbidities Epigenetic Biological Age Clocks

A highly accurate age estimator

The ratio between methylated DNA age and chronological age

Multiple review studies have determined Biological age testing is best deﬁned by epigenetics

“In the language of Greek mythology, DNAm age is Clotho’s ‘thread of life’, connecting development from conception to post-maturity maintenance and ultimately death. As such, the epigenetic clock reveals that biological ageing is intricately woven into the very biological processes that initiate, develop and maintain life.” [Horvath & Raj] How Are Epigenetic Tests Created?

Mathematical models are used to design a powerful algorithm to interpret the methylation data

DNA methylation is a collection of innate aging processes that play an important role in tissue maintenance

Epigenetic age estimators are sets of CpGs, known as clock CpGs, coupled with the algorithm to estimate one’s biological age Algorithm vs Methylation Measurements

Methylation measurements are molecular genetic tools

Algorithms are the way we read this data!

It would be ideal to test all 26 million CpG sites on the DNA and have a precise algorithm trained with huge data sets and correlated to medical outcomes

Epigenetic Testing: The Algorithms Intrinsic Epigenetic Age

“Intrinsic epigenetic age is independent of changes in the blood cell composition that occur with time and is considered a measure of ‘pure’ epigenetic aging effects in blood cells” [Gensous et al.]

This component of epigenetic aging is out of one’s own control

Deals with underlying genetic predispositions Extrinsic Epigenetic Age

Tracks both age-related decline of the immune system and incorporates intrinsic epigenetic changes

Associated with lifestyle and environmental factors to one’s biological age

“This measure is dependent on age-related changes in blood cell composition and can be considered as a measure of aging in the immune system“ [Gensous et al.] How Does This Compare to Telomere Testing?

Telomere length and epigenetics are independent predictors of age and mortality risk estimated by the Hannum clock [1]. It is important to know which method is more accurate for predicting age in a clinical setting. A comparative review of different molecular age estimators concluded that DNA methylation is the most promising biomarker for age [2].

Numerous large scale epidemiological studies have concluded that telomere length has a weak negative association with markers of biological age [3]. This could be because telomere degradation does not have marked effects on cell physiology until a critical telomere length is reached, which doesn’t help the average population of people. After all, this method relies on the point a cell becomes senescent [4].

Based on Horvath’s 353 epigenetic clock, one study determined the difference of methylated DNA age did not correlate with telomere length [3]. Epigenetic age acceleration is correlated with aging-related phenotypes through pathways unrelated to cellular senescence, telomere length relies on cellular senescence to indicate biological age [Breitling]. Whereas, any person at any age can use DNA methylation as a biomarker for age before they have accumulated a high number of senescent cells in their tissues.

Telomere length explains only 6.6% of the variance in age whereas the epigenetic clock explains 19.8% of age variance signifying that telomere length is a weak basis for predicting biological age [5]. Beneﬁts of Methylation DNA Analysis: Capturing a Phenomenon that others Don’t

The following features of these clock demonstrates that its age estimates capture several aspects of biological age:

It can accurately measure the age of cells regardless of tissue types including brain, liver, kidney, breast and lung [34] Its accuracy (r = 0.96 on subjects aged between 0 to 100 and r = 0.77 in middle age subjects) is substantially higher than that of other molecular markers such as telomere length (r = 0.5) [36] It is able to predict mortality independent of health, life-style or genetic factors [37] Its measurements correlate with cognitive and physical fitness amongst the elderly [38] It is able to detect accelerated ageing induced by various factors including obesity [39], Down syndrome [40] and HIV infection [41]. More Proof that Telomeres Do Not Capture the Aging Process

“These cells continue to proliferate in culture beyond passage 50 and do not exhibit any signs of senescence, demonstrating that the process of cellular ageing continues unabated in cells whose telomeres were maintained. This shows that removal of the inducers of senescence does not halt ageing, once again underlining the fact that cellular ageing is a process that is distinct from senescence.”

“Telomerase-immortalised cells aged in culture without having been treated with any senescence inducers or DNA-damaging agents, re-affirming the independence of the process of ageing from telomeres and senescence.” The 2019 Break Through The TRIIM Study

Combining rhGH with both dehydroepiandrosterone (DHEA) and metformin might limit the “diabetogenic” effect of GH. Metformin is a powerful calorie restriction mimetic and AMPK stimulant in aging mice. DHEAS and metformin themselves have no known thymotrophic effects. Dr. Fahy from UCLA conducted what was the ﬁrst human clinical trial designed to reverse aspects of human aging, the TRIIM (Thymus In a preliminary human clinical trial (TRIMM) Fahy et al Regeneration, Immunorestoration, and Insulin observed that treatment with a cocktail of growth Mitigation) trial, in 2015–2017. hormone, metformin and DHEA can partially restore atrophied thymus, improve composition of immune cell populations and, most interestingly, reduce four separate measurements of Epigenetic Age.

Fahy, G. Reversal of epigenetic aging and immunosenescent trends in humans. Proteomics. 2019 The Importance Of Knowing Your Epigenetic Age

The epigenetic clock is the most promising molecular estimator of one’s biological age If your EpiAge™ ratio is above 1, you could have an increased risk for death It is crucial to understand DNA methylation changes through use of TruAge™ because epigenetic age can be reversed The Predictive Power of Epigenetics: Disease

“A 5% increase in methylation of identiﬁed CpGs were related to differences in coronary heart disease (CHD) risk… ranging from 46% decrease in the risk of CHD to a 65% increase in risk of CHD” (Agha et al. 2019)

Adults of the same chronological age could possess different risks for age-associated diseases. Biological age predictions can associate aging-related disease that is independent of the chronological age.

“The relevance of measures of epigenetic age acceleration can be appreciated by the fact that they are associated with a great number of age-related conditions and diseases” (Horvath & Raj 2018) The Predictive Power of Epigenetics: Cancer

Cancer is an age-related condition linked to epigenetic age acceleration

“For each one year increase in the difference between chronological and epigenetic age (the Δage), there was a 6% increased risk of developing cancer within three years and a 17% increased risk of dying of cancer in the next ﬁve years” (Jylhävä et al 2017)

“Some cancers, tumours with fewer somatic mutations, indicative of more stable genomes, have greater epigenetic age acceleration” (Horvath & Raj 2018) The Predictive Power of Epigenetics: Death

Hazard ratios for Δage (per 5 years) calculated using the epigenetic clock developed by Horvath were 1.23 for all-cause mortality, 1.22 for cancer mortality, and 1.19 for cardiovascular mortality after adjustment for batch effects, age, sex, educational level, history of chronic diseases, hypertension, smoking status, body mass index, and leukocyte distribution.

Recent biomarkers for lifespan have been developed that combine mortality associated CpGs into an overall mortality risk score

“Both intrinsic and extrinsic measures of epigenetic age acceleration in blood are associated with an increased risk of death from all-natural causes even after accounting for known risk factors” (Horvath & Raj 2018) TruDiagnostic™

We are an epigenetic testing company that recognizes the need for objective information regarding aging and aging related diseases for integrative, functional, and preventative medical space. We want to help patients and prescribers treat aging as a disease with the best up to date info on their own aging. Our Algorithm

Our algorithm is built by computer learning and artiﬁcial intelligence. Our algorithm uses values assigned to the methylation state of speciﬁc CpGs in the genome to measure 850,000 places on the DNA to estimate the age of the person.

By linking these methylation values to other covariates such as blood tests, physical measurements, and others we are able to develop algorithms for predictive risk. Our Goals

Create a inexpensive widely accessible test which can be made available to the integrative cash pay medicine community so that we can gather data on the best interventions to make a difference in the health of the world.

Eventually, we would love for aging to be classiﬁed as a disease and have the world do this test twice yearly to evaluate their aging trends! Our Test Kit

$399.00 (direct to consumer)

$300.00 (physician price) What Is Reported to Patients

A personalized TruAge™ treatment framework with detailed explanations about what your reported biological age and EpiAge™ ratio means about your current health. The Results Our Research

Only 2 studies have documented how interventions can reverse epigenetic age, our plan is to change that Our goal is to look at factors that can reverse biological aging, and to give specialized treatments to patients who work with us Our Future Tests

TruDiagnostic™ looks into an extensive amount of data We are constantly looking for new biomarkers to support the creation of future tests; currently we are looking at all of these things and more:

Telomere Estimation Cardiovascular Disease Risk

Senescence Burden Estimation Cancer Risk

Alzheimer’s Risk Best Fitness and Diet Estimator Interventions Currently Being Studied to Reduce Epigenetic Age

NAD+ Therapy Bariatric Surgery Thymosin Alpha-1 Interventions Growth Hormone Therapies Exosomes Young Plasma Apheresis Mitochondrial Peptides Stem Cell Procedures Senolytic Therapy What Can I Do To Slow My Aging?

This brings up the questions of what causes aging! This brings up discussions of anti-aging technologies which have shown to help extend lifespan. Questions?