Stroke Patients Tend to be Biologically Older, as Measured by DNA Methylation
Today I thought I'd point out one of the recent results to emerge from the discovery that DNA methylation patterns correlate well with age. These patterns best correlate not with chronological age, but with biological age, as they reflect the pace at which cell and tissue damage has accumulated. They are thus a potential biomarker capable of distinguishing natural variations in the pace of aging between individuals. The authors of the paper linked below show that, per their chosen forms of DNA methylation assessment of age, stroke patients tend to be biologically older. This all ties together very well: age-related diseases are caused by an accumulation of molecular damage. That damage takes the same form in every individual, and thus the cellular reactions to that damage are much the same. These reactions include alterations in DNA methylation, a part of the epigenetic system of controls that determine whether and how rapidly various proteins are manufactured from their genetic blueprints. Variations in aging between individuals take the form of more or less damage at a given age, and thus these methylation patterns reflect an earlier or later age by level of damage. More damage means a greater risk of biological systems failures, such as chronic age-related disease or incidents like stroke.
The paper below is but one example of a range of initiatives focused on building and trialing accurate biomarkers of biological age. DNA methylation patterns are the best and most advanced of these to date; there has been something of a blossoming in this part of the field as researchers eagerly apply and attempt to validate this class of biomarker. For example, a recent study showed that older age as assessed by a methylation clock correlates with higher mortality. This isn't just about the gloomy matter of being able to quantify exactly where in the downward spiral of degenerative aging any one particular individual might be, however. The real advance in the state of the art that accompanies a reliable biomarker for aging is the ability to quickly and cheaply assess the potential of newly developed rejuvenation therapies. At present the only way to figure out whether something works or not is to, at minimum, run a lifespan study in a large enough number of mice to ensure statistical significance. That is something that tends to cost millions and take years, and such a high level of required investment means that there is far less experimentation and development than might otherwise be the case. But if that can be cut down to a month-long study with a biomarker test at beginning and end? Well, a much larger set of laboratories and projects now become contenders - and, as an added bonus, the proposals that don't in fact work will be quickly winnowed rather than lingering on in a state of uncertainty.
One thing to take away from this particular paper is that there is a still a fair way to go for DNA methylation - or another approach to a biomarker of biological age - to reach desirable levels of accuracy. It is still better than other candidate biomarkers, but at present would only be capable of detecting fairly large effects if used to assess interventions intended to slow or reverse the aging process. That might be good enough for the type of therapies proposed in the SENS vision of rejuvenation biotechnology: large positive effects on molecular damage and aging are the goal, after all. As work on the SENS approach of senescent cell clearance progresses, we'll soon enough be seeing DNA methylation biomarkers used as a matter of course in mouse studies of that rejuvenation treatment, I'd imagine.
Ischemic stroke patients are biologically older than their chronological age
Ischemic stroke (IS) is a complex age-related disease with high mortality and long-term disability. Despite current attention to risk factors and preventive treatment, the number of stroke cases has risen in recent decades, likely because the aging population has increased. Stroke pathogenesis involves a number of different disease processes as well as interactions between environmental, vascular, systemic, genetic, and central nervous system factors. Approximately 10% of IS occurs in individuals younger than 50 years, which is called "young stroke". In older patients, stroke remains associated with the traditional risk factors: hypertension, hypercholesterolemia, diabetes mellitus, and obesity.
The epigenetic marker that has been studied most extensively is DNA methylation (DNAm), which is essential for regulation of gene expression. This mechanism consists of the covalent addition of a methyl group to a cytosine nucleotide, primarily in the context of a CpG dinucleotide. This dinucleotide is quite rare in mammalian genomes (~1%) and is clustered in regions known as CpG islands. Methylation of the CpG island is associated with gene silencing. DNAm is dynamic, varies throughout the life course, and its levels are influenced by lifestyle and environmental factors, as well as by genetic variation. Given its dynamic nature, epigenetics has been referred to as the interface between the genome and the environment.
Age-related changes in DNA methylation are well documented, and two recent studies used methylation measured from multiple CpGs across the genome to predict chronological age in humans. Hannum et al created an age predictor from whole blood DNA, based on a single cohort of 656 individuals aged 19 to 101 years. Horvath developed a multi-tissue age predictor using DNA methylation data from multiple studies. Both models are based on the Illumina BeadChip. The difference between chronological age and methylation-predicted age, defined as average age acceleration (Δage), can be used to determine whether the DNAm age is consistently higher or lower than expected. These age predictors are influenced by clinical and lifestyle parameters, they are predictive of all-cause mortality, indicating that they are more suggestive of biological age than of chronological age.
Age is one of the main risk factors for stroke. We hypothesized that biological age would be even more closely associated with stroke risk, and that "young stroke" patients may be undergoing accelerated aging, with a higher biological than chronological age. We examined a cohort of 123 individuals, 41 controls and 82 patients with IS, matched by chronological age. We initially used two approaches described in the literature to predict biological age, the Hannum and Horvath methods. The average biological age of controls showed a mean Hannum-predicted age higher than their chronological ages by a mean of 1.1 years; their Horvath-predicted age was lower than their chronological ages by 4.6 years. In patients with IS, we observed a Hannum-predicted age higher than their chronological age by a mean of 3.3 years, statistically significant compared to controls. Their Horvath-predicted age was lower than their chronological ages by 3.2 years. DNAm age had a strong positive correlation with chronological age in control samples (0.93 for both Hannum and Horvath methods, and 0.94 between the Hannum- and Horvath-predicted ages). In IS cases, the correlations were lower (0.83 for the Hannum method, 0.72 for the Horvath method, and 0.82 between the two. Although both age predictors showed high accuracy in our samples, Hannum DNAm age performed better, with fewer differences in chronological age in controls and better correlation in patients with IS than the Horvath method.
The sensitivity analysis evaluating which age predictor performed better in our study determined that the Hannum predictor was superior. This is likely because this method is constructed on the basis of DNA methylation data from whole blood, like our data, while the Horvath method is constructed on a range of different tissues and cell types. In conclusion, we found that IS status was associated with a significant increase in Hannum DNA methylation, likely as a consequence of the accumulation of cardiovascular risk factors, and near signification with Horvath method. Patients with IS were biologically older than controls, a difference that was more obvious in young stroke. This could open up the possibility of useful new biomarker of stroke risk.
Hi ! Nice study, the more study on epigenetics the better.
This study is great and, though they say the Hannum method is more accurate (which is true in this case because of better correlation to ischemic stroke),
Horvath method is still very decent and also, as they say, his method is ''constructed on a range of different tissues and cell types''. Thus, that
gives more power to his method than simply using one tissue or fluid and say it correlates better; comparing different tissues against one another
paints a bigger/better picture. I believe the reason the single element/just using whole blood and getting a better prediction result is because
sometimes 'more is less, and less is more'; sometimes more organs thrown in can muddle the correlation; and, ironically, a single organ can predict overall outcome
better than many organs as a combined ensemble to 'increase precision/correlative power' (since not just blood ages, our whole body/organs); it seems it's the inverse that happens and the precision is less.
As such, one element like blood itself measured alone, can be quite accurate of what happens pretty much everywhere in the body and represent aging overall.
It's why blood leukocytes telomeres were often used as surrogate for many other organs' tissue's telomeres (meaning simply looking at leukocytes'
telomeres gave enough precision and prediction as a 'barometer' of the 'overal'' telomere length in almost every other organ of the body (without even needing to check them all out)).
I think the other reason for that is that when you enter 'more factors in' you can reduce or Increase the noise - to - factor ratio; meaning not all
data you 'feed in' your model or computer model will necessarily 'help' in finding better correlations or causations; it can hinder them (
that's why sometimes you see scientists have to 'redo/update' their studies to make sure there is no false positive or some other element 'infecting/biasing'
the results, making something look more 'causative' than just correlative associative. I often read things like : ''After independent phylogeny
and smoke, diabetes and other factors were added by multi-factor regression/multi-variate analysis regression (like ANOVA), the correlation was non-significant p < 0.01 (Pearson correlation is lost).''
''In conclusion, we found that IS status was associated with a significant increase in Hannum DNA methylation, likely as a consequence of the accumulation of cardiovascular risk factors, and near signification with Horvath method. Patients with IS were biologically older than controls, a difference that was more obvious in young stroke.''
When they say Increased DNA methylation, it only means in CpG-rich areas not in CpG-poor areas, CpG-rich areas are the one that Hypermethylated
by disease like IS, cancer and others. Not CpG-poor ones. It is quite confusion-inducing to say that it increases methylation (in these areas yes),
but it's the inverse that happens for CpG-poor areas. And for 'regular intrinsic' aging - it is clear manifestation of Global DNA Demethylation (reduction of methylation)
- not - an increase in methylation. Some genes are hypermethylated and contribute to the inflammation such in IS and cancer (cancers have Hypermethylation of these CpG-rich areas), but in regular aging,
overall there is Loss of Methyl count in CpG-poor areas; these CpG-poor areas control aging (intrinsic one). New born DNA methylome vs 26 year old vs 58 year old vs 103 year old methylomes :
A very progressive decline in global DNA methylation in CpG-poor areas (the New born has 16,800,000 Methylated CpG sites, while the 26 year old has 16,700,000 and the Centenarian has 16,275,000 ones.
80.5% in New born, 77.8% in 26-y, and 73% in Centenarian) This means there is about 7% loss of CpG-poor 'methyl content' (like 5-methylcytosine loss).
Centenarians offsprings (who will most likely reach the age of their parent and are thus biologically younger/age Slower than rest of population) - Delay the Global DNA demethylation - compared to offsprings from regular shorter-lived parents (non-centenarian) that happens with aging proving without a doubt that, for intrinsic aging,
Hypomethylation of certain 'areas' (CpG poor) is the 'driver' of intrisic 'healthy (no disease) aging', while 'degenerative aging (IS, diabetes, cancer...)' is seen in the Hypermethylation of genes of CpG-rich areas (these genes are mostly the ones that control cell replication and are implicated in inflammation/oxidative stress production such as : p53, p16, TNF-a and IL-6). That distinction should be in those studies.
Many studies that verify oxidative stress (Such as one in arsenic poising oxidative stress-induced death) show that indeed what happens is that the Redox is oxidized immensely and alters the methylation towars a Hypermethylation in CpG-rich regions (activating the inflammation cascade and the cell replication inhibitors/oxidative-stress oncogenes/tumor-suppressors like p53, p16, p21; which are abrogated for cancer cell replication).
This means degenerative aging/pathological aging is of the 'Hypermethylation' kind (in CpG-rich), while when healthy, regular intrinsic 'cell division passages limit/replicative senescence/telomere loss' is of the 'Hypomethylation' kind (in CpG-poor). One study showed that people with higher oxidized blood redox (in Bangladesh people) had - accelerated DNA demethylation and Lower DNA methyl count (thus Demethylation/Hypomethylation of those CpG-poor areas which Control Intrinsic Aging and Are Correlative to the Chronological Age of the human subject's tissues/thus it's it chronological lifespan if remaining healthy (enough and disease-free) until death).
For SENS, 4 or 5 therapies will affect aberrant Hypermethylation (degenerative aging/pathologies : cancer, hypertension,.. ) while 1 or 2 therapies will affect Hypomethylation (intrinsic 'healthy' aging and maximum human specie lifespan Limit (dependent on the cell passages/replication/replicative senescence/telomere structure as 'replication rounds'' Counter Inhibitors), by altering the oxidative stress from mitochondrial dysfunction (allotopic expression) or age pigment clogging the cells (LysoSENS). ApoptoSENS may be a 3rd one with smaller impact, by removing Replicatively senescent cells - but that is so far away in person's life that it won't matter in young age - only in very old near death age; it may have less impact for that matter of 'very late application').
Blood glutathione redox status and global methylation of peripheral blood mononuclear cell DNA in Bangladeshi adults
1. http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3781192/