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Mirre J.P. Simons 2015

Abstract (my paragraphing)

2.2.3. from the Results

- there is an effect of Vitamin D on telomeres
- EBV, CMV and one Enterovirus have been shown to block vitamin D receptor (VDR)
- HCV is associated with Vitamin D, Parvovirus B19 can well be associated
- HHV-6 is not associated with Vitamin but is known to affect telomeres (
**thread and lit.**to all of these)

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**Questioning causal involvement of telomeres in aging**Mirre J.P. Simons 2015

Abstract (my paragraphing)

Multiple studies have demonstrated that telomere length predicts mortality and that telomeres shorten with age. Although rarely acknowledged these associations do not dictate causality.

I review telomerase knockout and overexpression studies and find little support that telomeres cause aging. In addition, the causality hypothesis assumes that there is a critical telomere length at which senescence is induced. This generates the prediction that variance in telomere length decreases with age.

In contrast, using meta-analysis of human data, I find no such decline. Inferring the causal involvement of telomeres in aging from current knowledge is therefore speculative and could hinder scientific progress.

I review telomerase knockout and overexpression studies and find little support that telomeres cause aging. In addition, the causality hypothesis assumes that there is a critical telomere length at which senescence is induced. This generates the prediction that variance in telomere length decreases with age.

In contrast, using meta-analysis of human data, I find no such decline. Inferring the causal involvement of telomeres in aging from current knowledge is therefore speculative and could hinder scientific progress.

For the meta-analysis, I collected data on standard deviation from a large meta-analysis on sex differences in telomere length in the general population (Gardner et al., 2014) and I enriched this set with data from two other recent meta-analyses (Boonekamp et al., 2013, Müezzinler et al., 2013). I selected samples from which the age at sampling was on average over 45 years, after which age-related mortality occurs. Moreover, I restricted the data to include only studies that used terminal restriction fragment (TRF) analysis (southern blotting) (Kimura et al., 2010). TRF analysis is the only method in which the means and standard deviations can be reliably compared between laboratories, because it uses a single standard across laboratories (a DNA molecular weight ladder) to calculate the mean telomere length per individual (Verhulst et al., 2015). However when I analysed the available data on qPCR, the other main method used to measure telomere length, the conclusions below did not change.

Data were analysed using the natural logarithm of the reported standard deviation of telomere length, for which the sampling variance is known to be a function of sample size (Nakagawa et al., 2014), in a mixed model setting (with study included as random term) using the R package

The predicted reductions in the variance of telomere length are, however, not linear but depend on the increase in mortality with age (Fig. 2). The quadratic term for age, however, was also close to zero and far from significant (−0.0001 ± 0.0003,

These results, and earlier epidemiological evidence (Boonekamp et al., 2013), therefore suggest that telomere length is not a determinant of aging but rather a marker able to explain life expectancy and disease risk, for currently unknown mechanistic reasons.

[original paragraph]

Data were analysed using the natural logarithm of the reported standard deviation of telomere length, for which the sampling variance is known to be a function of sample size (Nakagawa et al., 2014), in a mixed model setting (with study included as random term) using the R package

*metafor*(Viechtbauer, 2010). Separate models were fitted that also included covariates such as sex, the natural logarithm of mean telomere length (Nakagawa et al., 2014), the standard deviation of subject age in the study, and any combination of these. In none of these models did variance significantly decrease with age and, in general, the estimated slope was positive rather than negative (slope of age without any covariates: 0.0015 ± 0.0036 (s.e.),*p*= 0.68).The predicted reductions in the variance of telomere length are, however, not linear but depend on the increase in mortality with age (Fig. 2). The quadratic term for age, however, was also close to zero and far from significant (−0.0001 ± 0.0003,

*p*= 0.69). Because there were no studies with mean ages between 59 and 71 years, the data could also be objectively dichotomised between young (<60 years) and old (>70 years). These two categories did not differ in telomere variance (difference 0.055 ± 0.095,*p*= 0.56), corroborating earlier analyses.These results, and earlier epidemiological evidence (Boonekamp et al., 2013), therefore suggest that telomere length is not a determinant of aging but rather a marker able to explain life expectancy and disease risk, for currently unknown mechanistic reasons.

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Aging Research Reviews

Aging Research Reviews

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