Heterogeneity in telomere length in myeloid cells predicts chronological age

Telomere length shortening occurs with age in most cells types, and shorter telomeres are associated with increased risk of age-related diseases, including cardiovascular disease. The majority of studies to-date analyze mean telomere length in peripheral leukocytes, as material is plentiful and circumvents the practical and ethical problems associated with obtaining vascular tissue. Telomere length is strongly correlated between leukocytes and vascular tissues, validating the use of leukocyte telomere length as a proxy for length in vascular cells. However, leukocytes comprise a number of cell types; so do they all “age” at the same rate?

In a step towards answering this question Hoffmann et al. examined telomere length in lymphocytes and granulocytes separately:

Telomere length-heterogeneity among myeloid cells is a predictor for chronological ageing.

We have previously shown that mean telomere length (TL) of granulocytes reflects TL of myeloid bone marrow cells extremely well. Here we analysed the distribution of TL from peripheral blood granulocytes and lymphocytes in 61 female and 68 age-matched male healthy volunteers. We show that the age-dependent decline in TL occurs more rapid in peripheral blood lymphocytes (53 bp/year) than in granulocytes (39 bp/year; p<0.001), while women having longer telomeres than men. We also observed the best correlation for age and telomere length to be present in lymphocytes. The coefficient variation (CV) of TL distribution in granulocytes and monocytes was significantly higher in older compared to younger individuals, indicating an increase in telomere length heterogeneity of myeloid cells and their bone marrow residing precursors during ageing. In a multivariate statistical model, CV and lymphocyte TL were able to explain 50% of chronological ageing.

Telomere attrition is significantly faster in lymphocytes than in granulocytes, with lymphocyte telomere length correlating most strongly with age. Furthermore, the coefficient of variation (CV; essentially an indication of the distribution of telomere lengths) increased significantly with age in both cell types. As the authors have previously reported that telomere length in granulocytes reflects that of myeloid bone marrow precursors, the present study implies that telomere length heterogeneity in bone marrow residing precursors also increases with age.

These findings imply that if two subjects have the same mean telomere length, the subject with increased heterogeneity (i.e., the older one) is likely to have a greater proportion of shorter telomeres in the stem cell compartment. The presence of just one critically shortened telomere may be sufficient to induce senescence (though this hypothesis is controversial; hence, telomere length heterogeneity may provide useful information that mean telomere length alone cannot.

The impact of sex on telomere length is the subject of some debate, with some studies reporting longer telomeres in women, while others show no difference. The present study may shed a little light on the subject: women were found to have longer lymphocyte telomere lengths, while granulocyte length did not differ. Thus, the relative number of each cell type in prior studies may skew interpretation of the data.

All subjects in this study were physically fit, walking or exercising “at least 20 km/week”; the authors stress this point in the methods, but fail to mention it in the discussion. This is disappointing in light of a recent high-impact study demonstrating that exercise improves the cardiovascular risk profile, increasing telomerase activity in peripheral blood mononuclear cells. The study may have aimed to examine the “healthiest” possible subjects, but as a consequence the results may not be representative of the general population.

Overall, this study highlights the importance of analyzing cell types individually to avoid the impact of differences in the ratios of cell type on interpreting telomere length data from peripheral blood. Furthermore, it adds telomere length heterogeneity to the list of important factors requiring further study.



  1. Good post. When I was interested in telomere lengths maybe a decade ago that data related to longevity did not seem very strong to me (though there was a lot of hype at the time). Glad to the series of papers you have blogged about recently are finding some compelling results. I wonder if measuring telomere lengths clinically (or with some home-kit) will become common?


  2. Richard Cawthon (based in Utah) published a PCR-based method in 2002. I have published a couple of papers using it myself, and it seems to be becoming an “accepted” method for telomere length analysis. He has a patent-pending on the assay, and has recently updated it in a way that makes it reproducible from lab-to-lab (by using an internal telomere-oligo template that samples are normalised to). One can see that with these types of improvements to the methodology results can be compared across labs, a step in the direction of standardising the analysis. The prognostic value of your telomere length is a subject that is receiving considerable interest, and I am in talks with a number of medics who want to know if clinical decisions can be made on the basis of telomere length…

  3. good post. which method did you use to analyze the telomere length. I developed a method to measure telomere length using Quantigene technology (bDNA), which is easy to use. There is no need of purifying DNA or amplifying DNA.

    Also I am developing a method to measure the telomere length for each specific chromosome arm. I am not sure whether this is useful or not.

  4. The paper presented here used a Flow-FISH method. I have used Southern blotting, dot/slot blotting and the Cawthon PCR myself. You mention telomere length analysis for specific chromosome arms – Duncan Baird published STELA, a method for amplifying individual telomeres a few years ago. Are you familiar with this? I would also be interested in hearing about your method.

    Thanks for reading.

  5. Thanks for your information. I tested my method with different sample amount input. The result is great. If you would like to try my method in your future work, please let me know.

  6. If you let me know when your method is published I will certainly have a look. Many thanks.

  7. Any feedback re: Umea University population study featured in ScienceDaily in Feb.and in PloGenetics on Telemeres? The researchers suggest that their
    “findings might challenge the hypothesis that individual TL can predict possible life span” for the individual, and that in vivo and in vitro realities may confound.
    Please respond re: the degree of confidence a MPH grad student might have in correlating
    ageing and telomere length, given differences in male/female and ethnic populations. Thank you so much!!!!

  8. Hi,
    i hav tried Cawthons method for telomere analysis,using primers of 2002 pub;ished paper,and i couldnt get proper melting curve and the cT value after 22 cyles, (and in paper 11 cycles),and changed primers to tel 1b and tel 2b.I’m bit not satisfied with the results obtained and i couldnt understand i one could get the melting curve analysis as single peak as the extended primers of diff length should give varied length and varied melting curve? I need help in solving the issues.

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