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Measurement and initial characterization of leukocyte telomere length in 474,074 participants in UK Biobank

Abstract

Leukocyte telomere length (LTL) is a proposed marker of biological age. Here we report the measurement and initial characterization of LTL in 474,074 participants in UK Biobank. We confirm that older age and male sex associate with shorter LTL, with women on average ~7 years younger in ‘biological age’ than men. Compared to white Europeans, LTL is markedly longer in African and Chinese ancestries. Older paternal age at birth is associated with longer individual LTL. Higher white cell count is associated with shorter LTL, but proportions of white cell subtypes show weaker associations. Age, ethnicity, sex and white cell count explain ~5.5% of LTL variance. Using paired samples from 1,351 participants taken ~5 years apart, we estimate the within-individual variability in LTL and provide a correction factor for this. This resource provides opportunities to investigate determinants and biomedical consequences of variation in LTL.

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Fig. 1: DNA sample workflow to derive the final dataset.
Fig. 2: Distribution of weekly average LTL across duration of the study.

Data availability

Access to samples was made available through the UKB Resource under application no. 6077. As per the standard terms of UKB, all data for the telomere measurements were returned to UKB to be made available to other researchers. All source data used in this study, including all data related to the telomere measurements are accessible via application to UKB. Further information on registration to access the data can be found at http://www.ukbiobank.ac.uk/register-apply/. Information on telomere measurements can be viewed in the data showcase (https://biobank.ndph.ox.ac.uk/showcase/) under the following fields: 22190 (unadjusted), 22191 (adjusted), 22192 (adjusted and z-transformed) and 22194 (both time point measurements for the regression dilution bias experiment).

Code availability

LTL measurement data were added to a custom-built database application. The source code for this is available at https://github.com/LCBRU/telomere. No other custom code was used in this study.

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Acknowledgements

This research has been conducted using the UKB Resource under application no. 6077 and was funded by the UK Medical Research Council (MRC), Biotechnology and Biological Sciences Research Council and British Heart Foundation (BHF) through MRC grant MR/M012816/1 (V.C., C.P.N., J.R.T., J.N.D. and N.J.S.). The authors are also supported by grants from the BHF, SP/16/4/32697 (C.P.N.), RG/13/13/30194, RG/18/13/33946, CH/12/2/29428 (E.A., S.K., T.J., E.D.A., A.M.W., A.S.B. and J.N.D.); MRC, MR/L003120/1 (E.A., S.K., T.J., E.D.A., A.M.W., A.S.B. and J.N.D.); the National Institute for Health Research (NIHR) Leicester Cardiovascular Biomedical Research Centre (BRC-1215–20010, V.C., C.A.B., C.M., V.B., Q.W., S.E.H., C.P.N. and N.J.S.), NIHR Cambridge Biomedical Research Centre (BRC-1215-20014, E.A., S.K., T.J., E.D.A., A.M.W., A.S.B. and J.N.D.), NIHR Blood and Transplant Research Unit in Donor Health and Genomics (NIHR BTRU-2014-10024, E.A., S.K., T.J., E.D.A., A.M.W., A.S.B. and J.N.D.), Health Data Research UK (E.A., S.K., T.J., E.D.A., A.M.W., A.S.B. and J.N.D.) and EU/EFPIA Innovative Medicines Initiative Joint Undertaking BigData@Heart (11607, A.M.W. and E.A.). J.N.D. holds a BHF Personal Professorship. V.C., Q.W. and C.P.N. acknowledge support from the van Geest Heart and Cardiovascular Diseases Research Fund, University of Leicester. P. Akbari, T. Bolton and M. Arnold made computational and biostatistical contributions to this work. We thank L. Courtney, S. Welsh and D. Fry for assistance with UKB samples.

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M.D., C.S., M.P., S. Sheth, D.E.N. and V.C. generated the data. S.C.W., C.A.B., R.B., J.R.T., V.C. and C.P.N. curated the data. C.M., V.B., Q.W., A.S.B., J.R.T., V.C. and C.P.N. performed statistical analyses. V.C., C.P.N., C.M., Q.W., C.A.B., E.A., S.K., S. Stoma, V.B., T.J., E.D.A., A.M.W., A.S.B., J.R.T., J.N.D. and N.J.S. drafted the manuscript and all authors revised it. V.C., C.P.N., J.R.T., J.N.D. and N.J.S. (Principal Investigator) secured funding and oversaw the project.

Corresponding authors

Correspondence to V. Codd or N. J. Samani.

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Nature Aging thanks Timothy Hohman, Immaculata De Vivo, Sara Hagg and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Extended data

Extended Data Fig. 1 Significant technical parameters affecting LTL measurements based on the stage 1 adjustment.

Summary box plots are shown for the 474, 074 LTL measurements for each associated parameter: Enzyme batch (A), PCR machine (B), primer batch (C), operator (D). Individual data points show minimum and maximum measures, the box represents the lower quartile (bottom), upper quartile (top) and median (internal line). The upper and lower whiskers extend to a value no further than 1.5 * IQR from the respective quartile. Linear relationships were seen between LTL and temperature (E) and humidity (F). For both (E) and (F) a fitted regression line is shown with 95% confidence intervals (gray shading).

Extended Data Fig. 2 Significant interactions based on the stage 2 adjustment.

(A) LTL by Primer and Operator. (B) LTL by primer and PCR machine. PCR machines 5 and 6 were not used at the start of the pilot study (primer batch 1) and machines 7 and 8 were used from the end of the pilot stage (primer batch 3 onwards).

Extended Data Fig. 3 Effect of A260/280 on LTL.

The distribution of DNA sample A260/280 ratios is illustrated in (A). We observed an increase in LTL with very low and very high A260/280 ratios (B). Data shown is mean LTL (blue0 with 95% confidence interval (gray).

Extended Data Fig. 4 Distribution of the coefficients of variation for the repeat samples.

Distribution of CVs after technical adjustment for both the blinded repeats (A) (n=528) and deliberate repeats (B) (n=22,615) are shown. The gray dotted line represents the median coefficient of variation with the shaded region representing the interquartile range.

Extended Data Fig. 5 Data on the first and second DNA sample used to estimate regression dilution ratio.

(A) Histogram showing that the gap between the two sample collections has a mean interval of 5.5 years (range: 2–10 years, N=1,312). (B) Correlation between the first and second loge-LTL measure by time, estimated by the difference in years between the two sample collections and shown with 95% confidence intervals. The blue circle reflects the correlation estimate (center) with size reflecting the number of participants measured each year (exact N shown in brackets). The black line shows the overall pooled correlation for all samples and the red dotted lines indicate the 95% confidence interval for this estimate.

Extended Data Fig. 6 Age and sex relationships for participants used to estimate regression dilution bias.

The decline of LTL with age is shown for men (blue) and women (plum) for both the first (A) and second (B) LTL measurements. The estimated effect sizes are shown for age (β_Age) and sex (β_Sex) within the figures.

Extended Data Fi. 7 Decline of LTL with age.

The decline of z-standardized loge-LTL with age is shown for men (blue) and women (plum) in adjusted data. The y-axis is truncated at -5SD to +5 SD with 166 data points (80 women, 86 men) not shown. A small number of participants recruited by UK Biobank fall outside of the stated 40–69 age range.

Extended Data Fig. 8 Decline in LTL with age by sex.

Using stratified regression for men (blue) and women (plum) for all participants (N=474,074) we considered the non-linear effect of age within each sex. Here we show the predicted shape in a solid line and the observed data in a dashed line with 95% confidence intervals. There is significant non-linearity observed for women, where the rate of LTL decline increases as the population ages.

Extended Data Fig. 9 Telomere lengths within individual ethnic groups.

Data adjusted for both age and sex are shown in purple for individual observations to indicate the range and quantity of data alongside a box-plot to show the median (line) and interquartile range (box) with whiskers extending to a value no further than 1.5 * IQR from the respective quartile. Box plots of data with additional adjustment for BMI, CRP, HbA1c, smoking status, alcohol consumption and measures of physical activity, socioeconomic status and diet are shown in blue. Ethnicity is self-reported and presented as defined by UK Biobank Data-Field 21000. Note that we shorten “Asian or Asian British” to Asian and “Black or Black British” to Black.

Extended Data Fig. 10 LTL by age in different ethnic groups.

LTL measurements were adjusted for sex, BMI, CRP, HbA1c, smoking status, alcohol consumption and measures of physical activity, socioeconomic status and diet.

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Codd, V., Denniff, M., Swinfield, C. et al. Measurement and initial characterization of leukocyte telomere length in 474,074 participants in UK Biobank. Nat Aging 2, 170–179 (2022). https://doi.org/10.1038/s43587-021-00166-9

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