A study published in Frontiers in Aging Neuroscience examined the relationship between epigenetic age acceleration and hearing [1].
Since 1958, a team of researchers from the National Institute on Aging Intramural Research program has been conducting the Baltimore Longitudinal Study of Aging (BLSA). The BLSA study continuously enrolls volunteers free of chronic conditions from a variety of age groups and conducts visits every 1 to 4 years, depending on age. Participants younger than 60 were seen every 4 years, participants between 60 and 79 were seen every 2 years, and participants who were at least 80 were seen every year.
Major revisions were made in 2003 to the BLSA study to add phenotypic measurements and molecular biomarkers. Due to the longitudinal nature of the study, changes in technology have occurred during the study effort, and extensive efforts have been made over time to control for these changes in analysis according to Dr. Luigi Ferruci and colleagues [2].
Epigenetic aging and hearing loss in a longitudinal study
236 individuals from the BLSA study were enrolled in this secondary analysis study. DNA was extracted from blood samples and CpG methylation status was determined from 485,577 CpG sites. Hearing was tested by trained technicians in a soundproof booth with an audiometer device.
Epigenetic age acceleration was measured with the GrimAge [3], Intrinsic Epigenetic Age Acceleration (IEAA) Horvath [4], Hannum [5], Phenoage [6], and Dunedin Pace of Aging (DunedinPACE) [7] clocks.
GrimAge and DunedinPACE had the strongest association with hearing
After adjusting for age, sex, race, and time, hearing was statistically associated with the GrimAge and DunedinPACE clocks. Both the direction and magnitude of the associations continued to be consistent after adjustment for congestive heart failure, hypertension, peripheral arterial disease, and smoking history.
An additional subanalysis was done on 197 participants, as some of the epigenetic clocks were limited to people who were at least 60 years old. In this older subset of participants, similar to the prior result, the GrimAge clock and the DunedinPACE clock were statistically associated with hearing. The researchers then ran an additional analysis to adjust for the variable of smoking cigarettes history. Like the prior two results, the GrimAge clock and the DunedinPACE clock were statistically associated with hearing. When the variable changed from the better hearing ear to the worse hearing ear, the results remained consistent.
Conclusion
This study was the first to examine the relationship between hearing loss via audiometric measurement and epigenetic clocks. The authors note some possible confounding factors and potential inaccuracies in the study, make it clear that future studies are needed, and finish as follows:
In conclusion, our findings demonstrate that not all epigenetic clocks were strongly correlated with hearing. Only those epigenetic clocks established using many cardiovascular measurements with longitudinal information were associated with hearing. Future research is needed to study the potential subclinical cardiovascular causes of hearing and to investigate the relationship between DNA methylation and hearing longitudinally.
Literature
[1] Kuo, P. L., Moore, A. Z., Lin, F. R., & Ferrucci, L. (2021). Epigenetic Age Acceleration and Hearing: Observations From the Baltimore Longitudinal Study of Aging. Frontiers in aging neuroscience, 13, 790926. https://doi.org/10.3389/fnagi.2021.790926
[2] Kuo, P. L., Schrack, J. A., Shardell, M. D., Levine, M., Moore, A. Z., An, Y., Elango, P., Karikkineth, A., Tanaka, T., de Cabo, R., Zukley, L. M., AlGhatrif, M., Chia, C. W., Simonsick, E. M., Egan, J. M., Resnick, S. M., & Ferrucci, L. (2020). A roadmap to build a phenotypic metric of ageing: insights from the Baltimore Longitudinal Study of Aging. Journal of internal medicine, 287(4), 373–394. https://doi.org/10.1111/joim.13024
[3] Lu, A. T., Quach, A., Wilson, J. G., Reiner, A. P., Aviv, A., Raj, K., Hou, L., Baccarelli, A. A., Li, Y., Stewart, J. D., Whitsel, E. A., Assimes, T. L., Ferrucci, L., & Horvath, S. (2019). DNA methylation GrimAge strongly predicts lifespan and healthspan. Aging, 11(2), 303–327. https://doi.org/10.18632/aging.101684
[4] Horvath S. (2013). DNA methylation age of human tissues and cell types. Genome biology, 14(10), R115. https://doi.org/10.1186/gb-2013-14-10-r115
[5] Hannum, G., Guinney, J., Zhao, L., Zhang, L., Hughes, G., Sadda, S., Klotzle, B., Bibikova, M., Fan, J. B., Gao, Y., Deconde, R., Chen, M., Rajapakse, I., Friend, S., Ideker, T., & Zhang, K. (2013). Genome-wide methylation profiles reveal quantitative views of human aging rates. Molecular cell, 49(2), 359–367. https://doi.org/10.1016/j.molcel.2012.10.016
[6] Levine, M. E., Lu, A. T., Quach, A., Chen, B. H., Assimes, T. L., Bandinelli, S., Hou, L., Baccarelli, A. A., Stewart, J. D., Li, Y., Whitsel, E. A., Wilson, J. G., Reiner, A. P., Aviv, A., Lohman, K., Liu, Y., Ferrucci, L., & Horvath, S. (2018). An epigenetic biomarker of aging for lifespan and healthspan. Aging, 10(4), 573–591. https://doi.org/10.18632/aging.101414
[7] Belsky, D. W., Caspi, A., Arseneault, L., Baccarelli, A., Corcoran, D. L., Gao, X., Hannon, E., Harrington, H. L., Rasmussen, L. J., Houts, R., Huffman, K., Kraus, W. E., Kwon, D., Mill, J., Pieper, C. F., Prinz, J. A., Poulton, R., Schwartz, J., Sugden, K., Vokonas, P., … Moffitt, T. E. (2020). Quantification of the pace of biological aging in humans through a blood test, the DunedinPoAm DNA methylation algorithm. eLife, 9, e54870. https://doi.org/10.7554/eLife.54870
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