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More About The DunedinPACE Study and its Development

Dunedin: a small city located in the South Island of New Zealand and home to the Dunedin School of Medicine at the University of Otago.

PACE: the pace of aging measure.

The Dunedin Multidisciplinary Health and Development Study is a detailed study of human health, development, and behavior. The Dunedin Study has followed the lives of 1037 babies born between April 1, 1972, and March 31, 1973, at Queen Mary Maternity Hospital, Dunedin, New Zealand, since their birth. The study is now in its fifth decade and has produced a considerable amount of data that shapes what we know about the pace at which humans age. [1] This algorithm was created by looking at over 1,000 individuals’ data at 173 CpG sites.

The Dunedin Study

The Dunedin cohort is one of the most remarkable resources for studying human biology. This is not the biggest nor the longest longitudinal study conducted, but it is special because it has a very high retention rate of participants. With 95% of the original cohort remaining in the study since its launch, the Dunedin cohort is THE MOST closely examined group on earth. To put in perspective a good retention rate for longitudinal studies is between 60 to 80 percent of the original cohort population. [11]

Previous studies have attempted to measure the pace of aging by analyzing DNA methylation differences between people of different chronological ages. However, the “limitation of this approach is that individuals born in different years have grown up under different historical conditions, with a possibility of more exposure to childhood diseases, tobacco smoke, airborne lead, and less exposure to antibiotics and other medications, as well as lower quality nutrition – all of which affect DNA methylation.

An alternative approach is to study individuals who were all born the same year, and find methylation patterns that differentiate those who have been aging biologically faster or slower than their same-age peers.” [3] The Dunedin study focuses on a one-year age cohort makes it more effective at tracking its participants, which contributes to the low number of extraneous variability in the results.

Following the one-year birth cohort, the repeated measures of data were collected via blood when the study members were 26, 32, 38, and 45 years old to quantify their rates of biological aging. The gathered data represents a personal rate of multi-organ system decline over a dozen years which determines the algorithm for pace of aging.

Four-Step Approach

The researchers took a four-step approach toward developing a blood DNA methylation metric that represents individual variation in the pace of biological aging.

Dunedin Longitudinal Study

Pace of Aging

Elastic Net Regression

DundedinPACE Algorithm

Step 1 - Dunedin Longitudinal Study

In the initial step, the Dunedin researchers collected a blood panel of 18 and organ-system-function biomarkers at three successive waves of the Dunedin Study. By using repeated measures of data the study members were aged 26, 32, 38, and 45 years old. They calculated the rate of change in each biomarker and how each individual’s rate of change differed from the cohort’s norm. Then they combined the individual’s 18 personal rates of change across the panel of biomarkers to compute a composite for each study member, which is how they determine the pace of aging. [7]

Step 2 - Pace of Aging

In the second step they validated the pace of aging from known criteria. Members of the studys cohort who had faster paces of aging performed more poorly on tests of physical function, by showing signs of cognitive decline on a panel of dementia-relevant neuropsychological tests from an early-life baseline for the individuals. These individuals were also rated, using an impartial system, as looking older based on their facial photographs. They also reported themselves to be in worse health.

They also found that a faster pace of aging is associated with early-life factors important for aging: familial longevity, low childhood social class, and adverse childhood experiences. [6] Notably, the pace of aging was not well-correlated with published epigenetic clocks, which were designed to measure how old a person is rather than how fast they are biologically aging. [5]

Step 3 - Elastic Net Regression

In step three, they refined the pace of aging into a measurement that is obtained from a single blood sample. Here we focused on blood DNA methylation as an accessible molecular measurement that is sensitive to changes in physiology occurring in multiple organ systems. Researchers used the data from a previous study published by the same authors (Belsky et al., 2018b) to apply an algorithm that captured the DNA methylation patterns linked with variation among individuals in their pace of aging. This algorithm is what they termed “DunedinPACE.”

Step 4 - DundedinPACE Algorithm

Step four is the validation step of the algorithm. They validated it in five ways:

First, using the Dunedin Study, they tested if study members’ DunedinPACE measured when they were aged 45 years could predict deficits in physical and cognitive functioning seven years later.

Second, researchers applied the DunedinPACE algorithm to DNA methylation data from a second, cross-sectional, study of adults to evaluate patterning of DunedinPACE by chronological age and sex and to test correlations of DunedinPACE with self-reported health and proposed measures of biological age, including three epigenetic clocks.

Third, the DunedinPACE algorithm was applied to DNA methylation data from a third, longitudinal study of older men to test associations with chronic-disease morbidity and mortality.

Fourth, the DunedinPACE algorithm was then applied to DNA methylation data from a fourth, longitudinal, study of young people to test if DunedinPACE was accelerated by exposure to poverty and victimization, factors which are known to shorten healthy lifespan.

Fifth, to ascertain the potential usefulness of DunedinPACE as a measure for trials of geroprotector treatments, the algorithm was applied to DNA methylation data from a randomized trial of caloric restriction, CALERIE [Ravussin et al., 2015]. Earlier we reported from this trial that the intervention (two years of prescribed 25% caloric restriction) slowed the rate of biological aging as measured by a blood-chemistry biological-age composite measure [Belsky et al., 2018a]. Here, using newly generated methylation data from blood drawn at the CALERIE baseline assessment, it was tested if (a) DunedinPACE from blood drawn before caloric restriction could predict the future rate of biological aging of participants during the two-year trial, and (b) if this prediction was disrupted in participants who underwent caloric restriction, but not among control participants. Promising results from this four-step research program was reported, while appreciating that additional measurement development will be needed to support the applied use of DunedinPACE.

Dunedin Longitudinal Study

The above chart shows the Dunedin Longitudinal Study. Dunedin researchers collected a blood panel of 19 markers (shown above) and organ-system-function biomarkers at four successive waves of the Dunedin Study. By using repeated measures of data the study members were aged 26, 32, 38, and 45 years old.

They calculated the rate of change in each biomarker and how each individual’s rate of change differed from the cohort’s norm. Then they combined the individual’s 18 personal rates of change across the panel of biomarkers to compute a composite for each study member, which is how they determine the pace of aging.

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DunedinPACE (or PoAm) Pace of Aging measure: 

Literature reporting findings up to December 2022

The name of the dataset is below each citation. 

Correlates are in bold. 

Raffington, L., Tanksley, P. T., Sabhlok, A., Vinnik, L., Mallard, T., King, L. S., Goosby, B., Harden, K. P., & Tucker-Drob, E. M. (2022). Socially Stratified Epigenetic Profiles Are Associated With Cognitive Functioning in Children and Adolescents. Psychological Science, 0(0). https://doi.org/10.1177/09567976221122760

Texas Twin Study. 

Etzel, L, et al. Shalev, I. (2022). Obesity and accelerated epigenetic aging in a high-risk cohort of children. Scientific Reports. 12,

The Child Health Study

Kuzawa CW, Ryan CP, Adair LS, Lee NR, Carba DB, MacIsaac JL, Dever K, Atashzay P, Kobor MS, McDade TW. Birth weight and maternal energy status during pregnancy as predictors of epigenetic age acceleration in young adults from metropolitan Cebu, Philippines. Epigenetics. 2022 Nov;17(11):1535-1545. doi: 10.1080/15592294.2022.2070105 

Cebu Longitudinal Health and Nutrition Survey (CLHNS Phillipines)

Freni-Sterrantino A, Fiorito G, D’Errico A, Robinson O, Virtanen M, Ala-Mursula L, Järvelin MR, Ronkainen J, Vineis P. Work-related stress and well-being in association with epigenetic age acceleration: A Northern Finland Birth Cohort 1966 Study. Aging (Albany NY). 2022 Feb 2;14(3):1128-1156. doi: 10.18632/aging.203872.

Northern Finland Birth Cohort 1966 Study

Botong Shen, Ph.D.1, Nicolle A. Mode, M.S.1, Nicole Noren Hooten, Ph.D.1, Natasha L. Pacheco Ph.D.,1, Ngozi Ezike, M.D.1, Alan B. Zonderman, Ph.D.1, and Michele K. Evans, M.D.  (in review 2022). Association of race and poverty status with a faster pace of biological aging. 

The HANDLE Study (NIA intramural study of older adults)

Kim Y, Huan T, Joehanes R, McKeown NM, Horvath S, Levy D, Ma J. Higher diet quality relates to decelerated epigenetic aging. Am J Clin Nutr. 2022 Jan 11;115(1):163-170. doi: 10.1093/ajcn/nqab201.

The Framingham Offspring Study. 

Simons, R. L., Lei, M.-K., Klopach, E., Berg, M., Zhang, Y., & Beach, S. S. R. (2021). (Re)Setting Epigenetic Clocks: An Important Avenue Whereby Social Conditions Become Biologically Embedded across the Life Course. Journal of Health and Social Behavior, 62(3), 436–453. https://doi.org/10.1177/00221465211009309

The FACHS Study (Family and Community Health Study of African American Families)

Simons, R., Ong, M., Lei, M., Klopack, E., Berg, M., Zhang, Y., Philibert, R., & Beach, S. Unstable Childhood, Adult Adversity, and Smoking Accelerate Biological Aging Among Middle-Age African Americans: Similar Findings for GrimAge and PoAm. J of Aging and Health 089826432110436. 10.1177/08982643211043668.

The FACHS Study

Simons, Ronald L., Mei Ling Ong, Man-Kit Lei, Eric Klopach, Mark Berg, Yue Zhang, Robert Philibert, Frederick X. Gibbons, Steven R.H. Beach (2022). Shifts in lifestyle and socioeconomic circumstances predict change—for better or worse—in speed of epigenetic aging: A study of middle-aged black women, Social Science & Medicine, Volume 307, 2022, 115175,

https://doi.org/10.1016/j.socscimed.2022.115175.

The FACHS Study

Beach, S.R.H.; Klopack, E.T.; Carter, S.E.; Philibert, R.A.; Simons, R.L.; Gibbons, F.X.; Ong, M.L.; Gerrard, M.; Lei, M.-K.  (2022) Do Loneliness and Per Capita Income Combine to Increase the Pace of Biological Aging for Black Adults across Late Middle Age? Int. J. Environ. Res. Public Health 2022, 19, 13421. https://doi.org/10.3390/ijerph192013421

The FACHS Study

Lei MK, Berg MT, Simons RL, Beach SRH. (2022). Neighborhood structural disadvantage and biological aging in a sample of Black middle age and young adults.  Soc Sci Med

The FACHS Study

Yu, Y.-L. (2023). Current Marital Status and Epigenetic Clocks Among Older Adults in the United States: Evidence From the Health and Retirement Study. Journal of Aging and Health, 35(1–2), 71–82. https://doi.org/10.1177/08982643221104928

The US Health and Retirement Study

Avila-Rieger, Justina, Indira C. Turney, Jet M.J. Vonk, Precious Esie, Dominika Seblova, Vanessa R. Weir, Daniel W. Belsky, Jennifer J. Manly (2022).  Socioeconomic Status, Biological Aging, and Memory in a Diverse National Sample of Older US Men and Women. 

Neurology 99 (19) e2114-e2124;  DOI: 10.1212/WNL.0000000000201032 

Health and Retirement Study

Graf Gloria H, Christopher L Crowe, Meeraj Kothari, Dayoon Kwon, Jennifer J Manly, Indira C Turney, Linda Valeri, Daniel W Belsky, Testing Black-White Disparities in Biological Aging Among Older Adults in the United States: Analysis of DNA-Methylation and Blood-Chemistry Methods, American Journal of Epidemiology, Volume 191, Issue 4, April 2022, Pages 613–625, https://doi.org/10.1093/aje/kwab281

Health and Retirement Study

Graf Gloria Huei-Jong, Yalu Zhang, Benjamin W Domingue, Kathleen Mullan Harris, Meeraj Kothari, Dayoon Kwon, Peter Muennig, Daniel W Belsky, (2022). Social mobility and biological aging among older adults in the United States, PNAS Nexus, Volume 1, Issue 2, pgac029, https://doi.org/10.1093/pnasnexus/pgac029

Health and Retirement Study

Kelly E. Rentscher, Eric T. Klopack, Eileen M. Crimmins, Teresa E. Seeman, Steve W. Cole, Judith E. Carroll  (in review). Lower Social Support is Associated with Accelerated Epigenetic Aging: Results from the Health and Retirement Study

medRxiv 2022.06.03.22275977; doi: https://doi.org/10.1101/2022.06.03.22275977 

Health and Retirement Study

Schmitz, Lauren L. & Duque, Valentina (2022). In-utero exposure to the Great Depression is reflected in late-life epigenetic aging signatures. PNAS, 119 (46) e2208530119

https://doi.org/10.1073/pnas.2208530119

Health and Retirement Study

Peterson, Mark D. Stacey CollinsHelen C.S. MeierAlexander BrahmsteadtJessica D. Faul (2022). Grip strength is inversely associated with DNA methylation age acceleration. J of Cachexia, sarcopenia, and muscle. https://doi.org/10.1002/jcsm.13110

Health and Retirement Study

Schmitz LL, Zhao W, Ratliff SM, Goodwin J, Miao J, Lu Q, Guo X, Taylor KD, Ding J, Liu Y, Levine M, Smith JA. The Socioeconomic Gradient in Epigenetic Ageing Clocks: Evidence from the Multi-Ethnic Study of Atherosclerosis and the Health and Retirement Study. Epigenetics. 2022 Jun;17(6):589-611. doi: 10.1080/15592294.2021.1939479

MESA (Multi-ethnic Study of Atherosclerosis) and the Health and Retirement Study

Reed RG, Carroll JE, Marsland AL, Manuck SB. (2022). DNA methylation-based measures of biological aging and cognitive decline over 16-years: preliminary longitudinal findings in midlife. Aging; 14:9423-9444 . https://doi.org/10.18632/aging.204376

AHAB Study (Adult Health and Behavior Pittsburgh)

McCrory C, Fiorito G, O’Halloran AM, Polidoro S, Vineis P, Kenny RA. (2022) Early life adversity and age acceleration at mid-life and older ages indexed using the next-generation GrimAge and Pace of Aging epigenetic clocks. Psychoneuroendocrinology. Mar;137:105643. doi: 10.1016/j.psyneuen.2021.105643.

TILDA (the Irish Longitudinal Study of Aging)

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, Article 790926. https://doi.org/10.3389/fnagi.2021.790926

BLSA (Baltimore Longitudinal Study of Aging)

Caro, Juan Carlos, Cyrielle Holuka, Giorgia Menta, Jonathan D. Turner, Claus Vögele, Conchita D’Ambrosio, (2023). Children’s internalizing behavior development is heterogeneously associated with the pace of epigenetic aging, Biological Psychology, Volume 176, 2023,

108463, https://doi.org/10.1016/j.biopsycho.2022.108463.

Jesse R. Poganik, Bohan Zhang, Gurpreet S. Baht, Csaba Kerepesi, Sun Hee Yim, Ake T. Lu, Amin Haghani, Tong Gong, Anna M. Hedman, Ellika Andolf, Göran Pershagen, Catarina Almqvist, James P. White, Steve Horvath, Vadim N. Gladyshev, Biological age is increased by stress, and restored upon recovery from stress, BioRxiv, 2022,

Three Clinical Datasets

Michael Safaee, Varun Dwaraka, Justin K. Scheer, Marissa Fury, Tavis Mendez, Ryan Smith, Jue Lin, Dana Smith, Christopher P. Ames, (2022).  Cellular aging for risk stratification in adult deformity surgery: utilization of seven epigenetic clocks and two telomere length measurements in the analysis of comorbidity burden, frailty, disability and complications in adult deformity surgery, The Spine Journal, Volume 22, Issue 9, Supplement, 2022, Pages S13-S14,

ISSN 1529-9430, https://doi.org/10.1016/j.spinee.2022.06.041.

Clinical sample. 

Effect of Long-Term Caloric Restriction on DNA Methylation Measures of Biological Aging in Healthy Adults: CALERIE™ Trial Analysis (2023).  R Waziry, DL Corcoran, KM Huffman, MS Kobor, M Kothari, VB Kraus, WE Kraus, DTS Lin, CF Pieper, ME Ramaker, M Bhapkar, SK Das, L Ferrucci, WJ Hastings, M Kebbe, DC Parker, SB Racette, I Shalev, B Schilling, DW Belsky,  medRxiv 2021.09.21.21263912; doi: https://doi.org/10.1101/2021.09.21.21263912 

CALERIE Trial 

Sugden, K., A. Caspi, ML Elliott, KJ Bourassa, K Chamarti, DL Corcoran, AR Hariri, RM Houts, Meeraj Kothari, S Kritchevsky, GA Kuchel, J Mill. BS Williams, DW Belsky, TE Moffitt (2022). Association of Pace of Aging measured by blood-based DNA methylation with age related cognitive decline and dementia. Neurology 

ADNI Study (Alzheimers Disease Neuroimaging Initiative), Framingham Offspring Study

Sugden, Karen, Terrie E. Moffitt, Thalida Em Arpawong, Daniel W. Belsky, David L. Corcoran, Eileen M. Crimmins, Eilis Hannon, Renate Houts, Jonathan S. Mill, Richie Poulton, Sandyha Ramrakha, Jasmin Wertz, Benjamin S. Williams, Avshalom Caspi, (in review). Cross-national and cross-generational evidence that educational attainment may slow the pace of aging. J of Gerontology

Health and Retirement Study, Generation Scotland, E-Risk Study, UK Understanding Society, Dunedin Study

Belsky, DW, A Caspi, L Arseneault, Baccarelli, A., D Corcoran, Gao, X, Hannon, HL Harrington, L J Rassmussen, R Houts, K Huffman, WE Kraus, Kwon, D, J Mill, C Pieper, J Prinz, R Poulton, Schwartz, J, K Sugden, Vokonas, P, B Williams, TE Moffitt (2020). Quantification of the pace of biological aging in humans through a blood test: The DunedinPoAm DNA methylation algorithm, eLife https://elifesciences.org/articles/54870

Dunedin Study, Normative Aging Study, E-Risk Study, UK Understanding Society

Belsky, DW, A Caspi, D Corcoran, K Sugden, R Poulton, L Arseneault, A Baccarelli, K Chamarti, X Goa, E Hannon,, HL Harrington, R Houts, M Kotharti, D Kwon, J Mill, J Schwartz, P Vokonas, C Wang, B Williams,  TE Moffitt (2022). DunedinPACE, A DNA methylation biomarker of the Pace of Aging, eLife

Dunedin Study, Normative Aging Study, E-Risk Study, Framingham Heart Study, UK Understanding Society

Bourassa, K. J., Caspi, A., Harrington, H. L., Houts, R. M., Poulton, R., Ramrakha, S., & Moffitt, T. E. (2020). Intimate partner violence and lower relationship quality are associated with faster biological aging. Psychology and Aging

Dunedin Study. 

Ruiz, Begoña, Jonathan M. Broadbent, W. Murray Thomson, Sandhya Ramrakha, Terrie E. Moffitt, Avshalom Caspi, Richie Poulton. (in review). Childhood caries is associated with poor health and a faster pace of ageing by midlife. 

Dunedin Study

Belsky DW, Caspi A, Cohen HJ, Kraus WE, Ramrakha S, Poulton R, Moffitt TE. (2017). Impact of Early Personal History Characteristics on the Pace of Aging: Implications for Clinical Trials of Therapies to Slow Aging and Extend Healthspan. Aging Cell.  

Dunedin Study

Bourassa, K. J., Moffitt, T. E. Ambler, A., Hariri, A., Harrington, H. L., Houts, R. M., Ireland, D., Knodt, A., Poulton, R., Ramrakha, S., Caspi, A., (2022). Accelerated aging in midlife is antedated by treatable adolescent health conditions. JAMA Pediatrics   https://jamanetwork.com/journals/jamapediatrics/fullarticle/2789349

Dunedin Study

Meier, Madeline H., Avshalom Caspi, Antony Ambler, Ahmad R. Hariri, HonaLee Harrington, Sean Hogan, Renate Houts, Annchen R. Knodt, Sandhya Ramrakha, Leah Richmond-Rakerd, Richie Poulton Terrie E. Moffitt (2022). Long-term Cannabis Users’ Preparedness for Healthy Aging: A Population-Representative Longitudinal Study. Lancet Healthy Longevity

Dunedin Study

Langevin, S., Caspi, A., Barnes, J.C, Brennan, G., Poulton, R., Purdy, S., Tanksley, P.T., Thorne, P., Wilson, G., & Moffitt, T.E. (2022). Life-course persistent antisocial behavior and accelerated biological aging in a longitudinal birth cohort. International Journal of Environmental Research and Public Health 

Dunedin Study

Bourassa, K. J., Caspi, A., Hall, K. S., Harrington, H. L., Houts, R. M., Kimbrel, N. A., Poulton, R., Ramrakha, S., Taylor, G. A., & Moffitt, T. E. Which measures of stress best predict accelerated biological aging? Comparing perceived stress, stressful life events, and posttraumatic stress disorder. Under review. 

Dunedin Study

Wertz, Jasmin, Avshalom Caspi, Antony Ambler, Jonathan Broadbent, Robert J. Hancox, HonaLee Harrington, Renate M. Houts, Joan H. Leung, Richie Poulton, Suzanne C. Purdy, Sandhya Ramrakha, Line Jee Hartmann Rasmussen, Leah S. Richmond-Rakerd, Peter R. Thorne, Graham A. Wilson, Terrie E. Moffitt, (2021). History of psychiatric illness as a risk factor for accelerated aging: Evidence from a population-representative longitudinal cohort study. JAMA-Psychiatry, 

Dunedin Study

Belsky DW, Caspi A, Houts R, Cohen HJ, Corcoran D, Danese A, Harrington HL, Israel S, Levine ME, Schaefer J, Sugden K, Williams B, Yashin A, Poulton R, Moffitt TE. (2015). Quantification of biological aging in young adults. Proceedings of the National Academy of Sciences of the United States of America. 77, 601-617. 

Dunedin Study

Belsky DW, Moffitt TE, Cohen AA, Corcoran DL, Levine ME, Prinz J, Schaefer J, Sugden K, Williams B, Poulton R, Caspi A. (2017). Eleven telomere, epigenetic clock, and biomarker-composite quantifications of biological aging: Do they measure the same thing? American J of Epidemiology. doi: http://dx.doi.org/10.1101/071373 )

Dunedin Study 

Elliott, Maxwell L. Daniel W. Belsky, Annchen R. Knodt, David Ireland, Tracy R. Melzer, Richie Poulton, Sandhya Ramrakha, Avshalom Caspi, Terrie E. Moffitt, Ahmad R. Hariri (2019) Brain-age in midlife is associated with accelerated biological aging and cognitive decline in a longitudinal birth-cohort.  Molecular Psychiatry, 

Dunedin Study 

Elliott, Max, Avshalom Caspi, RM Houts, A Ambler, JM Broadbent, RJ Hancox, HL Harrinton, S Hogan, R Keenan, A Knodt, JH Leung, TR Melzer, SC Purdy, S Ramrakha, LS Richmond-Rakerd, A Righarts, K Sugden, WM Thomson, PR thorne, BS Williams, G Wilson, AR Hariri, R Poulton, TE Moffitt (2021) Disparities in the pace of biological aging among midlife adults of the same chronological age: Implications for future frailty risk and policy. Nature Aging https://rdcu.be/cgNdq

Dunedin Study

Richmond-Rakerd, Leah S., Avshalom Caspi, Antony Ambler Tracy d’Arbeloff, Marieke de Bruine, Maxwell Elliott, HonaLee Harrington, Sean Hogan, Renate M. Houts, David Ireland, Ross Keenan, Annchen R. Knodt, Tracy R. Melzer, Sena Park, Richie Poulton, Sandhya Ramrakha, Line Jee Hartmann Rasmussen, Elizabeth Sack, Adam T. Schmidt, Maria L. Sison, Jasmin Wertz, Ahmad R. Hariri, & Terrie E. Moffitt (2021). Childhood self-control forecasts the pace of midlife aging and preparedness for old age. PNAS    https://www.pnas.org/content/118/3/e2010211118

Dunedin Study.

Rasmussen, LJ, A Caspi, A Ambler, A Danese, M Elliott, J Eugen-olsen, A Hariri, HL Harrington, R Houts, R Poulton, S Ramrakha, K Sugden, B Williams, TE Moffitt. (2020). Association between elevated suPAR, a new biomarker of chronic inflammation, and accelerated aging. Journal of Gerontology, Medical Sciences

Dunedin Study