Midlife Aging in the Dunedin Study Phase 52
Lead Research Organisation:
KING'S COLLEGE LONDON
Department Name: Social Genetic and Dev Psychiatry Centre
Abstract
The overarching goal of our research program is to discover why some people age earlier and faster than others, and what might be done to prevent this. Increasingly, prevention-minded gerontologists and geroscientists look to midlife as the life stage offering a propitious opportunity to prevent or delay the multiple diseases that shrink older adults' health span. But because most studies of aging have enrolled participants well past midlife, and most studies of younger adults have not measured aging as a process of change over time, there is surprisingly little basic knowledge about aging during midlife. Our research program uniquely fills this gap. This is a proposal to follow up at age 52 a cohort of all 1037 infants born in one city in one year and exhaustively studied ever since: the Dunedin Longitudinal Study, in New Zealand. Some cohort members are becoming biologically older than their peers as they pass through midlife, others remain biologically younger. The proposed follow-up will allow us to quantify how fast or slowly each cohort member is aging in each of 8 different domains: the pace of biological aging, functional aging, facial aging, social aging, sexual aging, inflammatory aging, microvascular aging, and cognitive aging (Objective 1). These 8 domains are typically studied by different scientific disciplines in silos, but we will study them together in one cohort to attract scientific recognition to the great heterogeneity within the whole-person experience of aging. We will develop a measure of each of the 8 kinds of aging, by modelling 3 or more waves of data on each. Three data waves are the minimum requirement to disentangle each person's decline (aging-related decline, how people have changed; their slope) from their level (initial health, where people started; their intercept). Studies with fewer than 3 waves conflate decline over the years (aging) with low scores present since earlier life (not aging). The proposed follow-up at age 52 is necessary to add the essential 3rd midlife wave for this cohort of participants. This follow-up will create an unprecedented unique dataset. We will further generate new knowledge about the early-life antecedents of each kind of aging (Objective 2). We will also generate new knowledge about the risk each of the 8 kinds of aging poses for late-life dementing disease (Objective 3). This involves testing the hypothesis that fast-aging individuals exhibit accelerated brain aging. This will be established through a second wave of neuroimaging at age 52. We previously imaged the brains of Dunedin participants at age 45. We will test 7-year changes in functional neural connectivity and clinical measures of brain structure, while correcting for measurement error. It also involves testing the hypothesis that fast-aging individuals have elevated scores at age 52 on plasma Alzheimers disease biomarkers. To amplify scientific progress, we will deliver to the research community a reliable, valid, open-access DNA-methylation version of each of the 8 new measures of how rapidly a person has been aging (Objective 4). To evaluate generalizability of findings for under-represented ethnic-ancestry groups, we will export the 8 new DNA-methylation measures to Black, Hispanic, and Asian cohorts with methylation, where we have established collaborations to study the pace of aging.
Technical Summary
This is a proposal to follow up at age 52 a cohort of all 1037 infants born in one city in one year and exhaustively studied ever since: the Dunedin Longitudinal Study, in New Zealand. The proposed follow-up will allow us to quantify how fast or slowly each cohort member is aging in each of 8 different domains: the pace of biological aging, functional aging, facial aging, social aging, sexual aging, inflammatory aging, microvascular aging, and cognitive aging (Objective 1). We will develop a measure of each of the 8 kinds of aging, by modelling 3 or more waves of data on each. Three data waves are the minimum requirement to disentangle each person's decline (aging-related decline, how people have changed; their slope) from their level (initial health, where people started; their intercept). The proposed follow-up at age 52 is necessary to add the essential 3rd midlife wave for this cohort of participants. This follow-up will create an unprecedented unique dataset. We will further generate new knowledge about the early-life antecedents of each kind of aging (Objective 2). We will also generate new knowledge about the risk each of the 8 kinds of aging poses for late-life dementing disease (Objective 3). This involves testing the hypothesis that fast-aging individuals exhibit accelerated brain aging, as assessed by 7-year changes in functional neural connectivity and clinical measures of brain structure from neuroimaging. It also involves testing the hypothesis that fast-aging individuals have elevated scores at age 52 on plasma Alzheimer disease biomarkers. To amplify scientific progress, we will deliver to the research community a reliable, valid, open-access DNA-methylation version of each of the 8 new measures of how rapidly a person has been aging (Objective 4). To evaluate generalizability of findings for under-represented ethnic-ancestry groups, we will export the 8 new DNA-methylation measures to Black, Hispanic, and Asian cohorts with methylation.
Organisations
- KING'S COLLEGE LONDON (Lead Research Organisation)
- University of Oslo (Collaboration)
- Columbia University (Collaboration)
- University of Virginia (UVa) (Collaboration)
- Max Planck Society (Collaboration)
- Broad Institute (Collaboration)
- Singapore Eye Research Institute (Collaboration)
- Duke University (Collaboration)
- University of Pennsylvania (Collaboration)
- University of Otago (Collaboration)
- University of Michigan (Collaboration)
- Rigshospitalet (Collaboration)
- University of Exeter (Collaboration)
Publications
Hong CL
(2023)
Oral Health-Related Quality of Life from Young Adulthood to Mid-Life.
in Healthcare (Basel, Switzerland)
Balachandran A
(2025)
Pace of Aging analysis of healthspan and lifespan in older adults in the US and UK.
in Nature aging
Sunde HF
(2026)
Parental income and psychiatric disorders from age 10 to 40: a genetically informative population study.
in Journal of child psychology and psychiatry, and allied disciplines
Wertz J
(2025)
Parenting in childhood predicts personality in early adulthood: A longitudinal twin-differences study.
in The American psychologist
Cheyne K
(2025)
Persistent Cannabis Use and Ocular Health in Midlife.
in American journal of preventive medicine
Bourassa KJ
(2024)
Posttraumatic stress disorder, trauma, and accelerated biological aging among post-9/11 veterans.
in Translational psychiatry
Hill ED
(2025)
Prediction of mental health risk in adolescents.
in Nature medicine
Bourassa K
(2026)
PTSD and suPAR: A multicohort investigation of chronic inflammation
in Brain, Behavior, and Immunity
Whitman ET
(2026)
Replicated evidence for an accelerated rate of whole-body aging in schizophrenia.
in Psychological medicine
Lay-Yee R
(2023)
Social isolation from childhood to mid-adulthood: is there an association with older brain age?
in Psychological medicine
Matthews T
(2024)
Social isolation, loneliness, and inflammation: A multi-cohort investigation in early and mid-adulthood.
in Brain, behavior, and immunity
Islam S
(2026)
Social mobility and parenting: Testing associations in a prospective longitudinal cohort study.
in Child development
Knodt AR
(2023)
Test-retest reliability and predictive utility of a macroscale principal functional connectivity gradient.
in Human brain mapping
Andersen SH
(2024)
The causal effect of mental health on labor market outcomes: The case of stress-related mental disorders following a human-made disaster.
in Proceedings of the National Academy of Sciences of the United States of America
Brennan GM
(2024)
The Continuity of Adversity: Negative Emotionality Links Early Life Adversity With Adult Stressful Life Events.
in Clinical psychological science : a journal of the Association for Psychological Science
Poulton R
(2023)
The Dunedin study after half a century: reflections on the past, and course for the future.
in Journal of the Royal Society of New Zealand
Caspi A
(2024)
The general factor of psychopathology (p): Choosing among competing models and interpreting p.
in Clinical psychological science : a journal of the Association for Psychological Science
Gjerde LC
(2023)
The p factor of psychopathology and personality in middle childhood: Genetic and gestational risk factors - Corrigendum.
in Psychological medicine
Gjerde LC
(2023)
The p factor of psychopathology and personality in middle childhood: genetic and gestational risk factors.
in Psychological medicine
Brennan GM
(2023)
Tracing the origins of midlife despair: association of psychopathology during adolescence with a syndrome of despair-related maladies at midlife.
in Psychological medicine
Leung JH
(2024)
Trajectories of Hearing From Childhood to Adulthood.
in Ear and hearing
Barnes JC
(2024)
Using risk of crime detection to study change in mechanisms of decision making.
in Journal of personality and social psychology
Bourassa KJ
(2023)
Which Types of Stress Are Associated With Accelerated Biological Aging? Comparing Perceived Stress, Stressful Life Events, Childhood Adversity, and Posttraumatic Stress Disorder.
in Psychosomatic medicine
Coleman O
(2024)
Why do prospective and retrospective measures of childhood maltreatment differ? Qualitative analyses in a cohort study.
in Child abuse & neglect
Røysamb E
(2023)
Worldwide Well-Being: Simulated Twins Reveal Genetic and (Hidden) Environmental Influences.
in Perspectives on psychological science : a journal of the Association for Psychological Science
| Title | DunedinPACE an epigenetic measure of the whole-body pace of human biological aging |
| Description | DunedinPACE an epigenetic measure of the whole-body pace of human biological aging |
| Type Of Material | Physiological assessment or outcome measure |
| Year Produced | 2021 |
| Provided To Others? | Yes |
| Impact | Imported into 28 large cohort studies, generated >40 publications by other teams |
| Description | Aaron Reuben, iniversity of Virginia Dept of Psychology |
| Organisation | University of Virginia (UVa) |
| Country | United States |
| Sector | Academic/University |
| PI Contribution | ideas, analysis plans, data, analyses, writing, publications |
| Collaborator Contribution | ideas, analysis plans, data, analyses, writing, publications |
| Impact | several publications |
| Start Year | 2023 |
| Description | Columbia Univ School of Public Health |
| Organisation | Columbia University |
| Department | School of Public Health |
| Country | United States |
| Sector | Academic/University |
| PI Contribution | we provide data |
| Collaborator Contribution | Columbia provides funded young researcher |
| Impact | none yet |
| Start Year | 2012 |
| Description | Duke University Geriatrics School of Medicine |
| Organisation | Duke University |
| Department | School of Medicine Duke |
| Country | United States |
| Sector | Academic/University |
| PI Contribution | coauthor papears |
| Collaborator Contribution | coauthor papers |
| Impact | PNAS publication |
| Start Year | 2014 |
| Description | Evan Macosko, Genomics, Broad Institute, MIT. |
| Organisation | Broad Institute |
| Country | United States |
| Sector | Academic/University |
| PI Contribution | Shared depletable tissue |
| Collaborator Contribution | New Technology |
| Impact | genomics |
| Start Year | 2021 |
| Description | Go-DMC methylation consortium |
| Organisation | University of Exeter |
| Department | Exeter University Arts Faculty |
| Country | United Kingdom |
| Sector | Academic/University |
| PI Contribution | data collaboration |
| Collaborator Contribution | data collaboration |
| Impact | none yet |
| Start Year | 2018 |
| Description | Leah Richmond-Rakerd, Univ of Michigan Dept pf Psychology |
| Organisation | University of Michigan |
| Country | United States |
| Sector | Academic/University |
| PI Contribution | Data, writing, analyses, planning projects |
| Collaborator Contribution | Data, writing, analyses, planning projects |
| Impact | several publications and grants |
| Start Year | 2022 |
| Description | MAx Planck Institute of Psychiatry |
| Organisation | Max Planck Society |
| Department | Max Planck Institute of Psychiatry |
| Country | Germany |
| Sector | Academic/University |
| PI Contribution | replication on findings in independent studies |
| Collaborator Contribution | replication of findings |
| Impact | publication |
| Start Year | 2010 |
| Description | PROMENTA Centre University of Oslo Norway |
| Organisation | University of Oslo |
| Country | Norway |
| Sector | Academic/University |
| PI Contribution | PROMENTA Centre University of Oslo Norway |
| Collaborator Contribution | collab |
| Impact | Psychology, public health |
| Start Year | 2018 |
| Description | Rijkshospitalet Psychiatry Denmark |
| Organisation | Rigshospitalet |
| Department | Rigshospitalet |
| Country | Denmark |
| Sector | Hospitals |
| PI Contribution | coauthor and train students |
| Collaborator Contribution | data registries |
| Impact | publication |
| Start Year | 2014 |
| Description | Singapore Eye Inst Retinal micro-vasculature |
| Organisation | Singapore Eye Research Institute |
| Country | Singapore |
| Sector | Academic/University |
| PI Contribution | we contributed the cohort sample, and wrote the papers |
| Collaborator Contribution | SERI did the grading of digital retinal photos |
| Impact | 2 papers in press |
| Start Year | 2010 |
| Description | The Dunedin Multidisciplinary Health & Development Study, Otago School of Medicine |
| Organisation | University of Otago |
| Department | Dunedin Multidisciplinary Health & Development Research Unit |
| Country | New Zealand |
| Sector | Academic/University |
| PI Contribution | We raised funds and designed protocols and analysed the data |
| Collaborator Contribution | the Unit at Otago runs the cohort study and undertakes data-collection waves |
| Impact | over 1000 publications |
| Description | Univ of Pennsylvania studies of child abuse |
| Organisation | University of Pennsylvania |
| Department | Department of Psychology |
| Country | United States |
| Sector | Academic/University |
| PI Contribution | we provided data |
| Collaborator Contribution | data and idea exchange |
| Impact | 2 articles |
| Start Year | 2007 |
