A single New Zealand cohort of 1,037 people, all born in the same city in the same year, is being tracked through midlife to measure how fast each person is aging across eight different biological and social systems at once. Most aging studies start too late—after people are already old—or measure only one kind of aging in isolation. This project fills that gap by following the same individuals from birth to age 52, generating the first dataset that can separate genuine aging-related decline from pre-existing differences that were present since childhood. If successful, the research will produce eight open-access DNA-methylation measures that any lab can use to calculate how rapidly a person is aging. These tools could eventually help clinicians identify people in midlife who are aging faster than their peers, allowing earlier intervention to delay or prevent dementia and other age-related diseases. The findings will also be tested in Black, Hispanic, and Asian cohorts to check whether they hold across different ethnic groups. This is fundamentally a discovery-driven project. It aims to establish basic knowledge about how aging unfolds in midlife—a life stage that has been surprisingly neglected—rather than to deliver an immediate clinical tool or treatment.
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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.
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