Observable traits predict changes in cognitive and physical health

A new measurement system based on phenotypic (observed) data can identify individuals at risk of adverse health outcomes based on their estimated ‘aging score’. After collecting this data from nearly 1,000 people ages 24 to 93, NIA-funded researchers found that people with higher biological aging scores showed faster physical and cognitive decline, developed multiple health problems, and had shorter life. The approach may be a better predictor of health outcomes over time than the traditional focus on a person’s chronological age, which is based on date of birth. The results of the study were published in Aging of nature.

The NIA’s Baltimore Longitudinal Study of Aging (BLSA), the longest-running scientific study of human aging in the United States, has shown that the manifestations of aging are highly variable among individuals. Because people age differently, chronological age alone does not provide a complete picture of the impact and effects of aging. Phenotypes, which are observed traits based on genes and the effects of the environment on those genes, can provide insight into biological aging. Phenotypes can reveal biological aging at the cellular and molecular level and indicate how quickly health changes will occur, such as chronic disease progression and decline in physical and cognitive function.

For this phenotypic study, researchers from the NIA, Johns Hopkins Bloomberg School of Public Health, Yale School of Medicine, and the University of Maryland School of Medicine used data from 968 BLSA participants. The researchers organized the phenotypic data into four groups: body composition such as waist size, energetics such as oxygen consumption, homeostatic mechanisms such as blood pressure, and neuroplasticity/neurodegeneration such as brain volume and neural firing.

For each phenotype, the researchers measured the difference between the individual’s changes over time and the sex- and age-specific mean changes over time in the study population. It should be noted that by using these changes over time as a reference, the resulting phenotypic scores account for non-linear rates of change. These nonlinear rates are important because certain measures of aging, such as fitness, do not change linearly over time. The study also included changes in mobility and cognitive tests, the number of medical conditions reported by participants, and participants’ life expectancy.

The researchers averaged the individual phenotypic scores in each phenotypic group, then averaged the results of the four groups to find the participant’s longitudinal (over time) phenotypic score for aging. Those with higher scores, representing a faster rate of phenotypic aging than the general population, had a faster decline in functional aging, a faster increase in the number of their medical conditions, and a shorter lifespan. This longitudinal approach showed stronger associations with changes in physical and cognitive function than measures of aging that use data from a single point in time. Next research steps could include linking the phenotypic aging result to cellular and molecular measurements to improve understanding of the biology of aging.

This research was supported by NIA grants R01AG061786, U01AG057545, U01AG032947, R01AG048069, R56AG068673, R03AG070178, P30AG028747-15S1, R01AG069915, 1R01AG068285-01, 1R01AG065403-01A1, and 1R01AG057912-01.

Reference: Kuo PL, et al. Longitudinal phenotypic indicators of aging in the Baltimore Longitudinal Study of Aging. Aging of nature. 2022; 2: 635-643. two: 10.1038/s43587-022-00243-7.

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