Understanding Frailty, Aging and Mortality Risk
Women are more frail – with attendant health problems – than men at every age but have lower risk of mortality. Why this is the case is not clear. To transform how we understand disease and health in aging for all older adults, Ling/Obrzut Assistant Professor Alice Kane’s research, supported by a prestigious new faculty NIH grant, aims to understand frailty and aging at the molecular level.
Alice Kane at the glass whiteboard with her lab at ISB. Photo credit: Trevor Dykstra.
A key area of aging research is developing estimates of life expectancy with algorithms that incorporate a range of cellular, molecular, and physiological measurements. Alice Kane, PhD, and her team at ISB are focused on generating such “aging clocks” in mice, a model of human aging. The researchers are using machine learning to integrate multiple measurements into the clocks, including physiological assessments of frailty and data on DNA-associated molecules called epigenetic marks, both of which show associations with life expectancy in humans. By providing estimates of remaining life expectancy, the new aging clocks will substantially reduce the time required for preclinical testing of potential life-extending interventions.
- Funded by Institutes of Health
- Led by Alice Kane, PhD
- Timeline: 2023 – 2026
bAFRAID (blood-based Analysis of Frailty in Death) Clocks for Measuring Lifespan and Testing Life-extending Interventions
Aging is a complex biological process that scientists are only beginning to understand. With age, people become increasingly frail, and the composition of cells and cellular molecules in the body shifts. For instance, cells accumulate changes in specific types of epigenetic marks, molecules associated with DNA that affect gene activity. Mice and humans undergo many of the same changes as they age, and the mouse is used as a model to test interventions designed to prolong life.
Aging clocks incorporate different types of data to assess aspects of aging, such as to estimate chronological age or remaining lifespan. Some aging clocks incorporate information on DNA CpG methylation, an epigenetic mark known to accumulate with age. Others incorporate information on measurements of frailty such as grip strength and gait speed, such as the commonly-used human frailty index.
ISB researcher Dr. Alice Kane and her colleagues previously generated clocks in mice based on a mouse frailty index. Thirty-three different frailty measurements were integrated using machine learning, which is adept at weighing how multiple factors contribute to a single outcome. The resulting AFRAID (Analysis of Frailty in Death) clock was able to predict the remaining lifespan in older male mice. The clock predicted time to death within 1.7 months for mice over 21 months of age, in a commonly-used laboratory strain that typically lives to about 30 months. The AFRAID clock outperformed other mouse aging clocks at predicting lifespan, consistent with similar findings on frailty-based clocks in humans.
To build yet more powerful clocks to predict lifespan in mice, Dr. Kane and her colleagues are now using machine learning to incorporate additional data streams into the AFRAID clock. The new bAFRAID (blood-based AFRAID) clocks are being developed based on the following additional types of information:
- Data on DNA CpG methylation. Preliminary experiments by Dr. Kane and her colleagues show that a clock based on DNA methylation predicts the remaining lifespan in aging mice. The experiments are facilitated by Tagmentation-based Indexing for MEthylation Sequencing (TIMEseq), a method developed by Dr. Kane that rapidly and cost-effectively assesses DNA methylation.
- Data on a panel of hundreds of serum metabolites. Preliminary findings from Dr. Kane and her colleagues show that an aging clock based on such data similarly predicts the remaining lifespan.
- Other types of data, including non-invasive physiological measurements, microbial diversity in the stool, and additional types of epigenetic marks.
In a key set of experiments, the researchers are collecting all these data longitudinally, at specific time points as mice age. They are testing both sexes in two different mouse strains, to show the broad applicability of their findings.
The resulting clocks will serve as effective tools for investigating the effect of drug and lifestyle interventions on aging. Such studies currently take years, as scientists generally wait for mice to die to measure the effects on mortality. The researchers estimate the new clocks will cut years off of such experiments: the bAFRAID clocks are anticipated to predict death within one month in mice 13 months and older and to predict whether interventions will increase lifespan by as little as 5 percent.
The research could lead to the identification of specific biological markers that show a high predictive value for lifespan. The work also dovetails with ongoing studies by Dr. Kane and others on the many scientific unknowns about aging, such as whether DNA methylation or other biological markers drive fragility and other physiological aspects of aging.
Citations
- Schultz, M.B., et al. Age and life expectancy clocks based on machine learning analysis of mouse frailty. Nat Commun. 2020. doi: 10.1038/s41467-020-18446-0.
- Griffin, P.T. et al., TIME-seq reduces time and cost of DNA methylation measurement for epigenetic clock construction. Nat. Aging. 2024. doi: 10.1038/s43587-023-00555-2.
Technologies Developed
bAFRAID (blood-based Analysis of Frailty in Death) clocks for measuring mouse lifespan
Contact Dr. Alice Kane
Ling/Obrzut Assistant Professor
ISB