Proteomics-Based Measure of Accelerating Aging and Brain Age Gap
Author Information
Author(s): Casanova Ramon, Walker Keenan, Lu Lingyi, Kritchevsky Stephen, Hughes Timothy, Wagenknecht Lynne
Primary Institution: Wake Forest University School of Medicine
Hypothesis
The study investigates the correlation between a proteomic predictor of aging and MRI-derived brain age.
Conclusion
The proteomic age measure is correlated with various health indicators and the brain age gap, suggesting a link between brain and body aging.
Supporting Evidence
- The proteomic age measure was correlated with the brain age gap (0.26 p< 0.001).
- It was also correlated with hypertension (0.25 p< 0.001) and diabetes (0.18 p< 0.001).
- Gait speed showed a correlation of 0.24 p< 0.001 with the proteomic age measure.
- Total cholesterol was correlated at 0.25 p< 0.001.
Takeaway
Scientists found that certain proteins in the body can help predict how old your brain is, showing that brain and body aging are connected.
Methodology
The study used a Cox regression elastic net model on data from ARIC participants to predict all-cause mortality based on protein levels, age, and sex.
Participant Demographics
Participants were from the Atherosclerosis Risk in Communities (ARIC) Study.
Statistical Information
P-Value
p<0.001
Statistical Significance
p<0.001
Digital Object Identifier (DOI)
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