Details

Autor(en) / Beteiligte

• Parvin, Mohammadiarvejeh
• Klinedinst, Brandon S
• Wang, Qian
• Pollpeter, Amy
• Larsen, Brittany A
• Moody, Shannin
• Li, Tianqi
• Barnett, Neil
• Pappas, Colleen
• Willette, Sara A
• Jonathan, Mochel
• Allenspach‐Jorn, Karin
• Willette, Auriel A

Titel

Bioenergetic and vascular predictors of potential super‐ager and cognitive decline trajectories – A UK Biobank random forest classification study

Ist Teil von

• Alzheimer's & dementia, 2023-06, Vol.19 (S2), p.n/a

Erscheinungsjahr

2023

Link zum Volltext

Quelle

Wiley Online Library Journals Frontfile Complete

Beschreibungen/Notizen

• Background Aging is often characterized by progressive cognitive decline in memory and executive function. Yet, some adults aged 80 years or older, are “Super‐Agers” that exhibit cognitive performance akin to younger adults. It is unknown if there are adults in mid‐life with similar superior cognitive performance (“positive‐aging”) versus cognitive decline over time, and if there are blood biomarkers that can distinguish between these groups. Method Among 1303 participants in UK Biobank, latent growth curve models classified participants into different cognitive groups based on longitudinal Fluid Intelligence (FI) scores over 7‐9 years. Random Forest (RF) classification was then used to predict cognitive trajectory types using longitudinal predictors including demographic, vascular, bioenergetic, and immune factors. Feature ranking importance and performance metrics of the model were reported. Result Despite model complexity, we achieved a precision of 77% when determining who would be in the “positive‐aging” group. Among the top fifteen features, an equal number were related to either vascular health or cellular bioenergetics but not demographics like age, sex, or socioeconomic status (see figure). Conclusion Our results suggest that optimal cognitive aging may not be driven by age per se, but biological factors that may be amenable to lifestyle or pharmacological changes.