Deep neural networks and genome-wide associations reveal the polygenic architecture of local brain aging.

Nicholas J Kim, Ayati Mishra, Nahian F Chowdhury, Samuel D Anderson, Owen M Vega, Nikhil N Chaudhari, Kenneth H Buetow, Paul M Thompson, Andrei Irimia

Alfred E. Mann Department of Biomedical Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, CA, USA. · pubmed

Paper

Abstract

Local brain age (LBA) is a regional metric of brain aging that offers a spatially resolved alternative to global brain age, but whose genetic basis is unexplored. This study reports the first genome-wide association study of cortical LBA, as estimated by a deep neural network from the T

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Research summary

This study identifies the genetic basis of local brain aging through genome-wide association studies. The research is relevant as it explores the polygenic architecture of brain aging, which could contribute to understanding the biological mechanisms underlying aging and potentially inform strategies for lifespan extension.

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