2023
DOI: 10.1101/2023.12.26.23300533
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Genome-wide analysis of brain age identifies 25 associated loci and unveils relationships with mental and physical health

Philippe Jawinski,
Helena Forstbach,
Holger Kirsten
et al.

Abstract: Neuroimaging and machine learning are opening up new opportunities in studying biological aging mechanisms. In this field, ‘brain age gap’ has emerged as promising MRI-based biomarker quantifying the deviation between an individual’s biological and chronological age of the brain – an indicator of accelerated/decelerated aging. Here, we investigated the genetic architecture of brain age gap and its relationships with over 1,000 health traits. Genome-wide analyses in 32,634 UK Biobank individuals unveiled a 30% … Show more

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