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Brain age prediction using deep learning uncovers associated sequence variants

Brain age prediction using deep learning uncovers associated sequence variants

Title: Brain age prediction using deep learning uncovers associated sequence variants
Author: Jónsson, Benedikt Atli   orcid.org/0000-0002-5401-5940
Bjornsdottir, Gyda   orcid.org/0000-0002-8100-0306
Thorgeirsson, Thorgeir   orcid.org/0000-0002-5149-7040
Ellingsen, Lotta María   orcid.org/0000-0003-2139-0979
Walters, G. Bragi   orcid.org/0000-0002-5415-6487
Gudbjartsson, Daniel   orcid.org/0000-0002-5222-9857
Stefansson, Hreinn   orcid.org/0000-0002-9331-6666
Stefansson, Kari   orcid.org/0000-0003-1676-864X
Ulfarsson, Magnus   orcid.org/0000-0002-0461-040X
Date: 2019-11-27
Language: English
Scope: 5409
University/Institute: Háskóli Íslands
University of Iceland
Series: Nature Communications;10(1)
ISSN: 2041-1723
DOI: 10.1038/s41467-019-13163-9
Subject: Heilinn; Öldrun; Erfðarannsóknir
URI: https://hdl.handle.net/20.500.11815/1517

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Jonsson, B.A., Bjornsdottir, G., Thorgeirsson, T.E. et al. Brain age prediction using deep learning uncovers associated sequence variants. Nat Commun 10, 5409 (2019). https://doi.org/10.1038/s41467-019-13163-9


Machine learning algorithms can be trained to estimate age from brain structural MRI. The difference between an individual’s predicted and chronological age, predicted age difference (PAD), is a phenotype of relevance to aging and brain disease. Here, we present a new deep learning approach to predict brain age from a T1-weighted MRI. The method was trained on a dataset of healthy Icelanders and tested on two datasets, IXI and UK Biobank, utilizing transfer learning to improve accuracy on new sites. A genome-wide association study (GWAS) of PAD in the UK Biobank data (discovery set: N= 12378 , replication set: N= 4456) yielded two sequence variants, rs1452628-T (β= − 0.08 , P= 1.15 × 10 − 9) and rs2435204-G (β= 0.102 , P= 9.73 × 1 0 − 12). The former is near KCNK2 and correlates with reduced sulcal width, whereas the latter correlates with reduced white matter surface area and tags a well-known inversion at 17q21.31 (H2).


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