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Lookup NU author(s): Dr Conor Turner, Professor Jaume Bacardit
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0).
© 2024 The Author(s). Journal of the European Academy of Dermatology and Venereology published by John Wiley & Sons Ltd on behalf of European Academy of Dermatology and Venereology. Background: Perceived age (PA) has been associated with mortality, genetic variants linked to ageing and several age-related morbidities. However, estimating PA in large datasets is laborious and costly to generate, limiting its practical applicability. Objectives: To determine if estimating PA using deep learning-based algorithms results in the same associations with morbidities and genetic variants as human-estimated perceived age. Methods: Self-supervised learning (SSL) and deep feature transfer (DFT) deep learning (DL) approaches were trained and tested on human-estimated PAs and their corresponding frontal face images of middle-aged to elderly Dutch participants (n = 2679) from a population-based study in the Netherlands. We compared the DL-estimated PAs with morbidities previously associated with human-estimated PA as well as genetic variants in the gene MC1R; we additionally tested the PA associations with MC1R in a new validation cohort (n = 1158). Results: The DL approaches predicted PA in this population with a mean absolute error of 2.84 years (DFT) and 2.39 years (SSL). In the training–test dataset, we found the same significant (p < 0.05) associations for DL PA with osteoporosis, ARHL, cognition, COPD and cataracts and MC1R, as with human PA. We also found a similar but less significant association for SSL and DFT PAs (0.69 and 0.71 years per allele, p = 0.008 and 0.011, respectively) with MC1R variants in the validation dataset as that found with human, SSL and DFT PAs in the training–test dataset (0.79, 0.78 and 0.71 years per allele respectively; all p < 0.0001). Conclusions: Deep learning methods can automatically estimate PA from facial images with enough accuracy to replicate known links between human-estimated perceived age and several age-related morbidities. Furthermore, DL predicted perceived age associated with MC1R gene variants in a validation cohort. Hence, such DL PA techniques may be used instead of human estimations in perceived age studies thereby reducing time and costs.
Author(s): Turner C, Pardo LM, Gunn DA, Zillmer R, Mekic S, Liu F, Ikram MA, Klaver CCW, Croll PH, Goedegebure A, Trajanoska K, Rivadeneira F, Kavousi M, Brusselle GGO, Kayser M, Nijsten T, Bacardit J
Publication type: Article
Publication status: Published
Journal: Journal of the European Academy of Dermatology and Venereology
Year: 2024
Pages: ePub ahead of Print
Online publication date: 03/10/2024
Acceptance date: 04/09/2024
Date deposited: 15/10/2024
ISSN (print): 0926-9959
ISSN (electronic): 1468-3083
Publisher: John Wiley and Sons Inc.
URL: https://doi.org/10.1111/jdv.20365
DOI: 10.1111/jdv.20365
Data Access Statement: Data can be obtained upon request. Requests should be directed towards the management team of the Rotterdam Study (datamanagement.ergo@erasmusmc.nl), which has a protocol for approving data requests. Because of restrictions based on privacy regulations and informed consent of the participants, data cannot be made freely available in a public repository.
PubMed id: 39360788
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