| Title: |
Machine learning based histology phenotyping to investigate the epidemiologic and genetic basis of adipocyte morphology and cardiometabolic traits. |
| Authors: |
Glastonbury, CA; Pulit, SL; Honecker, J; Censin, JC; Laber, S; Yaghootkar, H; Rahmioglu, N; Pastel, E; Kos, K; Pitt, A; Hudson, M; Nellåker, C; Beer, NL; Hauner, H; Becker, CM; Zondervan, KT; Frayling, TM; Claussnitzer, M; Lindgren, CM |
| Publisher Information: |
Public Library of Science |
| Publication Year: |
2020 |
| Collection: |
Oxford University Research Archive (ORA) |
| Description: |
Genetic studies have recently highlighted the importance of fat distribution, as well as overall adiposity, in the pathogenesis of obesity-associated diseases. Using a large study (n = 1,288) from 4 independent cohorts, we aimed to investigate the relationship between mean adipocyte area and obesity-related traits, and identify genetic factors associated with adipocyte cell size. To perform the first large-scale study of automatic adipocyte phenotyping using both histological and genetic data, we developed a deep learning-based method, the Adipocyte U-Net, to rapidly derive mean adipocyte area estimates from histology images. We validate our method using three state-of-the-art approaches; CellProfiler, Adiposoft and floating adipocytes fractions, all run blindly on two external cohorts. We observe high concordance between our method and the state-of-the-art approaches (Adipocyte U-net vs. CellProfiler: R2visceral = 0.94, P < 2.2 × 10−16, R2subcutaneous=0.91, P < 2.2 × 10−16), and faster run times (10,000 images: 6mins vs 3.5hrs). We applied the Adipocyte U-Net to 4 cohorts with histology, genetic, and phenotypic data (total N = 820). After meta-analysis, we found that mean adipocyte area positively correlated with body mass index (BMI) (Psubq = 8.13 × 10−69, βsubq = 0.45; Pvisc = 2.5 × 10−55, βvisc = 0.49; average R2 across cohorts = 0.49) and that adipocytes in subcutaneous depots are larger than their visceral counterparts (Pmeta = 9.8 × 10−7). Lastly, we performed the largest GWAS and subsequent meta-analysis of mean adipocyte area and intra-individual adipocyte variation (N = 820). Despite having twice the number of samples than any similar study, we found no genome-wide significant associations, suggesting that larger sample sizes and a homogenous collection of adipose tissue are likely needed to identify robust genetic associations. |
| Document Type: |
article in journal/newspaper |
| Language: |
English |
| Relation: |
https://doi.org/10.1371/journal.pcbi.1008044 |
| DOI: |
10.1371/journal.pcbi.1008044 |
| Availability: |
https://doi.org/10.1371/journal.pcbi.1008044; https://ora.ox.ac.uk/objects/uuid:d0aa2673-b221-41f8-b7bf-b5309ede572e |
| Rights: |
info:eu-repo/semantics/openAccess ; CC Attribution (CC BY) |
| Accession Number: |
edsbas.31978AF3 |
| Database: |
BASE |