Machine Learning based histology phenotyping to investigate the epidemiologic and genetic basis of adipocyte morphology and cardiometabolic traits.

doi:10.1371/journal.pcbi.1008044

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Article

Machine Learning based histology phenotyping to investigate the epidemiologic and genetic basis of adipocyte morphology and cardiometabolic traits.

PLoS computational biology - 1 Aug 2020

Glastonbury Craig A, Pulit Sara L, Honecker Julius, Censin Jenny C, Laber Samantha, Yaghootkar Hanieh, Rahmioglu Nilufer, Pastel Emilie, Kos Katerina, Pitt Andrew, Hudson Michelle, Nellåker Christoffer, Beer Nicola L, Hauner Hans, Becker Christian M, Zondervan Krina T, Frayling Timothy M, Claussnitzer Melina, Lindgren Cecilia M

Abstract excerpt

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...

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Identifiers

PMID: 32797044
DOI: 10.1371/journal.pcbi.1008044
PMCID: PMC7449405

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PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026. Manifest publication-graph-cohort-2026-09-07.1.

Source receipt: pubmed, retrieved 7 Sept 2026.

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