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

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.This article is freely available via Open Access. Click on the Publisher URL to access it via the publisher's site.C.A.G received a pump priming grant from Novo Nordisk to carry out this work. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.published version, accepted versio

Specific miRNAs are associated with human cancer cachexia in an organ‐specific manner

Abstract Background Cancer cachexia (CCx) is a complex and multi‐organ wasting syndrome characterized by substantial weight loss and poor prognosis. An improved understanding of the mechanisms involved in the onset and progression of cancer cachexia is essential. How microRNAs contribute to the clinical manifestation and progression of CCx remains elusive. The aim of this study was to identify specific miRNAs related to organ‐specific CCx and explore their functional role in humans. Methods miRNA patterns in serum and in cachexia target organs (liver, muscle and adipose tissue) from weight stable (N ≤ 12) and cachectic patients (N ≤ 23) with gastrointestinal cancer were analysed. As a first step, a miRNA array (158 miRNAs) was performed in pooled serum samples. Identified miRNAs were validated in serum and corresponding tissue samples. Using in silico prediction, related genes were identified and evaluated. The findings were confirmed in vitro by siRNA knock‐down experiments in human visceral preadipocytes and C2C12 myoblast cells and consecutive gene expression analyses. Results Validating the results of the array, a 2‐fold down‐regulation of miR‐122‐5p (P = 0.0396) and a 4.5‐fold down‐regulation of miR‐194‐5p (P < 0.0001) in serum of CCx patients in comparison with healthy controls were detected. Only miR‐122‐5p correlated with weight loss and CCx status (P = 0.0367). Analysing corresponding tissues six muscle and eight visceral adipose tissue (VAT) cachexia‐associated miRNAs were identified. miR‐27b‐3p, miR‐375 and miR‐424‐5p were the most consistently affected miRNAs in tissues of CCx patients correlating negatively with the severity of body weight loss (P = 0.0386, P = 0.0112 and P = 0.0075, respectively). We identified numerous putative target genes of the miRNAs in association with muscle atrophy and lipolysis pathways. Knock‐down experiments in C2C12 myoblast cells revealed an association of miR‐27b‐3p and the in silico predicted atrophy‐related target genes IL‐15 and TRIM63. Both were up‐regulated in miR‐27b‐3p knock‐down cells (P < 0.05). Concordantly, in muscle tissue of CCx individuals, significant higher expression levels of IL‐15 (P = 0.0237) and TRIM63 (P = 0.0442) were detected. miR‐424‐5p was identified to regulate the expression of lipase genes. Knock‐down experiments in human visceral preadipocytes revealed an inverse association of miR‐424‐5p with its predicted target genes LIPE, PNPLA2, MGLL and LPL (P < 0.01). Conclusions The identified miRNAs, in particular miR‐122‐5p, miR‐27b‐3p, miR‐375 and miR‐424‐5p, represent features of human CCx and may contribute to tissue wasting and skeletal muscle atrophy through the regulation of catabolic signals. Further studies are needed to explore the potential of the identified miRNAs as a screening tool for early detection of cancer cachexia