Self-supervised learning for characterising histomorphological diversity and spatial RNA expression prediction across 23 human tissue types.

As vast histological archives are digitised, there is a pressing need to be able to associate specific tissue substructures and incident pathology to disease outcomes without arduous annotation. Here, we learn self-supervised representations using a Vision Transformer, trained on 1.7 M histology images across 23 healthy tissues in 838 donors from the Genotype Tissue Expression consortium (GTEx).

An automatic entropy method to efficiently mask histology whole-slide images.

Tissue segmentation of histology whole-slide images (WSI) remains a critical task in automated digital pathology workflows for both accurate disease diagnosis and deep phenotyping for research purposes. This is especially challenging when the tissue structure of biospecimens is relatively porous and heterogeneous, such as for atherosclerotic plaques. In this study, we developed a unique approach called 'EntropyMasker' based on image entropy to tackle the fore- and background segmentation (masking) task in histology WSI.

Identification of Rare Loss-of-Function Genetic Variation Regulating Body Fat Distribution.

Context: Biological and translational insights from large-scale, array-based genetic studies of fat distribution, a key determinant of metabolic health, have been limited by the difficulty in linking predominantly noncoding variants to specific gene targets. Rare coding variant analyses provide greater confidence that a specific gene is involved, but do not necessarily indicate whether gain or loss of function (LoF) would be of most therapeutic benefit.

Objective: This work aimed to identify genes/proteins involved in determining fat distribution.

Response to comment on "Evaluating the cardiovascular safety of sclerostin inhibition using evidence from meta-analysis of clinical trials and human genetics".

Triangulation of evidence from clinical trials and human genetics suggests a potential excess risk of cardiovascular disease events arising from therapeutic inhibition of sclerostin.

Further evidence supporting a potential role for ADH1B in obesity.

Insulin is an essential hormone that regulates glucose homeostasis and metabolism. Insulin resistance (IR) arises when tissues fail to respond to insulin, and it leads to serious health problems including Type 2 Diabetes (T2D). Obesity is a major contributor to the development of IR and T2D.

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.

Evaluating the cardiovascular safety of sclerostin inhibition using evidence from meta-analysis of clinical trials and human genetics.

Inhibition of sclerostin is a therapeutic approach to lowering fracture risk in patients with osteoporosis. However, data from phase 3 randomized controlled trials (RCTs) of romosozumab, a first-in-class monoclonal antibody that inhibits sclerostin, suggest an imbalance of serious cardiovascular events, and regulatory agencies have issued marketing authorizations with warnings of cardiovascular disease. Here, we meta-analyze published and unpublished cardiovascular outcome trial data of romosozumab and investigate whether genetic variants that mimic therapeutic inhibition of sclerostin are associated with higher risk of cardiovascular disease.

Cell-Type Heterogeneity in Adipose Tissue Is Associated with Complex Traits and Reveals Disease-Relevant Cell-Specific eQTLs.

Adipose tissue is an important endocrine organ with a role in many cardiometabolic diseases. It is comprised of a heterogeneous collection of cell types that can differentially impact disease phenotypes. Cellular heterogeneity can also confound -omic analyses but is rarely taken into account in analysis of solid-tissue transcriptomes.

GWAS Identifies Risk Locus for Erectile Dysfunction and Implicates Hypothalamic Neurobiology and Diabetes in Etiology.

Erectile dysfunction (ED) is a common condition affecting more than 20% of men over 60 years, yet little is known about its genetic architecture. We performed a genome-wide association study of ED in 6,175 case subjects among 223,805 European men and identified one locus at 6q16.3 (lead variant rs57989773, OR 1.

Smoking induces coordinated DNA methylation and gene expression changes in adipose tissue with consequences for metabolic health.

Background: Tobacco smoking is a risk factor for multiple diseases, including cardiovascular disease and diabetes. Many smoking-associated signals have been detected in the blood methylome, but the extent to which these changes are widespread to metabolically relevant tissues, and impact gene expression or metabolic health, remains unclear.

Methods: We investigated smoking-associated DNA methylation and gene expression variation in adipose tissue biopsies from 542 healthy female twins.

Meta-analysis of genome-wide association studies for body fat distribution in 694 649 individuals of European ancestry.

More than one in three adults worldwide is either overweight or obese. Epidemiological studies indicate that the location and distribution of excess fat, rather than general adiposity, are more informative for predicting risk of obesity sequelae, including cardiometabolic disease and cancer. We performed a genome-wide association study meta-analysis of body fat distribution, measured by waist-to-hip ratio (WHR) adjusted for body mass index (WHRadjBMI), and identified 463 signals in 346 loci.

Fasting and time of day independently modulate circadian rhythm relevant gene expression in adipose and skin tissue.

Background: Intermittent fasting and time-restricted diets are associated with lower risk biomarkers for cardio-metabolic disease. The shared mechanisms underpinning the similar physiological response to these events is not established, but circadian rhythm could be involved. Here we investigated the transcriptional response to fasting in a large cross-sectional study of adipose and skin tissue from healthy volunteers (N = 625) controlling for confounders of circadian rhythm: time of day and season.

Author Correction: Integration of human adipocyte chromosomal interactions with adipose gene expression prioritizes obesity-related genes from GWAS.

In the original version of this Article, Supplementary Table 10 contained incorrect primer sequences for the mobility shift assay for SNP rs4776984. These errors have now been fixed and the corrected version of the Supplementary Information PDF is available to download from the HTML version of the Article.

Author Correction: Regulatory variants at KLF14 influence type 2 diabetes risk via a female-specific effect on adipocyte size and body composition.

In the version of this article originally published, minus signs were missing from the three β-values for BMI given in Table 1. The errors have been corrected in the HTML and PDF versions of the article.

The genetic underpinnings of body fat distribution.

Obesity, defined as a body mass index (BMI) ≥ 30 kg/m, has reached epidemic proportions; people who are overweight (BMI > 25 kg/m) or obese now comprise more than 25% of the world's population. Obese individuals have a higher risk of comorbidity development including type 2 diabetes, cardiovascular disease, cancer, and fertility complications. Areas covered: The study of monogenic and syndromic forms of obesity have revealed a small number of genes key to metabolic perturbations.

Integration of human adipocyte chromosomal interactions with adipose gene expression prioritizes obesity-related genes from GWAS.

Increased adiposity is a hallmark of obesity and overweight, which affect 2.2 billion people world-wide. Understanding the genetic and molecular mechanisms that underlie obesity-related phenotypes can help to improve treatment options and drug development.

Regulatory variants at KLF14 influence type 2 diabetes risk via a female-specific effect on adipocyte size and body composition.

Individual risk of type 2 diabetes (T2D) is modified by perturbations to the mass, distribution and function of adipose tissue. To investigate the mechanisms underlying these associations, we explored the molecular, cellular and whole-body effects of T2D-associated alleles near KLF14. We show that KLF14 diabetes-risk alleles act in adipose tissue to reduce KLF14 expression and modulate, in trans, the expression of 385 genes.

Adiposity-Dependent Regulatory Effects on Multi-tissue Transcriptomes.

Obesity is a global epidemic that is causally associated with a range of diseases, including type 2 diabetes and cardiovascular disease, at the population-level. However, there is marked heterogeneity in obesity-related outcomes among individuals. This might reflect genotype-dependent responses to adiposity.

Metabolomic profiling to dissect the role of visceral fat in cardiometabolic health.

Objective: Abdominal obesity is associated with increased risk of type 2 diabetes (T2D) and cardiovascular disease. The aim of this study was to assess whether metabolomic markers of T2D and blood pressure (BP) act on these traits via visceral fat (VF) mass.

Methods: Metabolomic profiling of 280 fasting plasma metabolites was conducted on 2,401 women from TwinsUK.

Genome-wide association analysis identifies TXNRD2, ATXN2 and FOXC1 as susceptibility loci for primary open-angle glaucoma.

Primary open-angle glaucoma (POAG) is a leading cause of blindness worldwide. To identify new susceptibility loci, we performed meta-analysis on genome-wide association study (GWAS) results from eight independent studies from the United States (3,853 cases and 33,480 controls) and investigated the most significantly associated SNPs in two Australian studies (1,252 cases and 2,592 controls), three European studies (875 cases and 4,107 controls) and a Singaporean Chinese study (1,037 cases and 2,543 controls). A meta-analysis of the top SNPs identified three new associated loci: rs35934224[T] in TXNRD2 (odds ratio (OR) = 0.