Biology subjects

Barnes, M. R.

Publications and source records attributed to Barnes, M. R..

5 recordsLinked to original sources

bioRxiv2026

Population-scale drug target and variant prioritization with Varformer

Human genetic variation is a powerful driver of therapeutic target prioritization, yet current models struggle to aggregate variable numbers of variants per gene and are bottlenecked by the scarcity of validated targets. We present Varformer, a multimodal transformer that uses cross-modal attention to integrate contextual representations of missense variants with gene-level features. Trained via positive-unlabeled learning on clinically validated targets across four genetic ancestry groups, Varformer achieves a precision@20 of 0.95, 0.86, and 0.48 across three benchmarks of increasing difficulty. It surpasses a logistic regression ablation by 20% and DrugnomeAI by 23% on the hardest benchmark. Cross-population rank normalization isolates targets with consistent genetic support across ancestry groups. The variant encoder also scores individual variants. Across 1,164 carrier-variant pairs in Genes & Health, Varformer ranked the known pathogenic variant in the carrier's top 20 in 57% of pairs. Varformer is available as an open-source framework for unified target and variant prioritization.

bioinformatics↗

bioRxiv2025

Transcriptomic profiling and machine learning uncover gene signatures of psoriasis endotypes and disease severity

BackgroundDespite increased understanding of psoriasis pathogenesis, molecular classification of clinical phenotypes and disease severity is poorly defined. Knowledge gaps include whether molecular endotypes of psoriasis underlie distinct clinical phenotypes and the positive and negative molecular regulators of disease severity across tissue compartments. MethodsWe performed comprehensive RNA-sequencing of skin and blood (n=718) from prospectively-recruited, deeply-phenotyped discovery and replication cohorts of 146 subjects with moderate-to-severe psoriasis initiating TNF-inhibitor (adalimumab) or IL-12/23-inhibitor (ustekinumab) therapy. ResultsUsing two complementary methods for dimensionality reduction, we defined distinct but interconnected co-expression modules and factors within skin and blood that were significantly associated with disease phenotypes and disease severity, as measured by Psoriasis Area Severity Index (PASI). We identified a 14-gene signature negatively associated with BMI in nonlesional skin and disease severity in lesional skin, respectively. Genotype integration revealed that HLA-DQA1*01 and HLA-DRB1*15 genotypes were positively associated with baseline disease severity. Using Gaussian process regression followed by SHAP (SHapley Additive exPlanations), we defined two core drug independent and disease severity-associated gene modules in lesional skin - one positive, one negative - and a lesional 9-gene signature predictive of disease severity. Disease severity signatures in blood were only seen following adalimumab exposure, suggesting greater systemic impact of adalimumab compared to ustekinumab, in line with its side effect profile. In contrast, a gene signature in blood linked to HLA-C*06:02 status was independent of disease severity or drug. ConclusionsThese findings delineate gene-environmental and genetic effects on the psoriasis transcriptome linked to disease severity. Plain Language SummaryPsoriasis is a common and debilitating skin disease, linked to multiple other inflammatory conditions. A lot is known about the mechanism of psoriasis and its inherited and external influences. Despite this, doctors cannot yet offer personalised treatments as it has been difficult to discover whether biological pathways are associated with disease severity, response to treatment or a persons likelihood of having other linked diseases. To help address this, we collected skin and blood samples and the personal characteristics of a group of people with severe psoriasis across the United Kingdom. Using computer-based methods, we discovered common biological processes underlying different psoriasis types, including genes that connect psoriasis severity with obesity, and another set of genes that help predict disease severity.

systems biology↗

bioRxiv2024

The nitrite reductase activity of xanthine oxidoreductase sustains cardiovascular health

BackgroundXanthine oxidoreductase (XOR) is a multi-functional enzyme that metabolises purines generating uric acid and is a generator of reactive oxygen species. Both functions have been implicated in the pathogenesis of cardiovascular disease. More recently, a third function of XOR as a nitrite reductase has been identified and been shown to play a key role in the benefits of targeting the non-canonical pathway for nitric oxide (NO) generation in the cardiovascular disease setting. This effect has been specifically attributed to XOR dependent recovery of NO levels. However, whether XOR derived NO plays any role in maintaining cardiovascular homeostasis in health is unknown. To explore this, we used global and hepatocyte-specific Xdh-deleted mice to assess cardiovascular homeostasis. MethodsXdh+/+ and Xdh+/-, Xdhfl/fl and Xdhfl/flAlbCre+/-(HXOR KO) mice littermates, matched for sex and age, were used for in vivo cardiovascular phenotyping; blood pressure, cardiac function, endothelial reactivity, and leukocyte trafficking. Tissues from these mice were used for biochemical measurements of nitrate, nitrite, and markers of NO downstream signalling. ResultsXdh+/- and HXOR KO mice expressed significantly attenuated liver and plasma nitrite reductase activity and platelet cGMP levels versus littermate controls. These effects were associated with increased systolic blood pressure, left ventricular remodelling, and increased leukocyte activation. These effects were associated with and likely driven by endothelial dysfunction evident in both mouse models. This dysfunction was reflected by increased endothelial adhesion molecule expression (P-selectin), increased ischaemia-induced vasoconstriction, during vessel occlusion, and an impaired flow-mediated dilation response of the iliac artery in vivo. ConclusionsIn summary, XOR derived NO is critical for maintaining vascular homeostasis under physiological conditions and is key in mediating the benefits of dietary nitrate regimes in cardiovascular pathology

pharmacology and toxicology↗

bioRxiv2021

GEOexplorer: an R/Bioconductor package for gene expression analysis and visualisation

BackgroundOver the past three decades there have been numerous molecular biology developments that have led to an explosion in the number of gene expression studies being performed. Many of these gene expression studies publish their data to the public database GEO, making them freely available. By analysing gene expression datasets, researchers can identify genes that are differentially expressed between two groups. This can provide insights that lead to the development of new tests and treatments for diseases. Despite the wide availability of gene expression datasets, analysing them is difficult for several reasons. These reasons include the fact that most methods for performing gene expression analysis require programming proficiency. ResultsWe developed the GEOexplorer software package to overcome several of the difficulties in performing gene expression analysis. GEOexplorer was therefore developed as a web application, that can perform interactive and reproducible microarray gene expression analysis, while producing a wealth of interactive visualisations to facilitate result exploration. GEOexplorer is implemented in R using the Shiny framework and is fully integrated with the existing core structures of the Bioconductor project. Users can perform the essential steps of exploratory data analysis and differential gene expression analysis intuitively and generate a broad spectrum of publication ready outputs. ConclusionGEOexplorer is distributed as an R package in the Bioconductor project (http://bioconductor.org/packages/GEOexplorer/). GEOexplorer provides a solution for performing interactive and reproducible analyses of microarray gene expression data, empowering life scientists to perform exploratory data analysis and differential gene expression analysis on GEO microarray datasets.

bioinformatics↗

bioRxiv2019

Multi-ancestry GWAS of the electrocardiographic PR interval identifies 210 loci underlying cardiac conduction

The electrocardiographic PR interval reflects atrioventricular conduction, and is associated with conduction abnormalities, pacemaker implantation, atrial fibrillation (AF), and cardiovascular mortality1,2. We performed multi-ancestry (N=293,051) and European only (N=271,570) genome-wide association (GWAS) meta-analyses for the PR interval, discovering 210 loci of which 149 are novel. Variants at all loci nearly doubled the percentage of heritability explained, from 33.5% to 62.6%. We observed enrichment for genes involved in cardiac muscle development/contraction and the cytoskeleton highlighting key regulation processes for atrioventricular conduction. Additionally, 19 novel loci harbour genes underlying inherited monogenic heart diseases suggesting the role of these genes in cardiovascular pathology in the general population. We showed that polygenic predisposition to PR interval duration is an endophenotype for cardiovascular disease risk, including distal conduction disease, AF, atrioventricular pre-excitation, non-ischemic cardiomyopathy, and coronary heart disease. These findings advance our understanding of the polygenic basis of cardiac conduction, and the genetic relationship between PR interval duration and cardiovascular disease.

genetics↗