Biology subjects

Adcock, I. M.

Publications and source records attributed to Adcock, I. M..

5 recordsLinked to original sources

bioRxiv2026

Topology-Based Query Framework for Longitudinal Omics Trajectories

1 Abstract 1.1 Background Many longitudinal omics studies contain only a small number of repeated measurements collected before, during, or after an intervention. Existing approaches, including mixed-effects models and generalized additive models, estimate temporal effects but do not generally provide a discrete representation of trajectory topology that can be queried directly across experimental groups. 1.2 Methods We developed LongOmicsTraj, an open-source R package for topology-based representation and querying of short longitudinal omics trajectories. The framework encodes the direction of change between adjacent visits as up, down, or flat, with the ordered sequence defining an Ordinal Trajectory State (OTS). LongOmicsTraj operates downstream of trajectory estimation and can therefore be applied to empirical summaries or model-derived visit-level estimates, including those from linear mixed-effects models, generalized additive models, and polynomial regression, following a maSigPro-style time-course formulation [1]. OTS labels provide a common representation for topology-based querying, cross-group comparison, and evaluation of higherlevel representations such as trajectory clusters. We evaluated the framework using controlled simulations and bronchial biopsy transcriptomic data from the GLUCOLD corticosteroid intervention study (GEO accession GSE36221), measured at baseline, 6 months, and 30 months. The biological analysis compared continued inhaled corticosteroid (ICS) treatment, ICS withdrawal after 6 months, and placebo. 1.3 Results In simulations, LongOmicsTraj recovered predefined stable, monotonic, transient, rebound, and oscillatory trajectories with high accuracy when longitudinal signal was sufficiently clear, with performance declining under high-noise conditions and depending partly on the upstream estimator. In GLUCOLD, comparator-aware topology queries reduced 20,358 measured transcripts to 168 genes showing a corticosteroid response that was maintained during continued treatment, reversed following withdrawal, and was not reproduced under placebo. The selected genes included established corticosteroid-response genes and were enriched for immune-cell migration, chemotaxis, cell adhesion, and extracellular-matrix organisation. Topology-aware evaluation of FlexMix trajectory clusters additionally revealed substantial within-cluster temporal heterogeneity, with topology purities of approximately 46% to 60%. 1.4 Conclusions LongOmicsTraj provides a compact, directly queryable representation of temporal direction and order in short longitudinal omics studies. It complements existing longitudinal estimation and clustering methods by making trajectory structure explicit, enabling structured cross-group queries and quantification of temporal heterogeneity within trajectory clusters.

bioinformatics↗

bioRxiv2025

Does mechanobiology drive respiratory disease? Biomechanical induction of mucus hypersecretion in human bronchial organoids using a photocontrolled biomaterial gel

Respiratory diseases such as COPD, IPF and severe asthma are major causes of death globally, characterized by chronic inflammation and by fibrotic biomechanical remodelling of the lung ECM. However, present treatments focus on relieving inflammation and symptoms and do not address the mechanobiological aspect. This is in great part because the role of mechanobiology in disease progression and aetiology is not well-understood, indicating a need for new investigatory models. Here we introduce a combined biomaterial and 3D-organoid model, based on a hybrid biomaterial-matrix double-network gel, whose mechanical properties are dynamically photocontrolled by the application of light. This combines basement membrane extract (Matrigel) with biocompatible polymer (poly(ethylene glycol) diacrylate), and a low-toxicity photoinitation system. We achieve rapid (<5 mins) photoinduced stiffening over the range of remodelled lung tissue (up to [~]140 kPa). Bronchosphere organoids from primary human bronchial epithelial cells, embedded within the hybrid gel, replicate airway physiology and exhibit a dynamic biological response to matrix stiffening. We show that the expression of mucus proteins Muc5AC and Muc5B is biomechanically enhanced over a period of 24 - 72 h, with in particular Muc5B showing a substantial response at 48 h after matrix stiffening. Mucus hypersecretion is a symptom of respiratory disease, and these results support the hypothesis that biomechanics is a driver of disease aetiology. We combine the photostiffened hybrid matrix gel with organoids from COPD donors, generating an advanced disease model including both cellular and biomechanical aspects. We propose this technology platform for evaluating mechanomodulatory therapeutics in respiratory disease.

biophysics↗

bioRxiv2020

Epithelial-stromal cell interactions and ECM mechanics drive the formation of airway-mimetic tubular morphology in lung organoids

The complex cellular organisation of the human airway tract where interaction between epithelial and stromal lineages and the extracellular matrix (ECM) make it a difficult organ to study in vitro. Current in vitro lung models focus on modelling the lung epithelium such as air-liquid interface (ALI) cultures and bronchospheres, do not model the complex morphology and the cell-ECM interaction seen in vivo. Models that include stromal populations often separate them via a semipermeable barrier, which precludes the effect of cell-cell interaction or do not include the ECM or the effect of ECM mechanics such as viscoelasticity and stiffness. Here we investigated the effect of stromal cells on basal epithelial cell-derived bronchosphere structure and function through a triple culture of bronchial epithelial, lung fibroblast and airway smooth muscle cells. Epithelial-stromal cross talk enabled formation of epithelial cell-driven branching tubules consisting of luminal epithelial cells surrounded by stromal cells termed bronchotubules. Addition of agarose to the Matrigel scaffold (Agrigel) created a mechanically tunable ECM, where viscoelasticity and stiffness could be altered to enable long term tubule survival. Bronchotubule models enable the investigation of how epithelial-stromal cell and cell-ECM communication drive tissue patterning, repair and development of disease. Significance StatementCurrent models of airways diseases such as asthma and COPD do not reflect the physical characteristics of the diseased airway which may impact upon our understanding of disease pathophysiology. We have utilised the physical properties of agarose to modify the 3D stiffness of Matrigel to resemble the human airway. Using a primary airway epithelial cell-derived organoid model we demonstrate that a combined Matrigel/agrigel matrix allows sustained 3D organoid structure and the creation of tubules that can contract in response to a clinically relevant bronchoconstrictor. A complex 3D organoid composed of functioning epithelial cells, smooth muscle cells and fibroblasts may provide opportunities for refined drug discovery programmes. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=141 SRC="FIGDIR/small/408815v1_ufig1.gif" ALT="Figure 1"> View larger version (26K): org.highwire.dtl.DTLVardef@906212org.highwire.dtl.DTLVardef@1168e15org.highwire.dtl.DTLVardef@1ca16b2org.highwire.dtl.DTLVardef@980f65_HPS_FORMAT_FIGEXP M_FIG C_FIG O_LIMixture of healthy lung basal epithelial cells and healthy lung fibroblast cultured in matrigel result in tubules that fail in 4 days. C_LIO_LIAddition of healthy airway smooth muscle allows for a contractile phenotype. C_LIO_LITriple culture of cells in a stiffer scaffold agrigel allows maintenance of tubular organoids for a minimum of 20 days. C_LI

bioengineering↗

bioRxiv2020

Novel Type 2-high gene clusters associated with corticosteroid sensitivity in COPD

RationaleSevere asthma and COPD share common pathophysiologic traits such as relative corticosteroid insensitivity. We recently published three transcriptome-associated clusters (TACs) using hierarchical analysis of the sputum transcriptome in asthmatics from the U-BIOPRED cohort with one Type 2-high signature (TAC1) and 2 Type 2-low signatures. ObjectiveWe examined whether gene-expression signatures obtained in asthma can be used to identify the subgroup of COPD patients with steroid sensitivity. MethodsUsing gene set variation analysis (GSVA), we examined the distribution and enrichment scores (ES) of the 3 TACs in the transcriptome of bronchial biopsies from 46 patients who participated in the GLUCOLD COPD study that received 30 months of treatment with inhaled corticosteroids (ICS) with and without an added long-acting {beta}-agonist (LABA). The identified signatures were then associated with longitudinal clinical variables after treatment. Measurements and main resultsBronchial biopsies in COPD patients at baseline showed a wide range of expression of the 3 TACs. After ICS{+/-}LABA treatment, the ES of TAC1 was significantly reduced at 30 months, but those of TAC2 and TAC3 were unaffected. A corticosteroid-sensitive TAC1 (sub)signature was developed from the TAC1 ICS-responsive genes. This signature consisted of mast cell-specific genes identified by single-cell RNA-seq and positively correlated with bronchial biopsy mast cell numbers following ICS{+/-}LABA. Baseline levels of gene transcription predicted change in FEV1 %predicted following 30-month ICS{+/-}LABA. ConclusionsSputum-derived transcriptomic signatures from an asthma cohort can be recapitulated in bronchial biopsies of COPD patients and identified airway wall mast cells as a predictor of those COPD patients who will benefit from inhaled corticosteroids.

bioinformatics↗

bioRxiv2019

A Topological Data Analysis Network Model of Asthma Based on Blood Gene Expression Profiles

Stratified medicine requires discretisation of disease populations for targeted treatments. We have developed and applied a discrete Morse theory clustering algorithm to a Topological Data Analysis (TDA) network model of 498 gene expression profiles of peripheral blood from asthma and healthy participants. The Morse clustering algorithm defined nine clusters, BC1-9, representing molecular phenotypes with discrete phenotypes including Type-1, 2 & 17 cytokine inflammatory pathways. The TDA network model and clusters were also characterised by activity of glucocorticoid receptor signalling associated with different expression profiles of glucocorticoid receptor (GR), according to microarray probesets targeted to the start or end of the GR mRNAs 3 UTR; suggesting differential GR mRNA processing as a possible driver of asthma phenotypes including steroid insensitivity.

molecular biology↗