Biology subjects

Grieve, S.

Publications and source records attributed to Grieve, S..

4 recordsLinked to original sources

bioRxiv2025

Endothelial Colony-Forming Cell Transcriptomic Profiling in CT-defined Coronary Artery Disease from the BioHEART-CT Study Implicate CCBE1 in Mitochondrial Dysfunction-associated Atherosclerosis

BackgroundEndothelial dysfunction is an early contributor to atherosclerosis. This study combined CT imaging of coronary artery disease (CAD) and patient-dervied endothelial colony-forming cells (ECFCs) transcriptional profiling to investigate potential mechanisms underlying endothelial dysfunction in atherosclerosis. MethodsTwenty-six individuals with CT-defined CAD and eighteen non-CAD controls were included in the Discovery Cohort for bulk RNA sequencing and transcriptomic analysis of ECFCs. Differential gene expression analysis was performed, and candidate genes were selected based on logFC and p-value. Candidate genes were carried forward for gene expression validation using quantitative real-time PCR (qRT-PCR) in a Validation Cohort. Mitochondrial reactive oxygen species (mROS) production and mitochondrial mass were assessed using multi-colour flow cytometry. Functional validation of the top candidate was conducted in using human umbilical vein endothelial cells (HUVECs) using loss-of-function genetic approach. Expression Quantitative Trait Loci (eQTL)-association analysis was conducted using genotype data from the BioHEART-CT cohort. ResultsPairwise analysis identified six differentially expressed protein-coding genes in CAD ECFCs: CCBE1 (Collagen and Calcium Binding EGF Domain-Containing 1), SPINT2, CRISPLD1, PIEZO2, EPB41L3, and AC005943.1. qRT-PCR in the Validation Cohort confirmed significantly higher CCBE1 expression in CAD patients. Individuals with relative CCBE1 fold change expression>10 had a 2.8-fold increase in the log-odds ratio of CT-defined CAD. CAD ECFCs displayed elevated mROS and mitochondrial mass. CCBE1 knockdown in HUVECs reduced mROS and mitochondrial mass without affecting proliferation or permeability, but shifted cells into a metabolically elevated state, marked by increased ATP production, respiration and glycolysis. CCBE1 cis-eQTLs were associated with increased odds of CAD in the BioHEART-CT cohort. ConclusionsCCBE1 expression in ECFCs was higher in patients with CT-defined CAD versus non-CAD. Quantitative assessment of transcript levels supported a causal relationship between greater CCBE1 expression and CAD burden and risk, and functional experiments on CCBE1 knockdown demonstrated improved mitochondrial function in human endothelial cells. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=138 SRC="FIGDIR/small/670989v1_ufig1.gif" ALT="Figure 1"> View larger version (43K): org.highwire.dtl.DTLVardef@4e609aorg.highwire.dtl.DTLVardef@1a85810org.highwire.dtl.DTLVardef@12d97cdorg.highwire.dtl.DTLVardef@494ab3_HPS_FORMAT_FIGEXP M_FIG C_FIG Novelty and SignificanceO_ST_ABSWhat is Known?C_ST_ABSO_LIThe endothelium plays a critical role in vascular health and susceptibility to atherosclerosis. C_LIO_LIMitochondrial dysfunction has been implicated in atherosclerosis, but its role and mechanism in individual susceptibility to CAD in humans is not known. C_LI What New Information Does This Article Contribute?O_LINovel approach integrating CT imaging with ECFC functional data to link vascular structure with endothelial biology ex vivo. C_LIO_LIPatients with CT-defined CAD had 3.6-fold higher CCBE1 expression compared to non-CAD within the Validation Cohort. C_LIO_LICis-eQTL-association analysis revealed increased odds of CAD. C_LIO_LICCBE1 knockdown improved mitochondrial function in human endothelial cells. C_LIO_LITogether, these 4 lines of evidence point to a novel and causal role for CCBE1 in human CAD. C_LI

cell biology↗

bioRxiv2024

Polymorphic tandem repeats shape single-cell gene expression across the immune landscape

Tandem repeats (TRs) - highly polymorphic, repetitive sequences across the human genome - are important regulators of gene expression but remain underexplored due to challenges in accurate genotyping and analysis1. Here, we generate new whole genome and single-cell RNA sequencing from >5.4 million blood-derived cells across 1,925 individuals in two cohorts [Cuomo et al., accompanying manuscript], and perform meta-analysis to characterize the impact of variation in >1.7 million TR loci on immune cell type-specific gene expression. We identify >69,000 single-cell expression TR loci (sc-eTRs), 30.7% of which are specific to one of 28 immune cell types, and reveal dynamic regulatory effects using cell-state inference. Matched single-cell ATAC sequencing profiles from >3.4 million nuclei in 922 individuals [Xue et al., accompanying manuscript]. uncover chromatin accessibility QTLs for nearly one-third of expression-associated TRs, supporting coordinated effects on cis-regulatory architecture. Fine-mapping implicates 1,490 TRs as candidate causal drivers of gene expression in 6.1% of tested genes, and colocalization analyses highlight >200 genes in which TRs likely mediate genetic associations with immune and hematological traits. Together, these results provide a genome-wide, multiomic view of TR-mediated regulation in the human immune system, establishing TRs as key contributors to cell type-specific regulatory variation and complex trait architecture.

genomics↗

bioRxiv2024

deadtrees.earth - An Open-Access and Interactive Database for Centimeter-Scale Aerial Imagery to Uncover Global Tree Mortality Dynamics

Excessive tree mortality is a global concern and remains poorly understood as it is a complex phenomenon. We lack global and temporally continuous coverage on tree mortality data. Ground-based observations on tree mortality, e.g., derived from national inventories, are very sparse, not standardized and not spatially explicit. Earth observation data, combined with supervised machine learning, offer a promising approach to map tree mortality over time. However, global-scale machine learning requires broad training data covering a wide range of environmental settings and forest types. Drones provide a cost-effective source of training data by capturing high-resolution orthophotos of tree mortality events at sub-centimeter resolution. Here, we introduce deadtrees.earth, an open-access platform hosting more than a thousand centimeter-resolution orthophotos, covering already more than 300,000 ha, of which more than 58,000 ha are fully annotated. This community-sourced and rigorously curated dataset shall serve as a foundation for a global initiative to gather comprehensive reference data. In concert with Earth observation data and machine learning it will serve to uncover tree mortality patterns from local to global scales. This will provide the foundation to attribute tree mortality patterns to environmental changes or project tree mortality dynamics to the future. Thus, the open and interactive nature of deadtrees.earth together with the collective effort of the community is meant to continuously increase our capacity to uncover and understand tree mortality patterns.

ecology↗

bioRxiv2023

Construction and optimization of multi-platform precision pathways for precision medicine

In the enduring challenge against disease, advancements in medical technology have empowered clinicians with novel diagnostic platforms. Whilst in some cases, a single test may provide a confident diagnosis, often additional tests are required. However, to strike a balance between diagnostic accuracy and cost-effectiveness, one must rigorously construct the clinical pathways. Here, we developed a framework to build multi-platform precision pathways in an automated, unbiased way, recommending the key steps a clinician would take to reach a diagnosis. We achieve this by developing a confidence score, used to simulate a clinical scenario, where at each stage, either a confident diagnosis is made, or another test is performed. Our framework provides a range of tools to interpret, visualize and compare the pathways, improving communication and enabling their evaluation on accuracy and cost, specific to different contexts. This framework will guide the development of novel diagnostic pathways for different diseases, accelerating the implementation of precision medicine into clinical practice.

bioinformatics↗