Biology subjects

Hodgkinson, A.

Publications and source records attributed to Hodgkinson, A..

12 recordsLinked to original sources

bioRxiv2026

Why diabetes matters in dementia studies. Excluding diabetes status masks regional mitochondrial DNA copy number changes in human hippocampus, amygdala, and cerebellum in Alzheimers disease

STRUCTURED ABSTRACTO_ST_ABSINTRODUCTIONC_ST_ABSDiabetes is a major risk factor for Alzheimers disease (AD), and both diseases involve mitochondrial dysfunction. We hypothesised that AD is associated with reduced mitochondrial DNA copy number (mtDNA-CN) in vulnerable brain regions, and that diabetes modifies these changes. METHODSPost-mortem hippocampus, amygdala, and cerebellum samples (N=66-77) from non-cognitively impaired (NCI) and AD donors, with and without diabetes, were analysed. mtDNA-CN was quantified by absolute quantification. RESULTSOverall, mtDNA-CN was lower in AD. However, stratification by diabetes revealed opposite changes: non-diabetic AD cases showed reduced mtDNA-CN, whereas diabetic cases showed higher mtDNA-CN across all regions irrespective of cognitive status. DISCUSSIONThese findings confirm multiregional loss of mtDNA-CN in the AD brain, most evident in the absence of diabetes. The functional significance of higher mtDNA-CN in the diabetic brain remains unclear, but evidence that diabetes can mask effects has important implications for dementia studies.

neuroscience↗

bioRxiv2022

Computational Model of Heterogeneity in Melanoma: Designing Therapies and Predicting Outcomes

Cutaneous melanoma is a highly invasive tumor and, despite the development of recent therapies, most patients with advanced metastatic melanoma have a poor clinical outcome. The most frequent mutations in melanoma affect the BRAF oncogene, a protein kinase of the MAPK signaling pathway. Therapies targeting both BRAF and MEK are effective for only 50% of patients and, almost systematically, generate drug resistance. Genetic and non-genetic mechanisms associated with the strong heterogeneity and plasticity of melanoma cells have been suggested to favor drug resistance but are still poorly understood. Recently, we have introduced a novel mathematical formalism allowing the representation of the relation between tumor heterogeneity and drug resistance and proposed several models for the development of resistance of melanoma treated with BRAF/MEK inhibitors. In this paper, we further investigate this relationship by using a new computational model that copes with multiple cell states identified by single cell mRNA sequencing data in melanoma treated with BRAF/MEK inhibitors. We use this model to predict the outcome of different therapeutic strategies. The reference therapy, referred to as "continuous" consists in applying one drug (or several drugs) without disruption. In "combination therapy", several drugs are used sequentially. In "adaptive therapy" drug application is interrupted when the tumor size is below a lower threshold and resumed when the size goes over an upper threshold. We show that, counter-intuitively, the optimal protocol in combination therapy of BRAF/MEK inhibitors with a hypothetical drug targeting cell states that develop later during the tumor response to kinase inhibitors, is to treat first with this hypothetical drug. Also, even though there is little difference in the timing of emergence of the resistance between continuous and adaptive therapies, the spatial distribution of the different melanoma subpopulations is more zonated in the case of adaptive therapy.

systems biology↗

bioRxiv2021

TREM2 impacts brain microglia, oligodendrocytes and endothelial co-expression modules revealing genes and pathways important in Alzheimer s disease

A microglia response to pathogenic signals in diseases such as Alzheimers disease (AD) has long been recognised, but recent genetic findings have cemented their direct causal contribution to AD and thus the potential to target them or their effector pathways as a possible treatment strategy. TREM2 is a highly penetrant microglia risk gene for AD, which appears central to the coordination of the damage response by microglia in AD. Its absence has a negative impact on Tau and amyloid symptoms and pathologies. Full knowledge of its pathway and relationships with other brain cells in AD has not been fully characterised, but will be essential to fully evaluate the impact of manipulating this pathway for treatment development and to establish the best targets for achieving this. We used whole genome RNA sequencing of hippocampus and cortical brain samples from control, AD, and AD TREM2 risk carriers to identify TREM2-dependent genes driving changes in pathways, processes and cell types in AD. Through highly influential intra and intermodular hub genes and overall changes in the levels of gene expression, TREM2-DAP12 was found to strongly influence a number of other microglia, oligodendrocyte and endothelial genes, notably those involved in complement and Fc{gamma} receptor function, microglia-associated ribosomal genes and oligodendrocyte genes, particularly proteosomal subunits. These strong TREM2 centred co-expression relationships were significantly disrupted in AD cases with a TREM2 risk variant, revealing for the first time genes and pathways directly impacted by TREM2 in the brains of AD patients. Consistent with its function as a lipid sensor, our data supports a role for TREM2 in mediating oligodendrocyte and/or myelin clearance in AD which may be essential not only for preserving healthy tissue homeostasis but may also serve to minimise the persistence of antigenic peptides and lipids which may lead to detrimental pro-inflammatory sequelae. Further work should expand our knowledge of TREM2 on complement and Fc{gamma} receptor function and its impact on oligodendcrotye and myelin integrity and further evaluate the genes and pathways we have identified as possible treatment targets for AD.

neuroscience↗

bioRxiv2021

PAC: Highly accurate quantification of allelic gene expression for population and disease genetics

Analysis of allele-specific gene expression (ASE) is a powerful approach for studying gene regulation. However, detection of ASE events relies on accurate alignment of RNA-sequencing reads, where challenges still remain. We have developed PAC, a method that combines multiple steps to improve the quantification of allelic reads, including personalised (i.e. diploid) read alignment with improved allocation of multi-mapping reads. We show that PAC outperforms standard alignment approaches for ASE detection in both accuracy and in the number of sites it can reliably quantify.

genomics↗

bioRxiv2021

The Epiallelic Nature of Mouse rDNA

BackgroundRibosomal DNA (rDNA) displays substantial inter-individual genetic variation in human and mouse. A systematic analysis of how this variation impacts epigenetic states and expression of the rDNA has thus far not been performed. ResultsUsing a combination of long- and short-read sequencing, we establish that 45S rDNA units in the C57BL/6J mouse strain exist as distinct genetic haplotypes that influence the epigenetic state and transcriptional output of any given unit. DNA methylation dynamics at these haplotypes are dichotomous and life-stage specific: at one haplotype, the DNA methylation state is sensitive to the in utero environment, but refractory to post-weaning influences, whereas other haplotypes entropically gain DNA methylation during ageing only. On the other hand, individual rDNA units in human show limited evidence of genetic haplotypes, and hence little discernible correlation between genetic and epigenetic states. However, in both species, adjacent units show similar epigenetic profiles, and the overall epigenetic state at rDNA is strongly positively correlated with total rDNA copy number. Analysis of different mouse inbred strains reveals that in some strains, such as 129S1/SvImJ, rDNA copy number is only approximately 150 copies per diploid genome and DNA methylation levels are <5%. ConclusionsOur work demonstrates that rDNA-associated genetic variation has a considerable influence on rDNA epigenetic state and consequently rRNA expression outcomes. In the future, it will be important to consider the impact of inter-individual rDNA (epi)genetic variation on mammalian phenotypes and diseases.

genomics↗

bioRxiv2021

Human brain mitochondrial-nuclear cross-talk is cell-type specific and is perturbed by neurodegeneration

Mitochondrial dysfunction contributes to the pathogenesis of many neurodegenerative diseases as mitochondria are essential to neuronal function. The mitochondrial genome encodes a small number of core respiratory chain proteins, whereas the vast majority of mitochondrial proteins are encoded by the nuclear genome. Here we focus on establishing a profile of nuclear-mitochondrial transcriptional relationships in healthy human central nervous system tissue data, before examining perturbations of these processes in Alzheimer&#8217s disease using transcriptomic data originating from affected human brain tissue. Through cross-central nervous system analysis of mitochondrial-nuclear gene pair relationships, we find that the cell type composition underlies regional variation, and variation is driven at the subcellular level by heterogeneity of nuclear-mitochondrial coordination in post-synaptic regions. We show that nuclear genes causally implicated in sporadic Parkinson&#8217s disease and Alzheimer&#8217s disease show much stronger relationships with the mitochondrial genome than expected by chance, and that nuclear-mitochondrial relationships are significantly perturbed in Alzheimer&#8217s disease cases, particularly amongst genes involved in synaptic and lysosomal pathways. Finally, we present MitoNuclearCOEXPlorer, a web tool designed to allow users to interrogate and visualise key mitochondrial-nuclear relationships in multi-dimensional brain data. We conclude that mitochondrial-nuclear relationships differ significantly across regions of the healthy brain, which appears to be driven by the functional specialisation of different cell types. We also find that mitochondrial-nuclear co-expression in critical pathways is disrupted in Alzheimer&#8217s disease, potentially implicating the regulation of energy balance and removal of dysfunctional mitochondria in the etiology or progression of the disease and making the case for the relevance of bi-genomic co-ordination in the pathogenesis of neurodegenerative diseases.

genomics↗

bioRxiv2019

Intellectual disability-associated factor Zbtb11 cooperates with NRF-2/GABP to control mitochondrial function

Zbtb11 is a conserved transcription factor mutated in families with hereditary intellectual disability. Its precise molecular and cellular functions are currently unknown, precluding our understanding of the aetiology of this disease. Using a combination of functional genomics, genetic and biochemical approaches here we show that Zbtb11 plays essential roles in maintaining the homeostasis of mitochondrial function. Mechanistically, we find Zbtb11 facilitates the recruitment of Nuclear Respiratory Factor 2 (NRF-2) to its target promoters, activating a subset of nuclear genes with roles in the biogenesis of respiratory complex I and the mitoribosome. Genetic inactivation of Zbtb11 resulted in a severe complex I assembly defect, impaired mitochondrial respiration, mitochondrial depolarisation, and ultimately proliferation arrest and cell death. Experimental modelling of the pathogenic human mutations showed these have a destabilising effect on the protein, resulting in reduced Zbtb11 dosage, down-regulation of its target genes, and impaired complex I biogenesis. Our study establishes Zbtb11 as a novel essential mitochondrial regulator, improves our understanding of the transcriptional mechanisms of nuclear control over mitochondria, and provides a rationale for the aetiology of Zbtb11-associated intellectual disability.

cell biology↗

bioRxiv2019

Nuclear genetic regulation of human mitochondrial RNA modification

RNA modifications affect the stability and function of RNA species, regulating important downstream processes. Modification levels are often dynamic, varying between tissues and individuals, although it is not always clear what modulates this variation or what impact it has on biological systems. Here, we quantify variation in RNA modification levels at functionally important positions in the mitochondrial genome across 11,552 samples from 39 tissue/cell types and find evidence that modification levels impact mitochondrial transcript processing. We identify novel links between mitochondrial RNA modification levels in whole blood and genetic variants in the nuclear genome, including missense mutations in LONP1 and PNPT1, as well as missense mutations in MRPP3, SLC25A26 and MTPAP that associate with RNA modification levels across multiple tissue types. Genetic variants linked to modification levels are associated with multiple disease phenotypes, including blood pressure, breast cancer and Moyamoya disease, suggesting a role for these processes in complex disease.

genomics↗

bioRxiv2018

Spatio-Genetic and Phenotypic Modelling Elucidates Resistance and Re-Sensitisation to Treatment in Heterogeneous Melanoma

Although novel targeted therapies have significantly improved the overall survival of patients with advanced melanoma, understanding and combatting drug resistance remains a major clinical challenge. Using partial differential equations, we describe the evolution of a cellular population through time, space, and phenotype dimensions, in the presence of various drug species. We then use this framework to explore models in which resistance is attained by either mutations (irreversible) or plasticity (reversible). Numerical results suggest that punctuated evolutionary assumptions are more consistent with results obtained from murine melanoma models than gradual evolution. Furthermore, in the context of an evolving tumour cell population, sequencing the treatment, for instance applying immunotherapy before BRAF inhibitors, can increase treatment effectiveness. However, drug strategies which showed success within a spatially homogeneous tumour environment were unsuccessful under heterogeneous conditions, suggesting that spatio-environmental heterogeneity may be the greatest challenge to tumour therapies. Plastic metabolic models are additionally capable of reproducing the characteristic resistant tumour volume curves and predicting re-sensitisation to secondary waves of treatment observed in patient derived xenograft (PDX) melanomas treated with MEK and BRAF inhibitors. Nevertheless, secondary relapse due to a pre-adapted subpopulation, remaining after the first wave of treatment, results in a more rapid development of resistance. Our model provides a framework through which tumour resistance can be understood and would suggest that carefully phased treatments may be able to overcome the development of long-term resistance in melanoma.

cancer biology↗

bioRxiv2018

Time Dependent Stochastic mRNA and Protein Synthesis in Piecewise-deterministic Models of Gene Networks.

We discuss piecewise-deterministic approximations of gene networks dynamics. These approximations capture in a simple way the stochasticity of gene expression and the propagation of expression noise in networks and circuits. By using partial omega expansions, piecewise deterministic approximations can be formally derived from the more commonly used Markov pure jump processes (chemical master equation). We are interested in time dependent multivariate distributions that describe the stochastic dynamics of the gene networks. This problem is difficult even in the simplified framework of piecewise-determinisitic processes. We consider three methods to compute these distributions: the direct Monte-Carlo, the numerical integration of the Liouville-master equation and the push-forward method. This approach is applied to multivariate fluctuations of gene expression, generated by gene circuits. We find that stochastic fluctuations of the proteome and much less those of the transcriptome can discriminate between various circuit topologies.

systems biology↗

bioRxiv2017

Genomic and Environmental Contributions to Chronic Diseases in Urban Populations

Uncovering the interaction between genomes and the environment is a principal challenge of modern genomics and preventive medicine. While theoretical models are well defined, little is known of the GxE interactions in humans. We used a system biology approach to comprehensively assess the interactions between 1.6 million environmental exposure data, health, and expression phenotypes, together with whole genome genetic variation, for [~]1000 individuals from a founder-population in Quebec. We reveal a substantial impact of the urbanization gradient on the transcriptome and clinical endophenotypes, overpowering that of genetic ancestry. In detail, air pollution impacts gene expression and pathways affecting cardio-metabolic and respiratory traits when controlling for genetic ancestry. Finally, we capture 34 clinically associated expression quantitative trait loci that interact with the environment (air pollution). Our findings demonstrate how the local environment directly affects chronic disease development, and that genetic variation, including rare variants, can modulate individuals response to environmental challenges.\n\nHighlightsO_LIFine scale environmental effects overpower those of ancestry on gene expression\nC_LIO_LIAir pollution (geographic and temporal) is associated with transcriptional response\nC_LIO_LIGene-by-environment interactions with air pollution include asthma associated loci\nC_LIO_LIInflammatory pathways and cardio-respiratory clinical traits are among those affected\nC_LI

genomics↗

bioRxiv2016

Integrated Genomic Analysis of Mitochondrial RNA Processing in Human Cancers

Alterations to mitochondrial function and mutations in mitochondrial genes have been reported for a wide variety of cancers, however the mitochondrial transcriptome remains largely unexplored in cancer despite an emerging appreciation of the role that post-transcriptional regulation plays in the etiology of these diseases. Here, we quantify and assess changes to mitochondrial RNA processing in human cancers using integrated genomic analysis of RNA Sequencing and genotyping data from 1226 samples across 12 different cancer types. We find significant changes to m1A and m1G post-transcriptional methylation rates at functionally important positions in mitochondrial tRNAs in tumor tissues across all cancers. Pathways of RNA processing are strongly associated with methylation rates in normal tissues (P=2.85x10-27), yet these associations are lost in tumors. Furthermore, we report 18 gene-by-disease-state interactions where altered methylation rates occur under cancer status conditional on genotype, implicating genes associated with mitochondrial function or cancer (e.g. CACNA2D2, LMO2 and FLT3) and suggesting that nuclear genetic variation can potentially modulate an individuals ability to maintain unaltered rates of mitochondrial RNA processing under cancer status. Finally, we report a significant association between the magnitude of methylation rate changes in tumors and patient survival outcomes. These results highlight mitochondrial post-transcriptional events as a clinically relevant mechanism and as a theme for the further investigation of cancer processes, biomarkers and therapeutic interventions.

genomics↗