Biology subjects

Denis, M.

Publications and source records attributed to Denis, M..

7 recordsLinked to original sources

bioRxiv2026

Preserved Spontaneous Interpersonal Entrainment during Rhythmic Synchronization in Autism Spectrum Disorder

PurposeInterpersonal entrainment, defined as the tendency of interacting individuals to temporally align their behaviours, is considered a key mechanism supporting social interactions through predictive and multisensory processes. Autism Spectrum Disorder (ASD), characterized by social and communication difficulties, has been associated with atypical predictive and multisensory integration processes, which may affect spontaneous entrainment to others actions during rhythmic interactions. MethodsThe present study investigated spontaneous interpersonal entrainment in 24 autistic and 22 neurotypical young adults using a unidirectional adaptation of the drifting metronomes paradigm developed by Rosso et al. (2021). Participants synchronized their finger tapping with an auditory metronome while either seeing or not seeing a partners hand movements performing the same task at a slightly different tempo. Individual synchronization performance was assessed using asynchrony measures and computational modelling of sensorimotor synchronization, while interpersonal coordination dynamics were quantified using joint recurrence analysis. ResultsVisual exposure to the partners hand movements significantly increased tapping variability while simultaneously enhancing spontaneous interpersonal entrainment. Contrary to previous findings, these effects were comparable across groups, suggesting similar sensitivity to spontaneous low-level interpersonal coupling under stable and predictable conditions. ConclusionOverall, the findings support accounts proposing selective rather than generalized atypicalities in predictive processing and interpersonal entrainment in ASD.

neuroscience↗

bioRxiv2026

A Bayesian multidimensional approach to decipher the genetic basis of dynamic phenotypes in multiple species

Deciphering the genetic architecture of complex quantitative phenotypes remains challenging in quantitative genetics. These traits not only depend of multiple genetic factors but are also established over time and environments. Although quantitative genetics has investigated the genetic determinism of phenotypic plasticity in contrasted environmental conditions, the time related phenotypic plasticity has received less attention. Here we proposed a multivariate Bayesian framework, the Bayesian Varying Coefficient Model, designed for analysing the genetic architecture of the time related phenotypic plasticity by a multilocus approach. We applied the BVCM to time series phenotypes measured at various time scales (daily, monthly, yearly) across a diverse set of biological species. We included in this study: yeast (Saccharomyces cerevisiae), fungi (Fusarium graminearum), eucalyptus (Eucalyptus urophylla x E. grandis), and sweet cherry tree (Prunus avium). The BVCM results were compared with those obtained with a known genome-wide association method carried out time by time. For all species and traits, the BVCM was able to detect the major QTL identified by marker-trait association methods and revealed additional genetic regions of weak effect. It also increased the phenotypic variance explained for most of the phenotypes considered. It revealed dynamic QTLs with transitory, increasing or decreasing effects over time. By considering both the temporal and genetic multivariate structures in a single statistical model, we increased our understanding of the genetic architecture of complex traits notably by reducing the issue of missing heritability. More broadly, this work raises the foundation for extended applications in functional genomics, evolutionary ecology, and crop breeding programs, in which time-related phenotypic plasticity remains crucial for predicting and selecting key quantitative complex traits. Key messageBy capturing the genetic factors influencing the time related phenotypic plasticity, our approach contributes to a deeper understanding of the dynamic nature of genotype-phenotype relationships.

genetics↗

bioRxiv2024

In Utero Hematopoietic Stem Cell Transplant for Fanconi Anemia

Fanconi Anemia (FA) is an inherited DNA-repair deficiency caused by mutations in diverse Fanc genes that leads to bone marrow failure and malignancies. FA disease begins at early embryonic stages, and while FA prenatal testing has long been available, no fetal therapies for FA currently exist. Postnatally, FA hematologic disease can be cured through allogeneic hematopoietic stem cell transplantation (HSCT); however, this requires chemotherapy and/or irradiation-based conditioning which amongst various side-effects also increases likelihood of malignancies later in life in these fragile patients. Given fetal immune tolerance and the competitive advantage of healthy hematopoietic stem and progenitor cells (HSPCs) over failing FA HSPCs, in utero HSCT without conditioning may be an alternative approach to stabilization of the hematopoietic system without conventional toxicities. We performed in utero HSCT using HSPCs from wildtype (WT) donors into two FA mouse models (Fancd2-/-, Fanca-/-) and observed robust multi-lineage hematopoietic donor engraftment in homozygous FA mice compared to both heterozygous FA and WT littermates. Upon serial assessments, we also observed increasing donor chimerism up to 94.1%, showcasing the competitive advantage of WT donor HSPCs over FA HSPCs. Given that 1% donor chimerism is predicted to stabilize FA BM, in utero HSCT may be a safe and curative prenatal treatment for all subtypes of FA.

cell biology↗

bioRxiv2022

Repurposing of Amisulpride, a known antipsychotic drug, to target synovial fibroblasts activation in arthritis.

Synovial Fibroblasts (SFs) are key pathogenic drivers in arthritis and their in vivo activation by TNF is sufficient to orchestrate full arthritic pathogenesis in animal models. TNF blockade has been efficacious for a large percentage of Rheumatoid Arthritis (RA) patients, although characterized by a plethora of side effects. Novel therapeutic discoveries remain however challenging, especially in optimizing drug safety, side effects, longer-term responses, costs and administration routes. Aiming to find new potent therapeutics, we applied the L1000CDS2 search engine, in order to identify compounds that could potentially reverse the pathogenic expression signature of arthritogenic SFs, derived from the human TNF transgenic mouse model (hTNFtg). We identified a neuroleptic drug, namely Amisulpride, which was validated to reduce SFs inflammatory potential while decreasing the clinical score of hTNFtg polyarthritis. Notably, we found that Amisulpride did not exert its biological activities through its known targets Dopamine receptors 2 and 3 and Serotonin Receptor 7, nor through TNF-TNFRI binding inhibition. By applying a click chemistry approach, novel potential targets of Amisulpride were identified, which were further validated to repress hTNFtg SFs inflammatory potential in vitro (Ascc3 and Sec62), while phosphoproteomics analysis revealed important fibroblast activation pathways, such as adhesion, to be altered upon treatment. Our data support that Amisulpride could provide an additive beneficial effect to patients suffering from RA and comorbid dysthymia, as it may reduce SFs pathogenicity in parallel with its anti-depressive activity. Importantly, Amisulpride may also serve as a "lead" compound for the development of novel, more potent therapeutics against chronic inflammatory diseases.

pharmacology and toxicology↗

bioRxiv2022

miR-221/222 drive synovial fibroblast expansion and pathogenesis of TNF-mediated arthritis

MicroRNAs (miRNAs) constitute fine tuners of gene expression and are implicated in a variety of diseases spanning from inflammation to cancer. miRNA expression is deregulated in rheumatoid arthritis (RA), however, their specific role in key arthritogenic cells such as the synovial fibroblast (SF) remains elusive. We have shown in the past that the expression of the miR-221/222 cluster is upregulated in RA SFs. Here, we demonstrate that miR-221/222 activation is downstream of major inflammatory cytokines, such as TNF and IL-1{beta}, which promote miR-221/222 expression independently. miR-221/222 expression in SFs from the huTNFtg mouse model of arthritis correlates with disease progression. Targeted transgenic overexpression of miR-221/222 in SFs of the huTNFtg mouse model led to further expansion of synovial fibroblasts and disease exacerbation. miR-221/222 overexpression altered the transcriptional profile of SFs igniting pathways involved in cell cycle progression and ECM regulation. Validated targets of miR-221/222 included p27 and p57 cell cycle inhibitors, as well as Smarca1 (a chromatin remodeling component). In contrast, complete genetic ablation of miR-221/222 in arthritic mice led to decreased proliferation of fibroblasts, reduced synovial expansion and attenuated disease. scATAC-seq data analysis revealed increased miR-221/222 gene activity in the pathogenic and activated clusters of the intermediate and lining compartment. Taken together, our results establish an SF-specific pathogenic role of the miR-221/222 cluster in arthritis and suggest that its therapeutic targeting in specific subpopulations should inform the design of novel fibroblast-targeted therapies for human disease.

cell biology↗

bioRxiv2019

Data Resource Profile:The Dementias Platform UK (DPUK) Data Portal

The Dementias Platform UK (DPUK) Data Portal is a data repository facilitating access to data for 3 370 929 individuals in 42 cohorts. The Data Portal is an end-to-end data management solution providing a secure, fully auditable, remote access environment for the analysis of cohort data. All projects utilising the data are by default collaborations with the cohort research teams generating the data. The Data Portal uses UK Secure eResearch Platform (UKSeRP) infrastructure to provide three core utilities: data discovery, access, and analysis. These are delivered using a 7 layered architecture comprising: data ingestion, data curation, platform interoperability, data discovery, access brokerage, data analysis and knowledge preservation. Automated, streamlined, and standardised procedures reduce the administrative burden for all stakeholders, particularly for requests involving multiple independent datasets, where a single request may be forwarded to multiple data controllers. Researchers are provided with their own secure lab using VMware which is accessed using two factor authentication. Over the last 2 years, 160 project proposals involving 579 individual cohort data access requests were received. These were received from 268 applicants spanning 72 institutions (56 academic, 13 commercial, 3 government) in 16 countries with 84 requests involving multiple cohorts. Project are varied including multi-modal, machine learning, and Mendelian randomisation analyses. Data access is usually free at point of use although a small number of cohorts require a data access fee.

neuroscience↗

bioRxiv2017

A Balance Between Regulatory Constraints And Pathogen Pressure Shapes The Evolution Of Innate Immunity

As the first line of defence against pathogens, cells mount an innate immune response, which is highly variable from cell to cell. The response must be potent yet carefully controlled to avoid self-damage. How these constraints have shaped the evolution of innate immunity remains poorly understood. Here, we characterise this programmes transcriptional divergence between species and expression variability across cells. Using bulk and single-cell transcriptomics in primate and rodent fibroblasts challenged with an immune stimulus, we reveal a striking architecture of the innate immune response. Rapidly diverging genes, including cytokines and chemokines, also vary across cells and have distinct promoter structures. Conversely, genes involved in response regulation, such as transcription factors and kinases, are conserved between species and display low cell-to-cell variability. We suggest that this unique expression pattern, observed across species and conditions, has evolved as a mechanism for fine-tuned regulation, to achieve an effective but balanced response.

evolutionary biology↗