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Where Can We Share the Impactful Work of Applied, Practicing Statisticians?
No full textAvenues for disseminating work by applied and collaborative statisticians to statistical audiences are extremely limited. Methodological advances made in the course of effectively executing applied work often fail to reach an audience of other practicing statisticians. We consider questions posed from several viewpoints, including as members of the professional community in academia, government, industry, and independent statistical consulting. We highlight key challenges and opportunities that exist in this space and start the discussion to examine pathways to share this important work. We conclude with recommendations for possible next steps for the dissemination of impactful work by applied, practicing statisticians
The Ecological Genome Project and the Promises of Ecogenomics for Society: Realising a Shared Vision as One Health.
No full textThis paper develops a vision for The Ecological Genome Project: an aspirational, global endeavour to connect human genomic sciences with the ethos of ecological sciences. The Project\u27s goal is to strengthen interdisciplinary networks that relate to diverse initiatives using genomic technologies, with respect to shared ethical frameworks and governance structures. To this end, this paper proposes a practical definition of ecogenomics to align various methodologies and values in a single environmental field using principles used to safeguard all forms of life in their habitats. We achieve this by using a One Health approach as a pretext for disparate disciplines to collaborate and also a lens to view the Ethical, Legal and Social Implications (ELSI) inherent in ecological systems
PAK1 inhibitor NVS-PAK1-1 preserves dendritic spines in amyloid/tau exposed neurons and 5xFAD mice.
No full textINTRODUCTION: Synaptic spine loss in Alzheimer\u27s disease (AD) contributes to cognitive decline. p21-activated kinase 1 (PAK1), a regulator of spine integrity, is aberrantly activated in AD. We investigated whether PAK1 inhibition might preserve dendritic spines in vitro and in vivo.
METHODS: Oligomeric amyloid beta (oAβ) or tau (oTau) were applied to hippocampal neurons ± NVS-PAK1-1, a selective PAK1 inhibitor. NVS-PAK1-1 was orally administered to 5xFAD mice. The effects of NVS-PAK1-1 treatment on PAK1 activity, spine density, and the proteome were assessed using phospho-PAK1 (pPAK1) western blotting, Golgi staining, and mass spectrometry for proteomic analyses.
RESULTS: NVS-PAK1-1 prevented oAβ and oTau-induced spine loss in vitro. In 5xFAD mice, NVS-PAK1-1 demonstrated brain exposure after oral administration and reduced PAK1 activation, prevented spine loss, and partially normalized synaptic proteomic signatures in females in absence of alterations in brain or plasma Aβ.
DISCUSSION: PAK1 inhibition enhances spine resilience in AD models, supporting its therapeutic potential.
HIGHLIGHTS: p21-activated kinase 1 (PAK1) inhibitors prevent oligomeric amyloid beta (oAβ) and oligomeric tau-induced spine loss and dendritic degeneration in cultured mouse hippocampal neurons. NVS-PAK1-1, a selective PAK1 inhibitor, protects against oAβ-induced spine loss in a dose-dependent manner (E
Machine vision-based frailty assessment for genetically diverse mice.
No full textFrailty indexes (FIs) capture health status in humans and model organisms. To accelerate our understanding of biological aging and carry out scalable interventional studies, high-throughput approaches are necessary. We previously introduced a machine vision-based visual frailty index (vFI) that uses mouse behavior in the open field to assess frailty using C57BL/6J (B6J) data. Aging trajectories are highly genetic and are frequently modeled in genetically diverse animals. In order to extend the vFI to genetically diverse mouse populations, we collect frailty and behavior data on a large cohort of aged Diversity Outbred (DO) mice. Combined with previous data, this represents one of the largest video-based aging behavior datasets to date. Using these data, we build accurate predictive models of frailty, chronological age, and even the proportion of life lived. The extension of automated and objective frailty assessment tools to genetically diverse mice will enable better modeling of aging mechanisms and enable high-throughput interventional aging studies
A compendium of human gene functions derived from evolutionary modelling.
Get PDFA comprehensive, computable representation of the functional repertoire of all macromolecules encoded within the human genome is a foundational resource for biology and biomedical research. The Gene Ontology Consortium has been working towards this goal by generating a structured body of information about gene functions, which now includes experimental findings reported in more than 175,000 publications for human genes and genes in experimentally tractable model organisms 1,2 . Here, we describe the results of a large, international effort to integrate all of these findings to create a representation of human gene functions that is as complete and accurate as possible. Specifically, we apply an expert-curated, explicit evolutionary modelling approach to all human protein-coding genes. This approach integrates available experimental information across families of related genes into models that reconstruct the gain and loss of functional characteristics over evolutionary time. The models and the resulting set of 68,667 integrated gene functions cover approximately 82% of human protein-coding genes. The functional repertoire reveals a marked preponderance of molecular regulatory functions, and the models provide insights into the evolutionary origins of human gene functions. We show that our set of descriptions of functions can improve the widely used genomic technique of Gene Ontology enrichment analysis. The experimental evidence for each functional characteristic is recorded, thereby enabling the scientific community to help review and improve the resource, which we have made publicly available
Modifications in media composition and antioxidant support influences in vitro produced bovine blastocyst inner cell mass and trophectoderm numbers.
No full textMost of the in vitro bovine embryo production work completed over the past several decades has relied on using a medium formulation developed based on the chemical composition of sheep oviduct fluid (SOFBE1). This work explored how changes in the composition of this medium (modSOFBE1) and the inclusion of five antioxidant molecules (5AO) affect in vitro bovine embryo development. Studies used cumulus oocyte complexes collected from abattoir-derived ovaries that underwent in vitro maturation and fertilization, then presumptive zygotes were placed into the various media formulations. No medium type or 5AO supplementation effects were observed on the percentage of zygotes that cleaved or the percentage of cleaved embryos that formed blastocysts. Trophectoderm (TE) cell numbers were increased in blastocysts cultured in modSOFBE1, and inner cell mass (ICM) numbers were increased in blastocyst developed in modSOFBE1+5AO. Sex ratio of blastocysts was not influenced by medium type and 5AO supplementation. This work provides evidence that improvements in the base SOFBE1 formulation and the addition of multiple antioxidants may not improve overall blastocyst development rates, but they may be a useful means for promoting TE and ICM cell numbers in blastocysts. These modifications to the cellular composition of blastocysts and other subsequent activities on post-transfer development that have yet to be described may offer us with new opportunities to improve post-transfer pregnancy success of in vitro produced bovine embryos
Transcripts with high distal heritability mediate genetic effects on complex metabolic traits.
Get PDFAlthough many genes are subject to local regulation, recent evidence suggests that complex distal regulation may be more important in mediating phenotypic variability. To assess the role of distal gene regulation in complex traits, we combine multi-tissue transcriptomes with physiological outcomes to model diet-induced obesity and metabolic disease in a population of Diversity Outbred mice. Using a novel high-dimensional mediation analysis, we identify a composite transcriptome signature that summarizes genetic effects on gene expression and explains 30% of the variation across all metabolic traits. The signature is heritable, interpretable in biological terms, and predicts obesity status from gene expression in an independently derived mouse cohort and multiple human studies. Transcripts contributing most strongly to this composite mediator frequently have complex, distal regulation distributed throughout the genome. These results suggest that trait-relevant variation in transcription is largely distally regulated, but is nonetheless identifiable, interpretable, and translatable across species
Immunosuppressive Tumor Microenvironment of Osteosarcoma.
Get PDFBackground/Objectives: Osteosarcoma is the most common malignant bone tumor in children, characterized by a high degree of genomic instability, resulting in copy number alterations and genomic rearrangements without disease-defining recurrent mutations. Clinical trials based on molecular characterization have failed to find new effective therapies or improve outcomes over the last 40 years. Methods: To better understand the immune microenvironment of osteosarcoma, we performed single-cell RNA sequencing on six tumor biopsy samples, combined with a previously published cohort of six samples. Additional osteosarcoma samples were profiled using spatial transcriptomics for the validation of discovered subtypes and to add spatial context. Results: Analysis revealed immunosuppressive cells, including myeloid-derived suppressor cells (MDSCs), regulatory and exhausted T cells, and LAMP3+ dendritic cells. Conclusions: Using cell–cell communication modeling, we identified robust interactions between MDSCs and other cells, leading to NF-κB upregulation and an immunosuppressive microenvironment, as well as interactions involving regulatory T cells and osteosarcoma cells that promoted tumor progression and a proangiogenic niche
AI-driven multi-omics modeling of myalgic encephalomyelitis/chronic fatigue syndrome.
No full textMyalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a chronic illness with a multifactorial etiology and heterogeneous symptomatology, posing major challenges for diagnosis and treatment. Here we present BioMapAI, a supervised deep neural network trained on a 4-year, longitudinal, multi-omics dataset from 249 participants, which integrates gut metagenomics, plasma metabolomics, immune cell profiling, blood laboratory data and detailed clinical symptoms. By simultaneously modeling these diverse data types to predict clinical severity, BioMapAI identifies disease- and symptom-specific biomarkers and classifies ME/CFS in both held-out and independent external cohorts. Using an explainable AI approach, we construct a unique connectivity map spanning the microbiome, immune system and plasma metabolome in health and ME/CFS adjusted for age, gender and additional clinical factors. This map uncovers altered associations between microbial metabolism (for example, short-chain fatty acids, branched-chain amino acids, tryptophan, benzoate), plasma lipids and bile acids, and heightened inflammatory responses in mucosal and inflammatory T cell subsets (MAIT, γδT) secreting IFN-γ and GzA. Overall, BioMapAI provides unprecedented systems-level insights into ME/CFS, refining existing hypotheses and hypothesizing unique mechanisms-specifically, how multi-omics dynamics are associated to the disease\u27s heterogeneous symptoms
Spectral divergence prioritizes key classes, genes, and pathways shared between substance use disorders and cardiovascular disease.
Get PDFIntroduction: Substance use disorders (SUDs) are heterogeneous diseases with overlapping biological mechanisms and often present with co-occurring disease, such as cardiovascular disease (CVD). Gene networks associated with SUDs also implicate additional biological pathways and may be used to stratify disease subtypes. Node and edge arrangements within gene networks impact comparisons between classes of disease, and connectivity metrics, such as those focused on degrees, betweenness, and centrality, do not yield sufficient discernment of disease network classification. Comparatively, the graph spectrum\u27s use of comprehensive information facilitates hypothesis testing and inter-disease clustering by using a larger range of graph characteristics. By adding a connectivity-based method, network rankings of similarity and relationships are explored between classes of SUDs and CVD.
Methods: Graph spectral clustering\u27s utility is evaluated relative to commonly used network algorithms for discernment between two distinct co-occurring disorders and capacity to rank pathways based on their distinctiveness. A collection of graphs\u27 structures and connectivity to functionally identify the relationship between CVD and each of four classes of SUDs, namely alcohol use disorder (AUD), cocaine use disorder (CUD), nicotine use disorder (NUD), and opioid use disorder (OUD) is evaluated. Moreover, a Kullback-Leibler (KL) divergence is implemented to identify maximally distinctive genes (Dg). The emphasis of genes with high Dg enables a Jaccard similarity ranking of pathway distinctiveness, creating a functional “network fingerprint”.
Results: Spectral graph outperforms other connectivity-based approaches and reveals interesting observations about the relationship among SUDs. Between CUD and CVD, the gamma-aminobutyric acidergic and arginine metabolism pathways are distinctive. The neurodegenerative prion disease and tyrosine metabolism are emphasized between OUD and CVD. The graph spectrum between AUD and NUD to CVD is not significantly divergent.
Conclusion: Graph spectral clustering with KL divergence illustrates differences among SUDs with respect to their relationship to CVD, suggesting that despite a high-level co-occurring diagnosis or comorbidity, the nature of the relationship between SUD and CVD varies depending on the substance involved. The graph clustering method simultaneously provides insight into the specific biological pathways underlying these distinctions and may reveal future basic and clinical research avenues into addressing the cardiovascular sequelae of SUD