Biology subjects

Stevenson, J.

Publications and source records attributed to Stevenson, J..

3 recordsLinked to original sources

bioRxiv2024

AI-readiness for Biomedical Data: Bridge2AI Recommendations

Biomedical research is rapidly adopting artificial intelligence (AI). Yet the inherent complexity of biomedical data preparation requires implementing actionable, robust criteria for ethical and explainable AI (XAI) at the "pre-model" stage, encompassing data acquisition, detailed transformations, and ethical governance. Simple conformance to FAIR (Findable, Accessible, Interoperable, Reusable) Principles is insufficient. Here, we define criteria and practices for reliable AI-readiness of biomedical data, developed by the NIH Bridge to Artificial Intelligence (Bridge2AI) Standards Working Group across seven core dimensions of dataset AI-readiness: FAIRness, Provenance, Characterization, Ethics, Pre-model Explainability, Sustainability, and Computability. Conformance to these criteria provides a basis for pre-model scientific rigor and ethical integrity, mitigating downstream risks of bias and error prior to AI modeling. We apply and evaluate these standards across all four Bridge2AI flagship datasets, spanning functional genomics to clinical medicine, and encode them in machine-actionable metadata bound to the datasets. This framework sets a benchmark for preparing ethical, reusable datasets in biomedical AI and provides standardized methods for reliable pre-model data evaluation.

bioinformatics↗

bioRxiv2023

Transcriptomic signatures of Abeta- and tau-induced neuronal dysfunction reveal inflammatory processes at the core of Alzheimer's disease pathophysiology

Molecular mechanisms enabling pathology-induced neuronal dysfunction in Alzheimers disease (AD) remain elusive. Here, we use mechanistic computational models to infer the combined influence of PET-measured A{beta} and tau burdens on fMRI-derived neuronal activity and to subsequently identify the transcriptomic spatial correlates of AD pathophysiology. Our results reveal overrepresented genes and biological processes that participate in synaptic degeneration and interact with A{beta} and tau deposits. Furthermore, we confirmed the central role of the immune system and neuroinflammatory pathways within AD pathogenesis; microglia were significantly enriched in the gene set associated with A{beta} and tau synergistic influences on neuronal activity. Lastly, our computational approach unveiled drug candidates with the potential to halt or reduce the observed pathological effects on neuronal activity, including existing medication for cancer, immune disorders, and cardiovascular diseases, many currently under clinical evaluation in AD. Overall, these findings support the notion that the AD brain experiences functional changes intricately associated with a diverse spectrum of molecular processes.

neuroscience↗

bioRxiv2022

Parallel CRISPR-Cas9 screens reveal mechanisms of PLIN2 and lipid droplet regulation

Lipid droplets (LDs) are lipid storage organelles that consist of a central core of neutral lipids surrounded by a phospholipid monolayer decorated with a unique set of integral and peripheral proteins. Invariably, at least one member of the perilipin family of proteins (PLIN1-5) associates with LDs in all cell types. Despite key roles of PLIN2 in governing hepatic lipid metabolism, the mechanisms that regulate PLIN2 levels remain incompletely understood. Here, we develop a set of genome-edited PLIN2 reporter cell lines that facilitate the analysis of genes that regulate PLIN2 and LD abundance. Leveraging these reporter cells in a series of CRISPR-Cas9 loss-of-function screens, we generate a comprehensive inventory of genes that influence PLIN2 levels under different metabolic conditions. Moreover, we uncouple their effects on PLIN2 expression and post-translational stability. Identified genetic modifiers include canonical genes that control LD metabolism (e.g., ACSL3, DGAT2, PNPLA2, ABHD5) as well as genes with less characterized roles in PLIN2 and LD regulation such as ubiquitination machinery (e.g., MARCH6, UBE2J2), transcription regulators (e.g., HNF4A, HDAC3), mitochondrial pathways (e.g., electron transport chain and mitochondrial fatty acid synthesis), and others. These CRISPR screens, and several published screens that focus on different aspects of lipid metabolism, provide the foundation for CRISPRlipid (http://crisprlipid.org), a versatile, online data commons for lipid-related functional genomics data. Together, our study uncovers new mechanisms of PLIN2 regulation and provides an extensive, phenotype-rich resource for the exploration of LD biology and lipid metabolism.

cell biology↗