Andrew Cole
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Andrew Cole has a total of 4 co-authors. Here are the top co-authors by number of shared publications:
- Bryce Fukuda
School of Engineering and Technology, University of Washington, Box 358426, Tacoma, WA 98402, USA
1 shared publication - Ka Yee Yeung
School of Engineering and Technology, University of Washington, Box 358426, Tacoma, WA 98402, USA
1 shared publication - Ling-Hong Hung
School of Engineering and Technology, University of Washington, Box 358426, Tacoma, WA 98402, USA
1 shared publication - Thomas J. Dahlstrom
School of Engineering and Technology, University of Washington Tacoma, USA
1 shared publication
Latest Publications
- Open Access
Uncovering the Pathophysiological Pattern of Expression from Integrated Analysis across Uniformly Processed RNA Sequencing COVID-19 Datasets
Background: Post-acute sequelae of SARS-CoV-2 infection (PASC) affects millions globally, yet the molecular mechanisms underlying acute COVID-19 and its chronic sequelae remain poorly understood. Methods: We performed an integrative transcriptomic analysis of three independent RNA-seq datasets, capturing the complete COVID-19 pathophysiology from health through acute severe infection to post-acute sequelae and mortality (n=142 total samples). We implemented a containerized analytical pipeline from data download, quantification, differential gene expression to uniformly process these three RNA-seq datasets. Results: Our analysis reveals striking molecular dichotomies contrasting disease phases with profound clinical implications. Acute severe/critical COVID-19 reveals predominant enrichment of TNF-α signaling via NF-κB pathways (normalized enrichment score >2.5, FDR 2.2, FDR <0.005), indicating important shifts toward cellular adaptation. Pathway signature analysis identifies core differentially expressed genes that reliably distinguish disease phases, thereby offering objective biomarkers for precision diagnosis and monitoring. Conclusions: These findings establish a comprehensive molecular framework distinguishing acute inflammatory from chronic metabolic COVID-19 phases, with potential clinical applicability. TNF-α/NF-κB pathway signatures identify patients at risk for severe disease progression, while Myc/OXPHOS signatures allow objective PASC diagnosis, addressing current reliance on subjective and eliminative diagnosis. This integrative analytical framework has utility beyond COVID-19, offering an applicable approach for precision medicine implementation across other diseases processes. Clinical Significance: This study transforms COVID-19 from a symptom-based to a molecularly-defined disease spectrum, enabling precision diagnosis, prognostic monitoring, classification, and targeted therapeutic possibilities based on pathway-specific biomarkers rather than subjective clinical assessments.
Open AccessUncovering the Pathophysiological Pattern of Expression from Integrated Analysis across Uniformly Processed RNA Sequencing COVID-19 Datasets
Background: Post-acute sequelae of SARS-CoV-2 infection (PASC) affects millions globally, yet the molecular mechanisms underlying acute COVID-19 and its chronic sequelae remain poorly understood. Methods: We performed an integrative transcriptomic analysis of three independent RNA-seq datasets, capturing the complete COVID-19 pathophysiology from health through acute severe infection to post-acute sequelae and mortality (n=142 total samples). We implemented a containerized analytical pipeline from data download, quantification, differential gene expression to uniformly process these three RNA-seq datasets. Results: Our analysis reveals striking molecular dichotomies contrasting disease phases with profound clinical implications. Acute severe/critical COVID-19 reveals predominant enrichment of TNF-α signaling via NF-κB pathways (normalized enrichment score >2.5, FDR 2.2, FDR <0.005), indicating important shifts toward cellular adaptation. Pathway signature analysis identifies core differentially expressed genes that reliably distinguish disease phases, thereby offering objective biomarkers for precision diagnosis and monitoring. Conclusions: These findings establish a comprehensive molecular framework distinguishing acute inflammatory from chronic metabolic COVID-19 phases, with potential clinical applicability. TNF-α/NF-κB pathway signatures identify patients at risk for severe disease progression, while Myc/OXPHOS signatures allow objective PASC diagnosis, addressing current reliance on subjective and eliminative diagnosis. This integrative analytical framework has utility beyond COVID-19, offering an applicable approach for precision medicine implementation across other diseases processes. Clinical Significance: This study transforms COVID-19 from a symptom-based to a molecularly-defined disease spectrum, enabling precision diagnosis, prognostic monitoring, classification, and targeted therapeutic possibilities based on pathway-specific biomarkers rather than subjective clinical assessments.