Lam C. Tsoi

This study shows that IL-17 targets different cell types in inflammatory skin diseases, with fibroblasts being key in hidradenitis suppurativa and both fibroblasts and keratinocytes in psoriasis.

This study uses multiomic analysis to identify IFN signaling as a key driver in Hailey-Hailey disease and shows that ruxolitinib treatment reduces inflammation and improves patient outcomes.

The paper investigates how particulate matter exposure affects nasal epithelial cells in chronic rhinosinusitis (CRS) and controls, finding amplified inflammatory and barrier dysfunction responses in CRS cells.

SEBULA detects multiplets in snATAC-seq using a semi-parametric empirical Bayes model and integrates with scRNA-seq data, showing superior performance on benchmark datasets.

This study shows KRT16 inhibits type I interferon signaling and innate immunity in skin diseases, providing new insights into inflammatory skin disorder mechanisms.

singIST quantifies disease model similarity to human conditions at single-cell resolution using pathway and cell type-level measures, demonstrating its utility in atopic dermatitis models.

The paper shows that restoring keratinocyte homeostasis reduces skin inflammation by reversing gene programs and normalizing epidermal architecture in a murine model.

This study identifies genetic risk factors associated with severe psoriasis and shows that polygenic risk scores can predict severe disease outcomes better than traditional risk factors.

The paper shows that altering primary cilia length in fibroblasts can reduce fibrotic responses across different fibrotic conditions.

This study compares dermatomyositis and lupus skin lesions using single-cell RNA-sequencing to identify inflammatory monocytes and JAK-1 signaling as drivers of vasculopathy in dermatomyositis.

Loopsim performs enrichment analysis on Hi-C loop profiles by simulating empirical null distributions to assess statistical significance of loop features.

The paper identifies TWEAK-IL-13 signaling as a driver of paradoxical skin reactions following anti-TNF, IL-17, or IL-23 therapy.

This study identifies interferon-responsive dermal fibroblasts in Sweet's syndrome that promote neutrophil recruitment through chemokine expression and spatial positioning.

This study identifies VGLL3 as a key driver of preeclampsia by linking it to placental, vascular, and immune defects, showing its therapeutic potential through genetic and pharmacological inhibition.

This study creates a high-resolution single-cell atlas of healthy human skin, revealing region-specific transcriptional networks and their links to inflammatory diseases.

The paper identifies ZBP1 and mitochondrial Z-DNA as drivers of autoimmune photosensitivity through cGAS-STING activation in response to UVB.

This study performs a GWAS meta-analysis of psoriasis, identifying 109 susceptibility loci, including 45 new ones, and highlights potential therapeutic targets and disease mechanisms.

The paper identifies increased activation of the IL1A/IRAK1 axis and downstream proinflammatory signaling in healthy African American skin compared to White Non-Hispanic skin, potentially contributing to higher risk of inflammatory skin diseases.

This study conducts a multi-ancestry GWAS meta-analysis of 56,146 AD cases and 602,280 controls, identifying 101 genomic loci, 15 novel to AD or eczema, and linking them to AD pathophysiology through functional analyses.

tauFisher predicts circadian time from bulk and single-cell transcriptomic data by analyzing rhythmic gene correlations, showing strong performance across multiple tissues and experimental settings.

SKiM discovers and annotates biomedical knowledge using co-occurrence and transformer models to find A-B-C relationships between user-defined concepts.

This paper performs RNA-seq on skin samples from three acantholytic diseases to identify shared transcriptomic features and mechanisms of pathogenesis.

This study identifies 144 genetic loci associated with abdominal aortic aneurysm and highlights PCSK9 as a therapeutic target through Mendelian Randomization and pre-clinical validation.

SKiM is a literature-based discovery system that rediscovered biomedical knowledge and identified potential drug candidates by analyzing PubMed literature.

The paper introduces a Bayesian method for transcriptomic data imputation that improves gene mapping of complex traits by enhancing imputation accuracy and TWAS power over existing tools.

The paper investigates genetic correlations between psychiatric and immune-related phenotypes using GWAS summary data, finding significant shared genetic variants.

This study uses Mendelian Randomization to show that higher BMI causally increases the risk of psoriasis and eczema, with a stronger effect on psoriasis.