Peter Izmirly

This study identifies novel SLE autoantigens and links EBV-driven immunity to autoimmunity through longitudinal PhIP-seq and machine learning analysis.

This study defines the single-cell landscape of Class II lupus nephritis and identifies fibroblast transcriptional programs and chronicity index as potential predictors of kidney outcomes.

This paper develops a serial immunohistochemistry method to detect multiple antigens on kidney biopsy slides, enabling high-dimensional single-cell spatial analysis.

The paper uses serum proteomics to identify molecular signatures that classify lupus nephritis, differentiate disease activity and chronicity, and predict treatment response.

This study uses single-cell RNA-sequencing and spatial transcriptomics to analyze myeloid cell dynamics in lupus nephritis, showing shifts in immune responses linked to disease progression.

The paper identifies distinct genetic mechanisms for early (nuclear) and late (cellular) RNA eQTL by comparing their genomic localization and functional effects across tissues.

A single-cell atlas of blood and tissue samples from lupus nephritis patients and healthy controls identifies stromal and immune populations, including scar-associated macrophages, which correlate with disease activity.

This study examines inflammation in fibrotic areas of kidney biopsies from lupus nephritis patients and finds that the degree of inflammation correlates with future kidney function decline.

The paper identifies three immunologically distinct groups in lupus nephritis patients based on blood immunophenotyping, correlating with histopathology, treatment response, and renal outcomes.