Jennifer L. Barnas

Serum proteomic atlas reveals distinct molecular signatures of lupus nephritis activity, chronicity, and treatment response

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

Deep profiling of lupus nephritis kidneys reveals dynamic changes in myeloid cells associated with disease progression

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.

Early and late RNA eQTL are driven by different genetic mechanisms

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 population-scale atlas of blood and tissue in lupus nephritis

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.

Granzyme K drives a newly-intentified pathway of complement activation

This study identifies granzyme K as a driver of a novel complement activation pathway independent of classical, lectin, or alternative pathways.

Tissue-specific enhancer-gene maps from multimodal single-cell data identify causal disease alleles

The paper develops SCENT, a method to create cell-type-specific enhancer-gene maps from single-cell multimodal data, identifying causal variants and genes for diseases.

Mapping the dynamic genetic regulatory architecture of HLA genes at single-cell resolution

The paper maps cell-type-specific eQTLs for HLA genes across multiple tissues and identifies dynamic regulation of HLA-DQ genes in immune cells.

Cellular deconstruction of inflamed synovium defines diverse inflammatory phenotypes in rheumatoid arthritis

The paper deconstructs RA synovium using single-cell data to identify six cell type abundance phenotypes associated with distinct inflammatory states.