Single-cell RNA-seq reveals cell type-specific molecular and genetic associations to lupus.
Richard K PerezM Grace GordonMeena SubramaniamMin Cheol KimGeorge C HartoularosSasha TargYang SunAnton OgorodnikovRaymund BuenoAndrew LuMike ThompsonNadav RappoportAndrew W DahlCristina M LanataMehrdad MatloubianLenka MaliskovaSerena S KwekTony LiMichal SlyperJulia WaldmanDanielle DionneOrit Rozenblatt-RosenLawrence FongMaria Dall'EraBrunilda BalliuAviv RegevRebecca GraingerLindsey A CriswellNoah A ZaitlenChun Jimmie YePublished in: Science (New York, N.Y.) (2022)
Systemic lupus erythematosus (SLE) is a heterogeneous autoimmune disease. Knowledge of circulating immune cell types and states associated with SLE remains incomplete. We profiled more than 1.2 million peripheral blood mononuclear cells (162 cases, 99 controls) with multiplexed single-cell RNA sequencing (mux-seq). Cases exhibited elevated expression of type 1 interferon-stimulated genes (ISGs) in monocytes, reduction of naïve CD4 + T cells that correlated with monocyte ISG expression, and expansion of repertoire-restricted cytotoxic GZMH + CD8 + T cells. Cell type-specific expression features predicted case-control status and stratified patients into two molecular subtypes. We integrated dense genotyping data to map cell type-specific cis-expression quantitative trait loci and to link SLE-associated variants to cell type-specific expression. These results demonstrate mux-seq as a systematic approach to characterize cellular composition, identify transcriptional signatures, and annotate genetic variants associated with SLE.
Keyphrases
- single cell
- systemic lupus erythematosus
- rna seq
- poor prognosis
- genome wide
- disease activity
- high throughput
- dendritic cells
- binding protein
- end stage renal disease
- healthcare
- chronic kidney disease
- long non coding rna
- rheumatoid arthritis
- high resolution
- peritoneal dialysis
- deep learning
- machine learning
- patient reported outcomes
- high density