<?xml version="1.0" encoding="UTF-8"?>
<STUDY_SET xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">
  <STUDY center_name="GEO" alias="GSE174188" accession="SRP319208">
    <IDENTIFIERS>
      <PRIMARY_ID>SRP319208</PRIMARY_ID>
      <EXTERNAL_ID namespace="BioProject" label="primary">PRJNA728702</EXTERNAL_ID>
      <EXTERNAL_ID namespace="GEO">GSE174188</EXTERNAL_ID>
    </IDENTIFIERS>
    <DESCRIPTOR>
      <STUDY_TITLE>Multiplexed scRNA-seq reveals the cellular and genetic correlates of systemic lupus erythematosus</STUDY_TITLE>
      <STUDY_TYPE existing_study_type="Transcriptome Analysis"/>
      <STUDY_ABSTRACT>Systemic lupus erythematosus (SLE) is a heterogeneous autoimmune disease. Knowledge of circulating immune cell types and cell states associated with SLE remains incomplete. We profiled over 1.2 million PBMCs (162 cases, 99 controls) with multiplexed single-cell RNA-seq (mux-seq). Cases exhibited prominent expression of type-1 interferon-stimulated genes (ISG) 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 accurately predicted case-control status and stratified patients into two molecular subtypes. We integrated dense genotyping data, mapping cell-type-specific cis-eQTLs and linked known and novel SLE-associated variants to cell-type-specific gene expression. These results demonstrate mux-seq as a systematic approach to characterize cellular composition, identify transcriptional signatures, and annotate genetic variants associated with SLE. Overall design: Examination of 1.2 million PBMCs in 162 SLE donors and 99 healthy individuals to find cellular and genetic correlates of SLE.</STUDY_ABSTRACT>
      <CENTER_PROJECT_NAME>GSE174188</CENTER_PROJECT_NAME>
    </DESCRIPTOR>
    <STUDY_LINKS>
      <STUDY_LINK>
        <XREF_LINK>
          <DB>pubmed</DB>
          <ID>35389781</ID>
        </XREF_LINK>
      </STUDY_LINK>
      <STUDY_LINK>
        <XREF_LINK>
          <DB>pubmed</DB>
          <ID>36171194</ID>
        </XREF_LINK>
      </STUDY_LINK>
    </STUDY_LINKS>
  </STUDY>
</STUDY_SET>
