RESEARCH ARTICLE |  IMMUNOGENOMICS

Single-cell sequencing is transforming our understanding of complex tissues but their application to large population cohorts has been limited. Large sample sizes are particularly important for studying complex autoimmune diseases such as lupus where patients present a variety of symptoms and may respond very differently to current treatments. By using genetic information encoded in each single cell, we’ve previously developed a method called mux-seq to enable single-cell profiling of large populations. 

At 1.2 million cells from more than 250 samples, we have now used mux-seq to generate one of the largest single-cell sequencing dataset to date to characterize immune cells in lupus patients. Our analysis, published on April 8, 2022 in Science, has uncovered how differences in ancestry affects both the composition and state of immune cells which may explain the disparities in lupus susceptibility and severity. We also used the dataset to pinpoint genetic variants associated with autoimmunity and suggest mechanisms that they may act through. As a foundational component of the Human Cell Atlas, a Chan Zuckerberg Initiative funded effort to systematically map cells in humans, this data is broadly available to researchers around the world as a reference for current and future studies.

Authors: Richard K. Perez, M. Grace Gordon, Meena Subramaniam, Min Cheol Kim, George C. Hartoularos, Sasha Targ, Yang Sun, Anton Ogorodnikov, Raymund Bueno, Andrew Lu, Mike Thompson, Nadav Rappoport, Andrew Dahl, Cristina M. Lanata, Mehrdad Matloubian, Lenka Maliskova, Serena S. Kwek, Tony Li, Michal Slyper, Julia Waldman, Danielle Dionne, Orit Rozenblatt-Rosen, Lawrence Fong, Maria Dall’Era, Brunilda Balliu, Aviv Regev, Jinoos Yazdany, Lindsey A. Criswell, Noah Zaitlen, and Chun Jimmie Ye.

Media Contact: 

Leticia Ortiz | Marketing & Communications | Building a community around data science in biomedicine
leticiaortiz@mednet.ucla.edu​
@CompMedUCLA