Barbara Stranger Lab

Barbara Stranger

Institute for Genomics and Systems Biology
The University of Chicago
KCBD 10134
900 E. 57th St.
Chicago, IL 60637

Phone: 773-702-4301

About the Lab

The overriding research interest of the lab is trying to disentangle the relationship between genotype and phenotype, and to understand the forces shaping functional genetic variation in humans. We use a combination of experimental and computational approaches: We employ high-throughput functional genomics and genome-wide association analysis (GWAS) to identify variable regions of the genome with functional effects on the transcriptome and proteome, and to investigate the context-specificity of these patterns. At the same time, we examine the levels and patterns of genetic variation within and between human populations, and between human and other species to identify regions of the genome with patterns of variation suggestive of natural selection.

Current projects in the lab investigate genetic effects on transcriptome regulation in disease contexts that include cancer, immune-mediated diseases, neuropsychiatric diseases, and pre-eclampsia. We also have a project examining the role of genetic regulation of the transcriptome in pharmacogenomics phenotypes. In parallel, as part of the ImmVar Consortium, we are studying immune cells of healthy cohorts to obtain a baseline against which to compare disease regulatory networks in immune-mediated diseases. We are active members of the Analysis Working Group of the Genotype-Tissue Expression (GTEx) Consortium, and have received funding to generate proteomic data and to perform analyses associating genetic variation data with proteomic expression data within and between tissues of the GTEx cohort. These approaches complement disease-mapping studies and provide hypotheses for the mechanism of action of specific variants in creating disease phenotypes.

We recently integrated GWAS results with protein-protein interaction networks and transcriptome data to examine the relationship between genome evolution and inflammatory disease (Raj et al, 2013).  We identified 21 genome regions with a ‘signature’ for both inflammatory disease susceptibility and natural selection. Our study suggests that genetic variants selected through human evolution based on their ability to function in pathogen-protection mechanisms can - in our modern, more pathogen-free, environment – predispose to autoimmune disease.

In Li et al (2014), we combined GWASs and data from The Cancer Genome Atlas (TCGA) to gain insight into the mechanisms by which cancer risk alleles predispose to disease.  We performed expression quantitative trait locus (eQTL) analyses for mRNA and miRNA expression levels in five tumor types (breast, colon, kidney, lung and prostate), thus identifying the germline genetic determinants of tumor gene expression and microRNA expression. We next tested 149 known cancer risk loci for eQTL effects, observing that nearly 30% were significantly associated with at least one transcript. For each of the risk loci, our study suggested 1 to 81 candidate causal variants that may be prioritized for downstream functional analysis. In summary, our study provided a comprehensive landscape of the genetic determinants of gene expression in different tumor types and ranked the genes and loci for further functional assessment of known cancer risk loci.

The lab is also interested in projects that are less disease centric and would be categorized as basic genome science.  We are interested in investigating:  1) the evolution of paralogs in the human genome; 2) the influence of genetic variation, ancestry, age, sex, cell-type, epigenome, and tissue-type on transcriptional networks; 3) genetic and epigenetic roles in gene splicing and 4) population genomics of regulatory regions and variants. We are constantly re-tooling and developing new analytic methods and tools to most effectively and efficiently make use of large-scale genomics data.

Selected Publications

Raj T, et al. Polarization of the effects of autoimmune and neurodegenerative risk alleles in leukocytes
Science. 2014 May 2. science.1249547.
PMID: 24786080

Lee MN, et al. Common genetic variants modulate pathogen-sensing responses in human dendritic cells
Science. 2014 Mar 7. science.1246980.
PMID: 24604203

Ye CJ, et al. Intersection of population variation and autoimmunity genetics in human T cell activation
Science. 2014 Sep 12. science.1254665.
PMID: 25214635

Hu X, et al. Regulation of gene expression in autoimmune disease loci and the genetic basis of proliferation in CD4+ effector memory T cells
PLoS Genet. 2014 Jun 26. eCollection 2014 Jun.
PMID: 24968232

Li Q, et al. Expression QTL-based analyses reveal candidate causal genes and loci across five tumor types
Hum Mol Genet. 2014 Oct 1. Epub 2014 Jun 6.
PMID: 24907074

Lab Members


Mark Applebaum

Mark Applebaum

Clinical Associate,
Department of Pediatrics, Section of Hematology/Oncology
Susan Cohn Lab and Barbara Stranger Lab
(773) 702-6808
Ian J. Begeman

Ian J. Begeman

Research Professional,
Research Specialist
Marian Fernando

Marian Fernando

Research Specialist
Eve Grumish, M.S.

Eve Grumish, M.S.

Research Professional,
Research Specialist I
Ekaterina (Katya) Khramtsova

Ekaterina (Katya) Khramtsova

Postdoctoral Scholar
Department of Medicine
Section of Genetic Medicine
Elizabeth Lipschultz

Elizabeth Lipschultz

Undergraduate Research Assistant
Meritxell Oliva Pavia

Meritxell Oliva Pavia

Stranger lab / Genetic Medicine Department / IGSB
PostDoctoral Scholar

Andrew Skol

Senior Statistical Geneticist
Stranger Lab and CDIS (Center for Data Intensive Science)
Barbara Stranger

Barbara Stranger

IGSB, Core Member, Fellow,
Assistant Professor, Department of Medicine, Section of Genetic Medicine


NIH Funding to Study the Effects of Gender on Complex Human Traits

IGSB core investigator <a href="/people/barbara-stranger">Barbara Stranger</a> received supplemental funding from NIH to explore the effects of gender on human traits. 

IGSB Core Member Co-Authors Paper

Barbara Stranger and her lab led analyses of data published in the journal, Science. The report, “Polarization of the Effects of Autoimmune and Neurodegenerative Risk Alleles in Leukocytes,” demonstrates how genetic variations among healthy, young individuals can influence immune cell function. Many of those variants are also genetic risk factors for Alzheimer’s disease, diabetes, and multiple sclerosis later in life, offering new insight into disease pathology.

Immunity, inflammation and natural selection

Barbara Stranger and colleagues take a systems approach, integrating GWAS, eQTL and protein interaction data, to demonstrate that loci associated with inflammatory disease susceptibility are enriched for genomic signatures of recent evolutionary selection.  Their analyses suggest that natural selection for pathogen-defense mechanisms through human evolution may underlie modern susceptibility to inflammatory diseases.

Research Papers