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These studies typically identify clusters of hundreds of single-nucleotide polymorphisms, or variants, that could cause a particular disease, but the studies themselves are unable to identify which ones are responsible. This is because the majority of variants are not in the genes themselves, but in the intervening DNA, researchers said. GWAS does not necessarily solve which genes are impacted by disease-associated polymorphisms.
Instead of using a typical GWAS approach, the research team set out to create three-dimensional maps that match variants with the genes they likely regulate. The approach used variants as signposts to identify potential gene enhancers in normal tissue.
“Prior to this study, no 3D structural genomic maps had been generated for this lupus-relevant cell type before,” said Andrew D. Wells, PhD, Co-Director of the Center for Spatial and Functional Genomics at CHOP, and co-senior author of the study. “With our approach, we believe we were in a position to identify genes and pathways that had no prior known role in lupus.”
With this method, the team identified 393 variants in proximity to genes in 3D, and therefore potentially involved in their regulation. About 90 percent of those variants would have been considered distant to their gene in one dimension, but were actually close in the three-dimensional map developed by the team.
Researchers were able to pinpoint two kinases, HIPK1 and MINK1, which previously had no known role in lupus. When these enzymes are targeted in follicular helper T cells, they inhibit the production of interleukin-21, a cytokine that’s involved in regulating antibody production.
The method could be used to better understand and treat other autoimmune conditions, the researchers noted.
“We believe that HIPK1 and MINK1 may serve as valuable therapeutic targets for lupus, a disease that is in dire need of new treatment options,” Wells said. “We also want to take the methods we used in this study and apply them to other autoimmune diseases and help pinpoint more causal variations that may have otherwise remained obscured by GWAS alone.”
The team is planning to develop HIPK1 transgenic mouse models to study their susceptibility to experimental lupus, as well as the potential impact of HIPK1 on antiviral immunity.
Healthcare researchers have increasingly sought to develop novel methods of analyzing genomes and advancing precision medicine for common diseases. A team from St. Jude Children’s Research Hospital recently created a genome analytics tool to detect alterations that drive tumor formations, which could help advance precision medicine for cancer.
The method, called cis-expression or cis-X, works by identifying abnormal expression of tumor RNA.
“Cis-X is a fundamental change from existing approaches that require thousands of tumor samples and only identify noncoding variants that happen recurrently,” said Jinghui Zhang, PhD, St. Jude Department of Computational Biology chair.
“By using aberrant gene transcription to reveal the function of noncoding variants, we developed cis-X to enable discovery of noncoding variants driving cancer in individual tumor genomes. Identifying variants that lead to dysregulation of oncogenes can expand the scope of the precision medicine to noncoding regions for identifying therapeutic options to suppress aberrantly activated oncogenes in tumors.”
By Jessica Kent