Minoli Perera
Northwestern University, IL·Genetics
People respond to the same drug differently, partly because of their genes. Many genetic variants linked to drug response sit outside protein-coding regions.
- Fields
Genetics
Pharmacology
Medicine & Clinical Research
- Topics
pharmacogenomics
drug metabolism
drug-metabolizing enzymes
- Grants
- 1 known grant, through Mar 2030
What they work on
- Identify regulatory variants that affect drug-metabolizing enzymes by analyzing genomic and transcriptomic data from 120 primary hepatocyte cultures, with a focus on African ancestry samples.
- Determine which eQTLs, genetic variants linked to gene activity levels, truly change gene expression, using a massively parallel reporter assay in HepG2 liver cells.
- Measure how eQTLs alter the activity of drug-metabolizing enzymes by introducing the variants with prime editing, a precise genome-editing technique, and quantifying enzyme activity.
More about the research
Such variants likely work by changing how much of a nearby gene is made, which makes their role hard to pin down. Researchers trace these effects with eQTLs (expression quantitative trait loci), variants linked to gene activity levels. Doing this requires multi-omic data, meaning combined genomic and gene-expression measurements. Nearly all such data come from people of European ancestry. African ancestry populations carry greater genetic diversity, which could reveal variants relevant to everyone, but they remain poorly represented.
Why it matters
Doctors lack good genetic markers to predict how a patient will process a medication. By identifying liver regulatory variants that change drug-metabolizing enzyme activity, this work could provide more predictive biomarkers for dosing and drug response. Because it draws on African ancestry samples that existing databases lack, it may make such tools useful for more diverse patient populations.
Known grants
From NIH and NSF research grants. Labs often have other funding we can't see.
Closest labs
Anat Kreimer
Rutgers University-New Brunswick, NJ·Genetics
Develop methods that integrate massively parallel reporter assay (MPRA) data, which test thousands of DNA sequences at once, with other genomic assays and deep learning to reconstruct cell-type-specific gene regulatory networks and their condition-specific regulators.
Hyejung Won
University of North Carolina at Chapel Hill, NC·Genetics
Develop single-cell massively parallel reporter assays (scMPRA), which combine DNA barcoding with single-cell RNA sequencing, to measure thousands of Alzheimer's-linked regulatory elements in different brain cell types at once.
Melissa Gymrek
University of California-San Diego, CA·Genetics
Develop scalable methods for tandem repeat (TR)-based GWAS that genotype repeats directly from UK Biobank and All of Us whole genome sequences, producing a catalog of TRs linked to complex traits.
The school
Northwestern University: 71 labs on PI Pages, $1.3B a year on research, 536 research doctorates a year.
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