Please describe the research questions of your lab.
My lab is a computational group whose overarching goal is to use biomedical informatics approaches to better understand complex respiratory diseases. We gather new omics data as well as leverage the large volume of underutilized publicly available respiratory research data to gain insights and identify novel hypotheses based on diseased-focused integration of diverse data types. We collaborate with experts in pulmonary biology to experimentally validate our findings and collect novel genome-scale datasets. We build apps to share results with others for the sake of transparency and to maximize the chances that our findings contribute to the efforts of others in the scientific community. Some of the specific diseases we are working on are asthma, acute respiratory distress syndrome, and lymphangioleiomyomatosis.
What genetics/genomics techniques do you utilize in your lab?
We have experience with GWAS, exome sequencing analysis, microarrays, and RNA-Seq. We are in the early stages of using histone post-translational modification and phosphoproteomic data to understand aspects of asthma drug treatment response.
Describe a key technique/assay/instrument utilized in your lab, and what novel insights does it bring to your research question?
A good high-performance computing environment is critical to my lab and our ability to gain novel insights for any technique. Those who don’t work with large datasets often don’t realize how many funds are spent on hosting data and compute time for analyses. A well maintained computing environment that is properly staffed helps us complete tasks in hours/days that would otherwise take weeks/months or be intractable.
At what point in your life did you decide you wanted to be a scientist/physician?
When I was in second grade. Back then my first choice was to study penguins in Antarctica or become a geologist to explore remote locations. While my scientific track shifted considerably over the years, my commitment to being a scientist has not.
In your opinion, what is one of the most important discoveries in the field of respiratory illness/disease/function that was dependent on genomics or similar techniques?
I think the discovery of the 17q21 locus association with asthma, near the ORMDL3/GSDMB genes, is one of the most important genomics findings that will retrospectively become a turning point in our understanding of asthma. While the precise mechanism by which this association modulates asthma risk is still unknown, progress is being made to understand this signal that has been reproduced by over 20 research groups around the world since 2007. The unbiased nature of GWAS allowed us to identify this association, as no one would have hypothesized that a region with genes of unknown function is the most reproducibly associated asthma locus.
Please describe your favorite publication involving genomics/omics that you were involved with.
A memorable publication that I enjoyed working on was a GWAS of bronchodilator response published in 2012 (PMID: 22792082). Bronchodilator response, a measure that is often used in the diagnosis of asthma, is also a pharmacogenetic phenotype that indicates response to β2-agonist drugs. Using data of subjects from six asthma clinical trials with available bronchodilator response measures, we identified a strong region of association near a gene of unknown function called SPATS2L. Based on genetics data alone, we weren’t sure whether this was a false positive result because lack of knowledge about the gene left us unable to make any hypotheses about its function. We sought help of an experimental collaborator, Dr. Quan Lu, and with his help we found experimental support that SPATS2L is involved in bronchodilator response. Specifically, knockdown of the gene in human airway smooth muscle cells increased presence of the β2 adrenergic receptor, the target of β2-agonists that mediates bronchodilator response. This functional link between SPATS2L and bronchodilator response greatly enhanced our findings, and increased my confidence in using unbiased approaches to identify novel disease targets.
http://journals.plos.org/plosgenetics/article?id=10.1371/journal.pgen.1002824
What is your favorite aspect of ATS?
ATS has been an invaluable resource to meet and work with diverse scientists, learn about research efforts before they are published, navigate the ATS meeting, and more broadly, build camaraderie with those who share similar goals of performing research to improve our understanding of pulmonary diseases.
How could your research assist scientists and clinicians in other assemblies at ATS?
Generating, analyzing, and integrating omics data is becoming an integral part of research carried out across all ATS assemblies. Biomedical informatics expertise is utilized in basic science research to identify disease and drug response mechanisms, in translational research to identify endotypes, perform unbiased screens for biomarkers and disease-associated variation, and in clinical research to capture and deliver patient/provider data.
Would you be open to collaborations with GG and/or non-GG scientists and clinicians? Do you have any potential lab openings currently or in the near future?
I am always open to discussing potential collaborations with scientists and clinicians although my time for substantial contributions is limited. Highly motivated individuals who seek postdoctoral positions are welcome to inquire about joining the lab, especially those with a quantitative background, proficiency in R/Matlab/Python programming, experience working in a high performance computing environment, and/or a demonstrated interest in omics research.
