Please describe the research questions of your lab.

The primary goal of my research group is understanding the genetic susceptibility and heterogeneity of chronic lung diseases, with a focus on COPD and related phenotypes. While COPD is generally thought of as a purely smoking-related disease, many studies have found genetics plays a substantial role in why most smokers do not develop disease. Excluding patients who have severe alpha-1 anti-trypsin deficiency, the most commonly known form of the disease, there is a substantial contribution of genetics to disease. Studying genetic risk factors can identify causal pathophysiology important in human disease that can lead to improvements in therapy. Our group has led both common and rare variant studies to identify these genetic factors, and have also collaborated to determine how these genetic variants affect risk. COPD is a heterogeneous disease (some have called it a syndrome). We have also been studying the genetics of COPD-related phenotypes, and the identification of novel phenotypes or subtypes using machine learning methods using genetics and other omics data. While our focus is on COPD, we’ve recently started an exciting project (together with Matt Hunninghake) on interstitial lung abnormalities.

What genetics/genomics techniques do you utilize in your lab?

The core of work is in genetic variation, which comes from genome- or exome-wide genotyping, or exome or whole genome sequencing. We have also been involved in analysis of other omics, such as transcriptome (RNA-Seq) and protein biomarker data, through colleagues and collaborators. We are use a large variety of bioinformatic tools to analyze and interpret this data. Most of our work is computational.

Describe a key technique/assay/instrument utilized in your lab, and what novel insights does it bring to your research question?

The advances in genetics have really been tremendous. I think it’s hard to identify a ‘key’ technique since all it’s really all the components together that make modern genetic analyses so powerful. This includes having the right laboratory methods, equipment (microarray and second-generation sequencing machines), computational techniques that accurately identify genetic variants, and statistical methods and software that can analyze billions of data points. The ability to look genome-wide at large samples has really revolutionized our ability to examine the basis of human disease.

At what point in your life did you decide you wanted to be a scientist/physician?

Probably later than most people. I was an engineering and computer science as an undergraduate, but wanted to my skills to more directly benefit people. I was fortunate be part of a special program for engineering students at Mount Sinai, which turned out to be a great experience, and made me decide to become a physician. My interests in medical school and residency / fellowship were diverse. I was always interested in research, but didn’t have a full sense of the real experience until the research portion of my fellowship. I credit the great training and mentorship at the Channing / BWH for helping me make my decision to stay in research.

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?

It’s difficult as a pulmonologist to think of a bigger genetic success story than cystic fibrosis – though it’s taken many years, the discovery of the gene and all the subsequent mutations were critical to discovery the targeted therapies we now have available. It’s also a good reminder that for the new discoveries using other methods and in other diseases we are still in the relatively early days.

Briefly describe your favorite publication involving genomics/omics that you were involved with in general-audience terms.

The International COPD Genetics Consortium (ICGC) genome-wide association study published in Nature Genetics (doi:10.1038/ng.3752) is my recent favorite for two reasons. First, of the best things about science is the ability to work with and interact with great colleagues. This was a collaborative project involving dozens of investigators from around the globe - including my ICGC co-leader, Marike Boezen – and a talented junior faculty and SGG member, Brian Hobbs. Second, while I think there is still a lot of skepticism about GWAS and genetics of COPD in general, hopefully our work shows the value of these studies. We found 22 regions of the genome associated with COPD, including some that overlap with pulmonary fibrosis – increasing risk for fibrosis but decreasing risk for COPD. We found a genetic correlation between COPD and asthma and population-based lung function (the latter the subject of an impressive companion paper in the same issue). Our study helps emphasize that there are clear genetic risk factors for COPD, and paves the way for future functional experiments to understand COPD susceptibility and heterogeneity - and we’re still just scratching the surface.

What is your favorite aspect of ATS?

The best part about ATS for me is the opportunity to meet and build relationships with other respiratory clinicians and investigators. It’s through the ATS that I’ve received some of my most valuable advice about my career, feedback about my science, and gained important knowledge as both a clinician and an investigator. I’ve also met many of the ICGC investigators at the International Conference which has been really important for future studies. I’ve of course really enjoyed being a part of the Section of Genetics and Genomics, as a ‘home’ for like-minded investigators. As the new co-chair, one of my goals is to increase the awareness and recognition of the importance of genetics and genomics in the ATS.

How could your research assist scientists and clinicians in other assemblies at ATS?

I hope our work in human genetics of COPD and in other diseases and phenotypes helps basic and translational scientists by highlighting specific molecular mechanisms and pathways relevant for human disease. While it’s been harder to find a direct clinical impact, our work in genetic risk scores and phenotype heterogeneity could eventually identify subsets of patients that would be managed differently. I also think more broadly, one of the goals of our research is to advance and emphasize the important role of omics and data analysis generally.

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?

We are always open to collaborations with GG and non-GG scientists and clinicians. We also have a lot of exciting data and projects to be done and would welcome inquiries from any talented, hard-working, and data-minded analysts, fellows, and post-docs!

Michael Cho (remhc@channing.harvard.edu)