2023 ASHG Leadership Award

This article is based on the address given by the author at the 2023 meeting of The American Society of Human Genetics (ASHG). A video of the original address can be found at the ASHG website. This article is based on the address given by the author at the 2023 meeting of The American Society of Human Genetics (ASHG). A video of the original address can be found at the ASHG website. It has been such a pleasure to be a part of the American Society of Human Genetics (ASHG) for so many years—since I was a graduate student—and a true honor to have been selected for the 2023 Leadership Award. I want to start my long list of thanks by thanking the ASHG for serving as my science home and for allowing me to give back by serving the Society. Thanks also to Mike Boehnke for the lovely introduction. Few people in our field had the luxury that I had of being able to take a high school course in genetics—in 1972, as a junior. I grew up in the small town of Hillsboro, IL (4,200 people). Mr. Kenneth Schaal was a new teacher there when I took biology as a sophomore. He followed the general biology class with four additional one-semester offerings: genetics, environmental studies, anatomy, and physiology. I believe I was a student in the first genetics class that he taught. It changed and oriented my life, since after that semester, I was sure about what I wanted to do with my life. But Mr. Schaal had similar effects on many other students. Several others over the years chose genetics as a career (at least one genetic counselor and a forensic geneticist), but there were many who chose to become health professionals (physicians, dentists, nurses, nurse practitioners, physician assistants, physical therapists), at least one PhD in forestry, and many, many generations of committed recyclers. He had a network of contacts that enabled him to get chimpanzees for dissection in the anatomy and physiology classes for the first couple of years, and that allowed him to set up field trips to universities in St. Louis where we were able to talk with scientists and physicians. It was on one of those field trips that I learned that the University of Notre Dame had an excellent mosquito genetics program and a good shot at the National Championship in football over the next few years. They had just gone co-ed, and the sex ratio was 6 males:1 female. It's kind of embarrassing now to consider how much each of those facts motivated my college choice. So, I went to Notre Dame as a biology major, continued my interests in genetics by doing research in a mosquito genetics lab, took nine of my classmates to the Cotton Bowl in the back of my truck (just a cap on the back—no heat or seat belts) where we won the National Championship during my senior year, got really interested in quantitative biology through a biostatistics class, and generally had a great college experience. It was one of my professors at Notre Dame who suggested that I apply to graduate school at Yale because he had done a recent sabbatical there and said that there was a new professor doing research in quantitative human genetics at Yale in the new Department of Human Genetics. I was able to start graduate school early by doing a rotation in Ken Kidd's lab starting July 1, 1978, before classes started. Ken was a terrific advisor who had a real gift for helping students to see how to use quantitative analysis for testing biological hypotheses. His wife, Judy, taught me how to run a lab by outstanding example; the Kidd Lab was an engaging environment doing exciting research. But it was the 14-year-old lab volunteer (faculty offspring too young to be paid) who helped me learn computer programming, which I have long thought was the most useful thing I have ever done. Yale was intimidating as an institution, but even I could ask questions of a 14 year old. Thank you, Michael Braverman, for being a good such a good teacher! It was Ken who influenced my post-doctoral decision, as he had been a faculty member at Washington University for a couple of years before he went to Yale, and he made it sound like a great learning environment. So, when I got the offer for post-doctoral research there, I was happy to be able to go. Several of the post-doctoral mentors in the program, including Bob Cloninger, John Rice, Ted Reich, and Brian Suarez were direct mentors for me; many others contributed to the educational environment, including Irv Gottesman, Greg Carey, D.C. Rao, and in the summers, Jean-Marc Lalouel. Ted was an amazing mentor. He had been educated in quantitative genetics in Edinburgh, Scotland, still one of the foremost programs in quantitative genetics, and I really treasured the opportunity to learn more of that science. There was a good didactic part of the program that involved going through various classic books of the time together as a group. Over time, I worked more with Brian Suarez, whose background was in physical anthropology. Brian was a true original thinker and a role model for building community. He always said that if you want to publish a paper, you should be prepared to review three. If you want to obtain grant funding, you should be prepared to review grants for the places from which you obtain funding. And if you enjoy attending scientific meetings, you should be prepared to do the work needed for meetings and to make societies sustainable. I have never known anyone to have more former trainees who ended up leading scientific meetings and societies than Brian—in physical anthropology, human genetics, genetic epidemiology, psychiatry, and behavioral genetics. I also learned a tremendous amount from other post-docs at Washington University. Paul Van Eerdewegh and I started about the same time, and we overlapped with Dennis O'Rourke, Mike Province, Matt McGue, and Ingrid Borecki—it was a really great intellectual environment. But the use of DNA markers to enable large-scale linkage mapping was really starting to take off as I finished the post-doc, and many of my contemporaries who had done only quantitative research to that point were either opening wet labs or considering it. Doing a second post-doc seemed to be a good way to try out the new molecular techniques for gene mapping. Rich Spielman, who was the outside reader on my thesis, had done a sabbatical in the UK to learn the molecular mapping methods and had started a wet lab at the University of Pennsylvania. He was willing to take me on as a wet lab post-doc though I had only computational experience to that point. While it was a great experience—and I totally mastered the high-tech art of Southern blotting—I enjoyed much more the experience of completely computerizing Rich's entire lab which helped clarify for me that it was really the computational science that I wanted to spend my time doing. Fortunately, the Spielman lab was a great mix of molecular and quantitative science, and Rich's long-standing collaborator, Warren Ewens, was a wonderful bonus mentor for me. At that time, Warren and his wife Kathy (who was Rich's lab manager), spent six months a year in Australia where he chaired the Math Department at Monash University and six months a year at the University of Pennsylvania where he chaired the Biology Department. Warren had a real talent for figuring out the best way to frame a problem so that it could be solved. Even though I ultimately decided never to run a wet lab of my own, learning more about what the quality issues were in generating the genotyping data was a tremendously valuable experience that shaped how I thought about and tested data quality the entire rest of my career. I had primarily worked on the genetics of diabetes, both type 1 and type 2 diabetes, while I was working in the Spielman lab, and it was that experience that enabled me to obtain my next position at the University of Chicago. Graeme Bell was developing a new program on the genetics of diabetes there, and they were also planning to develop a new Department of Human Genetics over the next couple of years. I was excited by all of the possibilities, as the University of Chicago had a tremendous program in population genetics and evolutionary biology, as well as groundbreaking human geneticists like Janet Rowley. Graeme had been part of the team that had cloned the human insulin gene and is one of the most talented scientists I have ever met—someone who makes everyone around him a better scientist. While the diabetes genetics environment was great, I did miss having more colleagues in quantitative human genetics. I had to invite myself to the University of Michigan to Mike Boehnke's lab or drive down to my friends at Washington University to be able to talk with colleagues about new ideas. Within a year or two though, Augie Kong had joined the Department of Statistics at the University of Chicago. Augie's previous research in statistics was the perfect background for developing an interest in statistical genetics—he was a natural! And he was such a fun (and hilariously funny) collaborator and one of the few people at the University of Chicago who could be counted on to actually stop working and eat lunch. Whether it was the 25-cent hot dog special on Friday afternoons, a quick trip to China town, or lunch at the faculty club (so I could tell my mom I had lunch with the Nobel Prize winners from the econ department), it was always a good time. Of course, it took another 10 years or so to actually get a department of human genetics set up at the University of Chicago, but with Carole Ober, Anna DiRienzo, and David Ledbetter (and a major assist from Janet Rowley), it was finally done. It was David, Carole, and Anna who helped me learn what it really takes to build the kind of intellectual environment that can support a department. Within a few years, we had recruited Jonathan Pritchard, Molly Przeworski, Matthew Stephens, Abe Palmer, Marcelo Nobrega, Bill Dobyns, Christa Lese Martin, Soma Das, Kathy Millen, and Yoav Gilad; Augie, Graeme, Peter Donnelly, Funmi Olopade, Beth McNally, and Janet Rowley all had secondary appointments as well. And we had a whole series of simply outstanding trainees. But the only constant in academia is change. Peter moved to Oxford to head up statistics there, although he came back to our Department of Human Genetics for a sabbatical. Augie moved on to head statistical genetics for deCODE Genetics and then later to Oxford, and I moved back to the Department of Medicine to direct the Section of Genetic Medicine. David Ledbetter and Christa Lese Martin moved on to Emory and then Geisinger. Jonathan is now at Stanford University, Abe is at the University of San Diego, Bill Dobyns and Kathy Millen went to the University of Washington, and Bill then moved back the University of Minnesota in his home state; Beth moved to Northwestern, and then after 28 years at the University of Chicago, I moved to Vanderbilt as the inaugural director of the Vanderbilt Genetics Institute (VGI) and the director of the Division of Genetic Medicine. BioVU, the biobank at Vanderbilt, is an astonishingly rich resource for discovery, and it has been a tremendous experience to learn the myriad ways BioVU and the extensive electronic records data at Vanderbilt can be used to better understand the genetic component to human health and disease. I'm grateful to Dan Roden for pushing to build BioVU and to Dan and the rest of the faculty who recruited me to Vanderbilt: Josh Denny, Lisa Bastarache, Jim Sutcliffe, Bingshan Li, David Samuels, Todd Edwards, Digna Velez-Edwards, Ela Knapik, Michelle Southard-Smith, Jeff Smith, and Georgia Wiesner. This Vanderbilt community helped recruit and welcomed a new cadre of faculty, including Doug Ruderfer, Lea Davis, Piper Below, Eric Gamazon, Melinda Aldrich, Ran Tao, Tuya Pal, Maggie Ng, Ruben Barricarte, Alex Bick, and Nikhil Kankhari in the first wave, as well as our newest faculty, Kevin Li, Jacklyn Hellwege, Maria Niarchou, Patrick Evans, Tyne Miller-Fleming, Megan Shuey, Jibril Hirbo, and Garrett Kaas. And thanks also to all of our current and former trainees who have made this such a rich environment! One of the best parts of a life in academia includes the friends you make all over the world. Mike Boehnke and I first met as trainees when we had back-to-back talks at an ASHG meeting. Many years later, we started the first consortium in the genetics community built around type 2 diabetes genetics. Over many years, Mike and I worked with colleagues such as Mark McCarthy, Craig Hanis, David Altshuler, Jose Florez, and Alan Shuldiner along with many outstanding trainees to learn what we could about the genetics of type 2 diabetes. While I have enjoyed working in many other consortia since then, my diabetes colleagues still have the record for phone hours of science. I still also collaborate with colleagues at the University of Chicago, including Haky Im on a variety of methods that we still really have fun working on and M. Eileen Dolan, together with Lois Travis at Indiana University, on pharmacogenomics studies of platinum in testicular cancer survivors. And I currently also have a really stimulating collaboration with Yun Li and colleagues at the University of North Carolina and Alex Reiner at the Fred Hutchinson Cancer Center as part of the PRIMED Consortium—my first collaboration with colleagues several generations younger than I. Finally, I owe deep thanks to my family. My daughters were slow to appreciate having an unconventional mom, but the travel opportunities eventually won them over. They are the joy of my life and my best genetic projects by far. My husband has been unfailingly supportive of my career in science and has attended more ASHG meetings than most members of the Society. I have always thought a life in academia is the perfect background for a happy family life—hugely satisfying work coupled with great flexibility and trainees who keep us young and in shape for parenting our offspring at home. It is, of course, barely controlled chaos when everything is working perfectly, and uncontrolled chaos most of the time, but I can live (happily) with that. In closing, I'd like to share a few thoughts with all of you future leaders in human genetics. The first ASHG meeting I attended was as a second-year grad student at the meeting in New York City in 1980. The ways human genetics has changed since that time is just remarkable. Even the most optimistic of us would never have imagined how rapidly technology would move the field and how much we would learn and do over the next 43 years. The video at the opening of the awards session really captured a lot of the excitement over many years in how human genetics has grown to be such a prominent part of biological sciences and now medicine. But one of the most surprising things that I think I have learned over that time is how much less deterministic and more complex human genetics is than we thought back then. For example, it is humbling to learn how many healthy people are carrying mutations that we once thought would inevitably lead to the development of a serious Mendelian disease. Similarly, the polygenic models supported by our current large-scale data on common disease are quite different from and more complex (more loci, smaller effect sizes, more sensitive to context) than the models of polygenic liability we were assuming (and regularly simulating) at the beginning of my career. Most dismaying, however, is that while we have indeed made real and substantial progress in discovery of genetic factors contributing to common human diseases, we still understand very little about how these variants drive the biology of common disease. I recently worked with NIH scientists as well as scientists from academia and industry to help plan a workshop on the genetic architecture of common human disease and was reminded of a much earlier NIH meeting on the same topic. Of all the things that we imagined back then that we would need to learn to better understand the genetic architecture of common diseases, it turns out that the things we now know that we needed to learn to understand the aspects of genetic architecture that still elude us to this day were not even on the agenda of that first meeting. We lacked the imagination to understand how little we knew and what large holes that the combination of ignorance and lack of imagination had left in our design plans for understanding genetic architecture. Even our grandest successes can serve to remind of how much less we know and understand than we think. For example, the GLP1R analogs and SGLT2 inhibitors now used to treat type 2 diabetes have turned out to be far more effective in improving health across multiple organ systems than were ever imagined during their development. Being able to hold opposing thoughts simultaneously is essentially a requirement in science. We are—and ought to be—awed by the progress in human genetics over the last half century. And we should simultaneously be all but certain that we do not understand perfectly (or maybe even at all) everything we think we do and have completely failed to imagine the pitfalls that await us as we keep trying to move our science forward. Human genetics is and always has been of great interest to the public, and we need to be more proactive in making sure that our discoveries are shared broadly with the larger community. The effort to explain complicated research that yields complex findings can lead easily to oversimplifications that do more harm than good. We also have to guard against the tendency of some parts of the press to sensationalize genetic results to appear more deterministic than our data can support. No one is in a better position than all of us in ASHG to make sure that our discoveries are placed in the right context and reported with all of the nuance that our science deserves.