Gladstone data scientist elected to NATIO

Katie Pollard Gladstone Data Scientist

image: Katie Pollard is recognized by the National Academy of Medicine for discovering rapidly evolving regions of the human genome and for creating open source software used by scientists worldwide.
Opinion more

Credit: Photo: Michael Short / Gladstone Institutes

San Francisco, California – Data scientist and statistician Katie Pollard, Ph.D., He has been elected Director of the Gladstone Institute for Data Science and Biotechnology to the National Academy of Medicine (NAM), one of the highest honors in health and medicine. Through the election process, the Academy honors individuals who have demonstrated outstanding professional achievement and commitment to service.

Pollard is perhaps best known for developing a new statistical method to determine it accelerated human areas (HARs), They are stretches of DNA that changed rapidly when humans evolved from primate ancestors. Many of these regions of the human genome help determine when and where important genes—including those associated with disease—turn on or off.

Pollard has also been recognized for creating statistical models and open-source bioinformatics software, which researchers around the world use to investigate gene activity, genome evolution, and the microbiome (the group of microbes found in the human gut).

“As a statistician, I am honored that the National Academy of Medicine and my nominees appreciate our contributions — and the contributions of data scientists more broadly — to biomedical research and medicine,” Pollard says. “I love programming and math, but what really motivates me is using these methods to understand how our bodies work and how they cause disease to spread.”

Pollard, who is also a professor in the Department of Epidemiology and Biostatistics at UCSF and an investigator for the Chan Zuckerberg Biohub, attended graduate school at the University of California, Berkeley, with an interest in using mathematics and statistics for public health applications. She was transitioning from schoolwork to research when the human genome was first sequenced.

“I immediately became interested in using genome sequencing to measure differences in gene activity between tissues and disease states, such as in tumors versus adjacent healthy tissues,” she recalls. “I also wanted to develop statistical methods that could help me, and other researchers, obtain reliable results from the unprecedentedly large arrays of genomic data being produced.”

Since then, Pollard and her lab have made important contributions to many other areas of research, including deciphering how the genome works using comparative genomics; Create statistical models, open source bioinformatics software, and machine learning frameworks to better understand the human genome; and developing analytical tools to study the human microbiome.

Leading medical research using bioinformatics approaches

When Pollard began her post-doctoral work, the chimpanzee’s genome was sequenced. As she studied anthropology (including primates) as an undergraduate, she understood the importance of the new information and its potential applications, and performed one of the first genome-wide comparisons of human and chimpanzee DNA. This work led to the discovery of HARs.

“HARs are short pieces of DNA where chimpanzees and other non-human mammals have nearly identical sequences,” she explains. “But human HARs are very different from chimpanzees, which makes HARs exciting candidates for understanding the unique traits of humans, such as spoken language, susceptibility to HIV infection, and mental illness.”

After scientists have attempted to discover the function of HARs for nearly a decade, Pollard and her team have made significant advances using an innovative approach inspired by the fields of bioinformatics, stem cell biology and genomics.

They discovered that the vast majority of HARs are not genes, but rather “enhancers” that fluctuate the activity of neighboring genes up or down. They also found that many HARs control genes involved in brain development and in psychiatric diseases that are uniquely human, such as autism and schizophrenia.

In parallel, Pollard’s team over the past 15 years has developed new methods for analyzing the hundreds of species of microbes that grow within the human gut, and which play many roles in health and disease. Their breakthroughs could lead to the development of treatments to maintain or improve gut health. They also help pave the way for the use of the microbiome in precision medicine.

“To make these discoveries, we first had to create the right bioinformatics tools to address the questions we wanted to answer,” Pollard says. We then applied our tools to massive analyzes of terabytes of publicly available data, and collected data sets that were not originally collected for the same purpose. And we used these data sets to ask new questions that go beyond what was analyzed in the original studies.”

It helped create several computational approaches to better analyze typical data sets, including an approach that allows researchers to perform larger and more accurate analyzes of the microbiome than ever before. Their approaches are also faster and cheaper than previous technologies, which puts them within reach of most labs — not just those that can withstand high-performance computing power.

For Pollard, this is one of the most important aspects of technology development: creating tools that can be shared with as many scientists and students as possible and used. That’s why she is a strong advocate of open science, and a world leader in open source bioinformatics software.

“The machine learning tools and statistical methods we develop can be used to study a wide range of diseases,” Pollard says. “It’s important to me that it can be made available to anyone who needs it, so that we can open the door to important discoveries to researchers around the world, across a variety of fields.”

Expanding the role of data science

Looking to the future, Pollard would like to help expand the role of data science in modern biomedical research. Instead of her current job of supporting the analysis of empirical research that has already been done, she would like to see that Data science sets the direction for experimentation and technology development.

“What makes me happy is the use of predictive models to run experiments and develop new tools and technologies,” she says. “Having data scientists in the driver’s seat will also ensure that we design experiments and machines that best address the questions we want to ask in the future.”

Pollard received her bachelor’s degree from Pomona College and her master’s and doctoral degrees in biostatistics from the University of California, Berkeley. She is a fellow of the American Institute of Biomedical Engineering, the California Academy of Sciences, and the International Society for Computational Biology. She is also a member of the American Society of Human Genetics and the American Statistical Society.

Pollard’s election was announced on October 17, 2022, by the Non-Aligned Movement, part of the Congress-sanctioned National Academy of Sciences – a group of private, nonprofit foundations that provide objective advice on science, technology, and health matters.

Pollard joins seven fellow NAM members from the Gladstone Institutes: Jennifer Doudna, Ph.D., great detective Warner Green, MD, PhD, great detective Robert W Mahley, MD, PhD, chief investigator, chief emeritus and founder of Gladstone; Lennart Mok, MD, Senior Investigator and Director of the Gladstone Institute of Neurological Diseases; Deepak Srivastava, MD, Chief investigator and chief of Gladstone. R. Sanders Williams, MD, former president of Gladstone Corporation; And the Shinya Yamanaka, MD, PhD, Senior investigator.

Leave a Comment