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One of the immune system’s oldest branches, called complement, may be influencing the severity of COVID disease, according to a new study from Drs. Sagi Shapira and Nicholas Tatonetti at the Department of Systems Biology.

Drs. Sagi Shapira (right) and Nick Tatonetti
Drs. Nicholas Tatonetti (left) and Sagi Shapira

Among other findings linking complement to COVID, the researchers found that people with age-related macular degeneration—a disorder caused by overactive complement—are at greater risk of developing severe complications and dying from COVID.

The connection with complement suggests that existing drugs that inhibit the complement system could help treat patients with severe COVID-19.

The study was published in Nature Medicine . For the full article , visit the Columbia University Irving Medical Center Newsroom. 

Sagi Shapira,PhD, assistant professor of systems biology at Columbia’s Vagelos College of Physicians & Surgeons and Nicholas Tatonetti, PhD, associate professor of bioinformatics and of systems biology at VP&S, have recently been awarded a new pilot grant to support their collaboration in COVID-19 research.

Drs. Shapira and Tatonetti are one of three teams who have been awarded a COVID-19 research pilot grant from the Herbert Irving Comprehensive Cancer Center. The pair will work on accurately identifying pathophysiological factors that modulate SARS-CoV-2 infection and explain variability in disease outcomes.

Read the full article here

Yufeng Shen , PhD, found his passion for science in childhood, but he developed a fascination for both math and physics as his education progressed. In an earlier generation, he would have needed to choose between divergent paths. Instead, he chased his calling within an important emerging discipline. 

Yufeng Shen, PhD
Dr. Yufeng Shen

Dr. Shen was awarded tenure and promoted to the rank of associate professor in Columbia University's Departments of Systems Biology and Biomedical Informatics (DBMI) last summer. Utilizing new methods, he answers long-standing questions that impact health. Specifically, his research has focused on discovering novel genetic variants that cause human diseases.

His current work focuses on developing new computational methods to interpret genome data, identifying genetic causes of human diseases by integrating multiple types of genomic data, and modeling of immune cell populations. That research has led to important findings, including his work on the Deep Genetic Connection between Cancer and Developmental Disorders , published in Human Mutation.

Using innovative sequencing techniques from published studies of cancer and developmental disorders, Dr. Shen and his students identified a significant number of genes implicated in both diseases.

“This project allows us to use the larger cancer data to inform analysis in genetic variations of developmental disorders, and to find new risk genes and new risk variance,” he said. “It also provides a new perspective on how to optimize care for kids with developmental disorders. There is probably two to three times more risk of developing cancer for kids with developmental disorders than otherwise healthy kids.”

December 10, 2019

Highly Cited Researchers

Raul Rabadan Highly Cited
Raul Rabadan, PhD, (standing) with Francesco Brundu, postdoctoral research scientist in the Rabadan lab (Credit: Jeffrey Schifman)

Congratulations to Drs. Raul Rabadan and Xuebing Wu who were recently named a Highly Cited Researcher, according to the 2019 list from the Web of Science Group . Overall, Columbia University ranked 15th on the list of global institutions, with a total of 47 Highly Cited Researchers.

The Highly Cited Researchers list, which was released Nov. 19,  identifies scientists and social scientists who have produced multiple papers ranking in the top 1% by citations for their field and year of publication, demonstrating significant research influence among their peers.

Xuebing Wu, PhD
Xuebing Wu, PhD

Dr. Rabadan is professor of systems biology , with a joint appointment in biomedical informatics, at Columbia’s Vagelos College of Physicians and Surgeons . At Columbia, the Rabadan lab consists of an interdisciplinary team developing mathematical and computational tools to extract useful biological information from large data sets. In 2017, Dr. Rabadan established the Program for Mathematical Genomics , a multidisciplinary research hub that brings together researchers from the fields of mathematics, physics, computer science, engineering, and medicine, with the common goal of solving pressing biomedical problems through quantitative methods and analyses. He also serves as program lead for the Cancer Genomics and Epigenomics Program at the Herbert Irving Comprehensive Cancer Center at NYP/Columbia. 

Congenital diaphragmatic hernia (CDH) is a severe birth defect. For babies born with CDH, their diaphragms are not developed properly, with some or all parts of the abdominal organs pushed into the chest. The displacement of these critical organs can have a significant impact on how the lungs develop and grow. 

Dr. Yufeng Shen
Yufeng Shen, PhD, associate professor of systems biology

A recent study , led by Yufeng Shen , PhD, and Wendy Chung , MD, PhD, and their labs at Columbia University Irving Medical Center , investigated the genetic risk factors linked to CDH and analyzed data from whole genome sequencing and exome sequencing to determine novel mutations. The study also uncovered the link between CDH and additional developmental disorders. 

“Many babies with this birth defect also have lung hypoplasia or pulmonary hypertension and babies have difficulty breathing. Even with advanced care available, the mortality rate is still about 20 percent,” says Dr. Shen, associate professor of systems biology at Columbia, with a joint appointment in the Department of Biomedical Informatics

“One hypothesis is that the lung condition is not necessarily caused by the physical compression on the developing lungs in the chest,” explains Dr. Shen, “it can be caused by the same genetic defect that causes CDH. Finding those genes is absolutely necessary to improve care and develop effective treatment in the long run.”   

Scientists have been aiming to identify new risk genes in CDH—and other developmental disorders—with  the hope that with improved genetic diagnosis more tailored or long-term care for patients born with this defect could be provided, as well as potential targets for intervention down the road. 

Nicholas Tatonetti, PhD
Nicholas Tatonetti, Phd

Nicholas Tatonetti , PhD, solves problems. He has always enjoyed it, and as the informatics community has discovered, he is both creative and proficient in his methods.

Dr. Tatonetti, who was recently awarded tenure and promoted to the rank of Associate Professor in the Columbia Department of Biomedical Informatics (DBMI) and Department of Systems Biology , focuses on the use of advanced data science methods, including artificial intelligence and machine learning, to investigate medicine safety. Using emerging resources, such as electronic health records (EHR) and genomics databases, his lab is working to identify for whom these drugs will be safe and effective and for whom they will not.

His path to Columbia wasn’t a traditional one, but that fits his work. Since joining in 2012, Dr. Tatonetti has used non-traditional thinking to benefit both health and healthcare.

Utilizing both data mining of medical records and prospective lab experiments, Dr. Tatonetti created a methodology for both finding and validating adverse drug reactions and drug-drug interactions. During a two-year collaboration with Pulitzer Prize-winning journalist Sam Roe of the Chicago Tribune , Dr. Tatonetti discovered that the drugs ceftriaxone and lansoprazole, when taken together, induces an arrhythmia in the heart.

The data mining identified adverse effects, while the lab experiments established causality. Dr. Tatonetti wasn’t specifically looking for a negative reaction of those particular drugs; he had no reason to suspect them.

“We are able to find things that nobody expects to happen because the world of hypotheses we consider is basically everything,” he said. “We consider every possible combination, a type of analysis that would be impossible without a huge data set and significant computational power.”

Newly Tenured Faculty
Awarded tenure this year in the Department of Systems Biology, left to right: Dr. Nicholas Tatonetti, Dr. Yufeng Shen, and Dr. Chaolin Zhang.

Congratulations to Drs. Yufeng Shen, Nicholas Tatonetti, and Chaolin Zhang of the Department of Systems Biology, who have been awarded tenure and promoted to associate professor. Their new appointments are effective July 1, 2019. 

Yufeng Shen, PhD

Dr. Shen joined Columbia University Irving Medical Center in 2011 as an Assistant Professor in Systems Biology and Biomedical Informatics. He directs a research group focused on studies of human biology and diseases using genomic and computational approaches. They are developing new methods to interpret genomic variations by machine learning based on biological mechanisms, and using these methods in large-scale genome sequencing studies to identify new genetic causes of human diseases, such as autism, birth defects, and cancer. His group also works on modeling of clonal and transcriptional dynamics of immune cells to improve our understanding of human adaptive immune system under normal and clinical conditions. Dr. Shen serves as an Associate Director of the JP Sulzberger Columbia Genome Center, a member of the Program in Mathematical Genomics, and an adjunct member of Columbia Center for Translational Immunology. 

Nicholas Tatonetti, PhD

Dr. Tatonetti, whose primary appointment is in the Department of Bioinformatics, has an interdisciplinary appointment with both the Departments of Systems Biology and Medicine. Dr. Tatonetti’s lab specializes in advancing the application of data science in biology and health science. His group integrates their medical observations with systems and chemical biology models to not only explain drug effects, but also to gain further understanding of basic biology and human disease.

Columbia researchers have learned why some glioblastomas—the most common type of brain cancer—respond to immunotherapy. The findings, reported by the CUIMC Newsroom, could help identify patients who are most likely to benefit from treatment with immunotherapy drugs and lead to the development of more broadly effective treatments.

The study, led by Raul Rabadan, PhD, professor of systems biology and biomedical informatics at Columbia University Vagelos College of Physicians and Surgeons and the Herbert Irving Comprehensive Cancer Center, was published online in the journal Nature Medicine

Fewer than 1 in 10 patients with glioblastoma­ respond to immunotherapy, which has shown remarkable success in the past few years in treating a variety of aggressive cancers. But there has been no way to know in advance which glioblastoma patients will respond. Like many other cancers, glioblastomas are able to prevent the immune system from attacking cancer cells. Cancers sometimes put the brakes on the immune system by acting on a protein called PD-1. Immunotherapy drugs called PD-1 inhibitors are designed to release those brakes, unleashing the immune system. Given the success of PD-1 inhibitors in other cancers, doctors were hopeful that the immunotherapy drugs would help patients with glioblastoma. 

To understand why only a few of these tumors respond to the immunotherapy drugs, Dr. Rabadan’s team took a comprehensive look at the tumor microenvironment—which includes the tumor itself and all of the cells that support it—in 66 glioblastoma patients before and after treatment with PD-1 inhibitors (nivolumab or pembrolizumab). Of these, 17 had a response to the drugs of six months or longer.

Nonresponsive tumors had more mutations in a gene called PTEN, which led to higher levels of macrophages, immune cells that usually help the body fight bacteria and other invaders. But in glioblastoma, the macrophages release a number of growth factors that promote the survival and spread of cancer cells.

Tatonetti Heritability Image

Each subgraph in this image is a family reconstructed from EHR data: Each node represents an individual and the colors represent different health conditions. (Figure: Nicholas Tatonetti, PhD, Columbia University Vagelos College of Physicians and Surgeons).

Acne is highly heritable, passed down through families via genes, but anxiety appears more strongly linked to environmental causes, according to a new study that analyzed data from millions of electronic health records to estimate the heritability of hundreds of different traits and conditions. 

As reported by the Columbia Newsroom, the findings, published in Cell by researchers at Columbia University Irving Medical Center and NewYork-Presbyterian could streamline efforts to understand and mitigate disease risk—especially for diseases with no known disease-associated genes.

“Knowledge of a condition’s heritability—how much the condition’s variability can be attributed to genes—is essential for understanding the biological causes of the disease and for precision medicine,” says study co-leader Nicholas Tatonetti, PhD , the Herbert Irving Assistant Professor of Biomedical Informatics at Columbia University Vagelos College of Physicians and Surgeons and an assistant professor of systems biology. “It is clinically useful for estimating disease risk, customizing treatment, and tailoring patient care.”

May 7, 2018

From Code to Cure

Columbia Magazine

Published Spring 2018 cover story , Columbia Magazine

As reported by David J. Craig, senior editor at Columbia Magazine , we are living in the age of big data, and with every link we click, every message we send, and every movement we make, we generate torrents of information. In the past two years, the world has produced more than 90 percent of all the digital data that has ever been created. New technologies churn out an estimated 2.5 quintillion bytes per day. 

Today, researchers at Columbia University Irving Medical Center (CUIMC) are using the power of data to identify previously unrecognized drug side effects; they are predicting outbreaks of infectious diseases by monitoring Google search queries and social-media activity; and they are developing novel cancer treatments by using predictive analytics to model the internal dynamics of diseased cells. These ambitious projects, many of which involve large interdisciplinary teams of computer scientists, engineers, statisticians, and physicians, represent the future of academic research.

Craig covers Dr. Nicholas Tatonetti's work involving prescription drug safety and his innovative use of digital health and clinical records and Dr. Andrea Califano's unconventional computational approaches in advancing cancer research.

To read the full article , visit the online issue of Columbia Magazine

Faculty

Dennis Vitkup

Associate Professor, Department of Systems Biology
Associate Professor, Department of Systems Biology

Faculty

Nicholas Tatonetti

Associate Professor of Biomedical Informatics (in Systems Biology and in Medicine)

Associate Professor of Biomedical Informatics (in Systems Biology and in Medicine)

Faculty

Yufeng Shen

Associate Professor, Department of Systems Biology
Associate Director

Faculty

Raul Rabadan

Gerald and Janet Carrus Professor
Professor, Department of Systems Biology

Co-director, Next-Generation Sequencing

Faculty

Aris Floratos

Executive Research Director, Center for Computational Biology and Bioinformatics
Executive Research Director, Center for Computational Biology and Bioinformatics

Faculty

Andrea Califano

Chair, Department of Systems Biology
Director, JP Sulzberger Columbia Genome Center