Most people think of illness in a binary way: a patient is either sick or well. But scientists have found a more nuanced reality. “Looking beneath the data in medical records, at health information across millions of patients, we have found a large spectrum of disease and disease risk that can inform individualized treatment plans in a more sophisticated and tailored way than the ‘one size fits all’ paradigm of today,” says Eric Schadt, the founder and CEO of Sema4, a patient-centered predictive health company.

A big data-driven approach to medicine could help researchers assess underlying mechanisms of disease, develop accurate diagnostics for the early identification or prevention of disease, and match optimal treatments to patients based on their disease, history, and environment.

“The current health care systems, including large hospitals and physician networks, are not well enough equipped to provide this type of approach yet—but they soon could be,” Schadt says.

Over the past few years, the Mount Sinai Health System in New York City has created several entities to advance the growing field of precision medicine, including the Institute for Next Generation Healthcare and its Lab100, a hybrid clinic and research lab, and Schadt’s own Sema4, which was spun out from Mount Sinai in 2017.

With access to new capabilities in gene sequencing, RNA analysis, supercomputing, bioinformatics, and pharmacogenetics, researchers at Mount Sinai now regularly work across groups and departments to advance health care both at a population level and a personal one.

Mount Sinai’s Alan Copperman explains how doctors are now using precision medicine techniques to help overcome infertility and hereditary disease. Credit: Mount Sinai Health System

Harnessing Big Data

Sema4 was founded to bring precision medicine to health care systems. The idea was to bring teams of scientists, data engineers, and clinicians to work together to advance precision medicine approaches, says Schadt, who is also Dean for Precision Medicine at the Icahn School of Medicine at Mount Sinai.

The researchers at Sema4 in 2015 carried out the first study to sequence a human diploid genome, using what are known as long-read DNA sequencing technologies. It delivered the highest-quality reference genome at the time it was published. The team also presented one of the first holistic molecular models for Alzheimer’s disease, which demonstrated the complex interactions of thousands of genes in combination with environmental factors, providing novel insights into potential new gene therapies to be explored in clinical trials.

A different group at Sema4 has developed, and conducts, unique noninvasive genetics tests for oncology and reproductive health. In August 2018, the company announced two new reproductive health tests developed with an informatics-driven approach using the Sema4 Health Intelligence Platform (SHIP). The company’s tests include the only noninvasive prenatal test that routinely screens for trisomy 15 to aid in detection of Prader-Willi and Angelman syndromes, genetic disorders that can cause severe developmental delays, and a new screen that improves detection rates for genes traditionally difficult to sequence, including CYP21A2 (in which mutations cause growth and development problems related to adrenal disorders) and GBA (in which mutations cause Gaucher disease, with liver disorders, bone pain, and anemia).

“We help develop decision-support tools so patients understand what this information means in the context of themselves, their families, and their family-building goals,” says Alan B. Copperman, director of the Division of Reproductive Endocrinology and Infertility, Icahn School of Medicine at Mount Sinai, and chief medical officer of Sema4. And when the tests are used in connection with in vitro fertilization, “we can use the information to probe the embryos and figure out which embryo from a cohort is most likely to implant and become a healthy baby.”

At Mount Sinai’s Lab100, clinicians and physicians are exploring the use of virtual reality, body scanning and cognition tests to redesign the standard physical. Credit: Mount Sinai Health System

Collaboration as Clinical Tool

Doctors and researchers are now certain that advances in health care will rely on a cross-disciplinary approach, and the doctors at the seven Mount Sinai hospitals routinely work closely with researchers from the Icahn School of Medicine at Mount Sinai.

In a recent study, a team led by Joel Dudley, director of the Institute for Next Generation Healthcare, and Samir Parekh, Associate Professor of Medicine (Hematology, and Medical Oncology), used advanced computer analytics to treat blood and bone marrow cancers, focusing on multiple myeloma. While solid tumors can often be typed with DNA analysis, these cancers are typically too heterogeneous for that approach.

The Institute created a sophisticated software program called DAPHNE that uses machine learning to decipher the RNA of multiple myeloma cancer cells, revealing complex molecular disease patterns far beyond what DNA analysis alone could show. Together, myeloma specialists and genomics scientists then identified non-myeloma drugs that could be repurposed to help patients whose disease had relapsed despite having FDA-approved treatments. Twenty-six patients received the treatments that were recommended, and of those, 16 saw their disease markers reduced by 25 percent or more.

Mount Sinai has further strengthened its efforts in this area with the hiring of Adam Margolin, PhD, a leader in developing machine learning algorithms to analyze large-scale molecular datasets, as director of the Icahn Institute of Genomics and Multiscale Biology.

Addressing common diseases, such as inflammatory bowel disease (IBD), which affects three million Americans, is another of Mount Sinai’s priorities. Judy H. Cho, MD, director of the Institute for Personalized Medicine, Icahn School of Medicine, notes that “IBD is a polygenic disease, meaning that many genes and genomic regions contribute to susceptibility.”  

Currently, IBD is diagnosed only after ruling out other possible causes for a patient’s symptoms, which can include intense abdominal pain, fatigue, and weight loss. Dr. Cho’s research has contributed to defining the pathophysiologic mechanisms of IBD by identifying its associations to NOD2, IL23R, and more than 200 genetic loci. With the wealth of such genetic discovery, now the goal is early and precise detection, she says.

The future of health care will depend on harnessing genetic and personalized information, and it is already improving the wellbeing of many, says Copperman. “By assembling information about a patient’s genes, environmental exposures, and clinical history, we can truly practice generational health, and impact the lives of our patients, their children, and their children’s children.”

To learn more about how scientists are translating research into life-changing treatments, visit the New Heights in Medicine.