We collaborate with scientists on a broad range of innovative research. We are continually growing relationships with the broader community, including higher education, business and government organizations—all to help facilitate the process of discovery.
Here is a selection of some of the projects that we are involved in:
Children’s Health Exposure Analysis Resource Data Center
In 2015, the Icahn School of Medicine at Mount Sinai was named by the National Institute of Environmental Health Sciences to provide the home for a data center for environmental and genetic factors influencing children’s health. Patricia Kovatch, Senior Associate Dean, is the Director for the Data Repository and Management Core for the Children’s Health Exposure and Analysis Resource (CHEAR). CHEAR’s goal is to advance the “exposome” concept in children’s health studies. An exposome can be defined as the measure of all the exposures of an individual from the womb throughout his or her lifetime. Influences can be genetic, environmental or occupational. The CHEAR Data Center provides the capacity and capability to correlate these vast, multi-layered data sources. Our expertise includes creating ontologies to enable researchers to harmonize data from different data sets. The overarching goal is to help researchers better understand the influences of environmental and genetic factors on children’s health.
To date, CHEAR has supported more than 30 children’s health studies in which nearly 50,000 samples were analyzed for a broad range of environmental exposures and associated biological responses. Health outcomes explored through CHEAR include asthma, diabetes, autism, and obesity. (S. Teitelbaum, PI)
Department of Genetics and Genomic Sciences
Scientific Computing provided computational resources and staff expertise for research into genetic factors influencing Alzheimer’s disease. Researchers at the Department of Genetics and Genomic Sciences at the Icahn School of Medicine at Mount Sinai were able to use deep sequencing to identify sources of variation in mRNA splicing in the aging brain of 450 subjects. Even though the sequencing accuracy for each individual nucleotide is very high, the very large number of nucleotides in the genome means that if an individual genome is only sequenced once, there will be a significant number of sequencing errors. By applying state-of-the-art analytic methods, they were able to generate a comprehensive genome-wide map of splicing variation in the aging prefrontal cortex. Overall, the study provides evidence that dysregulation of mRNA splicing is a feature of Alzheimer’s disease and is, in some cases, genetically driven.
Community Research Education and Engagement for Data Science
We have continually sought to reach out to the communities we serve in order to raise the awareness and expertise in big data sets and tools. One of our initiatives in the past was the Community Research and Education and Engagement for Data Science (CREEDS). This effort had several components:
- We hosted 150 graduate students for intensive, two-week summer sessions
- We mentored another 30 NYC-based graduate students in their participation in DREAM challenge teams which solved difficult, real-life biomedical problems.
As part of this program, we also sought to increase diversity within the field of data science by reaching out to organizations which serve underrepresented groups to boost participation within this exciting, fast-paced field. (P. Kovatch, PI; A. Sharp, PI; L. Claudio, PI)
A New Disease Platform Leveraging Complex Drosophila and Mammalian Models
The objective of this proposal is to develop a platform and pipeline that can be adapted to a broad range of genetic-based diseases. We will build ‘fly avatar’ models that reflect the genetic complexity of RASopathy and colorectal cancer patients. We will then use stem cell approaches to explore the most promising leads in a human cell context. Once these therapies are developed, we will use them as a platform to screen for patient-matched personalized therapeutics, as well as offer a readily accessible standard operating procedure to the applied science community. (R. Cagan, PI)
GeNYC: Genomic Implementation Research in the Diverse Settings and Populations of New York City
The goal of this collaborative effort is to bring the promise of genomic medicine to diverse populations and the clinicians who care for them. By engaging diverse stakeholders, including researchers, patients, clinicians, and advocates through the creation of a Genomics Stakeholder Board, researchers are harnessing expertise within New York City to conduct genomics implementation research. Central to this effort is a multi-site pragmatic clinical trial (PCT) to study effects and challenges of incorporating genetic risk information into primary care. The team is conducting clinical trials in diverse populations, including one with >2000 African ancestry patients with high genetic risk for CKD. The aim is to implement genomic medicine trials in NYC and study risk-informed disease management in multi-ancestry populations and diverse practices. (C. Horowitz, PI)
MSHS Translational Science Hub
ConduITS, the Institutes for Translational Sciences at Icahn School of Medicine at Mount Sinai (ISMMS), was established in 2009 when ISMMS received a prestigious Clinical and Translational Science Award (CTSA) from the National Institutes of Health (NIH). ConduITS’ long-term goal is to transform the vast resources of the Mount Sinai Health System into a translational research laboratory. This multi-disciplinary hub encompasses partnering with our community patients and physicians, health system clinicians, institutional and affiliate scientists, and investigators at other CTSA Network Hubs to ensure the highest quality research, promotion of team science, education of translational investigators, and development of unique, innovative resources. The hub will serve as a catalyst for the translation of biomedical discoveries into better health across the “lifespan,” from pediatric to geriatric medicine. (R. Wright, PI)
The Autism Sequencing Consortium
The new research in this proposal will accelerate the identification of autism spectrum disorder (ASD) genes, thereby facilitating our long-term goal of building the foundation from which therapeutic targets for ASD emerge. Our rationale is that the identification of genes conferring significant risk to ASD and associated neurodevelopmental disorders can form the basis of studies to understand ASD neurobiology as well the basis for novel therapies. (J. Buxbaum, PI)
Incorporating Genomics into the Clinical Care of Diverse NYC children
We propose a new Clinical Sequencing Evidence-Generating Research (CSER) site, NYCKidSeq, to advance the implementation of genomic medicine in children from under-represented minority populations in Harlem and the Bronx. The NYCKidSeq program will assess the clinical utility of genomic medicine in three broad areas of pediatric disorders, while engaging a range of providers and community members to overcome the well-documented barriers to inclusion of under-served and under-represented populations in genomic research. This research will test, analyze, and implement web-based technologies to enhance education and counseling about genomic medicine, and communicate findings to careers at all levels of expertise, in two health systems, in a clinically useful, technologically savvy, culturally sensitive, and ethically sound manner. (E. Kenny, PI)
High-Dimensional Immune Monitoring of NCI-Supported Immunotherapy Trials
Immunotherapy is transforming decades of clinical practice in cancer care, but it also comes with new questions about understanding mechanisms of action contributing to both antitumor activity and potential associated toxicity. Most importantly, identifying why only a fraction of patients derives clinical benefit is at the forefront of future developments, with the validation of useful clinical biomarkers as the ultimate goal. Through a comprehensive array of assays and analytical tools that bridge innovation and standardization, the Mount Sinai Cancer Immune Monitoring and Analysis Center (MS-CIMAC) intends to pursue the following three aims: a) help characterize immune-competence at baseline and assess global immune changes during treatment, b) drill down the specificity and quality of immune responses for mechanistic evaluation of drugs, and c) automate, optimize, and integrate analyses of resulting datasets to facilitate sharing, and to ultimately discover composite immune biomarkers that will impact clinical cancer care. (S. Gnjatic, PI)