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(http://www.niehs.nih.gov//portfolio/index.cfm?do=portfolio.grantdetail&&grant_number=K99ES035120&format=word)
| Principal Investigator: Rechtman, Elza | |
|---|---|
| Institute Receiving Award | Icahn School Of Medicine At Mount Sinai |
| Location | New York, NY |
| Grant Number | K99ES035120 |
| Funding Organization | National Institute of Environmental Health Sciences |
| Award Funding Period | 12 May 2023 to 30 Apr 2025 |
| DESCRIPTION (provided by applicant): | PROJECT SUMMARY I am a dually trained neuroscientist and environmental epidemiologist. My primary research interest is the impact of early life environmental exposures on the developing brain. The goal of this proposal is to gain training in biostatistics, epidemiology, and data science, supporting my transition into an independent transdisciplinary researcher in the emerging field of big-data environmental developmental neuroscience. I propose a novel application of the lagged weighted quantile sum (LWQS) regression to link temporally resolved air pollution (particulate matter < 2.5 µm; PM2.5) with diagnostic and transdiagnostic (multi-dimensional behavioral and neural changes) in children with autism spectrum disorder (ASD) and attention deficit hyperactivity disorder (ADHD). I leverage rich, existent behavioral and magnetic resonance imaging (MRI) phenotyping from a well-established big-data biobank, the Healthy Brain Network (HBN), along with a novel spatiotemporal model of weekly PM2.5 exposure. I hypothesize that higher PM2.5 exposure during critical windows of prenatal development is associated with increased ASD and ADHD diagnosis, and a transdiagnostic approach captures the population burden of exposure. In the K99 phase, I propose to uncover mechanistic links between prenatal ambient PM2.5 exposure and behavioral (Aim 1) and MRI (Aim 2) phenotypes in children with ASD and ADHD. In the R00 phase, I propose to acquire longitudinal behavioral and MRI data to examine associations between prenatal PM2.5 exposure on developmental trajectories (Aim 3). To achieve these scientific goals, I will obtain training and mentorship from an expert mentoring team with transdisciplinary expertise which will provide me with balanced training in both technical skills, and professional development. Technical skills will cover: 1) high dimensional longitudinal analytic approaches with Dr. Chris Gennings, 2) environmental developmental epidemiology with Dr. Megan Horton, and 3) processing of big-data MRI and behavioral datasets with Dr. Mike Milham. Dr. Horton will also lead my professional development skills training, including grant writing, project management, strategic planning to accomplish short- and long- term goals, maintaining scientific rigor and reproducibility, and cultivating a professional network. The proposed complementary training plan positions me to pioneer the use of big data to investigate the link between multidimensional exposures and behavioral and neuroimaging outcomes in typically and atypically developing children. My long-term career goal is to use big data to assess the impact of the changing climate on children’s brain and behavioral outcomes. I will use this K99/R00 as a foundation for a future R01 grant and career as an independent tenure-track faculty member. This application overcomes barriers in environmental developmental neuroscience thus advancing our ability to identify mechanisms underlying associations between climate- related environmental exposures and neurodevelopmental disorders. |
| Science Code(s)/Area of Science(s) |
Primary: 61 - Neurodevelopmental Secondary: 03 - Carcinogenesis/Cell Transformation |
| Publications | No publications associated with this grant |
| Program Officer | Cindy Lawler |