Alcohol use and smoking during pregnancy often occur in the context of maternal anxiety and depression. However, little is known regarding how various combinations of maternal alcohol consumption, smoking, and psychiatric symptoms interact to alter early central and autonomic nervous system (CNS, ANS) development and, in turn, how these changes underlie long-term neurobehavioral outcomes. The overall goals of the project are to a) comprehensively characterize maternal drinking, smoking, depression, and anxiety during pregnancy; b) perform deep phenotyping of electrocortical and physiological data from infants; c) relate maternal prenatal exposure clusters to deep phenotyping of CNS/ANS function and neurobehavioral outcomes; d) test the hypothesis that these measures mediate relationships between maternal prenatal exposures and subsequent child neurodevelopmental outcomes. To accomplish these goals, we will use existing data from an extensive study of mother-infant dyads recruited for the completed Safe Passage Study from recently completed follow-up studies which enrolled subsets of the PASS participants at 1 and 3 years of age. PASS participants were from geographically and socio-economically diverse regions in South Africa (SA) and the Northern Plains of the United States (US). The student(s) will be required to rapidly become familiar with a variety of data types, e.g., questionnaire data, physiological high-dimensional signals, neurobehavioral clinical examinations, neurodevelopmental assessments, etc. From a methodological point of view, the student(s) will support the development of: i) pipelines for the standardized and automated preprocessing and cleaning of physiological signals; ii) machine learning techniques (data-drive clustering, prediction) and iii) advanced statistical methodologies (inference, mediation, multidimensional data integration) tailored to the data available in this project. The student(s) will join a young and highly dynamic multidisciplinary team of experts, students, and RAs (some who originally joined the lab as DSI-students).

Continue reading

Cardiovascular disease is the leading cause of death in women. There are risk factors specific to women such as pregnancy complications and menopausal status that may play a role in the development of cardiovascular disease in women. The American Heart Association (AHA) recently launched the Research Goes Red registry in collaboration with Verily’s Project Baseline. Verily is a corporation owned by Alphabet (Google’s parent company). The Research Goes Red registry is a novel online platform designed to be participant-focused. Dr. Brooke Aggarwal is Principal Investigator of the Research Goes Red Weight Study, a new 1-year prospective observational study to determine links between weight changes and novel physiologic and behavioral outcomes related to cardiovascular disease in women. The study, a collaboration between AHA and Verily, is conducted primarily remotely. Online questionnaires are completed via an app, and tailored to optimize the experience for research participants. Participants log their waist circumference, body composition via scale, and home blood pressure via the app. An in-person visit to a local LabCorp facility is required to obtain blood samples and blood pressure measurements. All data is synced into the AHA-Verily online platform for the study team to download files with coded data, in real-time. This study is the first of its kind to demonstrate the feasibility of collecting data from the Research Goes Red registry in a decentralized way. We have a rich dataset ready to be analyzed among 300 women across the US, including markers associated with adverse weight gain: body composition, glucose, lipids, insulin resistance, inflammation (C-reactive protein, interleukin-6), as well as correlates of weight gain during the menopausal transition including meal timing, meal frequency, reproductive history, physical activity, perceived stress, and sleep patterns.

Continue reading

Cardiovascular disease remains the leading cause of death in women. There are risk factors specific to women such as pregnancy complications, menopausal status, emotional stress, and sleep quality which play a role in the development of cardiovascular disease in women. In 2019, the American Heart Association (AHA) launched the Research Goes Red registry in collaboration with Verily’s Project Baseline. Verily is a corporation owned by Alphabet (Google’s parent company). The Research Goes Red registry is a novel online platform designed to be participant-centric and highly customizable and scalable. Dr. Brooke Aggarwal is Principal Investigator of the Research Goes Red Weight Study, a new 1-year prospective observational study to determine links between weight changes and novel physiologic and behavioral outcomes related to cardiovascular disease in women. The study, a collaboration between AHA and Verily, is conducted primarily remotely; online questionnaires are completed via the Trialkit app, developed and tailored to optimize the experience for research participants. Participants log their waist circumference, body composition via scale, and home blood pressure via the app. An in-person visit to a local LabCorp facility is required to obtain blood samples and blood pressure measurements. All data and electronic consents collected on the Trialkit app are synced into the AHA-Verily online platform for the study team to download files with coded data, in real-time. This study is the first of its kind to demonstrate the feasibility of collecting data from the Research Goes Red registry in a decentralized way. We have a rich dataset ready to be analyzed among 300 women across the US, including markers associated with adverse weight gain: body composition, glucose, lipids, insulin resistance, inflammation (C-reactive protein, interleukin-6), as well as correlates of weight gain during the menopausal transition including meal timing, meal frequency, reproductive history, physical activity, perceived stress, and sleep patterns.

Continue reading

Background: Genomes are inextricably tied to life as we know it, encoding all the molecular information used by organisms. Next-generation DNA sequencing has resulted in the scalable reading of genomes from organisms that inhabit complex environments - rather than being limited to organisms typically studied in the lab. Alongside this, algorithmic development is beginning to reveal the complex biology of genomes.

Continue reading

Despite identification of modifiable behavioral targets for childhood obesity prevention, prevalence of obesity remains historically high in the United States and the most severe forms are increasing among young children. Disparities in obesity have been exacerbated in the wake of the COVID-19 pandemic. The goal of this project is to examine the effects of social needs (eg food insecurity, housing needs), neighborhood factors, and use of social service referrals on childhood obesity before and after COVID-19. The data scholar will gain hands-on experience with data cleaning, merging, and visualizations. If appropriate to skill level, checking code and conducting analytic tests may be part of the learning experience. Opportunities for abstract and manuscript co-authorship may be possible for exceptional Scholars.

Continue reading

In this project, we aim to develop GAN based models to predict spatio-temporal evolution using open human mobility datasets – SafeGraph (https://www.safegraph.com/).

Continue reading

In this project, we aim to develop GAN based models to predict spatio-temporal evolution using open human mobility datasets – SafeGraph (https://www.safegraph.com/).

Continue reading