Pitt Psychiatry Awarded $17.8M National Institute of Mental Health U01 Grant Focused on Sleep and Pediatric Mental Health
The National Institute of Mental Health has awarded Pitt Psychiatry a multi-PI, multi-site U01 award focused on applying computational methods to identify sleep signatures predictive of mental health outcomes among youth engaged in pediatric primary care.
The Pediatric Precision Sleep Network (PPSN) will be led by contact principal investigator Adriane Soehner, PhD (Associate Professor of Psychiatry), and multiple principal investigators Meredith Wallace, PhD (Associate Professor of Psychiatry and Biostatistics), from Pitt Psychiatry, along with Maria Jalbrzikowski, PhD (Boston Children’s Hospital/Harvard Medical School), and Dana McMakin, PhD (Florida International University).
The Pediatric Precision Sleep Network
The transition from childhood to adolescence can yield an escalation in mental health risk, with peri-adolescence (ages 10-13) as a crucial window for early detection and intervention. Over half of peri-adolescent children experience unhealthy sleep patterns, and sleep problems during this period prospectively predict negative mental health outcomes more strongly than at other times in development. Despite significant advances in our understanding of sleep health, our ability to use sleep data to identify the youth who are at greatest risk for developing negative mental health outcomes is exceedingly limited because: (1) the heterogeneity of sleep characteristics hinders the differentiation of normative versus at-risk sleep patterns; (2) the multidimensionality and multimodality of sleep data has led to inconsistencies regarding which particular features and modalities are critical for screening; and (3) until recently, it has been impossible to capture crucial behavioral and physiological measures of habitual sleep in sufficiently large samples.
To address these challenges, the PPSN will recruit a diverse sample of 1,200 youth (ages 10-13 years old) who have not developed severe mental health diagnoses, at three sites (Pittsburgh, Miami, and Boston). The study will leverage multiple data types and advanced computational methods to identify sleep signatures, link these signatures to prospective changes in transdiagnostic mental health, and develop sleep-informed transdiagnostic mental health screening algorithms. Moreover, the PPSN will coordinate with the NIMH IMPACT-MH Data Coordinating Center to share data and processing pipelines with the broader scientific community.
The University of Pittsburgh MPIs
Trained as a clinical psychologist and affective neuroscientist, Dr. Soehner has focused her research career across neurodevelopment, sleep, and mood disorders. She uses novel statistical and experimental methodologies to answer critical questions about the role of sleep-circadian processes in emotion regulation and dysfunction in youth and young adults, with the goal of elucidating treatment targets for sleep and circadian health during sensitive developmental periods.
“We are so excited to have the opportunity to contribute to National Institute of Mental Health’s IMPACT-MH initiative, which supports projects that use behavioral assessments to augment standard clinical data to improve prediction of mental health outcomes,” said Dr. Soehner. “With our colleagues in Boston and Miami, our goal is to leverage low-burden wearable and smartphone technologies to comprehensively assess sleep at a large scale and, ultimately, develop algorithms that help clinicians more easily identify sleep signatures most crucial to mental health risk in adolescents.”
Trained in both psychiatry research and biostatistics, Dr. Wallace is a leading investigator in the emerging field of multidimensional sleep health, supplemented by methodological innovations related to clustering and optimal combined moderators for personalized treatment. By incorporating novel statistical methods, such as the application of machine learning to high-dimensional datasets, Dr. Wallace has advanced personalized medicine research, and contributed critical insights that have influenced the methodological framework for determining the influence of sleep health on health outcomes, including mortality and depression.
“The Pediatric Precision Sleep Network is truly innovative in its combination of scalable sleep technologies, natural language processing of electronic health records, and sophisticated statistical approaches for high-dimensional sleep data,” said Dr. Wallace. “Sleep is exceedingly informative for physical, mental and cognitive health across the lifespan, but its dimensionality poses numerous methodological roadblocks surrounding data collection, processing and analysis. We are committed to bringing sleep and mental health data to our broader scientific community, along with the accompanying tools and resources needed to process and analyze sleep data.”