University of Pittsburgh Department of Psychiatry and UPMC Western Psychiatric Hospital: Research Updates

January 28, 2020

The robust, varied, and multidisciplinary research programs within the University of Pittsburgh Department of Psychiatry continue to propel forward the evidence-base underlying the pathophysiology, natural history, basic science underpinnings, and the clinical treatment of the full spectrum of psychiatric disorders.

Below are brief synopses of two papers from Department faculty that have been published recently. To learn more about the contributing faculty and the Department of Psychiatry, view the schedule of upcoming lectures and symposia, and other faculty news, please visit psychiatry.pitt.edu.

Now in Cell Reports: New Findings Related to Early Abnormal Striatal Development and Autism Spectrum Disorders

Autism spectrum disorder (ASD) is characterized by cognitive and behavioral deficits that typically emerge before the age of three. While this distinctive developmental trajectory and the selective degradation of particular abilities suggest that ASD arises from impaired developmental processes affecting the maturation of specific neural circuits, the developmental stage at which circuit dysfunction associated with behavioral abnormalities in ASD begin to occur has not been established. 

ASD has a strong genetic basis and is associated with de novo gene mutations and copy number variants. Researchers, including Rui Peixoto, PhD, of the Department of Psychiatry, have examined how mutations in SHANK3, a postsynaptic scaffolding protein strongly associated with ASD, lead to behavioral deficits in mice. To determine when these abnormalities emerge in mice with SHANK3 mutations (referred to here as Shank3B−/− mice), the team tested their performance during multiple behavioral assays completed across postnatal days 15–90. 

In a study published in Cell Reports, the researchers demonstrated that several of the behavioral deficits previously reported in adult Shank3B−/− mice could be observed as early as the first 15–21 postnatal days. This observation suggests that the pathogenic processes implicated in the emergence of maladaptive behaviors occur during or before this early developmental stage, which, in mice, is roughly homologous to the first one to two years of human brain development. The investigators found that the abnormal postnatal development of striatal circuits is implicated in the onset of behavioral deficits in Shank3B−/− mice.

Dr. Peixoto, lead author of the study, remarked on the findings: “Our data shows that Shank3 deletions in mice lead to an early onset of behavioral abnormalities, similar to what is observed in children with similar genetic disturbances. This finding provides confidence that mouse models of Shank3 recapitulate the relevant pathogenic processes that afflict humans. In addition, we show that the postnatal maturation of striatal circuits is orchestrated by many ASD risk factors that drive distinct forms of corticostriatal synaptic plasticity across development—which might help understand how Shank3 dysfunction ultimately leads to repetitive behaviors and other cognitive deficits in ASD.”

Reference:

Peixoto RT, Chantranupong L, Hakim R, Levasseur J, Wang W, Merchant T, Gorman K,9Budnik B, Sabatini BL. Abnormal Striatal Development Underlies the Early Onset of Behavioral Deficits in Shank3B−/− Mice. Cell Reports. 2019; (29)7: 2016-2027.

SLEEP Editor’s Choice: How Empirically Differentiating “Good” from “Poor” Sleep Relates to Cardiometabolic Health

The paper described below was selected as a SLEEP Editor’s Choice.

Sleep can play an important role in overall mental and physical health. A multidimensional sleep health score assesses sleep through six dimensions: sleep duration, timing, regularity, efficiency and quality, and daytime alertness. Although this score helps scientists create a nuanced sleep health profile, which is critical to analyzing sleep quality in relation to mental and physical health outcomes, empirical measures of what constitutes “good” and “poor” sleep, across each of these dimensions, has so far been missing from the literature.

In a new study published in SLEEP, researchers including Ryan C. Brindle, PhD, (former Department of Psychiatry postdoctoral fellow; current assistant professor of Cognitive and Behavioral Science at Washington and Lee University) and Martica Hall, PhD, professor of Psychiatry, Psychology, and Clinical and Translational Science from the University of Pittsburgh School of Medicine, analyzed data from MIDUS II and MIDUS Refresher Biomarker studies to empirically derive cut-off values of all six sleep dimensions. Further, they examined the degree to which sleep health is associated with cardiovascular diseases and metabolic disorders and evaluated whether the sleep health metric outperformed other, more commonly used epidemiological measures.

Data for the current study were collected from 700 MIDUS II and MIDUS Refresher Biomarker study participants who wore wrist actigraphs and completed a sleep diary for seven consecutive days. Sleep health dimension data from the MIDUS II participants informed the development of sleep health score cut-off values, which were then used to analyze the relationship between sleep health scores and cardiometabolic morbidity in participants from the MIDUS Refresher study. Cardiometabolic outcomes were calculated based on current medication use, blood panel values, self-reported physician diagnoses of heart disease, hypertension, stroke, and diabetes. The six dimensions of sleep health were derived from self-reported information (sleep quality and daytime alertness) and the actigraphy data (sleep duration, timing, regularity, and efficiency).

The investigators found that the cut-off values that emerged from their analysis were reasonably aligned with cut-off values already reported in previous literature, although the value for sleep duration was notably shorter than in earlier studies. In addition, the research team confirmed their hypothesis that better sleep is significantly associated with reduced odds of reporting cardiometabolic morbidity and hypertension, even after controlling for sociodemographic and biological risk factors. 

Regarding these findings, Dr. Hall, the study's senior author, remarked, "Dr. Brindle's analyses of the MIDUS data go a long way towards establishing that health is best predicted by multidimensional measures of sleep. These data quite clearly show that sleep duration alone does not tell the whole story. Among other factors, when we think about the importance of sleep to health, we need to consider when, how soundly, and how regularly we sleep."

Reference:

Brindle RC, Yu L, Buysse DJ, Hall MH. Empirical Derivation of Cut-off Values for the Sleep Health Metric and Its Relationship to Cardiometabolic Morbidity: Results From the Midlife in the United States (MIDUS) Study. Sleep. 2019; 42(9): 1-9.