Faculty Bibliography

Treatment response heterogeneity poses serious challenges for selecting treatment for many diseases. To better understand this heterogeneity and to help in determining the best patient-specific treatments for a given disease, many clinical trials are collecting large amounts of patient-level data prior to administering treatment in the hope that some of these data can be used to identify moderators of treatment effect. These data can range from simple scalar values to complex functional data such as curves or images. Combining these various types of baseline data to discover "biosignatures" of treatment response is crucial for advancing precision medicine. Motivated by the problem of selecting optimal treatment for subjects with depression based on clinical and neuroimaging data, we present an approach that both (1) identifies covariates associated with differential treatment effect and (2) estimates a treatment decision rule based on these covariates. We focus on settings where there is a potentially large collection of candidate biomarkers consisting of both scalar and functional data. The validity of the proposed approach is justified via extensive simulation experiments and illustrated using data from a placebo-controlled clinical trial investigating antidepressant treatment response in subjects with depression.

BACKGROUND:Sleep problems are common and impairing in individuals with autism spectrum disorders (ASD). Evidence synthesis including both subjective (ie, measured with questionnaires) and objective (ie, quantified with neurophysiological tools) sleep alterations in youth with ASD is currently lacking. OBJECTIVE:We conducted a systematic review and meta-analysis of subjective and objective studies sleep studies in youth with ASD. METHODS:FINDINGS: From a pool of 3359 non-duplicate potentially relevant references, 47 datasets were included in the meta-analyses. Subjective and objective sleep outcome measures were extracted from 37 and 15 studies, respectively. Only five studies were based on comorbidity free, medication-naïve participants. Compared with typically developing controls, youth with ASD significantly differed in 10/14 subjective parameters and in 7/14 objective sleep parameters. The average quality score in the Newcastle-Ottawa Scale was 5.9/9. DISCUSSION AND CLINICAL IMPLICATIONS/UNASSIGNED:A number of subjective and, to a less extent, objective sleep alterations might characterise youth with ASD, but future studies should assess the impact of pharmacological treatment and psychiatric comorbidities.

Early age of sexual debut is associated with an increase in negative outcomes, including higher incidence of nonconsensual sexual experiences, higher rates of sexually transmitted infections, and risky sexual practices. Little research has examined the role of parental psychopathology as a predictor of adolescent sexual activity, however. The current study aims to close this gap by examining the relationship between parental psychopathology and sexual activity in a longitudinal sample of youth. Participants were 685 adolescents from the Longitudinal Assessment of Manic Symptoms study, the majority of whom were male (67%) and White (65%). Analyses considering likelihood of sexual initiation included the full sample, whereas analyses considering predictors of the age of sexual debut included the 162 participants who reported ever having sexual intercourse (62% male, 51% White) via the Youth Risk Behavior Surveillance-High School version. Cox regression analyses suggested that maternal generalized anxiety disorder predicted decreased likelihood of initiating sex during the 8-year follow-up period, whereas paternal conduct disorder predicted increased likelihood of initiating sex. Multivariate linear regressions also showed that maternal conduct disorder predicted earlier age of sexual debut among those who had initiated, whereas paternal antisocial personality disorder predicted later age of sexual debut. These associations were observed in both male and female adolescents. Furthermore, these effects were largely not explained by the established relationship between youth psychopathology and sexual behavior. Results have implications for interventions aimed at decreasing sexual risk taking in vulnerable youth.

The ability to mentalize, or theory of mind (ToM), is sexually dimorphic in humans and impaired in schizophrenia. This sex-stratified study probed cognitive (indexed by intelligence) and affective (indexed by olfactory tasks) contributions to ToM performance in 37 individuals with schizophrenia and 31 healthy controls. The schizophrenia group showed impairments in mental state identification and inferring intentions compared to controls. Higher intelligence was correlated with mental state identification and inferring intentions in healthy females, whereas better smell identification was associated with mental state identification in healthy males. Conversely, higher intelligence was associated with mental state identification and inferring intentions in schizophrenia males, while better smell identification was correlated with mental state identification in schizophrenia females. These findings suggest that for ToM circuitry, the cognitive influences in healthy females and affective influences in healthy males are reversed in schizophrenia and may be displaced to lower circuitries by disease pathology. Symptom associations with emotion and cognition are also dimorphic, plausibly due to similar pathology superimposed on normal sex-specific circuitries. Males appear to rely on limbic processing for ToM, and disruption to this circuitry may contribute to development of negative symptoms. These findings highlight the importance of utilizing sex-stratified designs in schizophrenia research.

BACKGROUND:Mandatory trial registration, and later results reporting, were proposed to mitigate selective clinical trial publication and outcome reporting. The Food and Drug Administration (FDA) Amendments Act (FDAAA) was enacted by Congress on September 27, 2007, requiring the registration of all non-phase I clinical trials involving FDA-regulated medical interventions and results reporting for approved drugs. The association between FDAAA enactment and the registration, results reporting, and publication bias of neuropsychiatric trials has not been studied. METHODS:We conducted a retrospective cohort study of all efficacy trials supporting FDA new drug approvals between 2005 to 2014 for neuropsychiatric indications. Trials were categorized as pre- or post-FDAAA based on initiation and/or completion dates. The main outcomes were the proportions of trials registered and reporting results in ClinicalTrials.gov, and the degree of publication bias, estimated using the relative risks pre- and post-FDAAA of both the publication of positive vs non-positive trials, as well as of publication of positive vs non-positive trials without misleading interpretations. Registration and results reporting proportions were compared pre- and post-FDAAA using the two-tailed Fisher exact test, and the degrees of publication bias were compared by calculating the ratio of relative risks (RRR) for each period. RESULTS:The FDA approved 37 new drugs for neuropsychiatric indications between 2005 and 2014 on the basis of 142 efficacy trials, of which 101 were pre-FDAAA and 41 post-FDAAA. Post-FDAAA trials were significantly more likely to be registered (100% vs 64%; p < 0.001) and report results (100% vs 10%; p < 0.001) than pre-FDAAA trials. Pre-FDAAA, positive trials were more likely to be published (relative risk [RR] = 1.52; 95% confidence interval [CI] = 1.17-1.99; p = 0.002) and published without misleading interpretations (RR = 2.47; CI = 1.57-3.73; p < 0.001) than those with non-positive results. In contrast, post-FDAAA positive trials were equally likely to have been published (RR = 1; CI = 1-1, p = NA) and published without misleading interpretations (RR = 1.20; CI = 0.84-1.72; p = 0.30). The likelihood of publication bias pre-FDAAA vs post-FDAAA was greater for positive vs non-positive trials (RRR = 1.52; CI = 1.16-1.99; p = 0.002) and for publication without misleading interpretations (RRR = 2.06, CI = 1.17-3.61, p = 0.01). CONCLUSIONS:The enactment of FDAAA was followed by significantly higher proportions of trials that were registered and reporting results on ClinicalTrials.gov and significantly lower degrees of publication bias among trials supporting recent FDA approval of drugs for neuropsychiatric indications.

The latent structure of schizotypy and psychosis-spectrum symptoms remains poorly understood. Furthermore, molecular genetic substrates are poorly defined, largely due to the substantial resources required to collect rich phenotypic data across diverse populations. Sample sizes of phenotypic studies are often insufficient for advanced structural equation modeling approaches. In the last 50 years, efforts in both psychiatry and psychological science have moved toward (1) a dimensional model of psychopathology (eg, the current Hierarchical Taxonomy of Psychopathology [HiTOP] initiative), (2) an integration of methods and measures across traits and units of analysis (eg, the RDoC initiative), and (3) powerful, impactful study designs maximizing sample size to detect subtle genomic variation relating to complex traits (the Psychiatric Genomics Consortium [PGC]). These movements are important to the future study of the psychosis spectrum, and to resolving heterogeneity with respect to instrument and population. The International Consortium of Schizotypy Research is composed of over 40 laboratories in 12 countries, and to date, members have compiled a body of schizotypy- and psychosis-related phenotype data from more than 30000 individuals. It has become apparent that compiling data into a protected, relational database and crowdsourcing analytic and data science expertise will result in significant enhancement of current research on the structure and biological substrates of the psychosis spectrum. The authors present a data-sharing infrastructure similar to that of the PGC, and a resource-sharing infrastructure similar to that of HiTOP. This report details the rationale and benefits of the phenotypic data collective and presents an open invitation for participation.

The human brain is a highly dynamic system with non-stationary neural activity and rapidly-changing neural interaction. Resting-state dynamic functional connectivity (dFC) has been widely studied during recent years, and the emerging aberrant dFC patterns have been identified as important features of many mental disorders such as schizophrenia (SZ). However, only focusing on the time-varying patterns in FC is not enough, since the local neural activity itself (in contrast to the inter-connectivity) is also found to be highly fluctuating from research using high-temporal-resolution imaging techniques. Exploring the time-varying patterns in brain activity and their relationships with time-varying brain connectivity is important for advancing our understanding of the co-evolutionary property of brain network and the underlying mechanism of brain dynamics. In this study, we introduced a framework for characterizing time-varying brain activity and exploring its associations with time-varying brain connectivity, and applied this framework to a resting-state fMRI dataset including 151 SZ patients and 163 age- and gender matched healthy controls (HCs). In this framework, 48 brain regions were first identified as intrinsic connectivity networks (ICNs) using group independent component analysis (GICA). A sliding window approach was then adopted for the estimation of dynamic amplitude of low-frequency fluctuation (dALFF) and dFC, which were used to measure time-varying brain activity and time-varying brain connectivity respectively. The dALFF was further clustered into six reoccurring states by the k-means clustering method and the group difference in occurrences of dALFF states was explored. Lastly, correlation coefficients between dALFF and dFC were calculated and the group difference in these dALFF-dFC correlations was explored. Our results suggested that 1) ALFF of brain regions was highly fluctuating during the resting-state and such dynamic patterns are altered in SZ, 2) dALFF and dFC were correlated in time and their correlations are altered in SZ. The overall results support and expand prior work on abnormalities of brain activity, static FC (sFC) and dFC in SZ, and provide new evidence on aberrant time-varying brain activity and its associations with brain connectivity in SZ, which might underscore the disrupted brain cognitive functions in this mental disorder.

Non-human primate neuroimaging is a rapidly growing area of research that promises to transform and scale translational and cross-species comparative neuroscience. Unfortunately, the technological and methodological advances of the past two decades have outpaced the accrual of data, which is particularly challenging given the relatively few centers that have the necessary facilities and capabilities. The PRIMatE Data Exchange (PRIME-DE) addresses this challenge by aggregating independently acquired non-human primate magnetic resonance imaging (MRI) datasets and openly sharing them via the International Neuroimaging Data-sharing Initiative (INDI). Here, we present the rationale, design, and procedures for the PRIME-DE consortium, as well as the initial release, consisting of 25 independent data collections aggregated across 22 sites (total = 217 non-human primates). We also outline the unique pitfalls and challenges that should be considered in the analysis of non-human primate MRI datasets, including providing automated quality assessment of the contributed datasets.

OBJECTIVE:/UNASSIGNED:The authors examined the impact of a Web-based shared decision-making application, MyCHOIS-CommonGround, on ongoing outpatient mental health treatment engagement (all users) and antipsychotic medication adherence (users with schizophrenia). METHODS:/UNASSIGNED:An intervention study was conducted by comparing Medicaid-enrolled MyCHOIS-CommonGround users in 12 participating mental health clinics (N=472) with propensity score-matched adults receiving services in nonparticipating clinics (N=944). Medicaid claims were used to assess ongoing treatment engagement and antipsychotic adherence (among individuals with schizophrenia) one year prior to and after entry into the cohort. Multilevel linear models were conducted to estimate the effects of the MyCHOIS-CommonGround program over time. RESULTS:/UNASSIGNED:No differences during the baseline year were found between the MyCHOIS-CommonGround group and the matched control group on demographic, diagnostic, or service use characteristics. At one-year follow-up, engagement in outpatient mental health services was significantly higher for MyCHOIS-CommonGround users than for the control group (months with a service, 8.54±.22 versus 6.95±.15; β=1.40, p<.001). Among individuals with schizophrenia, antipsychotic medication adherence was also higher during the follow-up year among MyCHOIS-CommonGround users compared with the control group (proportion of days covered by medication, .78±.04 versus .69±.03; β=.06, p<.01). CONCLUSIONS:/UNASSIGNED:These findings provide new evidence that shared decision-making tools may promote ongoing mental health treatment engagement for individuals with serious mental illness and improved antipsychotic medication adherence for those with schizophrenia.

Although infants learn and remember, they rapidly forget, a phenomenon known as infantile amnesia. While myriad mechanisms impact this rapid forgetting, the molecular events supporting memory maintenance have yet to be explored. To explore memory mechanisms across development, we used amygdala-dependent odor-shock conditioning and focused on mechanisms important in adult memory, the AMPA receptor subunits GluA1/2 and upstream protein kinases important for trafficking AMPAR, protein kinase M zeta (PKMζ) and iota/lambda (PKCι/λ). We use odor-shock conditioning in infant rats because it is late-developing (postnatal day, PN10) and can be modulated by corticosterone during a sensitive period in early life. Our results show that memory-related molecules did not change in pups too young to learn threat (PN8) but were activated in pups old enough to learn (PN12), with increased PKMζ-PKCι/λ and GluA2 similar to that observed in adult memory, but with an uncharacteristic decrease in GluA1. This molecular signature and behavioral avoidance of the conditioned odor was recapitulated in PN8 pups injected with CORT before conditioning to precociously induce learning. Blocking learning via CORT inhibition in older pups (PN12) blocked the expression of these molecules. PN16 pups showed a more adult-like molecular cascade of increased PKMζ-PKCι/λ and GluA1-2. Finally, at all ages, zeta inhibitory peptide (ZIP) infusions into the amygdala 24 hr after conditioning blocked memory. Together, these results identify unique features of memory processes across early development: AMPAR subunits GluA1/2 and PKC isoform expression are differentially used, which may contribute to mechanisms of early life forgetting.