Down syndrome (DS) is the most prevalent cause of intellectual disability (ID). Individuals with DS show a variety of cognitive deficits, most notably in hippocampal learning and memory, and display pathological hallmarks of Alzheimer's disease (AD), with neurodegeneration of cholinergic basal forebrain (CBF) neurons. Elucidation of the molecular and cellular underpinnings of neuropathology has been assessed via gene expression analysis in a relevant animal model, termed the Ts65Dn mouse. The Ts65Dn mouse is a segmental trisomy model of DS that mimics DS/AD pathology, notably age-related cognitive dysfunction and degeneration of basal forebrain cholinergic neurons (BFCNs). To determine expression level changes, molecular fingerprinting of cornu ammonis 1 (CA1) pyramidal neurons was performed in adult (4-9 month-old) Ts65Dn mice, at the initiation of BFCN degeneration. To quantitate transcriptomic changes during this early time period, laser capture microdissection (LCM), terminal continuation (TC) RNA amplification, custom-designed microarray analysis, and subsequent validation of individual transcripts by qPCR and protein analysis via immunoblotting was performed. The results indicate significant alterations within CA1 pyramidal neurons of Ts65Dn mice compared with normal disomic (2N) littermates, notably in the downregulation of neurotrophins and their cognate neurotrophin receptors among other classes of transcripts relevant to neurodegeneration. The results of this single-population gene expression analysis at the time of septohippocampal deficits in a trisomic mouse model shed light on a vulnerable circuit that may cause the AD-like pathology invariably seen in DS that could help to identify mechanisms of degeneration, and provide novel gene targets for therapeutic interventions. J. Comp. Neurol. 523:61-74, 2015. © 2014 Wiley Periodicals, Inc.

To date, only one study has examined test-retest reliability of resting state fMRI (R-fMRI) in children, none in clinical developing groups. Here, we assessed short-term test-retest reliability in a sample of 46 children (11-17.9 years) with attention-deficit/hyperactivity disorder (ADHD) and 57 typically developing children (TDC). Our primary test-retest reliability measure was the intraclass correlation coefficient (ICC), quantified for a range of R-fMRI metrics. We aimed to (1) survey reliability within and across diagnostic groups, and (2) compare voxel-wise ICC between groups. We found moderate-to-high ICC across all children and within groups, with higher-order functional networks showing greater ICC. Nearly all R-fMRI metrics exhibited significantly higher ICC in TDC than in children with ADHD for one or more regions. In particular, posterior cingulate and ventral precuneus exhibited group differences in ICC across multiple measures. In the context of overall moderate-to-high test-retest reliability in children, regional differences in ICC related to diagnostic groups likely reflect the underlying pathophysiology for ADHD. Our currently limited understanding of the factors contributing to inter- and intra-subject variability in ADHD underscores the need for large initiatives aimed at examining their impact on test-retest reliability in both clinical and developing populations.

Disengagement from treatment is common in first episode schizophrenia (FES) and is associated with poor outcomes. Our aim was to determine whether hippocampal subfield volumes predict disengagement during maintenance treatment of FES.

Functional connectivity of an individual human brain is often studied by acquiring a resting state functional magnetic resonance imaging scan, and mapping the correlation of each voxel's BOLD time series with that of a seed region. As large collections of such maps become available, including multisite data sets, there is an increasing need for ways to distill the information in these maps in a readily visualized form. Here we propose a two-step analytic strategy. First, we construct connectivity-distance profiles, which summarize the connectivity of each voxel in the brain as a function of distance from the seed, a functional relationship that has attracted much recent interest. Next, these profile functions are regressed on predictors of interest, whether categorical (e.g., acquisition site or diagnostic group) or continuous (e.g., age). This procedure can provide insight into the roles of multiple sources of variation, and detect large-scale patterns not easily available from conventional analyses. We illustrate the proposed methods with a resting state data set pooled across four imaging sites.

Epidemiological findings suggest that diabetic individuals are at a greater risk for developing Alzheimer's disease (AD). To examine the mechanisms by which diabetes mellitus (DM) may contribute to AD pathology in humans, we examined brain tissue from streptozotocin-treated type 1 diabetic adult male vervet monkeys receiving twice-daily exogenous insulin injections for 8-20 weeks. We found greater inhibitory phosphorylation of insulin receptor substrate 1 in each brain region examined of the diabetic monkeys when compared with controls, consistent with a pattern of brain insulin resistance that is similar to that reported in the human AD brain. Additionally, a widespread increase in phosphorylated tau was seen, including brain areas vulnerable in AD, as well as relatively spared structures, such as the cerebellum. An increase in active ERK1/2 was also detected, consistent with DM leading to changes in tau-kinase activity broadly within the brain. In contrast to these widespread changes, we found an increase in soluble amyloid-β (Aβ) levels that was restricted to the temporal lobe, with the greatest increase seen in the hippocampus. Consistent with this localized Aβ increase, a hippocampus-restricted decrease in the protein and mRNA for the Aβ-degrading enzyme neprilysin (NEP) was found, whereas various Aβ-clearing and -degrading proteins were unchanged. Thus, we document multiple biochemical changes in the insulin-controlled DM monkey brain that can link DM with the risk of developing AD, including dysregulation of the insulin-signaling pathway, changes in tau phosphorylation, and a decrease in NEP expression in the hippocampus that is coupled with a localized increase in Aβ.

The National Institute of Mental Health strategic plan for advancing psychiatric neuroscience calls for an acceleration of discovery and the delineation of developmental trajectories for risk and resilience across the lifespan. To attain these objectives, sufficiently powered datasets with broad and deep phenotypic characterization, state-of-the-art neuroimaging, and genetic samples must be generated and made openly available to the scientific community. The enhanced Nathan Kline Institute-Rockland Sample (NKI-RS) is a response to this need. NKI-RS is an ongoing, institutionally centered endeavor aimed at creating a large-scale (N > 1000), deeply phenotyped, community-ascertained, lifespan sample (ages 6-85 years old) with advanced neuroimaging and genetics. These data will be publically shared, openly, and prospectively (i.e., on a weekly basis). Herein, we describe the conceptual basis of the NKI-RS, including study design, sampling considerations, and steps to synchronize phenotypic and neuroimaging assessment. Additionally, we describe our process for sharing the data with the scientific community while protecting participant confidentiality, maintaining an adequate database, and certifying data integrity. The pilot phase of the NKI-RS, including challenges in recruiting, characterizing, imaging, and sharing data, is discussed while also explaining how this experience informed the final design of the enhanced NKI-RS. It is our hope that familiarity with the conceptual underpinnings of the enhanced NKI-RS will facilitate harmonization with future data collection efforts aimed at advancing psychiatric neuroscience and nosology.

This tutorial introduces recent developments in precision medicine for estimating treatment decision rules. The objective of these developments is to advance personalised healthcare by identifying an optimal treatment option for each individual patient based on each patient's characteristics. The methods detailed in this tutorial define composite variables from the patient measures that can be viewed as 'biosignatures' for differential treatment response, which we have termed 'generated effect modifiers'. In contrast to most machine learning approaches to precision medicine, these biosignatures are derived from linear and non-linear regression models and thus have the advantage of easy visualisation and ready interpretation. The methods are illustrated using examples from randomised clinical trials.

Although major depressive disorder (MDD) and schizophrenia (SZ) are closely associated with disrupted functions in frontal and limbic areas of cerebral cortex, cellular pathology has also been found in other brain areas, including primary sensory cortex. Auditory cortex is of particular interest, given the prominence of auditory hallucinations in SZ, and sensory deficits in MDD. We used stereological sampling methods in auditory cortex to look for cellular differences between MDD, SZ and non-psychiatric subjects. Additionally, as all of our MDD subjects died of suicide, we evaluated the association of suicide with our measurements by selecting a SZ sample that was divided between suicide and non-suicide subjects. Measurements were done in primary auditory cortex (area A1) and auditory association cortex (area Tpt), two areas with distinct roles in sensory processing and obvious differences in neuron density and size. In MDD, densities of GABAergic interneurons immunolabeled for calretinin (CR) and calbindin (CB) were 23-29% lower than non-psychiatric controls in both areas. Parvalbumin (PV) interneurons (counted only in area Tpt) showed a nominally smaller (16%) reduction that was not statistically significant. Total neuron and glia densities measured in Nissl stained sections did not show corresponding reductions. Analysis of suicide in the SZ sample indicated that reduced CR cell density was associated with suicide, whereas the densities of CB and other cells were not. Our results are consistent with previous studies in MDD that found altered GABA-associated markers throughout the cerebral cortex including primary sensory areas.

This article provides a description of the rationale, design, and methods of a multisite clinical trial which evaluates the potential benefits of an evidence-based psychosocial treatment, STAIR Narrative Therapy, among women with posttraumatic stress disorder (PTSD) related to interpersonal violence who are seeking services in public sector community mental health clinics. This is the first large multisite trial of an evidence-based treatment for PTSD provided in the context of community settings that are dedicated to the treatment of poverty-level patient populations.