Relapse prevention through health technology program reduces hospitalization in schizophrenia.

BACKGROUND: Psychiatric hospitalization is a major driver of cost in the treatment of schizophrenia. Here, we asked whether a technology-enhanced approach to relapse prevention could reduce days spent in a hospital after discharge. METHODS: The Improving Care and Reducing Cost (ICRC) study was a quasi-experimental clinical trial in outpatients with schizophrenia conducted between 26 February 2013 and 17 April 2015 at 10 different sites in the USA in an outpatient setting. Patients were between 18 and 60 years old with a diagnosis of schizophrenia, schizoaffective disorder, or psychotic disorder not otherwise specified. Patients received usual care or a technology-enhanced relapse prevention program during a 6-month period after discharge. The health technology program included in-person, individualized relapse prevention planning with treatments delivered via smartphones and computers, as well as a web-based prescriber decision support program. The main outcome measure was days spent in a psychiatric hospital during 6 months after discharge. RESULTS: The study included 462 patients, of which 438 had complete baseline data and were thus used for propensity matching and analysis. Control participants (N = 89; 37 females) were enrolled first and received usual care for relapse prevention followed by 349 participants (128 females) who received technology-enhanced relapse prevention. During 6-month follow-up, 43% of control and 24% of intervention participants were hospitalized (χ2 = 11.76, p<0.001). Days of hospitalization were reduced by 5 days (mean days: b = -4.58, 95% CI -9.03 to -0.13, p = 0.044) in the intervention condition compared to control. CONCLUSIONS: These results suggest that technology-enhanced relapse prevention is an effective and feasible way to reduce rehospitalization days among patients with schizophrenia.

Characterizing and detecting delirium with clinical and computational measures of speech and language disturbance.

BACKGROUND: Delirium is a critically underdiagnosed syndrome of altered mental status affecting more than 50% of older adults admitted to hospital. Few studies have incorporated speech and language disturbance in delirium detection. We sought to describe speech and language disturbances in delirium, and provide a proof of concept for detecting delirium using computational speech and language features. METHODS: Participants underwent delirium assessment and completed language tasks. Speech and language disturbances were rated using standardized clinical scales. Recordings and transcripts were processed using an automated pipeline to extract acoustic and textual features. We used binomial, elastic net, machine learning models to predict delirium status. RESULTS: We included 33 older adults admitted to hospital, of whom 10 met criteria for delirium. The group with delirium scored higher on total language disturbances and incoherence, and lower on category fluency. Both groups scored lower on category fluency than the normative population. Cognitive dysfunction as a continuous measure was correlated with higher total language disturbance, incoherence, loss of goal and lower category fluency. Including computational language features in the model predicting delirium status increased accuracy to 78%. LIMITATIONS: This was a proof-of-concept study with limited sample size, without a set-aside cross-validation sample. Subsequent studies are needed before establishing a generalizable model for detecting delirium. CONCLUSION: Language impairments were elevated among patients with delirium and may also be used to identify subthreshold cognitive disturbances. Computational speech and language features are promising as accurate, noninvasive and efficient biomarkers of delirium.

Antenatal Antidepressant Prescription Associated With Reduced Fetal Femur Length but Not Estimated Fetal Weight: A Retrospective Ultrasonographic Study.

PURPOSE/BACKGROUND: Antidepressants are among the most frequently prescribed medications during pregnancy and may affect fetal weight. Associations between antenatal antidepressant use and ultrasonographic measures of fetal development have rarely been examined. We hypothesized that the prescription of an antenatal antidepressant would be associated with lower estimated fetal weight (EFW). METHODS/PROCEDURES: A retrospective analysis of routine ultrasonographic data extracted from electronic medical records was performed on a cohort of pregnant women with psychiatric diagnoses and grouped according to the presence of an antenatal antidepressant prescription (n = 32 antidepressant-prescribed and n = 44 antidepressant prescription-free). After stratifying for gestational age, comparisons included 13 ultrasonographic parameters, frequency of oligohydramnios and polyhydramnios and growth deceleration, and maternal serum protein markers assessed per routine care, including α-fetoprotein, free ß-human chorionic gonadotropin, and unconjugated estriol levels, using t tests, nonparametric and Fisher tests, and effect sizes (ESs) were computed. FINDINGS/RESULTS: No statistically significant EFW differences between groups at any time point were detected (P > 0.05). Antenatal antidepressant prescription was associated with lower femur length at weeks 33 to 40 (P = 0.046, ES = 0.75) and greater left ventricular diameter at weeks 25 to 32 (P = 0.04, ES = 1.18). No differences for frequency of oligohydramnios or polyhydramnios or growth deceleration were observed (P > 0.05). We did not detect group differences for maternal proteins (P > 0.05). IMPLICATIONS/CONCLUSIONS: Our evidence suggested a lack of association between antenatal antidepressant prescription and lower EFW but indicated an association with lower femur length and greater left ventricular diameter in mid-late gestation. Future research should examine the clinical implications of these findings.

Evidence for validity for the Cognitive Load Inventory for Handoffs.

CONTEXT: Patient handovers remain a significant patient safety challenge. Cognitive load theory (CLT) can be used to identify the cognitive mechanisms for handover errors. The ability to measure cognitive load types during handovers could drive the development of more effective curricula and protocols. No such measure currently exists. METHODS: The authors developed the Cognitive Load Inventory for Handoffs (CLIH) using a multi-step process, including expert interviews to enhance content validity and talk-alouds to optimise response process validity. The final version contained 28 items. From January to March 2019, we administered a cross-sectional survey to 1807 residents and fellows from a large health care system in the USA. Participants completed the CLIH following a handover. Exploratory factor analysis of data from one-third of respondents identified high-performing items; confirmatory factor analysis of data from the remaining sample assessed model fit. Model fit was evaluated using the comparative fit index (CFI) (>0.90), Tucker-Lewis index (TFI) (>0.80), standardised root mean square residual (SRMR) (<0.08) and root mean square of error of approximation (RMSEA) (<0.08). RESULTS: Participants included 693 trainees (38.4%) (231 in the exploratory study and 462 in the confirmatory study). Eleven items were removed during exploratory factor analysis. Confirmatory factor analysis of the 16 remaining items (five for intrinsic load, seven for extraneous load and four for germane load) supported a three-factor model and met criteria for good model fit: the CFI was 0.95, TFI was 0.93, RMSEA was 0.074 and SRMR was 0.07. The factor structure was comparable for gender and role. Intrinsic, extraneous and germane load scales had high internal consistency. With one exception, scale scores were associated, as hypothesised, with postgraduate level and clinical setting. CONCLUSIONS: The CLIH measures three types of cognitive load during patient handovers. Evidencefor validity is provided for the CLIH's content, response process, internal structure and association with other variables. This instrument can be used to determine the relative drivers of cognitive load during handovers in order to optimize handover instruction and protocols.

Exploring the relationship between emotion and cognitive load types during patient handovers.

Cognitive Load Theory has emerged as an important approach to improving instruction in the health professions workplace, including patient handovers. At the same time, there is growing recognition that emotion influences learning through numerous cognitive processes including motivation, attention, working memory, and long-term memory. This study explores how emotion influences the cognitive load experienced by trainees performing patient handovers. From January to March 2019, 693 (38.7%) of 1807 residents and fellows from a 24-hospital health system in New York city completed a survey after performing a handover. Participants rated their emotional state and cognitive load. The survey included questions about features of the learner, task, and instructional environment. The authors used factor analysis to identify the core dimensions of emotion. Regression analyses explored the relationship between the emotion factors and cognitive load types. Two emotion dimensions were identified representing invigoration and tranquility. In regression analyses, higher levels of invigoration, tranquility, and their interaction were independently associated with lower intrinsic load and extraneous load. The interaction of invigoration and tranquility predicted lower germane load. The addition of the emotion variables to multivariate models including other predictors of cognitive load types significantly increased the amount of variance explained. The study provides a model for measuring emotions in workplace learning. Because emotion appears to have a significant influence on cognitive load types, instructional designers should consider strategies that help trainees regulate emotion in order to reduce cognitive load and improve learning and performance.

Parasympathetic arousal-related cortical activity is associated with attention during cognitive task performance.

Parasympathetic arousal is associated with states of heightened attention and well-being. Arousal may affect widespread cortical and subcortical systems across the brain, however, little is known about its influence on cognitive task processing and performance. In the current study, healthy adult participants (n â€‹= â€‹20) underwent multi-band echo-planar imaging (TR â€‹= â€‹0.72 â€‹s) with simultaneous pulse oximetry recordings during performance of the Multi Source Interference Task (MSIT), the Oddball Task (OBT), and during rest. Processing speed on both tasks was robustly related to heart rate (HR). Participants with slower HR responded faster on both the MSIT (33% variance explained) and the OBT (25% variance explained). Within all participants, trial-to-trial fluctuations in processing speed were robustly related to the heartbeat-stimulus interval, a metric that is dependent both on the concurrent HR and the stimulus timing with respect to the heartbeat. Models examining the cardiac-BOLD response revealed that a distributed set of regions showed arousal-related activity that was distinct for different task conditions. Across these cortical regions, activity increased with slower HR. Arousal-related activity was distinct from task-evoked activity and it was robust to the inclusion of additional physiological nuisance regressors into the models. For the MSIT, such arousal-related activity occurred across visual and dorsal attention network regions. For the OBT, this activity occurred within fronto-parietal regions. For rest, arousal-related activity also occurred, but was confined to visual regions. The pulvinar nucleus of the thalamus showed arousal-related activity during all three task conditions. Widespread cortical activity, associated with increased parasympathetic arousal, may be propagated by thalamic circuits and contributes to improved attention. This activity is distinct from task-evoked activity, but affects cognitive performance and therefore should be incorporated into neurobiological models of cognition and clinical disorders.

Estimation of Dynamic Bivariate Correlation Using a Weighted Graph Algorithm.

Dynamic correlation is the correlation between two time series across time. Two approaches that currently exist in neuroscience literature for dynamic correlation estimation are the sliding window method and dynamic conditional correlation. In this paper, we first show the limitations of these two methods especially in the presence of extreme values. We present an alternate approach for dynamic correlation estimation based on a weighted graph and show using simulations and real data analyses the advantages of the new approach over the existing ones. We also provide some theoretical justifications and present a framework for quantifying uncertainty and testing hypotheses.

Continuation Electroconvulsive Therapy for Patients With Clozapine-Resistant Schizophrenia: A Pilot Study.

OBJECTIVES: The risk of relapse after a successful acute course of treatment is a clinical challenge in electroconvulsive therapy (ECT) practice, particularly in patients with a history of marked resistance to previous treatments. Research suggests that a gradual decrease of ECT or its long-term continuation might be the best strategy. Notwithstanding, current studies do not address the role of continuation ECT in the truly refractory cases, that is, the clozapine-resistant patients. Our group published a randomized controlled trial of ECT augmentation of clozapine in clozapine-resistant patients with schizophrenia, where the augmentation was vastly superior in efficacy for the acute treatment. The aim of the current study is to evaluate the efficacy of continuation ECT for patients who showed response to the combination of acute ECT and clozapine for treatment-resistant schizophrenia. METHODS: Continuation ECT was offered to all patients who completed the acute study and who met response criterion. We followed a tapered schedule of 4 weekly ECT sessions, followed by 4 ECT sessions every 2 weeks and 2 monthly ECT sessions for a total of 10 sessions. RESULTS: Patients sustained the gains achieved with the acute course of ECT, and no individual patient presented with clinically relevant worsening of symptoms. Moreover, the long-term use of ECT was not associated with added adverse effects. CONCLUSIONS: This is an open pilot study with a small sample size, and results should be interpreted accordingly, but this report offers a relevant starting point for much needed future studies.

Brain white matter development is associated with a human-specific haplotype increasing the synthesis of long chain fatty acids.

The genetic and molecular pathways driving human brain white matter (WM) development are only beginning to be discovered. Long chain polyunsaturated fatty acids (LC-PUFAs) have been implicated in myelination in animal models and humans. The biosynthesis of LC-PUFAs is regulated by the fatty acid desaturase (FADS) genes, of which a human-specific haplotype is strongly associated with ω-3 and ω-6 LC-PUFA concentrations in blood. To investigate the relationship between LC-PUFA synthesis and human brain WM development, we examined whether this FADS haplotype is associated with age-related WM differences across the life span in healthy individuals 9-86 years of age (n = 207). Diffusion tensor imaging was performed to measure fractional anisotropy (FA), a putative measure of myelination, of the cerebral WM tracts. FADS haplotype status was determined with a single nucleotide polymorphism (rs174583) that tags this haplotype. Overall, normal age-related WM differences were observed, including higher FA values in early adulthood compared with childhood, followed by lower FA values across older age ranges. However, individuals homozygous for the minor allele (associated with lower LC-PUFA concentrations) did not display these normal age-related WM differences (significant age × genotype interactions, p(corrected) < 0.05). These findings suggest that LC-PUFAs are involved in human brain WM development from childhood into adulthood. This haplotype and LC-PUFAs may play a role in myelin-related disorders of neurodevelopmental origin.

The accumbofrontal tract: Diffusion tensor imaging characterization and developmental change from childhood to adulthood.

The presence of an anatomical connection between the orbitofrontal cortex and ventral striatum, forming a so-called reward network, is well established across species. This connection has important implications for reward processing and is relevant to a number of neuropsychiatric disorders. Moreover, white matter (WM) is known to continue to mature across adolescence and into early adulthood, and developmental change in the reward network is an important component of models of decision making and risk taking. Despite the importance of this connection, the underlying WM has only recently been characterized in humans histologically, and not yet in-vivo using brain imaging. Here, we implemented diffusion tensor imaging (DTI) in a large cross-sectional sample of 295 healthy individuals ages 8-68 to further characterize the WM of this connection and its development from childhood into adulthood. We demonstrate that the accumbofrontal tract, connecting the orbitofrontal cortex and nucleus accumbens, can be identified using standard DTI sequences. Using Poisson modeling, we show that the accumbofrontal tract undergoes significant change across the lifespan, with males showing a higher and earlier peak compared to females. Moreover, the change occurs in a pattern consistent with developmental models of decision-making. These findings support the hypothesis that developmental differences in WM integrity may be a contributing factor to the observed risk taking that occurs in adolescence. The accumbofrontal tract is not yet included in standard WM atlases, but may be important for inclusion in studies investigating fronto-striatal networks, as well as in investigations of substance abuse and decision making.

Age and sex effects on corpus callosum morphology across the lifespan.

The corpus callosum (CC) is the largest interhemispheric white matter tract in the human brain, and is characterized by pronounced differences in morphology among individuals. There are limited data, however, regarding typical development, sex differences, and the neuropsychological correlates of individual differences within CC subregions. Magnetic resonance (MR) imaging exams were collected in a large cohort (N = 305) of healthy individuals (ages 8-68). We used a highly reliable program to automatically identify the midsagittal plane and obtain CC subregion measures according to approaches described by Witelson [1989]: Brain 112:799-835 and Hampel et al. [1998]: Arch Neurol 55:193-198 and a measure of whole CC shape (i.e., circularity). CC measurement parameters, including area, perimeter, length, circularity, and CC subregion area values were generally characterized by inverted U-shaped curves across the observed age range. Peak values for CC subregions were observed between ages 32 and 45, and descriptive linear correlations were consistent with sharper area changes in development. We also observed differing age-associated changes across the lifespan between males and females in the CC subregion corresponding to the genu (Witelson's subregion 2), as well as CC circularity. Mediation analysis using path modeling indicated that genu area mediated the relationship between age and processing speed for females, and the relationship between age and visual learning and executive functioning for males. Taken together, our findings implicate sex differences in CC morphology across the lifespan that are localized to the genu, which appear to mediate neuropsychological functions.

Age-associated alterations in corpus callosum white matter integrity in bipolar disorder assessed using probabilistic tractography.

OBJECTIVES: Atypical age-associated changes in white matter integrity may play a role in the neurobiology of bipolar disorder, but no studies have examined the major white matter tracts using nonlinear statistical modeling across a wide age range in this disorder. The goal of this study was to identify possible deviations in the typical pattern of age-associated changes in white matter integrity in patients with bipolar disorder across the age range of 9-62 years. METHODS: Diffusion tensor imaging was performed in 57 (20 male and 37 female) patients with a diagnosis of bipolar disorder and 57 (20 male and 37 female) age- and sex-matched healthy volunteers. Mean diffusivity and fractional anisotropy were computed for the genu and splenium of the corpus callosum, two projection tracts, and five association tracts using probabilistic tractography. RESULTS: Overall, patients had lower fractional anisotropy and higher mean diffusivity compared to healthy volunteers across all tracts (while controlling for the effects of age and age(2) ). In addition, there were greater age-associated increases in mean diffusivity in patients compared to healthy volunteers within the genu and splenium of the corpus callosum beginning in the second and third decades of life. CONCLUSIONS: Our findings provide evidence for alterations in the typical pattern of white matter development in patients with bipolar disorder compared to healthy volunteers. Changes in white matter development within the corpus callosum may lead to altered inter-hemispheric communication that is considered integral to the neurobiology of the disorder.

Independent evidence for an association between general cognitive ability and a genetic locus for educational attainment.

Cognitive deficits and reduced educational achievement are common in psychiatric illness; understanding the genetic basis of cognitive and educational deficits may be informative about the etiology of psychiatric disorders. A recent, large genome-wide association study (GWAS) reported a genome-wide significant locus for years of education, which subsequently demonstrated association to general cognitive ability ("g") in overlapping cohorts. The current study was designed to test whether GWAS hits for educational attainment are involved in general cognitive ability in an independent, large-scale collection of cohorts. Using cohorts in the Cognitive Genomics Consortium (COGENT; up to 20,495 healthy individuals), we examined the relationship between g and variants associated with educational attainment. We next conducted meta-analyses with 24,189 individuals with neurocognitive data from the educational attainment studies, and then with 53,188 largely independent individuals from a recent GWAS of cognition. A SNP (rs1906252) located at chromosome 6q16.1, previously associated with years of schooling, was significantly associated with g (P = 1.47 × 10(-4) ) in COGENT. The first joint analysis of 43,381 non-overlapping individuals for this a priori-designated locus was strongly significant (P = 4.94 × 10(-7) ), and the second joint analysis of 68,159 non-overlapping individuals was even more robust (P = 1.65 × 10(-9) ). These results provide independent replication, in a large-scale dataset, of a genetic locus associated with cognitive function and education. As sample sizes grow, cognitive GWAS will identify increasing numbers of associated loci, as has been accomplished in other polygenic quantitative traits, which may be relevant to psychiatric illness.

Independent component analysis of resting state activity in pediatric obsessive-compulsive disorder.

Obsessive-compulsive disorder (OCD) is an often severely disabling illness with onset generally in childhood or adolescence. Little is known, however, regarding the pattern of brain resting state activity in OCD early in the course of illness. We therefore examined differences in brain resting state activity in patients with pediatric OCD compared with healthy volunteers and their clinical correlates. Twenty-three pediatric OCD patients and 23 healthy volunteers (age range 9-17), matched for sex, age, handedness, and IQ completed a resting state functional magnetic resonance imaging exam at 3T. Patients completed the Children's Yale Brown Obsessive Scale. Data were decomposed into 36 functional networks using spatial group independent component analysis (ICA) and logistic regression was used to identify the components that yielded maximum group separation. Using ICA we identified three components that maximally separated the groups: a middle frontal/dorsal anterior cingulate network, an anterior/posterior cingulate network, and a visual network yielding an overall group classification of 76.1% (sensitivity = 78.3% and specificity = 73.9%). Independent component expression scores were significantly higher in patients compared with healthy volunteers in the middle frontal/dorsal anterior cingulate and the anterior/posterior cingulate networks, but lower in patients within the visual network. Higher expression scores in the anterior/posterior cingulate network correlated with greater severity of compulsions among patients. These findings implicate resting state fMRI abnormalities within the cingulate cortex and related control regions in the pathogenesis and phenomenology of OCD early in the course of the disorder and prior to extensive pharmacologic intervention.

A few theoretical results for Laplace and arctan penalized ordinary least squares linear regression estimators.

Two new nonconvex penalty functions - Laplace and arctan - were recently introduced in the literature to obtain sparse models for high-dimensional statistical problems. In this paper, we study the theoretical properties of Laplace and arctan penalized ordinary least squares linear regression models. We first illustrate the near-unbiasedness of the nonzero regression weights obtained by the new penalty functions, in the orthonormal design case. In the general design case, we present theoretical results in two asymptotic settings: (a) the number of features, p fixed, but the sample size, n → ∞ , and (b) both n and p tend to infinity. The theoretical results shed light onto the differences between the solutions based on the new penalty functions and those based on existing convex and nonconvex Bridge penalty functions. Our theory also shows that both Laplace and arctan penalties satisfy the oracle property. Finally, we also present results from a brief simulations study illustrating the performance of Laplace and arctan penalties based on the gradient descent optimization algorithm.

Improving processing speed in adolescents at clinical high risk for psychosis with the Specific COgnitive REmediation plus Surround (SCORES) intervention: Study protocol.

AIM: Recent preventative approaches with young people at clinical high risk for psychosis (CHR-P) have focused on the remediation of the cognitive deficits that are readily apparent and predictive of future illness. However, the small number of trials using cognitive remediation with CHR-P individuals have reported mixed results. The proposed 2-phased study will test an innovative internet-based and remotely-delivered Specific COgnitive REmediation plus Surround (or SCORES) intervention that targets early processing speed deficits in CHR-P adolescents aged 14-20 years old. METHODS: In the first R61 phase, a single-arm 2-year proof of concept study, 30 CHR-P individuals will receive SCORES for 10 weeks (4 h per week/40 h total) with a midpoint assessment at 20 h (5 weeks) to demonstrate target engagement and identify the optimal dose needed to engage the target. The Go/No-Go criteria to move to the R33 phase will be processing speed scores improving by a medium effect size (Cohen's d ≥ .6). The proposed package includes a set of complimentary support surround procedures to increase enjoyment and ensure that participants will complete the home-based training. In the second R33 phase, a 3-year pilot study, we will replicate target engagement in a new and larger sample of 54 CHR-P individuals randomized to SCORES (optimized dose) or to a video game playing control condition. In addition, the R33 phase will determine if changes in processing speed are associated with improved social functioning and decreasing attenuated positive symptoms. The support surround components of the intervention will remain constant across phases and conditions in the R33 phase to firmly establish the centrality of processing speed training for successful remediation. CONCLUSIONS: The SCORES study is a completely virtual intervention that targets a core cognitive mechanism, processing speed, which is a rate-limiting factor to higher order behaviours and clinical outcomes in CHR-P adolescents. The virtual nature of this study should increase feasibility as well improve the future scalability of the intervention with considerable potential for future dissemination as a complete treatment package.

Examining the Effectiveness of a Digital Media Campaign at Reducing the Duration of Untreated Psychosis in New York State: Results From a Stepped-wedge Randomized Controlled Trial.

BACKGROUND AND HYPOTHESIS: Longer duration of untreated psychosis (DUP) predicts worse outcomes in First Episode Psychosis (FEP). Searching online represents one of the first proactive step toward treatment initiation for many, yet few studies have informed how best to support FEP youth as they engage in early online help-seeking steps to care. STUDY DESIGN: Using a stepped-wedge randomized design, this project evaluated the effectiveness of a digital marketing campaign at reducing DUP and raising rates of referrals to FEP services by proactively targeting and engaging prospective patients and their adult allies online. STUDY RESULTS: Throughout the 18-month campaign, 41 372 individuals visited our website, and 371 advanced to remote clinical assessment (median age = 24.4), including 53 allies and 318 youth. Among those assessed (n = 371), 53 individuals (14.3%) reported symptoms consistent with psychotic spectrum disorders (62.2% female, mean age 20.7 years) including 39 (10.5%) reporting symptoms consistent with either Clinical High Risk (ie, attenuated psychotic symptoms; n = 26) or FEP (n = 13). Among those with either suspected CHR or FEP (n = 39), 20 (51.3%) successfully connected with care. The campaign did not result in significant differences in DUP. CONCLUSION: This study highlights the potential to leverage digital media to help identify and engage youth with early psychosis online. However, despite its potential, online education and professional support alone are not yet sufficient to expedite treatment initiation and reduce DUP.

Functional phenotypes in schizophrenia spectrum disorders: defining the constructs and identifying biopsychosocial correlates using data-driven methods.

Functional impairments contribute to poor quality of life in schizophrenia spectrum disorders (SSD). We sought to (Objective I) define the main functional phenotypes in SSD, then (Objective II) identify key biopsychosocial correlates, emphasizing interpretable data-driven methods. Objective I was tested on independent samples: Dataset I (N = 282) and Dataset II (N = 317), with SSD participants who underwent assessment of multiple functioning areas. Participants were clustered based on functioning. Objective II was evaluated in Dataset I by identifying key features for classifying functional phenotype clusters from among 65 sociodemographic, psychological, clinical, cognitive, and brain volume measures. Findings were replicated across latent discriminant analyses (LDA) and one-vs.-rest binomial regularized regressions to identify key predictors. We identified three clusters of participants in each dataset, demonstrating replicable functional phenotypes: Cluster 1-poor functioning across domains; Cluster 2-impaired Role Functioning, but partially preserved Independent and Social Functioning; Cluster 3-good functioning across domains. Key correlates were Avolition, anhedonia, left hippocampal volume, and measures of emotional intelligence and subjective social experience. Avolition appeared more closely tied to role functioning, and anhedonia to independent and social functioning. Thus, we found three replicable functional phenotypes with evidence that recovery may not be uniform across domains. Avolition and anhedonia were both critical but played different roles for different functional domains. It may be important to identify critical functional areas for individual patients and target interventions accordingly.

Overlapping and distinct gray and white matter abnormalities in schizophrenia and bipolar I disorder.

OBJECTIVES: Schizophrenia and bipolar disorder may share common neurobiological mechanisms, but few studies have directly compared gray and white matter structure in these disorders. We used diffusion-weighted magnetic resonance imaging and a region of interest based analysis to identify overlapping and distinct gray and white matter abnormalities in 35 patients with schizophrenia and 20 patients with bipolar I disorder in comparison to 56 healthy volunteers. METHODS: We examined fractional anisotropy within the white matter and mean diffusivity within the gray matter in 42 regions of interest defined on a probabilistic atlas following non-linear registration of the images to atlas space. RESULTS: Patients with schizophrenia had significantly lower fractional anisotropy in temporal (superior temporal and parahippocampal) and occipital (superior and middle occipital) white matter compared to patients with bipolar disorder and healthy volunteers. By contrast, both patient groups demonstrated significantly higher mean diffusivity in frontal (inferior frontal and lateral orbitofrontal) and temporal (superior temporal and parahippocampal) gray matter compared to healthy volunteers, but did not differ from each other. CONCLUSIONS: Our study implicates overlapping gray matter frontal and temporal lobe structural alterations in the neurobiology of schizophrenia and bipolar I disorder, but suggests that temporal and occipital lobe white matter deficits may be an additional risk factor for schizophrenia. Our findings may have relevance for future diagnostic classification systems and the identification of susceptibility genes for these disorders.

Potential application of elastic nets for shared polygenicity detection with adapted threshold selection.

Current research suggests that hundreds to thousands of single nucleotide polymorphisms (SNPs) with small to modest effect sizes contribute to the genetic basis of many disorders, a phenomenon labeled as polygenicity. Additionally, many such disorders demonstrate polygenic overlap, in which risk alleles are shared at associated genetic loci. A simple strategy to detect polygenic overlap between two phenotypes is based on rank-ordering the univariate p-values from two genome-wide association studies (GWASs). Although high-dimensional variable selection strategies such as Lasso and elastic nets have been utilized in other GWAS analysis settings, they are yet to be utilized for detecting shared polygenicity. In this paper, we illustrate how elastic nets, with polygenic scores as the dependent variable and with appropriate adaptation in selecting the penalty parameter, may be utilized for detecting a subset of SNPs involved in shared polygenicity. We provide theory to better understand our approaches, and illustrate their utility using synthetic datasets. Results from extensive simulations are presented comparing the elastic net approaches with the rank ordering approach, in various scenarios. Results from simulations studies exhibit one of the elastic net approaches to be superior when the correlations among the SNPs are high. Finally, we apply the methods on two real datasets to illustrate further the capabilities, limitations and differences among the methods.