Revisiting delusion subtypes in schizophrenia based on their underlying structures.

A clear understanding of the pathophysiology of schizophrenia and related spectrum disorders has been limited by clinical heterogeneity. We investigated whether relative severity and predominance of one or more delusion subtypes might yield clinically differentiable patient profiles. Patients (N = 286) with schizophrenia spectrum disorders (SSD) completed the 21-item Peters et al. Delusions Inventory (PDI-21). We performed factor analysis followed by k-means clustering to identify delusion factors and patient subtypes. Patients were further assessed via the Brief Psychiatric Rating Scale, Brief Negative Symptom Scale, Digit Symbol and Digit Substitution tasks, use of cannabis and tobacco, and stressful life events. The overall patient sample clustered into subtypes corresponding to Low-Delusion, Grandiose-Predominant, Paranoid-Predominant, and Pan-Delusion patients. Paranoid-Predominant and Pan-Delusion patients showed significantly higher burden of positive symptoms, while Low-Delusion patients showed the highest burden of negative symptoms. The Paranoia delusion factor score showed a positive association with Digit Symbol and Digit Substitution tasks in the overall sample, and the Paranoid-Predominant subtype exhibited the best performance on both tasks. Grandiose-Predominant patients showed significantly higher tobacco smoking severity than other subtypes, while Paranoid-Predominant patients were significantly more likely to have a lifetime diagnosis of Cannabis Use Disorder. We suggest that delusion self-report inventories such as the PDI-21 may be of utility in identifying sub-syndromes in SSD. From the current study, a Paranoid-Predominant form may be most distinctive, with features including less cognitive impairment and a stronger association with cannabis use.

Effects of independent versus dependent stressful life events on major symptom domains of schizophrenia.

We evaluated two models to link stressful life events (SLEs) with the psychopathology of schizophrenia spectrum disorders (SSD). We separated SLEs into independent (iSLEs, unlikely influenced by one's behavior) and dependent (dSLEs, likely influenced by one's behavior). Stress-diathesis and stress generation models were evaluated for the relationship between total, i- and d- SLEs and the severity of positive, negative, and depressive symptoms in participants with SSD. Participants with SSD (n = 286; 196 males; age = 37.5 ± 13.5 years) and community controls (n = 121; 83 males; 35.4 ± 13.9 years) completed self-report of lifetime negative total, i- and d- SLEs. Participants with SSD reported a significantly higher number of total SLEs compared to controls (B = 1.11, p = 6.4 × 10-6). Positive symptom severity was positively associated with the total number of SLEs (ß = 0.20, p = 0.001). iSLEs (ß = 0.11, p = 0.09) and dSLEs (ß = 0.21, p = 0.0006) showed similar association with positive symptoms (p = 0.16) suggesting stress-diathesis effects. Negative symptom severity was negatively associated with the number of SLEs (ß = -0.19, p = 0.003) and dSLEs (ß = -0.20, p = 0.001) but not iSLEs (ß = -0.04, p = 0.52), suggesting stress generation effects. Depressive symptom severity was positively associated with SLEs (ß = 0.34, p = 1.0 × 10-8), and the association was not statistically stronger for dSLEs (ß = 0.33, p = 2.7 × 10-8) than iSLEs (ß = 0.21, p = 0.0006), p = 0.085, suggesting stress-diathesis effects. The SLE - symptom relationships in SSD may be attributed to stress generation or stress-diathesis, depending on symptom domain. Findings call for a domain-specific approach to clinical intervention for SLEs in SSD.

Cortical connectomic mediations on gamma band synchronization in schizophrenia.

Aberrant gamma frequency neural oscillations in schizophrenia have been well demonstrated using auditory steady-state responses (ASSR). However, the neural circuits underlying 40 Hz ASSR deficits in schizophrenia remain poorly understood. Sixty-six patients with schizophrenia spectrum disorders and 85 age- and gender-matched healthy controls completed one electroencephalography session measuring 40 Hz ASSR and one imaging session for resting-state functional connectivity (rsFC) assessments. The associations between the normalized power of 40 Hz ASSR and rsFC were assessed via linear regression and mediation models. We found that rsFC among auditory, precentral, postcentral, and prefrontal cortices were positively associated with 40 Hz ASSR in patients and controls separately and in the combined sample. The mediation analysis further confirmed that the deficit of gamma band ASSR in schizophrenia was nearly fully mediated by three of the rsFC circuits between right superior temporal gyrus-left medial prefrontal cortex (MPFC), left MPFC-left postcentral gyrus (PoG), and left precentral gyrus-right PoG. Gamma-band ASSR deficits in schizophrenia may be associated with deficient circuitry level connectivity to support gamma frequency synchronization. Correcting gamma band deficits in schizophrenia may require corrective interventions to normalize these aberrant networks.

Computational Modeling of Electroencephalography and Functional Magnetic Resonance Imaging Paradigms Indicates a Consistent Loss of Pyramidal Cell Synaptic Gain in Schizophrenia.

BACKGROUND: Diminished synaptic gain-the sensitivity of postsynaptic responses to neural inputs-may be a fundamental synaptic pathology in schizophrenia. Evidence for this is indirect, however. Furthermore, it is unclear whether pyramidal cells or interneurons (or both) are affected, or how these deficits relate to symptoms. METHODS: People with schizophrenia diagnoses (PScz) (n = 108), their relatives (n = 57), and control subjects (n = 107) underwent 3 electroencephalography (EEG) paradigms-resting, mismatch negativity, and 40-Hz auditory steady-state response-and resting functional magnetic resonance imaging. Dynamic causal modeling was used to quantify synaptic connectivity in cortical microcircuits. RESULTS: Classic group differences in EEG features between PScz and control subjects were replicated, including increased theta and other spectral changes (resting EEG), reduced mismatch negativity, and reduced 40-Hz power. Across all 4 paradigms, characteristic PScz data features were all best explained by models with greater self-inhibition (decreased synaptic gain) in pyramidal cells. Furthermore, disinhibition in auditory areas predicted abnormal auditory perception (and positive symptoms) in PScz in 3 paradigms. CONCLUSIONS: First, characteristic EEG changes in PScz in 3 classic paradigms are all attributable to the same underlying parameter change: greater self-inhibition in pyramidal cells. Second, psychotic symptoms in PScz relate to disinhibition in neural circuits. These findings are more commensurate with the hypothesis that in PScz, a primary loss of synaptic gain on pyramidal cells is then compensated by interneuron downregulation (rather than the converse). They further suggest that psychotic symptoms relate to this secondary downregulation.

Multiple dimensions of stress vs. genetic effects on depression.

Many psychiatric disorders including depression involve complex interactions of genetics and environmental stressors. Environmental influence is challenging to measure objectively and account for in genetic studies because the necessary large population samples in these studies involve individuals with varying cultures and life experiences, clouding genetic findings. In a unique population with relative sociocultural homogeneity and a narrower range of types of stress experiences, we quantitatively assessed multiple stress dimensions and measured their potential influence in biasing the heritability estimate of depression. We quantified depressive symptoms, major lifetime stressors, current perceived stress, and a culturally specific community stress measure in individuals with depression-related diagnoses and community controls in Old Order Amish and Mennonite populations. Results showed that lifetime stressors measured by lifetime stressor inventory (R2 = 0.06, p = 2 × 10-5) and current stress measured by Perceived Stress Scale (R2 = 0.13, p < 1 × 10-6) were both associated with current depressive symptoms quantified by Beck Depression Inventory in community controls, but current stress was the only measure associated with current depressive symptoms in individuals with a depression diagnosis, and to a greater degree (R2 = 0.41, p < 1 × 10-6). A novel, culturally specific community stress measure demonstrated internal reliability and was associated with current stress but was not significantly related to depression. Heritability (h2) for depression diagnosis (0.46 ± 0.14) and quantitative depression severity as measured by Beck Depression Inventory (0.45 ± 0.12) were significant, but h2 for depression diagnosis decreased to 0.25 ± 0.14 once stressors were accounted for in the model. This quantifies and demonstrates the importance of accounting for environmental influence in reducing phenotypic heterogeneity of depression and improving the power and replicability of genetic association findings that can be better translated to patient groups.

White matter brain aging in relationship to schizophrenia and its cognitive deficit.

We hypothesized that cerebral white matter deficits in schizophrenia (SZ) are driven in part by accelerated white matter aging and are associated with cognitive deficits. We used a machine learning model to predict individual age from diffusion tensor imaging features and calculated the delta age (Δage) as the difference between predicted and chronological age. Through this approach, we translated multivariate white matter imaging features into an age-scaled metric and used it to test the temporal trends of accelerated aging-related white matter deficit in SZ and its association with the cognition. A feature selection procedure was first employed to choose fractional anisotropy values in 34 of 43 white fiber tracts. Using these features, a machine learning model was trained based on a training set consisted of 107 healthy controls (HC). The brain age of 166 SZs and 107 HCs in the testing set were calculated using this model. Then, we examined the SZ-HC group effect on Δage and whether this effect was moderated by chronological age using the regression spline model. The results showed that Δage was significantly elevated in the age > 30 group in patients (p < 0.001) but not in age ≤ 30 group (p = 0.364). Δage in patients was significantly and negatively associated with both working memory (ß = -0.176, p = 0.007) and processing speed (ß = -0.519, p = 0.035) while adjusting sex and chronological age. Overall, these findings indicate that the Δage is elevated in SZs and become significantly from the third decade of life; the increase of Δage in SZs is associated with the declined neurocognitive performance.

A White Matter Connection of Schizophrenia and Alzheimer's Disease.

Schizophrenia (SZ) is a severe psychiatric illness associated with an elevated risk for developing Alzheimer's disease (AD). Both SZ and AD have white matter abnormalities and cognitive deficits as core disease features. We hypothesized that aging in SZ patients may be associated with the development of cerebral white matter deficit patterns similar to those observed in AD. We identified and replicated aging-related increases in the similarity between white matter deficit patterns in patients with SZ and AD. The white matter "regional vulnerability index" (RVI) for AD was significantly higher in SZ patients compared with healthy controls in both the independent discovery (Cohen's d = 0.44, P = 1·10-5, N = 173 patients/230 control) and replication (Cohen's d = 0.78, P = 9·10-7, N = 122 patients/64 controls) samples. The degree of overlap with the AD deficit pattern was significantly correlated with age in patients (r = .21 and .29, P < .01 in discovery and replication cohorts, respectively) but not in controls. Elevated RVI-AD was significantly associated with cognitive measures in both SZ and AD. Disease and cognitive specificities were also tested in patients with mild cognitive impairment and showed intermediate overlap. SZ and AD have diverse etiologies and clinical courses; our findings suggest that white matter deficits may represent a key intersecting point for these 2 otherwise distinct diseases. Identifying mechanisms underlying this white matter deficit pattern may yield preventative and treatment targets for cognitive deficits in both SZ and AD patients.

Clinical and genetic validity of quantitative bipolarity.

Research has yet to provide a comprehensive understanding of the genetic basis of bipolar disorder (BP). In genetic studies, defining the phenotype by diagnosis may miss risk-allele carriers without BP. The authors aimed to test whether quantitatively detected subclinical symptoms of bipolarity identifies a heritable trait that infers risk for BP. The Quantitative Bipolarity Scale (QBS) was administered to 310 Old Order Amish or Mennonite individuals from multigenerational pedigrees; 110 individuals had psychiatric diagnoses (20 BP, 61 major depressive disorders (MDD), 3 psychotic disorders, 26 other psychiatric disorders). Familial aggregation of QBS was calculated using the variance components method to derive heritability and shared household effects. The QBS score was significantly higher in BP subjects (31.5 ± 3.6) compared to MDD (16.7 ± 2.0), other psychiatric diagnoses (7.0 ± 1.9), and no psychiatric diagnosis (6.0 ± 0.65) (all p < 0.001). QBS in the whole sample was significantly heritable (h2 = 0.46 ± 0.15, p < 0.001) while the variance attributed to the shared household effect was not significant (p = 0.073). When subjects with psychiatric illness were removed, the QBS heritability was similar (h2 = 0.59 ± 0.18, p < 0.001). These findings suggest that quantitative bipolarity as measured by QBS can separate BP from other psychiatric illnesses yet is significantly heritable with and without BP included in the pedigrees suggesting that the quantitative bipolarity describes a continuous heritable trait that is not driven by a discrete psychiatric diagnosis. Bipolarity trait assessment may be used to supplement the diagnosis of BP in future genetic studies and could be especially useful for capturing subclinical genetic contributions to a BP phenotype.

Functional network connectivity impairments and core cognitive deficits in schizophrenia.

Cognitive deficits contribute to functional disability in patients with schizophrenia and may be related to altered functional networks that serve cognition. We evaluated the integrity of major functional networks and assessed their role in supporting two cognitive functions affected in schizophrenia: processing speed (PS) and working memory (WM). Resting-state functional magnetic resonance imaging (rsfMRI) data, N = 261 patients and 327 controls, were aggregated from three independent cohorts and evaluated using Enhancing NeuroImaging Genetics through Meta Analysis rsfMRI analysis pipeline. Meta- and mega-analyses were used to evaluate patient-control differences in functional connectivity (FC) measures. Canonical correlation analysis was used to study the association between cognitive deficits and FC measures. Patients showed consistent patterns of cognitive and resting-state FC (rsFC) deficits across three cohorts. Patient-control differences in rsFC calculated using seed-based and dual-regression approaches were consistent (Cohen's d: 0.31 ± 0.09 and 0.29 ± 0.08, p < 10-4 ). RsFC measures explained 12-17% of the individual variations in PS and WM in the full sample and in patients and controls separately, with the strongest correlations found in salience, auditory, somatosensory, and default-mode networks. The pattern of association between rsFC (within-network) and PS (r = .45, p = .07) and WM (r = .36, p = .16), and rsFC (between-network) and PS (r = .52, p = 8.4 × 10-3 ) and WM (r = .47, p = .02), derived from multiple networks was related to effect size of patient-control differences in the functional networks. No association was detected between rsFC and current medication dose or psychosis ratings. Patients demonstrated significant reduction in several FC networks that may partially underlie some of the core neurocognitive deficits in schizophrenia. The strength of connectivity-cognition relationships in different networks was strongly associated with network's vulnerability to schizophrenia.

White Matter in Schizophrenia Treatment Resistance.

OBJECTIVE: Failure of antipsychotic medications to resolve symptoms in patients with schizophrenia creates a clinical challenge that is known as treatment resistance. The causes of treatment resistance are unknown, but it is associated with earlier age at onset and more severe cognitive deficits. The authors tested the hypothesis that white matter deficits that are involved in both neurodevelopment and severity of cognitive deficits in schizophrenia are associated with a higher risk of treatment resistance. METHODS: The study sample (N=122; mean age, 38.2 years) included schizophrenia patients at treatment initiation (N=45), patients whose symptoms were treatment responsive (N=40), and patients whose symptoms were treatment resistant (N=37), as well as healthy control subjects (N=78; mean age, 39.2 years). White matter regional vulnerability index (RVI) was tested as a predictor of treatment resistance and cognitive deficits. Higher RVI is indicative of better agreement between diffusion tensor imaging fractional anisotropy across the brain in an individual and the pattern identified by the largest-to-date meta-analysis of white matter deficits in schizophrenia. RESULTS: Patients with treatment-resistant symptoms showed the highest white matter RVI (mean=0.38 [SD=0.2]), which was significantly higher than the RVI among patients with treatment-responsive symptoms (mean=0.30 [SD=0.02]). At the onset of treatment, schizophrenia patients showed significantly higher RVI than healthy control subjects (mean=0.18 [SD=0.03] and mean=0.13 [SD=0.02], respectively). RVIs were significantly correlated with performance on processing speed and negative symptoms. CONCLUSIONS: Schizophrenia affects white matter microstructure in specific regional patterns. Susceptibility to white matter regional deficits is associated with an increased likelihood of treatment resistance. Developments to overcome schizophrenia treatment resistance should consider white matter as an important target.

Aberrant Frontostriatal Connectivity in Negative Symptoms of Schizophrenia.

Negative symptoms represent a distinct component of psychopathology in schizophrenia (SCZ) and are a stable construct over time. Although impaired frontostriatal connectivity has been frequently described in SCZ, its link with negative symptoms has not been carefully studied. We tested the hypothesis that frontostriatal connectivity at rest may be associated with the severity of negative symptoms in SCZ. Resting state functional connectivity (rsFC) data from 95 mostly medicated patients with SCZ and 139 healthy controls (HCs) were acquired. Negative symptoms were assessed using the Brief Negative Symptom Scale. The study analyzed voxel-wise rsFC between 9 frontal "seed regions" and the entire striatum, with the intention to reduce potential biases introduced by predefining any single frontal or striatal region. SCZ showed significantly reduced rsFC between the striatum and the right medial and lateral orbitofrontal cortex (OFC), lateral prefrontal cortex, and rostral anterior cingulate cortex compared with HCs. Further, rsFC between the striatum and the right medial OFC was significantly associated with negative symptom severity. The involved striatal regions were primarily at the ventral putamen. Our results support reduced frontostriatal functional connectivity in SCZ and implicate striatal connectivity with the right medial OFC in negative symptoms. This task-independent resting functional magnetic resonance imaging study showed that medial OFC-striatum functional connectivity is reduced in SCZ and associated with severity of negative symptoms. This finding supports a significant association between frontostriatal connectivity and negative symptoms and thus may provide a potential circuitry-level biomarker to study the neurobiological mechanisms of negative symptoms.

Association of White Matter With Core Cognitive Deficits in Patients With Schizophrenia.

Importance: Efforts to remediate the multiple cognitive function impairments in schizophrenia should consider white matter as one of the underlying neural mechanisms. Objective: To determine whether altered structural brain connectivity is responsible for 2 of the core cognitive deficits in schizophrenia- reduced information processing speed and impaired working memory. Design, Setting, and Participants: This cross-sectional study design took place in outpatient clinics from August 1, 2004, to August 31, 2015. Participants included 166 patients with schizophrenia and 213 healthy control individuals. These participants were from 3 independent cohorts, each of which had its own healthy control group. No participant had current or past neurological conditions or major medical conditions. Patients were diagnosed with either schizophrenia or schizoaffective disorder as defined by the DSM-IV. Controls had no Axis I psychiatric disorder. Main Outcomes and Measures: Mediation analyses and structural equation modeling were used to analyze the associations among processing speed, working memory, and white matter microstructures. Whole-brain and regional diffusion tensor imaging fractional anisotropy were used to measure white matter microstructures. Results: Of the study participants, the 166 patients with schizophrenia had a mean (SD) age of 38.2 (13.3) years and the 213 healthy controls had a mean (SD) age of 39.2 (14.0) years. There were significantly more male patients than controls in each of the 3 cohorts (117 [70%] vs 91 [43%]), but there were no significant differences in sex composition among the 3 cohorts. Patients had significantly reduced processing speed (Cohen d = 1.24; P = 6.91 × 10-30) and working memory deficits (Cohen d = 0.83; P = 1.10 × 10-14) as well as a significant whole-brain fractional anisotropy deficit (Cohen d = 0.63; P = 2.20 × 10-9). In schizophrenia, working memory deficit was mostly accounted for by processing speed deficit, but this deficit remained when accounting for working memory (Cohen d = 0.89; P = 2.21 × 10-17). Mediation analyses showed a significant association pathway from fractional anisotropy to processing speed to working memory (P = 5.01 × 10-7). The strength of this brain-to-cognition pathway in different white matter tracts was strongly associated with the severity of schizophrenia-associated fractional anisotropy deficits in the corresponding white matter tracts as determined by a meta-analysis (r = 0.85-0.94; all P < .001). The same pattern was observed in patients and controls either jointly or independently. Conclusions and Relevance: Study findings suggest that (1) processing speed contributes to the association between white matter microstructure and working memory in schizophrenia and (2) white matter impairment in schizophrenia is regional tract-specific, particularly in tracts normally supporting processing speed performance.

Lipid Metabolism, Abdominal Adiposity, and Cerebral Health in the Amish.

OBJECTIVE: To assess the association between peripheral lipid/fat profiles and cerebral gray matter (GM) and white matter (WM) in healthy Old Order Amish (OOA). METHODS: Blood lipids, abdominal adiposity, liver lipid contents, and cerebral microstructure were assessed in OOA (N = 64, 31 males/33 females, ages 18-77). Orthogonal factors were extracted from lipid and imaging adiposity measures. GM assessment used the Human Connectome Project protocol to measure whole-brain average cortical thickness. Diffusion-weighted imaging was used to derive WM fractional anisotropy and kurtosis anisotropy measurements. RESULTS: Lipid/fat measures were captured by three orthogonal factors explaining 80% of the variance. Factor one loaded on cholesterol and/or low-density lipoprotein cholesterol measurements; factor two loaded on triglyceride/liver measurements; and factor three loaded on abdominal fat measurements. A two-stage regression including age/sex (first stage) and the three factors (second stage) examined the peripheral lipid/fat effects. Factors two and three significantly contributed to WM measures after Bonferroni corrections (P < 0.007). No factor significantly contributed to GM. Blood pressure (BP) inclusion did not meaningfully alter the lipid/fat-WM relationship. CONCLUSIONS: Peripheral lipid/fat indicators were significantly and negatively associated with cerebral WM rather than with GM, independent of age and BP level. Dissecting the fat/lipid components contributing to different brain imaging parameters may open a new understanding of the body-brain connection through lipid metabolism.

Diffusion-weighted imaging uncovers likely sources of processing-speed deficits in schizophrenia.

Schizophrenia, a devastating psychiatric illness with onset in the late teens to early 20s, is thought to involve disrupted brain connectivity. Functional and structural disconnections of cortical networks may underlie various cognitive deficits, including a substantial reduction in the speed of information processing in schizophrenia patients compared with controls. Myelinated white matter supports the speed of electrical signal transmission in the brain. To examine possible neuroanatomical sources of cognitive deficits, we used a comprehensive diffusion-weighted imaging (DWI) protocol and characterized the white matter diffusion signals using diffusion kurtosis imaging (DKI) and permeability-diffusivity imaging (PDI) in patients (n = 74), their nonill siblings (n = 41), and healthy controls (n = 113). Diffusion parameters that showed significant patient-control differences also explained the patient-control differences in processing speed. This association was also found for the nonill siblings of the patients. The association was specific to processing-speed abnormality but not specific to working memory abnormality or psychiatric symptoms. Our findings show that advanced diffusion MRI in white matter may capture microstructural connectivity patterns and mechanisms that govern the association between a core neurocognitive measure-processing speed-and neurobiological deficits in schizophrenia that are detectable with in vivo brain scans. These non-Gaussian diffusion white matter metrics are promising surrogate imaging markers for modeling cognitive deficits and perhaps, guiding treatment development in schizophrenia.

Heterochronicity of white matter development and aging explains regional patient control differences in schizophrenia.

BACKGROUND: Altered brain connectivity is implicated in the development and clinical burden of schizophrenia. Relative to matched controls, schizophrenia patients show (1) a global and regional reduction in the integrity of the brain's white matter (WM), assessed using diffusion tensor imaging (DTI) fractional anisotropy (FA), and (2) accelerated age-related decline in FA values. In the largest mega-analysis to date, we tested if differences in the trajectories of WM tract development influenced patient-control differences in FA. We also assessed if specific tracts showed exacerbated decline with aging. METHODS: Three cohorts of schizophrenia patients (total n = 177) and controls (total n = 249; age = 18-61 years) were ascertained with three 3T Siemens MRI scanners. Whole-brain and regional FA values were extracted using ENIGMA-DTI protocols. Statistics were evaluated using mega- and meta-analyses to detect effects of diagnosis and age-by-diagnosis interactions. RESULTS: In mega-analysis of whole-brain averaged FA, schizophrenia patients had lower FA (P = 10-11 ) and faster age-related decline in FA (P = 0.02) compared with controls. Tract-specific heterochronicity measures, that is, abnormal rates of adolescent maturation and aging explained approximately 50% of the regional variance effects of diagnosis and age-by-diagnosis interaction in patients. Interactive, three-dimensional visualization of the results is available at www.enigma-viewer.org. CONCLUSION: WM tracts that mature later in life appeared more sensitive to the pathophysiology of schizophrenia and were more susceptible to faster age-related decline in FA values. Hum Brain Mapp 37:4673-4688, 2016. © 2016 Wiley Periodicals, Inc.

The common genetic influence over processing speed and white matter microstructure: Evidence from the Old Order Amish and Human Connectome Projects.

Speed with which brain performs information processing influences overall cognition and is dependent on the white matter fibers. To understand genetic influences on processing speed and white matter FA, we assessed processing speed and diffusion imaging fractional anisotropy (FA) in related individuals from two populations. Discovery analyses were performed in 146 individuals from large Old Order Amish (OOA) families and findings were replicated in 485 twins and siblings of the Human Connectome Project (HCP). The heritability of processing speed was h(2)=43% and 49% (both p<0.005), while the heritability of whole brain FA was h(2)=87% and 88% (both p<0.001), in the OOA and HCP, respectively. Whole brain FA was significantly correlated with processing speed in the two cohorts. Quantitative genetic analysis demonstrated a significant degree to which common genes influenced joint variation in FA and brain processing speed. These estimates suggested common sets of genes influencing variation in both phenotypes, consistent with the idea that common genetic variations contributing to white matter may also support their associated cognitive behavior.

Cortisol Reactivity to Stress and Its Association With White Matter Integrity in Adults With Schizophrenia.

OBJECTIVES: Although acute hypothalamic-pituitary-adrenal axis response to stress is often adaptive, prolonged responses may have detrimental effects. Many components of white matter structures are sensitive to prolonged cortisol exposure. We aimed to identify a behavioral laboratory assay for cortisol response related to brain pathophysiology in schizophrenia. We hypothesized that an abnormally prolonged cortisol response to stress may be linked to abnormal white matter integrity in patients with schizophrenia. METHODS: Acute and prolonged salivary cortisol response was measured outside the scanner at pretest and then at 0, 20, and 40 minutes after a psychological stress task in patients with schizophrenia (n = 45) and controls (n = 53). Tract-averaged white matter was measured by 64-direction diffusion tensor imaging in a subset of patients (n = 30) and controls (n = 33). RESULTS: Patients who did not tolerate the psychological stress task and quit had greater acute (t = 2.52 [p = .016] and t = 3.51 [p = .001] at 0 and 20 minutes) and prolonged (t = 3.62 [p = .001] at 40 minutes) cortisol reactivity compared with patients who finished the task. Abnormally prolonged cortisol reactivity in patients was significantly associated with reduced white matter integrity (r = -0.468, p = .009). Regardless of task completion status, acute cortisol response was not related to the white matter measures in patients or controls. CONCLUSIONS: This paradigm was successful at identifying a subset of patients whose cortisol response was associated with brain pathophysiology. Abnormal cortisol response may adversely affect white matter integrity, partly explaining this pathology observed in schizophrenia. Prolonged stress responses may be targeted for intervention to test for protective effects against white matter damages.

Edge-Centered DTI Connectivity Analysis: Application to Schizophrenia.

Diffusion tensor imaging (DTI) provides connectivity information that helps illuminate the processes underlying normal development as well as brain disorders such as autism and schizophrenia. Researchers have widely adopted graph representations to model DTI connectivity among brain structures; however, most measures of connectivity have been centered on nodes, rather than edges, in these graphs. We present an edge-based algorithm for assessing anatomic connectivity; this approach provides information about connections among brain structures, rather than information about structures themselves. This perspective allows us to formulate multivariate graph-based models of altered connectivity that distinguish among experimental groups. We demonstrate the utility of this approach by analyzing data from an ongoing study of schizophrenia.

Testing trait depression as a potential clinical domain in schizophrenia.

The DSM-5 includes depression as a dimension of psychosis. We tested whether persistent experience of depression, called 'trait depression', is a clinical feature separate from psychosis and several well-known, trait-like deficits of schizophrenia. 126 individuals with schizophrenia and 151 control participants completed the Maryland Trait and State Depression questionnaire, with a subset completing measures of cognition and functional capacity, and diffusion tensor imaging (n=73 patients and 102 controls for imaging analysis). Subjectively experienced, longitudinal trait depression is significantly higher in patients with schizophrenia compared with controls. Higher trait depression scores were associated with more severe psychosis. Surprisingly, individuals with higher trait depression manifested less cognitive and global functioning deficits. In addition, trait depression scores were positively associated with fractional anisotropy of white matter. Trait depression appears to be a highly relevant clinical domain in the care of patients with schizophrenia that also has distinct relationships with some other known traits of the disease. Trait depression may be an important contributor to the clinical heterogeneity of schizophrenia.

Multimodal white matter imaging to investigate reduced fractional anisotropy and its age-related decline in schizophrenia.

We hypothesized that reduced fractional anisotropy (FA) of water diffusion and its elevated aging-related decline in schizophrenia patients may be caused by elevated hyperintensive white matter (HWM) lesions, by reduced permeability-diffusivity index (PDI), or both. We tested this hypothesis in 40/30 control/patient participants. FA values for the corpus callosum were calculated from high angular resolution diffusion tensor imaging (DTI). Whole-brain volume of HWM lesions was quantified by 3D-T2w-fluid-attenuated inversion recovery (FLAIR) imaging. PDI for corpus callosum was ascertained using multi b-value diffusion imaging (15 b-shells with 30 directions per shell). Patients had significantly lower corpus callosum FA values, and there was a significant age-by-diagnosis interaction. Patients also had significantly reduced PDI but no difference in HWM volume. PDI and HWM volume were significant predictors of FA and captured the diagnosis-related variance. Separately, PDI robustly explained FA variance in schizophrenia patients, but not in controls. Conversely, HWM volume made equally significant contributions to variability in FA in both groups. The diagnosis-by-age effect of FA was explained by a PDI-by-diagnosis interaction. Post hoc testing showed a similar trend for PDI of gray mater. Our study demonstrated that reduced FA and its accelerated decline with age in schizophrenia were explained by pathophysiology indexed by PDI, rather than HWM volume.