Genome-Transcriptome-Functional Connectivity-Cognition Link Differentiates Schizophrenia From Bipolar Disorder

BACKGROUND AND HYPOTHESIS

Schizophrenia (SZ) and bipolar disorder (BD) share genetic risk factors, yet patients display differential levels of cognitive impairment. We hypothesized a genome-transcriptome-functional connectivity (frontoparietal)-cognition pathway linked to SZ-versus-BD differences, and conducted a multiscale study to delineate this pathway.

STUDY DESIGNS

Large genome-wide studies provided single nucleotide polymorphisms (SNPs) conferring more risk for SZ than BD, and we identified their regulated genes, namely SZ-biased SNPs and genes. We then (a) computed the polygenic risk score for SZ (PRSSZ) of SZ-biased SNPs and examined its associations with imaging-based frontoparietal functional connectivity (FC) and cognitive performances; (b) examined the spatial correlation between ex vivo postmortem expressions of SZ-biased genes and in vivo, SZ-related FC disruptions across frontoparietal regions; (c) investigated SZ-versus-BD differences in frontoparietal FC; and (d) assessed the associations of frontoparietal FC with cognitive performances.

STUDY RESULTS

PRSSZ of SZ-biased SNPs was significantly associated with frontoparietal FC and working memory test scores. SZ-biased genes' expressions significantly correlated with SZ-versus-BD differences in FC across frontoparietal regions. SZ patients showed more reductions in frontoparietal FC than BD patients compared to controls. Frontoparietal FC was significantly associated with test scores of multiple cognitive domains including working memory, and with the composite scores of all cognitive domains.

CONCLUSIONS

Collectively, these multiscale findings support the hypothesis that SZ-biased genetic risk, through transcriptome regulation, is linked to frontoparietal dysconnectivity, which in turn contributes to differential cognitive deficits in SZ-versus BD, suggesting that potential biomarkers for more precise patient stratification and treatment.

N-BiC: A Method for Multi-Component and Symptom Biclustering of Structural MRI Data: Application to Schizophrenia

OBJECTIVE

We propose and develop a novel biclustering (N-BiC) approach for performing N-way biclustering of neuroimaging data. Our approach is applicable to an arbitrary number of features from both imaging and behavioral data (e.g., symptoms). We applied it to structural MRI data from patients with schizophrenia.

METHODS

It uses a source-based morphometry approach [i.e., independent component analysis of gray matter segmentation maps] to decompose the data into a set of spatial maps, each of which includes regions that covary among individuals. Then, the loading parameters for components of interest are entered to an exhaustive search, which incorporates a modified depth-first search technique to carry out the biclustering, with the goal of obtaining submatrices where the selected rows (individuals) show homogeneity in their expressions of selected columns (components) and vice versa.

RESULTS

Findings demonstrate that multiple biclusters have an evident association with distinct brain networks for the different types of symptoms in schizophrenia. The study identifies two components: inferior temporal gyrus (16) and brainstem (7), which are related to positive (distortion/excess of normal function) and negative (diminution/loss of normal function) symptoms in schizophrenia, respectively.

CONCLUSION

N-BiC is a data-driven method of biclustering MRI data that can exhaustively explore relationships/substructures from a dataset without any prior information with a higher degree of robustness than earlier biclustering applications.

SIGNIFICANCE

The use of such approaches is important to investigate the underlying biological substrates of mental illness by grouping patients into homogeneous subjects, as the schizophrenia diagnosis is known to be relatively nonspecific and heterogeneous.

Glutamatergic and Neuronal Dysfunction in Gray and White Matter: A Spectroscopic Imaging Study in a Large Schizophrenia Sample

Glutamine plus glutamate (Glx), as well as N-acetylaspartate compounds (NAAc, N-acetylaspartate plus N-acetyl-aspartyl-glutamate), a marker of neuronal viability, can be quantified with proton magnetic resonance spectroscopy (1H-MRS). We used 1H-MRS imaging to assess Glx and NAAc, as well as total-choline (glycerophospho-choline plus phospho-choline), myo-inositol and total-creatine (creatine plus phosphocreatine) from an axial supraventricular slab of gray matter (GM, medial-frontal and medial-parietal) and white matter (WM, bilateral-frontal and bilateral-parietal) voxels. Schizophrenia subjects (N = 104) and healthy controls (N = 97) with a broad age range (16 to 65) were studied. In schizophrenia, Glx was increased in GM (P < .001) and WM (P = .01), regardless of age. However, with greater age, NAAc increased in GM (P < .001) but decreased in WM (P < .001) in schizophrenia. In patients, total creatine decreased with age in WM (P < .001). Finally, overall cognitive score correlated positively with WM neurometabolites in controls but negatively in the schizophrenia group (NAAc, P < .001; and creatine [only younger], P < .001). We speculate the results support an ongoing process of increased glutamate metabolism in schizophrenia. Later in the illness, disease progression is suggested by increased cortical compaction without neuronal loss (elevated NAAc) and reduced axonal integrity (lower NAAc). Furthermore, this process is associated with fundamentally altered relationships between neurometabolite concentrations and cognitive function in schizophrenia.

Multimodal Classification of Schizophrenia Patients with MEG and fMRI Data Using Static and Dynamic Connectivity Measures

Mental disorders like schizophrenia are currently diagnosed by physicians/psychiatrists through clinical assessment and their evaluation of patient's self-reported experiences as the illness emerges. There is great interest in identifying biological markers of prognosis at the onset of illness, rather than relying on the evolution of symptoms across time. Functional network connectivity, which indicates a subject's overall level of "synchronicity" of activity between brain regions, demonstrates promise in providing individual subject predictive power. Many previous studies reported functional connectivity changes during resting-state using only functional magnetic resonance imaging (fMRI). Nevertheless, exclusive reliance on fMRI to generate such networks may limit the inference of the underlying dysfunctional connectivity, which is hypothesized to be a factor in patient symptoms, as fMRI measures connectivity via hemodynamics. Therefore, combination of connectivity assessments using fMRI and magnetoencephalography (MEG), which more directly measures neuronal activity, may provide improved classification of schizophrenia than either modality alone. Moreover, recent evidence indicates that metrics of dynamic connectivity may also be critical for understanding pathology in schizophrenia. In this work, we propose a new framework for extraction of important disease related features and classification of patients with schizophrenia based on using both fMRI and MEG to investigate functional network components in the resting state. Results of this study show that the integration of fMRI and MEG provides important information that captures fundamental characteristics of functional network connectivity in schizophrenia and is helpful for prediction of schizophrenia patient group membership. Combined fMRI/MEG methods, using static functional network connectivity analyses, improved classification accuracy relative to use of fMRI or MEG methods alone (by 15 and 12.45%, respectively), while combined fMRI/MEG methods using dynamic functional network connectivity analyses improved classification up to 5.12% relative to use of fMRI alone and up to 17.21% relative to use of MEG alone.

Patterns of Gray Matter Abnormalities in Schizophrenia Based on an International Mega-analysis

Analyses of gray matter concentration (GMC) deficits in patients with schizophrenia (Sz) have identified robust changes throughout the cortex. We assessed the relationships between diagnosis, overall symptom severity, and patterns of gray matter in the largest aggregated structural imaging dataset to date. We performed both source-based morphometry (SBM) and voxel-based morphometry (VBM) analyses on GMC images from 784 Sz and 936 controls (Ct) across 23 scanning sites in Europe and the United States. After correcting for age, gender, site, and diagnosis by site interactions, SBM analyses showed 9 patterns of diagnostic differences. They comprised separate cortical, subcortical, and cerebellar regions. Seven patterns showed greater GMC in Ct than Sz, while 2 (brainstem and cerebellum) showed greater GMC for Sz. The greatest GMC deficit was in a single pattern comprising regions in the superior temporal gyrus, inferior frontal gyrus, and medial frontal cortex, which replicated over analyses of data subsets. VBM analyses identified overall cortical GMC loss and one small cluster of increased GMC in Sz, which overlapped with the SBM brainstem component. We found no significant association between the component loadings and symptom severity in either analysis. This mega-analysis confirms that the commonly found GMC loss in Sz in the anterior temporal lobe, insula, and medial frontal lobe form a single, consistent spatial pattern even in such a diverse dataset. The separation of GMC loss into robust, repeatable spatial patterns across multiple datasets paves the way for the application of these methods to identify subtle genetic and clinical cohort effects.

Increased glutamine in patients undergoing long-term treatment for schizophrenia: a proton magnetic resonance spectroscopy study at 3 T

IMPORTANCE

The N-methyl-d-aspartic acid receptor hypofunction model of schizophrenia predicts a paradoxical increase in synaptic glutamate release. In vivo measurement of glutamatergic neurotransmission in humans is challenging, but glutamine, the principal metabolite of synaptic glutamate, can be quantified with proton magnetic resonance spectroscopy (1H-MRS). Although a few studies have measured glutamate, glutamine, and glutamine to glutamate ratio, it is not clear which of these 1H-MRS indices of glutamatergic neurotransmission is altered in schizophrenia.

OBJECTIVE

To examine glutamine, glutamate, and glutamine to glutamate ratio in the dorsal anterior cingulate, as well as their relationships with symptoms and cognition in schizophrenia.

DESIGN, SETTING, AND PARTICIPANTS

Cross-sectional design using 3-T 1H-MRS in participants recruited from university-based psychiatric outpatient clinics who underwent neuroimaging at an affiliated research facility. Participants were 84 patients with a DSM-IV-TR diagnosis of schizophrenia and 81 psychiatrically healthy volunteers, matched in age, sex, ethnicity, and occupational level to the head of household of family of origin.

MAIN OUTCOMES AND MEASURES

Glutamine, glutamate, and glutamine to glutamate ratio. Also symptoms and cognition.

RESULTS

Glutamine was increased in the schizophrenia group (P = .01) as well as the glutamine to glutamate ratio (P = .007) but not glutamate (P = .89). Glutamine levels were positively correlated with severity of psychotic symptoms (P = .02). Choline was also increased in schizophrenia (P = .002).

CONCLUSIONS AND RELEVANCE

Elevated glutamine, which was directly related to psychotic symptoms, is consistent with increased glutamatergic synaptic release in schizophrenia, as predicted by the N-methyl-d-aspartic acid receptor hypofunction model. Further understanding the underlying mechanism of glutamatergic dysfunction in schizophrenia may lead to new pharmacological strategies to treat psychosis.

Posttraumatic stress disorder and its comorbidities among American Indian veterans

Goal consists of describing the demographic and comorbid characteristics associated with Posttraumatic Stress Disorder (PTSD) among American Indian veterans with any lifetime Axis 1 disorder. Sample included 252 American Indian veterans, obtained from a community sample of 557, using targeted sampling designed to provide a representative sample, structured to include equal numbers of rural and urban veterans and a twofold over sample of women. Data collection involved lifetime diagnoses based on the Diagnostic Interview Schedule/Quick Version/DSM-III-R, demographic characteristics, and combat exposure. Findings Bivariate comparisons showed positive relationships of PTSD with combat exposure, mood disorder and anxiety disorders (excluding PTSD), but a negative relationship with substance use disorder. Binary logistic regression analyses showed an independent association of PTSD with mood and anxiety disorders as well as combat exposure.

Combination of Resting State fMRI, DTI, and sMRI Data to Discriminate Schizophrenia by N-way MCCA + jICA

Multimodal brain imaging data have shown increasing utility in answering both scientifically interesting and clinically relevant questions. Each brain imaging technique provides a different view of brain function or structure, while multimodal fusion capitalizes on the strength of each and may uncover hidden relationships that can merge findings from separate neuroimaging studies. However, most current approaches have focused on pair-wise fusion and there is still relatively little work on N-way data fusion and examination of the relationships among multiple data types. We recently developed an approach called “mCCA + jICA” as a novel multi-way fusion method which is able to investigate the disease risk factors that are either shared or distinct across multiple modalities as well as the full correspondence across modalities. In this paper, we applied this model to combine resting state fMRI (amplitude of low-frequency fluctuation, ALFF), gray matter (GM) density, and DTI (fractional anisotropy, FA) data, in order to elucidate the abnormalities underlying schizophrenia patients (SZs, n = 35) relative to healthy controls (HCs, n = 28). Both modality-common and modality-unique abnormal regions were identified in SZs, which were then used for successful classification for seven modality-combinations, showing the potential for a broad applicability of the mCCA + jICA model and its results. In addition, a pair of GM-DTI components showed significant correlation with the positive symptom subscale of Positive and Negative Syndrome Scale (PANSS), suggesting that GM density changes in default model network along with white-matter disruption in anterior thalamic radiation are associated with increased positive PANSS. Findings suggest the DTI anisotropy changes in frontal lobe may relate to the corresponding functional/structural changes in prefrontal cortex and superior temporal gyrus that are thought to play a role in the clinical expression of SZ.

Nicotine dependence and psychiatric and substance use comorbidities in a sample of American Indian male veterans

BACKGROUND

American Indians and Alaska Natives have the highest rates of nicotine dependence in the U.S. However, studies analyzing associations between nicotine dependence and psychiatric and substance use disorders in these groups have been limited.

METHODS

This study analyzes the co-occurrence of current and lifetime DSM-III-R nicotine dependence with psychiatric and substance use disorders in a community sample of 480 American Indian male veterans.

RESULTS

Lifetime nicotine dependence (23.3%) was associated with all lifetime disorders studied, including alcohol use and drug use disorders, affective and anxiety disorders, PTSD, pathological gambling and antisocial personality disorder. Current nicotine dependence was present in 19% of the sample and significantly associated with current affective and gambling disorder.

CONCLUSIONS

Substantial co-morbidity exists between nicotine dependence and other substance abuse and psychiatric disorders among this sample of American Indian male veterans, particularly for lifetime diagnoses. Screening for all psychiatric disorders among American Indian/Alaska Native smokers may be warranted. Although these results are similar to those observed among the general U.S. population, unique risk factors exist among American Indians/Alaska Natives which may require further attention. Specific public health and clinical interventions to reduce the rate of nicotine dependence among American Indians/Alaska Natives are recommended.

The effects of stimulus modality and frequency of stimulus presentation on cross-modal distraction

Selective attention produces enhanced activity (attention-related modulations [ARMs]) in cortical regions corresponding to the attended modality and suppressed activity in cortical regions corresponding to the ignored modality. However, effects of behavioral context (e.g., temporal vs. spatial tasks) and basic stimulus properties (i.e., stimulus frequency) on ARMs are not fully understood. The current study used functional magnetic resonance imaging to investigate selectively attending and responding to either a visual or auditory metronome in the presence of asynchronous cross-modal distractors of 3 different frequencies (0.5, 1, and 2 Hz). Attending to auditory information while ignoring visual distractors was generally more efficient (i.e., required coordination of a smaller network) and less effortful (i.e., decreased interference and presence of ARMs) than attending to visual information while ignoring auditory distractors. However, these effects were modulated by stimulus frequency, as attempting to ignore auditory information resulted in the obligatory recruitment of auditory cortical areas during infrequent (0.5 Hz) stimulation. Robust ARMs were observed in both visual and auditory cortical areas at higher frequencies (2 Hz), indicating that participants effectively allocated attention to more rapidly presented targets. In summary, results provide neuroanatomical correlates for the dominance of the auditory modality in behavioral contexts that are highly dependent on temporal processing.

Severity of combat-related posttraumatic stress disorder versus noncombat-related posttraumatic stress disorder: a community-based study in American Indian and Hispanic veterans

The goal of the study was to compare severity of combat-related posttraumatic stress disorder (PTSD) versus noncombat-related PTSD in a group known to have high rates of combat-related PTSD. Sample consisted of 255 male American Indian and Hispanic veterans with lifetime PTSD who were contacted in communities in 2 regions of the country. Measures of PTSD severity included current posttraumatic symptoms, remission from lifetime PTSD, lifetime severity of alcohol-drug related problems, and mental health treatment history. Our findings revealed that veterans with combat-related PTSD had more severe posttraumatic symptoms, were less apt to have remitted from PTSD during the last year, and-contrary to expectation-were less apt to have sought mental health treatment since military duty. In conclusion, combat-related PTSD was more severe, as compared with noncombat-related PTSD, in this group, on 2 out of 5 measures. A low rate of mental health treatment since military duty may have contributed to increased symptoms and a lower remission rate.

Remission from pathological gambling among Hispanics and Native Americans

This community survey studied remission from pathological gambling (PG) among American Indian (AI) and Hispanic American (HA) veterans. Remission was defined as having a lifetime diagnosis of PG, but no gambling symptoms in the last year. Sample consisted of 1624 AI and Hispanic veterans. Instruments included demographic data, the computer-based algorithmic Quick Diagnostic Interview Schedule Symptom, and three symptom checklists, one each for substance related problems (MAST/AD), anxiety and depressive symptoms (BSI-57), and combat-related post-trauma symptoms (PCL/M). Remission was associated with absence of a current Axis 1 diagnosis, especially absence of a current post-traumatic stress disorder.

Lifetime prevalence of pathological gambling among american Indian and Hispanic American Veterans

OBJECTIVES

We examined the prevalence and clinical correlates of pathological gambling among 1228 American Indian and Hispanic American veterans in the southwest and north central regions of the United States.

METHODS

We surveyed a community sample of American Indian and Hispanic American veterans to obtain data on psychiatric disorder and treatment.

RESULTS

American Indian veterans had a 10% lifetime prevalence of pathological gambling. The Hispanic American lifetime prevalence was less than that of the American Indian veterans but higher than the prevalence found for Hispanic American veterans in other surveys. Comorbid conditions associated with pathological gambling included substance, mood, and antisocial personality disorders. Ready access to casino gambling may encourage, support, or contribute to high rates of pathological gambling in both men and women.

CONCLUSIONS

A 70% lifetime comorbidity of psychiatric disorders suggests that early interventions for pathological gambling should consider common psychiatric conditions rather than focusing on pathological gambling alone.

Perceived barriers to VA mental health care among Upper Midwest American Indian veterans: description and associations

OBJECTIVES

This community-based study was undertaken to understand why Native-American veterans in the Upper Midwest choose not to use VA mental health services despite high rates of certain psychiatric disorders.

RESEARCH DESIGN

A sample consisting of 543 Native-American veterans was obtained using a focused-intensive nonprobability sampling method, structured to over-sample urban and female veterans. Data sources included (1) interview (ie, an open-ended query regarding barriers to VA mental health care), (2) questionnaire (demography, psychiatric rating scales), and (3) computer-based diagnostic questionnaire, the Quick Diagnostic Interview Schedule, and a treatment questionnaire.

RESULTS

These data confirmed that Native-American veterans were less apt to employ VA mental health services as compared with other professional and nonprofessional mental health services. Perceived barriers to VA mental health care were coded using a schema developed among Native American and Hispanic VA workers. Types of perceived barriers were qualitatively similar to those obtained from the VA workers, ie, barriers in the VA system, among Native-American veterans themselves, in VA staff members, and among Native American families and communities. Demographic and clinical characteristics among these 543 veterans were not associated with presence-versus-absence of barrier reporting. Among those who did report any barriers, veterans who used more traditional-alternative-complementary (TAC) care reported more barriers than did other veterans. Secondary analysis of those who reported barriers and used TAC revealed that this group had high current rates of Mood Disorder and PTSD symptoms, and high lifetime rates of PTSD and Mood Disorder. Although this latter group had tended to use VA mental health services in the past, they had generally not used them in the last year.