Combining neuroimaging and brain stimulation to test alternative causal pathways for nicotine addiction in schizophrenia.

The smoking rate is high in patients with schizophrenia. Brain stimulation targeting conventional brain circuits associated with nicotine addiction has also yielded mixed results. We aimed to identify alternative circuitries associated with nicotine addiction in both the general population and schizophrenia, and then test whether modulation of such circuitries may alter nicotine addiction behaviors in schizophrenia. In Study I of 40 schizophrenia smokers and 51 non-psychiatric smokers, cross-sectional neuroimaging analysis identified resting state functional connectivity (rsFC) between the dorsomedial prefrontal cortex (dmPFC) and multiple extended amygdala regions to be most robustly associated with nicotine addiction severity in healthy controls and schizophrenia patients (p = 0.006 to 0.07). In Study II with another 30 patient smokers, a proof-of-concept, patient- and rater-blind, randomized, sham-controlled rTMS design was used to test whether targeting the newly identified dmPFC location may causally enhance the rsFC and reduce nicotine addiction in schizophrenia. Although significant interactions were not observed, exploratory analyses showed that this dmPFC-extended amygdala rsFC was enhanced by 4-week active 10Hz rTMS (p = 0.05) compared to baseline; the severity of nicotine addiction showed trends of reduction after 3 and 4 weeks (p ≤ 0.05) of active rTMS compared to sham; Increased rsFC by active rTMS predicted reduction of cigarettes/day (R = -0.56, p = 0.025 uncorrected) and morning smoking severity (R = -0.59, p = 0.016 uncorrected). These results suggest that the dmPFC-extended amygdala circuit may be linked to nicotine addiction in schizophrenia and healthy individuals, and future efforts targeting its underlying pathophysiological mechanisms may yield more effective treatment for nicotine addiction.

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.

An in-depth association analysis of genetic variants within nicotine-related loci: Meeting in middle of GWAS and genetic fine-mapping.

In the last two decades of Genome-wide association studies (GWAS), nicotine-dependence-related genetic loci (e.g., nicotinic acetylcholine receptor - nAChR subunit genes) are among the most replicable genetic findings. Although GWAS results have reported tens of thousands of SNPs within these loci, further analysis (e.g., fine-mapping) is required to identify the causal variants. However, it is computationally challenging for existing fine-mapping methods to reliably identify causal variants from thousands of candidate SNPs based on the posterior inclusion probability. To address this challenge, we propose a new method to select SNPs by jointly modeling the SNP-wise inference results and the underlying structured network patterns of the linkage disequilibrium (LD) matrix. We use adaptive dense subgraph extraction method to recognize the latent network patterns of the LD matrix and then apply group LASSO to select causal variant candidates. We applied this new method to the UK biobank data to identify the causal variant candidates for nicotine addiction. Eighty-one nicotine addiction-related SNPs (i.e.,-log(p) > 50) of nAChR were selected, which are highly correlated (average r2>0.8) although they are physically distant (e.g., >200 kilobase away) and from various genes. These findings revealed that distant SNPs from different genes can show higher LD r2 than their neighboring SNPs, and jointly contribute to a complex trait like nicotine addiction.

Brain deficit patterns of metabolic illnesses overlap with those for major depressive disorder: A new metric of brain metabolic disease.

Metabolic illnesses (MET) are detrimental to brain integrity and are common comorbidities in patients with mental illnesses, including major depressive disorder (MDD). We quantified effects of MET on standard regional brain morphometric measures from 3D brain MRI as well as diffusion MRI in a large sample of UK BioBank participants. The pattern of regional effect sizes of MET in non-psychiatric UKBB subjects was significantly correlated with the spatial profile of regional effects reported by the largest meta-analyses in MDD but not in bipolar disorder, schizophrenia or Alzheimer's disease. We used a regional vulnerability index (RVI) for MET (RVI-MET) to measure individual's brain similarity to the expected patterns in MET in the UK Biobank sample. Subjects with MET showed a higher effect size for RVI-MET than for any of the individual brain measures. We replicated elevation of RVI-MET in a sample of MDD participants with MET versus non-MET. RVI-MET scores were significantly correlated with the volume of white matter hyperintensities, a neurological consequence of MET and age, in both groups. Higher RVI-MET in both samples was associated with obesity, tobacco smoking and frequent alcohol use but was unrelated to antidepressant use. In summary, MET effects on the brain were regionally specific and individual similarity to the pattern was more strongly associated with MET than any regional brain structural metric. Effects of MET overlapped with the reported brain differences in MDD, likely due to higher incidence of MET, smoking and alcohol use in subjects with MDD.

Evaluating the causal effect of tobacco smoking on white matter brain aging: a two-sample Mendelian randomization analysis in UK Biobank.

BACKGROUND AND AIMS: Tobacco smoking is a risk factor for impaired brain function, but its causal effect on white matter brain aging remains unclear. This study aimed to measure the causal effect of tobacco smoking on white matter brain aging. DESIGN: Mendelian randomization (MR) analysis using two non-overlapping data sets (with and without neuroimaging data) from UK Biobank (UKB). The group exposed to smoking and control group consisted of current smokers and never smokers, respectively. Our main method was generalized weighted linear regression with other methods also included as sensitivity analysis. SETTING: United Kingdom. PARTICIPANTS: The study cohort included 23 624 subjects [10 665 males and 12 959 females with a mean age of 54.18 years, 95% confidence interval (CI) = 54.08, 54.28]. MEASUREMENTS: Genetic variants were selected as instrumental variables under the MR analysis assumptions: (1) associated with the exposure; (2) influenced outcome only via exposure; and (3) not associated with confounders. The exposure smoking status (current versus never smokers) was measured by questionnaires at the initial visit (2006-10). The other exposure, cigarettes per day (CPD), measured the average number of cigarettes smoked per day for current tobacco users over the life-time. The outcome was the 'brain age gap' (BAG), the difference between predicted brain age and chronological age, computed by training machine learning model on a non-overlapping set of never smokers. FINDINGS: The estimated BAG had a mean of 0.10 (95% CI = 0.06, 0.14) years. The MR analysis showed evidence of positive causal effect of smoking behaviors on BAG: the effect of smoking is 0.21 (in years, 95% CI = 6.5 × 10-3 , 0.41; P-value = 0.04), and the effect of CPD is 0.16 year/cigarette (UKB: 95% CI = 0.06, 0.26; P-value = 1.3 × 10-3 ; GSCAN: 95% CI = 0.02, 0.31; P-value = 0.03). The sensitivity analyses showed consistent results. CONCLUSIONS: There appears to be a significant causal effect of smoking on the brain age gap, which suggests that smoking prevention can be an effective intervention for accelerated brain aging and the age-related decline in cognitive function.

Modeling multivariate age-related imaging variables with dependencies.

Neuroimaging techniques have been increasingly used to understand the neural biology of aging brains. The neuroimaging variables from distinct brain locations and modalities can exhibit age-related patterns that reflect localized neural decline. However, it is a challenge to identify the impacts of risk factors (eg, mental disorders) on multivariate imaging variables while simultaneously accounting for the dependence structure and nonlinear age trajectories using existing tools. We propose a mixed-effects model to address this challenge by building random effects based on the latent brain aging status. We develop computationally efficient algorithms to estimate the parameters of new random effects. The simulations show that our approach provides accurate parameter estimates, improves the inference efficiency, and reduces the root mean square error compared to existing methods. We further apply this method to the UK Biobank data to investigate the effects of tobacco smoking on the white matter integrity of the entire brain during aging and identify the adverse effects on white matter integrity with multiple fiber tracts.

White Matter Integrity and Nicotine Dependence: Evaluating Vertical and Horizontal Pleiotropy.

Tobacco smoking is an addictive behavior that supports nicotine dependence and is an independent risk factor for cancer and other illnesses. Its neurogenetic mechanisms are not fully understood but may act through alterations in the cerebral white matter (WM). We hypothesized that the vertical pleiotropic pathways, where genetic variants influence a trait that in turn influences another trait, link genetic factors, integrity of cerebral WM, and nicotine addiction. We tested this hypothesis using individual genetic factors, WM integrity measured by fractional anisotropy (FA), and nicotine dependence-related smoking phenotypes, including smoking status (SS) and cigarettes per day (CPDs), in a large epidemiological sample collected by the UK Biobank. We performed a genome-wide association study (GWAS) to identify previously reported loci associated with smoking behavior. Smoking was found to be associated with reduced WM integrity in multiple brain regions. We then evaluated two competing vertical pathways: Genes → WM integrity → Smoking versus Genes → Smoking → WM integrity and a horizontal pleiotropy pathway where genetic factors independently affect both smoking and WM integrity. The causal pathway analysis identified 272 pleiotropic single-nucleotide polymorphisms (SNPs) whose effects on SS were mediated by FA, as well as 22 pleiotropic SNPs whose effects on FA were mediated by CPD. These SNPs were mainly located in important susceptibility genes for smoking-induced diseases NCAM1 and IREB2. Our findings revealed the role of cerebral WM in the maintenance of the complex addiction and provided potential genetic targets for future research in examining how changes in WM integrity contribute to the nicotine effects on the brain.

Meta-Analysis of Transcriptome-Wide Association Studies across 13 Brain Tissues Identified Novel Clusters of Genes Associated with Nicotine Addiction.

Genome-wide association studies (GWAS) have identified and reproduced thousands of diseases associated loci, but many of them are not directly interpretable due to the strong linkage disequilibrium among variants. Transcriptome-wide association studies (TWAS) incorporated expression quantitative trait loci (eQTL) cohorts as a reference panel to detect associations with the phenotype at the gene level and have been gaining popularity in recent years. For nicotine addiction, several important susceptible genetic variants were identified by GWAS, but TWAS that detected genes associated with nicotine addiction and unveiled the underlying molecular mechanism were still lacking. In this study, we used eQTL data from the Genotype-Tissue Expression (GTEx) consortium as a reference panel to conduct tissue-specific TWAS on cigarettes per day (CPD) over thirteen brain tissues in two large cohorts: UK Biobank (UKBB; number of participants (N) = 142,202) and the GWAS & Sequencing Consortium of Alcohol and Nicotine use (GSCAN; N = 143,210), then meta-analyzing the results across tissues while considering the heterogeneity across tissues. We identified three major clusters of genes with different meta-patterns across tissues consistent in both cohorts, including homogenous genes associated with CPD in all brain tissues; partially homogeneous genes associated with CPD in cortex, cerebellum, and hippocampus tissues; and, lastly, the tissue-specific genes associated with CPD in only a few specific brain tissues. Downstream enrichment analyses on each gene cluster identified unique biological pathways associated with CPD and provided important biological insights into the regulatory mechanism of nicotine dependence in the brain.

NeuroMark: An automated and adaptive ICA based pipeline to identify reproducible fMRI markers of brain disorders.

Many mental illnesses share overlapping or similar clinical symptoms, confounding the diagnosis. It is important to systematically characterize the degree to which unique and similar changing patterns are reflective of brain disorders. Increasing sharing initiatives on neuroimaging data have provided unprecedented opportunities to study brain disorders. However, it is still an open question on replicating and translating findings across studies. Standardized approaches for capturing reproducible and comparable imaging markers are greatly needed. Here, we propose a pipeline based on the priori-driven independent component analysis, NeuroMark, which is capable of estimating brain functional network measures from functional magnetic resonance imaging (fMRI) data that can be used to link brain network abnormalities among different datasets, studies, and disorders. NeuroMark automatically estimates features adaptable to each individual subject and comparable across datasets/studies/disorders by taking advantage of the reliable brain network templates extracted from 1828 healthy controls as guidance. Four studies including 2442 subjects were conducted spanning six brain disorders (schizophrenia, autism spectrum disorder, mild cognitive impairment, Alzheimer's disease, bipolar disorder, and major depressive disorder) to evaluate validity of the proposed pipeline from different perspectives (replication of brain abnormalities, cross-study comparison, identification of subtle brain changes, and multi-disorder classification using identified biomarkers). Our results highlight that NeuroMark effectively identified replicated brain network abnormalities of schizophrenia across different datasets; revealed interesting neural clues on the overlap and specificity between autism and schizophrenia; demonstrated brain functional impairments present to varying degrees in mild cognitive impairments and Alzheimer's disease; and captured biomarkers that achieved good performance in classifying bipolar disorder and major depressive disorder.

Evidence for genetic correlation between human cerebral white matter microstructure and inflammation.

White matter microstructure is affected by immune system activity via the actions of circulating pro-inflammatory cytokines. Although white matter microstructure and inflammatory measures are significantly heritable, it is unclear if overlapping genetic factors influence these traits in humans. We conducted genetic correlation analyses of these traits using randomly ascertained extended pedigrees from the Genetics of Brain Structure and Function Study (N = 1862, 59% females, ages 18-97 years; 42 ± 15.7). White matter microstructure was assessed using fractional anisotropy (FA) calculated from diffusion tensor imaging (DTI). Circulating levels (pg/mL) of pro-inflammatory cytokines (IL-6, IL-8, and TNFα) phenotypically associated with white matter microstructure were quantified from blood serum. All traits were significantly heritable (h2 ranging from 0.41 to 0.66 for DTI measures and from 0.18 to 0.30 for inflammatory markers). Phenotypically, higher levels of circulating inflammatory markers were associated with lower FA values across the brain (r = -.03 to r = -.17). There were significant negative genetic correlations between most DTI measures and IL-8 and TNFα, although effects for TNFα were no longer significant when covarying for body mass index. Genetic correlations between DTI measures and IL-6 were not significant. Understanding the genetic correlation between specific inflammatory markers and DTI measures may help researchers focus questions related to inflammatory processes and brain structure.

White matter and hypoxic hypobaria in humans.

Occupational exposure to hypobaria (low atmospheric pressure) is a risk factor for reduced white matter integrity, increased white matter hyperintensive burden, and decline in cognitive function. We tested the hypothesis that a discrete hypobaric exposure will have a transient impact on cerebral physiology. Cerebral blood flow, fractional anisotropy of water diffusion in cerebral white matter, white matter hyperintensity volume, and concentrations of neurochemicals were measured at baseline and 24 hr and 72 hr postexposure in N = 64 healthy aircrew undergoing standard US Air Force altitude chamber training and compared to N = 60 controls not exposed to hypobaria. We observed that hypobaric exposure led to a significant rise in white matter cerebral blood flow (CBF) 24 hr postexposure that remained elevated, albeit not significantly, at 72 hr. No significant changes were observed in structural measurements or gray matter CBF. Subjects with higher baseline concentrations of neurochemicals associated with neuroprotection and maintenance of normal white matter physiology (glutathione, N-acetylaspartate, glutamate/glutamine) showed proportionally less white matter CBF changes. Our findings suggest that discrete hypobaric exposure may provide a model to study white matter injury associated with occupational hypobaric exposure.

Comparing the reproducibility of commonly used magnetic resonance spectroscopy techniques to quantify cerebral glutathione.

BACKGROUND: Cerebral glutathione (GSH), a marker of oxidative stress, has been quantified in neurodegenerative diseases and psychiatric disorders using proton magnetic resonance spectroscopy (MRS). Using a reproducible MRS technique is important, as it minimizes the impact of measurement technique variability on the study results and ensures that other studies can replicate the results. HYPOTHESIS: We hypothesized that very short echo time (TE) acquisitions would have comparable reproducibility to a long TE MEGA-PRESS acquisition, and that the short TE PRESS acquisition would have the poorest reproducibility. STUDY TYPE: Prospective. SUBJECTS/PHANTOMS: Ten healthy adults were scanned during two visits, and six metabolite phantoms containing varying concentrations of GSH and metabolites with resonances that overlap with GSH were scanned once. FIELD STRENGTH/SEQUENCE: At 3T we acquired MRS data using four different sequences: PRESS, SPECIAL, PR-STEAM, and MEGA-PRESS. ASSESSMENT: Reproducibility of each MRS sequence across two visits was assessed. STATISTICAL TESTS: Mean coefficients of variation (CV) and mean absolute difference (AD) were used to assess reproducibility. Linear regressions were performed on data collected from phantoms to examine the agreement between known and quantified levels of GSH. RESULTS: Of the four techniques, PR-STEAM had the lowest mean CV and AD (5.4% and 7.5%, respectively), implying excellent reproducibility, followed closely by PRESS (5.8% and 8.2%) and SPECIAL (8.0 and 10.1%), and finally by MEGA-PRESS (13.5% and 17.1%). Phantom data revealed excellent fits (R2 ≥ 0.98 or higher) using all methods. DATA CONCLUSION: Our data suggest that GSH can be quantified reproducibly without the use of spectral editing. LEVEL OF EVIDENCE: 2 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;49:176-183.

Disrupted glucocorticoid--Immune interactions during stress response in schizophrenia.

Glucocorticoid and immune pathways typically interact dynamically to optimize adaptation to stressful environmental challenges. We tested the hypothesis that a dysfunctional glucocorticoid-immune relationship contributes to abnormal stress response in schizophrenia. Saliva samples from 34 individuals with schizophrenia (20 male, 14 female) and 40 healthy controls (20 male, 20 female) were collected prior to and at 3 time points following completion of a computerized psychological challenge meant to be frustrating. Salivary concentrations of cortisol and interleukin-6 (IL-6) and their response to the challenge were examined. Both cortisol and IL-6 significantly increased in response to stress in the combined sample (both p<.05). In controls, the rise in cortisol following the challenge was negatively correlated to the subsequent changes in IL-6 (r=-.461, p=.003), such that rise of cortisol immediately after stress predicts subsequently lower IL-6 levels. In contrast, this relationship was positive in schizophrenia patients (r=.379, p=.027). The trends were significantly different (Z=3.7, p=.0002). This stress paradigm induces a rise in both cortisol and IL-6. In healthy controls, a more robust acute cortisol response was associated with a steeper decline of IL-6 levels following stress, corresponding to the expected anti-inflammatory effects of cortisol. Patients exhibited the opposite relationship, suggesting an inability to down-regulate inflammatory responses to psychological stress in schizophrenia; or even a paradoxical increase of IL-6 response. This finding may partially underlie abnormalities in inflammatory and stress pathways previously found in the illness, implicating dysregulated stress response in the chronic inflammatory state in schizophrenia.

Perfusion shift from white to gray matter may account for processing speed deficits in schizophrenia.

Reduced speed of cerebral information processing is a cognitive deficit associated with schizophrenia. Normal information processing speed (PS) requires intact white matter (WM) physiology to support information transfer. In a cohort of 107 subjects (47/60 patients/controls), we demonstrate that PS deficits in schizophrenia patients are explained by reduced WM integrity, which is measured using diffusion tensor imaging, mediated by the mismatch in WM/gray matter blood perfusion, and measured using arterial spin labeling. Our findings are specific to PS, and testing this hypothesis for patient-control differences in working memory produces no explanation. We demonstrate that PS deficits in schizophrenia can be explained by neurophysiological alterations in cerebral WM. Whether the disproportionately low WM integrity in schizophrenia is due to illness or secondary due to this disorder deserves further examination.

Familial aggregation of tobacco use behaviors among Amish men.

INTRODUCTION: Tobacco use is a complex behavior. The Old Order Amish community offers unique advantages for the study of tobacco use because of homogenous ancestral background, sociocultural similarity, sex-specific social norms regarding tobacco use, and large family size. Tobacco use in the Old Order Amish community is almost exclusively confined to males. METHODS: We examined characteristics of tobacco use and familial aggregation among 1,216 Amish males from cross-sectional prospectively collected data. Outcomes examined included ever using tobacco regularly, current use, quantity of use, duration of use, and frequency of use. RESULTS: Sixteen percent of Amish men were current tobacco users, with the majority reporting cigar use only. Higher rates of tobacco use were found among sons of fathers who smoked compared with sons of fathers who did not smoke (46% vs. 22%, p < .001) as well as among brothers of index cases who smoked compared with brothers of index cases who did not smoke (61% vs. 29%, p < .001). After controlling for shared household effects and age, heritability accounted for 66% of the variance in ever smoking regularly (p = .045). CONCLUSIONS: The familial patterns of tobacco use observed among Amish men highlight the important role of family in propagating tobacco use and support the usefulness of this population for future genetic studies of nicotine addiction.

Reproducibility of phase rotation STEAM at 3T: focus on glutathione.

PURPOSE: The purpose of this study was to determine the reproducibility of a very short echo time (TE) phase rotation stimulated echo acquisition mode (STEAM) sequence at 3T with a focus on the detection of glutathione. METHODS: Ten healthy subjects were scanned on two separate visits. Spectra were acquired from voxels placed in the anterior and posterior cingulates. Reproducibility was assessed using mean coefficients of variation (CVs) and mean absolute differences (ADs), and reliability was assessed using standard error of measurement (SEM) and intraclass correlations (ICCs). Phantoms containing glutathione and metabolites with overlapping resonances were scanned to test the validity of glutathione quantification. RESULTS: Excellent reproducibility as illustrated by CVs ≤8.3% and ADs ≤11.6% for both regions was obtained for glutathione and other commonly reported metabolites. Reproducibility measures for γ-aminobutyric acid and glutamine were good overall with CVs ranging from 6.4%-10.5% and ADs ranging from 8.6%-15.5% for both regions. Glutathione absolute and relative reliability were very good (SEMs ≤9.9%) and fair (ICCs = 0.42-0.51), respectively. Phantom studies demonstrated the ability to accurately detect glutathione from other metabolites with overlapping resonances with great precision (R(2) = 0.99). CONCLUSION: A very short TE phase rotation STEAM sequence proved reproducible for metabolites difficult to quantify but important for the study of psychiatric and neurological illness.

Acute nicotine administration effects on fractional anisotropy of cerebral white matter and associated attention performance.

INTRODUCTION: Nicotinic acetylcholine receptors are present in the cerebral white matter (WM). We hypothesized that WM response to nicotine can be detected by diffusion tensor imaging (DTI); and that such responses may be associated with nicotine-led cognitive enhancement in sustained attention. METHODS: A randomized, nicotine-placebo patch, crossover, double-blind clinical trial in two non-overlapping cohorts of smokers was used to test the hypothesis. The discovery cohort consisted of 39 subjects (N = 20/19 controls/schizophrenic patients, age = 36.8 ± 10.1 years) and the replication cohorts consisted of 38 healthy smokers (31.7 ± 10.5 years). WM integrity was measured by fractional anisotropy (FA) values for the whole brain and nine preselected WM tracts using tract-based-spatial-statistics. RESULTS: Nicotine significantly enhanced FA values for the genu of corpus callosum compared with placebo (ΔFAgenu) (p = 0.01) in smokers with low recent smoking exposure as measured by low average cotinine level. This finding was replicated in the second cohort (p = 0.02). ΔFAgenu values explained 22% of variance in performance of a sustained attention task during the nicotine session (p = 0.006). However, this effect was limited to schizophrenia patients (r = 0.62 and 0.09; p = 0.003 and 0.7 for patients and controls, respectively). CONCLUSION: Acute pharmacological influence of nicotine patch on WM integrity appeared present, but was dependent on nicotine intake from recent smoking. Change in the WM integrity in the genu of corpus callosum was associated with a significant proportion of variability of nicotine-led changes in sustained attention/working memory of the smokers. Further studies will be necessary to understand biophysical underpinning of the nicotine-related changes in FA.

Electrophysiological intermediate biomarkers for oxidative stress in schizophrenia.

OBJECTIVE: Diverse electrophysiological abnormalities have been associated with schizophrenia, but the underlying causes remain elusive. We tested whether the altered oxidative stress in schizophrenia contributes to the electrophysiological abnormalities. METHODS: We used an auditory oddball task to measure mismatch negativity (MMN) and gamma band response on 29 schizophrenia patients and 25 normal controls. Oxidative stress was assessed by monomeric glutathione (GSH, reduced form) and glutathione disulfide (GSSG, oxidized form). RESULTS: Patients had reduced MMN (p=0.015) and reduced power of gamma band responses at 21-40 Hz and 41-85 Hz (all p<0.001). GSH was significantly lower (p<0.001) while %GSSG was higher (p=0.023) in patients compared with controls. MMN was correlated with GSH in controls; while 21-40 Hz responses were correlated with GSH in patients. Lower GSH and higher GSSG levels were associated with low community functioning (p=0.018). Multivariate mediation modeling showed that gamma band at 21-40 Hz was a significant mediator for GSH effect on community functions. CONCLUSIONS: High beta/low gamma range (21-40 Hz) responses may be an intermediate biomarker indexing oxidative stress and its effect on clinical functions. SIGNIFICANCE: Electrophysiological abnormalities and associated clinical functional changes may in part be associated with heightened oxidative stress in schizophrenia.

No evidence of exogenous origin for the abnormal glutathione redox state in schizophrenia.

Schizophrenia has been associated with low glutathione (GSH), one of the most important substrates for natural defense against oxidative stress. This abnormality is often attributed to genetic or other pathological causes. However, low GSH in schizophrenia could also be due to insufficient antioxidant consumption or other exogenous factors. We evaluated GSH in relation to diet, smoking, and medication status in schizophrenia patients. We recruited 54 participants (29 schizophrenia patients and 25 normal controls). The Antioxidant Dietary Source Questions was used to estimate the total antioxidant capacity (TAC) from participants' diet. GSH and the oxidized form of glutathione (GSSG) were assayed. We found that GSH was significantly lower (p<0.001) while %GSSG was 2 to 5 fold higher (p = 0.023) in patients compared with controls. No evidence for lower TAC dietary intake was found in schizophrenia patients compared with controls; rather nominally higher TAC level was found in the patients diet (p = 0.02). Analysis of consumption of individual food categories also failed to find evidence of reduced dietary antioxidant intake in schizophrenia patients. Smoking and medications did not significantly predict the GSH deficit either. However, there was a significant smoking by diagnosis interaction on GSH (p = 0.026) such that smoking was associated with higher GSH level in controls while smoking in patients was not associated with this effect. Schizophrenia patients may have an impaired upregulation of GSH synthesis that normally occurs due to smoking-induced antioxidative response. Lower GSH was independently present in patients on clozapine (p = 0.005) and patients on other antipsychotics (p<0.001) compared with controls. In conclusion, none of the exogenous sources played a major role in explaining abnormalities in the glutathione pathway in patients. The state of abnormal glutathione redox may therefore be a part of schizophrenia pathophysiology.

Brain circuits that link schizophrenia to high risk of cigarette smoking.

Schizophrenia is associated with a high prevalence of smoking. Functional connectivity between the dorsal anterior cingulate (dACC) and limbic regions including the ventral striatum, extended amygdala and parahippocampal areas has been previously implicated in the genetics and clinical severity of smoking. In this study, we test the hypothesis that dACC functional circuits are key paths for the high risk of smoking comorbidity in schizophrenia. Resting state functional magnetic resonance imaging (fMRI) was performed using the dACC as a seed region in smoking and nonsmoking patients with schizophrenia (n = 54), matched controls (n = 65), and nonpsychotic first-degree relatives (n = 24). Multiple regions had decreased connectivity with the dACC in schizophrenia patients when compared with matched controls (n = 65). Several of these functional circuits were also associated with nicotine addiction severity; the largest cluster included limbic areas such as the parahippocampal, extended amygdala, ventral striatal, and posterior insula regions, indicating an overlap of schizophrenia and nicotine addiction on to this circuit. These same functional connectivity-defined circuits were also significantly impaired in schizophrenia nonsmokers compared with control nonsmokers and in nonpsychotic first-degree relatives. Functional connectivity between the dACC and limbic regions is inherently abnormal in schizophrenia, related to its genetic liability regardless of smoking, and overlaps with a nicotine addiction-related circuit. Our findings establish a biologically defined brain circuit mechanism that contributes to the high prevalence of smoking.