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 \u3c .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

Genomic kinship construction to enhance genetic analyses in the human connectome project data

Imaging genetic analyses quantify genetic control over quantitative measurements of brain structure and function using coefficients of relationship (CR) that code the degree of shared genetics between subjects. CR can be inferred through self-reported relatedness or calculated empirically using genome-wide SNP scans. We hypothesized that empirical CR provides a more accurate assessment of shared genetics than self-reported relatedness. We tested this in 1,046 participants of the Human Connectome Project (HCP) (480 M/566 F) recruited from the Missouri twin registry. We calculated the heritability for 17 quantitative traits drawn from four categories (brain diffusion and structure, cognition, and body physiology) documented by the HCP. We compared the heritability and genetic correlation estimates calculated using self-reported and empirical CR methods Kinship-based INference for GWAS (KING) and weighted allelic correlation (WAC). The polygenetic nature of traits was assessed by calculating the empirical CR from chromosomal SNP sets. The heritability estimates based on whole-genome empirical CR were higher but remained significantly correlated (r ∼0.9) with those obtained using self-reported values. Population stratification in the HCP sample has likely influenced the empirical CR calculations and biased heritability estimates. Heritability values calculated using empirical CR for chromosomal SNP sets were significantly correlated with the chromosomal length (r 0.7) suggesting a polygenic nature for these traits. The chromosomal heritability patterns were correlated among traits from the same knowledge domains; among traits with significant genetic correlations; and among traits sharing biological processes, without being genetically related. The pedigree structures generated in our analyses are available online as a web-based calculator (www.solar-eclipse-genetics.org/HCP)

Effects of Ketamine and Midazolam on resting state connectivity and comparison with ENIGMA connectivity deficit patterns in schizophrenia

Subanesthetic administration of ketamine is a pharmacological model to elicit positiveand negative symptoms of psychosis in healthy volunteers. We used resting statepharmacological functional MRI (rsPhfMRI) to identify cerebral networks affected by ketamineand compared them to the functional connectivity (FC) in schizophrenia. Ketamine can producesedation and we contrasted its effects with the effects of the anxiolytic drug midazolam.Thirty healthy male volunteers (age=19-37 years) underwent a randomized, three-way,cross-over study consisting of three imaging sessions, with 48 hours between sessions. A sessionconsisted of a control period followed by infusion of placebo or ketamine or midazolam. TheENIGMA rsfMRI pipeline was used to derive two long distance (seed-based and dualregression)and one local (regional homogeneity, ReHo) FC measures. Ketamine inducedsignificant reductions in the connectivity of the salience network (Cohen’s d:1.13±0.28,p=4.0×10-3), auditory network (d: 0.67±0.26, p=0.04) and default mode network (DMN,d:0.63±0.26, p=0.05). Midazolam significantly reduced connectivity in the DMN (d:0.77±0.27,p=0.03). The effect sizes for ketamine for resting networks showed a positive correlation(r=0.59, p=0.07) with the effect sizes for schizophrenia related deficits derived from ENIGMA’sstudy of 261 patients and 327 controls. Effect sizes for midazolam were not correlated with theschizophrenia pattern (r=-0.17, p=0.65). The subtraction of ketamine and midazolam patternsshowed a significant positive correlation with the pattern of schizophrenia deficits (r=0.68,p=0.03).RsPhfMRI reliably detected the shared and divergent pharmacological actions ofketamine and midazolam on cerebral networks. The pattern of disconnectivity produced byketamine was positively correlated with the pattern of connectivity deficits observed inschizophrenia, suggesting a brain functional basis for previously poorly understood effects of thedrug

Cardiovascular risks impact human brain N -acetylaspartate in regionally specific patterns

Cardiovascular risk factors such as dyslipidemia and hypertension increase the risk for white matter pathology and cognitive decline. We hypothesize that white matter levels of -acetylaspartate (NAA), a chemical involved in the metabolic pathway for myelin lipid synthesis, could serve as a biomarker that tracks the influence of cardiovascular risk factors on white matter prior to emergence of clinical changes. To test this, we measured levels of NAA across white matter and gray matter in the brain using echo planar spectroscopic imaging (EPSI) in 163 individuals and examined the relationship of regional NAA levels and cardiovascular risk factors as indexed by the Framingham Cardiovascular Risk Score (FCVRS). NAA was strongly and negatively correlated with FCVRS across the brain, but, after accounting for age and sex, the association was found primarily in white matter regions, with additional effects found in the thalamus, hippocampus, and cingulate gyrus. FCVRS was also negatively correlated with creatine levels, again primarily in white matter. The results suggest that cardiovascular risks are related to neurochemistry with a predominantly white matter pattern and some subcortical and cortical gray matter involvement. NAA mapping of the brain may provide early surveillance for the potential subclinical impact of cardiovascular and metabolic risk factors on the brain

Genomic kinship construction to enhance genetic analyses in the human connectome project data

Imaging genetic analyses quantify genetic control over quantitative measurements of brain structure and function using coefficients of relationship (CR) that code the degree of shared genetics between subjects. CR can be inferred through self-reported relatedness or calculated empirically using genome-wide SNP scans. We hypothesized that empirical CR provides a more accurate assessment of shared genetics than self-reported relatedness. We tested this in 1,046 participants of the Human Connectome Project (HCP) (480 M/566 F) recruited from the Missouri twin registry. We calculated the heritability for 17 quantitative traits drawn from four categories (brain diffusion and structure, cognition, and body physiology) documented by the HCP. We compared the heritability and genetic correlation estimates calculated using self-reported and empirical CR methods Kinship-based INference for GWAS (KING) and weighted allelic correlation (WAC). The polygenetic nature of traits was assessed by calculating the empirical CR from chromosomal SNP sets. The heritability estimates based on whole-genome empirical CR were higher but remained significantly correlated (r ∼0.9) with those obtained using self-reported values. Population stratification in the HCP sample has likely influenced the empirical CR calculations and biased heritability estimates. Heritability values calculated using empirical CR for chromosomal SNP sets were significantly correlated with the chromosomal length (r 0.7) suggesting a polygenic nature for these traits. The chromosomal heritability patterns were correlated among traits from the same knowledge domains; among traits with significant genetic correlations; and among traits sharing biological processes, without being genetically related. The pedigree structures generated in our analyses are available online as a web-based calculator (www.solar-eclipse-genetics.org/HCP)

Plexus 2007

Sponsors: School of Medicine Dean’s Office, Office of Educational Affairs, Office of AdmissionsThe PLEXUS staff wishes to recognize the hard work and support of the following individuals:Ellena Peterson, PhD, Gayle Pierce, Linda Hill, Carroll Rudy, Dale Fukuda from Printing Division.The Senior Editors also wish to thank Sarah Mourra and Boback Ziaeian for their endless guidance and encouragement.Co-Editors-in-Chief Jamie “Akiva” Kahn; Mariam NaqviManaging Editor: Pooya JavidanSenior EditorsAudio: Lauren CheungBeautification Project: Janet LimCreative Writing: Jamie “Akiva” KahnLayout & Design: Mariam NaqviMarketing & Outreach: Janet LimVisual Arts: Vicky MillayAssociate EditorsAudio: Wesley RyanBeautification Project: Christina UmberCreative Writing: Dana SteenhardLayout & Design: Rod MortazaviMarketing & Outreach: Julie HuiVisual Arts: Neera SodhiSelection Editors: Antony Hazel; Pooya Javidan; Jane LeeSelection Committee: Sarah Blaschko; Brian McMichael; Sarah Mourra; Manijeh Torki; Roya Saisan; Tracy Slone; Josh Waltzman; Randy Wei; Boback ZiaeianFaculty Advisors: Elizabeth Morrison, MD; Johanna Shapiro, PhDPlexus Audio provides audio artists with a way to showcase their talents. All of the work hasbeen created by affiliates of the UC Irvine School of Medicine and Medical Center. We hope that you enjoy the large variety of innovative and creative works and stay tuned for future developments from Plexus Audio.Senior Audio Editor: Lauren CheungAssociate Audio Editor: Wesley Ryan WWW.PLEXUSAUDIO.COM UCI School of Medicine  (c) 2007 PLEXUSPublished works were contributed by UCI School of Medicine students, faculty, staff, alumni, and patients

The additive impact of cardio-metabolic disorders and psychiatric illnesses on accelerated brain aging

Severe mental illnesses (SMI) including major depressive disorder (MDD), bipolar disorder (BD), and schizophrenia spectrum disorder (SSD) elevate accelerated brain aging risks. Cardio-metabolic disorders (CMD) are common comorbidities in SMI and negatively impact brain health. We validated a linear quantile regression index (QRI) approach against the machine learning BrainAge index in an independent SSD cohort (N = 206). We tested the direct and additive effects of SMI and CMD effects on accelerated brain aging in the N = 1,618 (604 M/1,014 F, average age = 63.53 ± 7.38) subjects with SMI and N = 11,849 (5,719 M/6,130 F; 64.42 ± 7.38) controls from the UK Biobank. Subjects were subdivided based on diagnostic status: SMI+/CMD+ (N = 665), SMI+/CMD- (N = 964), SMI-/CMD+ (N = 3,765), SMI-/CMD- (N = 8,083). SMI (F = 40.47, p = 2.06 × 10 ) and CMD (F = 24.69, p = 6.82 × 10 ) significantly, independently impacted whole-brain QRI in SMI+. SSD had the largest effect (Cohen\u27s d = 1.42) then BD (d = 0.55), and MDD (d = 0.15). Hypertension had a significant effect on SMI+ (d = 0.19) and SMI- (d = 0.14). SMI effects were direct, independent of MD, and remained significant after correcting for effects of antipsychotic medications. Whole-brain QRI was significantly (p \u3c 10 ) associated with the volume of white matter hyperintensities (WMH). However, WMH did not show significant association with SMI and was driven by CMD, chiefly hypertension (p \u3c 10 ). We used a simple and robust index, QRI, the demonstrate additive effect of SMI and CMD on accelerated brain aging. We showed a greater effect of psychiatric illnesses on QRI compared to cardio-metabolic illness. Our findings suggest that subjects with SMI should be among the targets for interventions to protect against age-related cognitive decline

Translating ENIGMA

Patients with schizophrenia have patterns of brain deficits including reduced cortical thickness, subcortical gray matter volumes, and cerebral white matter integrity. We proposed the regional vulnerability index (RVI) to translate the results of Enhancing Neuro Imaging Genetics Meta-Analysis studies to the individual level. We calculated RVIs for cortical, subcortical, and white matter measurements and a multimodality RVI. We evaluated RVI as a measure sensitive to schizophrenia-specific neuroanatomical deficits and symptoms and studied the timeline of deficit formations in: early (≤5 years since diagnosis, N = 45, age = 28.8 ± 8.5); intermediate (6-20 years, N = 30, age 43.3 ± 8.6); and chronic (21+ years, N = 44, age = 52.5 ± 5.2) patients and healthy controls (N = 76, age = 38.6 ± 12.4). All RVIs were significantly elevated in patients compared to controls, with the multimodal RVI showing the largest effect size, followed by cortical, white matter and subcortical RVIs (d = 1.57, 1.23, 1.09, and 0.61, all p < 10-6 ). Multimodal RVI was significantly correlated with multiple cognitive variables including measures of visual learning, working memory and the total score of the MATRICS consensus cognitive battery, and with negative symptoms. The multimodality and white matter RVIs were significantly elevated in the intermediate and chronic versus early diagnosis group, consistent with ongoing progression. Cortical RVI was stable in the three disease-duration groups, suggesting neurodevelopmental origins of cortical deficits. In summary, neuroanatomical deficits in schizophrenia affect the entire brain; the heterochronicity of their appearance indicates both the neurodevelopmental and progressive nature of this illness. These deficit patterns may be useful for early diagnosis and as quantitative targets for more effective treatment strategies aiming to alter these neuroanatomical deficit patterns

Translating ENIGMA schizophrenia findings using the regional vulnerability index: Association with cognition, symptoms, and disease trajectory

Patients with schizophrenia have patterns of brain deficits including reduced cortical thickness, subcortical gray matter volumes, and cerebral white matter integrity. We proposed the regional vulnerability index (RVI) to translate the results of Enhancing Neuro Imaging Genetics Meta-Analysis studies to the individual level. We calculated RVIs for cortical, subcortical, and white matter measurements and a multimodality RVI. We evaluated RVI as a measure sensitive to schizophrenia-specific neuroanatomical deficits and symptoms and studied the timeline of deficit formations in: early (≤5 years since diagnosis, N = 45, age = 28.8 ± 8.5); intermediate (6-20 years, N = 30, age 43.3 ± 8.6); and chronic (21+ years, N = 44, age = 52.5 ± 5.2) patients and healthy controls (N = 76, age = 38.6 ± 12.4). All RVIs were significantly elevated in patients compared to controls, with the multimodal RVI showing the largest effect size, followed by cortical, white matter and subcortical RVIs (d = 1.57, 1.23, 1.09, and 0.61, all p < 10-6 ). Multimodal RVI was significantly correlated with multiple cognitive variables including measures of visual learning, working memory and the total score of the MATRICS consensus cognitive battery, and with negative symptoms. The multimodality and white matter RVIs were significantly elevated in the intermediate and chronic versus early diagnosis group, consistent with ongoing progression. Cortical RVI was stable in the three disease-duration groups, suggesting neurodevelopmental origins of cortical deficits. In summary, neuroanatomical deficits in schizophrenia affect the entire brain; the heterochronicity of their appearance indicates both the neurodevelopmental and progressive nature of this illness. These deficit patterns may be useful for early diagnosis and as quantitative targets for more effective treatment strategies aiming to alter these neuroanatomical deficit patterns