White matter 'potholes' in early-onset schizophrenia: a new approach to evaluate white matter microstructure using diffusion tensor imaging

Polygenic susceptibility for multiple sclerosis is associated with working memory in low-performing young adults

BACKGROUND

Multiple sclerosis (MS) is a complex disease with substantial heritability estimates. Besides typical clinical manifestations such as motor and sensory deficits, MS is characterized by structural and functional brain abnormalities, and by cognitive impairment such as decreased working memory (WM) performance.

OBJECTIVES

We investigated the possible link between the polygenic risk for MS and WM performance in healthy adults (18-35 years). Additionally, we addressed the relationship between polygenic risk for MS and white matter fractional anisotropy (FA).

METHODS

We generated a polygenic risk score (PRS) of MS susceptibility and investigated its association with WM performance in 3282 healthy adults (two subsamples, N1 = 1803, N2 = 1479). The association between MS-PRS and FA was studied in the second subsample. MS severity PRS associations were also investigated for the WM and FA measurements.

RESULTS

MS-PRS was significantly associated with WM performance within the 10% lowest WM-performing individuals (p = 0.001; pFDR = 0.018). It was not significantly associated with any of the investigated FA measurements. MS severity PRS was significantly associated with brain-wide mean FA (p = 0.041) and showed suggestive associations with additional FA measurements.

CONCLUSIONS

By identifying a genetic link between MS and WM performance this study contributes to the understanding of the genetic complexity of MS, and hopefully to the possible identification of molecular pathways linked to cognitive deficits in MS. It also contributes to the understanding of genetic associations with MS severity, as these associations seem to involve distinct biological pathways compared to genetic variants linked to the overall risk of developing MS.

White matter changes and its relationship with clinical symptom in medication-naive first-episode early onset schizophrenia

Previous studies have highlighted the role of white matter (WM) alterations as biomarkers of the disease state and prognosis of schizophrenia. However, less is known about WM abnormalities in the rarely occurring adolescent early onset schizophrenia (EOS). In this study, T1-weighted and diffusion-weighted images were collected in 56 medication-naive first-episode participants with EOS and 43 healthy controls (HCs). Using Tract-based Spatial Statistics, we calculate case-control differences in scalar diffusion measures, i.e. fractional anisotropy (FA) and mean diffusivity (MD), and investigated their association with clinical feature in participants with EOS. Compared with HCs, decreased MD was found in EOS group most notably in the inferior longitudinal fasciculus, anterior thalamic radiation, inferior fronto-occipital fasciculus and corticospinal tract in the right hemisphere. No significant difference was found in FA between these two groups. The FA values of the forceps minor and the right superior longitudinal fasciculus were suggested to be related to the severity of clinical symptom in participants with EOS. These results provide clues about the neural basis of schizophrenia and a potential biomarker for clinical studies.

Disrupted white matter microstructure correlates with impulsivity in children and adolescents with bipolar disorder

Altered white matter (WM) microstructure likely occurs in children with bipolar disorder (BD) with impulsivity representing one of the core features. However, altered WM microstructures and their age-related trendlines in children with BD and those at high-risk of developing BD, as well as correlations of WM microstructures with impulsivity, have been poorly investigated. In this study, diffusion MRI, cognitive, and impulsivity assessments were obtained from children/adolescents diagnosed with BD, offspring of individuals with BD (high-risk BD) and age-matched healthy controls. A novel atlas-based WM skeleton measurement approach was used to quantify WM microstructural integrity with all diffusion-tensor-imaging (DTI) metrics including fractional anisotropy, axial, mean and radial diffusivity to survey entire WM tracts and ameliorate partial volume effects. Among all DTI-derived metric measures, radial diffusivity quantifying WM myelination was found significantly higher primarily in corpus callosum and in the corona radiata in children with BD compared to controls. Distinguished from age-related progressively decreasing diffusivities and increasing fractional anisotropy in healthy controls, flattened age-related trendlines were found in BD group, and intermediate developmental rates were observed in high-risk group. Larger radial diffusivity in the corpus callosum and corona radiata significantly correlated with shorter response times to affective words that indicate higher impulsivity in the BD group, whereas no such correlation was found in the healthy control group. This work corroborates the progressive nature of pediatric BD and suggests that WM microstructural disruption involved in affective regulation and sensitive to impulsivity may serve as a biomarker of pediatric BD progression.

Improving the predictive potential of diffusion MRI in schizophrenia using normative models-Towards subject-level classification

Diffusion MRI studies consistently report group differences in white matter between individuals diagnosed with schizophrenia and healthy controls. Nevertheless, the abnormalities found at the group-level are often not observed at the individual level. Among the different approaches aiming to study white matter abnormalities at the subject level, normative modeling analysis takes a step towards subject-level predictions by identifying affected brain locations in individual subjects based on extreme deviations from a normative range. Here, we leveraged a large harmonized diffusion MRI dataset from 512 healthy controls and 601 individuals diagnosed with schizophrenia, to study whether normative modeling can improve subject-level predictions from a binary classifier. To this aim, individual deviations from a normative model of standard (fractional anisotropy) and advanced (free-water) dMRI measures, were calculated by means of age and sex-adjusted z-scores relative to control data, in 18 white matter regions. Even though larger effect sizes are found when testing for group differences in z-scores than are found with raw values (p < .001), predictions based on summary z-score measures achieved low predictive power (AUC < 0.63). Instead, we find that combining information from the different white matter tracts, while using multiple imaging measures simultaneously, improves prediction performance (the best predictor achieved AUC = 0.726). Our findings suggest that extreme deviations from a normative model are not optimal features for prediction. However, including the complete distribution of deviations across multiple imaging measures improves prediction, and could aid in subject-level classification.

White matter microstructural differences in children and genetic risk for multiple sclerosis: A population-based study

Background:

MS patients show abnormalities in white matter (WM) on brain imaging, with heterogeneity in the location of WM lesions. The “pothole” method can be applied to diffusion-weighted images to identify spatially distinct clusters of divergent brain WM microstructure.

Objective:

To investigate the association between genetic risk for MS and spatially independent clusters of decreased or increased fractional anisotropy (FA) in the brain. In addition, we studied sex- and age-related differences.

Methods:

3 Tesla diffusion tensor imaging (DTI) data were collected in 8- to 12-year-old children from a population-based study. Global and tract-based potholes (lower FA clusters) and molehills (higher FA clusters) were quantified in 3047 participants with usable DTI data. A polygenic risk score (PRS) for MS was calculated in genotyped individuals (n = 1087) and linear regression analyses assessed the relationship between the PRS and the number of potholes and molehills, correcting for multiple testing using the False Discovery Rate.

Results:

The number of molehills increased with age, potholes decreased with age, and fewer potholes were observed in girls during typical development. The MS-PRS was positively associated with the number of molehills (β = 0.9, SE = 0.29, p = 0.002). Molehills were found more often in the corpus callosum (β = 0.3, SE = 0.09, p = 0.0003).

Conclusion:

Genetic risk for MS is associated with spatially distinct clusters of increased FA during childhood brain development.

Individual deviations from normative models of brain structure in a large cross-sectional schizophrenia cohort

The heterogeneity of schizophrenia has defied efforts to derive reproducible and definitive anatomical maps of structural brain changes associated with the disorder. We aimed to map deviations from normative ranges of brain structure for individual patients and evaluate whether the loci of individual deviations recapitulated group-average brain maps of schizophrenia pathology. For each of 48 white matter tracts and 68 cortical regions, normative percentiles of variation in fractional anisotropy (FA) and cortical thickness (CT) were established using diffusion-weighted and structural MRI from healthy adults (n = 195). Individuals with schizophrenia (n = 322) were classified as either within the normative range for healthy individuals of the same age and sex (5-95% percentiles), infra-normal (<5% percentile) or supra-normal (>95% percentile). Repeating this classification for each tract and region yielded a deviation map for each individual. Compared to the healthy comparison group, the schizophrenia group showed widespread reductions in FA and CT, involving virtually all white matter tracts and cortical regions. Paradoxically, however, no more than 15-20% of patients deviated from the normative range for any single tract or region. Furthermore, 79% of patients showed infra-normal deviations for at least one locus (healthy individuals: 59 ± 2%, p < 0.001). Thus, while infra-normal deviations were common among patients, their anatomical loci were highly inconsistent between individuals. Higher polygenic risk for schizophrenia associated with a greater number of regions with infra-normal deviations in CT (r = -0.17, p = 0.006). We conclude that anatomical loci of schizophrenia-related changes are highly heterogeneous across individuals to the extent that group-consensus pathological maps are not representative of most individual patients. Normative modeling can aid in parsing schizophrenia heterogeneity and guiding personalized interventions.

Strategic white matter injury associated with long-term information processing speed deficits in mild traumatic brain injury

Deficits in information processing speed (IPS) are among the earliest and most prominent cognitive manifestations in mild traumatic brain injury (mTBI). We investigated the impact of white matter fiber location on IPS outcome in an individual basis assessment. A total of 112 acute mild TBI with all CT negative underwent brain DTI and blood sampling for inflammation cytokines within 7 days postinjury and 72 age- and sex matched healthy controls with same assessments were enrolled. IPS outcome was assessed by the trail making test at 6-12 month postinjury in mild TBI. Fractional anisotropy (FA) features were extracted using a novel lesion-load analytical strategy to capture spatially heterogeneous white matter injuries and minimize implicit assumptions of uniform injury across diverse clinical presentations. Acute mild TBI exhibited a general pattern of increased and decreased FA in specific white matter tracts. The power of acute FA measures to identify patients developing IPS deficits with 92% accuracy and further improved to 96% accuracy by adding inflammation cytokines. The classifiers predicted individual's IPS and working memory ratings (r = .74 and .80, respectively, p < .001). The thalamo-cortical circuits and commissural tracts projecting or connecting frontal regions became important predictors. This prognostic model was also verified by an independent replicate sample. Our findings highlighted damage to frontal interhemispheric and thalamic projection fiber tracts harboring frontal-subcortical neuronal circuits as a predictor for processing speed performance in mild TBI.

Editorial: White Matter Matters: Neurobiological Differences Between Pediatric Bipolar Disorder and Disruptive Mood Dysregulation Disorder

Think about this: Linke et al.¹ are publishing the "first" ever study using diffusion tensor imaging (DTI) in children with disruptive mood dysregulation disorder (DMDD). Child and adolescent psychiatrists know that these children are not new and are not uncommonly seen in both inpatient and outpatient mental health settings. So, why does the first paper examining the microstructural differences in white matter tracts in children with DMDD emerge in 2019? If you search PubMed using the key words "autism" and "diffusion tensor imaging" (as children with autistic symptoms have likely been around for as long as children with symptoms of dysregulation), you end up with 305 papers. So, what's the story? Was aberrant white matter microstructure never considered as a putative hypothesis for DMDD? Or did DMDD fall under a different name, and, as Shakespeare once wrote, "a rose by any other name would smell as sweet"? Or, in our loose psychiatric-based translation from Old English, "a pediatric bipolar child by any other name is just as dysregulated?" Indeed, DMDD has had a circuitous and somewhat shady history, with its roots in the name "pediatric bipolar disorder."² Because a number of long-term studies showed that few children with chronic irritable mood problems progressed to develop adult bipolar affective disorder (BPAD),³ DMDD emerged in the DSM-5.⁴.

Comparative Neuropsychiatry: White Matter Abnormalities in Children and Adolescents with Schizophrenia, Bipolar Affective Disorder, and Obsessive-Compulsive Disorder

Background:

There is considerable evidence that white matter abnormalities play a key role in the pathogenesis of a number of major psychiatric disorders, including schizophrenia, bipolar affective disorder, and obsessive-compulsive disorder. Few studies, however, have compared white matter abnormalities early in the course of the illness.

Methods:

A total of 102 children and adolescents participated in the study, including 43 with early-onset schizophrenia, 13 with early-onset bipolar affective disorder, 17 with obsessive-compulsive disorder, and 29 healthy controls. Diffusion tensor imaging scans were obtained on all children and the images were assessed for the presence of non-spatially overlapping regions of white matter differences, a novel algorithm known as the pothole approach.

Results:

Patients with early-onset schizophrenia and early-onset bipolar affective disorder had a significantly greater number of white matter potholes compared to controls, but the total number of potholes did not differ between the two groups. The volumes of the potholes were significantly larger in patients with early-onset bipolar affective disorder compared to the early-onset schizophrenia group. Children and adolescents with obsessive-compulsive disorder showed no differences in the total number of white matter potholes compared to controls.

Conclusions:

White matter abnormalities in early-onset schizophrenia and bipolar affective disorder are more global in nature, whereas children and adolescents with obsessive-compulsive disorder do not show widespread differences in FA.

Oligodendrocytes express synaptic proteins that modulate myelin sheath formation

Vesicular release from neurons promotes myelin sheath growth on axons. Oligodendrocytes express proteins that allow dendrites to respond to vesicular release at synapses, suggesting that axon-myelin contacts use similar communication mechanisms as synapses to form myelin sheaths. To test this, we used fusion proteins to track synaptic vesicle localization and membrane fusion in zebrafish during developmental myelination and investigated expression and localization of PSD95, a dendritic post-synaptic protein, within oligodendrocytes. Synaptic vesicles accumulate and exocytose at ensheathment sites with variable patterning and most sheaths localize PSD95 with patterning similar to exocytosis site location. Disruption of candidate PDZ-binding transsynaptic adhesion proteins in oligodendrocytes cause variable effects on sheath length and number. One candidate, Cadm1b, localizes to myelin sheaths where both PDZ binding and extracellular adhesion to axons mediate sheath growth. Our work raises the possibility that axon-glial communication contributes to myelin plasticity, providing new targets for mechanistic unraveling of developmental myelination.

White matter alterations in early-stage Alzheimer's disease: A tract-specific study

Introduction

Diffusion magnetic resonance imaging may allow for microscopic characterization of white matter degeneration in early stages of Alzheimer's disease.

Methods

Multishell Diffusion magnetic resonance imaging data were acquired from 100 participants (40 cognitively normal, 38 with subjective cognitive decline, and 22 with mild cognitive impairment [MCI]). White matter microscopic degeneration in 27 major tracts of interest was assessed using diffusion tensor imaging (DTI), neurite orientation dispersion and density imaging, and q-space imaging.

Results

Lower DTI fractional anisotropy and higher radial diffusivity were observed in the cingulum, thalamic radiation, and forceps major of participants with MCI. These tracts of interest also had the highest predictive power to discriminate groups. Diffusion metrics were associated with cognitive performance, particularly Rey Auditory Verbal Learning Test immediate recall, with the highest association observed in participants with MCI.

Discussion

While DTI was the most sensitive, neurite orientation dispersion and density imaging and q-space imaging complementarily characterized reduced axonal density accompanied with dispersed and less restricted white matter microstructures.

•

Mild cognitive decline poses microstructural alterations in white matter tracts.

•

The alterations include higher axonal dispersion and lower tissue restriction.

•

Diffusion metrics are associated with cognitive outcomes in AD continuum.

Close-Range Blast Exposure Is Associated with Altered White Matter Integrity in Apolipoprotein ɛ4 Carriers

Evidence suggests that blast exposure has profound negative consequences for the health of the human brain, and that it may confer risk for the development of neurodegenerative diseases such as chronic traumatic encephalopathy and Alzheimer's disease (AD). Although the molecular mechanisms linking blast exposure to subsequent neurodegeneration is an active focus of research, recent studies suggest that genetic risk for AD may elevate the risk of neurodegeneration following traumatic brain injury (TBI). However, it is currently unknown if blast exposure also interacts with AD risk to promote neurodegeneration. In this study we examined whether apolipoprotein (APOE) ɛ4, a well-known genetic risk factor for AD, influenced the relationship between blast exposure and white matter integrity in a cohort of 200 Iraq and Afghanistan war veterans. Analyses revealed a significant interaction between close-range blast exposure (CBE) (close range being within 10 m) and APOE ɛ4 carrier status in predicting white matter abnormalities, measured by a voxelwise cluster-based method that captures spatial heterogeneity in white matter disruptions. This interaction remained significant after controlling for TBI, pointing to the specificity of CBE and APOE in white matter disruptions. Further, among veteran ɛ4 carriers exposed to close-range blast, we observed a positive association between the number of CBEs and the number of white matter abnormalities. These results raise the possibility that CBE interacts with AD genetic influences on neuropathological processes such as the degradation of white matter integrity.

Longitudinal Changes in Diffusion Tensor Imaging Following Mild Traumatic Brain Injury and Correlation With Outcome

The chronic consequences of traumatic brain injury (TBI) may contribute to the increased risk for early cognitive decline and dementia, primarily due to diffusion axonal injury. Previous studies in mild TBI (mTBI) have been controversial in describing the white matter tract integrity changes occurring at acute and subacute post-injury. In this prospective longitudinal study, we aim to investigate the longitudinal changes of white matter (WM) using diffusion tensor imaging (DTI) and their correlations with neuropsychological tests. Thirty-three patients with subacute mTBI and 31 matched healthy controls were studied with an extensive imaging and clinical battery. Neuroimaging was obtained within 7 days post-injury for acute scans and repeated at 1 and 3 months post-injury. Using a region-of-interest-based approach, tract-based spatial statistics was used to conduct voxel-wise analysis on diffusion changes in mTBI and was compared to those of healthy matched controls, scanned during the same time period and rescanned with an interval similar to that of patients. We found decreased fractional anisotropy (FA) values in the left anterior limb of internal capsule (ALIC) and right inferior fronto-occipital fasciculus (IFOF) during the 7 days post-injury, which showed longitudinal evidence of recovery following 1 month post-injury. Increased FA values in these two tracts at 1 month post-injury were positively associated with better performance on cognitive information processing speed at initial assessment. By contrast, there were also some tracts (right anterior corona radiata, forceps major, and body of corpus callosum) exhibiting the continuing loss of integrity sustaining even beyond 3 months, which can predict the persisting post-concussion syndromes. Continuing loss of structural integrity in some tracts may contribute to the persistent post-concussion syndromes in mTBI patients, suggesting certain tracts providing an objective biomarker for tracking the pathological recovery process following mTBI.

Candidate CSPG4 mutations and induced pluripotent stem cell modeling implicate oligodendrocyte progenitor cell dysfunction in familial schizophrenia

Schizophrenia is highly heritable, yet its underlying pathophysiology remains largely unknown. Among the most well-replicated findings in neurobiological studies of schizophrenia are deficits in myelination and white matter integrity; however, direct etiological genetic and cellular evidence has thus far been lacking. Here, we implement a family-based approach for genetic discovery in schizophrenia combined with functional analysis using induced pluripotent stem cells (iPSCs). We observed familial segregation of two rare missense mutations in Chondroitin Sulfate Proteoglycan 4 (CSPG4) (c.391G > A [p.A131T], MAF 7.79 × 10-5 and c.2702T > G [p.V901G], MAF 2.51 × 10-3). The CSPG4A131T mutation was absent from the Swedish Schizophrenia Exome Sequencing Study (2536 cases, 2543 controls), while the CSPG4V901G mutation was nominally enriched in cases (11 cases vs. 3 controls, P = 0.026, OR 3.77, 95% CI 1.05-13.52). CSPG4/NG2 is a hallmark protein of oligodendrocyte progenitor cells (OPCs). iPSC-derived OPCs from CSPG4A131T mutation carriers exhibited abnormal post-translational processing (P = 0.029), subcellular localization of mutant NG2 (P = 0.007), as well as aberrant cellular morphology (P = 3.0 × 10-8), viability (P = 8.9 × 10-7), and myelination potential (P = 0.038). Moreover, transfection of healthy non-carrier sibling OPCs confirmed a pathogenic effect on cell survival of both the CSPG4A131T (P = 0.006) and CSPG4V901G (P = 3.4 × 10-4) mutations. Finally, in vivo diffusion tensor imaging of CSPG4A131T mutation carriers demonstrated a reduction of brain white matter integrity compared to unaffected sibling and matched general population controls (P = 2.2 × 10-5). Together, our findings provide a convergence of genetic and functional evidence to implicate OPC dysfunction as a candidate pathophysiological mechanism of familial schizophrenia.

An evaluation of Z-transform algorithms for identifying subject-specific abnormalities in neuroimaging data

The need for algorithms that capture subject-specific abnormalities (SSA) in neuroimaging data is increasingly recognized across many neuropsychiatric disorders. However, the effects of initial distributional properties (e.g., normal versus non-normally distributed data), sample size, and typical preprocessing steps (spatial normalization, blurring kernel and minimal cluster requirements) on SSA remain poorly understood. The current study evaluated the performance of several commonly used z-transform algorithms [leave-one-out (LOO); independent sample (IDS); Enhanced Z-score Microstructural Assessment of Pathology (EZ-MAP); distribution-corrected z-scores (DisCo-Z); and robust z-scores (ROB-Z)] for identifying SSA using simulated and diffusion tensor imaging data from healthy controls (N = 50). Results indicated that all methods (LOO, IDS, EZ-MAP and DisCo-Z) with the exception of the ROB-Z eliminated spurious differences that are present across artificially created groups following a standard z-transform. However, LOO and IDS consistently overestimated the true number of extrema (i.e., SSA) across all sample sizes and distributions. The EZ-MAP and DisCo-Z algorithms more accurately estimated extrema across most distributions and sample sizes, with the exception of skewed distributions. DTI results indicated that registration algorithm (linear versus non-linear) and blurring kernel size differentially affected the number of extrema in positive versus negative tails. Increasing the blurring kernel size increased the number of extrema, although this effect was much more prominent when a minimum cluster volume was applied to the data. In summary, current results highlight the need to statistically compare the frequency of SSA in control samples or to develop appropriate confidence intervals for patient data.

White matter abnormalities in mild traumatic brain injury with and without post-traumatic stress disorder: a subject-specific diffusion tensor imaging study

Mild traumatic brain injuries (mTBIs) are often associated with posttraumatic stress disorder (PTSD). In cases of chronic mTBI, accurate diagnosis can be challenging due to the overlapping symptoms this condition shares with PTSD. Furthermore, mTBIs are heterogeneous and not easily observed using conventional neuroimaging tools, despite the fact that diffuse axonal injuries are the most common injury. Diffusion tensor imaging (DTI) is sensitive to diffuse axonal injuries and is thus more likely to detect mTBIs, especially when analyses account for the inter-individual variability of these injuries. Using a subject-specific approach, we compared fractional anisotropy (FA) abnormalities between groups with a history of mTBI (n = 35), comorbid mTBI and PTSD (mTBI + PTSD; n = 22), and healthy controls (n = 37). We compared all three groups on the number of abnormal FA clusters derived from subject-specific injury profiles (i.e., individual z-score maps) along a common white matter skeleton. The mTBI + PTSD group evinced a greater number of abnormally low FA clusters relative to both the healthy controls and the mTBI group without PTSD (p < .05). Across the groups with a history of mTBI, increased numbers of abnormally low FA clusters were significantly associated with PTSD symptom severity, depression, post-concussion symptoms, and reduced information processing speed (p < .05). These findings highlight the utility of subject-specific microstructural analyses when searching for mTBI-related brain abnormalities, particularly in patients with PTSD. This study also suggests that patients with a history of mTBI and comorbid PTSD, relative to those without PTSD, are at increased risk of FA abnormalities.

Preserved white matter microstructure in young patients with anorexia nervosa?

A massive but reversible reduction of cortical thickness and subcortical gray matter (GM) volumes in Anorexia Nervosa (AN) has been recently reported. However, the literature on alterations in white matter (WM) volume and microstructure changes in both acutely underweight AN (acAN) and after recovery (recAN) is sparse and results are inconclusive. Here, T1-weighted and diffusion-weighted MRI data in a sizable sample of young and medication-free acAN (n = 35), recAN (n = 32), and age-matched female healthy controls (HC, n = 62) were obtained. For analysis, a well-validated global probabilistic tractography reconstruction algorithm including rigorous motion correction implemented in FreeSurfer: TRACULA (TRActs Constrained by UnderLying Anatomy) were used. Additionally, a clustering algorithm and a multivariate pattern classification technique to WM metrics to predict group membership were applied. No group differences in either WM volume or WM microstructure were detected with standard analysis procedures either in acAN or recAN relative to HC after controlling for the number of performed statistical tests. These findings were not affected by age, IQ, or psychiatric symptoms. While cluster analysis was unsuccessful at discriminating between groups, multivariate pattern classification showed some ability to separate acAN from HC (but not recAN from HC). However, these results were not compatible with a straightforward hypothesis of impaired WM microstructure. The current findings suggest that WM integrity is largely preserved in non-chronic AN. This finding stands in contrast to findings in GM, but may help to explain the relatively intact cognitive performance of young patients with AN and provide the basis for the fast recovery of GM structures. Hum Brain Mapp 37:4069-4083, 2016. © 2016 Wiley Periodicals, Inc.

Aberrant White Matter Microstructure in Children and Adolescents With the Subtype of Prader-Willi Syndrome at High Risk for Psychosis

Prader-Willi Syndrome (PWS) is a complex neurogenetic disorder caused by loss of the paternal 15q11.2-q13 locus, due to deletion (DEL), maternal uniparental disomy (mUPD), or imprinting center defects. Individuals with mUPD have up to 60% risk of developing psychosis in early adulthood. Given the increasing evidence for white matter abnormalities in psychotic disorders, we investigated white matter microstructure in children and adolescents with PWS, with a particular emphasis on the DEL and mUPD subtypes. Magnetic resonance diffusion weighted images were acquired in 35 directions at 3T and analyzed using fractional anisotropy (FA), mean, axial, and radial diffusivity (MD, AD, RD) values obtained by tract-based spatial statistics (TBSS) in 28 children and adolescents with PWS and 61 controls. In addition, we employed a recently developed white matter pothole approach, which does not require local FA differences to be spatially co-localized across subjects. After accounting for age and gender, individuals with PWS had significantly lower global FA and higher MD, compared with controls. Individuals with mUPD had lower FA in multiple regions including the corpus callosum, cingulate, and superior longitudinal fasciculus and larger potholes, compared with DEL and controls. The observed differences in individuals with mUPD are similar to the white matter abnormalities in individuals with psychotic disorders. Conversely, the subtle white matter abnormalities in individuals with DEL are consistent with their substantially lower risk of psychosis. Future studies to investigate the specific neurobiological mechanism underlying the differential psychosis risk between the DEL and mUPD subtypes of PWS are highly warranted.

Dynamic changes in diffusion measures improve sensitivity in identifying patients with mild traumatic brain injury

The goal of this study was to investigate patterns of axonal injury in the first week after mild traumatic brain injury (mTBI). We performed a prospective cohort study of 20 patients presenting to the emergency department with mTBI, using 3.0T diffusion tensor MRI immediately after injury and again at 1 week post-injury. Corresponding data were acquired from 16 controls over a similar time interval. Fractional anisotropy (FA) and other diffusion measures were calculated from 11 a priori selected axon tracts at each time-point, and the change across time in each region was quantified for each subject. Clinical outcomes were determined by standardized neurocognitive assessment. We found that mTBI subjects were significantly more likely to have changes in FA in those 11 regions of interest across the one week time period, compared to control subjects whose FA measurements were stable across time. Longitudinal imaging was more sensitive to these subtle changes in white matter integrity than cross-sectional assessments at either of two time points, alone. Analyzing the sources of variance in our control population, we show that this increased sensitivity is likely due to the smaller within-subject variability obtained by longitudinal analysis with each subject as their own control. This is in contrast to the larger between-subject variability obtained by cross-sectional analysis of each individual subject to normalized data from a control group. We also demonstrated that inclusion of all a priori ROIs in an analytic model as opposed to measuring individual ROIs improves detection of white matter changes by overcoming issues of injury heterogeneity. Finally, we employed genetic programming (a bio-inspired computational method for model estimation) to demonstrate that longitudinal changes in FA have utility in predicting the symptomatology of patients with mTBI. We conclude concussive brain injury caused acute, measurable changes in the FA of white matter tracts consistent with evolving axonal injury and/or edema, which may contribute to post-concussive symptoms.

Inter-Subject Variability of Axonal Injury in Diffuse Traumatic Brain Injury

Traumatic brain injury (TBI) is a leading cause of cognitive morbidity worldwide for which reliable biomarkers are needed. Diffusion tensor imaging (DTI) is a promising biomarker of traumatic axonal injury (TAI); however, existing studies have been limited by a primary reliance on group-level analytic methods not well suited to account for inter-subject variability. In this study, 42 adults with TBI of at least moderate severity were examined 3 months following injury and compared with 35 healthy controls. DTI data were used for both traditional group-level comparison and subject-specific analysis using the distribution-corrected Z-score (DisCo-Z) approach. Inter-subject variation in TAI was assessed in a threshold-invariant manner using a threshold-weighted overlap map derived from subject-specific analysis. Receiver operator curve analysis was used to examine the ability of subject-specific DTI analysis to identify TBI subjects with significantly impaired processing speed in comparison with region of interest-based fractional anisotropy (FA) measurements and clinical characteristics. Traditional group-wise analysis demonstrated widespread reductions of white matter FA within the TBI group (voxel-wise p < 0.05, corrected), despite relatively low consistency of subject-level effects secondary to widespread variation in the spatial distribution of TAI. Subject-specific mapping of TAI with the DisCo-Z approach was the best predictor of impaired processing speed, achieving high classification accuracy (area under the curve [AUC] = 0.94). In moderate-to-severe TBI, there is substantial inter-subject variation in TAI, with extent strongly correlated to post-traumatic deficits in processing speed. Significant group-level effects do not necessarily represent consistent effects at the individual level. Better accounting for inter-subject variability in neurobiological manifestations of TBI may substantially improve the ability to detect and classify patterns of injury.

Assessing connectivity related injury burden in diffuse traumatic brain injury

Many of the clinical and behavioral manifestations of traumatic brain injury (TBI) are thought to arise from disruption to the structural network of the brain due to diffuse axonal injury (DAI). However, a principled way of summarizing diffuse connectivity alterations to quantify injury burden is lacking. In this study, we developed a connectome injury score, Disruption Index of the Structural Connectome (DISC), which summarizes the cumulative effects of TBI-induced connectivity abnormalities across the entire brain. Forty patients with moderate-to-severe TBI examined at 3 months postinjury and 35 uninjured healthy controls underwent magnetic resonance imaging with diffusion tensor imaging, and completed behavioral assessment including global clinical outcome measures and neuropsychological tests. TBI patients were selected to maximize the likelihood of DAI in the absence of large focal brain lesions. We found that hub-like regions, with high betweenness centrality, were most likely to be impaired as a result of diffuse TBI. Clustering of participants revealed a subgroup of TBI patients with similar connectivity abnormality profiles who exhibited relatively poor cognitive performance. Among TBI patients, DISC was significantly correlated with post-traumatic amnesia, verbal learning, executive function, and processing speed. Our experiments jointly demonstrated that assessing structural connectivity alterations may be useful in development of patient-oriented diagnostic and prognostic tools. Hum Brain Mapp 38:2913-2922, 2017. © 2017 Wiley Periodicals, Inc.

Subject-specific abnormal region detection in traumatic brain injury using sparse model selection on high dimensional diffusion data

We present a method to estimate a multivariate Gaussian distribution of diffusion tensor features in a set of brain regions based on a small sample of healthy individuals, and use this distribution to identify imaging abnormalities in subjects with mild traumatic brain injury. The multivariate model receives apriori knowledge in the form of a neighborhood graph imposed on the precision matrix, which models brain region interactions, and an additional L₁ sparsity constraint. The model is then estimated using the graphical LASSO algorithm and the Mahalanobis distance of healthy and TBI subjects to the distribution mean is used to evaluate the discriminatory power of the model. Our experiments show that the addition of the apriori neighborhood graph results in significant improvements in classification performance compared to a model which does not take into account the brain region interactions or one which uses a fully connected prior graph. In addition, we describe a method, using our model, to detect the regions that contribute the most to the overall abnormality of the DTI profile of a subject's brain.

In vivo imaging of neuroinflammation in schizophrenia

In recent years evidence has accumulated to suggest that neuroinflammation might be an early pathology of schizophrenia that later leads to neurodegeneration, yet the exact role in the etiology, as well as the source of neuroinflammation, are still not known. The hypothesis of neuroinflammation involvement in schizophrenia is quickly gaining popularity, and thus it is imperative that we have reliable and reproducible tools and measures that are both sensitive, and, most importantly, specific to neuroinflammation. The development and use of appropriate human in vivo imaging methods can help in our understanding of the location and extent of neuroinflammation in different stages of the disorder, its natural time-course, and its relation to neurodegeneration. Thus far, there is little in vivo evidence derived from neuroimaging methods. This is likely the case because the methods that are specific and sensitive to neuroinflammation are relatively new or only just being developed. This paper provides a methodological review of both existing and emerging positron emission tomography and magnetic resonance imaging techniques that identify and characterize neuroinflammation. We describe \how these methods have been used in schizophrenia research. We also outline the shortcomings of existing methods, and we highlight promising future techniques that will likely improve state-of-the-art neuroimaging as a more refined approach for investigating neuroinflammation in schizophrenia.

White Matter Microstructure in Early-Onset Schizophrenia: A Systematic Review of Diffusion Tensor Imaging Studies

OBJECTIVE

Neurodevelopmental processes and neural connectivity are thought to play pivotal roles in schizophrenia. This article reviews diffusion tensor imaging (DTI) studies of brain white matter connections and microstructure and their development in patients with early-onset schizophrenia (EOS), that is, schizophrenia with an age of onset before 18 years.

METHOD

A systematic literature search revealed 21 original case-control DTI studies of children and/or adolescents with EOS.

RESULTS

Nearly all studies report significantly lower regional fractional anisotropy (FA) in patients with EOS than in healthy control participants. However, the anatomical locations and extent of these differences are highly variable across studies. Furthermore, consistent evidence for associations between DTI indices and age of onset, medication variables, and measures of symptomatology and cognition in EOS is lacking. Only 3 available studies have investigated cross-sectional age-related differences or longitudinal changes in DTI measures in adolescents with EOS. The results are mixed, with different studies indicating diverging, converging, or parallel developmental FA trajectories between patients and controls.

CONCLUSION

The study of brain structural connectivity, as inferred from DTI, and its development in EOS may inform us on the origin and ontogeny of schizophrenia. We suggest some directions for future research in this field and argue for increased focus on developmental questions. Specifically, further investigations of age of onset effects and multimethod longitudinal studies of structural and functional connectivity development before, at, and after onset of schizophrenia and related syndromes in children and adolescents are called for.

Diffusion tensor imaging alterations in patients with postconcussion syndrome undergoing exercise treatment: a pilot longitudinal study

PURPOSE

To investigate diffusion tensor imaging characteristics in patients with postconcussion syndrome (PCS) who received exercise (n = 4) and placebo stretching (n = 4) treatments compared with a group of healthy controls (n = 15).

METHODS

Subjects diagnosed with PCS obtained a diffusion tensor imaging magnetic resonance image at pretreatment (baseline) and approximately 8 weeks later (follow-up). Analyses included a groupwise comparison using tract-based spatial statistics and a z-score map that investigated localized regional anomalies compared with the healthy control group projected onto the tract-based spatial statistics skeleton.

RESULTS

The tract-based spatial statistics analysis detected groupwise differences in the genu of the corpus callosum at both time points with decreased fractional anisotropy and increased radial diffusivity and mean diffusivity values. In contrast, the z-score analysis was more sensitive to heterogeneous changes in fractional anisotropy, with both low- and high-localized areas across various white matter regions, the most prevalent being the corpus callosum, anterior and superior corona radiata, and internal and external capsules. The mean number of voxels different in patients with PCS versus healthy controls was greater in all cases (baseline lower: P < .03 and higher: P < .0001; follow-up lower: P < .0001 and higher: P < .0001). The volume and location of these abnormal regions changed between the 2 diffusion tensor imaging scans, but these did not correlate with the mitigation of symptoms in the patients with PCS.

CONCLUSIONS

Diffusion tensor imaging revealed spatially varying and heterogeneous localized irregularities in patients with PCS that persisted even as patient symptoms decreased and prognosis improved.

White matter abnormalities are associated with chronic postconcussion symptoms in blast-related mild traumatic brain injury

Blast-related mild traumatic brain injury (mTBI) is a common injury among Iraq and Afghanistan military veterans due to the frequent use of improvised explosive devices. A significant minority of individuals with mTBI report chronic postconcussion symptoms (PCS), which include physical, emotional, and cognitive complaints. However, chronic PCS are nonspecific and are also associated with mental health disorders such as posttraumatic stress disorder (PTSD). Identifying the mechanisms that contribute to chronic PCS is particularly challenging in blast-related mTBI, where the incidence of comorbid PTSD is high. In this study, we examined whether blast-related mTBI is associated with diffuse white matter changes, and whether these neural changes are associated with chronic PCS. Ninety Operation Enduring Freedom/Operation Iraqi Freedom (OEF/OIF) veterans were assigned to one of three groups including a blast-exposed no--TBI group, a blast-related mTBI without loss of consciousness (LOC) group (mTBI--LOC), and a blast-related mTBI with LOC group (mTBI + LOC). PCS were measured with the Rivermead Postconcussion Questionnaire. Results showed that participants in the mTBI + LOC group had more spatially heterogeneous white matter abnormalities than those in the no--TBI group. These white matter abnormalities were significantly associated with physical PCS severity even after accounting for PTSD symptoms, but not with cognitive or emotional PCS severity. A mediation analysis revealed that mTBI + LOC significantly influenced physical PCS severity through its effect on white matter integrity. These results suggest that white matter abnormalities are associated with chronic PCS independent of PTSD symptom severity and that these abnormalities are an important mechanism explaining the relationship between mTBI and chronic physical PCS.

Investigation of white matter abnormalities in first episode psychosis patients with persistent negative symptoms

Aberrant white matter structures in fronto-temporal regions have previously been identified in patients with schizophrenia. However, scant research has focused on white matter integrity in patients presenting with a first episode of psychosis (FEP) with persistent negative symptoms (PNS). This study aimed to explore microstructure in the neurocircuitry proposed to be involved in PNS, by using a region-of-interest approach. Secondly, the relationship between individual negative symptoms and white matter were explored. Fractional anisotropy (FA) was measured in the fornix and three other tracts bilaterally including the uncinate fasciculus, superior longitudinal fasciculus and the cingulum bundle. Twelve patients with PNS were compared to a non-PNS group (52) and a healthy control group (51). Results showed that the PNS group had significantly lower FA values in the fornix when compared to healthy controls and that the non-PNS group had significantly lower FA values in the right uncinate fasciculus compared to healthy controls. Significant correlations were observed between SANS global score for anhedonia-asociality and lower FA values in the right cingulum bundle. Our results suggest that fronto-temporal white matter might be more closely related to PNS and that this relationship may possibly be mediated by greater anhedonia in PNS patients.

Integrated Analysis and Visualization of Group Differences in Structural and Functional Brain Connectivity: Applications in Typical Ageing and Schizophrenia

Structural and functional brain connectivity are increasingly used to identify and analyze group differences in studies of brain disease. This study presents methods to analyze uni- and bi-modal brain connectivity and evaluate their ability to identify differences. Novel visualizations of significantly different connections comparing multiple metrics are presented. On the global level, “bi-modal comparison plots” show the distribution of uni- and bi-modal group differences and the relationship between structure and function. Differences between brain lobes are visualized using “worm plots”. Group differences in connections are examined with an existing visualization, the “connectogram”. These visualizations were evaluated in two proof-of-concept studies: (1) middle-aged versus elderly subjects; and (2) patients with schizophrenia versus controls. Each included two measures derived from diffusion weighted images and two from functional magnetic resonance images. The structural measures were minimum cost path between two anatomical regions according to the “Statistical Analysis of Minimum cost path based Structural Connectivity” method and the average fractional anisotropy along the fiber. The functional measures were Pearson’s correlation and partial correlation of mean regional time series. The relationship between structure and function was similar in both studies. Uni-modal group differences varied greatly between connectivity types. Group differences were identified in both studies globally, within brain lobes and between regions. In the aging study, minimum cost path was highly effective in identifying group differences on all levels; fractional anisotropy and mean correlation showed smaller differences on the brain lobe and regional levels. In the schizophrenia study, minimum cost path and fractional anisotropy showed differences on the global level and within brain lobes; mean correlation showed small differences on the lobe level. Only fractional anisotropy and mean correlation showed regional differences. The presented visualizations were helpful in comparing and evaluating connectivity measures on multiple levels in both studies.

Corpus callosum size and diffusion tensor anisotropy in adolescents and adults with schizophrenia

The corpus callosum has been implicated as a region of dysfunctional connectivity in schizophrenia, but the association between age and callosal pathology is unclear. Magnetic resonance imaging (MRI) and diffusion-tensor imaging (DTI) were performed on adults (n=34) and adolescents (n=17) with schizophrenia and adult (n=33) and adolescent (n=15) age- and sex-matched healthy controls. The corpus callosum was manually traced on each participant׳s MRI, and the DTI scan was co-registered to the MRI. The corpus callosum was divided into five anteroposterior segments. Area and anisotropy were calculated for each segment. Both patient groups demonstrated reduced callosal anisotropy; however, the adolescents exhibited reductions mostly in anterior regions while the reductions were more prominent in posterior regions of the adults. The adolescent patients showed greater decreases in absolute area as compared with the adult patients, particularly in the anterior segments. However, the adults showed greater reductions when area was considered relative to whole brain white matter volume. Our results suggest that the initial stages of the illness are characterized by deficiencies in frontal connections, and the chronic phase is characterized by deficits in the posterior corpus callosum; or, alternatively, adolescent-onset schizophrenia may represent a different or more severe form of the illness.

Approaching a network connectivity-driven classification of the psychosis continuum: a selective review and suggestions for future research

Brain changes in schizophrenia evolve along a dynamic trajectory, emerging before disease onset and proceeding with ongoing illness. Recent investigations have focused attention on functional brain interactions, with experimental imaging studies supporting the disconnection hypothesis of schizophrenia. These studies have revealed a broad spectrum of abnormalities in brain connectivity in patients, particularly for connections integrating the frontal cortex. A critical point is that brain connectivity abnormalities, including altered resting state connectivity within the fronto-parietal (FP) network, are already observed in non-help-seeking individuals with psychotic-like experiences. If we consider psychosis as a continuum, with individuals with psychotic-like experiences at the lower and psychotic patients at the upper ends, individuals with psychotic-like experiences represent a key population for investigating the validity of putative biomarkers underlying the onset of psychosis. This paper selectively addresses the role played by FP connectivity in the psychosis continuum, which includes patients with chronic psychosis, early psychosis, clinical high risk, genetic high risk, as well as the general population with psychotic experiences. We first discuss structural connectivity changes among the FP pathway in each domain in the psychosis continuum. This may provide a basis for us to gain an understanding of the subsequent changes in functional FP connectivity. We further indicate that abnormal FP connectivity may arise from glutamatergic disturbances of this pathway, in particular from abnormal NMDA receptor-mediated plasticity. In the second part of this paper we propose some concepts for further research on the use of network connectivity in the classification of the psychosis continuum. These concepts are consistent with recent efforts to enhance the role of data in driving the diagnosis of psychiatric spectrum diseases.

Does diffusion MRI tell us anything about the white matter? An overview of methods and pitfalls

One key pitfall in diffusion magnetic resonance imaging (dMRI) clinical neuroimaging research is the challenge of understanding and interpreting the results of a complex analysis pipeline. The sophisticated algorithms employed by the analysis software, combined with the relatively non-specific nature of many diffusion measurements, lead to challenges in interpretation of the results. This paper is aimed at an intended audience of clinical researchers who are learning about dMRI or trying to interpret dMRI results, and who may be wondering "Does dMRI tell us anything about the white matter?" We present a critical review of dMRI methods and measures used in clinical neuroimaging research, focusing on the most commonly used analysis methods and the most commonly reported measures. We describe important pitfalls in every section, and provide extensive references for the reader interested in more detail.

White matter abnormalities associated with military PTSD in the context of blast TBI

Mild traumatic brain injury (mTBI) and post-traumatic stress disorder (PTSD) are common among recent military veterans and involve substantial symptom overlap, making clinical distinction and effective intervention difficult. Emerging evidence of cerebral white matter abnormalities associated with mTBI may provide a biological measure to inform diagnosis and treatment, but the potentially confounding effects between PTSD and mTBI have largely gone unexamined. We collected diffusion imaging data from 133 recently-deployed American service members who developed PTSD and/or sustained mTBI, or had neither condition. Effects of PTSD and mTBI on traditional tensor-based measures of cerebral white matter integrity (fractional anisotropy [FA] and mean diffusivity [MD]) were compared in anatomical regions of interest and individual voxels throughout the brain. Generalized FA (GFA), which allows for multiple fiber orientations per voxel, was also included to improve sensitivity in white matter areas containing crossing or diverging axon bundles. PTSD was consistently associated with high GFA in select brain regions, greater likelihood of regions and voxels with abnormally low MD, and a greater number of voxels with abnormally high FA, while mTBI was associated with fewer high MD regions. Overall, PTSD was associated with more restricted diffusion (low MD) and greater anisotropy (high GFA) in regions of crossing/diverging fibers poorly characterized by a single tensor (FA), suggesting that interstitial fibers may be involved. Contrary to earlier results in a sample without PTSD, mTBI was not associated with anisotropy abnormalities, perhaps indicating the cooccurrence of PTSD and mTBI requires special consideration with regard to structural brain connectivity.

White matter changes in early phase schizophrenia and cannabis use: an update and systematic review of diffusion tensor imaging studies

OBJECTIVES

The impact of cannabis use on the brain tissue is still unclear, both in the healthy developing brain and in people with schizophrenia. The focus of this review is on white matter, the primary connective infrastructure of the brain.

METHODS

We systematically reviewed diffusion tensor imaging (DTI) studies of early phase schizophrenia (illness effect), of cannabis use in otherwise healthy brains (drug effect), and of early phase schizophrenia with cannabis use (combined effects). Studies had to include a healthy, non-cannabis using, control group as well as report on fractional anisotropy as it is the most commonly used DTI index. We excluded cohorts with heavy alcohol or illicit drug use and studies with a sample size of less than 20 in the clinical group.

RESULTS

We retained 17 studies of early phase schizophrenia, which together indicate deficits in white matter integrity observed in all fiber tract families, but most frequently in association, callosal and projection fibers. In otherwise healthy cannabis users (2 studies), deficits in white matter tracts were reported mainly in callosal fibers, but also in projection and limbic fibers. In cannabis users with early phase schizophrenia (1 study), deficits in white matter integrity were also observed in all fiber tract families, except for limbic fibers.

CONCLUSIONS

The current literature points to several families of white matter tracts being differentially affected in early phase schizophrenia. Further work is required to reveal the impact of cannabis use in otherwise healthy people as well as those with schizophrenia.

LIMITATIONS

Paucity of available studies as well as restricting analysis to FA values represent the main limitations of this review.

Methods for identifying subject-specific abnormalities in neuroimaging data

Algorithms that are capable of capturing subject-specific abnormalities (SSA) in neuroimaging data have long been an area of focus for diverse neuropsychiatric conditions such as multiple sclerosis, schizophrenia, and traumatic brain injury. Several algorithms have been proposed that define SSA in patients (i.e., comparison group) relative to image intensity levels derived from healthy controls (HC) (i.e., reference group) based on extreme values. However, the assumptions underlying these approaches have not always been fully validated, and may be dependent on the statistical distributions of the transformed data. The current study evaluated variations of two commonly used techniques ("pothole" method and standardization with an independent reference group) for identifying SSA using simulated data (derived from normal, t and chi-square distributions) and fractional anisotropy maps derived from 50 HC. Results indicated substantial group-wise bias in the estimation of extreme data points using the pothole method, with the degree of bias being inversely related to sample size. Statistical theory was utilized to develop a distribution-corrected z-score (DisCo-Z) threshold, with additional simulations demonstrating elimination of the bias and a more consistent estimation of extremes based on expected distributional properties. Data from previously published studies examining SSA in mild traumatic brain injury were then re-analyzed using the DisCo-Z method, with results confirming the evidence of group-wise bias. We conclude that the benefits of identifying SSA in neuropsychiatric research are substantial, but that proposed SSA approaches require careful implementation under the different distributional properties that characterize neuroimaging data.

Associations of white matter integrity and cortical thickness in patients with schizophrenia and healthy controls

Typical brain development includes coordinated changes in both white matter (WM) integrity and cortical thickness (CT). These processes have been shown to be disrupted in schizophrenia, which is characterized by abnormalities in WM microstructure and by reduced CT. The aim of this study was to identify patterns of association between WM markers and cortex-wide CT in healthy controls (HCs) and patients with schizophrenia (SCZ). Using diffusion tensor imaging and structural magnetic resonance imaging data of the Mind Clinical Imaging Consortium study (130 HC and 111 SCZ), we tested for associations between (a) fractional anisotropy in selected manually labeled WM pathways (corpus callosum, anterior thalamic radiation, and superior longitudinal fasciculus) and CT, and (b) the number of lesion-like WM regions ("potholes") and CT. In HC, but not SCZ, we found highly significant negative associations between WM integrity and CT in several pathways, including frontal, temporal, and occipital brain regions. Conversely, in SCZ the number of WM potholes correlated with reduced CT in the left lateral temporal gyrus, left fusiform, and left lateral occipital brain area. Taken together, we found differential patterns of association between WM integrity and CT in HC and SCZ. Although the pattern in HC can be explained from a developmental perspective, the reduced gray matter CT in SCZ patients might be the result of focal but spatially heterogeneous disruptions of WM integrity.

Potholes and molehills: bias in the diagnostic performance of diffusion-tensor imaging in concussion

PURPOSE

To investigate the extent of bias in a clinical study involving "pothole analysis" of diffusion-tensor imaging (DTI) data used to quantify white matter lesion load in diseases with a heterogeneous spatial distribution of pathologic findings, such as mild traumatic brain injury (TBI), and create a mathematical model of the bias.

MATERIALS AND METHODS

Use of the same reference population to define normal findings and make comparisons with a patient group introduces bias, which potentially inflates reported diagnostic performance. In this institutional review board-approved prospective observational cohort study, DTI data were obtained in 20 patients admitted to the emergency department with mild TBI and in 16 control subjects. Potholes and molehills were defined as clusters of voxels with fractional anisotropy values more than 2 standard deviations below and above the mean of the corresponding voxels in the reference population, respectively. The number and volume of potholes and molehills in the two groups were compared by using a Mann-Whitney U test.

RESULTS

Standard analysis showed significantly more potholes in mild TBI than in the control group (102.5 ± 34.3 vs 50.6 ± 28.9, P < .001). Repeat analysis by using leave-one-out cross-validation decreased the apparent difference in potholes between groups (mild TBI group, 102.5 ± 34.3; control group, 93.4 ± 27.2; P = .369). It was demonstrated that even with 100 subjects, this bias can decrease the voxelwise false-positive rate by more than 30% in the control group.

CONCLUSION

The pothole approach to neuroimaging data may introduce bias, which can be minimized by independent training and test groups or cross-validation methods. This bias is sufficient to call into question the previously reported diagnostic performance of DTI for mild TBI.

White matter abnormalities and cognitive impairment in early-onset schizophrenia-spectrum disorders

OBJECTIVE

To characterize white matter abnormalities in adolescents with early-onset schizophrenia (EOS) relative to 3 comparison groups (adolescents at clinical high risk for developing schizophrenia [CHR], adolescents with cannabis use disorder [CUD], and healthy controls [HC]), and to identify neurocognitive correlates of white matter abnormalities in EOS.

METHOD

We used diffusion tensor imaging and tractography methods to examine fractional anisotropy (FA) of the cingulum bundle, superior longitudinal fasciculus, corticospinal tract (CST), inferior longitudinal fasciculus (ILF), inferior fronto-occipital fasciculus (IFOF), and uncinate fasciculus in adolescents with EOS (n = 55), CHR (n = 21), CUD (n = 31), and HC (n = 55). FA in tracts that were significantly altered in EOS was correlated with neurocognitive performance.

RESULTS

EOS and CHR groups had significantly lower FA than HC in 4 tracts, namely, bilateral CST, left ILF, and left IFOF. CUD had lower FA than HC in left IFOF. Lower FA in left IFOF and left ILF predicted worse neurocognitive performance in EOS.

CONCLUSIONS

This study identified white matter abnormalities of the left ILF and left IFOF as possible biomarkers of vulnerability for developing schizophrenia. Lower FA in these tracts may disrupt functioning of ventral visual and language streams, producing domain-specific neurocognitive deficits that interfere with higher-order cognitive abilities.

The MCIC collection: a shared repository of multi-modal, multi-site brain image data from a clinical investigation of schizophrenia

Expertly collected, well-curated data sets consisting of comprehensive clinical characterization and raw structural, functional and diffusion-weighted DICOM images in schizophrenia patients and sex and age-matched controls are now accessible to the scientific community through an on-line data repository (coins.mrn.org). The Mental Illness and Neuroscience Discovery Institute, now the Mind Research Network (MRN, http://www.mrn.org/ ), comprised of investigators at the University of New Mexico, the University of Minnesota, Massachusetts General Hospital, and the University of Iowa, conducted a cross-sectional study to identify quantitative neuroimaging biomarkers of schizophrenia. Data acquisition across multiple sites permitted the integration and cross-validation of clinical, cognitive, morphometric, and functional neuroimaging results gathered from unique samples of schizophrenia patients and controls using a common protocol across sites. Particular effort was made to recruit patients early in the course of their illness, at the onset of their symptoms. There is a relatively even sampling of illness duration in chronic patients. This data repository will be useful to 1) scientists who can study schizophrenia by further analysis of this cohort and/or by pooling with other data; 2) computer scientists and software algorithm developers for testing and validating novel registration, segmentation, and other analysis software; and 3) educators in the fields of neuroimaging, medical image analysis and medical imaging informatics who need exemplar data sets for courses and workshops. Sharing provides the opportunity for independent replication of already published results from this data set and novel exploration. This manuscript describes the inclusion/exclusion criteria, imaging parameters and other information that will assist those wishing to use this data repository.

A comparative diffusion tensor imaging study of corpus callosum subregion integrity in bipolar disorder and schizophrenia

Structural magnetic resonance imaging (MRI) studies have provided evidence for corpus callosum (CC) white matter abnormalities in bipolar disorder (BD) and schizophrenia (SZ). These findings include alterations in shape, volume, white matter intensity and structural integrity compared to healthy control populations. Although CC alterations are implicated in both SZ and BD, no study of which we are aware has investigated callosal subregion differences between these two patient populations. We used diffusion tensor imaging (DTI) to assess CC integrity in patients with BD (n=16), SZ (n=19) and healthy controls (HC) (n=24). Fractional anisotropy (FA) of CC subregions was measured using region of interest (ROI) analysis and compared in the three groups. Significant group differences of FA values were revealed in five CC subregions, including the anterior genu, middle genu, posterior genu, posterior body and anterior splenium. FA values of the same subregions were significantly reduced in patients with SZ compared with HC. FA values were also significantly reduced in patients with BD compared to the HC group in the same subregions, excepting the middle genu. No significant difference was found between patient groups in any region. Most of the alterations in CC subregions were present in both the BD and SZ groups. These results imply an overlap in potential pathology, possibly relating to risk factors common to both disorders. The one region that differed between patient groups, the middle genu area, may serve as an illness marker and is perhaps involved in the different cognitive impairments observed in BD and SZ.

Multimodal neuroimaging of frontal white matter microstructure in early phase schizophrenia: the impact of early adolescent cannabis use

BACKGROUND

A disturbance in connectivity between different brain regions, rather than abnormalities within the separate regions themselves, could be responsible for the clinical symptoms and cognitive dysfunctions observed in schizophrenia. White matter, which comprises axons and their myelin sheaths, provides the physical foundation for functional connectivity in the brain. Myelin sheaths are located around the axons and provide insulation through the lipid membranes of oligodendrocytes. Empirical data suggests oligodendroglial dysfunction in schizophrenia, based on findings of abnormal myelin maintenance and repair in regions of deep white matter. The aim of this in vivo neuroimaging project is to assess the impact of early adolescent onset of regular cannabis use on brain white matter tissue integrity, and to differentiate this impact from the white matter abnormalities associated with schizophrenia. The ultimate goal is to determine the liability of early adolescent use of cannabis on brain white matter, in a vulnerable brain.

METHODS/DESIGN

Young adults with schizophrenia at the early stage of the illness (less than 5 years since diagnosis) will be the focus of this project. Four magnetic resonance imaging measurements will be used to assess different cellular aspects of white matter: a) diffusion tensor imaging, b) localized proton magnetic resonance spectroscopy with a focus on the neurochemical N-acetylaspartate, c) the transverse relaxation time constants of regional tissue water, d) and of N-acetylaspartate. These four neuroimaging indices will be assessed within the same brain region of interest, that is, a large white matter fibre bundle located in the frontal region, the left superior longitudinal fasciculus.

DISCUSSION

We will expand our knowledge regarding current theoretical models of schizophrenia with a more comprehensive multimodal neuroimaging approach to studying the underlying cellular abnormalities of white matter, while taking into consideration the important confounding variable of early adolescent onset of regular cannabis use.

Spatial characteristics of white matter abnormalities in schizophrenia

There is considerable evidence implicating brain white matter (WM) abnormalities in the pathophysiology of schizophrenia; however, the spatial localization of WM abnormalities reported in the existing studies is heterogeneous. Thus, the goal of this study was to quantify the spatial characteristics of WM abnormalities in schizophrenia. One hundred and fourteen patients with schizophrenia and 138 matched controls participated in this multisite study involving the Universities of Iowa, Minnesota, and New Mexico, and the Massachusetts General Hospital. We measured fractional anisotropy (FA) in brain WM regions extracted using 3 different image-processing algorithms: regions of interest, tract-based spatial statistics, and the pothole approach. We found that FA was significantly lower in patients using each of the 3 image-processing algorithms. The region-of-interest approach showed multiple regions with lower FA in patients with schizophrenia, with overlap at all 4 sites in the corpus callosum and posterior thalamic radiation. The tract-based spatial statistic approach showed (1) global differences in 3 of the 4 cohorts and (2) lower frontal FA at the Iowa site. Finally, the pothole approach showed a significantly greater number of WM potholes in patients compared to controls at each of the 4 sites. In conclusion, the spatial characteristics of WM abnormalities in schizophrenia reflect a combination of a global low-level decrease in FA, suggesting a diffuse process, coupled with widely dispersed focal reductions in FA that vary spatially among individuals (ie, potholes).

Updating the mild encephalitis hypothesis of schizophrenia

Schizophrenia seems to be a heterogeneous disorder. Emerging evidence indicates that low level neuroinflammation (LLNI) may not occur infrequently. Many infectious agents with low overall pathogenicity are risk factors for psychoses including schizophrenia and for autoimmune disorders. According to the mild encephalitis (ME) hypothesis, LLNI represents the core pathogenetic mechanism in a schizophrenia subgroup that has syndromal overlap with other psychiatric disorders. ME may be triggered by infections, autoimmunity, toxicity, or trauma. A 'late hit' and gene-environment interaction are required to explain major findings about schizophrenia, and both aspects would be consistent with the ME hypothesis. Schizophrenia risk genes stay rather constant within populations despite a resulting low number of progeny; this may result from advantages associated with risk genes, e.g., an improved immune response, which may act protectively within changing environments, although they are associated with the disadvantage of increased susceptibility to psychotic disorders. Specific schizophrenic symptoms may arise with instances of LLNI when certain brain functional systems are involved, in addition to being shaped by pre-existing liability factors. Prodrome phase and the transition to a diseased status may be related to LLNI processes emerging and varying over time. The variability in the course of schizophrenia resembles the varying courses of autoimmune disorders, which result from three required factors: genes, the environment, and the immune system. Preliminary criteria for subgrouping neurodevelopmental, genetic, ME, and other types of schizophrenias are provided. A rare example of ME schizophrenia may be observed in Borna disease virus infection. Neurodevelopmental schizophrenia due to early infections has been estimated by others to explain approximately 30% of cases, but the underlying pathomechanisms of transition to disease remain in question. LLNI (e.g. from reactivation related to persistent infection) may be involved and other pathomechanisms including dysfunction of the blood-brain barrier or the blood-CSF barrier, CNS-endogenous immunity and the volume transmission mode balancing wiring transmission (the latter represented mainly by synaptic transmission, which is often described as being disturbed in schizophrenia). Volume transmission is linked to CSF signaling; and together could represent a common pathogenetic link for the distributed brain dysfunction, dysconnectivity, and brain structural abnormalities observed in schizophrenia. In addition, CSF signaling may extend into peripheral tissues via the CSF outflow pathway along brain nerves and peripheral nerves, and it may explain the peripheral topology of neuronal dysfunctions found, like in olfactory dysfunction, dysautonomia, and even in peripheral tissues, i.e., the muscle lesions that were found in 50% of cases. Modulating factors in schizophrenia, such as stress, hormones, and diet, are also modulating factors in the immune response. Considering recent investigations of CSF, the ME schizophrenia subgroup may constitute approximately 40% of cases.

Mild traumatic brain injury in translation

This Introduction to a Special Issue on Mild Traumatic Brain Injury (mTBI) highlights the methodological challenges in outcome studies and clinical trials involving patients who sustain mTBI. Recent advances in brain imaging and portable, computerized cognitive tasks have contributed to protocols that are sensitive to the effects of mTBI and efficient in time for completion. Investigation of civilian mTBI has been extended to single and repeated injuries in athletes and blast-related mTBI in service members and veterans. Despite differences in mechanism of injury, there is evidence for similar effects of acceleration-deceleration and blast mechanisms of mTBI on cognition. Investigation of repetitive mTBI suggests that the effects may be cumulative and that repeated mTBI and repeated subconcussive head trauma may lead to neurodegenerative conditions. Although animal models of mTBI using cortical impact and fluid percussion injury in rodents have been able to reproduce some of the cognitive deficits frequently exhibited by patients after mTBI, modeling post-concussion symptoms is difficult. Recent use of closed head and blast injury animal models may more closely approximate clinical mTBI. Translation of interventions that are developed in animal models to patients with mTBI is a priority for the research agenda. This Special Issue on mTBI integrates basic neuroscience studies using animal models with studies of human mTBI, including the cognitive sequelae, persisting symptoms, brain imaging, and host factors that facilitate recovery.

Extensive white matter abnormalities in patients with first-episode schizophrenia: a Diffusion Tensor Iimaging (DTI) study

BACKGROUND

Previous voxelwise Diffusion Tensor Imaging (DTI) investigations of white matter in first-episode schizophrenia (FESZ) have been limited to the analysis of Fractional Anisotropy (FA) and mean diffusivity (MD), with their findings inconsistent in terms of the anatomical locations and extent of abnormalities. This study examines white matter abnormalities in FESZ, compared with healthy controls, using a tract-based spatial statistics (TBSS) approach applied to multiple measures of tract integrity, and correlates these findings with symptom severity.

METHODS

Seventeen first-episode patients with schizophrenia and seventeen age- and gender-matched healthy controls (HC) participated in this imaging study where FA, MD, and axial and radial diffusivities were compared between the two groups using TBSS.

RESULTS

First-episode patients with schizophrenia showed lower FA values in the genu and body of corpus callosum, the internal capsule, the external capsule, the fornix, the superior, inferior fronto-occipital fasciculus, the cingulum, and the uncinate fasciculus compared with HC. Increased MD and radial diffusivity were shown in virtually all white matter regions. There was no significant difference, however, observed for axial diffusivity between the two groups. Pearson correlation analysis showed that the FA values of the right inferior fronto-occipital fasciculus were positively correlated with positive symptoms, negative symptoms, and total correct items of the Wisconsin Card Sorting Test. FA values of right external capsule also showed significant positive correlation with category completed scores of the WCST.

CONCLUSIONS

These data suggest extensive, possibly myelin related white matter disruptions in FESZ.

Pediatric population-based neuroimaging and the Generation R Study: the intersection of developmental neuroscience and epidemiology

Neuroimaging studies of typically developing children and adolescents have provided valuable information on global and regional developmental trajectories of brain development. As these studies become larger and population-based, they are generating an intersection between the fields of developmental neuroscience and epidemiology. However, few of these studies have adequately probed the contribution of multiple environmental and genetic factors on brain development. Studies designed to optimally evaluate the role of multiple environmental and genetic factors on brain development require both large sample sizes and the prospective collection of multiple environmental factors. The Generation R Study is a large, prospective, prenatal-cohort study of nearly 10,000 children that began in 2002 in Rotterdam, the Netherlands. In September of 2009, 6-8 year old children from the Generation R Study were invited to participate in a magnetic resonance imaging component of the study. We provide an overview of the study design and experience for the first 801 children recruited for the neuroimaging component of the study. The protocol includes a 1-h neuropsychological assessment using the NEPSY-II, a mock scanning session, and a neuroimaging session that includes high-resolution structural, diffusion tensor, and resting-state functional MRI sequences. Image quality has been good to excellent in over 80% of the children to date. The infusion of imaging into the Generation R Study will set the stage for evaluating the role of multiple environmental and genetic factors in both typical and atypical neurodevelopment.

White matter abnormalities in veterans with mild traumatic brain injury

OBJECTIVE

It has been estimated that 10%-20% of U.S. veterans of the wars in Iraq and Afghanistan experienced mild traumatic brain injury (TBI), mostly secondary to blast exposure. Diffusion tensor imaging (DTI) may detect subtle white matter changes in both the acute and chronic stages of mild TBI and thus has the potential to detect white matter damage in patients with TBI. The authors used DTI to examine white matter integrity in a relatively large group of veterans with a history of mild TBI.

METHOD

DTI images from 72 veterans of the wars in Iraq and Afghanistan who had mild TBI were compared with DTI images from 21 veterans with no exposure to TBI during deployment. Conventional voxel-based analysis as well as a method of identifying spatially heterogeneous areas of decreased fractional anisotropy ("potholes") were used. Veterans also underwent psychiatric and neuropsychological assessments.

RESULTS

Voxel-based analysis did not reveal differences in DTI parameters between the veterans with mild TBI and those with no TBI. However, the veterans with mild TBI had a significantly higher number of potholes than those without TBI. The difference in the number of potholes was not influenced by age, time since trauma, a history of mild TBI unrelated to deployment, or coexisting psychopathology. The number of potholes was correlated with the severity of TBI and with performance in executive functioning tasks.

CONCLUSIONS

Veterans who had blast-related mild TBI showed evidence of multifocal white matter abnormalities that were associated with severity of the injury and with relevant functional measures. Overall, white matter potholes may constitute a sensitive biomarker of axonal injury that can be identified in mild TBI at acute and chronic stages of its clinical course.