Automated, high accuracy classification of Parkinsonian disorders: a pattern recognition approach

Progressive supranuclear palsy (PSP), multiple system atrophy (MSA) and idiopathic Parkinson’s disease (IPD) can be clinically indistinguishable, especially in the early stages, despite distinct patterns of molecular pathology. Structural neuroimaging holds promise for providing objective biomarkers for discriminating these diseases at the single subject level but all studies to date have reported incomplete separation of disease groups. In this study, we employed multi-class pattern recognition to assess the value of anatomical patterns derived from a widely available structural neuroimaging sequence for automated classification of these disorders. To achieve this, 17 patients with PSP, 14 with IPD and 19 with MSA were scanned using structural MRI along with 19 healthy controls (HCs). An advanced probabilistic pattern recognition approach was employed to evaluate the diagnostic value of several pre-defined anatomical patterns for discriminating the disorders, including: (i) a subcortical motor network; (ii) each of its component regions and (iii) the whole brain. All disease groups could be discriminated simultaneously with high accuracy using the subcortical motor network. The region providing the most accurate predictions overall was the midbrain/brainstem, which discriminated all disease groups from one another and from HCs. The subcortical network also produced more accurate predictions than the whole brain and all of its constituent regions. PSP was accurately predicted from the midbrain/brainstem, cerebellum and all basal ganglia compartments; MSA from the midbrain/brainstem and cerebellum and IPD from the midbrain/brainstem only. This study demonstrates that automated analysis of structural MRI can accurately predict diagnosis in individual patients with Parkinsonian disorders, and identifies distinct patterns of regional atrophy particularly useful for this process

Cortical thickness across the lifespan: Data from 17,075healthy individuals aged 3–90 years

Delineating the association of age and cortical thickness in healthy individuals is criti-cal given the association of cortical thickness with cognition and behavior. Previousresearch has shown that robust estimates of the association between age and brainmorphometry require large-scale studies. In response, we used cross-sectional datafrom 17,075 individuals aged 3–90 years from the Enhancing Neuroimaging Geneticsthrough Meta-Analysis (ENIGMA) Consortium to infer age-related changes in corticalthickness. We used fractional polynomial (FP) regression to quantify the associationbetween age and cortical thickness, and we computed normalized growth centilesusing the parametric Lambda, Mu, and Sigma method. Interindividual variability wasestimated using meta-analysis and one-way analysis of variance. For most regions,their highest cortical thickness value was observed in childhood. Age and corticalthickness showed a negative association; the slope was steeper up to the thirddecade of life and more gradual thereafter; notable exceptions to this general patternwere entorhinal, temporopolar, and anterior cingulate cortices. Interindividual vari-ability was largest in temporal and frontal regions across the lifespan. Age and its FPcombinations explained up to 59% variance in cortical thickness. These results mayform the basis of further investigation on normative deviation in cortical thicknessand its significance for behavioral and cognitive outcomes.Instituto de Salud Carlos III PI02049

The cortical thickness phenotype of individuals with <i>DISC1</i> translocation resembles schizophrenia

BACKGROUND. The disrupted in schizophrenia 1 (DISC1) gene locus was originally identified in a Scottish pedigree with a high incidence of psychiatric disorders that is associated with a balanced t(1;11)(q42.1;q14.3) chromosomal translocation. Here, we investigated whether members of this family carrying the t(1;11)(q42.1;q14.3) translocation have a common brain-related phenotype and whether this phenotype is similar to that observed in schizophrenia (SCZ), using multivariate pattern recognition techniques. METHODS. We measured cortical thickness, cortical surface area, subcortical volumes, and regional cerebral blood flow (rCBF) in healthy controls (HC) (n = 24), patients diagnosed with SCZ (n = 24), patients diagnosed with bipolar disorder (BP) (n = 19), and members of the original Scottish family (n = 30) who were either carriers (T+) or noncarriers (T–) of the DISC1 translocation. Binary classification models were developed to assess the differences and similarities across groups. RESULTS. Based on cortical thickness, 72% of the T– group were assigned to the HC group, 83% of the T+ group were assigned to the SCZ group, and 45% of the BP group were classified as belonging to the SCZ group, suggesting high specificity of this measurement in predicting brain-related phenotypes. Shared brain-related phenotypes between SCZ and T+ individuals were found for cortical thickness only. Finally, a classification accuracy of 73% was achieved when directly comparing the pattern of cortical thickness of T+ and T– individuals. CONCLUSION. Together, the results of this study suggest that the DISC1 translocation may increase the risk of psychiatric disorders in this pedigree by affecting neurostructural phenotypes such as cortical thickness. FUNDING. This work was supported by the National Health Service Research Scotland, the Scottish Translational Medicine Research Collaboration, the Innovative Medicines Initiative (IMI), the Engineering and Physical Sciences Research Council (EPSRC), The Wellcome Trust, the National Institute of Health Research (NIHR), and Pfizer

Atypical processing of voice sounds in infants at risk for Autism Spectrum Disorder

Adults diagnosed with autism spectrum disorder (ASD) show a reduced sensitivity (degree of selective response) to social stimuli such as human voices. In order to determine whether this reduced sensitivity is a consequence of years of poor social interaction and communication or is present prior to significant experience, we used functional MRI to examine cortical sensitivity to auditory stimuli in infants at high familial risk for later emerging ASD (HR group, N = 15), and compared this to infants with no family history of ASD (LR group, N = 18). The infants (aged between 4 and 7 months) were presented with voice and environmental sounds while asleep in the scanner and their behaviour was also examined in the context of observed parent-infant interaction. Whereas LR infants showed early specialisation for human voice processing in right temporal and medial frontal regions, the HR infants did not. Similarly, LR infants showed stronger sensitivity than HR infants to sad vocalisations in the right fusiform gyrus and left hippocampus. Also, in the HR group only, there was an association between each infant's degree of engagement during social interaction and the degree of voice sensitivity in key cortical regions. These results suggest that at least some infants at high-risk for ASD have atypical neural responses to human voice with and without emotional valence. Further exploration of the relationship between behaviour during social interaction and voice processing may help better understand the mechanisms that lead to different outcomes in at risk populations

Preservation and compensation: The functional neuroanatomy of insight and working memory in schizophrenia

Background: Poor insight in schizophrenia has been theorised to reflect a cognitive deficit that is secondary to brain abnormalities, localized in the brain regions that are implicated in higher order cognitive functions, including working memory (WM). This study investigated WM-related neural substrates of preserved and poor insight in schizophrenia. Method: Forty stable schizophrenia outpatients, 20 with preserved and 20 with poor insight (usable data obtained from 18 preserved and 14 poor insight patients), and 20 healthy participants underwent functional magnetic resonance imaging (fMRI) during a parametric 'n-back' task. The three groups were preselected to match on age, education and predicted IQ, and the two patient groups to have distinct insight levels. Performance and fMRI data were analysed to determine how groups of patients with preserved and poor insight differed from each other, and from healthy participants. Results: Poor insight patients showed lower performance accuracy, relative to healthy participants (p. = 0.01) and preserved insight patients (p. = 0.08); the two patient groups were comparable on symptoms and medication. Preserved insight patients, relative to poor insight patients, showed greater activity most consistently in the precuneus and cerebellum (both bilateral) during WM; they also showed greater activity than healthy participants in the inferior-superior frontal gyrus and cerebellum (bilateral). Group differences in brain activity did not co-vary significantly with performance accuracy. Conclusions: The precuneus and cerebellum function contribute to preserved insight in schizophrenia. Preserved insight as well as normal-range WM capacity in schizophrenia sub-groups may be achieved via compensatory neural activity in the frontal cortex and cerebellum. © 2013 Elsevier B.V.Wellcome Trust, UK; NIHR Birmingham and Black Country CLAHRC, UK; Biomedical Research Centre for Mental Health at the Institute of Psychiatry, King's College London; South London and Maudsley NHS Foundation Trust, UK

A new strategy for enhancing imputation quality of rare variants from next-generation sequencing data via combining SNP and exome chip data

Background: Rare variants have gathered increasing attention as a possible alternative source of missing heritability. Since next generation sequencing technology is not yet cost-effective for large-scale genomic studies, a widely used alternative approach is imputation. However, the imputation approach may be limited by the low accuracy of the imputed rare variants. To improve imputation accuracy of rare variants, various approaches have been suggested, including increasing the sample size of the reference panel, using sequencing data from study-specific samples (i.e., specific populations), and using local reference panels by genotyping or sequencing a subset of study samples. While these approaches mainly utilize reference panels, imputation accuracy of rare variants can also be increased by using exome chips containing rare variants. The exome chip contains 250 K rare variants selected from the discovered variants of about 12,000 sequenced samples. If exome chip data are available for previously genotyped samples, the combined approach using a genotype panel of merged data, including exome chips and SNP chips, should increase the imputation accuracy of rare variants. Results: In this study, we describe a combined imputation which uses both exome chip and SNP chip data simultaneously as a genotype panel. The effectiveness and performance of the combined approach was demonstrated using a reference panel of 848 samples constructed using exome sequencing data from the T2D-GENES consortium and 5,349 sample genotype panels consisting of an exome chip and SNP chip. As a result, the combined approach increased imputation quality up to 11 %, and genomic coverage for rare variants up to 117.7 % (MAF < 1 %), compared to imputation using the SNP chip alone. Also, we investigated the systematic effect of reference panels on imputation quality using five reference panels and three genotype panels. The best performing approach was the combination of the study specific reference panel and the genotype panel of combined data. Conclusions: Our study demonstrates that combined datasets, including SNP chips and exome chips, enhances both the imputation quality and genomic coverage of rare variants

Impaired fear recognition and attentional set-shifting is associated with brain structural changes in alcoholic patients

Alcoholic patients with multiple detoxifications/relapses show cognitive and emotional deficits. We performed structural magnetic resonance imaging and examined performance on a cognitive flexibility task (intra-extradimensional set shift and reversal; IED). We also presented subjects with fearful, disgust and anger facial emotional expressions. Participants were abstaining, multiply detoxified (MDTx; n = 12) or singly detoxified patients (SDTx; n = 17) and social drinker controls (n = 31). Alcoholic patients were less able than controls to change their behavior in accordance with the changing of the rules in the IED and they were less accurate in recognizing fearful expressions in particular. They also showed lower gray matter volume compared with controls in frontal brain areas, including inferior frontal cortex (IFC) and insula that mediate emotional processing, inferior parietal lobule and medial frontal cortex that mediate attentional and motor planning processes, respectively. Impairments in performance and some of the regional decreases in gray matter were greater in MDTx. Gray matter volume in IFC in patients was negatively correlated with the number of detoxifications, whereas inferior parietal lobule was negatively correlated with the control over drinking score (impaired control over drinking questionnaire). Performance in IED was also negatively correlated with gray matter volume in IFC/BA47, whereas recognition of fearful faces was positively correlated with the IFC gray matter. Repeated episodes of detoxification from alcohol, related to severity of dependency, are coupled with altered brain structure in areas of emotional regulation, attention and motor planning. Such changes may confer increased inability to switch behavior according to environmental demands and social incompetence, contributing to relapse

Simultaneous high-resolution T2-weighted imaging and quantitative T2 mapping at low magnetic field strengths using a multiple TE and multi-orientation acquisition approach

Purpose: Low magnetic field systems provide an important opportunity to expand MRI to new and diverse clinical and research study populations. However, a fundamental limitation of low field strength systems is the reduced SNR compared to 1.5 or 3T, necessitating compromises in spatial resolution and imaging time. Most often, images are acquired with anisotropic voxels with low through-plane resolution, which provide acceptable image quality with reasonable scan times, but can impair visualization of subtle pathology. Methods: Here, we describe a super-resolution approach to reconstruct high-resolution isotropic T2-weighted images from a series of low-resolution anisotropic images acquired in orthogonal orientations. Furthermore, acquiring each image with an incremented TE allows calculations of quantitative T2 images without time penalty. Results: Our approach is demonstrated via phantom and in vivo human brain imaging, with simultaneous 1.5 × 1.5 × 1.5 mm3 T2-weighted and quantitative T2 maps acquired using a clinically feasible approach that combines three acquisition that require approximately 4-min each to collect. Calculated T2 values agree with reference multiple TE measures with intraclass correlation values of 0.96 and 0.85 in phantom and in vivo measures, respectively, in line with previously reported brain T2 values at 150 mT, 1.5T, and 3T. Conclusion: Our multi-orientation and multi-TE approach is a time-efficient method for high-resolution T2-weighted images for anatomical visualization with simultaneous quantitative T2 imaging for increased sensitivity to tissue microstructure and chemical composition