M Novak

Huntington’s disease

#### Summary points Huntington’s disease is a devastating inherited neurodegenerative disease characterised by progressive motor, cognitive, and psychiatric symptoms. Patients may present with any of these symptoms, and familiarity with the phenotype is therefore important. Chorea and loss of balance are early symptoms that patients notice, although families often notice cognitive or personality changes before this. #### Sources and selection criteria This review is based on our experience of leading (SJT) and working in (MJUN) the multidisciplinary Huntington’s disease clinic at the National Hospital for Neurology and Neurosurgery, supported by an up to date literature review performed using PubMed and a review of the Cochrane database. The disease occurs in all racial groups but is most common in people of northern European origin. Its prevalence in the Western hemisphere is 7-10/100 000.w1 The mean age of onset of symptoms is 40 years, but juvenile onset ( 70 years) forms are well recognised. The Huntington’s Disease Association (HDA) has records of 6161 adults with symptomatic Huntington’s disease and 541 children with juvenile Huntington’s disease (in England and Wales) at the time of writing. This is a conservative estimate of prevalence because it includes only those people in contact with the HDA, and it suggests that the true prevalence of the disease is higher than previously thought.1 Although relatively uncommon, Huntington’s disease can be devastating for patients and their families. People who are at risk of developing the disease because of a family history face difficult decisions about genetic testing. We review …

Unified segmentation based correction of R1 brain maps for RF transmit field inhomogeneities (UNICORT)

Quantitative mapping of the longitudinal relaxation rate (R1 = 1/T1) in the human brain enables the investigation of tissue microstructure and macroscopic morphology which are becoming increasingly important for clinical and neuroimaging applications. R1 maps are now commonly estimated from two fast high-resolution 3D FLASH acquisitions with variable excitation flip angles, because this approach is fast and does not rely on special acquisition techniques. However, these R1 maps need to be corrected for bias due to RF transmit field (B1+) inhomogeneities, requiring additional B1+ mapping which is usually time consuming and difficult to implement. We propose a technique that simultaneously estimates the B1+ inhomogeneities and R1 values from the uncorrected R1 maps in the human brain without need for B1+ mapping. It employs a probabilistic framework for unified segmentation based correction of R1 maps for B1+ inhomogeneities (UNICORT). The framework incorporates a physically informed generative model of smooth B1+ inhomogeneities and their multiplicative effect on R1 estimates. Extensive cross-validation with the established standard using measured B1+ maps shows that UNICORT yields accurate B1+ and R1 maps with a mean deviation from the standard of less than 4.3% and 5%, respectively. The results of different groups of subjects with a wide age range and different levels of atypical brain anatomy further suggest that the method is robust and generalizes well to wider populations. UNICORT is easy to apply, as it is computationally efficient and its basic framework is implemented as part of the tissue segmentation in SPM8.

Altered brain mechanisms of emotion processing in pre-manifest Huntington's disease

Huntingtons disease is an inherited neurodegenerative disease that causes motor, cognitive and psychiatric impairment, including an early decline in ability to recognize emotional states in others. The pathophysiology underlying the earliest manifestations of the disease is not fully understood; the objective of our study was to clarify this. We used functional magnetic resonance imaging to investigate changes in brain mechanisms of emotion recognition in pre-manifest carriers of the abnormal Huntingtons disease gene (subjects with pre-manifest Huntingtons disease): 16 subjects with pre-manifest Huntingtons disease and 14 control subjects underwent 1.5 tesla magnetic resonance scanning while viewing pictures of facial expressions from the Ekman and Friesen series. Disgust, anger and happiness were chosen as emotions of interest. Disgust is the emotion in which recognition deficits have most commonly been detected in Huntingtons disease; anger is the emotion in which impaired recognition was detected in the largest behavioural study of emotion recognition in pre-manifest Huntingtons disease to date; and happiness is a positive emotion to contrast with disgust and anger. Ekman facial expressions were also used to quantify emotion recognition accuracy outside the scanner and structural magnetic resonance imaging with voxel-based morphometry was used to assess the relationship between emotion recognition accuracy and regional grey matter volume. Emotion processing in pre-manifest Huntingtons disease was associated with reduced neural activity for all three emotions in partially separable functional networks. Furthermore, the Huntingtons disease-associated modulation of disgust and happiness processing was negatively correlated with genetic markers of pre-manifest disease progression in distributed, largely extrastriatal networks. The modulated disgust network included insulae, cingulate cortices, pre- and postcentral gyri, precunei, cunei, bilateral putamena, right pallidum, right thalamus, cerebellum, middle frontal, middle occipital, right superior and left inferior temporal gyri, and left superior parietal lobule. The modulated happiness network included postcentral gyri, left caudate, right cingulate cortex, right superior and inferior parietal lobules, and right superior frontal, middle temporal, middle occipital and precentral gyri. These effects were not driven merely by striatal dysfunction. We did not find equivalent associations between brain structure and emotion recognition, and the pre-manifest Huntingtons disease cohort did not have a behavioural deficit in out-of-scanner emotion recognition relative to controls. In addition, we found increased neural activity in the pre-manifest subjects in response to all three emotions in frontal regions, predominantly in the middle frontal gyri. Overall, these findings suggest that pathophysiological effects of Huntingtons disease may precede the development of overt clinical symptoms and detectable cerebral atrophy.

Emotion recognition in Huntington's disease: A systematic review

There is increasing interest in the nature of the emotion recognition deficit in Huntingtons disease (HD). There are conflicting reports of disproportionate impairments for some emotions in some modalities in HD. A systematic review and narrative synthesis was conducted for studies investigating emotion recognition in HD. Embase, MEDLINE, PsychINFO and Pubmed were searched from 1993 to 2010, and citations and reference lists were searched. 1724 citations were identified. Sixteen studies were included. In manifest HD evidence of impaired recognition of facial expressions of anger was found consistently, although recognition of all negative emotions (facial and vocal) tended to be impaired. In premanifest HD impairments were inconsistent, but are seen in all facial expressions of negative emotion. Inconsistency may represent the variability inherent in HD although may also be due to between-study differences in methodology. Current evidence supports the conclusion that recognition of all negative emotions tends to be impaired in HD, particularly in the facial domain. Future work should focus on using more ecologically-valid tests, and testing inter-modality differences.

Huntington's Disease: Clinical Presentation and Treatment

Huntingtons disease (HD) is a devastating inherited neurodegenerative disease characterized primarily by progressive motor, cognitive, and psychiatric symptoms. It is caused by autosomal dominant inheritance of an expanded CAG repeat within the Huntingtons gene on chromosome 4. In this chapter, we characterize the typical and variant motor phenotypes of the disease and then proceed to describe the cognitive and psychiatric profile. We then give an overview of a suggested multidisciplinary approach to the management of HD, emphasizing the fact that it is a disease which impacts on entire families rather than affecting individuals in isolation. We then describe the pharmacological and nonpharmacological options available for management of specific symptoms.

An ITPR1 gene deletion causes spinocerebellar ataxia 15/16: a genetic, clinical and radiological description.

the purpose of this study was to characterise a novel family with very slowly progressive pure spinocerebellar ataxia (SCA) caused by a deletion in the inositol 1,4,5‐triphosphate receptor 1 (ITPR1) gene on chromosome 3. This is a detailed clinical, genetic, and radiological description of the genotype. Deletions in ITPR1 have been shown to cause SCA15/SCA16 in six families to date. A further Japanese family has been identified with an ITPR1 point mutation. The exact prevalence is as yet unknown, but is probably higher than previously thought. The clinical phenotype of the family is described, and videotaped clinical examinations are presented. Serial brain magnetic resonance imaging studies were carried out on one affected individual, and genetic analysis was performed on several family members. Protein analysis confirmed the ITPR1 deletion. Affected subjects display a remarkably slow, almost pure cerebellar syndrome. Serial magnetic resonance imaging shows moderate cerebellar atrophy with mild inferior parietal and temporal cortical volume loss. Genetic analysis shows a deletion of 346,487 bp in ITPR1 (the second largest ITPR1 deletion reported to date), suggesting SCA15 is due to a loss of ITPR1 function. Western blotting of lymphoblastoid cell line protein confirms reduced ITPR1 protein levels. SCA15 is a slowly or nonprogressive pure cerebellar ataxia, which appears to be caused by a loss of ITPR1 function and a reduction in the translated protein. Patients with nonprogressive or slowly progressive ataxia should be screened for ITPR1 defects.

Basal Ganglia-Cortical Structural Connectivity in Huntington's Disease

Huntingtons disease is an incurable neurodegenerative disease caused by inheritance of an expanded cytosine‐adenine‐guanine (CAG) trinucleotide repeat within the Huntingtin gene. Extensive volume loss and altered diffusion metrics in the basal ganglia, cortex and white matter are seen when patients with Huntingtons disease (HD) undergo structural imaging, suggesting that changes in basal ganglia‐cortical structural connectivity occur. The aims of this study were to characterise altered patterns of basal ganglia‐cortical structural connectivity with high anatomical precision in premanifest and early manifest HD, and to identify associations between structural connectivity and genetic or clinical markers of HD. 3‐Tesla diffusion tensor magnetic resonance images were acquired from 14 early manifest HD subjects, 17 premanifest HD subjects and 18 controls. Voxel‐based analyses of probabilistic tractography were used to quantify basal ganglia‐cortical structural connections. Canonical variate analysis was used to demonstrate disease‐associated patterns of altered connectivity and to test for associations between connectivity and genetic and clinical markers of HD; this is the first study in which such analyses have been used. Widespread changes were seen in basal ganglia‐cortical structural connectivity in early manifest HD subjects; this has relevance for development of therapies targeting the striatum. Premanifest HD subjects had a pattern of connectivity more similar to that of controls, suggesting progressive change in connections over time. Associations between structural connectivity patterns and motor and cognitive markers of disease severity were present in early manifest subjects. Our data suggest the clinical phenotype in manifest HD may be at least partly a result of altered connectivity. Hum Brain Mapp 36:1728–1740, 2015.

Stability of white matter changes related to Huntington's disease in the presence of imaging noise: a DTI study

Movement artifacts and other sources of noise are a matter of concern particularly in the neuroimaging research of movement disorders such as Huntington’s disease (HD). Using diffusion weighted imaging (DWI) and fractional anisotropy (FA) as a compound marker of white matter integrity, we investigated the effect of movement on HD specific changes in magnetic resonance imaging (MRI) data and how post hoc compensation for it affects the MRI results. To this end, we studied by 3T MRI: 18 early affected, 22 premanifest gene-positive subjects, 23 healthy controls (50 slices of 2.3 mm thickness per volume, 64 diffusion-weighted directions (b = 1000 s/mm2), 8 minimal diffusion-weighting (b = 100 s/mm2)); and by 1.5 T imaging: 29 premanifest HD, 30 controls (40 axial slices of 2.3 mm thickness per volume, 61 diffusion-weighted directions (b = 1000 s/mm2), minimal diffusion-weighting (b = 100 s/mm2)). An outlier based method was developed to identify movement and other sources of noise by comparing the index DWI direction against a weighted average computed from all other directions of the same subject. No significant differences were observed when separately comparing each group of patients with and without removal of DWI volumes that contained artifacts. In line with previous DWI-based studies, decreased FA in the corpus callosum and increased FA around the basal ganglia were observed when premanifest mutation carriers and early affected patients were compared with healthy controls. These findings demonstrate the robustness of the FA value in the presence of movement and thus encourage multi-center imaging studies in HD.

ITPR1 GENE DELETION CAUSES SPINOCEREBELLAR ATAXIA 15/16: A GENETIC, CLINICAL AND RADIOLOGICAL DESCRIPTION OF A NOVEL KINDRED

An ITPR1 gene deletion causes spinocerebellar ataxia 15/16: a genetic, clinical and radiological description of a novel kindred. Spinocerebellar ataxia (SCA) 15/16 is an autosomal dominantly inherited, almost pure cerebellar ataxia, which shows slow or no progression. (It has been designated variably SCA15 and SCA 16; we refer to it here as SCA15/16 to avoid confusion). Deletions in the inositol 1,4,5-triphosphate receptor 1 (ITPR1) on chromosome 3 have been shown to cause SCA15/16 in six families worldwide to date, with one further Japanese family identified as having an ITPR1 point mutation. We present a previously unreported SCA15/16 kindred. We describe the clinical phenotype of the family in detail; affected subjects display a remarkably slow, almost pure cerebellar syndrome. We also present genetic analyses for all subjects and longitudinal MRI data for one affected subject. Genetic analysis shows a deletion of 346 487 bp in ITPR1 (the second largest ITPR1 deletion reported to date), suggesting SCA15 is due to a loss of ITPR1 function, and western blotting of lymphoblastoid cell line protein confirms reduced ITPR1 protein levels. Serial MRIs show midline cerebellar atrophy with mild inferior parietal and temporal cortical volume loss. We believe that genetic testing for SCA15/16 should become a routine DNA screen available in all neurogenetics clinics, which is likely to lead to an increased rate of the diagnosis. Familiarity with the phenotype is therefore important for all neurologists.

fMRI Data Analysis Using SPM

Statistical parametric mapping (SPM) is an established statistical data analysis framework through which regionally specific effects in structural and functional neuroimaging data can be characterised. SPM is also the name of a free and open source academic software package through which this framework (amongst other things) can be implemented. In summary, SPM analyses contain three key components: data are (a) spatially transformed to bring them into a common space; (b) described in terms of experimental effects, confounding effects and residual variability using a general linear model; and (c) subject to statistical inference using random field theory. In this chapter, we will give an overview of the underlying concepts of the SPM framework and will illustrate these by describing how to analyse a typical block-design functional MRI (fMRI) data set using the SPM software.