Giulia Silvestri

Mitochondrial neurogastrointestinal encephalomyopathy (MNGIE) Clinical, biochemical, and genetic features of an autosomal recessive mitochondrial disorder

We studied the clinical, biochemical, and genetic features of eight patients with the autosomal recessive mitochondrial syndrome mitochondrial neurogastrointestinal encephalomyopathy (MNGIE). MNGIE is clinically characterized by ophthalmoparesis, peripheral neuropathy, leukoencephalopathy, gastrointestinal symptoms (recurrent nausea, vomiting, or diarrhea) with intestinal dysmotility, and histologically abnormal mitochondria in muscle. Brain MRI scans were consistent with leukodystrophy in seven patients examined. Nerve conduction and EMG studies were compatible with a sensorimotor neuropathy; quantitative EMG of two patients suggested a myogenic process. Muscle mitochondrial enzyme analysis revealed a partial defect of cytochrome c oxidase activity in five patients; three had additional respiratory chain enzyme defects. Two patients had isolated complex I defects, and one had normal respiratory chain function. Southern blot analysis revealed multiple deletions of mitochondrial DNA in four of eight patients.

Clinical features associated with the A → G transition at nucleotide 8344 of mtDNA (“MERRF mutation”)

We looked for the A → G transition at position 8344 of mtDNA in 150 patients, most of them with diagnosed or suspected mitochondrial disease, to assess the specificity of this mutation for the MERRF phenotype, to define the clinical spectrum associated with the mutation, and to study the relationship between percentage of mutation in muscle and clinical severity. Our results confirm the high correlation between the A → G transition at position 8344 and the MERRF syndrome, but they also show that this mutation can be associated with other phenotypes, including Leighs syndrome, myoclonus or myopathy with truncal lipomas, and proximal myopathy. The absence of the mutation in four typical MERRF patients suggests that other mutations in the tRNALys gene, or elsewhere in the mitochondrial DNA, can produce the same phenotype.

Impaired sequence learning in carriers of the DYT1 dystonia mutation

Previous positron emission tomography (PET) studies have shown that nonmanifesting carriers of the DYT1 dystonia mutation express an abnormal pattern of resting glucose metabolism. To determine whether motor behavior is impaired in these subjects, we compared movement and sequence learning in 12 clinically unaffected DYT1 carriers with 12 age‐matched controls. Regional differences in brain function during task performance were assessed with simultaneous H215O/PET. We found that motor performance was similar in the DYT1 and control groups, with no significant differences in movement time and spatial accuracy measured during each of the tasks. In contrast, sequence learning was reduced in gene carriers relative to controls (p < 0.01). PET imaging during motor execution showed increased activation in gene carriers (p < 0.001, uncorrected) in the left premotor cortex and right supplementary motor area, with concomitant reduction in the posterior medial cerebellum. During sequence learning, activation responses in DYT1 carriers were increased in the left ventral prefrontal cortex, and lateral cerebellum. These findings suggest that abnormalities in motor behavior and brain function exist in clinically nonmanifesting DYT1 carriers. Although localized increases in neural activity may enable normal movement execution in these subjects, this mechanism may not compensate for their defect in sequence learning. Ann Neurol 2003;54:102–109

Widespread tissue distribution of a tRNALeu(UUR) mutation in the mitochondrial DNA of a patient with MELAS syndrome

We documented the presence of a newly described point mutation in the tRNALeu(UUR) gene of mitochondrial DNA in five postmortem tissues from a patient with MELAS syndrome. The mutation was heteroplasmic, but the percentage of mutant genomes was similar (79 to 88%) in both clinically affected and unaffected tissues.

The differential effect of PD and normal aging on early explicit sequence learning

Background: Motor sequence learning is abnormal in PD. However, it is not known whether this defect is present during the earliest stages of the illness or whether it reflects specific limitations in dividing attention between cognitive and motor requirements. Methods: Fifteen patients with early stage PD and 10 age-matched and 9 younger normal controls moved the right dominant hand on a digitizing tablet to eight targets presented on a screen in synchrony with a tone at 1-second intervals. The tasks were as follows: 1) CCW—a timed-response task where targets appeared in a predictable counterclockwise order; 2) RAN—a reaction time task where targets were random and unpredictable; 3) SEQ—a task with multiple demands emphasizing explicit learning and target anticipation in which subjects learned a sequence while reaching for targets; and 4) VSEQ—subjects learned a visual sequence without moving. Results: CCW and RAN yielded similar results in all groups. In patients with PD, sequence learning was the same in SEQ and VSEQ and was slower compared to both control groups. In older controls, learning was faster in VSEQ than in SEQ, whereas younger controls learned equally fast in both tasks. Conclusions: Despite normal motor execution, the initial phases of sequence learning are impaired in early PD independent of task requirements, possibly reflecting reduced working memory. Learning was slower in older than younger controls only in tasks with multiple demands, presumably due to reduced attentional resources.

Learning of a Sequential Motor Skill Comprises Explicit and Implicit Components That Consolidate Differently

The ability to perform accurate sequential movements is essential to normal motor function. Learning a sequential motor behavior is comprised of two basic components: explicit identification of the order in which the sequence elements should be performed and implicit acquisition of spatial accuracy for each element. Here we investigated the time course of learning of these components for a first sequence (SEQA) and their susceptibility to interference from learning a second sequence (SEQB). We assessed explicit learning with a discrete index, the number of correct anticipatory movements, and implicit learning with a continuous variable, spatial error, which decreased during learning without subject awareness. Spatial accuracy to individual sequence elements reached asymptotic levels only when the whole sequence order was known. Interference with recall of the order of SEQA persisted even when SEQB was learned 24 h after SEQA. However, there was resistance to interference by SEQB with increased initial training with SEQA. For implicit learning of spatial accuracy, SEQB interfered at 5 min but not 24 h after SEQA. As in the case of sequence order, prolonged initial training with SEQA induced resistance to interference by SEQB. We conclude that explicit sequence learning is more susceptible to anterograde interference and implicit sequence learning is more susceptible to retrograde interference. However, both become resistant to interference with saturation training. We propose that an essential feature of motor skill learning is the process by which discrete explicit task elements are combined with continuous implicit features of movement to form flawless sequential actions.

Learning networks in health and Parkinson's disease: Reproducibility and treatment effects

In a previous H215O/PET study of motor sequence learning, we used principal components analysis (PCA) of region of interest (ROI) data to identify performance‐related activation patterns in normal subjects and patients with Parkinsons disease (PD). In the present study, we determined whether these patterns predicted learning performance in subsequent normal and untreated PD cohorts. Using a voxel‐based PCA approach, we correlated the changes in network activity that occurred during antiparkinsonian treatment and their relationship to learning performance. We found that the previously identified ROI‐based patterns correlated with learning performance in the prospective normal (P < 0.01) and untreated PD (P < 0.05) cohorts. Voxel analysis revealed that target retrieval was related to a network characterized by bilateral activation of the dorsolateral prefrontal, premotor and anterior cingulate cortex, the precuneus, and the occipital association areas as well as the right ventral prefrontal and inferior parietal regions. Target acquisition was associated with a different network involving activation of the caudate, putamen, and right dentate nucleus, as well as the left ventral prefrontal and inferior parietal areas. Antiparkinsonian therapy gave rise to changes in retrieval performance that correlated with network modulation (P < 0.01). Increases in network activation and learning performance occurred with internal pallidal deep brain stimulation (GPi DBS); decrements in these measures were present with levodopa. Our findings suggest that network analysis of activation data can provide stable descriptors of learning performance. Network quantification can provide an objective means of assessing the effects of therapy on cognitive functioning in neurodegenerative disorders. Hum. Brain Mapping 11:197–211, 2003.

Implicit and explicit aspects of sequence learning in pre-symptomatic Huntington's disease

Learning deficits may be part of the early symptoms of Huntingtons disease (HD). Here we characterized implicit and explicit aspects of sequence learning in 11 pre-symptomatic HD gene carriers (pHD) and 11 normal controls. Subjects moved a cursor on a digitizing tablet and performed the following tasks: SEQ: learning to anticipate the appearance of a target sequence in two blocks; VSEQ: learning a sequence by attending to the display without moving for one block, and by moving to the sequence in a successive block (VSEQ test). Explicit learning was measured with declarative scores and number of anticipatory movements. Implicit learning was measured as a strategy change reflected in movement time. By the end of SEQ, pHD had a significantly lower number of correct anticipatory movements and lower declarative scores than controls, while in VSEQ and VSEQ test these indices improved. During all three tasks, movement time changed in controls, but not in pHD. These results suggest that both explicit and implicit aspects of sequence learning may be impaired before the onset of motor symptoms. However, when attentional demands decrease, explicit, but not implicit, learning may improve.