Applying the Huntington’s Disease Integrated Staging System (HD-ISS) to Observational Studies

Background: The Huntington’s Disease Integrated Staging System (HD-ISS) has four stages that characterize disease progression. Classification is based on CAG length as a marker of Huntington’s disease (Stage 0), striatum atrophy as a biomarker of pathogenesis (Stage 1), motor or cognitive deficits as HD signs and symptoms (Stage 2), and functional decline (Stage 3). One issue for implementation is the possibility that not all variables are measured in every study, and another issue is that the stages are broad and may benefit from progression subgrouping./ Objective: Impute stages of the HD-ISS for observational studies in which missing data precludes direct stage classification, and then define progression subgroups within stages./ Methods: A machine learning algorithm was used to impute stages. Agreement of the imputed stages with the observed stages was evaluated using graphical methods and propensity score matching. Subgroups were defined based on descriptive statistics and optimal cut-point analysis./ Results: There was good overall agreement between the observed stages and the imputed stages, but the algorithm tended to over-assign Stage 0 and under-assign Stage 1 for individuals who were early in progression./ Conclusion: There is evidence that the imputed stages can be treated similarly to the observed stages for large-scale analyses. When imaging data are not available, imputation can be avoided by collapsing the first two stages using the categories of Stage≤1, Stage 2, and Stage 3. Progression subgroups defined within a stage can help to identify groups of more homogeneous individuals.

Dynamic Functional Connectivity Analysis Reveals Transient States of Dysconnectivity in Schizophrenia

Schizophrenia is a psychotic disorder characterized by functional dysconnectivity or abnormal integration between distant brain regions. Recent functional imaging studies have implicated large-scale thalamo-cortical connectivity as being disrupted in patients.However, observed connectivity differences in schizophrenia have been inconsistent between studies,with reports of hyperconnectivity and hypoconnectivity between the same brain regions. Using resting state eyes-closed functional imaging and independent component analysis on amulti-site data that included 151 schizophrenia patients and 163 age- and gender matched healthy controls, we decomposed the functional brain data into 100 components and identified 47 as functionally relevant intrinsic connectivity networks. We subsequently evaluated group differences in functional network connectivity, both in a static sense, computed as the pairwise Pearson correlations between the full network time courses (5.4 minutes in length), and a dynamic sense, computed using slidingwindows (44 s in length) and k-means clustering to characterize five discrete functional connectivity states. Static connectivity analysis revealed that compared to healthy controls, patients show significantly stronger connectivity, i.e., hyperconnectivity, between the thalamus and sensory networks (auditory, motor and visual), as well as reduced connectivity (hypoconnectivity) between sensory networks from all modalities. Dynamic analysis suggests that (1), on average, schizophrenia patients spendmuch less time than healthy controls in states typified by strong, large-scale connectivity, and (2), that abnormal connectivity patterns are more pronounced during these connectivity states. In particular, states exhibiting cortical–subcortical antagonism (anticorrelations) and strong positive connectivity between sensory networks are those that showthe group differences of thalamic hyperconnectivity and sensory hypoconnectivity. Group differences are weak or absent during other connectivity states. Dynamic analysis also revealed hypoconnectivity between the putamen and sensory networks during the same states of thalamic hyperconnectivity; notably, this finding cannot be observed in the static connectivity analysis. Finally, in post-hoc analyses we observed that the relationships between sub-cortical low frequency power and connectivitywith sensory networks is altered in patients, suggesting different functional interactions between sub-cortical nuclei and sensorimotor cortex during specific connectivity states. While important differences between patients with schizophrenia and healthy controls have been identified, one should interpret the results with caution given the history of medication in patients. Taken together, our results support and expand current knowledge regarding dysconnectivity in schizophrenia, and strongly advocate the use of dynamic analyses to better account for and understand functional connectivity differences

Neuropsychological profile in adult schizophrenia measured with the CMINDS

Schizophrenia neurocognitive domain profiles are predominantly based on paper-and-pencil batteries. This study presents the first schizophrenia domain profile based on the Computerized Multiphasic Interactive Neurocognitive System (CMINDS®). Neurocognitive domain z-scores were computed from computerized neuropsychological tests, similar to those in the Measurement and Treatment Research to Improve Cognition in Schizophrenia Consensus Cognitive Battery (MCCB), administered to 175 patients with schizophrenia and 169 demographically similar healthy volunteers. The schizophrenia domain profile order by effect size was Speed of Processing (d=−1.14), Attention/Vigilance (d=−1.04), Working Memory (d=−1.03), Verbal Learning (d=−1.02), Visual Learning (d=−0.91), and Reasoning/Problem Solving (d=−0.67). There were no significant group by sex interactions, but overall women, compared to men, showed advantages on Attention/Vigilance, Verbal Learning, and Visual Learning compared to Reasoning/Problem Solving on which men showed an advantage over women. The CMINDS can readily be employed in the assessment of cognitive deficits in neuropsychiatric disorders; particularly in large-scale studies that may benefit most from electronic data capture

Relating Intrinsic Low-Frequency BOLD Cortical Oscillations to Cognition in Schizophrenia

The amplitude of low-frequency fluctuations (ALFF) in the blood oxygenation level-dependent (BOLD) signal during resting-state fMRI reflects the magnitude of local low-frequency BOLD oscillations, rather than interregional connectivity. ALFF is of interest to studies of cognition because fluctuations in spontaneous intrinsic brain activity relate to, and possibly even constrain, task-evoked brain responses in healthy people. Lower ALFF has been reported in schizophrenia, but the cognitive correlates of these reductions remain unknown. Here, we assess relationships between ALFF and attention and working memory in order to establish the functional relevance of intrinsic BOLD oscillatory power alterations with respect to specific cognitive impairments in schizophrenia. As part of the multisite FBIRN study, resting-state fMRI data were collected from schizophrenia subjects (SZ; n=168) and healthy controls (HC; n=166). Voxelwise fractional ALFF (fALFF), a normalized ALFF measure, was regressed on neuropsychological measures of sustained attention and working memory in SZ and HC to identify regions showing either common slopes across groups or slope differences between groups (all findings p<0.01 height, p<0.05 family-wise error cluster corrected). Poorer sustained attention was associated with smaller fALFF in the left superior frontal cortex and bilateral temporoparietal junction in both groups, with additional relationships in bilateral posterior parietal, posterior cingulate, dorsal anterior cingulate (ACC), and right dorsolateral prefrontal cortex (DLPFC) evident only in SZ. Poorer working memory was associated with smaller fALFF in bilateral ACC/mPFC, DLPFC, and posterior parietal cortex in both groups. Our findings indicate that smaller amplitudes of low-frequency BOLD oscillations during rest, measured by fALFF, were significantly associated with poorer cognitive performance, sometimes similarly in both groups and sometimes only in SZ, in regions known to subserve sustained attention and working memory. Taken together, these data suggest that the magnitude of resting-state BOLD oscillations shows promise as a biomarker of cognitive function in health and disease

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals &lt;1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

Recognition of emotion from body language among patients with unipolar depression

Major depression may be associated with abnormal perception of emotions and impairment in social adaptation. Emotion recognition from body language and its possible implications to social adjustment have not been examined in patients with depression. Three groups of participants (51 with depression; 68 with history of depression in remission; and 69 never depressed healthy volunteers) were compared on static and dynamic tasks of emotion recognition from body language. Psychosocial adjustment was assessed using the Social Adjustment Scale Self-Report (SAS-SR). Participants with current depression showed reduced recognition accuracy for happy stimuli across tasks relative to remission and comparison participants. Participants with depression tended to show poorer psychosocial adaptation relative to remission and comparison groups. Correlations between perception accuracy of happiness and scores on the SAS-SR were largely not significant. These results indicate that depression is associated with reduced ability to appraise positive stimuli of emotional body language but emotion recognition performance is not tied to social adjustment. These alterations do not appear to be present in participants in remission suggesting state-like qualities

Aging and Alexithymia: Association With Reduced Right Rostral Cingulate Volume

Piazzetta Giovanni Labus, 3 Brescia, Italyfull view, ruins incorporated into modern building

Regions demonstrating significant activity for absolute anticipation.

<p>Note. Negative peak t-values indicate areas that showed greater activation to failure to obtain rewards. VS = ventral striatum; M = mesial.</p