Conduction aphasia is a language disorder characterized by frequent speech errors, impaired verbatim repetition, a deficit in phonological short-term memory, and naming difficulties in the presence ...of otherwise fluent and grammatical speech output. While traditional models of conduction aphasia have typically implicated white matter pathways, recent advances in lesions reconstruction methodology applied to groups of patients have implicated left temporoparietal zones. Parallel work using functional magnetic resonance imaging (fMRI) has pinpointed a region in the posterior most portion of the left planum temporale, area Spt, which is critical for phonological working memory. Here we show that the region of maximal lesion overlap in a sample of 14 patients with conduction aphasia perfectly circumscribes area Spt, as defined in an aggregate fMRI analysis of 105 subjects performing a phonological working memory task. We provide a review of the evidence supporting the idea that Spt is an interface site for the integration of sensory and vocal tract-related motor representations of complex sound sequences, such as speech and music and show how the symptoms of conduction aphasia can be explained by damage to this system.
Since the early 1990s it has been postulated that hypofunction of N -methyl- d -aspartate (NMDA) receptors in brain networks supporting perception and cognition underlies schizophrenic psychosis. ...Recently, NMDA receptor hypofunction was described in patients with psychotic manifestations who exhibited autoantibodies binding the GluN1 subunit of the receptor, and who improved when the level of these antibodies was lowered by immunomodulation. In this disorder, NMDA receptor antibodies decrease the availability of NMDA receptors by internalizing them. In this opinion article, we review this mechanism as well as data supporting or refuting the possibility that this disorder or similar autoimmune disorders affecting synaptic proteins, which are therefore treatable with immunomodulation, could account for some cases of idiopathic psychosis. We also suggest methodological approaches to clarify this issue.
A data-driven hypothesis-free genome-wide association (GWA) approach in imaging genetics studies allows screening the entire genome to discover novel genes that modulate brain structure, chemistry, ...and function. However, a whole brain voxel-wise analysis approach in such genome-wide based imaging genetic studies can be computationally intense and also likely has low statistical power since a stringent multiple comparisons correction is needed for searching over the entire genome and brain. In imaging genetics with functional magnetic resonance imaging (fMRI) phenotypes, since many experimental paradigms activate focal regions that can be pre-specified based on a priori knowledge, reducing the voxel-wise search to single-value summary measures within a priori ROIs could prove efficient and promising. The goal of this investigation is to evaluate the sensitivity and reliability of different single-value ROI summary measures and provide guidance in future work. Four different fMRI databases were tested and comparisons across different groups (patients with schizophrenia, their siblings, vs. normal control subjects; across genotype groups) were conducted. Our results show that four of these measures, particularly those that represent values from the top most-activated voxels within an ROI are more powerful at reliably detecting group differences and generating greater effect sizes than the others.
See Calafato and Bramon (doi:10.1093/brain/awy345) for a scientific commentary on this article.
Cognitive deficits accompany schizophrenia and are associated with genetic risk but the direction of ...causality is unclear. Using causal modelling, Toulopoulou et al. show that cognitive deficits partially mediate the effects of cumulative genetic risk for schizophrenia. Impaired cognition is an intermediate phenotype on the causal path to the disorder with implications for diagnosis and intervention.
Abstract
Cognitive deficit is thought to represent, at least in part, genetic mechanisms of risk for schizophrenia, with recent evidence from statistical modelling of twin data suggesting direct causality from the former to the latter. However, earlier evidence was based on inferences from twin not molecular genetic data and it is unclear how much genetic influence 'passes through' cognition on the way to diagnosis. Thus, we included direct measurements of genetic risk (e.g. schizophrenia polygenic risk scores) in causation models to assess the extent to which cognitive deficit mediates some of the effect of polygenic risk scores on the disorder. Causal models of family data tested relationships among key variables and allowed parsing of genetic variance components. Polygenic risk scores were calculated from summary statistics from the current largest genome-wide association study of schizophrenia and were represented as a latent trait. Cognition was also modelled as a latent trait. Participants were 1313 members of 1078 families: 416 patients with schizophrenia, 290 unaffected siblings, and 607 controls. Modelling supported earlier findings that cognitive deficit has a putatively causal role in schizophrenia. In total, polygenic risk score explained 8.07% confidence interval (CI) 5.45-10.74% of schizophrenia risk in our sample. Of this, more than a third (2.71%, CI 2.41-3.85%) of the polygenic risk score influence was mediated through cognition paths, exceeding the direct influence of polygenic risk score on schizophrenia risk (1.43%, CI 0.46-3.08%). The remainder of the polygenic risk score influence (3.93%, CI 2.37-4.48%) reflected reciprocal causation between schizophrenia liability and cognition (e.g. mutual influences in a cyclical manner). Analysis of genetic variance components of schizophrenia liability indicated that 26.87% (CI 21.45-32.57%) was associated with cognition-related pathways not captured by polygenic risk score. The remaining variance in schizophrenia was through pathways other than cognition-related and polygenic risk score. Although our results are based on inference through statistical modelling and do not provide an absolute proof of causality, we find that cognition pathways mediate a significant part of the influence of cumulative genetic risk on schizophrenia. We estimate from our model that 33.51% (CI 27.34-43.82%) of overall genetic risk is mediated through influences on cognition, but this requires further studies and analyses as the genetics of schizophrenia becomes better characterized.
Different cognitive development histories in schizophrenia may reflect variation across dimensions of genetic influence. The authors derived and characterized cognitive development trajectory ...subgroups within a schizophrenia sample and profiled the subgroups across polygenic scores (PGSs) for schizophrenia, cognition, educational attainment, and attention deficit hyperactivity disorder (ADHD).
Demographic, clinical, and genetic data were collected at the National Institute of Mental Health from 540 schizophrenia patients, 247 unaffected siblings, and 844 control subjects. Cognitive trajectory subgroups were derived through cluster analysis using estimates of premorbid and current IQ. PGSs were generated using standard methods. Associations were tested using general linear models and logistic regression.
Cluster analyses identified three cognitive trajectory subgroups in the schizophrenia group: preadolescent cognitive impairment (19%), adolescent disruption of cognitive development (44%), and cognitively stable adolescent development (37%). Together, the four PGSs significantly predicted 7.9% of the variance in subgroup membership. Subgroup characteristics converged with genetic patterns. Cognitively stable individuals had the best adult clinical outcomes and differed from control subjects only in schizophrenia PGSs. Those with adolescent disruption of cognitive development showed the most severe symptoms after diagnosis and were cognitively impaired. This subgroup had the highest schizophrenia PGSs and had disadvantageous cognitive PGSs relative to control subjects and cognitively stable individuals. Individuals showing preadolescent impairment in cognitive and academic performance and poor adult outcome exhibited a generalized PGS disadvantage relative to control subjects and were the only subgroup to differ significantly in education and ADHD PGSs.
Subgroups derived from patterns of premorbid and current IQ showed different premorbid and clinical characteristics, which converged with broad genetic profiles. Simultaneous analysis of multiple PGSs may contribute to useful clinical stratification in schizophrenia.
Understanding neurogenetic mechanisms underlying neuropsychiatric disorders such as schizophrenia and autism is complicated by their inherent clinical and genetic heterogeneity. Williams syndrome ...(WS), a rare neurodevelopmental condition in which both the genetic alteration (hemideletion of ~ twenty-six 7q11.23 genes) and the cognitive/behavioral profile are well-defined, offers an invaluable opportunity to delineate gene-brain-behavior relationships. People with WS are characterized by increased social drive, including particular interest in faces, together with hallmark difficulty in visuospatial processing. Prior work, primarily in adults with WS, has searched for neural correlates of these characteristics, with reports of altered fusiform gyrus function while viewing socioemotional stimuli such as faces, along with hypoactivation of the intraparietal sulcus during visuospatial processing. Here, we investigated neural function in children and adolescents with WS by using four separate fMRI paradigms, two that probe each of these two cognitive/behavioral domains. During the two visuospatial tasks, but not during the two face processing tasks, we found bilateral intraparietal sulcus hypoactivation in WS. In contrast, during both face processing tasks, but not during the visuospatial tasks, we found fusiform hyperactivation. These data not only demonstrate that previous findings in adults with WS are also present in childhood and adolescence, but also provide a clear example that genetic mechanisms can bias neural circuit function, thereby affecting behavioral traits.
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