17 research outputs found
Initial evidence that non-clinical autistic traits are associated with lower income
Among non-clinical samples, autistic traits correlate with a range of educational and social outcomes. However, previous work has not investigated the relationship between autistic traits and income, a key determinant of socio-economic status and wellbeing. In 5 studies (total N = 2491), we recruited participants without a diagnosis of autism from the general US population via an on-line platform, and administered the short-form Autism Spectrum Quotient (AQ) as well as asking a range of demographic questions. We found a negative association between AQ and household income, which remained robust after controlling for age, gender, education, employment status, ethnicity, and socially-desirable responding. The effect was primarily driven by the participant’s own income, and was mainly due to the social subscale of the AQ. These results provide initial evidence that income is negatively related to autistic traits among the general population, with potential implications for a range of social, psychological, and health outcomes.WJS was supported by Wellcome Trust grant RG76641 and Isaac Newton Trust grant RG70368. SBC was supported by the Autism Research Trust
Search for the Decays B^0 -> D^{(*)+} D^{(*)-}
Using the CLEO-II data set we have searched for the Cabibbo-suppressed decays
B^0 -> D^{(*)+} D^{(*)-}. For the decay B^0 -> D^{*+} D^{*-}, we observe one
candidate signal event, with an expected background of 0.022 +/- 0.011 events.
This yield corresponds to a branching fraction of Br(B^0 -> D^{*+} D^{*-}) =
(5.3^{+7.1}_{-3.7}(stat) +/- 1.0(syst)) x 10^{-4} and an upper limit of Br(B^0
-> D^{*+} D^{*-}) D^{*\pm} D^\mp and
B^0 -> D^+ D^-, no significant excess of signal above the expected background
level is seen, and we calculate the 90% CL upper limits on the branching
fractions to be Br(B^0 -> D^{*\pm} D^\mp) D^+
D^-) < 1.2 x 10^{-3}.Comment: 12 page postscript file also available through
http://w4.lns.cornell.edu/public/CLNS, submitted to Physical Review Letter
Synaptic and transcriptionally downregulated genes are associated with cortical thickness differences in autism.
Differences in cortical morphology-in particular, cortical volume, thickness and surface area-have been reported in individuals with autism. However, it is unclear what aspects of genetic and transcriptomic variation are associated with these differences. Here we investigate the genetic correlates of global cortical thickness differences (ΔCT) in children with autism. We used Partial Least Squares Regression (PLSR) on structural MRI data from 548 children (166 with autism, 295 neurotypical children and 87 children with ADHD) and cortical gene expression data from the Allen Institute for Brain Science to identify genetic correlates of ΔCT in autism. We identify that these genes are enriched for synaptic transmission pathways and explain significant variation in ΔCT. These genes are also significantly enriched for genes dysregulated in the autism post-mortem cortex (Odd Ratio (OR) = 1.11, Pcorrected  10-14), driven entirely by downregulated genes (OR = 1.87, Pcorrected  10-15). We validated the enrichment for downregulated genes in two independent data sets: Validation 1 (OR = 1.44, Pcorrected = 0.004) and Validation 2 (OR = 1.30; Pcorrected = 0.001). We conclude that transcriptionally downregulated genes implicated in autism are robustly associated with global changes in cortical thickness variability in children with autism
Motor signatures of emotional reactivity in frontotemporal dementia
Automatic motor mimicry is essential to the normal processing of perceived emotion, and disrupted automatic imitation might underpin socio-emotional deficits in neurodegenerative diseases, particularly the frontotemporal dementias. However, the pathophysiology of emotional reactivity in these diseases has not been elucidated. We studied facial electromyographic responses during emotion identification on viewing videos of dynamic facial expressions in 37 patients representing canonical frontotemporal dementia syndromes versus 21 healthy older individuals. Neuroanatomical associations of emotional expression identification accuracy and facial muscle reactivity were assessed using voxel-based morphometry. Controls showed characteristic profiles of automatic imitation, and this response predicted correct emotion identification. Automatic imitation was reduced in the behavioural and right temporal variant groups, while the normal coupling between imitation and correct identification was lost in the right temporal and semantic variant groups. Grey matter correlates of emotion identification and imitation were delineated within a distributed network including primary visual and motor, prefrontal, insular, anterior temporal and temporo-occipital junctional areas, with common involvement of supplementary motor cortex across syndromes. Impaired emotional mimesis may be a core mechanism of disordered emotional signal understanding and reactivity in frontotemporal dementia, with implications for the development of novel physiological biomarkers of socio-emotional dysfunction in these diseases